Cellular imaging of deep organ using two-photon Bessel light-sheet nonlinear structured illumination microscopy

PubMed Central

Zhao, Ming; Zhang, Han; Li, Yu; Ashok, Amit; Liang, Rongguang; Zhou, Weibin; Peng, Leilei

2014-01-01

In vivo fluorescent cellular imaging of deep internal organs is highly challenging, because the excitation needs to penetrate through strong scattering tissue and the emission signal is degraded significantly by photon diffusion induced by tissue-scattering. We report that by combining two-photon Bessel light-sheet microscopy with nonlinear structured illumination microscopy (SIM), live samples up to 600 microns wide can be imaged by light-sheet microscopy with 500 microns penetration depth, and diffused background in deep tissue light-sheet imaging can be reduced to obtain clear images at cellular resolution in depth beyond 200 microns. We demonstrate in vivo two-color imaging of pronephric glomeruli and vasculature of zebrafish kidney, whose cellular structures located at the center of the fish body are revealed in high clarity by two-color two-photon Bessel light-sheet SIM. PMID:24876996

Shaping field for deep tissue microscopy

NASA Astrophysics Data System (ADS)

Colon, J.; Lim, H.

2015-05-01

Information capacity of a lossless image-forming system is a conserved property determined by two imaging parameters - the resolution and the field of view (FOV). Adaptive optics improves the former by manipulating the phase, or wavefront, in the pupil plane. Here we describe a homologous approach, namely adaptive field microscopy, which aims to enhance the FOV by controlling the phase, or defocus, in the focal plane. In deep tissue imaging, the useful FOV can be severely limited if the region of interest is buried in a thick sample and not perpendicular to the optic axis. One must acquire many z-scans and reconstruct by post-processing, which exposes tissue to excessive radiation and is also time consuming. We demonstrate the effective FOV can be substantially enhanced by dynamic control of the image plane. Specifically, the tilt of the image plane is continuously adjusted in situ to match the oblique orientation of the sample plane within tissue. The utility of adaptive field microscopy is tested for imaging tissue with non-planar morphology. Ocular tissue of small animals was imaged by two-photon excited fluorescence. Our results show that adaptive field microscopy can utilize the full FOV. The freedom to adjust the image plane to account for the geometrical variations of sample could be extremely useful for 3D biological imaging. Furthermore, it could facilitate rapid surveillance of cellular features within deep tissue while avoiding photo damages, making it suitable for in vivo imaging.

Imaging deep skeletal muscle structure using a high-sensitivity ultrathin side-viewing optical coherence tomography needle probe

PubMed Central

Yang, Xiaojie; Lorenser, Dirk; McLaughlin, Robert A.; Kirk, Rodney W.; Edmond, Matthew; Simpson, M. Cather; Grounds, Miranda D.; Sampson, David D.

2013-01-01

We have developed an extremely miniaturized optical coherence tomography (OCT) needle probe (outer diameter 310 µm) with high sensitivity (108 dB) to enable minimally invasive imaging of cellular structure deep within skeletal muscle. Three-dimensional volumetric images were acquired from ex vivo mouse tissue, examining both healthy and pathological dystrophic muscle. Individual myofibers were visualized as striations in the images. Degradation of cellular structure in necrotic regions was seen as a loss of these striations. Tendon and connective tissue were also visualized. The observed structures were validated against co-registered hematoxylin and eosin (H&E) histology sections. These images of internal cellular structure of skeletal muscle acquired with an OCT needle probe demonstrate the potential of this technique to visualize structure at the microscopic level deep in biological tissue in situ. PMID:24466482

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf

NASA Astrophysics Data System (ADS)

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; An Nguyen, Thien; Alfano, Robert R.

2014-06-01

Two-photon (2P) excitation of the second singlet (S) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S2 state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf.

PubMed

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; Nguyen, Thien An; Alfano, Robert R

2014-06-01

Two-photon (2P) excitation of the second singlet (S₂) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S₂ state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S₂ state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

Contrast-enhanced photoacoustic imaging with an optical wavelength of 1064 nm

NASA Astrophysics Data System (ADS)

Kim, Jeesu; Park, Sara; Park, Gyeong Bae; Choi, Wonseok; Jeong, Unyong; Kim, Chulhong

2018-02-01

Photoacoustic (PA) imaging is a biomedical imaging method that can provide both structural and functional information of living tissues beyond the optical diffusion limit by combining the concepts of conventional optical and ultrasound imaging methods. Although endogenous chromophores can be utilized to acquire PA images of biological tissues, exogenous contrast agents that absorb near-infrared (NIR) lights have been extensively explored to improve the contrast and penetration depth of PA images. Here, we demonstrate Bi2Se3 nanoplates, that strongly absorbs NIR lights, as a contrast agent for PA imaging. In particularly, the Bi2Se3 nanoplates produce relatively strong PA signals with an optical wavelength of 1064 nm, which has several advantages for deep tissue imaging including: (1) relatively low absorption by other intrinsic chromophores, (2) cost-effective light source using Nd:YAG laser, and (3) higher available energy than other NIR lights according to American National Standards Institute (ANSI) safety limit. We have investigated deep tissue imaging capability of the Bi2Se3 nanoplates by acquiring in vitro PA images of microtubes under chicken breast tissues. We have also acquired in vivo PA images of bladders, gastrointestinal tracts, and sentinel lymph nodes in mice after injection of the Bi2Se3 nanoplates to verify their applicability to a variety of biomedical research. The results show the promising potential of the Bi2Se3 nanoplates as a PA contrast agent for deep tissue imaging with an optical wavelength of 1064 nm.

RGD-conjugated two-photon absorbing near-IR emitting fluorescent probes for tumor vascular imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Belfield, Kevin D.; Yue, Xiling; Morales, Alma R.; Githaiga, Grace W.; Woodward, Adam W.; Tang, Simon; Sawada, Junko; Komatsu, Masanobu; Liu, Xuan

2016-03-01

Observation of the activation and inhibition of angiogenesis processes is important in the progression of cancer. Application of targeting peptides, such as a small peptide that contains adjacent L-arginine (R), glycine (G) and L-aspartic acid (D) residues can afford high selectivity and deep penetration in vessel imaging. To facilitate deep tissue vasculature imaging, probes that can be excited via two-photon absorption (2PA) in the near-infrared (NIR) and subsequently emit in the NIR are essential. In this study, the enhancement of tissue image quality with RGD conjugates was investigated with new NIR-emitting pyranyl fluorophore derivatives in two-photon fluorescence microscopy. Linear and nonlinear photophysical properties of the new probes were comprehensively characterized; significantly the probes exhibited good 2PA over a broad spectral range from 700-1100 nm. Cell and tissue images were then acquired and examined, revealing deep penetration and high contrast with the new pyranyl RGD-conjugates up to 350 μm in tumor tissue.

Deep-tissue two-photon imaging in brain and peripheral nerve with a compact high-pulse energy ytterbium fiber laser

NASA Astrophysics Data System (ADS)

Fontaine, Arjun K.; Kirchner, Matthew S.; Caldwell, John H.; Weir, Richard F.; Gibson, Emily A.

2018-02-01

Two-photon microscopy is a powerful tool of current scientific research, allowing optical visualization of structures below the surface of tissues. This is of particular value in neuroscience, where optically accessing regions within the brain is critical for the continued advancement in understanding of neural circuits. However, two-photon imaging at significant depths have typically used Ti:Sapphire based amplifiers that are prohibitively expensive and bulky. In this study, we demonstrate deep tissue two-photon imaging using a compact, inexpensive, turnkey operated Ytterbium fiber laser (Y-Fi, KM Labs). The laser is based on all-normal dispersion (ANDi) that provides short pulse durations and high pulse energies. Depth measurements obtained in ex vivo mouse cortex exceed those obtainable with standard two-photon microscopes using Ti:Sapphire lasers. In addition to demonstrating the capability of deep-tissue imaging in the brain, we investigated imaging depth in highly-scattering white matter with measurements in sciatic nerve showing limited optical penetration of heavily myelinated nerve tissue relative to grey matter.

Photoacoustic diagnosis of burns in rats: two-dimensional photo-acoustic imaging of burned tissue

NASA Astrophysics Data System (ADS)

Yamazaki, Mutsuo; Sato, Shunichi; Saito, Daizo; Okada, Yoshiaki; Kurita, Akira; Kikuchi, Makoto; Ashida, Hiroshi; Obara, Minoru

2003-06-01

We previously reported that for rat burn models, deep dermal burns and deep burns can be well differentiated by measuring the propagation time of the photoacoustic signals originated from the blood in the healthy skin tissue under the damaged tissue layer. However, the diagnosis was based on point measurement in the wound, and therefore site-dependent information on the injuries was not obtained; such information is very important for diagnosis of extended burns. In the present study, we scanned a photoacoustic detector on the wound and constructed two-dimensional (2-D) images of the blood-originated photoacoustic signals for superficial dermal burns (SDB), deep dermal burns (DDB), deep burns (DB), and healthy skins (control) in rats. For each burn model, site-dependent variation of the signal was observed; the variation probably reflects the distribution of blood vessels in the skin tissue. In spite of the variation, clear differentiation was obtained between SDB, DDB, and DB from the 2D images. The images were constructed as a function of post burn time. Temporal signal variation will be also presented.

A deep learning approach to estimate chemically-treated collagenous tissue nonlinear anisotropic stress-strain responses from microscopy images.

PubMed

Liang, Liang; Liu, Minliang; Sun, Wei

2017-11-01

Biological collagenous tissues comprised of networks of collagen fibers are suitable for a broad spectrum of medical applications owing to their attractive mechanical properties. In this study, we developed a noninvasive approach to estimate collagenous tissue elastic properties directly from microscopy images using Machine Learning (ML) techniques. Glutaraldehyde-treated bovine pericardium (GLBP) tissue, widely used in the fabrication of bioprosthetic heart valves and vascular patches, was chosen to develop a representative application. A Deep Learning model was designed and trained to process second harmonic generation (SHG) images of collagen networks in GLBP tissue samples, and directly predict the tissue elastic mechanical properties. The trained model is capable of identifying the overall tissue stiffness with a classification accuracy of 84%, and predicting the nonlinear anisotropic stress-strain curves with average regression errors of 0.021 and 0.031. Thus, this study demonstrates the feasibility and great potential of using the Deep Learning approach for fast and noninvasive assessment of collagenous tissue elastic properties from microstructural images. In this study, we developed, to our best knowledge, the first Deep Learning-based approach to estimate the elastic properties of collagenous tissues directly from noninvasive second harmonic generation images. The success of this study holds promise for the use of Machine Learning techniques to noninvasively and efficiently estimate the mechanical properties of many structure-based biological materials, and it also enables many potential applications such as serving as a quality control tool to select tissue for the manufacturing of medical devices (e.g. bioprosthetic heart valves). Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Photoacoustic tomography of foreign bodies in soft biological tissue.

PubMed

Cai, Xin; Kim, Chulhong; Pramanik, Manojit; Wang, Lihong V

2011-04-01

In detecting small foreign bodies in soft biological tissue, ultrasound imaging suffers from poor sensitivity (52.6%) and specificity (47.2%). Hence, alternative imaging methods are needed. Photoacoustic (PA) imaging takes advantage of strong optical absorption contrast and high ultrasonic resolution. A PA imaging system is employed to detect foreign bodies in biological tissues. To achieve deep penetration, we use near-infrared light ranging from 750 to 800 nm and a 5-MHz spherically focused ultrasonic transducer. PA images were obtained from various targets including glass, wood, cloth, plastic, and metal embedded more than 1 cm deep in chicken tissue. The locations and sizes of the targets from the PA images agreed well with those of the actual samples. Spectroscopic PA imaging was also performed on the objects. These results suggest that PA imaging can potentially be a useful intraoperative imaging tool to identify foreign bodies.

Clutter elimination for deep clinical optoacoustic imaging using localised vibration tagging (LOVIT)☆

PubMed Central

Jaeger, Michael; Bamber, Jeffrey C.; Frenz, Martin

2013-01-01

This paper investigates a novel method which allows clutter elimination in deep optoacoustic imaging. Clutter significantly limits imaging depth in clinical optoacoustic imaging, when irradiation optics and ultrasound detector are integrated in a handheld probe for flexible imaging of the human body. Strong optoacoustic transients generated at the irradiation site obscure weak signals from deep inside the tissue, either directly by propagating towards the probe, or via acoustic scattering. In this study we demonstrate that signals of interest can be distinguished from clutter by tagging them at the place of origin with localised tissue vibration induced by the acoustic radiation force in a focused ultrasonic beam. We show phantom results where this technique allowed almost full clutter elimination and thus strongly improved contrast for deep imaging. Localised vibration tagging by means of acoustic radiation force is especially promising for integration into ultrasound systems that already have implemented radiation force elastography. PMID:25302147

3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

PubMed

Montoya, J C; Li, Y; Strother, C; Chen, G-H

2018-05-01

Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral angiograms from a single contrast-enhanced C-arm conebeam CT acquisition in order to reduce image artifacts and radiation dose. A set of 105 3D rotational angiography examinations were randomly selected from an internal data base. All were acquired using a clinical system in conjunction with a standard injection protocol. More than 150 million labeled voxels from 35 subjects were used for training. A deep convolutional neural network was trained to classify each image voxel into 3 tissue types (vasculature, bone, and soft tissue). The trained deep learning angiography model was then applied for tissue classification into a validation cohort of 8 subjects and a final testing cohort of the remaining 62 subjects. The final vasculature tissue class was used to generate the 3D deep learning angiography images. To quantify the generalization error of the trained model, we calculated the accuracy, sensitivity, precision, and Dice similarity coefficients for vasculature classification in relevant anatomy. The 3D deep learning angiography and clinical 3D rotational angiography images were subjected to a qualitative assessment for the presence of intersweep motion artifacts. Vasculature classification accuracy and 95% CI in the testing dataset were 98.7% (98.3%-99.1%). No residual signal from osseous structures was observed for any 3D deep learning angiography testing cases except for small regions in the otic capsule and nasal cavity compared with 37% (23/62) of the 3D rotational angiographies. Deep learning angiography accurately recreated the vascular anatomy of the 3D rotational angiography reconstructions without a mask. Deep learning angiography reduced misregistration artifacts induced by intersweep motion, and it reduced radiation exposure required to obtain clinically useful 3D rotational angiography. © 2018 by American Journal of Neuroradiology.

Swept-source optical coherence tomography powered by a 1.3-μm vertical cavity surface emitting laser enables 2.3-mm-deep brain imaging in mice in vivo

NASA Astrophysics Data System (ADS)

Choi, Woo June; Wang, Ruikang K.

2015-10-01

We report noninvasive, in vivo optical imaging deep within a mouse brain by swept-source optical coherence tomography (SS-OCT), enabled by a 1.3-μm vertical cavity surface emitting laser (VCSEL). VCSEL SS-OCT offers a constant signal sensitivity of 105 dB throughout an entire depth of 4.25 mm in air, ensuring an extended usable imaging depth range of more than 2 mm in turbid biological tissue. Using this approach, we show deep brain imaging in mice with an open-skull cranial window preparation, revealing intact mouse brain anatomy from the superficial cerebral cortex to the deep hippocampus. VCSEL SS-OCT would be applicable to small animal studies for the investigation of deep tissue compartments in living brains where diseases such as dementia and tumor can take their toll.

A Dual-Modality System for Both Multi-Color Ultrasound-Switchable Fluorescence and Ultrasound Imaging

PubMed Central

Kandukuri, Jayanth; Yu, Shuai; Cheng, Bingbing; Bandi, Venugopal; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Yuan, Baohong

2017-01-01

Simultaneous imaging of multiple targets (SIMT) in opaque biological tissues is an important goal for molecular imaging in the future. Multi-color fluorescence imaging in deep tissues is a promising technology to reach this goal. In this work, we developed a dual-modality imaging system by combining our recently developed ultrasound-switchable fluorescence (USF) imaging technology with the conventional ultrasound (US) B-mode imaging. This dual-modality system can simultaneously image tissue acoustic structure information and multi-color fluorophores in centimeter-deep tissue with comparable spatial resolutions. To conduct USF imaging on the same plane (i.e., x-z plane) as US imaging, we adopted two 90°-crossed ultrasound transducers with an overlapped focal region, while the US transducer (the third one) was positioned at the center of these two USF transducers. Thus, the axial resolution of USF is close to the lateral resolution, which allows a point-by-point USF scanning on the same plane as the US imaging. Both multi-color USF and ultrasound imaging of a tissue phantom were demonstrated. PMID:28165390

In vivo deep tissue fluorescence imaging of the murine small intestine and colon

NASA Astrophysics Data System (ADS)

Crosignani, Viera; Dvornikov, Alexander; Aguilar, Jose S.; Stringari, Chiara; Edwards, Roberts; Mantulin, Williams; Gratton, Enrico

2012-03-01

Recently we described a novel technical approach with enhanced fluorescence detection capabilities in two-photon microscopy that achieves deep tissue imaging, while maintaining micron resolution. This technique was applied to in vivo imaging of murine small intestine and colon. Individuals with Inflammatory Bowel Disease (IBD), commonly presenting as Crohn's disease or Ulcerative Colitis, are at increased risk for developing colorectal cancer. We have developed a Giα2 gene knock out mouse IBD model that develops colitis and colon cancer. The challenge is to study the disease in the whole animal, while maintaining high resolution imaging at millimeter depth. In the Giα2-/- mice, we have been successful in imaging Lgr5-GFP positive stem cell reporters that are found in crypts of niche structures, as well as deeper structures, in the small intestine and colon at depths greater than 1mm. In parallel with these in vivo deep tissue imaging experiments, we have also pursued autofluorescence FLIM imaging of the colon and small intestine-at more shallow depths (roughly 160μm)- on commercial two photon microscopes with excellent structural correlation (in overlapping tissue regions) between the different technologies.

Automatic tissue image segmentation based on image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Musculoskeletal MRI findings of juvenile localized scleroderma.

PubMed

Eutsler, Eric P; Horton, Daniel B; Epelman, Monica; Finkel, Terri; Averill, Lauren W

2017-04-01

Juvenile localized scleroderma comprises a group of autoimmune conditions often characterized clinically by an area of skin hardening. In addition to superficial changes in the skin and subcutaneous tissues, juvenile localized scleroderma may involve the deep soft tissues, bones and joints, possibly resulting in functional impairment and pain in addition to cosmetic changes. There is literature documenting the spectrum of findings for deep involvement of localized scleroderma (fascia, muscles, tendons, bones and joints) in adults, but there is limited literature for the condition in children. We aimed to document the spectrum of musculoskeletal magnetic resonance imaging (MRI) findings of both superficial and deep juvenile localized scleroderma involvement in children and to evaluate the utility of various MRI sequences for detecting those findings. Two radiologists retrospectively evaluated 20 MRI studies of the extremities in 14 children with juvenile localized scleroderma. Each imaging sequence was also given a subjective score of 0 (not useful), 1 (somewhat useful) or 2 (most useful for detecting the findings). Deep tissue involvement was detected in 65% of the imaged extremities. Fascial thickening and enhancement were seen in 50% of imaged extremities. Axial T1, axial T1 fat-suppressed (FS) contrast-enhanced and axial fluid-sensitive sequences were rated most useful. Fascial thickening and enhancement were the most commonly encountered deep tissue findings in extremity MRIs of children with juvenile localized scleroderma. Because abnormalities of the skin, subcutaneous tissues and fascia tend to run longitudinally in an affected limb, axial T1, axial fluid-sensitive and axial T1-FS contrast-enhanced sequences should be included in the imaging protocol.

Breaking the acoustic diffraction limit via nonlinear effect and thermal confinement for potential deep-tissue high-resolution imaging

PubMed Central

Yuan, Baohong; Pei, Yanbo; Kandukuri, Jayanth

2013-01-01

Our recently developed ultrasound-switchable fluorescence (USF) imaging technique showed that it was feasible to conduct high-resolution fluorescence imaging in a centimeter-deep turbid medium. Because the spatial resolution of this technique highly depends on the ultrasound-induced temperature focal size (UTFS), minimization of UTFS becomes important for further improving the spatial resolution USF technique. In this study, we found that UTFS can be significantly reduced below the diffraction-limited acoustic intensity focal size via nonlinear acoustic effects and thermal confinement by appropriately controlling ultrasound power and exposure time, which can be potentially used for deep-tissue high-resolution imaging. PMID:23479498

Automated classification of multiphoton microscopy images of ovarian tissue using deep learning.

PubMed

Huttunen, Mikko J; Hassan, Abdurahman; McCloskey, Curtis W; Fasih, Sijyl; Upham, Jeremy; Vanderhyden, Barbara C; Boyd, Robert W; Murugkar, Sangeeta

2018-06-01

Histopathological image analysis of stained tissue slides is routinely used in tumor detection and classification. However, diagnosis requires a highly trained pathologist and can thus be time-consuming, labor-intensive, and potentially risk bias. Here, we demonstrate a potential complementary approach for diagnosis. We show that multiphoton microscopy images from unstained, reproductive tissues can be robustly classified using deep learning techniques. We fine-train four pretrained convolutional neural networks using over 200 murine tissue images based on combined second-harmonic generation and two-photon excitation fluorescence contrast, to classify the tissues either as healthy or associated with high-grade serous carcinoma with over 95% sensitivity and 97% specificity. Our approach shows promise for applications involving automated disease diagnosis. It could also be readily applied to other tissues, diseases, and related classification problems. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer

NASA Astrophysics Data System (ADS)

Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T. C.

2017-10-01

Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.

In Vivo Deep Tissue Fluorescence and Magnetic Imaging Employing Hybrid Nanostructures.

PubMed

Ortgies, Dirk H; de la Cueva, Leonor; Del Rosal, Blanca; Sanz-Rodríguez, Francisco; Fernández, Nuria; Iglesias-de la Cruz, M Carmen; Salas, Gorka; Cabrera, David; Teran, Francisco J; Jaque, Daniel; Martín Rodríguez, Emma

2016-01-20

Breakthroughs in nanotechnology have made it possible to integrate different nanoparticles in one single hybrid nanostructure (HNS), constituting multifunctional nanosized sensors, carriers, and probes with great potential in the life sciences. In addition, such nanostructures could also offer therapeutic capabilities to achieve a wider variety of multifunctionalities. In this work, the encapsulation of both magnetic and infrared emitting nanoparticles into a polymeric matrix leads to a magnetic-fluorescent HNS with multimodal magnetic-fluorescent imaging abilities. The magnetic-fluorescent HNS are capable of simultaneous magnetic resonance imaging and deep tissue infrared fluorescence imaging, overcoming the tissue penetration limits of classical visible-light based optical imaging as reported here in living mice. Additionally, their applicability for magnetic heating in potential hyperthermia treatments is assessed.

Molecular imaging needles: dual-modality optical coherence tomography and fluorescence imaging of labeled antibodies deep in tissue

PubMed Central

Scolaro, Loretta; Lorenser, Dirk; Madore, Wendy-Julie; Kirk, Rodney W.; Kramer, Anne S.; Yeoh, George C.; Godbout, Nicolas; Sampson, David D.; Boudoux, Caroline; McLaughlin, Robert A.

2015-01-01

Molecular imaging using optical techniques provides insight into disease at the cellular level. In this paper, we report on a novel dual-modality probe capable of performing molecular imaging by combining simultaneous three-dimensional optical coherence tomography (OCT) and two-dimensional fluorescence imaging in a hypodermic needle. The probe, referred to as a molecular imaging (MI) needle, may be inserted tens of millimeters into tissue. The MI needle utilizes double-clad fiber to carry both imaging modalities, and is interfaced to a 1310-nm OCT system and a fluorescence imaging subsystem using an asymmetrical double-clad fiber coupler customized to achieve high fluorescence collection efficiency. We present, to the best of our knowledge, the first dual-modality OCT and fluorescence needle probe with sufficient sensitivity to image fluorescently labeled antibodies. Such probes enable high-resolution molecular imaging deep within tissue. PMID:26137379

In vivo multiphoton microscopy beyond 1 mm in the brain

NASA Astrophysics Data System (ADS)

Miller, David R.; Medina, Flor A.; Hassan, Ahmed; Perillo, Evan P.; Hagan, Kristen; Kazmi, S. M. Shams; Zemelman, Boris V.; Dunn, Andrew K.

2017-02-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. We demonstrate an imaging depth of 1,200 μm in vasculature and 1,160 μm in neurons. We also demonstrate deep-tissue imaging using Indocyanine Green (ICG), which is FDA approved and a promising route to translate multiphoton microscopy to human applications.

A bright cyan-excitable orange fluorescent protein facilitates dual-emission microscopy and enhances bioluminescence imaging in vivo

PubMed Central

Chu, Jun; Oh, Young-Hee; Sens, Alex; Ataie, Niloufar; Dana, Hod; Macklin, John J.; Laviv, Tal; Welf, Erik S.; Dean, Kevin M.; Zhang, Feijie; Kim, Benjamin B.; Tang, Clement Tran; Hu, Michelle; Baird, Michelle A.; Davidson, Michael W.; Kay, Mark A.; Fiolka, Reto; Yasuda, Ryohei; Kim, Douglas S.; Ng, Ho-Leung; Lin, Michael Z.

2016-01-01

Orange-red fluorescent proteins (FPs) are widely used in biomedical research for multiplexed epifluorescence microscopy with GFP-based probes, but their different excitation requirements make multiplexing with new advanced microscopy methods difficult. Separately, orange-red FPs are useful for deep-tissue imaging in mammals due to the relative tissue transmissibility of orange-red light, but their dependence on illumination limits their sensitivity as reporters in deep tissues. Here we describe CyOFP1, a bright engineered orange-red FP that is excitable by cyan light. We show that CyOFP1 enables single-excitation multiplexed imaging with GFP-based probes in single-photon and two-photon microscopy, including time-lapse imaging in light-sheet systems. CyOFP1 also serves as an efficient acceptor for resonance energy transfer from the highly catalytic blue-emitting luciferase NanoLuc. An optimized fusion of CyOFP1 and NanoLuc, called Antares, functions as a highly sensitive bioluminescent reporter in vivo, producing substantially brighter signals from deep tissues than firefly luciferase and other bioluminescent proteins. PMID:27240196

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Study of Tissue Phantoms, Tissues, and Contrast Agent with the Biophotoacoustic Radar and Comparison to Ultrasound Imaging for Deep Subsurface Imaging

NASA Astrophysics Data System (ADS)

Alwi, R.; Telenkov, S.; Mandelis, A.; Gu, F.

2012-11-01

In this study, the imaging capability of our wide-spectrum frequency-domain photoacoustic (FD-PA) imaging alias "photoacoustic radar" methodology for imaging of soft tissues is explored. A practical application of the mathematical correlation processing method with relatively long (1 ms) frequency-modulated optical excitation is demonstrated for reconstruction of the spatial location of the PA sources. Image comparison with ultrasound (US) modality was investigated to see the complementarity between the two techniques. The obtained results with a phased array probe on tissue phantoms and their comparison to US images demonstrated that the FD-PA technique has strong potential for deep subsurface imaging with excellent contrast and high signal-to-noise ratio. FD-PA images of blood vessels in a human wrist and an in vivo subcutaneous tumor in a rat model are presented. As in other imaging modalities, the employment of contrast agents is desirable to improve the capability of medical diagnostics. Therefore, this study also evaluated and characterized the use of Food and Drug Administration (FDA)-approved superparamagnetic iron oxide nanoparticles (SPION) as PA contrast agents.

Automated assessment of breast tissue density in non-contrast 3D CT images without image segmentation based on a deep CNN

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.

ReagentTF: a rapid and versatile optical clearing method for biological imaging(Conference Presentation)

NASA Astrophysics Data System (ADS)

Yu, Tingting; Zhu, Jingtan; Li, Yusha; Qi, Yisong; Xu, Jianyi; Gong, Hui; Luo, Qingming; Zhu, Dan

2017-02-01

The emergence of various optical clearing methods provides a great potential for imaging deep inside tissues by combining with multiple-labelling and microscopic imaging techniques. They were generally developed for specific imaging demand thus presented some non-negligible limitations such as long incubation time, tissue deformation, fluorescence quenching, incompatibility with immunostaining or lipophilic tracers. In this study, we developed a rapid and versatile clearing method, termed ReagentTF, for deep imaging of various fluorescent samples. This method can not only efficiently clear embryos, neonatal whole-brains and adult thick brain sections by simple immersion in aqueous mixtures with minimal volume change, but also can preserve fluorescence of various fluorescent proteins and simultaneously be compatible with immunostaining and lipophilic neuronal dyes. We demonstrate the effectiveness of this method in reconstructing the cell distributions of mouse hippocampus, visualizing the neural projection from CA1 (Cornu Ammonis 1) to HDB (nucleus of the horizontal limb of the diagonal band), and observing the growth of forelimb plexus in whole-mount embryos. These results suggest that ReagentTF is useful for large-volume imaging and will be an option for the deep imaging of biological tissues.

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer.

PubMed

Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T C

2017-10-01

Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

M13 phage-functionalized single-walled carbon nanotubes as nanoprobes for second near-infrared window fluorescence imaging of targeted tumors.

PubMed

Yi, Hyunjung; Ghosh, Debadyuti; Ham, Moon-Ho; Qi, Jifa; Barone, Paul W; Strano, Michael S; Belcher, Angela M

2012-03-14

Second near-infrared (NIR) window light (950-1400 nm) is attractive for in vivo fluorescence imaging due to its deep penetration depth in tissues and low tissue autofluorescence. Here we show genetically engineered multifunctional M13 phage can assemble fluorescent single-walled carbon nanotubes (SWNTs) and ligands for targeted fluorescence imaging of tumors. M13-SWNT probe is detectable in deep tissues even at a low dosage of 2 μg/mL and up to 2.5 cm in tissue-like phantoms. Moreover, targeted probes show specific and up to 4-fold improved uptake in prostate specific membrane antigen positive prostate tumors compared to control nontargeted probes. This M13 phage-based second NIR window fluorescence imaging probe has great potential for specific detection and therapy monitoring of hard-to-detect areas. © 2012 American Chemical Society

M13 phage-functionalized single-walled carbon nanotubes as nanoprobes for second near-infrared window fluorescence imaging of targeted tumors

PubMed Central

HAM, MOON-HO; QI, JIFA; BARONE, PAUL W.; STRANO, MICHAEL S.; BELCHER, ANGELA M.

2014-01-01

Second near-infrared (NIR) window light (950-1,400 nm) is attractive for in vivo fluorescence imaging due to its deep penetration depth in tissues and low tissue autofluorescence. Here we show genetically engineered multifunctional M13 phage can assemble fluorescent single-walled carbon nanotubes (SWNTs) and ligands for targeted fluorescence imaging of tumors. M13-SWNT probe is detectable in deep tissues even at a low dosage of 2 μg/mL and up to 2.5 cm in tissue-like phantoms. Moreover, targeted probes show specific and up to four-fold improved uptake in prostate specific membrane antigen positive prostate tumors compared to control non-targeted probes. This M13 phage-based second NIR window fluorescence imaging probe has great potential for specific detection and therapy monitoring of hard-to-detect areas. PMID:22268625

Applications of two-photon fluorescence microscopy in deep-tissue imaging

NASA Astrophysics Data System (ADS)

Dong, Chen-Yuan; Yu, Betty; Hsu, Lily L.; Kaplan, Peter D.; Blankschstein, D.; Langer, Robert; So, Peter T. C.

2000-07-01

Based on the non-linear excitation of fluorescence molecules, two-photon fluorescence microscopy has become a significant new tool for biological imaging. The point-like excitation characteristic of this technique enhances image quality by the virtual elimination of off-focal fluorescence. Furthermore, sample photodamage is greatly reduced because fluorescence excitation is limited to the focal region. For deep tissue imaging, two-photon microscopy has the additional benefit in the greatly improved imaging depth penetration. Since the near- infrared laser sources used in two-photon microscopy scatter less than their UV/glue-green counterparts, in-depth imaging of highly scattering specimen can be greatly improved. In this work, we will present data characterizing both the imaging characteristics (point-spread-functions) and tissue samples (skin) images using this novel technology. In particular, we will demonstrate how blind deconvolution can be used further improve two-photon image quality and how this technique can be used to study mechanisms of chemically-enhanced, transdermal drug delivery.

Dual-mode imaging with radiolabeled gold nanorods

NASA Astrophysics Data System (ADS)

Agarwal, Ashish; Shao, Xia; Rajian, Justin R.; Zhang, Huanan; Chamberland, David L.; Kotov, Nicholas A.; Wang, Xueding

2011-05-01

Many nanoparticle contrast agents have difficulties with deep tissue and near-bone imaging due to limited penetration of visible photons in the body and mineralized tissues. We are looking into the possibility of mediating this problem while retaining the capabilities of the high spatial resolution associated with optical imaging. As such, the potential combination of emerging photoacoustic imaging and nuclear imaging in monitoring of antirheumatic drug delivery by using a newly developed dual-modality contrast agent is investigated. The contrast agent is composed of gold nanorods (GNRs) conjugated to the tumor necrosis factor (TNF-α) antibody and is subsequently radiolabeled by 125I. ELISA experiments designed to test TNF-α binding are performed to prove the specificity and biological activity of the radiolabeled conjugated contrast agent. Photoacoustic and nuclear imaging are performed to visualize the distribution of GNRs in articular tissues of the rat tail joints in situ. Findings from the two imaging modalities correspond well with each other in all experiments. Our system can image GNRs down to a concentration of 10 pM in biological tissues and with a radioactive label of 5 μCi. This study demonstrates the potential of combining photoacoustic and nuclear imaging modalities through one targeted contrast agent for noninvasive monitoring of drug delivery as well as deep and mineralized tissue imaging.

Versatile Polymer Nanoparticles as Two-Photon-Triggered Photosensitizers for Simultaneous Cellular, Deep-Tissue Imaging, and Photodynamic Therapy.

PubMed

Guo, Liang; Ge, Jiechao; Liu, Qian; Jia, Qingyan; Zhang, Hongyan; Liu, Weimin; Niu, Guangle; Liu, Sha; Gong, Jianru; Hackbarth, Steffen; Wang, Pengfei

2017-06-01

Clinical applications of current photodynamic therapy (PDT) photosensitizers (PSs) are often limited by their absorption in the UV-vis range that possesses limited tissue penetration ability, leading to ineffective therapeutic response for deep-seated tumors. Alternatively, two-photon excited PS (TPE-PS) using NIR light triggered is one the most promising candidates for PDT improvement. Herein, multimodal polymer nanoparticles (PNPs) from polythiophene derivative as two-photon fluorescence imaging as well as two-photon-excited PDT agent are developed. The prepared PNPs exhibit excellent water dispersibility, high photostability and pH stability, strong fluorescence brightness, and low dark toxicity. More importantly, the PNPs also possess other outstanding features including: (1) the high 1 O 2 quantum yield; (2) the strong two-photon-induced fluorescence and efficient 1 O 2 generation; (3) the specific accumulation in lysosomes of HeLa cells; and (4) the imaging detection depth up to 2100 µm in the mock tissue under two-photon. The multifunctional PNPs are promising candidates as TPE-PDT agent for simultaneous cellular, deep-tissue imaging, and highly efficient in vivo PDT of cancer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictive validity of granulation tissue color measured by digital image analysis for deep pressure ulcer healing: a multicenter prospective cohort study.

PubMed

Iizaka, Shinji; Kaitani, Toshiko; Sugama, Junko; Nakagami, Gojiro; Naito, Ayumi; Koyanagi, Hiroe; Konya, Chizuko; Sanada, Hiromi

2013-01-01

This multicenter prospective cohort study examined the predictive validity of granulation tissue color evaluated by digital image analysis for deep pressure ulcer healing. Ninety-one patients with deep pressure ulcers were followed for 3 weeks. From a wound photograph taken at baseline, an image representing the granulation red index (GRI) was processed in which a redder color represented higher values. We calculated the average GRI over granulation tissue and the proportion of pixels exceeding the threshold intensity of 80 for the granulation tissue surface (%GRI80) and wound surface (%wound red index 80). In the receiver operating characteristics curve analysis, most GRI parameters had adequate discriminative values for both improvement of the DESIGN-R total score and wound closure. Ulcers were categorized by the obtained cutoff points of the average GRI (≤80, >80), %GRI80 (≤55, >55-80, >80%), and %wound red index 80 (≤25, >25-50, >50%). In the linear mixed model, higher classes for all GRI parameters showed significantly greater relative improvement in overall wound severity during the 3 weeks after adjustment for patient characteristics and wound locations. Assessment of granulation tissue color by digital image analysis will be useful as an objective monitoring tool for granulation tissue quality or surrogate outcomes of pressure ulcer healing. © 2012 by the Wound Healing Society.

Deep, noninvasive imaging and surgical guidance of submillimeter tumors using targeted M13-stabilized single-walled carbon nanotubes

PubMed Central

Ghosh, Debadyuti; Bagley, Alexander F.; Na, Young Jeong; Birrer, Michael J.; Bhatia, Sangeeta N.; Belcher, Angela M.

2014-01-01

Highly sensitive detection of small, deep tumors for early diagnosis and surgical interventions remains a challenge for conventional imaging modalities. Second-window near-infrared light (NIR2, 950–1,400 nm) is promising for in vivo fluorescence imaging due to deep tissue penetration and low tissue autofluorescence. With their intrinsic fluorescence in the NIR2 regime and lack of photobleaching, single-walled carbon nanotubes (SWNTs) are potentially attractive contrast agents to detect tumors. Here, targeted M13 virus-stabilized SWNTs are used to visualize deep, disseminated tumors in vivo. This targeted nanoprobe, which uses M13 to stably display both tumor-targeting peptides and an SWNT imaging probe, demonstrates excellent tumor-to-background uptake and exhibits higher signal-to-noise performance compared with visible and near-infrared (NIR1) dyes for delineating tumor nodules. Detection and excision of tumors by a gynecological surgeon improved with SWNT image guidance and led to the identification of submillimeter tumors. Collectively, these findings demonstrate the promise of targeted SWNT nanoprobes for noninvasive disease monitoring and guided surgery. PMID:25214538

Deep, noninvasive imaging and surgical guidance of submillimeter tumors using targeted M13-stabilized single-walled carbon nanotubes.

PubMed

Ghosh, Debadyuti; Bagley, Alexander F; Na, Young Jeong; Birrer, Michael J; Bhatia, Sangeeta N; Belcher, Angela M

2014-09-23

Highly sensitive detection of small, deep tumors for early diagnosis and surgical interventions remains a challenge for conventional imaging modalities. Second-window near-infrared light (NIR2, 950-1,400 nm) is promising for in vivo fluorescence imaging due to deep tissue penetration and low tissue autofluorescence. With their intrinsic fluorescence in the NIR2 regime and lack of photobleaching, single-walled carbon nanotubes (SWNTs) are potentially attractive contrast agents to detect tumors. Here, targeted M13 virus-stabilized SWNTs are used to visualize deep, disseminated tumors in vivo. This targeted nanoprobe, which uses M13 to stably display both tumor-targeting peptides and an SWNT imaging probe, demonstrates excellent tumor-to-background uptake and exhibits higher signal-to-noise performance compared with visible and near-infrared (NIR1) dyes for delineating tumor nodules. Detection and excision of tumors by a gynecological surgeon improved with SWNT image guidance and led to the identification of submillimeter tumors. Collectively, these findings demonstrate the promise of targeted SWNT nanoprobes for noninvasive disease monitoring and guided surgery.

Realistic tissue visualization using photoacoustic image

NASA Astrophysics Data System (ADS)

Cho, Seonghee; Managuli, Ravi; Jeon, Seungwan; Kim, Jeesu; Kim, Chulhong

2018-02-01

Visualization methods are very important in biomedical imaging. As a technology that understands life, biomedical imaging has the unique advantage of providing the most intuitive information in the image. This advantage of biomedical imaging can be greatly improved by choosing a special visualization method. This is more complicated in volumetric data. Volume data has the advantage of containing 3D spatial information. Unfortunately, the data itself cannot directly represent the potential value. Because images are always displayed in 2D space, visualization is the key and creates the real value of volume data. However, image processing of 3D data requires complicated algorithms for visualization and high computational burden. Therefore, specialized algorithms and computing optimization are important issues in volume data. Photoacoustic-imaging is a unique imaging modality that can visualize the optical properties of deep tissue. Because the color of the organism is mainly determined by its light absorbing component, photoacoustic data can provide color information of tissue, which is closer to real tissue color. In this research, we developed realistic tissue visualization using acoustic-resolution photoacoustic volume data. To achieve realistic visualization, we designed specialized color transfer function, which depends on the depth of the tissue from the skin. We used direct ray casting method and processed color during computing shader parameter. In the rendering results, we succeeded in obtaining similar texture results from photoacoustic data. The surface reflected rays were visualized in white, and the reflected color from the deep tissue was visualized red like skin tissue. We also implemented the CUDA algorithm in an OpenGL environment for real-time interactive imaging.

Fiber-based tunable repetition rate source for deep tissue two-photon fluorescence microscopy.

PubMed

Charan, Kriti; Li, Bo; Wang, Mengran; Lin, Charles P; Xu, Chris

2018-05-01

Deep tissue multiphoton imaging requires high peak power to enhance signal and low average power to prevent thermal damage. Both goals can be advantageously achieved through laser repetition rate tuning instead of simply adjusting the average power. We show that the ideal repetition rate for deep two-photon imaging in the mouse brain is between 1 and 10 MHz, and we present a fiber-based source with an arbitrarily tunable repetition rate within this range. The performance of the new source is compared to a mode-locked Ti:Sapphire (Ti:S) laser for in vivo imaging of mouse brain vasculature. At 2.5 MHz, the fiber source requires 5.1 times less average power to obtain the same signal as a standard Ti:S laser operating at 80 MHz.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

New approaches in renal microscopy: volumetric imaging and superresolution microscopy.

PubMed

Kim, Alfred H J; Suleiman, Hani; Shaw, Andrey S

2016-05-01

Histologic and electron microscopic analysis of the kidney has provided tremendous insight into structures such as the glomerulus and nephron. Recent advances in imaging, such as deep volumetric approaches and superresolution microscopy, have the capacity to dramatically enhance our current understanding of the structure and function of the kidney. Volumetric imaging can generate images millimeters below the surface of the intact kidney. Superresolution microscopy breaks the diffraction barrier inherent in traditional light microscopy, enabling the visualization of fine structures. Here, we describe new approaches to deep volumetric and superresolution microscopy of the kidney. Rapid advances in lasers, microscopic objectives, and tissue preparation have transformed our ability to deep volumetric image the kidney. Innovations in sample preparation have allowed for superresolution imaging with electron microscopy correlation, providing unprecedented insight into the structures within the glomerulus. Technological advances in imaging have revolutionized our capacity to image both large volumes of tissue and the finest structural details of a cell. These new advances have the potential to provide additional profound observations into the normal and pathologic functions of the kidney.

Energy-Looping Nanoparticles: Harnessing Excited-State Absorption for Deep-Tissue Imaging.

PubMed

Levy, Elizabeth S; Tajon, Cheryl A; Bischof, Thomas S; Iafrati, Jillian; Fernandez-Bravo, Angel; Garfield, David J; Chamanzar, Maysamreza; Maharbiz, Michel M; Sohal, Vikaas S; Schuck, P James; Cohen, Bruce E; Chan, Emory M

2016-09-27

Near infrared (NIR) microscopy enables noninvasive imaging in tissue, particularly in the NIR-II spectral range (1000-1400 nm) where attenuation due to tissue scattering and absorption is minimized. Lanthanide-doped upconverting nanocrystals are promising deep-tissue imaging probes due to their photostable emission in the visible and NIR, but these materials are not efficiently excited at NIR-II wavelengths due to the dearth of lanthanide ground-state absorption transitions in this window. Here, we develop a class of lanthanide-doped imaging probes that harness an energy-looping mechanism that facilitates excitation at NIR-II wavelengths, such as 1064 nm, that are resonant with excited-state absorption transitions but not ground-state absorption. Using computational methods and combinatorial screening, we have identified Tm(3+)-doped NaYF4 nanoparticles as efficient looping systems that emit at 800 nm under continuous-wave excitation at 1064 nm. Using this benign excitation with standard confocal microscopy, energy-looping nanoparticles (ELNPs) are imaged in cultured mammalian cells and through brain tissue without autofluorescence. The 1 mm imaging depths and 2 μm feature sizes are comparable to those demonstrated by state-of-the-art multiphoton techniques, illustrating that ELNPs are a promising class of NIR probes for high-fidelity visualization in cells and tissue.

Deep Learning in Medical Image Analysis.

PubMed

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

Multimodality molecular imaging and extracellular vesicle release based genetic profiling with porphyrin nanodroplets (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zemp, Roger J.; Paproski, Robert J.

2017-03-01

For emerging tissue-engineering applications, transplants, and cell-based therapies it is important to assess cell viability and function in vivo in deep tissues. Bioluminescence and fluorescence methods are poorly suited to deep monitoring applications with high resolution and require genetically-engineered reporters which are not always feasible. We report on a method for imaging cell viability using deep, high-resolution photoacoustic imaging. We use an exogenous dye, Resazurin, itself weakly fluorescent until it is reduced from blue to a pink color with bright red fluorescence. Upon cell death fluorescence is lost and an absorption shift is observed. The irreversible reaction of resazurin to resorufin is proportional to aerobic respiration. We detect colorimetric absorption shifts using multispectral photoacoustic imaging and quantify the fraction of viable cells. SKOV-3 cells with and without ±80oC heat treatment were imaged after Resazurin treatment. High 575nm:620nm ratiometric absorption and photoacoustic signals in viable cells were observed with a much lower ratio in low-viability populations.

Monitoring of tissue modification with optical coherence tomography

NASA Astrophysics Data System (ADS)

Zhang, Wei; Luo, Qingming; Yao, Lei; Cheng, Haiying; Zeng, Shaoqun

2002-04-01

An experimental monitoring of tissue modification of in vitro and in vivo rabbit dura mater with administration of osmotical agents, 40% glucose solution and glycerol, using optical coherence tomography was presented. The preliminary results of experimental study of influence of osmotical liquids (glucose solutions, glycerol) of rabbit dura mater were reported. The significant decreasing of the light from surface and increasing of the light from the deep of dura mater under action of osmotical solutions and the increasing of OCT imaging depth were demonstrated. Experiments showed that administration of osmolytes to dura mater allowed for effective and temporary control of its optical characteristics, which made dura mater more transparent, increased the ability of light penetrating the tissue, and consequently improved the optical imaging depth. It is a significant study, which can improve penetration of optical imaging of cerebral function and acquire more information of the deep brain tissue.

Fiber-based tunable repetition rate source for deep tissue two-photon fluorescence microscopy

PubMed Central

Charan, Kriti; Li, Bo; Wang, Mengran; Lin, Charles P.; Xu, Chris

2018-01-01

Deep tissue multiphoton imaging requires high peak power to enhance signal and low average power to prevent thermal damage. Both goals can be advantageously achieved through laser repetition rate tuning instead of simply adjusting the average power. We show that the ideal repetition rate for deep two-photon imaging in the mouse brain is between 1 and 10 MHz, and we present a fiber-based source with an arbitrarily tunable repetition rate within this range. The performance of the new source is compared to a mode-locked Ti:Sapphire (Ti:S) laser for in vivo imaging of mouse brain vasculature. At 2.5 MHz, the fiber source requires 5.1 times less average power to obtain the same signal as a standard Ti:S laser operating at 80 MHz. PMID:29760989

Prediction of Tissue Outcome and Assessment of Treatment Effect in Acute Ischemic Stroke Using Deep Learning.

PubMed

Nielsen, Anne; Hansen, Mikkel Bo; Tietze, Anna; Mouridsen, Kim

2018-06-01

Treatment options for patients with acute ischemic stroke depend on the volume of salvageable tissue. This volume assessment is currently based on fixed thresholds and single imagine modalities, limiting accuracy. We wish to develop and validate a predictive model capable of automatically identifying and combining acute imaging features to accurately predict final lesion volume. Using acute magnetic resonance imaging, we developed and trained a deep convolutional neural network (CNN deep ) to predict final imaging outcome. A total of 222 patients were included, of which 187 were treated with rtPA (recombinant tissue-type plasminogen activator). The performance of CNN deep was compared with a shallow CNN based on the perfusion-weighted imaging biomarker Tmax (CNN Tmax ), a shallow CNN based on a combination of 9 different biomarkers (CNN shallow ), a generalized linear model, and thresholding of the diffusion-weighted imaging biomarker apparent diffusion coefficient (ADC) at 600×10 -6 mm 2 /s (ADC thres ). To assess whether CNN deep is capable of differentiating outcomes of ±intravenous rtPA, patients not receiving intravenous rtPA were included to train CNN deep, -rtpa to access a treatment effect. The networks' performances were evaluated using visual inspection, area under the receiver operating characteristic curve (AUC), and contrast. CNN deep yields significantly better performance in predicting final outcome (AUC=0.88±0.12) than generalized linear model (AUC=0.78±0.12; P =0.005), CNN Tmax (AUC=0.72±0.14; P <0.003), and ADC thres (AUC=0.66±0.13; P <0.0001) and a substantially better performance than CNN shallow (AUC=0.85±0.11; P =0.063). Measured by contrast, CNN deep improves the predictions significantly, showing superiority to all other methods ( P ≤0.003). CNN deep also seems to be able to differentiate outcomes based on treatment strategy with the volume of final infarct being significantly different ( P =0.048). The considerable prediction improvement accuracy over current state of the art increases the potential for automated decision support in providing recommendations for personalized treatment plans. © 2018 American Heart Association, Inc.

An optical clearing technique for plant tissues allowing deep imaging and compatible with fluorescence microscopy.

PubMed

Warner, Cherish A; Biedrzycki, Meredith L; Jacobs, Samuel S; Wisser, Randall J; Caplan, Jeffrey L; Sherrier, D Janine

2014-12-01

We report on a nondestructive clearing technique that enhances transmission of light through specimens from diverse plant species, opening unique opportunities for microscope-enabled plant research. After clearing, plant organs and thick tissue sections are amenable to deep imaging. The clearing method is compatible with immunocytochemistry techniques and can be used in concert with common fluorescent probes, including widely adopted protein tags such as GFP, which has fluorescence that is preserved during the clearing process. © 2014 American Society of Plant Biologists. All Rights Reserved.

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.

Deep lamellar keratoplasty on air with lyophilised tissue.

PubMed Central

Chau, G K; Dilly, S A; Sheard, C E; Rostron, C K

1992-01-01

Deep lamellar keratoplasty on air involves injecting air into the corneal stroma to expand it to several times its normal thickness. This method is designed to facilitate dissection of the deep stroma and reduce the risk of perforation of Descemet's membrane when carrying out deep lamellar keratoplasty. We have modified the technique by using prelathed freeze-dried donor tissue and report our results in a series of patients with corneal stromal scarring owing to a variety of corneal problems, namely, keratoconus, pterygium, and herpes zoster ophthalmicus. All patients achieved best corrected postoperative visual acuity of 6/12 or better without problems associated with graft failure or rejection. Histopathological examination of corneal tissue following air injection showed surgical emphysema within the cornea and separation of deep stromal fibres from the underlying Descemet's membrane. Images PMID:1477037

A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head.

PubMed

Devalla, Sripad Krishna; Chin, Khai Sing; Mari, Jean-Martial; Tun, Tin A; Strouthidis, Nicholas G; Aung, Tin; Thiéry, Alexandre H; Girard, Michaël J A

2018-01-01

To develop a deep learning approach to digitally stain optical coherence tomography (OCT) images of the optic nerve head (ONH). A horizontal B-scan was acquired through the center of the ONH using OCT (Spectralis) for one eye of each of 100 subjects (40 healthy and 60 glaucoma). All images were enhanced using adaptive compensation. A custom deep learning network was then designed and trained with the compensated images to digitally stain (i.e., highlight) six tissue layers of the ONH. The accuracy of our algorithm was assessed (against manual segmentations) using the dice coefficient, sensitivity, specificity, intersection over union (IU), and accuracy. We studied the effect of compensation, number of training images, and performance comparison between glaucoma and healthy subjects. For images it had not yet assessed, our algorithm was able to digitally stain the retinal nerve fiber layer + prelamina, the RPE, all other retinal layers, the choroid, and the peripapillary sclera and lamina cribrosa. For all tissues, the dice coefficient, sensitivity, specificity, IU, and accuracy (mean) were 0.84 ± 0.03, 0.92 ± 0.03, 0.99 ± 0.00, 0.89 ± 0.03, and 0.94 ± 0.02, respectively. Our algorithm performed significantly better when compensated images were used for training (P < 0.001). Besides offering a good reliability, digital staining also performed well on OCT images of both glaucoma and healthy individuals. Our deep learning algorithm can simultaneously stain the neural and connective tissues of the ONH, offering a framework to automatically measure multiple key structural parameters of the ONH that may be critical to improve glaucoma management.

Adaptive focus for deep tissue using diffuse backscatter

NASA Astrophysics Data System (ADS)

Kress, Jeremy; Pourrezaei, Kambiz

2014-02-01

A system integrating high density diffuse optical imaging with adaptive optics using MEMS for deep tissue interaction is presented. In this system, a laser source is scanned over a high density fiber bundle using Digital Micromirror Device (DMD) and channeled to a tissue phantom. Backscatter is then collected from the tissue phantom by a high density fiber array of different fiber type and channeled to CMOS sensor for image acquisition. Intensity focus is directly verified using a second CMOS sensor which measures intensity transmitted though the tissue phantom. A set of training patterns are displayed on the DMD and backscatter is numerically fit to the transmission intensity. After the training patterns are displayed, adaptive focus is performed using only the backscatter and fitting functions. Additionally, tissue reconstruction and prediction of interference focusing by photoacoustic and optical tomographic methods is discussed. Finally, potential NIR applications such as in-vivo adaptive neural photostimulation and cancer targeting are discussed.

Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Halicek, Martin; Lu, Guolan; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

2017-06-01

Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.

In vivo tomographic imaging of deep seated cancer using fluorescence lifetime contrast

PubMed Central

Rice, William L.; Shcherbakova, Daria M; Verkusha, Vladislav V.; Kumar, Anand T.N.

2015-01-01

Preclinical cancer research would benefit from non-invasive imaging methods that allow tracking and visualization of early stage metastasis in vivo. While fluorescent proteins revolutionized intravital microscopy, two major challenges which still remain are tissue autofluorescence and hemoglobin absorption, which act to limit intravital optical techniques to large or subcutaneous tumors. Here we employ time-domain technology for the effective separation of tissue autofluorescence from extrinsic fluorophores, based on their distinct fluorescence lifetimes. Additionally, we employ cancer cells labelled with near infra-red fluorescent proteins (iRFP) to allow deep-tissue imaging. Our results demonstrate that time-domain imaging allows the detection of metastasis in deep-seated organs of living mice with a more than 20-fold increase in sensitivity compared to conventional continuous wave techniques. Furthermore, the distinct fluorescence lifetimes of each iRFP enables lifetime multiplexing of three different tumors, each expressing unique iRFP labels in the same animal. Fluorescence tomographic reconstructions reveal 3D distributions of iRFP720-expressing cancer cells in lungs and brain of live mice, allowing ready longitudinal monitoring of cancer cell fate with greater sensitivity than otherwise currently possible. PMID:25670171

Tutorial on photoacoustic tomography

NASA Astrophysics Data System (ADS)

Zhou, Yong; Yao, Junjie; Wang, Lihong V.

2016-06-01

Photoacoustic tomography (PAT) has become one of the fastest growing fields in biomedical optics. Unlike pure optical imaging, such as confocal microscopy and two-photon microscopy, PAT employs acoustic detection to image optical absorption contrast with high-resolution deep into scattering tissue. So far, PAT has been widely used for multiscale anatomical, functional, and molecular imaging of biological tissues. We focus on PAT's basic principles, major implementations, imaging contrasts, and recent applications.

3D printed optical phantoms and deep tissue imaging for in vivo applications including oral surgery

NASA Astrophysics Data System (ADS)

Bentz, Brian Z.; Costas, Alfonso; Gaind, Vaibhav; Garcia, Jose M.; Webb, Kevin J.

2017-03-01

Progress in developing optical imaging for biomedical applications requires customizable and often complex objects known as "phantoms" for testing, evaluation, and calibration. This work demonstrates that 3D printing is an ideal method for fabricating such objects, allowing intricate inhomogeneities to be placed at exact locations in complex or anatomically realistic geometries, a process that is difficult or impossible using molds. We show printed mouse phantoms we have fabricated for developing deep tissue fluorescence imaging methods, and measurements of both their optical and mechanical properties. Additionally, we present a printed phantom of the human mouth that we use to develop an artery localization method to assist in oral surgery.

Deep multi-spectral ensemble learning for electronic cleansing in dual-energy CT colonography

NASA Astrophysics Data System (ADS)

Tachibana, Rie; Näppi, Janne J.; Hironaka, Toru; Kim, Se Hyung; Yoshida, Hiroyuki

2017-03-01

We developed a novel electronic cleansing (EC) method for dual-energy CT colonography (DE-CTC) based on an ensemble deep convolution neural network (DCNN) and multi-spectral multi-slice image patches. In the method, an ensemble DCNN is used to classify each voxel of a DE-CTC image volume into five classes: luminal air, soft tissue, tagged fecal materials, and partial-volume boundaries between air and tagging and those between soft tissue and tagging. Each DCNN acts as a voxel classifier, where an input image patch centered at the voxel is generated as input to the DCNNs. An image patch has three channels that are mapped from a region-of-interest containing the image plane of the voxel and the two adjacent image planes. Six different types of spectral input image datasets were derived using two dual-energy CT images, two virtual monochromatic images, and two material images. An ensemble DCNN was constructed by use of a meta-classifier that combines the output of multiple DCNNs, each of which was trained with a different type of multi-spectral image patches. The electronically cleansed CTC images were calculated by removal of regions classified as other than soft tissue, followed by a colon surface reconstruction. For pilot evaluation, 359 volumes of interest (VOIs) representing sources of subtraction artifacts observed in current EC schemes were sampled from 30 clinical CTC cases. Preliminary results showed that the ensemble DCNN can yield high accuracy in labeling of the VOIs, indicating that deep learning of multi-spectral EC with multi-slice imaging could accurately remove residual fecal materials from CTC images without generating major EC artifacts.

In vivo mapping of current density distribution in brain tissues during deep brain stimulation (DBS)

NASA Astrophysics Data System (ADS)

Sajib, Saurav Z. K.; Oh, Tong In; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-01-01

New methods for in vivo mapping of brain responses during deep brain stimulation (DBS) are indispensable to secure clinical applications. Assessment of current density distribution, induced by internally injected currents, may provide an alternative method for understanding the therapeutic effects of electrical stimulation. The current flow and pathway are affected by internal conductivity, and can be imaged using magnetic resonance-based conductivity imaging methods. Magnetic resonance electrical impedance tomography (MREIT) is an imaging method that can enable highly resolved mapping of electromagnetic tissue properties such as current density and conductivity of living tissues. In the current study, we experimentally imaged current density distribution of in vivo canine brains by applying MREIT to electrical stimulation. The current density maps of three canine brains were calculated from the measured magnetic flux density data. The absolute current density values of brain tissues, including gray matter, white matter, and cerebrospinal fluid were compared to assess the active regions during DBS. The resulting current density in different tissue types may provide useful information about current pathways and volume activation for adjusting surgical planning and understanding the therapeutic effects of DBS.

Tutorial on photoacoustic tomography

PubMed Central

Zhou, Yong; Yao, Junjie; Wang, Lihong V.

2016-01-01

Abstract. Photoacoustic tomography (PAT) has become one of the fastest growing fields in biomedical optics. Unlike pure optical imaging, such as confocal microscopy and two-photon microscopy, PAT employs acoustic detection to image optical absorption contrast with high-resolution deep into scattering tissue. So far, PAT has been widely used for multiscale anatomical, functional, and molecular imaging of biological tissues. We focus on PAT’s basic principles, major implementations, imaging contrasts, and recent applications. PMID:27086868

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization.

PubMed

Kainz, Philipp; Pfeiffer, Michael; Urschler, Martin

2017-01-01

Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses.

Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

PubMed Central

Kainz, Philipp; Pfeiffer, Michael

2017-01-01

Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses. PMID:29018612

Ultrasonically Encoded Photoacoustic Flowgraphy in Biological Tissue

NASA Astrophysics Data System (ADS)

Wang, Lidai; Xia, Jun; Yao, Junjie; Maslov, Konstantin I.; Wang, Lihong V.

2013-11-01

Blood flow speed is an important functional parameter. Doppler ultrasound flowmetry lacks sufficient sensitivity to slow blood flow (several to tens of millimeters per second) in deep tissue. To address this challenge, we developed ultrasonically encoded photoacoustic flowgraphy combining ultrasonic thermal tagging with photoacoustic imaging. Focused ultrasound generates a confined heat source in acoustically absorptive fluid. Thermal waves propagate with the flow and are directly visualized in pseudo color using photoacoustic computed tomography. The Doppler shift is employed to calculate the flow speed. This method requires only acoustic and optical absorption, and thus is applicable to continuous fluid. A blood flow speed as low as 0.24mm·s-1 was successfully measured. Deep blood flow imaging was experimentally demonstrated under 5-mm-thick chicken breast tissue.

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

NASA Astrophysics Data System (ADS)

Wei, Lu; Zhu, Xinxin; Chen, Zhixing; Min, Wei

2014-02-01

Two-photon excited fluorescence microscopy (TPFM) offers the highest penetration depth with subcellular resolution in light microscopy, due to its unique advantage of nonlinear excitation. However, a fundamental imaging-depth limit, accompanied by a vanishing signal-to-background contrast, still exists for TPFM when imaging deep into scattering samples. Formally, the focusing depth, at which the in-focus signal and the out-of-focus background are equal to each other, is defined as the fundamental imaging-depth limit. To go beyond this imaging-depth limit of TPFM, we report a new class of super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging, including multiphoton activation and imaging (MPAI) harnessing novel photo-activatable fluorophores, stimulated emission reduced fluorescence (SERF) microscopy by adding a weak laser beam for stimulated emission, and two-photon induced focal saturation imaging with preferential depletion of ground-state fluorophores at focus. The resulting image contrasts all exhibit a higher-order (third- or fourth- order) nonlinear signal dependence on laser intensity than that in the standard TPFM. Both the physical principles and the imaging demonstrations will be provided for each super-nonlinear microscopy. In all these techniques, the created super-nonlinearity significantly enhances the imaging contrast and concurrently extends the imaging depth-limit of TPFM. Conceptually different from conventional multiphoton processes mediated by virtual states, our strategy constitutes a new class of fluorescence microscopy where high-order nonlinearity is mediated by real population transfer.

Focusing light through biological tissue and tissue-mimicking phantoms up to 9.6 cm in thickness with digital optical phase conjugation

NASA Astrophysics Data System (ADS)

Shen, Yuecheng; Liu, Yan; Ma, Cheng; Wang, Lihong V.

2016-08-01

Optical phase conjugation (OPC)-based wavefront shaping techniques focus light through or within scattering media, which is critically important for deep-tissue optical imaging, manipulation, and therapy. However, to date, the sample thickness in OPC experiments has been limited to only a few millimeters. Here, by using a laser with a long coherence length and an optimized digital OPC system that can safely deliver more light power, we focused 532-nm light through tissue-mimicking phantoms up to 9.6 cm thick, as well as through ex vivo chicken breast tissue up to 2.5 cm thick. Our results demonstrate that OPC can be achieved even when photons have experienced on average 1000 scattering events. The demonstrated penetration of nearly 10 cm (˜100 transport mean free paths) has never been achieved before by any optical focusing technique, and it shows the promise of OPC for deep-tissue noninvasive optical imaging, manipulation, and therapy.

An integrated single- and two-photon non-diffracting light-sheet microscope

NASA Astrophysics Data System (ADS)

Lau, Sze Cheung; Chiu, Hoi Chun; Zhao, Luwei; Zhao, Teng; Loy, M. M. T.; Du, Shengwang

2018-04-01

We describe a fluorescence optical microscope with both single-photon and two-photon non-diffracting light-sheet excitations for large volume imaging. With a special design to accommodate two different wavelength ranges (visible: 400-700 nm and near infrared: 800-1200 nm), we combine the line-Bessel sheet (LBS, for single-photon excitation) and the scanning Bessel beam (SBB, for two-photon excitation) light sheet together in a single microscope setup. For a transparent thin sample where the scattering can be ignored, the LBS single-photon excitation is the optimal imaging solution. When the light scattering becomes significant for a deep-cell or deep-tissue imaging, we use SBB light-sheet two-photon excitation with a longer wavelength. We achieved nearly identical lateral/axial resolution of about 350/270 nm for both imagings. This integrated light-sheet microscope may have a wide application for live-cell and live-tissue three-dimensional high-speed imaging.

