Cartilage Repair Surgery: Outcome Evaluation by Using Noninvasive Cartilage Biomarkers Based on Quantitative MRI Techniques?

PubMed Central

Jungmann, Pia M.; Baum, Thomas; Bauer, Jan S.; Karampinos, Dimitrios C.; Link, Thomas M.; Li, Xiaojuan; Trattnig, Siegfried; Rummeny, Ernst J.; Woertler, Klaus; Welsch, Goetz H.

2014-01-01

Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. Methods. Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. Results. Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. Conclusions. A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair. PMID:24877139

Feasibility of gadoteric acid for delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) at the wrist and knee and comparison with Gd-DTPA.

PubMed

Rehnitz, Christoph; Klaan, Bastian; Do, Thuy; Barié, Alexander; Kauczor, Hans-Ulrich; Weber, Marc-André

2017-11-01

To assess the feasibility of gadoteric acid for delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and to compare the dGEMRIC values obtained using gadoteric acid with those obtained by an equimolar dose of Gd-DTPA. At 3T, dGEMRIC of the wrist was performed twice using a T 1 -weighted 3D-volumetric interpolated breath-hold examination sequence in 16 healthy volunteers (10 women; mean age 26.0 years) using gadoteric acid first and Gd-DTPA 3 weeks later. In addition, 24 patients with knee pain were examined using gadoteric acid (n = 12; seven women; mean age 45.8 years) or Gd-DTPA (n = 12; four women; mean age 47.1 years). T 1 values, the relative decrease in T 1 , and the delta R1 were compared using t-tests. Interobserver agreement was assessed using the intraclass correlation (ICC) between two independent readers. At the wrist, there was no significant difference in delta R1 values (0.34 ± 0.10/s, 95% confidence interval [0.30;0.38]/s for gadoteric acid and 0.32 ± 0.09 [0.29;0.35]/s for Gd-DTPA, P = 0.24) or the relative decrease in T 1 (0.25 ± 0.06 [0.29;0.35] msec for gadoteric acid and 0.24 ± 0.05 [0.22;0.27] msec for Gd-DTPA, P = 0.35). High observer agreement was found at precontrast (ICC = 0.87, P < 0.001) and postcontrast (ICC = 0.89, P < 0.001). Similarly, at the knee, there was no significant difference in delta R1 (0.39 ± 0.18 [0.32;0.47]/s for gadoteric acid and 0.41 ± 0.09 [0.38;0.45]/s for Gd-DTPA, P = 0.59) or the relative decrease in T 1 (0.30 ± 0.10 [0.26;0.34] msec for gadoteric acid and 0.33 ± 0.05 [0.30;0.35] msec for Gd-DTPA, P = 0.28). High ICCs of 0.96 (P < 0.01) were noted both at precontrast and postcontrast. dGEMRIC using gadoteric acid is feasible and yields comparable values when compared with Gd-DTPA. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1433-1440. © 2017 International Society for Magnetic Resonance in Medicine.

Preoperative Delayed Gadolinium-Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC) for Patients Undergoing Hip Arthroscopy: Indices Are Predictive of Magnitude of Improvement in Two-Year Patient-Reported Outcomes.

PubMed

Chandrasekaran, Sivashankar; Vemula, S Pavan; Lindner, Dror; Lodhia, Parth; Suarez-Ahedo, Carlos; Domb, Benjamin G

2015-08-19

Delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) has been used in the detection of chondropathy. Our study aimed to determine whether dGEMRIC indices are predictive of two-year patient-reported outcomes and pain scores following hip arthroscopy. Between August 2008 and April 2012, sixty-five patients (seventy-four hips) underwent primary hip arthroscopy with preoperative dGEMRIC and a minimum of two years of follow-up. Exclusion criteria were previous hip surgery, slipped capital femoral epiphysis, inflammatory arthropathy, Legg-Calvé-Perthes disease, and arthritis of >1 Tönnis grade. Patients were classified in two groups on the basis of a dGEMRIC cutoff of 323 msec, which was one standard deviation (SD) below the study cohort mean dGEMRIC index of 426 msec. Patient-reported outcome tools used included the modified Harris hip score (mHHS), the Nonarthritic Hip Score (NAHS), the Hip Outcome Score Activities of Daily Living (HOS-ADL), and the Hip Outcome Score Sport-Specific Subscale (HOS-SSS) as well as a visual analog scale (VAS) for pain and a patient satisfaction score. There were sixty-four hips that met the inclusion criteria; fifty-two (81.3%) had a minimum of two years of follow-up. Twelve of the sixty-four hips had a dGEMRIC index of <323 msec (Group 1), and fifty-two hips had a dGEMRIC index of ≥323 msec (Group 2). There was no significant difference between the groups with respect to age, sex, and body mass index. There was no significant difference between the groups in mean preoperative patient-reported outcome scores and the VAS for pain. At the two-year follow-up, Group 1 had significant improvement in the mHHS, whereas Group 2 demonstrated significant improvement in all patient-reported outcome scores and the VAS. The improvement in all patient-reported outcome scores was significantly larger for Group 2 compared with Group 1. There was no significant difference in patient satisfaction between groups and no significant correlation between dGEMRIC indices and the patient-reported outcome measures. Patients with a dGEMRIC index of ≥323 msec (less than one SD below the cohort mean) demonstrated significantly greater improvement in patient-reported outcome scores and the VAS for pain after hip arthroscopy. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

Using the dGEMRIC technique to evaluate cartilage health in the presence of surgical hardware at 3T: comparison of inversion recovery and saturation recovery approaches.

PubMed

d'Entremont, Agnes G; Kolind, Shannon H; Mädler, Burkhard; Wilson, David R; MacKay, Alexander L

2014-03-01

To evaluate the effect of metal artifact reduction techniques on dGEMRIC T(1) calculation with surgical hardware present. We examined the effect of stainless-steel and titanium hardware on dGEMRIC T(1) maps. We tested two strategies to reduce metal artifact in dGEMRIC: (1) saturation recovery (SR) instead of inversion recovery (IR) and (2) applying the metal artifact reduction sequence (MARS), in a gadolinium-doped agarose gel phantom and in vivo with titanium hardware. T(1) maps were obtained using custom curve-fitting software and phantom ROIs were defined to compare conditions (metal, MARS, IR, SR). A large area of artifact appeared in phantom IR images with metal when T(I) ≤ 700 ms. IR maps with metal had additional artifact both in vivo and in the phantom (shifted null points, increased mean T(1) (+151 % IR ROI(artifact)) and decreased mean inversion efficiency (f; 0.45 ROI(artifact), versus 2 for perfect inversion)) compared to the SR maps (ROI(artifact): +13 % T(1) SR, 0.95 versus 1 for perfect excitation), however, SR produced noisier T(1) maps than IR (phantom SNR: 118 SR, 212 IR). MARS subtly reduced the extent of artifact in the phantom (IR and SR). dGEMRIC measurement in the presence of surgical hardware at 3T is possible with appropriately applied strategies. Measurements may work best in the presence of titanium and are severely limited with stainless steel. For regions near hardware where IR produces large artifacts making dGEMRIC analysis impossible, SR-MARS may allow dGEMRIC measurements. The position and size of the IR artifact is variable, and must be assessed for each implant/imaging set-up.

In vitro determination of biomechanical properties of human articular cartilage in osteoarthritis using multi-parametric MRI

NASA Astrophysics Data System (ADS)

Juras, Vladimir; Bittsansky, Michal; Majdisova, Zuzana; Szomolanyi, Pavol; Sulzbacher, Irene; Gäbler, Stefan; Stampfl, Jürgen; Schüller, Georg; Trattnig, Siegfried

2009-03-01

The objective of this study was to evaluate the correlations between MR parameters and the biomechanical properties of naturally degenerated human articular cartilage. Human cartilage explants from the femoral condyles of patients who underwent total knee replacement were evaluated on a micro-imaging system at 3 T. To quantify glycosaminoglycan (GAG) content, delayed gadolinium-enhanced MRI of the cartilage (dGEMRIC) was used. T2 maps were created by using multi-echo, multi-slice spin echo sequences with six echoes: 15, 30, 45, 60, 75, and 90 ms. Data for apparent diffusion constant (ADC) maps were obtained from pulsed gradient spin echo (PGSE) sequences with five b-values: 10.472, 220.0, 627.0, 452.8, 724.5, and 957.7. MR parameters were correlated with mechanical parameters (instantaneous ( I) and equilibrium ( Eq) modulus and relaxation time ( τ)), and the OA stage of each cartilage specimen was determined by histological evaluation of hematoxylin-eosin stained slices. For some parameters, a high correlation was found: the correlation of T1Gd vs Eq ( r = 0.8095), T1Gd vs I/ Eq ( r = -0.8441) and T1Gd vs τ ( r = 0.8469). The correlation of T2 and ADC with selected biomechanical parameters was not statistically significant. In conclusion, GAG content measured by dGEMRIC is highly related to the selected biomechanical properties of naturally degenerated articular cartilage. In contrast, T2 and ADC were unable to estimate these properties. The results of the study imply that some MR parameters can non-invasively predict the biomechanical properties of degenerated articular cartilage.

Effects of B1 inhomogeneity correction for three-dimensional variable flip angle T1 measurements in hip dGEMRIC at 3 T and 1.5 T.

PubMed

Siversson, Carl; Chan, Jenny; Tiderius, Carl-Johan; Mamisch, Tallal Charles; Jellus, Vladimir; Svensson, Jonas; Kim, Young-Jo

2012-06-01

Delayed gadolinium-enhanced MRI of cartilage is a technique for studying the development of osteoarthritis using quantitative T(1) measurements. Three-dimensional variable flip angle is a promising method for performing such measurements rapidly, by using two successive spoiled gradient echo sequences with different excitation pulse flip angles. However, the three-dimensional variable flip angle method is very sensitive to inhomogeneities in the transmitted B(1) field in vivo. In this study, a method for correcting for such inhomogeneities, using an additional B(1) mapping spin-echo sequence, was evaluated. Phantom studies concluded that three-dimensional variable flip angle with B(1) correction calculates accurate T(1) values also in areas with high B(1) deviation. Retrospective analysis of in vivo hip delayed gadolinium-enhanced MRI of cartilage data from 40 subjects showed the difference between three-dimensional variable flip angle with and without B(1) correction to be generally two to three times higher at 3 T than at 1.5 T. In conclusion, the B(1) variations should always be taken into account, both at 1.5 T and at 3 T. Copyright © 2011 Wiley-Liss, Inc.

Contrast agent enhanced pQCT of articular cartilage

NASA Astrophysics Data System (ADS)

Kallioniemi, A. S.; Jurvelin, J. S.; Nieminen, M. T.; Lammi, M. J.; Töyräs, J.

2007-02-01

The delayed gadolinium enhanced MRI of cartilage (dGEMRIC) technique is the only non-invasive means to estimate proteoglycan (PG) content in articular cartilage. In dGEMRIC, the anionic paramagnetic contrast agent gadopentetate distributes in inverse relation to negatively charged PGs, leading to a linear relation between T1,Gd and spatial PG content in tissue. In the present study, for the first time, contrast agent enhanced peripheral quantitative computed tomography (pQCT) was applied, analogously to dGEMRIC, for the quantitative detection of spatial PG content in cartilage. The suitability of two anionic radiographic contrast agents, gadopentetate and ioxaglate, to detect enzymatically induced PG depletion in articular cartilage was investigated. First, the interrelationships of x-ray absorption, as measured with pQCT, and the contrast agent solution concentration were investigated. Optimal contrast agent concentrations for the following experiments were selected. Second, diffusion rates for both contrast agents were investigated in intact (n = 3) and trypsin-degraded (n = 3) bovine patellar cartilage. The contrast agent concentration of the cartilaginous layer was measured prior to and 2-27 h after immersion. Optimal immersion time for the further experiments was selected. Third, the suitability of gadopentetate and ioxaglate enhanced pQCT to detect the enzymatically induced specific PG depletion was investigated by determining the contrast agent concentrations and uronic acid and water contents in digested and intact osteochondral samples (n = 16). After trypsin-induced PG loss (-70%, p < 0.05) the penetration of gadopentetate and ioxaglate increased (p < 0.05) by 34% and 48%, respectively. Gadopentetate and ioxaglate concentrations both showed strong correlation (r = -0.95, r = -0.94, p < 0.01, respectively) with the uronic acid content. To conclude, contrast agent enhanced pQCT provides a technique to quantify PG content in normal and experimentally degraded articular cartilage in vitro. As high resolution imaging of e.g. the knee joint is possible with pQCT, the present technique may be further developed for in vivo quantification of PG depletion in osteoarthritic cartilage. However, careful in vitro and in vivo characterization of diffusion mechanics and optimal contrast agent concentrations are needed before diagnostic applications are feasible.

Feasibility of texture analysis for the assessment of biochemical changes in meniscal tissue on T1 maps calculated from delayed gadolinium-enhanced magnetic resonance imaging of cartilage data: comparison with conventional relaxation time measurements.

PubMed

Mayerhoefer, Marius E; Welsch, Goetz H; Riegler, Georg; Mamisch, Tallal C; Materka, Andrzej; Weber, Michael; El-Rabadi, Karem; Friedrich, Klaus M; Dirisamer, Albert; Trattnig, Siegfried

2010-09-01

To (1) establish the feasibility of texture analysis for the in vivo assessment of biochemical changes in meniscal tissue on delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), and (2) compare textural with conventional T1 relaxation time measurements calculated from dGEMRIC data ("T1(Gd) relaxation times"). We enrolled 10 asymptomatic volunteers (7 men and 3 women; mean age, 27.2 +/- 4.5 years), without a history of meniscus damage, in our study. MRI of the right knee was performed at 3.0 T. An isotropic, 3-dimensional (3D), double-echo steady-state sequences was used for morphologic evaluation, and a dual flip angle 3D gradient echo sequence was used for T1(Gd) mapping. All MRI scans were performed 90 minutes after injection of 0.2 mmol/kg of Gd-diethylenetriamine pentaacetic acid (DTPA), and subsequently, during application of a compressive force (50% of the body weight) in the axial direction. Regions of interest, covering the central portions of the posterior horn of the medial meniscus, were defined on 3 adjacent sagittal sections. Based on the relaxation time maps, mean T1(Gd), as well as the T1(Gd) texture features derived from the co-occurrence matrix (COC: Angular Second Moment, Entropy, Inverse Difference Moment) and wavelet transform (WAV: WavEnLL, WavEnHL, WavEnHH, WavEnLH), were calculated. Paired t tests were used to assess differences between baseline and compression, and intraclass correlation coefficients (ICC) were calculated to establish the intrarater reliability of the measurements. Mean T1(Gd) (-67.3 ms, P = 0.011), Angular Second Moment (-0.0002, P = 0.009), Entropy (+0.033, P = 0.025), WavEnLL (+1011.16, P = 0.002), WavEnHL (+18.64, P = 0.012), and WavEnLH (+72.74, P = 0.035) differed significantly between baseline and compression. Intrarater reliability was substantial for mean T1(Gd) relaxation times (ICC = 0.99-1.0), and also for T1(Gd) co-occurrence matrix (ICC = 0.63-0.92) and WAV (ICC = 0.86-0.98) features. Texture features extracted from T1 maps calculated from dGEMRIC data are feasible for the in vivo assessment of biochemical changes in the menisci, such as might be induced by mechanical loading. Thus, T1(Gd) texture features complement conventional relaxation time measurements. Further studies are necessary to determine whether the mechanical compression, or a prolonged Gd-DTPA uptake, or both, are responsible for the observed decrease in mean T1(Gd) relaxation times in the menisci.

Delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) of cadaveric shoulders: comparison of contrast dynamics in hyaline and fibrous cartilage after intraarticular gadolinium injection.

PubMed

Wiener, E; Hodler, J; Pfirrmann, C W A

2009-01-01

Delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) is a novel method to investigate cartilaginous and fibrocartilaginous structures. To investigate the contrast dynamics in hyaline and fibrous cartilage of the glenohumeral joint after intraarticular injection of gadopentetate dimeglumine. Transverse T(1) maps were acquired on a 1.5T scanner before and after intraarticular injection of 2.0 mmol/l gadopentetate dimeglumine in five cadaveric shoulders using a dual flip angle three-dimensional gradient echo (3D-GRE) sequence. The acquisition time for the T(1) maps was 5 min 5 s for the whole shoulder. Measurements were repeated every 15 min over 2.5 hours. Regions of interest (ROIs) covering the glenoid cartilage and the labrum were drawn to assess the temporal evolution of the relaxation parameters. T(1) of unenhanced hyaline cartilage of the glenoid was 568+/-34 ms. T(1) of unenhanced fibrous cartilage of the labrum was 552+/-38 ms. Significant differences (P=0.002 and 0.03) in the relaxation parameters were already measurable after 15 min. After 2 to 2.5 hours, hyaline and fibrous cartilage still demonstrated decreasing relaxation parameters, with a larger range of the T(1)(Gd) values in fibrous cartilage. T(1) and triangle Delta R(1) values of hyaline and fibrous cartilage after 2.5 hours were 351+/-16 ms and 1.1+/-0.09 s(-1), and 332+/-31 ms and 1.2+/-0.1 s(-1), respectively. A significant decrease in T(1)(Gd) was found 15 min after intraarticular contrast injection. Contrast accumulation was faster in hyaline than in fibrous cartilage. After 2.5 hours, contrast accumulation showed a higher rate of decrease in hyaline cartilage, but neither hyaline nor fibrous cartilage had reached equilibrium.

Bone and cartilage characteristics in postmenopausal women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis

PubMed Central

Multanen, J.; Heinonen, A.; Häkkinen, A.; Kautiainen, H.; Kujala, U.M.; Lammentausta, E.; Jämsä, T.; Kiviranta, I.; Nieminen, M.T.

2015-01-01

Objectives: To evaluate the association between radiographically-assessed knee osteoarthritis and femoral neck bone characteristics in women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis. Methods: Ninety postmenopausal women (mean age [SD], 58 [4] years; height, 163 [6] cm; weight, 71 [11] kg) participated in this cross-sectional study. The severity of radiographic knee osteoarthritis was defined using Kellgren-Lawrence grades 0=normal (n=12), 1=doubtful (n=25) or 2=minimal (n=53). Femoral neck bone mineral content (BMC), section modulus (Z), and cross-sectional area (CSA) were measured with DXA. The biochemical composition of ipsilateral knee cartilage was estimated using quantitative MRI measures, T2 mapping and dGEMRIC. The associations between radiographic knee osteoarthritis grades and bone and cartilage characteristics were analyzed using generalized linear models. Results: Age-, height-, and weight-adjusted femoral neck BMC (p for linearity=0.019), Z (p for linearity=0.033), and CSA (p for linearity=0.019) increased significantly with higher knee osteoarthritis grades. There was no linear relationship between osteoarthritis grades and knee cartilage indices. Conclusions: Increased DXA assessed hip bone strength is related to knee osteoarthritis severity. These results are hypothesis driven that there is an inverse relationship between osteoarthritis and osteoporosis. However, MRI assessed measures of cartilage do not discriminate mild radiographic osteoarthritis severity. PMID:25730654

Protocol for a multi-centre randomised controlled trial comparing arthroscopic hip surgery to physiotherapy-led care for femoroacetabular impingement (FAI): the Australian FASHIoN trial.

PubMed

Murphy, Nicholas J; Eyles, Jillian; Bennell, Kim L; Bohensky, Megan; Burns, Alexander; Callaghan, Fraser M; Dickenson, Edward; Fary, Camdon; Grieve, Stuart M; Griffin, Damian R; Hall, Michelle; Hobson, Rachel; Kim, Young Jo; Linklater, James M; Lloyd, David G; Molnar, Robert; O'Connell, Rachel L; O'Donnell, John; O'Sullivan, Michael; Randhawa, Sunny; Reichenbach, Stephan; Saxby, David J; Singh, Parminder; Spiers, Libby; Tran, Phong; Wrigley, Tim V; Hunter, David J

2017-09-26

Femoroacetabular impingement syndrome (FAI), a hip disorder affecting active young adults, is believed to be a leading cause of hip osteoarthritis (OA). Current management approaches for FAI include arthroscopic hip surgery and physiotherapy-led non-surgical care; however, there is a paucity of clinical trial evidence comparing these approaches. In particular, it is unknown whether these management approaches modify the future risk of developing hip OA. The primary objective of this randomised controlled trial is to determine if participants with FAI who undergo hip arthroscopy have greater improvements in hip cartilage health, as demonstrated by changes in delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) index between baseline and 12 months, compared to those who undergo physiotherapy-led non-surgical management. This is a pragmatic, multi-centre, two-arm superiority randomised controlled trial comparing hip arthroscopy to physiotherapy-led management for FAI. A total of 140 participants with FAI will be recruited from the clinics of participating orthopaedic surgeons, and randomly allocated to receive either surgery or physiotherapy-led non-surgical care. The surgical intervention involves arthroscopic FAI surgery from one of eight orthopaedic surgeons specialising in this field, located in three different Australian cities. The physiotherapy-led non-surgical management is an individualised physiotherapy program, named Personalised Hip Therapy (PHT), developed by a panel to represent the best non-operative care for FAI. It entails at least six individual physiotherapy sessions over 12 weeks, and up to ten sessions over six months, provided by experienced musculoskeletal physiotherapists trained to deliver the PHT program. The primary outcome measure is the change in dGEMRIC score of a ROI containing both acetabular and femoral head cartilages at the chondrolabral transitional zone of the mid-sagittal plane between baseline and 12 months. Secondary outcomes include patient-reported outcomes and several structural and biomechanical measures relevant to the pathogenesis of FAI and development of hip OA. Interventions will be compared by intention-to-treat analysis. The findings will help determine whether hip arthroscopy or an individualised physiotherapy program is superior for the management of FAI, including for the prevention of hip OA. Australia New Zealand Clinical Trials Registry reference: ACTRN12615001177549 . Trial registered 2/11/2015 (retrospectively registered).

Efficacy of progressive aquatic resistance training for tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis: a randomised controlled trial.

PubMed

Munukka, M; Waller, B; Rantalainen, T; Häkkinen, A; Nieminen, M T; Lammentausta, E; Kujala, U M; Paloneva, J; Sipilä, S; Peuna, A; Kautiainen, H; Selänne, H; Kiviranta, I; Heinonen, A

2016-10-01

To study the efficacy of aquatic resistance training on biochemical composition of tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis (OA). Eighty seven volunteer postmenopausal women, aged 60-68 years, with mild knee OA (Kellgren-Lawrence grades I/II and knee pain) were recruited and randomly assigned to an intervention (n = 43) and control (n = 44) group. The intervention group participated in 48 supervised aquatic resistance training sessions over 16 weeks while the control group maintained usual level of physical activity. The biochemical composition of the medial and lateral tibiofemoral cartilage was estimated using single-slice transverse relaxation time (T2) mapping and delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC index). Secondary outcomes were cardiorespiratory fitness, isometric knee extension and flexion force and knee injury and OA outcome (KOOS) questionnaire. After 4-months aquatic training, there was a significant decrease in both T2 -1.2 ms (95% confidence interval (CI): -2.3 to -0.1, P = 0.021) and dGEMRIC index -23 ms (-43 to -3, P = 0.016) in the training group compared to controls in the full thickness posterior region of interest (ROI) of the medial femoral cartilage. Cardiorespiratory fitness significantly improved in the intervention group by 9.8% (P = 0.010). Our results suggest that, in postmenopausal women with mild knee OA, the integrity of the collagen-interstitial water environment (T2) of the tibiofemoral cartilage may be responsive to low shear and compressive forces during aquatic resistance training. More research is required to understand the exact nature of acute responses in dGEMRIC index to this type of loading. Further, aquatic resistance training improves cardiorespiratory fitness. ISRCTN65346593. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Delayed gadolinium-enhanced MRI of cartilage and T2 mapping for evaluation of reparative cartilage-like tissue after autologous chondrocyte implantation associated with Atelocollagen-based scaffold in the knee.

PubMed

Tadenuma, Taku; Uchio, Yuji; Kumahashi, Nobuyuki; Fukuba, Eiji; Kitagaki, Hajime; Iwasa, Junji; Ochi, Mitsuo

2016-10-01

To elucidate the quality of tissue-engineered cartilage after an autologous chondrocyte implantation (ACI) technique with Atelocollagen gel as a scaffold in the knee in the short- to midterm postoperatively, we assessed delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) and T2 mapping and clarified the relationship between T1 and T2 values and clinical results. In this cross-sectional study, T1 and T2 mapping were performed on 11 knees of 8 patients (mean age at ACI, 37.2 years) with a 3.0-T MRI scanner. T1implant and T2implant values were compared with those of the control cartilage region (T1control and T2control). Lysholm scores were also assessed for clinical evaluation. The relationships between the T1 and T2 values and the clinical Lysholm score were also assessed. There were no significant differences in the T1 values between the T1implant (386.64 ± 101.78 ms) and T1control (375.82 ± 62.89 ms) at the final follow-up. The implants showed significantly longer T2 values compared to the control cartilage (53.83 ± 13.89 vs. 38.21 ± 4.43 ms). The postoperative Lysholm scores were significantly higher than the preoperative scores. A significant correlation was observed between T1implant and clinical outcomes, but not between T2implant and clinical outcomes. Third-generation ACI implants might have obtained an almost equivalent glycosaminoglycan concentration compared to the normal cartilage, but they had lower collagen density at least 3 years after transplantation. The T1implant value, but not the T2 value, might be a predictor of clinical outcome after ACI.

On the detection of early osteoarthritis by quantitative microscopic imaging

NASA Astrophysics Data System (ADS)

Mittelstaedt, Daniel John

Articular cartilage is a thin layer of connective tissue that protects the ends of bones in diarthroidal joints. Cartilage distributes mechanical forces during daily movement throughout its unique depth-dependent structure. The extracellular matrix (ECM) of cartilage primarily contains water, collagen, and glycosaminoglycan (GAG). The collagen fibers are intertwined with negatively charged GAG and surround the cells (i.e. chondrocytes) in cartilage. Degradation to the ECM reduces the load bearing properties of cartilage which can be initiated by injury (e.g. anterior cruciate ligament (ACL) rupture) or disease (e.g. osteoarthritis (OA)). Magnetic resonance imaging (MRI) and x-ray computed tomography (CT) are noninvasive imaging techniques that are increasingly being used in the clinical detection of cartilage degradation. The aim of the first project in this dissertation was to quantify and compare the depth-dependent GAG concentration from healthy and biochemically degraded humeral ex vivo articular cartilage using quantitative contrast enhanced micro-computed tomography (qCECT) at high resolution. The second project in this dissertation was aimed to measure the topographical and depth-dependent GAG concentration using qCECT and delayed gadolinium enhanced magnetic resonance imaging of cartilage (dGEMRIC) from the medial tibia cartilage three weeks after unilateral ACL transection which is an animal model of OA (i.e. modified Pond-Nuki model). These GAG measurements were correlated with a biochemical method, inductively couple plasma optical emission spectrometry, to compare the degradation on the medial tibia between the OA and contralateral cartilage. The third project in this dissertation used the same cartilage specimens as in project two to investigate the change in T2 due to OA and the effect on T2 from a contrast agent. Furthermore, the change in T2 relaxation was investigated from static unconfined compression with correlations by biomechanical measurements. These studies demonstrate the ability to use two quantitative microscopic imaging techniques, microCT and microMRI, to detect microscopic changes in collagen and GAG from healthy, biochemically degraded, and early OA cartilage. The capability for microscopic imaging to detect alterations at the earliest stages of OA will ultimately improve the understanding of degradation and may help aid in the detection for the prevention of disease and repair of damaged cartilage.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2014-06-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2015-04-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

A review of MRI evaluation of demyelination in cuprizone murine model

NASA Astrophysics Data System (ADS)

Krutenkova, E.; Pan, E.; Khodanovich, M.

2015-11-01

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular proton fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Low Field Squid MRI Devices, Components and Methods

NASA Technical Reports Server (NTRS)

Hahn, Inseob (Inventor); Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor)

2013-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low Field Squid MRI Devices, Components and Methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor); Hahn, Inseob (Inventor)

2014-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low field SQUID MRI devices, components and methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor); Hahn, Inseob (Inventor)

2011-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low field SQUID MRI devices, components and methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H (Inventor); Hahn, Inseob (Inventor)

2010-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

A review of MRI evaluation of demyelination in cuprizone murine model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krutenkova, E., E-mail: len--k@yandex.ru; Pan, E.; Khodanovich, M., E-mail: khodanovich@mail.tsu.ru

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular protonmore » fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.« less

Advanced MRI in Blast-related TBI

DTIC Science & Technology

2012-07-01

test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI patients acutely after injury and correlate...Introduction: The purpose of the research effort was to test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI...clinical follow-up assessments and repeat scans on 78 subjects with TBI and 18 controls. 9) We extensively analyzed DTI , resting-state fMRI, and

SU-G-IeP1-13: Sub-Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, B; Gao, H

Purpose: Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub-Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k-t space for accelerated dynamic MRI. This work is to investigate sub-Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM). Methods: The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub-Nyquist reconstruction. In PRISM, the low-rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify themore » residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k-t space is made more incoherent by sampling a different set of k-space points at different temporal frames. Results: Reconstruction results from L1-sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI. Conclusion: A sub- Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1-sparsity method.« less

Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andreasen, Daniel, E-mail: dana@dtu.dk; Van Leemput, Koen; Hansen, Rasmus H.

Purpose: In radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, the information on electron density must be derived from the MRI scan by creating a so-called pseudo computed tomography (pCT). This is a nontrivial task, since the voxel-intensities in an MRI scan are not uniquely related to electron density. To solve the task, voxel-based or atlas-based models have typically been used. The voxel-based models require a specialized dual ultrashort echo time MRI sequence for bone visualization and the atlas-based models require deformable registrations of conventional MRI scans. In this study, we investigate the potential of amore » patch-based method for creating a pCT based on conventional T{sub 1}-weighted MRI scans without using deformable registrations. We compare this method against two state-of-the-art methods within the voxel-based and atlas-based categories. Methods: The data consisted of CT and MRI scans of five cranial RT patients. To compare the performance of the different methods, a nested cross validation was done to find optimal model parameters for all the methods. Voxel-wise and geometric evaluations of the pCTs were done. Furthermore, a radiologic evaluation based on water equivalent path lengths was carried out, comparing the upper hemisphere of the head in the pCT and the real CT. Finally, the dosimetric accuracy was tested and compared for a photon treatment plan. Results: The pCTs produced with the patch-based method had the best voxel-wise, geometric, and radiologic agreement with the real CT, closely followed by the atlas-based method. In terms of the dosimetric accuracy, the patch-based method had average deviations of less than 0.5% in measures related to target coverage. Conclusions: We showed that a patch-based method could generate an accurate pCT based on conventional T{sub 1}-weighted MRI sequences and without deformable registrations. In our evaluations, the method performed better than existing voxel-based and atlas-based methods and showed a promising potential for RT of the brain based only on MRI.« less

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011

Advanced MRI in Acute Military TBI

DTIC Science & Technology

2015-11-01

advanced MRI methods, DTI and resting-state fMRI correlation analysis, in military TBI patients acutely after injury and correlate findings with TBI...14 4 Introduction The objective of the project was to test two advanced MRI methods, DTI and resting-state fMRI correlation analysis, in...of Concussion Exam (MACE )(44) were reviewed. This brief cognitive test 279 assesses orientation, immediate verbal memory , concentration, and short

Comparison of the diagnostic efficacy between ultrasound elastography and magnetic resonance imaging for breast masses

PubMed Central

Cheng, Rong; Li, Jing; Ji, Li; Liu, Huining; Zhu, Limin

2018-01-01

The present study compared the efficacy of ultrasound elastography (UE), magnetic resonance imaging (MRI) and the combination of the two methods (UE+MRI) in the differential diagnosis of benign and malignant breast tumors. In total, 86 patients with breast masses were recruited and evaluated by UE, MRI and UE+MRI. Strain ratios of UE were calculated for the breast mass and adjacent normal tissues. In addition, the receiver operating characteristic (ROC) curve was obtained, while the sensitivity and specificity were calculated to determine the optimal cut-off point for the differential diagnosis. The area under the ROC curve (AUC) was also calculated to evaluate the diagnostic performance of these methods. The results indicated that the diagnostic accuracy of UE+MRI was significantly higher compared with the UE or MRI methods in the differential diagnosis of invasive ductal, invasive lobular, intraductal papillary, medullary and mucinous carcinomas (all P<0.05). The optimal cut-off points of ROC curve of the Strain Ratio in the diagnosis of breast lesions were 2.81, 3.76 and 3.42 for UE, MRI and UE+MRI, respectively. Furthermore, the AUC values were 86.7, 79.2 and 91.4%, while the diagnostic accuracy rates were 82.5, 75.5 and 95.3%, for UE, MRI and UE+MRI, respectively. Accuracy rate differences between UE and MRI or between UE and UE+MRI were statistically significant (P<0.05), whereas no significant difference existed between MRI and UE+MRI (P>0.05). Finally, the diagnostic consistency of the UE+MRI method with the pathological diagnosis was higher compared with UE or MRI alone. In conclusion, the combination of UE and MRI is superior to the use of UE or MRI alone in the differential diagnosis of benign and malignant breast masses. PMID:29456656

Topical Review: Unique Contributions of Magnetic Resonance Imaging to Pediatric Psychology Research

PubMed Central

Duraccio, Kara M.; Carbine, Kaylie M.; Kirwan, C. Brock

2016-01-01

Objective This review aims to provide a brief introduction of the utility of magnetic resonance imaging (MRI) methods in pediatric psychology research, describe several exemplar studies that highlight the unique benefits of MRI techniques for pediatric psychology research, and detail methods for addressing several challenges inherent to pediatric MRI research. Methods Literature review. Results Numerous useful applications of MRI research in pediatric psychology have been illustrated in published research. MRI methods yield information that cannot be obtained using neuropsychological or behavioral measures. Conclusions Using MRI in pediatric psychology research may facilitate examination of neural structures and processes that underlie health behaviors. Challenges inherent to conducting MRI research with pediatric research participants (e.g., head movement) may be addressed using evidence-based strategies. We encourage pediatric psychology researchers to consider adopting MRI techniques to answer research questions relevant to pediatric health and illness. PMID:26141118

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

PubMed Central

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available. PMID:23847511

Correction of MRI-induced geometric distortions in whole-body small animal PET-MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frohwein, Lynn J., E-mail: frohwein@uni-muenster.de; Schäfers, Klaus P.; Hoerr, Verena

Purpose: The fusion of positron emission tomography (PET) and magnetic resonance imaging (MRI) data can be a challenging task in whole-body PET-MRI. The quality of the registration between these two modalities in large field-of-views (FOV) is often degraded by geometric distortions of the MRI data. The distortions at the edges of large FOVs mainly originate from MRI gradient nonlinearities. This work describes a method to measure and correct for these kind of geometric distortions in small animal MRI scanners to improve the registration accuracy of PET and MRI data. Methods: The authors have developed a geometric phantom which allows themore » measurement of geometric distortions in all spatial axes via control points. These control points are detected semiautomatically in both PET and MRI data with a subpixel accuracy. The spatial transformation between PET and MRI data is determined with these control points via 3D thin-plate splines (3D TPS). The transformation derived from the 3D TPS is finally applied to real MRI mouse data, which were acquired with the same scan parameters used in the phantom data acquisitions. Additionally, the influence of the phantom material on the homogeneity of the magnetic field is determined via field mapping. Results: The spatial shift according to the magnetic field homogeneity caused by the phantom material was determined to a mean of 0.1 mm. The results of the correction show that distortion with a maximum error of 4 mm could be reduced to less than 1 mm with the proposed correction method. Furthermore, the control point-based registration of PET and MRI data showed improved congruence after correction. Conclusions: The developed phantom has been shown to have no considerable negative effect on the homogeneity of the magnetic field. The proposed method yields an appropriate correction of the measured MRI distortion and is able to improve the PET and MRI registration. Furthermore, the method is applicable to whole-body small animal imaging routines including different standard MRI sequences.« less

Advancements in Orthopedic Intervention: Retrograde Drilling and Bone Grafting of Osteochondral Lesions of the Knee Using Magnetic Resonance Imaging Guidance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seebauer, Christian J., E-mail: christian.seebauer@charite.d; Bail, Hermann J., E-mail: hermann-josef.bail@klinikum-nuernberg.d; Rump, Jens C., E-mail: jens.rump@charite.de

Computer-assisted surgery is currently a novel challenge for surgeons and interventional radiologists. Magnetic resonance imaging (MRI)-guided procedures are still evolving. In this experimental study, we describe and assess an innovative passive-navigation method for MRI-guided treatment of osteochondritis dissecans of the knee. A navigation principle using a passive-navigation device was evaluated in six cadaveric knee joint specimens for potential applicability in retrograde drilling and bone grafting of osteochondral lesions using MRI guidance. Feasibility and accuracy were evaluated in an open MRI scanner (1.0 T Philips Panorama HFO MRI System). Interactive MRI navigation allowed precise drilling and bone grafting of osteochondral lesionsmore » of the knee. All lesions were hit with an accuracy of 1.86 mm in the coronal plane and 1.4 mm the sagittal plane. Targeting of all lesions was possible with a single drilling. MRI allowed excellent assessment of correct positioning of the cancellous bone cylinder during bone grafting. The navigation device and anatomic structures could be clearly identified and distinguished throughout the entire drilling procedure. MRI-assisted navigation method using a passive navigation device is feasible for the treatment of osteochondral lesions of the knee under MRI guidance and allows precise and safe drilling without exposure to ionizing radiation. This method may be a viable alternative to other navigation principles, especially for pediatric and adolescent patients. This MRI-navigated method is also potentially applicable in many other MRI-guided interventions.« less

Comparison between target magnetic resonance imaging (MRI) in-gantry and cognitively directed transperineal or transrectal-guided prostate biopsies for Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 MRI lesions.

PubMed

Yaxley, Anna J; Yaxley, John W; Thangasamy, Isaac A; Ballard, Emma; Pokorny, Morgan R

2017-11-01

To compare the detection rates of prostate cancer (PCa) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 abnormalities on 3-Tesla multiparametric (mp) magnetic resonance imaging (MRI) using in-bore MRI-guided biopsy compared with cognitively directed transperineal (cTP) biopsy and transrectal ultrasonography (cTRUS) biopsy. This was a retrospective single-centre study of consecutive men attending the private practice clinic of an experienced urologist performing MRI-guided biopsy and an experienced urologist performing cTP and cTRUS biopsy techniques for PI-RADS 3-5 lesions identified on 3-Tesla mpMRI. There were 595 target mpMRI lesions from 482 men with PI-RADS 3-5 regions of interest during 483 episodes of biopsy. The abnormal mpMRI target lesion was biopsied using the MRI-guided method for 298 biopsies, the cTP method for 248 biopsies and the cTRUS method for 49 biopsies. There were no significant differences in PCa detection among the three biopsy methods in PI-RADS 3 (48.9%, 40.0% and 44.4%, respectively), PI-RADS 4 (73.2%, 81.0% and 85.0%, respectively) or PI-RADS 5 (95.2, 92.0% and 95.0%, respectively) lesions, and there was no significant difference in detection of significant PCa among the biopsy methods in PI-RADS 3 (42.2%, 30.0% and 33.3%, respectively), PI-RADS 4 (66.8%, 66.0% and 80.0%, respectively) or PI-RADS 5 (90.5%, 89.8% and 90.0%, respectively) lesions. There were also no differences in PCa or significant PCa detection based on lesion location or size among the methods. We found no significant difference in the ability to detect PCa or significant PCa using targeted MRI-guided, cTP or cTRUS biopsy methods. Identification of an abnormal area on mpMRI appears to be more important in increasing the detection of PCa than the technique used to biopsy an MRI abnormality. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Topical Review: Unique Contributions of Magnetic Resonance Imaging to Pediatric Psychology Research.

PubMed

Jensen, Chad D; Duraccio, Kara M; Carbine, Kaylie M; Kirwan, C Brock

2016-03-01

This review aims to provide a brief introduction of the utility of magnetic resonance imaging (MRI) methods in pediatric psychology research, describe several exemplar studies that highlight the unique benefits of MRI techniques for pediatric psychology research, and detail methods for addressing several challenges inherent to pediatric MRI research. Literature review. Numerous useful applications of MRI research in pediatric psychology have been illustrated in published research. MRI methods yield information that cannot be obtained using neuropsychological or behavioral measures. Using MRI in pediatric psychology research may facilitate examination of neural structures and processes that underlie health behaviors. Challenges inherent to conducting MRI research with pediatric research participants (e.g., head movement) may be addressed using evidence-based strategies. We encourage pediatric psychology researchers to consider adopting MRI techniques to answer research questions relevant to pediatric health and illness. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times

NASA Astrophysics Data System (ADS)

Edmund, Jens M.; Kjer, Hans M.; Van Leemput, Koen; Hansen, Rasmus H.; Andersen, Jon AL; Andreasen, Daniel

2014-12-01

Radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, so-called MRI-only RT, would remove the systematic registration error between MR and computed tomography (CT), and provide co-registered MRI for assessment of treatment response and adaptive RT. Electron densities, however, need to be assigned to the MRI images for dose calculation and patient setup based on digitally reconstructed radiographs (DRRs). Here, we investigate the geometric and dosimetric performance for a number of popular voxel-based methods to generate a so-called pseudo CT (pCT). Five patients receiving cranial irradiation, each containing a co-registered MRI and CT scan, were included. An ultra short echo time MRI sequence for bone visualization was used. Six methods were investigated for three popular types of voxel-based approaches; (1) threshold-based segmentation, (2) Bayesian segmentation and (3) statistical regression. Each approach contained two methods. Approach 1 used bulk density assignment of MRI voxels into air, soft tissue and bone based on logical masks and the transverse relaxation time T2 of the bone. Approach 2 used similar bulk density assignments with Bayesian statistics including or excluding additional spatial information. Approach 3 used a statistical regression correlating MRI voxels with their corresponding CT voxels. A similar photon and proton treatment plan was generated for a target positioned between the nasal cavity and the brainstem for all patients. The CT agreement with the pCT of each method was quantified and compared with the other methods geometrically and dosimetrically using both a number of reported metrics and introducing some novel metrics. The best geometrical agreement with CT was obtained with the statistical regression methods which performed significantly better than the threshold and Bayesian segmentation methods (excluding spatial information). All methods agreed significantly better with CT than a reference water MRI comparison. The mean dosimetric deviation for photons and protons compared to the CT was about 2% and highest in the gradient dose region of the brainstem. Both the threshold based method and the statistical regression methods showed the highest dosimetrical agreement. Generation of pCTs using statistical regression seems to be the most promising candidate for MRI-only RT of the brain. Further, the total amount of different tissues needs to be taken into account for dosimetric considerations regardless of their correct geometrical position.

Advanced MRI Methods for Assessment of Chronic Liver Disease

PubMed Central

Taouli, Bachir; Ehman, Richard L.; Reeder, Scott B.

2010-01-01

MRI plays an increasingly important role for assessment of patients with chronic liver disease. MRI has numerous advantages, including lack of ionizing radiation and the possibility of performing multiparametric imaging. With recent advances in technology, advanced MRI methods such as diffusion-, perfusion-weighted MRI, MR elastography, chemical shift based fat-water separation and MR spectroscopy can now be applied to liver imaging. We will review the respective roles of these techniques for assessment of chronic liver disease. PMID:19542391

PET/MR Synchronization by Detection of Switching Gradients

NASA Astrophysics Data System (ADS)

Weissler, Bjoern; Gebhardt, Pierre; Lerche, Christoph W.; Soultanidis, Georgios M.; Wehner, Jakob; Heberling, Dirk; Schulz, Volkmar

2015-06-01

The full potential of simultaneous Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) acquisition, such as dynamic studies or motion compensation, can only be explored if the data of both modalities is temporally synchronized. As such hybrid imaging systems are commonly realized as custom-made PET inserts for commercially available MRI scanner, a synchronization solution has to be implemented (depending on the vendor of the MRI system). In contrast, we demonstrate a simple method for temporal synchronization, which does not require a connection to the MRI. It uses the normally undesired effect of induced voltages on the PET electronics from switching MRI gradients. The electronic circuit needs very few components and the gradient pick-up coils are made from PCB traces and vias on the PET detector boards. Neither programming the MRI nor any physical connection to the MR scanner is needed, thus avoiding electromagnetic compatibility problems. This method works inherently with most MRI sequences and is a vendor- independent solution. A characterization of the sensors in an MRI scanner showed that the MRI gradients are detected with a precision of 120 μs (with the current implementation). Using different trigger thresholds, it is possible to trigger selectively on certain MRI sequences, depending on their gradient slew rate settings. Timings and pulse diagrams of MRI sequences can be recognized from the generated data. The method was successfully used for temporal alignment between PET and MRI in an MRI-based PET-motion-compensation application.

Accurate and simple method for quantification of hepatic fat content using magnetic resonance imaging: a prospective study in biopsy-proven nonalcoholic fatty liver disease.

PubMed

Hatta, Tomoko; Fujinaga, Yasunari; Kadoya, Masumi; Ueda, Hitoshi; Murayama, Hiroaki; Kurozumi, Masahiro; Ueda, Kazuhiko; Komatsu, Michiharu; Nagaya, Tadanobu; Joshita, Satoru; Kodama, Ryo; Tanaka, Eiji; Uehara, Tsuyoshi; Sano, Kenji; Tanaka, Naoki

2010-12-01

To assess the degree of hepatic fat content, simple and noninvasive methods with high objectivity and reproducibility are required. Magnetic resonance imaging (MRI) is one such candidate, although its accuracy remains unclear. We aimed to validate an MRI method for quantifying hepatic fat content by calibrating MRI reading with a phantom and comparing MRI measurements in human subjects with estimates of liver fat content in liver biopsy specimens. The MRI method was performed by a combination of MRI calibration using a phantom and double-echo chemical shift gradient-echo sequence (double-echo fast low-angle shot sequence) that has been widely used on a 1.5-T scanner. Liver fat content in patients with nonalcoholic fatty liver disease (NAFLD, n = 26) was derived from a calibration curve generated by scanning the phantom. Liver fat was also estimated by optical image analysis. The correlation between the MRI measurements and liver histology findings was examined prospectively. Magnetic resonance imaging measurements showed a strong correlation with liver fat content estimated from the results of light microscopic examination (correlation coefficient 0.91, P < 0.001) regardless of the degree of hepatic steatosis. Moreover, the severity of lobular inflammation or fibrosis did not influence the MRI measurements. This MRI method is simple and noninvasive, has excellent ability to quantify hepatic fat content even in NAFLD patients with mild steatosis or advanced fibrosis, and can be performed easily without special devices.

QUESPOWR MRI: QUantification of Exchange as a function of Saturation Power On the Water Resonance

PubMed Central

Randtke, Edward A.; Pagel, Mark D.; Cárdenas-Rodríguez, Julio

2018-01-01

QUantification of Exchange as a function of Saturation Power On the Water Resonance (QUESPOWR) MRI is a new method that can estimate chemical exchange rates. This method acquires a series of OPARACHEE MRI acquisitions with a range of RF powers for the WALTZ16* pulse train, which are applied on the water resonance. A QUESPOWR plot can be generated from the power dependence of the % water signal, which is similar to a QUESP plot that is generated from CEST MRI acquisition methods with RF saturation applied off-resonance from water. A QUESPOWR plot can be quantitatively analyzed using linear fitting methods to provide estimates of average chemical exchange rates. Analyses of the shapes of QUESPOWR plots can also be used to estimate relative differences in average chemical exchange rates and concentrations of biomolecules. The performance of QUESPOWR MRI was assessed via simulations, an in vitro study with iopamidol, and an in vivo study with a mouse model of mammary carcinoma. The results showed that QUESPOWR MRI is especially sensitive to chemical exchange between water and biomolecules that have intermediate to fast chemical exchange rates and chemical shifts that are close to water, which are notoriously difficult to assess with other CEST MRI methods. In addition, in vivo QUESPOWR MRI detected acidic tumor tissues relative to normal tissues that are pH-neutral, and therefore may be a new paradigm for tumor detection with MRI. PMID:27404128

Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optshrink LR + S: accelerated fMRI reconstruction using non-convex optimal singular value shrinkage.

PubMed

Aggarwal, Priya; Shrivastava, Parth; Kabra, Tanay; Gupta, Anubha

2017-03-01

This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l 1 minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.

Comparison among T1-Weighted Magnetic Resonance Imaging, Modified Dixon Method, and Magnetic Resonance Spectroscopy in Measuring Bone Marrow Fat

PubMed Central

Shen, Wei; Gong, Xiuqun; Weiss, Jessica; Jin, Ye

2013-01-01

Introduction. An increasing number of studies are utilizing different magnetic resonance (MR) methods to quantify bone marrow fat due to its potential role in osteoporosis. Our aim is to compare the measurements of bone marrow fat among T1-weighted magnetic resonance imaging (MRI), modified Dixon method (also called fat fraction MRI (FFMRI)), and magnetic resonance spectroscopy (MRS). Methods. Contiguous MRI scans were acquired in 27 Caucasian postmenopausal women with a modified Dixon method (i.e., FFMRI). Bone marrow adipose tissue (BMAT) of T1-weighted MRI and bone marrow fat fraction of the L3 vertebra and femoral necks were quantified using SliceOmatic and Matlab. MRS was also acquired at the L3 vertebra. Results. Correlation among the three MR methods measured bone marrow fat fraction and BMAT ranges from 0.78 to 0.88 (P < 0.001) in the L3 vertebra. Correlation between BMAT measured by T1-weighted MRI and bone marrow fat fraction measured by modified FFMRI is 0.86 (P < 0.001) in femoral necks. Conclusion. There are good correlations among T1-weighted MRI, FFMRI, and MRS for bone marrow fat quantification. The inhomogeneous distribution of bone marrow fat, the threshold segmentation of the T1-weighted MRI, and the ambiguity of the FFMRI may partially explain the difference among the three methods. PMID:23606951

A Novel Marker Based Method to Teeth Alignment in MRI

NASA Astrophysics Data System (ADS)

Luukinen, Jean-Marc; Aalto, Daniel; Malinen, Jarmo; Niikuni, Naoko; Saunavaara, Jani; Jääsaari, Päivi; Ojalammi, Antti; Parkkola, Riitta; Soukka, Tero; Happonen, Risto-Pekka

2018-04-01

Magnetic resonance imaging (MRI) can precisely capture the anatomy of the vocal tract. However, the crowns of teeth are not visible in standard MRI scans. In this study, a marker-based teeth alignment method is presented and evaluated. Ten patients undergoing orthognathic surgery were enrolled. Supraglottal airways were imaged preoperatively using structural MRI. MRI visible markers were developed, and they were attached to maxillary teeth and corresponding locations on the dental casts. Repeated measurements of intermarker distances in MRI and in a replica model was compared using linear regression analysis. Dental cast MRI and corresponding caliper measurements did not differ significantly. In contrast, the marker locations in vivo differed somewhat from the dental cast measurements likely due to marker placement inaccuracies. The markers were clearly visible in MRI and allowed for dental models to be aligned to head and neck MRI scans.

Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets.

PubMed

Guy, Joseph R; Sati, Pascal; Leibovitch, Emily; Jacobson, Steven; Silva, Afonso C; Reich, Daniel S

2016-01-15

MRI has the advantage of sampling large areas of tissue and locating areas of interest in 3D space in both living and ex vivo systems, whereas histology has the ability to examine thin slices of ex vivo tissue with high detail and specificity. Although both are valuable tools, it is currently difficult to make high-precision comparisons between MRI and histology due to large differences inherent to the techniques. A method combining the advantages would be an asset to understanding the pathological correlates of MRI. 3D-printed brain holders were used to maintain marmoset brains in the same orientation during acquisition of ex vivo MRI and pathologic cutting of the tissue. The results of maintaining this same orientation show that sub-millimeter, discrete neuropathological features in marmoset brain consistently share size, shape, and location between histology and ex vivo MRI, which facilitates comparison with serial imaging acquired in vivo. Existing methods use computational approaches sensitive to data input in order to warp histologic images to match large-scale features on MRI, but the new method requires no warping of images, due to a preregistration accomplished in the technique, and is insensitive to data formatting and artifacts in both MRI and histology. The simple method of using 3D-printed brain holders to match brain orientation during pathologic sectioning and MRI acquisition enables rapid and precise comparison of small features seen on MRI to their underlying histology. Published by Elsevier B.V.

A new method based on Dempster-Shafer theory and fuzzy c-means for brain MRI segmentation

NASA Astrophysics Data System (ADS)

Liu, Jie; Lu, Xi; Li, Yunpeng; Chen, Xiaowu; Deng, Yong

2015-10-01

In this paper, a new method is proposed to decrease sensitiveness to motion noise and uncertainty in magnetic resonance imaging (MRI) segmentation especially when only one brain image is available. The method is approached with considering spatial neighborhood information by fusing the information of pixels with their neighbors with Dempster-Shafer (DS) theory. The basic probability assignment (BPA) of each single hypothesis is obtained from the membership function of applying fuzzy c-means (FCM) clustering to the gray levels of the MRI. Then multiple hypotheses are generated according to the single hypothesis. Then we update the objective pixel’s BPA by fusing the BPA of the objective pixel and those of its neighbors to get the final result. Some examples in MRI segmentation are demonstrated at the end of the paper, in which our method is compared with some previous methods. The results show that the proposed method is more effective than other methods in motion-blurred MRI segmentation.

Novel MRI tests of orocecal transit time and whole gut transit time: studies in normal subjects

PubMed Central

Chaddock, G; Lam, C; Hoad, C L; Costigan, C; Cox, E F; Placidi, E; Thexton, I; Wright, J; Blackshaw, P E; Perkins, A C; Marciani, L; Gowland, P A; Spiller, R C

2014-01-01

Background Colonic transit tests are used to manage patients with Functional Gastrointestinal Disorders. Some tests used expose patients to ionizing radiation. The aim of this study was to compare novel magnetic resonance imaging (MRI) tests for measuring orocecal transit time (OCTT) and whole gut transit time (WGT), which also provide data on colonic volumes. Methods 21 healthy volunteers participated. Study 1: OCTT was determined from the arrival of the head of a meal into the cecum using MRI and the Lactose Ureide breath test (LUBT), performed concurrently. Study 2: WGT was assessed using novel MRI marker capsules and radio-opaque markers (ROMs), taken on the same morning. Studies were repeated 1 week later. Key Results OCTT measured using MRI and LUBT was 225 min (IQR 180–270) and 225 min (IQR 165–278), respectively, correlation rs = 0.28 (ns). WGT measured using MRI marker capsules and ROMs was 28 h (IQR 4–50) and 31 h ± 3 (SEM), respectively, correlation rs = 0.85 (p < 0.0001). Repeatability assessed using the intraclass correlation coefficient (ICC) was 0.45 (p = 0.017) and 0.35 (p = 0.058) for MRI and LUBT OCTT tests. Better repeatability was observed for the WGT tests, ICC being 0.61 for the MRI marker capsules (p = 0.001) and 0.69 for the ROM method (p < 0.001) respectively. Conclusions & Inferences The MRI WGT method is simple, convenient, does not use X-ray and compares well with the widely used ROM method. Both OCTT measurements showed modest reproducibility and the MRI method showed modest inter-observer agreement. PMID:24165044

MR Imaging-based Semi-quantitative Methods for Knee Osteoarthritis

PubMed Central

JARRAYA, Mohamed; HAYASHI, Daichi; ROEMER, Frank Wolfgang; GUERMAZI, Ali

2016-01-01

Magnetic resonance imaging (MRI)-based semi-quantitative (SQ) methods applied to knee osteoarthritis (OA) have been introduced during the last decade and have fundamentally changed our understanding of knee OA pathology since then. Several epidemiological studies and clinical trials have used MRI-based SQ methods to evaluate different outcome measures. Interest in MRI-based SQ scoring system has led to continuous update and refinement. This article reviews the different SQ approaches for MRI-based whole organ assessment of knee OA and also discuss practical aspects of whole joint assessment. PMID:26632537

The evolving role of MRI in the assessment of coronary artery disease.

PubMed

Blackwell, G G; Pohost, G M

1995-04-13

Magnetic resonance imaging (MRI) methods are positioned to make a major impact in the care of patients with ischemic heart disease. Further advances are to be expected in the area of myocardial perfusion imaging and noninvasive MRI coronary "angiography." Work also continues in determining quantitative flow via MRI. Although expensive, the unique ability of MRI methods to provide multiple pieces of information in a single examination may make this technology cost effective. The concept of a "one-step shop" is progressing steadily toward a clinical reality.

Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with MR spectroscopy as a reference.

PubMed

Haufe, William M; Wolfson, Tanya; Hooker, Catherine A; Hooker, Jonathan C; Covarrubias, Yesenia; Schlein, Alex N; Hamilton, Gavin; Middleton, Michael S; Angeles, Jorge E; Hernando, Diego; Reeder, Scott B; Schwimmer, Jeffrey B; Sirlin, Claude B

2017-12-01

To assess and compare the accuracy of magnitude-based magnetic resonance imaging (MRI-M) and complex-based MRI (MRI-C) for estimating hepatic proton density fat fraction (PDFF) in children, using MR spectroscopy (MRS) as the reference standard. A secondary aim was to assess the agreement between MRI-M and MRI-C. This was a HIPAA-compliant, retrospective analysis of data collected in children enrolled in prospective, Institutional Review Board (IRB)-approved studies between 2012 and 2014. Informed consent was obtained from 200 children (ages 8-19 years) who subsequently underwent 3T MR exams that included MRI-M, MRI-C, and T 1 -independent, T 2 -corrected, single-voxel stimulated echo acquisition mode (STEAM) MRS. Both MRI methods acquired six echoes at low flip angles. T2*-corrected PDFF parametric maps were generated. PDFF values were recorded from regions of interest (ROIs) drawn on the maps in each of the nine Couinaud segments and three ROIs colocalized to the MRS voxel location. Regression analyses assessing agreement with MRS were performed to evaluate the accuracy of each MRI method, and Bland-Altman and intraclass correlation coefficient (ICC) analyses were performed to assess agreement between the MRI methods. MRI-M and MRI-C PDFF were accurate relative to the colocalized MRS reference standard, with regression intercepts of 0.63% and -0.07%, slopes of 0.998 and 0.975, and proportion-of-explained-variance values (R 2 ) of 0.982 and 0.979, respectively. For individual Couinaud segments and for the whole liver averages, Bland-Altman biases between MRI-M and MRI-C were small (ranging from 0.04 to 1.11%) and ICCs were high (≥0.978). Both MRI-M and MRI-C accurately estimated hepatic PDFF in children, and high intermethod agreement was observed. 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1641-1647. © 2017 International Society for Magnetic Resonance in Medicine.

Inner experience in the scanner: can high fidelity apprehensions of inner experience be integrated with fMRI?

PubMed Central

Kühn, Simone; Fernyhough, Charles; Alderson-Day, Benjamin; Hurlburt, Russell T.

2014-01-01

To provide full accounts of human experience and behavior, research in cognitive neuroscience must be linked to inner experience, but introspective reports of inner experience have often been found to be unreliable. The present case study aimed at providing proof of principle that introspection using one method, descriptive experience sampling (DES), can be reliably integrated with fMRI. A participant was trained in the DES method, followed by nine sessions of sampling within an MRI scanner. During moments where the DES interview revealed ongoing inner speaking, fMRI data reliably showed activation in classic speech processing areas including left inferior frontal gyrus. Further, the fMRI data validated the participant’s DES observations of the experiential distinction between inner speaking and innerly hearing her own voice. These results highlight the precision and validity of the DES method as a technique of exploring inner experience and the utility of combining such methods with fMRI. PMID:25538649

Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

NASA Astrophysics Data System (ADS)

Choi, Jinhyeok; Kim, Hyeonjin

2016-12-01

To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

Comparison among T1-weighted magnetic resonance imaging, modified dixon method, and magnetic resonance spectroscopy in measuring bone marrow fat.

PubMed

Shen, Wei; Gong, Xiuqun; Weiss, Jessica; Jin, Ye

2013-01-01

An increasing number of studies are utilizing different magnetic resonance (MR) methods to quantify bone marrow fat due to its potential role in osteoporosis. Our aim is to compare the measurements of bone marrow fat among T1-weighted magnetic resonance imaging (MRI), modified Dixon method (also called fat fraction MRI (FFMRI)), and magnetic resonance spectroscopy (MRS). Contiguous MRI scans were acquired in 27 Caucasian postmenopausal women with a modified Dixon method (i.e., FFMRI). Bone marrow adipose tissue (BMAT) of T1-weighted MRI and bone marrow fat fraction of the L3 vertebra and femoral necks were quantified using SliceOmatic and Matlab. MRS was also acquired at the L3 vertebra. Correlation among the three MR methods measured bone marrow fat fraction and BMAT ranges from 0.78 to 0.88 (P < 0.001) in the L3 vertebra. Correlation between BMAT measured by T1-weighted MRI and bone marrow fat fraction measured by modified FFMRI is 0.86 (P < 0.001) in femoral necks. There are good correlations among T1-weighted MRI, FFMRI, and MRS for bone marrow fat quantification. The inhomogeneous distribution of bone marrow fat, the threshold segmentation of the T1-weighted MRI, and the ambiguity of the FFMRI may partially explain the difference among the three methods.

Quantification of liver fat with respiratory-gated quantitative chemical shift encoded MRI.

PubMed

Motosugi, Utaroh; Hernando, Diego; Bannas, Peter; Holmes, James H; Wang, Kang; Shimakawa, Ann; Iwadate, Yuji; Taviani, Valentina; Rehm, Jennifer L; Reeder, Scott B

2015-11-01

To evaluate free-breathing chemical shift-encoded (CSE) magnetic resonance imaging (MRI) for quantification of hepatic proton density fat-fraction (PDFF). A secondary purpose was to evaluate hepatic R2* values measured using free-breathing quantitative CSE-MRI. Fifty patients (mean age, 56 years) were prospectively recruited and underwent the following four acquisitions to measure PDFF and R2*; 1) conventional breath-hold CSE-MRI (BH-CSE); 2) respiratory-gated CSE-MRI using respiratory bellows (BL-CSE); 3) respiratory-gated CSE-MRI using navigator echoes (NV-CSE); and 4) single voxel MR spectroscopy (MRS) as the reference standard for PDFF. Image quality was evaluated by two radiologists. MRI-PDFF measured from the three CSE-MRI methods were compared with MRS-PDFF using linear regression. The PDFF and R2* values were compared using two one-sided t-test to evaluate statistical equivalence. There was no significant difference in the image quality scores among the three CSE-MRI methods for either PDFF (P = 1.000) or R2* maps (P = 0.359-1.000). Correlation coefficients (95% confidence interval [CI]) for the PDFF comparisons were 0.98 (0.96-0.99) for BH-, 0.99 (0.97-0.99) for BL-, and 0.99 (0.98-0.99) for NV-CSE. The statistical equivalence test revealed that the mean difference in PDFF and R2* between any two of the three CSE-MRI methods was less than ±1 percentage point (pp) and ±5 s(-1) , respectively (P < 0.046). Respiratory-gated CSE-MRI with respiratory bellows or navigator echo are feasible methods to quantify liver PDFF and R2* and are as valid as the standard breath-hold technique. © 2015 Wiley Periodicals, Inc.

Fully Automated Prostate Magnetic Resonance Imaging and Transrectal Ultrasound Fusion via a Probabilistic Registration Metric.

PubMed

Sparks, Rachel; Bloch, B Nicolas; Feleppa, Ernest; Barratt, Dean; Madabhushi, Anant

2013-03-08

In this work, we present a novel, automated, registration method to fuse magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) images of the prostate. Our methodology consists of: (1) delineating the prostate on MRI, (2) building a probabilistic model of prostate location on TRUS, and (3) aligning the MRI prostate segmentation to the TRUS probabilistic model. TRUS-guided needle biopsy is the current gold standard for prostate cancer (CaP) diagnosis. Up to 40% of CaP lesions appear isoechoic on TRUS, hence TRUS-guided biopsy cannot reliably target CaP lesions and is associated with a high false negative rate. MRI is better able to distinguish CaP from benign prostatic tissue, but requires special equipment and training. MRI-TRUS fusion, whereby MRI is acquired pre-operatively and aligned to TRUS during the biopsy procedure, allows for information from both modalities to be used to help guide the biopsy. The use of MRI and TRUS in combination to guide biopsy at least doubles the yield of positive biopsies. Previous work on MRI-TRUS fusion has involved aligning manually determined fiducials or prostate surfaces to achieve image registration. The accuracy of these methods is dependent on the reader's ability to determine fiducials or prostate surfaces with minimal error, which is a difficult and time-consuming task. Our novel, fully automated MRI-TRUS fusion method represents a significant advance over the current state-of-the-art because it does not require manual intervention after TRUS acquisition. All necessary preprocessing steps (i.e. delineation of the prostate on MRI) can be performed offline prior to the biopsy procedure. We evaluated our method on seven patient studies, with B-mode TRUS and a 1.5 T surface coil MRI. Our method has a root mean square error (RMSE) for expertly selected fiducials (consisting of the urethra, calcifications, and the centroids of CaP nodules) of 3.39 ± 0.85 mm.

Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

PubMed

Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

2008-12-01

Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

An automated method for identifying artifact in independent component analysis of resting-state FMRI.

PubMed

Bhaganagarapu, Kaushik; Jackson, Graeme D; Abbott, David F

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.

Instrumentation and method for measuring NIR light absorbed in tissue during MR imaging in medical NIRS measurements

NASA Astrophysics Data System (ADS)

Myllylä, Teemu S.; Sorvoja, Hannu S. S.; Nikkinen, Juha; Tervonen, Osmo; Kiviniemi, Vesa; Myllylä, Risto A.

2011-07-01

Our goal is to provide a cost-effective method for examining human tissue, particularly the brain, by the simultaneous use of functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). Due to its compatibility requirements, MRI poses a demanding challenge for NIRS measurements. This paper focuses particularly on presenting the instrumentation and a method for the non-invasive measurement of NIR light absorbed in human tissue during MR imaging. One practical method to avoid disturbances in MR imaging involves using long fibre bundles to enable conducting the measurements at some distance from the MRI scanner. This setup serves in fact a dual purpose, since also the NIRS device will be less disturbed by the MRI scanner. However, measurements based on long fibre bundles suffer from light attenuation. Furthermore, because one of our primary goals was to make the measuring method as cost-effective as possible, we used high-power light emitting diodes instead of more expensive lasers. The use of LEDs, however, limits the maximum output power which can be extracted to illuminate the tissue. To meet these requirements, we improved methods of emitting light sufficiently deep into tissue. We also show how to measure NIR light of a very small power level that scatters from the tissue in the MRI environment, which is characterized by strong electromagnetic interference. In this paper, we present the implemented instrumentation and measuring method and report on test measurements conducted during MRI scanning. These measurements were performed in MRI operating rooms housing 1.5 Tesla-strength closed MRI scanners (manufactured by GE) in the Dept. of Diagnostic Radiology at the Oulu University Hospital.

[MRI semiotics features of experimental acute intracerebral hematomas].

PubMed

Burenchev, D V; Skvortsova, V I; Tvorogova, T V; Guseva, O I; Gubskiĭ, L V; Kupriianov, D A; Pirogov, Iu A

2009-01-01

The aim of this study was to assess the possibility of revealing intracerebral hematomas (ICH), using MRI, within the first hours after onset and to determine their MRI semiotics features. Thirty animals with experimental ICH were studied. A method of two-stage introduction of autologous blood was used to develop ICH as human spontaneous intracranial hematomas. Within 3-5h after blood introduction to the rat brain. The control MRI was performed in the 3rd and 7th days after blood injections. ICH were definitely identified in the first MRI scans. The MRI semiotics features of acute ICH and their transformations were assessed. The high sensitivity of MRI to ICH as well as the uniform manifestations in all animals were shown. In conclusion, the method has high specificity for acute ICH detection.

Dictionary learning and time sparsity in dynamic MRI.

PubMed

Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

2012-01-01

Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

A comparison between EEG source localization and fMRI during the processing of emotional visual stimuli

NASA Astrophysics Data System (ADS)

Hu, Jin; Tian, Jie; Pan, Xiaohong; Liu, Jiangang

2007-03-01

The purpose of this paper is to compare between EEG source localization and fMRI during emotional processing. 108 pictures for EEG (categorized as positive, negative and neutral) and 72 pictures for fMRI were presented to 24 healthy, right-handed subjects. The fMRI data were analyzed using statistical parametric mapping with SPM2. LORETA was applied to grand averaged ERP data to localize intracranial sources. Statistical analysis was implemented to compare spatiotemporal activation of fMRI and EEG. The fMRI results are in accordance with EEG source localization to some extent, while part of mismatch in localization between the two methods was also observed. In the future we should apply the method for simultaneous recording of EEG and fMRI to our study.

Reproducibility of MR-Based Liver Fat Quantification Across Field Strength: Same-Day Comparison Between 1.5T and 3T in Obese Subjects

PubMed Central

Artz, Nathan S.; Haufe, William M.; Hooker, Catherine A.; Hamilton, Gavin; Wolfson, Tanya; Campos, Guilherme M.; Gamst, Anthony C.; Schwimmer, Jeffrey B.; Sirlin, Claude B.; Reeder, Scott B.

2016-01-01

Purpose To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths. Materials and Methods This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38–53 kg/m2) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths. Results 1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R2 values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = −1.4 [−2.4, −0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [−0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R2 = 0.98 (m = 1.1 [1.02, 1.16], b = −1.8 [−2.8, −1.1]) at 1.5T, and R2 = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T. Conclusion This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods. PMID:25620624

Computing moment to moment BOLD activation for real-time neurofeedback

PubMed Central

Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W.; Yoo, Julie J.; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D.E.

2013-01-01

Estimating moment to moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment to moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment to moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI timeseries, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method. PMID:20682350

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Myocardial perfusion quantification using simultaneously acquired 13 NH3 -ammonia PET and dynamic contrast-enhanced MRI in patients at rest and stress.

PubMed

Kunze, Karl P; Nekolla, Stephan G; Rischpler, Christoph; Zhang, Shelley HuaLei; Hayes, Carmel; Langwieser, Nicolas; Ibrahim, Tareq; Laugwitz, Karl-Ludwig; Schwaiger, Markus

2018-04-19

Systematic differences with respect to myocardial perfusion quantification exist between DCE-MRI and PET. Using the potential of integrated PET/MRI, this study was conceived to compare perfusion quantification on the basis of simultaneously acquired 13 NH 3 -ammonia PET and DCE-MRI data in patients at rest and stress. Twenty-nine patients were examined on a 3T PET/MRI scanner. DCE-MRI was implemented in dual-sequence design and additional T 1 mapping for signal normalization. Four different deconvolution methods including a modified version of the Fermi technique were compared against 13 NH 3 -ammonia results. Cohort-average flow comparison yielded higher resting flows for DCE-MRI than for PET and, therefore, significantly lower DCE-MRI perfusion ratios under the common assumption of equal arterial and tissue hematocrit. Absolute flow values were strongly correlated in both slice-average (R 2  = 0.82) and regional (R 2  = 0.7) evaluations. Different DCE-MRI deconvolution methods yielded similar flow result with exception of an unconstrained Fermi method exhibiting outliers at high flows when compared with PET. Thresholds for Ischemia classification may not be directly tradable between PET and MRI flow values. Differences in perfusion ratios between PET and DCE-MRI may be lifted by using stress/rest-specific hematocrit conversion. Proper physiological constraints are advised in model-constrained deconvolution. © 2018 International Society for Magnetic Resonance in Medicine.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

SU-E-J-221: A Novel Expansion Method for MRI Based Target Delineation in Prostate Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruiz, B; East Carolina University, Greenville, NC; Feng, Y

Purpose: To compare a novel bladder/rectum carveout expansion method on MRI delineated prostate to standard CT and expansion based methods for maintaining prostate coverage while providing superior bladder and rectal sparing. Methods: Ten prostate cases were planned to include four trials: MRI vs CT delineated prostate/proximal seminal vesicles, and each image modality compared to both standard expansions (8mm 3D expansion and 5mm posterior, i.e. ∼8mm) and carveout method expansions (5mm 3D expansion, 4mm posterior for GTV-CTV excluding expansion into bladder/rectum followed by additional 5mm 3D expansion to PTV, i.e. ∼1cm). All trials were planned to total dose 7920 cGy viamore » IMRT. Evaluation and comparison was made using the following criteria: QUANTEC constraints for bladder/rectum including analysis of low dose regions, changes in PTV volume, total control points, and maximum hot spot. Results: ∼8mm MRI expansion consistently produced the most optimal plan with lowest total control points and best bladder/rectum sparing. However, this scheme had the smallest prostate (average 22.9% reduction) and subsequent PTV volume, consistent with prior literature. ∼1cm MRI had an average PTV volume comparable to ∼8mm CT at 3.79% difference. Bladder QUANTEC constraints were on average less for the ∼1cm MRI as compared to the ∼8mm CT and observed as statistically significant with 2.64% reduction in V65. Rectal constraints appeared to follow the same trend. Case-by-case analysis showed variation in rectal V30 with MRI delineated prostate being most favorable regardless of expansion type. ∼1cm MRI and ∼8mm CT had comparable plan quality. Conclusion: MRI delineated prostate with standard expansions had the smallest PTV leading to margins that may be too tight. Bladder/rectum carveout expansion method on MRI delineated prostate was found to be superior to standard CT based methods in terms of bladder and rectal sparing while maintaining prostate coverage. Continued investigation is warranted for further validation.« less

Hepatic fat quantification using the two-point Dixon method and fat color maps based on non-alcoholic fatty liver disease activity score.

PubMed

Hayashi, Tatsuya; Saitoh, Satoshi; Takahashi, Junji; Tsuji, Yoshinori; Ikeda, Kenji; Kobayashi, Masahiro; Kawamura, Yusuke; Fujii, Takeshi; Inoue, Masafumi; Miyati, Tosiaki; Kumada, Hiromitsu

2017-04-01

The two-point Dixon method for magnetic resonance imaging (MRI) is commonly used to non-invasively measure fat deposition in the liver. The aim of the present study was to assess the usefulness of MRI-fat fraction (MRI-FF) using the two-point Dixon method based on the non-alcoholic fatty liver disease activity score. This retrospective study included 106 patients who underwent liver MRI and MR spectroscopy, and 201 patients who underwent liver MRI and histological assessment. The relationship between MRI-FF and MR spectroscopy-fat fraction was used to estimate the corrected MRI-FF for hepatic multi-peaks of fat. Then, a color FF map was generated with the corrected MRI-FF based on the non-alcoholic fatty liver disease activity score. We defined FF variability as the standard deviation of FF in regions of interest. Uniformity of hepatic fat was visually graded on a three-point scale using both gray-scale and color FF maps. Confounding effects of histology (iron, inflammation and fibrosis) on corrected MRI-FF were assessed by multiple linear regression. The linear correlations between MRI-FF and MR spectroscopy-fat fraction, and between corrected MRI-FF and histological steatosis were strong (R 2  = 0.90 and R 2  = 0.88, respectively). Liver fat variability significantly increased with visual fat uniformity grade using both of the maps (ρ = 0.67-0.69, both P < 0.001). Hepatic iron, inflammation and fibrosis had no significant confounding effects on the corrected MRI-FF (all P > 0.05). The two-point Dixon method and the gray-scale or color FF maps based on the non-alcoholic fatty liver disease activity score were useful for fat quantification in the liver of patients without severe iron deposition. © 2016 The Japan Society of Hepatology.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

Removal of intensity bias in magnitude spin-echo MRI images by nonlinear diffusion filtering

NASA Astrophysics Data System (ADS)

Samsonov, Alexei A.; Johnson, Chris R.

2004-05-01

MRI data analysis is routinely done on the magnitude part of complex images. While both real and imaginary image channels contain Gaussian noise, magnitude MRI data are characterized by Rice distribution. However, conventional filtering methods often assume image noise to be zero mean and Gaussian distributed. Estimation of an underlying image using magnitude data produces biased result. The bias may lead to significant image errors, especially in areas of low signal-to-noise ratio (SNR). The incorporation of the Rice PDF into a noise filtering procedure can significantly complicate the method both algorithmically and computationally. In this paper, we demonstrate that inherent image phase smoothness of spin-echo MRI images could be utilized for separate filtering of real and imaginary complex image channels to achieve unbiased image denoising. The concept is demonstrated with a novel nonlinear diffusion filtering scheme developed for complex image filtering. In our proposed method, the separate diffusion processes are coupled through combined diffusion coefficients determined from the image magnitude. The new method has been validated with simulated and real MRI data. The new method has provided efficient denoising and bias removal in conventional and black-blood angiography MRI images obtained using fast spin echo acquisition protocols.

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

MRI-based methods for quantification of the cerebral metabolic rate of oxygen

PubMed Central

Rodgers, Zachary B; Detre, John A

2016-01-01

The brain depends almost entirely on oxidative metabolism to meet its significant energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) represents a key measure of brain function. Quantification of CMRO2 has helped elucidate brain functional physiology and holds potential as a clinical tool for evaluating neurological disorders including stroke, brain tumors, Alzheimer’s disease, and obstructive sleep apnea. In recent years, a variety of magnetic resonance imaging (MRI)-based CMRO2 quantification methods have emerged. Unlike positron emission tomography – the current “gold standard” for measurement and mapping of CMRO2 – MRI is non-invasive, relatively inexpensive, and ubiquitously available in modern medical centers. All MRI-based CMRO2 methods are based on modeling the effect of paramagnetic deoxyhemoglobin on the magnetic resonance signal. The various methods can be classified in terms of the MRI contrast mechanism used to quantify CMRO2: T2*, T2′, T2, or magnetic susceptibility. This review article provides an overview of MRI-based CMRO2 quantification techniques. After a brief historical discussion motivating the need for improved CMRO2 methodology, current state-of-the-art MRI-based methods are critically appraised in terms of their respective tradeoffs between spatial resolution, temporal resolution, and robustness, all of critical importance given the spatially heterogeneous and temporally dynamic nature of brain energy requirements. PMID:27089912

PET/MRI for neurologic applications.

PubMed

Catana, Ciprian; Drzezga, Alexander; Heiss, Wolf-Dieter; Rosen, Bruce R

2012-12-01

PET and MRI provide complementary information in the study of the human brain. Simultaneous PET/MRI data acquisition allows the spatial and temporal correlation of the measured signals, creating opportunities impossible to realize using stand-alone instruments. This paper reviews the methodologic improvements and potential neurologic and psychiatric applications of this novel technology. We first present methods for improving the performance and information content of each modality by using the information provided by the other technique. On the PET side, we discuss methods that use the simultaneously acquired MRI data to improve the PET data quantification. On the MRI side, we present how improved PET quantification can be used to validate several MRI techniques. Finally, we describe promising research, translational, and clinical applications that can benefit from these advanced tools.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

WE-AB-BRA-09: Registration of Preoperative MRI to Intraoperative Radiographs for Automatic Vertebral Target Localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Silva, T; Uneri, A; Ketcha, M

Purpose: Accurate localization of target vertebrae is essential to safe, effective spine surgery, but wrong-level surgery occurs with surprisingly high frequency. Recent research yielded the “LevelCheck” method for 3D-2D registration of preoperative CT to intraoperative radiographs, providing decision support for level localization. We report a new method (MR-LevelCheck) to perform 3D-2D registration based on preoperative MRI, presenting a solution for the increasingly common scenario in which MRI (not CT) is used for preoperative planning. Methods: Direct extension of LevelCheck is confounded by large mismatch in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simplemore » vertebrae segmentation. Using seed points at centroids, vertebrae are segmented using continuous max-flow method and dilated by 1.8 mm to include surrounding cortical bone (inconspicuous in T2w-MRI). MRI projections are computed (analogous to DRR) using segmentation and registered to intraoperative radiographs. The method was tested in a retrospective IRB-approved study involving 11 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Registration accuracy was evaluated in terms of projection-distance-error (PDE) between the true and estimated location of vertebrae in each radiograph. Results: The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch, and large capture range. Segmentation achieved Dice coefficient = 89.2 ± 2.3 and mean-absolute-distance (MAD) = 1.5 ± 0.3 mm. Registration demonstrated robust performance under realistic patient variations, with PDE = 4.0 ± 1.9 mm (median ± iqr) and converged with run-time = 23.3 ± 1.7 s. Conclusion: The MR-LevelCheck algorithm provides an important extension to a previously validated decision support tool in spine surgery by extending its utility to preoperative MRI. With initial studies demonstrating PDE <5 mm and 0% failure rate, the method is now in translation to larger scale prospective clinical studies. S. Vogt and G. Kleinszig are employees of Siemens Healthcare.« less

Intra- and inter-examination repeatability of magnetic resonance spectroscopy, magnitude-based MRI, and complex-based MRI for estimation of hepatic proton density fat fraction in overweight and obese children and adults

PubMed Central

Tyagi, Avishkar; Yeganeh, Omid; Levin, Yakir; Hooker, Jonathan C.; Hamilton, Gavin C.; Wolfson, Tanya; Gamst, Anthony; Zand, Amir K.; Heba, Elhamy; Loomba, Rohit; Schwimmer, Jeffrey; Middleton, Michael S.; Sirlin, Claude B.

2016-01-01

Purpose Determine intra- and inter-examination repeatability of magnitude-based magnetic resonance imaging (MRI-M), complex-based magnetic resonance imaging (MRI-C), and magnetic resonance spectroscopy (MRS) at 3T for estimating hepatic proton density fat fraction (PDFF), and using MRS as a reference, confirm MRI-M and MRI-C accuracy. Methods Twenty-nine overweight and obese pediatric (n = 20) and adult (n = 9) subjects (23 male, 6 female) underwent three same-day 3T MR examinations. In each examination MRI-M, MRI-C, and single-voxel MRS were acquired three times. For each MRI acquisition, hepatic PDFF was estimated at the MRS voxel location. Intra- and inter-examination repeatability were assessed by computing standard deviations (SDs) and intra-class correlation coefficients (ICCs). Aggregate SD was computed for each method as the square root of the average of first repeat variances. MRI-M and MRI-C PDFF estimation accuracy was assessed using linear regression with MRS as a reference. Results For MRI-M, MRI-C, and MRS acquisitions, respectively, mean intra-examination SDs were 0.25%, 0.42%, and 0.49%; mean intra-examination ICCs were 0.999, 0.997, and 0.995; mean inter-examination SDs were 0.42%, 0.45%, and 0.46%; and inter-examination ICCs were 0.995, 0.992, and 0.990. Aggregate SD for each method was <0.9%. Using MRS as a reference, regression slope, intercept, average bias, and R2, respectively, for MRI-M were 0.99%, 1.73%, 1.61%, and 0.986, and for MRI-C were 0.96%, 0.43%, 0.40%, and 0.991. Conclusion MRI-M, MRI-C, and MRS showed high intra- and inter-examination hepatic PDFF estimation repeatability in overweight and obese subjects. Longitudinal hepatic PDFF change >1.8% (twice the maximum aggregate SD) may represent real change rather than measurement imprecision. Further research is needed to assess whether examinations performed on different days or with different MR technologists affect repeatability of MRS voxel placement and MRS-based PDFF measurements. PMID:26350282

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

PubMed

Liu, Fang; Velikina, Julia V; Block, Walter F; Kijowski, Richard; Samsonov, Alexey A

2017-02-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed  ∼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

PubMed Central

Velikina, Julia V.; Block, Walter F.; Kijowski, Richard; Samsonov, Alexey A.

2017-01-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure. PMID:28113746

Registration of MRI to Intraoperative Radiographs for Target Localization in Spinal Interventions

PubMed Central

De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Goerres, J; Jacobson, M W; Vogt, S; Kleinszig, G; Khanna, A J; Wolinsky, J-P; Siewerdsen, J H

2017-01-01

Purpose Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Methods Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (Covariance-Matrix-Adaptation Evolutionary-Strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Results The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median ± iqr) = 4.3 ± 2.6 mm (median ± iqr) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded Dice coefficient = 88.1 ± 5.2, Accuracy = 90.6 ± 5.7, RMSE = 1.8 ± 0.6 mm, and contour affinity ratio (CAR) = 0.82 ± 0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE < 3 mm and CAR > 0.50. Conclusion The MR-LevelCheck method provides a potentially valuable extension to a previously developed decision support tool for spine surgery target localization by extending its utility to preoperative MRI while maintaining characteristics of accuracy and robustness. PMID:28050972

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

PCA-based groupwise image registration for quantitative MRI.

PubMed

Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

2016-04-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI. Copyright © 2015 Elsevier B.V. All rights reserved.

Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

PubMed

Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H

2009-01-01

Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.

Reproducibility of MR-based liver fat quantification across field strength: Same-day comparison between 1.5T and 3T in obese subjects.

PubMed

Artz, Nathan S; Haufe, William M; Hooker, Catherine A; Hamilton, Gavin; Wolfson, Tanya; Campos, Guilherme M; Gamst, Anthony C; Schwimmer, Jeffrey B; Sirlin, Claude B; Reeder, Scott B

2015-09-01

To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths. This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38-53 kg/m(2) ) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths. 1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R(2) values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = -1.4 [-2.4, -0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [-0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R(2)  = 0.98 (m = 1.1 [1.02, 1.16], b = -1.8 [-2.8, -1.1]) at 1.5T, and R(2)  = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T. This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods. © 2015 Wiley Periodicals, Inc.

Vessel wall characterization using quantitative MRI: what's in a number?

PubMed

Coolen, Bram F; Calcagno, Claudia; van Ooij, Pim; Fayad, Zahi A; Strijkers, Gustav J; Nederveen, Aart J

2018-02-01

The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

MRI in ocular drug delivery

PubMed Central

Li, S. Kevin; Lizak, Martin J.; Jeong, Eun-Kee

2008-01-01

Conventional pharmacokinetic methods for studying ocular drug delivery are invasive and cannot be conveniently applied to humans. The advancement of MRI technology has provided new opportunities in ocular drug-delivery research. MRI provides a means to non-invasively and continuously monitor ocular drug-delivery systems with a contrast agent or compound labeled with a contrast agent. It is a useful technique in pharmacokinetic studies, evaluation of drug-delivery methods, and drug-delivery device testing. Although the current status of the technology presents some major challenges to pharmaceutical research using MRI, it has a lot of potential. In the past decade, MRI has been used to examine ocular drug delivery via the subconjunctival route, intravitreal injection, intrascleral injection to the suprachoroidal space, episcleral and intravitreal implants, periocular injections, and ocular iontophoresis. In this review, the advantages and limitations of MRI in the study of ocular drug delivery are discussed. Different MR contrast agents and MRI techniques for ocular drug-delivery research are compared. Ocular drug-delivery studies using MRI are reviewed. PMID:18186077

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

EEG-Informed fMRI: A Review of Data Analysis Methods

PubMed Central

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy

NASA Astrophysics Data System (ADS)

Grova, C.; Jannin, P.; Biraben, A.; Buvat, I.; Benali, H.; Bernard, A. M.; Scarabin, J. M.; Gibaud, B.

2003-12-01

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Three-dimensional liver motion tracking using real-time two-dimensional MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brix, Lau, E-mail: lau.brix@stab.rm.dk; Ringgaard, Steffen; Sørensen, Thomas Sangild

2014-04-15

Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (ormore » tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial, sagittal, and coronal 2D MRI series yielded 3D respiratory motion curves for all volunteers. The motion directionality and amplitude were very similar when measured directly as in-plane motion or estimated indirectly as through-plane motion. The mean peak-to-peak breathing amplitude was 1.6 mm (left-right), 11.0 mm (craniocaudal), and 2.5 mm (anterior-posterior). The position of the watermelon structure was estimated in 2D MRI images with a root-mean-square error of 0.52 mm (in-plane) and 0.87 mm (through-plane). Conclusions: A method for 3D tracking in 2D MRI series was developed and demonstrated for liver tracking in volunteers. The method would allow real-time 3D localization with integrated MR-Linac systems.« less

Medical image segmentation using 3D MRI data

NASA Astrophysics Data System (ADS)

Voronin, V.; Marchuk, V.; Semenishchev, E.; Cen, Yigang; Agaian, S.

2017-05-01

Precise segmentation of three-dimensional (3D) magnetic resonance imaging (MRI) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Accurate automatic extraction a 3D component from images obtained by magnetic resonance imaging (MRI) is a challenging segmentation problem due to the small size objects of interest (e.g., blood vessels, bones) in each 2D MRA slice and complex surrounding anatomical structures. Our objective is to develop a specific segmentation scheme for accurately extracting parts of bones from MRI images. In this paper, we use a segmentation algorithm to extract the parts of bones from Magnetic Resonance Imaging (MRI) data sets based on modified active contour method. As a result, the proposed method demonstrates good accuracy in a comparison between the existing segmentation approaches on real MRI data.

Image formation in diffusion MRI: A review of recent technical developments

PubMed Central

Miller, Karla L.

2017-01-01

Diffusion magnetic resonance imaging (MRI) is a standard imaging tool in clinical neurology, and is becoming increasingly important for neuroscience studies due to its ability to depict complex neuroanatomy (eg, white matter connectivity). Single‐shot echo‐planar imaging is currently the predominant formation method for diffusion MRI, but suffers from blurring, distortion, and low spatial resolution. A number of methods have been proposed to address these limitations and improve diffusion MRI acquisition. Here, the recent technical developments for image formation in diffusion MRI are reviewed. We discuss three areas of advance in diffusion MRI: improving image fidelity, accelerating acquisition, and increasing the signal‐to‐noise ratio. Level of Evidence: 5 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:646–662 PMID:28194821

Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model.

PubMed

Ting, Samuel T; Ahmad, Rizwan; Jin, Ning; Craft, Jason; Serafim da Silveira, Juliana; Xue, Hui; Simonetti, Orlando P

2017-04-01

Sparsity-promoting regularizers can enable stable recovery of highly undersampled magnetic resonance imaging (MRI), promising to improve the clinical utility of challenging applications. However, lengthy computation time limits the clinical use of these methods, especially for dynamic MRI with its large corpus of spatiotemporal data. Here, we present a holistic framework that utilizes the balanced sparse model for compressive sensing and parallel computing to reduce the computation time of cardiac MRI recovery methods. We propose a fast, iterative soft-thresholding method to solve the resulting ℓ1-regularized least squares problem. In addition, our approach utilizes a parallel computing environment that is fully integrated with the MRI acquisition software. The methodology is applied to two formulations of the multichannel MRI problem: image-based recovery and k-space-based recovery. Using measured MRI data, we show that, for a 224 × 144 image series with 48 frames, the proposed k-space-based approach achieves a mean reconstruction time of 2.35 min, a 24-fold improvement compared a reconstruction time of 55.5 min for the nonlinear conjugate gradient method, and the proposed image-based approach achieves a mean reconstruction time of 13.8 s. Our approach can be utilized to achieve fast reconstruction of large MRI datasets, thereby increasing the clinical utility of reconstruction techniques based on compressed sensing. Magn Reson Med 77:1505-1515, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Automated prostate cancer localization without the need for peripheral zone extraction using multiparametric MRI.

PubMed

Liu, Xin; Yetik, Imam Samil

2011-06-01

Multiparametric magnetic resonance imaging (MRI) has been shown to have higher localization accuracy than transrectal ultrasound (TRUS) for prostate cancer. Therefore, automated cancer segmentation using multiparametric MRI is receiving a growing interest, since MRI can provide both morphological and functional images for tissue of interest. However, all automated methods to this date are applicable to a single zone of the prostate, and the peripheral zone (PZ) of the prostate needs to be extracted manually, which is a tedious and time-consuming job. In this paper, our goal is to remove the need of PZ extraction by incorporating the spatial and geometric information of prostate tumors with multiparametric MRI derived from T2-weighted MRI, diffusion-weighted imaging (DWI) and dynamic contrast enhanced MRI (DCE-MRI). In order to remove the need of PZ extraction, the authors propose a new method to incorporate the spatial information of the cancer. This is done by introducing a new feature called location map. This new feature is constructed by applying a nonlinear transformation to the spatial position coordinates of each pixel, so that the location map implicitly represents the geometric position of each pixel with respect to the prostate region. Then, this new feature is combined with multiparametric MR images to perform tumor localization. The proposed algorithm is applied to multiparametric prostate MRI data obtained from 20 patients with biopsy-confirmed prostate cancer. The proposed method which does not need the masks of PZ was found to have prostate cancer detection specificity of 0.84, sensitivity of 0.80 and dice coefficient value of 0.42. The authors have found that fusing the spatial information allows us to obtain tumor outline without the need of PZ extraction with a considerable success (better or similar performance to methods that require manual PZ extraction). Our experimental results quantitatively demonstrate the effectiveness of the proposed method, depicting that the proposed method has a slightly better or similar localization performance compared to methods which require the masks of PZ.

PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction.

PubMed

Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou

2018-02-08

The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.

MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Peter C.; Schreibmann, Eduard; Roper, Justin

2015-03-15

Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR.more » Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.« less

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

Dual-TRACER: High resolution fMRI with constrained evolution reconstruction.

PubMed

Li, Xuesong; Ma, Xiaodong; Li, Lyu; Zhang, Zhe; Zhang, Xue; Tong, Yan; Wang, Lihong; Sen Song; Guo, Hua

2018-01-01

fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm 2 ) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

PubMed Central

Signori, Alessio; Valdora, Francesca; Rossi, Federica; Calabrese, Massimo; Durando, Manuela; Mariscotto, Giovanna; Tagliafico, Alberto

2017-01-01

Objective: To perform a systematic review of the methods used for background parenchymal enhancement (BPE) evaluation on breast MRI. Methods: Studies dealing with BPE assessment on breast MRI were retrieved from major medical libraries independently by four reviewers up to 6 October 2015. The keywords used for database searching are “background parenchymal enhancement”, “parenchymal enhancement”, “MRI” and “breast”. The studies were included if qualitative and/or quantitative methods for BPE assessment were described. Results: Of the 420 studies identified, a total of 52 articles were included in the systematic review. 28 studies performed only a qualitative assessment of BPE, 13 studies performed only a quantitative assessment and 11 studies performed both qualitative and quantitative assessments. A wide heterogeneity was found in the MRI sequences and in the quantitative methods used for BPE assessment. Conclusion: A wide variability exists in the quantitative evaluation of BPE on breast MRI. More studies focused on a reliable and comparable method for quantitative BPE assessment are needed. Advances in knowledge: More studies focused on a quantitative BPE assessment are needed. PMID:27925480

Changes in fat and skeletal muscle with exercise training in obese adolescents: comparison of whole-body MRI and dual energy X-ray absorptiometry

PubMed Central

Lee, SoJung; Kuk, Jennifer L.

2013-01-01

Objective We examined skeletal muscle (SM) and fat distribution using whole-body MRI in response to aerobic (AE) versus resistance exercise (RE) training in obese adolescents and whether DXA provides similar estimates of fat and SM change as MRI. Design and Methods Thirty-nine obese boys (12–18 yr) were randomly assigned to one of three 3-month interventions: AE (n=14), RE (n=14) or a control (n=11). Results At baseline, MRI-measured total fat was significantly greater than DXA-measured total fat [Δ=3.1 kg (95% CI: −0.4 to 7.4 kg, P<0.05)], wherein underestimation by DXA was greatest in those with the highest total fat. Overall, the changes in total fat were not significantly different between MRI and DXA [Δ= −0.4 kg (95% CI: −3.5 to 2.6 kg, P>0.05)], but DXA tended to overestimate MRI fat losses in those with larger fat losses. MRI-measured SM and DXA-measured LBM (lean body mass) were significantly correlated, but as expected the absolute values were different at baseline [Δ= −28.4 kg (95% CI: −35.4 to −21.3 kg, P<0.05)]. Further, DXA overestimated MRI gains in SM in those with larger SM gains. Conclusions Although DXA and MRI-measured total and regional measures tended to be correlated at baseline and changes with exercise, there were substantial differences in the absolute values derived using DXA versus MRI. Further, there were systemic biases in the estimation between the methods wherein DXA tended to overestimate fat losses and SM gains compared to MRI. Thus, the changes in body composition observed are influenced by the method employed. PMID:23512818

Advances in locally constrained k-space-based parallel MRI.

PubMed

Samsonov, Alexey A; Block, Walter F; Arunachalam, Arjun; Field, Aaron S

2006-02-01

In this article, several theoretical and methodological developments regarding k-space-based, locally constrained parallel MRI (pMRI) reconstruction are presented. A connection between Parallel MRI with Adaptive Radius in k-Space (PARS) and GRAPPA methods is demonstrated. The analysis provides a basis for unified treatment of both methods. Additionally, a weighted PARS reconstruction is proposed, which may absorb different weighting strategies for improved image reconstruction. Next, a fast and efficient method for pMRI reconstruction of data sampled on non-Cartesian trajectories is described. In the new technique, the computational burden associated with the numerous matrix inversions in the original PARS method is drastically reduced by limiting direct calculation of reconstruction coefficients to only a few reference points. The rest of the coefficients are found by interpolating between the reference sets, which is possible due to the similar configuration of points participating in reconstruction for highly symmetric trajectories, such as radial and spirals. As a result, the time requirements are drastically reduced, which makes it practical to use pMRI with non-Cartesian trajectories in many applications. The new technique was demonstrated with simulated and actual data sampled on radial trajectories. Copyright 2006 Wiley-Liss, Inc.

Forensic age estimation based on magnetic resonance imaging of third molars: converting 2D staging into 3D staging.

PubMed

De Tobel, Jannick; Hillewig, Elke; Verstraete, Koenraad

2017-03-01

Established methods to stage development of third molars for forensic age estimation are based on the evaluation of radiographs, which show a 2D projection. It has not been investigated whether these methods require any adjustments in order to apply them to stage third molars on magnetic resonance imaging (MRI), which shows 3D information. To prospectively study root stage assessment of third molars in age estimation using 3 Tesla MRI and to compare this with panoramic radiographs, in order to provide considerations for converting 2D staging into 3D staging and to determine the decisive root. All third molars were evaluated in 52 healthy participants aged 14-26 years using MRI in three planes. Three staging methods were investigated by two observers. In sixteen of the participants, MRI findings were compared with findings on panoramic radiographs. Decisive roots were palatal in upper third molars and distal in lower third molars. Fifty-seven per cent of upper third molars were not assessable on the radiograph, while 96.9% were on MRI. Upper third molars were more difficult to evaluate on radiographs than on MRI (p < .001). Lower third molars were equally assessable on both imaging techniques (93.8% MRI, 98.4% radiograph), with no difference in level of difficulty (p = .375). Inter- and intra-observer agreement for evaluation was higher in MRI than in radiographs. In both imaging techniques lower third molars showed greater inter- and intra-observer agreement compared to upper third molars. MR images in the sagittal plane proved to be essential for staging. In age estimation, 3T MRI of third molars could be valuable. Some considerations are, however, necessary to transfer known staging methods to this 3D technique.

Multi-echo acquisition

PubMed Central

Posse, Stefan

2011-01-01

The rapid development of fMRI was paralleled early on by the adaptation of MR spectroscopic imaging (MRSI) methods to quantify water relaxation changes during brain activation. This review describes the evolution of multi-echo acquisition from high-speed MRSI to multi-echo EPI and beyond. It highlights milestones in the development of multi-echo acquisition methods, such as the discovery of considerable gains in fMRI sensitivity when combining echo images, advances in quantification of the BOLD effect using analytical biophysical modeling and interleaved multi-region shimming. The review conveys the insight gained from combining fMRI and MRSI methods and concludes with recent trends in ultra-fast fMRI, which will significantly increase temporal resolution of multi-echo acquisition. PMID:22056458

Feasibility study on 3D image reconstruction from 2D orthogonal cine-MRI for MRI-guided radiotherapy.

PubMed

Paganelli, Chiara; Lee, Danny; Kipritidis, John; Whelan, Brendan; Greer, Peter B; Baroni, Guido; Riboldi, Marco; Keall, Paul

2018-02-11

In-room MRI is a promising image guidance strategy in external beam radiotherapy to acquire volumetric information for moving targets. However, limitations in spatio-temporal resolution led several authors to use 2D orthogonal images for guidance. The aim of this work is to present a method to concurrently compensate for non-rigid tumour motion and provide an approach for 3D reconstruction from 2D orthogonal cine-MRI slices for MRI-guided treatments. Free-breathing sagittal/coronal interleaved 2D cine-MRI were acquired in addition to a pre-treatment 3D volume in two patients. We performed deformable image registration (DIR) between cine-MRI slices and corresponding slices in the pre-treatment 3D volume. Based on an extrapolation of the interleaved 2D motion fields, the 3D motion field was estimated and used to warp the pre-treatment volume. Due to the lack of a ground truth for patients, the method was validated on a digital 4D lung phantom. On the phantom, the 3D reconstruction method was able to compensate for tumour motion and compared favourably to the results of previously adopted strategies. The difference in the 3D motion fields between the phantom and the extrapolated motion was 0.4 ± 0.3 mm for tumour and 0.8 ± 1.5 mm for whole anatomy, demonstrating feasibility of performing a 3D volumetric reconstruction directly from 2D orthogonal cine-MRI slices. Application of the method to patient data confirmed the feasibility of utilizing this method in real world scenarios. Preliminary results on phantom and patient cases confirm the feasibility of the proposed approach in an MRI-guided scenario, especially for non-rigid tumour motion compensation. © 2018 The Royal Australian and New Zealand College of Radiologists.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yee, Seonghwan, E-mail: Seonghwan.Yee@Beaumont.edu; Gao, Jia-Hong

Purpose: To investigate whether the direction of spin-lock field, either parallel or antiparallel to the rotating magnetization, has any effect on the spin-lock MRI signal and further on the quantitative measurement of T1ρ, in a clinical 3 T MRI system. Methods: The effects of inverted spin-lock field direction were investigated by acquiring a series of spin-lock MRI signals for an American College of Radiology MRI phantom, while the spin-lock field direction was switched between the parallel and antiparallel directions. The acquisition was performed for different spin-locking methods (i.e., for the single- and dual-field spin-locking methods) and for different levels ofmore » clinically feasible spin-lock field strength, ranging from 100 to 500 Hz, while the spin-lock duration was varied in the range from 0 to 100 ms. Results: When the spin-lock field was inverted into the antiparallel direction, the rate of MRI signal decay was altered and the T1ρ value, when compared to the value for the parallel field, was clearly different. Different degrees of such direction-dependency were observed for different spin-lock field strengths. In addition, the dependency was much smaller when the parallel and the antiparallel fields are mixed together in the dual-field method. Conclusions: The spin-lock field direction could impact the MRI signal and further the T1ρ measurement in a clinical MRI system.« less

Resting-state fMRI data reflects default network activity rather than null data: A defense of commonly employed methods to correct for multiple comparisons.

PubMed

Slotnick, Scott D

2017-07-01

Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

PubMed Central

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

PubMed

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

Investigating the enhancement of template-free activation detection of event-related fMRI data using wavelet shrinkage and figures of merit.

PubMed

Ngan, Shing-Chung; Hu, Xiaoping; Khong, Pek-Lan

2011-03-01

We propose a method for preprocessing event-related functional magnetic resonance imaging (fMRI) data that can lead to enhancement of template-free activation detection. The method is based on using a figure of merit to guide the wavelet shrinkage of a given fMRI data set. Several previous studies have demonstrated that in the root-mean-square error setting, wavelet shrinkage can improve the signal-to-noise ratio of fMRI time courses. However, preprocessing fMRI data in the root-mean-square error setting does not necessarily lead to enhancement of template-free activation detection. Motivated by this observation, in this paper, we move to the detection setting and investigate the possibility of using wavelet shrinkage to enhance template-free activation detection of fMRI data. The main ingredients of our method are (i) forward wavelet transform of the voxel time courses, (ii) shrinking the resulting wavelet coefficients as directed by an appropriate figure of merit, (iii) inverse wavelet transform of the shrunk data, and (iv) submitting these preprocessed time courses to a given activation detection algorithm. Two figures of merit are developed in the paper, and two other figures of merit adapted from the literature are described. Receiver-operating characteristic analyses with simulated fMRI data showed quantitative evidence that data preprocessing as guided by the figures of merit developed in the paper can yield improved detectability of the template-free measures. We also demonstrate the application of our methodology on an experimental fMRI data set. The proposed method is useful for enhancing template-free activation detection in event-related fMRI data. It is of significant interest to extend the present framework to produce comprehensive, adaptive and fully automated preprocessing of fMRI data optimally suited for subsequent data analysis steps. Copyright © 2010 Elsevier B.V. All rights reserved.

Wavelet-space Correlation Imaging for High-speed MRI without Motion Monitoring or Data Segmentation

PubMed Central

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2014-01-01

Purpose This study aims to 1) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and 2) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Methods Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called “wavelet-space correlation imaging”, is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Results Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Conclusion Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. PMID:25470230

Magnetic Resonance Imaging of Liver Metastasis.

PubMed

Karaosmanoglu, Ali Devrim; Onur, Mehmet Ruhi; Ozmen, Mustafa Nasuh; Akata, Deniz; Karcaaltincaba, Musturay

2016-12-01

Liver magnetic resonance imaging (MRI) is becoming the gold standard in liver metastasis detection and treatment response assessment. The most sensitive magnetic resonance sequences are diffusion-weighted images and hepatobiliary phase images after Gd-EOB-DTPA. Peripheral ring enhancement, diffusion restriction, and hypointensity on hepatobiliary phase images are hallmarks of liver metastases. In patients with normal ultrasonography, computed tomography (CT), and positron emission tomography (PET)-CT findings and high clinical suspicion of metastasis, MRI should be performed for diagnosis of unseen metastasis. In melanoma, colon cancer, and neuroendocrine tumor metastases, MRI allows confident diagnosis of treatment-related changes in liver and enables differential diagnosis from primary liver tumors. Focal nodular hyperplasia-like nodules in patients who received platinum-based chemotherapy, hypersteatosis, and focal fat can mimic metastasis. In cancer patients with fatty liver, MRI should be preferred to CT. Although the first-line imaging for metastases is CT, MRI can be used as a problem-solving method. MRI may be used as the first-line method in patients who would undergo curative surgery or metastatectomy. Current limitation of MRI is low sensitivity for metastasis smaller than 3mm. MRI fingerprinting, glucoCEST MRI, and PET-MRI may allow simpler and more sensitive diagnosis of liver metastasis. Copyright © 2016 Elsevier Inc. All rights reserved.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes

NASA Astrophysics Data System (ADS)

Bjerre, Troels; Crijns, Sjoerd; Rosenschöld, Per Munck af; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-01

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes.

PubMed

Bjerre, Troels; Crijns, Sjoerd; af Rosenschöld, Per Munck; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-21

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease

PubMed Central

Liu, Hongcheng; Du, Guangwei; Zhang, Lijun; Lewis, Mechelle M.; Wang, Xue; Yao, Tao; Li, Runze; Huang, Xuemei

2016-01-01

Background Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. New method This study introduces folded concave penalized (FCP) sparse logistic regression to identify biomarkers for PD from a large number of potential factors. The proposed statistical procedures target the challenges of high-dimensionality with limited data samples acquired. The maximization problem associated with the sparse logistic regression model is solved by local linear approximation. The proposed procedures then are applied to the empirical analysis of multimodal MRI data. Results From 45 features, the proposed approach identified 15 MRI markers and the UPSIT, which are known to be clinically relevant to PD. By combining the MRI and clinical markers, we can enhance substantially the specificity and sensitivity of the model, as indicated by the ROC curves. Comparison to existing methods We compare the folded concave penalized learning scheme with both the Lasso penalized scheme and the principle component analysis-based feature selection (PCA) in the Parkinson’s biomarker identification problem that takes into account both the clinical features and MRI markers. The folded concave penalty method demonstrates a substantially better clinical potential than both the Lasso and PCA in terms of specificity and sensitivity. Conclusions For the first time, we applied the FCP learning method to MRI biomarker discovery in PD. The proposed approach successfully identified MRI markers that are clinically relevant. Combining these biomarkers with clinical features can substantially enhance performance. PMID:27102045

Lean body mass correction of standardized uptake value in simultaneous whole-body positron emission tomography and magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Jochimsen, Thies H.; Schulz, Jessica; Busse, Harald; Werner, Peter; Schaudinn, Alexander; Zeisig, Vilia; Kurch, Lars; Seese, Anita; Barthel, Henryk; Sattler, Bernhard; Sabri, Osama

2015-06-01

This study explores the possibility of using simultaneous positron emission tomography—magnetic resonance imaging (PET-MRI) to estimate the lean body mass (LBM) in order to obtain a standardized uptake value (SUV) which is less dependent on the patients' adiposity. This approach is compared to (1) the commonly-used method based on a predictive equation for LBM, and (2) to using an LBM derived from PET-CT data. It is hypothesized that an MRI-based correction of SUV provides a robust method due to the high soft-tissue contrast of MRI. A straightforward approach to calculate an MRI-derived LBM is presented. It is based on the fat and water images computed from the two-point Dixon MRI primarily used for attenuation correction in PET-MRI. From these images, a water fraction was obtained for each voxel. Averaging over the whole body yielded the weight-normalized LBM. Performance of the new approach in terms of reducing variations of 18F-Fludeoxyglucose SUVs in brain and liver across 19 subjects was compared with results using predictive methods and PET-CT data to estimate the LBM. The MRI-based method reduced the coefficient of variation of SUVs in the brain by 41  ± 10% which is comparable to the reduction by the PET-CT method (35  ± 10%). The reduction of the predictive LBM method was 29  ± 8%. In the liver, the reduction was less clear, presumably due to other sources of variation. In conclusion, employing the Dixon data in simultaneous PET-MRI for calculation of lean body mass provides a brain SUV which is less dependent on patient adiposity. The reduced dependency is comparable to that obtained by CT and predictive equations. Therefore, it is more comparable across patients. The technique does not impose an overhead in measurement time and is straightforward to implement.

Lean body mass correction of standardized uptake value in simultaneous whole-body positron emission tomography and magnetic resonance imaging.

PubMed

Jochimsen, Thies H; Schulz, Jessica; Busse, Harald; Werner, Peter; Schaudinn, Alexander; Zeisig, Vilia; Kurch, Lars; Seese, Anita; Barthel, Henryk; Sattler, Bernhard; Sabri, Osama

2015-06-21

This study explores the possibility of using simultaneous positron emission tomography--magnetic resonance imaging (PET-MRI) to estimate the lean body mass (LBM) in order to obtain a standardized uptake value (SUV) which is less dependent on the patients' adiposity. This approach is compared to (1) the commonly-used method based on a predictive equation for LBM, and (2) to using an LBM derived from PET-CT data. It is hypothesized that an MRI-based correction of SUV provides a robust method due to the high soft-tissue contrast of MRI. A straightforward approach to calculate an MRI-derived LBM is presented. It is based on the fat and water images computed from the two-point Dixon MRI primarily used for attenuation correction in PET-MRI. From these images, a water fraction was obtained for each voxel. Averaging over the whole body yielded the weight-normalized LBM. Performance of the new approach in terms of reducing variations of (18)F-Fludeoxyglucose SUVs in brain and liver across 19 subjects was compared with results using predictive methods and PET-CT data to estimate the LBM. The MRI-based method reduced the coefficient of variation of SUVs in the brain by 41 ± 10% which is comparable to the reduction by the PET-CT method (35 ± 10%). The reduction of the predictive LBM method was 29 ± 8%. In the liver, the reduction was less clear, presumably due to other sources of variation. In conclusion, employing the Dixon data in simultaneous PET-MRI for calculation of lean body mass provides a brain SUV which is less dependent on patient adiposity. The reduced dependency is comparable to that obtained by CT and predictive equations. Therefore, it is more comparable across patients. The technique does not impose an overhead in measurement time and is straightforward to implement.

MRI for peripheral artery disease: Introductory physics for vascular physicians.

PubMed

Roy, Trisha L; Forbes, Thomas L; Dueck, Andrew D; Wright, Graham A

2018-04-01

Magnetic resonance imaging (MRI) has advanced significantly in the past decade and provides a safe and non-invasive method of evaluating peripheral artery disease (PAD), with and without using exogenous contrast agents. MRI offers a promising alternative for imaging patients but the complexity of MRI can make it less accessible for physicians to understand or use. This article provides a brief introduction to the technical principles of MRI for physicians who manage PAD patients. We discuss the basic principles of how MRI works and tailor the discussion to how MRI can evaluate anatomic characteristics of peripheral arterial lesions.

Magnetic Resonance Imaging (MRI) -- Head

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Localization of cortical primary motor area of the hand using navigated transcranial magnetic stimulation, BOLD and arterial spin labeling fMRI.

PubMed

Kallioniemi, Elisa; Pitkänen, Minna; Könönen, Mervi; Vanninen, Ritva; Julkunen, Petro

2016-11-01

Although the relationship between neuronavigated transcranial magnetic stimulation (nTMS) and functional magnetic resonance imaging (fMRI) has been widely studied in motor mapping, it is unknown how the motor response type or the choice of motor task affect this relationship. Centers of gravity (CoGs) and response maxima were measured with blood-oxygen-level dependent (BOLD) and arterial spin labeling (ASL) fMRI during motor tasks against nTMS CoGs and response maxima, which were mapped with motor evoked potentials (MEPs) and silent periods (SPs). No differences in motor representations (CoGs and response maxima) were observed in lateral-medial direction (p=0.265). fMRI methods localized the motor representation more posterior than nTMS (p<0.001). This was not affected by the BOLD fMRI motor task (p>0.999) nor nTMS response type (p>0.999). ASL fMRI maxima did not differ from the nTMS nor BOLD fMRI CoGs (p≥0.070), but the ASL CoG was deeper in comparison to other methods (p≤0.042). The BOLD fMRI motor task did not influence the depth of the motor representation (p≥0.745). The median Euclidean distances between the nTMS and fMRI motor representations varied between 7.7mm and 14.5mm and did not differ between the methods (F≤1.23, p≥0.318). The relationship between fMRI and nTMS mapped excitatory (MEP) and inhibitory (SP) responses, and whether the choice of motor task affects this relationship, have not been studied before. The congruence between fMRI and nTMS is good. The choice of nTMS motor response type nor BOLD fMRI motor task had no effect on this relationship. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of a non-stationary voxelation-corrected cluster-size test with TFCE for group-Level MRI inference.

PubMed

Li, Huanjie; Nickerson, Lisa D; Nichols, Thomas E; Gao, Jia-Hong

2017-03-01

Two powerful methods for statistical inference on MRI brain images have been proposed recently, a non-stationary voxelation-corrected cluster-size test (CST) based on random field theory and threshold-free cluster enhancement (TFCE) based on calculating the level of local support for a cluster, then using permutation testing for inference. Unlike other statistical approaches, these two methods do not rest on the assumptions of a uniform and high degree of spatial smoothness of the statistic image. Thus, they are strongly recommended for group-level fMRI analysis compared to other statistical methods. In this work, the non-stationary voxelation-corrected CST and TFCE methods for group-level analysis were evaluated for both stationary and non-stationary images under varying smoothness levels, degrees of freedom and signal to noise ratios. Our results suggest that, both methods provide adequate control for the number of voxel-wise statistical tests being performed during inference on fMRI data and they are both superior to current CSTs implemented in popular MRI data analysis software packages. However, TFCE is more sensitive and stable for group-level analysis of VBM data. Thus, the voxelation-corrected CST approach may confer some advantages by being computationally less demanding for fMRI data analysis than TFCE with permutation testing and by also being applicable for single-subject fMRI analyses, while the TFCE approach is advantageous for VBM data. Hum Brain Mapp 38:1269-1280, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Diagnostic Performance of a Rapid Magnetic Resonance Imaging Method of Measuring Hepatic Steatosis

PubMed Central

House, Michael J.; Gan, Eng K.; Adams, Leon A.; Ayonrinde, Oyekoya T.; Bangma, Sander J.; Bhathal, Prithi S.; Olynyk, John K.; St. Pierre, Tim G.

2013-01-01

Objectives Hepatic steatosis is associated with an increased risk of developing serious liver disease and other clinical sequelae of the metabolic syndrome. However, visual estimates of steatosis from histological sections of biopsy samples are subjective and reliant on an invasive procedure with associated risks. The aim of this study was to test the ability of a rapid, routinely available, magnetic resonance imaging (MRI) method to diagnose clinically relevant grades of hepatic steatosis in a cohort of patients with diverse liver diseases. Materials and Methods Fifty-nine patients with a range of liver diseases underwent liver biopsy and MRI. Hepatic steatosis was quantified firstly using an opposed-phase, in-phase gradient echo, single breath-hold MRI methodology and secondly, using liver biopsy with visual estimation by a histopathologist and by computer-assisted morphometric image analysis. The area under the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of the MRI method against the biopsy observations. Results The MRI approach had high sensitivity and specificity at all hepatic steatosis thresholds. Areas under ROC curves were 0.962, 0.993, and 0.972 at thresholds of 5%, 33%, and 66% liver fat, respectively. MRI measurements were strongly associated with visual (r2 = 0.83) and computer-assisted morphometric (r2 = 0.84) estimates of hepatic steatosis from histological specimens. Conclusions This MRI approach, using a conventional, rapid, gradient echo method, has high sensitivity and specificity for diagnosing liver fat at all grades of steatosis in a cohort with a range of liver diseases. PMID:23555650

Brain tumor segmentation using holistically nested neural networks in MRI images.

PubMed

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of 0.83 and 0.85 were achieved. A quantitative comparison indicated that the proposed method outperforms the popular fully convolutional network (FCN) method. In terms of efficiency, the proposed method took around 10 h for training with 50,000 iterations, and approximately 30 s for testing of a typical MRI image in the BRATS 2013 dataset with a size of 160 × 216 × 176, using a DELL PRECISION workstation T7400, with an NVIDIA Tesla K20c GPU. An effective brain tumor segmentation method for MRI images based on a HNN has been developed. The high level of accuracy and efficiency make this method practical in brain tumor segmentation. It may play a crucial role in both brain tumor diagnostic analysis and in the treatment planning of radiation therapy. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Volume estimation of brain abnormalities in MRI data

NASA Astrophysics Data System (ADS)

Suprijadi, Pratama, S. H.; Haryanto, F.

2014-02-01

The abnormality of brain tissue always becomes a crucial issue in medical field. This medical condition can be recognized through segmentation of certain region from medical images obtained from MRI dataset. Image processing is one of computational methods which very helpful to analyze the MRI data. In this study, combination of segmentation and rendering image were used to isolate tumor and stroke. Two methods of thresholding were employed to segment the abnormality occurrence, followed by filtering to reduce non-abnormality area. Each MRI image is labeled and then used for volume estimations of tumor and stroke-attacked area. The algorithms are shown to be successful in isolating tumor and stroke in MRI images, based on thresholding parameter and stated detection accuracy.

[Determination of joint contact area using MRI].

PubMed

Yoshida, Hidenori; Kobayashi, Koichi; Sakamoto, Makoto; Tanabe, Yuji

2009-10-20

Elevated contact stress on the articular joints has been hypothesized to contribute to articular cartilage wear and joint pain. However, given the limitations of using contact stress and areas from human cadaver specimens to estimate articular joint stress, there is need for an in vivo method to obtain such data. Magnetic resonance imaging (MRI) has been shown to be a valid method of quantifying the human joint contact area, indicating the potential for in vivo assessment. The purpose of this study was to describe a method of quantifying the tibiofemoral joint contact area using MRI. The validity of this technique was established in porcine cadaver specimens by comparing the contact area obtained from MRI with the contact area obtained using pressure-sensitive film (PSF). In particular, we assessed the actual condition of contact by using the ratio of signal intensity of MR images of cartilage surfaces. Two fresh porcine cadaver knees were used. A custom loading apparatus was designed to apply a compressive load to the tibiofemoral joint. We measured the contact area by using MRI and PSF methods. When the ratio of signal intensity of the cartilage surface was 0.9, the error of the contact area between the MR image and PSF was about 6%. These results suggest that this MRI method may be a valuable tool in quantifying joint contact area in vivo.

Current whole-body MRI applications in the neurofibromatoses

PubMed Central

Fayad, Laura M.; Khan, Muhammad Shayan; Bredella, Miriam A.; Harris, Gordon J.; Evans, D. Gareth; Farschtschi, Said; Jacobs, Michael A.; Chhabra, Avneesh; Salamon, Johannes M.; Wenzel, Ralph; Mautner, Victor F.; Dombi, Eva; Cai, Wenli; Plotkin, Scott R.; Blakeley, Jaishri O.

2016-01-01

Objectives: The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. Methods: A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. Results: WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. Conclusions: WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. PMID:27527647

What approach to brain partial volume correction is best for PET/MRI?

NASA Astrophysics Data System (ADS)

Hutton, B. F.; Thomas, B. A.; Erlandsson, K.; Bousse, A.; Reilhac-Laborde, A.; Kazantsev, D.; Pedemonte, S.; Vunckx, K.; Arridge, S. R.; Ourselin, S.

2013-02-01

Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms.

[4D-MRI using the synchronized sampling method (SSM)].

PubMed

Shimada, Yasuhiro; Fujimoto, Ichirou; Takemoto, Hironori; Takano, Sayoko; Masaki, Shinobu; Honda, Kiyoshi; Takeo, Kazuhiro

2002-12-01

A synchronized sampling method (SSM) was developed for the study of voluntary movements by combining the electrocardiographic (ECG) gating method with an external triggering device, and four-dimensional magnetic resonance imaging (4D-MRI) at a rate of 30 frames per second was accomplished by volumetric imaging with the SSM. This method was first applied to the motion imaging of articulatory organs during repetitions of a Japanese five-vowel sequence, and the dynamic change in vocal tract area function was demonstrated with sufficient temporal resolution. This paper describes the methodology, applicability, and limitations of 4D-MRI with the SSM.

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

PubMed

Dalmış, Mehmet Ufuk; Litjens, Geert; Holland, Katharina; Setio, Arnaud; Mann, Ritse; Karssemeijer, Nico; Gubern-Mérida, Albert

2017-02-01

Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surface detection, have been applied to solve this task. However, applicability of these methods is usually limited by the characteristics of the images used in the study datasets, while breast MRI varies with respect to the different MRI protocols used, in addition to the variability in breast shapes. All this variability, in addition to various MRI artifacts, makes it a challenging task to develop a robust breast and FGT segmentation method using traditional approaches. Therefore, in this study, we investigated the use of a deep-learning approach known as "U-net." We used a dataset of 66 breast MRI's randomly selected from our scientific archive, which includes five different MRI acquisition protocols and breasts from four breast density categories in a balanced distribution. To prepare reference segmentations, we manually segmented breast and FGT for all images using an in-house developed workstation. We experimented with the application of U-net in two different ways for breast and FGT segmentation. In the first method, following the same pipeline used in traditional approaches, we trained two consecutive (2C) U-nets: first for segmenting the breast in the whole MRI volume and the second for segmenting FGT inside the segmented breast. In the second method, we used a single 3-class (3C) U-net, which performs both tasks simultaneously by segmenting the volume into three regions: nonbreast, fat inside the breast, and FGT inside the breast. For comparison, we applied two existing and published methods to our dataset: an atlas-based method and a sheetness-based method. We used Dice Similarity Coefficient (DSC) to measure the performances of the automated methods, with respect to the manual segmentations. Additionally, we computed Pearson's correlation between the breast density values computed based on manual and automated segmentations. The average DSC values for breast segmentation were 0.933, 0.944, 0.863, and 0.848 obtained from 3C U-net, 2C U-nets, atlas-based method, and sheetness-based method, respectively. The average DSC values for FGT segmentation obtained from 3C U-net, 2C U-nets, and atlas-based methods were 0.850, 0.811, and 0.671, respectively. The correlation between breast density values based on 3C U-net and manual segmentations was 0.974. This value was significantly higher than 0.957 as obtained from 2C U-nets (P < 0.0001, Steiger's Z-test with Bonferoni correction) and 0.938 as obtained from atlas-based method (P = 0.0016). In conclusion, we applied a deep-learning method, U-net, for segmenting breast and FGT in MRI in a dataset that includes a variety of MRI protocols and breast densities. Our results showed that U-net-based methods significantly outperformed the existing algorithms and resulted in significantly more accurate breast density computation. © 2016 American Association of Physicists in Medicine.

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain

PubMed Central

Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.

2010-01-01

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Renal damages after extracorporeal shock wave lithotripsy evaluated by Gd-DTPA-enhanced dynamic magnetic resonance imaging.

PubMed

Umekawa, T; Kohri, K; Yamate, T; Amasaki, N; Ishikawa, Y; Takada, M; Iguchi, M; Kurita, T

1992-01-01

Renal damages after extracorporeal shock wave lithotripsy (ESWL) were evaluated by magnetic resonance imaging (MRI) including Gd-DTPA-enhanced dynamic MRI in 37 patients with renal stone by spin echo methods (T1 and T2-weighted scan) and small tip angle gradient echo method (T2-weighted scan). Sixty-eight percent of the patients had changes in the MRI findings after ESWL. The frequently observed findings were perirenal fluid collection (38%), loss of corticomedullary junction (35%), and increased signal intensity of muscle and other adjacent tissue (34%). Preoperative Gd-DTPA-enhanced dynamic MRI showed low intensity band which suggests Gd-DTPA secretion from the glomerulus into the renal tubulus. In all cases the low intensity band became unclear after ESWL because of renal contusion due to ESWL. MRI, including Gd-DTPA-enhanced dynamic MRI, is considered to be a good procedure for evaluation of renal damages due to ESWL.

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

The benefits of magnetic resonance imaging methods to extend the knowledge of the anatomical organisation of the periaqueductal gray in mammals.

PubMed

Menant, Ophélie; Andersson, Frédéric; Zelena, Dóra; Chaillou, Elodie

2016-11-01

The periaqueductal gray (PAG) is a mesencephalic brain structure involved in the expression of numerous behaviours such as maternal, sexual and emotional. Histological approaches showed the PAG is composed by subdivisions with specific cell organisation, neurochemical composition and connections with the rest of the brain. The comparison of studies performed in rodents and cats as the most often examined species, suggests that PAG organisation differs between mammals. However, we should also consider the plurality of the methods used in these studies that makes difficult the comparison of the PAG organisation between species. Therefore, to study the PAG in all mammals including human, the most relevant in vivo imaging method seems to be the magnetic resonance imaging (MRI). The purpose of this review was to summarize the knowledge of the anatomical organisation of the PAG in mammals and highlights the benefits of MRI methods to extend this knowledge. Results obtained by MRI so far support the conclusions of ex vivo studies, especially to describe the subdivisions and the connections of the PAG. In these latter, diffusion-weighted MRI and functional connectivity seem the most appropriate methods. In conclusion firstly, the MRI seems to be the best judicious method to compare species and improve the comprehension of the role of the PAG. Secondly, MRI is an in vivo method aimed to manage repeated measures in the same cohort of subjects allowing to study the impact of aging and the development on the anatomical organisation of the PAG. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Contrast Magnetic Resonance Imaging (DCE-MRI) and Diffusion Weighted MR Imaging (DWI) for Differentiation between Benign and Malignant Salivary Gland Tumors

PubMed Central

Assili, S.; Fathi Kazerooni, A.; Aghaghazvini, L.; Saligheh Rad, H.R.; Pirayesh Islamian, J.

2015-01-01

Background Salivary gland tumors form nearly 3% of head and neck tumors. Due to their large histological variety and vicinity to facial nerves, pre-operative diagnosis and differentiation of benign and malignant parotid tumors are a major challenge for radiologists. Objective The majority of these tumors are benign; however, sometimes they tend to transform into a malignant form. Functional MRI techniques, namely dynamic contrast enhanced (DCE-) MRI and diffusion-weighted MRI (DWI) can indicate the characteristics of tumor tissue. Methods DCE-MRI analysis is based on the parameters of time intensity curve (TIC) before and after contrast agent injection. This method has the potential to identify the angiogenesis of tumors. DWI analysis is performed according to diffusion of water molecules in a tissue for determination of the cellularity of tumors. Conclusion According to the literature, these methods cannot be used individually to differentiate benign from malignant salivary gland tumors. An effective approach could be to combine the aforementioned methods to increase the accuracy of discrimination between different tumor types. The main objective of this study is to explore the application of DCE-MRI and DWI for assessment of salivary gland tumor types. PMID:26688794

3-T MRI safety assessments of magnetic dental attachments and castable magnetic alloys

PubMed Central

Miyata, K; Abe, Y; Ishii, T; Ishigami, T; Ohtani, K; Nagai, E; Ohyama, T; Umekawa, Y; Nakabayashi, S

2015-01-01

Objectives: To assess the safety of different magnetic dental attachments during 3-T MRI according to the American Society for Testing and Materials F2182-09 and F2052-06e1 standard testing methods and to develop a method to determine MRI compatibility by measuring magnetically induced torque. Methods: The temperature elevations, magnetically induced forces and torques of a ferromagnetic stainless steel keeper, a coping comprising a keeper and a cast magnetic alloy coping were measured on MRI systems. Results: The coping comprising a keeper demonstrated the maximum temperature increase (1.42 °C) for the whole-body-averaged specific absorption rate and was calculated as 2.1 W kg−1 with the saline phantom. All deflection angles exceeded 45°. The cast magnetic alloy coping had the greatest deflection force (0.33 N) during 3-T MRI and torque (1.015 mN m) during 0.3-T MRI. Conclusions: The tested devices showed minimal radiofrequency (RF)-induced heating in a 3-T MR environment, but the cast magnetic alloy coping showed a magnetically induced deflection force and torque approximately eight times that of the keepers. For safety, magnetic dental attachments should be inspected before and after MRI and large prostheses containing cast magnetic alloy should be removed. Although magnetic dental attachments may pose no great risk of RF-induced heating or magnetically induced torque during 3-T MRI, their magnetically induced deflection forces tended to exceed acceptable limits. Therefore, the inspection of such devices before and after MRI is important for patient safety. PMID:25785821

Four-Dimensional Magnetic Resonance Imaging With 3-Dimensional Radial Sampling and Self-Gating–Based K-Space Sorting: Early Clinical Experience on Pancreatic Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Wensha, E-mail: wensha.yang@cshs.org; Fan, Zhaoyang; Tuli, Richard

2015-12-01

Purpose: To apply a novel self-gating k-space sorted 4-dimensional MRI (SG-KS-4D-MRI) method to overcome limitations due to anisotropic resolution and rebinning artifacts and to monitor pancreatic tumor motion. Methods and Materials: Ten patients were imaged using 4D-CT, cine 2-dimensional MRI (2D-MRI), and the SG-KS-4D-MRI, which is a spoiled gradient recalled echo sequence with 3-dimensional radial-sampling k-space projections and 1-dimensional projection-based self-gating. Tumor volumes were defined on all phases in both 4D-MRI and 4D-CT and then compared. Results: An isotropic resolution of 1.56 mm was achieved in the SG-KS-4D-MRI images, which showed superior soft-tissue contrast to 4D-CT and appeared to be free of stitchingmore » artifacts. The tumor motion trajectory cross-correlations (mean ± SD) between SG-KS-4D-MRI and cine 2D-MRI in superior–inferior, anterior–posterior, and medial–lateral directions were 0.93 ± 0.03, 0.83 ± 0.10, and 0.74 ± 0.18, respectively. The tumor motion trajectories cross-correlations between SG-KS-4D-MRI and 4D-CT in superior–inferior, anterior–posterior, and medial–lateral directions were 0.91 ± 0.06, 0.72 ± 0.16, and 0.44 ± 0.24, respectively. The average standard deviation of gross tumor volume calculated from the 10 breathing phases was 0.81 cm{sup 3} and 1.02 cm{sup 3} for SG-KS-4D-MRI and 4D-CT, respectively (P=.012). Conclusions: A novel SG-KS-4D-MRI acquisition method capable of reconstructing rebinning artifact–free, high-resolution 4D-MRI images was used to quantify pancreas tumor motion. The resultant pancreatic tumor motion trajectories agreed well with 2D-cine-MRI and 4D-CT. The pancreatic tumor volumes shown in the different phases for the SG-KS-4D-MRI were statistically significantly more consistent than those in the 4D-CT.« less

FPGA-based RF interference reduction techniques for simultaneous PET–MRI

PubMed Central

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-01-01

Abstract The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET–MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling–decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion IID PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector. PMID:27049898

FPGA-based RF interference reduction techniques for simultaneous PET-MRI.

PubMed

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-05-07

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II (D) PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.

FPGA-based RF interference reduction techniques for simultaneous PET-MRI

NASA Astrophysics Data System (ADS)

Gebhardt, P.; Wehner, J.; Weissler, B.; Botnar, R.; Marsden, P. K.; Schulz, V.

2016-05-01

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II D PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.

fMRI capture of auditory hallucinations: Validation of the two-steps method.

PubMed

Leroy, Arnaud; Foucher, Jack R; Pins, Delphine; Delmaire, Christine; Thomas, Pierre; Roser, Mathilde M; Lefebvre, Stéphanie; Amad, Ali; Fovet, Thomas; Jaafari, Nemat; Jardri, Renaud

2017-10-01

Our purpose was to validate a reliable method to capture brain activity concomitant with hallucinatory events, which constitute frequent and disabling experiences in schizophrenia. Capturing hallucinations using functional magnetic resonance imaging (fMRI) remains very challenging. We previously developed a method based on a two-steps strategy including (1) multivariate data-driven analysis of per-hallucinatory fMRI recording and (2) selection of the components of interest based on a post-fMRI interview. However, two tests still need to be conducted to rule out critical pitfalls of conventional fMRI capture methods before this two-steps strategy can be adopted in hallucination research: replication of these findings on an independent sample and assessment of the reliability of the hallucination-related patterns at the subject level. To do so, we recruited a sample of 45 schizophrenia patients suffering from frequent hallucinations, 20 schizophrenia patients without hallucinations and 20 matched healthy volunteers; all participants underwent four different experiments. The main findings are (1) high accuracy in reporting unexpected sensory stimuli in an MRI setting; (2) good detection concordance between hypothesis-driven and data-driven analysis methods (as used in the two-steps strategy) when controlled unexpected sensory stimuli are presented; (3) good agreement of the two-steps method with the online button-press approach to capture hallucinatory events; (4) high spatial consistency of hallucinatory-related networks detected using the two-steps method on two independent samples. By validating the two-steps method, we advance toward the possible transfer of such technology to new image-based therapies for hallucinations. Hum Brain Mapp 38:4966-4979, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Assessment of nerve involvement in the lumbar spine: agreement between magnetic resonance imaging, physical examination and pain drawing findings

PubMed Central

2010-01-01

Background Detection of nerve involvement originating in the spine is a primary concern in the assessment of spine symptoms. Magnetic resonance imaging (MRI) has become the diagnostic method of choice for this detection. However, the agreement between MRI and other diagnostic methods for detecting nerve involvement has not been fully evaluated. The aim of this diagnostic study was to evaluate the agreement between nerve involvement visible in MRI and findings of nerve involvement detected in a structured physical examination and a simplified pain drawing. Methods Sixty-one consecutive patients referred for MRI of the lumbar spine were - without knowledge of MRI findings - assessed for nerve involvement with a simplified pain drawing and a structured physical examination. Agreement between findings was calculated as overall agreement, the p value for McNemar's exact test, specificity, sensitivity, and positive and negative predictive values. Results MRI-visible nerve involvement was significantly less common than, and showed weak agreement with, physical examination and pain drawing findings of nerve involvement in corresponding body segments. In spine segment L4-5, where most findings of nerve involvement were detected, the mean sensitivity of MRI-visible nerve involvement to a positive neurological test in the physical examination ranged from 16-37%. The mean specificity of MRI-visible nerve involvement in the same segment ranged from 61-77%. Positive and negative predictive values of MRI-visible nerve involvement in segment L4-5 ranged from 22-78% and 28-56% respectively. Conclusion In patients with long-standing nerve root symptoms referred for lumbar MRI, MRI-visible nerve involvement significantly underestimates the presence of nerve involvement detected by a physical examination and a pain drawing. A structured physical examination and a simplified pain drawing may reveal that many patients with "MRI-invisible" lumbar symptoms need treatment aimed at nerve involvement. Factors other than present MRI-visible nerve involvement may be responsible for findings of nerve involvement in the physical examination and the pain drawing. PMID:20831785

A novel method based on learning automata for automatic lesion detection in breast magnetic resonance imaging.

PubMed

Salehi, Leila; Azmi, Reza

2014-07-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. In this way, magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of breast cancer. Breast MRI presently has two major challenges. First, its specificity is relatively poor, and it detects many false positives (FPs). Second, the method involves acquiring several high-resolution image volumes before, during, and after the injection of a contrast agent. The large volume of data makes the task of interpretation by the radiologist both complex and time-consuming. These challenges have led to the development of the computer-aided detection systems to improve the efficiency and accuracy of the interpretation process. Detection of suspicious regions of interests (ROIs) is a critical preprocessing step in dynamic contrast-enhanced (DCE)-MRI data evaluation. In this regard, this paper introduces a new automatic method to detect the suspicious ROIs for breast DCE-MRI based on region growing. The results indicate that the proposed method is thoroughly able to identify suspicious regions (accuracy of 75.39 ± 3.37 on PIDER breast MRI dataset). Furthermore, the FP per image in this method is averagely 7.92, which shows considerable improvement comparing to other methods like ROI hunter.

Measuring hepatic functional reserve using low temporal resolution Gd-EOB-DTPA dynamic contrast-enhanced MRI: a preliminary study comparing galactosyl human serum albumin scintigraphy with indocyanine green retention.

PubMed

Saito, Kazuhiro; Ledsam, Joseph; Sourbron, Steven; Hashimoto, Tsuyoshi; Araki, Yoichi; Akata, Soichi; Tokuuye, Koichi

2014-01-01

To investigate if tracer kinetic modelling of low temporal resolution dynamic contrast-enhanced (DCE) MRI with Gd-EOB-DTPA could replace technetium-99 m galactosyl human serum albumin (GSA) single positron emission computed tomography (SPECT) and indocyanine green (ICG) retention for the measurement of liver functional reserve. Twenty eight patients awaiting liver resection for various cancers were included in this retrospective study that was approved by the institutional review board. The Gd-EOB-DTPA MRI sequence acquired five images: unenhanced, double arterial phase, portal phase, and 4 min after injection. Intracellular contrast uptake rate (UR) and extracellular volume (Ve) were calculated from DCE-MRI, along with the ratio of GSA radioactivity of liver to heart-plus-liver and per cent of cumulative uptake from 15-16 min (LHL15 and LU15, respectively) from GSA-scintigraphy. ICG retention at 15 min, Child-Pugh cirrhosis score (CPS) and postoperative Inuyama fibrosis criteria were also recorded. Statistical analysis was with Spearman rank correlation analysis. Comparing MRI parameters with the reference methods, significant correlations were obtained for UR and LHL15, LU15, ICG15 (all 0.4-0.6, P < 0.05); UR and CPS (-0.64, P < 0.001); Ve and Inuyama (0.44, P < 0.05). Measures of liver function obtained by routine Gd-EOB-DTPA DCE-MRI with tracer kinetic modelling may provide a suitable method for the evaluation of liver functional reserve. • Magnetic resonance imaging (MRI) provides new methods of measuring hepatic functional reserve. • DCE-MRI with Gd-EOB-DTPA offers the possibility of replacing scintigraphy. • The analysis method can be used for preoperative liver function evaluation.

Magnetic Resonance Imaging of Stroke in the Rat

PubMed Central

CHOPP, Michael; LI, Lian; ZHANG, Li; ZHANG, Zheng-gang; LI, Qing-jiang; JIANG, Quan

2014-01-01

Magnetic resonance imaging (MRI) is now a routine neuroimaging tool in the clinic. Throughout all phases of stroke from acute to chronic, MRI plays an important role to diagnose, evaluate and monitor the cerebral tissue undergoing stroke. This review provides a description of various MRI methods and an overview of selected MRI studies, with an embolic stroke model of rat, performed in the MRI laboratory of Department of Neurology, Henry Ford Hospital, Detroit, Michigan, US. PMID:24920874

Connective tissue of cervical carcinoma xenografts: associations with tumor hypoxia and interstitial fluid pressure and its assessment by DCE-MRI and DW-MRI.

PubMed

Hompland, Tord; Ellingsen, Christine; Galappathi, Kanthi; Rofstad, Einar K

2014-01-01

Abstract Background. A high fraction of stroma in malignant tissues is associated with tumor progression, metastasis, and poor prognosis. Possible correlations between the stromal and physiologic microenvironments of tumors and the potential of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance imaging (MRI) in quantification of the stromal microenvironment were investigated in this study. Material and methods. CK-160 cervical carcinoma xenografts were used as preclinical tumor model. A total of 43 tumors were included in the study, and of these tumors, 17 were used to search for correlations between the stromal and physiologic microenvironments, 11 were subjected to DCE-MRI, and 15 were subjected to DW-MRI. DCE-MRI and DW-MRI were carried out at 1.5 T with a clinical MR scanner and a slotted tube resonator transceiver coil constructed for mice. Fraction of connective tissue (CTFCol) and fraction of hypoxic tissue (HFPim) were determined by immunohistochemistry. A Millar SPC 320 catheter was used to measure tumor interstitial fluid pressure (IFP). Results. CTFCol showed a positive correlation to IFP and an inverse correlation to HFPim. The apparent diffusion coefficient assessed by DW-MRI was inversely correlated to CTFCol, whereas no correlation was found between DCE-MRI-derived parameters and CTFCol. Conclusion. DW-MRI is a potentially useful method for characterizing the stromal microenvironment of tumors.

Characterization of thalamocortical association using amplitude and connectivity of fMRI in mild traumatic brain injury

PubMed Central

Zhou, Yongxia; Lui, Yvonne W; Zuo, Xi-Nian; Milham, Michael P.; Reaume, Joseph; Grossman, Robert I.; Ge, Yulin

2013-01-01

Purpose To examine thalamic and cortical injuries using fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity MRI (fcMRI) based on resting state (RS) and task-related fMRI in patients with mild traumatic brain injury (MTBI). Materials and Methods Twenty-seven patients and 27 age-matched controls were recruited. 3T fMRI at RS and finger tapping task were used to assess fALFF and fcMRI patterns. fALFF was computed with filtering (0.01-0.08Hz) and scaling after preprocessing. fcMRI was performed using a standard seed-based correlation method, and delayed fcMRI (coherence) in frequency domain were also performed between thalamus and cortex. Results In comparison with controls, MTBI patients exhibited significantly decreased fALFF in the thalamus (and frontal/temporal sub segments) and cortical frontal and temporal lobes; as well as decreased thalamo-thalamo and thalamo-frontal/thalamo-temporal fcMRI at rest based on RS-fMRI (corrected P<0.05). This thalamic and cortical disruption also existed at task-related condition in patients. Conclusion The decreased fALFF (i.e. lower neuronal activity) in the thalamus and its segments provides additional evidence of thalamic injury in patients with MTBI. Our findings of fALFF and fcMRI changes during motor task and resting state may offer insights into the underlying cause and primary location of disrupted thalamo-cortical networks after MTBI. PMID:24014176

Voltage-based Device Tracking in a 1.5 Tesla MRI during Imaging: Initial validation in swine models

PubMed Central

Schmidt, Ehud J; Tse, Zion TH; Reichlin, Tobias R; Michaud, Gregory F; Watkins, Ronald D; Butts-Pauly, Kim; Kwong, Raymond Y; Stevenson, William; Schweitzer, Jeffrey; Byrd, Israel; Dumoulin, Charles L

2013-01-01

Purpose Voltage-based device-tracking (VDT) systems are commonly used for tracking invasive devices in electrophysiological (EP) cardiac-arrhythmia therapy. During EP procedures, electro-anatomic-mapping (EAM) workstations provide guidance by integrating VDT location and intra-cardiac-ECG information with X-ray, CT, Ultrasound, and MR images. MR assists navigation, mapping and radio-frequency-ablation. Multi-modality interventions require multiple patient transfers between an MRI and the X-ray/ultrasound EP suite, increasing the likelihood of patient-motion and image mis-registration. An MRI-compatible VDT system may increase efficiency, since there is currently no single method to track devices both inside and outside the MRI scanner. Methods An MRI-compatible VDT system was constructed by modifying a commercial system. Hardware was added to reduce MRI gradient-ramp and radio-frequency-unblanking-pulse interference. VDT patches and cables were modified to reduce heating. Five swine cardiac VDT EAM-mapping interventions were performed, navigating inside and thereafter outside the MRI. Results Three-catheter VDT interventions were performed at >12 frames-per-second both inside and outside the MRI scanner with <3mm error. Catheters were followed on VDT- and MRI-derived maps. Simultaneous VDT and imaging was possible in repetition-time (TR) >32 msec sequences with <0.5mm errors, and <5% MRI SNR loss. At shorter TRs, only intra-cardiac-ECG was reliable. RF Heating was <1.5C°. Conclusion An MRI-compatible VDT system is feasible. PMID:23580479

Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures

PubMed Central

Cetin, Mustafa S.; Houck, Jon M.; Rashid, Barnaly; Agacoglu, Oktay; Stephen, Julia M.; Sui, Jing; Canive, Jose; Mayer, Andy; Aine, Cheryl; Bustillo, Juan R.; Calhoun, Vince D.

2016-01-01

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of “synchronicity” of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI). Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG), which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15 and 12.45%, respectively), while combined fMRI/MEG methods using dynamic functional network connectivity analyses improved classification up to 5.12% relative to use of fMRI alone and up to 17.21% relative to use of MEG alone. PMID:27807403

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

PubMed Central

Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.

2015-01-01

To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244

Diagnostic accuracy of MRI in the measurement of glenoid bone loss.

PubMed

Gyftopoulos, Soterios; Hasan, Saqib; Bencardino, Jenny; Mayo, Jason; Nayyar, Samir; Babb, James; Jazrawi, Laith

2012-10-01

The purpose of this study is to assess the accuracy of MRI quantification of glenoid bone loss and to compare the diagnostic accuracy of MRI to CT in the measurement of glenoid bone loss. MRI, CT, and 3D CT examinations of 18 cadaveric glenoids were obtained after the creation of defects along the anterior and anteroinferior glenoid. The defects were measured by three readers separately and blindly using the circle method. These measurements were compared with measurements made on digital photographic images of the cadaveric glenoids. Paired sample Student t tests were used to compare the imaging modalities. Concordance correlation coefficients were also calculated to measure interobserver agreement. Our data show that MRI could be used to accurately measure glenoid bone loss with a small margin of error (mean, 3.44%; range, 2.06-5.94%) in estimated percentage loss. MRI accuracy was similar to that of both CT and 3D CT for glenoid loss measurements in our study for the readers familiar with the circle method, with 1.3% as the maximum expected difference in accuracy of the percentage bone loss between the different modalities (95% confidence). Glenoid bone loss can be accurately measured on MRI using the circle method. The MRI quantification of glenoid bone loss compares favorably to measurements obtained using 3D CT and CT. The accuracy of the measurements correlates with the level of training, and a learning curve is expected before mastering this technique.

FIACH: A biophysical model for automatic retrospective noise control in fMRI.

PubMed

Tierney, Tim M; Weiss-Croft, Louise J; Centeno, Maria; Shamshiri, Elhum A; Perani, Suejen; Baldeweg, Torsten; Clark, Christopher A; Carmichael, David W

2016-01-01

Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

MRI-based hip cartilage measures in osteoarthritic and non-osteoarthritic individuals: a systematic review

PubMed Central

Aguilar, Hector N; Battié, Michele C

2017-01-01

Osteoarthritis is a common hip joint disease, involving loss of articular cartilage. The prevalence and prognosis of hip osteoarthritis have been difficult to determine, with various clinical and radiological methods used to derive epidemiological estimates exhibiting significant heterogeneity. MRI-based methods directly visualise hip joint cartilage, and offer potential to more reliably define presence and severity of osteoarthritis, but have been underused. We performed a systematic review of MRI-based estimates of hip articular cartilage in the general population and in patients with established osteoarthritis, using MEDLINE, EMBASE and SCOPUS current to June 2016, with search terms such as ‘hip’, ‘femoral head’, ‘cartilage’, ‘volume’, ‘thickness’, ‘MRI’, etc. Ultimately, 11 studies were found appropriate for inclusion, but they were heterogeneous in osteoarthritis assessment methodology and composition. Overall, the studies consistently demonstrate the reliability and potential clinical utility of MRI-based estimates. However, no longitudinal data or reference values for hip cartilage thickness or volume have been published, limiting the ability of MRI to define or risk-stratify hip osteoarthritis. MRI-based techniques are available to quantify articular cartilage signal, volume, thickness and defects, which could establish the sequence and rate of articular cartilage changes at the hip that yield symptomatic osteoarthritis. However, prevalence and rates of progression of hip osteoarthritis have not been established in any MRI studies in the general population. Future investigations could fill this important knowledge gap using robust MRI methods in population-based cross-sectional and longitudinal studies. PMID:28405471

[Gastric magnetic resonance study (methods, semiotics)].

PubMed

Stashuk, G A

2003-01-01

The paper shows the potentialities of gastric study by magnetic resonance imaging (MRI). The methodic aspects of gastric study have been worked out. The MRI-semiotics of the unchanged and tumor-affected wall of the stomach and techniques in examining patients with gastric cancer of various sites are described. Using the developed procedure, MRI was performed in 199 patients, including 154 patients with gastric pathology and 45 control individuals who had no altered gastric wall. Great emphasis is placed on the role of MRI in the diagnosis of endophytic (diffuse) gastric cancer that is of priority value in its morphological structure. MRI was found to play a role in the diagnosis of the spread of a tumorous process both along the walls of the stomach and to its adjacent anatomic structures.

An MRI-Compatible Robotic System With Hybrid Tracking for MRI-Guided Prostate Intervention

PubMed Central

Krieger, Axel; Iordachita, Iulian I.; Guion, Peter; Singh, Anurag K.; Kaushal, Aradhana; Ménard, Cynthia; Pinto, Peter A.; Camphausen, Kevin; Fichtinger, Gabor

2012-01-01

This paper reports the development, evaluation, and first clinical trials of the access to the prostate tissue (APT) II system—a scanner independent system for magnetic resonance imaging (MRI)-guided transrectal prostate interventions. The system utilizes novel manipulator mechanics employing a steerable needle channel and a novel six degree-of-freedom hybrid tracking method, comprising passive fiducial tracking for initial registration and subsequent incremental motion measurements. Targeting accuracy of the system in prostate phantom experiments and two clinical human-subject procedures is shown to compare favorably with existing systems using passive and active tracking methods. The portable design of the APT II system, using only standard MRI image sequences and minimal custom scanner interfacing, allows the system to be easily used on different MRI scanners. PMID:22009867

Studying neuroanatomy using MRI.

PubMed

Lerch, Jason P; van der Kouwe, André J W; Raznahan, Armin; Paus, Tomáš; Johansen-Berg, Heidi; Miller, Karla L; Smith, Stephen M; Fischl, Bruce; Sotiropoulos, Stamatios N

2017-02-23

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

Incorporation of MRI-AIF Information For Improved Kinetic Modelling of Dynamic PET Data

NASA Astrophysics Data System (ADS)

Sari, Hasan; Erlandsson, Kjell; Thielemans, Kris; Atkinson, David; Ourselin, Sebastien; Arridge, Simon; Hutton, Brian F.

2015-06-01

In the analysis of dynamic PET data, compartmental kinetic analysis methods require an accurate knowledge of the arterial input function (AIF). Although arterial blood sampling is the gold standard of the methods used to measure the AIF, it is usually not preferred as it is an invasive method. An alternative method is the simultaneous estimation method (SIME), where physiological parameters and the AIF are estimated together, using information from different anatomical regions. Due to the large number of parameters to estimate in its optimisation, SIME is a computationally complex method and may sometimes fail to give accurate estimates. In this work, we try to improve SIME by utilising an input function derived from a simultaneously obtained DSC-MRI scan. With the assumption that the true value of one of the six parameter PET-AIF model can be derived from an MRI-AIF, the method is tested using simulated data. The results indicate that SIME can yield more robust results when the MRI information is included with a significant reduction in absolute bias of Ki estimates.

Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients

PubMed Central

Cordova, James S.; Shu, Hui-Kuo G.; Liang, Zhongxing; Gurbani, Saumya S.; Cooper, Lee A. D.; Holder, Chad A.; Olson, Jeffrey J.; Kairdolf, Brad; Schreibmann, Eduard; Neill, Stewart G.; Hadjipanayis, Constantinos G.; Shim, Hyunsuk

2016-01-01

Background The standard of care for glioblastoma (GBM) is maximal safe resection followed by radiation therapy with chemotherapy. Currently, contrast-enhanced MRI is used to define primary treatment volumes for surgery and radiation therapy. However, enhancement does not identify the tumor entirely, resulting in limited local control. Proton spectroscopic MRI (sMRI), a method reporting endogenous metabolism, may better define the tumor margin. Here, we develop a whole-brain sMRI pipeline and validate sMRI metrics with quantitative measures of tumor infiltration. Methods Whole-brain sMRI metabolite maps were coregistered with surgical planning MRI and imported into a neuronavigation system to guide tissue sampling in GBM patients receiving 5-aminolevulinic acid fluorescence-guided surgery. Samples were collected from regions with metabolic abnormalities in a biopsy-like fashion before bulk resection. Tissue fluorescence was measured ex vivo using a hand-held spectrometer. Tissue samples were immunostained for Sox2 and analyzed to quantify the density of staining cells using a novel digital pathology image analysis tool. Correlations among sMRI markers, Sox2 density, and ex vivo fluorescence were evaluated. Results Spectroscopic MRI biomarkers exhibit significant correlations with Sox2-positive cell density and ex vivo fluorescence. The choline to N-acetylaspartate ratio showed significant associations with each quantitative marker (Pearson's ρ = 0.82, P < .001 and ρ = 0.36, P < .0001, respectively). Clinically, sMRI metabolic abnormalities predated contrast enhancement at sites of tumor recurrence and exhibited an inverse relationship with progression-free survival. Conclusions As it identifies tumor infiltration and regions at high risk for recurrence, sMRI could complement conventional MRI to improve local control in GBM patients. PMID:26984746

Prostate cancer localization with multispectral MRI using cost-sensitive support vector machines and conditional random fields.

PubMed

Artan, Yusuf; Haider, Masoom A; Langer, Deanna L; van der Kwast, Theodorus H; Evans, Andrew J; Yang, Yongyi; Wernick, Miles N; Trachtenberg, John; Yetik, Imam Samil

2010-09-01

Prostate cancer is a leading cause of cancer death for men in the United States. Fortunately, the survival rate for early diagnosed patients is relatively high. Therefore, in vivo imaging plays an important role for the detection and treatment of the disease. Accurate prostate cancer localization with noninvasive imaging can be used to guide biopsy, radiotherapy, and surgery as well as to monitor disease progression. Magnetic resonance imaging (MRI) performed with an endorectal coil provides higher prostate cancer localization accuracy, when compared to transrectal ultrasound (TRUS). However, in general, a single type of MRI is not sufficient for reliable tumor localization. As an alternative, multispectral MRI, i.e., the use of multiple MRI-derived datasets, has emerged as a promising noninvasive imaging technique for the localization of prostate cancer; however almost all studies are with human readers. There is a significant inter and intraobserver variability for human readers, and it is substantially difficult for humans to analyze the large dataset of multispectral MRI. To solve these problems, this study presents an automated localization method using cost-sensitive support vector machines (SVMs) and shows that this method results in improved localization accuracy than classical SVM. Additionally, we develop a new segmentation method by combining conditional random fields (CRF) with a cost-sensitive framework and show that our method further improves cost-sensitive SVM results by incorporating spatial information. We test SVM, cost-sensitive SVM, and the proposed cost-sensitive CRF on multispectral MRI datasets acquired from 21 biopsy-confirmed cancer patients. Our results show that multispectral MRI helps to increase the accuracy of prostate cancer localization when compared to single MR images; and that using advanced methods such as cost-sensitive SVM as well as the proposed cost-sensitive CRF can boost the performance significantly when compared to SVM.

Language Lateralization in Children Aged 10 to 11 Years: A Combined fMRI and Dichotic Listening Study

PubMed Central

Norrelgen, Fritjof; Lilja, Anders; Ingvar, Martin; Gisselgård, Jens; Fransson, Peter

2012-01-01

Objective The aims of this study were to develop and assess a method to map language networks in children with two auditory fMRI protocols in combination with a dichotic listening task (DL). The method is intended for pediatric patients prior to epilepsy surgery. To evaluate the potential clinical usefulness of the method we first wanted to assess data from a group of healthy children. Methods In a first step language test materials were developed, intended for subsequent implementation in fMRI protocols. An evaluation of this material was done in 30 children with typical development, 10 from the 1st, 4th and the 7th grade, respectively. The language test material was then adapted and implemented in two fMRI protocols intended to target frontal and posterior language networks. In a second step language lateralization was assessed in 17 typical 10–11 year olds with fMRI and DL. To reach a conclusion about language lateralization, firstly, quantitative analyses of the index data from the two fMRI tasks and the index data from the DL task were done separately. In a second step a set of criteria were applied to these results to reach a conclusion about language lateralization. The steps of these analyses are described in detail. Results The behavioral assessment of the language test material showed that it was well suited for typical children. The results of the language lateralization assessments, based on fMRI data and DL data, showed that for 15 of the 17 subjects (88%) a conclusion could be reached about hemispheric language dominance. In 2 cases (12%) DL provided critical data. Conclusions The employment of DL combined with language mapping using fMRI for assessing hemispheric language dominance is novel and it was deemed valuable since it provided additional information compared to the results gained from each method individually. PMID:23284796

Automatic and Reproducible Positioning of Phase-Contrast MRI for the Quantification of Global Cerebral Blood Flow

PubMed Central

Liu, Peiying; Lu, Hanzhang; Filbey, Francesca M.; Pinkham, Amy E.; McAdams, Carrie J.; Adinoff, Bryon; Daliparthi, Vamsi; Cao, Yan

2014-01-01

Phase-Contrast MRI (PC-MRI) is a noninvasive technique to measure blood flow. In particular, global but highly quantitative cerebral blood flow (CBF) measurement using PC-MRI complements several other CBF mapping methods such as arterial spin labeling and dynamic susceptibility contrast MRI by providing a calibration factor. The ability to estimate blood supply in physiological units also lays a foundation for assessment of brain metabolic rate. However, a major obstacle before wider applications of this method is that the slice positioning of the scan, ideally placed perpendicular to the feeding arteries, requires considerable expertise and can present a burden to the operator. In the present work, we proposed that the majority of PC-MRI scans can be positioned using an automatic algorithm, leaving only a small fraction of arteries requiring manual positioning. We implemented and evaluated an algorithm for this purpose based on feature extraction of a survey angiogram, which is of minimal operator dependence. In a comparative test-retest study with 7 subjects, the blood flow measurement using this algorithm showed an inter-session coefficient of variation (CoV) of . The Bland-Altman method showed that the automatic method differs from the manual method by between and , for of the CBF measurements. This is comparable to the variance in CBF measurement using manually-positioned PC MRI alone. In a further application of this algorithm to 157 consecutive subjects from typical clinical cohorts, the algorithm provided successful positioning in 89.7% of the arteries. In 79.6% of the subjects, all four arteries could be planned using the algorithm. Chi-square tests of independence showed that the success rate was not dependent on the age or gender, but the patients showed a trend of lower success rate (p = 0.14) compared to healthy controls. In conclusion, this automatic positioning algorithm could improve the application of PC-MRI in CBF quantification. PMID:24787742

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

Intraoperative magnetic resonance imaging to update interactive navigation in neurosurgery: method and preliminary experience.

PubMed

Wirtz, C R; Bonsanto, M M; Knauth, M; Tronnier, V M; Albert, F K; Staubert, A; Kunze, S

1997-01-01

We report on the first successful intraoperative update of interactive image guidance based on an intraoperatively acquired magnetic resonance imaging (MRI) date set. To date, intraoperative imaging methods such as ultrasound, computerized tomography (CT), or MRI have not been successfully used to update interactive navigation. We developed a method of imaging patients intraoperatively with the surgical field exposed in an MRI scanner (Magnetom Open; Siemens Corp., Erlangen, Germany). In 12 patients, intraoperatively acquired 3D data sets were used for successful recalibration of neuronavigation, accounting for any anatomical changes caused by surgical manipulations. The MKM Microscope (Zeiss Corp., Oberkochen, Germany) was used as navigational system. With implantable fiducial markers, an accuracy of 0.84 +/- 0.4 mm for intraoperative reregistration was achieved. Residual tumor detected on MRI was consequently resected using navigation with the intraoperative data. No adverse effects were observed from intraoperative imaging or the use of navigation with intraoperative images, demonstrating the feasibility of recalibrating navigation with intraoperative MRI.

Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.

PubMed

Featherstone, Adam K; O'Connor, James P B; Little, Ross A; Watson, Yvonne; Cheung, Sue; Babur, Muhammad; Williams, Kaye J; Matthews, Julian C; Parker, Geoff J M

2018-04-01

Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data. DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach. The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Combination of rs-fMRI and sMRI Data to Discriminate Autism Spectrum Disorders in Young Children Using Deep Belief Network.

PubMed

Akhavan Aghdam, Maryam; Sharifi, Arash; Pedram, Mir Mohsen

2018-05-07

In recent years, the use of advanced magnetic resonance (MR) imaging methods such as functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) has recorded a great increase in neuropsychiatric disorders. Deep learning is a branch of machine learning that is increasingly being used for applications of medical image analysis such as computer-aided diagnosis. In a bid to classify and represent learning tasks, this study utilized one of the most powerful deep learning algorithms (deep belief network (DBN)) for the combination of data from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets. The DBN was employed so as to focus on the combination of resting-state fMRI (rs-fMRI), gray matter (GM), and white matter (WM) data. This was done based on the brain regions that were defined using the automated anatomical labeling (AAL), in order to classify autism spectrum disorders (ASDs) from typical controls (TCs). Since the diagnosis of ASD is much more effective at an early age, only 185 individuals (116 ASD and 69 TC) ranging in age from 5 to 10 years were included in this analysis. In contrast, the proposed method is used to exploit the latent or abstract high-level features inside rs-fMRI and sMRI data while the old methods consider only the simple low-level features extracted from neuroimages. Moreover, combining multiple data types and increasing the depth of DBN can improve classification accuracy. In this study, the best combination comprised rs-fMRI, GM, and WM for DBN of depth 3 with 65.56% accuracy (sensitivity = 84%, specificity = 32.96%, F1 score = 74.76%) obtained via 10-fold cross-validation. This result outperforms previously presented methods on ABIDE I dataset.

Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

PubMed

Farsani, Zahra Amini; Schmid, Volker J

2017-01-01

In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI. Schattauer GmbH.

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

Advanced flow MRI: emerging techniques and applications

PubMed Central

Markl, M.; Schnell, S.; Wu, C.; Bollache, E.; Jarvis, K.; Barker, A. J.; Robinson, J. D.; Rigsby, C. K.

2016-01-01

Magnetic resonance imaging (MRI) techniques provide non-invasive and non-ionising methods for the highly accurate anatomical depiction of the heart and vessels throughout the cardiac cycle. In addition, the intrinsic sensitivity of MRI to motion offers the unique ability to acquire spatially registered blood flow simultaneously with the morphological data, within a single measurement. In clinical routine, flow MRI is typically accomplished using methods that resolve two spatial dimensions in individual planes and encode the time-resolved velocity in one principal direction, typically oriented perpendicular to the two-dimensional (2D) section. This review describes recently developed advanced MRI flow techniques, which allow for more comprehensive evaluation of blood flow characteristics, such as real-time flow imaging, 2D multiple-venc phase contrast MRI, four-dimensional (4D) flow MRI, quantification of complex haemodynamic properties, and highly accelerated flow imaging. Emerging techniques and novel applications are explored. In addition, applications of these new techniques for the improved evaluation of cardiovascular (aorta, pulmonary arteries, congenital heart disease, atrial fibrillation, coronary arteries) as well as cerebrovascular disease (intra-cranial arteries and veins) are presented. PMID:26944696

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Random Forest Segregation of Drug Responses May Define Regions of Biological Significance.

PubMed

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies.

Parkinson's disease patient preference and experience with various methods of DBS lead placement.

PubMed

LaHue, Sara C; Ostrem, Jill L; Galifianakis, Nicholas B; San Luciano, Marta; Ziman, Nathan; Wang, Sarah; Racine, Caroline A; Starr, Philip A; Larson, Paul S; Katz, Maya

2017-08-01

Physiology-guided deep brain stimulation (DBS) surgery requires patients to be awake during a portion of the procedure, which may be poorly tolerated. Interventional MRI-guided (iMRI) DBS surgery was developed to use real-time image guidance, obviating the need for patients to be awake during lead placement. All English-speaking adults with PD who underwent iMRI DBS between 2010 and 2014 at our Center were invited to participate. Subjects completed a structured interview that explored perioperative preferences and experiences. We compared these responses to patients who underwent the physiology-guided method, matched for age and gender. Eighty-nine people with PD completed the study. Of those, 40 underwent iMRI, 44 underwent physiology-guided implantation, and five underwent both methods. There were no significant differences in baseline characteristics between groups. The primary reason for choosing iMRI DBS was a preference to be asleep during implantation due to: 1) a history of claustrophobia; 2) concerns about the potential for discomfort during the awake physiology-guided procedure in those with an underlying pain syndrome or severe off-medication symptoms; or 3) non-specific fear about being awake during neurosurgery. Participants were satisfied with both DBS surgery methods. However, identification of the factors associated with a preference for iMRI DBS may allow for optimization of patient experience and satisfaction when choices of surgical methods for DBS implantation are available. Published by Elsevier Ltd.

Automated determination of arterial input function for DCE-MRI of the prostate

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

2011-03-01

Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.

Sodium MRI: Methods and applications

PubMed Central

Madelin, Guillaume; Lee, Jae-Seung; Regatte, Ravinder R.; Jerschow, Alexej

2014-01-01

Sodium NMR spectroscopy and MRI have become popular in recent years through the increased availability of high-field MRI scanners, advanced scanner hardware and improved methodology. Sodium MRI is being evaluated for stroke and tumor detection, for breast cancer studies, and for the assessment of osteoarthritis and muscle and kidney functions, to name just a few. In this article, we aim to present an up-to-date review of the theoretical background, the methodology, the challenges and limitations, and current and potential new applications of sodium MRI. PMID:24815363

[Mechanical Shimming Method and Implementation for Permanent Magnet of MRI System].

PubMed

Xue, Tingqiang; Chen, Jinjun

2015-03-01

A mechanical shimming method and device for permanent magnet of MRI system has been developed to meet its stringent homogeneity requirement without time-consuming passive shimming on site, installation and adjustment efficiency has been increased.

Multiattribute probabilistic prostate elastic registration (MAPPER): Application to fusion of ultrasound and magnetic resonance imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sparks, Rachel, E-mail: rachel.sparks@ucl.ac.uk; Barratt, Dean; Nicolas Bloch, B.