Joint deep shape and appearance learning: application to optic pathway glioma segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Li, Ien; Packer, Roger J.; Avery, Robert A.; Linguraru, Marius George

2017-03-01

Automated tissue characterization is one of the major applications of computer-aided diagnosis systems. Deep learning techniques have recently demonstrated impressive performance for the image patch-based tissue characterization. However, existing patch-based tissue classification techniques struggle to exploit the useful shape information. Local and global shape knowledge such as the regional boundary changes, diameter, and volumetrics can be useful in classifying the tissues especially in scenarios where the appearance signature does not provide significant classification information. In this work, we present a deep neural network-based method for the automated segmentation of the tumors referred to as optic pathway gliomas (OPG) located within the anterior visual pathway (AVP; optic nerve, chiasm or tracts) using joint shape and appearance learning. Voxel intensity values of commonly used MRI sequences are generally not indicative of OPG. To be considered an OPG, current clinical practice dictates that some portion of AVP must demonstrate shape enlargement. The method proposed in this work integrates multiple sequence magnetic resonance image (T1, T2, and FLAIR) along with local boundary changes to train a deep neural network. For training and evaluation purposes, we used a dataset of multiple sequence MRI obtained from 20 subjects (10 controls, 10 NF1+OPG). To our best knowledge, this is the first deep representation learning-based approach designed to merge shape and multi-channel appearance data for the glioma detection. In our experiments, mean misclassification errors of 2:39% and 0:48% were observed respectively for glioma and control patches extracted from the AVP. Moreover, an overall dice similarity coefficient of 0:87+/-0:13 (0:93+/-0:06 for healthy tissue, 0:78+/-0:18 for glioma tissue) demonstrates the potential of the proposed method in the accurate localization and early detection of OPG.

Engineering of bacterial phytochromes for in vivo imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Verkhusha, Vladislav; Shcherbakova, Daria M.; Kaberniuk, Andrii A.; Baloban, Mikhail

2017-03-01

Genetically encoded probes with absorbance and fluorescence spectra within a near-infrared tissue transparency window are preferable for deep-tissue imaging. On the basis of bacterial phytochromes we engineered several types of near-infrared absorbing probes for photoacoustic tomography and fluorescent probes for purely optical imaging. They can be used as protein and cell labels and as building blocks for biosensors. The probes enabled imaging of tumors and metastases, protein-protein interactions, RNA visualization, detection of apoptosis, cellular metabolites, signaling pathways and cell proliferation. The developed probes allow non-invasive visualization of biological processes across scales, from super-resolution microscopy to tissue and whole-body animal imaging.

Biocompatible near-infrared fluorescent nanoparticles for macro and microscopic in vivo functional bioimaging

PubMed Central

Chu, Liliang; Wang, Shaowei; Li, Kanghui; Xi, Wang; Zhao, Xinyuan; Qian, Jun

2014-01-01

Near-infrared (NIR) imaging technology has been widely used for biomedical research and applications, since it can achieve deep penetration in biological tissues due to less absorption and scattering of NIR light. In our research, polymer nanoparticles with NIR fluorophores doped were synthesized. The morphology, absorption/emission features and chemical stability of the fluorescent nanoparticles were characterized, separately. NIR fluorescent nanoparticles were then utilized as bright optical probes for macro in vivo imaging of mice, including sentinel lymph node (SLN) mapping, as well as distribution and excretion monitoring of nanoparticles in animal body. Furthermore, we applied the NIR fluorescent nanoparticles in in vivo microscopic bioimaging via a confocal microscope. Under the 635 nm-CW excitation, the blood vessel architecture in the ear and the brain of mice, which were administered with nanoparticles, was visualized very clearly. The imaging depth of our one-photon microscopy, which was assisted with NIR fluorescent nanoprobes, can reach as deep as 500 μm. Our experiments show that NIR fluorescent nanoparticles have great potentials in various deep-tissue imaging applications. PMID:25426331

Automatical and accurate segmentation of cerebral tissues in fMRI dataset with combination of image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.

Ballistic and snake photon imaging for locating optical endomicroscopy fibres

PubMed Central

Tanner, M. G.; Choudhary, T. R.; Craven, T. H.; Mills, B.; Bradley, M.; Henderson, R. K.; Dhaliwal, K.; Thomson, R. R.

2017-01-01

We demonstrate determination of the location of the distal-end of a fibre-optic device deep in tissue through the imaging of ballistic and snake photons using a time resolved single-photon detector array. The fibre was imaged with centimetre resolution, within clinically relevant settings and models. This technique can overcome the limitations imposed by tissue scattering in optically determining the in vivo location of fibre-optic medical instruments. PMID:28966848

Time-lapse imaging of disease progression in deep brain areas using fluorescence microendoscopy

PubMed Central

Barretto, Robert P. J.; Ko, Tony H.; Jung, Juergen C.; Wang, Tammy J.; Capps, George; Waters, Allison C.; Ziv, Yaniv; Attardo, Alessio; Recht, Lawrence; Schnitzer, Mark J.

2013-01-01

The combination of intravital microscopy and animal models of disease has propelled studies of disease mechanisms and treatments. However, many disorders afflict tissues inaccessible to light microscopy in live subjects. Here we introduce cellular-level time-lapse imaging deep within the live mammalian brain by one- and two-photon fluorescence microendoscopy over multiple weeks. Bilateral imaging sites allowed longitudinal comparisons within individual subjects, including of normal and diseased tissues. Using this approach we tracked CA1 hippocampal pyramidal neuron dendrites in adult mice, revealing these dendrites' extreme stability (>8,000 day mean lifetime) and rare examples of their structural alterations. To illustrate disease studies, we tracked deep lying gliomas by observing tumor growth, visualizing three-dimensional vasculature structure, and determining microcirculatory speeds. Average erythrocyte speeds in gliomas declined markedly as the disease advanced, notwithstanding significant increases in capillary diameters. Time-lapse microendoscopy will be applicable to studies of numerous disorders, including neurovascular, neurological, cancerous, and trauma-induced conditions. PMID:21240263

Optoacoustic imaging of gold nanoparticles targeted to breast cancer cells

NASA Astrophysics Data System (ADS)

Eghtedari, Mohammad; Motamedi, Massoud; Popov, Vsevolod L.; Kotov, Nicholas A.; Oraevsky, Alexander A.

2004-07-01

Optoacoustic Tomography (OAT) is a rapidly growing technology that enables noninvasive deep imaging of biological tissues based on their light absorption. In OAT, the interaction of a pulsed laser with tissue increases the temperature of the absorbing components in a confined volume of tissue. Rapid perturbation of the temperature (<1°C) deep within tissue produces weak acoustic waves that easily travel to the surface of the tissue with minor attenuation. Abnormal angiogenesis in a malignant tumor, that increases its blood content, makes a native contrast for optoacoustic imaging; however, the application of OAT for early detection of malignant tumors requires the enhancement of optoacoustic signals originated from tumor by using an exogenous contrast agent. Due to their strong absorption, we have used gold nanoparticles (NP) as a contrast agent. 40nm spherical gold nanoparticles were attached to monoclonal antibody to target cell surface of breast cancer cells. The targeted cancer cells were implanted at depth of 5-6cm within a gelatinous object that optically resembles human breast. Experimental sensitivity measurements along with theoretical analysis showed that our optoacoustic imaging system is capable of detecting a phantom breast tumor with the volume of 0.15ml, which is composed of 25 million NP-targeted cancer cells, at a depth of 5 centimeters in vitro.

Longitudinal in vivo two-photon fluorescence imaging

PubMed Central

Crowe, Sarah E.; Ellis-Davies, Graham C.R.

2014-01-01

Fluorescence microscopy is an essential technique for the basic sciences, especially biomedical research. Since the invention of laser scanning confocal microscopy in 1980s, that enabled imaging both fixed and living biological tissue with three-dimensional precision, high-resolution fluorescence imaging has revolutionized biological research. Confocal microscopy, by its very nature, has one fundamental limitation. Due to the confocal pinhole, deep tissue fluorescence imaging is not practical. In contrast (no pun intended), two-photon fluorescence microscopy allows, in principle, the collection of all emitted photons from fluorophores in the imaged voxel, dramatically extending our ability to see deep into living tissue. Since the development of transgenic mice with genetically encoded fluorescent protein in neocortical cells in 2000, two-photon imaging has enabled the dynamics of individual synapses to be followed for up to two years. Since the initial landmark contributions to this field in 2002, the technique has been used to understand how neuronal structure are changed by experience, learning and memory and various diseases. Here we provide a basic summary of the crucial elements that are required for such studies, and discuss many applications of longitudinal two-photon fluorescence microscopy that have appeared since 2002. PMID:24214350

Image processing and 3D visualization in the interpretation of patterned injury of the skin

NASA Astrophysics Data System (ADS)

Oliver, William R.; Altschuler, Bruce R.

1995-09-01

The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing in the analysis of patterned injuries and tissue damage. Our interests are currently concentrated on 1) the use of image processing techniques to aid the investigator in observing and evaluating patterned injuries in photographs, 2) measurement of the 3D shape characteristics of surface lesions, and 3) correlation of patterned injuries with deep tissue injury as a problem in 3D visualization. We are beginning investigations in data-acquisition problems for performing 3D scene reconstructions from the pathology perspective of correlating tissue injury to scene features and trace evidence localization. Our primary tool for correlation of surface injuries with deep tissue injuries has been the comparison of processed surface injury photographs with 3D reconstructions from antemortem CT and MRI data. We have developed a prototype robot for the acquisition of 3D wound and scene data.

Three-Dimensional Imaging of the Intracellular Fate of Plasmid DNA and Transgene Expression: ZsGreen1 and Tissue Clearing Method CUBIC Are an Optimal Combination for Multicolor Deep Imaging in Murine Tissues.

PubMed

Fumoto, Shintaro; Nishimura, Koyo; Nishida, Koyo; Kawakami, Shigeru

2016-01-01

Evaluation methods for determining the distribution of transgene expression in the body and the in vivo fate of viral and non-viral vectors are necessary for successful development of in vivo gene delivery systems. Here, we evaluated the spatial distribution of transgene expression using tissue clearing methods. After hydrodynamic injection of plasmid DNA into mice, whole tissues were subjected to tissue clearing. Tissue clearing followed by confocal laser scanning microscopy enabled evaluation of the three-dimensional distribution of transgene expression without preparation of tissue sections. Among the tested clearing methods (ClearT2, SeeDB, and CUBIC), CUBIC was the most suitable method for determining the spatial distribution of transgene expression in not only the liver but also other tissues such as the kidney and lung. In terms of the type of fluorescent protein, the observable depth for green fluorescent protein ZsGreen1 was slightly greater than that for red fluorescent protein tdTomato. We observed a depth of ~1.5 mm for the liver and 500 μm for other tissues without preparation of tissue sections. Furthermore, we succeeded in multicolor deep imaging of the intracellular fate of plasmid DNA in the murine liver. Thus, tissue clearing would be a powerful approach for determining the spatial distribution of plasmid DNA and transgene expression in various murine tissues.

Designed Er(3+)-singly doped NaYF4 with double excitation bands for simultaneous deep macroscopic and microscopic upconverting bioimaging.

PubMed

Wen, Xuanyuan; Wang, Baoju; Wu, Ruitao; Li, Nana; He, Sailing; Zhan, Qiuqiang

2016-06-01

Simultaneous deep macroscopic imaging and microscopic imaging is in urgent demand, but is challenging to achieve experimentally due to the lack of proper fluorescent probes. Herein, we have designed and successfully synthesized simplex Er(3+)-doped upconversion nanoparticles (UCNPs) with double excitation bands for simultaneous deep macroscopic and microscopic imaging. The material structure and the excitation wavelength of Er(3+)-singly doped UCNPs were further optimized to enhance the upconversion emission efficiency. After optimization, we found that NaYF4:30%Er(3+)@NaYF4:2%Er(3+) could simultaneously achieve efficient two-photon excitation (2PE) macroscopic tissue imaging and three-photon excitation (3PE) deep microscopic when excited by 808 nm continuous wave (CW) and 1480 nm CW lasers, respectively. In vitro cell imaging and in vivo imaging have also been implemented to demonstrate the feasibility and potential of the proposed simplex Er(3+)-doped UCNPs as bioprobe.

Ultrafast fluorescence imaging in vivo with conjugated polymer fluorophores in the second near-infrared window

NASA Astrophysics Data System (ADS)

Hong, Guosong; Zou, Yingping; Antaris, Alexander L.; Diao, Shuo; Wu, Di; Cheng, Kai; Zhang, Xiaodong; Chen, Changxin; Liu, Bo; He, Yuehui; Wu, Justin Z.; Yuan, Jun; Zhang, Bo; Tao, Zhimin; Fukunaga, Chihiro; Dai, Hongjie

2014-06-01

In vivo fluorescence imaging in the second near-infrared window (1.0-1.7 μm) can afford deep tissue penetration and high spatial resolution, owing to the reduced scattering of long-wavelength photons. Here we synthesize a series of low-bandgap donor/acceptor copolymers with tunable emission wavelengths of 1,050-1,350 nm in this window. Non-covalent functionalization with phospholipid-polyethylene glycol results in water-soluble and biocompatible polymeric nanoparticles, allowing for live cell molecular imaging at >1,000 nm with polymer fluorophores for the first time. Importantly, the high quantum yield of the polymer allows for in vivo, deep-tissue and ultrafast imaging of mouse arterial blood flow with an unprecedented frame rate of >25 frames per second. The high time-resolution results in spatially and time resolved imaging of the blood flow pattern in cardiogram waveform over a single cardiac cycle (~200 ms) of a mouse, which has not been observed with fluorescence imaging in this window before.

Deep learning classifier with optical coherence tomography images for early dental caries detection

NASA Astrophysics Data System (ADS)

Karimian, Nima; Salehi, Hassan S.; Mahdian, Mina; Alnajjar, Hisham; Tadinada, Aditya

2018-02-01

Dental caries is a microbial disease that results in localized dissolution of the mineral content of dental tissue. Despite considerable decline in the incidence of dental caries, it remains a major health problem in many societies. Early detection of incipient lesions at initial stages of demineralization can result in the implementation of non-surgical preventive approaches to reverse the demineralization process. In this paper, we present a novel approach combining deep convolutional neural networks (CNN) and optical coherence tomography (OCT) imaging modality for classification of human oral tissues to detect early dental caries. OCT images of oral tissues with various densities were input to a CNN classifier to determine variations in tissue densities resembling the demineralization process. The CNN automatically learns a hierarchy of increasingly complex features and a related classifier directly from training data sets. The initial CNN layer parameters were randomly selected. The training set is split into minibatches, with 10 OCT images per batch. Given a batch of training patches, the CNN employs two convolutional and pooling layers to extract features and then classify each patch based on the probabilities from the SoftMax classification layer (output-layer). Afterward, the CNN calculates the error between the classification result and the reference label, and then utilizes the backpropagation process to fine-tune all the layer parameters to minimize this error using batch gradient descent algorithm. We validated our proposed technique on ex-vivo OCT images of human oral tissues (enamel, cortical-bone, trabecular-bone, muscular-tissue, and fatty-tissue), which attested to effectiveness of our proposed method.

Ultrasound modulation of bioluminescence generated inside a turbid medium

NASA Astrophysics Data System (ADS)

Ahmad, Junaid; Jayet, Baptiste; Hill, Philip J.; Mather, Melissa L.; Dehghani, Hamid; Morgan, Stephen P.

2017-03-01

In vivo bioluminescence imaging (BLI) has poor spatial resolution owing to strong light scattering by tissue, which also affects quantitative accuracy. This paper proposes a hybrid acousto-optic imaging platform that images bioluminescence modulated at ultrasound (US) frequency inside an optically scattering medium. This produces an US modulated light within the tissue that reduces the effects of light scattering and improves the spatial resolution. The system consists of a continuously excited 3.5 MHz US transducer applied to a tissue like phantom of known optical properties embedded with bio-or chemiluminescent sources that are used to mimic in vivo experiments. Scanning US over the turbid medium modulates the luminescent sources deep inside tissue at several US scan points. These modulated signals are recorded by a photomultiplier tube and lock-in detection to generate a 1D profile. Indeed, high frequency US enables small focal volume to improve spatial resolution, but this leads to lower signal-to-noise ratio. First experimental results show that US enables localization of a small luminescent source (around 2 mm wide) deep ( 20 mm) inside a tissue phantom having a scattering coefficient of 80 cm-1. Two sources separated by 10 mm could be resolved 20 mm inside a chicken breast.

In Vivo Fluorescence Resonance Energy Transfer Imaging for Targeted Anti-Cancer Drug Delivery Kinetics

NASA Astrophysics Data System (ADS)

Webb, Kevin; Gaind, Vaibhav; Tsai, Hsiaorho; Bentz, Brian; Chelvam, Venkatesh; Low, Philip

2012-02-01

We describe an approach for the evaluation of targeted anti-cancer drug delivery in vivo. The method emulates the drug release and activation process through acceptor release from a targeted donor-acceptor pair that exhibits fluorescence resonance energy transfer (FRET). In this case, folate targeting of the cancer cells is used - 40 % of all human cancers, including ovarian, lung, breast, kidney, brain and colon cancer, over-express folate receptors. We demonstrate the reconstruction of the spatially-dependent FRET parameters in a mouse model and in tissue phantoms. The FRET parameterization is incorporated into a source for a diffusion equation model for photon transport in tissue, in a variant of optical diffusion tomography (ODT) called FRET-ODT. In addition to the spatially-dependent tissue parameters in the diffusion model (absorption and diffusion coefficients), the FRET parameters (donor-acceptor distance and yield) are imaged as a function of position. Modulated light measurements are made with various laser excitation positions and a gated camera. More generally, our method provides a new vehicle for studying disease at the molecular level by imaging FRET parameters in deep tissue, and allows the nanometer FRET ruler to be utilized in deep tissue.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

NASA Astrophysics Data System (ADS)

Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan

2016-03-01

Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non-epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin-eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long-term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04-4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84-3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99-3.88, AUC 0.61). As a conclusion, a deep-learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.

An interventional multispectral photoacoustic imaging platform for the guidance of minimally invasive procedures

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; Nikitichev, Daniil I.; Mari, Jean Martial; West, Simeon J.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2015-07-01

Precise and efficient guidance of medical devices is of paramount importance for many minimally invasive procedures. These procedures include fetal interventions, tumor biopsies and treatments, central venous catheterisations and peripheral nerve blocks. Ultrasound imaging is commonly used for guidance, but it often provides insufficient contrast with which to identify soft tissue structures such as vessels, tumors, and nerves. In this study, a hybrid interventional imaging system that combines ultrasound imaging and multispectral photoacoustic imaging for guiding minimally invasive procedures was developed and characterized. The system provides both structural information from ultrasound imaging and molecular information from multispectral photoacoustic imaging. It uses a commercial linear-array ultrasound imaging probe as the ultrasound receiver, with a multimode optical fiber embedded in a needle to deliver pulsed excitation light to tissue. Co-registration of ultrasound and photoacoustic images is achieved with the use of the same ultrasound receiver for both modalities. Using tissue ex vivo, the system successfully discriminated deep-located fat tissue from the surrounding muscle tissue. The measured photoacoustic spectrum of the fat tissue had good agreement with the lipid spectrum in literature.

Reconstruction of initial pressure from limited view photoacoustic images using deep learning

NASA Astrophysics Data System (ADS)

Waibel, Dominik; Gröhl, Janek; Isensee, Fabian; Kirchner, Thomas; Maier-Hein, Klaus; Maier-Hein, Lena

2018-02-01

Quantification of tissue properties with photoacoustic (PA) imaging typically requires a highly accurate representation of the initial pressure distribution in tissue. Almost all PA scanners reconstruct the PA image only from a partial scan of the emitted sound waves. Especially handheld devices, which have become increasingly popular due to their versatility and ease of use, only provide limited view data because of their geometry. Owing to such limitations in hardware as well as to the acoustic attenuation in tissue, state-of-the-art reconstruction methods deliver only approximations of the initial pressure distribution. To overcome the limited view problem, we present a machine learning-based approach to the reconstruction of initial pressure from limited view PA data. Our method involves a fully convolutional deep neural network based on a U-Net-like architecture with pixel-wise regression loss on the acquired PA images. It is trained and validated on in silico data generated with Monte Carlo simulations. In an initial study we found an increase in accuracy over the state-of-the-art when reconstructing simulated linear-array scans of blood vessels.

Ultrahigh-resolution optical coherence elastography through a micro-endoscope: towards in vivo imaging of cellular-scale mechanics

PubMed Central

Fang, Qi; Curatolo, Andrea; Wijesinghe, Philip; Yeow, Yen Ling; Hamzah, Juliana; Noble, Peter B.; Karnowski, Karol; Sampson, David D.; Ganss, Ruth; Kim, Jun Ki; Lee, Woei M.; Kennedy, Brendan F.

2017-01-01

In this paper, we describe a technique capable of visualizing mechanical properties at the cellular scale deep in living tissue, by incorporating a gradient-index (GRIN)-lens micro-endoscope into an ultrahigh-resolution optical coherence elastography system. The optical system, after the endoscope, has a lateral resolution of 1.6 µm and an axial resolution of 2.2 µm. Bessel beam illumination and Gaussian mode detection are used to provide an extended depth-of-field of 80 µm, which is a 4-fold improvement over a fully Gaussian beam case with the same lateral resolution. Using this system, we demonstrate quantitative elasticity imaging of a soft silicone phantom containing a stiff inclusion and a freshly excised malignant murine pancreatic tumor. We also demonstrate qualitative strain imaging below the tissue surface on in situ murine muscle. The approach we introduce here can provide high-quality extended-focus images through a micro-endoscope with potential to measure cellular-scale mechanics deep in tissue. We believe this tool is promising for studying biological processes and disease progression in vivo. PMID:29188108

Optical toolkits for in vivo deep tissue laser scanning microscopy: a primer

NASA Astrophysics Data System (ADS)

Lee, Woei Ming; McMenamin, Thomas; Li, Yongxiao

2018-06-01

Life at the microscale is animated and multifaceted. The impact of dynamic in vivo microscopy in small animals has opened up opportunities to peer into a multitude of biological processes at the cellular scale in their native microenvironments. Laser scanning microscopy (LSM) coupled with targeted fluorescent proteins has become an indispensable tool to enable dynamic imaging in vivo at high temporal and spatial resolutions. In the last few decades, the technique has been translated from imaging cells in thin samples to mapping cells in the thick biological tissue of living organisms. Here, we sought to provide a concise overview of the design considerations of a LSM that enables cellular and subcellular imaging in deep tissue. Individual components under review include: long working distance microscope objectives, laser scanning technologies, adaptive optics devices, beam shaping technologies and photon detectors, with an emphasis on more recent advances. The review will conclude with the latest innovations in automated optical microscopy, which would impact tracking and quantification of heterogeneous populations of cells in vivo.

Fiber-optic fluorescence imaging

PubMed Central

Flusberg, Benjamin A; Cocker, Eric D; Piyawattanametha, Wibool; Jung, Juergen C; Cheung, Eunice L M; Schnitzer, Mark J

2010-01-01

Optical fibers guide light between separate locations and enable new types of fluorescence imaging. Fiber-optic fluorescence imaging systems include portable handheld microscopes, flexible endoscopes well suited for imaging within hollow tissue cavities and microendoscopes that allow minimally invasive high-resolution imaging deep within tissue. A challenge in the creation of such devices is the design and integration of miniaturized optical and mechanical components. Until recently, fiber-based fluorescence imaging was mainly limited to epifluorescence and scanning confocal modalities. Two new classes of photonic crystal fiber facilitate ultrashort pulse delivery for fiber-optic two-photon fluorescence imaging. An upcoming generation of fluorescence imaging devices will be based on microfabricated device components. PMID:16299479

Hand-held optoacoustic probe for three-dimensional imaging of human morphology and function

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Razansky, Daniel

2014-03-01

We report on a hand-held imaging probe for real-time optoacoustic visualization of deep tissues in three dimensions. The proposed solution incorporates a two-dimensional array of ultrasonic sensors densely distributed on a spherical surface, whereas illumination is performed coaxially through a cylindrical cavity in the array. Visualization of three-dimensional tomographic data at a frame rate of 10 images per second is enabled by parallel recording of 256 time-resolved signals for each individual laser pulse along with a highly efficient GPUbased real-time reconstruction. A liquid coupling medium (water), enclosed in a transparent membrane, is used to guarantee transmission of the optoacoustically generated waves to the ultrasonic detectors. Excitation at multiple wavelengths further allows imaging spectrally distinctive tissue chromophores such as oxygenated and deoxygenated haemoglobin. The performance is showcased by video-rate tracking of deep tissue vasculature and three-dimensional measurements of blood oxygenenation in a healthy human volunteer. The flexibility provided by the hand-held hardware design, combined with the real-time operation, makes the developed platform highly usable for both small animal research and clinical imaging in multiple indications, including cancer, inflammation, skin and cardiovascular diseases, diagnostics of lymphatic system and breast

Enhanced near-infrared photoacoustic imaging of silica-coated rare-earth doped nanoparticles.

PubMed

Sheng, Yang; Liao, Lun-De; Bandla, Aishwarya; Liu, Yu-Hang; Yuan, Jun; Thakor, Nitish; Tan, Mei Chee

2017-01-01

Near-infrared photoacoustic (PA) imaging is an emerging diagnostic technology that utilizes the tissue transparent window to achieve improved contrast and spatial resolution for deep tissue imaging. In this study, we investigated the enhancement effect of the SiO 2 shell on the PA property of our core/shell rare-earth nanoparticles (REs) consisting of an active rare-earth doped core of NaYF 4 :Yb,Er (REDNPs) and an undoped NaYF 4 shell. We observed that the PA signal amplitude increased with SiO 2 shell thickness. Although the SiO 2 shell caused an observed decrease in the integrated fluorescence intensity due to the dilution effect, fluorescence quenching of the rare earth emitting ions within the REDNPs cores was successfully prevented by the undoped NaYF 4 shell. Therefore, our multilayer structure consisting of an active core with successive functional layers was demonstrated to be an effective design for dual-modal fluorescence and PA imaging probes with improved PA property. The result from this work addresses a critical need for the development of dual-modal contrast agent that advances deep tissue imaging with high resolution and signal-to-noise ratio. Copyright © 2016 Elsevier B.V. All rights reserved.

Three-Photon Luminescence of Gold Nanorods and Its Applications for High Contrast Tissue and Deep In Vivo Brain Imaging

PubMed Central

Wang, Shaowei; Xi, Wang; Cai, Fuhong; Zhao, Xinyuan; Xu, Zhengping; Qian, Jun; He, Sailing

2015-01-01

Gold nanoparticles can be used as contrast agents for bio-imaging applications. Here we studied multi-photon luminescence (MPL) of gold nanorods (GNRs), under the excitation of femtosecond (fs) lasers. GNRs functionalized with polyethylene glycol (PEG) molecules have high chemical and optical stability, and can be used as multi-photon luminescent nanoprobes for deep in vivo imaging of live animals. We have found that the depth of in vivo imaging is dependent upon the transmission and focal capability of the excitation light interacting with the GNRs. Our study focused on the comparison of MPL from GNRs with two different aspect ratios, as well as their ex vivo and in vivo imaging effects under 760 nm and 1000 nm excitation, respectively. Both of these wavelengths were located at an optically transparent window of biological tissue (700-1000 nm). PEGylated GNRs, which were intravenously injected into mice via the tail vein and accumulated in major organs and tumor tissue, showed high image contrast due to distinct three-photon luminescence (3PL) signals upon irradiation of a 1000 nm fs laser. Concerning in vivo mouse brain imaging, the 3PL imaging depth of GNRs under 1000 nm fs excitation could reach 600 μm, which was approximately 170 μm deeper than the two-photon luminescence (2PL) imaging depth of GNRs with a fs excitation of 760 nm. PMID:25553113

Linear-array based full-view high-resolution photoacoustic computed tomography of whole mouse brain functions in vivo

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Pengfei; Wang, Lihong V.

2018-02-01

Photoacoustic computed tomography (PACT) is a non-invasive imaging technique offering high contrast, high resolution, and deep penetration in biological tissues. We report a photoacoustic computed tomography (PACT) system equipped with a high frequency linear array for anatomical and functional imaging of the mouse whole brain. The linear array was rotationally scanned in the coronal plane to achieve the full-view coverage. We investigated spontaneous neural activities in the deep brain by monitoring the hemodynamics and observed strong interhemispherical correlations between contralateral regions, both in the cortical layer and in the deep regions.

Internal-illumination photoacoustic computed tomography

NASA Astrophysics Data System (ADS)

Li, Mucong; Lan, Bangxin; Liu, Wei; Xia, Jun; Yao, Junjie

2018-03-01

We report a photoacoustic computed tomography (PACT) system using a customized optical fiber with a cylindrical diffuser to internally illuminate deep targets. The traditional external light illumination in PACT usually limits the penetration depth to a few centimeters from the tissue surface, mainly due to strong optical attenuation along the light propagation path from the outside in. By contrast, internal light illumination, with external ultrasound detection, can potentially detect much deeper targets. Different from previous internal illumination PACT implementations using forward-looking optical fibers, our internal-illumination PACT system uses a customized optical fiber with a 3-cm-long conoid needle diffuser attached to the fiber tip, which can homogeneously illuminate the surrounding space and substantially enlarge the field of view. We characterized the internal illumination distribution and PACT system performance. We performed tissue phantom and in vivo animal studies to further demonstrate the superior imaging depth using internal illumination over external illumination. We imaged a 7.5-cm-deep leaf target embedded in optically scattering medium and the beating heart of a mouse overlaid with 3.7-cm-thick chicken tissue. Our results have collectively demonstrated that the internal light illumination combined with external ultrasound detection might be a useful strategy to improve the penetration depth of PACT in imaging deep organs of large animals and humans.

Speckle contrast diffuse correlation tomography of complex turbid medium flow

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

Huang, Chong; Irwin, Daniel; Lin, Yu

2015-07-15

Purpose: Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans. Methods: A highly sensitive CCD camera was integrated into a reflectance-based optical system. Four long-coherence laser source positions were coupledmore » to an optical switch for sequencing of tomographic data acquisition providing multiple projections through the sample. This system was investigated through incorporation of liquid and solid tissue-like phantoms exhibiting optical properties and flow characteristics typical of human tissues. Computer simulations were also performed for comparisons. A uniquely encountered smear correction algorithm was employed to correct point-source illumination contributions during image capture with the frame-transfer CCD and reflectance setup. Results: Measurements with scDCT on a homogeneous liquid phantom showed that speckle contrast-based deep flow indices were within 12% of those from standard DCT. Inclusion of a solid phantom submerged below the liquid phantom surface allowed for heterogeneity detection and validation. The heterogeneity was identified successfully by reconstructed 3D flow contrast tomography with scDCT. The heterogeneity center and dimensions and averaged relative flow (within 3%) and localization were in agreement with actuality and computer simulations, respectively. Conclusions: A custom cost-effective CCD-based reflectance 3D flow imaging system demonstrated rapid acquisition of dense boundary data and, with further studies, a high potential for translatability to real tissues with arbitrary boundaries. A requisite correction was also found for measurements in the fashion of scDCT to recover accurate speckle contrast of deep tissues.« less

A simple model for deep tissue attenuation correction and large organ analysis of Cerenkov luminescence imaging

NASA Astrophysics Data System (ADS)

Habte, Frezghi; Natarajan, Arutselvan; Paik, David S.; Gambhir, Sanjiv S.

2014-03-01

Cerenkov luminescence imaging (CLI) is an emerging cost effective modality that uses conventional small animal optical imaging systems and clinically available radionuclide probes for light emission. CLI has shown good correlation with PET for organs of high uptake such as kidney, spleen, thymus and subcutaneous tumors in mouse models. However, CLI has limitations for deep tissue quantitative imaging since the blue-weighted spectral characteristics of Cerenkov radiation attenuates highly by mammalian tissue. Large organs such as the liver have also shown higher signal due to the contribution of emission of light from a greater thickness of tissue. In this study, we developed a simple model that estimates the effective tissue attenuation coefficient in order to correct the CLI signal intensity with a priori estimated depth and thickness of specific organs. We used several thin slices of ham to build a phantom with realistic attenuation. We placed radionuclide sources inside the phantom at different tissue depths and imaged it using an IVIS Spectrum (Perkin-Elmer, Waltham, MA, USA) and Inveon microPET (Preclinical Solutions Siemens, Knoxville, TN). We also performed CLI and PET of mouse models and applied the proposed attenuation model to correct CLI measurements. Using calibration factors obtained from phantom study that converts the corrected CLI measurements to %ID/g, we obtained an average difference of less that 10% for spleen and less than 35% for liver compared to conventional PET measurements. Hence, the proposed model has a capability of correcting the CLI signal to provide comparable measurements with PET data.

White Matter Tract Injury is Associated with Deep Gray Matter Iron Deposition in Multiple Sclerosis.

PubMed

Bergsland, Niels; Tavazzi, Eleonora; Laganà, Maria Marcella; Baglio, Francesca; Cecconi, Pietro; Viotti, Stefano; Zivadinov, Robert; Baselli, Giuseppe; Rovaris, Marco

2017-01-01

With respect to healthy controls (HCs), increased iron concentrations in the deep gray matter (GM) and decreased white matter (WM) integrity are common findings in multiple sclerosis (MS) patients. The association between these features of the disease remains poorly understood. We investigated the relationship between deep iron deposition in the deep GM and WM injury in associated fiber tracts in MS patients. Sixty-six MS patients (mean age 50.0 years, median Expanded Disability Status Scale 5.25, mean disease duration 19.1 years) and 29 HCs, group matched for age and sex were imaged on a 1.5T scanner. Susceptibility-weighted imaging and diffusion tensor imaging (DTI) were used for assessing high-pass filtered phase values in the deep GM and normal appearing WM (NAWM) integrity in associated fiber tracts, respectively. Correlation analyses investigated the associations between filtered phase values (suggestive of iron content) and WM damage. Areas indicative of increased iron levels were found in the left and right caudates as well as in the left thalamus. MS patients presented with decreased DTI-derived measures of tissue integrity in the associated WM tracts. Greater mean, axial and radial diffusivities were associated with increased iron levels in all three GM areas (r values .393 to .514 with corresponding P values .003 to <.0001). Global NAWM diffusivity measures were not related to mean filtered phase values within the deep GM. Increased iron concentration in the deep GM is associated with decreased tissue integrity of the connected WM in MS patients. Copyright © 2016 by the American Society of Neuroimaging.

Recent progress in tissue optical clearing for spectroscopic application

NASA Astrophysics Data System (ADS)

Sdobnov, A. Yu.; Darvin, M. E.; Genina, E. A.; Bashkatov, A. N.; Lademann, J.; Tuchin, V. V.

2018-05-01

This paper aims to review recent progress in optical clearing of the skin and over naturally turbid biological tissues and blood using this technique in vivo and in vitro with multiphoton microscopy, confocal Raman microscopy, confocal microscopy, NIR spectroscopy, optical coherence tomography, and laser speckle contrast imaging. Basic principles of the technique, its safety, advantages and limitations are discussed. The application of optical clearing agent on a tissue allows for controlling the optical properties of tissue. Optical clearing-induced reduction of tissue scattering significantly facilitates the observation of deep-located tissue regions, at the same time improving the resolution and image contrast for a variety of optical imaging methods suitable for clinical applications, such as diagnostics and laser treatment of skin diseases, mucosal tumor imaging, laser disruption of pathological abnormalities, etc. Structural images of different skin layers obtained ex vivo for porcine ear skin samples at application of Omnipaque™ and glycerol solutions during 60 min. Red color corresponds to TPEAF signal channel. Green color corresponds to SHG signal channel.

Two-Element Transducer for Ultrasound

NASA Technical Reports Server (NTRS)

Lecroissette, D. H.; Heyser, R. C.

1986-01-01

Separation of transmitting and receiving units improves probing of deep tissue. Ultrasonic transducer has dual elements to increase depth at which sonic images are made of biological tissue. Transducer uses separate transmitting and receiving elements, and frequency response of receiving element independently designed to accommodate attenuation of higher frequencies by tissue. New transducer intended for pulse-echo ultrasonic systems in which reflected sound pulses reveal features in tissue.

Three-Dimensional Optical Mapping of Nanoparticle Distribution in Intact Tissues.

PubMed

Sindhwani, Shrey; Syed, Abdullah Muhammad; Wilhelm, Stefan; Glancy, Dylan R; Chen, Yih Yang; Dobosz, Michael; Chan, Warren C W

2016-05-24

The role of tissue architecture in mediating nanoparticle transport, targeting, and biological effects is unknown due to the lack of tools for imaging nanomaterials in whole organs. Here, we developed a rapid optical mapping technique to image nanomaterials in intact organs ex vivo and in three-dimensions (3D). We engineered a high-throughput electrophoretic flow device to simultaneously transform up to 48 tissues into optically transparent structures, allowing subcellular imaging of nanomaterials more than 1 mm deep into tissues which is 25-fold greater than current techniques. A key finding is that nanomaterials can be retained in the processed tissue by chemical cross-linking of surface adsorbed serum proteins to the tissue matrix, which enables nanomaterials to be imaged with respect to cells, blood vessels, and other structures. We developed a computational algorithm to analyze and quantitatively map nanomaterial distribution. This method can be universally applied to visualize the distribution and interactions of materials in whole tissues and animals including such applications as the imaging of nanomaterials, tissue engineered constructs, and biosensors within their intact biological environment.

Flexible biodegradable citrate-based polymeric step-index optical fiber.

PubMed

Shan, Dingying; Zhang, Chenji; Kalaba, Surge; Mehta, Nikhil; Kim, Gloria B; Liu, Zhiwen; Yang, Jian

2017-10-01

Implanting fiber optical waveguides into tissue or organs for light delivery and collection is among the most effective ways to overcome the issue of tissue turbidity, a long-standing obstacle for biomedical optical technologies. Here, we report a citrate-based material platform with engineerable opto-mechano-biological properties and demonstrate a new type of biodegradable, biocompatible, and low-loss step-index optical fiber for organ-scale light delivery and collection. By leveraging the rich designability and processibility of citrate-based biodegradable polymers, two exemplary biodegradable elastomers with a fine refractive index difference and yet matched mechanical properties and biodegradation profiles were developed. Furthermore, we developed a two-step fabrication method to fabricate flexible and low-loss (0.4 db/cm) optical fibers, and performed systematic characterizations to study optical, spectroscopic, mechanical, and biodegradable properties. In addition, we demonstrated the proof of concept of image transmission through the citrate-based polymeric optical fibers and conducted in vivo deep tissue light delivery and fluorescence sensing in a Sprague-Dawley (SD) rat, laying the groundwork for realizing future implantable devices for long-term implantation where deep-tissue light delivery, sensing and imaging are desired, such as cell, tissue, and scaffold imaging in regenerative medicine and in vivo optogenetic stimulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D morphological analysis of the mouse cerebral vasculature: Comparison of in vivo and ex vivo methods

PubMed Central

Steinman, Joe; Koletar, Margaret M.; Stefanovic, Bojana; Sled, John G.

2017-01-01

Ex vivo 2-photon fluorescence microscopy (2PFM) with optical clearing enables vascular imaging deep into tissue. However, optical clearing may also produce spherical aberrations if the objective lens is not index-matched to the clearing material, while the perfusion, clearing, and fixation procedure may alter vascular morphology. We compared in vivo and ex vivo 2PFM in mice, focusing on apparent differences in microvascular signal and morphology. Following in vivo imaging, the mice (four total) were perfused with a fluorescent gel and their brains fructose-cleared. The brain regions imaged in vivo were imaged ex vivo. Vessels were segmented in both images using an automated tracing algorithm that accounts for the spatially varying PSF in the ex vivo images. This spatial variance is induced by spherical aberrations caused by imaging fructose-cleared tissue with a water-immersion objective. Alignment of the ex vivo image to the in vivo image through a non-linear warping algorithm enabled comparison of apparent vessel diameter, as well as differences in signal. Shrinkage varied as a function of diameter, with capillaries rendered smaller ex vivo by 13%, while penetrating vessels shrunk by 34%. The pial vasculature attenuated in vivo microvascular signal by 40% 300 μm below the tissue surface, but this effect was absent ex vivo. On the whole, ex vivo imaging was found to be valuable for studying deep cortical vasculature. PMID:29053753

Common-path biodynamic imaging for dynamic fluctuation spectroscopy of 3D living tissue

NASA Astrophysics Data System (ADS)

Li, Zhe; Turek, John; Nolte, David D.

2017-03-01

Biodynamic imaging is a novel 3D optical imaging technology based on short-coherence digital holography that measures intracellular motions of cells inside their natural microenvironments. Here both common-path and Mach-Zehnder designs are presented. Biological tissues such as tumor spheroids and ex vivo biopsies are used as targets, and backscattered light is collected as signal. Drugs are applied to samples, and their effects are evaluated by identifying biomarkers that capture intracellular dynamics from the reconstructed holograms. Through digital holography and coherence gating, information from different depths of the samples can be extracted, enabling the deep-tissue measurement of the responses to drugs.

Characterizing Fibrosis in Mouse Kidney using Label Free Fluorescence Lifetime and Second Harmonic Generation Imaging Microscopy in Unilateral Ureteral Obstruction Model

PubMed Central

Ranjit, Suman; Dobrinskikh, Evgenia; Montford, John; Dvornikov, Alexander; Lehman, Allison; Orlicky, David J.; Nemenoff, Raphael; Gratton, Enrico; Levi, Moshe; Furgeson, Seth

2017-01-01

All forms of progressive renal diseases develop a final pathway of tubulointerstitial fibrosis and glomerulosclerosis. Renal fibrosis is usually quantified using histological staining, a process that is time-consuming and pathologist dependent. The work described here shows the development of a fast and operator-independent method to measure fibrosis. To study renal fibrosis, the unilateral ureteral obstruction (UUO) model was chosen. Mice develop a time-dependent increase in obstructed kidneys; contralateral kidneys are used as controls. After UUO, kidneys were analyzed at three time points: 7 days, 14 days, and 21 days. Fibrosis was investigated using FLIM (Fluorescence Lifetime Imaging) and SHG (Second Harmonic Generation) in the deep tissue imaging microscope called DIVER (Deep Imaging via Enhanced photon Recovery). This microscope was developed for deep tissue and SHG and THG (Third Harmonic Generation) imaging and has extraordinary sensitivity towards harmonic generation. SHG data suggests the presence of more fibrillar collagen in the diseased kidneys. The combinations of short wavelength FLIM and SHG analysis results in a robust analysis procedure independent of observer interpretation and let us create a criterion to quantify the extent of fibrosis directly from the image. The progression of fibrosis in UUO model has been studied using this new FLIM-SHG technique and it shows remarkable improvement in quantification of fibrosis compared to standard histological techniques. PMID:27555119

A least squares approach to estimating the probability distribution of unobserved data in multiphoton microscopy

NASA Astrophysics Data System (ADS)

Salama, Paul

2008-02-01

Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiphoton microscopy and image guided light activated therapy using nanomaterials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prasad, Paras N.

2017-02-01

This talk will focus on design and applications of nanomaterials exhibiting strong multiphoton upconversion for multiphoton microscopy as well as for image-guided and light activated therapy .1-3 Such processes can occur by truly nonlinear optical interactions proceeding through virtual intermediate states or by stepwise coupled linear excitations through real intermediate states. Multiphoton processes in biocompatible multifunctional nanoparticles allow for 3D deep tissue imaging. In addition, they can produce in-situ photon conversion of deep tissue penetrating near IR light into a needed shorter wavelength light for photo-activated therapy at a targeted site, thus overcoming the limited penetration of UV or visible light into biological media. We are using near IR emitters such as silicon quantum dots which also exhibit strong multiphoton excitation for multiphoton microscopy. Another approach involves nonlinear nanocrystals such as ZnO which can produce four wave mixing, sum frequency generation as well as second harmonic generation to convert a deep tissue penetrating Near IR light at the targeted biological site to a desired shorter wavelength light suitable for bio imaging or activation of a therapy. We have utilized this approach to activate a photosensitizer for photodynamic therapy. Yet another type of upconversion materials is rare-earth ion doped optical nanotransformers which transform a Near IR (NIR) light from an external source by sequential single photon absorption, in situ and on demand, to a needed wavelength. Applications of these nanotransformers in multiphoton photoacoustic imaging will also be presented. An exciting direction pursued by us using these multiphoton nanoparticles, is functional imaging of brain. Simultaneously, they can effect optogenetics for regioselective stimulation of neurons for providing an effective intervention/augmentation strategy to enhance the cognitive state and lead to a foundation for futuristic vision of super human capabilities. Challenges and opportunities will be discussed.

Reflection-artifact-free photoacoustic imaging using PAFUSion (photoacoustic-guided focused ultrasound)

NASA Astrophysics Data System (ADS)

Kuniyil Ajith Singh, Mithun; Jaeger, Michael; Frenz, Martin; Steenbergen, Wiendelt

2016-03-01

Reflection artifacts caused by acoustic inhomogeneities are a main challenge to deep-tissue photoacoustic imaging. Photoacoustic transients generated by the skin surface and superficial vasculature will propagate into the tissue and reflect back from echogenic structures to generate reflection artifacts. These artifacts can cause problems in image interpretation and limit imaging depth. In its basic version, PAFUSion mimics the inward travelling wave-field from blood vessel-like PA sources by applying focused ultrasound pulses, and thus provides a way to identify reflection artifacts. In this work, we demonstrate reflection artifact correction in addition to identification, towards obtaining an artifact-free photoacoustic image. In view of clinical applications, we implemented an improved version of PAFUSion in which photoacoustic data is backpropagated to imitate the inward travelling wave-field and thus the reflection artifacts of a more arbitrary distribution of PA sources that also includes the skin melanin layer. The backpropagation is performed in a synthetic way based on the pulse-echo acquisitions after transmission on each single element of the transducer array. We present a phantom experiment and initial in vivo measurements on human volunteers where we demonstrate significant reflection artifact reduction using our technique. The results provide a direct confirmation that reflection artifacts are prominent in clinical epi-photoacoustic imaging, and that PAFUSion can reduce these artifacts significantly to improve the deep-tissue photoacoustic imaging.

Pre-operative CT angiography and three-dimensional image post processing for deep inferior epigastric perforator flap breast reconstructive surgery.

PubMed

Lam, D L; Mitsumori, L M; Neligan, P C; Warren, B H; Shuman, W P; Dubinsky, T J

2012-12-01

Autologous breast reconstructive surgery with deep inferior epigastric artery (DIEA) perforator flaps has become the mainstay for breast reconstructive surgery. CT angiography and three-dimensional image post processing can depict the number, size, course and location of the DIEA perforating arteries for the pre-operative selection of the best artery to use for the tissue flap. Knowledge of the location and selection of the optimal perforating artery shortens operative times and decreases patient morbidity.

In vivo three-photon microscopy of subcortical structures within an intact mouse brain

NASA Astrophysics Data System (ADS)

Horton, Nicholas G.; Wang, Ke; Kobat, Demirhan; Clark, Catharine G.; Wise, Frank W.; Schaffer, Chris B.; Xu, Chris

2013-03-01

Two-photon fluorescence microscopy enables scientists in various fields including neuroscience, embryology and oncology to visualize in vivo and ex vivo tissue morphology and physiology at a cellular level deep within scattering tissue. However, tissue scattering limits the maximum imaging depth of two-photon fluorescence microscopy to the cortical layer within mouse brain, and imaging subcortical structures currently requires the removal of overlying brain tissue or the insertion of optical probes. Here, we demonstrate non-invasive, high-resolution, in vivo imaging of subcortical structures within an intact mouse brain using three-photon fluorescence microscopy at a spectral excitation window of 1,700 nm. Vascular structures as well as red fluorescent protein-labelled neurons within the mouse hippocampus are imaged. The combination of the long excitation wavelength and the higher-order nonlinear excitation overcomes the limitations of two-photon fluorescence microscopy, enabling biological investigations to take place at a greater depth within tissue.

NMR Reconstructive Elasticity Imaging of Breast: Surrogate Remote Palpation Using Quantitative 3-D Displacement

DTIC Science & Technology

1998-09-01

breast tissues may provide unique information which could increase detection and/or characterization of potentially malignant masses not accessible... masses deep in the breast , or within relatively dense, stiff, or heterogeneous tissues, is poor. The principal objective of this project is to develop...or propagating shear wave is documented by imaging devices. In the original MRI method, spatial magnetization tagging was applied, but this had poor

Spectroscopic Imaging of Deep Tissue through Photoacoustic Detection of Molecular Vibration

PubMed Central

Wang, Pu; Rajian, Justin R.; Cheng, Ji-Xin

2013-01-01

The quantized vibration of chemical bonds provides a way of imaging target molecules in a complex tissue environment. Photoacoustic detection of harmonic vibrational transitions provides an approach to visualize tissue content beyond the ballistic photon regime. This method involves pulsed laser excitation of overtone transitions in target molecules inside a tissue. Fast relaxation of the vibrational energy into heat results in a local temperature rise on the order of mK and a subsequent generation of acoustic waves detectable with an ultrasonic transducer. In this perspective, we review recent advances that demonstrate the advantages of vibration-based photoacoustic imaging and illustrate its potential in diagnosing cardiovascular plaques. An outlook into future development of vibrational photoacoustic endoscopy and tomography is provided. PMID:24073304

NanoLuc reporter for dual luciferase imaging in living animals.

PubMed

Stacer, Amanda C; Nyati, Shyam; Moudgil, Pranav; Iyengar, Rahul; Luker, Kathryn E; Rehemtulla, Alnawaz; Luker, Gary D

2013-10-01

Bioluminescence imaging is widely used for cell-based assays and animal imaging studies in biomedical research and drug development, capitalizing on the high signal to background of this technique. A relatively small number of luciferases are available for imaging studies, substantially limiting the ability to image multiple molecular and cellular events, as done commonly with fluorescence imaging. To advance dual reporter bioluminescence molecular imaging, we tested a recently developed, adenosine triphosphate–independent luciferase enzyme from Oplophorus gracilirostris (NanoLuc [NL]) as a reporter for animal imaging. We demonstrated that NL could be imaged in superficial and deep tissues in living mice, although the detection of NL in deep tissues was limited by emission of predominantly blue light by this enzyme. Changes in bioluminescence from NL over time could be used to quantify tumor growth, and secreted NL was detectable in small volumes of serum. We combined NL and firefly luciferase reporters to quantify two key steps in transforming growth factor β signaling in intact cells and living mice, establishing a novel dual luciferase imaging strategy for quantifying signal transduction and drug targeting. Our results establish NL as a new reporter for bioluminescence imaging studies in intact cells and living mice that will expand imaging of signal transduction in normal physiology, disease, and drug development.

NanoLuc Reporter for Dual Luciferase Imaging in Living Animals

PubMed Central

Stacer, Amanda C.; Nyati, Shyam; Moudgil, Pranav; Iyengar, Rahul; Luker, Kathryn E.; Rehemtulla, Alnawaz; Luker, Gary D.

2014-01-01

Bioluminescence imaging is utilized widely for cell-based assays and animal imaging studies in biomedical research and drug development, capitalizing on high signal-to-background of this technique. A relatively small number of luciferases are available for imaging studies, substantially limiting the ability to image multiple molecular and cellular events as done commonly with fluorescence imaging. To advance dual reporter bioluminescence molecular imaging, we tested a recently developed, ATP-independent luciferase enzyme from Oplophorus gracilirostris (NanoLuc, NL) as a reporter for animal imaging. We demonstrated that NL could be imaged in superficial and deep tissues in living mice, although detection of NL in deep tissues was limited by emission of predominantly blue light by this enzyme. Changes in bioluminescence from NL over time could be used to quantify tumor growth, and secreted NL was detectable in small volumes of serum. We combined NL and firefly luciferase reporters to quantify two key steps in TGF-β signaling in intact cells and living mice, establishing a novel dual luciferase imaging strategy for quantifying signal transduction and drug targeting. Our results establish NL as new reporter for bioluminescence imaging studies in intact cells and living mice that will expand imaging of signal transduction in normal physiology, disease, and drug development. PMID:24371848

Stimulated Raman photoacoustic imaging

PubMed Central

Yakovlev, Vladislav V.; Zhang, Hao F.; Noojin, Gary D.; Denton, Michael L.; Thomas, Robert J.; Scully, Marlan O.

2010-01-01

Achieving label-free, molecular-specific imaging with high spatial resolution in deep tissue is often considered the grand challenge of optical imaging. To accomplish this goal, significant optical scattering in tissues has to be overcome while achieving molecular specificity without resorting to extrinsic labeling. We demonstrate the feasibility of developing such an optical imaging modality by combining the molecularly specific stimulated Raman excitation with the photoacoustic detection. By employing two ultrashort excitation laser pulses, separated in frequency by the vibrational frequency of a targeted molecule, only the specific vibrational level of the target molecules in the illuminated tissue volume is excited. This targeted optical absorption generates ultrasonic waves (referred to as stimulated Raman photoacoustic waves) which are detected using a traditional ultrasonic transducer to form an image following the design of the established photoacoustic microscopy. PMID:21059930

Maximizing fluorescence collection efficiency in multiphoton microscopy

PubMed Central

Zinter, Joseph P.; Levene, Michael J.

2011-01-01

Understanding fluorescence propagation through a multiphoton microscope is of critical importance in designing high performance systems capable of deep tissue imaging. Optical models of a scattering tissue sample and the Olympus 20X 0.95NA microscope objective were used to simulate fluorescence propagation as a function of imaging depth for physiologically relevant scattering parameters. The spatio-angular distribution of fluorescence at the objective back aperture derived from these simulations was used to design a simple, maximally efficient post-objective fluorescence collection system. Monte Carlo simulations corroborated by data from experimental tissue phantoms demonstrate collection efficiency improvements of 50% – 90% over conventional, non-optimized fluorescence collection geometries at large imaging depths. Imaging performance was verified by imaging layer V neurons in mouse cortex to a depth of 850 μm. PMID:21934897

Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging

NASA Astrophysics Data System (ADS)

Errico, Claudia; Pierre, Juliette; Pezet, Sophie; Desailly, Yann; Lenkei, Zsolt; Couture, Olivier; Tanter, Mickael

2015-11-01

Non-invasive imaging deep into organs at microscopic scales remains an open quest in biomedical imaging. Although optical microscopy is still limited to surface imaging owing to optical wave diffusion and fast decorrelation in tissue, revolutionary approaches such as fluorescence photo-activated localization microscopy led to a striking increase in resolution by more than an order of magnitude in the last decade. In contrast with optics, ultrasonic waves propagate deep into organs without losing their coherence and are much less affected by in vivo decorrelation processes. However, their resolution is impeded by the fundamental limits of diffraction, which impose a long-standing trade-off between resolution and penetration. This limits clinical and preclinical ultrasound imaging to a sub-millimetre scale. Here we demonstrate in vivo that ultrasound imaging at ultrafast frame rates (more than 500 frames per second) provides an analogue to optical localization microscopy by capturing the transient signal decorrelation of contrast agents—inert gas microbubbles. Ultrafast ultrasound localization microscopy allowed both non-invasive sub-wavelength structural imaging and haemodynamic quantification of rodent cerebral microvessels (less than ten micrometres in diameter) more than ten millimetres below the tissue surface, leading to transcranial whole-brain imaging within short acquisition times (tens of seconds). After intravenous injection, single echoes from individual microbubbles were detected through ultrafast imaging. Their localization, not limited by diffraction, was accumulated over 75,000 images, yielding 1,000,000 events per coronal plane and statistically independent pixels of ten micrometres in size. Precise temporal tracking of microbubble positions allowed us to extract accurately in-plane velocities of the blood flow with a large dynamic range (from one millimetre per second to several centimetres per second). These results pave the way for deep non-invasive microscopy in animals and humans using ultrasound. We anticipate that ultrafast ultrasound localization microscopy may become an invaluable tool for the fundamental understanding and diagnostics of various disease processes that modify the microvascular blood flow, such as cancer, stroke and arteriosclerosis.

Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging.

PubMed

Errico, Claudia; Pierre, Juliette; Pezet, Sophie; Desailly, Yann; Lenkei, Zsolt; Couture, Olivier; Tanter, Mickael

2015-11-26

Non-invasive imaging deep into organs at microscopic scales remains an open quest in biomedical imaging. Although optical microscopy is still limited to surface imaging owing to optical wave diffusion and fast decorrelation in tissue, revolutionary approaches such as fluorescence photo-activated localization microscopy led to a striking increase in resolution by more than an order of magnitude in the last decade. In contrast with optics, ultrasonic waves propagate deep into organs without losing their coherence and are much less affected by in vivo decorrelation processes. However, their resolution is impeded by the fundamental limits of diffraction, which impose a long-standing trade-off between resolution and penetration. This limits clinical and preclinical ultrasound imaging to a sub-millimetre scale. Here we demonstrate in vivo that ultrasound imaging at ultrafast frame rates (more than 500 frames per second) provides an analogue to optical localization microscopy by capturing the transient signal decorrelation of contrast agents--inert gas microbubbles. Ultrafast ultrasound localization microscopy allowed both non-invasive sub-wavelength structural imaging and haemodynamic quantification of rodent cerebral microvessels (less than ten micrometres in diameter) more than ten millimetres below the tissue surface, leading to transcranial whole-brain imaging within short acquisition times (tens of seconds). After intravenous injection, single echoes from individual microbubbles were detected through ultrafast imaging. Their localization, not limited by diffraction, was accumulated over 75,000 images, yielding 1,000,000 events per coronal plane and statistically independent pixels of ten micrometres in size. Precise temporal tracking of microbubble positions allowed us to extract accurately in-plane velocities of the blood flow with a large dynamic range (from one millimetre per second to several centimetres per second). These results pave the way for deep non-invasive microscopy in animals and humans using ultrasound. We anticipate that ultrafast ultrasound localization microscopy may become an invaluable tool for the fundamental understanding and diagnostics of various disease processes that modify the microvascular blood flow, such as cancer, stroke and arteriosclerosis.

Visualization of ultrasound induced cavitation bubbles using the synchrotron x-ray Analyzer Based Imaging technique.

PubMed

Izadifar, Zahra; Belev, George; Izadifar, Mohammad; Izadifar, Zohreh; Chapman, Dean

2014-12-07

Observing cavitation bubbles deep within tissue is very difficult. The development of a method for probing cavitation, irrespective of its location in tissues, would improve the efficiency and application of ultrasound in the clinic. A synchrotron x-ray imaging technique, which is capable of detecting cavitation bubbles induced in water by a sonochemistry system, is reported here; this could possibly be extended to the study of therapeutic ultrasound in tissues. The two different x-ray imaging techniques of Analyzer Based Imaging (ABI) and phase contrast imaging (PCI) were examined in order to detect ultrasound induced cavitation bubbles. Cavitation was not observed by PCI, however it was detectable with ABI. Acoustic cavitation was imaged at six different acoustic power levels and six different locations through the acoustic beam in water at a fixed power level. The results indicate the potential utility of this technique for cavitation studies in tissues, but it is time consuming. This may be improved by optimizing the imaging method.

Adult stem cell lineage tracing and deep tissue imaging

PubMed Central

Fink, Juergen; Andersson-Rolf, Amanda; Koo, Bon-Kyoung

2015-01-01

Lineage tracing is a widely used method for understanding cellular dynamics in multicellular organisms during processes such as development, adult tissue maintenance, injury repair and tumorigenesis. Advances in tracing or tracking methods, from light microscopy-based live cell tracking to fluorescent label-tracing with two-photon microscopy, together with emerging tissue clearing strategies and intravital imaging approaches have enabled scientists to decipher adult stem and progenitor cell properties in various tissues and in a wide variety of biological processes. Although technical advances have enabled time-controlled genetic labeling and simultaneous live imaging, a number of obstacles still need to be overcome. In this review, we aim to provide an in-depth description of the traditional use of lineage tracing as well as current strategies and upcoming new methods of labeling and imaging. [BMB Reports 2015; 48(12): 655-667] PMID:26634741

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

PubMed

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Deep and Structured Robust Information Theoretic Learning for Image Analysis.

PubMed

Deng, Yue; Bao, Feng; Deng, Xuesong; Wang, Ruiping; Kong, Youyong; Dai, Qionghai

2016-07-07

This paper presents a robust information theoretic (RIT) model to reduce the uncertainties, i.e. missing and noisy labels, in general discriminative data representation tasks. The fundamental pursuit of our model is to simultaneously learn a transformation function and a discriminative classifier that maximize the mutual information of data and their labels in the latent space. In this general paradigm, we respectively discuss three types of the RIT implementations with linear subspace embedding, deep transformation and structured sparse learning. In practice, the RIT and deep RIT are exploited to solve the image categorization task whose performances will be verified on various benchmark datasets. The structured sparse RIT is further applied to a medical image analysis task for brain MRI segmentation that allows group-level feature selections on the brain tissues.

Deep learning and three-compartment breast imaging in breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Drukker, Karen; Huynh, Benjamin Q.; Giger, Maryellen L.; Malkov, Serghei; Avila, Jesus I.; Fan, Bo; Joe, Bonnie; Kerlikowske, Karla; Drukteinis, Jennifer S.; Kazemi, Leila; Pereira, Malesa M.; Shepherd, John

2017-03-01

We investigated whether deep learning has potential to aid in the diagnosis of breast cancer when applied to mammograms and biologic tissue composition images derived from three-compartment (3CB) imaging. The dataset contained diagnostic mammograms and 3CB images (water, lipid, and protein content) of biopsy-sampled BIRADS 4 and 5 lesions in 195 patients. In 58 patients, the lesion manifested as a mass (13 malignant vs. 45 benign), in 87 as microcalcifications (19 vs. 68), and in 56 as (focal) asymmetry or architectural distortion (11 vs. 45). Six patients had both a mass and calcifications. For each mammogram and corresponding 3CB images, a 128x128 region of interest containing the lesion was selected by an expert radiologist and used directly as input to a deep learning method pretrained on a very large independent set of non-medical images. We used a nested leave-one-out-by-case (patient) model selection and classification protocol. The area under the ROC curve (AUC) for the task of distinguishing between benign and malignant lesions was used as performance metric. For the cases with mammographic masses, the AUC increased from 0.83 (mammograms alone) to 0.89 (mammograms+3CB, p=.162). For the microcalcification and asymmetry/architectural distortion cases the AUC increased from 0.84 to 0.91 (p=.116) and from 0.61 to 0.87 (p=.006), respectively. Our results indicate great potential for the application of deep learning methods in the diagnosis of breast cancer and additional knowledge of the biologic tissue composition appeared to improve performance, especially for lesions mammographically manifesting as asymmetries or architectural distortions.

Preparation of wholemount mouse intestine for high-resolution three-dimensional imaging using two-photon microscopy.

PubMed

Appleton, P L; Quyn, A J; Swift, S; Näthke, I

2009-05-01

Visualizing overall tissue architecture in three dimensions is fundamental for validating and integrating biochemical, cell biological and visual data from less complex systems such as cultured cells. Here, we describe a method to generate high-resolution three-dimensional image data of intact mouse gut tissue. Regions of highest interest lie between 50 and 200 mum within this tissue. The quality and usefulness of three-dimensional image data of tissue with such depth is limited owing to problems associated with scattered light, photobleaching and spherical aberration. Furthermore, the highest-quality oil-immersion lenses are designed to work at a maximum distance of

Improvement of depth resolution on photoacoustic imaging using multiphoton absorption

NASA Astrophysics Data System (ADS)

Yamaoka, Yoshihisa; Fujiwara, Katsuji; Takamatsu, Tetsuro

2007-07-01

Commercial imaging systems, such as computed tomography and magnetic resonance imaging, are frequently used powerful tools for observing structures deep within the human body. However, they cannot precisely visualized several-tens micrometer-sized structures for lack of spatial resolution. In this presentation, we propose photoacoustic imaging using multiphoton absorption technique to generate ultrasonic waves as a means of improving depth resolution. Since the multiphoton absorption occurs at only the focus point and the employed infrared pulses deeply penetrate living tissues, it enables us to extract characteristic features of structures embedded in the living tissue. When nanosecond pulses from a 1064-nm Nd:YAG laser were focused on Rhodamine B/chloroform solution (absorption peak: 540 nm), the peak intensity of the generated photoacoustic signal was proportional to the square of the input pulse energy. This result shows that the photoacoustic signals can be induced by the two-photon absorption of infrared nanosecond pulse laser and also can be detected by a commercial low-frequency MHz transducer. Furthermore, in order to evaluate the depth resolution of multiphoton-photoacoustic imaging, we investigated the dependence of photoacoustic signal on depth position using a 1-mm-thick phantom in a water bath. We found that the depth resolution of two-photon photoacoustic imaging (1064 nm) is greater than that of one-photon photoacoustic imaging (532 nm). We conclude that evolving multiphoton-photoacoustic imaging technology renders feasible the investigation of biomedical phenomena at the deep layer in living tissue.

Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking.

PubMed

Zhou, Xinyi Y; Tay, Zhi Wei; Chandrasekharan, Prashant; Yu, Elaine Y; Hensley, Daniel W; Orendorff, Ryan; Jeffris, Kenneth E; Mai, David; Zheng, Bo; Goodwill, Patrick W; Conolly, Steven M

2018-05-10

Magnetic particle imaging (MPI) is an emerging ionizing radiation-free biomedical tracer imaging technique that directly images the intense magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI offers ideal image contrast because MPI shows zero signal from background tissues. Moreover, there is zero attenuation of the signal with depth in tissue, allowing for imaging deep inside the body quantitatively at any location. Recent work has demonstrated the potential of MPI for robust, sensitive vascular imaging and cell tracking with high contrast and dose-limited sensitivity comparable to nuclear medicine. To foster future applications in MPI, this new biomedical imaging field is welcoming researchers with expertise in imaging physics, magnetic nanoparticle synthesis and functionalization, nanoscale physics, and small animal imaging applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Thermoacoustic Imaging and Therapy Guidance based on Ultra-short Pulsed Microwave Pumped Thermoelastic Effect Induced with Superparamagnetic Iron Oxide Nanoparticles

PubMed Central

Wen, Liewei; Yang, Sihua; Zhong, Junping; Zhou, Quan; Xing, Da

2017-01-01

Multifunctional nanoparticle-mediated imaging and therapeutic techniques are promising modalities for accurate localization and targeted treatment of cancer in clinical settings. Thermoacoustic (TA) imaging is highly sensitive to detect the distribution of water, ions or specific nanoprobes and provides excellent resolution, good contrast and superior tissue penetrability. TA therapy is a potential non-invasive approach for the treatment of deep-seated tumors. In this study, human serum albumin (HSA)-functionalized superparamagnetic iron oxide nanoparticle (HSA-SPIO) is used as a multifunctional nanoprobe with clinical application potential for MRI, TA imaging and treatment of tumor. In addition to be a MRI contrast agent for tumor localization, HSA-SPIO can absorb pulsed microwave energy and transform it into shockwave via the thermoelastic effect. Thereby, the reconstructed TA image by detecting TA signal is expected to be a sensitive and accurate representation of the HSA-SPIO accumulation in tumor. More importantly, owing to the selective retention of HSA-SPIO in tumor tissues and strong TA shockwave at the cellular level, HSA-SPIO induced TA effect under microwave-pulse radiation can be used to highly-efficiently kill cancer cells and inhibit tumor growth. Furthermore, ultra-short pulsed microwave with high excitation efficiency and deep penetrability in biological tissues makes TA therapy a highly-efficient anti-tumor modality on the versatile platform. Overall, HSA-SPIO mediated MRI and TA imaging would offer more comprehensive diagnostic information and enable dynamic visualization of nanoagents in the tumorous tissue thereby tumor-targeted therapy. PMID:28638483

Thermoacoustic Imaging and Therapy Guidance based on Ultra-short Pulsed Microwave Pumped Thermoelastic Effect Induced with Superparamagnetic Iron Oxide Nanoparticles.

PubMed

Wen, Liewei; Yang, Sihua; Zhong, Junping; Zhou, Quan; Xing, Da

2017-01-01

Multifunctional nanoparticle-mediated imaging and therapeutic techniques are promising modalities for accurate localization and targeted treatment of cancer in clinical settings. Thermoacoustic (TA) imaging is highly sensitive to detect the distribution of water, ions or specific nanoprobes and provides excellent resolution, good contrast and superior tissue penetrability. TA therapy is a potential non-invasive approach for the treatment of deep-seated tumors. In this study, human serum albumin (HSA)-functionalized superparamagnetic iron oxide nanoparticle (HSA-SPIO) is used as a multifunctional nanoprobe with clinical application potential for MRI, TA imaging and treatment of tumor. In addition to be a MRI contrast agent for tumor localization, HSA-SPIO can absorb pulsed microwave energy and transform it into shockwave via the thermoelastic effect. Thereby, the reconstructed TA image by detecting TA signal is expected to be a sensitive and accurate representation of the HSA-SPIO accumulation in tumor. More importantly, owing to the selective retention of HSA-SPIO in tumor tissues and strong TA shockwave at the cellular level, HSA-SPIO induced TA effect under microwave-pulse radiation can be used to highly-efficiently kill cancer cells and inhibit tumor growth. Furthermore, ultra-short pulsed microwave with high excitation efficiency and deep penetrability in biological tissues makes TA therapy a highly-efficient anti-tumor modality on the versatile platform. Overall, HSA-SPIO mediated MRI and TA imaging would offer more comprehensive diagnostic information and enable dynamic visualization of nanoagents in the tumorous tissue thereby tumor-targeted therapy.

Hyperspectral imaging in SWIR: from stain-free microscopy to deep tissue imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Berezin, Mikhail Y.

2016-03-01

Recent advances in relatively unexplored short wave infrared (SWIR) range from 800-1600 nm detectors make wide-field imaging in this spectral range attractive to biology. The distinct advantages of SWIR region over the visible and near infrared (NIR) in tissue analysis are two-fold: (i) high abundance endogenous chromophores (i.e. water and lipids) enable tissue component differentiation based on wavelength-dependent absorption properties and (ii) the weak scattering of tissue permits better resolution of imaging in thick specimens. When combined with high spectral resolution, SWIR imaging produces a spectroscopic image, where every pixel corresponds to the entire high-resolution spectrum. This hyperspectral (HS) approach provides rich information about the relative abundance of individual chromophores and their interactions that contribute to the intensity and location of the optical signal. The presentation discusses the challenges in the SWIR-HS instrument design and data analysis and demonstrates some of the promising applications of this technology in life science and medicine.

Bessel light sheet structured illumination microscopy

NASA Astrophysics Data System (ADS)

Noshirvani Allahabadi, Golchehr

Biomedical study researchers using animals to model disease and treatment need fast, deep, noninvasive, and inexpensive multi-channel imaging methods. Traditional fluorescence microscopy meets those criteria to an extent. Specifically, two-photon and confocal microscopy, the two most commonly used methods, are limited in penetration depth, cost, resolution, and field of view. In addition, two-photon microscopy has limited ability in multi-channel imaging. Light sheet microscopy, a fast developing 3D fluorescence imaging method, offers attractive advantages over traditional two-photon and confocal microscopy. Light sheet microscopy is much more applicable for in vivo 3D time-lapsed imaging, owing to its selective illumination of tissue layer, superior speed, low light exposure, high penetration depth, and low levels of photobleaching. However, standard light sheet microscopy using Gaussian beam excitation has two main disadvantages: 1) the field of view (FOV) of light sheet microscopy is limited by the depth of focus of the Gaussian beam. 2) Light-sheet images can be degraded by scattering, which limits the penetration of the excitation beam and blurs emission images in deep tissue layers. While two-sided sheet illumination, which doubles the field of view by illuminating the sample from opposite sides, offers a potential solution, the technique adds complexity and cost to the imaging system. We investigate a new technique to address these limitations: Bessel light sheet microscopy in combination with incoherent nonlinear Structured Illumination Microscopy (SIM). Results demonstrate that, at visible wavelengths, Bessel excitation penetrates up to 250 microns deep in the scattering media with single-side illumination. Bessel light sheet microscope achieves confocal level resolution at a lateral resolution of 0.3 micron and an axial resolution of 1 micron. Incoherent nonlinear SIM further reduces the diffused background in Bessel light sheet images, resulting in confocal quality images in thick tissue. The technique was applied to live transgenic zebra fish tg(kdrl:GFP), and the sub-cellular structure of fish vasculature genetically labeled with GFP was captured in 3D. The superior speed of the microscope enables us to acquire signal from 200 layers of a thick sample in 4 minutes. The compact microscope uses exclusively off-the-shelf components and offers a low-cost imaging solution for studying small animal models or tissue samples.

Co-encapsulation of magnetic nanoparticles and doxorubicin into biodegradable microcarriers for deep tissue targeting by vascular MRI navigation.

PubMed

Pouponneau, Pierre; Leroux, Jean-Christophe; Soulez, Gilles; Gaboury, Louis; Martel, Sylvain

2011-05-01

Magnetic tumor targeting with external magnets is a promising method to increase the delivery of cytotoxic agents to tumor cells while reducing side effects. However, this approach suffers from intrinsic limitations, such as the inability to target areas within deep tissues, due mainly to a strong decrease of the magnetic field magnitude away from the magnets. Magnetic resonance navigation (MRN) involving the endovascular steering of therapeutic magnetic microcarriers (TMMC) represents a clinically viable alternative to reach deep tissues. MRN is achieved with an upgraded magnetic resonance imaging (MRI) scanner. In this proof-of-concept preclinical study, the preparation and steering of TMMC which were designed by taking into consideration the constraints of MRN and liver chemoembolization are reported. TMMC were biodegradable microparticles loaded with iron-cobalt nanoparticles and doxorubicin (DOX). These particles displayed high saturation magnetization (Ms = 72 emu g(-1)), MRI tracking compatibility (strong contrast on T2∗-weighted images), appropriate size for the blood vessel embolization (∼50 μm), and sustained release of DOX (over several days). The TMMC were successfully steered in vitro and in vivo in the rabbit model. In vivo targeting of the right or left liver lobes was achieved by MRN through the hepatic artery located 4 cm beneath the skin. Parameters such as flow velocity, TMMC release site in the artery, magnetic gradient and TMMC properties, affected the steering efficiency. These data illustrate the potential of MRN to improve drug targeting in deep tissues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterization of water molecular state in in-vivo thick tissues using diffuse optical spectroscopic imaging

NASA Astrophysics Data System (ADS)

Chung, So Hyun

Structural changes in water molecules are related to physiological, anatomical and pathological properties of tissues. Near infrared (NIR) optical absorption methods are sensitive to water; however, detailed characterization of water in thick tissues is difficult to achieve because subtle spectral shifts can be obscured by multiple light scattering. In the NIR, a water absorption peak is observed around 975 nm. The precise NIR peak's shape and position are highly sensitive to water molecular disposition. A bound water index (BWI) was developed that quantifies the spectral shift and shape changes observed in tissue water absorption spectra measured by broadband diffuse optical spectroscopic imaging (DOSI). DOSI quantitatively measures light absorption and scattering spectra in cm-deep tissues and therefore reveals bound water spectral shifts. BWI as a water state index was validated by comparing broadband DOSI to MRI and a conductivity cell using bound water phantoms. Non-invasive BWI measurements of malignant and normal tissues in 18 subjects showed a significantly higher fraction of free water in malignant tissues (p<0.0001) compared to normal tissues. BWI showed potential as a prognostic index based on high correlations with tumor grade and size. An algorithm for absolute temperature measurements in deep tissues was developed based on resolving opposing effects of water vibrational frequency shifts due to macromolecular binding. DOSI measures absolute temperature with a difference of 1.1+/-0.91°C from a thermistor. Deep tissue temperature measured in forearms during cold-stress was consistent with previously reported invasively-measured deep tissue temperature. Finally, the BWI was compared to Apparent Diffusion Coefficient (ADC) of diffusion weighted MRI in 9 breast cancer patients. The BWI and ADC correlated (R=0.8, p=<0.01) and both parameters decreased with increasing bulk water content in cancer tissues. Although BWI and ADC are positively correlated in vivo, BWI appears to be more sensitive to free water in the extracellular matrix while ADC reflects increased tumor cellularity. The relationship between ADC, BWI and bulk water concentration suggests that both parameters have potential for assessing tumor histopathological grade. My results confirm the importance of water as a critical tissue component that can potentially provide unique insight into the molecular pathophysiology of cancer.

A novel deep learning-based approach to high accuracy breast density estimation in digital mammography

NASA Astrophysics Data System (ADS)

Ahn, Chul Kyun; Heo, Changyong; Jin, Heongmin; Kim, Jong Hyo

2017-03-01

Mammographic breast density is a well-established marker for breast cancer risk. However, accurate measurement of dense tissue is a difficult task due to faint contrast and significant variations in background fatty tissue. This study presents a novel method for automated mammographic density estimation based on Convolutional Neural Network (CNN). A total of 397 full-field digital mammograms were selected from Seoul National University Hospital. Among them, 297 mammograms were randomly selected as a training set and the rest 100 mammograms were used for a test set. We designed a CNN architecture suitable to learn the imaging characteristic from a multitudes of sub-images and classify them into dense and fatty tissues. To train the CNN, not only local statistics but also global statistics extracted from an image set were used. The image set was composed of original mammogram and eigen-image which was able to capture the X-ray characteristics in despite of the fact that CNN is well known to effectively extract features on original image. The 100 test images which was not used in training the CNN was used to validate the performance. The correlation coefficient between the breast estimates by the CNN and those by the expert's manual measurement was 0.96. Our study demonstrated the feasibility of incorporating the deep learning technology into radiology practice, especially for breast density estimation. The proposed method has a potential to be used as an automated and quantitative assessment tool for mammographic breast density in routine practice.

High frame-rate MR-guided near-infrared tomography system to monitor breast hemodynamics

NASA Astrophysics Data System (ADS)

Li, Zhiqiu; Jiang, Shudong; Krishnaswamy, Venkataramanan; Davis, Scott C.; Srinivasan, Subhadra; Paulsen, Keith D.; Pogue, Brian W.

2011-02-01

A near-infrared (NIR) tomography system with spectral-encoded sources at two wavelength bands was built to quantify the temporal contrast at 20 Hz bandwidth, while imaging breast tissue. The NIR system was integrated with a magnetic resonance (MR) machine through a custom breast coil interface, and both NIR data and MR images were acquired simultaneously. MR images provided breast tissue structural information for NIR reconstruction. Acquisition of finger pulse oximeter (PO) plethysmogram was synchronized with the NIR system in the experiment to offer a frequency-locked reference. The recovered absorption coefficients of the breast at two wavelengths showed identical temporal frequency as the PO output, proving this multi-modality design can recover the small pulsatile variation of absorption property in breast tissue related to the heartbeat. And it also showed the system's ability on novel contrast imaging of fast flow signals in deep tissue.

Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing.

PubMed

Shah, Sheel; Lubeck, Eric; Schwarzkopf, Maayan; He, Ting-Fang; Greenbaum, Alon; Sohn, Chang Ho; Lignell, Antti; Choi, Harry M T; Gradinaru, Viviana; Pierce, Niles A; Cai, Long

2016-08-01

Accurate and robust detection of mRNA molecules in thick tissue samples can reveal gene expression patterns in single cells within their native environment. Preserving spatial relationships while accessing the transcriptome of selected cells is a crucial feature for advancing many biological areas - from developmental biology to neuroscience. However, because of the high autofluorescence background of many tissue samples, it is difficult to detect single-molecule fluorescence in situ hybridization (smFISH) signals robustly in opaque thick samples. Here, we draw on principles from the emerging discipline of dynamic nucleic acid nanotechnology to develop a robust method for multi-color, multi-RNA imaging in deep tissues using single-molecule hybridization chain reaction (smHCR). Using this approach, single transcripts can be imaged using epifluorescence, confocal or selective plane illumination microscopy (SPIM) depending on the imaging depth required. We show that smHCR has high sensitivity in detecting mRNAs in cell culture and whole-mount zebrafish embryos, and that combined with SPIM and PACT (passive CLARITY technique) tissue hydrogel embedding and clearing, smHCR can detect single mRNAs deep within thick (0.5 mm) brain slices. By simultaneously achieving ∼20-fold signal amplification and diffraction-limited spatial resolution, smHCR offers a robust and versatile approach for detecting single mRNAs in situ, including in thick tissues where high background undermines the performance of unamplified smFISH. © 2016. Published by The Company of Biologists Ltd.

Breaking the acoustic diffraction barrier with localization optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Razansky, Daniel

2018-02-01

Diffraction causes blurring of high-resolution features in images and has been traditionally associated to the resolution limit in light microscopy and other imaging modalities. The resolution of an imaging system can be generally assessed via its point spread function, corresponding to the image acquired from a point source. However, the precision in determining the position of an isolated source can greatly exceed the diffraction limit. By combining the estimated positions of multiple sources, localization-based imaging has resulted in groundbreaking methods such as super-resolution fluorescence optical microscopy and has also enabled ultrasound imaging of microvascular structures with unprecedented spatial resolution in deep tissues. Herein, we introduce localization optoacoustic tomography (LOT) and discuss on the prospects of using localization imaging principles in optoacoustic imaging. LOT was experimentally implemented by real-time imaging of flowing particles in 3D with a recently-developed volumetric optoacoustic tomography system. Provided the particles were separated by a distance larger than the diffraction-limited resolution, their individual locations could be accurately determined in each frame of the acquired image sequence and the localization image was formed by superimposing a set of points corresponding to the localized positions of the absorbers. The presented results demonstrate that LOT can significantly enhance the well-established advantages of optoacoustic imaging by breaking the acoustic diffraction barrier in deep tissues and mitigating artifacts due to limited-view tomographic acquisitions.

Optical coherence tomography (OCT) guided smart laser knife for cancer surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Katta, Nitesh; Mcelroy, Austin; Estrada, Arnold; Milner, Thomas E.

2017-02-01

Neurological cancer surgeries require specialized tools that enhance imaging for precise cutting and removal of tissue without damaging adjacent neurological structures. The novel combination of high-resolution fast optical coherence tomography (OCT) alongside short pulsed nanosecond thulium (Tm) lasers offers stark advantages utilizing the superior beam quality, high volumetric tissue removal rates of thulium lasers with minimal residual thermal footprint in the tissue and avoiding damage to delicate sub-surface structures (e.g., nerves and microvessels); which has not been showcased before. A bench-top system is constructed, using a 15W 1940nm nanosecond pulsed Tm fiber laser (500uJ pulse energy, 100ns pulse duration, 30kHz repetition rate) for removing tissue and a swept source laser (1310±70nm, 100kHz sweep rate) is utilized for OCT imaging, forming a combined Tm/OCT system - a smart laser knife. The OCT image-guidance informs the Tm laser for cutting/removal of targeted tissue structures. Tissue phantoms were constructed to demonstrate surgical incision with blood vessel avoidance on the surface where 2mm wide 600um deep cuts are executed around the vessel using OCT to guide the procedure. Cutting up to delicate subsurface blood vessels (2mm deep) is demonstrated while avoiding damage to their walls. A tissue removal rate of 5mm^3/sec is obtained from the bench-top system. We constructed a blow-off model to characterize Tm cut depths taking into account the absorption coefficients and beam delivery systems to compute Arrhenius damage integrals. The model is used to compare predicted tissue removal rate and residual thermal injury with experimental values in response to Tm laser-tissue modification.

Detecting mineral content in turbid medium using nonlinear Raman imaging: feasibility study

PubMed Central

Arora, Rajan; Petrov, Georgi I.; Noojin, Gary D.; Thomas, Patrick A.; Denton, Michael L.; Rockwell, Benjamin A.; Thomas, Robert J.; Yakovlev, Vladislav V.

2012-01-01

Osteoporosis is a bone disease characterized by reduced mineral content with resulting changes in bone architecture, which in turn increases the risk of bone fracture. Raman spectroscopy has an intrinsic sensitivity to the chemical content of the bone, but its application to study bones in vivo is limited due to strong optical scattering in tissue. It has been proposed that Raman excitation with photoacoustic detection can successfully address the problem of chemically specific imaging in deep tissue. In this report, the principal possibility of photoacoustic imaging for detecting mineral content is evaluated. PMID:22337734

Photoacoustic imaging of fluorophores using pump-probe excitation

PubMed Central

Märk, Julia; Schmitt, Franz-Josef; Theiss, Christoph; Dortay, Hakan; Friedrich, Thomas; Laufer, Jan

2015-01-01

A pump-probe technique for the detection of fluorophores in tomographic PA images is introduced. It is based on inducing stimulated emission in fluorescent molecules, which in turn modulates the amount of thermalized energy, and hence the PA signal amplitude. A theoretical model of the PA signal generation in fluorophores is presented and experimentally validated on cuvette measurements made in solutions of Rhodamine 6G, a fluorophore of known optical and molecular properties. The application of this technique to deep tissue tomographic PA imaging is demonstrated by determining the spatial distribution of a near-infrared fluorophore in a tissue phantom. PMID:26203378

Single myelin fiber imaging in living rodents without labeling by deep optical coherence microscopy.

PubMed

Ben Arous, Juliette; Binding, Jonas; Léger, Jean-François; Casado, Mariano; Topilko, Piotr; Gigan, Sylvain; Boccara, A Claude; Bourdieu, Laurent

2011-11-01

Myelin sheath disruption is responsible for multiple neuropathies in the central and peripheral nervous system. Myelin imaging has thus become an important diagnosis tool. However, in vivo imaging has been limited to either low-resolution techniques unable to resolve individual fibers or to low-penetration imaging of single fibers, which cannot provide quantitative information about large volumes of tissue, as required for diagnostic purposes. Here, we perform myelin imaging without labeling and at micron-scale resolution with >300-μm penetration depth on living rodents. This was achieved with a prototype [termed deep optical coherence microscopy (deep-OCM)] of a high-numerical aperture infrared full-field optical coherence microscope, which includes aberration correction for the compensation of refractive index mismatch and high-frame-rate interferometric measurements. We were able to measure the density of individual myelinated fibers in the rat cortex over a large volume of gray matter. In the peripheral nervous system, deep-OCM allows, after minor surgery, in situ imaging of single myelinated fibers over a large fraction of the sciatic nerve. This allows quantitative comparison of normal and Krox20 mutant mice, in which myelination in the peripheral nervous system is impaired. This opens promising perspectives for myelin chronic imaging in demyelinating diseases and for minimally invasive medical diagnosis.

Single myelin fiber imaging in living rodents without labeling by deep optical coherence microscopy

NASA Astrophysics Data System (ADS)

Ben Arous, Juliette; Binding, Jonas; Léger, Jean-François; Casado, Mariano; Topilko, Piotr; Gigan, Sylvain; Claude Boccara, A.; Bourdieu, Laurent

2011-11-01

Myelin sheath disruption is responsible for multiple neuropathies in the central and peripheral nervous system. Myelin imaging has thus become an important diagnosis tool. However, in vivo imaging has been limited to either low-resolution techniques unable to resolve individual fibers or to low-penetration imaging of single fibers, which cannot provide quantitative information about large volumes of tissue, as required for diagnostic purposes. Here, we perform myelin imaging without labeling and at micron-scale resolution with >300-μm penetration depth on living rodents. This was achieved with a prototype [termed deep optical coherence microscopy (deep-OCM)] of a high-numerical aperture infrared full-field optical coherence microscope, which includes aberration correction for the compensation of refractive index mismatch and high-frame-rate interferometric measurements. We were able to measure the density of individual myelinated fibers in the rat cortex over a large volume of gray matter. In the peripheral nervous system, deep-OCM allows, after minor surgery, in situ imaging of single myelinated fibers over a large fraction of the sciatic nerve. This allows quantitative comparison of normal and Krox20 mutant mice, in which myelination in the peripheral nervous system is impaired. This opens promising perspectives for myelin chronic imaging in demyelinating diseases and for minimally invasive medical diagnosis.

Deep tissue single cell MSC ablation using a fiber laser source to evaluate therapeutic potential in osteogenesis imperfecta

NASA Astrophysics Data System (ADS)

Tehrani, Kayvan F.; Pendleton, Emily G.; Lin, Charles P.; Mortensen, Luke J.

2016-04-01

Osteogenesis imperfecta (OI) is a currently uncurable disease where a mutation in collagen type I yields brittle bones. One potential therapy is transplantation of mesenchymal stem cells (MSCs), but controlling and enhancing transplanted cell survival has proven challenging. Therefore, we use a 2- photon imaging system to study individual transplanted cells in the living bone marrow. We ablated cells deep in the bone marrow and observed minimal collateral damage to surrounding tissue. Future work will evaluate the local impact of transplanted MSCs on bone deposition in vivo.

Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score

NASA Astrophysics Data System (ADS)

Jiménez del Toro, Oscar; Atzori, Manfredo; Otálora, Sebastian; Andersson, Mats; Eurén, Kristian; Hedlund, Martin; Rönnquist, Peter; Müller, Henning

2017-03-01

The Gleason grading system was developed for assessing prostate histopathology slides. It is correlated to the outcome and incidence of relapse in prostate cancer. Although this grading is part of a standard protocol performed by pathologists, visual inspection of whole slide images (WSIs) has an inherent subjectivity when evaluated by different pathologists. Computer aided pathology has been proposed to generate an objective and reproducible assessment that can help pathologists in their evaluation of new tissue samples. Deep convolutional neural networks are a promising approach for the automatic classification of histopathology images and can hierarchically learn subtle visual features from the data. However, a large number of manual annotations from pathologists are commonly required to obtain sufficient statistical generalization when training new models that can evaluate the daily generated large amounts of pathology data. A fully automatic approach that detects prostatectomy WSIs with high-grade Gleason score is proposed. We evaluate the performance of various deep learning architectures training them with patches extracted from automatically generated regions-of-interest rather than from manually segmented ones. Relevant parameters for training the deep learning model such as size and number of patches as well as the inclusion or not of data augmentation are compared between the tested deep learning architectures. 235 prostate tissue WSIs with their pathology report from the publicly available TCGA data set were used. An accuracy of 78% was obtained in a balanced set of 46 unseen test images with different Gleason grades in a 2-class decision: high vs. low Gleason grade. Grades 7-8, which represent the boundary decision of the proposed task, were particularly well classified. The method is scalable to larger data sets with straightforward re-training of the model to include data from multiple sources, scanners and acquisition techniques. Automatically generated heatmaps for theWSIs could be useful for improving the selection of patches when training networks for big data sets and to guide the visual inspection of these images.

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

PubMed Central

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-01-01

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions. PMID:28154470

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

PubMed

Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

2016-05-26

Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions.

Deep tissue volume imaging of birefringence through fibre-optic needle probes for the delineation of breast tumour

NASA Astrophysics Data System (ADS)

Villiger, Martin; Lorenser, Dirk; McLaughlin, Robert A.; Quirk, Bryden C.; Kirk, Rodney W.; Bouma, Brett E.; Sampson, David D.

2016-07-01

Identifying tumour margins during breast-conserving surgeries is a persistent challenge. We have previously developed miniature needle probes that could enable intraoperative volume imaging with optical coherence tomography. In many situations, however, scattering contrast alone is insufficient to clearly identify and delineate malignant regions. Additional polarization-sensitive measurements provide the means to assess birefringence, which is elevated in oriented collagen fibres and may offer an intrinsic biomarker to differentiate tumour from benign tissue. Here, we performed polarization-sensitive optical coherence tomography through miniature imaging needles and developed an algorithm to efficiently reconstruct images of the depth-resolved tissue birefringence free of artefacts. First ex vivo imaging of breast tumour samples revealed excellent contrast between lowly birefringent malignant regions, and stromal tissue, which is rich in oriented collagen and exhibits higher birefringence, as confirmed with co-located histology. The ability to clearly differentiate between tumour and uninvolved stroma based on intrinsic contrast could prove decisive for the intraoperative assessment of tumour margins.

Bond-selective imaging of deep tissue through the optical window between 1600 and 1850 nm.

PubMed

Wang, Pu; Wang, Han-Wei; Sturek, Michael; Cheng, Ji-Xin

2012-01-01

We report the employment of an optical window between 1600 nm and 1850 nm for bond-selective deep tissue imaging through harmonic vibrational excitation and acoustic detection of resultant pressure waves. In this window where a local minimum of water absorption resides, we found a 5 times enhancement of photoacoustic signal by first overtone excitation of the methylene group CH(2) at 1730 nm, compared to the second overtone excitation at 1210 nm. The enhancement allows 3D mapping of intramuscular fat with improved contrast and of lipid deposition inside an atherosclerotic artery wall in the presence of blood. Moreover, lipid and protein are differentiated based on the first overtone absorption profiles of CH(2) and methyl group CH(3) in this window. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Transurethral illumination probe design for deep photoacoustic imaging of prostate

NASA Astrophysics Data System (ADS)

Ai, Min; Salcudean, Tim; Rohling, Robert; Abolmaesumi, Purang; Tang, Shuo

2018-02-01

Photoacoustic (PA) imaging with internal light illumination through optical fiber could enable imaging of internal organs at deep penetration. We have developed a transurethral probe with a multimode fiber inserted in a rigid cystoscope sheath for illuminating the prostate. At the distal end, the fiber tip is processed to diffuse light circumferentially over 2 cm length. A parabolic cylinder mirror then reflects the light to form a rectangular-shaped parallel beam which has at least 1 cm2 at the probe surface. The relatively large rectangular beam size can reduce the laser fluence rate on the urethral wall and thus reduce the potential of tissue damage. A 3 cm optical penetration in chicken tissue is achieved at a fluence rate around 7 mJ/cm2 . For further validation, a prostate phantom was built with similar optical properties of the human prostate. A 1.5 cm penetration depth is achieved in the prostate mimicking phantom at 10 mJ/cm2 fluence rate. PA imaging of prostate can potentially be carried out in the future by combining a transrectal ultrasound transducer and the transurethral illumination.

3D Printer Generated Tissue iMolds for Cleared Tissue Using Single- and Multi-Photon Microscopy for Deep Tissue Evaluation.

PubMed

Miller, Sean J; Rothstein, Jeffrey D

2017-01-01

Pathological analyses and methodology has recently undergone a dramatic revolution. With the creation of tissue clearing methods such as CLARITY and CUBIC, groups can now achieve complete transparency in tissue samples in nano-porous hydrogels. Cleared tissue is then imagined in a semi-aqueous medium that matches the refractive index of the objective being used. However, one major challenge is the ability to control tissue movement during imaging and to relocate precise locations post sequential clearing and re-staining. Using 3D printers, we designed tissue molds that fit precisely around the specimen being imaged. First, images are taken of the specimen, followed by importing and design of a structural mold, then printed with affordable plastics by a 3D printer. With our novel design, we have innovated tissue molds called innovative molds (iMolds) that can be generated in any laboratory and are customized for any organ, tissue, or bone matter being imaged. Furthermore, the inexpensive and reusable tissue molds are made compatible for any microscope such as single and multi-photon confocal with varying stage dimensions. Excitingly, iMolds can also be generated to hold multiple organs in one mold, making reconstruction and imaging much easier. Taken together, with iMolds it is now possible to image cleared tissue in clearing medium while limiting movement and being able to relocate precise anatomical and cellular locations on sequential imaging events in any basic laboratory. This system provides great potential for screening widespread effects of therapeutics and disease across entire organ systems.

Optical Brain Imaging: A Powerful Tool for Neuroscience.

PubMed

Zhu, Xinpei; Xia, Yanfang; Wang, Xuecen; Si, Ke; Gong, Wei

2017-02-01

As the control center of organisms, the brain remains little understood due to its complexity. Taking advantage of imaging methods, scientists have found an accessible approach to unraveling the mystery of neuroscience. Among these methods, optical imaging techniques are widely used due to their high molecular specificity and single-molecule sensitivity. Here, we overview several optical imaging techniques in neuroscience of recent years, including brain clearing, the micro-optical sectioning tomography system, and deep tissue imaging.

Hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic imaging

NASA Astrophysics Data System (ADS)

Chen, Zhenyue; Deán-Ben, Xosé Luís.; Gottschalk, Sven; Razansky, Daniel

2018-02-01

Fluorescence imaging is widely employed in all fields of cell and molecular biology due to its high sensitivity, high contrast and ease of implementation. However, the low spatial resolution and lack of depth information, especially in strongly-scattering samples, restrict its applicability for deep-tissue imaging applications. On the other hand, optoacoustic imaging is known to deliver a unique set of capabilities such as high spatial and temporal resolution in three dimensions, deep penetration and spectrally-enriched imaging contrast. Since fluorescent substances can generate contrast in both modalities, simultaneous fluorescence and optoacoustic readings can provide new capabilities for functional and molecular imaging of living organisms. Optoacoustic images can further serve as valuable anatomical references based on endogenous hemoglobin contrast. Herein, we propose a hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic tomography, both operating in reflection mode, which synergistically combines the advantages of stand-alone systems. Validation of the spatial resolution and sensitivity of the system were first carried out in tissue mimicking phantoms while in vivo imaging was further demonstrated by tracking perfusion of an optical contrast agent in a mouse brain in the hybrid imaging mode. Experimental results show that the proposed system effectively exploits the contrast mechanisms of both imaging modalities, making it especially useful for accurate monitoring of fluorescence-based signal dynamics in highly scattering samples.

Spatial Statistics for Segmenting Histological Structures in H&E Stained Tissue Images.

PubMed

Nguyen, Luong; Tosun, Akif Burak; Fine, Jeffrey L; Lee, Adrian V; Taylor, D Lansing; Chennubhotla, S Chakra

2017-07-01

Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g., tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. This paper focuses on segmenting histological structures in hematoxylin- and eosin-stained images of breast tissues, e.g., invasive carcinoma, carcinoma in situ, atypical and normal ducts, adipose tissue, and lymphocytes. We propose two graph-theoretic segmentation methods based on local spatial color and nuclei neighborhood statistics. For benchmarking, we curated a data set of 232 high-power field breast tissue images together with expertly annotated ground truth. To accurately model the preference for histological structures (ducts, vessels, tumor nets, adipose, etc.) over the remaining connective tissue and non-tissue areas in ground truth annotations, we propose a new region-based score for evaluating segmentation algorithms. We demonstrate the improvement of our proposed methods over the state-of-the-art algorithms in both region- and boundary-based performance measures.

Needle-based polarization-sensitive OCT of breast tumor (Conference Presentation)

NASA Astrophysics Data System (ADS)

Villiger, Martin; Lorenser, Dirk; McLaughlin, Robert A.; Quirk, Bryden C.; Kirk, Rodney W.; Bouma, Brett E.; Sampson, David D.

2016-03-01

OCT imaging through miniature needle probes has extended the range of OCT and enabled structural imaging deep inside breast tissue, with the potential to assist in the intraoperative assessment of tumor margins. However, in many situations, scattering contrast alone is insufficient to clearly identify and delineate malignant areas. Here, we present a portable, depth-encoded polarization-sensitive OCT system, connected to a miniature needle probe. From the measured polarization states we constructed the tissue Mueller matrix at each sample location and improved the accuracy of the measured polarization states through incoherent averaging before retrieving the depth-resolved tissue birefringence. With the Mueller matrix at hand, additional polarization properties such as depolarization are readily available. We then imaged freshly excised breast tissue from a patient undergoing lumpectomy. The reconstructed local retardation highlighted regions of connective tissue, which exhibited birefringence due to the abundance of collagen fibers, and offered excellent contrast to areas of malignant tissue, which exhibited less birefringence due to their different tissue composition. Results were validated against co-located histology sections. The combination of needle-based imaging with the complementary contrast provided by polarization-sensitive analysis offers a powerful instrument for advanced tissue imaging and has potential to aid in the assessment of tumor margins during the resection of breast cancer.

Enhancement of photoacoustic tomography by ultrasonic computed tomography based on optical excitation of elements of a full-ring transducer array.

PubMed

Xia, Jun; Huang, Chao; Maslov, Konstantin; Anastasio, Mark A; Wang, Lihong V

2013-08-15

Photoacoustic computed tomography (PACT) is a hybrid technique that combines optical excitation and ultrasonic detection to provide high-resolution images in deep tissues. In the image reconstruction, a constant speed of sound (SOS) is normally assumed. This assumption, however, is often not strictly satisfied in deep tissue imaging, due to acoustic heterogeneities within the object and between the object and the coupling medium. If these heterogeneities are not accounted for, they will cause distortions and artifacts in the reconstructed images. In this Letter, we incorporated ultrasonic computed tomography (USCT), which measures the SOS distribution within the object, into our full-ring array PACT system. Without the need for ultrasonic transmitting electronics, USCT was performed using the same laser beam as for PACT measurement. By scanning the laser beam on the array surface, we can sequentially fire different elements. As a first demonstration of the system, we studied the effect of acoustic heterogeneities on photoacoustic vascular imaging. We verified that constant SOS is a reasonable approximation when the SOS variation is small. When the variation is large, distortion will be observed in the periphery of the object, especially in the tangential direction.

Improved QD-BRET conjugates for detection and imaging

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

Xing Yun; So, Min-kyung; Koh, Ai Leen

2008-08-01

Self-illuminating quantum dots, also known as QD-BRET conjugates, are a new class of quantum dot bioconjugates which do not need external light for excitation. Instead, light emission relies on the bioluminescence resonance energy transfer from the attached Renilla luciferase enzyme, which emits light upon the oxidation of its substrate. QD-BRET combines the advantages of the QDs (such as superior brightness and photostability, tunable emission, multiplexing) as well as the high sensitivity of bioluminescence imaging, thus holding the promise for improved deep tissue in vivo imaging. Although studies have demonstrated the superior sensitivity and deep tissue imaging potential, the stability ofmore » the QD-BRET conjugates in biological environment needs to be improved for long-term imaging studies such as in vivo cell tracking. In this study, we seek to improve the stability of QD-BRET probes through polymeric encapsulation with a polyacrylamide gel. Results show that encapsulation caused some activity loss, but significantly improved both the in vitro serum stability and in vivo stability when subcutaneously injected into the animal. Stable QD-BRET probes should further facilitate their applications for both in vitro testing as well as in vivo cell tracking studies.« less

Cardiovascular Imaging Using Two-Photon Microscopy

PubMed Central

Scherschel, John A.; Rubart, Michael

2008-01-01

Two-photon excitation microscopy has become the standard technique for high resolution deep tissue and intravital imaging. It provides intrinsic three-dimensional resolution in combination with increased penetration depth compared to single-photon confocal microscopy. This article will describe the basic physical principles of two-photon excitation and will review its multiple applications to cardiovascular imaging, including second harmonic generation and fluorescence laser scanning microscopy. In particular, the capability and limitations of multiphoton microscopy to assess functional heterogeneity on a cellular scale deep within intact, Langendorff-perfused hearts are demonstrated. It will also discuss the use of two-photon excitation-induced release of caged compounds for the study of intracellular calcium signaling and intercellular dye transfer. PMID:18986603

Deep Learning in Gastrointestinal Endoscopy.

PubMed

Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

2016-01-01

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

Biodynamic Doppler imaging of subcellular motion inside 3D living tissue culture and biopsies (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nolte, David D.

2016-03-01

Biodynamic imaging is an emerging 3D optical imaging technology that probes up to 1 mm deep inside three-dimensional living tissue using short-coherence dynamic light scattering to measure the intracellular motions of cells inside their natural microenvironments. Biodynamic imaging is label-free and non-invasive. The information content of biodynamic imaging is captured through tissue dynamics spectroscopy that displays the changes in the Doppler signatures from intracellular constituents in response to applied compounds. The affected dynamic intracellular mechanisms include organelle transport, membrane undulations, cytoskeletal restructuring, strain at cellular adhesions, cytokinesis, mitosis, exo- and endo-cytosis among others. The development of 3D high-content assays such as biodynamic profiling can become a critical new tool for assessing efficacy of drugs and the suitability of specific types of tissue growth for drug discovery and development. The use of biodynamic profiling to predict clinical outcome of living biopsies to cancer therapeutics can be developed into a phenotypic companion diagnostic, as well as a new tool for therapy selection in personalized medicine. This invited talk will present an overview of the optical, physical and physiological processes involved in biodynamic imaging. Several different biodynamic imaging modalities include motility contrast imaging (MCI), tissue-dynamics spectroscopy (TDS) and tissue-dynamics imaging (TDI). A wide range of potential applications will be described that include process monitoring for 3D tissue culture, drug discovery and development, cancer therapy selection, embryo assessment for in-vitro fertilization and artificial reproductive technologies, among others.

Multimodal optoacoustic and multiphoton fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sela, Gali; Razansky, Daniel; Shoham, Shy

2013-03-01

Multiphoton microscopy is a powerful imaging modality that enables structural and functional imaging with cellular and sub-cellular resolution, deep within biological tissues. Yet, its main contrast mechanism relies on extrinsically administered fluorescent indicators. Here we developed a system for simultaneous multimodal optoacoustic and multiphoton fluorescence 3D imaging, which attains both absorption and fluorescence-based contrast by integrating an ultrasonic transducer into a two-photon laser scanning microscope. The system is readily shown to enable acquisition of multimodal microscopic images of fluorescently labeled targets and cell cultures as well as intrinsic absorption-based images of pigmented biological tissue. During initial experiments, it was further observed that that detected optoacoustically-induced response contains low frequency signal variations, presumably due to cavitation-mediated signal generation by the high repetition rate (80MHz) near IR femtosecond laser. The multimodal system may provide complementary structural and functional information to the fluorescently labeled tissue, by superimposing optoacoustic images of intrinsic tissue chromophores, such as melanin deposits, pigmentation, and hemoglobin or other extrinsic particle or dye-based markers highly absorptive in the NIR spectrum.

Development of multifunctional optical coherence tomography and application to mouse myocardial infarction model in vivo (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jang, Sun-Joo; Park, Taejin; Shin, Inho; Park, Hyun Sang; Shin, Paul; Oh, Wang-Yuhl

2016-02-01

Optical coherence tomography (OCT) is a useful imaging method for in vivo tissue imaging with deep penetration and high spatial resolution. However, imaging of the beating mouse heart is still challenging due to limited temporal resolution or penetration depth. Here, we demonstrate a multifunctional OCT system for a beating mouse heart, providing various types of visual information about heart pathophysiology with high spatiotemporal resolution and deep tissue imaging. Angiographic imaging and polarization-sensitive (PS) imaging were implemented with the electrocardiogram (ECG)-triggered beam scanning scheme on the high-speed OCT platform (A-line rate: 240 kHz). Depth-resolved local birefringence and the local orientation of the mouse myocardial fiber were visualized from the PS-OCT. ECG-triggered angiographic OCT (AOCT) with the custom-built motion stabilization imaging window provided myocardial vasculature of a beating mouse heart. Mice underwent coronary artery ligation to derive myocardial infarction (MI) and were imaged with the multifunctional OCT system at multiple time points. AOCT and PS-OCT visualize change of functionality of coronary vessels and myocardium respectively at different phases (acute and chronic) of MI in an ischemic mouse heart. Taken together, the integrated imaging of PS-OCT and AOCT would play an important role in study of MI providing multi-dimensional information of the ischemic mouse heart in vivo.

Use of kurtosis for locating deep blood vessels in raw speckle imaging using a homogeneity representation.

PubMed

Peregrina-Barreto, Hayde; Perez-Corona, Elizabeth; Rangel-Magdaleno, Jose; Ramos-Garcia, Ruben; Chiu, Roger; Ramirez-San-Juan, Julio C

2017-06-01

Visualization of deep blood vessels in speckle images is an important task as it is used to analyze the dynamics of the blood flow and the health status of biological tissue. Laser speckle imaging is a wide-field optical technique to measure relative blood flow speed based on the local speckle contrast analysis. However, it has been reported that this technique is limited to certain deep blood vessels (about ? = 300 ?? ? m ) because of the high scattering of the sample; beyond this depth, the quality of the vessel’s image decreases. The use of a representation based on homogeneity values, computed from the co-occurrence matrix, is proposed as it provides an improved vessel definition and its corresponding diameter. Moreover, a methodology is proposed for automatic blood vessel location based on the kurtosis analysis. Results were obtained from the different skin phantoms, showing that it is possible to identify the vessel region for different morphologies, even up to 900 ?? ? m in depth.

Penetration depth of photons in biological tissues from hyperspectral imaging in shortwave infrared in transmission and reflection geometries.

PubMed

Zhang, Hairong; Salo, Daniel; Kim, David M; Komarov, Sergey; Tai, Yuan-Chuan; Berezin, Mikhail Y

2016-12-01

Measurement of photon penetration in biological tissues is a central theme in optical imaging. A great number of endogenous tissue factors such as absorption, scattering, and anisotropy affect the path of photons in tissue, making it difficult to predict the penetration depth at different wavelengths. Traditional studies evaluating photon penetration at different wavelengths are focused on tissue spectroscopy that does not take into account the heterogeneity within the sample. This is especially critical in shortwave infrared where the individual vibration-based absorption properties of the tissue molecules are affected by nearby tissue components. We have explored the depth penetration in biological tissues from 900 to 1650 nm using Monte–Carlo simulation and a hyperspectral imaging system with Michelson spatial contrast as a metric of light penetration. Chromatic aberration-free hyperspectral images in transmission and reflection geometries were collected with a spectral resolution of 5.27 nm and a total acquisition time of 3 min. Relatively short recording time minimized artifacts from sample drying. Results from both transmission and reflection geometries consistently revealed that the highest spatial contrast in the wavelength range for deep tissue lies within 1300 to 1375 nm; however, in heavily pigmented tissue such as the liver, the range 1550 to 1600 nm is also prominent.

MRI in necrotizing fasciitis of the extremities.

PubMed

Ali, S Z; Srinivasan, S; Peh, W C G

2014-01-01

Necrotizing fasciitis is a life-threatening soft-tissue infection of bacterial origin, which involves mainly the deep fascia. Early recognition of this condition may be hampered by the uncommon nature of the disease and non-specificity of initial clinical signs and symptoms in less fulminant cases, making the role of imaging important. MRI is the most useful imaging modality in the diagnosis of necrotizing fasciitis. The presence of thick (>3 mm) hyperintense signal in the deep fascia (particularly intermuscular fascia) on fat-suppressed T2 weighted or short tau inversion-recovery images is an important marker for necrotizing fasciitis. Contrast enhancement of the thickened necrotic fascia can be variable, with a mixed-pattern of enhancement being more commonly encountered. Involvement of multiple musculofascial compartments increases the likelihood of necrotizing fasciitis. It is important to remember that T2-hyperintense signal in the deep fascia is not specific to necrotizing fasciitis and can also be seen in cases such as non-infective inflammatory fasciitis or muscle tear. In this pictorial essay, we aim to review the MRI findings in necrotizing fasciitis, discuss its limitations and pitfalls and identify differentiating features from non-necrotizing soft-tissue infections, such as cellulitis and infective myositis/pyomyositis, conditions which may clinically mimic necrotizing fasciitis.

MRI in necrotizing fasciitis of the extremities

PubMed Central

Srinivasan, S; Peh, W C G

2014-01-01

Necrotizing fasciitis is a life-threatening soft-tissue infection of bacterial origin, which involves mainly the deep fascia. Early recognition of this condition may be hampered by the uncommon nature of the disease and non-specificity of initial clinical signs and symptoms in less fulminant cases, making the role of imaging important. MRI is the most useful imaging modality in the diagnosis of necrotizing fasciitis. The presence of thick (>3 mm) hyperintense signal in the deep fascia (particularly intermuscular fascia) on fat-suppressed T2 weighted or short tau inversion–recovery images is an important marker for necrotizing fasciitis. Contrast enhancement of the thickened necrotic fascia can be variable, with a mixed-pattern of enhancement being more commonly encountered. Involvement of multiple musculofascial compartments increases the likelihood of necrotizing fasciitis. It is important to remember that T2-hyperintense signal in the deep fascia is not specific to necrotizing fasciitis and can also be seen in cases such as non-infective inflammatory fasciitis or muscle tear. In this pictorial essay, we aim to review the MRI findings in necrotizing fasciitis, discuss its limitations and pitfalls and identify differentiating features from non-necrotizing soft-tissue infections, such as cellulitis and infective myositis/pyomyositis, conditions which may clinically mimic necrotizing fasciitis. PMID:24288403

Birefringence and vascular imaging of in vivo human skin by Jones-matrix optical coherence tomography

NASA Astrophysics Data System (ADS)

Li, En; Makita, Shuichi; Hong, Young-Joo; Kasaragod, Deepa; Yasuno, Yoshiaki

2017-02-01

A customized 1310-nm Jones-matrix optical coherence tomography (JM-OCT) for dermatological investigation was constructed and used for in vivo normal human skin tissue imaging. This system can simultaneously measure the threedimensional depth-resolved local birefringence, complex-correlation based OCT angiography (OCT-A), degree-ofpolarization- uniformity (DOPU) and scattering OCT intensity. By obtaining these optical properties of tissue, the morphology, vasculature, and collagen content of skin can be deduced and visualized. Structures in the deep layers of the epithelium were observed with depth-resolved local birefringence and polarization uniformity images. These results suggest high diagnostic and investigative potential of JM-OCT for dermatology.

In vivo microwave-based thermoacoustic tomography of rats (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lin, Li; Zhou, Yong; Wang, Lihong V.

2016-03-01

Microwave-based thermoacoustic tomography (TAT), based on the measurement of ultrasonic waves induced by microwave pulses, can reveal tissue dielectric properties that may be closely related to the physiological and pathological status of the tissues. Using microwaves as the excitation source improved imaging depth because of their deep penetration into biological tissues. We demonstrate, for the first time, in vivo microwave-based thermoacoustic imaging in rats. The transducer is rotated around the rat in a full circle, providing a full two-dimensional view. Instead of a flat ultrasonic transducer, we used a virtual line detector based on a cylindrically focused transducer. A 3 GHz microwave source with 0.6 µs pulse width and an electromagnetically shielded transducer with 2.25 MHz central frequency provided clear cross-sectional images of the rat's body. The high imaging contrast, based on the tissue's rate of absorption, and the ultrasonically defined spatial resolution combine to reveal the spine, kidney, muscle, and other deeply seated anatomical features in the rat's abdominal cavity. This non-invasive and non-ionizing imaging modality achieved an imaging depth beyond 6 cm in the rat's tissue. Cancer diagnosis based on information about tissue properties from microwave band TAT can potentially be more accurate than has previously been achievable.

In vivo multiphoton imaging of a diverse array of fluorophores to investigate deep neurovascular structure

PubMed Central

Miller, David R.; Hassan, Ahmed M.; Jarrett, Jeremy W.; Medina, Flor A.; Perillo, Evan P.; Hagan, Kristen; Shams Kazmi, S. M.; Clark, Taylor A.; Sullender, Colin T.; Jones, Theresa A.; Zemelman, Boris V.; Dunn, Andrew K.

2017-01-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. By combining the high repetition rate (511 kHz) and high pulse energy (400 nJ) of our amplifier laser system, we demonstrate imaging of vasculature labeled with Texas Red and Indocyanine Green, and neurons expressing tdTomato and yellow fluorescent protein. We measure the blood flow speed of a single capillary at a depth of 1.2 mm, and image vasculature to a depth of 1.53 mm with fine axial steps (5 μm) and reasonable acquisition times. The high image quality enabled analysis of vascular morphology at depths to 1.45 mm. PMID:28717582

Focal switching of photochromic fluorescent proteins enables multiphoton microscopy with superior image contrast.

PubMed

Kao, Ya-Ting; Zhu, Xinxin; Xu, Fang; Min, Wei

2012-08-01

Probing biological structures and functions deep inside live organisms with light is highly desirable. Among the current optical imaging modalities, multiphoton fluorescence microscopy exhibits the best contrast for imaging scattering samples by employing a spatially confined nonlinear excitation. However, as the incident laser power drops exponentially with imaging depth into the sample due to the scattering loss, the out-of-focus background eventually overwhelms the in-focus signal, which defines a fundamental imaging-depth limit. Herein we significantly improve the image contrast for deep scattering samples by harnessing reversibly switchable fluorescent proteins (RSFPs) which can be cycled between bright and dark states upon light illumination. Two distinct techniques, multiphoton deactivation and imaging (MPDI) and multiphoton activation and imaging (MPAI), are demonstrated on tissue phantoms labeled with Dronpa protein. Such a focal switch approach can generate pseudo background-free images. Conceptually different from wave-based approaches that try to reduce light scattering in turbid samples, our work represents a molecule-based strategy that focused on imaging probes.

Focal switching of photochromic fluorescent proteins enables multiphoton microscopy with superior image contrast

PubMed Central

Kao, Ya-Ting; Zhu, Xinxin; Xu, Fang; Min, Wei

2012-01-01

Probing biological structures and functions deep inside live organisms with light is highly desirable. Among the current optical imaging modalities, multiphoton fluorescence microscopy exhibits the best contrast for imaging scattering samples by employing a spatially confined nonlinear excitation. However, as the incident laser power drops exponentially with imaging depth into the sample due to the scattering loss, the out-of-focus background eventually overwhelms the in-focus signal, which defines a fundamental imaging-depth limit. Herein we significantly improve the image contrast for deep scattering samples by harnessing reversibly switchable fluorescent proteins (RSFPs) which can be cycled between bright and dark states upon light illumination. Two distinct techniques, multiphoton deactivation and imaging (MPDI) and multiphoton activation and imaging (MPAI), are demonstrated on tissue phantoms labeled with Dronpa protein. Such a focal switch approach can generate pseudo background-free images. Conceptually different from wave-based approaches that try to reduce light scattering in turbid samples, our work represents a molecule-based strategy that focused on imaging probes. PMID:22876358

Recent Advances of Light-Mediated Theranostics

PubMed Central

Ai, Xiangzhao; Mu, Jing; Xing, Bengang

2016-01-01

Currently, precision theranostics have been extensively demanded for the effective treatment of various human diseases. Currently, efficient therapy at the targeted disease areas still remains challenging since most available drug molecules lack of selectivity to the pathological sites. Among different approaches, light-mediated therapeutic strategy has recently emerged as a promising and powerful tool to precisely control the activation of therapeutic reagents and imaging probes in vitro and in vivo, mostly attributed to its unique properties including minimally invasive capability and highly spatiotemporal resolution. Although it has achieved initial success, the conventional strategies for light-mediated theranostics are mostly based on the light with short wavelength (e.g., UV or visible light), which may usually suffer from several undesired drawbacks, such as limited tissue penetration depth, unavoidable light absorption/scattering and potential phototoxicity to healthy tissues, etc. Therefore, a near-infrared (NIR) light-mediated approach on the basis of long-wavelength light (700-1000 nm) irradiation, which displays deep-tissue penetration, minimized photo-damage and low autofluoresence in living systems, has been proposed as an inspiring alternative for precisely phototherapeutic applications in the last decades. Despite numerous NIR light-responsive molecules have been currently proposed for clinical applications, several inherent drawbacks, such as troublesome synthetic procedures, low water solubility and limited accumulation abilities in targeted areas, heavily restrict their applications in deep-tissue therapeutic and imaging studies. Thanks to the amazing properties of several nanomaterials with large extinction coefficient in the NIR region, the construction of NIR light responsive nanoplatforms with multifunctions have become promising approaches for deep-seated diseases diagnosis and therapy. In this review, we summarized various light-triggered theranostic strategies and introduced their great advances in biomedical applications in recent years. Moreover, some other promising light-assisted techniques, such as photoacoustic and Cerenkov radiation, were also systemically discussed. Finally, the potential challenges and future perspectives for light-mediated deep-tissue diagnosis and therapeutics were proposed. PMID:27877246

Ex vivo validation of photo-magnetic imaging.

PubMed

Luk, Alex; Nouizi, Farouk; Erkol, Hakan; Unlu, Mehmet B; Gulsen, Gultekin

2017-10-15

We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions. We have previously demonstrated the feasibility of PMI with experimental studies using tissue simulating agarose phantoms. In this Letter, we present the preliminary ex vivo PMI results obtained with a chicken breast sample. Similarly to the results obtained on phantoms, the reconstructed images reveal that PMI can quantitatively resolve an inclusion with a 3 mm diameter embedded deep in a biological tissue sample with only 10% error. These encouraging results demonstrate the high performance of PMI in ex vivo biological tissue and its potential for in vivo imaging.

Pulsed Magneto-motive Ultrasound Imaging Using Ultrasmall Magnetic Nanoprobes

PubMed Central

Mehrmohammadi, Mohammad; Oh, Junghwan; Mallidi, Srivalleesha; Emelianov, Stanislav Y.

2011-01-01

Nano-sized particles are widely regarded as a tool to study biologic events at the cellular and molecular levels. However, only some imaging modalities can visualize interaction between nanoparticles and living cells. We present a new technique, pulsed magneto-motive ultrasound imaging, which is capable of in vivo imaging of magnetic nanoparticles in real time and at sufficient depth. In pulsed magneto-motive ultrasound imaging, an external high-strength pulsed magnetic field is applied to induce the motion within the magnetically labeled tissue and ultrasound is used to detect the induced internal tissue motion. Our experiments demonstrated a sufficient contrast between normal and iron-laden cells labeled with ultrasmall magnetic nanoparticles. Therefore, pulsed magneto-motive ultrasound imaging could become an imaging tool capable of detecting magnetic nanoparticles and characterizing the cellular and molecular composition of deep-lying structures. PMID:21439255

Identifying mitosis deep in tissue using dynamic light scattering fluctuation spectroscopy

NASA Astrophysics Data System (ADS)

An, Ran; Jeong, Kwan; Turek, John; Nolte, David

2012-03-01

In the cell cycle, mitosis is the most dramatic phase, especially in Telophase and Cytokinesis. For single cells and cell monolayer, there are precise microscopic studies of mitosis, while for 3-D tissue such as tumor spheroids the light signal is obscured by the high background of diffusely scattered light. Therefore, the mitosis phase cannot be detected deep inside 3-D tissue using conventional microscopic techniques. In this work, we detect mitosis in living tissue using Tissue Dynamic Imaging (TDI). We trace depth-gated dynamic speckles from a tumor spheroid (up to 1mm in diameter) using coherence-gated digital holography imaging. Frequency-versus-time spectrograms depend on specific types of perturbation such as cell shape change, membrane undulation and cell organelles movements. By using these spectral responses as functional finger prints, we can identify mitosis events from different voxels at a specified depth inside tumor spheroids. By performing B-scans of the tumor spheroid, we generate 3-D mitosis maps (or movies) for the entire tumor spheroids. We show that for healthy tumor spheroids, the mitosis events only happen within the proliferating shell. We also compare results when anti-cancer drugs are applied to arrest, release and synchronize mitosis. This shows the application of TDI for drug screening. The technique can identify and monitor complex motilities inside 3-D tissue with a strong potential for drug diagnosis and developmental biology studies.

Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches

NASA Astrophysics Data System (ADS)

Amit, Guy; Ben-Ari, Rami; Hadad, Omer; Monovich, Einat; Granot, Noa; Hashoul, Sharbell

2017-03-01

Diagnostic interpretation of breast MRI studies requires meticulous work and a high level of expertise. Computerized algorithms can assist radiologists by automatically characterizing the detected lesions. Deep learning approaches have shown promising results in natural image classification, but their applicability to medical imaging is limited by the shortage of large annotated training sets. In this work, we address automatic classification of breast MRI lesions using two different deep learning approaches. We propose a novel image representation for dynamic contrast enhanced (DCE) breast MRI lesions, which combines the morphological and kinetics information in a single multi-channel image. We compare two classification approaches for discriminating between benign and malignant lesions: training a designated convolutional neural network and using a pre-trained deep network to extract features for a shallow classifier. The domain-specific trained network provided higher classification accuracy, compared to the pre-trained model, with an area under the ROC curve of 0.91 versus 0.81, and an accuracy of 0.83 versus 0.71. Similar accuracy was achieved in classifying benign lesions, malignant lesions, and normal tissue images. The trained network was able to improve accuracy by using the multi-channel image representation, and was more robust to reductions in the size of the training set. A small-size convolutional neural network can learn to accurately classify findings in medical images using only a few hundred images from a few dozen patients. With sufficient data augmentation, such a network can be trained to outperform a pre-trained out-of-domain classifier. Developing domain-specific deep-learning models for medical imaging can facilitate technological advancements in computer-aided diagnosis.

Three-photon tissue imaging using moxifloxacin.

PubMed

Lee, Seunghun; Lee, Jun Ho; Wang, Taejun; Jang, Won Hyuk; Yoon, Yeoreum; Kim, Bumju; Jun, Yong Woong; Kim, Myoung Joon; Kim, Ki Hean

2018-06-20

Moxifloxacin is an antibiotic used in clinics and has recently been used as a clinically compatible cell-labeling agent for two-photon (2P) imaging. Although 2P imaging with moxifloxacin labeling visualized cells inside tissues using enhanced fluorescence, the imaging depth was quite limited because of the relatively short excitation wavelength (<800 nm) used. In this study, the feasibility of three-photon (3P) excitation of moxifloxacin using a longer excitation wavelength and moxifloxacin-based 3P imaging were tested to increase the imaging depth. Moxifloxacin fluorescence via 3P excitation was detected at a >1000 nm excitation wavelength. After obtaining the excitation and emission spectra of moxifloxacin, moxifloxacin-based 3P imaging was applied to ex vivo mouse bladder and ex vivo mouse small intestine tissues and compared with moxifloxacin-based 2P imaging by switching the excitation wavelength of a Ti:sapphire oscillator between near 1030 and 780 nm. Both moxifloxacin-based 2P and 3P imaging visualized cellular structures in the tissues via moxifloxacin labeling, but the image contrast was better with 3P imaging than with 2P imaging at the same imaging depths. The imaging speed and imaging depth of moxifloxacin-based 3P imaging using a Ti:sapphire oscillator were limited by insufficient excitation power. Therefore, we constructed a new system for moxifloxacin-based 3P imaging using a high-energy Yb fiber laser at 1030 nm and used it for in vivo deep tissue imaging of a mouse small intestine. Moxifloxacin-based 3P imaging could be useful for clinical applications with enhanced imaging depth.

High resolution and deep tissue imaging using a near infrared acoustic resolution photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Moothanchery, Mohesh; Sharma, Arunima; Periyasamy, Vijitha; Pramanik, Manojit

2018-02-01

It is always a great challenge for pure optical techniques to maintain good resolution and imaging depth at the same time. Photoacoustic imaging is an emerging technique which can overcome the limitation by pulsed light illumination and acoustic detection. Here, we report a Near Infrared Acoustic-Resolution Photoacoustic Microscopy (NIR-AR-PAM) systm with 30 MHz transducer and 1064 nm illumination which can achieve a lateral resolution of around 88 μm and imaging depth of 9.2 mm. Compared to visible light NIR beam can penetrate deeper in biological tissue due to weaker optical attenuation. In this work, we also demonstrated the in vivo imaging capabilty of NIRARPAM by near infrared detection of SLN with black ink as exogenous photoacoustic contrast agent in a rodent model.

Lumen-based detection of prostate cancer via convolutional neural networks

NASA Astrophysics Data System (ADS)

Kwak, Jin Tae; Hewitt, Stephen M.

2017-03-01

We present a deep learning approach for detecting prostate cancers. The approach consists of two steps. In the first step, we perform tissue segmentation that identifies lumens within digitized prostate tissue specimen images. Intensity- and texture-based image features are computed at five different scales, and a multiview boosting method is adopted to cooperatively combine the image features from differing scales and to identify lumens. In the second step, we utilize convolutional neural networks (CNN) to automatically extract high-level image features of lumens and to predict cancers. The segmented lumens are rescaled to reduce computational complexity and data augmentation by scaling, rotating, and flipping the rescaled image is applied to avoid overfitting. We evaluate the proposed method using two tissue microarrays (TMA) - TMA1 includes 162 tissue specimens (73 Benign and 89 Cancer) and TMA2 comprises 185 tissue specimens (70 Benign and 115 Cancer). In cross-validation on TMA1, the proposed method achieved an AUC of 0.95 (CI: 0.93-0.98). Trained on TMA1 and tested on TMA2, CNN obtained an AUC of 0.95 (CI: 0.92-0.98). This demonstrates that the proposed method can potentially improve prostate cancer pathology.

Necrotizing fasciitis: contribution and limitations of diagnostic imaging.

PubMed

Malghem, Jacques; Lecouvet, Frédéric E; Omoumi, Patrick; Maldague, Baudouin E; Vande Berg, Bruno C

2013-03-01

Necrotizing fasciitis is a rare, rapidly spreading, deep-seated infection causing thrombosis of the blood vessels located in the fascia. Necrotizing fasciitis is a surgical emergency. The diagnosis typically relies on clinical findings of severe sepsis and intense pain, although subacute forms may be difficult to recognize. Imaging studies can help to differentiate necrotizing fasciitis from infections located more superficially (dermohypodermitis). The presence of gas within the necrotized fasciae is characteristic but may be lacking. The main finding is thickening of the deep fasciae due to fluid accumulation and reactive hyperemia, which can be visualized using computed tomography and, above all, magnetic resonance imaging (high signal on contrast-enhanced T1 images and T2 images, best seen with fat saturation). These findings lack specificity, as they can be seen in non-necrotizing fasciitis and even in non-inflammatory conditions. Signs that support a diagnosis of necrotizing fasciitis include extensive involvement of the deep intermuscular fascias (high sensitivity but low specificity), thickening to more than 3mm, and partial or complete absence on post-gadolinium images of signal enhancement of the thickened fasciae (fairly high sensitivity and specificity). Ultrasonography is not recommended in adults, as the infiltration of the hypodermis blocks ultrasound transmission. Thus, imaging studies in patients with necrotizing fasciitis may be challenging to interpret. Although imaging may help to confirm deep tissue involvement and to evaluate lesion spread, it should never delay emergency surgical treatment in patients with established necrotizing fasciitis. Copyright © 2012. Published by Elsevier SAS.

Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls.

PubMed

Yoo, Youngjin; Tang, Lisa Y W; Brosch, Tom; Li, David K B; Kolind, Shannon; Vavasour, Irene; Rauscher, Alexander; MacKay, Alex L; Traboulsee, Anthony; Tam, Roger C

2018-01-01

Myelin imaging is a form of quantitative magnetic resonance imaging (MRI) that measures myelin content and can potentially allow demyelinating diseases such as multiple sclerosis (MS) to be detected earlier. Although focal lesions are the most visible signs of MS pathology on conventional MRI, it has been shown that even tissues that appear normal may exhibit decreased myelin content as revealed by myelin-specific images (i.e., myelin maps). Current methods for analyzing myelin maps typically use global or regional mean myelin measurements to detect abnormalities, but ignore finer spatial patterns that may be characteristic of MS. In this paper, we present a machine learning method to automatically learn, from multimodal MR images, latent spatial features that can potentially improve the detection of MS pathology at early stage. More specifically, 3D image patches are extracted from myelin maps and the corresponding T1-weighted (T1w) MRIs, and are used to learn a latent joint myelin-T1w feature representation via unsupervised deep learning. Using a data set of images from MS patients and healthy controls, a common set of patches are selected via a voxel-wise t -test performed between the two groups. In each MS image, any patches overlapping with focal lesions are excluded, and a feature imputation method is used to fill in the missing values. A feature selection process (LASSO) is then utilized to construct a sparse representation. The resulting normal-appearing features are used to train a random forest classifier. Using the myelin and T1w images of 55 relapse-remitting MS patients and 44 healthy controls in an 11-fold cross-validation experiment, the proposed method achieved an average classification accuracy of 87.9% (SD = 8.4%), which is higher and more consistent across folds than those attained by regional mean myelin (73.7%, SD = 13.7%) and T1w measurements (66.7%, SD = 10.6%), or deep-learned features in either the myelin (83.8%, SD = 11.0%) or T1w (70.1%, SD = 13.6%) images alone, suggesting that the proposed method has strong potential for identifying image features that are more sensitive and specific to MS pathology in normal-appearing brain tissues.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Bioluminescence resonance energy transfer (BRET) imaging of protein–protein interactions within deep tissues of living subjects

PubMed Central

Dragulescu-Andrasi, Anca; Chan, Carmel T.; Massoud, Tarik F.; Gambhir, Sanjiv S.

2011-01-01

Identifying protein–protein interactions (PPIs) is essential for understanding various disease mechanisms and developing new therapeutic approaches. Current methods for assaying cellular intermolecular interactions are mainly used for cells in culture and have limited use for the noninvasive assessment of small animal disease models. Here, we describe red light-emitting reporter systems based on bioluminescence resonance energy transfer (BRET) that allow for assaying PPIs both in cell culture and deep tissues of small animals. These BRET systems consist of the recently developed Renilla reniformis luciferase (RLuc) variants RLuc8 and RLuc8.6, used as BRET donors, combined with two red fluorescent proteins, TagRFP and TurboFP635, as BRET acceptors. In addition to the native coelenterazine luciferase substrate, we used the synthetic derivative coelenterazine-v, which further red-shifts the emission maxima of Renilla luciferases by 35 nm. We show the use of these BRET systems for ratiometric imaging of both cells in culture and deep-tissue small animal tumor models and validate their applicability for studying PPIs in mice in the context of rapamycin-induced FK506 binding protein 12 (FKBP12)-FKBP12 rapamycin binding domain (FRB) association. These red light-emitting BRET systems have great potential for investigating PPIs in the context of drug screening and target validation applications. PMID:21730157

Biodynamic imaging for phenotypic profiling of three-dimensional tissue culture

PubMed Central

Sun, Hao; Merrill, Daniel; An, Ran; Turek, John; Matei, Daniela; Nolte, David D.

2017-01-01

Abstract. Three-dimensional (3-D) tissue culture represents a more biologically relevant environment for testing new drugs compared to conventional two-dimensional cancer cell culture models. Biodynamic imaging is a high-content 3-D optical imaging technology based on low-coherence interferometry and digital holography that uses dynamic speckle as high-content image contrast to probe deep inside 3-D tissue. Speckle contrast is shown to be a scaling function of the acquisition time relative to the persistence time of intracellular transport and hence provides a measure of cellular activity. Cellular responses of 3-D multicellular spheroids to paclitaxel are compared among three different growth techniques: rotating bioreactor (BR), hanging-drop (HD), and nonadherent (U-bottom, UB) plate spheroids, compared with ex vivo living tissues. HD spheroids have the most homogeneous tissue, whereas BR spheroids display large sample-to-sample variability as well as spatial heterogeneity. The responses of BR-grown tumor spheroids to paclitaxel are more similar to those of ex vivo biopsies than the responses of spheroids grown using HD or plate methods. The rate of mitosis inhibition by application of taxol is measured through tissue dynamics spectroscopic imaging, demonstrating the ability to monitor antimitotic chemotherapy. These results illustrate the potential use of low-coherence digital holography for 3-D pharmaceutical screening applications. PMID:28301634

Biodynamic imaging for phenotypic profiling of three-dimensional tissue culture

NASA Astrophysics Data System (ADS)

Sun, Hao; Merrill, Daniel; An, Ran; Turek, John; Matei, Daniela; Nolte, David D.

2017-01-01

Three-dimensional (3-D) tissue culture represents a more biologically relevant environment for testing new drugs compared to conventional two-dimensional cancer cell culture models. Biodynamic imaging is a high-content 3-D optical imaging technology based on low-coherence interferometry and digital holography that uses dynamic speckle as high-content image contrast to probe deep inside 3-D tissue. Speckle contrast is shown to be a scaling function of the acquisition time relative to the persistence time of intracellular transport and hence provides a measure of cellular activity. Cellular responses of 3-D multicellular spheroids to paclitaxel are compared among three different growth techniques: rotating bioreactor (BR), hanging-drop (HD), and nonadherent (U-bottom, UB) plate spheroids, compared with ex vivo living tissues. HD spheroids have the most homogeneous tissue, whereas BR spheroids display large sample-to-sample variability as well as spatial heterogeneity. The responses of BR-grown tumor spheroids to paclitaxel are more similar to those of ex vivo biopsies than the responses of spheroids grown using HD or plate methods. The rate of mitosis inhibition by application of taxol is measured through tissue dynamics spectroscopic imaging, demonstrating the ability to monitor antimitotic chemotherapy. These results illustrate the potential use of low-coherence digital holography for 3-D pharmaceutical screening applications.

A smart upconversion-based light-triggered polymer for synergetic chemo-photodynamic therapy and dual-modal MR/UCL imaging.

PubMed

Du, Bin; Han, Shuping; Zhao, Feifei; Lim, Kok Hwa; Xi, Hongwei; Su, Xiangjie; Yao, Hanchun; Zhou, Jie

2016-10-01

We have developed a novel nanocomposite to achieve effective therapy and live surveillance of tumor tissue. In this study, fullerene (C 60 ) with iron oxide (Fe 3 O 4 ) nanoparticles and upconversion nanophosphors (UCNPs) was loaded into N-succinyl-N'-4-(2-nitrobenzyloxy)-succinyl-chitosan micelles (SNSC) with good biocompatibility. In addition, hydrophobic anticancer drug docetaxel (DTX) was also loaded into the nanocomposites. The experiments conducted in vitro and in vivo demonstrated that C 60 /Fe 3 O 4 -UCNPs@DTX@SNSC can act synergistically to kill tumor cells by releasing chemotherapy drugs at specific target site as well as generating reactive oxygen using 980nm. In addition, it can also be used for non-invasive deep magnetic resonance and upconversion fluorescence dual-mode imaging. The results indicated that this system provided an efficient method to surmount the drawback of UV or visible light-responsive polymeric systems for controlled drug release and generated reactive oxygen in deep tissues and ultimately realized the integration of dual-modal imaging and treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

High-throughput isotropic mapping of whole mouse brain using multi-view light-sheet microscopy

NASA Astrophysics Data System (ADS)

Nie, Jun; Li, Yusha; Zhao, Fang; Ping, Junyu; Liu, Sa; Yu, Tingting; Zhu, Dan; Fei, Peng

2018-02-01

Light-sheet fluorescence microscopy (LSFM) uses an additional laser-sheet to illuminate selective planes of the sample, thereby enabling three-dimensional imaging at high spatial-temporal resolution. These advantages make LSFM a promising tool for high-quality brain visualization. However, even by the use of LSFM, the spatial resolution remains insufficient to resolve the neural structures across a mesoscale whole mouse brain in three dimensions. At the same time, the thick-tissue scattering prevents a clear observation from the deep of brain. Here we use multi-view LSFM strategy to solve this challenge, surpassing the resolution limit of standard light-sheet microscope under a large field-of-view (FOV). As demonstrated by the imaging of optically-cleared mouse brain labelled with thy1-GFP, we achieve a brain-wide, isotropic cellular resolution of 3μm. Besides the resolution enhancement, multi-view braining imaging can also recover complete signals from deep tissue scattering and attenuation. The identification of long distance neural projections across encephalic regions can be identified and annotated as a result.

Intrauterine photoacoustic and ultrasound imaging probe

NASA Astrophysics Data System (ADS)

Miranda, Christopher; Barkley, Joel; Smith, Barbara S.

2018-04-01

Intrauterine photoacoustic and ultrasound imaging are probe-based imaging modalities with translational potential for use in detecting endometrial diseases. This deep-tissue imaging probe design allows for the retrofitting of commercially available endometrial sampling curettes. The imaging probe presented here has a 2.92-mm diameter and approximate length of 26 cm, which allows for entry into the human endometrial cavity, making it possible to use photoacoustic imaging and high-resolution ultrasound to characterize the uterus. We demonstrate the imaging probes' ability to provide structural information of an excised pig uterus using ultrasound imaging and detect photoacoustic signals at a radial depth of 1 cm.

Deep Tissue Photoacoustic Imaging Using a Miniaturized 2-D Capacitive Micromachined Ultrasonic Transducer Array

PubMed Central

Kothapalli, Sri-Rajasekhar; Ma, Te-Jen; Vaithilingam, Srikant; Oralkan, Ömer

2014-01-01

In this paper, we demonstrate 3-D photoacoustic imaging (PAI) of light absorbing objects embedded as deep as 5 cm inside strong optically scattering phantoms using a miniaturized (4 mm × 4 mm × 500 µm), 2-D capacitive micromachined ultrasonic transducer (CMUT) array of 16 × 16 elements with a center frequency of 5.5 MHz. Two-dimensional tomographic images and 3-D volumetric images of the objects placed at different depths are presented. In addition, we studied the sensitivity of CMUT-based PAI to the concentration of indocyanine green dye at 5 cm depth inside the phantom. Under optimized experimental conditions, the objects at 5 cm depth can be imaged with SNR of about 35 dB and a spatial resolution of approximately 500 µm. Results demonstrate that CMUTs with integrated front-end amplifier circuits are an attractive choice for achieving relatively high depth sensitivity for PAI. PMID:22249594

Penetration depth of photons in biological tissues from hyperspectral imaging in shortwave infrared in transmission and reflection geometries

PubMed Central

Zhang, Hairong; Salo, Daniel; Kim, David M.; Komarov, Sergey; Tai, Yuan-Chuan; Berezin, Mikhail Y.

2016-01-01

Abstract. Measurement of photon penetration in biological tissues is a central theme in optical imaging. A great number of endogenous tissue factors such as absorption, scattering, and anisotropy affect the path of photons in tissue, making it difficult to predict the penetration depth at different wavelengths. Traditional studies evaluating photon penetration at different wavelengths are focused on tissue spectroscopy that does not take into account the heterogeneity within the sample. This is especially critical in shortwave infrared where the individual vibration-based absorption properties of the tissue molecules are affected by nearby tissue components. We have explored the depth penetration in biological tissues from 900 to 1650 nm using Monte–Carlo simulation and a hyperspectral imaging system with Michelson spatial contrast as a metric of light penetration. Chromatic aberration-free hyperspectral images in transmission and reflection geometries were collected with a spectral resolution of 5.27 nm and a total acquisition time of 3 min. Relatively short recording time minimized artifacts from sample drying. Results from both transmission and reflection geometries consistently revealed that the highest spatial contrast in the wavelength range for deep tissue lies within 1300 to 1375 nm; however, in heavily pigmented tissue such as the liver, the range 1550 to 1600 nm is also prominent. PMID:27930773

Alveolar soft part sarcoma causing perianal abscess.

PubMed

Sullivan, Niall; McCulloch, Tom; Leverton, David

2011-07-01

A 34-year-old woman presented with a perianal abscess that communicated with the vagina. There was a background of a one-year history of a conservatively treated, traumatic, paravaginal haematoma. Histology of the fistula tract showed alveolar soft part sarcoma and subsequent imaging identified a large soft tissue mass in the pelvis with lung metastases. Alveolar soft part sarcoma is a rare soft tissue sarcoma of unknown cellular origin affecting predominantly young women, often in deep soft tissues and lower extremities.

Fast Calcium Imaging with Optical Sectioning via HiLo Microscopy.

PubMed

Lauterbach, Marcel A; Ronzitti, Emiliano; Sternberg, Jenna R; Wyart, Claire; Emiliani, Valentina

2015-01-01

Imaging intracellular calcium concentration via reporters that change their fluorescence properties upon binding of calcium, referred to as calcium imaging, has revolutionized our way to probe neuronal activity non-invasively. To reach neurons densely located deep in the tissue, optical sectioning at high rate of acquisition is necessary but difficult to achieve in a cost effective manner. Here we implement an accessible solution relying on HiLo microscopy to provide robust optical sectioning with a high frame rate in vivo. We show that large calcium signals can be recorded from dense neuronal populations at high acquisition rates. We quantify the optical sectioning capabilities and demonstrate the benefits of HiLo microscopy compared to wide-field microscopy for calcium imaging and 3D reconstruction. We apply HiLo microscopy to functional calcium imaging at 100 frames per second deep in biological tissues. This approach enables us to discriminate neuronal activity of motor neurons from different depths in the spinal cord of zebrafish embryos. We observe distinct time courses of calcium signals in somata and axons. We show that our method enables to remove large fluctuations of the background fluorescence. All together our setup can be implemented to provide efficient optical sectioning in vivo at low cost on a wide range of existing microscopes.

Fast Calcium Imaging with Optical Sectioning via HiLo Microscopy

PubMed Central

Sternberg, Jenna R.; Wyart, Claire; Emiliani, Valentina

2015-01-01

Imaging intracellular calcium concentration via reporters that change their fluorescence properties upon binding of calcium, referred to as calcium imaging, has revolutionized our way to probe neuronal activity non-invasively. To reach neurons densely located deep in the tissue, optical sectioning at high rate of acquisition is necessary but difficult to achieve in a cost effective manner. Here we implement an accessible solution relying on HiLo microscopy to provide robust optical sectioning with a high frame rate in vivo. We show that large calcium signals can be recorded from dense neuronal populations at high acquisition rates. We quantify the optical sectioning capabilities and demonstrate the benefits of HiLo microscopy compared to wide-field microscopy for calcium imaging and 3D reconstruction. We apply HiLo microscopy to functional calcium imaging at 100 frames per second deep in biological tissues. This approach enables us to discriminate neuronal activity of motor neurons from different depths in the spinal cord of zebrafish embryos. We observe distinct time courses of calcium signals in somata and axons. We show that our method enables to remove large fluctuations of the background fluorescence. All together our setup can be implemented to provide efficient optical sectioning in vivo at low cost on a wide range of existing microscopes. PMID:26625116

Three-dimensional brain MRI for DBS patients within ultra-low radiofrequency power limits.

PubMed

Sarkar, Subhendra N; Papavassiliou, Efstathios; Hackney, David B; Alsop, David C; Shih, Ludy C; Madhuranthakam, Ananth J; Busse, Reed F; La Ruche, Susan; Bhadelia, Rafeeque A

2014-04-01

For patients with deep brain stimulators (DBS), local absorbed radiofrequency (RF) power is unknown and is much higher than what the system estimates. We developed a comprehensive, high-quality brain magnetic resonance imaging (MRI) protocol for DBS patients utilizing three-dimensional (3D) magnetic resonance sequences at very low RF power. Six patients with DBS were imaged (10 sessions) using a transmit/receive head coil at 1.5 Tesla with modified 3D sequences within ultra-low specific absorption rate (SAR) limits (0.1 W/kg) using T2 , fast fluid-attenuated inversion recovery (FLAIR) and T1 -weighted image contrast. Tissue signal and tissue contrast from the low-SAR images were subjectively and objectively compared with routine clinical images of six age-matched controls. Low-SAR images of DBS patients demonstrated tissue contrast comparable to high-SAR images and were of diagnostic quality except for slightly reduced signal. Although preliminary, we demonstrated diagnostic quality brain MRI with optimized, volumetric sequences in DBS patients within very conservative RF safety guidelines offering a greater safety margin. © 2014 International Parkinson and Movement Disorder Society.

A CANDLE for a deeper in vivo insight

PubMed Central

Coupé, Pierrick; Munz, Martin; Manjón, Jose V; Ruthazer, Edward S; Louis Collins, D.

2012-01-01

A new Collaborative Approach for eNhanced Denoising under Low-light Excitation (CANDLE) is introduced for the processing of 3D laser scanning multiphoton microscopy images. CANDLE is designed to be robust for low signal-to-noise ratio (SNR) conditions typically encountered when imaging deep in scattering biological specimens. Based on an optimized non-local means filter involving the comparison of filtered patches, CANDLE locally adapts the amount of smoothing in order to deal with the noise inhomogeneity inherent to laser scanning fluorescence microscopy images. An extensive validation on synthetic data, images acquired on microspheres and in vivo images is presented. These experiments show that the CANDLE filter obtained competitive results compared to a state-of-the-art method and a locally adaptive optimized nonlocal means filter, especially under low SNR conditions (PSNR<8dB). Finally, the deeper imaging capabilities enabled by the proposed filter are demonstrated on deep tissue in vivo images of neurons and fine axonal processes in the Xenopus tadpole brain. PMID:22341767

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

PubMed Central

Kurihara, Daisuke; Mizuta, Yoko; Sato, Yoshikatsu; Higashiyama, Tetsuya

2015-01-01

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research. PMID:26493404

Intramuscular Lipoma: A Review of the Literature

PubMed Central

McTighe, Shane; Chernev, Ivan

2014-01-01

Lipomas are the most common type of soft tissue mesenchymal tumors. They are typically located subcutaneously and consist of mature fatty tissue. When they occur under the enclosing fascia, they are called deep-seated lipomas. Infrequently, lipomas can arise inside the muscle and are called intramuscular lipomas. Intramuscular lipomas have been commonly investigated and categorized in the same group as other deep-seated and superficial lipomatous lesions. Their clinical, histological and imaging characteristics may resemble well-differentiated liposarcomas, further adding to the difficulties in the differential diagnosis. This article summarizes the available literature and describes the typical epidemiological, pathological and clinical features of intramuscular lipomas, as well as delineating their treatment and prognosis. PMID:25568733

Ultrasound in Radiology: from Anatomic, Functional, Molecular Imaging to Drug Delivery and Image-Guided Therapy

PubMed Central

Klibanov, Alexander L.; Hossack, John A.

2015-01-01

During the past decade, ultrasound has expanded medical imaging well beyond the “traditional” radiology setting - a combination of portability, low cost and ease of use makes ultrasound imaging an indispensable tool for radiologists as well as for other medical professionals who need to obtain imaging diagnosis or guide a therapeutic intervention quickly and efficiently. Ultrasound combines excellent ability for deep penetration into soft tissues with very good spatial resolution, with only a few exceptions (i.e. those involving overlying bone or gas). Real-time imaging (up to hundreds and thousands frames per second) enables guidance of therapeutic procedures and biopsies; characterization of the mechanical properties of the tissues greatly aids with the accuracy of the procedures. The ability of ultrasound to deposit energy locally brings about the potential for localized intervention encompassing: tissue ablation, enhancing penetration through the natural barriers to drug delivery in the body and triggering drug release from carrier micro- and nanoparticles. The use of microbubble contrast agents brings the ability to monitor and quantify tissue perfusion, and microbubble targeting with ligand-decorated microbubbles brings the ability to obtain molecular biomarker information, i.e., ultrasound molecular imaging. Overall, ultrasound has become the most widely used imaging modality in modern medicine; it will continue to grow and expand. PMID:26200224

Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.

PubMed

Ehteshami Bejnordi, Babak; Mullooly, Maeve; Pfeiffer, Ruth M; Fan, Shaoqi; Vacek, Pamela M; Weaver, Donald L; Herschorn, Sally; Brinton, Louise A; van Ginneken, Bram; Karssemeijer, Nico; Beck, Andrew H; Gierach, Gretchen L; van der Laak, Jeroen A W M; Sherman, Mark E

2018-06-13

The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, visual classification of such changes is subjective and non-quantitative, limiting its diagnostic utility. To gain insights into stromal changes associated with breast cancer, we applied automated machine learning techniques to digital images of 2387 hematoxylin and eosin stained tissue sections of benign and malignant image-guided breast biopsies performed to investigate mammographic abnormalities among 882 patients, ages 40-65 years, that were enrolled in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project. Using deep convolutional neural networks, we trained an algorithm to discriminate between stroma surrounding invasive cancer and stroma from benign biopsies. In test sets (928 whole-slide images from 330 patients), this algorithm could distinguish biopsies diagnosed as invasive cancer from benign biopsies solely based on the stromal characteristics (area under the receiver operator characteristics curve = 0.962). Furthermore, without being trained specifically using ductal carcinoma in situ as an outcome, the algorithm detected tumor-associated stroma in greater amounts and at larger distances from grade 3 versus grade 1 ductal carcinoma in situ. Collectively, these results suggest that algorithms based on deep convolutional neural networks that evaluate only stroma may prove useful to classify breast biopsies and aid in understanding and evaluating the biology of breast lesions.

An MRI-based leg model used to simulate biomechanical phenomena during cuff algometry: a finite element study.

PubMed

Manafi-Khanian, Bahram; Arendt-Nielsen, Lars; Graven-Nielsen, Thomas

2016-03-01

Cuff pressure stimulation is applicable for assessing deep-tissue pain sensitivity by exciting a variety of deep-tissue nociceptors. In this study, the relative transfer of biomechanical stresses and strains from the cuff via the skin to the muscle and the somatic tissue layers around bones were investigated. Cuff pressure was applied on the lower leg at three different stimulation intensities (mild pressure to pain). Three-dimensional finite element models including bones and three different layers of deep tissues were developed based on magnetic resonance images (MRI). The skin indentation maps at mild pressure, pain threshold, and intense painful stimulations were extracted from MRI and applied to the model. The mean stress under the cuff position around tibia was 4.6, 4.9 and around fibula 14.8, 16.4 times greater than mean stress of muscle surface in the same section at pain threshold and intense painful stimulations, respectively. At the same stimulation intensities, the mean strains around tibia were 36.4, 42.3 % and around fibula 32.9, 35.0 %, respectively, of mean strain on the muscle surface. Assuming strain as the ideal stimulus for nociceptors the results suggest that cuff algometry is less capable to challenge the nociceptors of tissues around bones as compared to more superficially located muscles.

Ultralow-Power Near Infrared Lamp Light Operable Targeted Organic Nanoparticle Photodynamic Therapy.

PubMed

Huang, Ling; Li, Zhanjun; Zhao, Yang; Zhang, Yuanwei; Wu, Shuang; Zhao, Jianzhang; Han, Gang

2016-11-09

Tissue penetration depth is a major challenge in practical photodynamic therapy (PDT). A biocompatible and highly effective near infrared (NIR)-light-absorbing carbazole-substituted BODIPY (Car-BDP) molecule is reported as a class of imaging-guidable deep-tissue activatable photosensitizers for PDT. Car-BDP possesses an intense, broad NIR absorption band (600-800 nm) with a remarkably high singlet oxygen quantum yield (Φ Δ = 67%). After being encapsulated with biodegradable PLA-PEG-FA polymers, Car-BDP can form uniform and small organic nanoparticles that are water-soluble and tumor-targetable. Rather than using laser light, such nanoparticles offer an unprecedented deep-tissue, tumor targeting photodynamic therapeutic effect by using an exceptionally low-power-density and cost-effective lamp light (12 mW cm -2 ). In addition, these nanoparticles can be simultaneously traced in vivo due to their excellent NIR fluorescence. This study signals a major step forward in photodynamic therapy by developing a new class of NIR-absorbing biocompatible organic nanoparticles for effective targeting and treatment of deep-tissue tumors. This work also provides a potential new platform for precise tumor-targeting theranostics and novel opportunities for future affordable clinical cancer treatment.

A computational framework to detect normal and tuberculosis infected lung from H and E-stained whole slide images

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Beamer, Gillian; Gurcan, Metin N.

2017-03-01

Accurate detection and quantification of normal lung tissue in the context of Mycobacterium tuberculosis infection is of interest from a biological perspective. The automatic detection and quantification of normal lung will allow the biologists to focus more intensely on regions of interest within normal and infected tissues. We present a computational framework to extract individual tissue sections from whole slide images having multiple tissue sections. It automatically detects the background, red blood cells and handwritten digits to bring efficiency as well as accuracy in quantification of tissue sections. For efficiency, we model our framework with logical and morphological operations as they can be performed in linear time. We further divide these individual tissue sections into normal and infected areas using deep neural network. The computational framework was trained on 60 whole slide images. The proposed computational framework resulted in an overall accuracy of 99.2% when extracting individual tissue sections from 120 whole slide images in the test dataset. The framework resulted in a relatively higher accuracy (99.7%) while classifying individual lung sections into normal and infected areas. Our preliminary findings suggest that the proposed framework has good agreement with biologists on how define normal and infected lung areas.

Brain Slice Staining and Preparation for Three-Dimensional Super-Resolution Microscopy

PubMed Central

German, Christopher L.; Gudheti, Manasa V.; Fleckenstein, Annette E.; Jorgensen, Erik M.

2018-01-01

Localization microscopy techniques – such as photoactivation localization microscopy (PALM), fluorescent PALM (FPALM), ground state depletion (GSD), and stochastic optical reconstruction microscopy (STORM) – provide the highest precision for single molecule localization currently available. However, localization microscopy has been largely limited to cell cultures due to the difficulties that arise in imaging thicker tissue sections. Sample fixation and antibody staining, background fluorescence, fluorophore photoinstability, light scattering in thick sections, and sample movement create significant challenges for imaging intact tissue. We have developed a sample preparation and image acquisition protocol to address these challenges in rat brain slices. The sample preparation combined multiple fixation steps, saponin permeabilization, and tissue clarification. Together, these preserve intracellular structures, promote antibody penetration, reduce background fluorescence and light scattering, and allow acquisition of images deep in a 30 μm thick slice. Image acquisition challenges were resolved by overlaying samples with a permeable agarose pad and custom-built stainless steel imaging adapter, and sealing the imaging chamber. This approach kept slices flat, immobile, bathed in imaging buffer, and prevented buffer oxidation during imaging. Using this protocol, we consistently obtained single molecule localizations of synaptic vesicle and active zone proteins in three-dimensions within individual synaptic terminals of the striatum in rat brain slices. These techniques may be easily adapted to the preparation and imaging of other tissues, substantially broadening the application of super-resolution imaging. PMID:28924666

MRI-induced heating of deep brain stimulation leads

NASA Astrophysics Data System (ADS)

Mohsin, Syed A.; Sheikh, Noor M.; Saeed, Usman

2008-10-01

The radiofrequency (RF) field used in magnetic resonance imaging is scattered by medical implants. The scattered field of a deep brain stimulation lead can be very intense near the electrodes stimulating the brain. The effect is more pronounced if the lead behaves as a resonant antenna. In this paper, we examine the resonant length effect. We also use the finite element method to compute the near field for (i) the lead immersed in inhomogeneous tissue (fat, muscle, and brain tissues) and (ii) the lead connected to an implantable pulse generator. Electric field, specific absorption rate and induced temperature rise distributions have been obtained in the brain tissue surrounding the electrodes. The worst-case scenario has been evaluated by neglecting the effect of blood perfusion. The computed values are in good agreement with in vitro measurements made in the laboratory.

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.

PubMed

Islam, Jyoti; Zhang, Yanqing

2018-05-31

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research. Detection of Alzheimer's disease is exacting due to the similarity in Alzheimer's disease MRI data and standard healthy MRI data of older people. Recently, advanced deep learning techniques have successfully demonstrated human-level performance in numerous fields including medical image analysis. We propose a deep convolutional neural network for Alzheimer's disease diagnosis using brain MRI data analysis. While most of the existing approaches perform binary classification, our model can identify different stages of Alzheimer's disease and obtains superior performance for early-stage diagnosis. We conducted ample experiments to demonstrate that our proposed model outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue

PubMed Central

Peyster, Eliot G.; Frank, Renee; Margulies, Kenneth B.; Feldman, Michael D.

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome. PMID:29614076

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

PubMed

Nirschl, Jeffrey J; Janowczyk, Andrew; Peyster, Eliot G; Frank, Renee; Margulies, Kenneth B; Feldman, Michael D; Madabhushi, Anant

2018-01-01

Over 26 million people worldwide suffer from heart failure annually. When the cause of heart failure cannot be identified, endomyocardial biopsy (EMB) represents the gold-standard for the evaluation of disease. However, manual EMB interpretation has high inter-rater variability. Deep convolutional neural networks (CNNs) have been successfully applied to detect cancer, diabetic retinopathy, and dermatologic lesions from images. In this study, we develop a CNN classifier to detect clinical heart failure from H&E stained whole-slide images from a total of 209 patients, 104 patients were used for training and the remaining 105 patients for independent testing. The CNN was able to identify patients with heart failure or severe pathology with a 99% sensitivity and 94% specificity on the test set, outperforming conventional feature-engineering approaches. Importantly, the CNN outperformed two expert pathologists by nearly 20%. Our results suggest that deep learning analytics of EMB can be used to predict cardiac outcome.

Multiplexed aberration measurement for deep tissue imaging in vivo

PubMed Central

Wang, Chen; Liu, Rui; Milkie, Daniel E.; Sun, Wenzhi; Tan, Zhongchao; Kerlin, Aaron; Chen, Tsai-Wen; Kim, Douglas S.; Ji, Na

2014-01-01

We describe a multiplexed aberration measurement method that modulates the intensity or phase of light rays at multiple pupil segments in parallel to determine their phase gradients. Applicable to fluorescent-protein-labeled structures of arbitrary complexity, it allows us to obtain diffraction-limited resolution in various samples in vivo. For the strongly scattering mouse brain, a single aberration correction improves structural and functional imaging of fine neuronal processes over a large imaging volume. PMID:25128976

In vivo three-photon imaging of deep cerebellum

NASA Astrophysics Data System (ADS)

Wang, Mengran; Wang, Tianyu; Wu, Chunyan; Li, Bo; Ouzounov, Dimitre G.; Sinefeld, David; Guru, Akash; Nam, Hyung-Song; Capecchi, Mario R.; Warden, Melissa R.; Xu, Chris

2018-02-01

We demonstrate three-photon microscopy (3PM) of mouse cerebellum at 1 mm depth by imaging both blood vessels and neurons. We compared 3PM and 2PM in the mouse cerebellum for imaging green (using excitation sources at 1300 nm and 920 nm, respectively) and red fluorescence (using excitation sources at 1680 nm and 1064 nm, respectively). 3PM enabled deeper imaging than 2PM because the use of longer excitation wavelength reduces the scattering in biological tissue and the higher order nonlinear excitation provides better 3D localization. To illustrate these two advantages quantitatively, we measured the signal decay as well as the signal-to-background ratio (SBR) as a function of depth. We performed 2-photon imaging from the brain surface all the way down to the area where the SBR reaches 1, while at the same depth, 3PM still has SBR above 30. The segmented decay curve shows that the mouse cerebellum has different effective attenuation lengths at different depths, indicating heterogeneous tissue property for this brain region. We compared the third harmonic generation (THG) signal, which is used to visualize myelinated fibers, with the decay curve. We found that the regions with shorter effective attenuation lengths correspond to the regions with more fibers. Our results indicate that the widespread, non-uniformly distributed myelinated fibers adds heterogeneity to mouse cerebellum, which poses additional challenges in deep imaging of this brain region.

Optical coherence tomography of the prostate nerves

NASA Astrophysics Data System (ADS)

Chitchian, Shahab

Preservation of the cavernous nerves during prostate cancer surgery is critical in preserving a man's ability to have spontaneous erections following surgery. These microscopic nerves course along the surface of the prostate within a few millimeters of the prostate capsule, and they vary in size and location from one patient to another, making preservation of the nerves difficult during dissection and removal of a cancerous prostate gland. These observations may explain in part the wide variability in reported sexual potency rates (9--86%) following prostate cancer surgery. Any technology capable of providing improved identification, imaging, and visualization of the cavernous nerves during prostate cancer surgery would be of great assistance in improving sexual function after surgery, and result in direct patient benefit. Optical coherence tomography (OCT) is a noninvasive optical imaging technique capable of performing high-resolution cross-sectional in vivo and in situ imaging of microstructures in biological tissues. OCT imaging of the cavernous nerves in the rat and human prostate has recently been demonstrated. However, improvements in the OCT system and the quality of the images for identification of the cavernous nerves is necessary before clinical use. The following chapters describe complementary approaches to improving identification and imaging of the cavernous nerves during OCT of the prostate gland. After the introduction to OCT imaging of the prostate gland, the optimal wavelength for deep imaging of the prostate is studied in Chapter 2. An oblique-incidence single point measurement technique using a normal-detector scanning system was implemented to determine the absorption and reduced scattering coefficients, mua and m's , of fresh canine prostate tissue, ex vivo, from the diffuse reflectance profile of near-IR light as a function of source-detector distance. The effective attenuation coefficient, mueff, and the Optical Penetration Depth (OPD) were then calculated for near-IR wavelengths of 1064 nm, 1307 nm, and 1555 nm. Chapters 3 and 4 describe locally adaptive denoising algorithms applied to reduce speckle noise in OCT images of the prostate taken by experimental and clinical systems, respectively. The dual-tree complex wavelet transform (CDWT) is a relatively recent enhancement to the discrete wavelet transform (DWT), with important additional properties: It is nearly shift invariant and directionally selective in two and higher dimensions. The CDWT algorithm was implemented for denoising of OCT images. In Chapter 5, 2-D OCT images of the rat prostate were segmented to differentiate the cavernous nerves from the prostate gland. To detect these nerves, three image features were employed: Gabor filter, Daubechies wavelet, and Laws filter. The Gabor feature was applied with different standard deviations in the x and y directions. In the Daubechies wavelet feature, an 8-tap Daubechies orthonormal wavelet was implemented, and the low pass sub-band was chosen as the filtered image. Finally, Laws feature extraction was applied to the images. The features were segmented using a nearest-neighbor classifier. Morphological post-processing was used to remove small voids. In Chapter 6, a new algorithm based on thresholding and first-order derivative class of differential edge detection was implemented to see deeper in the OCT images. One of the main limitations in OCT imaging of the prostate tissue is the inability to image deep into opaque tissues. Currently, OCT is limited to an image depth of approximately 1 min in opaque tissues. Theoretical comparisons of detection performance for Fourier domain (FD) and time domain (TD) OCT have been previously reported. In Chapter 7, we compare several image quality metrics including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and equivalent number of looks (ENL) for TD-OCT and FD-OCT images taken of the rat prostate, in vivo. The results show that TD-OCT has inferior CNR, but superior SNR compared to FD-OCT, and that TD-OCT is better for deep imaging of opaque tissues. Finally, Chapter 8 summarizes the study and future directions for OCT imaging of the prostate gland are discussed.

Transmural Ultrasound-based Visualization of Patterns of Action Potential Wave Propagation in Cardiac Tissue

PubMed Central

Luther, Stefan; Singh, Rupinder; Gilmour, Robert F.

2010-01-01

The pattern of action potential propagation during various tachyarrhythmias is strongly suspected to be composed of multiple re-entrant waves, but has never been imaged in detail deep within myocardial tissue. An understanding of the nature and dynamics of these waves is important in the development of appropriate electrical or pharmacological treatments for these pathological conditions. We propose a new imaging modality that uses ultrasound to visualize the patterns of propagation of these waves through the mechanical deformations they induce. The new method would have the distinct advantage of being able to visualize these waves deep within cardiac tissue. In this article, we describe one step that would be necessary in this imaging process—the conversion of these deformations into the action potential induced active stresses that produced them. We demonstrate that, because the active stress induced by an action potential is, to a good approximation, only nonzero along the local fiber direction, the problem in our case is actually overdetermined, allowing us to obtain a complete solution. Use of two- rather than three-dimensional displacement data, noise in these displacements, and/or errors in the measurements of the fiber orientations all produce substantial but acceptable errors in the solution. We conclude that the reconstruction of action potential-induced active stress from the deformation it causes appears possible, and that, therefore, the path is open to the development of the new imaging modality. PMID:20499183

Noncontact 3-D Speckle Contrast Diffuse Correlation Tomography of Tissue Blood Flow Distribution.

PubMed

Huang, Chong; Irwin, Daniel; Zhao, Mingjun; Shang, Yu; Agochukwu, Nneamaka; Wong, Lesley; Yu, Guoqiang

2017-10-01

Recent advancements in near-infrared diffuse correlation techniques and instrumentation have opened the path for versatile deep tissue microvasculature blood flow imaging systems. Despite this progress there remains a need for a completely noncontact, noninvasive device with high translatability from small/testing (animal) to large/target (human) subjects with trivial application on both. Accordingly, we discuss our newly developed setup which meets this demand, termed noncontact speckle contrast diffuse correlation tomography (nc_scDCT). The nc_scDCT provides fast, continuous, portable, noninvasive, and inexpensive acquisition of 3-D tomographic deep (up to 10 mm) tissue blood flow distributions with straightforward design and customization. The features presented include a finite-element-method implementation for incorporating complex tissue boundaries, fully noncontact hardware for avoiding tissue compression and interactions, rapid data collection with a diffuse speckle contrast method, reflectance-based design promoting experimental translation, extensibility to related techniques, and robust adjustable source and detector patterns and density for high resolution measurement with flexible regions of interest enabling unique application-specific setups. Validation is shown in the detection and characterization of both high and low contrasts in flow relative to the background using tissue phantoms with a pump-connected tube (high) and phantom spheres (low). Furthermore, in vivo validation of extracting spatiotemporal 3-D blood flow distributions and hyperemic response during forearm cuff occlusion is demonstrated. Finally, the success of instrument feasibility in clinical use is examined through the intraoperative imaging of mastectomy skin flap.

Whole-organ atlas imaged by label-free high-resolution photoacoustic microscopy assisted by a microtome

NASA Astrophysics Data System (ADS)

Wong, Terence T. W.; Zhang, Ruiying; Hsu, Hsun-Chia; Maslov, Konstantin I.; Shi, Junhui; Chen, Ruimin; Shung, K. Kirk; Zhou, Qifa; Wang, Lihong V.

2018-02-01

In biomedical imaging, all optical techniques face a fundamental trade-off between spatial resolution and tissue penetration. Therefore, obtaining an organelle-level resolution image of a whole organ has remained a challenging and yet appealing scientific pursuit. Over the past decade, optical microscopy assisted by mechanical sectioning or chemical clearing of tissue has been demonstrated as a powerful technique to overcome this dilemma, one of particular use in imaging the neural network. However, this type of techniques needs lengthy special preparation of the tissue specimen, which hinders broad application in life sciences. Here, we propose a new label-free three-dimensional imaging technique, named microtomy-assisted photoacoustic microscopy (mPAM), for potentially imaging all biomolecules with 100% endogenous natural staining in whole organs with high fidelity. We demonstrate the first label-free mPAM, using UV light for label-free histology-like imaging, in whole organs (e.g., mouse brains), most of them formalin-fixed and paraffin- or agarose-embedded for minimal morphological deformation. Furthermore, mPAM with dual wavelength illuminations is also employed to image a mouse brain slice, demonstrating the potential for imaging of multiple biomolecules without staining. With visible light illumination, mPAM also shows its deep tissue imaging capability, which enables less slicing and hence reduces sectioning artifacts. mPAM could potentially provide a new insight for understanding complex biological organs.

Analysis of the potential for non-invasive imaging of oxygenation at heart depth, using ultrasound optical tomography (UOT) or photo-acoustic tomography (PAT).

PubMed

Walther, Andreas; Rippe, Lars; Wang, Lihong V; Andersson-Engels, Stefan; Kröll, Stefan

2017-10-01

Despite the important medical implications, it is currently an open task to find optical non-invasive techniques that can image deep organs in humans. Addressing this, photo-acoustic tomography (PAT) has received a great deal of attention in the past decade, owing to favorable properties like high contrast and high spatial resolution. However, even with optimal components PAT cannot penetrate beyond a few centimeters, which still presents an important limitation of the technique. Here, we calculate the absorption contrast levels for PAT and for ultrasound optical tomography (UOT) and compare them to their relevant noise sources as a function of imaging depth. The results indicate that a new development in optical filters, based on rare-earth-ion crystals, can push the UOT technique significantly ahead of PAT. Such filters allow the contrast-to-noise ratio for UOT to be up to three orders of magnitude better than for PAT at depths of a few cm into the tissue. It also translates into a significant increase of the image depth of UOT compared to PAT, enabling deep organs to be imaged in humans in real time. Furthermore, such spectral holeburning filters are not sensitive to speckle decorrelation from the tissue and can operate at nearly any angle of incident light, allowing good light collection. We theoretically demonstrate the improved performance in the medically important case of non-invasive optical imaging of the oxygenation level of the frontal part of the human myocardial tissue. Our results indicate that further studies on UOT are of interest and that the technique may have large impact on future directions of biomedical optics.

Vibration amplitude sonoelastography lesion imaging using low-frequency audible vibration

NASA Astrophysics Data System (ADS)

Taylor, Lawrence; Parker, Kevin

2003-04-01

Sonoelastography or vibration amplitude imaging is an ultrasound imaging technique in which low-amplitude, low-frequency shear waves, less than 0.1-mm displacement and 1-kHz frequency, are propagated deep into tissue, while real time Doppler techniques are used to image the resulting vibration pattern. Finite-element studies and experiments on tissue-mimicking phantoms verify that a discrete hard inhomogeneity present within a larger region of soft tissue will cause a decrease in the vibration field at its location. This forms the basis for tumor detection using sonoelastography. Real time relative imaging of the vibration field is possible because a vibrating particle will phase modulate an ultrasound signal. The particle's amplitude is directly proportional to the spectral spread of the reflected Doppler echo. Real time estimation of the variance of the Doppler power spectrum at each pixel allows the vibration field to be imaged. Results are shown for phantom lesions, thermal lesions, and 3-D in vitro and 2-D in vivo prostate cancer. MRI and whole mount histology is used to validate the system accuracy.

A metadata-aware application for remote scoring and exchange of tissue microarray images

PubMed Central

2013-01-01

Background The use of tissue microarrays (TMA) and advances in digital scanning microscopy has enabled the collection of thousands of tissue images. There is a need for software tools to annotate, query and share this data amongst researchers in different physical locations. Results We have developed an open source web-based application for remote scoring of TMA images, which exploits the value of Microsoft Silverlight Deep Zoom to provide a intuitive interface for zooming and panning around digital images. We use and extend existing XML-based standards to ensure that the data collected can be archived and that our system is interoperable with other standards-compliant systems. Conclusion The application has been used for multi-centre scoring of TMA slides composed of tissues from several Phase III breast cancer trials and ten different studies participating in the International Breast Cancer Association Consortium (BCAC). The system has enabled researchers to simultaneously score large collections of TMA and export the standardised data to integrate with pathological and clinical outcome data, thereby facilitating biomarker discovery. PMID:23635078

NaGdF4:Nd3+/Yb3+ Nanoparticles as Multimodal Imaging Agents

NASA Astrophysics Data System (ADS)

Pedraza, Francisco; Rightsell, Chris; Kumar, Ga; Giuliani, Jason; Monton, Car; Sardar, Dhiraj

Medical imaging is a fundamental tool used for the diagnosis of numerous ailments. Each imaging modality has unique advantages; however, they possess intrinsic limitations. Some of which include low spatial resolution, sensitivity, penetration depth, and radiation damage. To circumvent this problem, the combination of imaging modalities, or multimodal imaging, has been proposed, such as Near Infrared Fluorescence imaging (NIRF) and Magnetic Resonance Imaging (MRI). Combining individual advantages, specificity and selectivity of NIRF with the deep penetration and high spatial resolution of MRI, it is possible to circumvent their shortcomings for a more robust imaging technique. In addition, both imaging modalities are very safe and minimally invasive. Fluorescent nanoparticles, such as NaGdF4:Nd3 +/Yb3 +, are excellent candidates for NIRF/MRI multimodal imaging. The dopants, Nd and Yb, absorb and emit within the biological window; where near infrared light is less attenuated by soft tissue. This results in less tissue damage and deeper tissue penetration making it a viable candidate in biological imaging. In addition, the inclusion of Gd results in paramagnetic properties, allowing their use as contrast agents in multimodal imaging. The work presented will include crystallographic results, as well as full optical and magnetic characterization to determine the nanoparticle's viability in multimodal imaging.

Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses

NASA Astrophysics Data System (ADS)

Kooi, Thijs; Karssemeijer, Nico

2017-03-01

When humans identify objects in images, context is an important cue; a cheetah is more likely to be a domestic cat when a television set is recognised in the background. Similar principles apply to the analysis of medical images. The detection of diseases that manifest unilaterally in symmetrical organs or organ pairs can in part be facilitated by a search for symmetrical discrepancies in or between the organs in question. During a mammographic exam, images are recorded of each breast and absence of a certain structure around the same location in the contralateral image will render the area under scrutiny more suspicious and conversely, the presence of similar tissue less so. In this paper, we present a fusion scheme for a deep Convolutional Neural Network (CNN) architecture with the goal to optimally capture such asymmetries. The method is applied to the domain of mammography CAD, but can be relevant to other medical image analysis tasks where symmetry is important such as lung, prostate or brain images.

Toward Rechargeable Persistent Luminescence for the First and Third Biological Windows via Persistent Energy Transfer and Electron Trap Redistribution.

PubMed

Xu, Jian; Murata, Daisuke; Ueda, Jumpei; Viana, Bruno; Tanabe, Setsuhisa

2018-05-07

Persistent luminescence (PersL) imaging without real-time external excitation has been regarded as the next generation of autofluorescence-free optical imaging technology. However, to achieve improved imaging resolution and deep tissue penetration, developing new near-infrared (NIR) persistent phosphors with intense and long duration PersL over 1000 nm is still a challenging but urgent task in this field. Herein, making use of the persistent energy transfer process from Cr 3+ to Er 3+ , we report a novel garnet persistent phosphor of Y 3 Al 2 Ga 3 O 12 codoped with Er 3+ and Cr 3+ (YAG G:Er-Cr), which shows intense Cr 3+ PersL (∼690 nm) in the deep red region matching well with the first biological window (NIR-I, 650-950 nm) and Er 3+ PersL (∼1532 nm) in the NIR region matching well with the third biological window (NIR-III, 1500-1800 nm). The optical imaging through raw-pork tissues (thickness of 1 cm) suggests that the emission band of Er 3+ can achieve higher spatial resolution and more accurate signal location than that of Cr 3+ due to the reduced light scattering at longer wavelengths. Furthermore, by utilizing two independent electron traps with two different trap depths in YAG G:Er-Cr, the Cr 3+ /Er 3+ PersL can even be recharged in situ by photostimulation with 660 nm LED thanks to the redistribution of trapped electrons from the deep trap to the shallow one. Our results serve as a guide in developing promising NIR (>1000 nm) persistent phosphors for long-term optical imaging.

First in vivo magnetic particle imaging of lung perfusion in rats

NASA Astrophysics Data System (ADS)

Zhou, Xinyi Y.; Jeffris, Kenneth E.; Yu, Elaine Y.; Zheng, Bo; Goodwill, Patrick W.; Nahid, Payam; Conolly, Steven M.

2017-05-01

Pulmonary embolism (PE), along with the closely related condition of deep vein thrombosis, affect an estimated 600 000 patients in the US per year. Untreated, PE carries a mortality rate of 30%. Because many patients experience mild or non-specific symptoms, imaging studies are necessary for definitive diagnosis of PE. Iodinated CT pulmonary angiography is recommended for most patients, while nuclear medicine-based ventilation/perfusion (V/Q) scans are reserved for patients in whom the use of iodine is contraindicated. Magnetic particle imaging (MPI) is an emerging tracer imaging modality with high image contrast (no tissue background signal) and sensitivity to superparamagnetic iron oxide (SPIO) tracer. Importantly, unlike CT or nuclear medicine, MPI uses no ionizing radiation. Further, MPI is not derived from magnetic resonance imaging (MRI); MPI directly images SPIO tracers via their strong electronic magnetization, enabling deep imaging of anatomy including within the lungs, which is very challenging with MRI. Here, the first high-contrast in vivo MPI lung perfusion images of rats are shown using a novel lung perfusion agent, MAA-SPIOs.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries.

PubMed

Noor, Siti Salwa Md; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-11-16

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability.

Tractography patterns of subthalamic nucleus deep brain stimulation.

PubMed

Vanegas-Arroyave, Nora; Lauro, Peter M; Huang, Ling; Hallett, Mark; Horovitz, Silvina G; Zaghloul, Kareem A; Lungu, Codrin

2016-04-01

Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fluorescence Imaging In Vivo at Wavelengths beyond 1500 nm.

PubMed

Diao, Shuo; Blackburn, Jeffrey L; Hong, Guosong; Antaris, Alexander L; Chang, Junlei; Wu, Justin Z; Zhang, Bo; Cheng, Kai; Kuo, Calvin J; Dai, Hongjie

2015-12-01

Compared to imaging in the visible and near-infrared regions below 900 nm, imaging in the second near-infrared window (NIR-II, 1000-1700 nm) is a promising method for deep-tissue high-resolution optical imaging in vivo mainly owing to the reduced scattering of photons traversing through biological tissues. Herein, semiconducting single-walled carbon nanotubes with large diameters were used for in vivo fluorescence imaging in the long-wavelength NIR region (1500-1700 nm, NIR-IIb). With this imaging agent, 3-4 μm wide capillary blood vessels at a depth of about 3 mm could be resolved. Meanwhile, the blood-flow speeds in multiple individual vessels could be mapped simultaneously. Furthermore, NIR-IIb tumor imaging of a live mouse was explored. NIR-IIb imaging can be generalized to a wide range of fluorophores emitting at up to 1700 nm for high-performance in vivo optical imaging. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CT/FMT dual-model imaging of breast cancer based on peptide-lipid nanoparticles

NASA Astrophysics Data System (ADS)

Xu, Guoqiang; Lin, Qiaoya; Lian, Lichao; Qian, Yuan; Lu, Lisen; Zhang, Zhihong

2016-03-01

Breast cancer is one of the most harmful cancers in human. Its early diagnosis is expected to improve the patients' survival rate. X-ray computed tomography (CT) has been widely used in tumor detection for obtaining three-dimentional information. Fluorescence Molecular Tomography (FMT) imaging combined with near-infrared fluorescent dyes provides a powerful tool for the acquisition of molecular biodistribution information in deep tissues. Thus, the combination of CT and FMT imaging modalities allows us to better differentiate diseased tissues from normal tissues. Here we developed a tumor-targeting nanoparticle for dual-modality imaging based on a biocompatible HDL-mimicking peptide-phospholipid scaffold (HPPS) nanocarrier. By incorporation of CT contrast agents (iodinated oil) and far-infrared fluorescent dyes (DiR-BOA) into the hydrophobic core of HPPS, we obtained the FMT and CT signals simultaneously. Increased accumulation of the nanoparticles in the tumor lesions was achieved through the effect of the tumor-targeting peptide on the surface of nanoparticle. It resulted in excellent contrast between lesions and normal tissues. Together, the abilities to sensitively separate the lesions from adjacent normal tissues with the aid of a FMT/CT dual-model imaging approach make the targeting nanoparticles a useful tool for the diagnostics of breast cancer.

Click beetle luciferase mutant and near infrared naphthyl-luciferins for improved bioluminescence imaging.

PubMed

Hall, Mary P; Woodroofe, Carolyn C; Wood, Monika G; Que, Ivo; Van't Root, Moniek; Ridwan, Yanto; Shi, Ce; Kirkland, Thomas A; Encell, Lance P; Wood, Keith V; Löwik, Clemens; Mezzanotte, Laura

2018-01-09

The sensitivity of bioluminescence imaging in animals is primarily dependent on the amount of photons emitted by the luciferase enzyme at wavelengths greater than 620 nm where tissue penetration is high. This area of work has been dominated by firefly luciferase and its substrate, D-luciferin, due to the system's peak emission (~ 600 nm), high signal to noise ratio, and generally favorable biodistribution of D-luciferin in mice. Here we report on the development of a codon optimized mutant of click beetle red luciferase that produces substantially more light output than firefly luciferase when the two enzymes are compared in transplanted cells within the skin of black fur mice or in deep brain. The mutant enzyme utilizes two new naphthyl-luciferin substrates to produce near infrared emission (730 nm and 743 nm). The stable luminescence signal and near infrared emission enable unprecedented sensitivity and accuracy for performing deep tissue multispectral tomography in mice.

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain structures is critical. Copyright © 2017 Elsevier Inc. All rights reserved.

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PubMed

Kruse, Christian

2018-06-01

To review current practices and technologies within the scope of "Big Data" that can further our understanding of diabetes mellitus and osteoporosis from large volumes of data. "Big Data" techniques involving supervised machine learning, unsupervised machine learning, and deep learning image analysis are presented with examples of current literature. Supervised machine learning can allow us to better predict diabetes-induced osteoporosis and understand relative predictor importance of diabetes-affected bone tissue. Unsupervised machine learning can allow us to understand patterns in data between diabetic pathophysiology and altered bone metabolism. Image analysis using deep learning can allow us to be less dependent on surrogate predictors and use large volumes of images to classify diabetes-induced osteoporosis and predict future outcomes directly from images. "Big Data" techniques herald new possibilities to understand diabetes-induced osteoporosis and ascertain our current ability to classify, understand, and predict this condition.

Activatable Fluorescence Probe via Self-Immolative Intramolecular Cyclization for Histone Deacetylase Imaging in Live Cells and Tissues.

PubMed

Liu, Xianjun; Xiang, Meihao; Tong, Zongxuan; Luo, Fengyan; Chen, Wen; Liu, Feng; Wang, Fenglin; Yu, Ru-Qin; Jiang, Jian-Hui

2018-05-01

Histone deacetylases (HDACs) play essential roles in transcription regulation and are valuable theranostic targets. However, there are no activatable fluorescent probes for imaging of HDAC activity in live cells. Here, we develop for the first time a novel activatable two-photon fluorescence probe that enables in situ imaging of HDAC activity in living cells and tissues. The probe is designed by conjugating an acetyl-lysine mimic substrate to a masked aldehyde-containing fluorophore via a cyanoester linker. Upon deacetylation by HDAC, the probe undergoes a rapid self-immolative intramolecular cyclization reaction, producing a cyanohydrin intermediate that is spontaneously rapidly decomposed into the highly fluorescent aldehyde-containing two-photon fluorophore. The probe is shown to exhibit high sensitivity, high specificity, and fast response for HDAC detection in vitro. Imaging studies reveal that the probe is able to directly visualize and monitor HDAC activity in living cells. Moreover, the probe is demonstrated to have the capability of two-photon imaging of HDAC activity in deep tissue slices up to 130 μm. This activatable fluorescent probe affords a useful tool for evaluating HDAC activity and screening HDAC-targeting drugs in both live cell and tissue assays.

Microscopic medical image classification framework via deep learning and shearlet transform.

PubMed

Rezaeilouyeh, Hadi; Mollahosseini, Ali; Mahoor, Mohammad H

2016-10-01

Cancer is the second leading cause of death in US after cardiovascular disease. Image-based computer-aided diagnosis can assist physicians to efficiently diagnose cancers in early stages. Existing computer-aided algorithms use hand-crafted features such as wavelet coefficients, co-occurrence matrix features, and recently, histogram of shearlet coefficients for classification of cancerous tissues and cells in images. These hand-crafted features often lack generalizability since every cancerous tissue and cell has a specific texture, structure, and shape. An alternative approach is to use convolutional neural networks (CNNs) to learn the most appropriate feature abstractions directly from the data and handle the limitations of hand-crafted features. A framework for breast cancer detection and prostate Gleason grading using CNN trained on images along with the magnitude and phase of shearlet coefficients is presented. Particularly, we apply shearlet transform on images and extract the magnitude and phase of shearlet coefficients. Then we feed shearlet features along with the original images to our CNN consisting of multiple layers of convolution, max pooling, and fully connected layers. Our experiments show that using the magnitude and phase of shearlet coefficients as extra information to the network can improve the accuracy of detection and generalize better compared to the state-of-the-art methods that rely on hand-crafted features. This study expands the application of deep neural networks into the field of medical image analysis, which is a difficult domain considering the limited medical data available for such analysis.

Deep neural network-based bandwidth enhancement of photoacoustic data.

PubMed

Gutta, Sreedevi; Kadimesetty, Venkata Suryanarayana; Kalva, Sandeep Kumar; Pramanik, Manojit; Ganapathy, Sriram; Yalavarthy, Phaneendra K

2017-11-01

Photoacoustic (PA) signals collected at the boundary of tissue are always band-limited. A deep neural network was proposed to enhance the bandwidth (BW) of the detected PA signal, thereby improving the quantitative accuracy of the reconstructed PA images. A least square-based deconvolution method that utilizes the Tikhonov regularization framework was used for comparison with the proposed network. The proposed method was evaluated using both numerical and experimental data. The results indicate that the proposed method was capable of enhancing the BW of the detected PA signal, which inturn improves the contrast recovery and quality of reconstructed PA images without adding any significant computational burden. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Radiotherapy-induced Cherenkov luminescence imaging in a human body phantom.

PubMed

Ahmed, Syed Rakin; Jia, Jeremy Mengyu; Bruza, Petr; Vinogradov, Sergei; Jiang, Shudong; Gladstone, David J; Jarvis, Lesley A; Pogue, Brian W

2018-03-01

Radiation therapy produces Cherenkov optical emission in tissue, and this light can be utilized to activate molecular probes. The feasibility of sensing luminescence from a tissue molecular oxygen sensor from within a human body phantom was examined using the geometry of the axillary lymph node region. Detection of regions down to 30-mm deep was feasible with submillimeter spatial resolution with the total quantity of the phosphorescent sensor PtG4 near 1 nanomole. Radiation sheet scanning in an epi-illumination geometry provided optimal coverage, and maximum intensity projection images provided illustration of the concept. This work provides the preliminary information needed to attempt this type of imaging in vivo. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Taking a deep look: modern microscopy technologies to optimize the design and functionality of biocompatible scaffolds for tissue engineering in regenerative medicine

PubMed Central

Vielreicher, M.; Schürmann, S.; Detsch, R.; Schmidt, M. A.; Buttgereit, A.; Boccaccini, A.; Friedrich, O.

2013-01-01

This review focuses on modern nonlinear optical microscopy (NLOM) methods that are increasingly being used in the field of tissue engineering (TE) to image tissue non-invasively and without labelling in depths unreached by conventional microscopy techniques. With NLOM techniques, biomaterial matrices, cultured cells and their produced extracellular matrix may be visualized with high resolution. After introducing classical imaging methodologies such as µCT, MRI, optical coherence tomography, electron microscopy and conventional microscopy two-photon fluorescence (2-PF) and second harmonic generation (SHG) imaging are described in detail (principle, power, limitations) together with their most widely used TE applications. Besides our own cell encapsulation, cell printing and collagen scaffolding systems and their NLOM imaging the most current research articles will be reviewed. These cover imaging of autofluorescence and fluorescence-labelled tissue and biomaterial structures, SHG-based quantitative morphometry of collagen I and other proteins, imaging of vascularization and online monitoring techniques in TE. Finally, some insight is given into state-of-the-art three-photon-based imaging methods (e.g. coherent anti-Stokes Raman scattering, third harmonic generation). This review provides an overview of the powerful and constantly evolving field of multiphoton microscopy, which is a powerful and indispensable tool for the development of artificial tissues in regenerative medicine and which is likely to gain importance also as a means for general diagnostic medical imaging. PMID:23864499

Fluorescence diffuse tomography of small animals with DsRed2 fluorescent protein

NASA Astrophysics Data System (ADS)

Turchin, I. V.; Plehanov, V. I.; Orlova, A. G.; Kamenskiy, V. A.; Kleshnin, M. S.; Shirmanova, M. V.; Shakhova, N. M.; Balalaeva, I. V.; Savitskiy, A. P.

2006-05-01

Fluorescent compounds are used as markers to diagnose oncological diseases, to study molecular processes typical for carcinogenesis, and to investigate metastasis formation and tumor regress under the influence of therapeutics. Different types of tomography, such as continuous wave (CW), frequency-domain (FD), and time-domain (TD) tomography, allow fluorescence imaging of tumors located deep in human or animal tissue. In this work, preliminary results of the frequency domain fluorescent diffuse tomography (FDT) method in application to DsRed2 protein as a fluorescent agent are presented. For the first step of our experiments, we utilized low-frequency amplitude modulation (1 kHz) of second harmonic of Nd: YAG (532 nm). The transilluminative configuration was used in the setup. The results of post mortem experiments with capsules containing DsRed2 inserted inside the esophagus of a 3-day-old hairless rat to simulate tumor are shown. An algorithm of processing fluorescent images based on calculating the zero of maximum curvature has been applied to detect fluorescent inclusion boundaries in the image. This work demonstrates the potential capability of the FDT method for imaging deep fluorescent tumors in human tissue or animal models of human cancer. Improvement of the setup can be accomplished by using high-frequency modulation (using a 110-MHz acoustooptical modulator).

A Reconstruction Method for the Estimation of Temperatures of Multiple Sources Applied for Nanoparticle-Mediated Hyperthermia.

PubMed

Steinberg, Idan; Tamir, Gil; Gannot, Israel

2018-03-16

Solid malignant tumors are one of the leading causes of death worldwide. Many times complete removal is not possible and alternative methods such as focused hyperthermia are used. Precise control of the hyperthermia process is imperative for the successful application of such treatment. To that end, this research presents a fast method that enables the estimation of deep tissue heat distribution by capturing and processing the transient temperature at the boundary based on a bio-heat transfer model. The theoretical model is rigorously developed and thoroughly validated by a series of experiments. A 10-fold improvement is demonstrated in resolution and visibility on tissue mimicking phantoms. The inverse problem is demonstrated as well with a successful application of the model for imaging deep-tissue embedded heat sources. Thereby, allowing the physician then ability to dynamically evaluate the hyperthermia treatment efficiency in real time.

Hot topics in biomedical ultrasound: ultrasound therapy and its integration with ultrasonic imaging

NASA Astrophysics Data System (ADS)

Everbach, E. Carr

2005-09-01

Since the development of biomedical ultrasound imaging from sonar after WWII, there has been a clear divide between ultrasonic imaging and ultrasound therapy. While imaging techniques are designed to cause as little change as possible in the tissues through which ultrasound propagates, ultrasound therapy typically relies upon heating or acoustic cavitation to produce a desirable therapeutic effect. Concerns over the increasingly high acoustic outputs of diagnostic ultrasound scanners prompted the adoption of the Mechanical Index (MI) and Thermal Index (TI) in the early 1990s. Therapeutic applications of ultrasound, meanwhile, have evolved from deep tissue heating in sports medicine to include targeted drug delivery, tumor and plaque ablation, cauterization via high intensity focused ultrasound (HIFU), and accelerated dissolution of blood clots. The integration of ultrasonic imaging and therapy in one device is just beginning, but the promise of improved patient outcomes is balanced by regulatory and practical impediments.

Hyperspectral vibrational photoacoustic imaging of lipids and collagen

NASA Astrophysics Data System (ADS)

Wang, Pu; Wang, Ping; Wang, Han-Wei; Cheng, Ji-Xin

2012-02-01

The recently developed vibrational photoacoustic (VPA) microscopy allows bond-selective imaging of deep tissues by taking advantage of intrinsic contrast from harmonic vibration of C-H bonds. Due to the spectral similarity of molecules in the overtone vibration region, the compositional information is not available from VPA images acquired by single wavelength excitation. Here we demonstrate that lipids and collagen, two critical markers in many kinds of diseases, can be distinguished by hyperspectral VPA imaging. A phantom consisted of rat tail tendon (collagen) and fat tissue (lipids) was constructed. Wavelengths between 1650 and 1850 nm were scanned to excite the first overtone/combination vibration of C-H bond. B-scan hyperspectral VPA images, in which each pixel contains a spectrum, was analyzed by a Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) algorism to recover the spatial distribution of two chemical components in the phantom.