2015-03-15

Purpose: Transrectal ultrasound (TRUS)-guided needle biopsy is the current gold standard for prostate cancer diagnosis. However, up to 40% of prostate cancer lesions appears isoechoic on TRUS. Hence, TRUS-guided biopsy has a high false negative rate for prostate cancer diagnosis. Magnetic resonance imaging (MRI) is better able to distinguish prostate cancer from benign tissue. However, MRI-guided biopsy requires special equipment and training and a longer procedure time. MRI-TRUS fusion, where MRI is acquired preoperatively and then aligned to TRUS, allows for advantages of both modalities to be leveraged during biopsy. MRI-TRUS-guided biopsy increases the yield of cancer positive biopsies. Inmore » this work, the authors present multiattribute probabilistic postate elastic registration (MAPPER) to align prostate MRI and TRUS imagery. Methods: MAPPER involves (1) segmenting the prostate on MRI, (2) calculating a multiattribute probabilistic map of prostate location on TRUS, and (3) maximizing overlap between the prostate segmentation on MRI and the multiattribute probabilistic map on TRUS, thereby driving registration of MRI onto TRUS. MAPPER represents a significant advancement over the current state-of-the-art as it requires no user interaction during the biopsy procedure by leveraging texture and spatial information to determine the prostate location on TRUS. Although MAPPER requires manual interaction to segment the prostate on MRI, this step is performed prior to biopsy and will not substantially increase biopsy procedure time. Results: MAPPER was evaluated on 13 patient studies from two independent datasets—Dataset 1 has 6 studies acquired with a side-firing TRUS probe and a 1.5 T pelvic phased-array coil MRI; Dataset 2 has 7 studies acquired with a volumetric end-firing TRUS probe and a 3.0 T endorectal coil MRI. MAPPER has a root-mean-square error (RMSE) for expert selected fiducials of 3.36 ± 1.10 mm for Dataset 1 and 3.14 ± 0.75 mm for Dataset 2. State-of-the-art MRI-TRUS fusion methods report RMSE of 3.06–2.07 mm. Conclusions: MAPPER aligns MRI and TRUS imagery without manual intervention ensuring efficient, reproducible registration. MAPPER has a similar RMSE to state-of-the-art methods that require manual intervention.« less

A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andreasen, Daniel, E-mail: dana@dtu.dk

Purpose: In radiotherapy based only on magnetic resonance imaging (MRI), knowledge about tissue electron densities must be derived from the MRI. This can be achieved by converting the MRI scan to the so-called pseudo-computed tomography (pCT). An obstacle is that the voxel intensities in conventional MRI scans are not uniquely related to electron density. The authors previously demonstrated that a patch-based method could produce accurate pCTs of the brain using conventional T{sub 1}-weighted MRI scans. The method was driven mainly by local patch similarities and relied on simple affine registrations between an atlas database of the co-registered MRI/CT scan pairsmore » and the MRI scan to be converted. In this study, the authors investigate the applicability of the patch-based approach in the pelvis. This region is challenging for a method based on local similarities due to the greater inter-patient variation. The authors benchmark the method against a baseline pCT strategy where all voxels inside the body contour are assigned a water-equivalent bulk density. Furthermore, the authors implement a parallelized approximate patch search strategy to speed up the pCT generation time to a more clinically relevant level. Methods: The data consisted of CT and T{sub 1}-weighted MRI scans of 10 prostate patients. pCTs were generated using an approximate patch search algorithm in a leave-one-out fashion and compared with the CT using frequently described metrics such as the voxel-wise mean absolute error (MAE{sub vox}) and the deviation in water-equivalent path lengths. Furthermore, the dosimetric accuracy was tested for a volumetric modulated arc therapy plan using dose–volume histogram (DVH) point deviations and γ-index analysis. Results: The patch-based approach had an average MAE{sub vox} of 54 HU; median deviations of less than 0.4% in relevant DVH points and a γ-index pass rate of 0.97 using a 1%/1 mm criterion. The patch-based approach showed a significantly better performance than the baseline water pCT in almost all metrics. The approximate patch search strategy was 70x faster than a brute-force search, with an average prediction time of 20.8 min. Conclusions: The authors showed that a patch-based method based on affine registrations and T{sub 1}-weighted MRI could generate accurate pCTs of the pelvis. The main source of differences between pCT and CT was positional changes of air pockets and body outline.« less

Hepatic fat quantification using chemical shift MR imaging and MR spectroscopy in the presence of hepatic iron deposition: validation in phantoms and in patients with chronic liver disease.

PubMed

Lee, Seung Soo; Lee, Youngjoo; Kim, Namkug; Kim, Seong Who; Byun, Jae Ho; Park, Seong Ho; Lee, Moon-Gyu; Ha, Hyun Kwon

2011-06-01

To compare the accuracy of four chemical shift magnetic resonance imaging (MRI) (CS-MRI) analysis methods and MR spectroscopy (MRS) with and without T2-correction in fat quantification in the presence of excess iron. CS-MRI with six opposed- and in-phase acquisitions and MRS with five-echo acquisitions (TEs of 20, 30, 40, 50, 60 msec) were performed at 1.5 T on phantoms containing various fat fractions (FFs), on phantoms containing various iron concentrations, and in 18 patients with chronic liver disease. For CS-MRI, FFs were estimated with the dual-echo method, with two T2*-correction methods (triple- and multiecho), and with multiinterference methods that corrected for both T2* and spectral interference effects. For MRS, FF was estimated without T2-correction (single-echo MRS) and with T2-correction (multiecho MRS). In the phantoms, T2*- or T2-correction methods for CS-MRI and MRS provided unbiased estimations of FFs (mean bias, -1.1% to 0.5%) regardless of iron concentration, whereas the dual-echo method (-5.5% to -8.4%) and single-echo MRS (12.1% to 37.3%) resulted in large biases in FFs. In patients, the FFs estimated with triple-echo (R = 0.98), multiecho (R = 0.99), and multiinterference (R = 0.99) methods had stronger correlations with multiecho MRS FFs than with the dual-echo method (R = 0.86; P ≤ 0.011). The FFs estimated with multiinterference method showed the closest agreement with multiecho MRS FFs (the 95% limit-of-agreement, -0.2 ± 1.1). T2*- or T2-correction methods are effective in correcting the confounding effects of iron, enabling an accurate fat quantification throughout a wide range of iron concentrations. Spectral modeling of fat may further improve the accuracy of CS-MRI in fat quantification. Copyright © 2011 Wiley-Liss, Inc.

[Imaging and quantitative measurement of brain extracellular space using MRI Gd-DTPA tracer method].

PubMed

He, Qing-yuan; Han, Hong-bin; Xu, Fang-jing-wei; Yan, Jun-hao; Zeng, Jin-jin; Li, Xiao-gang; Fu, Yu; Peng, Yun; Chen, He; Hou, Chao; Xu, Xiao-juan

2010-04-18

To observe the diffusion of Gd-DTPA in brain extracellular space (ECS) by magnetic resonance imaging(MRI) and investigate the feasibility of ECS measurement by using MRI tracer method in vivo. 2 microL Gd-DTPA was introduced into ECS by caudate nucleus according to stereotaxic atlas in 8 Sprague Dawley(SD) rats (male, 280-320 g). The MRI scans were performed at 1 h, 3 h, 6 h, 9 h and 12 h respectively after administration. MRI appearances of Gd-DTPA diffusion and distribution was observed and compared. The MRI signal enhancement was measured at each time point. The neuroethology assessment was performed after MRI scanning at 12 h. The injection was accurate at the center of the caudate nucleus in 6 rats, while, at the capsula externa in other 2 rats. Gd-DTPA diffused isotropically after it was introduced into caudate nucleus, which spread into lateral cortex at 3 h. The MRI signal enhancement distributed mainly in the middle cerebral artery territory. A significant difference was found between the signal enhancement ratio at 1 h and that at 3 h in the original point of caudate nucleus (t=95.63, P<0.01), and the signal enhancement attenuated following the exponential power function y=1.7886x(-0.1776) (R2=0.94). In 2 rats with the injection point at capsula externa, Gd-DTPA diffused anisotropically along the fiber track of white matter during 1 h to 3 h, and spread into the lateral cortex at 6 h. The diffusion and clearance of Gd-DTPA in brain ECS could be monitored and measured quantitatively in vivo by MRI tracer method.

Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

NASA Astrophysics Data System (ADS)

Kontos, Despina; Xing, Ye; Bakic, Predrag R.; Conant, Emily F.; Maidment, Andrew D. A.

2010-03-01

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, p<=0.001). The correlation between the volumetric and the area-based density measures is lower and depends on the training background of the Cumulus software user (r=0.73-84, p<=0.001). In terms of absolute values, MRI provides the lowest volumetric estimates (mean=14.63%), followed by the DM volumetric (mean=22.72%) and area-based measures (mean=29.35%). The MRI estimates of the fibroglandular volume are statistically significantly lower than the DM estimates for women with very low-density breasts (p<=0.001). We attribute these differences to potential partial volume effects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

Oxidative stress measured in vivo without an exogenous contrast agent using QUEST MRI

NASA Astrophysics Data System (ADS)

Berkowitz, Bruce A.

2018-06-01

Decades of experimental studies have implicated excessive generation of reactive oxygen species (ROS) in the decline of tissue function during normal aging, and as a pathogenic factor in a vast array of fatal or debilitating morbidities. This massive body of work has important clinical implications since many antioxidants are FDA approved, readily cross blood-tissue barriers, and are effective at improving disease outcomes. Yet, the potential benefits of antioxidants have remained largely unrealized in patients because conventional methods cannot determine the dose, timing, and drug combinations to be used in clinical trials to localize and decrease oxidative stress. To address this major problem and improve translational success, new methods are urgently needed that non-invasively measure the same ROS biomarker both in animal models and patients with high spatial resolution. Here, we summarize a transformative solution based on a novel method: QUEnch-assiSTed MRI (QUEST MRI). The QUEST MRI index is a significant antioxidant-induced improvement in pathophysiology, or a reduction in 1/T1 (i.e., R1). The latter form of QUEST MRI provides a unique measure of uncontrolled production of endogenous, paramagnetic reactive oxygen species (ROS). QUEST MRI results to-date have been validated by gold standard oxidative stress assays. QUEST MRI has high translational potential because it does not use an exogenous contrast agent and requires only standard MRI equipment. Summarizing, QUEST MRI is a powerful non-invasive approach with unprecedented potential for (i) bridging antioxidant treatment in animal models and patients, (ii) identifying tissue subregions exhibiting oxidative stress, and (iii) coupling oxidative stress localization with behavioral dysfunction, disease pathology, and genetic vulnerabilities to serve as a marker of susceptibility.

Perfusion MRI: The Five Most Frequently Asked Clinical Questions

PubMed Central

Essig, Marco; Nguyen, Thanh Binh; Shiroishi, Mark S.; Saake, Marc; Provenzale, James M.; Enterline, David S.; Anzalone, Nicoletta; Dörfler, Arnd; Rovira, Àlex; Wintermark, Max; Law, Meng

2013-01-01

OBJECTIVE This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging. CONCLUSION Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols. PMID:23971482

Imaging of prostate cancer: a platform for 3D co-registration of in-vivo MRI ex-vivo MRI and pathology

NASA Astrophysics Data System (ADS)

Orczyk, Clément; Mikheev, Artem; Rosenkrantz, Andrew; Melamed, Jonathan; Taneja, Samir S.; Rusinek, Henry

2012-02-01

Objectives: Multi-parametric MRI is emerging as a promising method for prostate cancer diagnosis. prognosis and treatment planning. However, the localization of in-vivo detected lesions and pathologic sites of cancer remains a significant challenge. To overcome this limitation we have developed and tested a system for co-registration of in-vivo MRI, ex-vivo MRI and histology. Materials and Methods: Three men diagnosed with localized prostate cancer (ages 54-72, PSA levels 5.1-7.7 ng/ml) were prospectively enrolled in this study. All patients underwent 3T multi-parametric MRI that included T2W, DCEMRI, and DWI prior to robotic-assisted prostatectomy. Ex-vivo multi-parametric MRI was performed on fresh prostate specimen. Excised prostates were then sliced at regular intervals and photographed both before and after fixation. Slices were perpendicular to the main axis of the posterior capsule, i.e., along the direction of the rectal wall. Guided by the location of the urethra, 2D digital images were assembled into 3D models. Cancer foci, extra-capsular extensions and zonal margins were delineated by the pathologist and included in 3D histology data. A locally-developed software was applied to register in-vivo, ex-vivo and histology using an over-determined set of anatomical landmarks placed in anterior fibro-muscular stroma, central. transition and peripheral zones. The mean root square distance across corresponding control points was used to assess co-registration error. Results: Two specimens were pT3a and one pT2b (negative margin) at pathology. The software successfully fused invivo MRI. ex-vivo MRI fresh specimen and histology using appropriate (rigid and affine) transformation models with mean square error of 1.59 mm. Coregistration accuracy was confirmed by multi-modality viewing using operator-guided variable transparency. Conclusion: The method enables successful co-registration of pre-operative MRI, ex-vivo MRI and pathology and it provides initial evidence of feasibility of MRI-guided surgical planning.

Cost Analysis of MRI Services in Iran: An Application of Activity Based Costing Technique

PubMed Central

Bayati, Mohsen; Mahboub Ahari, Alireza; Badakhshan, Abbas; Gholipour, Mahin; Joulaei, Hassan

2015-01-01

Background: Considerable development of MRI technology in diagnostic imaging, high cost of MRI technology and controversial issues concerning official charges (tariffs) have been the main motivations to define and implement this study. Objectives: The present study aimed to calculate the unit-cost of MRI services using activity-based costing (ABC) as a modern cost accounting system and to fairly compare calculated unit-costs with official charges (tariffs). Materials and Methods: We included both direct and indirect costs of MRI services delivered in fiscal year 2011 in Shiraz Shahid Faghihi hospital. Direct allocation method was used for distribution of overhead costs. We used micro-costing approach to calculate unit-cost of all different MRI services. Clinical cost data were retrieved from the hospital registering system. Straight-line method was used for depreciation cost estimation. To cope with uncertainty and to increase the robustness of study results, unit costs of 33 MRI services was calculated in terms of two scenarios. Results: Total annual cost of MRI activity center (AC) was calculated at USD 400,746 and USD 532,104 based on first and second scenarios, respectively. Ten percent of the total cost was allocated from supportive departments. The annual variable costs of MRI center were calculated at USD 295,904. Capital costs measured at USD 104,842 and USD 236, 200 resulted from the first and second scenario, respectively. Existing tariffs for more than half of MRI services were above the calculated costs. Conclusion: As a public hospital, there are considerable limitations in both financial and administrative databases of Shahid Faghihi hospital. Labor cost has the greatest share of total annual cost of Shahid Faghihi hospital. The gap between unit costs and tariffs implies that the claim for extra budget from health providers may not be relevant for all services delivered by the studied MRI center. With some adjustments, ABC could be implemented in MRI centers. With the settlement of a reliable cost accounting system such as ABC technique, hospitals would be able to generate robust evidences for financial management of their overhead, intermediate and final ACs. PMID:26715979

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

Diffusion properties of conventional and calcium-sensitive MRI contrast agents in the rat cerebral cortex.

PubMed

Hagberg, Gisela E; Mamedov, Ilgar; Power, Anthony; Beyerlein, Michael; Merkle, Hellmut; Kiselev, Valerij G; Dhingra, Kirti; Kubìček, Vojtĕch; Angelovski, Goran; Logothetis, Nikos K

2014-01-01

Calcium-sensitive MRI contrast agents can only yield quantitative results if the agent concentration in the tissue is known. The agent concentration could be determined by diffusion modeling, if relevant parameters were available. We have established an MRI-based method capable of determining diffusion properties of conventional and calcium-sensitive agents. Simulations and experiments demonstrate that the method is applicable both for conventional contrast agents with a fixed relaxivity value and for calcium-sensitive contrast agents. The full pharmacokinetic time-course of gadolinium concentration estimates was observed by MRI before, during and after intracerebral administration of the agent, and the effective diffusion coefficient D* was determined by voxel-wise fitting of the solution to the diffusion equation. The method yielded whole brain coverage with a high spatial and temporal sampling. The use of two types of MRI sequences for sampling of the diffusion time courses was investigated: Look-Locker-based quantitative T(1) mapping, and T(1) -weighted MRI. The observation times of the proposed MRI method is long (up to 20 h) and consequently the diffusion distances covered are also long (2-4 mm). Despite this difference, the D* values in vivo were in agreement with previous findings using optical measurement techniques, based on observation times of a few minutes. The effective diffusion coefficient determined for the calcium-sensitive contrast agents may be used to determine local tissue concentrations and to design infusion protocols that maintain the agent concentration at a steady state, thereby enabling quantitative sensing of the local calcium concentration. Copyright © 2014 John Wiley & Sons, Ltd.

Intra- and inter-examination repeatability of magnetic resonance spectroscopy, magnitude-based MRI, and complex-based MRI for estimation of hepatic proton density fat fraction in overweight and obese children and adults.

PubMed

Tyagi, Avishkar; Yeganeh, Omid; Levin, Yakir; Hooker, Jonathan C; Hamilton, Gavin C; Wolfson, Tanya; Gamst, Anthony; Zand, Amir K; Heba, Elhamy; Loomba, Rohit; Schwimmer, Jeffrey; Middleton, Michael S; Sirlin, Claude B

2015-10-01

Determine intra- and inter-examination repeatability of magnitude-based magnetic resonance imaging (MRI-M), complex-based magnetic resonance imaging (MRI-C), and magnetic resonance spectroscopy (MRS) at 3T for estimating hepatic proton density fat fraction (PDFF), and using MRS as a reference, confirm MRI-M and MRI-C accuracy. Twenty-nine overweight and obese pediatric (n = 20) and adult (n = 9) subjects (23 male, 6 female) underwent three same-day 3T MR examinations. In each examination MRI-M, MRI-C, and single-voxel MRS were acquired three times. For each MRI acquisition, hepatic PDFF was estimated at the MRS voxel location. Intra- and inter-examination repeatability were assessed by computing standard deviations (SDs) and intra-class correlation coefficients (ICCs). Aggregate SD was computed for each method as the square root of the average of first repeat variances. MRI-M and MRI-C PDFF estimation accuracy was assessed using linear regression with MRS as a reference. For MRI-M, MRI-C, and MRS acquisitions, respectively, mean intra-examination SDs were 0.25%, 0.42%, and 0.49%; mean intra-examination ICCs were 0.999, 0.997, and 0.995; mean inter-examination SDs were 0.42%, 0.45%, and 0.46%; and inter-examination ICCs were 0.995, 0.992, and 0.990. Aggregate SD for each method was <0.9%. Using MRS as a reference, regression slope, intercept, average bias, and R (2), respectively, for MRI-M were 0.99%, 1.73%, 1.61%, and 0.986, and for MRI-C were 0.96%, 0.43%, 0.40%, and 0.991. MRI-M, MRI-C, and MRS showed high intra- and inter-examination hepatic PDFF estimation repeatability in overweight and obese subjects. Longitudinal hepatic PDFF change >1.8% (twice the maximum aggregate SD) may represent real change rather than measurement imprecision. Further research is needed to assess whether examinations performed on different days or with different MR technologists affect repeatability of MRS voxel placement and MRS-based PDFF measurements.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) Combined with Positron Emission Tomography-Computed Tomography (PET-CT) and Video-Electroencephalography (VEEG) Have Excellent Diagnostic Value in Preoperative Localization of Epileptic Foci in Children with Epilepsy.

PubMed

Wang, Gui-Bin; Long, Wei; Li, Xiao-Dong; Xu, Guang-Yin; Lu, Ji-Xiang

2017-01-01

BACKGROUND To investigate the effect that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has on surgical decision making relative to video-electroencephalography (VEEG) and positron emission tomography-computed tomography (PET-CT), and if the differences in these variables translates to differences in surgical outcomes. MATERIAL AND METHODS A total of 166 children with epilepsy undergoing preoperative DCE-MRI, VEEG, and PET-CT examinations, surgical resection of epileptic foci, and intraoperative electrocorticography (ECoG) monitoring were enrolled. All children were followed up for 12 months and grouped by Engles prognostic classification for epilepsy. Based on intraoperative ECoG as gold standard, the diagnostic values of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and combined application of DCE-MRI, VEEG, and PET-CT in preoperative localization for epileptic foci were evaluated. RESULTS The sensitivity of DCE-MRI, VEEG, and PET-CT was 59.64%, 76.51%, and 93.98%, respectively; the accuracy of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, and DCE-MRI combined with PET-CT was 57.58%, 67.72%, 91.03%, 91.23%, and 96.49%, respectively. Localization accuracy rate of the combination of DCE-MRI, VEEG, and PET-CT was 98.25% (56/57), which was higher than that of DCE-MRI combined with VEEG and of DCE-MRI combined with PET-CT. No statistical difference was found in the accuracy rate of localization between these three combined techniques. During the 12-month follow-up, children were grouped into Engles grade I (n=106), II (n=31), III (n=21), and IV (n=8) according to postoperative conditions. CONCLUSIONS All DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and DCE-MRI combined with VEEG and PET-CT examinations have excellent accuracy in preoperative localization of epileptic foci and present excellent postoperative efficiency, suggesting that these combined imaging methods are suitable for serving as the reference basis in preoperative localization of epileptic foci in children with epilepsy.

TU-AB-BRA-09: A Novel Method of Generating Ultrafast Volumetric Cine MRI (VC-MRI) Using Prior 4D-MRI and On-Board Phase-Skipped Encoding Acquisition for Radiotherapy Target Localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, C; Yin, F; Harris, W

Purpose: To develop a technique generating ultrafast on-board VC-MRI using prior 4D-MRI and on-board phase-skipped encoding k-space acquisition for real-time 3D target tracking of liver and lung radiotherapy. Methods: The end-of-expiration (EOE) volume in 4D-MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on-board VC-MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformationmore » patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC-MRI volume to match with the 2D on-board sampling data, which was generated by 8-fold phase skipped-encoding k-space acquisition (i.e., sample 1 phase-encoding line out of every 8 lines) to achieve an ultrafast 16–24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end-ofinhalation (EOI) phase at the treatment day was used as ground-truth onboard VC-MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in-vivo feasibility demonstration. Results: The comparison between ground truth and estimated on-board VC-MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume-percent-difference(VPD) between ground-truth and estimated tumor volumes at EOI was 6.28% and the Center-of-Mass-Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed method Conclusion: Preliminary results suggest the feasibility to estimate ultrafast VC-MRI for on-board target localization with phase skipped-encoding k-space acquisition. Research grant from NIH R01-184173.« less

Multi-class SVM model for fMRI-based classification and grading of liver fibrosis

NASA Astrophysics Data System (ADS)

Freiman, M.; Sela, Y.; Edrei, Y.; Pappo, O.; Joskowicz, L.; Abramovitch, R.

2010-03-01

We present a novel non-invasive automatic method for the classification and grading of liver fibrosis from fMRI maps based on hepatic hemodynamic changes. This method automatically creates a model for liver fibrosis grading based on training datasets. Our supervised learning method evaluates hepatic hemodynamics from an anatomical MRI image and three T2*-W fMRI signal intensity time-course scans acquired during the breathing of air, air-carbon dioxide, and carbogen. It constructs a statistical model of liver fibrosis from these fMRI scans using a binary-based one-against-all multi class Support Vector Machine (SVM) classifier. We evaluated the resulting classification model with the leave-one out technique and compared it to both full multi-class SVM and K-Nearest Neighbor (KNN) classifications. Our experimental study analyzed 57 slice sets from 13 mice, and yielded a 98.2% separation accuracy between healthy and low grade fibrotic subjects, and an overall accuracy of 84.2% for fibrosis grading. These results are better than the existing image-based methods which can only discriminate between healthy and high grade fibrosis subjects. With appropriate extensions, our method may be used for non-invasive classification and progression monitoring of liver fibrosis in human patients instead of more invasive approaches, such as biopsy or contrast-enhanced imaging.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Feasibility study using MRI and two optical CT scanners for readout of polymer gel and PresageTM

NASA Astrophysics Data System (ADS)

Svensson, H.; Skyt, P. S.; Ceberg, S.; Doran, S.; Muren, L. P.; Balling, P.; Petersen, J. B. B.; Bäck, S. Å. J.

2013-06-01

The aim of this study was to compare the conventional combination of three-dimensional dosimeter (nPAG gel) and readout method (MRI) with other combinations of three-dimensional dosimeters (nPAG gel/PresageTM) and readout methods (optical CT scanners). In the first experiment, the dose readout of a gel irradiated with a four field-box technique was performed with both an Octopus IQ scanner and MRI. It was seen that the MRI readout agreed slightly better to the TPS. In another experiment, a gel and a PresageTM sample were irradiated with a VMAT field and read out using MRI and a fast laser scanner, respectively. A comparison between the TPS and the volumes revealed that the MRI/gel readout had closer resemblance to the TPS than the optical CT/PresageTM readout. There are clearly potential in the evaluated optical CT scanners, but more time has to be invested in the particular scanning scenario than was possible in this study.

[RSF model optimization and its application to brain tumor segmentation in MRI].

PubMed

Cheng, Zhaoning; Song, Zhijian

2013-04-01

Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.

In Vivo Cytometry of Antigen-Specific T Cells Using 19F MRI

PubMed Central

Srinivas, Mangala; Turner, Michael S.; Janjic, Jelena M.; Morel, Penelope A.; Laidlaw, David H.; Ahrens, Eric T.

2009-01-01

Noninvasive methods to image the trafficking of phenotypically defined immune cells are paramount as we attempt to understand adaptive immunity. A 19F MRI-based methodology for tracking and quantifying cells of a defined phenotype is presented. These methods were applied to a murine inflammation model using antigen-specific T cells. The T cells that were intracellularly labeled ex vivo with a perfluoropolyether (PFPE) nanoemulsion and cells were transferred to a host receiving a localized inoculation of antigen. Longitudinal 19F MRI over 21 days revealed a dynamic accumulation and clearance of T cells in the lymph node (LN) draining the antigen. The apparent T-cell numbers were calculated in the LN from the time-lapse 19F MRI data. The effect of in vivo T-cell division on the 19F MRI cell quantification accuracy was investigated using fluorescence assays. Overall, in vivo cytometry using PFPE labeling and 19F MRI is broadly applicable to studies of whole-body cell biodistribution. PMID:19585593

An update on risk factors for cartilage loss in knee osteoarthritis assessed using MRI-based semiquantitative grading methods.

PubMed

Alizai, Hamza; Roemer, Frank W; Hayashi, Daichi; Crema, Michel D; Felson, David T; Guermazi, Ali

2015-03-01

Arthroscopy-based semiquantitative scoring systems such as Outerbridge and Noyes' scores were the first to be developed for the purpose of grading cartilage defects. As magnetic resonance imaging (MRI) became available for evaluation of the osteoarthritic knee joint, these systems were adapted for use with MRI. Later on, grading methods such as the Whole Organ Magnetic Resonance Score, the Boston-Leeds Osteoarthritis Knee Score and the MRI Osteoarthritis Knee Score were designed specifically for performing whole-organ assessment of the knee joint structures, including cartilage. Cartilage grades on MRI obtained with these scoring systems represent optimal outcome measures for longitudinal studies, and are designed to enhance understanding of the knee osteoarthritis disease process. The purpose of this narrative review is to describe cartilage assessment in knee osteoarthritis using currently available MRI-based semiquantitative whole-organ scoring systems, and to provide an update on the risk factors for cartilage loss in knee osteoarthritis as assessed with these scoring systems.

Development of a histologically validated segmentation protocol for the hippocampal body.

PubMed

Steve, Trevor A; Yasuda, Clarissa L; Coras, Roland; Lail, Mohjevan; Blumcke, Ingmar; Livy, Daniel J; Malykhin, Nikolai; Gross, Donald W

2017-08-15

Recent findings have demonstrated that hippocampal subfields can be selectively affected in different disease states, which has led to efforts to segment the human hippocampus with in vivo magnetic resonance imaging (MRI). However, no studies have examined the histological accuracy of subfield segmentation protocols. The presence of MRI-visible anatomical landmarks with known correspondence to histology represents a fundamental prerequisite for in vivo hippocampal subfield segmentation. In the present study, we aimed to: 1) develop a novel method for hippocampal body segmentation, based on two MRI-visible anatomical landmarks (stratum lacunosum moleculare [SLM] & dentate gyrus [DG]), and assess its accuracy in comparison to the gold standard direct histological measurements; 2) quantify the accuracy of two published segmentation strategies in comparison to the histological gold standard; and 3) apply the novel method to ex vivo MRI and correlate the results with histology. Ultra-high resolution ex vivo MRI was performed on six whole cadaveric hippocampal specimens, which were then divided into 22 blocks and histologically processed. The hippocampal bodies were segmented into subfields based on histological criteria and subfield boundaries and areas were directly measured. A novel method was developed using mean percentage of the total SLM distance to define subfield boundaries. Boundary distances and subfield areas on histology were then determined using the novel method and compared to the gold standard histological measurements. The novel method was then used to determine ex vivo MRI measures of subfield boundaries and areas, which were compared to histological measurements. For direct histological measurements, the mean percentages of total SLM distance were: Subiculum/CA1 = 9.7%, CA1/CA2 = 78.4%, CA2/CA3 = 97.5%. When applied to histology, the novel method provided accurate measures for CA1/CA2 (ICC = 0.93) and CA2/CA3 (ICC = 0.97) boundaries, but not for the Subiculum/CA1 (ICC = -0.04) boundary. Accuracy was poorer using previous techniques for CA1/CA2 (maximum ICC = 0.85) and CA2/CA3 (maximum ICC = 0.88), with the previously reported techniques also performing poorly in defining the Subiculum/CA1 boundary (maximum ICC = 0.00). Ex vivo MRI measurements using the novel method were linearly related to direct measurements of SLM length (r 2 = 0.58), CA1/CA2 boundary (r 2 = 0.39) and CA2/CA3 boundary (r 2 = 0.47), but not for Subiculum/CA1 boundary (r 2 = 0.01). Subfield areas measured with the novel method on histology and ex vivo MRI were linearly related to gold standard histological measures for CA1, CA2, and CA3/CA4/DG. In this initial proof of concept study, we used ex vivo MRI and histology of cadaveric hippocampi to develop a novel segmentation protocol for the hippocampal body. The novel method utilized two anatomical landmarks, SLM & DG, and provided accurate measurements of CA1, CA2, and CA3/CA4/DG subfields in comparison to the gold standard histological measurements. The relationships demonstrated between histology and ex vivo MRI supports the potential feasibility of applying this method to in vivo MRI studies. Copyright © 2017. Published by Elsevier Inc.

Magnetic Resonance Imaging Criteria for Thrombolysis in Hyperacute Cerebral Infarction

PubMed Central

AHMETGJEKAJ, ILIR; KABASHI-MUÇAJ, SERBEZE; LASCU, LUANA CORINA; KABASHI, ANTIGONA; BONDARI, A.; BONDARI, SIMONA; DEDUSHI-HOTI, KRESHNIKE; BIÇAKU, ARDIAN; SHATRI, JETON

2014-01-01

Purpose: Selection of patients with cerebral infarction for MRI that is suitable for thrombolytic therapy as an emerging application. Although the efficiency of the therapy with i.v. tissue plasminogen activator (tPA) within 3 hours after onset of symptoms has been proven in selected patients with CT, now these criteria are determined by MRI, as the data we gather are fast and accurate in the first hours. Material and methods: MRI screening in patients with acute cerebral infarction before application of thrombolytic therapy was done in a UCC Mannheim in Germany. Unlike trials with CT, MRI studies demonstrated the benefits of therapy up to 6 hours after the onset of symptoms. We studied 21 patients hospitalized in Clinic of Neuroradiology at University Clinical Centre in Mannheim-Germany. They all undergo brain MRI evaluation for stroke. This article reviews literature that has followed application of thrombolysis in patients with cerebral infarction based on MRI. Results: We have analyzed the MRI criteria for i.v. application of tPA at this University Centre. Alongside the personal viewpoints of clinicians, survey reveals a variety of clinical aspects and MRI features that are opened for further more exploration: therapeutic effects, the use of the MRI angiography, dynamics, and other. Conclusions: MRI is a tested imaging method for rapid evaluation of patients with hyperacute cerebral infarction, replacing the use of CT imaging and clinical features. MRI criteria for thrombolytic therapy are being applied in some cerebral vascular centres. In Kosovo, the application of thrombolytic therapy has not started yet. PMID:25729591

Signal-to-noise ratio comparison of encoding methods for hyperpolarized noble gas MRI

NASA Technical Reports Server (NTRS)

Zhao, L.; Venkatesh, A. K.; Albert, M. S.; Panych, L. P.

2001-01-01

Some non-Fourier encoding methods such as wavelet and direct encoding use spatially localized bases. The spatial localization feature of these methods enables optimized encoding for improved spatial and temporal resolution during dynamically adaptive MR imaging. These spatially localized bases, however, have inherently reduced image signal-to-noise ratio compared with Fourier or Hadamad encoding for proton imaging. Hyperpolarized noble gases, on the other hand, have quite different MR properties compared to proton, primarily the nonrenewability of the signal. It could be expected, therefore, that the characteristics of image SNR with respect to encoding method will also be very different from hyperpolarized noble gas MRI compared to proton MRI. In this article, hyperpolarized noble gas image SNRs of different encoding methods are compared theoretically using a matrix description of the encoding process. It is shown that image SNR for hyperpolarized noble gas imaging is maximized for any orthonormal encoding method. Methods are then proposed for designing RF pulses to achieve normalized encoding profiles using Fourier, Hadamard, wavelet, and direct encoding methods for hyperpolarized noble gases. Theoretical results are confirmed with hyperpolarized noble gas MRI experiments. Copyright 2001 Academic Press.

TH-C-BRD-06: A Novel MRI Based CT Artifact Correction Method for Improving Proton Range Calculation in the Presence of Severe CT Artifacts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, P; Schreibmann, E; Fox, T

2014-06-15

Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. Themore » CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.« less

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, S; Tianjin University, Tianjin; Hara, W

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2)more » electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.« less

Update on the MRI Core of the Alzheimer's Disease Neuroimaging Initiative

PubMed Central

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; DeCarli, Charles S; Dale, Anders M; Weiner, Michael W

2010-01-01

Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications. PMID:20451869

A comparison of exogenous and endogenous CEST MRI methods for evaluating in vivo pH.

PubMed

Lindeman, Leila R; Randtke, Edward A; High, Rachel A; Jones, Kyle M; Howison, Christine M; Pagel, Mark D

2018-05-01

Extracellular pH (pHe) is an important biomarker for cancer cell metabolism. Acido-chemical exchange saturation transfer (CEST) MRI uses the contrast agent iopamidol to create spatial maps of pHe. Measurements of amide proton transfer exchange rates (k ex ) from endogenous CEST MRI were compared to pHe measurements by exogenous acido-CEST MRI to determine whether endogenous k ex could be used as a proxy for pHe measurements. Spatial maps of pHe and k ex were obtained using exogenous acidoCEST MRI and an endogenous CEST MRI analyzed with the omega plot method, respectively, to evaluate mouse kidney, a flank tumor model, and a spontaneous lung tumor model. The pHe and k ex results were evaluated using pixelwise comparisons. The k ex values obtained from endogenous CEST measurements did not correlate with the pHe results from exogenous CEST measurements. The k ex measurements were limited to fewer pixels and had a limited dynamic range relative to pHe measurements. Measurements of k ex with endogenous CEST MRI cannot substitute for pHe measurements with acidoCEST MRI. Whereas endogenous CEST MRI may still have good utility for evaluating some specific pathologies, exogenous acido-CEST MRI is more appropriate when evaluating pathologies based on pHe values. Magn Reson Med 79:2766-2772, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Comparison between Breast MRI and Contrast-Enhanced Spectral Mammography

PubMed Central

Łuczyńska, Elżbieta; Heinze-Paluchowska, Sylwia; Hendrick, Edward; Dyczek, Sonia; Ryś, Janusz; Herman, Krzysztof; Blecharz, Paweł; Jakubowicz, Jerzy

2015-01-01

Background The main goal of this study was to compare contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) with histopathological results and to compare the sensitivity, accuracy, and positive and negative predictive values for both imaging modalities. Material/Methods After ethics approval, CESM and MRI examinations were performed in 102 patients who had suspicious lesions described in conventional mammography. All visible lesions were evaluated independently by 2 experienced radiologists using BI-RADS classifications (scale 1–5). Dimensions of lesions measured with each modality were compared to postoperative histopathology results. Results There were 102 patients entered into CESM/MRI studies and 118 lesions were identified by the combination of CESM and breast MRI. Histopathology confirmed that 81 of 118 lesions were malignant and 37 were benign. Of the 81 malignant lesions, 72 were invasive cancers and 9 were in situ cancers. Sensitivity was 100% with CESM and 93% with breast MRI. Accuracy was 79% with CESM and 73% with breast MRI. ROC curve areas based on BI-RADS were 0.83 for CESM and 0.84 for breast MRI. Lesion size estimates on CESM and breast MRI were similar, both slightly larger than those from histopathology. Conclusions Our results indicate that CESM has the potential to be a valuable diagnostic method that enables accurate detection of malignant breast lesions, has high negative predictive value, and a false-positive rate similar to that of breast MRI. PMID:25963880

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype.

PubMed

Catana, Ciprian; van der Kouwe, Andre; Benner, Thomas; Michel, Christian J; Hamm, Michael; Fenchel, Matthias; Fischl, Bruce; Rosen, Bruce; Schmand, Matthias; Sorensen, A Gregory

2010-09-01

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e.,

Cardiac MRI in patients with complex CHD following primary or secondary implantation of MRI-conditional pacemaker system.

PubMed

Al-Wakeel, Nadya; O h-Ici, Darach; Schmitt, Katharina R; Messroghli, Daniel R; Riesenkampff, Eugénie; Berger, Felix; Kuehne, Titus; Peters, Bjoern

2016-02-01

In patients with CHD, cardiac MRI is often indicated for functional and anatomical assessment. With the recent introduction of MRI-conditional pacemaker systems, cardiac MRI has become accessible for patients with pacemakers. The present clinical study aims to evaluate safety, susceptibility artefacts, and image reading of cardiac MRI in patients with CHD and MRI-conditional pacemaker systems. Material and methods CHD patients with MRI-conditional pacemaker systems and a clinical need for cardiac MRI were examined with a 1.5-T MRI system. Lead function was tested before and after MRI. Artefacts and image readings were evaluated using a four-point grading scale. A total of nine patients with CHD (mean age 34.0 years, range 19.5-53.6 years) received a total of 11 cardiac MRI examinations. Owing to clinical indications, seven patients had previously been converted from conventional to MRI-conditional pacemaker systems. All MRI examinations were completed without adverse effects. Device testing immediately after MRI and at follow-up showed no alteration of pacemaker device and lead function. Clinical questions could be addressed and answered in all patients. Cardiac MRI can be performed safely with high certainty of diagnosis in CHD patients with MRI-conditional pacemaker systems. In case of clinically indicated lead and box changing, CHD patients with non-MRI-conditional pacemaker systems should be considered for complete conversion to MRI-conditional systems.

A novel anisotropic fast marching method and its application to blood flow computation in phase-contrast MRI.

PubMed

Schwenke, M; Hennemuth, A; Fischer, B; Friman, O

2012-01-01

Phase-contrast MRI (PC MRI) can be used to assess blood flow dynamics noninvasively inside the human body. The acquired images can be reconstructed into flow vector fields. Traditionally, streamlines can be computed based on the vector fields to visualize flow patterns and particle trajectories. The traditional methods may give a false impression of precision, as they do not consider the measurement uncertainty in the PC MRI images. In our prior work, we incorporated the uncertainty of the measurement into the computation of particle trajectories. As a major part of the contribution, a novel numerical scheme for solving the anisotropic Fast Marching problem is presented. A computing time comparison to state-of-the-art methods is conducted on artificial tensor fields. A visual comparison of healthy to pathological blood flow patterns is given. The comparison shows that the novel anisotropic Fast Marching solver outperforms previous schemes in terms of computing time. The visual comparison of flow patterns directly visualizes large deviations of pathological flow from healthy flow. The novel anisotropic Fast Marching solver efficiently resolves even strongly anisotropic path costs. The visualization method enables the user to assess the uncertainty of particle trajectories derived from PC MRI images.

Optimum SNR data compression in hardware using an Eigencoil array.

PubMed

King, Scott B; Varosi, Steve M; Duensing, G Randy

2010-05-01

With the number of receivers available on clinical MRI systems now ranging from 8 to 32 channels, data compression methods are being explored to lessen the demands on the computer for data handling and processing. Although software-based methods of compression after reception lessen computational requirements, a hardware-based method before the receiver also reduces the number of receive channels required. An eight-channel Eigencoil array is constructed by placing a hardware radiofrequency signal combiner inline after preamplification, before the receiver system. The Eigencoil array produces signal-to-noise ratio (SNR) of an optimal reconstruction using a standard sum-of-squares reconstruction, with peripheral SNR gains of 30% over the standard array. The concept of "receiver channel reduction" or MRI data compression is demonstrated, with optimal SNR using only four channels, and with a three-channel Eigencoil, superior sum-of-squares SNR was achieved over the standard eight-channel array. A three-channel Eigencoil portion of a product neurovascular array confirms in vivo SNR performance and demonstrates parallel MRI up to R = 3. This SNR-preserving data compression method advantageously allows users of MRI systems with fewer receiver channels to achieve the SNR of higher-channel MRI systems. (c) 2010 Wiley-Liss, Inc.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Multiple velocity encoding in the phase of an MRI signal

NASA Astrophysics Data System (ADS)

Benitez-Read, E. E.

2017-01-01

The measurement of fluid velocity by encoding it in the phase of a magnetic resonance imaging (MRI) signal could allow the discrimination of the stationary spins signals from those of moving spins. This results in a wide variety of applications i.e. in medicine, in order to obtain more than angiograms, blood velocity images of veins, arteries and other vessels without having static tissue perturbing the signal of fluid in motion. The work presented in this paper is a theoretical analysis of some novel methods for multiple fluid velocity encoding in the phase of an MRI signal. These methods are based on a tripolar gradient (TPG) and can be an alternative to the conventional methods based on a bipolar gradient (BPG) and could be more suitable for multiple velocity encoding in the phase of an MRI signal.

Estimating neural response functions from fMRI

PubMed Central

Kumar, Sukhbinder; Penny, William

2014-01-01

This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response Function (HRF) that are simultaneously fitted to fMRI data using a Bayesian optimization algorithm. This algorithm also produces a model evidence score, providing a formal model comparison method for evaluating alternative NRFs. The HRF is characterized using previously established “Balloon” and BOLD signal models. We illustrate the method with two example applications based on fMRI studies of the auditory system. In the first, we estimate the time constants of repetition suppression and facilitation, and in the second we estimate the parameters of population receptive fields in a tonotopic mapping study. PMID:24847246

Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom.

PubMed

Maikusa, Norihide; Yamashita, Fumio; Tanaka, Kenichiro; Abe, Osamu; Kawaguchi, Atsushi; Kabasawa, Hiroyuki; Chiba, Shoma; Kasahara, Akihiro; Kobayashi, Nobuhisa; Yuasa, Tetsuya; Sato, Noriko; Matsuda, Hiroshi; Iwatsubo, Takeshi

2013-06-01

Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based distortion correction method that accommodates the variation in geometric distortion within MRI images obtained with multivendor MRI scanners. The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for distortion correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a distortion correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this correction improves the test-retest reproducibility of voxel-based morphometry in human studies. A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' distortion correction. Additionally, the authors' method was significantly better than a distortion correction method based on a description of spherical harmonics in improving the distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after distortion correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). The authors proposed a phantom-based distortion correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test-retest reproducibility. The results showed that distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after distortion correction using the authors' method.

[Joint correction for motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging].

PubMed

Wu, Wenchuan; Fang, Sheng; Guo, Hua

2014-06-01

Aiming at motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging (MRI), we proposed a joint correction method in this paper to correct the two kinds of artifacts simultaneously without additional acquisition of navigation data and field map. We utilized the proposed method using multi-shot variable density spiral sequence to acquire MRI data and used auto-focusing technique for image deblurring. We also used direct method or iterative method to correct motion induced phase errors in the process of deblurring. In vivo MRI experiments demonstrated that the proposed method could effectively suppress motion artifacts and off-resonance artifacts and achieve images with fine structures. In addition, the scan time was not increased in applying the proposed method.

Comparative Effectiveness of Frame-based, Frameless and Intraoperative MRI Guided Brain Biopsy Techniques

PubMed Central

Lu, Yi; Yeung, Cecil; Radmanesh, Alireza; Wiemann, Robert; Black, Peter M.; Golby, Alexandra J.

2015-01-01

Objective Intraoperative MRI (IoMRI) guided brain biopsy provides a real time visual feedback of the lesion that is sampled during surgery. The objective of the study is to compare the diagnostic yield and safety profiles of ioMRI needle brain biopsy with two traditional brain biopsy methods: frame-based and frameless stereotactic brain biopsies. Methods A retrospective analysis from 288 consecutive needle brain biopsies in 277 patients undergoing stereotactic brain biopsy with any of the three biopsy methods at Brigham and Women's Hospital from 2000 to 2008 was performed. Variables such as age, sex, history of radiation and previous surgery, pathology results, complications and postoperative stays were analyzed. Results Over the course of eight years, 288 brain biopsies were performed. 253 (87.8%) biopsies yielded positive diagnostic tissue. Young age (<40 years), history of brain radiation or surgery were significant negative predictors for a positive biopsy diagnostic yield. Excluding patients with prior radiation or surgeries, no significant difference in diagnostic yield was detected among the three groups, with frame-based, frameless and ioMRI guided needle biopsies yield 96.9%, 91.8% and 89.9% positive diagnostic yield, respectively. 19 biopsies (6.6%) were complicated by serious adverse events. The ioMRI-guided brain biopsy was associated with less serious adverse events and the shortest postoperative hospital stay. Conclusions Frame-based, frameless stereotactic and ioMRI guided brain needle biopsy have comparable diagnostic yield for patients with no prior treatments (either radiation or surgery). IoMRI guided brain biopsy is associated with fewer serious adverse events and shorter hospital stay. PMID:25088233

Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.

PubMed

Chiew, Mark; Graedel, Nadine N; Miller, Karla L

2018-07-01

Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however, functional data recovery can be poor or incomplete. We introduce a method for improving reconstruction fidelity using external constraints, like an experimental design matrix, to partially orient the estimated fMRI temporal subspace. Combining these external constraints with low-rank constraints introduces a new image reconstruction model that is analogous to using a mixture of subspace-decomposition (PCA/ICA) and regression (GLM) models in fMRI analysis. We show that this approach improves fMRI reconstruction quality in simulations and experimental data, focusing on the model problem of detecting subtle 1-s latency shifts between brain regions in a block-design task-fMRI experiment. Successful latency discrimination is shown at acceleration factors up to R = 16 in a radial-Cartesian acquisition. We show that this approach works with approximate, or not perfectly informative constraints, where the derived benefit is commensurate with the information content contained in the constraints. The proposed method extends low-rank approximation methods for under-sampled fMRI data acquisition by leveraging knowledge of expected task-based variance in the data, enabling improvements in the speed and efficiency of fMRI data acquisition without the loss of subtle features. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

fMRI and EEG responses to periodic visual stimulation.

PubMed

Guy, C N; ffytche, D H; Brovelli, A; Chumillas, J

1999-08-01

EEG/VEP and fMRI responses to periodic visual stimulation are reported. The purpose of these experiments was to look for similar patterns in the time series produced by each method to help understand the relationship between the two. The stimulation protocol was the same for both sets of experiments and consisted of five complete cycles of checkerboard pattern reversal at 1.87 Hz for 30 s followed by 30 s of a stationary checkerboard. The fMRI data was analyzed using standard methods, while the EEG was analyzed with a new measurement of activation-the VEPEG. Both VEPEG and fMRI time series contain the fundamental frequency of the stimulus and quasi harmonic components-an unexplained double frequency commonly found in fMRI data. These results have prompted a reappraisal of the methods for analyzing fMRI data and have suggested a connection between our findings and much older published invasive electrophysiological measurements of blood flow and the partial pressures of oxygen and carbon dioxide. Overall our new analysis suggests that fMRI signals are strongly dependant on hydraulic blood flow effects. We distinguish three categories of fMRI signal corresponding to: focal activated regions of brain tissue; diffuse nonspecific regions of steal; and major cerebral vessels of arterial supply or venous drainage. Each category of signal has its own finger print in frequency, amplitude, and phase. Finally, we put forward the hypothesis that modulations in blood flow are not only the consequence but are also the cause of modulations in functional activity. Copyright 1999 Academic Press.

Registration of MRI to intraoperative radiographs for target localization in spinal interventions

NASA Astrophysics Data System (ADS)

De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Goerres, J.; Jacobson, M. W.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Siewerdsen, J. H.

2017-01-01

Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (covariance-matrix-adaptation evolutionary-strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median  ±  IQR)  =  4.3  ±  2.6 mm (median  ±  IQR) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded dice coefficient  =  88.1  ±  5.2, accuracy  =  90.6  ±  5.7, RMSE  =  1.8  ±  0.6 mm, and contour affinity ratio (CAR)  =  0.82  ±  0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE  <3 mm and CAR  >0.50. The MR-LevelCheck method provides a potentially valuable extension to a previously developed decision support tool for spine surgery target localization by extending its utility to preoperative MRI while maintaining characteristics of accuracy and robustness.

MRI EVALUATION OF KNEE CARTILAGE

PubMed Central

Rodrigues, Marcelo Bordalo; Camanho, Gilberto Luís

2015-01-01

Through the ability of magnetic resonance imaging (MRI) to characterize soft tissue noninvasively, it has become an excellent method for evaluating cartilage. The development of new and faster methods allowed increased resolution and contrast in evaluating chondral structure, with greater diagnostic accuracy. In addition, physiological techniques for cartilage assessment that can detect early changes before the appearance of cracks and erosion have been developed. In this updating article, the various techniques for chondral assessment using knee MRI will be discussed and demonstrated. PMID:27022562

Contrast agents in dynamic contrast-enhanced magnetic resonance imaging

PubMed Central

Yan, Yuling; Sun, Xilin; Shen, Baozhong

2017-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive method to assess angiogenesis, which is widely used in clinical applications including diagnosis, monitoring therapy response and prognosis estimation in cancer patients. Contrast agents play a crucial role in DCE-MRI and should be carefully selected in order to improve accuracy in DCE-MRI examination. Over the past decades, there was much progress in the development of optimal contrast agents in DCE-MRI. In this review, we describe the recent research advances in this field and discuss properties of contrast agents, as well as their advantages and disadvantages. Finally, we discuss the research perspectives for improving this promising imaging method. PMID:28415647

A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125

RAPID COMMUNICATION: Magnetic resonance imaging inside metallic vessels

NASA Astrophysics Data System (ADS)

Han, Hui; Balcom, Bruce J.

2010-10-01

We introduce magnetic resonance imaging (MRI) measurements inside metallic vessels. Until now, MRI has been unusable inside metallic vessels because of eddy currents in the walls. We have solved the problem and generated high quality images by employing a magnetic field gradient monitoring method. The ability to image within metal enclosures and structures means many new samples and systems are now amenable to MRI. Most importantly this study will form the basis of new MRI-compatible metallic pressure vessels, which will permit MRI of macroscopic systems at high pressure.

Acute vertigo in an anesthesia provider during exposure to a 3T MRI scanner

PubMed Central

Gorlin, Andrew; Hoxworth, Joseph M; Pavlicek, William; Thunberg, Christopher A; Seamans, David

2015-01-01

Vertigo induced by exposure to the magnetic field of a magnetic resonance imaging (MRI) scanner is a well-known phenomenon within the radiology community but is not widely appreciated by other clinical specialists. Here, we describe a case of an anesthetist experiencing acute vertigo while providing sedation to a patient undergoing a 3 Tesla MRI scan. After discussing previous reports, and the evidence surrounding MRI-induced vertigo, we review potential etiologies that include the effects of both static and time-varying magnetic fields on the vestibular apparatus. We conclude our review by discussing the occupational standards that exist for MRI exposure and methods to minimize the risks of MRI-induced vertigo for clinicians working in the MRI environment. PMID:25792858

Fully automatic lesion segmentation in breast MRI using mean-shift and graph-cuts on a region adjacency graph.

PubMed

McClymont, Darryl; Mehnert, Andrew; Trakic, Adnan; Kennedy, Dominic; Crozier, Stuart

2014-04-01

To present and evaluate a fully automatic method for segmentation (i.e., detection and delineation) of suspicious tissue in breast MRI. The method, based on mean-shift clustering and graph-cuts on a region adjacency graph, was developed and its parameters tuned using multimodal (T1, T2, DCE-MRI) clinical breast MRI data from 35 subjects (training data). It was then tested using two data sets. Test set 1 comprises data for 85 subjects (93 lesions) acquired using the same protocol and scanner system used to acquire the training data. Test set 2 comprises data for eight subjects (nine lesions) acquired using a similar protocol but a different vendor's scanner system. Each lesion was manually delineated in three-dimensions by an experienced breast radiographer to establish segmentation ground truth. The regions of interest identified by the method were compared with the ground truth and the detection and delineation accuracies quantitatively evaluated. One hundred percent of the lesions were detected with a mean of 4.5 ± 1.2 false positives per subject. This false-positive rate is nearly 50% better than previously reported for a fully automatic breast lesion detection system. The median Dice coefficient for Test set 1 was 0.76 (interquartile range, 0.17), and 0.75 (interquartile range, 0.16) for Test set 2. The results demonstrate the efficacy and accuracy of the proposed method as well as its potential for direct application across different MRI systems. It is (to the authors' knowledge) the first fully automatic method for breast lesion detection and delineation in breast MRI.

A Novel Diffusion MRI Phantom, and a Method for Enhancing MR Image Quality | NCI Technology Transfer Center | TTC

Cancer.gov

The use of Polyvinyl Pyrrolidone (PVP) solutions of varying concentrations as phantoms for diffusion MRI calibration and quality control is disclosed. This diffusion MRI phantom material is already being adopted by radiologists for quality control and assurance in clinical studies.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Functional Imaging of the Lungs with Gas Agents

PubMed Central

Kruger, Stanley J.; Nagle, Scott K.; Couch, Marcus J.; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B.

2015-01-01

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI) – hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas – and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multi-detector computed tomography (CT). However, MRI also offers capabilities for fast multi-spectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultra-short echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. Relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF) in both adults and children. PMID:26218920

Random Forest Segregation of Drug Responses May Define Regions of Biological Significance

PubMed Central

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies. PMID:27014046

Robust registration of sparsely sectioned histology to ex-vivo MRI of temporal lobe resections

NASA Astrophysics Data System (ADS)

Goubran, Maged; Khan, Ali R.; Crukley, Cathie; Buchanan, Susan; Santyr, Brendan; deRibaupierre, Sandrine; Peters, Terry M.

2012-02-01

Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate preoperative localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement. The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectralMagnetic Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful, these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned histology images of resected tissue represents a challenge for 3D reconstruction which we address with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm. This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for eventual registration with pre-operative MRI images.

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

PubMed

Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Quantitative body DW-MRI biomarkers uncertainty estimation using unscented wild-bootstrap.

PubMed

Freiman, M; Voss, S D; Mulkern, R V; Perez-Rossello, J M; Warfield, S K

2011-01-01

We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wild-bootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of -36% in the uncertainty values.

[A comparison between 3.0 T MRI and histopathology for preoperative T staging of potentially resectable esophageal cancer].

PubMed

Wang, Z Q; Zhang, F G; Guo, J; Zhang, H K; Qin, J J; Zhao, Y; Ding, Z D; Zhang, Z X; Zhang, J B; Yuan, J H; Li, H L; Qu, J R

2017-03-21

Objective: To explore the value of 3.0 T MRI using multiple sequences (star VIBE+ BLADE) in evaluating the preoperative T staging for potentially resectable esophageal cancer (EC). Methods: Between April 2015 and March 2016, a total of 66 consecutive patients with endoscopically proven resectable EC underwent 3.0T MRI in the Affiliated Cancer Hospital of Zhengzhou University.Two independent readers were assigned a T staging on MRI according to the 7th edition of UICC-AJCC TNM Classification, the results of preoperative T staging were compared and analyzed with post-operative pathologic confirmation. Results: The MRI T staging of two readers were highly consistent with histopathological findings, and the sensitivity, specificity and accuracy of preoperative T staging MR imaging were also very high. Conclusion: 3.0 T MRI using multiple sequences is with high accuracy for patients of potentially resectable EC in T staging. The staging accuracy of T1, T2 and T3 is better than that of T4a. 3.0T MRI using multiple sequences could be used as a noninvasive imaging method for pre-operative T staging of EC.

A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors.

PubMed

Bergamino, M; Bonzano, L; Levrero, F; Mancardi, G L; Roccatagliata, L

2014-09-01

In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Improvement in the measurement error of the specific binding ratio in dopamine transporter SPECT imaging due to exclusion of the cerebrospinal fluid fraction using the threshold of voxel RI count.

PubMed

Mizumura, Sunao; Nishikawa, Kazuhiro; Murata, Akihiro; Yoshimura, Kosei; Ishii, Nobutomo; Kokubo, Tadashi; Morooka, Miyako; Kajiyama, Akiko; Terahara, Atsuro

2018-05-01

In Japan, the Southampton method for dopamine transporter (DAT) SPECT is widely used to quantitatively evaluate striatal radioactivity. The specific binding ratio (SBR) is the ratio of specific to non-specific binding observed after placing pentagonal striatal voxels of interest (VOIs) as references. Although the method can reduce the partial volume effect, the SBR may fluctuate due to the presence of low-count areas of cerebrospinal fluid (CSF), caused by brain atrophy, in the striatal VOIs. We examined the effect of the exclusion of low-count VOIs on SBR measurement. We retrospectively reviewed DAT imaging of 36 patients with parkinsonian syndromes performed after injection of 123 I-FP-CIT. SPECT data were reconstructed using three conditions. We defined the CSF area in each SPECT image after segmenting the brain tissues. A merged image of gray and white matter images was constructed from each patient's magnetic resonance imaging (MRI) to create an idealized brain image that excluded the CSF fraction (MRI-mask method). We calculated the SBR and asymmetric index (AI) in the MRI-mask method for each reconstruction condition. We then calculated the mean and standard deviation (SD) of voxel RI counts in the reference VOI without the striatal VOIs in each image, and determined the SBR by excluding the low-count pixels (threshold method) using five thresholds: mean-0.0SD, mean-0.5SD, mean-1.0SD, mean-1.5SD, and mean-2.0SD. We also calculated the AIs from the SBRs measured using the threshold method. We examined the correlation among the SBRs of the threshold method, between the uncorrected SBRs and the SBRs of the MRI-mask method, and between the uncorrected AIs and the AIs of the MRI-mask method. The intraclass correlation coefficient indicated an extremely high correlation among the SBRs and among the AIs of the MRI-mask and threshold methods at thresholds between mean-2.0D and mean-1.0SD, regardless of the reconstruction correction. The differences among the SBRs and the AIs of the two methods were smallest at thresholds between man-2.0SD and mean-1.0SD. The SBR calculated using the threshold method was highly correlated with the MRI-SBR. These results suggest that the CSF correction of the threshold method is effective for the calculation of idealized SBR and AI values.