Image processing and 3D visualization in forensic pathologic examination

NASA Astrophysics Data System (ADS)

Oliver, William R.; Altschuler, Bruce R.

1996-02-01

The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing and three-dimensional visualization in the analysis of patterned injuries and tissue damage. While image processing will never replace classical understanding and interpretation of how injuries develop and evolve, it can be a useful tool in helping an observer notice features in an image, may help provide correlation of surface to deep tissue injury, and provide a mechanism for the development of a metric for analyzing how likely it may be that a given object may have caused a given wound. We are also exploring methods of acquiring three-dimensional data for such measurements, which is the subject of a second paper.

Optical coherence tomography image enhancement by using gold nanoparticles

NASA Astrophysics Data System (ADS)

Ponce-de-Leon, Y. R.; Lopez-Rios, J. A.; Pichardo-Molina, J. L.; Alcalá Ochoa, N.

2011-08-01

Optical Coherence Tomography (OCT) is an imaging technique to get cross-sectional images with resolutions of a few microns and deep penetration in tissue of some millimeters. For many years OCT has been applied to analyze different human tissues like eyes, skin, teeth, urinary bladders, gastrointestinal, respiratory or genitourinary tracts and recently breast cancer tissues have been studied. Many of these tissues are composed specially of lipids and collagen, proteins which cause multiple light scattering (MLS) reducing significantly the optical depth and the contrast of OCT imaging. So, one of the big challenges of this technique is to acquire images with good contrast. Gold nanoparticles (NPs) exhibit interesting optical properties due to its plasmon resonance frequency. Optical absorbance is strong when gold NPs have dimension under 50 nm, but over this size optical scattering becomes dominant. In this work we show the preliminary results of the use of gold NPs as a contrast medium to enhance the OCT images quality. Our experimental results show which type of particles (morphology and size) present the best enhancement in the region of 1325 nm which corresponds to the central wavelength source excitation. All our experiments were carried out with a commercial OCT (thorlabs) system and our NPs were tested in water and gel phantoms.

Flexible Integration of Both High Imaging Resolution and High Power Arrays for Ultrasound-Induced Thermal Strain Imaging (US-TSI)

PubMed Central

Stephens, Douglas N.; Mahmoud, Ahmed M.; Ding, Xuan; Lucero, Steven; Dutta, Debaditya; Yu, Francois T.H.; Chen, Xucai

2013-01-01

Ultrasound-induced thermal strain imaging (US-TSI) for carotid artery plaque detection requires both high imaging resolution (<100 μm) and sufficient US induced heating to elevate the tissue temperature (~1-3°C within 1-3 cardiac cycles) in order to produce a noticeable change in sound speed in the targeted tissues. Since the optimization of both imaging and heating in a monolithic array design is particularly expensive and inflexible, a new integrated approach is presented that utilizes independent ultrasound arrays to meet the requirements for this particular application. This work demonstrates a new approach in dual-array construction. A 3D printed manifold was built to support both a high resolution 20 MHz commercial imaging array and 6 custom heating elements operating in the 3.5-4 MHz range. For the application of US-TSI on carotid plaque characterization, the tissue target site is 20 to 30 mm deep, with a typical target volume of 2 mm (elevation) × 8 mm (azimuthal) × 5 mm (depth). The custom heating array performance was fully characterized for two design variants (flat and spherical apertures), and can easily deliver 30 W of total acoustic power to produce intensities greater than 15 W/cm2 in tissue target region. PMID:24297029

Correlative Imaging of Fluorescent Proteins in Resin-Embedded Plant Material1

PubMed Central

Bell, Karen; Mitchell, Steve; Paultre, Danae; Posch, Markus; Oparka, Karl

2013-01-01

Fluorescent proteins (FPs) were developed for live-cell imaging and have revolutionized cell biology. However, not all plant tissues are accessible to live imaging using confocal microscopy, necessitating alternative approaches for protein localization. An example is the phloem, a tissue embedded deep within plant organs and sensitive to damage. To facilitate accurate localization of FPs within recalcitrant tissues, we developed a simple method for retaining FPs after resin embedding. This method is based on low-temperature fixation and dehydration, followed by embedding in London Resin White, and avoids the need for cryosections. We show that a palette of FPs can be localized in plant tissues while retaining good structural cell preservation, and that the polymerized block face can be counterstained with cell wall probes. Using this method we have been able to image green fluorescent protein-labeled plasmodesmata to a depth of more than 40 μm beneath the resin surface. Using correlative light and electron microscopy of the phloem, we were able to locate the same FP-labeled sieve elements in semithin and ultrathin sections. Sections were amenable to antibody labeling, and allowed a combination of confocal and superresolution imaging (three-dimensional-structured illumination microscopy) on the same cells. These correlative imaging methods should find several uses in plant cell biology. PMID:23457228

High-frame-rate imaging of biological samples with optoacoustic micro-tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; López-Schier, Hernán.; Razansky, Daniel

2018-02-01

Optical microscopy remains a major workhorse in biological discovery despite the fact that light scattering limits its applicability to depths of ˜ 1 mm in scattering tissues. Optoacoustic imaging has been shown to overcome this barrier by resolving optical absorption with microscopic resolution in significantly deeper regions. Yet, the time domain is paramount for the observation of biological dynamics in living systems that exhibit fast motion. Commonly, acquisition of microscopy data involves raster scanning across the imaged volume, which significantly limits temporal resolution in 3D. To overcome these limitations, we have devised a fast optoacoustic micro-tomography (OMT) approach based on simultaneous acquisition of 3D image data with a high-density hemispherical ultrasound array having effective detection bandwidth around 25 MHz. We performed experiments by imaging tissue-mimicking phantoms and zebrafish larvae, demonstrating that OMT can provide nearly cellular resolution and imaging speed of 100 volumetric frames per second. As opposed to other optical microscopy techniques, OMT is a hybrid method that resolves optical absorption contrast acoustically using unfocused light excitation. Thus, no penetration barriers are imposed by light scattering in deep tissues, suggesting it as a powerful approach for multi-scale functional and molecular imaging applications.

TH-AB-209-04: 3D Light Sheet Luminescence Imaging with Cherenkov Radiation

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

Bruza, P; Lin, H; Jarvis, L

Purpose: To recover a three-dimensional density distribution of luminescent molecular probes located several centimeters deep within a highly scattering tissue. Methods: We developed a novel sheet beam Cherenkov-excited luminescence scanned imaging (CELSI) methodology. The sample was irradiated by a horizontally oriented, vertically scanned 6 MV X-ray sheet beam (200mm × 5mm, 0.2mm vertical step) from a radiotherapy linear accelerator. The resulting Cherenkov light emission – and thus luminescent probe excitation – occurred exclusively along the irradiation plane due to a short diffusion path of secondary particles and Cherenkov photons. Cherenkov-excited luminescence was detected orthogonally to the sheet beam by gated,more » intensified charge coupled device camera. Analogously to light sheet microscopy, a series of luminescence images was taken for varied axial positions (depths) of the Cherenkov light sheet in sample. Knowledge of the excitation plane position allowed a 3D image stack deconvolution and depth-variant attenuation correction. The 3D image post-processing yielded a true spatial density distribution of luminescent molecules in highly scattering tissue. Results: We recovered a three-dimensional shape and position of 400 µL lesion-mimicking phantom tubes containing 25 µM solution of PtG4 molecular probe from 3 centimeter deep tissue-like media. The high sensitivity of CELSI also allowed resolving 100 micron capillaries of test solution. Functional information of partial oxygen pressure at the site of PtG4 molecular probe was recovered from luminescence lifetime CELSI. Finally, in-vivo sheet beam CELSI localized milimeter-sized PtG4-labelled tumor phantoms in multiple biological objects (hairless mice) from single scan. Conclusion: Presented sheet beam CELSI technique greatly extended the useful depth range of luminescence molecular imaging. More importantly, the light sheet microscopy approach was successfully adapted to CELSI, providing means to recover a completely attenuation-corrected 3D image of luminescent probe distribution. Gated CELSI acquisition yielded functional information of a spatially resolved oxygen concentration map of deep lying targets. This work was supported by NIH research grant R01CA109558 and R21EB017559, as well as by Pilot Grant Funds from the Norris Cotton Cancer Center.« less

Deep residual networks for automatic segmentation of laparoscopic videos of the liver

NASA Astrophysics Data System (ADS)

Gibson, Eli; Robu, Maria R.; Thompson, Stephen; Edwards, P. Eddie; Schneider, Crispin; Gurusamy, Kurinchi; Davidson, Brian; Hawkes, David J.; Barratt, Dean C.; Clarkson, Matthew J.

2017-03-01

Motivation: For primary and metastatic liver cancer patients undergoing liver resection, a laparoscopic approach can reduce recovery times and morbidity while offering equivalent curative results; however, only about 10% of tumours reside in anatomical locations that are currently accessible for laparoscopic resection. Augmenting laparoscopic video with registered vascular anatomical models from pre-procedure imaging could support using laparoscopy in a wider population. Segmentation of liver tissue on laparoscopic video supports the robust registration of anatomical liver models by filtering out false anatomical correspondences between pre-procedure and intra-procedure images. In this paper, we present a convolutional neural network (CNN) approach to liver segmentation in laparoscopic liver procedure videos. Method: We defined a CNN architecture comprising fully-convolutional deep residual networks with multi-resolution loss functions. The CNN was trained in a leave-one-patient-out cross-validation on 2050 video frames from 6 liver resections and 7 laparoscopic staging procedures, and evaluated using the Dice score. Results: The CNN yielded segmentations with Dice scores >=0.95 for the majority of images; however, the inter-patient variability in median Dice score was substantial. Four failure modes were identified from low scoring segmentations: minimal visible liver tissue, inter-patient variability in liver appearance, automatic exposure correction, and pathological liver tissue that mimics non-liver tissue appearance. Conclusion: CNNs offer a feasible approach for accurately segmenting liver from other anatomy on laparoscopic video, but additional data or computational advances are necessary to address challenges due to the high inter-patient variability in liver appearance.

Dual-radiolabeled nanoparticle probes for depth-independent in vivo imaging of enzyme activation

NASA Astrophysics Data System (ADS)

Black, Kvar C. L.; Zhou, Mingzhou; Sarder, Pinaki; Kuchuk, Maryna; Al-Yasiri, Amal Y.; Gunsten, Sean P.; Liang, Kexian; Hennkens, Heather M.; Akers, Walter J.; Laforest, Richard; Brody, Steven L.; Cutler, Cathy S.; Achilefu, Samuel

2018-02-01

Quantitative and noninvasive measurement of protease activities has remained an imaging challenge in deep tissues such as the lungs. Here, we designed a dual-radiolabeled probe for reporting the activities of proteases such as matrix metalloproteinases (MMPs) with multispectral single photon emission computed tomography (SPECT) imaging. A gold nanoparticle (NP) was radiolabeled with 125I and 111In and functionalized with an MMP9-cleavable peptide to form a multispectral SPECT imaging contrast agent. In another design, incorporation of 199Au radionuclide into the metal crystal structure of gold NPs provided a superior and stable reference signal in lungs, and 111In was linked to the NP surface via a protease-cleavable substrate, which can serve as an enzyme activity reporter. This work reveals strategies to correlate protease activities with diverse pathologies in a tissue-depth independent manner.

Multifunctional gold nanorods for image-guided surgery and photothermal therapy

NASA Astrophysics Data System (ADS)

Barriere, Clement; Qi, Ji; Garcia-Allende, P. Beatriz; Newton, Richard; Elson, Daniel S.

2012-03-01

Nanoparticles are viewed as a promising tool for numerous medical applications, for instance imaging and photothermal therapy (PTT) has been proposed using gold nanorods. We are developing multi-functional gold nanorods (m-GNRs) which have potential for image guided endoscopic surgery of tumour tissue with a modified laparoscope system. A new synthesis method potentially allows any useful acid functionalised molecules to be bonded at the surface. We have created fluorescent m-GNRs which can be used for therapy as they absorb light in the infrared, which may penetrate deep into the tissue and produce localised heating. We have performed a tissue based experiment to demonstrate the feasibility of fluorescence guided PTT using m- GNRs. Ex vivo tests were performed using sheep heart. This measurement, correlated with the fluorescence signal of the m-GNRs measured by the laparoscope allows the clear discrimination of the artery system containing m-GNRs. A laser diode was used to heat the m-GNRs and a thermal camera was able to record the heat distribution. These images were compared to the fluorescence images for validation.

The Quality of In Vivo Upconversion Fluorescence Signals Inside Different Anatomic Structures.

PubMed

Wang, Lijiang; Draz, Mohamed Shehata; Wang, Wei; Liao, Guodong; Xu, Yuhong

2015-02-01

Fluorescence imaging is a broadly interesting and rapidly growing strategy for non-invasive clinical applications. However, because of interference from light scattering, absorbance, and tissue autofluorescence, the images can exhibit low sensitivity and poor quality. Upconversion fluorescence imaging, which is based on the use of near-infrared (NIR) light for excitation, has recently been introduced as an improved approach to minimize the effects of light scattering and tissue autofluorescence. This strategy is promising for ultrasensitive and deep tissue imaging applications. However, the emitted upconversion fluorescence signals are primarily in the visible range and are likely to be absorbed and scattered by tissues. Therefore, different anatomic structures could impose various effects on the quality of the images. In this study, we used upconversion-core/silica-shell nanoprobes to evaluate the quality of upconversion fluorescence at different anatomic locations in athymic nude mice. The nanoprobe contained an upconversion core, which was green (β-NaYF4:Yb3+/Ho3+) or red (β-NaYF4:Yb3+/Er3+), and a nonporous silica shell to allow for multicolor imaging. High-quality upconversion fluorescence signals were detected with signal-to-noise ratios of up to 170 at tissue depths of up to - 1.0 cm when a 980 nm laser excitation source and a bandpass emission filter were used. The presence of dense tissue structures along the imaging path reduced the signal intensity and imaging quality, and nanoprobes with longer-wavelength emission spectra were therefore preferable. This study offers a detailed analysis of the quality of upconversion signals in vivo inside different anatomic structures. Such information could be essential for the analysis of upconversion fluorescence images in any in vivo biodiagnostic and microbial tracking applications.

The molecular origin of a loading-induced black layer in the deep region of articular cartilage at the magic angle

PubMed Central

Wang, Nian; Kahn, David; Badar, Farid; Xia, Yang

2014-01-01

Purpose To investigate the molecular origin of an unusual low-intensity layer in the deep region of articular cartilage as seen in MRI when the tissue is imaged under compression and oriented at the magic angle. Materials and Methods Microscopic MRI (μMRI) T2 and T1ρ experiments were carried out for both native and degraded (treated with trypsin) 18 specimens. The glycosaminoglycan (GAG) concentrations in the specimens were quantified by both sodium ICP-OES and μMRI Gd(DTPA)2--contrast methods. The mechanical modulus of the specimens was also measured. Results Native tissue shows no load-induced layer, while the trypsin-degraded tissue shows clearly the low-intensity line at the deep part of tissue. The GAG reductions are confirmed by the sodium ICP-OES (from 81.7 ± 5.4 mg/ml to 9.2 ± 3.4 mg/ml), MRI GAG quantification (from 72.4 ± 6.7 mg/ml to 11.2 ± 2.9 mg/ml). The modulus reduction is confirmed by biomechanics (from 4.3 ± 0.7 MPa to 0.3 ± 0.1 MPa). Conclusion Both T2 and T1ρ profiles in native and degraded cartilage show strongly strain-, depth-, and angle-dependent using high resolution MRI. The GAG reduction is responsible for the visualization of a low-intensity layer in deep cartilage when it is loaded and orientated at 55°. PMID:24833266

Deep tissue massage: What are we talking about?

PubMed

Koren, Yogev; Kalichman, Leonid

2018-04-01

Massage is a common treatment in complementary and integrative medicine. Deep tissue massage, a form of therapeutic massage, has become more and more popular in recent years. Hence, the use of massage generally and deep tissue massage specifically, should be evaluated as any other modality of therapy to establish its efficacy and safety. To determine the definitions used for deep tissue massage in the scientific literature and to review the current scientific evidence for its efficacy and safety. Narrative review. There is no commonly accepted definition of deep tissue massage in the literature. The definition most frequently used is the intention of the therapist. We suggest separating the definitions of deep massage and deep tissue massage as follows: deep massage should be used to describe the intention of the therapist to treat deep tissue by using any form of massage and deep tissue massage should be used to describe a specific and independent method of massage therapy, utilizing the specific set of principles and techniques as defined by Riggs: "The understanding of the layers of the body, and the ability to work with tissue in these layers to relax, lengthen, and release holding patterns in the most effective and energy efficient way possible within the client's parameters of comfort". Heterogeneity of techniques and protocols used in published studies have made it difficult to draw any clear conclusions. Favorable outcomes may result from deep tissue massage in pain populations and patients with decreased range of motion. In addition, several rare serious adverse events were found related to deep tissue massage, probably as a result of the forceful application of massage therapy. Future research of deep tissue massage should be based on a common definition, classification system and the use of common comparators as controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

A super-resolution ultrasound method for brain vascular mapping

PubMed Central

O'Reilly, Meaghan A.; Hynynen, Kullervo

2013-01-01

Purpose: High-resolution vascular imaging has not been achieved in the brain due to limitations of current clinical imaging modalities. The authors present a method for transcranial ultrasound imaging of single micrometer-size bubbles within a tube phantom. Methods: Emissions from single bubbles within a tube phantom were mapped through an ex vivo human skull using a sparse hemispherical receiver array and a passive beamforming algorithm. Noninvasive phase and amplitude correction techniques were applied to compensate for the aberrating effects of the skull bone. The positions of the individual bubbles were estimated beyond the diffraction limit of ultrasound to produce a super-resolution image of the tube phantom, which was compared with microcomputed tomography (micro-CT). Results: The resulting super-resolution ultrasound image is comparable to results obtained via the micro-CT for small tissue specimen imaging. Conclusions: This method provides superior resolution to deep-tissue contrast ultrasound and has the potential to be extended to provide complete vascular network imaging in the brain. PMID:24320408

Autofluorescence-based diagnostic UV imaging of tissues and cells

NASA Astrophysics Data System (ADS)

Renkoski, Timothy E.

Cancer is the second leading cause of death in the United States, and its early diagnosis is critical to improving treatment options and patient outcomes. In autofluorescence (AF) imaging, light of controlled wavelengths is projected onto tissue, absorbed by specific molecules, and re-emitted at longer wavelengths. Images of re-emitted light are used together with spectral information to infer tissue functional information and diagnosis. This dissertation describes AF imaging studies of three different organs using data collected from fresh human surgical specimens. In the ovary study, illumination was at 365 nm, and images were captured at 8 emission wavelengths. Measurements from a multispectral imaging system and fiber optic probe were used to map tissue diagnosis at every image pixel. For the colon and pancreas studies, instrumentation was developed extending AF imaging capability to sub-300 nm excitation. Images excited in the deep UV revealed tryptophan and protein content which are believed to change with disease state. Several excitation wavelength bands from 280 nm to 440 nm were investigated. Microscopic AF images collected in the pancreas study included both cultured and primary cells. Several findings are reported. A method of transforming fiber optic probe spectra for direct comparison with imager spectra was devised. Normalization of AF data by green reflectance data was found useful in correcting hemoglobin absorption. Ratio images, both AF and reflectance, were formulated to highlight growths in the colon. Novel tryptophan AF images were found less useful for colon diagnostics than the new ratio techniques. Microscopic tryptophan AF images produce useful visualization of cellular protein content, but their diagnostic value requires further study.

A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head

PubMed Central

Mari, Jean-Martial; Aung, Tin; Cheng, Ching-Yu; Strouthidis, Nicholas G.; Girard, Michaël J. A.

2017-01-01

Purpose To digitally stain spectral-domain optical coherence tomography (OCT) images of the optic nerve head (ONH), and highlight either connective or neural tissues. Methods OCT volumes of the ONH were acquired from one eye of 10 healthy subjects. We processed all volumes with adaptive compensation to remove shadows and enhance deep tissue visibility. For each ONH, we identified the four most dissimilar pixel-intensity histograms, each of which was assumed to represent a tissue group. These four histograms formed a vector basis on which we ‘projected' each OCT volume in order to generate four digitally stained volumes P1 to P4. Digital staining was also verified using a digital phantom, and compared with k-means clustering for three and four clusters. Results Digital staining was able to isolate three regions of interest from the proposed phantom. For the ONH, the digitally stained images P1 highlighted mostly connective tissues, as demonstrated through an excellent contrast increase across the anterior lamina cribrosa boundary (3.6 ± 0.6 times). P2 highlighted the nerve fiber layer and the prelamina, P3 the remaining layers of the retina, and P4 the image background. Further, digital staining was able to separate ONH tissue layers that were not well separated by k-means clustering. Conclusion We have described an algorithm that can digitally stain connective and neural tissues in OCT images of the ONH. Translational Relevance Because connective and neural tissues are considerably altered in glaucoma, digital staining of the ONH tissues may be of interest in the clinical management of this pathology. PMID:28174676

Mesoporous composite nanoparticles for dual-modality ultrasound/magnetic resonance imaging and synergistic chemo-/thermotherapy against deep tumors.

PubMed

Zhang, Nan; Wang, Ronghui; Hao, Junnian; Yang, Yang; Zou, Hongmi; Wang, Zhigang

2017-01-01

High-intensity focused ultrasound (HIFU) is a promising and noninvasive treatment for solid tumors, which has been explored for potential clinical applications. However, the clinical applications of HIFU for large and deep tumors such as hepatocellular carcinoma (HCC) are severely limited by unsatisfactory imaging guidance, long therapeutic times, and damage to normal tissue around the tumor due to the high power applied. In this study, we developed doxorubicin/perfluorohexane-encapsulated hollow mesoporous Prussian blue nanoparticles (HMPBs-DOX/PFH) as theranostic agents, which can effectively guide HIFU therapy and enhance its therapeutic effects in combination with chemotherapy, by decreasing the cavitation threshold. We investigated the effects of this agent on ultrasound and magnetic resonance imaging in vitro and in vivo. In addition, we showed a highly efficient HIFU therapeutic effect against HCC tumors, as well as controlled drug release, owing to the phase-transitional performance of the PFH. We therefore conclude that HMPB-DOX/PFH is a safe and efficient nanoplatform, which holds significant promise for cancer theranostics against deep tumors in clinical settings.

Mesoporous composite nanoparticles for dual-modality ultrasound/magnetic resonance imaging and synergistic chemo-/thermotherapy against deep tumors

PubMed Central

Zhang, Nan; Wang, Ronghui; Hao, Junnian; Yang, Yang; Zou, Hongmi; Wang, Zhigang

2017-01-01

High-intensity focused ultrasound (HIFU) is a promising and noninvasive treatment for solid tumors, which has been explored for potential clinical applications. However, the clinical applications of HIFU for large and deep tumors such as hepatocellular carcinoma (HCC) are severely limited by unsatisfactory imaging guidance, long therapeutic times, and damage to normal tissue around the tumor due to the high power applied. In this study, we developed doxorubicin/perfluorohexane-encapsulated hollow mesoporous Prussian blue nanoparticles (HMPBs-DOX/PFH) as theranostic agents, which can effectively guide HIFU therapy and enhance its therapeutic effects in combination with chemotherapy, by decreasing the cavitation threshold. We investigated the effects of this agent on ultrasound and magnetic resonance imaging in vitro and in vivo. In addition, we showed a highly efficient HIFU therapeutic effect against HCC tumors, as well as controlled drug release, owing to the phase-transitional performance of the PFH. We therefore conclude that HMPB-DOX/PFH is a safe and efficient nanoplatform, which holds significant promise for cancer theranostics against deep tumors in clinical settings. PMID:29042775

High efficiency upconversion nanophosphors for high-contrast bioimaging

NASA Astrophysics Data System (ADS)

Alkahtani, Masfer H.; Alghannam, Fahad S.; Sanchez, Carlos; Gomes, Carmen L.; Liang, Hong; Hemmer, Philip R.

2016-12-01

Upconversion nanoparticles (UCNPs) are of interest because they allow suppression of tissue autofluorescence and are therefore visible deep inside biological tissue. Compared to upconversion dyes, UCNPs have a lower pump intensity threshold, better photostability, and less toxicity. Recently, YVO4: Er+3, Yb+3 nanoparticles were shown to exhibit strong up-conversion luminescence with a relatively low 10 kW cm-2 excitation intensity even in water, which makes them excellent bio-imaging candidates. Herein, we investigate their use as internal probes in insects by injecting YVO4 : Er+3, Yb+3 nanoparticles into fire ants as a biological model, and obtain 2D optical images with 980 nm illumination. High-contrast images with high signal-to-noise ratio are observed by detecting the up-conversion fluorescence as the excitation laser is scanned.

Well-circumscribed deep-seated lipomas of the upper extremity. A report of 13 cases.

PubMed

Elbardouni, A; Kharmaz, M; Salah Berrada, M; Mahfoud, M; Elyaacoubi, M

2011-04-01

The purpose of this study is to determine if giant size is of bad prognosis in deep lipomas of the upper extremity. We report a retrospective study of 13 patients with deep-seated lipomas of the upper extremity treated during the period from April 1997 to April 2008. We evaluated the clinical and radiological characteristics, treatment and evolution profile of these patients. There were 10 women and three men, with an average age of 53 years (range 30-79 years). Seven of these lipomas were in the arm, one in the shoulder, and five in the forearm. Six lipomas were intramuscular, six intermuscular (three of them being attached to bone and labelled parosteal lipoma) and one epivaginal lipoma of the flexor tendon sheath. All patients presented a progressive slow-growing mass that was associated with radial paralysis in one case and carpal tunnel syndrome in one case. Plain radiographs showed a radiolucent soft-tissue image in all cases and an associated osteochondroma in one parosteal lipoma. Computer tomography (CT) or magnetic resonance imaging (MRI) suggested the lipomatous nature and benign characteristics of these deep lipomas that were giant in all cases (mean size: 7 cm). Lipoma marginal excision was performed and histopathological examination demonstrated features consistent with a benign lipoma. There was good function and no clinical recurrence was observed after a mean follow-up of three years. Giant deep-seated lipomas of the upper extremity are uncommon and can be intermuscular or intramuscular. A painless soft-tissue mass is the most frequent chief complaint. MRI with fat suppression suggests the diagnosis and studies the extension of deep lipoma. Marginal excision is the treatment of choice and histopathology eliminates diagnosis of well-differentiated liposarcoma. Appropriate evaluation of deep lipoma is to rule out malignancy by systematically performing MRI and biopsy. In contrast to deep-seated lipomas of the lower extremity or the retroperitoneal space, the prognosis of deep-seated lipomas of the upper extremity is good irrelevant of their size. Recurrence and the degeneration are very rare. Level 4. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Deep tissue imaging of microfracture and non-displaced fracture of bone using the second and third near-infrared therapeutic windows

NASA Astrophysics Data System (ADS)

Sordillo, Laura A.; Pu, Yang; Sordillo, P. P.; Budansky, Yury; Alfano, Robert R.

2014-03-01

Near-infrared (NIR) light in the wavelengths of 700 nm to 2,000 nm has three NIR optical, or therapeutic, windows, which allow for deeper depth penetration in scattering tissue media. Microfractures secondary to repetitive stress, particularly in the lower extremities, are an important problem for military recruits and athletes. They also frequently occur in the elderly, or in patients taking bisphosphonates or denosumab. Microfractures can be early predictors of a major bone fracture. Using the second and third NIR therapeutic windows, we investigated the results from images of chicken bone and human tibial bone with microfractures and non-displaced fractures with and without overlying tissues of various thicknesses. Images of bone with microfractures and non-displaced fractures with tissue show scattering photons in the third NIR window with wavelengths between 1,650 nm and 1,870 nm are diminished and absorption is increased slightly from and second NIR windows. Results from images of fractured bones show the attenuation length of light through tissue in the third optical window to be larger than in the second therapeutic window. Use of these windows may aid in the detection of bone microfractures, and thus reduce the incidence of major bone fracture in susceptible groups.

Fibre-optic nonlinear optical microscopy and endoscopy.

PubMed

Fu, L; Gu, M

2007-06-01

Nonlinear optical microscopy has been an indispensable laboratory tool of high-resolution imaging in thick tissue and live animals. Rapid developments of fibre-optic components in terms of growing functionality and decreasing size provide enormous opportunities for innovations in nonlinear optical microscopy. Fibre-based nonlinear optical endoscopy is the sole instrumentation to permit the cellular imaging within hollow tissue tracts or solid organs that are inaccessible to a conventional optical microscope. This article reviews the current development of fibre-optic nonlinear optical microscopy and endoscopy, which includes crucial technologies for miniaturized nonlinear optical microscopy and their embodiments of endoscopic systems. A particular attention is given to several classes of photonic crystal fibres that have been applied to nonlinear optical microscopy due to their unique properties for ultrashort pulse delivery and signal collection. Furthermore, fibre-optic nonlinear optical imaging systems can be classified into portable microscopes suitable for imaging behaving animals, rigid endoscopes that allow for deep tissue imaging with minimally invasive manners, and flexible endoscopes enabling imaging of internal organs. Fibre-optic nonlinear optical endoscopy is coming of age and a paradigm shift leading to optical microscope tools for early cancer detection and minimally invasive surgery.

Calf tissue liquid stowage and muscular and deep vein distension in orthostatic tests after a 90-day head down bed rest

NASA Astrophysics Data System (ADS)

Arbeille, P.A.; Kerbeci, P.; Audebert, P.; Capri, A.; Pascaud, L.

2005-08-01

The objectives were to assess the contribution of (1) the calf veins distension and(2) the tissue liquid stowage during standtest, to orthostatic intolerance "OI" after a head down bed rest (HDBR) of 90days. Method: The population consisted of a control group (Co-gr, n=9) and an exercise Fly wheel counter-measure group (CM-gr, n=9). Calf vein cross sectional area (CSA) and surrounding tissue liquid content (tissue image darkness) were assessed by echography during pre and post HDBR stand-tests. Results: From supine to standing (post HDBR), the Tibial and muscular vein CSA increased significantly in non tolerant subjects whereas in tolerant subjects the vein CSA did not change. Post HDBR the tissue image darkness (proportional to tissue liquid content) increased more from supine to standing in non tolerant than in tolerant subjects. No significant difference were found between Co and exercise CM groups. Conclusion: High calf vein CSA and tissue liquid content increase at post-HDBR stand-test were significantly correlated with occurrence of OI but not with CM.

Fourth near-infrared optical window for assessment of bone and other tissues

NASA Astrophysics Data System (ADS)

Sordillo, Diana C.; Sordillo, Laura A.; Sordillo, Peter P.; Alfano, Robert R.

2016-02-01

Recently, additional near-infrared (NIR) optical windows beyond the conventional first therapeutic window have been utilized for deep tissue imaging through scattering media. Biomedical applications using a second optical window (1100 to 1300 nm) and a third (1600 to 1870 nm) are emerging. A fourth window (2100 to 2300 nm) has been largely ignored due to high water absorption and a lack of high sensitivity imaging detectors and ultrafast laser sources. In this study, optical properties of bone in this fourth NIR optical window, were investigated. Results were compared to those seen at the first, second and third windows, and are consistent with our previous work on malignant and benign breast and prostate tissues. Bone and malignant tissues showed highest uptake in the third and fourth windows. As collagen is a major chromophore with prominent spectral peaks between 2100 and 2300 nm, it may be that the fourth optical window is particularly useful for studying tissues with a higher collagen content, such as bone or malignant tumors.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries

PubMed Central

Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-01-01

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability. PMID:29144388

Optical medical imaging: from glass to man

NASA Astrophysics Data System (ADS)

Bradley, Mark

2016-11-01

A formidable challenge in modern respiratory healthcare is the accurate and timely diagnosis of lung infection and inflammation. The EPSRC Interdisciplinary Research Collaboration (IRC) `Proteus' seeks to address this challenge by developing an optical fibre based healthcare technology platform that combines physiological sensing with multiplexed optical molecular imaging. This technology will enable in situ measurements deep in the human lung allowing the assessment of tissue function and characterization of the unique signatures of pulmonary disease and is illustrated here with our in-man application of Optical Imaging SmartProbes and our first device Versicolour.

Comparison of excitation wavelengths for in vivo deep imaging of mouse brain

NASA Astrophysics Data System (ADS)

Wang, Mengran; Wu, Chunyan; Li, Bo; Xia, Fei; Sinefeld, David; Xu, Chris

2018-02-01

The attenuation of excitation power reaching the focus is the main issue that limits the depth penetration of highresolution imaging of biological tissue. The attenuation is caused by a combination of tissue scattering and absorption. Theoretical model of the effective attenuation length for in vivo mouse brain imaging has been built based on the data of the absorption of water and blood and the Mie scattering of a tissue-like phantom. Such a theoretical model has been corroborated at a number of excitation wavelengths, such as 800 nm, 1300 nm , and 1700 nm ; however, the attenuation caused by absorption is negligible when compared to tissue scattering at all these wavelength windows. Here we performed in vivo three-photon imaging of Texas Red-stained vasculature in the same mouse brain with different excitation wavelengths, 1700 nm, 1550 nm, 1500 nm and 1450 nm. In particular, our studies include the wavelength regime where strong water absorption is present (i.e., 1450 nm), and the attenuation by water absorption is predicted to be the dominant contribution in the excitation attenuation. Based on the experimental results, we found that the effective attenuation length at 1450 nm is significantly shorter than those at 1700 nm and 1300 nm. Our results confirm that the theoretical model based on tissue scattering and water absorption is accurate in predicting the effective attenuation lengths for in vivo imaging. The optimum excitation wavelength windows for in vivo mouse brain imaging are at 1300 nm and 1700 nm.

Optical coherence microscopy for deep tissue imaging of the cerebral cortex with intrinsic contrast

PubMed Central

Srinivasan, Vivek J.; Radhakrishnan, Harsha; Jiang, James Y.; Barry, Scott; Cable, Alex E.

2012-01-01

In vivo optical microscopic imaging techniques have recently emerged as important tools for the study of neurobiological development and pathophysiology. In particular, two-photon microscopy has proved to be a robust and highly flexible method for in vivo imaging in highly scattering tissue. However, two-photon imaging typically requires extrinsic dyes or contrast agents, and imaging depths are limited to a few hundred microns. Here we demonstrate Optical Coherence Microscopy (OCM) for in vivo imaging of neuronal cell bodies and cortical myelination up to depths of ~1.3 mm in the rat neocortex. Imaging does not require the administration of exogenous dyes or contrast agents, and is achieved through intrinsic scattering contrast and image processing alone. Furthermore, using OCM we demonstrate in vivo, quantitative measurements of optical properties (index of refraction and attenuation coefficient) in the cortex, and correlate these properties with laminar cellular architecture determined from the images. Lastly, we show that OCM enables direct visualization of cellular changes during cell depolarization and may therefore provide novel optical markers of cell viability. PMID:22330462

Long ranging swept-source optical coherence tomography-based angiography outperforms its spectral-domain counterpart in imaging human skin microcirculations

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Song, Shaozhen; Men, Shaojie; Wang, Ruikang K.

2017-11-01

There is an increasing demand for imaging tools in clinical dermatology that can perform in vivo wide-field morphological and functional examination from surface to deep tissue regions at various skin sites of the human body. The conventional spectral-domain optical coherence tomography-based angiography (SD-OCTA) system is difficult to meet these requirements due to its fundamental limitations of the sensitivity roll-off, imaging range as well as imaging speed. To mitigate these issues, we demonstrate a swept-source OCTA (SS-OCTA) system by employing a swept source based on a vertical cavity surface-emitting laser. A series of comparisons between SS-OCTA and SD-OCTA are conducted. Benefiting from the high system sensitivity, long imaging range, and superior roll-off performance, the SS-OCTA system is demonstrated with better performance in imaging human skin than the SD-OCTA system. We show that the SS-OCTA permits remarkable deep visualization of both structure and vasculature (up to ˜2 mm penetration) with wide field of view capability (up to 18×18 mm2), enabling a more comprehensive assessment of the morphological features as well as functional blood vessel networks from the superficial epidermal to deep dermal layers. It is expected that the advantages of the SS-OCTA system will provide a ground for clinical translation, benefiting the existing dermatological practice.

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

PubMed Central

Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

2016-01-01

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

PubMed

Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

2016-09-07

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

Towards real-time quantitative optical imaging for surgery

NASA Astrophysics Data System (ADS)

Gioux, Sylvain

2017-07-01

There is a pressing clinical need to provide image guidance during surgery. Currently, assessment of tissue that needs to be resected or avoided is performed subjectively leading to a large number of failures, patient morbidity and increased healthcare cost. Because near-infrared (NIR) optical imaging is safe, does not require contact, and can provide relatively deep information (several mm), it offers unparalleled capabilities for providing image guidance during surgery. In this work, we introduce a novel concept that enables the quantitative imaging of endogenous molecular information over large fields-of-view. Because this concept can be implemented in real-time, it is amenable to provide video-rate endogenous information during surgery.

Quantitative Fourier Domain Optical Coherence Tomography Imaging of the Ocular Anterior Segment

NASA Astrophysics Data System (ADS)

McNabb, Ryan Palmer

Clinical imaging within ophthalmology has had transformative effects on ocular health over the last century. Imaging has guided clinicians in their pharmaceutical and surgical treatments of macular degeneration, glaucoma, cataracts and numerous other pathologies. Many of the imaging techniques currently used are photography based and are limited to imaging the surface of ocular structures. This limitation forces clinicians to make assumptions about the underlying tissue which may reduce the efficacy of their diagnoses. Optical coherence tomography (OCT) is a non-invasive, non-ionizing imaging modality that has been widely adopted within the field of ophthalmology in the last 15 years. As an optical imaging technique, OCT utilizes low-coherence interferometry to produce micron-scale three-dimensional datasets of a tissue's structure. Much of the human body consists of tissues that significantly scatter and attenuate optical signals limiting the imaging depth of OCT in those tissues to only 1-2mm. However, the ocular anterior segment is unique among human tissue in that it is primarily transparent or translucent. This allows for relatively deep imaging of tissue structure with OCT and is no longer limited by the optical scattering properties of the tissue. This goal of this work is to develop methods utilizing OCT that offer the potential to reduce the assumptions made by clinicians in their evaluations of their patients' ocular anterior segments. We achieved this by first developing a method to reduce the effects of patient motion during OCT volume acquisitions allowing for accurate, three dimensional measurements of corneal shape. Having accurate corneal shape measurements then allowed us to determine corneal spherical and astigmatic refractive contribution in a given individual. This was then validated in a clinical study that showed OCT better measured refractive change due to surgery than other clinical devices. Additionally, a method was developed to combine the clinical evaluation of the iridocorneal angle through gonioscopy with OCT.

Nanoscale materials for hyperthermal theranostics

NASA Astrophysics Data System (ADS)

Smith, Bennett E.; Roder, Paden B.; Zhou, Xuezhe; Pauzauskie, Peter J.

2015-04-01

Recently, the use of nanoscale materials has attracted considerable attention with the aim of designing personalized therapeutic approaches that can enhance both spatial and temporal control over drug release, permeability, and uptake. Potential benefits to patients include the reduction of overall drug dosages, enabling the parallel delivery of different pharmaceuticals, and the possibility of enabling additional functionalities such as hyperthermia or deep-tissue imaging (LIF, PET, etc.) that complement and extend the efficacy of traditional chemotherapy and surgery. This mini-review is focused on an emerging class of nanometer-scale materials that can be used both to heat malignant tissue to reduce angiogenesis and DNA-repair while simultaneously offering complementary imaging capabilities based on radioemission, optical fluorescence, magnetic resonance, and photoacoustic methods.

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

PubMed

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

Wound botulism presenting as a deep neck space infection.

PubMed

Gouveia, Christopher; Mookherjee, Somnath; Russell, Matthew S

2012-12-01

Otolaryngologists commonly evaluate patients with findings suspicious for deep space soft tissue infections of the neck. In this case, a woman with a history of injection drug use (IDU) presented with dysphagia, odynophagia, and neck pain. Multiple neck abscesses, too small to drain, were seen on imaging. Despite broad-spectrum intravenous antibiotics, she unexpectedly and rapidly developed respiratory failure requiring intubation. Further work-up diagnosed wound botulism (WB). To our knowledge, this is the first report of WB presenting as a deep neck space infection, and illustrates the importance of considering this deadly diagnosis in patients with IDU history and bulbar symptoms. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

State of the Art: MR Imaging after Knee Cartilage Repair Surgery.

PubMed

Guermazi, Ali; Roemer, Frank W; Alizai, Hamza; Winalski, Carl S; Welsch, Goetz; Brittberg, Mats; Trattnig, Siegfried

2015-10-01

Cartilage injuries are common, especially in athletes. Because these injuries frequently affect young patients, and they have the potential to progress to osteoarthritis, treatment to alleviate symptoms and delay joint degeneration is warranted. A number of surgical techniques are available to treat focal chondral defects, including marrow stimulation, osteochondral auto- and allografting, and autologous chondrocyte implantation. Although arthroscopy is considered the standard of reference for the evaluation of cartilage before and after repair, it is invasive with associated morbidity and cannot adequately depict the deep cartilage layer and underlying bone. Magnetic resonance (MR) imaging provides unparalleled noninvasive assessment of the repair site and all other joint tissues. MR observation of cartilage repair tissue is a well-established semiquantitative scoring system for repair tissue that has primarily been used in clinical research studies. The cartilage repair osteoarthritis knee score (CROAKS) optimizes comprehensive morphologic assessment of the knee joint after cartilage repair. Furthermore, quantitative, compositional MR imaging measurements (eg, T2, T2*, T1ρ), delayed gadolinium-enhanced MR imaging of cartilage (dGEMRIC), and sodium imaging are available for biochemical assessment. These quantitative MR imaging techniques help assess collagen content and orientation, water content, and glycosaminoglycan and/or proteoglycan content both in the repair tissue as it matures and in the "native" cartilage. In this review, the authors discuss the principles of state-of-the-art morphologic and compositional MR imaging techniques for imaging of cartilage repair and their application to longitudinal studies. (©) RSNA, 2015.

Surgical Accuracy of 3-Tesla Versus 7-Tesla Magnetic Resonance Imaging in Deep Brain Stimulation for Parkinson Disease.

PubMed

van Laar, Peter Jan; Oterdoom, D L Marinus; Ter Horst, Gert J; van Hulzen, Arjen L J; de Graaf, Eva K L; Hoogduin, Hans; Meiners, Linda C; van Dijk, J Marc C

2016-09-01

In deep brain stimulation (DBS), accurate placement of the lead is critical. Target definition is highly dependent on visual recognition on magnetic resonance imaging (MRI). We prospectively investigated whether the 7-T MRI enabled better visualization of targets and led to better placement of leads compared with the 1.5-T and the 3-T MRI. Three patients with PD (mean, 55 years) were scanned on 1.5-, 3-, and 7-T MRI before surgery. Tissue contrast and signal-to-noise ratio were measured. Target coordinates were noted on MRI and during surgery. Differences were analyzed with post-hoc analysis of variance. The 7-T MRI demonstrated a significant improvement in tissue visualization (P < 0.005) and signal-to-noise ratio (P < 0.005). However, no difference in the target coordinates was found between the 7-T and the 3-T MRI. Although the 7-T MRI enables a significant better visualization of the DBS target in patients with PD, we found no clinical benefit for the placement of the DBS leads. Copyright © 2016 Elsevier Inc. All rights reserved.

Focused fluorescence excitation with time-reversed ultrasonically encoded light and imaging in thick scattering media

NASA Astrophysics Data System (ADS)

Lai, Puxiang; Suzuki, Yuta; Xu, Xiao; Wang, Lihong V.

2013-07-01

Scattering dominates light propagation in biological tissue, and therefore restricts both resolution and penetration depth in optical imaging within thick tissue. As photons travel into the diffusive regime, typically 1 mm beneath human skin, their trajectories transition from ballistic to diffusive due to the increased number of scattering events, which makes it impossible to focus, much less track, photon paths. Consequently, imaging methods that rely on controlled light illumination are ineffective in deep tissue. This problem has recently been addressed by a novel method capable of dynamically focusing light in thick scattering media via time reversal of ultrasonically encoded (TRUE) diffused light. Here, using photorefractive materials as phase conjugate mirrors, we show a direct visualization and dynamic control of optical focusing with this light delivery method, and demonstrate its application for focused fluorescence excitation and imaging in thick turbid media. These abilities are increasingly critical for understanding the dynamic interactions of light with biological matter and processes at different system levels, as well as their applications for biomedical diagnosis and therapy.

High resolution microphotonic needle for endoscopic imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tadayon, Mohammad Amin; Mohanty, Aseema; Roberts, Samantha P.; Barbosa, Felippe; Lipson, Michal

2017-02-01

GRIN (Graded index) lens have revolutionized micro endoscopy enabling deep tissue imaging with high resolution. The challenges of traditional GRIN lenses are their large size (when compared with the field of view) and their limited resolution. This is because of the relatively weak NA in standard graded index lenses. Here we introduce a novel micro-needle platform for endoscopy with much higher resolution than traditional GRIN lenses and a FOV that corresponds to the whole cross section of the needle. The platform is based on polymeric (SU-8) waveguide integrated with a microlens micro fabricated on a silicon substrate using a unique molding process. Due to the high index of refraction of the material the NA of the needle is much higher than traditional GRIN lenses. We tested the probe in a fluorescent dye solution (19.6 µM Alexa Flour 647 solution) and measured a numerical aperture of 0.25, focal length of about 175 µm and minimal spot size of about 1.6 µm. We show that the platform can image a sample with the field of view corresponding to the cross sectional area of the waveguide (80x100 µm2). The waveguide size can in principle be modified to vary size of the imaging field of view. This demonstration, combined with our previous work demonstrating our ability to implant the high NA needle in a live animal, shows that the proposed system can be used for deep tissue imaging with very high resolution and high field of view.

All-near-infrared multiphoton microscopy interrogates intact tissues at deeper imaging depths than conventional single- and two-photon near-infrared excitation microscopes

PubMed Central

Sarder, Pinaki; Yazdanfar, Siavash; Akers, Walter J.; Tang, Rui; Sudlow, Gail P.; Egbulefu, Christopher

2013-01-01

Abstract. The era of molecular medicine has ushered in the development of microscopic methods that can report molecular processes in thick tissues with high spatial resolution. A commonality in deep-tissue microscopy is the use of near-infrared (NIR) lasers with single- or multiphoton excitations. However, the relationship between different NIR excitation microscopic techniques and the imaging depths in tissue has not been established. We compared such depth limits for three NIR excitation techniques: NIR single-photon confocal microscopy (NIR SPCM), NIR multiphoton excitation with visible detection (NIR/VIS MPM), and all-NIR multiphoton excitation with NIR detection (NIR/NIR MPM). Homologous cyanine dyes provided the fluorescence. Intact kidneys were harvested after administration of kidney-clearing cyanine dyes in mice. NIR SPCM and NIR/VIS MPM achieved similar maximum imaging depth of ∼100  μm. The NIR/NIR MPM enabled greater than fivefold imaging depth (>500  μm) using the harvested kidneys. Although the NIR/NIR MPM used 1550-nm excitation where water absorption is relatively high, cell viability and histology studies demonstrate that the laser did not induce photothermal damage at the low laser powers used for the kidney imaging. This study provides guidance on the imaging depth capabilities of NIR excitation-based microscopic techniques and reveals the potential to multiplex information using these platforms. PMID:24150231

A finite element model of remote palpation of breast lesions using radiation force: factors affecting tissue displacement.

PubMed

Nightingale, K R; Nightingale, R W; Palmeri, M L; Trahey, G E

2000-01-01

The early detection of breast cancer reduces patient mortality. The most common method of breast cancer detection is palpation. However, lesions that lie deep within the breast are difficult to palpate when they are small. Thus, a method of remote palpation, which may allow the detection of small lesions lying deep within the breast, is currently under investigation. In this method, acoustic radiation force is used to apply localized forces within tissue (to tissue volumes on the order of 2 mm3) and the resulting tissue displacements are mapped using ultrasonic correlation based methods. A volume of tissue that is stiffer than the surrounding medium (i.e., a lesion) distributes the force throughout the tissue beneath it, resulting in larger regions of displacement, and smaller maximum displacements. The resulting displacement maps may be used to image tissue stiffness. A finite-element-model (FEM) of acoustic remote palpation is presented in this paper. Using this model, a parametric analysis of the affect of varying tissue and acoustic beam characteristics on radiation force induced tissue displacements is performed. The results are used to evaluate the potential of acoustic remote palpation to provide useful diagnostic information in a clinical setting. The potential for using a single diagnostic transducer to both generate radiation force and track the resulting displacements is investigated.

Confocal Imaging of the Embryonic Heart: How Deep?

NASA Astrophysics Data System (ADS)

Miller, Christine E.; Thompson, Robert P.; Bigelow, Michael R.; Gittinger, George; Trusk, Thomas C.; Sedmera, David

2005-06-01

Confocal microscopy allows for optical sectioning of tissues, thus obviating the need for physical sectioning and subsequent registration to obtain a three-dimensional representation of tissue architecture. However, practicalities such as tissue opacity, light penetration, and detector sensitivity have usually limited the available depth of imaging to 200 [mu]m. With the emergence of newer, more powerful systems, we attempted to push these limits to those dictated by the working distance of the objective. We used whole-mount immunohistochemical staining followed by clearing with benzyl alcohol-benzyl benzoate (BABB) to visualize three-dimensional myocardial architecture. Confocal imaging of entire chick embryonic hearts up to a depth of 1.5 mm with voxel dimensions of 3 [mu]m was achieved with a 10× dry objective. For the purpose of screening for congenital heart defects, we used endocardial painting with fluorescently labeled poly-L-lysine and imaged BABB-cleared hearts with a 5× objective up to a depth of 2 mm. Two-photon imaging of whole-mount specimens stained with Hoechst nuclear dye produced clear images all the way through stage 29 hearts without significant signal attenuation. Thus, currently available systems allow confocal imaging of fixed samples to previously unattainable depths, the current limiting factors being objective working distance, antibody penetration, specimen autofluorescence, and incomplete clearing.

Enhanced detection of myeloperoxidase activity in deep tissues through luminescent excitation of near-infrared nanoparticles.

PubMed

Zhang, Ning; Francis, Kevin P; Prakash, Arun; Ansaldi, Daniel

2013-04-01

A previous study reported the use of luminol for the detection of myeloperoxidase (MPO) activity using optical imaging in infiltrating neutrophils under inflammatory disease conditions. The detection is based on a photon-emitting reaction between luminol and an MPO metabolite. Because of tissue absorption and scattering, however, luminol-emitted blue light can be efficiently detected from superficial inflammatory foci only. In this study we report a chemiluminescence resonance energy transfer (CRET) methodology in which luminol-generated blue light excites nanoparticles to emit light in the near-infrared spectral range, resulting in remarkable improvement of MPO detectability in vivo. CRET caused a 37-fold increase in luminescence emission over luminol alone in detecting MPO activity in lung tissues after lipopolysaccharide challenge. We demonstrated a dependence of the chemiluminescent signal on MPO activity using MPO-deficient mice. In addition, co-administration of 4-aminobenzoic acid hydrazide (4-ABAH), an irreversible inhibitor of MPO, significantly attenuated luminescent emission from inflamed lungs. Inhibition of nitric oxide synthase with a nonspecific inhibitor, L-NAME, had no effect on luminol-mediated chemiluminescence production. Pretreatment of mice with MLN120B, a selective inhibitor of IKK-2, resulted in suppression of neutrophil infiltration to the lung tissues and reduction of MPO activity. We also demonstrated that CRET can effectively detect MPO activity at deep tissue tumor foci due to tumor development-associated neutrophil infiltration. We developed a sensitive MPO detection methodology that provides a means for visualizing and quantifying oxidative stress in deep tissue. This method is amenable to rapid evaluation of anti-inflammatory agents in animal models.

Noninvasive treatment of deep venous thrombosis using pulsed ultrasound cavitation therapy (histotripsy) in a porcine model.

PubMed

Maxwell, Adam D; Owens, Gabe; Gurm, Hitinder S; Ives, Kimberly; Myers, Daniel D; Xu, Zhen

2011-03-01

This study evaluated histotripsy as a noninvasive, image-guided method of thrombolysis in a porcine model of deep vein thrombosis. Histotripsy therapy uses short, high-intensity, focused ultrasound pulses to cause mechanical breakdown of targeted soft tissue by acoustic cavitation, which is guided by real-time ultrasound imaging. This is an in vivo feasibility study of histotripsy thrombolysis. Acute thrombi were formed in the femoral vein of juvenile pigs weighing 30-40 kg by balloon occlusion with two catheters and thrombin infusion. A 10-cm-diameter 1-MHz focused transducer was used for therapy. An 8-MHz ultrasound imager was used to align the clot with the therapy focus. Therapy consisted of five cycle pulses delivered at a rate of 1 kHz and peak negative pressure between 14 and 19 MPa. The focus was scanned along the long axis of the vessel to treat the entire visible clot during ultrasound exposure. The targeted region identified by a hyperechoic cavitation bubble cloud was visualized via ultrasound during treatment. Thrombus breakdown was apparent as a decrease in echogenicity within the vessel in 10 of 12 cases and in 7 cases improved flow through the vein as measured by color Doppler. Vessel histology found denudation of vascular endothelium and small pockets of hemorrhage in the vessel adventitia and underlying muscle and fatty tissue, but perforation of the vessel wall was never observed. The results indicate histotripsy has potential for development as a noninvasive treatment for deep vein thrombosis. Copyright © 2011 SIR. Published by Elsevier Inc. All rights reserved.

Pitfalls of CT for deep neck abscess imaging assessment: a retrospective review of 162 cases.

PubMed

Chuang, S Y; Lin, H T; Wen, Y S; Hsu, F J

2013-01-01

To investigate the diagnostic value of contrast-enhanced computed tomography (CT) for the prediction of deep neck abscesses in different deep neck spaces and to evaluate the false-positive results. We retrospectively analysed the clinical charts, CT examinations, surgical findings, bacteriology, pathological examinations and complications of hospitalised patients with a diagnosis of deep neck abscess from 2004 to 2010. The positive predictive values (PPV) for the prediction of abscesses by CT scan in different deep neck spaces were calculated individually on the basis of surgical findings. A total of 162 patients were included in this study. All patients received both intravenous antibiotics and surgical drainage. The parapharyngeal space was the most commonly involved space. The overall PPV for the prediction of deep neck abscess with contrast-enhanced CT was 79.6%. The PPV was 91.3% when more than one deep neck space was involved but only 50.0% in patients with isolated retropharyngeal abscesses. In the false-positive group, cellulitis was the most common final result, followed by cystic degeneration of cervical metastases. Five specimens taken intra-operatively revealed malignancy and four of these were not infected. There are some limitations affecting the differentiation of abscesses and cellulitis, particularly in the retropharyngeal space. A central necrotic cervical metastatic lymph node may sometimes also mimic a simple pyogenic deep neck abscess on both clinical pictures and CT images. Routine biopsy of the tissue must be performed during surgical drainage.

Determinants of the distribution and severity of hypoperfusion in patients with ischemic stroke.

PubMed

Bang, O Y; Saver, J L; Alger, J R; Starkman, S; Ovbiagele, B; Liebeskind, D S

2008-11-25

In acute cerebral ischemia, two variables characterize the extent of hypoperfusion: the volume of hypoperfused tissue and the intensity of hypoperfusion within these regions. We evaluated the determinants of the intensity of hypoperfusion within oligemic regions among patients who were eligible for recanalization therapy for acute ischemic stroke. We analyzed data, including pretreatment diffusion-weighted imaging (DWI) and perfusion-weighted imaging, on 119 patients with acute middle cerebral artery infarctions. The intensity of hypoperfusion within oligemic regions was characterized by the hypoperfusion intensity ratio (HIR), defined as the volume of tissue with severe hypoperfusion (Tmax > or = 8 seconds) divided by the volume of tissue with any hypoperfusion (Tmax > or = 2 seconds). Based on the DWI data, we divided the patients into four stroke phenotypes: large cortical, small (< 1 cm diameter) cortical, border-zone, and deep pattern. The mean (SD) volume of severe hypoperfusion was 54.6 (52.5) mL, and that of any hypoperfusion was 140.8 (81.3) mL. The HIR ranged widely, from 0.002 to 0.974, with a median of 0.35 (interquartile range 0.13-0.60). The volume of any hypoperfusion did not predict the intensity of hypoperfusion within the affected region (r = 0.10, p = 0.284). Angiographic collateral flow grade was associated with HIRs (p value for trend = 0.019) and differed among DWI lesion patterns. In multivariate analysis, diastolic pressure on admission (odds ratio 0.959, 95% CI 0.922-0.998) and DWI pattern of deep infarcts (odds ratio 18.004 compared with large cortical pattern, 95% CI 1.855-173.807) were independently associated with a low HIR. The intensity of hypoperfusion within an oligemic field is largely independent of the size of the oligemia region. Predictors of lesser intensity of hypoperfusion are lower diastolic blood pressure and presence of a deep diffusion-weighted imaging lesion pattern.

Quantitative characterization of viscoelastic behavior in tissue-mimicking phantoms and ex vivo animal tissues.

PubMed

Maccabi, Ashkan; Shin, Andrew; Namiri, Nikan K; Bajwa, Neha; St John, Maie; Taylor, Zachary D; Grundfest, Warren; Saddik, George N

2018-01-01

Viscoelasticity of soft tissue is often related to pathology, and therefore, has become an important diagnostic indicator in the clinical assessment of suspect tissue. Surgeons, particularly within head and neck subsites, typically use palpation techniques for intra-operative tumor detection. This detection method, however, is highly subjective and often fails to detect small or deep abnormalities. Vibroacoustography (VA) and similar methods have previously been used to distinguish tissue with high-contrast, but a firm understanding of the main contrast mechanism has yet to be verified. The contributions of tissue mechanical properties in VA images have been difficult to verify given the limited literature on viscoelastic properties of various normal and diseased tissue. This paper aims to investigate viscoelasticity theory and present a detailed description of viscoelastic experimental results obtained in tissue-mimicking phantoms (TMPs) and ex vivo tissues to verify the main contrast mechanism in VA and similar imaging modalities. A spherical-tip micro-indentation technique was employed with the Hertzian model to acquire absolute, quantitative, point measurements of the elastic modulus (E), long term shear modulus (η), and time constant (τ) in homogeneous TMPs and ex vivo tissue in rat liver and porcine liver and gallbladder. Viscoelastic differences observed between porcine liver and gallbladder tissue suggest that imaging modalities which utilize the mechanical properties of tissue as a primary contrast mechanism can potentially be used to quantitatively differentiate between proximate organs in a clinical setting. These results may facilitate more accurate tissue modeling and add information not currently available to the field of systems characterization and biomedical research.

Quantitative characterization of viscoelastic behavior in tissue-mimicking phantoms and ex vivo animal tissues

PubMed Central

Shin, Andrew; Namiri, Nikan K.; Bajwa, Neha; St. John, Maie; Taylor, Zachary D.; Grundfest, Warren; Saddik, George N.

2018-01-01

Viscoelasticity of soft tissue is often related to pathology, and therefore, has become an important diagnostic indicator in the clinical assessment of suspect tissue. Surgeons, particularly within head and neck subsites, typically use palpation techniques for intra-operative tumor detection. This detection method, however, is highly subjective and often fails to detect small or deep abnormalities. Vibroacoustography (VA) and similar methods have previously been used to distinguish tissue with high-contrast, but a firm understanding of the main contrast mechanism has yet to be verified. The contributions of tissue mechanical properties in VA images have been difficult to verify given the limited literature on viscoelastic properties of various normal and diseased tissue. This paper aims to investigate viscoelasticity theory and present a detailed description of viscoelastic experimental results obtained in tissue-mimicking phantoms (TMPs) and ex vivo tissues to verify the main contrast mechanism in VA and similar imaging modalities. A spherical-tip micro-indentation technique was employed with the Hertzian model to acquire absolute, quantitative, point measurements of the elastic modulus (E), long term shear modulus (η), and time constant (τ) in homogeneous TMPs and ex vivo tissue in rat liver and porcine liver and gallbladder. Viscoelastic differences observed between porcine liver and gallbladder tissue suggest that imaging modalities which utilize the mechanical properties of tissue as a primary contrast mechanism can potentially be used to quantitatively differentiate between proximate organs in a clinical setting. These results may facilitate more accurate tissue modeling and add information not currently available to the field of systems characterization and biomedical research. PMID:29373598

Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure.

PubMed

Cunningham, Ryan J; Harding, Peter J; Loram, Ian D

2017-02-01

Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

Intravital Fluorescence Excitation in Whole-Animal Optical Imaging.

PubMed

Nooshabadi, Fatemeh; Yang, Hee-Jeong; Bixler, Joel N; Kong, Ying; Cirillo, Jeffrey D; Maitland, Kristen C

2016-01-01

Whole-animal fluorescence imaging with recombinant or fluorescently-tagged pathogens or cells enables real-time analysis of disease progression and treatment response in live animals. Tissue absorption limits penetration of fluorescence excitation light, particularly in the visible wavelength range, resulting in reduced sensitivity to deep targets. Here, we demonstrate the use of an optical fiber bundle to deliver light into the mouse lung to excite fluorescent bacteria, circumventing tissue absorption of excitation light in whole-animal imaging. We present the use of this technology to improve detection of recombinant reporter strains of tdTomato-expressing Mycobacterium bovis BCG (Bacillus Calmette Guerin) bacteria in the mouse lung. A microendoscope was integrated into a whole-animal fluorescence imager to enable intravital excitation in the mouse lung with whole-animal detection. Using this technique, the threshold of detection was measured as 103 colony forming units (CFU) during pulmonary infection. In comparison, the threshold of detection for whole-animal fluorescence imaging using standard epi-illumination was greater than 106 CFU.

Intravital Fluorescence Excitation in Whole-Animal Optical Imaging

PubMed Central

Bixler, Joel N.; Kong, Ying; Cirillo, Jeffrey D.; Maitland, Kristen C.

2016-01-01

Whole-animal fluorescence imaging with recombinant or fluorescently-tagged pathogens or cells enables real-time analysis of disease progression and treatment response in live animals. Tissue absorption limits penetration of fluorescence excitation light, particularly in the visible wavelength range, resulting in reduced sensitivity to deep targets. Here, we demonstrate the use of an optical fiber bundle to deliver light into the mouse lung to excite fluorescent bacteria, circumventing tissue absorption of excitation light in whole-animal imaging. We present the use of this technology to improve detection of recombinant reporter strains of tdTomato-expressing Mycobacterium bovis BCG (Bacillus Calmette Guerin) bacteria in the mouse lung. A microendoscope was integrated into a whole-animal fluorescence imager to enable intravital excitation in the mouse lung with whole-animal detection. Using this technique, the threshold of detection was measured as 103 colony forming units (CFU) during pulmonary infection. In comparison, the threshold of detection for whole-animal fluorescence imaging using standard epi-illumination was greater than 106 CFU. PMID:26901051

Non-invasive imaging and cellular tracking of pulmonary emboli by near-infrared fluorescence and positron-emission tomography

PubMed Central

Page, Michael J.; Lourenço, André L.; David, Tovo; LeBeau, Aaron M.; Cattaruzza, Fiore; Castro, Helena C.; VanBrocklin, Henry F.; Coughlin, Shaun R.; Craik, Charles S.

2015-01-01

Functional imaging of proteolytic activity is an emerging strategy to quantify disease and response to therapy at the molecular level. We present a new peptide-based imaging probe technology that advances these goals by exploiting enzymatic activity to deposit probes labelled with near-infrared (NIR) fluorophores or radioisotopes in cell membranes of disease-associated proteolysis. This strategy allows for non-invasive detection of protease activity in vivo and ex vivo by tracking deposited probes in tissues. We demonstrate non-invasive detection of thrombin generation in a murine model of pulmonary embolism using our protease-activated peptide probes in microscopic clots within the lungs with NIR fluorescence optical imaging and positron-emission tomography. Thrombin activity is imaged deep in tissue and tracked predominantly to platelets within the lumen of blood vessels. The modular design of our probes allows for facile investigation of other proteases, and their contributions to disease by tailoring the protease activation and cell-binding elements. PMID:26423607

Video-rate functional photoacoustic microscopy at depths

NASA Astrophysics Data System (ADS)

Wang, Lidai; Maslov, Konstantin; Xing, Wenxin; Garcia-Uribe, Alejandro; Wang, Lihong V.

2012-10-01

We report the development of functional photoacoustic microscopy capable of video-rate high-resolution in vivo imaging in deep tissue. A lightweight photoacoustic probe is made of a single-element broadband ultrasound transducer, a compact photoacoustic beam combiner, and a bright-field light delivery system. Focused broadband ultrasound detection provides a 44-μm lateral resolution and a 28-μm axial resolution based on the envelope (a 15-μm axial resolution based on the raw RF signal). Due to the efficient bright-field light delivery, the system can image as deep as 4.8 mm in vivo using low excitation pulse energy (28 μJ per pulse, 0.35 mJ/cm2 on the skin surface). The photoacoustic probe is mounted on a fast-scanning voice-coil scanner to acquire 40 two-dimensional (2-D) B-scan images per second over a 9-mm range. High-resolution anatomical imaging is demonstrated in the mouse ear and brain. Via fast dual-wavelength switching, oxygen dynamics of mouse cardio-vasculature is imaged in realtime as well.

Real-time temperature feedback for nanoparticles based tumor thermal treatment (Conference Presentation)

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Tamir, Gil; Gannot, Israel

2017-02-01

Systemic hyperthermia therapy exploits the fact that cancer cells are more sensitive to elevated temperatures than healthy tissue. Systemic application of hyperthermia externally usually leads to low efficiency treatment. Recently, our group and others have proposed an antibody conjugated magnetic nanoparticles (MNPs) approach to overcome the limitation of systemic hyperthermia. MNPs can bind specifically to the tumor sites, thus delivering internal highly effective targeted hyperthermia. However, such internal mechanism requires more complicated controls and monitoring. This current work presents a deep tissue temperature monitoring method to control hyperthermia effectiveness and minimize collateral damage to surrounding tissues. A low-frequency narrowband modulation of the RF field used for MNP heating leads to the generation of diffused thermal waves which propagate to the tissue surface and captured by a thermal camera. A Fourier domain, analytical heat transfer model is used for temperature monitoring algorithm. The ill-posed thermal inverse problem is solved efficiently by iterating over the source power until both the amplitude and phase match the recorded thermal image sequence. The narrow bandwidth thermal stimulation enables acquiring deep signals with high SNR. We show that thermal transverse resolution improves as the stimulation frequency increases even slightly above DC, enabling better heat source transverse separation and margin identification in the case of distributed tumors. These results can be used as a part of an overall image and treat system for efficient detection of tumors, manipulation of MNPs and monitoring MNP based hyperthermia.

In Vivo Mammalian Brain Imaging Using One- and Two-Photon Fluorescence Microendoscopy

PubMed Central

Jung, Juergen C.; Mehta, Amit D.; Aksay, Emre; Stepnoski, Raymond; Schnitzer, Mark J.

2010-01-01

One of the major limitations in the current set of techniques available to neuroscientists is a dearth of methods for imaging individual cells deep within the brains of live animals. To overcome this limitation, we developed two forms of minimally invasive fluorescence microendoscopy and tested their abilities to image cells in vivo. Both one- and two-photon fluorescence microendoscopy are based on compound gradient refractive index (GRIN) lenses that are 350–1,000 μm in diameter and provide micron-scale resolution. One-photon microendoscopy allows full-frame images to be viewed by eye or with a camera, and is well suited to fast frame-rate imaging. Two-photon microendoscopy is a laser-scanning modality that provides optical sectioning deep within tissue. Using in vivo microendoscopy we acquired video-rate movies of thalamic and CA1 hippocampal red blood cell dynamics and still-frame images of CA1 neurons and dendrites in anesthetized rats and mice. Microendoscopy will help meet the growing demand for in vivo cellular imaging created by the rapid emergence of new synthetic and genetically encoded fluorophores that can be used to label specific brain areas or cell classes. PMID:15128753

Resolution enhancement of 2-photon microscopy using high-refractive index microspheres

NASA Astrophysics Data System (ADS)

Tehrani, Kayvan Forouhesh; Darafsheh, Arash; Phang, Sendy; Mortensen, Luke J.

2018-02-01

Intravital microscopy using multiphoton processes is the standard tool for deep tissue imaging inside of biological specimens. Usually, near-infrared and infrared light is used to excite the sample, which enables imaging several mean free path inside a scattering tissues. Using longer wavelengths, however, increases the width of the effective multiphoton Point Spread Function (PSF). Many features inside of cells and tissues are smaller than the diffraction limit, and therefore not possible to distinguish using a large PSF. Microscopy using high refractive index microspheres has shown promise to increase the numerical aperture of an imaging system and enhance the resolution. It has been shown that microspheres can image features λ/7 using single photon process fluorescence. In this work, we investigate resolution enhancement for Second Harmonic Generation (SHG) and 2-photon fluorescence microscopy. We used Barium Titanate glass microspheres with diameters ˜20-30 μm and refractive index ˜1.9-2.1. We show microsphere-assisted SHG imaging in bone collagen fibers. Since bone is a very dense tissue constructed of bundles of collagen fibers, it is nontrivial to image individual fibers. We placed microspheres on a dense area of the mouse cranial bone, and achieved imaging of individual fibers. We found that microsphere assisted SHG imaging resolves features of the bone fibers that are not readily visible in conventional SHG imaging. We extended this work to 2-photon microscopy of mitochondria in mouse soleus muscle, and with the help of microsphere resolving power, we were able to trace individual mitochondrion from their ensemble.

Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain

NASA Astrophysics Data System (ADS)

Zhou, Chao; Yu, Guoqiang; Furuya, Daisuke; Greenberg, Joel; Yodh, Arjun; Durduran, Turgut

2006-02-01

Diffuse optical correlation methods were adapted for three-dimensional (3D) tomography of cerebral blood flow (CBF) in small animal models. The image reconstruction was optimized using a noise model for diffuse correlation tomography which enabled better data selection and regularization. The tomographic approach was demonstrated with simulated data and during in-vivo cortical spreading depression (CSD) in rat brain. Three-dimensional images of CBF were obtained through intact skull in tissues(~4mm) deep below the cortex.

Motion corrected photoacoustic difference imaging of fluorescent contrast agents

NASA Astrophysics Data System (ADS)

Märk, Julia; Wagener, Asja; Pönick, Sarah; Grötzinger, Carsten; Zhang, Edward; Laufer, Jan

2016-03-01

In fluorophores, such as exogenous dyes and genetically expressed proteins, the excited state lifetime can be modulated using pump-probe excitation at wavelengths corresponding to the absorption and fluorescence spectra. Simultaneous pump-probe pulses induce stimulated emission (SE) which, in turn, modulates the thermalized energy, and hence the photoacoustic (PA) signal amplitude. For time-delayed pulses, by contrast, SE is suppressed. Since this is not observed in endogenous chromophores, the location of the fluorophore can be determined by subtracting images acquired using simultaneous and time-delayed pump-probe excitation. This simple experimental approach exploits a fluorophorespecific contrast mechanism, and has the potential to enable deep-tissue molecular imaging at fluences below the MPE. In this study, some of the challenges to its in vivo implementation are addressed. First, the PA signal amplitude generated in fluorophores in vivo is often much smaller than that in blood. Second, tissue motion can give rise to artifacts that correspond to endogenous chromophores in the difference image. This would not allow the unambiguous detection of fluorophores. A method to suppress motion artifacts based on fast switching between simultaneous and time-delayed pump-probe excitation was developed. This enables the acquisition of PA signals using the two excitation modes with minimal time delay (20 ms), thus minimizing the effects of tissue motion. The feasibility of this method is demonstrated by visualizing a fluorophore (Atto680) in tissue phantoms, which were moved during the image acquisition to mimic tissue motion.

Three-dimensional spatial localization of thin fluorophore-filled capillaries in thick scattering media

NASA Astrophysics Data System (ADS)

Desrochers, Johanne; Vermette, Patrick; Fontaine, Réjean; Bérubé-Lauzière, Yves

2008-06-01

Fluorescence optical diffuse tomography (fDOT) is of much interest in molecular imaging to retrieve information from fluorescence signals emitted from specifically targeted bioprocesses deep within living tissues. An exciting application of fDOT is in the growing field of tissue engineering, where 3D non-invasive imaging techniques are required to ultimately grow 3D engineered tissues. Via appropriate labelling strategies and fluorescent probes, fDOT has the potential to monitor culture environment and cells viability non-destructively directly within the bioreactor environment where tissues are to be grown. Our ultimate objective is to image the formation of blood vessels in bioreactor conditions. Herein, we use a non-contact setup for small animal fDOT imaging designed for 3D light collection around the sample. We previously presented a time of flight approach using a numerical constant fraction discrimination technique to assign an early photons arrival time to every fluorescence time point-spread function collected around the sample. Towards bioreactor in-situ imaging, we have shown the capability of our approach to localize a fluorophore-filled 500 μm capillary immersed coaxially in a cylindrically shaped bioreactor phantom containing an absorbing/scattering medium representative of experiments on real tissue cultures. Here, we go one step further, and present results for the 3D localization of thinner indocyanine green labelled capillaries (250 μm and 360 μm inner diameter) immersed in the same phantom conditions and geometry but with different spatial configurations (10° and 30° capillary inclination).

High sensitivity contrast enhanced optical coherence tomography for functional in vivo imaging

NASA Astrophysics Data System (ADS)

Liba, Orly; SoRelle, Elliott D.; Sen, Debasish; de la Zerda, Adam

2017-02-01

In this study, we developed and applied highly-scattering large gold nanorods (LGNRs) and custom spectral detection algorithms for high sensitivity contrast-enhanced optical coherence tomography (OCT). We were able to detect LGNRs at a concentration as low as 50 pM in blood. We used this approach for noninvasive 3D imaging of blood vessels deep in solid tumors in living mice. Additionally, we demonstrated multiplexed imaging of spectrally-distinct LGNRs that enabled observations of functional drainage in lymphatic networks. This method, which we call MOZART, provides a platform for molecular imaging and characterization of tissue noninvasively at cellular resolution.

Using the shortwave infrared to image middle ear pathologies

PubMed Central

Valdez, Tulio A.; Bruns, Oliver T.; Bawendi, Moungi G.

2016-01-01

Visualizing structures deep inside opaque biological tissues is one of the central challenges in biomedical imaging. Optical imaging with visible light provides high resolution and sensitivity; however, scattering and absorption of light by tissue limits the imaging depth to superficial features. Imaging with shortwave infrared light (SWIR, 1–2 μm) shares many advantages of visible imaging, but light scattering in tissue is reduced, providing sufficient optical penetration depth to noninvasively interrogate subsurface tissue features. However, the clinical potential of this approach has been largely unexplored because suitable detectors, until recently, have been either unavailable or cost prohibitive. Here, taking advantage of newly available detector technology, we demonstrate the potential of SWIR light to improve diagnostics through the development of a medical otoscope for determining middle ear pathologies. We show that SWIR otoscopy has the potential to provide valuable diagnostic information complementary to that provided by visible pneumotoscopy. We show that in healthy adult human ears, deeper tissue penetration of SWIR light allows better visualization of middle ear structures through the tympanic membrane, including the ossicular chain, promontory, round window niche, and chorda tympani. In addition, we investigate the potential for detection of middle ear fluid, which has significant implications for diagnosing otitis media, the overdiagnosis of which is a primary factor in increased antibiotic resistance. Middle ear fluid shows strong light absorption between 1,400 and 1,550 nm, enabling straightforward fluid detection in a model using the SWIR otoscope. Moreover, our device is easily translatable to the clinic, as the ergonomics, visual output, and operation are similar to a conventional otoscope. PMID:27551085

Anatomical and Functional Images of in vitro and in vivo Tissues by NIR Time-domain Diffuse Optical Tomography

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Homma, Kazuhiro; Onodera, Yoichi; Yamada, Yukio

Near infra-red (NIR) diffuse optical tomography (DOT) has gained much attention and it will be clinically applied to imaging breast, neonatal head, and the hemodynamics of the brain because of its noninvasiveness and deep penetration in biological tissue. Prior to achieving the imaging of infant brain using DOT, the developed methodologies need to be experimentally justified by imaging some real organs with simpler structures. Here we report our results of an in vitro chicken leg and an in vivo exercising human forearm from the data measured by a multi-channel time-resolved NIR system. Tomographic images were reconstructed by a two-dimensional image reconstruction algorithm based on a modified generalized pulse spectrum technique for simultaneous reconstruction of the µa and µs´. The absolute µa- and µs´-images revealed the inner structures of the chicken leg and the forearm, where the bones were clearly distinguished from the muscle. The Δµa-images showed the blood volume changes during the forearm exercise, proving that the system and the image reconstruction algorithm could potentially be used for imaging not only the anatomic structure but also the hemodynamics in neonatal heads.

Phantom testing of a novel endoscopic OCT probe: a prelude to clinical in-vivo laryngeal use

NASA Astrophysics Data System (ADS)

Tatla, Taran; Pang, J. Y.; Cernat, R.; Dobre, G.; Tadrous, P. J.; Bradu, A.; Gelikonov, G.; Gelikonov, V.; Podoleanu, A. G.

2012-12-01

Optical coherence tomography is a novel imaging technique providing potentially high resolution tri-dimensional images of tissue microstructure up to 2-3mm deep. We present pre-clinical data from a novel miniaturised OCT probe utilised for endoscopic imaging of laryngeal mucosa. A 1300nm SS-OCT probe was passed in tandem with a flexible fibreoptic nasoendoscope into the larynx of a manikin. Ex vivo OCT images were acquired using a desktop 1300nm TD-OCT imaging system. The feasibility, robustness and safety of this set-up was demonstrated as a preliminary step to extending the use of this assembly to a clinical patient cohort with varying laryngeal pathologies.

Dual-modality endoscopic probe for tissue surface shape reconstruction and hyperspectral imaging enabled by deep neural networks.

PubMed

Lin, Jianyu; Clancy, Neil T; Qi, Ji; Hu, Yang; Tatla, Taran; Stoyanov, Danail; Maier-Hein, Lena; Elson, Daniel S

2018-06-15

Surgical guidance and decision making could be improved with accurate and real-time measurement of intra-operative data including shape and spectral information of the tissue surface. In this work, a dual-modality endoscopic system has been proposed to enable tissue surface shape reconstruction and hyperspectral imaging (HSI). This system centers around a probe comprised of an incoherent fiber bundle, whose fiber arrangement is different at the two ends, and miniature imaging optics. For 3D reconstruction with structured light (SL), a light pattern formed of randomly distributed spots with different colors is projected onto the tissue surface, creating artificial texture. Pattern decoding with a Convolutional Neural Network (CNN) model and a customized feature descriptor enables real-time 3D surface reconstruction at approximately 12 frames per second (FPS). In HSI mode, spatially sparse hyperspectral signals from the tissue surface can be captured with a slit hyperspectral imager in a single snapshot. A CNN based super-resolution model, namely "super-spectral-resolution" network (SSRNet), has also been developed to estimate pixel-level dense hypercubes from the endoscope cameras standard RGB images and the sparse hyperspectral signals, at approximately 2 FPS. The probe, with a 2.1 mm diameter, enables the system to be used with endoscope working channels. Furthermore, since data acquisition in both modes can be accomplished in one snapshot, operation of this system in clinical applications is minimally affected by tissue surface movement and deformation. The whole apparatus has been validated on phantoms and tissue (ex vivo and in vivo), while initial measurements on patients during laryngeal surgery show its potential in real-world clinical applications. Copyright © 2018 Elsevier B.V. All rights reserved.

High-extinction virtually imaged phased array-based Brillouin spectroscopy of turbid biological media

NASA Astrophysics Data System (ADS)

Fiore, Antonio; Zhang, Jitao; Shao, Peng; Yun, Seok Hyun; Scarcelli, Giuliano

2016-05-01

Brillouin microscopy has recently emerged as a powerful technique to characterize the mechanical properties of biological tissue, cell, and biomaterials. However, the potential of Brillouin microscopy is currently limited to transparent samples, because Brillouin spectrometers do not have sufficient spectral extinction to reject the predominant non-Brillouin scattered light of turbid media. To overcome this issue, we combined a multi-pass Fabry-Perot interferometer with a two-stage virtually imaged phased array spectrometer. The Fabry-Perot etalon acts as an ultra-narrow band-pass filter for Brillouin light with high spectral extinction and low loss. We report background-free Brillouin spectra from Intralipid solutions and up to 100 μm deep within chicken muscle tissue.

Two-Photon Excitation Microscopy for the Study of Living Cells and Tissues

PubMed Central

Benninger, Richard K.P.; Piston, David W.

2013-01-01

Two-photon excitation microscopy is an alternative to confocal microscopy that provides advantages for three-dimensional and deep tissue imaging. This unit will describe the basic physical principles behind two-photon excitation and discuss the advantages and limitations of its use in laser-scanning microscopy. The principal advantages of two-photon microscopy are reduced phototoxicity, increased imaging depth, and the ability to initiate highly localized photochemistry in thick samples. Practical considerations for the application of two-photon microscopy will then be discussed, including recent technological advances. This unit will conclude with some recent applications of two-photon microscopy that highlight the key advantages over confocal microscopy and the types of experiments which would benefit most from its application. PMID:23728746

Modeling and image reconstruction in spectrally resolved bioluminescence tomography

NASA Astrophysics Data System (ADS)

Dehghani, Hamid; Pogue, Brian W.; Davis, Scott C.; Patterson, Michael S.

2007-02-01

Recent interest in modeling and reconstruction algorithms for Bioluminescence Tomography (BLT) has increased and led to the general consensus that non-spectrally resolved intensity-based BLT results in a non-unique problem. However, the light emitted from, for example firefly Luciferase, is widely distributed over the band of wavelengths from 500 nm to 650 nm and above, with the dominant fraction emitted from tissue being above 550 nm. This paper demonstrates the development of an algorithm used for multi-wavelength 3D spectrally resolved BLT image reconstruction in a mouse model. It is shown that using a single view data, bioluminescence sources of up to 15 mm deep can be successfully recovered given correct information about the underlying tissue absorption and scatter.

Nanoscale materials for hyperthermal theranostics

DOE PAGES

Smith, Bennett E.; Roder, Paden B.; Zhou, Xuezhe; ...

2015-03-18

Recently, the use of nanoscale materials has attracted considerable attention with the aim of designing personalized therapeutic approaches that can enhance both spatial and temporal control over drug release, permeability, and uptake. Potential benefits to patients include the reduction of overall drug dosages, enabling the parallel delivery of different pharmaceuticals, and the possibility of enabling additional functionalities such as hyperthermia or deep-tissue imaging (LIF, PET, etc.) that complement and extend the efficacy of traditional chemotherapy and surgery. Our mini review is focused on an emerging class of nanometer-scale materials that can be used both to heat malignant tissue to reducemore » angiogenesis and DNA-repair while simultaneously offering complementary imaging capabilities based on radioemission, optical fluorescence, magnetic resonance, and photoacoustic methods.« less

Non-invasive measurements of tissue hemodynamics with hybrid diffuse optical methods

NASA Astrophysics Data System (ADS)

Durduran, Turgut

Diffuse optical techniques were used to measure hemodynamics of tissues non-invasively. Spectroscopy and tomography of the brain, muscle and implanted tumors were carried out in animal models and humans. Two qualitatively different methods, diffuse optical tomography and diffuse correlation tomography, were hybridized permitting simultaneous measurement of total hemoglobin concentration, blood oxygen saturation and blood flow. This combination of information was processed further to derive estimates of oxygen metabolism (e.g. CMRO 2) in tissue. The diffuse correlation measurements of blood flow were demonstrated in human tissues, for the first time, demonstrating continous, non-invasive imaging of oxygen metabolism in large tissue volumes several centimeters below the tissue surface. The bulk of these investigations focussed on cerebral hemodynamics. Extensive validation of this methodology was carried out in in vivo rat brain models. Three dimensional images of deep tissue hemodynamics in middle cerebral artery occlusion and cortical spreading depression (CSD) were obtained. CSD hemodynamics were found to depend strongly on partial pressure of carbon dioxide. The technique was then adapted for measurement of human brain. All optical spectroscopic measurements of CMRO2 during functional activation were obtained through intact human skull non-invasively. Finally, a high spatio-temporal resolution measurement of cerebral blood flow due to somatosensory cortex activation following electrical forepaw stimulation in rats was carried out with laser speckle flowmetry. New analysis methods were introduced for laser speckle flowmetry. In other organs, deep tissue hemodynamics were measured on human calf muscle during exercise and cuff-ischemia and were shown to have some clinical utility for peripheral vascular disease. In mice tumor models, the measured hemodynamics were shown to be predictive of photodynamic therapy efficacy, again suggesting promise of clinical utility. In total, the research has pioneered the development of diffuse optical measurements of blood flow, oxygenation and oxygen metabolism in a large range of research and clinical applications.

Enhanced optical clearing of skin in vivo and optical coherence tomography in-depth imaging

NASA Astrophysics Data System (ADS)

Wen, Xiang; Jacques, Steven L.; Tuchin, Valery V.; Zhu, Dan

2012-06-01

The strong optical scattering of skin tissue makes it very difficult for optical coherence tomography (OCT) to achieve deep imaging in skin. Significant optical clearing of in vivo rat skin sites was achieved within 15 min by topical application of an optical clearing agent PEG-400, a chemical enhancer (thiazone or propanediol), and physical massage. Only when all three components were applied together could a 15 min treatment achieve a three fold increase in the OCT reflectance from a 300 μm depth and 31% enhancement in image depth Zthreshold.

Technique development for photoacoustic imaging guided interventions

NASA Astrophysics Data System (ADS)

Cheng, Qian; Zhang, Haonan; Yuan, Jie; Feng, Ting; Xu, Guan; Wang, Xueding

2015-03-01

Laser-induced thermotherapy (LITT), i.e. tissue destruction induced by a local increase of temperature by means of laser light energy transmission, has been frequently used for minimally invasive treatments of various diseases such as benign thyroid nodules and liver cancer. The emerging photoacoustic (PA) imaging, when integrated with ultrasound (US), could contribute to LITT procedure. PA can enable a good visualization of percutaneous apparatus deep inside tissue and, therefore, can offer accurate guidance of the optical fibers to the target tissue. Our initial experiment demonstrated that, by picking the strong photoacoustic signals generated at the tips of optical fibers as a needle, the trajectory and position of the fibers could be visualized clearly using a commercial available US unit. When working the conventional US Bscan mode, the fibers disappeared when the angle between the fibers and the probe surface was larger than 60 degree; while working on the new PA mode, the fibers could be visualized without any problem even when the angle between the fibers and the probe surface was larger than 75 degree. Moreover, with PA imaging function integrated, the optical fibers positioned into the target tissue, besides delivering optical energy for thermotherapy, can also be used to generate PA signals for on-line evaluation of LITT. Powered by our recently developed PA physio-chemical analysis, PA measurements from the tissue can provide a direct and accurate feedback of the tissue responses to laser ablation, including the changes in not only chemical compositions but also histological microstructures. The initial experiment on the rat liver model has demonstrated the excellent sensitivity of PA imaging to the changes in tissue temperature rise and tissue status (from native to coagulated) when the tissue is treated in vivo with LITT.

An ultrasound-guided fluorescence tomography system: design and specification

NASA Astrophysics Data System (ADS)

D'Souza, Alisha V.; Flynn, Brendan P.; Kanick, Stephen C.; Torosean, Sason; Davis, Scott C.; Maytin, Edward V.; Hasan, Tayyaba; Pogue, Brian W.

2013-03-01

An ultrasound-guided fluorescence molecular tomography system is under development for in vivo quantification of Protoporphyrin IX (PpIX) during Aminolevulinic Acid - Photodynamic Therapy (ALA-PDT) of Basal Cell Carcinoma. The system is designed to combine fiber-based spectral sampling of PPIX fluorescence emission with co-registered ultrasound images to quantify local fluorophore concentration. A single white light source is used to provide an estimate of the bulk optical properties of tissue. Optical data is obtained by sequential illumination of a 633nm laser source at 4 linear locations with parallel detection at 5 locations interspersed between the sources. Tissue regions from segmented ultrasound images, optical boundary data, white light-informed optical properties and diffusion theory are used to estimate the fluorophore concentration in these regions. Our system and methods allow interrogation of both superficial and deep tissue locations up to PpIX concentrations of 0.025ug/ml.

Fast subsurface fingerprint imaging with full-field optical coherence tomography system equipped with a silicon camera

NASA Astrophysics Data System (ADS)

Auksorius, Egidijus; Boccara, A. Claude

2017-09-01

Images recorded below the surface of a finger can have more details and be of higher quality than the conventional surface fingerprint images. This is particularly true when the quality of the surface fingerprints is compromised by, for example, moisture or surface damage. However, there is an unmet need for an inexpensive fingerprint sensor that is able to acquire high-quality images deep below the surface in short time. To this end, we report on a cost-effective full-field optical coherent tomography system comprised of a silicon camera and a powerful near-infrared LED light source. The system, for example, is able to record 1.7 cm×1.7 cm en face images in 0.12 s with the spatial sampling rate of 2116 dots per inch and the sensitivity of 93 dB. We show that the system can be used to image internal fingerprints and sweat ducts with good contrast. Finally, to demonstrate its biometric performance, we acquired subsurface fingerprint images from 240 individual fingers and estimated the equal-error-rate to be ˜0.8%. The developed instrument could also be used in other en face deep-tissue imaging applications because of its high sensitivity, such as in vivo skin imaging.

Two-dimensional and 3-D images of thick tissue using time-constrained times-of-flight and absorbance spectrophotometry

NASA Astrophysics Data System (ADS)

Benaron, David A.; Lennox, M.; Stevenson, David K.

1992-05-01

Reconstructing deep-tissue images in real time using spectrophotometric data from optically diffusing thick tissues has been problematic. Continuous wave applications (e.g., pulse oximetry, regional cerebral saturation) ignore both the multiple paths traveled by the photons through the tissue and the effects of scattering, allowing scalar measurements but only under limited conditions; interferometry works poorly in thick, highly-scattering media; frequency- modulated approaches may not allow full deconvolution of scattering and absorbance; and pulsed-light techniques allow for preservation of information regarding the multiple paths taken by light through the tissue, but reconstruction is both computation intensive and limited by the relative surface area available for detection of photons. We have developed a picosecond times-of-flight and absorbance (TOFA) optical system, time-constrained to measure only photons with a narrow range of path lengths and arriving within a narrow angel of the emitter-detector axis. The delay until arrival of the earliest arriving photons is a function of both the scattering and absorbance of the tissues in a direct line between the emitter and detector, reducing the influence of surrounding tissues. Measurement using a variety of emitter and detector locations produces spatial information which can be analyzed in a standard 2-D grid, or subject to computer reconstruction to produce tomographic images representing 3-D structure. Using such a technique, we have been able to demonstrate the principles of tc-TOFA, detect and localize diffusive and/or absorptive objects suspended in highly scattering media (such as blood admixed with yeast), and perform simple 3-D reconstructions using phantom objects. We are now attempting to obtain images in vivo. Potential future applications include use as a research tool, and as a continuous, noninvasive, nondestructive monitor in diagnostic imaging, fetal monitoring, neurologic and cardiac assessment. The technique may lead to real-time optical imaging and quantitation of tissues oxygen delivery.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images.

PubMed

Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant

2016-01-01

Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by 1) the large number of nuclei and the size of high resolution digitized pathology images, and 2) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of "Deep Learning" strategies for classification and analysis of big image data. Histopathology, given its size and complexity, represents an excellent use case for application of deep learning strategies. In this paper, a Stacked Sparse Autoencoder (SSAE), an instance of a deep learning strategy, is presented for efficient nuclei detection on high-resolution histopathological images of breast cancer. The SSAE learns high-level features from just pixel intensities alone in order to identify distinguishing features of nuclei. A sliding window operation is applied to each image in order to represent image patches via high-level features obtained via the auto-encoder, which are then subsequently fed to a classifier which categorizes each image patch as nuclear or non-nuclear. Across a cohort of 500 histopathological images (2200 × 2200) and approximately 3500 manually segmented individual nuclei serving as the groundtruth, SSAE was shown to have an improved F-measure 84.49% and an average area under Precision-Recall curve (AveP) 78.83%. The SSAE approach also out-performed nine other state of the art nuclear detection strategies.

Chronic Expanding Hematoma in the Extremities: A Clinical Problem of Adhesion to the Surrounding Tissues

PubMed Central

Okamoto, Takeshi; Matsuda, Shuichi

2017-01-01

Chronic expanding hematoma is characterized by continuous growth of a blood collection. We analyzed the clinical features of 7 patients with chronic expanding hematomas in the extremities, with an average age of 65.6 years. All lesions occurred in the lower extremities, with 4 seen in the thigh and 3 in the knee region. Six patients had subcutaneous hematomas, while 1 was deep-seated in the thigh. The magnetic resonance features of the lesion were compatible with those of a standard hematoma. A low signal intensity on T1- and T2-weighted imaging at the pseudocapsule was also characteristic. Cystic features were seen in 5 of 7 patients. All lesions were resected together with their pseudocapsule. In the subcutaneous lesions, it was necessary to resect adherent fascia, with or without involved skin. In the deep-seated thigh lesion, the common peroneal nerve was completely adherent to the pseudocapsule, a phenomenon from absence of the common peroneal nerve which appeared after resection. Chronic expanding hematomas of the extremities are predominantly located in the subcutaneous tissue of the lower extremity. The surrounding pseudocapsule is adherent to the adjacent tissues, and clinicians must be aware of this, especially when resecting a deep-seated lesion. PMID:28642872

Identification of intramural metastasis in esophageal cancer using multiphoton microscopy

NASA Astrophysics Data System (ADS)

Xu, Jian; Kang, Deyong; Zhuo, Shuangmu; Zhu, Xiaoqin; Lin, jiangbo; Chen, Jianxin

2017-02-01

Intramural metastasis (IM) of esophageal cancer is defined as metastasis from a primary lesion to the esophageal wall without intraepithelial cancer extension. Esophageal cancer with IM is more common and such cases indicate a poor prognosis. In esophageal surgery, if curative resection is possible, the complete removal of both primary tumor and associated IMs is required. Therefore, accurate diagnosis of IMs in esophageal cancer prior to surgery is of particular importance. Multiphoton microscopy (MPM) with subcellular resolution is well-suited for deep tissue imaging since many endogenous fluorophores of fresh biological tissues are excited through two-photon excited fluorescence (TPEF) and second harmonic generation (SHG). Here, a study to identify IM in fresh tissue section using MPM is reported. In this study, the morphological and spectral differences between IM and surrounding tissue are described. These results show that MPM has the ability to accurately identify IM in esophageal tissues. With improvement of the penetration depth of MPM and the development of multiphton microendoscope, MPM may be a promising imaging technique for preoperative diagnosis of IMs in esophageal cancer in the future.

Seeking: Accurate Measurement Techniques for Deep-Bone Density and Structure

NASA Technical Reports Server (NTRS)

Sibonga, Jean

2009-01-01

We are seeking a clinically-useful technology with enough sensitivity to assess the microstructure of "spongy" bone that is found in the marrow cavities of whole bones. However, this technology must be for skeletal sites surrounded by layers of soft tissues, such as the spine and the hip. Soft tissue interferes with conventional imaging and using a more accessible area -- for example, the wrist or the ankle of limbs-- as a proxy for the less accessible skeletal regions, will not be accurate. A non-radioactive technology is strongly preferred.

Photocleavable Hydrogel-Coated Upconverting Nanoparticles: A Multifunctional Theranostic Platform for NIR Imaging and On-Demand Macromolecular Delivery.

PubMed

Jalani, Ghulam; Naccache, Rafik; Rosenzweig, Derek H; Haglund, Lisbet; Vetrone, Fiorenzo; Cerruti, Marta

2016-01-27

Lanthanide-doped upconverting nanoparticles (UCNPs) have emerged as excellent nanotransducers for converting longer wavelength near-infrared (NIR) light to shorter wavelengths spanning the ultraviolet (UV) to the visible (Vis) regions of the spectrum via a multiphoton absorption process, known as upconversion. Here, we report the development of NIR to UV-Vis-NIR UCNPs consisting of LiYF4:Yb(3+)/Tm(3+)@SiO2 individually coated with a 10 ± 2 nm layer of chitosan (CH) hydrogel cross-linked with a photocleavable cross-linker (PhL). We encapsulated fluorescent-bovine serum albumin (FITC-BSA) inside the gel. Under 980 nm excitation, the upconverted UV emission cleaves the PhL cross-links and instantaneously liberates the FITC-BSA under 2 cm thick tissue. The release is immediately arrested if the excitation source is switched off. The upconverted NIR light allows for the tracking of particles under the tissue. Nucleus pulposus (NP) cells cultured with UCNPs are viable both in the presence and in the absence of laser irradiation. Controlled drug delivery of large biomolecules and deep tissue imaging make this system an excellent theranostic platform for tissue engineering, biomapping, and cellular imaging applications.

Multispectral measurement of contrast in tissue-mimicking phantoms in near-infrared spectral range of 650 to 1600 nm

PubMed Central

Salo, Daniel; Zhang, Hairong; Kim, David M.; Berezin, Mikhail Y.

2014-01-01

Abstract. In order to identify the optimal imaging conditions for the highest spatial contrast in biological tissue, we explored the properties of a tissue-mimicking phantom as a function of the wavelengths in a broad range of near-infrared spectra (650 to 1600 nm). Our customized multispectral hardware, which featured a scanning transmission microscope and imaging spectrographs equipped with silicon and InGaAs charge-coupled diode array detectors, allowed for direct comparison of the Michelson contrast obtained from a phantom composed of a honeycomb grid, Intralipid, and India ink. The measured contrast depended on the size of the grid, luminance, and the wavelength of measurements. We demonstrated that at low thickness of the phantom, a reasonable contrast of the objects can be achieved at any wavelength between 700 and 1400 nm and between 1500 and 1600 nm. At larger thicknesses, such contrast can be achieved mostly between 1200 and 1350 nm. These results suggest that distinguishing biological features in deep tissue and developing contrast agents for in vivo may benefit from imaging in this spectral range. PMID:25104414

Assessing photoplethysmographic imaging performance beyond facial perfusion analysis

NASA Astrophysics Data System (ADS)

Amelard, Robert; Hughson, Richard L.; Greaves, Danielle K.; Clausi, David A.; Wong, Alexander

2017-02-01

Photoplethysmographic imaging (PPGI) systems are relatively new non-contact biophotonic diffuse reflectance systems able to assess arterial pulsations through transient changes in light-tissue interaction. Many PPGI studies have focused on extracting heart rate from the face or hand. Though PPGI systems can be used for widefield imaging of any anatomical area, whole-body investigations are lacking. Here, using a novel PPGI system, coded hemodynamic imaging (CHI), we explored and analyzed the pulsatility at major arterial locations across the whole body, including the neck (carotid artery), arm/wrist (brachial, radial and ulnar arteries), and leg/feet (popliteal and tibial arteries). CHI was positioned 1.5 m from the participant, and diffuse reactance from a broadband tungsten-halogen illumination was filtered using 850{1000 nm bandpass filter for deep tissue penetration. Images were acquired over a highly varying 24-participant sample (11/13 female/male, age 28.7+/-12.4 years, BMI 25.5+/-5.2 kg/m2), and a preliminary case study was performed. B-mode ultrasound images were acquired to validate observations through planar arterial characteristics.

Photoacoustic and ultrasound imaging of cancellous bone tissue.

PubMed

Yang, Lifeng; Lashkari, Bahman; Tan, Joel W Y; Mandelis, Andreas

2015-07-01

We used ultrasound (US) and photoacoustic (PA) imaging modalities to characterize cattle trabecular bones. The PA signals were generated with an 805-nm continuous wave laser used for optimally deep optical penetration depth. The detector for both modalities was a 2.25-MHz US transducer with a lateral resolution of ~1 mm at its focal point. Using a lateral pixel size much larger than the size of the trabeculae, raster scanning generated PA images related to the averaged values of the optical and thermoelastic properties, as well as density measurements in the focal volume. US backscatter yielded images related to mechanical properties and density in the focal volume. The depth of interest was selected by time-gating the signals for both modalities. The raster scanned PA and US images were compared with microcomputed tomography (μCT) images averaged over the same volume to generate similar spatial resolution as US and PA. The comparison revealed correlations between PA and US modalities with the mineral volume fraction of the bone tissue. Various features and properties of these modalities such as detectable depth, resolution, and sensitivity are discussed.

Classifying magnetic resonance image modalities with convolutional neural networks

NASA Astrophysics Data System (ADS)

Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

2018-02-01

Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

Noninvasive Assessment of Early Dental Lesion Using a Dual-Contrast Photoacoustic Tomography

PubMed Central

Cheng, Renxiang; Shao, Jiaojiao; Gao, Xiaoxiang; Tao, Chao; Ge, Jiuyu; Liu, Xiaojun

2016-01-01

Dental hard tissue lesions, including caries, cracked-tooth, etc., are the most prevalent diseases of people worldwide. Dental lesions and correlative diseases greatly decrease the life quality of patients throughout their lifetime. It is still hard to noninvasively detect these dental lesions in their early stages. Photoacoustic imaging is an emerging hybrid technology combining the high spatial resolution of ultrasound in deep tissue with the rich optical contrasts. In this study, a dual-contrast photoacoustic tomography is applied to detect the early dental lesions. One contrast, named B-mode, is related to the optical absorption. It is good at providing the sharp image about the morphological and macro-structural features of the teeth. Another contrast, named S-mode, is associated with the micro-structural and mechanical properties of the hard tissue. It is sensitive to the change of tissue properties induced by the early dental lesions. Experiments show that the comprehensive analysis of dual-contrast information can provide reliable information of the early dental lesions. Moreover, the imaging parameter of S-mode is device-independent and it could measure tissue properties quantitatively. We expect that the proposed scheme could be beneficial for improving safety, accuracy and sensitivity of the clinical diagnosis of the dental lesion. PMID:26902394

Noninvasive Assessment of Early Dental Lesion Using a Dual-Contrast Photoacoustic Tomography

NASA Astrophysics Data System (ADS)

Cheng, Renxiang; Shao, Jiaojiao; Gao, Xiaoxiang; Tao, Chao; Ge, Jiuyu; Liu, Xiaojun

2016-02-01

Dental hard tissue lesions, including caries, cracked-tooth, etc., are the most prevalent diseases of people worldwide. Dental lesions and correlative diseases greatly decrease the life quality of patients throughout their lifetime. It is still hard to noninvasively detect these dental lesions in their early stages. Photoacoustic imaging is an emerging hybrid technology combining the high spatial resolution of ultrasound in deep tissue with the rich optical contrasts. In this study, a dual-contrast photoacoustic tomography is applied to detect the early dental lesions. One contrast, named B-mode, is related to the optical absorption. It is good at providing the sharp image about the morphological and macro-structural features of the teeth. Another contrast, named S-mode, is associated with the micro-structural and mechanical properties of the hard tissue. It is sensitive to the change of tissue properties induced by the early dental lesions. Experiments show that the comprehensive analysis of dual-contrast information can provide reliable information of the early dental lesions. Moreover, the imaging parameter of S-mode is device-independent and it could measure tissue properties quantitatively. We expect that the proposed scheme could be beneficial for improving safety, accuracy and sensitivity of the clinical diagnosis of the dental lesion.

Assessment of using ultrasound images as prior for diffuse optical tomography regularization matrix

NASA Astrophysics Data System (ADS)

Althobaiti, Murad; Vavadi, Hamed; Zhu, Quing

2017-02-01

Imaging of tissue with Ultrasound-guided diffuse optical tomography (DOT) is a rising imaging technique to map hemoglobin concentrations within tissue for breast cancer detection and diagnosis. Near-infrared optical imaging received a lot of attention in research as a possible technique to be used for such purpose especially for breast tumors. Since DOT images contrast is closely related to oxygenation and deoxygenating of the hemoglobin, which is an important factor in differentiating malignant and benign tumors. One of the optical imaging modalities used is the diffused optical tomography (DOT); which probes deep scattering tissue (1-5cm) by NIR optical source-detector probe and detects NIR photons in the diffusive regime. The photons in the diffusive regime usually reach the detector without significant information about their source direction and the propagation path. Because of that, the optical reconstruction problem of the medium characteristics is ill-posed even with the tomography and Back-projection techniques. The accurate recovery of images requires an effective image reconstruction method. Here, we illustrate a method in which ultrasound images are encoded as prior for regularization of the inversion matrix. Results were evaluated using phantom experiments of low and high absorption contrasts. This method improves differentiation between the low and the high contrasts targets. Ultimately, this method could improve malignant and benign cases by increasing reconstructed absorption ratio of malignant to benign. Besides that, the phantom results show improvements in target shape as well as the spatial resolution of the DOT reconstructed images.

Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach.

PubMed

Han, Xu; Kwitt, Roland; Aylward, Stephen; Bakas, Spyridon; Menze, Bjoern; Asturias, Alexander; Vespa, Paul; Van Horn, John; Niethammer, Marc

2018-08-01

Brain extraction from 3D medical images is a common pre-processing step. A variety of approaches exist, but they are frequently only designed to perform brain extraction from images without strong pathologies. Extracting the brain from images exhibiting strong pathologies, for example, the presence of a brain tumor or of a traumatic brain injury (TBI), is challenging. In such cases, tissue appearance may substantially deviate from normal tissue appearance and hence violates algorithmic assumptions for standard approaches to brain extraction; consequently, the brain may not be correctly extracted. This paper proposes a brain extraction approach which can explicitly account for pathologies by jointly modeling normal tissue appearance and pathologies. Specifically, our model uses a three-part image decomposition: (1) normal tissue appearance is captured by principal component analysis (PCA), (2) pathologies are captured via a total variation term, and (3) the skull and surrounding tissue is captured by a sparsity term. Due to its convexity, the resulting decomposition model allows for efficient optimization. Decomposition and image registration steps are alternated to allow statistical modeling of normal tissue appearance in a fixed atlas coordinate system. As a beneficial side effect, the decomposition model allows for the identification of potentially pathological areas and the reconstruction of a quasi-normal image in atlas space. We demonstrate the effectiveness of our approach on four datasets: the publicly available IBSR and LPBA40 datasets which show normal image appearance, the BRATS dataset containing images with brain tumors, and a dataset containing clinical TBI images. We compare the performance with other popular brain extraction models: ROBEX, BEaST, MASS, BET, BSE and a recently proposed deep learning approach. Our model performs better than these competing approaches on all four datasets. Specifically, our model achieves the best median (97.11) and mean (96.88) Dice scores over all datasets. The two best performing competitors, ROBEX and MASS, achieve scores of 96.23/95.62 and 96.67/94.25 respectively. Hence, our approach is an effective method for high quality brain extraction for a wide variety of images. Copyright © 2018 Elsevier Inc. All rights reserved.

A Brief Account of Nanoparticle Contrast Agents for Photoacoustic Imaging

PubMed Central

Pan, Dipanjan; Kim, Benjamin; Wang, Lihong V.; Lanza, Gregory M

2014-01-01

Photoacoustic imaging (PAI) is a hybrid, nonionizing modality offering excellent spatial resolution, deep penetration, and high soft tissue contrast. In PAI, signal is generated based on the absorption of laser-generated optical energy by endogenous tissues or exogenous contrast agents leading to acoustic emissions detected by an ultrasound transducer. Research in this area over the years has shown that PAI has the ability to provide both physiological and molecular imaging, which can be viewed alone or used in a hybrid modality fashion to extend the anatomic and hemodynamic sensitivities of clinical ultrasound. PAI may be performed using inherent contrast afforded by light absorbing molecules such as hemoglobin, myoglobin, and melanin or exogenous small molecule contrast agent such as near infrared dyes and porphyrins. However, this review summarizes the potential of exogenous nanoparticle-based agents for PAI applications including contrast based on gold particles, carbon nanotubes, and encapsulated copper compounds. PMID:23983210

Imaging Ultrasound Guidance and on-line Estimation of Thermal Behavior in HIFU Exposed Targets

NASA Astrophysics Data System (ADS)

Chauhan, Sunita; Haryanto, Amir

2006-05-01

Elevated temperatures have been used for many years to combat several diseases including treatment of certain types of cancers/tumors. High Intensity Focused Ultrasound (HIFU) has emerged as a potential non-invasive modality for trackless targeting of deep-seated cancers of human body. For the procedures which require thermal elevation such as hyperthermia and tissue ablation, temperature becomes a parameter of vital importance in order to monitor the treatment on-line. Also, embedding invasive temperature probes for this purpose beats the supremacy of the non-invasive ablating modality. In this paper, we describe the use of a non-invasive and inexpensive conventional imaging ultrasound modality for lesion positioning and estimation of thermal behavior of the tissue on exposure to HIFU. Representative results of our online lesion tracking algorithm for discerning lesioning behavior using image capture, processing and phase-shift measurements are presented.

Detection of soft tissue densities from digital breast tomosynthesis: comparison of conventional and deep learning approaches

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Haldankar, Hrishikesh; Hoffmeister, Jeffrey W.; Periaswamy, Senthil

2016-03-01

Computer-aided detection (CAD) has been used in screening mammography for many years and is likely to be utilized for digital breast tomosynthesis (DBT). Higher detection performance is desirable as it may have an impact on radiologist's decisions and clinical outcomes. Recently the algorithms based on deep convolutional architectures have been shown to achieve state of the art performance in object classification and detection. Similarly, we trained a deep convolutional neural network directly on patches sampled from two-dimensional mammography and reconstructed DBT volumes and compared its performance to a conventional CAD algorithm that is based on computation and classification of hand-engineered features. The detection performance was evaluated on the independent test set of 344 DBT reconstructions (GE SenoClaire 3D, iterative reconstruction algorithm) containing 328 suspicious and 115 malignant soft tissue densities including masses and architectural distortions. Detection sensitivity was measured on a region of interest (ROI) basis at the rate of five detection marks per volume. Moving from conventional to deep learning approach resulted in increase of ROI sensitivity from 0:832 +/- 0:040 to 0:893 +/- 0:033 for suspicious ROIs; and from 0:852 +/- 0:065 to 0:930 +/- 0:046 for malignant ROIs. These results indicate the high utility of deep feature learning in the analysis of DBT data and high potential of the method for broader medical image analysis tasks.

Real-Time Color-Doppler Guidance of HIFU for the Selective Avoidance or Occlusion of Blood Vessels

NASA Astrophysics Data System (ADS)

Rabkin, Brian A.; Zderic, Vesna; Vaezy, Shahram

2005-03-01

High-intensity focused ultrasound (HIFU) has been shown to effectively occlude blood vessels deep within tissue. The objective of the current study was to synchronize HIFU and color-Doppler ultrasound (US) for the real-time visualization of flow within blood vessels during HIFU treatment. The excitation of the HIFU was synchronized with the color-Doppler imager by collecting the excitation pulses of one of the elements of either a curved array intracavitary (C 9-5) or an intraoperative (CL 10-5) imaging probe. The collected excitation pulse was converted into a TTL-high pulse, which was delayed and gated to time the excitation duration and location of the HIFU pulse with respect to each imaging frame. The single pulse was used to drive a 3.2 MHz concave HIFU transducer (focal length of 3.5 cm, f-number 1) while the US imager was not collecting RF signals from the treatment region of the US image. The feasibility of the system was demonstrated in vivo by the selective ablation of tissue adjacent to, or the occlusion of, large vessels (including the femoral artery) both transcutaneously and interoperatively in the rabbit and pig. For the occlusion of vessels, the HIFU focus was placed immediately distal (with respect to the transducer) to the vessel at a depth of 2-2.5 cm. HIFU was applied at in situ intensities of 1000-2000 W/cm2, at a duty cycle of 50-75%, and a HIFU pulse repetition frequency (set by the US image frame rate) of 6-18 Hz. During each HIFU exposure, the HIFU pulse resulted in color interference bands running vertically within the color-Doppler window. Through the synchronization of the US imager with the HIFU excitation, the location and duration of the interference bands were set outside the treatment region within each image frame. This provided the operator with a clear view of the HIFU treatment site during therapy. Gross assessment showed necrosis of the tissue surrounding the HIFU treated vessel and occlusion of vessels up to 4 mm in diameter after a 30 s HIFU exposure. We have developed a method of synchronizing pulsed HIFU with color-Doppler US imaging for the real-time visualization of flow within blood vessels during HIFU therapy. This provides a means of guiding HIFU therapy for the detection and occlusion of deep vessels, or the selective ablation of tissue surrounding the vessels without vascular occlusion.

New Details of the Human Corneal Limbus Revealed With Second Harmonic Generation Imaging.

PubMed

Park, Choul Yong; Lee, Jimmy K; Zhang, Cheng; Chuck, Roy S

2015-09-01

To report novel findings of the human corneal limbus by using second harmonic generation (SHG) imaging. Corneal limbus was imaged by using an inverted two-photon excitation fluorescence microscope. Laser (Ti:Sapphire) was tuned at 850 nm for two-photon excitation. Backscatter signals of SHG and autofluorescence (AF) were collected through a 425/30-nm emission filter and a 525/45-emission filter, respectively. Multiple, consecutive, and overlapping image stacks (z-stack) were acquired for the corneal limbal area. Two novel collagen structures were revealed by SHG imaging at the limbus: an anterior limbal cribriform layer and presumed anchoring fibers. Anterior limbal cribriform layer is an intertwined reticular collagen architecture just beneath the limbal epithelial niche and is located between the peripheral cornea and Tenon's/scleral tissue. Autofluorescence imaging revealed high vascularity in this structure. Central to the anterior limbal cribriform layer, radial strands of collagen were found to connect the peripheral cornea to the limbus. These presumed anchoring fibers have both collagen and elastin and were found more extensively in the superficial layers than deep layer and were absent in very deep limbus near Schlemm's canal. By using SHG imaging, new details of the collagen architecture of human corneal limbal area were elucidated. High resolution images with volumetric analysis revealed two novel collagen structures.

A new method for the noninvasive determination of abdominal muscle feedforward activity based on tissue velocity information from tissue Doppler imaging.

PubMed

Mannion, A F; Pulkovski, N; Schenk, P; Hodges, P W; Gerber, H; Loupas, T; Gorelick, M; Sprott, H

2008-04-01

Rapid arm movements elicit anticipatory activation of the deep-lying abdominal muscles; this appears modified in back pain, but the invasive technique used for its assessment [fine-wire electromyography (EMG)] has precluded its widespread investigation. We examined whether tissue-velocity changes recorded with ultrasound (M-mode) tissue Doppler imaging (TDI) provided a viable noninvasive alternative. Fourteen healthy subjects rapidly flexed, extended, and abducted the shoulder; recordings were made of medial deltoid (MD) surface EMG and of fine-wire EMG and TDI tissue-velocity changes of the contralateral transversus abdominis, obliquus internus, and obliquus externus. Muscle onsets were determined by blinded visual analysis of EMG and TDI data. TDI could not distinguish between the relative activation of the three muscles, so in subsequent analyses only the onset of the earliest abdominal muscle activity was used. The latter occurred <50 ms after the onset of medial deltoid EMG (i.e., was feedforward) and correlated with the corresponding EMG onsets (r = 0.47, P < 0.0001). The mean difference between methods was 20 ms and was likely explained by electromechanical delay; limits of agreement were wide (-40 to +80 ms) but no greater than those typical of repeated measurements using either technique. The between-day standard error of measurement of the TDI onsets (examined in 16 further subjects) was 16 ms. TDI yielded reliable and valid measures of the earliest onset of feedforward activity within the anterolateral abdominal muscle group. The method can be used to assess muscle dysfunction in large groups of back-pain patients and may also be suitable for the noninvasive analysis of other deep-lying or small/thin muscles.

NIR DLP hyperspectral imaging system for medical applications

NASA Astrophysics Data System (ADS)

Wehner, Eleanor; Thapa, Abhas; Livingston, Edward; Zuzak, Karel

2011-03-01

DLP® hyperspectral reflectance imaging in the visible range has been previously shown to quantify hemoglobin oxygenation in subsurface tissues, 1 mm to 2 mm deep. Extending the spectral range into the near infrared reflects biochemical information from deeper subsurface tissues. Unlike any other illumination method, the digital micro-mirror device, DMD, chip is programmable, allowing the user to actively illuminate with precisely predetermined spectra of illumination with a minimum bandpass of approximately 10 nm. It is possible to construct active spectral-based illumination that includes but is not limited to containing sharp cutoffs to act as filters or forming complex spectra, varying the intensity of light at discrete wavelengths. We have characterized and tested a pure NIR, 760 nm to 1600 nm, DLP hyperspectral reflectance imaging system. In its simplest application, the NIR system can be used to quantify the percentage of water in a subject, enabling edema visualization. It can also be used to map vein structure in a patient in real time. During gall bladder surgery, this system could be invaluable in imaging bile through fatty tissue, aiding surgeons in locating the common bile duct in real time without injecting any contrast agents.

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

PubMed

Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

2017-08-01

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Segmentation of the Globus Pallidus Internus Using Probabilistic Diffusion Tractography for Deep Brain Stimulation Targeting in Parkinson Disease.

PubMed

Middlebrooks, E H; Tuna, I S; Grewal, S S; Almeida, L; Heckman, M G; Lesser, E R; Foote, K D; Okun, M S; Holanda, V M

2018-06-01

Although globus pallidus internus deep brain stimulation is a widely accepted treatment for Parkinson disease, there is persistent variability in outcomes that is not yet fully understood. In this pilot study, we aimed to investigate the potential role of globus pallidus internus segmentation using probabilistic tractography as a supplement to traditional targeting methods. Eleven patients undergoing globus pallidus internus deep brain stimulation were included in this retrospective analysis. Using multidirection diffusion-weighted MR imaging, we performed probabilistic tractography at all individual globus pallidus internus voxels. Each globus pallidus internus voxel was then assigned to the 1 ROI with the greatest number of propagated paths. On the basis of deep brain stimulation programming settings, the volume of tissue activated was generated for each patient using a finite element method solution. For each patient, the volume of tissue activated within each of the 10 segmented globus pallidus internus regions was calculated and examined for association with a change in the Unified Parkinson Disease Rating Scale, Part III score before and after treatment. Increasing volume of tissue activated was most strongly correlated with a change in the Unified Parkinson Disease Rating Scale, Part III score for the primary motor region (Spearman r = 0.74, P = .010), followed by the supplementary motor area/premotor cortex (Spearman r = 0.47, P = .15). In this pilot study, we assessed a novel method of segmentation of the globus pallidus internus based on probabilistic tractography as a supplement to traditional targeting methods. Our results suggest that our method may be an independent predictor of deep brain stimulation outcome, and evaluation of a larger cohort or prospective study is warranted to validate these findings. © 2018 by American Journal of Neuroradiology.

Magneto-optical nanoparticles for cyclic magnetomotive photoacoustic imaging

NASA Astrophysics Data System (ADS)

Arnal, Bastien; Yoon, Soon Joon; Li, Junwei; Gao, Xiaohu; O'Donnell, Matthew

2018-05-01

Photoacoustic imaging is a highly promising tool to visualize molecular events with deep tissue penetration. Like most other modalities, however, image contrast under in vivo conditions is far from optimal due to background signals from tissue. Using iron oxide-gold core-shell nanoparticles, we previously demonstrated that magnetomotive photoacoustic (mmPA) imaging can dramatically reduce the influence of background signals and produce high-contrast molecular images. Here we report two significant advances toward clinical translation of this technology. First, we introduce a new class of compact, uniform, magneto-optically coupled core-shell nanoparticle, prepared through localized copolymerization of polypyrrole (PPy) on an iron oxide nanoparticle surface. The resulting iron oxide-PPy nanoparticles solve the photo-instability and small-scale synthesis problems previously encountered by the gold coating approach, and extend the large optical absorption coefficient of the particles beyond 1000 nm in wavelength. In parallel, we have developed a new generation of mmPA imaging featuring cyclic magnetic motion and ultrasound speckle tracking, with an image capture frame rate several hundred times faster than the photoacoustic speckle tracking method demonstrated previously. These advances enable robust artifact elimination caused by physiologic motion and first application of the mmPA technology in vivo for sensitive tumor imaging.

Real-Time Monitoring of Singlet Oxygen and Oxygen Partial Pressure During the Deep Photodynamic Therapy In Vitro.

PubMed

Li, Weitao; Huang, Dong; Zhang, Yan; Liu, Yangyang; Gu, Yueqing; Qian, Zhiyu

2016-09-01

Photodynamic therapy (PDT) is an effective noninvasive method for the tumor treatment. The major challenge in current PDT research is how to quantitatively evaluate therapy effects. To our best knowledge, this is the first time to combine multi-parameter detection methods in PDT. More specifically, we have developed a set of system, including the high-sensitivity measurement of singlet oxygen, oxygen partial pressure and fluorescence image. In this paper, the detection ability of the system was validated by the different concentrations of carbon quantum dots. Moreover, the correlation between singlet oxygen and oxygen partial pressure with laser irradiation was observed. Then, the system could detect the signal up to 0.5 cm tissue depth with 660 nm irradiation and 1 cm tissue depth with 980 nm irradiation by using up-conversion nanoparticles during PDT in vitro. Furthermore, we obtained the relationship among concentration of singlet oxygen, oxygen partial pressure and tumor cell viability under certain conditions. The results indicate that the multi-parameter detection system is a promising asset to evaluate the deep tumor therapy during PDT. Moreover, the system might be potentially used for the further study in biology and molecular imaging.

Classification of C2C12 cells at differentiation by convolutional neural network of deep learning using phase contrast images.

PubMed

Niioka, Hirohiko; Asatani, Satoshi; Yoshimura, Aina; Ohigashi, Hironori; Tagawa, Seiichi; Miyake, Jun

2018-01-01

In the field of regenerative medicine, tremendous numbers of cells are necessary for tissue/organ regeneration. Today automatic cell-culturing system has been developed. The next step is constructing a non-invasive method to monitor the conditions of cells automatically. As an image analysis method, convolutional neural network (CNN), one of the deep learning method, is approaching human recognition level. We constructed and applied the CNN algorithm for automatic cellular differentiation recognition of myogenic C2C12 cell line. Phase-contrast images of cultured C2C12 are prepared as input dataset. In differentiation process from myoblasts to myotubes, cellular morphology changes from round shape to elongated tubular shape due to fusion of the cells. CNN abstract the features of the shape of the cells and classify the cells depending on the culturing days from when differentiation is induced. Changes in cellular shape depending on the number of days of culture (Day 0, Day 3, Day 6) are classified with 91.3% accuracy. Image analysis with CNN has a potential to realize regenerative medicine industry.

Detecting occlusion inside a ventricular catheter using photoacoustic imaging through skull

NASA Astrophysics Data System (ADS)

Tavakoli, Behnoosh; Guo, Xiaoyu; Taylor, Russell H.; Kang, Jin U.; Boctor, Emad M.

2014-03-01

Ventricular catheters are used to treat hydrocephalus by diverting the excess of the cerebrospinal fluid (CSF) to the reabsorption site so as to regulate the intracranial pressure. The failure rate of these shunts is extremely high due to the ingrown tissue that blocks the CSF flow. We have studied a method to image the occlusion inside the shunt through the skull. In this approach the pulsed laser light coupled to the optical fiber illuminate the occluding tissue inside the catheter and an external ultrasound transducer is applied to detect the generated photoacoustic signal. The feasibility of this method is investigated using a phantom made of ovis aries brain tissue and adult human skull. We were able to image the target inside the shunt located 20mm deep inside the brain through about 4mm thick skull bone. This study could lead to the development of a simple, safe and non-invasive device for percutaneous restoration of patency to occluded shunts. This will eliminate the need of the surgical replacement of the occluded catheters which expose the patients to risks including hemorrhage and brain injury.

The effect of adjunctive noncontact low frequency ultrasound on deep tissue pressure injury.

PubMed

Honaker, Jeremy S; Forston, Michael R; Davis, Emily A; Weisner, Michelle M; Morgan, Jennifer A; Sacca, Emily

2016-11-01

The optimal treatment for deep tissue pressure injuries has not been determined. Deep tissue pressure injuries represent a more ominous early stage pressure injury that may evolve into full thickness ulceration despite implementing the standard of care for pressure injury. A longitudinal prospective historical case control study design was used to determine the effectiveness of noncontact low frequency ultrasound plus standard of care (treatment group) in comparison to standard of care (control group) in reducing deep tissue pressure injury severity, total surface area, and final pressure injury stage. The Honaker Suspected Deep Tissue Injury Severity Scale (range 3-18[more severe]) was used to determine deep tissue pressure injury severity at enrollment (Time 1) and discharge (Time 2). A total of 60 subjects (Treatment = 30; Control= 30) were enrolled in the study. In comparison to the control group mean deep tissue pressure injury total surface area change at Time 2 (0.3 cm 2 ), the treatment group had a greater decrease (8.8 cm 2 ) that was significant (t = 2.41, p = 0.014, r 2  = 0.10). In regards to the Honaker Suspected Deep Tissue Injury Severity Scale scores, the treatment group had a significantly lower score (7.6) in comparison to the control group (11.9) at time 2, with a mean difference of 4.6 (t = 6.146, p = 0.0001, r 2  = 0.39). When considering the final pressure ulcer stage at Time 2, the control group were mostly composed of unstageable pressure ulcer (57%) and deep tissue pressure injury severity (27%). In contrast, the treatment group final pressure ulcer stages were less severe and were mostly composed of stage 2 pressure injury (50%) and deep tissue pressure injury severity (23%) were the most common at time 2. The results of this study have shown that deep tissue pressure injury severity treated with noncontact low frequency ultrasound within 5 days of onset and in conjunction with standard of care may improve outcomes as compared to standard of care only. © 2016 by the Wound Healing Society.

Shedding Light on Nanomedicine

PubMed Central

Tong, Rong

2012-01-01

Light is electromagnetic radiation that can convert its energy into different forms (e.g., heat, chemical energy, and acoustic waves). This property has been exploited in phototherapy (e.g., photothermal therapy and photodynamic therapy) and optical imaging (e.g., fluorescence imaging) for therapeutic and diagnostic purposes. Light-controlled therapies can provide minimally or non-invasive spatiotemporal control as well as deep tissue penetration. Nanotechnology provides a numerous advantages, including selective targeting of tissues, prolongation of therapeutic effect, protection of active payloads, and improved therapeutic indices. This review explores the advances that nanotechnology can bring to light-based therapies and diagnostics, and vice versa, including photo-triggered systems, nanoparticles containing photoactive molecules, and nanoparticles that are themselves photoactive. Limitations of light-based therapies such as photic injury and phototoxicity will be discussed. PMID:22887840

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data.

PubMed

He, Jiuming; Huang, Luojiao; Tian, Runtao; Li, Tiegang; Sun, Chenglong; Song, Xiaowei; Lv, Yiwei; Luo, Zhigang; Li, Xin; Abliz, Zeper

2018-07-26

Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Sensitive red protein calcium indicators for imaging neural activity

PubMed Central

Dana, Hod; Mohar, Boaz; Sun, Yi; Narayan, Sujatha; Gordus, Andrew; Hasseman, Jeremy P; Tsegaye, Getahun; Holt, Graham T; Hu, Amy; Walpita, Deepika; Patel, Ronak; Macklin, John J; Bargmann, Cornelia I; Ahrens, Misha B; Schreiter, Eric R; Jayaraman, Vivek; Looger, Loren L; Svoboda, Karel; Kim, Douglas S

2016-01-01

Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging. DOI: http://dx.doi.org/10.7554/eLife.12727.001 PMID:27011354

High-speed time-reversed ultrasonically encoded (TRUE) optical focusing inside dynamic scattering media at 793 nm

NASA Astrophysics Data System (ADS)

Liu, Yan; Lai, Puxiang; Ma, Cheng; Xu, Xiao; Suzuki, Yuta; Grabar, Alexander A.; Wang, Lihong V.

2014-03-01

Time-reversed ultrasonically encoded (TRUE) optical focusing is an emerging technique that focuses light deep into scattering media by phase-conjugating ultrasonically encoded diffuse light. In previous work, the speed of TRUE focusing was limited to no faster than 1 Hz by the response time of the photorefractive phase conjugate mirror, or the data acquisition and streaming speed of the digital camera; photorefractive-crystal-based TRUE focusing was also limited to the visible spectral range. These time-consuming schemes prevent this technique from being applied in vivo, since living biological tissue has a speckle decorrelation time on the order of a millisecond. In this work, using a Tedoped Sn2P2S6 photorefractive crystal at a near-infrared wavelength of 793 nm, we achieved TRUE focusing inside dynamic scattering media having a speckle decorrelation time as short as 7.7 ms. As the achieved speed approaches the tissue decorrelation rate, this work is an important step forward toward in vivo applications of TRUE focusing in deep tissue imaging, photodynamic therapy, and optical manipulation.

Tissue microstructure estimation using a deep network inspired by a dictionary-based framework.