Monitoring local heating around an interventional MRI antenna with RF radiometry

PubMed Central

Ertürk, M. Arcan; El-Sharkawy, AbdEl-Monem M.; Bottomley, Paul A.

2015-01-01

Purpose: Radiofrequency (RF) radiometry uses thermal noise detected by an antenna to measure the temperature of objects independent of medical imaging technologies such as magnetic resonance imaging (MRI). Here, an active interventional MRI antenna can be deployed as a RF radiometer to measure local heating, as a possible new method of monitoring device safety and thermal therapy. Methods: A 128 MHz radiometer receiver was fabricated to measure the RF noise voltage from an interventional 3 T MRI loopless antenna and calibrated for temperature in a uniformly heated bioanalogous gel phantom. Local heating (ΔT) was induced using the antenna for RF transmission and measured by RF radiometry, fiber-optic thermal sensors, and MRI thermometry. The spatial thermal sensitivity of the antenna radiometer was numerically computed using a method-of-moment electric field analyses. The gel’s thermal conductivity was measured by MRI thermometry, and the localized time-dependent ΔT distribution computed from the bioheat transfer equation and compared with radiometry measurements. A “H-factor” relating the 1 g-averaged ΔT to the radiometric temperature was introduced to estimate peak temperature rise in the antenna’s sensitive region. Results: The loopless antenna radiometer linearly tracked temperature inside a thermally equilibrated phantom up to 73 °C to within ±0.3 °C at a 2 Hz sample rate. Computed and MRI thermometric measures of peak ΔT agreed within 13%. The peak 1 g-average temperature was H = 1.36 ± 0.02 times higher than the radiometric temperature for any media with a thermal conductivity of 0.15–0.50 (W/m)/K, indicating that the radiometer can measure peak 1 g-averaged ΔT in physiologically relevant tissue within ±0.4 °C. Conclusions: Active internal MRI detectors can serve as RF radiometers at the MRI frequency to provide accurate independent measures of local and peak temperature without the artifacts that can accompany MRI thermometry or the extra space needed to accommodate alternative thermal transducers. A RF radiometer could be integrated in a MRI scanner to permit “self-monitoring” for assuring device safety and/or monitoring delivery of thermal therapy. PMID:25735295

Respiratory motion resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK)

PubMed Central

Han, Fei; Zhou, Ziwu; Cao, Minsong; Yang, Yingli; Sheng, Ke; Hu, Peng

2017-01-01

Purpose To propose and validate a respiratory motion resolved, self-gated (SG) 4D-MRI technique to assess patient-specific breathing motion of abdominal organs for radiation treatment planning. Methods The proposed 4D-MRI technique was based on the balanced steady-state free-precession (bSSFP) technique and 3D k-space encoding. A novel ROtating Cartesian K-space (ROCK) reordering method was designed that incorporates repeatedly sampled k-space centerline as the SG motion surrogate and allows for retrospective k-space data binning into different respiratory positions based on the amplitude of the surrogate. The multiple respiratory-resolved 3D k-space data were subsequently reconstructed using a joint parallel imaging and compressed sensing method with spatial and temporal regularization. The proposed 4D-MRI technique was validated using a custom-made dynamic motion phantom and was tested in 6 healthy volunteers, in whom quantitative diaphragm and kidney motion measurements based on 4D-MRI images were compared with those based on 2D-CINE images. Results The 5-minute 4D-MRI scan offers high-quality volumetric images in 1.2×1.2×1.6mm3 and 8 respiratory positions, with good soft-tissue contrast. In phantom experiments with triangular motion waveform, the motion amplitude measurements based on 4D-MRI were 11.89% smaller than the ground truth, whereas a −12.5% difference was expected due to data binning effects. In healthy volunteers, the difference between the measurements based on 4D-MRI and the ones based on 2D-CINE were 6.2±4.5% for the diaphragm, 8.2±4.9% and 8.9±5.1% for the right and left kidney. Conclusion The proposed 4D-MRI technique could provide high resolution, high quality, respiratory motion resolved 4D images with good soft-tissue contrast and are free of the “stitching” artifacts usually seen on 4D-CT and 4D-MRI based on resorting 2D-CINE. It could be used to visualize and quantify abdominal organ motion for MRI-based radiation treatment planning. PMID:28133752

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, L; Yin, F; Cai, J

Purpose: To develop a methodology of constructing physiological-based virtual thorax phantom based on hyperpolarized (HP) gas tagging MRI for evaluating deformable image registration (DIR). Methods: Three healthy subjects were imaged at both the end-of-inhalation (EOI) and the end-of-exhalation (EOE) phases using a high-resolution (2.5mm isovoxel) 3D proton MRI, as well as a hybrid MRI which combines HP gas tagging MRI and a low-resolution (4.5mm isovoxel) proton MRI. A sparse tagging displacement vector field (tDVF) was derived from the HP gas tagging MRI by tracking the displacement of tagging grids between EOI and EOE. Using the tDVF and the high-resolution MRmore » images, we determined the motion model of the entire thorax in the following two steps: 1) the DVF inside of lungs was estimated based on the sparse tDVF using a novel multi-step natural neighbor interpolation method; 2) the DVF outside of lungs was estimated from the DIR between the EOI and EOE images (Velocity AI). The derived motion model was then applied to the high-resolution EOI image to create a deformed EOE image, forming the virtual phantom where the motion model provides the ground truth of deformation. Five DIR methods were evaluated using the developed virtual phantom. Errors in DVF magnitude (Em) and angle (Ea) were determined and compared for each DIR method. Results: Among the five DIR methods, free form deformation produced DVF results that are most closely resembling the ground truth (Em=1.04mm, Ea=6.63°). The two DIR methods based on B-spline produced comparable results (Em=2.04mm, Ea=13.66°; and Em =2.62mm, Ea=17.67°), and the two optical-flow methods produced least accurate results (Em=7.8mm; Ea=53.04°; Em=4.45mm, Ea=31.02°). Conclusion: A methodology for constructing physiological-based virtual thorax phantom based on HP gas tagging MRI has been developed. Initial evaluation demonstrated its potential as an effective tool for robust evaluation of DIR in the lung.« less

Dipy, a library for the analysis of diffusion MRI data.

PubMed

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.

MRI-guided brain PET image filtering and partial volume correction

NASA Astrophysics Data System (ADS)

Yan, Jianhua; Chu-Shern Lim, Jason; Townsend, David W.

2015-02-01

Positron emission tomography (PET) image quantification is a challenging problem due to limited spatial resolution of acquired data and the resulting partial volume effects (PVE), which depend on the size of the structure studied in relation to the spatial resolution and which may lead to over or underestimation of the true tissue tracer concentration. In addition, it is usually necessary to perform image smoothing either during image reconstruction or afterwards to achieve a reasonable signal-to-noise ratio. Typically, an isotropic Gaussian filtering (GF) is used for this purpose. However, the noise suppression is at the cost of deteriorating spatial resolution. As hybrid imaging devices such as PET/MRI have become available, the complementary information derived from high definition morphologic images could be used to improve the quality of PET images. In this study, first of all, we propose an MRI-guided PET filtering method by adapting a recently proposed local linear model and then incorporate PVE into the model to get a new partial volume correction (PVC) method without parcellation of MRI. In addition, both the new filtering and PVC are voxel-wise non-iterative methods. The performance of the proposed methods were investigated with simulated dynamic FDG brain dataset and 18F-FDG brain data of a cervical cancer patient acquired with a simultaneous hybrid PET/MR scanner. The initial simulation results demonstrated that MRI-guided PET image filtering can produce less noisy images than traditional GF and bias and coefficient of variation can be further reduced by MRI-guided PET PVC. Moreover, structures can be much better delineated in MRI-guided PET PVC for real brain data.

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

Dipy, a library for the analysis of diffusion MRI data

PubMed Central

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing. PMID:24600385

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.

PubMed

Leynes, Andrew P; Yang, Jaewon; Wiesinger, Florian; Kaushik, Sandeep S; Shanbhag, Dattesh D; Seo, Youngho; Hope, Thomas A; Larson, Peder E Z

2018-05-01

Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone is neglected. Ultrashort-echo-time or zero-echo-time (ZTE) pulse sequences can capture bone information. We propose the use of patient-specific multiparametric MRI consisting of Dixon MRI and proton-density-weighted ZTE MRI to directly synthesize pseudo-CT images with a deep learning model: we call this method ZTE and Dixon deep pseudo-CT (ZeDD CT). Methods: Twenty-six patients were scanned using an integrated 3-T time-of-flight PET/MRI system. Helical CT images of the patients were acquired separately. A deep convolutional neural network was trained to transform ZTE and Dixon MR images into pseudo-CT images. Ten patients were used for model training, and 16 patients were used for evaluation. Bone and soft-tissue lesions were identified, and the SUV max was measured. The root-mean-squared error (RMSE) was used to compare the MR-based attenuation correction with the ground-truth CT attenuation correction. Results: In total, 30 bone lesions and 60 soft-tissue lesions were evaluated. The RMSE in PET quantification was reduced by a factor of 4 for bone lesions (10.24% for Dixon PET and 2.68% for ZeDD PET) and by a factor of 1.5 for soft-tissue lesions (6.24% for Dixon PET and 4.07% for ZeDD PET). Conclusion: ZeDD CT produces natural-looking and quantitatively accurate pseudo-CT images and reduces error in pelvic PET/MRI attenuation correction compared with standard methods. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

TH-A-BRF-08: Deformable Registration of MRI and CT Images for MRI-Guided Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, H; Wen, N; Gordon, J

2014-06-15

Purpose: To evaluate the quality of a commercially available MRI-CT image registration algorithm and then develop a method to improve the performance of this algorithm for MRI-guided prostate radiotherapy. Methods: Prostate contours were delineated on ten pairs of MRI and CT images using Eclipse. Each pair of MRI and CT images was registered with an intensity-based B-spline algorithm implemented in Velocity. A rectangular prism that contains the prostate volume was partitioned into a tetrahedral mesh which was aligned to the CT image. A finite element method (FEM) was developed on the mesh with the boundary constraints assigned from the Velocitymore » generated displacement vector field (DVF). The resultant FEM displacements were used to adjust the Velocity DVF within the prism. Point correspondences between the CT and MR images identified within the prism could be used as additional boundary constraints to enforce the model deformation. The FEM deformation field is smooth in the interior of the prism, and equal to the Velocity displacements at the boundary of the prism. To evaluate the Velocity and FEM registration results, three criteria were used: prostate volume conservation and center consistence under contour mapping, and unbalanced energy of their deformation maps. Results: With the DVFs generated by the Velocity and FEM simulations, the prostate contours were warped from MRI to CT images. With the Velocity DVFs, the prostate volumes changed 10.2% on average, in contrast to 1.8% induced by the FEM DVFs. The average of the center deviations was 0.36 and 0.27 cm, and the unbalance energy was 2.65 and 0.38 mJ/cc3 for the Velocity and FEM registrations, respectively. Conclusion: The adaptive FEM method developed can be used to reduce the error of the MIbased registration algorithm implemented in Velocity in the prostate region, and consequently may help improve the quality of MRI-guided radiation therapy.« less

Assessment of nerve involvement in the lumbar spine: agreement between magnetic resonance imaging, physical examination and pain drawing findings.

PubMed

Bertilson, Bo C; Brosjö, Eva; Billing, Hans; Strender, Lars-Erik

2010-09-10

Detection of nerve involvement originating in the spine is a primary concern in the assessment of spine symptoms. Magnetic resonance imaging (MRI) has become the diagnostic method of choice for this detection. However, the agreement between MRI and other diagnostic methods for detecting nerve involvement has not been fully evaluated. The aim of this diagnostic study was to evaluate the agreement between nerve involvement visible in MRI and findings of nerve involvement detected in a structured physical examination and a simplified pain drawing. Sixty-one consecutive patients referred for MRI of the lumbar spine were - without knowledge of MRI findings - assessed for nerve involvement with a simplified pain drawing and a structured physical examination. Agreement between findings was calculated as overall agreement, the p value for McNemar's exact test, specificity, sensitivity, and positive and negative predictive values. MRI-visible nerve involvement was significantly less common than, and showed weak agreement with, physical examination and pain drawing findings of nerve involvement in corresponding body segments. In spine segment L4-5, where most findings of nerve involvement were detected, the mean sensitivity of MRI-visible nerve involvement to a positive neurological test in the physical examination ranged from 16-37%. The mean specificity of MRI-visible nerve involvement in the same segment ranged from 61-77%. Positive and negative predictive values of MRI-visible nerve involvement in segment L4-5 ranged from 22-78% and 28-56% respectively. In patients with long-standing nerve root symptoms referred for lumbar MRI, MRI-visible nerve involvement significantly underestimates the presence of nerve involvement detected by a physical examination and a pain drawing. A structured physical examination and a simplified pain drawing may reveal that many patients with "MRI-invisible" lumbar symptoms need treatment aimed at nerve involvement. Factors other than present MRI-visible nerve involvement may be responsible for findings of nerve involvement in the physical examination and the pain drawing.

Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paulson, Eric S., E-mail: epaulson@mcw.edu; Erickson, Beth; Schultz, Chris

Purpose: The use of magnetic resonance imaging (MRI) in radiation oncology is expanding rapidly, and more clinics are integrating MRI into their radiation therapy workflows. However, radiation therapy presents a new set of challenges and places additional constraints on MRI compared to diagnostic radiology that, if not properly addressed, can undermine the advantages MRI offers for radiation treatment planning (RTP). The authors introduce here strategies to manage several challenges of using MRI for virtual simulation in external beam RTP. Methods: A total of 810 clinical MRI simulation exams were performed using a dedicated MRI scanner for external beam RTP ofmore » brain, breast, cervix, head and neck, liver, pancreas, prostate, and sarcoma cancers. Patients were imaged in treatment position using MRI-optimal immobilization devices. Radiofrequency (RF) coil configurations and scan protocols were optimized based on RTP constraints. Off-resonance and gradient nonlinearity-induced geometric distortions were minimized or corrected prior to using images for RTP. A multidisciplinary MRI simulation guide, along with window width and level presets, was created to standardize use of MR images during RTP. A quality assurance program was implemented to maintain accuracy and repeatability of MRI simulation exams. Results: The combination of a large bore scanner, high field strength, and circumferentially wrapped, flexible phased array RF receive coils permitted acquisition of thin slice images with high contrast-to-noise ratio (CNR) and image intensity uniformity, while simultaneously accommodating patient setup and immobilization devices. Postprocessing corrections and alternative acquisition methods were required to reduce or correct off-resonance and gradient nonlinearity induced geometric distortions. Conclusions: The methodology described herein contains practical strategies the authors have implemented through lessons learned performing clinical MRI simulation exams. In their experience, these strategies provide robust, high fidelity, high contrast MR images suitable for external beam RTP.« less

Comparative study of microelectrode recording-based STN location and MRI-based STN location in low to ultra-high field (7.0 T) T2-weighted MRI images

NASA Astrophysics Data System (ADS)

Verhagen, Rens; Schuurman, P. Richard; van den Munckhof, Pepijn; Fiorella Contarino, M.; de Bie, Rob M. A.; Bour, Lo J.

2016-12-01

Objective. The correspondence between the anatomical STN and the STN observed in T2-weighted MRI images used for deep brain stimulation (DBS) targeting remains unclear. Using a new method, we compared the STN borders seen on MRI images with those estimated by intraoperative microelectrode recordings (MER). Approach. We developed a method to automatically generate a detailed estimation of STN shape and the location of its borders, based on multiple-channel MER measurements. In 33 STNs of 19 Parkinson patients, we quantitatively compared the dorsal and lateral borders of this MER-based STN model with the STN borders visualized by 1.5 T (n = 14), 3.0 T (n = 10) and 7.0 T (n = 9) T2-weighted MRI. Main results. The dorsal border was identified more dorsally on coronal T2 MRI than by the MER-based STN model, with a significant difference in the 3.0 T (range 0.97-1.19 mm) and 7.0 T (range 1.23-1.25 mm) groups. The lateral border was significantly more medial on 1.5 T (mean: 1.97 mm) and 3.0 T (mean: 2.49 mm) MRI than in the MER-based STN; a difference that was not found in the 7.0 T group. Significance. The STN extends further in the dorsal direction on coronal T2 MRI images than is measured by MER. Increasing MRI field strength to 3.0 T or 7.0 T yields similar discrepancies between MER and MRI at the dorsal STN border. In contrast, increasing MRI field strength to 7.0 T may be useful for identification of the lateral STN border and thereby improve DBS targeting.

Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.

PubMed

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; Decarli, Charles S; Dale, Anders M; Carmichael, Owen W; Tosun, Duygu; Weiner, Michael W

2010-05-01

Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications. Copyright 2010 The Alzheimer

Improved operative efficiency using a real-time MRI-guided stereotactic platform for laser amygdalohippocampotomy.

PubMed

Ho, Allen L; Sussman, Eric S; Pendharkar, Arjun V; Le, Scheherazade; Mantovani, Alessandra; Keebaugh, Alaine C; Drover, David R; Grant, Gerald A; Wintermark, Max; Halpern, Casey H

2018-04-01

OBJECTIVE MR-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive method for thermal destruction of benign or malignant tissue that has been used for selective amygdalohippocampal ablation for the treatment of temporal lobe epilepsy. The authors report their initial experience adopting a real-time MRI-guided stereotactic platform that allows for completion of the entire procedure in the MRI suite. METHODS Between October 2014 and May 2016, 17 patients with mesial temporal sclerosis were selected by a multidisciplinary epilepsy board to undergo a selective amygdalohippocampal ablation for temporal lobe epilepsy using MRgLITT. The first 9 patients underwent standard laser ablation in 2 phases (operating room [OR] and MRI suite), whereas the next 8 patients underwent laser ablation entirely in the MRI suite with the ClearPoint platform. A checklist specific to the real-time MRI-guided laser amydalohippocampal ablation was developed and used for each case. For both cohorts, clinical and operative information, including average case times and accuracy data, was collected and analyzed. RESULTS There was a learning curve associated with using this real-time MRI-guided system. However, operative times decreased in a linear fashion, as did total anesthesia time. In fact, the total mean patient procedure time was less in the MRI cohort (362.8 ± 86.6 minutes) than in the OR cohort (456.9 ± 80.7 minutes). The mean anesthesia time was significantly shorter in the MRI cohort (327.2 ± 79.9 minutes) than in the OR cohort (435.8 ± 78.4 minutes, p = 0.02). CONCLUSIONS The real-time MRI platform for MRgLITT can be adopted in an expedient manner. Completion of MRgLITT entirely in the MRI suite may lead to significant advantages in procedural times.

The physics of functional magnetic resonance imaging (fMRI)

NASA Astrophysics Data System (ADS)

Buxton, Richard B.

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

The physics of functional magnetic resonance imaging (fMRI)

PubMed Central

Buxton, Richard B

2015-01-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology. PMID:24006360

The physics of functional magnetic resonance imaging (fMRI).

PubMed

Buxton, Richard B

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm(3) spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease. PMID:26023913

Validation of cone-beam computed tomography and magnetic resonance imaging of the porcine spine: a comparative study with multidetector computed tomography and anatomical specimens.

PubMed

de Freitas, Ricardo Miguel Costa; Andrade, Celi Santos; Caldas, José Guilherme Mendes Pereira; Kanas, Alexandre Fligelman; Cabral, Richard Halti; Tsunemi, Miriam Harumi; Rodríguez, Hernán Joel Cervantes; Rabbani, Said Rahnamaye

2015-05-01

New spinal interventions or implants have been tested on ex vivo or in vivo porcine spines, as they are readily available and have been accepted as a comparable model to human cadaver spines. Imaging-guided interventional procedures of the spine are mostly based on fluoroscopy or, still, on multidetector computed tomography (MDCT). Cone-beam computed tomography (CBCT) and magnetic resonance imaging (MRI) are also available methods to guide interventional procedures. Although some MDCT data from porcine spines are available in the literature, validation of the measurements on CBCT and MRI is lacking. To describe and compare the anatomical measurements accomplished with MDCT, CBCT, and MRI of lumbar porcine spines to determine if CBCT and MRI are also useful methods for experimental studies. An experimental descriptive-comparative study. Sixteen anatomical measurements of an individual vertebra from six lumbar porcine spines (n=36 vertebrae) were compared with their MDCT, CBCT, and MRI equivalents. Comparisons were made for the absolute values of the parameters. Similarities were found in all imaging methods. Significant correlation (p<.05) was observed with all variables except those that included cartilaginous tissue from the end plates when the anatomical study was compared with the imaging methods. The CBCT and MRI provided imaging measurements of the lumbar porcine spines that were similar to the anatomical and MDCT data, and they can be useful for specific experimental research studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessment of Reynolds stress components and turbulent pressure loss using 4D flow MRI with extended motion encoding.

PubMed

Haraldsson, Henrik; Kefayati, Sarah; Ahn, Sinyeob; Dyverfeldt, Petter; Lantz, Jonas; Karlsson, Matts; Laub, Gerhard; Ebbers, Tino; Saloner, David

2018-04-01

To measure the Reynolds stress tensor using 4D flow MRI, and to evaluate its contribution to computed pressure maps. A method to assess both velocity and Reynolds stress using 4D flow MRI is presented and evaluated. The Reynolds stress is compared by cross-sectional integrals of the Reynolds stress invariants. Pressure maps are computed using the pressure Poisson equation-both including and neglecting the Reynolds stress. Good agreement is seen for Reynolds stress between computational fluid dynamics, simulated MRI, and MRI experiment. The Reynolds stress can significantly influence the computed pressure loss for simulated (eg, -0.52% vs -15.34% error; P < 0.001) and experimental (eg, 306 ± 11 vs 203 ± 6 Pa; P < 0.001) data. A 54% greater pressure loss is seen at the highest experimental flow rate when accounting for Reynolds stress (P < 0.001). 4D flow MRI with extended motion-encoding enables quantification of both the velocity and the Reynolds stress tensor. The additional information provided by this method improves the assessment of pressure gradients across a stenosis in the presence of turbulence. Unlike conventional methods, which are only valid if the flow is laminar, the proposed method is valid for both laminar and disturbed flow, a common presentation in diseased vessels. Magn Reson Med 79:1962-1971, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

[Anatomy of the skull base and the cranial nerves in slice imaging].

PubMed

Bink, A; Berkefeld, J; Zanella, F

2009-07-01

Computed tomography (CT) and magnetic resonance imaging (MRI) are suitable methods for examination of the skull base. Whereas CT is used to evaluate mainly bone destruction e.g. for planning surgical therapy, MRI is used to show pathologies in the soft tissue and bone invasion. High resolution and thin slice thickness are indispensible for both modalities of skull base imaging. Detailed anatomical knowledge is necessary even for correct planning of the examination procedures. This knowledge is a requirement to be able to recognize and interpret pathologies. MRI is the method of choice for examining the cranial nerves. The total path of a cranial nerve can be visualized by choosing different sequences taking into account the tissue surrounding this cranial nerve. This article summarizes examination methods of the skull base in CT and MRI, gives a detailed description of the anatomy and illustrates it with image examples.

The evaluation of correction algorithms of intensity nonuniformity in breast MRI images: a phantom study

NASA Astrophysics Data System (ADS)

Borys, Damian; Serafin, Wojciech; Gorczewski, Kamil; Kijonka, Marek; Frackiewicz, Mariusz; Palus, Henryk

2018-04-01

The aim of this work was to test the most popular and essential algorithms of the intensity nonuniformity correction of the breast MRI imaging. In this type of MRI imaging, especially in the proximity of the coil, the signal is strong but also can produce some inhomogeneities. Evaluated methods of signal correction were: N3, N3FCM, N4, Nonparametric, and SPM. For testing purposes, a uniform phantom object was used to obtain test images using breast imaging MRI coil. To quantify the results, two measures were used: integral uniformity and standard deviation. For each algorithm minimum, average and maximum values of both evaluation factors have been calculated using the binary mask created for the phantom. In the result, two methods obtained the lowest values in these measures: N3FCM and N4, however, for the second method visually phantom was the most uniform after correction.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

A Graphics Processing Unit Accelerated Motion Correction Algorithm and Modular System for Real-time fMRI

PubMed Central

Scheinost, Dustin; Hampson, Michelle; Qiu, Maolin; Bhawnani, Jitendra; Constable, R. Todd; Papademetris, Xenophon

2013-01-01

Real-time functional magnetic resonance imaging (rt-fMRI) has recently gained interest as a possible means to facilitate the learning of certain behaviors. However, rt-fMRI is limited by processing speed and available software, and continued development is needed for rt-fMRI to progress further and become feasible for clinical use. In this work, we present an open-source rt-fMRI system for biofeedback powered by a novel Graphics Processing Unit (GPU) accelerated motion correction strategy as part of the BioImage Suite project (www.bioimagesuite.org). Our system contributes to the development of rt-fMRI by presenting a motion correction algorithm that provides an estimate of motion with essentially no processing delay as well as a modular rt-fMRI system design. Using empirical data from rt-fMRI scans, we assessed the quality of motion correction in this new system. The present algorithm performed comparably to standard (non real-time) offline methods and outperformed other real-time methods based on zero order interpolation of motion parameters. The modular approach to the rt-fMRI system allows the system to be flexible to the experiment and feedback design, a valuable feature for many applications. We illustrate the flexibility of the system by describing several of our ongoing studies. Our hope is that continuing development of open-source rt-fMRI algorithms and software will make this new technology more accessible and adaptable, and will thereby accelerate its application in the clinical and cognitive neurosciences. PMID:23319241

A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph.

PubMed

Bharath, Rose D; Panda, Rajanikant; Reddam, Venkateswara Reddy; Bhaskar, M V; Gohel, Suril; Bhardwaj, Sujas; Prajapati, Arvind; Pal, Pramod Kumar

2017-01-01

Background and Purpose : Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method : Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result : A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI ( p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion : Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo . Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise".

A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI.

PubMed

Scheinost, Dustin; Hampson, Michelle; Qiu, Maolin; Bhawnani, Jitendra; Constable, R Todd; Papademetris, Xenophon

2013-07-01

Real-time functional magnetic resonance imaging (rt-fMRI) has recently gained interest as a possible means to facilitate the learning of certain behaviors. However, rt-fMRI is limited by processing speed and available software, and continued development is needed for rt-fMRI to progress further and become feasible for clinical use. In this work, we present an open-source rt-fMRI system for biofeedback powered by a novel Graphics Processing Unit (GPU) accelerated motion correction strategy as part of the BioImage Suite project ( www.bioimagesuite.org ). Our system contributes to the development of rt-fMRI by presenting a motion correction algorithm that provides an estimate of motion with essentially no processing delay as well as a modular rt-fMRI system design. Using empirical data from rt-fMRI scans, we assessed the quality of motion correction in this new system. The present algorithm performed comparably to standard (non real-time) offline methods and outperformed other real-time methods based on zero order interpolation of motion parameters. The modular approach to the rt-fMRI system allows the system to be flexible to the experiment and feedback design, a valuable feature for many applications. We illustrate the flexibility of the system by describing several of our ongoing studies. Our hope is that continuing development of open-source rt-fMRI algorithms and software will make this new technology more accessible and adaptable, and will thereby accelerate its application in the clinical and cognitive neurosciences.

An Adaptive MR-CT Registration Method for MRI-guided Prostate Cancer Radiotherapy

PubMed Central

Zhong, Hualiang; Wen, Ning; Gordon, James; Elshaikh, Mohamed A; Movsas, Benjamin; Chetty, Indrin J.

2015-01-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ/cm3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for development of high-quality MRI-guided radiation therapy. PMID:25775937

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.

2015-04-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy.

MRI Volume Fusion Based on 3D Shearlet Decompositions.

PubMed

Duan, Chang; Wang, Shuai; Wang, Xue Gang; Huang, Qi Hong

2014-01-01

Nowadays many MRI scans can give 3D volume data with different contrasts, but the observers may want to view various contrasts in the same 3D volume. The conventional 2D medical fusion methods can only fuse the 3D volume data layer by layer, which may lead to the loss of interframe correlative information. In this paper, a novel 3D medical volume fusion method based on 3D band limited shearlet transform (3D BLST) is proposed. And this method is evaluated upon MRI T2* and quantitative susceptibility mapping data of 4 human brains. Both the perspective impression and the quality indices indicate that the proposed method has a better performance than conventional 2D wavelet, DT CWT, and 3D wavelet, DT CWT based fusion methods.

The use of high resolution magnetic resonance on 3.0-T system in the diagnosis and surgical planning of intraosseous lesions of the jaws: preliminary results of a retrospective study.

PubMed

Cassetta, M; Di Carlo, S; Pranno, N; Stagnitti, A; Pompa, V; Pompa, G

2012-12-01

The pre-operative evaluation in oral and maxillofacial surgery is currently performed by computerized tomography (CT). However in some case the information of the traditional imaging methods are not enough in the diagnosis and surgical planning. The efficacy of these imaging methods in the evaluation of soft tissues is lower than magnetic resonance imaging (MRI). The aim of the study was to show the use of MRI in the evaluation of relation between intraosseous lesions of the jaws and anatomical structures, when it was difficult using the traditional radiographic methods, and to evaluate the usefulness of MRI to depict the morphostructural characterization of the lesions and infiltration of the soft tissues. 10 patients with a lesion of jaw were selected. All the patients underwent panoramic radiography (OPT), CT and MRI. The images were examined by dental and maxillofacial radiology who compared the different imaging methods to analyze the morphological and structural characteristics of the lesion and assessed the relationship between the lesion and the anatomical structures. Magnetic resonance imaging provided more detailed spatial and structural information than other imaging methods. MRI allowed us to characterize the intraosseous lesions of the jaws and to plan the surgery, resulting in a lower risk of anatomic structures surgical injury.

Biological Image-Guided Radiotherapy in Rectal Cancer: Challenges and Pitfalls

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roels, Sarah; Slagmolen, Pieter; Nuyts, Johan

2009-11-01

Purpose: To investigate the feasibility of integrating multiple imaging modalities for image-guided radiotherapy in rectal cancer. Patients and Methods: Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were performed before, during, and after preoperative chemoradiotherapy (CRT) in patients with resectable rectal cancer. The FDG-PET signals were segmented with an adaptive threshold-based and a gradient-based method. Magnetic resonance tumor volumes (TVs) were manually delineated. A nonrigid registration algorithm was applied to register the images, and mismatch analyses were carried out between MR and FDG-PET TVs and between TVs over time. Tumor volumes delineated on the images after CRTmore » were compared with the pathologic TV. Results: Forty-five FDG-PET/CT and 45 MR images were analyzed from 15 patients. The mean MRI and FDG-PET TVs showed a tendency to shrink during and after CRT. In general, MRI showed larger TVs than FDG-PET. There was an approximately 50% mismatch between the FDG-PET TV and the MRI TV at baseline and during CRT. Sixty-one percent of the FDG-PET TV and 76% of the MRI TV obtained after 10 fractions of CRT remained inside the corresponding baseline TV. On MRI, residual tumor was still suspected in all 6 patients with a pathologic complete response, whereas FDG-PET showed a metabolic complete response in 3 of them. The FDG-PET TVs delineated with the gradient-based method matched closest with pathologic findings. Conclusions: Integration of MRI and FDG-PET into radiotherapy seems feasible. Gradient-based segmentation is recommended for FDG-PET. Spatial variance between MRI and FDG-PET TVs should be taken into account for target definition.« less

Agreement between methods of measurement of mean aortic wall thickness by MRI.

PubMed

Rosero, Eric B; Peshock, Ronald M; Khera, Amit; Clagett, G Patrick; Lo, Hao; Timaran, Carlos

2009-03-01

To assess the agreement between three methods of calculation of mean aortic wall thickness (MAWT) using magnetic resonance imaging (MRI). High-resolution MRI of the infrarenal abdominal aorta was performed on 70 subjects with a history of coronary artery disease who were part of a multi-ethnic population-based sample. MAWT was calculated as the mean distance between the adventitial and luminal aortic boundaries using three different methods: average distance at four standard positions (AWT-4P), average distance at 100 automated positions (AWT-100P), and using a mathematical computation derived from the total vessel and luminal areas (AWT-VA). Bland-Altman plots and Passing-Bablok regression analyses were used to assess agreement between methods. Bland-Altman analyses demonstrated a positive bias of 3.02+/-7.31% between the AWT-VA and the AWT-4P methods, and of 1.76+/-6.82% between the AWT-100P and the AWT-4P methods. Passing-Bablok regression analyses demonstrated constant bias between the AWT-4P method and the other two methods. Proportional bias was, however, not evident among the three methods. MRI methods of measurement of MAWT using a limited number of positions of the aortic wall systematically underestimate the MAWT value compared with the method that calculates MAWT from the vessel areas. Copyright (c) 2009 Wiley-Liss, Inc.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Motion correction in MRI of the brain

PubMed Central

Godenschweger, F; Kägebein, U; Stucht, D; Yarach, U; Sciarra, A; Yakupov, R; Lüsebrink, F; Schulze, P; Speck, O

2016-01-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed. PMID:26864183

Motion correction in MRI of the brain

NASA Astrophysics Data System (ADS)

Godenschweger, F.; Kägebein, U.; Stucht, D.; Yarach, U.; Sciarra, A.; Yakupov, R.; Lüsebrink, F.; Schulze, P.; Speck, O.

2016-03-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

Extraction of Overt Verbal Response from the Acoustic Noise in a Functional Magnetic Resonance Imaging Scan by Use of Segmented Active Noise Cancellation

PubMed Central

Jung, Kwan-Jin; Prasad, Parikshit; Qin, Yulin; Anderson, John R.

2013-01-01

A method to extract the subject's overt verbal response from the obscuring acoustic noise in an fMRI scan is developed by applying active noise cancellation with a conventional MRI microphone. Since the EPI scanning and its accompanying acoustic noise in fMRI are repetitive, the acoustic noise in one time segment was used as a reference noise in suppressing the acoustic noise in subsequent segments. However, the acoustic noise from the scanner was affected by the subject's movements, so the reference noise was adaptively adjusted as the scanner's acoustic properties varied in time. This method was successfully applied to a cognitive fMRI experiment with overt verbal responses. PMID:15723385

Design and preliminary accuracy studies of an MRI-guided transrectal prostate intervention system.

PubMed

Krieger, Axel; Csoma, Csaba; Iordachital, Iulian I; Guion, Peter; Singh, Anurag K; Fichtinger, Gabor; Whitcomb, Louis L

2007-01-01

This paper reports a novel system for magnetic resonance imaging (MRI) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery. The system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration and subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders and mechanical scales. Targeting accuracy of the system is evaluated in prostate phantom experiments. Achieved targeting accuracy and procedure times were found to compare favorably with existing systems using passive and active tracking methods. Moreover, the portable design of the system using only standard MRI image sequences and minimal custom scanner interfacing allows the system to be easily used on different MRI scanners.

Application of artificial neural network to fMRI regression analysis.

PubMed

Misaki, Masaya; Miyauchi, Satoru

2006-01-15

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Evaluation of Blalock-Taussig shunts in newborns: value of oblique MRI planes.

PubMed

Kastler, B; Livolsi, A; Germain, P; Zöllner, G; Dietemann, J L

1991-01-01

Eight infants with systemic-pulmonary Blalock-Taussig shunts were evaluated by spin-echo ECG-gated MRI. Contrary to Echocardiography, MRI using coronal oblique projections successfully visualized all palliative shunts entirely in one single plane (including one carried out on a right aberrant subclavian artery). MRI allowed assessment of size, course and patency of the shunt, including pulmonary and subclavian insertion. The proximal portion of the pulmonary and subclavian arteries were also visualized. We conclude that MRI with axial scans completed by coronal oblique planes is a promising, non invasive method for imaging the anatomical features of Blalock-Taussig shunts.

Cellular Imaging With MRI.

PubMed

Makela, Ashley V; Murrell, Donna H; Parkins, Katie M; Kara, Jenna; Gaudet, Jeffrey M; Foster, Paula J

2016-10-01

Cellular magnetic resonance imaging (MRI) is an evolving field of imaging with strong translational and research potential. The ability to detect, track, and quantify cells in vivo and over time allows for studying cellular events related to disease processes and may be used as a biomarker for decisions about treatments and for monitoring responses to treatments. In this review, we discuss methods for labeling cells, various applications for cellular MRI, the existing limitations, strategies to address these shortcomings, and clinical cellular MRI.

Magnetorotational instability: nonmodal growth and the relationship of global modes to the shearing box

DOE Office of Scientific and Technical Information (OSTI.GOV)

Squire, J.; Bhattacharjee, A.

2014-12-10

We study magnetorotational instability (MRI) using nonmodal stability techniques. Despite the spectral instability of many forms of MRI, this proves to be a natural method of analysis that is well-suited to deal with the non-self-adjoint nature of the linear MRI equations. We find that the fastest growing linear MRI structures on both local and global domains can look very different from the eigenmodes, invariably resembling waves shearing with the background flow (shear waves). In addition, such structures can grow many times faster than the least stable eigenmode over long time periods, and be localized in a completely different region ofmore » space. These ideas lead—for both axisymmetric and non-axisymmetric modes—to a natural connection between the global MRI and the local shearing box approximation. By illustrating that the fastest growing global structure is well described by the ordinary differential equations (ODEs) governing a single shear wave, we find that the shearing box is a very sensible approximation for the linear MRI, contrary to many previous claims. Since the shear wave ODEs are most naturally understood using nonmodal analysis techniques, we conclude by analyzing local MRI growth over finite timescales using these methods. The strong growth over a wide range of wave-numbers suggests that nonmodal linear physics could be of fundamental importance in MRI turbulence.« less

Characterization of Cerebral White Matter Properties Using Quantitative Magnetic Resonance Imaging Stains

PubMed Central

Hurley, Samuel A.; Samsonov, Alexey A.; Adluru, Nagesh; Hosseinbor, Ameer Pasha; Mossahebi, Pouria; Tromp, Do P.M.; Zakszewski, Elizabeth; Field, Aaron S.

2011-01-01

Abstract The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains. PMID:22432902

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

PubMed Central

A., Javadpour; A., Mohammadi

2016-01-01

Background Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Methods Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases. PMID:27672629

Ameliorating slice gaps in multislice magnetic resonance images: an interpolation scheme.

PubMed

Kashou, Nasser H; Smith, Mark A; Roberts, Cynthia J

2015-01-01

Standard two-dimension (2D) magnetic resonance imaging (MRI) clinical acquisition protocols utilize orthogonal plane images which contain slice gaps (SG). The purpose of this work is to introduce a novel interpolation method for these orthogonal plane MRI 2D datasets. Three goals can be achieved: (1) increasing the resolution based on a priori knowledge of scanning protocol, (2) ameliorating the loss of data as a result of SG and (3) reconstructing a three-dimension (3D) dataset from 2D images. MRI data was collected using a 3T GE scanner and simulated using Matlab. The procedure for validating the MRI data combination algorithm was performed using a Shepp-Logan and a Gaussian phantom in both 2D and 3D of varying matrix sizes (64-512), as well as on one MRI dataset of a human brain and on an American College of Radiology magnetic resonance accreditation phantom. The squared error and mean squared error were computed in comparing this scheme to common interpolating functions employed in MR consoles and workstations. The mean structure similarity matrix was computed in 2D as a means of qualitative image assessment. Additionally, MRI scans were used for qualitative assessment of the method. This new scheme was consistently more accurate than upsampling each orientation separately and averaging the upsampled data. An efficient new interpolation approach to resolve SG was developed. This scheme effectively fills in the missing data points by using orthogonal plane images. To date, there have been few attempts to combine the information of three MRI plane orientations using brain images. This has specific applications for clinical MRI, functional MRI, diffusion-weighted imaging/diffusion tensor imaging and MR angiography where 2D slice acquisition are used. In these cases, the 2D data can be combined using our method in order to obtain 3D volume.

Assessment of dosimetric impact of system specific geometric distortion in an MRI only based radiotherapy workflow for prostate

NASA Astrophysics Data System (ADS)

Gustafsson, C.; Nordström, F.; Persson, E.; Brynolfsson, J.; Olsson, L. E.

2017-04-01

Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. The displacement map for an optimized MRI treatment planning sequence was measured using a dedicated phantom in a 3 T MRI system. To simulate the distortion aspects of a synthetic CT (electron density derived from MR images), the displacement map was applied to CT images, referred to as distorted CT images. A volumetric modulated arc prostate treatment plan was applied to the original CT and the distorted CT, creating a reference and a distorted CT dose distribution. By applying the inverse of the displacement map to the distorted CT dose distribution, a dose distribution in the same geometry as the original CT images was created. For 10 prostate cancer patients, the dose difference between the reference dose distribution and inverse distorted CT dose distribution was analyzed in isodose level bins. The mean magnitude of the geometric distortion was 1.97 mm for the radial distance of 200-250 mm from isocenter. The mean percentage dose differences for all isodose level bins, were  ⩽0.02% and the radiotherapy structure mean volume deviations were  <0.2%. The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.

Assessment of dosimetric impact of system specific geometric distortion in an MRI only based radiotherapy workflow for prostate.

PubMed

Gustafsson, C; Nordström, F; Persson, E; Brynolfsson, J; Olsson, L E

2017-04-21

Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. The displacement map for an optimized MRI treatment planning sequence was measured using a dedicated phantom in a 3 T MRI system. To simulate the distortion aspects of a synthetic CT (electron density derived from MR images), the displacement map was applied to CT images, referred to as distorted CT images. A volumetric modulated arc prostate treatment plan was applied to the original CT and the distorted CT, creating a reference and a distorted CT dose distribution. By applying the inverse of the displacement map to the distorted CT dose distribution, a dose distribution in the same geometry as the original CT images was created. For 10 prostate cancer patients, the dose difference between the reference dose distribution and inverse distorted CT dose distribution was analyzed in isodose level bins. The mean magnitude of the geometric distortion was 1.97 mm for the radial distance of 200-250 mm from isocenter. The mean percentage dose differences for all isodose level bins, were  ⩽0.02% and the radiotherapy structure mean volume deviations were  <0.2%. The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.

Measurement of Murine Single-Kidney Glomerular Filtration Rate Using Dynamic Contrast-Enhanced MRI.

PubMed

Jiang, Kai; Tang, Hui; Mishra, Prasanna K; Macura, Slobodan I; Lerman, Lilach O

2018-06-01

To develop and validate a method for measuring murine single-kidney glomerular filtration rate (GFR) using dynamic contrast-enhanced MRI (DCE-MRI). This prospective study was approved by the Institutional Animal Care and Use Committee. A fast longitudinal relaxation time (T 1 ) measurement method was implemented to capture gadolinium dynamics (1 s/scan), and a modified two-compartment model was developed to quantify GFR as well as renal perfusion using 16.4T MRI in mice 2 weeks after unilateral renal artery stenosis (RAS, n = 6) or sham (n = 8) surgeries. This approach was validated by comparing model-derived GFR and perfusion to those obtained by fluorescein isothiocyanante (FITC)-inulin clearance and arterial spin labeling (ASL), respectively, using the Pearson's and Spearman's rank correlations and Bland-Altman analysis. The compartmental model provided a good fitting to measured gadolinium dynamics in both normal and RAS kidneys. The proposed DCE-MRI method offered assessment of single-kidney GFR and perfusion, comparable to the FITC-inulin clearance (Pearson's correlation coefficient r = 0.95 and Spearman's correlation coefficient ρ = 0.94, P < 0.0001, and mean difference -7.0 ± 11.0 μL/min) and ASL (r = 0.92 and ρ = 0.84, P < 0.0001, and mean difference 4.4 ± 66.1 mL/100 g/min) methods. The proposed DCE-MRI method may be useful for reliable noninvasive measurements of single-kidney GFR and perfusion in mice. Magn Reson Med 79:2935-2943, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Relationship Between Clinical and Immunological Features with Magnetic Resonance Imaging Abnormalities in Female Patients with Neuropsychiatric Systemic Lupus Erythematosus

PubMed Central

Wang, Hai-Peng; Wang, Cui-Yan; Pan, Zheng-Lun; Zhao, Jun-Yu; Zhao, Bin

2016-01-01

Background: Conventional magnetic resonance imaging (MRI) is the preferred neuroimaging method in the evaluation of neuropsychiatric systemic lupus erythematosus (NPSLE). The purpose of this study was to investigate the association between clinical and immunological features with MRI abnormalities in female patients with NPSLE, to screen for the value of conventional MRI in NPSLE. Methods: A total of 59 female NPSLE patients with conventional MRI examinations were enrolled in this retrospective study. All patients were classified into different groups according to MRI abnormalities. Both clinical and immunological features were compared between MRI abnormal and normal groups. One-way analysis of variance was used to compare the systemic lupus erythematosus disease activity index (SLEDAI) score for MRI abnormalities. Multivariate logistic regression analysis investigated the correlation between immunological features, neuropsychiatric manifestations, and MRI abnormalities. Results: Thirty-six NPSLE patients (61%) showed a variety of MRI abnormalities. There were statistically significant differences in SLEDAI scores (P < 0.001), incidence of neurologic disorders (P = 0.001), levels of 24-h proteinuria (P = 0.001) and immunoglobulin M (P = 0.004), and incidence of acute confusional state (P = 0.002), cerebrovascular disease (P = 0.004), and seizure disorder (P = 0.028) between MRI abnormal and normal groups. In the MRI abnormal group, SLEDAI scores for cerebral atrophy (CA), cortex involvement, and restricted diffusion (RD) were much higher than in the MRI normal group (P < 0.001, P = 0.002, P = 0.038, respectively). Statistically significant positive correlations between seizure disorder and cortex involvement (odds ratio [OR] = 14.90; 95% confidence interval [CI], 1.50–151.70; P = 0.023) and cerebrovascular disease and infratentorial involvement (OR = 10.00; 95% CI, 1.70–60.00; P = 0.012) were found. Conclusions: MRI abnormalities in NPSLE, especially CA, cortex involvement, and RD might be markers of high systemic lupus erythematosus activity. Some MRI abnormalities might correspond to neuropsychiatric manifestations and might be helpful in understanding the pathophysiology of NPSLE. PMID:26904988

WE-AB-202-07: Ventilation CT: Voxel-Level Comparison with Hyperpolarized Helium-3 & Xenon-129 MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tahir, B; Marshall, H; Hughes, P

Purpose: To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath-hold CT with hyperpolarized Helium-3 & Xenon-129 MRI in a cohort of lung cancer patients. Methods: 5 patients underwent expiration & inspiration breath-hold CT. Xenon-129 & {sup 1}H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium-3 & {sup 1}H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel-wise differences in Hounsfield units. Inspiration CTmore » and the Xenon-129’s corresponding anatomical {sup 1}H MRI were registered to Helium-3 MRI via the same-breath anatomical {sup 1}H MRI. This enabled direct comparison of CT ventilation with Helium-3 MRI & Xenon-129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in-plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same-breath {sup 1}H MRI lung mask. Spearman coefficients were used to assess voxel-level correlation. Results: The median Spearman’s coefficients of ventilation CT with Helium-3 & Xenon-129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively. Conclusion: This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium-3 & Xenon-129 MRI) in similar breath-holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non-ventilatory effects and registration errors at the voxel-level. Thus, it may be more beneficial to quantify ventilation at a more regional level.« less

WE-G-BRD-06: Volumetric Cine MRI (VC-MRI) Estimated Based On Prior Knowledge for On-Board Target Localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, W; Yin, F; Cai, J

Purpose: To develop a technique to generate on-board VC-MRI using patient prior 4D-MRI, motion modeling and on-board 2D-cine MRI for real-time 3D target verification of liver and lung radiotherapy. Methods: The end-expiration phase images of a 4D-MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end-expiration phase and all other phases. On-board 2D-cine MRI images are acquired in the axial view. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI atmore » the end-expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC-MRI with the acquired single 2D-cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D-MRI at every phase except end-expiration phase was used to simulate the ground-truth on-board VC-MRI at different instances, and the center-tumor slice was selected to simulate the on-board 2D-cine images. Results: Image subtraction of ground truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground-truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum-Volume-Percent-Difference between ground-truth and estimated tumor volumes was 1.6% and the maximum-Center-of-Mass-Shift was 0.9 mm. Conclusion: Preliminary studies demonstrated the feasibility to estimate real-time VC-MRI for on-board target localization before or during radiotherapy treatments. National Institutes of Health Grant No. R01-CA184173; Varian Medical System.« less

Diffuse intrinsic pontine glioma: is MRI surveillance improved by region of interest volumetry?

PubMed

Riley, Garan T; Armitage, Paul A; Batty, Ruth; Griffiths, Paul D; Lee, Vicki; McMullan, John; Connolly, Daniel J A

2015-02-01

Paediatric diffuse intrinsic pontine glioma (DIPG) is noteworthy for its fibrillary infiltration through neuroparenchyma and its resultant irregular shape. Conventional volumetry methods aim to approximate such irregular tumours to a regular ellipse, which could be less accurate when assessing treatment response on surveillance MRI. Region-of-interest (ROI) volumetry methods, using manually traced tumour profiles on contiguous imaging slices and subsequent computer-aided calculations, may prove more reliable. To evaluate whether the reliability of MRI surveillance of DIPGs can be improved by the use of ROI-based volumetry. We investigated the use of ROI- and ellipsoid-based methods of volumetry for paediatric DIPGs in a retrospective review of 22 MRI examinations. We assessed the inter- and intraobserver variability of the two methods when performed by four observers. ROI- and ellipsoid-based methods strongly correlated for all four observers. The ROI-based volumes showed slightly better agreement both between and within observers than the ellipsoid-based volumes (inter-[intra-]observer agreement 89.8% [92.3%] and 83.1% [88.2%], respectively). Bland-Altman plots show tighter limits of agreement for the ROI-based method. Both methods are reproducible and transferrable among observers. ROI-based volumetry appears to perform better with greater intra- and interobserver agreement for complex-shaped DIPG.

A new method in accelerating PROPELLER MRI.

PubMed

Li, Bing Keong; D'Arcy, Michael; Weber, Ewald; Crozier, Stuart

2008-01-01

In this work, a new method has been proposed to accelerate the PROPELLER MRI operation. The proposed method uses a rotary phased array coil and a new method in acquiring the k-space strips and preparing the complete k-space trajectories data set. It is numerically shown that for a 12 strips PROPELLER MR brain imaging sequence, the operation time can be reduced by four folds, with no apparent loss in the image quality.

Thermal noise calculation method for precise estimation of the signal-to-noise ratio of ultra-low-field MRI with an atomic magnetometer.

PubMed

Yamashita, Tatsuya; Oida, Takenori; Hamada, Shoji; Kobayashi, Tetsuo

2012-02-01

In recent years, there has been considerable interest in developing an ultra-low-field magnetic resonance imaging (ULF-MRI) system using an optically pumped atomic magnetometer (OPAM). However, a precise estimation of the signal-to-noise ratio (SNR) of ULF-MRI has not been carried out. Conventionally, to calculate the SNR of an MR image, thermal noise, also called Nyquist noise, has been estimated by considering a resistor that is electrically equivalent to a biological-conductive sample and is connected in series to a pickup coil. However, this method has major limitations in that the receiver has to be a coil and that it cannot be applied directly to a system using OPAM. In this paper, we propose a method to estimate the thermal noise of an MRI system using OPAM. We calculate the thermal noise from the variance of the magnetic sensor output produced by current-dipole moments that simulate thermally fluctuating current sources in a biological sample. We assume that the random magnitude of the current dipole in each volume element of the biological sample is described by the Maxwell-Boltzmann distribution. The sensor output produced by each current-dipole moment is calculated either by an analytical formula or a numerical method based on the boundary element method. We validate the proposed method by comparing our results with those obtained by conventional methods that consider resistors connected in series to a pickup coil using single-layered sphere, multi-layered sphere, and realistic head models. Finally, we apply the proposed method to the ULF-MRI model using OPAM as the receiver with multi-layered sphere and realistic head models and estimate their SNR. Copyright © 2011 Elsevier Inc. All rights reserved.

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results

NASA Astrophysics Data System (ADS)

Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A.

2014-03-01

The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance imaging (MRI) sequences. Typical MRI data sets consist of T1- and T2-weighted imaging (T1WI, T2WI) along with advanced MRI parameters of diffusion-weighted imaging (DWI) and perfusion weighted imaging (PWI) methods. Each of these parameters has distinct radiological-pathological meaning. For example, DWI interrogates the movement of water in the tissue and PWI gives an estimate of the blood flow, both are critical measures during the evolution of stroke. In order to integrate these data and give an estimate of the tissue at risk or damaged; we have developed advanced machine learning methods based on unsupervised non-linear dimensionality reduction (NLDR) techniques. NLDR methods are a class of algorithms that uses mathematically defined manifolds for statistical sampling of multidimensional classes to generate a discrimination rule of guaranteed statistical accuracy and they can generate a two- or three-dimensional map, which represents the prominent structures of the data and provides an embedded image of meaningful low-dimensional structures hidden in their high-dimensional observations. In this manuscript, we develop NLDR methods on high dimensional MRI data sets of preclinical animals and clinical patients with stroke. On analyzing the performance of these methods, we observed that there was a high of similarity between multiparametric embedded images from NLDR methods and the ADC map and perfusion map. It was also observed that embedded scattergram of abnormal (infarcted or at risk) tissue can be visualized and provides a mechanism for automatic methods to delineate potential stroke volumes and early tissue at risk.

Quantitative rotating frame relaxometry methods in MRI.

PubMed

Gilani, Irtiza Ali; Sepponen, Raimo

2016-06-01

Macromolecular degeneration and biochemical changes in tissue can be quantified using rotating frame relaxometry in MRI. It has been shown in several studies that the rotating frame longitudinal relaxation rate constant (R1ρ ) and the rotating frame transverse relaxation rate constant (R2ρ ) are sensitive biomarkers of phenomena at the cellular level. In this comprehensive review, existing MRI methods for probing the biophysical mechanisms that affect the rotating frame relaxation rates of the tissue (i.e. R1ρ and R2ρ ) are presented. Long acquisition times and high radiofrequency (RF) energy deposition into tissue during the process of spin-locking in rotating frame relaxometry are the major barriers to the establishment of these relaxation contrasts at high magnetic fields. Therefore, clinical applications of R1ρ and R2ρ MRI using on- or off-resonance RF excitation methods remain challenging. Accordingly, this review describes the theoretical and experimental approaches to the design of hard RF pulse cluster- and adiabatic RF pulse-based excitation schemes for accurate and precise measurements of R1ρ and R2ρ . The merits and drawbacks of different MRI acquisition strategies for quantitative relaxation rate measurement in the rotating frame regime are reviewed. In addition, this review summarizes current clinical applications of rotating frame MRI sequences. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI Methods

PubMed Central

Jack, Clifford R.; Bernstein, Matt A.; Fox, Nick C.; Thompson, Paul; Alexander, Gene; Harvey, Danielle; Borowski, Bret; Britson, Paula J.; Whitwell, Jennifer L.; Ward, Chadwick; Dale, Anders M.; Felmlee, Joel P.; Gunter, Jeffrey L.; Hill, Derek L.G.; Killiany, Ron; Schuff, Norbert; Fox-Bosetti, Sabrina; Lin, Chen; Studholme, Colin; DeCarli, Charles S.; Krueger, Gunnar; Ward, Heidi A.; Metzger, Gregory J.; Scott, Katherine T.; Mallozzi, Richard; Blezek, Daniel; Levy, Joshua; Debbins, Josef P.; Fleisher, Adam S.; Albert, Marilyn; Green, Robert; Bartzokis, George; Glover, Gary; Mugler, John; Weiner, Michael W.