PubMed

Ye, Chuyang

2017-12-01

Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies. It models the diffusion signal with three compartments that are characterized by distinct diffusion properties, and the parameters in the model describe tissue microstructure. In NODDI, these parameters are estimated in a maximum likelihood framework, where the nonlinear model fitting is computationally intensive. Therefore, efforts have been made to develop efficient and accurate algorithms for NODDI microstructure estimation, which is still an open problem. In this work, we propose a deep network based approach that performs end-to-end estimation of NODDI microstructure, which is named Microstructure Estimation using a Deep Network (MEDN). MEDN comprises two cascaded stages and is motivated by the AMICO algorithm, where the NODDI microstructure estimation is formulated in a dictionary-based framework. The first stage computes the coefficients of the dictionary. It resembles the solution to a sparse reconstruction problem, where the iterative process in conventional estimation approaches is unfolded and truncated, and the weights are learned instead of predetermined by the dictionary. In the second stage, microstructure properties are computed from the output of the first stage, which resembles the weighted sum of normalized dictionary coefficients in AMICO, and the weights are also learned. Because spatial consistency of diffusion signals can be used to reduce the effect of noise, we also propose MEDN+, which is an extended version of MEDN. MEDN+ allows incorporation of neighborhood information by inserting a stage with learned weights before the MEDN structure, where the diffusion signals in the neighborhood of a voxel are processed. The weights in MEDN or MEDN+ are jointly learned from training samples that are acquired with diffusion gradients densely sampling the q-space. We performed MEDN and MEDN+ on brain dMRI scans, where two shells each with 30 gradient directions were used, and measured their accuracy with respect to the gold standard. Results demonstrate that the proposed networks outperform the competing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Endoscopic probe optics for spectrally encoded confocal microscopy.

PubMed

Kang, Dongkyun; Carruth, Robert W; Kim, Minkyu; Schlachter, Simon C; Shishkov, Milen; Woods, Kevin; Tabatabaei, Nima; Wu, Tao; Tearney, Guillermo J

2013-01-01

Spectrally encoded confocal microscopy (SECM) is a form of reflectance confocal microscopy that can achieve high imaging speeds using relatively simple probe optics. Previously, the feasibility of conducting large-area SECM imaging of the esophagus in bench top setups has been demonstrated. Challenges remain, however, in translating SECM into a clinically-useable device; the tissue imaging performance should be improved, and the probe size needs to be significantly reduced so that it can fit into luminal organs of interest. In this paper, we report the development of new SECM endoscopic probe optics that addresses these challenges. A custom water-immersion aspheric singlet (NA = 0.5) was developed and used as the objective lens. The water-immersion condition was used to reduce the spherical aberrations and specular reflection from the tissue surface, which enables cellular imaging of the tissue deep below the surface. A custom collimation lens and a small-size grating were used along with the custom aspheric singlet to reduce the probe size. A dual-clad fiber was used to provide both the single- and multi- mode detection modes. The SECM probe optics was made to be 5.85 mm in diameter and 30 mm in length, which is small enough for safe and comfortable endoscopic imaging of the gastrointestinal tract. The lateral resolution was 1.8 and 2.3 µm for the single- and multi- mode detection modes, respectively, and the axial resolution 11 and 17 µm. SECM images of the swine esophageal tissue demonstrated the capability of this device to enable the visualization of characteristic cellular structural features, including basal cell nuclei and papillae, down to the imaging depth of 260 µm. These results suggest that the new SECM endoscopic probe optics will be useful for imaging large areas of the esophagus at the cellular scale in vivo.

Cartilage T2 assessment: differentiation of normal hyaline cartilage and reparative tissue after arthroscopic cartilage repair in equine subjects.

PubMed

White, Lawrence M; Sussman, Marshall S; Hurtig, Mark; Probyn, Linda; Tomlinson, George; Kandel, Rita

2006-11-01

To prospectively assess T2 mapping characteristics of normal articular cartilage and of cartilage at sites of arthroscopic repair, including comparison with histologic results and collagen organization assessed at polarized light microscopy (PLM). Study protocol was compliant with the Canadian Council on Animal Care Guidelines and approved by the institutional animal care committee. Arthroscopic osteochondral autograft transplantation (OAT) and microfracture arthroplasty (MFx) were performed in knees of 10 equine subjects (seven female, three male; age range, 3-5 years). A site of arthroscopically normal cartilage was documented in each joint as a control site. Joints were harvested at 12 (n = 5) and 24 (n = 5) weeks postoperatively and were imaged at 1.5-T magnetic resonance (MR) with a 10-echo sagittal fast spin-echo acquisition. T2 maps of each site (21 OAT harvest, 10 MFx, 12 OAT plug, and 10 control sites) were calculated with linear least-squares curve fitting. Cartilage T2 maps were qualitatively graded as "organized" (normal transition of low-to-high T2 signal from deep to superficial cartilage zones) or "disorganized." Quantitative mean T2 values were calculated for deep, middle, and superficial cartilage at each location. Results were compared with histologic and PLM assessments by using kappa analysis. T2 maps were qualitatively graded as organized at 20 of 53 sites and as disorganized at 33 sites. Perfect agreement was seen between organized T2 and histologic findings of hyaline cartilage and between disorganized T2 and histologic findings of fibrous reparative tissue (kappa = 1.0). Strong agreement was seen between organized T2 and normal PLM findings and between disorganized T2 and abnormal PLM findings (kappa = .92). Quantitative assessment of the deep, middle, and superficial cartilage, respectively, showed mean T2 values of 53.3, 58.6, and 54.9 msec at reparative fibrous tissue sites and 40.7, 53.6, and 61.6 msec at hyaline cartilage sites. A significant trend of increasing T2 values (from deep to superficial) was found in hyaline cartilage (P < .01). Fibrous tissue sites had no significant change with depth (P > .59). Qualitative and quantitative T2 mapping helped differentiate hyaline cartilage from reparative fibrocartilage after cartilage repair at 1.5-T MR imaging.

Ultrahigh resolution optical coherence elastography combined with a rigid micro-endoscope (Conference Presentation)

NASA Astrophysics Data System (ADS)

Fang, Qi; Curatolo, Andrea; Wijesinghe, Philip; Hamzah, Juliana; Ganss, Ruth; Noble, Peter B.; Karnowski, Karol; Sampson, David D.; Kim, Jun Ki; Lee, Wei M.; Kennedy, Brendan F.

2017-02-01

The mechanical forces that living cells experience represent an important framework in the determination of a range of intricate cellular functions and processes. Current insight into cell mechanics is typically provided by in vitro measurement systems; for example, atomic force microscopy (AFM) measurements are performed on cells in culture or, at best, on freshly excised tissue. Optical techniques, such as Brillouin microscopy and optical elastography, have been used for ex vivo and in situ imaging, recently achieving cellular-scale resolution. The utility of these techniques in cell mechanics lies in quick, three-dimensional and label-free mechanical imaging. Translation of these techniques toward minimally invasive in vivo imaging would provide unprecedented capabilities in tissue characterization. Here, we take the first steps along this path by incorporating a gradient-index micro-endoscope into an ultrahigh resolution optical elastography system. Using this endoscope, a lateral resolution of 2 µm is preserved over an extended depth-of-field of 80 µm, achieved by Bessel beam illumination. We demonstrate this combined system by imaging stiffness of a silicone phantom containing stiff inclusions and a freshly excised murine liver tissue. Additionally, we test this system on murine ribs in situ. We show that our approach can provide high quality extended depth-of-field images through an endoscope and has the potential to measure cell mechanics deep in tissue. Eventually, we believe this tool will be capable of studying biological processes and disease progression in vivo.

Histology-validated x-ray tomography for imaging human coronary arteries

NASA Astrophysics Data System (ADS)

Buscema, Marzia; Schulz, Georg; Deyhle, Hans; Khimchenko, Anna; Matviykiv, Sofiya; Holme, Margaret N.; Hipp, Alexander; Beckmann, Felix; Saxer, Till; Michaud, Katarzyna; Müller, Bert

2016-10-01

Heart disease is the number one cause of death worldwide. To improve therapy and patient outcome, the knowledge of anatomical changes in terms of lumen morphology and tissue composition of constricted arteries is crucial for designing a localized drug delivery to treat atherosclerosis disease. Traditional tissue characterization by histology is a pivotal tool, although it brings disadvantages such as vessel morphology modification during decalcification and slicing. X-ray tomography in absorption and phase contrast modes yields a deep understanding in blood vessel anatomy in healthy and diseased stages: measurements in absorption mode make visible highly absorbing tissue components including cholesterol plaques, whereas phase contrast tomography gains better contrast of the soft tissue components such as vessel walls. Established synchrotron radiation-based micro-CT techniques ensure high performance in terms of 3D visualization of highly absorbing and soft tissues.

Comparison of PA imaging by narrow beam scanning and one-shot broad beam excitation

NASA Astrophysics Data System (ADS)

Xia, Jinjun; Wei, Chen-Wei; Huang, Lingyun; Pelivanov, I. M.; O'Donnell, Matthew

2011-03-01

Current systems designed for deep photoacoustic (PA) imaging typically use a low repetition rate, high power pulsed laser to provide a ns-scale pulse illuminating a large tissue volume. Acoustic signals recorded on each laser firing can be used to reconstruct a complete 2-D (3-D) image of sources of heat release within that region. Using broad-beam excitation, the maximum frame rate of the imaging system is restricted by the pulse repetition rate of the laser. An alternate illumination approach is proposed based on fast scanning by a low energy (~ 1 mJ) high repetition rate (up to a few kHz) narrow laser beam (~1 mm) along the tissue surface over a region of interest. A final PA image is produced from the summation of individual PA images reconstructed at each laser beam position. This concept can take advantage of high repetition rate fiber lasers to create PA images with much higher frame rates than current systems, enabling true real-time integration of photoacoustics with ultrasound imaging. As an initial proof of concept, we compare conventional broad beam illumination to a scanned beam approach in a simple model system. Two transparent teflon tubes with diameters of 1.6 mm and 0.8 mm were filled with ink having an absorption coefficient of 5 cm-1. These tubes were buried inside chicken breast tissue acting as an optical scattering medium. They were separated by 3 mm or 10 mm to test spatial and contrast resolution for the two scan formats. The excitation wavelength was 700 nm. The excitation source is a traditional OPO pumped by a Q-switched Nd:YAG laser with doubler. Photoacoustic images were reconstructed using signals from a small, scanned PVDF transducer acting as an acoustic array. Two different illumination schemes were compared: one was 15 mm x 10 mm in cross section and acted as the broad beam; the other was 5 mm x 2 mm in cross section (15 times smaller than the broad beam case) and was scanned over an area equivalent to broad beam illumination. Multiple images obtained during narrow beam scanning were added together to form one PA image equivalent to the single-shot broad beam one. Results of the phantom study indicate that PA images formed by narrow beam scanning excitation can be equivalent to one shot broad beam illumination in signal to noise ratio and spatial resolution. Future studies will focus on high repetition-rate laser sources and scan formats appropriate for real-time, integrated deep photoacoustic/ultrasonic imaging.

Fast subsurface fingerprint imaging with full-field optical coherence tomography system equipped with a silicon camera.

PubMed

Auksorius, Egidijus; Boccara, A Claude

2017-09-01

Images recorded below the surface of a finger can have more details and be of higher quality than the conventional surface fingerprint images. This is particularly true when the quality of the surface fingerprints is compromised by, for example, moisture or surface damage. However, there is an unmet need for an inexpensive fingerprint sensor that is able to acquire high-quality images deep below the surface in short time. To this end, we report on a cost-effective full-field optical coherent tomography system comprised of a silicon camera and a powerful near-infrared LED light source. The system, for example, is able to record 1.7  cm×1.7  cmen face images in 0.12 s with the spatial sampling rate of 2116 dots per inch and the sensitivity of 93 dB. We show that the system can be used to image internal fingerprints and sweat ducts with good contrast. Finally, to demonstrate its biometric performance, we acquired subsurface fingerprint images from 240 individual fingers and estimated the equal-error-rate to be ∼0.8%. The developed instrument could also be used in other en face deep-tissue imaging applications because of its high sensitivity, such as in vivo skin imaging. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Sensory processing of deep tissue nociception in the rat spinal cord and thalamic ventrobasal complex.

PubMed

Sikandar, Shafaq; West, Steven J; McMahon, Stephen B; Bennett, David L; Dickenson, Anthony H

2017-07-01

Sensory processing of deep somatic tissue constitutes an important component of the nociceptive system, yet associated central processing pathways remain poorly understood. Here, we provide a novel electrophysiological characterization and immunohistochemical analysis of neural activation in the lateral spinal nucleus (LSN). These neurons show evoked activity to deep, but not cutaneous, stimulation. The evoked responses of neurons in the LSN can be sensitized to somatosensory stimulation following intramuscular hypertonic saline, an acute model of muscle pain, suggesting this is an important spinal relay site for the processing of deep tissue nociceptive inputs. Neurons of the thalamic ventrobasal complex (VBC) mediate both cutaneous and deep tissue sensory processing, but in contrast to the lateral spinal nucleus our electrophysiological studies do not suggest the existence of a subgroup of cells that selectively process deep tissue inputs. The sensitization of polymodal and thermospecific VBC neurons to mechanical somatosensory stimulation following acute muscle stimulation with hypertonic saline suggests differential roles of thalamic subpopulations in mediating cutaneous and deep tissue nociception in pathological states. Overall, our studies at both the spinal (lateral spinal nucleus) and supraspinal (thalamic ventrobasal complex) levels suggest a convergence of cutaneous and deep somatosensory inputs onto spinothalamic pathways, which are unmasked by activation of muscle nociceptive afferents to produce consequent phenotypic alterations in spinal and thalamic neural coding of somatosensory stimulation. A better understanding of the sensory pathways involved in deep tissue nociception, as well as the degree of labeled line and convergent pathways for cutaneous and deep somatosensory inputs, is fundamental to developing targeted analgesic therapies for deep pain syndromes. © 2017 University College London. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

Nonlinear adaptive optics: aberration correction in three photon fluorescence microscopy for mouse brain imaging

NASA Astrophysics Data System (ADS)

Sinefeld, David; Paudel, Hari P.; Wang, Tianyu; Wang, Mengran; Ouzounov, Dimitre G.; Bifano, Thomas G.; Xu, Chris

2017-02-01

Multiphoton fluorescence microscopy is a well-established technique for deep-tissue imaging with subcellular resolution. Three-photon microscopy (3PM) when combined with long wavelength excitation was shown to allow deeper imaging than two-photon microscopy (2PM) in biological tissues, such as mouse brain, because out-of-focus background light can be further reduced due to the higher order nonlinear excitation. As was demonstrated in 2PM systems, imaging depth and resolution can be improved by aberration correction using adaptive optics (AO) techniques which are based on shaping the scanning beam using a spatial light modulator (SLM). In this way, it is possible to compensate for tissue low order aberration and to some extent, to compensate for tissue scattering. Here, we present a 3PM AO microscopy system for brain imaging. Soliton self-frequency shift is used to create a femtosecond source at 1675 nm and a microelectromechanical (MEMS) SLM serves as the wavefront shaping device. We perturb the 1020 segment SLM using a modified nonlinear version of three-point phase shifting interferometry. The nonlinearity of the fluorescence signal used for feedback ensures that the signal is increasing when the spot size decreases, allowing compensation of phase errors in an iterative optimization process without direct phase measurement. We compare the performance for different orders of nonlinear feedback, showing an exponential growth in signal improvement as the nonlinear order increases. We demonstrate the impact of the method by applying the 3PM AO system for in-vivo mouse brain imaging, showing improvement in signal at 1-mm depth inside the brain.

Intraoperative MR-guided DBS implantation for treating PD and ET

NASA Astrophysics Data System (ADS)

Liu, Haiying; Maxwell, Robert E.; Truwit, Charles L.

2001-05-01

Deep brain stimulator (DBS) implantation is a promising treatment alternative for suppressing the motor tremor symptoms in Parkinson disease (PD) patient. The main objective is to develop a minimally invasive approach using high spatial resolution and soft-tissue contrast MR imaging techniques to guide the surgical placement of DBS. In the MR-guided procedure, the high spatial resolution MR images were obtained intra-operatively and used to target stereotactically a specific deep brain location. The neurosurgery for craniotomy was performed in the front of the magnet outside of the 10 Gauss line. Aided with positional registration assembly for the stereotactic head frame, the target location (VIM or GPi or STN) in deep brain areas was identified and measured from the MR images in reference to the markers in the calibration assembly of the head frame before the burrhole prep. In 20 patients, MR- guided DBS implantations have been performed according to the new methodology. MR-guided DBS implantation at high magnetic field strength has been shown to be feasible and desirable. In addition to the improved outcome, this offers a new surgical approach in which intra-operative visualization is possible during intervention, and any complications such as bleeding can be assessed in situ immediately prior to dural closure.

Chirp-coded excitation imaging with a high-frequency ultrasound annular array.

PubMed

Mamou, Jonathan; Ketterling, Jeffrey A; Silverman, Ronald H

2008-02-01

High-frequency ultrasound (HFU, > 15 MHz) is an effective means of obtaining fine-resolution images of biological tissues for applications such as opthalmologic, dermatologic, and small animal imaging. HFU has two inherent drawbacks. First, HFU images have a limited depth of field (DOF) because of the short wavelength and the low fixed F-number of conventional HFU transducers. Second, HFU can be used to image only a few millimeters deep into a tissue because attenuation increases with frequency. In this study, a five-element annular array was used in conjunction with a synthetic-focusing algorithm to extend the DOF. The annular array had an aperture of 10 mm, a focal length of 31 mm, and a center frequency of 17 MHz. To increase penetration depth, 8-micros, chirp-coded signals were designed, input into an arbitrary waveform generator, and used to excite each array element. After data acquisition, the received signals were linearly filtered to restore axial resolution and increase the SNR. To compare the chirpcoded imaging method with conventional impulse imaging in terms of resolution, a 25-microm diameter wire was scanned and the -6-dB axial and lateral resolutions were computed at depths ranging from 20.5 to 40.5 mm. The results demonstrated that chirp-coded excitation did not degrade axial or lateral resolution. A tissue-mimicking phantom containing 10-microm glass beads was scanned, and backscattered signals were analyzed to evaluate SNR and penetration depth. Finally, ex vivo ophthalmic images were formed and chirpcoded images showed features that were not visible in conventional impulse images.

Hadamard-Encoded Multipulses for Contrast-Enhanced Ultrasound Imaging.

PubMed

Gong, Ping; Song, Pengfei; Chen, Shigao

2017-11-01

The development of contrast-enhanced ultrasound (CEUS) imaging offers great opportunities for new ultrasound clinical applications such as myocardial perfusion imaging and abdominal lesion characterization. In CEUS imaging, the contrast agents (i.e., microbubbles) are utilized to improve the contrast between blood and tissue based on their high nonlinearity under low ultrasound pressure. In this paper, we propose a new CEUS pulse sequence by combining Hadamard-encoded multipulses (HEM) with fundamental frequency bandpass filter (i.e., filter centered on transmit frequency). HEM consecutively emits multipulses encoded by a second-order Hadamard matrix in each of the two transmission events (i.e., pulse-echo events), as opposed to conventional CEUS methods which emit individual pulses in two separate transmission events (i.e., pulse inversion (PI), amplitude modulation (AM), and PIAM). In HEM imaging, the microbubble responses can be improved by the longer transmit pulse, and the tissue harmonics can be suppressed by the fundamental frequency filter, leading to significantly improved contrast-to-tissue ratio (CTR) and signal-to-noise ratio (SNR). In addition, the fast polarity change between consecutive coded pulse emissions excites strong nonlinear microbubble echoes, further enhancing the CEUS image quality. The spatial resolution of HEM image is compromised as compared to other microbubble imaging methods due to the longer transmit pulses and the lower imaging frequency (i.e., fundamental frequency). However, the resolution loss was shown to be negligible and could be offset by the significantly enhanced CTR, SNR, and penetration depth. These properties of HEM can potentially facilitate robust CEUS imaging for many clinical applications, especially for deep abdominal organs and heart.

Characterisation of a novel transmission Raman spectroscopy platform for non-invasive detection of breast micro-calcifications

NASA Astrophysics Data System (ADS)

Ghita, Adrian; Matousek, Pavel; Stone, Nick

2018-02-01

Our work focuses on the development of a medical Raman spectroscopy based platform to non-invasively detect and determine in-vivo molecular information deep inside biological tissues by monitoring the chemical composition of breast calcifications. The ultimate goal is to replace a needle biopsy which typically follows the detection of an abnormality in mammographic images. Here we report the non-invasive detection of calcium oxalate monohydrate in tissue through 40 mm of phantom tissues using our recently developed advanced Raman instrument complementing our previous detection of calcium hydroxyapatite through this thickness of tissue. The ability to detect these two key types of calcifications opens avenues for the development of non-invasive in-vivo breast cancer diagnostic tool in the future.

Investigation in clinical potential of polarization sensitive optical coherence tomography in laryngeal tumor model study

NASA Astrophysics Data System (ADS)

Zhou, Xin; Oak, Chulho; Ahn, Yeh-Chan; Kim, Sung Won; Tang, Shuo

2018-02-01

Polarization-sensitive optical coherence tomography (PS-OCT) is capable of measuring tissue birefringence. It has been widely applied to access the birefringence in tissues such as skin and cartilage. The vocal cord tissue consists of three anatomical layers from the surface to deep inside, the epithelium that contains almost no collagen, the lamina propria that is composed with abundant collagen, and the vocalis muscle layer. Due to the variation in the organization of collagen fibers, the different tissue layers show different tissue birefringence, which can be evaluated by PS-OCT phase retardation measurement. Furthermore, collagen fibers in healthy connective tissues are usually well organized, which provides relatively high birefringence. When the collagen organization is destroyed by diseases such as tumor, the birefringence of the tissue will decrease. In this study, a rabbit laryngeal tumor model with different stages of tumor progression is investigated ex-vivo by PS-OCT. The PS-OCT images show a gradual decrease in birefringence from normal tissue to severe tumor tissue. A phase retardation slope-based analysis is conducted to distinguish the epithelium, lamina propria, and muscle layers, respectively. The phase retardation slope quantifies the birefringence in different layers. The quantitative study provides a more detailed comparison among different stages of the rabbit laryngeal tumor model. The PS-OCT result is validated by the corresponding histology images of the same samples.

Thermoacoustic and photoacoustic sensing of temperature.

PubMed

Pramanik, Manojit; Wang, Lihong V

2009-01-01

We present a novel temperature-sensing technique using thermoacoustic and photoacoustic measurements. This noninvasive method has been demonstrated using a tissue phantom to have high temporal resolution and temperature sensitivity. Because both photoacoustic and thermoacoustic signal amplitudes depend on the temperature of the source object, the signal amplitudes can be used to monitor the temperature. A temperature sensitivity of 0.15 degrees C was obtained at a temporal resolution as short as 2 s, taking the average of 20 signals. The deep-tissue imaging capability of this technique can potentially lead us to in vivo temperature monitoring in thermal or cryogenic applications.

Cancer cell motility: lessons from migration in confined spaces

PubMed Central

Paul, Colin D.; Mistriotis, Panagiotis; Konstantopoulos, Konstantinos

2017-01-01

Time-lapse, deep-tissue imaging made possible by advances in intravital microscopy has demonstrated the importance of tumour cell migration through confining tracks in vivo. These tracks may either be endogenous features of tissues or be created by tumour or tumour-associated cells. Importantly, migration mechanisms through confining microenvironments are not predicted by 2D migration assays. Engineered in vitro models have been used to delineate the mechanisms of cell motility through confining spaces encountered in vivo. Understanding cancer cell locomotion through physiologically relevant confining tracks could be useful in developing therapeutic strategies to combat metastasis. PMID:27909339

Towards precision medicine: from quantitative imaging to radiomics

PubMed Central

Acharya, U. Rajendra; Hagiwara, Yuki; Sudarshan, Vidya K.; Chan, Wai Yee; Ng, Kwan Hoong

2018-01-01

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine. PMID:29308604

Photoacoustic microscopy of human teeth

NASA Astrophysics Data System (ADS)

Rao, Bin; Cai, Xin; Favazza, Christopher; Yao, Junjie; Li, Li; Duong, Steven; Liaw, Lih-Huei; Holtzman, Jennifer; Wilder-Smith, Petra; Wang, Lihong V.

2011-03-01

Photoacoustic microscopy (PAM) utilizes short laser pulses to deposit energy into light absorbers and sensitively detects the ultrasonic waves the absorbers generate in response. PAM directly renders a three-dimensional spatial distribution of sub-surface optical absorbers. Unlike other optical imaging technologies, PAM features label-free optical absorption contrast and excellent imaging depths. Standard dental imaging instruments are limited to X-ray and CCD cameras. Subsurface optical dental imaging is difficult due to the highly-scattering enamel and dentin tissue. Thus, very few imaging methods can detect dental decay or diagnose dental pulp, which is the innermost part of the tooth, containing the nerves, blood vessels, and other cells. Here, we conducted a feasibility study on imaging dental decay and dental pulp with PAM. Our results showed that PAM is sensitive to the color change associated with dental decay. Although the relative PA signal distribution may be affected by surface contours and subsurface reflections from deeper dental tissue, monitoring changes in the PA signals (at the same site) over time is necessary to identify the progress of dental decay. Our results also showed that deep-imaging, near-infrared (NIR) PAM can sensitively image blood in the dental pulp of an in vitro tooth. In conclusion, PAM is a promising tool for imaging both dental decay and dental pulp.

Improved Contrast-Enhanced Ultrasound Imaging With Multiplane-Wave Imaging.

PubMed

Gong, Ping; Song, Pengfei; Chen, Shigao

2018-02-01

Contrast-enhanced ultrasound (CEUS) imaging has great potential for use in new ultrasound clinical applications such as myocardial perfusion imaging and abdominal lesion characterization. In CEUS imaging, contrast agents (i.e., microbubbles) are used to improve contrast between blood and tissue because of their high nonlinearity under low ultrasound pressure. However, the quality of CEUS imaging sometimes suffers from a low signal-to-noise ratio (SNR) in deeper imaging regions when a low mechanical index (MI) is used to avoid microbubble disruption, especially for imaging at off-resonance transmit frequencies. In this paper, we propose a new strategy of combining CEUS sequences with the recently proposed multiplane-wave (MW) compounding method to improve the SNR of CEUS in deeper imaging regions without increasing MI or sacrificing frame rate. The MW-CEUS method emits multiple Hadamard-coded CEUS pulses in each transmission event (i.e., pulse-echo event). The received echo signals first undergo fundamental bandpass filtering (i.e., the filter is centered on the transmit frequency) to eliminate the microbubble's second-harmonic signals because they cannot be encoded by pulse inversion. The filtered signals are then Hadamard decoded and realigned in fast time to recover the signals as they would have been obtained using classic CEUS pulses, followed by designed recombination to cancel the linear tissue responses. The MW-CEUS method significantly improved contrast-to-tissue ratio and SNR of CEUS imaging by transmitting longer coded pulses. The image resolution was also preserved. The microbubble disruption ratio and motion artifacts in MW-CEUS were similar to those of classic CEUS imaging. In addition, the MW-CEUS sequence can be adapted to other transmission coding formats. These properties of MW-CEUS can potentially facilitate CEUS imaging for many clinical applications, especially assessing deep abdominal organs or the heart.

Optical Drug Monitoring: Photoacoustic Imaging of Nanosensors to Monitor Therapeutic Lithium In Vivo

PubMed Central

Cash, Kevin J.; Li, Chiye; Xia, Jun; Wang, Lihong V.; Clark, Heather A.

2015-01-01

Personalized medicine could revolutionize how primary care physicians treat chronic disease and how researchers study fundamental biological questions. To realize this goal we need to develop more robust, modular tools and imaging approaches for in vivo monitoring of analytes. In this report, we demonstrate that synthetic nanosensors can measure physiologic parameters with photoacoustic contrast, and we apply that platform to continuously track lithium levels in vivo. Photoacoustic imaging achieves imaging depths that are unattainable with fluorescence or multiphoton microscopy. We validated the photoacoustic results that illustrate the superior imaging depth and quality of photoacoustic imaging with optical measurements. This powerful combination of techniques will unlock the ability to measure analyte changes in deep tissue and will open up photoacoustic imaging as a diagnostic tool for continuous physiological tracking of a wide range of analytes. PMID:25588028

Optical drug monitoring: photoacoustic imaging of nanosensors to monitor therapeutic lithium in vivo.

PubMed

Cash, Kevin J; Li, Chiye; Xia, Jun; Wang, Lihong V; Clark, Heather A

2015-02-24

Personalized medicine could revolutionize how primary care physicians treat chronic disease and how researchers study fundamental biological questions. To realize this goal, we need to develop more robust, modular tools and imaging approaches for in vivo monitoring of analytes. In this report, we demonstrate that synthetic nanosensors can measure physiologic parameters with photoacoustic contrast, and we apply that platform to continuously track lithium levels in vivo. Photoacoustic imaging achieves imaging depths that are unattainable with fluorescence or multiphoton microscopy. We validated the photoacoustic results that illustrate the superior imaging depth and quality of photoacoustic imaging with optical measurements. This powerful combination of techniques will unlock the ability to measure analyte changes in deep tissue and will open up photoacoustic imaging as a diagnostic tool for continuous physiological tracking of a wide range of analytes.

Quantitative Magnetic Resonance Thermometry and Its Use with MR-Guided Focused Ultrasound

NASA Astrophysics Data System (ADS)

Pauly, Kim

2014-03-01

Focused ultrasound (FUS) uses a large area array, typically outside the body, that is geometrically or electronically focused to a point deep in the body. Such focusing provides amplification of the ultrasound intensity, thereby allowing heating of tissue to the point of coagulation at the focus, without damage to the intervening tissue. Guidance of FUS treatments deep in the body can be done quantitatively with magnetic resonance (MR) thermometry, termed MRgFUS. The physics behind MR thermometry lie in the changes in hydrogen bonding with temperature. As tissue temperature rises, hydrogen bonds break, allowing the return of the electron cloud to shield water protons, reducing the magnetic field seen by the protons, and the resonant frequency. The change in resonant frequency is -0.01 ppm per degree C and is the same for all aqueous tissues. The result of the shift in proton resonant frequency is seen in the phase of gradient echo images. Subtraction of the phase of images acquired before and during heating allows the removal of background phase from other sources, yielding quantitative temperature maps. Temperature standard deviations less than 1 degree C are readily achievable and thermal dose maps are easily calculated. Thermal dose is found from a conversion of the whole temperature-time curve to an equivalent number of minutes at 43 degrees C. A thermal dose of 240 minutes is often taken as the threshold for tissue damage. MR thermometry is complicated by the motion of the target tissue and/or motion of other organs such as occurs during respiration. More sophisticated algorithms than the simple baseline subtraction take advantage of the facts that motion can be repetitive (in the case of respiratory motion) and/or the fact that the focal region in MRgFUS is small, allowing for extraction of the heat from the phase profile without subtraction of a background phase.

Deep Undercooling of Tissue Water and Winter Hardiness Limitations in Timberline Flora 1

PubMed Central

Becwar, Michael R.; Rajashekar, Channa; Bristow, Katherine J. Hansen; Burke, Michael J.

1981-01-01

Deep undercooled tissue water, which froze near −40 C, was found in winter collected stem and leaf tissue of the dominant timberline tree species of the Colorado Rocky Mountains, Engelmann spruce (Picea engelmannii (Parry) Engelm.) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.), and in numerous other woody species in and below the subalpine vegetation zone. Previous work on numerous woody plants indicates that deep undercooling in xylem makes probable a −40 C winter hardiness limit in stem tissue. Visual injury determinations and electrolyte loss measurements on stem tissue revealed injury near −40 C associated with the freezing of the deep undercooled stem tissue water. These results suggest that the winter hardiness limit of this woody flora is near −40 C. The relevance of deep undercooling in relation to timberline, the upper elevational limit of the subalpine forest, is discussed. PMID:16661852

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

In vivo quantitative imaging of point-like bioluminescent and fluorescent sources: Validation studies in phantoms and small animals post mortem

NASA Astrophysics Data System (ADS)

Comsa, Daria Craita

2008-10-01

There is a real need for improved small animal imaging techniques to enhance the development of therapies in which animal models of disease are used. Optical methods for imaging have been extensively studied in recent years, due to their high sensitivity and specificity. Methods like bioluminescence and fluorescence tomography report promising results for 3D reconstructions of source distributions in vivo. However, no standard methodology exists for optical tomography, and various groups are pursuing different approaches. In a number of studies on small animals, the bioluminescent or fluorescent sources can be reasonably approximated as point or line sources. Examples include images of bone metastases confined to the bone marrow. Starting with this premise, we propose a simpler, faster, and inexpensive technique to quantify optical images of point-like sources. The technique avoids the computational burden of a tomographic method by using planar images and a mathematical model based on diffusion theory. The model employs in situ optical properties estimated from video reflectometry measurements. Modeled and measured images are compared iteratively using a Levenberg-Marquardt algorithm to improve estimates of the depth and strength of the bioluminescent or fluorescent inclusion. The performance of the technique to quantify bioluminescence images was first evaluated on Monte Carlo simulated data. Simulated data also facilitated a methodical investigation of the effect of errors in tissue optical properties on the retrieved source depth and strength. It was found that, for example, an error of 4 % in the effective attenuation coefficient led to 4 % error in the retrieved depth for source depths of up to 12mm, while the error in the retrieved source strength increased from 5.5 % at 2mm depth, to 18 % at 12mm depth. Experiments conducted on images from homogeneous tissue-simulating phantoms showed that depths up to 10mm could be estimated within 8 %, and the relative source strength within 20 %. For sources 14mm deep, the inaccuracy in determining the relative source strength increased to 30 %. Measurements on small animals post mortem showed that the use of measured in situ optical properties to characterize heterogeneous tissue resulted in a superior estimation of the source strength and depth compared to when literature optical properties for organs or tissues were used. Moreover, it was found that regardless of the heterogeneity of the implant location or depth, our algorithm consistently showed an advantage over the simple assessment of the source strength based on the signal strength in the emission image. Our bioluminescence algorithm was generally able to predict the source strength within a factor of 2 of the true strength, but the performance varied with the implant location and depth. In fluorescence imaging a more complex technique is required, including knowledge of tissue optical properties at both the excitation and emission wavelengths. A theoretical study using simulated fluorescence data showed that, for example, for a source 5 mm deep in tissue, errors of up to 15 % in the optical properties would give rise to errors of +/-0.7 mm in the retrieved depth and the source strength would be over- or under-estimated by a factor ranging from 1.25 to 2. Fluorescent sources implanted in rats post mortem at the same depth were localized with an error just slightly higher than predicted theoretically: a root-mean-square value of 0.8 mm was obtained for all implants 5 mm deep. However, for this source depth, the source strength was assessed within a factor ranging from 1.3 to 4.2 from the value estimated in a controlled medium. Nonetheless, similarly to the bioluminescence study, the fluorescence quantification algorithm consistently showed an advantage over the simple assessment of the source strength based on the signal strength in the fluorescence image. Few studies have been reported in the literature that reconstruct known sources of bioluminescence or fluorescence in vivo or in heterogeneous phantoms. The few reported results show that the 3D tomographic methods have not yet reached their full potential. In this context, the simplicity of our technique emerges as a strong advantage.

Noninvasively Imaging Subcutaneous Tumor Xenograft by a Handheld Raman Detector, with the Assistance of an Optical Clearing Agent.

PubMed

Zhang, Yunfei; Liu, Haoran; Tang, Jiali; Li, Zhuoyun; Zhou, Xingyu; Zhang, Ren; Chen, Liang; Mao, Ying; Li, Cong

2017-05-31

A handheld Raman detector with operational convenience, high portability, and rapid acquisition rate has been applied in clinics for diagnostic purposes. However, the inherent weakness of Raman scattering and strong scattering of the turbid tissue restricts its utilization to superficial locations. To extend the applications of a handheld Raman detector to deep tissues, a gold nanostar-based surface-enhanced Raman scattering (SERS) nanoprobe with robust colloidal stability, a fingerprint-like spectrum, and extremely high sensitivity (5.0 fM) was developed. With the assistance of FPT, a multicomponent optical clearing agent (OCA) efficiently suppressing light scattering from the turbid dermal tissues, the handheld Raman detector noninvasively visualized the subcutaneous tumor xenograft with a high target-to-background ratio after intravenous injection of the gold nanostar-based SERS nanoprobe. To the best of our knowledge, this work is the first example to introduce the optical clearing technique in assisting SERS imaging in vivo. The combination of optical clearing technology and SERS is a promising strategy for the extension of the clinical applications of the handheld Raman detector from superficial tissues to subcutaneous or even deeper lesions that are usually "concealed" by the turbid dermal tissue.

Mapping the vascular anatomy of free transplanted soft tissue flaps with computed tomographic angiography.

PubMed

Rozen, Warren M; Chubb, Daniel; Ashton, Mark W; Webster, Howard R

2012-05-01

The use of advanced imaging technologies such as computed tomographic angiography (CTA) has opened the door to the analysis of microvascular anatomy not previously demonstrable with prior imaging techniques. While CTA has been used to evaluate the vascular anatomy of donor body regions in the planning of harvest of tissue for free flap transfer, the use of CTA to evaluate tissues after tissue transplantation has not been demonstrated. The current study aimed to explore whether vascular anatomy was able to highlight CTA within transferred flaps. The arterial and venous anatomy of a transferred deep inferior epigastric artery (DIEA) perforator (DIEP) flap was explored postoperatively with the use of CTA. Intra-flap vasculature was mapped and recorded qualitatively. Postoperative CTA is able to highlight the vascular pedicle of a transferred free flap, highlight the course of individual perforators supplying the flap, and map the zones of lesser perfusion by the source pedicle. The current study has demonstrated that CTA may be of value in identifying vascular anatomy within transferred tissue, as a guide to evaluate flap perfusion and planning further surgery involving the flap. © Springer-Verlag 2011

Computational adaptive optics for broadband optical interferometric tomography of biological tissue

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.

2015-03-01

High-resolution real-time tomography of biological tissues is important for many areas of biological investigations and medical applications. Cellular level optical tomography, however, has been challenging because of the compromise between transverse imaging resolution and depth-of-field, the system and sample aberrations that may be present, and the low imaging sensitivity deep in scattering tissues. The use of computed optical imaging techniques has the potential to address several of these long-standing limitations and challenges. Two related techniques are interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO). Through three-dimensional Fourierdomain resampling, in combination with high-speed OCT, ISAM can be used to achieve high-resolution in vivo tomography with enhanced depth sensitivity over a depth-of-field extended by more than an order-of-magnitude, in realtime. Subsequently, aberration correction with CAO can be performed in a tomogram, rather than to the optical beam of a broadband optical interferometry system. Based on principles of Fourier optics, aberration correction with CAO is performed on a virtual pupil using Zernike polynomials, offering the potential to augment or even replace the more complicated and expensive adaptive optics hardware with algorithms implemented on a standard desktop computer. Interferometric tomographic reconstructions are characterized with tissue phantoms containing sub-resolution scattering particles, and in both ex vivo and in vivo biological tissue. This review will collectively establish the foundation for high-speed volumetric cellular-level optical interferometric tomography in living tissues.

[Epidemiological characteristics and mortality risk factors in patients admitted in hospitals with soft tissue infections. A multicentric STIMG (Soft Tissue Infections Malacitan Group) study results].

PubMed

Salgado Ordóñez, F; Villar Jiménez, J; Hidalgo Conde, A; Villalobos Sánchez, A; de la Torre Lima, J; Aguilar García, J; da Rocha Costa, I; García Ordóñez, M A; Nuño Alvarez, E; Ramos Cantes, C; Martín Pérez, M

2006-07-01

To describe the characteristics of patients admitted in hospitals with soft tissue infections, and analyse the variables whose died, in order to define risk groups. retrospective analysis of medical reports of all patient admitted during 2002 year for soft tissue infections in public malacitans hospitals. We excluded the patient with soft tissue infections associated with burns, surgery, pressure ulcers, and orbit cellulitis. We analysed clinical, biochemical variables and indications for yields and imaging tests, so the empiric antibiotic treatment established and its correlations with practice guidelines. We analysed 391 admissions of 374 patients. Cellulitis was the most frequent diagnosis (69.3%). We did imaging tests in 51.6%. In 94.3% of cases were treated with empirics antibiotics. The most prescribed drug was amoxiciline plus clavulanate (39%). 27 patients died, 40.7% of them for septic cause. All deceased patients had chronic diseases. The only biochemical parameters associated with mortality were serum proteins and albumina (55 +/- 9 g/L vs. 63 +/- 8 g/L; p = 0.0231) and (22 +/- 7 g/L vs. 29 +/- 7 g/L; p = 0.0125) respectively. Cellullitis are the most frequent soft tissue infections that requires admissions in hospitals. We overuse imaging test and don t follow the practice guidelines recommendations in antibiotic therapy. Primary soft issue infection s mortality is low and it s restricted to people with chronic illness, deep infections and bad nutritional status.

In vivo terahertz imaging of rat skin burns

NASA Astrophysics Data System (ADS)

Tewari, Priyamvada; Kealey, Colin P.; Bennett, David B.; Bajwa, Neha; Barnett, Kelli S.; Singh, Rahul S.; Culjat, Martin O.; Stojadinovic, Alexander; Grundfest, Warren S.; Taylor, Zachary D.

2012-04-01

A reflective, pulsed terahertz (THz) imaging system was used to acquire high-resolution (d10-90/ λ~1.925) images of deep, partial thickness burns in a live rat. The rat's abdomen was burned with a brass brand heated to ~220°C and pressed against the skin with contact pressure for ~10 sec. The burn injury was imaged beneath a Mylar window every 15 to 30 min for up to 7 h. Initial images display an increase in local water concentration of the burned skin as evidenced by a marked increase in THz reflectivity, and this likely correlates to the post-injury inflammatory response. After ~1 h the area of increased reflectivity consolidated to the region of skin that had direct contact with the brand. Additionally, a low reflecting ring of tissue could be observed surrounding the highly reflective burned tissue. We hypothesize that these regions of increased and decreased reflectivity correlate to the zones of coagulation and stasis that are the classic foundation of burn wound histopathology. While further investigations are necessary to confirm this hypothesis, if true, it likely represents the first in vivo THz images of these pathologic zones and may represent a significant step forward in clinical application of THz technology.

A novel near-infrared nanomaterial with high quantum efficiency and its applications in real time in vivo imaging

NASA Astrophysics Data System (ADS)

Cui, X. X.; Fan, Q.; Shi, S. J.; Wen, W. H.; Chen, D. F.; Guo, H. T.; Xu, Y. T.; Gao, F.; Nie, R. Z.; Ford, Harold D.; Tang, Gordon H.; Hou, C. Q.; Peng, B.

2018-05-01

Fluorescence imaging signal is severely limited by the quantum efficiency and emission wavelength. To overcome these challenges, novel NIR-emitting K5NdLi2F10 nanoparticles under NIR excitation was introduced as fluorescence imaging probe for the first time. The photostability of K5NdLi2F10 nanoparticles in the water, phosphate buffer saline, fetal bovine serum and living mice was investigated. The fluorescence signal was detected with depths of 3.5 and 2.0 cm in phantom and pork tissue, respectively. Fluorescence spectrum with a significant signal-to-background ratio of 10:1 was captured in living mice. Moreover, clear NIR images were virtualized for the living mice after intravenous injection. The imaging ability of nanoparticles in tumor-beard mice were evaluated, the enrichment of K5NdLi2F10 nanoparticles in tumor site due to the enhanced permeability and retention effect was confirmed. The systematic studies of toxicity, bio-distribution and in-vivo dynamic imaging suggest that these materials give high biocompatibility and low toxicity. These NIR-emitting nanoparticles with high quantum efficiency, high penetration and low toxicity might facilitate tumor identification in deep tissues more sensitively.

A novel near-infrared nanomaterial with high quantum efficiency and its applications in real time in vivo imaging.

PubMed

Cui, X X; Fan, Q; Shi, S J; Wen, W H; Chen, D F; Guo, H T; Xu, Y T; Gao, F; Nie, R Z; Ford, Harold D; Tang, Gordon H; Hou, C Q; Peng, B

2018-05-18

Fluorescence imaging signal is severely limited by the quantum efficiency and emission wavelength. To overcome these challenges, novel NIR-emitting K 5 NdLi 2 F 10 nanoparticles under NIR excitation was introduced as fluorescence imaging probe for the first time. The photostability of K 5 NdLi 2 F 10 nanoparticles in the water, phosphate buffer saline, fetal bovine serum and living mice was investigated. The fluorescence signal was detected with depths of 3.5 and 2.0 cm in phantom and pork tissue, respectively. Fluorescence spectrum with a significant signal-to-background ratio of 10:1 was captured in living mice. Moreover, clear NIR images were virtualized for the living mice after intravenous injection. The imaging ability of nanoparticles in tumor-beard mice were evaluated, the enrichment of K 5 NdLi 2 F 10 nanoparticles in tumor site due to the enhanced permeability and retention effect was confirmed. The systematic studies of toxicity, bio-distribution and in-vivo dynamic imaging suggest that these materials give high biocompatibility and low toxicity. These NIR-emitting nanoparticles with high quantum efficiency, high penetration and low toxicity might facilitate tumor identification in deep tissues more sensitively.

Modulated-alignment dual-axis (MAD) confocal microscopy for deep optical sectioning in tissues

PubMed Central

Leigh, Steven Y.; Chen, Ye; Liu, Jonathan T.C.

2014-01-01

A strategy is presented to enable optical-sectioning microscopy with improved contrast and imaging depth using low-power (0.5 - 1 mW) diode laser illumination. This technology combines the inherent strengths of focal-modulation microscopy and dual-axis confocal (DAC) microscopy for rejecting out-of-focus and multiply scattered background light in tissues. The DAC architecture is unique in that it utilizes an intersecting pair of illumination and collection beams to improve the spatial-filtering and optical-sectioning performance of confocal microscopy while focal modulation selectively ‘labels’ in-focus signals via amplitude modulation. Simulations indicate that modulating the spatial alignment of dual-axis beams at a frequency f generates signals from the focal volume of the microscope that are modulated at 2f with minimal modulation of background signals, thus providing nearly an order-of-magnitude improvement in optical-sectioning contrast compared to DAC microscopy alone. Experiments show that 2f lock-in detection enhances contrast and imaging depth within scattering phantoms and fresh tissues. PMID:24940534

LED induced autofluorescence (LIAF) imager with eight multi-filters for oral cancer diagnosis

NASA Astrophysics Data System (ADS)

Huang, Ting-Wei; Cheng, Nai-Lun; Tsai, Ming-Hsui; Chiou, Jin-Chern; Mang, Ou-Yang

2016-03-01

Oral cancer is one of the serious and growing problem in many developing and developed countries. The simple oral visual screening by clinician can reduce 37,000 oral cancer deaths annually worldwide. However, the conventional oral examination with the visual inspection and the palpation of oral lesions is not an objective and reliable approach for oral cancer diagnosis, and it may cause the delayed hospital treatment for the patients of oral cancer or leads to the oral cancer out of control in the late stage. Therefore, a device for oral cancer detection are developed for early diagnosis and treatment. A portable LED Induced autofluorescence (LIAF) imager is developed by our group. It contained the multiple wavelength of LED excitation light and the rotary filter ring of eight channels to capture ex-vivo oral tissue autofluorescence images. The advantages of LIAF imager compared to other devices for oral cancer diagnosis are that LIAF imager has a probe of L shape for fixing the object distance, protecting the effect of ambient light, and observing the blind spot in the deep port between the gumsgingiva and the lining of the mouth. Besides, the multiple excitation of LED light source can induce multiple autofluorescence, and LIAF imager with the rotary filter ring of eight channels can detect the spectral images of multiple narrow bands. The prototype of a portable LIAF imager is applied in the clinical trials for some cases in Taiwan, and the images of the clinical trial with the specific excitation show the significant differences between normal tissue and oral tissue under these cases.

Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

PubMed

Ertosun, Mehmet Günhan; Rubin, Daniel L

2015-01-01

Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository.

Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks

PubMed Central

Ertosun, Mehmet Günhan; Rubin, Daniel L.

2015-01-01

Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository. PMID:26958289

Sensitive and rapid detection of endogenous hydrogen sulfide distributing in different mouse viscera via a two-photon fluorescent probe.

PubMed

Chen, Qian; Yang, Jinfeng; Li, Yinhui; Zheng, Jing; Yang, Ronghua

2015-10-08

Development of efficient methods for detection of endogenous H2S in living cells and tissues is of considerable significance for better understanding the biological and pathological functions of H2S. Two-photon (TP) fluorescent probes are favorable as powerful molecular tools for studying physiological process due to its non-invasiveness, high spatiotemporal resolution and deep-tissues imaging. Up to date, several TP probes for intracellular H2S imaging have been designed, but real-time imaging of endogenous H2S-related biological processes in tissues is hampered due to low sensitivity, long response time and interference from other biothiols. To address this issue, we herein report a novel two-photon fluorescent probe (TPP-H2S) for highly sensitive and fast monitoring and imaging H2S levels in living cells and tissues. In the presence of H2S, it exhibits obviously improved sensitivity (LOD: 0.12 μM) and fast response time (about 2 min) compared with the reported two-photon H2S probes. With two-photon excitation, TPP-H2S displays high signal-to-noise ratio and sensitivity even no interference in cell growth media. As further application, TPP-H2S is applied for fast imaging of H2S in living cells and different fresh tissues by two-photon confocal microscope. Most importantly we first measured the endogenous H2S level in different viscera by vivisection and found that the distribution of endogenous H2S mostly in brain, liver and lung. The excellent sensing properties of TPP-H2S make it a practically useful tool for further studying biological roles of H2S. Copyright © 2015 Elsevier B.V. All rights reserved.

Photoacoustic imaging of intravenously injected photosensitizer in rat burn models for efficient antibacterial photodynamic therapy

NASA Astrophysics Data System (ADS)

Tsunoi, Yasuyuki; Sato, Shunichi; Ashida, Hiroshi; Terakawa, Mitsuhiro

2012-02-01

For efficient photodynamic treatment of wound infection, a photosensitizer must be distributed in the whole infected tissue region. To ensure this, depth profiling of a photosensitizer is necessary in vivo. In this study, we applied photoacoustic (PA) imaging to visualize the depth profile of an intravenously injected photosensitizer in rat burn models. In burned tissue, pharmacokinetics is complicated; vascular occlusion takes place in the injured tissue, while vascular permeability increases due to thermal invasion. In this study, we first used Evans Blue (EB) as a test drug to examine the feasibility of photosensitizer dosimetry based on PA imaging. On the basis of the results, an actual photosensitizer, talaporfin sodium was used. An EB solution was intravenously injected into a rat deep dermal burn model. PA imaging was performed on the wound with 532 nm and 610 nm nanosecond light pulses for visualizing vasculatures (blood) and EB, respectively. Two hours after injection, the distribution of EB-originated signal spatially coincided well with that of blood-originated signal measured after injury, indicating that EB molecules leaked out from the blood vessels due to increased permeability. Afterwards, the distribution of EB signal was broadened in the depth direction due to diffusion. At 12 hours after injection, clear EB signals were observed even in the zone of stasis, demonstrating that the leaked EB molecules were delivered to the injured tissue layer. The level and time course of talaporfin sodium-originated signals were different compared with those of EB-originated signals, showing animal-dependent and/or drug-dependent permeabilization and diffusion in the tissue. Thus, photosensitizer dosimetry should be needed before every treatment to achieve desirable outcome of photodynamic treatment, for which PA imaging can be concluded to be valid and useful.

Applications of rigid and flexible GRIN-endoscopes

NASA Astrophysics Data System (ADS)

Schenkl, Selma; Ehlers, Alexander; Riemann, Iris; Messerschmidt, Bernhard; Bückle, Rainer; König, Karsten

2007-02-01

Multiphoton autofluorescence imaging became an important technique for minimal invasive examination of cells in biological tissue. Rigid and flexible endoscopes based on gradient index lenses (GRIN-lenses) extend this minimalinvasive technique to deep lying cell layers, inner body and specimens, difficult to access. In the rigid endoscope, a GRIN-lens overcomes the limited depth range, given by the working distance of the microscope objective. The focus of the conventional laser scanning tomography is reproduced tens of millimeters in the specimen under study by the GRIN-lens (diameter 1.8 and 3 μm). We will present images of fluorescent beads, proteins cells and skin tissue, as well as first in vivo measurements on human skin. The autofluorescence signal stems from the endogenous fluorophore elastin and SHG from collagen. The flexible endoscope dispenses completely the need of a microscope next to the specimen of interest. The excitation laser pulses is delivered via a well-characterized photonic crystal fiber and subsequently focused by a newly designed GRIN-lens system. The fluorescence, also transferred by a fiber is detected by a PMT detector. We will show the excellent imaging qualities of a newly developed GRIN-lens system with high-resolution images of proteins, cells and plant tissue and give an out-look on multiphoton endoscopy.

Investigating different skin and gastrointestinal tract (GIT) pathologies ex vivo by autofluorescence spectroscopy and optical imaging

NASA Astrophysics Data System (ADS)

Zhelyazkova, A.; Kuzmina, I.; Borisova, E.; Penkov, N.; Genova, Ts.; Spigulis, J.; Avramov, L.

2016-01-01

The skin neoplasias are on a second place in the world statistics of cancer incidence, and gastrointestinal tract (GIT) tumours are also in the "top ten" list. For the most of cutaneous and gastrointestinal tumours could be obtained better prognoses for patients, if an earlier and precise diagnostics procedure is applied. One of the most promising approaches for development of improved diagnostic techniques, is based on optical detection, and analysis of the signatures of biological tissues for detecting the presence of pathological alterations in the investigated objects. It is important to develop and combine novel diagnostic techniques for an accurate early stage diagnosis to improve the chances for skin and GIT tumours treatment. Optical techniques are very promising methods for such noninvasive diagnosis of skin and mucosa tumours, possessing the advantages of deep imaging depth, high resolution, fast imaging speed, and noninvasive character of detection. In this study we combine autofluorescence spectroscopy and optical imaging techniques to develop more precise evaluation of the tissue pathologies investigated. We obtain chromophore maps for GIT and cutaneous samples, with better visualization of the tumours borders and margins. In addition, fluorescence spectra give us information about the early changes in chromophores' contents into the tissues during neoplasia growth.

A Non-Invasive Deep Tissue PH Monitor.

DTIC Science & Technology

1995-08-11

disturbances in acid-base regulation may have serious effects on metabolic activity, circulation, and the central nervous system. Currently, acid-base...to tissue ischemia than is arterial pH. Consequently, a non-invasive deep tissue pH monitor has enormous value as a mechanism for rapid and effective ...achieved, and improve our understanding of what physical effects are important to successful non-invasive deep tissue pH monitoring. This last statement

Extending the fundamental imaging-depth limit of multi-photon microscopy by imaging with photo-activatable fluorophores.

PubMed

Chen, Zhixing; Wei, Lu; Zhu, Xinxin; Min, Wei

2012-08-13

It is highly desirable to be able to optically probe biological activities deep inside live organisms. By employing a spatially confined excitation via a nonlinear transition, multiphoton fluorescence microscopy has become indispensable for imaging scattering samples. However, as the incident laser power drops exponentially with imaging depth due to scattering loss, the out-of-focus fluorescence eventually overwhelms the in-focal signal. The resulting loss of imaging contrast defines a fundamental imaging-depth limit, which cannot be overcome by increasing excitation intensity. Herein we propose to significantly extend this depth limit by multiphoton activation and imaging (MPAI) of photo-activatable fluorophores. The imaging contrast is drastically improved due to the created disparity of bright-dark quantum states in space. We demonstrate this new principle by both analytical theory and experiments on tissue phantoms labeled with synthetic caged fluorescein dye or genetically encodable photoactivatable GFP.

Open-air multispectral fluorescence-guided surgery platform for intraoperative detection of malignant tissue under ambient lighting conditions

NASA Astrophysics Data System (ADS)

Behrooz, Ali; Vasquez, Kristine O.; Waterman, Peter; Meganck, Jeff; Peterson, Jeffrey D.; Miller, Peter; Kempner, Joshua

2017-02-01

Intraoperative resection of tumors currently relies upon the surgeon's ability to visually locate and palpate tumor nodules. Undetected residual malignant tissue often results in the need for additional treatment or surgical intervention. The Solaris platform is a multispectral open-air fluorescence imaging system designed for translational fluorescence-guided surgery. Solaris supports video-rate imaging in four fixed fluorescence channels ranging from visible to near infrared, and a multispectral channel equipped with a liquid crystal tunable filter (LCTF) for multispectral image acquisition (520-620 nm). Identification of tumor margins using reagents emitting in the visible spectrum (400-650 nm), such as fluorescein isothiocyanate (FITC), present challenges considering the presence of auto-fluorescence from tissue and food in the gastrointestinal (GI) tract. To overcome this, Solaris acquires LCTF-based multispectral images, and by applying an automated spectral unmixing algorithm to the data, separates reagent fluorescence from tissue and food auto-fluorescence. The unmixing algorithm uses vertex component analysis to automatically extract the primary pure spectra, and resolves the reagent fluorescent signal using non-negative least squares. For validation, intraoperative in vivo studies were carried out in tumor-bearing rodents injected with FITC-dextran reagent that is primarily residing in malignant tissue 24 hours post injection. In the absence of unmixing, fluorescence from tumors is not distinguishable from that of surrounding tissue. Upon spectral unmixing, the FITC-labeled malignant regions become well defined and detectable. The results of these studies substantiate the multispectral power of Solaris in resolving FITC-based agent signal in deep tumor masses, under ambient and surgical light, and enhancing the ability to surgically resect them.

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.

Nanoparticle-assisted-multiphoton microscopy for in vivo brain imaging of mice

NASA Astrophysics Data System (ADS)

Qian, Jun

2015-03-01

Neuro/brain study has attracted much attention during past few years, and many optical methods have been utilized in order to obtain accurate and complete neural information inside the brain. Relying on simultaneous absorption of two or more near-infrared photons by a fluorophore, multiphoton microscopy can achieve deep tissue penetration and efficient light detection noninvasively, which makes it very suitable for thick-tissue and in vivo bioimaging. Nanoparticles possess many unique optical and chemical properties, such as anti-photobleaching, large multiphoton absorption cross-section, and high stability in biological environment, which facilitates their applications in long-term multiphoton microscopy as contrast agents. In this paper, we will introduce several typical nanoparticles (e.g. organic dye doped polymer nanoparticles and gold nanorods) with high multiphoton fluorescence efficiency. We further applied them in two- and three-photon in vivo functional brain imaging of mice, such as brain-microglia imaging, 3D architecture reconstruction of brain blood vessel, and blood velocity measurement.

Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images.

PubMed

Khosravi, Pegah; Kazemi, Ehsan; Imielinski, Marcin; Elemento, Olivier; Hajirasouliha, Iman

2018-01-01

Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error. In this study, we utilize several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer. In particular, we demonstrate the utility of our pipeline to discriminate between two subtypes of lung cancer, four biomarkers of bladder cancer, and five biomarkers of breast cancer. In addition, we apply our pipeline to discriminate among four immunohistochemistry (IHC) staining scores of bladder and breast cancers. Our classification pipeline includes a basic CNN architecture, Google's Inceptions with three training strategies, and an ensemble of two state-of-the-art algorithms, Inception and ResNet. Training strategies include training the last layer of Google's Inceptions, training the network from scratch, and fine-tunning the parameters for our data using two pre-trained version of Google's Inception architectures, Inception-V1 and Inception-V3. We demonstrate the power of deep learning approaches for identifying cancer subtypes, and the robustness of Google's Inceptions even in presence of extensive tumor heterogeneity. On average, our pipeline achieved accuracies of 100%, 92%, 95%, and 69% for discrimination of various cancer tissues, subtypes, biomarkers, and scores, respectively. Our pipeline and related documentation is freely available at https://github.com/ih-_lab/CNN_Smoothie. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Structural and Functional Analysis of Intact Hair Follicles and Pilosebaceous Units by Volumetric Multispectral Optoacoustic Tomography.

PubMed

Ford, Steven J; Bigliardi, Paul L; Sardella, Thomas C P; Urich, Alexander; Burton, Neal C; Kacprowicz, Marcin; Bigliardi, Mei; Olivo, Malini; Razansky, Daniel

2016-04-01

Visualizing anatomical and functional features of hair follicle development in their unperturbed environment is key in understanding complex mechanisms of hair pathophysiology and in discovery of novel therapies. Of particular interest is in vivo visualization of the intact pilosebaceous unit, vascularization of the hair bulb, and evaluation of the hair cycle, particularly in humans. Furthermore, noninvasive visualization of the sebaceous glands could offer crucial insight into the pathophysiology of follicle-related diseases and dry or seborrheic skin, in particular by combining in vivo imaging with other phenotyping, genotyping, and microbial analyses. The available imaging techniques are limited in their ability for deep tissue in vivo imaging of hair follicles and lipid-rich sebaceous glands in their entirety without biopsy. We developed a noninvasive, painless, and risk-free volumetric multispectral optoacoustic tomography method for deep tissue three-dimensional visualization of whole hair follicles and surrounding structures with high spatial resolution below 80 μm. Herein we demonstrate on-the-fly assessment of key morphometric parameters of follicles and lipid content as well as functional oxygenation parameters of the associated capillary bed. The ease of handheld operation and versatility of the newly developed approach poise it as an indispensable tool for early diagnosis of disorders of the pilosebaceous unit and surrounding structures, and for monitoring the efficacy of cosmetic and therapeutic interventions. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Photoelectron Transfer at ZnTPyP Self-Assembly/TiO2 Interfaces for Enhanced Two-Photon Photodynamic Therapy.

PubMed

Liu, Yanyan; Meng, Xianfu; Wang, Han; Tang, Zhongmin; Zuo, Changjing; He, Mingyuan; Bu, Wenbo

2018-01-17

Two-photon (TP) absorption nanomaterials are highly desirable for deep-tissue clinical diagnostics and orthotopic disease treatment. Here, a well-designed core/shell nanostructure was successfully synthesized with a ZnTPyP self-assembly nanocrystal (ZSN) inner core coated by a homogeneous TiO 2 layer outside (ZSN-TO). The ZSN is a good photosemiconductor, showing both one-photon (OP) and TP absorption properties for red fluorescence emission and electron-hole pair generation; TiO 2 with good biocompatibility acts as the electron acceptor, which can transfer photoelectron from ZSN to TiO 2 for highly effective electron-hole separation, favoring the production of long-life superoxide anion (O 2 •- ) by electrons and oxygen and strong oxidizing hydroxyl radical (•OH) by holes and surrounding H 2 O. Once pretreated with ZSN-TO, the simultaneous OP-405 nm or TP-800 nm laser stimulation and fluorescent imaging of reactive oxygen species (ROS) showed dynamical and continuous generation of ROS in HeLa cells, with cytotoxicity significantly increasing via the type-1-like photodynamic therapy process. The results demonstrated that the combination of organic ZSN with inorganic TiO 2 has great applications as an excellent photosensitizer for deep-tissue fluorescent imaging and noninvasive disease treatment via TP photodynamic therapy.

Water-mediated green synthesis of PbS quantum dot and its glutathione and biotin conjugates for non-invasive live cell imaging

NASA Astrophysics Data System (ADS)

Vijaya Bharathi, M.; Maiti, Santanu; Sarkar, Bidisha; Ghosh, Kaustab; Paira, Priyankar

2018-03-01

This study addresses the cellular uptake of nanomaterials in the field of bio-applications. In the present study, we have synthesized water-soluble lead sulfide quantum dot (PbS QD) with glutathione and 3-MPA (mercaptopropionic acid) as the stabilizing ligand using a green approach. 3-MPA-capped QDs were further modified with streptavidin and then bound to biotin because of its high conjugation efficiency. Labelling and bio-imaging of cells with these bio-conjugated QDs were evaluated. The bright red fluorescence from these types of QDs in HeLa cells makes these materials suitable for deep tissue imaging.