2008-01-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorode-oxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1-weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced-scale clinical trial. The protocol selected for the ADNI study includes: back-to-back 3D magnetization prepared rapid gradient echo (MP-RAGE) scans; B1-calibration scans when applicable; and an axial proton density-T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom-based monitoring of all scanners could be used as a model for other multisite trials. PMID:18302232

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

[3-Tesla MRI vs. arthroscopy for diagnostics of degenerative knee cartilage diseases: preliminary clinical results].

PubMed

von Engelhardt, L V; Schmitz, A; Burian, B; Pennekamp, P H; Schild, H H; Kraft, C N; von Falkenhausen, M

2008-09-01

The literature contains only a few studies investigating the magnetic resonance imaging (MRI) diagnostics of degenerative cartilage diseases. Studies on MRI diagnostics of the cartilage using field strengths of 3-Tesla demonstrate promising results. To assess the value of 3-Tesla MRI for decision making regarding conservative or operative treatment possibilities, this study focused on patients with degenerative cartilage diseases. Thirty-two patients with chronic knee pain, a minimum age of 40 years, a negative history of trauma, and at least grade II degenerative cartilage disease were included. Cartilage abnormalities detected at preoperative 3-Tesla MRI (axial/koronar/sagittal PD-TSE-SPAIR, axial/sagittal 3D-T1-FFE, axial T2-FFE; Intera 3.0T, Philips Medical Systems) were classified (grades I-IV) and compared with arthroscopic findings. Thirty-six percent (70/192) of the examined cartilage surfaces demonstrated no agreement between MRI and arthroscopic grading. In most of these cases, grades II and III cartilage lesions were confounded with each other. Regarding the positive predictive values, the probability that a positive finding in MRI would be exactly confirmed by arthroscopy was 39-72%. In contrast, specificities and negative predictive values of different grades of cartilage diseases were 85-95%. Regarding the high specificities and negative predictive values, 3-Tesla MRI is a reliable method for excluding even slight cartilage degeneration. In summary, in degenerative cartilage diseases, 3-Tesla MRI is a supportive, noninvasive method for clinical decision making regarding conservative or operative treatment possibilities. However, the value of diagnostic arthroscopy for a definitive assessment of the articular surfaces and for therapeutic planning currently cannot be replaced by 3-Tesla MRI. This applies especially to treatment options in which a differentiation between grade II and III cartilage lesions is of interest.

Automatic cardiac LV segmentation in MRI using modified graph cuts with smoothness and interslice constraints.

PubMed

Albà, Xènia; Figueras I Ventura, Rosa M; Lekadir, Karim; Tobon-Gomez, Catalina; Hoogendoorn, Corné; Frangi, Alejandro F

2014-12-01

Magnetic resonance imaging (MRI), specifically late-enhanced MRI, is the standard clinical imaging protocol to assess cardiac viability. Segmentation of myocardial walls is a prerequisite for this assessment. Automatic and robust multisequence segmentation is required to support processing massive quantities of data. A generic rule-based framework to automatically segment the left ventricle myocardium is presented here. We use intensity information, and include shape and interslice smoothness constraints, providing robustness to subject- and study-specific changes. Our automatic initialization considers the geometrical and appearance properties of the left ventricle, as well as interslice information. The segmentation algorithm uses a decoupled, modified graph cut approach with control points, providing a good balance between flexibility and robustness. The method was evaluated on late-enhanced MRI images from a 20-patient in-house database, and on cine-MRI images from a 15-patient open access database, both using as reference manually delineated contours. Segmentation agreement, measured using the Dice coefficient, was 0.81±0.05 and 0.92±0.04 for late-enhanced MRI and cine-MRI, respectively. The method was also compared favorably to a three-dimensional Active Shape Model approach. The experimental validation with two magnetic resonance sequences demonstrates increased accuracy and versatility. © 2013 Wiley Periodicals, Inc.

Fetal MRI: A Technical Update with Educational Aspirations

PubMed Central

Gholipour, Ali; Estroff, Judith A.; Barnewolt, Carol E.; Robertson, Richard L.; Grant, P. Ellen; Gagoski, Borjan; Warfield, Simon K.; Afacan, Onur; Connolly, Susan A.; Neil, Jeffrey J.; Wolfberg, Adam; Mulkern, Robert V.

2015-01-01

Fetal magnetic resonance imaging (MRI) examinations have become well-established procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams when diagnostic doubts remain after US. Due to fetal motion, however, fetal MRI exams are challenging and require the MR scanner to be used in a somewhat different mode than that employed for more routine clinical studies. Herein we review the techniques most commonly used, and those that are available, for fetal MRI with an emphasis on the physics of the techniques and how to deploy them to improve success rates for fetal MRI exams. By far the most common technique employed is single-shot T2-weighted imaging due to its excellent tissue contrast and relative immunity to fetal motion. Despite the significant challenges involved, however, many of the other techniques commonly employed in conventional neuro- and body MRI such as T1 and T2*-weighted imaging, diffusion and perfusion weighted imaging, as well as spectroscopic methods remain of interest for fetal MR applications. An effort to understand the strengths and limitations of these basic methods within the context of fetal MRI is made in order to optimize their use and facilitate implementation of technical improvements for the further development of fetal MR imaging, both in acquisition and post-processing strategies. PMID:26225129

Numerical study on simultaneous emission and transmission tomography in the MRI framework

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Cong, Wenxiang; Wang, Ge

2017-09-01

Multi-modality imaging methods are instrumental for advanced diagnosis and therapy. Specifically, a hybrid system that combines computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI) will be a Holy Grail of medical imaging, delivering complementary structural/morphological, functional, and molecular information for precision medicine. A novel imaging method was recently demonstrated that takes advantage of radiotracer polarization to combine MRI principles with nuclear imaging. This approach allows the concentration of a polarized Υ-ray emitting radioisotope to be imaged with MRI resolution potentially outperforming the standard nuclear imaging mode at a sensitivity significantly higher than that of MRI. In our work, we propose to acquire MRI-modulated nuclear data for simultaneous image reconstruction of both emission and transmission parameters, suggesting the potential for simultaneous CT-SPECT-MRI. The synchronized diverse datasets allow excellent spatiotemporal registration and unique insight into physiological and pathological features. Here we describe the methodology involving the system design with emphasis on the formulation for tomographic images, even when significant radiotracer signals are limited to a region of interest (ROI). Initial numerical results demonstrate the feasibility of our approach for reconstructing concentration and attenuation images through a head phantom with various radio-labeled ROIs. Additional considerations regarding the radioisotope characteristics are also discussed.

Understanding the effects of diffusion and relaxation in magnetic resonance imaging using computational modeling

NASA Astrophysics Data System (ADS)

Russell, Greg

The work described in this dissertation was motivated by a desire to better understand the cellular pathology of ischemic stroke. Two of the three bodies of research presented herein address and issue directly related to the investigation of ischemic stroke through the use of diffusion weighted magnetic resonance imaging (DWMRI) methods. The first topic concerns the development of a computationally efficient finite difference method, designed to evaluate the impact of microscopic tissue properties on the formation of DWMRI signal. For the second body of work, the effect of changing the intrinsic diffusion coefficient of a restricted sample on clinical DWMRI experiments is explored. The final body of work, while motivated by the desire to understand stroke, addresses the issue of acquiring large amounts of MRI data well suited for quantitative analysis in reduced scan time. In theory, the method could be used to generate quantitative parametric maps, including those depicting information gleaned through the use of DWMRI methods. Chapter 1 provides an introduction to several topics. A description of the use of DWMRI methods in the study of ischemic stroke is covered. An introduction to the fundamental physical principles at work in MRI is also provided. In this section the means by which magnetization is created in MRI experiments, how MRI signal is induced, as well as the influence of spin-spin and spin-lattice relaxation are discussed. Attention is also given to describing how MRI measurements can be sensitized to diffusion through the use of qualitative and quantitative descriptions of the process. Finally, the reader is given a brief introduction to the use of numerical methods for solving partial differential equations. In Chapters 2, 3 and 4, three related bodies of research are presented in terms of research papers. In Chapter 2, a novel computational method is described. The method reduces the computation resources required to simulate DWMRI experiments. In Chapter 3, a detailed study on how changes in the intrinsic intracellular diffusion coefficient may influence clinical DWMRI experiments is described. In Chapter 4, a novel, non-steady state quantitative MRI method is described.

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

PubMed

Zhang, Shu; Li, Xiang; Lv, Jinglei; Jiang, Xi; Guo, Lei; Liu, Tianming

2016-03-01

A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100% classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release.

Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L.; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2017-02-01

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≍1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Studying microstructure and microstructural changes in plant tissues by advanced diffusion magnetic resonance imaging techniques

PubMed Central

Morozov, Darya; Tal, Iris; Pisanty, Odelia; Shani, Eilon

2017-01-01

Abstract As sessile organisms, plants must respond to the environment by adjusting their growth and development. Most of the plant body is formed post-embryonically by continuous activity of apical and lateral meristems. The development of lateral adventitious roots is a complex process, and therefore the development of methods that can visualize, non-invasively, the plant microstructure and organ initiation that occur during growth and development is of paramount importance. In this study, relaxation-based and advanced diffusion magnetic resonance imaging (MRI) methods including diffusion tensor (DTI), q-space diffusion imaging (QSI), and double-pulsed-field-gradient (d-PFG) MRI, at 14.1 T, were used to characterize the hypocotyl microstructure and the microstructural changes that occurred during the development of lateral adventitious roots in tomato. Better contrast was observed in relaxation-based MRI using higher in-plane resolution but this also resulted in a significant reduction in the signal-to-noise ratio of the T2-weighted MR images. Diffusion MRI revealed that water diffusion is highly anisotropic in the vascular cylinder. QSI and d-PGSE MRI showed that in the vascular cylinder some of the cells have sizes in the range of 6–10 μm. The MR images captured cell reorganization during adventitious root formation in the periphery of the primary vascular bundles, adjacent to the xylem pole that broke through the cortex and epidermis layers. This study demonstrates that MRI and diffusion MRI methods allow the non-invasive study of microstructural features of plants, and enable microstructural changes associated with adventitious root formation to be followed. PMID:28398563

Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly.

PubMed

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L; Assad, Albert; Abramson, Richard G; Landman, Bennett A

2017-02-11

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≈1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Diagnostic role of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for early and atypical bone metastases.

PubMed

Chen, Xiao-Liang; Li, Qian; Cao, Lin; Jiang, Shi-Xi

2014-01-01

The bone metastasis appeared early before the bone imaging for most of the above patients. (99)Tc(m)-MDP ((99)Tc(m) marked methylene diphosphonate) bone imaging could diagnosis the bone metastasis with highly sensitivity, but with lower specificity. The aim of this study is to explore the diagnostic value of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for the early period atypical bone metastases. 15 to 30 mCi (99)Tc(m)-MDP was intravenously injected to the 34 malignant patients diagnosed as doubtful early bone metastases. SPECT, CT and SPECT/CT images were captured and analyzed consequently. For the patients diagnosed as early period atypical bone metastases by SPECT/CT, combining the SPECT/CT and MRI together as the SPECT/MRI integrated image. The obtained SPECT/MRI image was analyzed and compared with the pathogenic results of patients. The results indicated that 34 early period doubtful metastatic focus, including 34 SPECT positive focus, 17 focus without special changes by using CT method, 11 bone metastases focus by using SPECT/CT method, 23 doubtful bone metastases focus, 8 doubtful bone metastases focus, 14 doubtful bone metastases focus and 2 focus without clear image. Totally, SPECT/CT combined with SPECT/MRI method diagnosed 30 bone metastatic focus and 4 doubtfully metastatic focus. In conclusion, (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging shows a higher diagnostic value for the early period bone metastases, which also enhances the diagnostic accuracy rate.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

PubMed Central

Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

Method and apparatus for magnetic resonance imaging and spectroscopy using microstrip transmission line coils

DOEpatents

Zhang, Xiaoliang; Ugurbil, Kamil; Chen, Wei

2006-04-04

Apparatus and method for MRI imaging using a coil constructed of microstrip transmission line (MTL coil) are disclosed. In one method, a target is positioned to be imaged within the field of a main magnetic field of a magnet resonance imaging (MRI) system, a MTL coil is positioned proximate the target, and a MRI image is obtained using the main magnet and the MTL coil. In another embodiment, the MRI coil is used for spectroscopy. MRI imaging and spectroscopy coils are formed using microstrip transmission line. These MTL coils have the advantageous property of good performance while occupying a relatively small space, thus allowing MTL coils to be used inside restricted areas more easily than some other prior art coils. In addition, the MTL coils are relatively simple to construct of inexpensive components and thus relatively inexpensive compared to other designs. Further, the MTL coils of the present invention can be readily formed in a wide variety of coil configurations, and used in a wide variety of ways. Further, while the MTL coils of the present invention work well at high field strengths and frequencies, they also work at low frequencies and in low field strengths as well.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI*

NASA Astrophysics Data System (ADS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-12-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning.

Cine phase contrast MRI to measure continuum Lagrangian finite strain fields in contracting skeletal muscle.

PubMed

Zhou, Hehe; Novotny, John E

2007-01-01

To measure the complex mechanics and Lagrangian finite strain of contracting human skeletal muscle in vivo with cine phase contrast MRI (CPC-MRI) applied to the human supraspinatus muscle of the shoulder. Processing techniques are applied to transform velocities from CPC-MRI images to displacements and planar Lagrangian finite strain. An interpolation method describing the continuity of the velocity field and forward-backward and Fourier transform methods were used to track the displacement of regions of interest during a cyclic abduction motion of a subject's arm. The components of the Lagrangian strain tensor were derived during the motion and principal and maximum in-plane shear strain fields calculated. Derived displacement and strain fields are shown that describe the contraction mechanics of the supraspinatus. Strains vary over time during the cyclic motion and are highly nonuniform throughout the muscle. This method presented overcomes the physical resolution of the MRI scanner, which is crucial for the detection of detailed information within muscles, such as the changes that might occur with partial tears of the supraspinatus. These can then be used as input or validation data for modeling human skeletal muscle.

An evaluation of independent component analyses with an application to resting-state fMRI

PubMed Central

Matteson, David S.; Ruppert, David; Eloyan, Ani; Caffo, Brian S.

2013-01-01

Summary We examine differences between independent component analyses (ICAs) arising from different as-sumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional magnetic resonance imaging (fMRI). ICA can be viewed as a generalization of principal component analysis (PCA) that takes into account higher-order cross-correlations. Whereas the PCA solution is unique, there are many ICA methods–whose solutions may differ. Infomax, FastICA, and JADE are commonly applied to fMRI studies, with FastICA being arguably the most popular. Hastie and Tibshirani (2003) demonstrated that ProDenICA outperformed FastICA in simulations with two components. We introduce the application of ProDenICA to simulations with more components and to fMRI data. ProDenICA was more accurate in simulations, and we identified differences between biologically meaningful ICs from ProDenICA versus other methods in the fMRI analysis. ICA methods require nonconvex optimization, yet current practices do not recognize the importance of, nor adequately address sensitivity to, initial values. We found that local optima led to dramatically different estimates in both simulations and group ICA of fMRI, and we provide evidence that the global optimum from ProDenICA is the best estimate. We applied a modification of the Hungarian (Kuhn-Munkres) algorithm to match ICs from multiple estimates, thereby gaining novel insights into how brain networks vary in their sensitivity to initial values and ICA method. PMID:24350655

MRI Post-processing in Pre-surgical Evaluation

PubMed Central

Wang, Z. Irene; Alexopoulos, Andreas V.

2016-01-01

Purpose of Review Advanced MRI post-processing techniques are increasingly used to complement visual analysis and elucidate structural epileptogenic lesions. This review summarizes recent developments in MRI post-processing in the context of epilepsy pre-surgical evaluation, with the focus on patients with unremarkable MRI by visual analysis (i.e., “nonlesional” MRI). Recent Findings Various methods of MRI post-processing have been reported to show additional clinical values in the following areas: (1) lesion detection on an individual level; (2) lesion confirmation for reducing the risk of over reading the MRI; (3) detection of sulcal/gyral morphologic changes that are particularly difficult for visual analysis; and (4) delineation of cortical abnormalities extending beyond the visible lesion. Future directions to improve performance of MRI post-processing include using higher magnetic field strength for better signal and contrast to noise ratio, adopting a multi-contrast frame work, and integration with other noninvasive modalities. Summary MRI post-processing can provide essential value to increase the yield of structural MRI and should be included as part of the presurgical evaluation of nonlesional epilepsies. MRI post-processing allows for more accurate identification/delineation of cortical abnormalities, which should then be more confidently targeted and mapped. PMID:26900745

Automatic selection of arterial input function using tri-exponential models

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Chen, Jeremy; Castro, Marcelo; Thomasson, David

2009-02-01

Dynamic Contrast Enhanced MRI (DCE-MRI) is one method for drug and tumor assessment. Selecting a consistent arterial input function (AIF) is necessary to calculate tissue and tumor pharmacokinetic parameters in DCE-MRI. This paper presents an automatic and robust method to select the AIF. The first stage is artery detection and segmentation, where knowledge about artery structure and dynamic signal intensity temporal properties of DCE-MRI is employed. The second stage is AIF model fitting and selection. A tri-exponential model is fitted for every candidate AIF using the Levenberg-Marquardt method, and the best fitted AIF is selected. Our method has been applied in DCE-MRIs of four different body parts: breast, brain, liver and prostate. The success rates in artery segmentation for 19 cases are 89.6%+/-15.9%. The pharmacokinetic parameters computed from the automatically selected AIFs are highly correlated with those from manually determined AIFs (R2=0.946, P(T<=t)=0.09). Our imaging-based tri-exponential AIF model demonstrated significant improvement over a previously proposed bi-exponential model.

Magnetic field shift due to mechanical vibration in functional magnetic resonance imaging.

PubMed

Foerster, Bernd U; Tomasi, Dardo; Caparelli, Elisabeth C

2005-11-01

Mechanical vibrations of the gradient coil system during readout in echo-planar imaging (EPI) can increase the temperature of the gradient system and alter the magnetic field distribution during functional magnetic resonance imaging (fMRI). This effect is enhanced by resonant modes of vibrations and results in apparent motion along the phase encoding direction in fMRI studies. The magnetic field drift was quantified during EPI by monitoring the resonance frequency interleaved with the EPI acquisition, and a novel method is proposed to correct the apparent motion. The knowledge on the frequency drift over time was used to correct the phase of the k-space EPI dataset. Since the resonance frequency changes very slowly over time, two measurements of the resonance frequency, immediately before and after the EPI acquisition, are sufficient to remove the field drift effects from fMRI time series. The frequency drift correction method was tested "in vivo" and compared to the standard image realignment method. The proposed method efficiently corrects spurious motion due to magnetic field drifts during fMRI. (c) 2005 Wiley-Liss, Inc.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

A Unified Framework for Brain Segmentation in MR Images

PubMed Central

Yazdani, S.; Yusof, R.; Karimian, A.; Riazi, A. H.; Bennamoun, M.

2015-01-01

Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets. PMID:26089978

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

PubMed

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

On NUFFT-based gridding for non-Cartesian MRI

NASA Astrophysics Data System (ADS)

Fessler, Jeffrey A.

2007-10-01

For MRI with non-Cartesian sampling, the conventional approach to reconstructing images is to use the gridding method with a Kaiser-Bessel (KB) interpolation kernel. Recently, Sha et al. [L. Sha, H. Guo, A.W. Song, An improved gridding method for spiral MRI using nonuniform fast Fourier transform, J. Magn. Reson. 162(2) (2003) 250-258] proposed an alternative method based on a nonuniform FFT (NUFFT) with least-squares (LS) design of the interpolation coefficients. They described this LS_NUFFT method as shift variant and reported that it yielded smaller reconstruction approximation errors than the conventional shift-invariant KB approach. This paper analyzes the LS_NUFFT approach in detail. We show that when one accounts for a certain linear phase factor, the core of the LS_NUFFT interpolator is in fact real and shift invariant. Furthermore, we find that the KB approach yields smaller errors than the original LS_NUFFT approach. We show that optimizing certain scaling factors can lead to a somewhat improved LS_NUFFT approach, but the high computation cost seems to outweigh the modest reduction in reconstruction error. We conclude that the standard KB approach, with appropriate parameters as described in the literature, remains the practical method of choice for gridding reconstruction in MRI.

Behavior, neuropsychology and fMRI.

PubMed

Bennett, Maxwell R; Hatton, Sean; Hermens, Daniel F; Lagopoulos, Jim

Cognitive neuroscientists in the late 20th century began the task of identifying the part(s) of the brain concerned with normal behavior as manifest in the psychological capacities as affective powers, reasoning, behaving purposively and the pursuit of goals, following introduction of the 'functional magnetic resonance imaging' (fMRI) method for identifying brain activity. For this research program to be successful two questions require satisfactory answers. First, as the fMRI method can currently only be used on stationary subjects, to what extent can neuropsychological tests applicable to such stationary subjects be correlated with normal behavior. Second, to what extent can correlations between the various neuropsychological tests on the one hand, and sites of brain activity determined with fMRI on the other, be regarded as established. The extent to which these questions have yet received satisfactory answers is reviewed, and suggestions made both for improving correlations of neuropsychological tests with behavior as well as with the results of fMRI-based observations. Copyright © 2016. Published by Elsevier Ltd.

Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

PubMed Central

Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

2012-01-01

In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

Genes involved in prostate cancer progression determine MRI visibility

PubMed Central

Li, Ping; You, Sungyong; Nguyen, Christopher; Wang, Yanping; Kim, Jayoung; Sirohi, Deepika; Ziembiec, Asha; Luthringer, Daniel; Lin, Shih-Chieh; Daskivich, Timothy; Wu, Jonathan; Freeman, Michael R; Saouaf, Rola; Li, Debiao; Kim, Hyung L.

2018-01-01

MRI is used to image prostate cancer and target tumors for biopsy or therapeutic ablation. The objective was to understand the biology of tumors not visible on MRI that may go undiagnosed and untreated. Methods: Prostate cancers visible or invisible on multiparametric MRI were macrodissected and examined by RNAseq. Differentially expressed genes (DEGs) based on MRI visibility status were cross-referenced with publicly available gene expression databases to identify genes associated with disease progression. Genes with potential roles in determining MRI visibility and disease progression were knocked down in murine prostate cancer xenografts, and imaged by MRI. Results: RNAseq identified 1,654 DEGs based on MRI visibility status. Comparison of DEGs based on MRI visibility and tumor characteristics revealed that Gleason score (dissimilarity test, p<0.0001) and tumor size (dissimilarity test, p<0.039) did not completely determine MRI visibility. Genes in previously reported prognostic signatures significantly correlated with MRI visibility suggesting that MRI visibility was prognostic. Cross-referencing DEGs with external datasets identified four genes (PHYHD1, CENPF, ALDH2, GDF15) that predict MRI visibility, progression free survival and metastatic deposits. Genetic modification of a human prostate cancer cell line to induce miR-101 and suppress CENPF decreased cell migration and invasion. As prostate cancer xenografts in mice, these cells had decreased visibility on diffusion weighted MRI and decreased perfusion, which correlated with immunostaining showing decreased cell density and proliferation. Conclusions: Genes involved in prostate cancer prognosis and metastasis determine MRI visibility, indicating that MRI visibility has prognostic significance. MRI visibility was associated with genetic features linked to poor prognosis. PMID:29556354

Validating the performance of one-time decomposition for fMRI analysis using ICA with automatic target generation process.

PubMed

Yao, Shengnan; Zeng, Weiming; Wang, Nizhuan; Chen, Lei

2013-07-01

Independent component analysis (ICA) has been proven to be effective for functional magnetic resonance imaging (fMRI) data analysis. However, ICA decomposition requires to optimize the unmixing matrix iteratively whose initial values are generated randomly. Thus the randomness of the initialization leads to different ICA decomposition results. Therefore, just one-time decomposition for fMRI data analysis is not usually reliable. Under this circumstance, several methods about repeated decompositions with ICA (RDICA) were proposed to reveal the stability of ICA decomposition. Although utilizing RDICA has achieved satisfying results in validating the performance of ICA decomposition, RDICA cost much computing time. To mitigate the problem, in this paper, we propose a method, named ATGP-ICA, to do the fMRI data analysis. This method generates fixed initial values with automatic target generation process (ATGP) instead of being produced randomly. We performed experimental tests on both hybrid data and fMRI data to indicate the effectiveness of the new method and made a performance comparison of the traditional one-time decomposition with ICA (ODICA), RDICA and ATGP-ICA. The proposed method demonstrated that it not only could eliminate the randomness of ICA decomposition, but also could save much computing time compared to RDICA. Furthermore, the ROC (Receiver Operating Characteristic) power analysis also denoted the better signal reconstruction performance of ATGP-ICA than that of RDICA. Copyright © 2013 Elsevier Inc. All rights reserved.

A general probabilistic model for group independent component analysis and its estimation methods

PubMed Central

Guo, Ying

2012-01-01

SUMMARY Independent component analysis (ICA) has become an important tool for analyzing data from functional magnetic resonance imaging (fMRI) studies. ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix and the uncertainty in between-subjects variability in fMRI data. We present a general probabilistic ICA (PICA) model that can accommodate varying group structures of multi-subject spatio-temporal processes. An advantage of the proposed model is that it can flexibly model various types of group structures in different underlying neural source signals and under different experimental conditions in fMRI studies. A maximum likelihood method is used for estimating this general group ICA model. We propose two EM algorithms to obtain the ML estimates. The first method is an exact EM algorithm which provides an exact E-step and an explicit noniterative M-step. The second method is an variational approximation EM algorithm which is computationally more efficient than the exact EM. In simulation studies, we first compare the performance of the proposed general group PICA model and the existing probabilistic group ICA approach. We then compare the two proposed EM algorithms and show the variational approximation EM achieves comparable accuracy to the exact EM with significantly less computation time. An fMRI data example is used to illustrate application of the proposed methods. PMID:21517789

A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment design.

PubMed

Varadarajan, Divya; Haldar, Justin P

2017-11-01

The data measured in diffusion MRI can be modeled as the Fourier transform of the Ensemble Average Propagator (EAP), a probability distribution that summarizes the molecular diffusion behavior of the spins within each voxel. This Fourier relationship is potentially advantageous because of the extensive theory that has been developed to characterize the sampling requirements, accuracy, and stability of linear Fourier reconstruction methods. However, existing diffusion MRI data sampling and signal estimation methods have largely been developed and tuned without the benefit of such theory, instead relying on approximations, intuition, and extensive empirical evaluation. This paper aims to address this discrepancy by introducing a novel theoretical signal processing framework for diffusion MRI. The new framework can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q-space sampling, and can be used to theoretically evaluate and compare the accuracy, resolution, and noise-resilience of different data acquisition and parameter estimation techniques. The framework is based on the EAP, and makes very limited modeling assumptions. As a result, the approach can even provide new insight into the behavior of model-based linear diffusion estimation methods in contexts where the modeling assumptions are inaccurate. The practical usefulness of the proposed framework is illustrated using both simulated and real diffusion MRI data in applications such as choosing between different parameter estimation methods and choosing between different q-space sampling schemes. Copyright © 2017 Elsevier Inc. All rights reserved.

Monitoring local heating around an interventional MRI antenna with RF radiometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ertürk, M. Arcan; El-Sharkawy, AbdEl-Monem M.; Bottomley, Paul A., E-mail: bottoml@mri.jhu.edu

Purpose: Radiofrequency (RF) radiometry uses thermal noise detected by an antenna to measure the temperature of objects independent of medical imaging technologies such as magnetic resonance imaging (MRI). Here, an active interventional MRI antenna can be deployed as a RF radiometer to measure local heating, as a possible new method of monitoring device safety and thermal therapy. Methods: A 128 MHz radiometer receiver was fabricated to measure the RF noise voltage from an interventional 3 T MRI loopless antenna and calibrated for temperature in a uniformly heated bioanalogous gel phantom. Local heating (ΔT) was induced using the antenna for RFmore » transmission and measured by RF radiometry, fiber-optic thermal sensors, and MRI thermometry. The spatial thermal sensitivity of the antenna radiometer was numerically computed using a method-of-moment electric field analyses. The gel’s thermal conductivity was measured by MRI thermometry, and the localized time-dependent ΔT distribution computed from the bioheat transfer equation and compared with radiometry measurements. A “H-factor” relating the 1 g-averaged ΔT to the radiometric temperature was introduced to estimate peak temperature rise in the antenna’s sensitive region. Results: The loopless antenna radiometer linearly tracked temperature inside a thermally equilibrated phantom up to 73 °C to within ±0.3 °C at a 2 Hz sample rate. Computed and MRI thermometric measures of peak ΔT agreed within 13%. The peak 1 g-average temperature was H = 1.36 ± 0.02 times higher than the radiometric temperature for any media with a thermal conductivity of 0.15–0.50 (W/m)/K, indicating that the radiometer can measure peak 1 g-averaged ΔT in physiologically relevant tissue within ±0.4 °C. Conclusions: Active internal MRI detectors can serve as RF radiometers at the MRI frequency to provide accurate independent measures of local and peak temperature without the artifacts that can accompany MRI thermometry or the extra space needed to accommodate alternative thermal transducers. A RF radiometer could be integrated in a MRI scanner to permit “self-monitoring” for assuring device safety and/or monitoring delivery of thermal therapy.« less

SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

PubMed

Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan

2017-09-01

With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.

Delineating potential epileptogenic areas utilizing resting functional magnetic resonance imaging (fMRI) in epilepsy patients.

PubMed

Pizarro, Ricardo; Nair, Veena; Meier, Timothy; Holdsworth, Ryan; Tunnell, Evelyn; Rutecki, Paul; Sillay, Karl; Meyerand, Mary E; Prabhakaran, Vivek

2016-08-01

Seizure localization includes neuroimaging like electroencephalogram, and magnetic resonance imaging (MRI) with limited ability to characterize the epileptogenic network. Temporal clustering analysis (TCA) characterizes epileptogenic network congruent with interictal epileptiform discharges by clustering together voxels with transient signals. We generated epileptogenic areas for 12 of 13 epilepsy patients with TCA, congruent with different areas of seizure onset. Resting functional MRI (fMRI) scans are noninvasive, and can be acquired quickly, in patients with different levels of severity and function. Analyzing resting fMRI data using TCA is quick and can complement clinical methods to characterize the epileptogenic network.

Joint fMRI analysis and subject clustering using sparse dictionary learning

NASA Astrophysics Data System (ADS)

Kim, Seung-Jun; Dontaraju, Krishna K.

2017-08-01

Multi-subject fMRI data analysis methods based on sparse dictionary learning are proposed. In addition to identifying the component spatial maps by exploiting the sparsity of the maps, clusters of the subjects are learned by postulating that the fMRI volumes admit a subspace clustering structure. Furthermore, in order to tune the associated hyper-parameters systematically, a cross-validation strategy is developed based on entry-wise sampling of the fMRI dataset. Efficient algorithms for solving the proposed constrained dictionary learning formulations are developed. Numerical tests performed on synthetic fMRI data show promising results and provides insights into the proposed technique.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

PubMed

Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

2014-07-15

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. Copyright © 2014. Published by Elsevier Inc.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

PubMed Central

Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

2014-01-01

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. PMID:24657353

Comparative Study of SVM Methods Combined with Voxel Selection for Object Category Classification on fMRI Data

PubMed Central

Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-01-01

Background Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Methodology/Principal Findings Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. Conclusions/Significance The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice. PMID:21359184

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

PubMed

Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-02-16

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

Magnetic Resonance Medical Imaging (MRI)-from the inside

NASA Astrophysics Data System (ADS)

Bottomley, Paul

There are about 36,000 magnetic resonance imaging (MRI) scanners in the world, with annual sales of 2500. In the USA about 34 million MRI studies are done annually, and 60-70% of all scanners operate at 1.5 Tesla (T). In 1982 there were none. How MRI got to be-and how it got to1.5T is the subject of this talk. Its an insider's view-mine-as a physics PhD student at Nottingham University when MRI (almost) began, through to the invention of the 1.5T clinical MRI scanner at GE's research center in Schenectady NY.Before 1977 all MRI was done on laboratory nuclear magnetic resonance instruments used for analyzing small specimens via chemical shift spectroscopy (MRS). It began with Lauterbur's 1973 observation that turning up the spectrometer's linear gradient magnetic field, generated a spectrum that was a 1D projection of the sample in the direction of the gradient. What followed in the 70's was the development of 3 key methods of 3D spatial localization that remain fundamental to MRI today.As the 1980's began, the once unimaginable prospect of upscaling from 2cm test-tubes to human body-sized magnets, gradient and RF transmit/receive systems, was well underway, evolving from arm-sized, to whole-body electromagnet-based systems operating at <0.2T. I moved to Johns Hopkins University to apply MRI methods to localized MRS and study cardiac metabolism, and then to GE to build a whole-body MRS machine. The largest uniform magnet possible-then, a 1.5T superconducting system-was required. Body MRI was first thought impossible above 0.35T due to RF penetration, detector coil and signal-to-noise ratio (SNR) issues. When GE finally did take on MRI, their plan was to drop the field to 0.3T. We opted to make MRI work at 1.5T instead. The result was a scanner that could study both anatomy and metabolism with a SNR way beyond its lower field rivals. MRI's success truly reflects the team efforts of many: from the NMR physics to the engineering of magnets, gradient and RF systems.

Magnetorotational Instability: Nonmodal Growth and the Relationship of Global Modes to the Shearing Box

DOE Office of Scientific and Technical Information (OSTI.GOV)

J Squire, A Bhattacharjee

We study the magnetorotational instability (MRI) (Balbus & Hawley 1998) using non-modal stability techniques.Despite the spectral instability of many forms of the MRI, this proves to be a natural method of analysis that is well-suited to deal with the non-self-adjoint nature of the linear MRI equations. We find that the fastest growing linear MRI structures on both local and global domains can look very diff erent to the eigenmodes, invariably resembling waves shearing with the background flow (shear waves). In addition, such structures can grow many times faster than the least stable eigenmode over long time periods, and be localizedmore » in a completely di fferent region of space. These ideas lead – for both axisymmetric and non-axisymmetric modes – to a natural connection between the global MRI and the local shearing box approximation. By illustrating that the fastest growing global structure is well described by the ordinary diff erential equations (ODEs) governing a single shear wave, we find that the shearing box is a very sensible approximation for the linear MRI, contrary to many previous claims. Since the shear wave ODEs are most naturally understood using non-modal analysis techniques, we conclude by analyzing local MRI growth over finite time-scales using these methods. The strong growth over a wide range of wave-numbers suggests that non-modal linear physics could be of fundamental importance in MRI turbulence (Squire & Bhattacharjee 2014).« less

Magnetic resonance imaging in the evaluation of clinical treatment of otospongiosis: a pilot study.

PubMed

de Oliveira Vicente, Andy; Chandrasekhar, Sujana S; Yamashita, Helio K; Cruz, Oswaldo Laercio M; Barros, Flavia A; Penido, Norma O

2015-06-01

To evaluate the applicability of magnetic resonance imaging (MRI) as a method for monitoring the activity of otospongiotic lesions before and after clinical treatment. Prospective, randomized, controlled, double-blind study. One single tertiary care institution in a large, cosmopolitan city. Twenty-six patients (n = 42 ears) with clinical, audiometric, and tomographic diagnosis of otosclerosis were enrolled. If computed tomography (CT) demonstrated active lesions, these patients underwent MRI to detect otospongiotic foci, seen as areas of gadolinium enhancement. Patients were divided into 3 groups and received treatment with placebo, sodium alendronate, or sodium fluoride for 6 months. After this period, clinical and audiometric evaluations and a second MRI were performed. Each MRI was evaluated by both a neuroradiologist and an otolaryngologist in a subjective (visual) and objective (using specific eFilm Workstation software) manner. Otospongiosis was most predominantly identified in the region anterior to the oval window, and this site was reliable for comparing pre- and posttreatment scans. The patients in the alendronate and sodium fluoride groups had MRI findings that suggested a decrease in activity of otospongiotic lesions, more relevant in the alendronate group. These findings were statistically significant for both subjective and objective MRI evaluations. MRI shows higher sensitivity than clinical or audiometric assessment for detecting reduction in activity of otospongiosis. The objective MRI evaluation based on software analysis was the most accurate method of monitoring clinical treatment response in otospongiosis. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Unravelling the complex MRI pattern in glutaric aciduria type I using statistical models-a cohort study in 180 patients.

PubMed

Garbade, Sven F; Greenberg, Cheryl R; Demirkol, Mübeccel; Gökçay, Gülden; Ribes, Antonia; Campistol, Jaume; Burlina, Alberto B; Burgard, Peter; Kölker, Stefan

2014-09-01

Glutaric aciduria type I (GA-I) is a cerebral organic aciduria caused by inherited deficiency of glutaryl-CoA dehydrogenase and is characterized biochemically by an accumulation of putatively neurotoxic dicarboxylic metabolites. The majority of untreated patients develops a complex movement disorder with predominant dystonia during age 3-36 months. Magnetic resonance imaging (MRI) studies have demonstrated striatal and extrastriatal abnormalities. The major aim of this study was to elucidate the complex neuroradiological pattern of patients with GA-I and to associate the MRI findings with the severity of predominant neurological symptoms. In 180 patients, detailed information about the neurological presentation and brain region-specific MRI abnormalities were obtained via a standardized questionnaire. Patients with a movement disorder had more often MRI abnormalities in putamen, caudate, cortex, ventricles and external CSF spaces than patients without or with minor neurological symptoms. Putaminal MRI changes and strongly dilated ventricles were identified as the most reliable predictors of a movement disorder. In contrast, abnormalities in globus pallidus were not clearly associated with a movement disorder. Caudate and putamen as well as cortex, ventricles and external CSF spaces clearly collocalized on a two-dimensional map demonstrating statistical similarity and suggesting the same underlying pathomechanism. This study demonstrates that complex statistical methods are useful to decipher the age-dependent and region-specific MRI patterns of rare neurometabolic diseases and that these methods are helpful to elucidate the clinical relevance of specific MRI findings.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.

PubMed

Jack, Clifford R; Barnes, Josephine; Bernstein, Matt A; Borowski, Bret J; Brewer, James; Clegg, Shona; Dale, Anders M; Carmichael, Owen; Ching, Christopher; DeCarli, Charles; Desikan, Rahul S; Fennema-Notestine, Christine; Fjell, Anders M; Fletcher, Evan; Fox, Nick C; Gunter, Jeff; Gutman, Boris A; Holland, Dominic; Hua, Xue; Insel, Philip; Kantarci, Kejal; Killiany, Ron J; Krueger, Gunnar; Leung, Kelvin K; Mackin, Scott; Maillard, Pauline; Malone, Ian B; Mattsson, Niklas; McEvoy, Linda; Modat, Marc; Mueller, Susanne; Nosheny, Rachel; Ourselin, Sebastien; Schuff, Norbert; Senjem, Matthew L; Simonson, Alix; Thompson, Paul M; Rettmann, Dan; Vemuri, Prashanthi; Walhovd, Kristine; Zhao, Yansong; Zuk, Samantha; Weiner, Michael

2015-07-01

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests

PubMed Central

Serag, Ahmed; Wilkinson, Alastair G.; Telford, Emma J.; Pataky, Rozalia; Sparrow, Sarah A.; Anblagan, Devasuda; Macnaught, Gillian; Semple, Scott I.; Boardman, James P.

2017-01-01

Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38–42 weeks gestational age), children and adolescents (4–17 years) and adults (35–71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course. PMID:28163680

Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

NASA Astrophysics Data System (ADS)

Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

Real time MRI prostate segmentation based on wavelet multiscale products flow tracking.

PubMed

Flores-Tapia, Daniel; Venugopal, Niranjan; Thomas, Gabriel; McCurdy, Boyd; Ryner, Lawrence; Pistorius, Stephen

2010-01-01

Currently, prostate cancer is the third leading cause of cancer-related deaths among men in North America. As with many others types of cancer, early detection and treatment greatly increases the patient's chance of survival. Combined Magnetic Resonance Imaging and Spectroscopic Imaging (MRI/MRSI) techniques have became a reliable tool for early stage prostate cancer detection. Nevertheless, their performance is strongly affected by the determination of the region of interest (ROI) prior to data acquisition process. The process of executing prostate MRI/MRSI techniques can be significantly enhanced by segmenting the whole prostate. A novel method for segmentation of the prostate in MRI datasets is presented. This method exploits the different behavior presented by signal singularities and noise in the wavelet domain in order to accurately detect the borders around the prostate. The prostate contour is then traced by using a set of spatially variant rules that are based on prior knowledge about the general shape of the prostate. The proposed method yielded promising results when applied to clinical datasets.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

In Vivo Evaluation of Magnetic Targeting in Mice Colon Tumors with Ultra-Magnetic Liposomes Monitored by MRI.

PubMed

Thébault, Caroline J; Ramniceanu, Grégory; Michel, Aude; Beauvineau, Claire; Girard, Christian; Seguin, Johanne; Mignet, Nathalie; Ménager, Christine; Doan, Bich-Thuy

2018-06-25

The development of theranostic nanocarriers as an innovative therapy against cancer has been improved by targeting properties in order to optimize the drug delivery to safely achieve its desired therapeutic effect. The aim of this paper is to evaluate the magnetic targeting (MT) efficiency of ultra-magnetic liposomes (UML) into CT26 murine colon tumor by magnetic resonance imaging (MRI). Dynamic susceptibility contrast MRI was applied to assess the bloodstream circulation time. A novel semi-quantitative method called %I 0.25 , based on the intensity distribution in T 2 * -weighted MRI images was developed to compare the accumulation of T 2 contrast agent in tumors with or without MT. To evaluate the efficiency of magnetic targeting, the percentage of pixels under the intensity value I 0.25 (I 0.25  = 0.25(I max  - I min )) was calculated on the intensity distribution histogram. This innovative method of processing MRI images showed the MT efficiency by a %I 0.25 that was significantly higher in tumors using MT compared to passive accumulation, from 15.3 to 28.6 %. This methodology was validated by ex vivo methods with an iron concentration that is 3-fold higher in tumors using MT. We have developed a method that allows a semi-quantitative evaluation of targeting efficiency in tumors, which could be applied to different T 2 contrast agents.

De-noising of 3D multiple-coil MR images using modified LMMSE estimator.

PubMed

Yaghoobi, Nima; Hasanzadeh, Reza P R

2018-06-20

De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones. Copyright © 2018. Published by Elsevier Inc.

Evaluation of MRI Models in the Measurement of CMRO2 and Its Relationship With CBF

PubMed Central

Lin, Ai-Ling; Fox, Peter T.; Yang, Yihong; Lu, Hanzhang; Tan, Li-Hai; Gao, Jia-Hong

2008-01-01

The aim of this study was to investigate the various MRI biophysical models in the measurements of local cerebral metabolic rate of oxygen (CMRO2) and the corresponding relationship with cerebral blood flow (CBF) during brain activation. This aim was addressed by simultaneously measuring the relative changes in CBF, cerebral blood volume (CBV), and blood oxygen level dependent (BOLD) MRI signals in the human visual cortex during visual stimulation. A radial checkerboard delivered flash stimulation at five different frequencies. Two MRI models, the single-compartment model (SCM) and the multi-compartment model (MCM), were used to determine the relative changes in CMRO2 using three methods: [1] SCM with parameters identical to those used in a prior MRI study (M = 0.22; α = 0.38); [2] SCM with directly measured parameters (M from hypercapnia and α from measured δCBV and δCBF); and [3] MCM. The magnitude of relative changes in CMRO2 and the nonlinear relationship between CBF and CMRO2 obtained with Methods [2] and [3] were not in agreement with those obtained using Method [1]. However, the results of Methods [2] and [3] were aligned with positron emission tomography findings from the literature. Our results indicate that if appropriate parameters are used, the SCM and MCM models are equivalent for quantifying the values of CMRO2 and determining the flow-metabolism relationship. PMID:18666102

MR and CT image fusion for postimplant analysis in permanent prostate seed implants.

PubMed

Polo, Alfredo; Cattani, Federica; Vavassori, Andrea; Origgi, Daniela; Villa, Gaetano; Marsiglia, Hugo; Bellomi, Massimo; Tosi, Giampiero; De Cobelli, Ottavio; Orecchia, Roberto

2004-12-01

To compare the outcome of two different image-based postimplant dosimetry methods in permanent seed implantation. Between October 1999 and October 2002, 150 patients with low-risk prostate carcinoma were treated with (125)I and (103)Pd in our institution. A CT-MRI image fusion protocol was used in 21 consecutive patients treated with exclusive brachytherapy. The accuracy and reproducibility of the method was calculated, and then the CT-based dosimetry was compared with the CT-MRI-based dosimetry using the dose-volume histogram (DVH) related parameters recommended by the American Brachytherapy Society and the American Association of Physicists in Medicine. Our method for CT-MRI image fusion was accurate and reproducible (median shift <1 mm). Differences in prostate volume were found, depending on the image modality used. Quality assurance DVH-related parameters strongly depended on the image modality (CT vs. CT-MRI): V(100) = 82% vs. 88%, p < 0.05. D(90) = 96% vs. 115%, p < 0.05. Those results depend on the institutional implant technique and reflect the importance of lowering inter- and intraobserver discrepancies when outlining prostate and organs at risk for postimplant dosimetry. Computed tomography-MRI fused images allow accurate determination of prostate size, significantly improving the dosimetric evaluation based on DVH analysis. This provides a consistent method to judge a prostate seed implant's quality.

Note: Progress on the use of MgB2 superconducting joint technique for the development of MgB2 magnets for magnetic resonance imaging (MRI).

PubMed

Kim, Y G; Song, J B; Kim, J C; Kim, J M; Yoo, B H; Yun, S B; Hwang, D Y; Lee, H G

2017-08-01

This note presents a superconducting joint technique for the development of MgB 2 magnetic resonance imaging (MRI) magnets. The MgB 2 superconducting joint was fabricated by a powder processing method using Mg and B powders to establish a wire-bulk-wire connection. The joint resistance measured using a field-decay method was <10 -14 Ω, demonstrating that the proposed joint technique could be employed for developing "next-generation" MgB 2 MRI magnets operating in the persistent current mode.

Magnetic resonance imaging: A tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation

PubMed Central

Scott, WE; Weegman, BP; Balamurugan, AN; Ferrer-Fabrega, J; Anazawa, T; Karatzas, T; Jie, T; Hammer, BE; Matsumoto, S; Avgoustiniatos, ES; Maynard, KS; Sutherland, DER; Hering, BJ; Papas, KK

2014-01-01

Background Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost effectiveness of this approach. Incomplete pancreas distension and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of Magnetic Resonance Imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Methods Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18g winged catheter and MRI performed at 1.5 T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Results Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distension were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distension of identified problem regions) resolved these issues and MRI was successfully utilized as a guide and assessment tool for improved delivery. Conclusion Current methods of porcine pancreas distension do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distension and enzyme delivery. PMID:24986758

MRI-determined liver proton density fat fraction, with MRS validation: Comparison of regions of interest sampling methods in patients with type 2 diabetes.

PubMed

Vu, Kim-Nhien; Gilbert, Guillaume; Chalut, Marianne; Chagnon, Miguel; Chartrand, Gabriel; Tang, An

2016-05-01

To assess the agreement between published magnetic resonance imaging (MRI)-based regions of interest (ROI) sampling methods using liver mean proton density fat fraction (PDFF) as the reference standard. This retrospective, internal review board-approved study was conducted in 35 patients with type 2 diabetes. Liver PDFF was measured by magnetic resonance spectroscopy (MRS) using a stimulated-echo acquisition mode sequence and MRI using a multiecho spoiled gradient-recalled echo sequence at 3.0T. ROI sampling methods reported in the literature were reproduced and liver mean PDFF obtained by whole-liver segmentation was used as the reference standard. Intraclass correlation coefficients (ICCs), Bland-Altman analysis, repeated-measures analysis of variance (ANOVA), and paired t-tests were performed. ICC between MRS and MRI-PDFF was 0.916. Bland-Altman analysis showed excellent intermethod agreement with a bias of -1.5 ± 2.8%. The repeated-measures ANOVA found no systematic variation of PDFF among the nine liver segments. The correlation between liver mean PDFF and ROI sampling methods was very good to excellent (0.873 to 0.975). Paired t-tests revealed significant differences (P < 0.05) with ROI sampling methods that exclusively or predominantly sampled the right lobe. Significant correlations with mean PDFF were found with sampling methods that included higher number of segments, total area equal or larger than 5 cm(2) , or sampled both lobes (P = 0.001, 0.023, and 0.002, respectively). MRI-PDFF quantification methods should sample each liver segment in both lobes and include a total surface area equal or larger than 5 cm(2) to provide a close estimate of the liver mean PDFF. © 2015 Wiley Periodicals, Inc.

Where and How Does Grammatically Geared Processing Take Place--And Why Is Broca's Area Often Involved. A Coordinated fMRI/ERBP Study of Language Processing

ERIC Educational Resources Information Center

Dogil, Grzegorz; Frese, Inga; Haider, Hubert; Rohm, Dietmar; Wokurek, Wolfgang

2004-01-01

We address the possibility of combining the results from hemodynamic and electrophysiological methods for the study of cognitive processing of language. The hemodynamic method we use is Event-Related fMRI, and the electrophysiological method measures Event-Related Band Power (ERBP) of the EEG signal. The experimental technique allows us to…

Design of Multishell Sampling Schemes with Uniform Coverage in Diffusion MRI

PubMed Central

Caruyer, Emmanuel; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid

2017-01-01

Purpose In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q-ball imaging, providing so-called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q-space offer an interesting trade-off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques. Methods The design of acquisition in multishell is still an open and active field of research, however. In this work, we provide a general method to design multishell acquisition with uniform angular coverage. This method is based on a generalization of electrostatic repulsion to multishell. Results We evaluate the impact of our method using simulations, on the angular resolution in one and two bundles of fiber configurations. Compared to more commonly used radial sampling, we show that our method improves the angular resolution, as well as fiber crossing discrimination. Discussion We propose a novel method to design sampling schemes with optimal angular coverage and show the positive impact on angular resolution in diffusion MRI. PMID:23625329

Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI.

PubMed

Adler, Daniel H; Pluta, John; Kadivar, Salmon; Craige, Caryne; Gee, James C; Avants, Brian B; Yushkevich, Paul A

2014-01-01

Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI, subfield delineation in MRI literature has largely relied on heuristic geometric rules, the validity of which with respect to the underlying anatomy is largely unknown. The development and evaluation of such rules are challenged by the limited availability of data linking MRI appearance to microscopic hippocampal anatomy, particularly in three dimensions (3D). The present paper, for the first time, demonstrates the feasibility of labeling hippocampal subfields in a high resolution volumetric MRI dataset based directly on microscopic features extracted from histology. It uses a combination of computational techniques and manual post-processing to map subfield boundaries from a stack of histology images (obtained with 200μm spacing and 5μm slice thickness; stained using the Kluver-Barrera method) onto a postmortem 9.4Tesla MRI scan of the intact, whole hippocampal formation acquired with 160μm isotropic resolution. The histology reconstruction procedure consists of sequential application of a graph-theoretic slice stacking algorithm that mitigates the effects of distorted slices, followed by iterative affine and diffeomorphic co-registration to postmortem MRI scans of approximately 1cm-thick tissue sub-blocks acquired with 200μm isotropic resolution. These 1cm blocks are subsequently co-registered to the MRI of the whole HF. Reconstruction accuracy is evaluated as the average displacement error between boundaries manually delineated in both the histology and MRI following the sequential stages of reconstruction. The methods presented and evaluated in this single-subject study can potentially be applied to multiple hippocampal tissue samples in order to construct a histologically informed MRI atlas of the hippocampal formation. © 2013 Elsevier Inc. All rights reserved.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

PubMed

Chang, Hing-Chiu; Gaur, Pooja; Chou, Ying-hui; Chu, Mei-Lan; Chen, Nan-kuei

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

WE-B-BRD-00: MRI for Radiation Oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

The use of MRI in radiation therapy is rapidly increasing. Applications vary from the MRI simulator, to the MRI fused with CT, and to the integrated MRI+RT system. Compared with the standard MRI QA, a broader scope of QA features has to be defined in order to maximize the benefits of using MRI in radiation therapy. These QA features include geometric fidelity, image registration, motion management, cross-system alignment, and hardware interference. Advanced MRI techniques require a specific type of QA, as they are being widely used in radiation therapy planning, dose calculations, post-implant dosimetry, and prognoses. A vigorous and adaptivemore » QA program is crucial to defining the responsibility of the entire radiation therapy group and detecting deviations from the performance of high-quality treatment. As a drastic departure from CT simulation, MRI simulation requires changes in the work flow of treatment planning and image guidance. MRI guided radiotherapy platforms are being developed and commercialized to take the advantage of the advance in knowledge, technology and clinical experience. This symposium will from an educational perspective discuss the scope and specific issues related to MRI guided radiotherapy. Learning Objectives: Understand the difference between a standard and a radiotherapy-specific MRI QA program. Understand the effects of MRI artifacts (geometric distortion and motion) on radiotherapy. Understand advanced MRI techniques (ultrashort echo, fast MRI including dynamic MRI and 4DMRI, diffusion, perfusion, and MRS) and related QA. Understand the methods to prepare MRI for treatment planning (electron density assignment, multimodality image registration, segmentation and motion management). Current status of MRI guided treatment platforms. Dr. Jihong Wang has a research grant with Elekta-MRL project. Dr. Ke Sheng receives research grants from Varian Medical systems.« less

In vivo estimation of normal amygdala volume from structural MRI scans with anatomical-based segmentation.

PubMed

Siozopoulos, Achilleas; Thomaidis, Vasilios; Prassopoulos, Panos; Fiska, Aliki

2018-02-01

Literature includes a number of studies using structural MRI (sMRI) to determine the volume of the amygdala, which is modified in various pathologic conditions. The reported values vary widely mainly because of different anatomical approaches to the complex. This study aims at estimating of the normal amygdala volume from sMRI scans using a recent anatomical definition described in a study based on post-mortem material. The amygdala volume has been calculated in 106 healthy subjects, using sMRI and anatomical-based segmentation. The resulting volumes have been analyzed for differences related to hemisphere, sex, and age. The mean amygdalar volume was estimated at 1.42 cm 3 . The mean right amygdala volume has been found larger than the left, but the difference for the raw values was within the limits of the method error. No intersexual differences or age-related alterations have been observed. The study provides a method for determining the boundaries of the amygdala in sMRI scans based on recent anatomical considerations and an estimation of the mean normal amygdala volume from a quite large number of scans for future use in comparative studies.

Multimodality localization of epileptic foci

NASA Astrophysics Data System (ADS)

Desco, Manuel; Pascau, Javier; Pozo, M. A.; Santos, Andres; Reig, Santiago; Gispert, Juan D.; Garcia-Barreno, Pedro

2001-05-01

This paper presents a multimodality approach for the localization of epileptic foci using PET, MRI and EEG combined without the need of external markers. Mutual Information algorithm is used for MRI-PET registration. Dipole coordinates (provided by BESA software) are projected onto the MRI using a specifically developed algorithm. The four anatomical references used for electrode positioning (nasion, inion and two preauricular points) are located on the MRI using a triplanar viewer combined with a surface-rendering tool. Geometric transformation using deformation of the ideal sphere used for dipole calculations is then applied to match the patient's brain size and shape. Eight treatment-refractory epileptic patients have been studied. The combination of the anatomical information from the MRI, hipoperfusion areas in PET and dipole position and orientation helped the physician in the diagnosis of epileptic focus location. Neurosurgery was not indicated for patients where PET and dipole results were inconsistent; in two cases it was clinically indicated despite the mismatch, showing a negative follow up. The multimodality approach presented does not require external markers for dipole projection onto the MRI, this being the main difference with previous methods. The proposed method may play an important role in the indication of surgery for treatment- refractory epileptic patients.

Evaluation of COPD's diaphragm motion extracted from 4D-MRI

NASA Astrophysics Data System (ADS)

Swastika, Windra; Masuda, Yoshitada; Kawata, Naoko; Matsumoto, Koji; Suzuki, Toshio; Iesato, Ken; Tada, Yuji; Sugiura, Toshihiko; Tanabe, Nobuhiro; Tatsumi, Koichiro; Ohnishi, Takashi; Haneishi, Hideaki

2015-03-01

We have developed a method called intersection profile method to construct a 4D-MRI (3D+time) from time-series of 2D-MRI. The basic idea is to find the best matching of the intersection profile from the time series of 2D-MRI in sagittal plane (navigator slice) and time series of 2D-MRI in coronal plane (data slice). In this study, we use 4D-MRI to semiautomatically extract the right diaphragm motion of 16 subjects (8 healthy subjects and 8 COPD patients). The diaphragm motion is then evaluated quantitatively by calculating the displacement of each subjects and normalized it. We also generate phase-length map to view and locate paradoxical motion of the COPD patients. The quantitative results of the normalized displacement shows that COPD patients tend to have smaller displacement compared to healthy subjects. The average normalized displacement of total 8 COPD patients is 9.4mm and the average of normalized displacement of 8 healthy volunteers is 15.3mm. The generated phase-length maps show that not all of the COPD patients have paradoxical motion, however if it has paradoxical motion, the phase-length map is able to locate where does it occur.

Local/non-local regularized image segmentation using graph-cuts: application to dynamic and multispectral MRI.

PubMed

Hanson, Erik A; Lundervold, Arvid

2013-11-01

Multispectral, multichannel, or time series image segmentation is important for image analysis in a wide range of applications. Regularization of the segmentation is commonly performed using local image information causing the segmented image to be locally smooth or piecewise constant. A new spatial regularization method, incorporating non-local information, was developed and tested. Our spatial regularization method applies to feature space classification in multichannel images such as color images and MR image sequences. The spatial regularization involves local edge properties, region boundary minimization, as well as non-local similarities. The method is implemented in a discrete graph-cut setting allowing fast computations. The method was tested on multidimensional MRI recordings from human kidney and brain in addition to simulated MRI volumes. The proposed method successfully segment regions with both smooth and complex non-smooth shapes with a minimum of user interaction.

Physics and instrumentation for imaging in-vivo drug distribution.

PubMed

Singh, M; Waluch, V

2000-03-15

Several imaging methods are currently available to measure drugs noninvasively. Of these, two techniques are today central to such measurements: nuclear imaging and magnetic resonance imaging/spectroscopy (MRI and MRS). While other methods, such as optical techniques, are rapidly gaining in interest, they have not yet attained the degree of development that makes them effective in measuring drugs in living systems, except in a small number of examples. The following introduction provides some basic elements of the potential and the limitations of both nuclear imaging and MRI/MRS techniques, methods that will be used in the studies described in the articles in this issue. However, and for those desiring to gain a better understanding of both methods, the reader is advised to consult much more extensive reviews and books describing such methods. A suggested list of books and articles on Nuclear Imaging and MRI/MRS is given.

Detection of early subclinical lung disease in children with cystic fibrosis by lung ventilation imaging with hyperpolarised gas MRI.

PubMed

Marshall, Helen; Horsley, Alex; Taylor, Chris J; Smith, Laurie; Hughes, David; Horn, Felix C; Swift, Andrew J; Parra-Robles, Juan; Hughes, Paul J; Norquay, Graham; Stewart, Neil J; Collier, Guilhem J; Teare, Dawn; Cunningham, Steve; Aldag, Ina; Wild, Jim M

2017-08-01

Hyperpolarised 3 He ventilation-MRI, anatomical lung MRI, lung clearance index (LCI), low-dose CT and spirometry were performed on 19 children (6-16 years) with clinically stable mild cystic fibrosis (CF) (FEV 1 >-1.96), and 10 controls. All controls had normal spirometry, MRI and LCI. Ventilation-MRI was the most sensitive method of detecting abnormalities, present in 89% of patients with CF, compared with CT abnormalities in 68%, LCI 47% and conventional MRI 22%. Ventilation defects were present in the absence of CT abnormalities and in patients with normal physiology, including LCI. Ventilation-MRI is thus feasible in young children, highly sensitive and provides additional information about lung structure-function relationships. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Exploiting the wavelet structure in compressed sensing MRI.

PubMed

Chen, Chen; Huang, Junzhou

2014-12-01

Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Generation of synthetic CT using multi-scale and dual-contrast patches for brain MRI-only external beam radiotherapy.

PubMed

Aouadi, Souha; Vasic, Ana; Paloor, Satheesh; Torfeh, Tarraf; McGarry, Maeve; Petric, Primoz; Riyas, Mohamed; Hammoud, Rabih; Al-Hammadi, Noora

2017-10-01

To create a synthetic CT (sCT) from conventional brain MRI using a patch-based method for MRI-only radiotherapy planning and verification. Conventional T1 and T2-weighted MRI and CT datasets from 13 patients who underwent brain radiotherapy were included in a retrospective study whereas 6 patients were tested prospectively. A new contribution to the Non-local Means Patch-Based Method (NMPBM) framework was done with the use of novel multi-scale and dual-contrast patches. Furthermore, the training dataset was improved by pre-selecting the closest database patients to the target patient for computation time/accuracy balance. sCT and derived DRRs were assessed visually and quantitatively. VMAT planning was performed on CT and sCT for hypothetical PTVs in homogeneous and heterogeneous regions. Dosimetric analysis was done by comparing Dose Volume Histogram (DVH) parameters of PTVs and organs at risk (OARs). Positional accuracy of MRI-only image-guided radiation therapy based on CBCT or kV images was evaluated. The retrospective (respectively prospective) evaluation of the proposed Multi-scale and Dual-contrast Patch-Based Method (MDPBM) gave a mean absolute error MAE=99.69±11.07HU (98.95±8.35HU), and a Dice in bones DI bone =83±0.03 (0.82±0.03). Good agreement with conventional planning techniques was obtained; the highest percentage of DVH metric deviations was 0.43% (0.53%) for PTVs and 0.59% (0.75%) for OARs. The accuracy of sCT/CBCT or DRR sCT /kV images registration parameters was <2mm and <2°. Improvements with MDPBM, compared to NMPBM, were significant. We presented a novel method for sCT generation from T1 and T2-weighted MRI potentially suitable for MRI-only external beam radiotherapy in brain sites. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Sparse magnetic resonance imaging reconstruction using the bregman iteration

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo

2013-01-01

Magnetic resonance imaging (MRI) reconstruction needs many samples that are sequentially sampled by using phase encoding gradients in a MRI system. It is directly connected to the scan time for the MRI system and takes a long time. Therefore, many researchers have studied ways to reduce the scan time, especially, compressed sensing (CS), which is used for sparse images and reconstruction for fewer sampling datasets when the k-space is not fully sampled. Recently, an iterative technique based on the bregman method was developed for denoising. The bregman iteration method improves on total variation (TV) regularization by gradually recovering the fine-scale structures that are usually lost in TV regularization. In this study, we studied sparse sampling image reconstruction using the bregman iteration for a low-field MRI system to improve its temporal resolution and to validate its usefulness. The image was obtained with a 0.32 T MRI scanner (Magfinder II, SCIMEDIX, Korea) with a phantom and an in-vivo human brain in a head coil. We applied random k-space sampling, and we determined the sampling ratios by using half the fully sampled k-space. The bregman iteration was used to generate the final images based on the reduced data. We also calculated the root-mean-square-error (RMSE) values from error images that were obtained using various numbers of bregman iterations. Our reconstructed images using the bregman iteration for sparse sampling images showed good results compared with the original images. Moreover, the RMSE values showed that the sparse reconstructed phantom and the human images converged to the original images. We confirmed the feasibility of sparse sampling image reconstruction methods using the bregman iteration with a low-field MRI system and obtained good results. Although our results used half the sampling ratio, this method will be helpful in increasing the temporal resolution at low-field MRI systems.

Self-gated golden angle spiral cine MRI for coronary endothelial function assessment.

PubMed

Bonanno, Gabriele; Hays, Allison G; Weiss, Robert G; Schär, Michael

2018-08-01

Depressed coronary endothelial function (CEF) is a marker for atherosclerotic disease, an independent predictor of cardiovascular events, and can be quantified non-invasively with ECG-triggered spiral cine MRI combined with isometric handgrip exercise (IHE). However, MRI-CEF measures can be hindered by faulty ECG-triggering, leading to prolonged breath-holds and degraded image quality. Here, a self-gated golden angle spiral method (SG-GA) is proposed to eliminate the need for ECG during cine MRI. SG-GA was tested against retrospectively ECG-gated golden angle spiral MRI (ECG-GA) and gold-standard ECG-triggered spiral cine MRI (ECG-STD) in 10 healthy volunteers. CEF data were obtained from cross-sectional images of the proximal right and left coronary arteries in a 3T scanner. Self-gating heart rates were compared to those from simultaneous ECG-gating. Coronary vessel sharpness and cross-sectional area (CSA) change with IHE were compared among the 3 methods. Self-gating precision, accuracy, and correlation-coefficient were 7.7 ± 0.5 ms, 9.1 ± 0.7 ms, and 0.93 ± 0.01, respectively (mean ± standard error). Vessel sharpness by SG-GA was equal or higher than ECG-STD (rest: 63.0 ± 1.7% vs. 61.3 ± 1.3%; exercise: 62.6 ± 1.3% vs. 56.7 ± 1.6%, P < 0.05). CSA changes were in agreement among the 3 methods (ECG-STD = 8.7 ± 4.0%, ECG-GA = 9.6 ± 3.1%, SG-GA = 9.1 ± 3.5%, P = not significant). CEF measures can be obtained with the proposed self-gated high-quality cine MRI method even when ECG is faulty or not available. Magn Reson Med 80:560-570, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Artifacts Quantification of Metal Implants in MRI

NASA Astrophysics Data System (ADS)

Vrachnis, I. N.; Vlachopoulos, G. F.; Maris, T. G.; Costaridou, L. I.

2017-11-01

The presence of materials with different magnetic properties, such as metal implants, causes distortion of the magnetic field locally, resulting in signal voids and pile ups, i.e. susceptibility artifacts in MRI. Quantitative and unbiased measurement of the artifact is prerequisite for optimization of acquisition parameters. In this study an image gradient based segmentation method is proposed for susceptibility artifact quantification. The method captures abrupt signal alterations by calculation of the image gradient. Then the artifact is quantified in terms of its extent by an automated cross entropy thresholding method as image area percentage. The proposed method for artifact quantification was tested in phantoms containing two orthopedic implants with significantly different magnetic permeabilities. The method was compared against a method proposed in the literature, considered as a reference, demonstrating moderate to good correlation (Spearman’s rho = 0.62 and 0.802 in case of titanium and stainless steel implants). The automated character of the proposed quantification method seems promising towards MRI acquisition parameter optimization.

Best method for right atrial volume assessment by two-dimensional echocardiography: validation with magnetic resonance imaging.

PubMed

Ebtia, Mahasti; Murphy, Darra; Gin, Kenneth; Lee, Pui K; Jue, John; Nair, Parvathy; Mayo, John; Barnes, Marion E; Thompson, Darby J S; Tsang, Teresa S M

2015-05-01

Echocardiographic methods for estimating right atrial (RA) volume have not been standardized. Our aim was to evaluate two-dimensional (2D) echocardiographic methods of RA volume assessment, using RA volume by magnetic resonance imaging (MRI) as the reference. Right atrial volume was assessed in 51 patients (mean age 63 ± 14 years, 33 female) who underwent comprehensive 2D echocardiography and cardiac MRI for clinically indicated reasons. Echocardiographic RA volume methods included (1) biplane area length, using four-chamber view twice (biplane 4C-4C); (2) biplane area length, using four-chamber and subcostal views (biplane 4C-subcostal); and (3) single plane Simpson's method of disks (Simpson's). Echocardiographic RA volumes as well as linear RA major and minor dimensions were compared to RA volume by MRI using correlation and Bland-Altman methods, and evaluated for inter-observer reproducibility and accuracy in discriminating RA enlargement. All echocardiography volumetric methods performed well compared to MRI, with Pearson's correlation of 0.98 and concordance correlation ≥0.91 for each. For bias and limits of agreement, biplane 4C-4C (bias -4.81 mL/m(2) , limits of agreement ±9.8 mL/m(2) ) and Simpson's (bias -5.15 mL/m(2) , limits of agreement ±10.1 mL/m(2) ) outperformed biplane 4C-subcostal (bias -8.36 mL/m(2) , limits of agreement ±12.5 mL/m(2) ). Accuracy for discriminating RA enlargement was higher for all volumetric methods than for linear measurements. Inter-observer variability was satisfactory across all methods. Compared to MRI, biplane 4C-4C and single plane Simpson's are highly accurate and reproducible 2D echocardiography methods for estimating RA volume. Linear dimensions are inaccurate and should be abandoned. © 2014, Wiley Periodicals, Inc.

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

Design and testing of an MRI-compatible cycle ergometer for non-invasive cardiac assessments during exercise

PubMed Central

2012-01-01

Background Magnetic resonance imaging (MRI) is an important tool for cardiac research, and it is frequently used for resting cardiac assessments. However, research into non-pharmacological stress cardiac evaluation is limited. Methods We aimed to design a portable and relatively inexpensive MRI cycle ergometer capable of continuously measuring pedalling workload while patients exercise to maintain target heart rates. Results We constructed and tested an MRI-compatible cycle ergometer for a 1.5 T MRI scanner. Resting and sub-maximal exercise images (at 110 beats per minute) were successfully obtained in 8 healthy adults. Conclusions The MRI-compatible cycle ergometer constructed by our research group enabled cardiac assessments at fixed heart rates, while continuously recording power output by directly measuring pedal force and crank rotation. PMID:22423637

AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Calculation of left ventricular volumes and ejection fraction from dynamic cardiac-gated 15O-water PET/CT: 5D-PET.

PubMed

Nordström, Jonny; Kero, Tanja; Harms, Hendrik Johannes; Widström, Charles; Flachskampf, Frank A; Sörensen, Jens; Lubberink, Mark

2017-11-14

Quantitative measurement of myocardial blood flow (MBF) is of increasing interest in the clinical assessment of patients with suspected coronary artery disease (CAD). 15 O-water positron emission tomography (PET) is considered the gold standard for non-invasive MBF measurements. However, calculation of left ventricular (LV) volumes and ejection fraction (EF) is not possible from standard 15 O-water uptake images. The purpose of the present work was to investigate the possibility of calculating LV volumes and LVEF from cardiac-gated parametric blood volume (V B ) 15 O-water images and from first pass (FP) images. Sixteen patients with mitral or aortic regurgitation underwent an eight-gate dynamic cardiac-gated 15 O-water PET/CT scan and cardiac MRI. V B and FP images were generated for each gate. Calculations of end-systolic volume (ESV), end-diastolic volume (EDV), stroke volume (SV) and LVEF were performed with automatic segmentation of V B and FP images, using commercially available software. LV volumes and LVEF were calculated with surface-, count-, and volume-based methods, and the results were compared with gold standard MRI. Using V B images, high correlations between PET and MRI ESV (r = 0.89, p < 0.001), EDV (r = 0.85, p < 0.001), SV (r = 0.74, p = 0.006) and LVEF (r = 0.72, p = 0.008) were found for the volume-based method. Correlations for FP images were slightly, but not significantly, lower than those for V B images when compared to MRI. Surface- and count-based methods showed no significant difference compared with the volume-based correlations with MRI. The volume-based method showed the best agreement with MRI with no significant difference on average for EDV and LVEF but with an overestimation of values for ESV (14%, p = 0.005) and SV (18%, p = 0.004) when using V B images. Using FP images, none of the parameters showed a significant difference from MRI. Inter-operator repeatability was excellent for all parameters (ICC > 0.86, p < 0.001). Calculation of LV volumes and LVEF from dynamic 15 O-water PET is feasible and shows good correlation with MRI. However, the analysis method is laborious, and future work is needed for more automation to make the method more easily applicable in a clinical setting.

WE-EF-BRD-00: New Developments in Hybrid MR-Treatment: Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2015-06-15

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

PubMed

Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

2017-06-01

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians. The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTV MRI enhanced the CTV more accurately than BTV in 25% of cases. The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTV MRI and GTV should be considered for a comprehensive treatment planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2017-04-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

Automated segmentation of the parotid gland based on atlas registration and machine learning: a longitudinal MRI study in head-and-neck radiation therapy.

PubMed

Yang, Xiaofeng; Wu, Ning; Cheng, Guanghui; Zhou, Zhengyang; Yu, David S; Beitler, Jonathan J; Curran, Walter J; Liu, Tian

2014-12-01

To develop an automated magnetic resonance imaging (MRI) parotid segmentation method to monitor radiation-induced parotid gland changes in patients after head and neck radiation therapy (RT). The proposed method combines the atlas registration method, which captures the global variation of anatomy, with a machine learning technology, which captures the local statistical features, to automatically segment the parotid glands from the MRIs. The segmentation method consists of 3 major steps. First, an atlas (pre-RT MRI and manually contoured parotid gland mask) is built for each patient. A hybrid deformable image registration is used to map the pre-RT MRI to the post-RT MRI, and the transformation is applied to the pre-RT parotid volume. Second, the kernel support vector machine (SVM) is trained with the subject-specific atlas pair consisting of multiple features (intensity, gradient, and others) from the aligned pre-RT MRI and the transformed parotid volume. Third, the well-trained kernel SVM is used to differentiate the parotid from surrounding tissues in the post-RT MRIs by statistically matching multiple texture features. A longitudinal study of 15 patients undergoing head and neck RT was conducted: baseline MRI was acquired prior to RT, and the post-RT MRIs were acquired at 3-, 6-, and 12-month follow-up examinations. The resulting segmentations were compared with the physicians' manual contours. Successful parotid segmentation was achieved for all 15 patients (42 post-RT MRIs). The average percentage of volume differences between the automated segmentations and those of the physicians' manual contours were 7.98% for the left parotid and 8.12% for the right parotid. The average volume overlap was 91.1% ± 1.6% for the left parotid and 90.5% ± 2.4% for the right parotid. The parotid gland volume reduction at follow-up was 25% at 3 months, 27% at 6 months, and 16% at 12 months. We have validated our automated parotid segmentation algorithm in a longitudinal study. This segmentation method may be useful in future studies to address radiation-induced xerostomia in head and neck radiation therapy. Copyright © 2014 Elsevier Inc. All rights reserved.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

2017-04-01

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners.

PubMed

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this "Atlas-T1w-DUTE" approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the "silver standard"; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally.

Improved FastICA algorithm in fMRI data analysis using the sparsity property of the sources.

PubMed

Ge, Ruiyang; Wang, Yubao; Zhang, Jipeng; Yao, Li; Zhang, Hang; Long, Zhiying

2016-04-01

As a blind source separation technique, independent component analysis (ICA) has many applications in functional magnetic resonance imaging (fMRI). Although either temporal or spatial prior information has been introduced into the constrained ICA and semi-blind ICA methods to improve the performance of ICA in fMRI data analysis, certain types of additional prior information, such as the sparsity, has seldom been added to the ICA algorithms as constraints. In this study, we proposed a SparseFastICA method by adding the source sparsity as a constraint to the FastICA algorithm to improve the performance of the widely used FastICA. The source sparsity is estimated through a smoothed ℓ0 norm method. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of SparseFastICA and made a performance comparison between SparseFastICA, FastICA and Infomax ICA. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of SparseFastICA for the source separation in fMRI data. Both the simulated and real fMRI experimental results showed that SparseFastICA has better robustness to noise and better spatial detection power than FastICA. Although the spatial detection power of SparseFastICA and Infomax did not show significant difference, SparseFastICA had faster computation speed than Infomax. SparseFastICA was comparable to the Infomax algorithm with a faster computation speed. More importantly, SparseFastICA outperformed FastICA in robustness and spatial detection power and can be used to identify more accurate brain networks than FastICA algorithm. Copyright © 2016 Elsevier B.V. All rights reserved.

3D Registration of mpMRI for Assessment of Prostate Cancer Focal Therapy.

PubMed

Orczyk, Clément; Rosenkrantz, Andrew B; Mikheev, Artem; Villers, Arnauld; Bernaudin, Myriam; Taneja, Samir S; Valable, Samuel; Rusinek, Henry

2017-12-01

This study aimed to assess a novel method of three-dimensional (3D) co-registration of prostate magnetic resonance imaging (MRI) examinations performed before and after prostate cancer focal therapy. We developed a software platform for automatic 3D deformable co-registration of prostate MRI at different time points and applied this method to 10 patients who underwent focal ablative therapy. MRI examinations were performed preoperatively, as well as 1 week and 6 months post treatment. Rigid registration served as reference for assessing co-registration accuracy and precision. Segmentation of preoperative and postoperative prostate revealed a significant postoperative volume decrease of the gland that averaged 6.49 cc (P = .017). Applying deformable transformation based on mutual information from 120 pairs of MRI slices, we refined by 2.9 mm (max. 6.25 mm) the alignment of the ablation zone, segmented from contrast-enhanced images on the 1-week postoperative examination, to the 6-month postoperative T2-weighted images. This represented a 500% improvement over the rigid approach (P = .001), corrected by volume. The dissimilarity by Dice index of the mapped ablation zone using deformable transformation vs rigid control was significantly (P = .04) higher at the ablation site than in the whole gland. Our findings illustrate our method's ability to correct for deformation at the ablation site. The preliminary analysis suggests that deformable transformation computed from mutual information of preoperative and follow-up MRI is accurate in co-registration of MRI examinations performed before and after focal therapy. The ability to localize the previously ablated tissue in 3D space may improve targeting for image-guided follow-up biopsy within focal therapy protocols. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Investigation of a calcium-responsive contrast agent in cellular model systems: feasibility for use as a smart molecular probe in functional MRI.

PubMed

Angelovski, Goran; Gottschalk, Sven; Milošević, Milena; Engelmann, Jörn; Hagberg, Gisela E; Kadjane, Pascal; Andjus, Pavle; Logothetis, Nikos K

2014-05-21

Responsive or smart contrast agents (SCAs) represent a promising direction for development of novel functional MRI (fMRI) methods for the eventual noninvasive assessment of brain function. In particular, SCAs that respond to Ca(2+) may allow tracking neuronal activity independent of brain vasculature, thus avoiding the characteristic limitations of current fMRI techniques. Here we report an in vitro proof-of-principle study with a Ca(2+)-sensitive, Gd(3+)-based SCA in an attempt to validate its potential use as a functional in vivo marker. First, we quantified its relaxometric response in a complex 3D cell culture model. Subsequently, we examined potential changes in the functionality of primary glial cells following administration of this SCA. Monitoring intracellular Ca(2+) showed that, despite a reduction in the Ca(2+) level, transport of Ca(2+) through the plasma membrane remained unaffected, while stimulation with ATP induced Ca(2+)-transients suggested normal cellular signaling in the presence of low millimolar SCA concentrations. SCAs merely lowered the intracellular Ca(2+) level. Finally, we estimated the longitudinal relaxation times (T1) for an idealized in vivo fMRI experiment with SCA, for extracellular Ca(2+) concentration level changes expected during intense neuronal activity which takes place upon repetitive stimulation. The values we obtained indicate changes in T1 of around 1-6%, sufficient to be robustly detectable using modern MRI methods in high field scanners. Our results encourage further attempts to develop even more potent SCAs and appropriate fMRI protocols. This would result in novel methods that allow monitoring of essential physiological processes at the cellular and molecular level.

Estimation of Error in Maximal Intensity Projection-Based Internal Target Volume of Lung Tumors: A Simulation and Comparison Study Using Dynamic Magnetic Resonance Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai Jing; Read, Paul W.; Baisden, Joseph M.

Purpose: To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Methods and Materials: Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA)more » from RedCAM ({epsilon}), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability ({nu}). Results: Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies ({epsilon} = -21.64% {+-} 8.23%) and lung tumor patient studies ({epsilon} = -20.31% {+-} 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly ({epsilon} = -5.13{nu} - 6.71, r{sup 2} = 0.76) with the subjects' respiratory variability. Conclusions: Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.« less

Quantification of Regional Myocardial Oxygenation by Magnetic Resonance Imaging: Validation with Positron Emission Tomography

PubMed Central

McCommis, Kyle S.; Goldstein, Thomas A.; Abendschein, Dana R.; Herrero, Pilar; Misselwitz, Bernd; Gropler, Robert J.; Zheng, Jie

2011-01-01

Background A comprehensive evaluation of myocardial ischemia requires measures of both oxygen supply and demand. Positron emission tomography (PET) is currently the gold standard for such evaluations, but its use is limited due to its ionizing radiation, limited availability, and high cost. A cardiac magnetic resonance imaging (MRI) method was developed for assessing myocardial oxygenation. The purpose of this study was to evaluate and validate this technique compared to PET during pharmacologic stress in a canine model of coronary artery stenosis. Methods and Results Twenty-one beagles and small mongrel dogs without coronary artery stenosis (controls), or with moderate to severe acute coronary artery stenosis underwent MRI and PET imaging at rest and during dipyridamole vasodilation or dobutamine stress to induce a wide range of changes in cardiac perfusion and oxygenation. MRI first-pass perfusion imaging was performed to quantify myocardial blood flow (MBF) and volume (MBV). The MRI blood-oxygen-level-dependent (BOLD) technique was used to determine the myocardial oxygen extraction fraction (OEF) during pharmacologic hyperemia. Myocardial oxygen consumption (MVO2) was determined by Fick’s law. In the same dogs, 15O-water and 11C-acetate were used to measure MBF and MVO2, respectively, by PET. Regional assessments were performed for both MR and PET. MRI data correlated nicely with PET values for MBF (R2 = 0.79, P < 0.001), MVO2 (R2 = 0.74, P < 0.001), and OEF (R2 = 0.66, P < 0.01). Conclusions Cardiac MRI methods may provide an alternative to radionuclide imaging in settings of myocardial ischemia. Our newly developed quantitative MRI oxygenation imaging technique may be a valuable non-invasive tool to directly evaluate myocardial energetics and efficiency. PMID:19933371

Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

PubMed

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D

2007-06-01

Independent component analysis (ICA) is a popular blind source separation technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist; however, the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely, information maximization, maximization of non-Gaussianity, joint diagonalization of cross-cumulant matrices and second-order correlation-based methods, when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study variability among different ICA algorithms, and we propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA and joint approximate diagonalization of eigenmatrices (JADE) all yield reliable results, with each having its strengths in specific areas. Eigenvalue decomposition (EVD), an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for iterative ICA algorithms, it is important to investigate the variability of estimates from different runs. We test the consistency of the iterative algorithms Infomax and FastICA by running the algorithm a number of times with different initializations, and we note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis.

MR guided breast interventions: role in biopsy targeting and lumpectomies

PubMed Central

Jagadeesan, Jayender; Richman, Danielle M; Kacher, Daniel F

2015-01-01

Synopsis Contrast enhanced breast MRI is increasingly being used to diagnose breast cancer and to perform biopsy procedures. The American Cancer Society has advised women at high risk for breast cancer to have breast MRI screening as an adjunct to screening mammography. This article places special emphasis on biopsy and operative planning involving MRI and reviews utility of breast MRI in monitoring response to neoadjuvant chemotherapy. We describe peer-reviewed data on currently accepted MR-guided therapeutic methods for addressing benign and malignant breast diseases, including intraoperative imaging. PMID:26499274

A Cinematic Magnetic Resonance Imaging Study of Milk of Magnesia Laxative and an Antiflatulent Diet to Reduce Intrafraction Prostate Motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichol, Alan M.; Warde, Padraig R.; Lockwood, Gina A.

Purpose: To determine the reduction of prostate motion during a typical radiotherapy (RT) fraction from a bowel regimen comprising an antiflatulent diet and daily milk of magnesia. Methods and Materials: Forty-two patients with T1c-T2c prostate cancer voided the bladder and rectum before three cinematic magnetic resonance imaging scans obtained every 9 s for 9 min in a vacuum immobilization device. The MRIs were at baseline without bowel regimen (MRI-BL), before CT planning with bowel regimen (MRI-CT), and before a randomly assigned RT fraction (1-42) with bowel regimen (MRI-RT). A single observer tracked displacement of the posterior midpoint (PM) of themore » prostate. The primary endpoints were comparisons of the proportion of time that the PM was displaced >3 mm (PTPM3) from its initial position, and the secondary endpoints were comparisons of the reduction of initial rectal area, with and without the bowel regimen. Results: The mean rectal area was: 13.5 cm{sup 2} at MRI-BL, 12.7 cm{sup 2} at MRI-CT, and 12.3 cm{sup 2} at MRI-RT (MRI-BL vs. MRI-CT, p = 0.11; MRI-BL vs. MRI-CT, p = 0.07). Moving rectal gas alone (56%) and moving gas and stool (18%) caused 74% of intrafraction prostate motion. The PTPM3 was 11.3% at MRI-BL, 4.8% at MRI-CT, and 12.0% at MRI-RT (MRI-BL vs. MRI-CT, p = 0.12; MRI-BL vs. MRI-RT, p = 0.89). Conclusion: For subjects voiding their rectum before imaging, an antiflatulent diet and milk of magnesia laxative did not significantly reduce initial rectal area or intrafraction prostate motion.« less

The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings.

PubMed

Kim, Dong-Youl; Yoo, Seung-Schik; Tegethoff, Marion; Meinlschmidt, Gunther; Lee, Jong-Hwan

2015-08-01

Real-time fMRI (rtfMRI) neurofeedback (NF) facilitates volitional control over brain activity and the modulation of associated mental functions. The NF signals of traditional rtfMRI-NF studies predominantly reflect neuronal activity within ROIs. In this study, we describe a novel rtfMRI-NF approach that includes a functional connectivity (FC) component in the NF signal (FC-added rtfMRI-NF). We estimated the efficacy of the FC-added rtfMRI-NF method by applying it to nicotine-dependent heavy smokers in an effort to reduce cigarette craving. ACC and medial pFC as well as the posterior cingulate cortex and precuneus are associated with cigarette craving and were chosen as ROIs. Fourteen heavy smokers were randomly assigned to receive one of two types of NF: traditional activity-based rtfMRI-NF or FC-added rtfMRI-NF. Participants received rtfMRI-NF training during two separate visits after overnight smoking cessation, and cigarette craving score was assessed. The FC-added rtfMRI-NF resulted in greater neuronal activity and increased FC between the targeted ROIs than the traditional activity-based rtfMRI-NF and resulted in lower craving score. In the FC-added rtfMRI-NF condition, the average of neuronal activity and FC was tightly associated with craving score (Bonferroni-corrected p = .028). However, in the activity-based rtfMRI-NF condition, no association was detected (uncorrected p > .081). Non-rtfMRI data analysis also showed enhanced neuronal activity and FC with FC-added NF than with activity-based NF. These results demonstrate that FC-added rtfMRI-NF facilitates greater volitional control over brain activity and connectivity and greater modulation of mental function than activity-based rtfMRI-NF.

A Window into the Brain: Advances in Psychiatric fMRI

PubMed Central

Zhan, Xiaoyan

2015-01-01

Functional magnetic resonance imaging (fMRI) plays a key role in modern psychiatric research. It provides a means to assay differences in brain systems that underlie psychiatric illness, treatment response, and properties of brain structure and function that convey risk factor for mental diseases. Here we review recent advances in fMRI methods in general use and progress made in understanding the neural basis of mental illness. Drawing on concepts and findings from psychiatric fMRI, we propose that mental illness may not be associated with abnormalities in specific local regions but rather corresponds to variation in the overall organization of functional communication throughout the brain network. Future research may need to integrate neuroimaging information drawn from different analysis methods and delineate spatial and temporal patterns of brain responses that are specific to certain types of psychiatric disorders. PMID:26413531

Registration of 3D ultrasound computer tomography and MRI for evaluation of tissue correspondences

NASA Astrophysics Data System (ADS)

Hopp, T.; Dapp, R.; Zapf, M.; Kretzek, E.; Gemmeke, H.; Ruiter, N. V.

2015-03-01

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

A stereotactic method for image-guided transcranial magnetic stimulation validated with fMRI and motor-evoked potentials.

PubMed

Neggers, S F W; Langerak, T R; Schutter, D J L G; Mandl, R C W; Ramsey, N F; Lemmens, P J J; Postma, A

2004-04-01

Transcranial Magnetic Stimulation (TMS) delivers short magnetic pulses that penetrate the skull unattenuated, disrupting neural processing in a noninvasive, reversible way. To disrupt specific neural processes, coil placement over the proper site is critical. Therefore, a neural navigator (NeNa) was developed. NeNa is a frameless stereotactic device using structural and functional magnetic resonance imaging (fMRI) data to guide TMS coil placement. To coregister the participant's head to his MRI, 3D cursors are moved to anatomical landmarks on a skin rendering of the participants MRI on a screen, and measured at the head with a position measurement device. A method is proposed to calculate a rigid body transformation that can coregister both sets of coordinates under realistic noise conditions. After coregistration, NeNa visualizes in real time where the device is located with respect to the head, brain structures, and activated areas, enabling precise placement of the TMS coil over a predefined target region. NeNa was validated by stimulating 5 x 5 positions around the 'motor hotspot' (thumb movement area), which was marked on the scalp guided by individual fMRI data, while recording motor-evoked potentials (MEPs) from the abductor pollicis brevis (APB). The distance between the center of gravity (CoG) of MEP responses and the location marked on the scalp overlying maximum fMRI activation was on average less then 5 mm. The present results demonstrate that NeNa is a reliable method for image-guided TMS coil placement.

MR to CT registration of brains using image synthesis

NASA Astrophysics Data System (ADS)

Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

2014-03-01

Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

Optimization of flow-sensitive alternating inversion recovery (FAIR) for perfusion functional MRI of rodent brain.

PubMed

Nasrallah, Fatima A; Lee, Eugene L Q; Chuang, Kai-Hsiang

2012-11-01

Arterial spin labeling (ASL) MRI provides a noninvasive method to image perfusion, and has been applied to map neural activation in the brain. Although pulsed labeling methods have been widely used in humans, continuous ASL with a dedicated neck labeling coil is still the preferred method in rodent brain functional MRI (fMRI) to maximize the sensitivity and allow multislice acquisition. However, the additional hardware is not readily available and hence its application is limited. In this study, flow-sensitive alternating inversion recovery (FAIR) pulsed ASL was optimized for fMRI of rat brain. A practical challenge of FAIR is the suboptimal global inversion by the transmit coil of limited dimensions, which results in low effective labeling. By using a large volume transmit coil and proper positioning to optimize the body coverage, the perfusion signal was increased by 38.3% compared with positioning the brain at the isocenter. An additional 53.3% gain in signal was achieved using optimized repetition and inversion times compared with a long TR. Under electrical stimulation to the forepaws, a perfusion activation signal change of 63.7 ± 6.3% can be reliably detected in the primary somatosensory cortices using single slice or multislice echo planar imaging at 9.4 T. This demonstrates the potential of using pulsed ASL for multislice perfusion fMRI in functional and pharmacological applications in rat brain. Copyright © 2012 John Wiley & Sons, Ltd.

Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: Block LOw-rank Sparsity with Motion-guidance (BLOSM)

PubMed Central

Chen, Xiao; Salerno, Michael; Yang, Yang; Epstein, Frederick H.

2014-01-01

Purpose Dynamic contrast-enhanced MRI of the heart is well-suited for acceleration with compressed sensing (CS) due to its spatiotemporal sparsity; however, respiratory motion can degrade sparsity and lead to image artifacts. We sought to develop a motion-compensated CS method for this application. Methods A new method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was developed to accelerate first-pass cardiac MRI, even in the presence of respiratory motion. This method divides the images into regions, tracks the regions through time, and applies matrix low-rank sparsity to the tracked regions. BLOSM was evaluated using computer simulations and first-pass cardiac datasets from human subjects. Using rate-4 acceleration, BLOSM was compared to other CS methods such as k-t SLR that employs matrix low-rank sparsity applied to the whole image dataset, with and without motion tracking, and to k-t FOCUSS with motion estimation and compensation that employs spatial and temporal-frequency sparsity. Results BLOSM was qualitatively shown to reduce respiratory artifact compared to other methods. Quantitatively, using root mean squared error and the structural similarity index, BLOSM was superior to other methods. Conclusion BLOSM, which exploits regional low rank structure and uses region tracking for motion compensation, provides improved image quality for CS-accelerated first-pass cardiac MRI. PMID:24243528

Free Radical Imaging Using In Vivo Dynamic Nuclear Polarization-MRI.

PubMed

Utsumi, Hideo; Hyodo, Fuminori

2015-01-01

Redox reactions that generate free radical intermediates are essential to metabolic processes, and their intermediates can produce reactive oxygen species, which may promote diseases related to oxidative stress. The development of an in vivo electron spin resonance (ESR) spectrometer and its imaging enables us noninvasive and direct measurement of in vivo free radical reactions in living organisms. The dynamic nuclear polarization magnetic resonance imaging (DNP-MRI), also called PEDRI or OMRI, is also a new imaging method for observing free radical species in vivo. The spatiotemporal resolution of free radical imaging with DNP-MRI is comparable with that in MRI, and each of the radical species can be distinguished in the spectroscopic images by changing the frequency or magnetic field of ESR irradiation. Several kinds of stable nitroxyl radicals were used as spin probes to detect in vivo redox reactions. The signal decay of nitroxyl probes, which is determined with in vivo DNP-MRI, reflects the redox status under oxidative stress, and the signal decay is suppressed by prior administration of antioxidants. In addition, DNP-MRI can also visualize various intermediate free radicals from the intrinsic redox molecules. This noninvasive method, in vivo DNP-MRI, could become a useful tool for investigating the mechanism of oxidative injuries in animal disease models and the in vivo effects of antioxidant drugs. © 2015 Elsevier Inc. All rights reserved.

Ventilation distribution in rats: Part 2 – A comparison of electrical impedance tomography and hyperpolarised helium magnetic resonance imaging

PubMed Central

2012-01-01

Background Hyperpolarised helium MRI (He3 MRI) is a new technique that enables imaging of the air distribution within the lungs. This allows accurate determination of the ventilation distribution in vivo. The technique has the disadvantages of requiring an expensive helium isotope, complex apparatus and moving the patient to a compatible MRI scanner. Electrical impedance tomography (EIT) a non-invasive bedside technique that allows constant monitoring of lung impedance, which is dependent on changes in air space capacity in the lung. We have used He3MRI measurements of ventilation distribution as the gold standard for assessment of EIT. Methods Seven rats were ventilated in supine, prone, left and right lateral position with 70% helium/30% oxygen for EIT measurements and pure helium for He3 MRI. The same ventilator and settings were used for both measurements. Image dimensions, geometric centre and global in homogeneity index were calculated. Results EIT images were smaller and of lower resolution and contained less anatomical detail than those from He3 MRI. However, both methods could measure positional induced changes in lung ventilation, as assessed by the geometric centre. The global in homogeneity index were comparable between the techniques. Conclusion EIT is a suitable technique for monitoring ventilation distribution and inhomgeneity as assessed by comparison with He3 MRI. PMID:22966835

A networked modular hardware and software system for MRI-guided robotic prostate interventions

NASA Astrophysics Data System (ADS)

Su, Hao; Shang, Weijian; Harrington, Kevin; Camilo, Alex; Cole, Gregory; Tokuda, Junichi; Hata, Nobuhiko; Tempany, Clare; Fischer, Gregory S.

2012-02-01

Magnetic resonance imaging (MRI) provides high resolution multi-parametric imaging, large soft tissue contrast, and interactive image updates making it an ideal modality for diagnosing prostate cancer and guiding surgical tools. Despite a substantial armamentarium of apparatuses and systems has been developed to assist surgical diagnosis and therapy for MRI-guided procedures over last decade, the unified method to develop high fidelity robotic systems in terms of accuracy, dynamic performance, size, robustness and modularity, to work inside close-bore MRI scanner still remains a challenge. In this work, we develop and evaluate an integrated modular hardware and software system to support the surgical workflow of intra-operative MRI, with percutaneous prostate intervention as an illustrative case. Specifically, the distinct apparatuses and methods include: 1) a robot controller system for precision closed loop control of piezoelectric motors, 2) a robot control interface software that connects the 3D Slicer navigation software and the robot controller to exchange robot commands and coordinates using the OpenIGTLink open network communication protocol, and 3) MRI scan plane alignment to the planned path and imaging of the needle as it is inserted into the target location. A preliminary experiment with ex-vivo phantom validates the system workflow, MRI-compatibility and shows that the robotic system has a better than 0.01mm positioning accuracy.

Conventional digital subtractional vs non-invasive MR angiography in the assessment of brain arteriovenous malformation.

PubMed

Cuong, Nguyen Ngoc; Luu, Vu Dang; Tuan, Tran Anh; Linh, Le Tuan; Hung, Kieu Dinh; Ngoc, Vo Truong Nhu; Sharma, Kulbhushan; Pham, Van Huy; Chu, Dinh-Toi

2018-06-01

Digital subtractional angiography (DSA) is the standard method for diagnosis, assessment and management of arteriovenous malformation in the brain. Conventional DSA (cDSA) is an invasive imaging modality that is often indicated before interventional treatments (embolization, open surgery, gamma knife). Here, we aimed to compare this technique with a non-invasive MR angiography (MRI DSA) for brain arteriovenous malformation (bAVM). Fourteen patients with ruptured brain AVM underwent embolization treatment pre-operation. Imaging was performed for all patients using MRI (1.5 T). After injecting contrast Gadolinium, dynamic MRI was performed with 40 phases, each phase of a duration of 1.2 s and having 70 images. The MRI results were independently assessed by experienced radiologist blinded to the cDSA. The AVM nidus was depicted in all patients using cDSA and MRI DSA; there was an excellent correlation between these techniques in terms of the maximum diameter and Spetzler Martin grading. Of the fourteen patients, the drainage vein was depicted in 13 by both cDSA and MRI DSA showing excellent correlation between the techniques used. MRI DSA is a non-invasive imaging modality that can give the images in dynamic view. It can be considered as an adjunctive method with cDSA to plan the strategy treatment for bAVM. Copyright © 2018 Elsevier B.V. All rights reserved.

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating the need for multi-modality comparisons which are inherently more challenging. Deformable registrations generated in this work significantly outperformed rigid alignments. Research reported in this abstract was supported by the NIH National Cancer Institute R21CA153826 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer” and Bankhead-Coley Cancer Research Program 10BT-03 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer”.« less

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

Inverse-consistent rigid registration of CT and MR for MR-based planning and adaptive prostate radiation therapy

NASA Astrophysics Data System (ADS)

Rivest-Hénault, David; Dowson, Nicholas; Greer, Peter; Dowling, Jason

2014-03-01

MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10--3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10--3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods.

Methods of the pharmacological imaging of the cannabinoid system (PhICS) study: towards understanding the role of the brain endocannabinoid system in human cognition.

PubMed

van Hell, Hendrika H; Bossong, Matthijs G; Jager, Gerry; Kahn, René S; Ramsey, Nick F

2011-03-01

Various lines of (pre)clinical research indicate that cannabinoid agents carry the potential for therapeutic application to reduce symptoms in several psychiatric disorders. However, direct testing of the involvement of cannabinoid brain systems in psychiatric syndromes is essential for further development. In the Pharmacological Imaging of the Cannabinoid System (PhICS) study, the involvement of the endocannabinoid system in cognitive brain function is assessed by comparing acute effects of the cannabinoid agonist Δ9-tetrahydrocannabinol (THC) on brain function between healthy controls and groups of psychiatric patients showing cognitive dysfunction. This article describes the objectives and methods of the PhICS study and presents preliminary results of the administration procedure on subjective and neurophysiological parameters. Core elements in the methodology of PhICS are the administration method (THC is administered by inhalation using a vaporizing device) and a comprehensive use of pharmacological magnetic resonance imaging (phMRI) combining several types of MRI scans including functional MRI (fMRI), Arterial Spin Labeling (ASL) to measure brain perfusion, and resting-state fMRI. Additional methods like neuropsychological testing further specify the exact role of the endocannabinoid system in regulating cognition. Preliminary results presented in this paper indicate robust behavioral and subjective effects of THC. In addition, fMRI paradigms demonstrate activation of expected networks of brain regions in the cognitive domains of interest. The presented administration and assessment protocol provides a basis for further research on the involvement of the endocannabionoid systems in behavior and in psychopathology, which in turn may lead to development of therapeutic opportunities of cannabinoid ligands. Copyright © 2011 John Wiley & Sons, Ltd.

Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight-channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built-in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1-weighted and T2-weighted images was well-controlled in the isocenter and 10 cm off-center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

PubMed

Glasser, Matthew F; Coalson, Timothy S; Bijsterbosch, Janine D; Harrison, Samuel J; Harms, Michael P; Anticevic, Alan; Van Essen, David C; Smith, Stephen M

2018-06-02

Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data. Copyright © 2018 Elsevier Inc. All rights reserved.

Differentiating between benign and malignant sinonasal lesions using dynamic contrast-enhanced MRI and intravoxel incoherent motion.

PubMed

Jiang, Jingxuan; Xiao, Zebin; Tang, Zuohua; Zhong, Yufeng; Qiang, Jinwei

2018-01-01

To explore the value of dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant sinonasal lesions and investigate the correlations between the two methods. Patients with sinonasal lesions (42 benign and 31 malignant) who underwent DCE-MRI and IVIM before confirmation by histopathology were enrolled in this prospective study. Parameters derived from DCE-MRI and IVIM were measured, the optimal cut-off values for differential diagnosis were determined, and the correlations between the two methods were evaluated. Statistical analyses were performed using the Wilcoxon rank sum test, receiver operating characteristic (ROC) curve analysis, and Spearman's rank correlation. Significantly higher K trans and K ep values but lower D and f values were found in malignant lesions than in benign lesions (all p<0.001). There were no significant differences in the V e and D* values between the two groups. The area under the curve (AUC) of K trans was significantly higher than those of other parameters. There was no significant difference between the AUCs of DCE-MRI and IVIM with parameters combined (p=0.86). Significant inverse but weak correlations were found between D and K trans (r=-0.46, p<0.001), f and K trans (r=-0.41, p<0.001), D and K ep (r=-0.37, p=0.008), and f and K ep (r=-0.33, p=0.004). DCE-MRI and IVIM can effectively differentiate between benign and malignant sinonasal lesions. IVIM findings correlate with DCE-MRI results and may represent an alternative to DCE-MRI. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of liver fat content as determined by magnetic resonance imaging-proton density fat fraction and MRS versus liver histology in non-alcoholic fatty liver disease.

PubMed

Idilman, Ilkay S; Keskin, Onur; Celik, Azim; Savas, Berna; Elhan, Atilla Halil; Idilman, Ramazan; Karcaaltincaba, Musturay

2016-03-01

Many imaging methods have been defined for quantification of hepatic steatosis in non-alcoholic fatty liver disease (NAFLD). However, studies comparing the efficiency of magnetic resonance imaging-proton density fat fraction (MRI-PDFF), magnetic resonance spectroscopy (MRS), and liver histology for quantification of liver fat content are limited. To compare the efficiency of MRI-PDFF and MRS in the quantification of liver fat content in individuals with NAFLD. A total of 19 NAFLD patients underwent MRI-PDFF, MRS, and liver biopsy for quantification of liver fat content. The MR examinations were performed on a 1.5 HDx MRI system. The MRI protocol included T1-independent volumetric multi-echo gradient-echo imaging with T2* correction and spectral fat modeling and MRS with STEAM technique. A close correlation was observed between liver MRI-PDFF- and histology- determined steatosis (r = 0.743, P < 0.001) and between liver MRS- and histology-determined steatosis (r = 0.712, P < 0.001), with no superiority between them (ƶ = 0.19, P = 0.849). For quantification of hepatic steatosis, a high correlation was observed between the two MRI methods (r = 0.986, P < 0.001). MRI-PDFF and MRS accurately differentiated moderate/severe steatosis from mild/no hepatic steatosis (P = 0.007 and 0.013, respectively), with no superiority between them (AUCMRI-PDFF = 0.881 ± 0.0856 versus AUCMRS = 0.857 ± 0.0924, P = 0.461). Both MRI-PDFF and MRS can be used for accurate quantification of hepatic steatosis. © The Foundation Acta Radiologica 2015.

Digital photography and 3D MRI-based multimodal imaging for individualized planning of resective neocortical epilepsy surgery.

PubMed

Wellmer, Jörg; von Oertzen, Joachim; Schaller, Carlo; Urbach, Horst; König, Roy; Widman, Guido; Van Roost, Dirk; Elger, Christian E

2002-12-01

Invasive presurgical work up of pharmacoresistant epilepsies presumes integration of multiple diagnostic modalities into a comprehensive picture of seizure onset and eloquent brain areas. During resection, reliable transfer of evaluation results to the patient's individual anatomy must be made. We investigated the value of digital photography-based grid localization in combination with preoperative three-dimensional (3D) magnetic resonance imaging (MRI) for clinical routine. Digital photographs of the exposed cortex were taken before and after grid placement. Location of electrode contacts on the cortex was identified and schematically indicated on native cortex prints. Accordingly, transfer of contact positions to a 3D MRI brain-surface rendering was carried out manually by using the rendering software. Results of the electrophysiologic evaluation were transferred to either electrode contact reproduction and co-registered with imaging-based techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), and functional MRI (fMRI). Digital photography allows precise and highly realistic documentation of electrode contact positions on the individual neocortical surface. Lesions underneath grids can be highlighted by semitransparent MRI surface rendering, and lobar boundaries can be identified. Because of integrating electrode contact positions into the postprocessed 3D MRI data set, imaging-based techniques can be codisplayed with the results of the electrophysiologic evaluation. Comparison with CT/MRI co-registration showed good accuracy of the method. However, grids not sewn to the dura at implantation can become subject to significant displacement. Digital photography in combination with preimplantation 3D MRI allows the generation of reliable tailored resection plans in neocortical epilepsy surgery. The method enhances surgical safety and confidence.

WE-EF-BRD-04: MR in the OR: The Growth and Applications of MRI for Interventional Radiology and Surgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fahrig, R.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

WE-EF-BRD-02: Battling Maxwell’s Equations: Physics Challenges and Solutions for Hybrid MRI Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keall, P.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

WE-EF-BRD-01: Past, Present and Future: MRI-Guided Radiotherapy From 2005 to 2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lagendijk, J.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

The role of fMRI in cognitive neuroscience: where do we stand?

PubMed

Poldrack, Russell A

2008-04-01

Functional magnetic resonance imaging (fMRI) has quickly become the most prominent tool in cognitive neuroscience. In this article, I outline some of the limits on the kinds of inferences that can be supported by fMRI, focusing particularly on reverse inference, in which the engagement of specific mental processes is inferred from patterns of brain activation. Although this form of inference is weak, newly developed methods from the field of machine learning offer the potential to formalize and strengthen reverse inferences. I conclude by discussing the increasing presence of fMRI results in the popular media and the ethical implications of the increasing predictive power of fMRI.

Cost Analysis of MRI Services in Iran: An Application of Activity Based Costing Technique.

PubMed

Bayati, Mohsen; Mahboub Ahari, Alireza; Badakhshan, Abbas; Gholipour, Mahin; Joulaei, Hassan

2015-10-01

Considerable development of MRI technology in diagnostic imaging, high cost of MRI technology and controversial issues concerning official charges (tariffs) have been the main motivations to define and implement this study. The present study aimed to calculate the unit-cost of MRI services using activity-based costing (ABC) as a modern cost accounting system and to fairly compare calculated unit-costs with official charges (tariffs). We included both direct and indirect costs of MRI services delivered in fiscal year 2011 in Shiraz Shahid Faghihi hospital. Direct allocation method was used for distribution of overhead costs. We used micro-costing approach to calculate unit-cost of all different MRI services. Clinical cost data were retrieved from the hospital registering system. Straight-line method was used for depreciation cost estimation. To cope with uncertainty and to increase the robustness of study results, unit costs of 33 MRI services was calculated in terms of two scenarios. Total annual cost of MRI activity center (AC) was calculated at USD 400,746 and USD 532,104 based on first and second scenarios, respectively. Ten percent of the total cost was allocated from supportive departments. The annual variable costs of MRI center were calculated at USD 295,904. Capital costs measured at USD 104,842 and USD 236, 200 resulted from the first and second scenario, respectively. Existing tariffs for more than half of MRI services were above the calculated costs. As a public hospital, there are considerable limitations in both financial and administrative databases of Shahid Faghihi hospital. Labor cost has the greatest share of total annual cost of Shahid Faghihi hospital. The gap between unit costs and tariffs implies that the claim for extra budget from health providers may not be relevant for all services delivered by the studied MRI center. With some adjustments, ABC could be implemented in MRI centers. With the settlement of a reliable cost accounting system such as ABC technique, hospitals would be able to generate robust evidences for financial management of their overhead, intermediate and final ACs.

Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

PubMed Central

Wang, Hai-yi; Su, Zi-hua; Xu, Xiao; Sun, Zhi-peng; Duan, Fei-xue; Song, Yuan-yuan; Li, Lu; Wang, Ying-wei; Ma, Xin; Guo, Ai-tao; Ma, Lin; Ye, Hui-yi

2016-01-01

Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K trans & Ve) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters. PMID:27380733

Upsampling to 400-ms Resolution for Assessing Effective Connectivity in Functional Magnetic Resonance Imaging Data with Granger Causality

PubMed Central

Kerr, Deborah L.; Nitschke, Jack B.

2013-01-01

Abstract Granger causality analysis of functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent signal data allows one to infer the direction and magnitude of influence that brain regions exert on one another. We employed a method for upsampling the time resolution of fMRI data that does not require additional interpolation beyond the interpolation that is regularly used for slice-timing correction. The mathematics for this new method are provided, and simulations demonstrate its viability. Using fMRI, 17 snake phobics and 19 healthy controls viewed snake, disgust, and neutral fish video clips preceded by anticipatory cues. Multivariate Granger causality models at the native 2-sec resolution and at the upsampled 400-ms resolution assessed directional associations of fMRI data among 13 anatomical regions of interest identified in prior research on anxiety and emotion. Superior sensitivity was observed for the 400-ms model, both for connectivity within each group and for group differences in connectivity. Context-dependent analyses for the 400-ms multivariate Granger causality model revealed the specific trial types showing group differences in connectivity. This is the first demonstration of effective connectivity of fMRI data using a method for achieving 400-ms resolution without sacrificing accuracy available at 2-sec resolution. PMID:23134194

Quantification of tumor mobility during the breathing cycle using 3D dynamic MRI

NASA Astrophysics Data System (ADS)

Schoebinger, Max; Plathow, Christian; Wolf, Ivo; Kauczor, Hans-Ulrich; Meinzer, Hans-Peter

2006-03-01

Respiration causes movement and shape changes in thoracic tumors, which has a direct influence on the radio-therapy planning process. Current methods for the estimation of tumor mobility are either two-dimensional (fluoroscopy, 2D dynamic MRI) or based on radiation (3D (+t) CT, implanted gold markers). With current advances in dynamic MRI acquisition, 3D+t image sequences of the thorax can be acquired covering the thorax over the whole breathing cycle. In this work, methods are presented for the interactive segmentation of tumors in dynamic images, the calculation of tumor trajectories, dynamic tumor volumetry and dynamic tumor rotation/deformation based on 3D dynamic MRI. For volumetry calculation, a set of 21 related partial volume correcting volumetry algorithms has been evaluated based on tumor surrogates. Conventional volumetry based on voxel counting yielded a root mean square error of 29% compared to a root mean square error of 11% achieved by the algorithm performing best among the different volumetry methods. The new workflow has been applied to a set of 26 patients. Preliminary results indicate, that 3D dynamic MRI reveals important aspects of tumor behavior during the breathing cycle. This might imply the possibility to further improve high-precision radiotherapy techniques.

[MRI methods for pulmonary ventilation and perfusion imaging].

PubMed

Sommer, G; Bauman, G

2016-02-01

Separate assessment of respiratory mechanics, gas exchange and pulmonary circulation is essential for the diagnosis and therapy of pulmonary diseases. Due to the global character of the information obtained clinical lung function tests are often not sufficiently specific in the differential diagnosis or have a limited sensitivity in the detection of early pathological changes. The standard procedures of pulmonary imaging are computed tomography (CT) for depiction of the morphology as well as perfusion/ventilation scintigraphy and single photon emission computed tomography (SPECT) for functional assessment. Magnetic resonance imaging (MRI) with hyperpolarized gases, O2-enhanced MRI, MRI with fluorinated gases and Fourier decomposition MRI (FD-MRI) are available for assessment of pulmonary ventilation. For assessment of pulmonary perfusion dynamic contrast-enhanced MRI (DCE-MRI), arterial spin labeling (ASL) and FD-MRI can be used. Imaging provides a more precise insight into the pathophysiology of pulmonary function on a regional level. The advantages of MRI are a lack of ionizing radiation, which allows a protective acquisition of dynamic data as well as the high number of available contrasts and therefore accessible lung function parameters. Sufficient clinical data exist only for certain applications of DCE-MRI. For the other techniques, only feasibility studies and case series of different sizes are available. The clinical applicability of hyperpolarized gases is limited for technical reasons. The clinical application of the techniques described, except for DCE-MRI, should be restricted to scientific studies.

Magnetic resonance imaging: a tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation.

PubMed

Scott, William E; Weegman, Bradley P; Balamurugan, Appakalai N; Ferrer-Fabrega, Joana; Anazawa, Takayuki; Karatzas, Theodore; Jie, Tun; Hammer, Bruce E; Matsumoto, Shuchiro; Avgoustiniatos, Efstathios S; Maynard, Kristen S; Sutherland, David E R; Hering, Bernhard J; Papas, Klearchos K

2014-01-01

Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost-effectiveness of this approach. Incomplete pancreas distention and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of magnetic resonance imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18-g winged catheter and MRI performed at 1.5-T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distention were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distention of identified problem regions) resolved these issues, and MRI was successfully utilized as a guide and assessment tool for improved delivery. Current methods of porcine pancreas distention do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distention and enzyme delivery. © 2014 John Wiley & Sons A/S Published by John Wiley & Sons Ltd.

Brain Volume Estimation Enhancement by Morphological Image Processing Tools.

PubMed

Zeinali, R; Keshtkar, A; Zamani, A; Gharehaghaji, N

2017-12-01

Volume estimation of brain is important for many neurological applications. It is necessary in measuring brain growth and changes in brain in normal/abnormal patients. Thus, accurate brain volume measurement is very important. Magnetic resonance imaging (MRI) is the method of choice for volume quantification due to excellent levels of image resolution and between-tissue contrast. Stereology method is a good method for estimating volume but it requires to segment enough MRI slices and have a good resolution. In this study, it is desired to enhance stereology method for volume estimation of brain using less MRI slices with less resolution. In this study, a program for calculating volume using stereology method has been introduced. After morphologic method, dilation was applied and the stereology method enhanced. For the evaluation of this method, we used T1-wighted MR images from digital phantom in BrainWeb which had ground truth. The volume of 20 normal brain extracted from BrainWeb, was calculated. The volumes of white matter, gray matter and cerebrospinal fluid with given dimension were estimated correctly. Volume calculation from Stereology method in different cases was made. In three cases, Root Mean Square Error (RMSE) was measured. Case I with T=5, d=5, Case II with T=10, D=10 and Case III with T=20, d=20 (T=slice thickness, d=resolution as stereology parameters). By comparing these results of two methods, it is obvious that RMSE values for our proposed method are smaller than Stereology method. Using morphological operation, dilation allows to enhance the estimation volume method, Stereology. In the case with less MRI slices and less test points, this method works much better compared to Stereology method.

Clustering-Constrained ICA for Ballistocardiogram Artifacts Removal in Simultaneous EEG-fMRI

PubMed Central

Wang, Kai; Li, Wenjie; Dong, Li; Zou, Ling; Wang, Changming

2018-01-01

Combination of electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) plays a potential role in neuroimaging due to its high spatial and temporal resolution. However, EEG is easily influenced by ballistocardiogram (BCG) artifacts and may cause false identification of the related EEG features, such as epileptic spikes. There are many related methods to remove them, however, they do not consider the time-varying features of BCG artifacts. In this paper, a novel method using clustering algorithm to catch the BCG artifacts' features and together with the constrained ICA (ccICA) is proposed to remove the BCG artifacts. We first applied this method to the simulated data, which was constructed by adding the BCG artifacts to the EEG signal obtained from the conventional environment. Then, our method was tested to demonstrate the effectiveness during EEG and fMRI experiments on 10 healthy subjects. In simulated data analysis, the value of error in signal amplitude (Er) computed by ccICA method was lower than those from other methods including AAS, OBS, and cICA (p < 0.005). In vivo data analysis, the Improvement of Normalized Power Spectrum (INPS) calculated by ccICA method in all electrodes was much higher than AAS, OBS, and cICA methods (p < 0.005). We also used other evaluation index (e.g., power analysis) to compare our method with other traditional methods. In conclusion, our novel method successfully and effectively removed BCG artifacts in both simulated and vivo EEG data tests, showing the potentials of removing artifacts in EEG-fMRI applications. PMID:29487499

A variational image-based approach to the correction of susceptibility artifacts in the alignment of diffusion weighted and structural MRI.

PubMed

Tao, Ran; Fletcher, P Thomas; Gerber, Samuel; Whitaker, Ross T

2009-01-01

This paper presents a method for correcting the geometric and greyscale distortions in diffusion-weighted MRI that result from inhomogeneities in the static magnetic field. These inhomogeneities may due to imperfections in the magnet or to spatial variations in the magnetic susceptibility of the object being imaged--so called susceptibility artifacts. Echo-planar imaging (EPI), used in virtually all diffusion weighted acquisition protocols, assumes a homogeneous static field, which generally does not hold for head MRI. The resulting distortions are significant, sometimes more than ten millimeters. These artifacts impede accurate alignment of diffusion images with structural MRI, and are generally considered an obstacle to the joint analysis of connectivity and structure in head MRI. In principle, susceptibility artifacts can be corrected by acquiring (and applying) a field map. However, as shown in the literature and demonstrated in this paper, field map corrections of susceptibility artifacts are not entirely accurate and reliable, and thus field maps do not produce reliable alignment of EPIs with corresponding structural images. This paper presents a new, image-based method for correcting susceptibility artifacts. The method relies on a variational formulation of the match between an EPI baseline image and a corresponding T2-weighted structural image but also specifically accounts for the physics of susceptibility artifacts. We derive a set of partial differential equations associated with the optimization, describe the numerical methods for solving these equations, and present results that demonstrate the effectiveness of the proposed method compared with field-map correction.

There's more than one way to scan a cat: imaging cat auditory cortex with high-field fMRI using continuous or sparse sampling.

PubMed

Hall, Amee J; Brown, Trecia A; Grahn, Jessica A; Gati, Joseph S; Nixon, Pam L; Hughes, Sarah M; Menon, Ravi S; Lomber, Stephen G

2014-03-15

When conducting auditory investigations using functional magnetic resonance imaging (fMRI), there are inherent potential confounds that need to be considered. Traditional continuous fMRI acquisition methods produce sounds >90 dB which compete with stimuli or produce neural activation masking evoked activity. Sparse scanning methods insert a period of reduced MRI-related noise, between image acquisitions, in which a stimulus can be presented without competition. In this study, we compared sparse and continuous scanning methods to identify the optimal approach to investigate acoustically evoked cortical, thalamic and midbrain activity in the cat. Using a 7 T magnet, we presented broadband noise, 10 kHz tones, or 0.5 kHz tones in a block design, interleaved with blocks in which no stimulus was presented. Continuous scanning resulted in larger clusters of activation and more peak voxels within the auditory cortex. However, no significant activation was observed within the thalamus. Also, there was no significant difference found, between continuous or sparse scanning, in activations of midbrain structures. Higher magnitude activations were identified in auditory cortex compared to the midbrain using both continuous and sparse scanning. These results indicate that continuous scanning is the preferred method for investigations of auditory cortex in the cat using fMRI. Also, choice of method for future investigations of midbrain activity should be driven by other experimental factors, such as stimulus intensity and task performance during scanning. Copyright © 2014 Elsevier B.V. All rights reserved.

A Metal-Free Method for Producing MRI Contrast at Amyloid-Beta

PubMed Central

Hilt, Silvia; Tang, Tang; Walton, Jeffrey H.; Budamagunta, Madhu; Maezawa, Izumi; Kálai, Tamás; Hideg, Kálmán; Singh, Vikrant; Wulff, Heike; Gong, Qizhi; Jin, Lee-Way; Louie, Angelique; Voss, John C.

2017-01-01

Alzheimer’s disease (AD) is characterized by depositions of the amyloid-β (Aβ) peptide in the brain. The disease process develops over decades, with substantial neurological loss occurring before a clinical diagnosis of dementia can be rendered. It is therefore imperative to develop methods that permit early detection and monitoring of disease progression. In addition, the multifactorial pathogenesis of AD has identified several potential avenues for AD intervention. Thus, evaluation of therapeutic candidates over lengthy trial periods also demands a practical, noninvasive method for measuring Aβ in the brain. Magnetic resonance imaging (MRI) is the obvious choice for such measurements, but contrast enhancement for Aβ has only been achieved using Gd(III)-based agents. There is great interest in gadolinium-free methods to image the brain. In this study, we provide the first demonstration that a nitroxide-based small-molecule produces MRI contrast in brain specimens with elevated levels of Aβ. The molecule is comprised of a fluorene (a molecule with high affinity for Aβ) and a nitroxide spin label (a paramagnetic MRI contrast species). Labeling of brain specimens with the spin-labeled fluorene produces negative contrast in samples from AD model mice whereas no negative contrast is seen in specimens harvested from wild-type mice. Injection of SLF into live mice resulted in good brain penetration, with the compound able to generate contrast 24-hr post injection. These results provide a proof of concept method that can be used for early, noninvasive, gadolinium-free detection of amyloid plaques by magnetic resonance imaging (MRI). PMID:27911291

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

PubMed Central

Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

PubMed

Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

Creatine ( methyl-d3) dilution in urine for estimation of total body skeletal muscle mass: accuracy and variability vs. MRI and DXA.

PubMed

Clark, Richard V; Walker, Ann C; Miller, Ram R; O'Connor-Semmes, Robin L; Ravussin, Eric; Cefalu, William T

2018-01-01

A noninvasive method to estimate muscle mass based on creatine ( methyl-d 3 ) (D 3 -creatine) dilution using fasting morning urine was evaluated for accuracy and variability over a 3- to 4-mo period. Healthy older (67- to 80-yr-old) subjects ( n = 14) with muscle wasting secondary to aging and four patients with chronic disease (58-76 yr old) fasted overnight and then received an oral 30-mg dose of D 3 -creatine at 8 AM ( day 1). Urine was collected during 4 h of continued fasting and then at consecutive 4- to 8-h intervals through day 5. Assessment was repeated 3-4 mo later in 13 healthy subjects and 1 patient with congestive heart failure. Deuterated and unlabeled creatine and creatinine were measured using liquid chromatography-tandem mass spectrometry. Total body creatine pool size and muscle mass were calculated from D 3 -creatinine enrichment in urine. Muscle mass was also measured by whole body MRI and 24-h urine creatinine, and lean body mass (LBM) was measured by dual-energy X-ray absorptiometry (DXA). D 3 -creatinine urinary enrichment from day 5 provided muscle mass estimates that correlated with MRI for all subjects ( r = 0.88, P < 0.0001), with less bias [difference from MRI = -3.00 ± 2.75 (SD) kg] than total LBM assessment by DXA, which overestimated muscle mass vs. MRI (+22.5 ± 3.7 kg). However, intraindividual variability was high with the D 3 -creatine dilution method, with intrasubject SD for estimated muscle mass of 2.5 kg vs. MRI (0.5 kg) and DXA (0.8 kg). This study supports further clinical validation of the D 3 -creatine method for estimating muscle mass. NEW & NOTEWORTHY Measurement of creatine ( methyl-d 3 ) (D 3 -creatine) and D 3 -creatinine excretion in fasted morning urine samples may be a simple, less costly alternative to MRI or dual-energy X-ray absorptiometry (DXA) to calculate total body muscle mass. The D 3 -creatine enrichment method provides estimates of muscle mass that correlate well with MRI, and with less bias than DXA. However, intraindividual variability is high with the D 3 -creatine method. Studies to refine the spot urine sample method for estimation of muscle mass may be warranted.

Automated Segmentation of the Parotid Gland Based on Atlas Registration and Machine Learning: A Longitudinal MRI Study in Head-and-Neck Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaofeng; Wu, Ning; Cheng, Guanghui

Purpose: To develop an automated magnetic resonance imaging (MRI) parotid segmentation method to monitor radiation-induced parotid gland changes in patients after head and neck radiation therapy (RT). Methods and Materials: The proposed method combines the atlas registration method, which captures the global variation of anatomy, with a machine learning technology, which captures the local statistical features, to automatically segment the parotid glands from the MRIs. The segmentation method consists of 3 major steps. First, an atlas (pre-RT MRI and manually contoured parotid gland mask) is built for each patient. A hybrid deformable image registration is used to map the pre-RTmore » MRI to the post-RT MRI, and the transformation is applied to the pre-RT parotid volume. Second, the kernel support vector machine (SVM) is trained with the subject-specific atlas pair consisting of multiple features (intensity, gradient, and others) from the aligned pre-RT MRI and the transformed parotid volume. Third, the well-trained kernel SVM is used to differentiate the parotid from surrounding tissues in the post-RT MRIs by statistically matching multiple texture features. A longitudinal study of 15 patients undergoing head and neck RT was conducted: baseline MRI was acquired prior to RT, and the post-RT MRIs were acquired at 3-, 6-, and 12-month follow-up examinations. The resulting segmentations were compared with the physicians' manual contours. Results: Successful parotid segmentation was achieved for all 15 patients (42 post-RT MRIs). The average percentage of volume differences between the automated segmentations and those of the physicians' manual contours were 7.98% for the left parotid and 8.12% for the right parotid. The average volume overlap was 91.1% ± 1.6% for the left parotid and 90.5% ± 2.4% for the right parotid. The parotid gland volume reduction at follow-up was 25% at 3 months, 27% at 6 months, and 16% at 12 months. Conclusions: We have validated our automated parotid segmentation algorithm in a longitudinal study. This segmentation method may be useful in future studies to address radiation-induced xerostomia in head and neck radiation therapy.« less

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

PubMed

Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

2017-08-15

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an acceleration of four and L+S reconstruction can achieve a brain coverage of 40 slices at 2mm isotropic resolution and 64 x 64 matrix size every 500ms. Copyright © 2017 Elsevier Inc. All rights reserved.

Computed tomography synthesis from magnetic resonance images in the pelvis using multiple random forests and auto-context features

NASA Astrophysics Data System (ADS)

Andreasen, Daniel; Edmund, Jens M.; Zografos, Vasileios; Menze, Bjoern H.; Van Leemput, Koen

2016-03-01

In radiotherapy treatment planning that is only based on magnetic resonance imaging (MRI), the electron density information usually obtained from computed tomography (CT) must be derived from the MRI by synthesizing a so-called pseudo CT (pCT). This is a non-trivial task since MRI intensities are neither uniquely nor quantitatively related to electron density. Typical approaches involve either a classification or regression model requiring specialized MRI sequences to solve intensity ambiguities, or an atlas-based model necessitating multiple registrations between atlases and subject scans. In this work, we explore a machine learning approach for creating a pCT of the pelvic region from conventional MRI sequences without using atlases. We use a random forest provided with information about local texture, edges and spatial features derived from the MRI. This helps to solve intensity ambiguities. Furthermore, we use the concept of auto-context by sequentially training a number of classification forests to create and improve context features, which are finally used to train a regression forest for pCT prediction. We evaluate the pCT quality in terms of the voxel-wise error and the radiologic accuracy as measured by water-equivalent path lengths. We compare the performance of our method against two baseline pCT strategies, which either set all MRI voxels in the subject equal to the CT value of water, or in addition transfer the bone volume from the real CT. We show an improved performance compared to both baseline pCTs suggesting that our method may be useful for MRI-only radiotherapy.

Identifying Lesions on Structural Brain Images-Validation of the Method and Application to Neuropsychological Patients

ERIC Educational Resources Information Center

Stamatakis, E.A.; Tyler, L.K.

2005-01-01

The study of neuropsychological disorders has been greatly facilitated by the localization of brain lesions on MRI scans. Current popular approaches for the assessment of MRI brain scans mostly depend on the successful segmentation of the brain into grey and white matter. These methods cannot be used effectively with large lesions because lesions…

3D geometric split-merge segmentation of brain MRI datasets.

PubMed

Marras, Ioannis; Nikolaidis, Nikolaos; Pitas, Ioannis

2014-05-01

In this paper, a novel method for MRI volume segmentation based on region adaptive splitting and merging is proposed. The method, called Adaptive Geometric Split Merge (AGSM) segmentation, aims at finding complex geometrical shapes that consist of homogeneous geometrical 3D regions. In each volume splitting step, several splitting strategies are examined and the most appropriate is activated. A way to find the maximal homogeneity axis of the volume is also introduced. Along this axis, the volume splitting technique divides the entire volume in a number of large homogeneous 3D regions, while at the same time, it defines more clearly small homogeneous regions within the volume in such a way that they have greater probabilities of survival at the subsequent merging step. Region merging criteria are proposed to this end. The presented segmentation method has been applied to brain MRI medical datasets to provide segmentation results when each voxel is composed of one tissue type (hard segmentation). The volume splitting procedure does not require training data, while it demonstrates improved segmentation performance in noisy brain MRI datasets, when compared to the state of the art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Real-time sonography to estimate muscle thickness: comparison with MRI and CT.

PubMed

Dupont, A C; Sauerbrei, E E; Fenton, P V; Shragge, P C; Loeb, G E; Richmond, F J

2001-05-01

We investigated the feasibility of using real-time sonography to measure muscle thickness. Clinically, this technique would be used to measure the thickness of human muscles in which intramuscular microstimulators have been implanted to treat or prevent disuse atrophy. Porcine muscles were implanted with microstimulators and imaged with sonography, MRI, and CT to assess image artifacts created by the microstimulators and to design protocols for image alignment between methods. Sonography and MRI were then used to image the deltoid and supraspinatus muscles of 6 healthy human subjects. Microstimulators could be imaged with all 3 methods, producing only small imaging artifacts. Muscle-thickness measurements agreed well between methods, particularly when external markers were used to precisely align the imaging planes. The correlation coefficients for sonographic and MRI measurements were 0.96 for the supraspinatus and 0.97 for the deltoid muscle. Repeated sonographic measurements had a low coefficient of variation: 2.3% for the supraspinatus and 3.1% for the deltoid muscle. Real-time sonography is a relatively simple and inexpensive method of accurately measuring muscle thickness as long as the operator adheres to a strict imaging protocol and avoids excessive pressure with the transducer. Copyright 2001 John Wiley & Sons, Inc.

Image Restoration Using Functional and Anatomical Information Fusion with Application to SPECT-MRI Images

PubMed Central

Benameur, S.; Mignotte, M.; Meunier, J.; Soucy, J. -P.

2009-01-01

Image restoration is usually viewed as an ill-posed problem in image processing, since there is no unique solution associated with it. The quality of restored image closely depends on the constraints imposed of the characteristics of the solution. In this paper, we propose an original extension of the NAS-RIF restoration technique by using information fusion as prior information with application in SPECT medical imaging. That extension allows the restoration process to be constrained by efficiently incorporating, within the NAS-RIF method, a regularization term which stabilizes the inverse solution. Our restoration method is constrained by anatomical information extracted from a high resolution anatomical procedure such as magnetic resonance imaging (MRI). This structural anatomy-based regularization term uses the result of an unsupervised Markovian segmentation obtained after a preliminary registration step between the MRI and SPECT data volumes from each patient. This method was successfully tested on 30 pairs of brain MRI and SPECT acquisitions from different subjects and on Hoffman and Jaszczak SPECT phantoms. The experiments demonstrated that the method performs better, in terms of signal-to-noise ratio, than a classical supervised restoration approach using a Metz filter. PMID:19812704

Contactless Abdominal Fat Reduction With Selective RF™ Evaluated by Magnetic Resonance Imaging (MRI): Case Study.

PubMed

Downie, Jeanine; Kaspar, Miroslav

2016-04-01

Noninvasive body shaping methods seem to be an ascending part of the aesthetics market. As a result, the pressure to develop reliable methods for the collection and presentation of their results has also increased. The most used techniques currently include ultrasound measurements of fat thickness in the treated area, caliper measurements, bioimpedance-based scale measurements or circumferential tape measurements. Although these are the most used techniques, almost all of them have some limitations in reproducibility and/or accuracy. This study shows Magnetic Resonance Imaging (MRI) as the new method for the presentation of results in the body shaping industry. Six subjects were treated by a contactless selective radiofrequency device (BTL Vanquish ME, BTL Industries Inc., Boston, MA). The MRI fat thickness was measured at the baseline and at 4-weeks following the treatment. In addition to MRI images and measurements, digital photographs and anthropometric evaluations such as weight, abdominal circumference, and caliper fat thickness measurements were recorded. Abdominal fat thickness measurements from the MRI were performed from the same slices determined by the same tissue artefacts. The MRI fat thickness difference between the baseline measurement and follow up visit showed an average reduction of 5.36 mm as calculated from the data of 5 subjects. One subject dropped out of study due to non-study related issues. The results were statistically significant based on the Student's T-test evaluation. Magnetic resonance imaging abdominal fat thickness measurements seems to be the best method for the evaluation of fat thickness reduction after non-invasive body shaping treatments. In this study, this method shows average fat thickness reduction of 5.36 mm while the weight of the subjects didn't change significantly. A large spot size measuring 1317 cm(2) (204 square inches) covers the abdomen flank to flank. The average thickness of 5.36 mm of the fat layer reduced under the applicator translates into significant cumulative circumferential reduction. The reduction was not related with dieting.

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Color-coded visualization of magnetic resonance imaging multiparametric maps

NASA Astrophysics Data System (ADS)

Kather, Jakob Nikolas; Weidner, Anja; Attenberger, Ulrike; Bukschat, Yannick; Weis, Cleo-Aron; Weis, Meike; Schad, Lothar R.; Zöllner, Frank Gerrit

2017-01-01

Multiparametric magnetic resonance imaging (mpMRI) data are emergingly used in the clinic e.g. for the diagnosis of prostate cancer. In contrast to conventional MR imaging data, multiparametric data typically include functional measurements such as diffusion and perfusion imaging sequences. Conventionally, these measurements are visualized with a one-dimensional color scale, allowing only for one-dimensional information to be encoded. Yet, human perception places visual information in a three-dimensional color space. In theory, each dimension of this space can be utilized to encode visual information. We addressed this issue and developed a new method for tri-variate color-coded visualization of mpMRI data sets. We showed the usefulness of our method in a preclinical and in a clinical setting: In imaging data of a rat model of acute kidney injury, the method yielded characteristic visual patterns. In a clinical data set of N = 13 prostate cancer mpMRI data, we assessed diagnostic performance in a blinded study with N = 5 observers. Compared to conventional radiological evaluation, color-coded visualization was comparable in terms of positive and negative predictive values. Thus, we showed that human observers can successfully make use of the novel method. This method can be broadly applied to visualize different types of multivariate MRI data.

[Abdominal ultrasound and magnetic resonance imaging: a comparative study on the non-alcoholic fatty liver disease diagnosis in morbidly obese patients].

PubMed

Chaves, Gabriela Villaça; Pereira, Sílvia Elaine; Saboya, Carlos José; Cortes, Caroline; Ramalho, Rejane

2009-01-01

To evaluate the concordance between abdominal ultrasound and an MRI (Magnetic Resonance Imaging) in the diagnosis of non-alcoholic fatty liver disease (NAFLD), and concordance of these two methods with the histopathological exam. The population studied was comprised of 145 patients with morbid obesity (BMI > or = 40 Kg/m(2)), of both genders. NAFLD diagnosis was performed by MRI and Ultrasound. Liver biopsy was performed in a sub-sample (n=40). To evaluate the concordance of these two methods, the kappa coefficient was used. Concordance between both methods (MRI and Ultrasound) was poor and not significant (Kappa adjusted= 0.27; CI 95%= 0.07-0.39.) Nevertheless a slight concordance was found between diagnosis of NAFLD by ultrasound and the hepatic biopsy, with 83.,3% of concordant results and Kappa adjusted= 0.67.Results of an MRI and the histopathological exam were compared and results showed 53.6% of concordant results and kappa adjusted= 0.07. The concordance found in the diagnosis performed using the ultrasound method and the hepatic biopsy, shows a need to implement and perform more research on the use of ultrasound to validate and reconsider these methods. This would minimize the need to perform biopsies to detect and diagnose such disease.

MRI Measurements of Iron Load in Transfusion‐Dependent Patients: Implementation, Challenges, and Pitfalls

PubMed Central

St Pierre, Tim G.

2015-01-01

Magnetic resonance imaging (MRI) has played a key role in studies of iron overload in transfusion‐dependent patients, providing insights into the relations among liver and cardiac iron loading, iron chelator dose, and morbidity. Currently, there is rapid uptake of these methods into routine clinical practice as part of the management strategy for iron overload in regularly transfused patients. Given the manifold methods of data acquisition and analysis, there are several potential pitfalls that may result in inappropriate decision making. Herein, we review the challenges of establishing suitable MRI techniques for tissue iron measurement in regularly transfused patients. PMID:26713769

Multivariate pattern analysis of fMRI: the early beginnings.

PubMed

Haxby, James V

2012-08-15

In 2001, we published a paper on the representation of faces and objects in ventral temporal cortex that introduced a new method for fMRI analysis, which subsequently came to be called multivariate pattern analysis (MVPA). MVPA now refers to a diverse set of methods that analyze neural responses as patterns of activity that reflect the varying brain states that a cortical field or system can produce. This paper recounts the circumstances and events that led to the original study and later developments and innovations that have greatly expanded this approach to fMRI data analysis, leading to its widespread application. Copyright © 2012 Elsevier Inc. All rights reserved.

New magnetic resonance imaging methods in nephrology

PubMed Central

Zhang, Jeff L.; Morrell, Glen; Rusinek, Henry; Sigmund, Eric; Chandarana, Hersh; Lerman, Lilach O.; Prasad, Pottumarthi Vara; Niles, David; Artz, Nathan; Fain, Sean; Vivier, Pierre H.; Cheung, Alfred K.; Lee, Vivian S.

2013-01-01

Established as a method to study anatomic changes, such as renal tumors or atherosclerotic vascular disease, magnetic resonance imaging (MRI) to interrogate renal function has only recently begun to come of age. In this review, we briefly introduce some of the most important MRI techniques for renal functional imaging, and then review current findings on their use for diagnosis and monitoring of major kidney diseases. Specific applications include renovascular disease, diabetic nephropathy, renal transplants, renal masses, acute kidney injury and pediatric anomalies. With this review, we hope to encourage more collaboration between nephrologists and radiologists to accelerate the development and application of modern MRI tools in nephrology clinics. PMID:24067433

Clinical use of cardiac PET/MRI: current state-of-the-art and potential future applications.

PubMed

Krumm, Patrick; Mangold, Stefanie; Gatidis, Sergios; Nikolaou, Konstantin; Nensa, Felix; Bamberg, Fabian; la Fougère, Christian

2018-05-01

Combined PET/MRI is a novel imaging method integrating the advances of functional and morphological MR imaging with PET applications that include assessment of myocardial viability, perfusion, metabolism of inflammatory tissue and tumors, as well as amyloid deposition imaging. As such, PET/MRI is a promising tool to detect and characterize ischemic and non-ischemic cardiomyopathies. To date, the greatest benefit may be expected for diagnostic evaluation of systemic diseases and cardiac masses that remain unclear in cardiac MRI, as well as for clinical and scientific studies in the setting of ischemic cardiomyopathies. Diagnosis and therapeutic monitoring of cardiac sarcoidosis has the potential of a possible 'killer-application' for combined cardiac PET/MRI. In this article, we review the current evidence and discuss current and potential future applications of cardiac PET/MRI.

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Decision forests for learning prostate cancer probability maps from multiparametric MRI

NASA Astrophysics Data System (ADS)

Ehrenberg, Henry R.; Cornfeld, Daniel; Nawaf, Cayce B.; Sprenkle, Preston C.; Duncan, James S.

2016-03-01

Objectives: Advances in multiparametric magnetic resonance imaging (mpMRI) and ultrasound/MRI fusion imaging offer a powerful alternative to the typical undirected approach to diagnosing prostate cancer. However, these methods require the time and expertise needed to interpret mpMRI image scenes. In this paper, a machine learning framework for automatically detecting and localizing cancerous lesions within the prostate is developed and evaluated. Methods: Two studies were performed to gather MRI and pathology data. The 12 patients in the first study underwent an MRI session to obtain structural, diffusion-weighted, and dynamic contrast enhanced image vol- umes of the prostate, and regions suspected of being cancerous from the MRI data were manually contoured by radiologists. Whole-mount slices of the prostate were obtained for the patients in the second study, in addition to structural and diffusion-weighted MRI data, for pathology verification. A 3-D feature set for voxel-wise appear- ance description combining intensity data, textural operators, and zonal approximations was generated. Voxels in a test set were classified as normal or cancer using a decision forest-based model initialized using Gaussian discriminant analysis. A leave-one-patient-out cross-validation scheme was used to assess the predictions against the expert manual segmentations confirmed as cancer by biopsy. Results: We achieved an area under the average receiver-operator characteristic curve of 0.923 for the first study, and visual assessment of the probability maps showed 21 out of 22 tumors were identified while a high level of specificity was maintained. In addition to evaluating the model against related approaches, the effects of the individual MRI parameter types were explored, and pathological verification using whole-mount slices from the second study was performed. Conclusions: The results of this paper show that the combination of mpMRI and machine learning is a powerful tool for quantitatively diagnosing prostate cancer.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avkshtol, V; Tanny, S; Reddy, K

Purpose: Stereotactic radiation therapy (SRT) provides an excellent alternative to embolization and surgical excision for the management of appropriately selected cerebral arteriovenous malformations (AVMs). The currently accepted standard for delineating AVMs is planar digital subtraction angiography (DSA). DSA can be used to acquire a 3D data set that preserves osseous structures (3D-DA) at the time of the angiography for SRT planning. Magnetic resonance imaging (MRI) provides an alternative noninvasive method of visualizing the AVM nidus with comparable spatial resolution. We utilized 3D-DA and T1 post-contrast MRI data to evaluate the differences in SRT target volumes. Methods: Four patients underwent 3D-DAmore » and high-resolution MRI. 3D T1 post-contrast images were obtained in all three reconstruction planes. A planning CT was fused with MRI and 3D-DA data sets. The AVMs were contoured utilizing one of the image sets at a time. Target volume, centroid, and maximum and minimum dimensions were analyzed for each patient. Results: Targets delineated using post-contrast MRI demonstrated a larger mean volume. AVMs >2 cc were found to have a larger difference between MRI and 3D-DA volumes. Larger AVMs also demonstrated a smaller relative uncertainty in contour centroid position (1 mm). AVM targets <2 cc had smaller absolute differences in volume, but larger differences in contour centroid position (2.5 mm). MRI targets demonstrated a more irregular shape compared to 3D-DA targets. Conclusions: Our preliminary data supports the use of MRI alone to delineate AVM targets >2 cc. The greater centroid stability for AVMs >2 cc ensures accurate target localization during image fusion. The larger MRI target volumes did not result in prohibitively greater volumes of normal brain tissue receiving the prescription dose. The larger centroid instability for AVMs <2 cc precludes the use of MRI alone for target delineation. We recommend incorporating a 3D-DA for these patients.« less

A Review of Numerical Simulation and Analytical Modeling for Medical Devices Safety in MRI

PubMed Central

Kabil, J.; Belguerras, L.; Trattnig, S.; Pasquier, C.; Missoffe, A.

2016-01-01

Summary Objectives To review past and present challenges and ongoing trends in numerical simulation for MRI (Magnetic Resonance Imaging) safety evaluation of medical devices. Methods A wide literature review on numerical and analytical simulation on simple or complex medical devices in MRI electromagnetic fields shows the evolutions through time and a growing concern for MRI safety over the years. Major issues and achievements are described, as well as current trends and perspectives in this research field. Results Numerical simulation of medical devices is constantly evolving, supported by calculation methods now well-established. Implants with simple geometry can often be simulated in a computational human model, but one issue remaining today is the experimental validation of these human models. A great concern is to assess RF heating on implants too complex to be traditionally simulated, like pacemaker leads. Thus, ongoing researches focus on alternative hybrids methods, both numerical and experimental, with for example a transfer function method. For the static field and gradient fields, analytical models can be used for dimensioning simple implants shapes, but limited for complex geometries that cannot be studied with simplifying assumptions. Conclusions Numerical simulation is an essential tool for MRI safety testing of medical devices. The main issues remain the accuracy of simulations compared to real life and the studies of complex devices; but as the research field is constantly evolving, some promising ideas are now under investigation to take up the challenges. PMID:27830244

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Image segmentation and 3D visualization for MRI mammography

NASA Astrophysics Data System (ADS)

Li, Lihua; Chu, Yong; Salem, Angela F.; Clark, Robert A.

2002-05-01

MRI mammography has a number of advantages, including the tomographic, and therefore three-dimensional (3-D) nature, of the images. It allows the application of MRI mammography to breasts with dense tissue, post operative scarring, and silicon implants. However, due to the vast quantity of images and subtlety of difference in MR sequence, there is a need for reliable computer diagnosis to reduce the radiologist's workload. The purpose of this work was to develop automatic breast/tissue segmentation and visualization algorithms to aid physicians in detecting and observing abnormalities in breast. Two segmentation algorithms were developed: one for breast segmentation, the other for glandular tissue segmentation. In breast segmentation, the MRI image is first segmented using an adaptive growing clustering method. Two tracing algorithms were then developed to refine the breast air and chest wall boundaries of breast. The glandular tissue segmentation was performed using an adaptive thresholding method, in which the threshold value was spatially adaptive using a sliding window. The 3D visualization of the segmented 2D slices of MRI mammography was implemented under IDL environment. The breast and glandular tissue rendering, slicing and animation were displayed.

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

NASA Astrophysics Data System (ADS)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

TH-EF-BRA-06: A Novel Retrospective 3D K-Space Sorting 4D-MRI Technique Using a Radial K-Space Acquisition MRI Sequence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Subashi, E; Yin, F

Purpose: Current retrospective 4D-MRI provides superior tumor-to-tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D-MRI techniques based on 2D-MRI image sorting require a high frame-rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame-rate. This study aims at developing a novel retrospective 3D k-space sorting 4D-MRI technique using radial k-space acquisition MRI sequences to improve 4D-MRI image quality and temporal-resolution for imaging irregular organ/tumor respiratory motion. Methods: The method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. A 3D radial k-space data acquisition trajectorymore » was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field-of-View. Respiratory signal can be extracted from the k-space center data point of each spoke. The spoke data was sorted based on its self-synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time-resolved 4D-MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k-space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D-MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated. Results: The signal extracted from k-space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D-MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively. Conclusion: A novel retrospective 3D k-space sorting 4D-MRI technique has been developed and evaluated on human digital phantom. NIH (1R21CA165384-01A1)« less

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Noninvasive Assessment of Tissue Heating During Cardiac Radiofrequency Ablation Using MRI Thermography

PubMed Central

Kolandaivelu, Aravindan; Zviman, Menekhem M.; Castro, Valeria; Lardo, Albert C.; Berger, Ronald D.; Halperin, Henry R.

2010-01-01

Background Failure to achieve properly localized, permanent tissue destruction is a common cause of arrhythmia recurrence after cardiac ablation. Current methods of assessing lesion size and location during cardiac radiofrequency ablation are unreliable or not suited for repeated assessment during the procedure. MRI thermography could be used to delineate permanent ablation lesions because tissue heating above 50°C is the cause of permanent tissue destruction during radiofrequency ablation. However, image artifacts caused by cardiac motion, the ablation electrode, and radiofrequency ablation currently pose a challenge to MRI thermography in the heart. In the current study, we sought to demonstrate the feasibility of MRI thermography during cardiac ablation. Methods and Results An MRI-compatible electrophysiology catheter and filtered radiofrequency ablation system was used to perform ablation in the left ventricle of 6 mongrel dogs in a 1.5-T MRI system. Fast gradient-echo imaging was performed before and during radiofrequency ablation, and thermography images were derived from the preheating and postheating images. Lesion extent by thermography was within 20% of the gross pathology lesion. Conclusions MR thermography appears to be a promising technique for monitoring lesion formation and may allow for more accurate placement and titration of ablation, possibly reducing arrhythmia recurrences. PMID:20657028

Dental MRI using wireless intraoral coils

NASA Astrophysics Data System (ADS)

Ludwig, Ute; Eisenbeiss, Anne-Katrin; Scheifele, Christian; Nelson, Katja; Bock, Michael; Hennig, Jürgen; von Elverfeldt, Dominik; Herdt, Olga; Flügge, Tabea; Hövener, Jan-Bernd

2016-03-01

Currently, the gold standard for dental imaging is projection radiography or cone-beam computed tomography (CBCT). These methods are fast and cost-efficient, but exhibit poor soft tissue contrast and expose the patient to ionizing radiation (X-rays). The need for an alternative imaging modality e.g. for soft tissue management has stimulated a rising interest in dental magnetic resonance imaging (MRI) which provides superior soft tissue contrast. Compared to X-ray imaging, however, so far the spatial resolution of MRI is lower and the scan time is longer. In this contribution, we describe wireless, inductively-coupled intraoral coils whose local sensitivity enables high resolution MRI of dental soft tissue. In comparison to CBCT, a similar image quality with complementary contrast was obtained ex vivo. In-vivo, a voxel size of the order of 250•250•500 μm3 was achieved in 4 min only. Compared to dental MRI acquired with clinical equipment, the quality of the images was superior in the sensitive volume of the coils and is expected to improve the planning of interventions and monitoring thereafter. This method may enable a more accurate dental diagnosis and avoid unnecessary interventions, improving patient welfare and bringing MRI a step closer to becoming a radiation-free alternative for dental imaging.

Thermo-Acoustic Ultrasound for Detection of RF-Induced Device Lead Heating in MRI.

PubMed

Dixit, Neerav; Stang, Pascal P; Pauly, John M; Scott, Greig C

2018-02-01

Patients who have implanted medical devices with long conductive leads are often restricted from receiving MRI scans due to the danger of RF-induced heating near the lead tips. Phantom studies have shown that this heating varies significantly on a case-by-case basis, indicating that many patients with implanted devices can receive clinically useful MRI scans without harm. However, the difficulty of predicting RF-induced lead tip heating prior to scanning prevents numerous implant recipients from being scanned. Here, we demonstrate that thermo-acoustic ultrasound (TAUS) has the potential to be utilized for a pre-scan procedure assessing the risk of RF-induced lead tip heating in MRI. A system was developed to detect TAUS signals by four different TAUS acquisition methods. We then integrated this system with an MRI scanner and detected a peak in RF power absorption near the tip of a model lead when transmitting from the scanner's body coil. We also developed and experimentally validated simulations to characterize the thermo-acoustic signal generated near lead tips. These results indicate that TAUS is a promising method for assessing RF implant safety, and with further development, a TAUS pre-scan could allow many more patients to have access to MRI scans of significant clinical value.

A Non-Invasive Assessment of Cardiopulmonary Hemodynamics with MRI in Pulmonary Hypertension

PubMed Central

Bane, Octavia; Shah, Sanjiv J.; Cuttica, Michael J.; Collins, Jeremy D.; Selvaraj, Senthil; Chatterjee, Neil R.; Guetter, Christoph; Carr, James C.; Carroll, Timothy J.

2015-01-01

Purpose We propose a method for non-invasive quantification of hemodynamic changes in the pulmonary arteries resulting from pulmonary hypertension (PH). Methods Using a two-element windkessel model, and input parameters derived from standard MRI evaluation of flow, cardiac function and valvular motion, we derive: pulmonary artery compliance (C), mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), pulmonary capillary wedge pressure (PCWP), time-averaged intra-pulmonary pressure waveforms and pulmonary artery pressures (systolic (sPAP) and diastolic (dPAP)). MRI results were compared directly to reference standard values from right heart catheterization (RHC) obtained in a series of patients with suspected pulmonary hypertension (PH). Results In 7 patients with suspected PH undergoing RHC, MRI and echocardiography, there was no statistically significant difference (p<0.05) between parameters measured by MRI and RHC. Using standard clinical cutoffs to define PH (mPAP ≥ 25 mmHg), MRI was able to correctly identify all patients as having pulmonary hypertension, and to correctly distinguish between pulmonary arterial (mPAP≥ 25 mmHg, PCWP<15 mmHg) and venous hypertension (mPAP ≥ 25 mmHg, PCWP ≥ 15 mmHg) in 5 of 7 cases. Conclusions We have developed a mathematical model capable of quantifying physiological parameters that reflect the severity of PH. PMID:26283577

[Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

PubMed

Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

2001-11-01

The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.

MRI in multiple sclerosis: current status and future prospects

PubMed Central

Bakshi, Rohit; Thompson, Alan J; Rocca, Maria A; Pelletier, Daniel; Dousset, Vincent; Barkhof, Frederik; Inglese, Matilde; Guttmann, Charles R G; Horsfield, Mark A; Filippi, Massimo

2008-01-01

Many promising MRI approaches for research or clinical management of multiple sclerosis (MS) have recently emerged, or are under development or refinement. Advanced MRI methods need to be assessed to determine whether they allow earlier diagnosis or better identification of phenotypes. Improved post-processing should allow more efficient and complete extraction of information from images. Magnetic resonance spectroscopy should improve in sensitivity and specificity with higher field strengths and should enable the detection of a wider array of metabolites. Diffusion imaging is moving closer to the goal of defining structural connectivity and, thereby, determining the functional significance of lesions at specific locations. Cell-specific imaging now seems feasible with new magnetic resonance contrast agents. The imaging of myelin water fraction brings the hope of providing a specific measure of myelin content. Ultra-high-field MRI increases sensitivity, but also presents new technical challenges. Here, we review these recent developments in MRI for MS, and also look forward to refinements in spinal-cord imaging, optic-nerve imaging, perfusion MRI, and functional MRI. Advances in MRI should improve our ability to diagnose, monitor, and understand the pathophysiology of MS. PMID:18565455

[Magnetic resonance imaging (MRI) in children and adolescents – study design of a feasibility study concerning examination related emotions].

PubMed

Jaite, Charlotte; Bachmann, Christian; Dewey, Marc; Weschke, Bernhard; Spors, Birgit; von Moers, Arpad; Napp, Adriane; Lehmkuhl, Ulrike; Kappel, Viola

2013-11-01

Numerous research centres apply magnetic resonance imaging (MRI) for research purposes in children. In view of this practical research, ethical concerns regarding the strains the study participants are exposed to during the MRI examination are discussed. The study evaluates whether an MRI examination induces negative emotions in children and adolescents which are more intense than the ones caused by electroencephalography (EEG), an examination method currently classified as causing "minimal stress." Furthermore, the emotional stress induced by the MRI examination in children and adolescents is compared with that induced in adults. The study gathers data on examination-related emotions in children (age 8-17;11, male and female) who undergo an MRI examination of the cerebrum with a medical indication. The comparison group is a sample of children and adolescents examined with EEG (age 8-17;11, male and female) as well as a sample of adults (age 18-65, male and female) examined with MRI. At present, the study is in the stage of data collection. This article presents the study design of the MRI research project.

Characterization of task-free and task-performance brain states via functional connectome patterns.

PubMed

Zhang, Xin; Guo, Lei; Li, Xiang; Zhang, Tuo; Zhu, Dajiang; Li, Kaiming; Chen, Hanbo; Lv, Jinglei; Jin, Changfeng; Zhao, Qun; Li, Lingjiang; Liu, Tianming

2013-12-01

Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive behaviors during R-fMRI/T-fMRI scans, it has been challenging to ascertain whether or not an R-fMRI/T-fMRI scan truly reflects the participant's functional brain states during task-free/task-performance periods. This paper presents a novel computational approach to characterizing and differentiating the brain's functional status into task-free or task-performance states, by which the functional brain activities can be effectively understood and differentiated. Briefly, the brain's functional state is represented by a whole-brain quasi-stable connectome pattern (WQCP) of R-fMRI or T-fMRI data based on 358 consistent cortical landmarks across individuals, and then an effective sparse representation method was applied to learn the atomic connectome patterns (ACPs) of both task-free and task-performance states. Experimental results demonstrated that the learned ACPs for R-fMRI and T-fMRI datasets are substantially different, as expected. A certain portion of ACPs from R-fMRI and T-fMRI data were overlapped, suggesting some subjects with overlapping ACPs were not in the expected task-free/task-performance brain states. Besides, potential outliers in the T-fMRI dataset were further investigated via functional activation detections in different groups, and our results revealed unexpected task-performances of some subjects. This work offers novel insights into the functional architectures of the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of Task-free and Task-performance Brain States via Functional Connectome Patterns

PubMed Central

Zhang, Xin; Guo, Lei; Li, Xiang; Zhang, Tuo; Zhu, Dajiang; Li, Kaiming; Chen, Hanbo; Lv, Jinglei; Jin, Changfeng; Zhao, Qun; Li, Lingjiang; Liu, Tianming

2014-01-01

Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive behaviors during R-fMRI/T-fMRI scans, it has been challenging to ascertain whether or not an R-fMRI/T-fMRI scan truly reflects the participant's functional brain states during task-free/task-performance periods. This paper presents a novel computational approach to characterizing and differentiating the brain's functional status into task-free or task-performance states, by which the functional brain activities can be effectively understood and differentiated. Briefly, the brain's functional state is represented by a whole-brain quasi-stable connectome pattern (WQCP) of R-fMRI or T-fMRI data based on 358 consistent cortical landmarks across individuals, and then an effective sparse representation method was applied to learn the atomic connectome patterns (ACP) of both task-free and task-performance states. Experimental results demonstrated that the learned ACPs for R-fMRI and T-fMRI datasets are substantially different, as expected. A certain portion of ACPs from R-fMRI and T-fMRI data were overlapped, suggesting some subjects with overlapping ACPs were not in the expected task-free/task-performance brain states. Besides, potential outliers in the T-fMRI dataset were further investigated via functional activation detections in different groups, and our results revealed unexpected task-performances of some subjects. This work offers novel insights into the functional architectures of the brain. PMID:23938590

Assessing perioperative complications associated with use of intraoperative magnetic resonance imaging during glioma surgery - a single centre experience with 516 cases.

PubMed

Ahmadi, Rezvan; Campos, Benito; Haux, Daniel; Rieke, Jörn; Beigel, Bernhard; Unterberg, Andreas

2016-08-01

Intraoperative magnetic resonance imaging (io-MRI) improves the extent of glioma resection. Due to the magnetic field, patients have to be covered with sterile drape and are then transferred into an io-MRI chamber, where ferromagnetic anaesthesia monitors and machines must be kept at distance and can only be applied with limitations. Despite the development of specific paramagnetic equipment for io-MRI use, this method is suspected to carry a higher risk for anaesthesiological and surgical complications. Particularly, serial draping and un-draping cycles as well as the extended surgery duration might increase the risk of perioperative infection. Given the importance of io-MRI for glioma surgery, the question regarding io-MRI safety needs to be answered. We prospectively evaluate the perioperative anaesthesiological and surgical complications for 516 cases of brain tumour surgery involving io-MRI (MRI cohort). As a control group, we evaluate a cohort of 610 cases of brain tumour surgery, performed without io-MRI (control group). The io-MRI procedure (including draping/undraping, transfer to and from the MRI cabinet and io-MRI scan) significantly extended surgery, defined as "skin to skin" time, by 57 min (SD = 16 min) (p ≤ 0.01). Still, we show low and comparable rates of surgical complications in the MRI cohort and the control group. Postoperative haemorrhage (3.7% versus 3.0% in MRI cohort versus control group; p = 0.49) and infections (2.2% versus 1.8% in MRI cohort versus control group; p = 0.69) were not significantly different between both groups. No anaesthesiological disturbances were reported. Despite prolonged surgery and serial draping and un-draping cycles, io-MRI was not linked to higher rates of infections and postoperative haemorrhage in this study.

Technical Note: Independent component analysis for quality assurance in functional MRI.

PubMed

Astrakas, Loukas G; Kallistis, Nikolaos S; Kalef-Ezra, John A

2016-02-01

Independent component analysis (ICA) is an established method of analyzing human functional MRI (fMRI) data. Here, an ICA-based fMRI quality control (QC) tool was developed and used. ICA-based fMRI QC tool to be used with a commercial phantom was developed. In an attempt to assess the performance of the tool relative to preexisting alternative tools, it was used seven weeks before and eight weeks after repair of a faulty gradient amplifier of a non-state-of-the-art MRI unit. More specifically, its performance was compared with the AAPM 100 acceptance testing and quality assurance protocol and two fMRI QC protocols, proposed by Freidman et al. ["Report on a multicenter fMRI quality assurance protocol," J. Magn. Reson. Imaging 23, 827-839 (2006)] and Stocker et al. ["Automated quality assurance routines for fMRI data applied to a multicenter study," Hum. Brain Mapp. 25, 237-246 (2005)], respectively. The easily developed and applied ICA-based QC protocol provided fMRI QC indices and maps equally sensitive to fMRI instabilities with the indices and maps of other established protocols. The ICA fMRI QC indices were highly correlated with indices of other fMRI QC protocols and in some cases theoretically related to them. Three or four independent components with slow varying time series are detected under normal conditions. ICA applied on phantom measurements is an easy and efficient tool for fMRI QC. Additionally, it can protect against misinterpretations of artifact components as human brain activations. Evaluating fMRI QC indices in the central region of a phantom is not always the optimal choice.

WE-EF-BRD-03: I Want It Now!: Advances in MRI Acquisition, Reconstruction and the Use of Priors to Enable Fast Anatomic and Physiologic Imaging to Inform Guidance and Adaptation Decisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Y.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

Mutual interferences and design principles for mechatronic devices in magnetic resonance imaging.

PubMed

Yu, Ningbo; Gassert, Roger; Riener, Robert

2011-07-01

Robotic and mechatronic devices that work compatibly with magnetic resonance imaging (MRI) are applied in diagnostic MRI, image-guided surgery, neurorehabilitation and neuroscience. MRI-compatible mechatronic systems must address the challenges imposed by the scanner's electromagnetic fields. We have developed objective quantitative evaluation criteria for device characteristics needed to formulate design guidelines that ensure MRI-compatibility based on safety, device functionality and image quality. The mutual interferences between an MRI system and mechatronic devices working in its vicinity are modeled and tested. For each interference, the involved components are listed, and a numerical measure for "MRI-compatibility" is proposed. These interferences are categorized into an MRI-compatibility matrix, with each element representing possible interactions between one part of the mechatronic system and one component of the electromagnetic fields. Based on this formulation, design principles for MRI-compatible mechatronic systems are proposed. Furthermore, test methods are developed to examine whether a mechatronic device indeed works without interferences within an MRI system. Finally, the proposed MRI-compatibility criteria and design guidelines have been applied to an actual design process that has been validated by the test procedures. Objective and quantitative MRI-compatibility measures for mechatronic and robotic devices have been established. Applying the proposed design principles, potential problems in safety, device functionality and image quality can be considered in the design phase to ensure that the mechatronic system will fulfill the MRI-compatibility criteria. New guidelines and test procedures for MRI instrument compatibility provide a rational basis for design and evaluation of mechatronic devices in various MRI applications. Designers can apply these criteria and use the tests, so that MRI-compatibility results can accrue to build an experiential database.

Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation.

PubMed

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2015-12-01

This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. © 2014 Wiley Periodicals, Inc.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Labeling and Magnetic Resonance Imaging of Exosomes Isolated from Adipose Stem Cells.

PubMed

Busato, Alice; Bonafede, Roberta; Bontempi, Pietro; Scambi, Ilaria; Schiaffino, Lorenzo; Benati, Donatella; Malatesta, Manuela; Sbarbati, Andrea; Marzola, Pasquina; Mariotti, Raffaella

2017-06-19

Adipose stem cells (ASC) represent a promising therapeutic approach for neurodegenerative diseases. Most biological effects of ASC are probably mediated by extracellular vesicles, such as exosomes, which influence the surrounding cells. Current development of exosome therapies requires efficient and noninvasive methods to localize, monitor, and track the exosomes. Among imaging methods used for this purpose, magnetic resonance imaging (MRI) has advantages: high spatial resolution, rapid in vivo acquisition, and radiation-free operation. To be detectable with MRI, exosomes must be labeled with MR contrast agents, such as ultra-small superparamagnetic iron oxide nanoparticles (USPIO). Here, we set up an innovative approach for exosome labeling that preserves their morphology and physiological characteristics. We show that by labeling ASC with USPIO before extraction of nanovesicles, the isolated exosomes retain nanoparticles and can be visualized by MRI. The current work aims at validating this novel USPIO-based exosome labeling method by monitoring the efficiency of the labeling with MRI both in ASC and in exosomes. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

SPION-enhanced magnetic resonance imaging of Alzheimer's disease plaques in AβPP/PS-1 transgenic mouse brain.

PubMed

Sillerud, Laurel O; Solberg, Nathan O; Chamberlain, Ryan; Orlando, Robert A; Heidrich, John E; Brown, David C; Brady, Christina I; Vander Jagt, Thomas A; Garwood, Michael; Vander Jagt, David L

2013-01-01

In our program to develop non-invasive magnetic resonance imaging (MRI) methods for the diagnosis of Alzheimer's disease (AD), we have synthesized antibody-conjugated, superparamagnetic iron oxide nanoparticles (SPIONs) for use as an in vivo agent for MRI detection of amyloid-β plaques in AD. Here we report studies in AβPP/PS1 transgenic mice, which demonstrate the ability of novel anti-AβPP conjugated SPIONs to penetrate the blood-brain barrier to act as a contrast agent for MR imaging of plaques. The conspicuity of the plaques increased from an average Z-score of 5.1 ± 0.5 to 8.3 ± 0.2 when the plaque contrast to noise ratio was compared in control AD mice with AD mice treated with SPIONs. The number of MRI-visible plaques per brain increased from 347 ± 45 in the control AD mice, to 668 ± 86 in the SPION treated mice. These results indicated that our SPION enhanced amyloid-β detection method delivers an efficacious, non-invasive MRI detection method in transgenic mice.

New Insights into Signed Path Coefficient Granger Causality Analysis.

PubMed

Zhang, Jian; Li, Chong; Jiang, Tianzi

2016-01-01

Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an "excitatory" or "inhibitory" influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation.

SPION-Enhanced Magnetic Resonance Imaging of Alzheimer’s Disease Plaques in AβPP/PS-1 Transgenic Mouse Brain

PubMed Central

Sillerud, Laurel O.; Solberg, Nathan O.; Chamberlain, Ryan; Orlando, Robert A.; Heidrich, John E.; Brown, David C.; Brady, Christina I.; Vander Jagt, Thomas A.; Garwood, Michael; Vander Jagt, David L.

2016-01-01

In our program to develop non-invasive magnetic resonance imaging (MRI) methods for the diagnosis of Alzheimer’s disease (AD), we have synthesized antibody-conjugated, superparamagnetic iron oxide nanoparticles (SPIONs) for use as an in vivo agent for MRI detection of amyloid-β plaques in AD. Here we report studies in AβPP/PS1 transgenic mice, which demonstrate the ability of novel anti-AβPP conjugated SPIONs to penetrate the blood-brain barrier to act as a contrast agent for MR imaging of plaques. The conspicuity of the plaques increased from an average Z-score of 5.1 ± 0.5 to 8.3 ± 0.2 when the plaque contrast to noise ratio was compared in control AD mice with AD mice treated with SPIONs. The number of MRI-visible plaques per brain increased from 347 ± 45 in the control AD mice, to 668 ± 86 in the SPION treated mice. These results indicated that our SPION enhanced amyloid-β detection method delivers an efficacious, non-invasive MRI detection method in transgenic mice. PMID:23229079

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Role of conventional radiology and MRi defecography of pelvic floor hernias

PubMed Central

2013-01-01

Background Purpose of the study is to define the role of conventional radiology and MRI in the evaluation of pelvic floor hernias in female pelvic floor disorders. Methods A MEDLINE and PubMed search was performed for journals before March 2013 with MeSH major terms 'MR Defecography' and 'pelvic floor hernias'. Results The prevalence of pelvic floor hernias at conventional radiology was higher if compared with that at MRI. Concerning the hernia content, there were significantly more enteroceles and sigmoidoceles on conventional radiology than on MRI, whereas, in relation to the hernia development modalities, the prevalence of elytroceles, edroceles, and Douglas' hernias at conventional radiology was significantly higher than that at MRI. Conclusions MRI shows lower sensitivity than conventional radiology in the detection of pelvic floor hernias development. The less-invasive MRI may have a role in a better evaluation of the entire pelvic anatomy and pelvic organ interaction especially in patients with multicompartmental defects, planned for surgery. PMID:24267789