Cherenkov imaging and biochemical sensing in vivo during radiation therapy

NASA Astrophysics Data System (ADS)

Zhang, Rongxiao

While Cherenkov emission was discovered more than eighty years ago, the potential applications of imaging this during radiation therapy have just recently been explored. With approximately half of all cancer patients being treated by radiation at some point during their cancer management, there is a constant challenge to ensure optimal treatment efficiency is achieved with maximal tumor to normal tissue therapeutic ratio. To achieve this, the treatment process as well as biological information affecting the treatment should ideally be effective and directly derived from the delivery of radiation to the patient. The value of Cherenkov emission imaging was examined here, primarily for visualization of treatment monitoring and then secondarily for Cherenkov-excited luminescence for tissue biochemical sensing within tissue. Through synchronized gating to the short radiation pulses of a linear accelerator (200Hz & 3 micros pulses), and applying a gated intensified camera for imaging, the Cherenkov radiation can be captured near video frame rates (30 frame per sec) with dim ambient room lighting. This procedure, sometimes termed Cherenkoscopy, is readily visualized without affecting the normal process of external beam radiation therapy. With simulation, phantoms and clinical trial data, each application of Cherenkoscopy was examined: i) for treatment monitoring, ii) for patient position monitoring and motion tracking, and iii) for superficial dose imaging. The temporal dynamics of delivered radiation fields can easily be directly imaged on the patient's surface. Image registration and edge detection of Cherenkov images were used to verify patient positioning during treatment. Inter-fraction setup accuracy and intra-fraction patient motion was detectable to better than 1 mm accuracy. Cherenkov emission in tissue opens up a new field of biochemical sensing within the tissue environment, using luminescent agents which can be activated by this light. In the first study of its kind with external beam irradiation, a dendritic platinum-based phosphor (PtG4) was used at micro-molar concentrations (~5 microM) to generate Cherenkov-induced luminescent signals, which are sensitive to the partial pressure of oxygen. Both tomographic reconstruction methods and linear scanned imaging were investigated here to examine the limits of detection. Recovery of optical molecular distributions was shown in tissue phantoms and small animals, with high accuracy (~1 microM), high spatial resolution (~0.2 mm) and deep-tissue detectability (~2 cm for Cherenkov luminescence scanned imaging (CELSI)), indicating potentials for in vivo and clinical use. In summary, many of the physical and technological details of Cherenkov imaging and Cherenkov-excited emission imaging were specified in this study.

Near-Infrared Imaging for the Assessment of Anastomotic Patency, Thrombosis, and Reperfusion in Microsurgery: A Pilot Study in a Porcine Model

PubMed Central

Vargas, Christina R.; Nguyen, John T.; Ashitate, Yoshitomo; Silvestre, Jason; Venugopal, Vivek; Neacsu, Florin; Kettenring, Frank; Frangioni, John V.; Gioux, Sylvain; Lee, Bernard T.

2015-01-01

Background Advances in microsurgical techniques have increased the use of free tissue transfer. Methods of intraoperative flap perfusion assessment, however, still rely primarily on subjective evaluation of traditional clinical parameters. Anastomotic thrombosis, if not expeditiously identified and revised, can result in flap loss with significant associated morbidity. This study aims to evaluate the use of near-infrared (NIR) fluorescence imaging in the assessment of microsurgical anastomotic patency, thrombosis, and vascular revision. Materials and Methods A model of pedicle thrombosis was created using bilateral abdominal flaps isolated on deep superior epigastric vascular pedicles in four Yorkshire pigs. Following flap elevation, microvascular arterial and venous anastomoses were performed unilaterally, preserving an intact contralateral control flap. Thrombosis was induced at the arterial anastomosis site using ferric chloride, and both flaps imaged using NIR fluorescence angiography. The thrombosed vascular segments were subsequently excised and new anastomoses performed to restore flow. Follow-up imaging of both flaps was then obtained to confirm patency using fluorescence imaging technology. Results Pedicled abdominal flaps were created and successful anastomotic thrombosis was induced unilaterally in each pig. Fluorescence imaging technology identified large decreases in tissue perfusion of the thrombosed flap within 2 minutes. After successful revision anastomosis, NIR imaging demonstrated dramatic increase in flow to the reconstructed flap, but intensity did not return to pre-thrombosis levels. Conclusions Early identification of anastomotic thrombosis is important in successful free tissue transfer. Real-time, intraoperative evaluation of flap perfusion, anastomotic thrombosis, and successful revision can be performed using NIR fluorescence imaging. PMID:25571855

Freehand diffuse optical spectroscopy imaging for intraoperative identification of major venous and arterial vessels underlying peritoneal fat: an in vivo demonstration in a pig model

NASA Astrophysics Data System (ADS)

Piao, Daqing; Ramadan, Mohammad; Park, Aaron; Bartels, Kenneth E.; Patel, Sanjay G.

2017-10-01

Inadvertent injury to important anatomic structures is a significant risk in minimally invasive surgery (MIS) that potentially requires conversion to an open procedure, which results in increased morbidity and mortality. Surgeons operating minimal-invasively currently do not have an easy-to-use, real-time device to aid in intraoperative identification of important anatomic structures that underlie tissue planes. We demonstrate freehand diffuse optical spectroscopy (DOS) imaging for intraoperatively identifying major underlying veins and arteries. An applicator probe that can be affixed to and detached from an 8-mm laparoscopic instrument has been developed. The 10-mm DOS source-detector separation renders sampling of tissue heterogeneities a few millimeters deep. DOS spectra acquired consecutively during freehand movement of the applicator probe on the tissue surface are displayed as a temporal and spectral image to assist in spatially resolved identification of the underlying structures. Open surgery identifications of the vena cava and aorta underlying peritoneal fat of ˜4 mm in thickness using the applicator probe under room light were demonstrated repeatedly in multiple pigs in vivo.

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.

PubMed

Choi, Hongyoon

2018-04-01

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Photothermal optical coherence tomography of epidermal growth factor receptor in live cells using immunotargeted gold nanospheres

NASA Astrophysics Data System (ADS)

Skala, Melissa C.; Crow, Matthew J.; Wax, Adam; Izatt, Joseph A.

2009-02-01

Molecular imaging is a powerful tool for investigating disease processes and potential therapies in both in vivo and in vitro systems. However, high resolution molecular imaging has been limited to relatively shallow penetration depths that can be accessed with microscopy. Optical coherence tomography (OCT) is an optical analogue to ultrasound with relatively good penetration depth (1-2 mm) and resolution (~1-10 μm). We have developed and characterized photothermal OCT as a molecular contrast mechanism that allows for high resolution molecular imaging at deeper penetration depths than microscopy. Our photothermal system consists of an amplitude-modulated heating beam that spatially overlaps with the focused spot of the sample arm of a spectral-domain OCT microscope. Validation experiments in tissue-like phantoms containing gold nanospheres that absorb at 532 nm revealed a sensitivity of 14 parts per million nanospheres (weight/weight) in a tissue-like environment. The nanospheres were then conjugated to anti-EGFR, and molecular targeting was confirmed in cells that over-express EGFR (MDA-MB-468) and cells that express low levels of EGFR (MDA-MB-435). Molecular imaging in three-dimensional tissue constructs was confirmed with a significantly lower photothermal signal (p<0.0001) from the constructs composed of cells that express low levels of EGFR compared to the over-expressing cell constructs (300% signal increase). This technique could potentially augment confocal and multiphoton microscopy as a method for deep-tissue, depth-resolved molecular imaging with relatively high resolution and target sensitivity, without photobleaching or cytotoxicity.

Particle velocity measurements with macroscopic fluorescence imaging in lymph tissue mimicking microfluidic phantoms

NASA Astrophysics Data System (ADS)

Hennessy, Ricky; Koo, Chiwan; Ton, Phuc; Han, Arum; Righetti, Raffaella; Maitland, Kristen C.

2011-03-01

Ultrasound poroelastography can quantify structural and mechanical properties of tissues such as stiffness, compressibility, and fluid flow rate. This novel ultrasound technique is being explored to detect tissue changes associated with lymphatic disease. We have constructed a macroscopic fluorescence imaging system to validate ultrasonic fluid flow measurements and to provide high resolution imaging of microfluidic phantoms. The optical imaging system is composed of a white light source, excitation and emission filters, and a camera with a zoom lens. The field of view can be adjusted from 100 mm x 75 mm to 10 mm x 7.5 mm. The microfluidic device is made of polydimethylsiloxane (PDMS) and has 9 channels, each 40 μm deep with widths ranging from 30 μm to 200 μm. A syringe pump was used to propel water containing 15 μm diameter fluorescent microspheres through the microchannels, with flow rates ranging from 0.5 μl/min to 10 μl/min. Video was captured at a rate of 25 frames/sec. The velocity of the microspheres in the microchannels was calculated using an algorithm that tracked the movement of the fluorescent microspheres. The imaging system was able to measure particle velocities ranging from 0.2 mm/sec to 10 mm/sec. The range of flow velocities of interest in lymph vessels is between 1 mm/sec to 10 mm/sec; therefore our imaging system is sufficient to measure particle velocity in phantoms modeling lymphatic flow.

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

PubMed

Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

2018-05-01

Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fluorescence lifetime imaging of endogenous molecules in live mouse cancer models (Conference Presentation)

NASA Astrophysics Data System (ADS)

Svindrych, Zdenek; Wang, Tianxiong; Hu, Song; Periasamy, Ammasi

2017-02-01

NADH and FAD are important endogenous fluorescent coenzymes participating in key enzymatic reactions of cellular metabolism. While fluorescence intensities of NADH and FAD have been used to determine the redox state of cells and tissues, this simple approach breaks down in the case of deep-tissue intravital imaging due to depth- and wavelength-dependent light absorption and scattering. To circumvent this limitation, our research focuses on fluorescence lifetimes of two-photon excited NADH and FAD emission to study the metabolic state of live tissues. In our custom-built scanning microscope we combine tunable femtosecond Ti:sapphire laser (operating at 740 nm for NADH excitation and 890 nm for FAD excitation), two GaAsP hybrid detectors for registering individual fluorescence photons and two Becker and Hickl time correlator boards for high precision lifetime measurements. Together with our rigorous FLIM analysis approach (including image segmentation, multi-exponential decay fitting and detailed statistical analysis) we are able to detect metabolic changes in cancer xenografts (human pancreatic cancer MPanc96 cells injected subcutaneously into the ear of an immunodeficient nude mouse), relative to surrounding healthy tissue. Advantageously, with the same instrumentation we can also take high-resolution and high-contrast images of second harmonic signal (SHG) originating from collagen fibers of both the healthy skin and the growing tumor. The combination of metabolic measurements (NADH and FAD lifetime) and morphological information (collagen SHG) allows us to follow the tumor growth in live mouse model and the changes in tumor microenvironment.

In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography

PubMed Central

Xie, Yijing; Martini, Nadja; Hassler, Christina; Kirch, Robert D.; Stieglitz, Thomas; Seifert, Andreas; Hofmann, Ulrich G.

2014-01-01

In neural prosthetics and stereotactic neurosurgery, intracortical electrodes are often utilized for delivering therapeutic electrical pulses, and recording neural electrophysiological signals. Unfortunately, neuroinflammation impairs the neuron-electrode-interface by developing a compact glial encapsulation around the implants in long term. At present, analyzing this immune reaction is only feasible with post-mortem histology; currently no means for specific in vivo monitoring exist and most applicable imaging modalities can not provide information in deep brain regions. Optical coherence tomography (OCT) is a well established imaging modality for in vivo studies, providing cellular resolution and up to 1.2 mm imaging depth in brain tissue. A fiber based spectral domain OCT was shown to be capable of minimally invasive brain imaging. In the present study, we propose to use a fiber based spectral domain OCT to monitor the progression of the tissue's immune response through scar encapsulation progress in a rat animal model. A fine fiber catheter was implanted in rat brain together with a flexible polyimide microelectrode in sight both of which acts as a foreign body and induces the brain tissue immune reaction. OCT signals were collected from animals up to 12 weeks after implantation and thus gliotic scarring in vivo monitored for that time. Preliminary data showed a significant enhancement of the OCT backscattering signal during the first 3 weeks after implantation, and increased attenuation factor of the sampled tissue due to the glial scar formation. PMID:25191264

Four dimensional optoacoustic imaging of perfusion in preclinical breast tumor model in vivo (Conference Presentation)

NASA Astrophysics Data System (ADS)

Deán-Ben, Xosé Luís.; Ermolayev, Vladimir; Mandal, Subhamoy; Ntziachristos, Vasilis; Razansky, Daniel

2016-03-01

Imaging plays an increasingly important role in clinical management and preclinical studies of cancer. Application of optical molecular imaging technologies, in combination with highly specific contrast agent approaches, eminently contributed to understanding of functional and histological properties of tumors and anticancer therapies. Yet, optical imaging exhibits deterioration in spatial resolution and other performance metrics due to light scattering in deep living tissues. High resolution molecular imaging at the whole-organ or whole-body scale may therefore bring additional understanding of vascular networks, blood perfusion and microenvironment gradients of malignancies. In this work, we constructed a volumetric multispectral optoacoustic tomography (vMSOT) scanner for cancer imaging in preclinical models and explored its capacity for real-time 3D intravital imaging of whole breast cancer allografts in mice. Intrinsic tissue properties, such as blood oxygenation gradients, along with the distribution of externally administered liposomes carrying clinically-approved indocyanine green dye (lipo-ICG) were visualized in order to study vascularization, probe penetration and extravasation kinetics in different regions of interest within solid tumors. The use of v-MSOT along with the application of volumetric image analysis and perfusion tracking tools for studies of pathophysiological processes within microenvironment gradients of solid tumors demonstrated superior volumetric imaging system performance with sustained competitive resolution and imaging depth suitable for investigations in preclinical cancer models.

Magnetization Transfer Ratio Relates to Cognitive Impairment in Normal Elderly

PubMed Central

Seiler, Stephan; Pirpamer, Lukas; Hofer, Edith; Duering, Marco; Jouvent, Eric; Fazekas, Franz; Mangin, Jean-Francois; Chabriat, Hugues; Dichgans, Martin; Ropele, Stefan; Schmidt, Reinhold

2014-01-01

Magnetization transfer imaging (MTI) can detect microstructural brain tissue changes and may be helpful in determining age-related cerebral damage. We investigated the association between the magnetization transfer ratio (MTR) in gray and white matter (WM) and cognitive functioning in 355 participants of the Austrian stroke prevention family study (ASPS-Fam) aged 38–86 years. MTR maps were generated for the neocortex, deep gray matter structures, WM hyperintensities, and normal appearing WM (NAWM). Adjusted mixed models determined whole brain and lobar cortical MTR to be directly and significantly related to performance on tests of memory, executive function, and motor skills. There existed an almost linear dose-effect relationship. MTR of deep gray matter structures and NAWM correlated to executive functioning. All associations were independent of demographics, vascular risk factors, focal brain lesions, and cortex volume. Further research is needed to understand the basis of this association at the tissue level, and to determine the role of MTR in predicting cognitive decline and dementia. PMID:25309438

Portable LED-induced autofluorescence spectroscopy for oral cancer diagnosis

NASA Astrophysics Data System (ADS)

Yan, Yung-Jhe; Huang, Ting-Wei; Cheng, Nai-Lun; Hsieh, Yao-Fang; Tsai, Ming-Hsui; Chiou, Jin-Chern; Duann, Jeng-Ren; Lin, Yung-Jiun; Yang, Chin-Siang; Ou-Yang, Mang

2017-04-01

Oral cancer is a serious and growing problem in many developing and developed countries. To improve the cancer screening procedure, we developed a portable light-emitting-diode (LED)-induced autofluorescence (LIAF) imager that contains two wavelength LED excitation light sources and multiple filters to capture ex vivo oral tissue autofluorescence images. Compared with conventional means of oral cancer diagnosis, the LIAF imager is a handier, faster, and more highly reliable solution. The compact design with a tiny probe allows clinicians to easily observe autofluorescence images of hidden areas located in concave deep oral cavities. The ex vivo trials conducted in Taiwan present the design and prototype of the portable LIAF imager used for analyzing 31 patients with 221 measurement points. Using the normalized factor of normal tissues under the excitation source with 365 nm of the central wavelength and without the bandpass filter, the results revealed that the sensitivity was larger than 84%, the specificity was not smaller than over 76%, the accuracy was about 80%, and the area under curve of the receiver operating characteristic (ROC) was achieved at about 87%, respectively. The fact shows the LIAF spectroscopy has the possibilities of ex vivo diagnosis and noninvasive examinations for oral cancer.

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

PubMed

Wang, Xinggang; Yang, Wei; Weinreb, Jeffrey; Han, Juan; Li, Qiubai; Kong, Xiangchuang; Yan, Yongluan; Ke, Zan; Luo, Bo; Liu, Tao; Wang, Liang

2017-11-13

Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning (P = 0.0007 < 0.001). The AUCs were 0.84 (95% CI 0.78-0.89) for deep learning method and 0.70 (95% CI 0.63-0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

High-resolution and high sensitivity mesoscopic fluorescence tomography based on de-scanning EMCCD: System design and thick tissue imaging applications

NASA Astrophysics Data System (ADS)

Ozturk, Mehmet Saadeddin

Optical microscopy has been one of the essential tools for biological studies for decades, however, its application areas was limited to superficial investigation due to strong scattering in live tissues. Even though advanced techniques such as confocal or multiphoton methods have been recently developed to penetrate beyond a few hundreds of microns deep in tissues, they still cannot perform in the mesoscopic regime (millimeter scale) without using destructive sample preparation protocols such as clearing techniques. They provide rich cellular information; however, they cannot be readily employed to investigate the biological processes at larger scales. Herein, we will present our effort to establish a novel imaging approach that can quantify molecular expression in intact tissues, well beyond the current microscopy depth limits. Mesoscopic Fluorescence Molecular Tomography (MFMT) is an emerging imaging modality that offers unique potential for the non-invasive molecular assessment of thick in-vitro and in-vivo live tissues. This novel imaging modality is based on an optical inverse problem that allows for retrieval of the quantitative spatial distribution of fluorescent tagged bio-markers at millimeter depth. MFMT is well-suited for in-vivo subsurface tissue imaging and thick bio-printed specimens due to its high sensitivity and fast acquisition times, as well as relatively large fields of view. Herein, we will first demonstrate the potential of this technique using our first generation MFMT system applied to multiplexed reporter gene imaging (in-vitro) and determination of Photodynamic Therapy (PDT) agent bio-distribution in a mouse model (in-vivo). Second, we will present the design rationale, in silico benchmarking, and experimental validation of a second generation MFMT (2GMFMT) system. We will demonstrate the gain in resolution and sensitivity achieved due to the de-scanned dense detector configuration implemented. The potential of this novel platform will be showcased by applying it to the longitudinal assessment of Ink-Jet Bio-Printed tumor models. This preliminary investigation focuses on monitoring four patient-derived glioblastoma multiforme (GBM) spheroids within their bioreactor for up to 70 days and following their volume change prior to and after exposure to a cytotoxic drug. Overall, our studies indicate that 2GMFMT is a powerful technique for in-vitro and in-vivo thick tissue molecular imaging applications due to its high resolution, fast tomographic imaging capability, and high sensitivity.

Image analysis and machine learning in digital pathology: Challenges and opportunities.

PubMed

Madabhushi, Anant; Lee, George

2016-10-01

With the rise in whole slide scanner technology, large numbers of tissue slides are being scanned and represented and archived digitally. While digital pathology has substantial implications for telepathology, second opinions, and education there are also huge research opportunities in image computing with this new source of "big data". It is well known that there is fundamental prognostic data embedded in pathology images. The ability to mine "sub-visual" image features from digital pathology slide images, features that may not be visually discernible by a pathologist, offers the opportunity for better quantitative modeling of disease appearance and hence possibly improved prediction of disease aggressiveness and patient outcome. However the compelling opportunities in precision medicine offered by big digital pathology data come with their own set of computational challenges. Image analysis and computer assisted detection and diagnosis tools previously developed in the context of radiographic images are woefully inadequate to deal with the data density in high resolution digitized whole slide images. Additionally there has been recent substantial interest in combining and fusing radiologic imaging and proteomics and genomics based measurements with features extracted from digital pathology images for better prognostic prediction of disease aggressiveness and patient outcome. Again there is a paucity of powerful tools for combining disease specific features that manifest across multiple different length scales. The purpose of this review is to discuss developments in computational image analysis tools for predictive modeling of digital pathology images from a detection, segmentation, feature extraction, and tissue classification perspective. We discuss the emergence of new handcrafted feature approaches for improved predictive modeling of tissue appearance and also review the emergence of deep learning schemes for both object detection and tissue classification. We also briefly review some of the state of the art in fusion of radiology and pathology images and also combining digital pathology derived image measurements with molecular "omics" features for better predictive modeling. The review ends with a brief discussion of some of the technical and computational challenges to be overcome and reflects on future opportunities for the quantitation of histopathology. Copyright © 2016 Elsevier B.V. All rights reserved.

Overview of deep learning in medical imaging.

PubMed

Suzuki, Kenji

2017-09-01

The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a lesser number of training cases than did CNNs. "Deep learning", or ML with image input, in medical imaging is an explosively growing, promising field. It is expected that ML with image input will be the mainstream area in the field of medical imaging in the next few decades.

Anatomy and histology of apical support: a literature review concerning cardinal and uterosacral ligaments.

PubMed

Ramanah, Rajeev; Berger, Mitchell B; Parratte, Bernard M; DeLancey, John O L

2012-11-01

The objective of this work was to collect and summarize relevant literature on the anatomy, histology, and imaging of apical support of the upper vagina and the uterus provided by the cardinal (CL) and uterosacral (USL) ligaments. A literature search in English, French, and German languages was carried out with the keywords apical support, cardinal ligament, transverse cervical ligament, Mackenrodt ligament, parametrium, paracervix, retinaculum uteri, web, uterosacral ligament, and sacrouterine ligament in the PubMed database. Other relevant journal and textbook articles were sought by retrieving references cited in previous PubMed articles. Fifty references were examined in peer-reviewed journals and textbooks. The USL extends from the S2 to the S4 vertebra region to the dorsal margin of the uterine cervix and/or to the upper third of the posterior vaginal wall. It has a superficial and deep component. Autonomous nerve fibers are a major constituent of the deep USL. CL is defined as a perivascular sheath with a proximal insertion around the origin of the internal iliac artery and a distal insertion on the cervix and/or vagina. It is divided into a cranial (vascular) and a caudal (neural) portions. Histologically, it contains mainly vessels, with no distinct band of connective tissue. Both the deep USL and the caudal CL are closely related to the inferior hypogastric plexus. USL and CL are visceral ligaments, with mesentery-like structures containing vessels, nerves, connective tissue, and adipose tissue.

Anatomy and histology of apical support: a literature review concerning cardinal and uterosacral ligaments

PubMed Central

Ramanah, Rajeev; Berger, Mitchell B.; Parratte, Bernard M.

2014-01-01

The objective of this work was to collect and summarize relevant literature on the anatomy, histology, and imaging of apical support of the upper vagina and the uterus provided by the cardinal (CL) and uterosacral (USL) ligaments. A literature search in English, French, and German languages was carried out with the keywords apical support, cardinal ligament, transverse cervical ligament, Mackenrodt ligament, parametrium, paracervix, retinaculum uteri, web, uterosacral ligament, and sacrouterine ligament in the PubMed database. Other relevant journal and textbook articles were sought by retrieving references cited in previous PubMed articles. Fifty references were examined in peer-reviewed journals and textbooks. The USL extends from the S2 to the S4 vertebra region to the dorsal margin of the uterine cervix and/or to the upper third of the posterior vaginal wall. It has a superficial and deep component. Autonomous nerve fibers are a major constituent of the deep USL. CL is defined as a perivascular sheath with a proximal insertion around the origin of the internal iliac artery and a distal insertion on the cervix and/or vagina. It is divided into a cranial (vascular) and a caudal (neural) portions. Histologically, it contains mainly vessels, with no distinct band of connective tissue. Both the deep USL and the caudal CL are closely related to the inferior hypogastric plexus. USL and CL are visceral ligaments, with mesentery-like structures containing vessels, nerves, connective tissue, and adipose tissue. PMID:22618209

Neuropathologic Characterization of Pontocerebellar Hypoplasia Type 6 Associated With Cardiomyopathy and Hydrops Fetalis and Severe Multisystem Respiratory Chain Deficiency due to Novel RARS2 Mutations.

PubMed

Lax, Nichola Z; Alston, Charlotte L; Schon, Katherine; Park, Soo-Mi; Krishnakumar, Deepa; He, Langping; Falkous, Gavin; Ogilvy-Stuart, Amanda; Lees, Christoph; King, Rosalind H; Hargreaves, Iain P; Brown, Garry K; McFarland, Robert; Dean, Andrew F; Taylor, Robert W

2015-07-01

Autosomal recessive mutations in the RARS2 gene encoding the mitochondrial arginyl-transfer RNA synthetase cause infantile-onset myoencephalopathy pontocerebellar hypoplasia type 6 (PCH6). We describe 2 sisters with novel compound heterozygous RARS2 mutations who presented perinatally with neurologic features typical of PCH6 but with additional features including cardiomyopathy, hydrops, and pulmonary hypoplasia and who died at 1 day and 14 days of age. Magnetic resonance imaging findings included marked cerebellar hypoplasia, gyral immaturity, punctate lesions in cerebral white matter, and unfused deep cerebral grey matter. Enzyme histochemistry of postmortem tissues revealed a near-global cytochrome c oxidase-deficiency; assessment of respiratory chain enzyme activities confirmed severe deficiencies involving complexes I, III, and IV. Molecular genetic studies revealed 2 RARS2 gene mutations: a c.1A>G, p.? variant predicted to abolish the initiator methionine, and a deep intronic c.613-3927C>T variant causing skipping of exons 6-8 in the mature RARS2 transcript. Neuropathologic investigation included low brain weights, small brainstem and cerebellum, deep cerebral white matter pathology, pontine nucleus neuron loss (in 1 sibling), and peripheral nerve pathology. Mitochondrial respiratory chain immunohistochemistry in brain tissues confirmed an absence of complexes I and IV immunoreactivity with sparing of mitochondrial numbers. These cases expand the clinical spectrum of RARS2 mutations, including antenatal features and widespread mitochondrial respiratory chain deficiencies in postmortem brain tissues.

Neuropathologic Characterization of Pontocerebellar Hypoplasia Type 6 Associated With Cardiomyopathy and Hydrops Fetalis and Severe Multisystem Respiratory Chain Deficiency due to Novel RARS2 Mutations

PubMed Central

Lax, Nichola Z.; Alston, Charlotte L.; Schon, Katherine; Park, Soo-Mi; Krishnakumar, Deepa; He, Langping; Falkous, Gavin; Ogilvy-Stuart, Amanda; Lees, Christoph; King, Rosalind H.; Hargreaves, Iain P.; Brown, Garry K.; McFarland, Robert; Dean, Andrew F.; Taylor, Robert W.

2015-01-01

Abstract Autosomal recessive mutations in the RARS2 gene encoding the mitochondrial arginyl-transfer RNA synthetase cause infantile-onset myoencephalopathy pontocerebellar hypoplasia type 6 (PCH6). We describe 2 sisters with novel compound heterozygous RARS2 mutations who presented perinatally with neurologic features typical of PCH6 but with additional features including cardiomyopathy, hydrops, and pulmonary hypoplasia and who died at 1 day and 14 days of age. Magnetic resonance imaging findings included marked cerebellar hypoplasia, gyral immaturity, punctate lesions in cerebral white matter, and unfused deep cerebral grey matter. Enzyme histochemistry of postmortem tissues revealed a near-global cytochrome c oxidase-deficiency; assessment of respiratory chain enzyme activities confirmed severe deficiencies involving complexes I, III, and IV. Molecular genetic studies revealed 2 RARS2 gene mutations: a c.1A>G, p.? variant predicted to abolish the initiator methionine, and a deep intronic c.613-3927C>T variant causing skipping of exons 6–8 in the mature RARS2 transcript. Neuropathologic investigation included low brain weights, small brainstem and cerebellum, deep cerebral white matter pathology, pontine nucleus neuron loss (in 1 sibling), and peripheral nerve pathology. Mitochondrial respiratory chain immunohistochemistry in brain tissues confirmed an absence of complexes I and IV immunoreactivity with sparing of mitochondrial numbers. These cases expand the clinical spectrum of RARS2 mutations, including antenatal features and widespread mitochondrial respiratory chain deficiencies in postmortem brain tissues. PMID:26083569

Image-guided smart laser system for precision implantation of cells in cartilage

NASA Astrophysics Data System (ADS)

Katta, Nitesh; Rector, John A.; Gardner, Michael R.; McElroy, Austin B.; Choy, Kevin C.; Crosby, Cody; Zoldan, Janet; Milner, Thomas E.

2017-03-01

State-of-the-art treatment for joint diseases like osteoarthritis focus on articular cartilage repair/regeneration by stem cell implantation therapy. However, the technique is limited by a lack of precision in the physician's imaging and cell deposition toolkit. We describe a novel combination of high-resolution, rapid scan-rate optical coherence tomography (OCT) alongside a short-pulsed nanosecond thulium (Tm) laser for precise cell seeding in cartilage. The superior beam quality of thulium lasers and wavelength of operation 1940 nm offers high volumetric tissue removal rates and minimizes the residual thermal footprint. OCT imaging enables targeted micro-well placement, precise cell deposition, and feature contrast. A bench-top system is constructed using a 15 W, 1940 nm, nanosecond-pulsed Tm fiber laser (500 μJ pulse energy, 100 ns pulse duration, 30kHz repetition rate) for removing tissue, and a swept source laser (1310 ± 70 nm, 100 kHz sweep rate) for OCT imaging, forming a combined Tm/OCT system - a "smart laser knife". OCT assists the smart laser knife user in characterizing cartilage to inform micro-well placement. The Tm laser creates micro-wells (2.35 mm diameter length, 1.5 mm width, 300 μm deep) and micro-incisions (1 mm wide, 200 μm deep) while OCT image-guidance assists and demonstrates this precision cutting and cell deposition with real-time feedback. To test micro-well creation and cell deposition protocol, gelatin phantoms are constructed mimicking cartilage optical properties and physiological structure. Cell viability is then assessed to illustrate the efficacy of the hydrogel deposition. Automated OCT feedback is demonstrated for cutting procedures to avoid important surface/subsurface structures. This bench-top smart laser knife system described here offers a new image-guided approach to precise stem cell seeding that can enhance the efficacy of articular cartilage repair.

Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples.

PubMed

Turkki, Riku; Linder, Nina; Kovanen, Panu E; Pellinen, Teijo; Lundin, Johan

2016-01-01

Immune cell infiltration in tumor is an emerging prognostic biomarker in breast cancer. The gold standard for quantification of immune cells in tissue sections is visual assessment through a microscope, which is subjective and semi-quantitative. In this study, we propose and evaluate an approach based on antibody-guided annotation and deep learning to quantify immune cell-rich areas in hematoxylin and eosin (H&E) stained samples. Consecutive sections of formalin-fixed parafin-embedded samples obtained from the primary tumor of twenty breast cancer patients were cut and stained with H&E and the pan-leukocyte CD45 antibody. The stained slides were digitally scanned, and a training set of immune cell-rich and cell-poor tissue regions was annotated in H&E whole-slide images using the CD45-expression as a guide. In analysis, the images were divided into small homogenous regions, superpixels, from which features were extracted using a pretrained convolutional neural network (CNN) and classified with a support of vector machine. The CNN approach was compared to texture-based classification and to visual assessments performed by two pathologists. In a set of 123,442 labeled superpixels, the CNN approach achieved an F-score of 0.94 (range: 0.92-0.94) in discrimination of immune cell-rich and cell-poor regions, as compared to an F-score of 0.88 (range: 0.87-0.89) obtained with the texture-based classification. When compared to visual assessment of 200 images, an agreement of 90% (κ = 0.79) to quantify immune infiltration with the CNN approach was achieved while the inter-observer agreement between pathologists was 90% (κ = 0.78). Our findings indicate that deep learning can be applied to quantify immune cell infiltration in breast cancer samples using a basic morphology staining only. A good discrimination of immune cell-rich areas was achieved, well in concordance with both leukocyte antigen expression and pathologists' visual assessment.

Frostbite: Spectrum of Imaging Findings and Guidelines for Management

PubMed Central

Brown, Richard K. J.; Levi, Benjamin; Kraft, Casey T.; Jacobson, Jon A.; Gross, Milton D.; Wong, Ka Kit

2016-01-01

Frostbite is a localized cold thermal injury that results from tissue freezing. Frostbite injuries can have a substantial effect on long-term limb function and mobility if not promptly evaluated and treated. Imaging plays a critical role in initial evaluation of frostbite injuries and in monitoring response to treatment. A multimodality approach involving radiography, digital subtraction angiography (DSA), and/or multiphase bone scintigraphy with hybrid single photon emission computed tomography (SPECT)/computed tomography (CT) is often necessary for optimal guidance of frostbite care. Radiographs serve as an initial survey of the affected limb and may demonstrate characteristic findings, depending on the time course and severity of injury. DSA is used to evaluate perfusion of affected soft tissues and identify potential targets for therapeutic intervention. Angiography-directed thrombolysis plays an essential role in tissue preservation and salvage in deep frostbite injuries. Multiphase bone scintigraphy with technetium 99m–labeled diphosphonate provides valuable information regarding the status of tissue viability after initial treatment. The addition of SPECT/CT to multiphase bone scintigraphy enables precise anatomic localization of the level and depth of tissue necrosis before its appearance at physical examination and can help uncover subtle findings that may remain occult at scintigraphy alone. Multiphase bone scintigraphy with SPECT/CT is the modality of choice for prognostication and planning of definitive surgical care of affected limbs. Appropriate use of imaging to direct frostbite care can help limit the effects that these injuries have on limb function and mobility. ©RSNA, 2016 PMID:27494386

Optical Coherence Tomography for Brain Imaging

NASA Astrophysics Data System (ADS)

Liu, Gangjun; Chen, Zhongping

Recently, there has been growing interest in using OCT for brain imaging. A feasibility study of OCT for guiding deep brain probes has found that OCT can differentiate the white matter and gray matter because the white matter tends to have a higher peak reflectivity and steeper attenuation rate compared to gray matter. In vivo 3D visualization of the layered organization of a rat olfactory bulb with OCT has been demonstrated. OCT has been used for single myelin fiber imaging in living rodents without labeling. The refractive index in the rat somatosensory cortex has also been measured with OCT. In addition, functional extension of OCT, such as Doppler-OCT (D-OCT), polarization sensitive-OCT (PS-OCT), and phase-resolved-OCT (PR-OCT), can image and quantify physiological parameters in addition to the morphological structure image. Based on the scattering changes during neural activity, OCT has been used to measure the functional activation in neuronal tissues. PS-OCT, which combines polarization sensitive detection with OCT to determine tissue birefringence, has been used for the localization of nerve fiber bundles and the mapping of micrometer-scale fiber pathways in the brain. D-OCT, also named optical Doppler tomography (ODT), combines the Doppler principle with OCT to obtain high resolution tomographic images of moving constituents in highly scattering biological tissues. D-OCT has been successfully used to image cortical blood flow and map the blood vessel network for brain research. In this chapter, the principle and technology of OCT and D-OCT are reviewed and examples of potential applications are described.

Imaging a photodynamic therapy photosensitizer in vivo with a time-gated fluorescence tomography system

NASA Astrophysics Data System (ADS)

Mo, Weirong; Rohrbach, Daniel; Sunar, Ulas

2012-07-01

We report the tomographic imaging of a photodynamic therapy (PDT) photosensitizer, 2-(1-hexyloxyethyl)-2-devinyl pyropheophorbide-a (HPPH) in vivo with time-domain fluorescence diffuse optical tomography (TD-FDOT). Simultaneous reconstruction of fluorescence yield and lifetime of HPPH was performed before and after PDT. The methodology was validated in phantom experiments, and depth-resolved in vivo imaging was achieved through simultaneous three-dimensional (3-D) mappings of fluorescence yield and lifetime contrasts. The tomographic images of a human head-and-neck xenograft in a mouse confirmed the preferential uptake and retention of HPPH by the tumor 24-h post-injection. HPPH-mediated PDT induced significant changes in fluorescence yield and lifetime. This pilot study demonstrates that TD-FDOT may be a good imaging modality for assessing photosensitizer distributions in deep tissue during PDT monitoring.

KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images.

PubMed

Eo, Taejoon; Jun, Yohan; Kim, Taeseong; Jang, Jinseong; Lee, Ho-Joon; Hwang, Dosik

2018-04-06

To demonstrate accurate MR image reconstruction from undersampled k-space data using cross-domain convolutional neural networks (CNNs) METHODS: Cross-domain CNNs consist of 3 components: (1) a deep CNN operating on the k-space (KCNN), (2) a deep CNN operating on an image domain (ICNN), and (3) an interleaved data consistency operations. These components are alternately applied, and each CNN is trained to minimize the loss between the reconstructed and corresponding fully sampled k-spaces. The final reconstructed image is obtained by forward-propagating the undersampled k-space data through the entire network. Performances of K-net (KCNN with inverse Fourier transform), I-net (ICNN with interleaved data consistency), and various combinations of the 2 different networks were tested. The test results indicated that K-net and I-net have different advantages/disadvantages in terms of tissue-structure restoration. Consequently, the combination of K-net and I-net is superior to single-domain CNNs. Three MR data sets, the T 2 fluid-attenuated inversion recovery (T 2 FLAIR) set from the Alzheimer's Disease Neuroimaging Initiative and 2 data sets acquired at our local institute (T 2 FLAIR and T 1 weighted), were used to evaluate the performance of 7 conventional reconstruction algorithms and the proposed cross-domain CNNs, which hereafter is referred to as KIKI-net. KIKI-net outperforms conventional algorithms with mean improvements of 2.29 dB in peak SNR and 0.031 in structure similarity. KIKI-net exhibits superior performance over state-of-the-art conventional algorithms in terms of restoring tissue structures and removing aliasing artifacts. The results demonstrate that KIKI-net is applicable up to a reduction factor of 3 to 4 based on variable-density Cartesian undersampling. © 2018 International Society for Magnetic Resonance in Medicine.

Speckle contrast optical tomography: A new method for deep tissue three-dimensional tomography of blood flow

PubMed Central

Varma, Hari M.; Valdes, Claudia P.; Kristoffersen, Anna K.; Culver, Joseph P.; Durduran, Turgut

2014-01-01

A novel tomographic method based on the laser speckle contrast, speckle contrast optical tomography (SCOT) is introduced that allows us to reconstruct three dimensional distribution of blood flow in deep tissues. This method is analogous to the diffuse optical tomography (DOT) but for deep tissue blood flow. We develop a reconstruction algorithm based on first Born approximation to generate three dimensional distribution of flow using the experimental data obtained from tissue simulating phantoms. PMID:24761306

Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

2017-05-01

Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

Second Harmonic Generation of Unpolarized Light

NASA Astrophysics Data System (ADS)

Ding, Changqin; Ulcickas, James R. W.; Deng, Fengyuan; Simpson, Garth J.

2017-11-01

A Mueller tensor mathematical framework was applied for predicting and interpreting the second harmonic generation (SHG) produced with an unpolarized fundamental beam. In deep tissue imaging through SHG and multiphoton fluorescence, partial or complete depolarization of the incident light complicates polarization analysis. The proposed framework has the distinct advantage of seamlessly merging the purely polarized theory based on the Jones or Cartesian susceptibility tensors with a more general Mueller tensor framework capable of handling partial depolarized fundamental and/or SHG produced. The predictions of the model are in excellent agreement with experimental measurements of z -cut quartz and mouse tail tendon obtained with polarized and depolarized incident light. The polarization-dependent SHG produced with unpolarized fundamental allowed determination of collagen fiber orientation in agreement with orthogonal methods based on image analysis. This method has the distinct advantage of being immune to birefringence or depolarization of the fundamental beam for structural analysis of tissues.

Control of rabbit dura mater optical properties with osmotical liquids

NASA Astrophysics Data System (ADS)

Yao, Lei; Cheng, Haiying; Luo, Qingming; Zhang, Wei; Zeng, Shaoqun; Tuchin, Valery V.

2002-04-01

An experimental study of controlling the optical properties of in vitro and in vivo rabbit dura mater with administration of osmotical agents, 40% glucose solution and glycerol, using video camera and spectrometer was presented. The preliminary results of experimental study of influence of osmotical liquids (glucose solutions, glycerol) on transmittance (in vitro) and reflectance (in vivo) spectra of rabbit dura mater were reported. The significant decreasing of the reflectance and increasing of the transmittance of dura mater under action of osmotical solutions were demonstrated. Experiments showed that administration of osmolytes to dura mater allowed for effective and temporary control of its optical characteristics, which made dura mater more transparent, increased the ability of light penetrating the tissue, and consequently improved the optical imaging depth. It is a significant study, which can improve penetration of optical imaging of cerebral function and acquire more information of the deep brain tissue.

In Vivo Noninvasive Analysis of Human Forearm Muscle Function and Fatigue: Applications to EVA Operations and Training Maneuvers

NASA Technical Reports Server (NTRS)

Fotedar, L. K.; Marshburn, T.; Quast, M. J.; Feeback, D. L.

1999-01-01

Forearm muscle fatigue is one of the major limiting factors affecting endurance during performance of deep-space extravehicular activity (EVA) by crew members. Magnetic resonance (MR) provides in vivo noninvasive analysis of tissue level metabolism and fluid exchange dynamics in exercised forearm muscles through the monitoring of proton magnetic resonance imaging (MRI) and phosphorus magnetic resonance spectroscopy (P-31-MRS) parameter variations. Using a space glove box and EVA simulation protocols, we conducted a preliminary MRS/MRI study in a small group of human test subjects during submaximal exercise and recovery and following exhaustive exercise. In assessing simulated EVA-related muscle fatigue and function, this pilot study revealed substantial changes in the MR image longitudinal relaxation times (T2) as an indicator of specific muscle activation and proton flux as well as changes in spectral phosphocreatine-to-phosphate (PCr/Pi) levels as a function of tissue bioenergetic potential.

Three-Dimensional Analysis of Long-Term Midface Volume Change After Vertical Vector Deep-Plane Rhytidectomy.

PubMed

Jacono, Andrew A; Malone, Melanie H; Talei, Benjamin

2015-07-01

Facial aging is a complicated process that includes volume loss and soft tissue descent. This study provides quantitative 3-dimensional (3D) data on the long-term effect of vertical vector deep-plane rhytidectomy on restoring volume to the midface. To determine if primary vertical vector deep-plane rhytidectomy resulted in long-term volume change in the midface. We performed a prospective study on patients undergoing primary vertical vector deep-plane rhytidectomy to quantitate 3D volume changes in the midface. Quantitative analysis of volume changes was made using the Vectra 3D imaging software (Canfield Scientific, Inc, Fairfield, New Jersey) at a minimum follow-up of 1 year. Forty-three patients (86 hemifaces) were analyzed. The average volume gained in each hemi-midface after vertical vector deep-plane rhytidectomy was 3.2 mL. Vertical vector deep-plane rhytidectomy provides significant long-term augmentation of volume in the midface. These quantitative data demonstrate that some midface volume loss is related to gravitational descent of the cheek fat compartments and that vertical vector deep-plane rhytidectomy may obviate the need for other volumization procedures such as autologous fat grafting in selected cases. 4 Therapeutic. © 2015 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

In vivo photoacoustic imaging of mouse embryos

NASA Astrophysics Data System (ADS)

Laufer, Jan; Norris, Francesca; Cleary, Jon; Zhang, Edward; Treeby, Bradley; Cox, Ben; Johnson, Peter; Scambler, Pete; Lythgoe, Mark; Beard, Paul

2012-06-01

The ability to noninvasively image embryonic vascular anatomy in mouse models is an important requirement for characterizing the development of the normal cardiovascular system and malformations in the heart and vascular supply. Photoacoustic imaging, which can provide high resolution non invasive images of the vasculature based upon optical absorption by endogenous hemoglobin, is well suited to this application. In this study, photoacoustic images of mouse embryos were obtained ex vivo and in vivo. The images show intricate details of the embryonic vascular system to depths of up to 10 mm, which allowed whole embryos to be imaged in situ. To achieve this, an all-optical photoacoustic scanner and a novel time reversal image reconstruction algorithm, which provide deep tissue imaging capability while maintaining high spatial resolution and contrast were employed. This technology may find application as an imaging tool for preclinical embryo studies in developmental biology as well as more generally in preclinical and clinical medicine for studying pathologies characterized by changes in the vasculature.

Context aware decision support in neurosurgical oncology based on an efficient classification of endomicroscopic data.

PubMed

Li, Yachun; Charalampaki, Patra; Liu, Yong; Yang, Guang-Zhong; Giannarou, Stamatia

2018-06-13

Probe-based confocal laser endomicroscopy (pCLE) enables in vivo, in situ tissue characterisation without changes in the surgical setting and simplifies the oncological surgical workflow. The potential of this technique in identifying residual cancer tissue and improving resection rates of brain tumours has been recently verified in pilot studies. The interpretation of endomicroscopic information is challenging, particularly for surgeons who do not themselves routinely review histopathology. Also, the diagnosis can be examiner-dependent, leading to considerable inter-observer variability. Therefore, automatic tissue characterisation with pCLE would support the surgeon in establishing diagnosis as well as guide robot-assisted intervention procedures. The aim of this work is to propose a deep learning-based framework for brain tissue characterisation for context aware diagnosis support in neurosurgical oncology. An efficient representation of the context information of pCLE data is presented by exploring state-of-the-art CNN models with different tuning configurations. A novel video classification framework based on the combination of convolutional layers with long-range temporal recursion has been proposed to estimate the probability of each tumour class. The video classification accuracy is compared for different network architectures and data representation and video segmentation methods. We demonstrate the application of the proposed deep learning framework to classify Glioblastoma and Meningioma brain tumours based on endomicroscopic data. Results show significant improvement of our proposed image classification framework over state-of-the-art feature-based methods. The use of video data further improves the classification performance, achieving accuracy equal to 99.49%. This work demonstrates that deep learning can provide an efficient representation of pCLE data and accurately classify Glioblastoma and Meningioma tumours. The performance evaluation analysis shows the potential clinical value of the technique.

Development and characterization of non-resonant multiphoton photoacoustic spectroscopy (NMPPAS) for brain tumor margining

NASA Astrophysics Data System (ADS)

Dahal, Sudhir

During tumor removal surgery, due to the problems associated with obtaining high-resolution, real-time chemical images of where exactly the tumor ends and healthy tissue begins (tumor margining), it is often necessary to remove a much larger volume of tissue than the tumor itself. In the case of brain tumor surgery, however, it is extremely unsafe to remove excess tissue. Therefore, without an accurate image of the tumor margins, some of the tumor's finger-like projections are inevitably left behind in the surrounding parenchyma to grow again. For this reason, the development of techniques capable of providing high-resolution real-time images of tumor margins up to centimeters below the surface of a tissue is ideal for the diagnosis and treatment of tumors, as well as surgical guidance during brain tumor excision. A novel spectroscopic technique, non-resonant multiphoton photoacoustic spectroscopy (NMPPAS), is being developed with the capabilities of obtaining high-resolution subsurface chemical-based images of underlying tumors. This novel technique combines the strengths of multiphoton tissue spectroscopy and photoacoustic spectroscopy into a diagnostic methodology that will, ultimately, provide unparalleled chemical information and images to provide the state of sub-surface tissues. The NMPPAS technique employs near-infrared light (in the diagnostic window) to excite ultraviolet and/or visible light absorbing species deep below the tissue's surface. Once a multiphoton absorption event occurs, non-radiative relaxation processes generates a localized thermal expansion and subsequent acoustic wave that can be detected using a piezoelectric transducer. Since NMPPAS employs an acoustic detection modality, much deeper diagnoses can be performed than that is possible using current state of the art high-resolution chemical imaging techniques such as multiphoton fluorescence spectroscopy. NMPPAS was employed to differentiate between excised brain tumors (astrocytoma III) and healthy tissue with over 99% accuracy. NMPPAS spectral features showed evident differences between tumor and healthy tissues, and ratiometric analysis ensured that only a few wavelengths could be used for excitation instead of using numerous wavelength excitations to create spectra. This process would significantly reduce the analysis time while maintaining the same degree of accuracy. Tissue phantoms were fabricated in order to characterize the properties of NMPPAS. Scattering particles were doped into the phantoms to simulate their light scattering properties to real tissues. This allowed for better control over shape, size, reproducibility and doping in the sample while maintaining the light-tissue interaction properties of real tissue. To make NMPPAS viable for clinical applications, the technique was characterized to determine the spatial (lateral and longitudinal) resolution, depth of penetration and its ability to image in three-dimension through layers of tissue. Both resolutions were determined to be near-cellular level resolution (50-70 microm), obtained initially with the aid of the technique of multiphoton fluorescence, and later verified using NMPPAS imaging. Additionally, the maximum depth of penetration and detection was determined to be about 1.4cm, making the technique extremely suitable to margin tumors from underlying tissues in the brain. The capability of NMPPAS to detect and image layers that lie beneath other structures and blood vessels was also investigated. Three-dimensional images were obtained for the first time using NMPPAS. The images were obtained from different depths and structures were imaged through other layers of existing structures in the sample. This verified that NMPPAS was capable of detecting and imaging structures that lie embedded within the tissues. NMPPAS images of embedded structures were also obtained with the presence of hemoglobin, which is potentially the largest source of background in blood-perfused tissues, thus showing that the technique is capable of detecting and differentiating in blood-perfused samples.

Three-Photon Luminescence of Gold Nanorods Excited by 1040 nm Femtosecond Laser for High Contrast Tissue and In Vivo Imaging

NASA Astrophysics Data System (ADS)

Wang, Shaowei; Zhao, Xinyuan; Zhang, Hequn; Cai, Fuhong; Qian, Jun

2016-01-01

Gold Nanorods (GNRs) with tunable aspect ratios can strongly absorb and scatter light in the NIR region due to their localized surface plasmon resonance (LSPR) property, and have been demonstrated to exhibit strong plasmon enhanced multiphoton luminescence (MPL) with brightness many times stronger than the conventional organic chromophores. In this study, we synthesized GNRs with longitudinal LSPR peak at 1036 nm to match our home-built light source 1040 nm femtosecond laser, which locates in the “optical window” where the tissue absorbs relatively little light. PEGylated GNRs with great biocompatibility were intravenously injected through the tail vein into mice. Excited by 1040 nm laser, the GNRs exhibit bright three-photon luminescence (3PL) signals while circulating in the blood vessels. The use of GNRs as bright contrast agents for 3PL imaging of mouse ear blood vessels in vivo was demonstrated. And GNRs targeted in tissues can be excited by 1040 nm laser and could be clearly visualized with no autofluorescence background. These results indicated that 3PL of GNRs is very promising for deep in vivo bioimaging and assessing the distribution of GNRs in tissues with high contrast.

Non-contact photoacoustic tomography and ultrasonography for brain imaging

NASA Astrophysics Data System (ADS)

Rousseau, Guy; Blouin, Alain; Monchalin, Jean-Pierre

2012-02-01

Photoacoustic tomography (PAT) and ultrasonography (US) of biological tissues usually rely on transducer arrays for the detection of ultrasound. Obtaining the best sensitivity requires a physical contact with the tissue using an intermediate coupling fluid (water or gel). This type of contact is a major drawback for several applications such as neurosurgery. Laser-ultrasonics is an established optical technique for the non-contact generation and detection of ultrasound in industrial materials. In this paper, the non-contact detection scheme used in laser-ultrasonics is adapted to allow probing of ultrasound in biological tissues while remaining below laser exposure safety limits. Both non-contact PAT (NCPAT) and non-contact US (NCUS) are demonstrated experimentally using a single-frequency detection laser emitting suitably shaped pulses and a confocal Fabry-Perot interferometer. It is shown that an acceptable sensitivity is obtained while remaining below the maximum permissible exposure (MPE) of biological tissues. Results obtained ex vivo with a calf brain specimen show that sub-mm endogenous and exogenous inclusions can be detected at depths exceeding 1 cm. When fully developed, the technique could be a unique diagnostic tool in neurosurgery providing deep imaging of blood vessels, blood clots and blood oxygenation.

Burn-injured tissue detection for debridement surgery through the combination of non-invasive optical imaging techniques.

PubMed

Heredia-Juesas, Juan; Thatcher, Jeffrey E; Lu, Yang; Squiers, John J; King, Darlene; Fan, Wensheng; DiMaio, J Michael; Martinez-Lorenzo, Jose A

2018-04-01

The process of burn debridement is a challenging technique requiring significant skills to identify the regions that need excision and their appropriate excision depths. In order to assist surgeons, a machine learning tool is being developed to provide a quantitative assessment of burn-injured tissue. This paper presents three non-invasive optical imaging techniques capable of distinguishing four kinds of tissue-healthy skin, viable wound bed, shallow burn, and deep burn-during serial burn debridement in a porcine model. All combinations of these three techniques have been studied through a k-fold cross-validation method. In terms of global performance, the combination of all three techniques significantly improves the classification accuracy with respect to just one technique, from 0.42 up to more than 0.76. Furthermore, a non-linear spatial filtering based on the mode of a small neighborhood has been applied as a post-processing technique, in order to improve the performance of the classification. Using this technique, the global accuracy reaches a value close to 0.78 and, for some particular tissues and combination of techniques, the accuracy improves by 13%.

Detection of lobular structures in normal breast tissue.

PubMed

Apou, Grégory; Schaadt, Nadine S; Naegel, Benoît; Forestier, Germain; Schönmeyer, Ralf; Feuerhake, Friedrich; Wemmert, Cédric; Grote, Anne

2016-07-01

Ongoing research into inflammatory conditions raises an increasing need to evaluate immune cells in histological sections in biologically relevant regions of interest (ROIs). Herein, we compare different approaches to automatically detect lobular structures in human normal breast tissue in digitized whole slide images (WSIs). This automation is required to perform objective and consistent quantitative studies on large data sets. In normal breast tissue from nine healthy patients immunohistochemically stained for different markers, we evaluated and compared three different image analysis methods to automatically detect lobular structures in WSIs: (1) a bottom-up approach using the cell-based data for subsequent tissue level classification, (2) a top-down method starting with texture classification at tissue level analysis of cell densities in specific ROIs, and (3) a direct texture classification using deep learning technology. All three methods result in comparable overall quality allowing automated detection of lobular structures with minor advantage in sensitivity (approach 3), specificity (approach 2), or processing time (approach 1). Combining the outputs of the approaches further improved the precision. Different approaches of automated ROI detection are feasible and should be selected according to the individual needs of biomarker research. Additionally, detected ROIs could be used as a basis for quantification of immune infiltration in lobular structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sex differences and hormonal modulation of deep tissue pain

PubMed Central

Traub, Richard J.; Ji, Yaping

2013-01-01

Women disproportionately suffer from many deep tissue pain conditions. Experimental studies show that women have lower pain thresholds, higher pain ratings and less tolerance to a range of painful stimuli. Most clinical and epidemiological reports suggest female gonadal hormones modulate pain for some, but not all, conditions. Similarly, animal studies support greater nociceptive sensitivity in females in many deep tissue pain models. Gonadal hormones modulate responses in primary afferents, dorsal horn neurons and supraspinal sites, but the direction of modulation is variable. This review will examine sex differences in deep tissue pain in humans and animals focusing on the role of gonadal hormones (mainly estradiol) as an underlying component of the modulation of pain sensitivity. PMID:23872333

Extracellular space preservation aids the connectomic analysis of neural circuits.

PubMed

Pallotto, Marta; Watkins, Paul V; Fubara, Boma; Singer, Joshua H; Briggman, Kevin L

2015-12-09

Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers

PubMed Central

Andresen, Volker; Sporbert, Anje

2014-01-01

Monitoring cellular communication by intravital deep-tissue multi-photon microscopy is the key for understanding the fate of immune cells within thick tissue samples and organs in health and disease. By controlling the scanning pattern in multi-photon microscopy and applying appropriate numerical algorithms, we developed a striped-illumination approach, which enabled us to achieve 3-fold better axial resolution and improved signal-to-noise ratio, i.e. contrast, in more than 100 µm tissue depth within highly scattering tissue of lymphoid organs as compared to standard multi-photon microscopy. The acquisition speed as well as photobleaching and photodamage effects were similar to standard photo-multiplier-based technique, whereas the imaging depth was slightly lower due to the use of field detectors. By using the striped-illumination approach, we are able to observe the dynamics of immune complex deposits on secondary follicular dendritic cells – on the level of a few protein molecules in germinal centers. PMID:24748007

In vivo photoacoustic monitoring of photosensitizer in skin: application to dosimetry for antibacterial photodynamic treatment

NASA Astrophysics Data System (ADS)

Hirao, Akihiro; Sato, Shunichi; Saitoh, Daizoh; Shinomiya, Nariyoshi; Ashida, Hiroshi; Obara, Minoru

2009-02-01

To obtain efficient antibacterial photodynamic effect in traumatic injuries such as burns, depth-resolved dosimetry of photosensitizer is required. In this study, we performed dual-wavelength photoacoustic (PA) measurement for rat burned skins injected with a photosensitizer. As a photosensitizer, methylene blue (MB) or porfimer sodium was injected into the subcutaneous tissue in rats with deep dermal burn. The wound was irradiated with red (665 nm or 630 nm) pulsed light to excite photosensitizers and green (532 nm) pulsed light to excite blood in the tissue; the latter signal was used to eliminate blood-associated component involved in the former signal. Acoustic attenuation was also compensated from the photosensitizer-associated PA signals. These signal processing was effective to obtain high-contrast image of a photosensitizer in the tissue. Behaviors of MB and porfimer sodium in the tissue were compared.

Implementation of spatial overlap modulation nonlinear optical microscopy using an electro-optic deflector

PubMed Central

Isobe, Keisuke; Kawano, Hiroyuki; Kumagai, Akiko; Miyawaki, Atsushi; Midorikawa, Katsumi

2013-01-01

A spatial overlap modulation (SPOM) technique is a nonlinear optical microscopy technique which enhances the three-dimensional spatial resolution and rejects the out-of-focus background limiting the imaging depth inside a highly scattering sample. Here, we report on the implementation of SPOM in which beam pointing modulation is achieved by an electro-optic deflector. The modulation and demodulation frequencies are enhanced to 200 kHz and 400 kHz, respectively, resulting in a 200-fold enhancement compared with the previously reported system. The resolution enhancement and suppression of the out-of-focus background are demonstrated by sum-frequency-generation imaging of pounded granulated sugar and deep imaging of fluorescent beads in a tissue-like phantom, respectively. PMID:24156055

A simple anaesthetic and monitoring system for magnetic resonance imaging.

PubMed

Rejger, V S; Cohn, B F; Vielvoye, G J; de Raadt, F B

1989-09-01

Clinical magnetic resonance imaging (MRI) is a digital tomographic technique which utilizes radio waves emitted by hydrogen protons in a powerful magnetic field to form an image of soft-tissue structures and abnormalities within the body. Unfortunately, because of the relatively long scanning time required and the narrow deep confines of the MRI tunnel and Faraday cage, some patients cannot be examined without the use of heavy sedation or general anaesthesia. Due to poor access to the patient and the strong magnetic field, several problems arise in monitoring and administering anaesthesia during this procedure. In this presentation these problems and their solutions, as resolved by our institution, are discussed. Of particular interest is the anaesthesia circuit specifically adapted for use during MRI scanning.

Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology

NASA Astrophysics Data System (ADS)

Heijblom, M.; Piras, D.; Brinkhuis, M.; van Hespen, J. C. G.; van den Engh, F. M.; van der Schaaf, M.; Klaase, J. M.; van Leeuwen, T. G.; Steenbergen, W.; Manohar, S.

2015-07-01

Photoacoustic (optoacoustic) imaging can visualize vasculature deep in tissue using the high contrast of hemoglobin to light, with the high-resolution possible with ultrasound detection. Since angiogenesis, one of the hallmarks of cancer, leads to increased vascularity, photoacoustics holds promise in imaging breast cancer as shown in proof-of-principle studies. Here for the first time, we investigate if there are specific photoacoustic appearances of breast malignancies which can be related to the tumor vascularity, using an upgraded research imaging system, the Twente Photoacoustic Mammoscope. In addition to comparisons with x-ray and ultrasound images, in subsets of cases the photoacoustic images were compared with MR images, and with vascular staining in histopathology. We were able to identify lesions in suspect breasts at the expected locations in 28 of 29 cases. We discovered generally three types of photoacoustic appearances reminiscent of contrast enhancement types reported in MR imaging of breast malignancies, and first insights were gained into the relationship with tumor vascularity.

NIR to NIR upconversion in KYb2F7: RE3+ (RE = Tm, Er) nanoparticles for biological imaging

NASA Astrophysics Data System (ADS)

Pedraza, F.; Yust, B.; Tsin, A.; Sardar, D.

2014-03-01

Until recently, many contrast agents widely used in biological imaging have absorbed and emitted in the visible region, limiting their usefulness for deeper tissue imaging. In order to push the boundaries of deep tissue imaging with non-ionizing radiation, contrast agents in the near infrared (NIR) regime, which is not strongly absorbed or scattered by most tissues, are being sought after. Upconverting nanoparticles (UCNPs) are attractive candidates since their upconversion emission is tunable with a very narrow bandwidth and they do not photobleach or blink. The upconversion produced by the nanoparticles can be tailored for NIR to NIR by carefully choosing the lanthanide dopants and dopant ratios such as KYb2F7: RE3+ (RE = Tm, Er). Spectroscopic characterization was done by analyzing absorption, fluorescence, and quantum yield data. In order to study the toxicity of the nanoparticles Monkey Retinal Endothelial Cells (MREC) were cultivated in 24 well plates and then treated with nanoparticles at different concentrations in triplicate to obtain the optimal concentration for in vivo experiments. It will be shown that these UCNPs do not elicit a strong toxic response such as quantum dots and some noble metal nanoparticles. 3-D optical slices of nanoparticle treated fibroblast cells were imaged using a confocal microscope where the nucleus and cytoplasm were stained with DAPI and Alexa Fluor respectively. These results presented support the initial assumption, which suggests that KYb2F7: RE3+ would be excellent candidates for NIR contrast agents.

Multiparametric evaluation of hindlimb ischemia using time-series indocyanine green fluorescence imaging.

PubMed

Guang, Huizhi; Cai, Chuangjian; Zuo, Simin; Cai, Wenjuan; Zhang, Jiulou; Luo, Jianwen

2017-03-01

Peripheral arterial disease (PAD) can further cause lower limb ischemia. Quantitative evaluation of the vascular perfusion in the ischemic limb contributes to diagnosis of PAD and preclinical development of new drug. In vivo time-series indocyanine green (ICG) fluorescence imaging can noninvasively monitor blood flow and has a deep tissue penetration. The perfusion rate estimated from the time-series ICG images is not enough for the evaluation of hindlimb ischemia. The information relevant to the vascular density is also important, because angiogenesis is an essential mechanism for post-ischemic recovery. In this paper, a multiparametric evaluation method is proposed for simultaneous estimation of multiple vascular perfusion parameters, including not only the perfusion rate but also the vascular perfusion density and the time-varying ICG concentration in veins. The target method is based on a mathematical model of ICG pharmacokinetics in the mouse hindlimb. The regression analysis performed on the time-series ICG images obtained from a dynamic reflectance fluorescence imaging system. The results demonstrate that the estimated multiple parameters are effective to quantitatively evaluate the vascular perfusion and distinguish hypo-perfused tissues from well-perfused tissues in the mouse hindlimb. The proposed multiparametric evaluation method could be useful for PAD diagnosis. The estimated perfusion rate and vascular perfusion density maps (left) and the time-varying ICG concentration in veins of the ankle region (right) of the normal and ischemic hindlimbs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Factors affecting the microbiological condition of the deep tissues of mechanically tenderized beef.

PubMed

Gill, C O; McGinnis, J C

2005-04-01

Whole or halved top butt prime beef cuts were treated in two types of mechanical tenderizing machines that both pierced the meat with thin blades but that used blades of different forms. Aerobes on meat surfaces and in the deep tissues of cuts after treatments were counted. When cuts were treated at a laboratory using a Lumar machine, the contamination of deep tissues increased significantly (P < 0.01) with increasing numbers of aerobic bacteria on meat surfaces and decreased significantly (P < 0.001) with increasing distance from the incised surface. However, contamination did not increase significantly (P > 0.1) with repeated incising of the meat. When halved cuts were incised one or eight times using a commercially cleaned Ross machine at a retail store, the numbers of aerobes recovered from deep tissues were similar with both treatments. When halved cuts were treated in one or other machine, deep tissue contamination was greater with the Lumar machine than with the Ross machine. Contamination of deep tissues as a result of tenderizing by piercing with thin blades can be minimized if the blades are designed to limit the number of bacteria carried into the meat and the microbiological condition of incised surface is well controlled.

Novel techniques with multiphoton microscopy: Deep-brain imaging with microprisms, neurometabolism of epilepsy, and counterfeit paper money detection

NASA Astrophysics Data System (ADS)

Chia, Thomas H.

Multiphoton microscopy is a laser-scanning fluorescence imaging method with extraordinary potential. We describe three innovative multiphoton microscopy techniques across various disciplines. Traditional in vivo fluorescence microscopy of the mammalian brain has a limited penetration depth (<400 microm). We present a method of imaging 1 mm deep into mouse neocortex by using a glass microprism to relay the excitation and emission light. This technique enables simultaneous imaging of multiple cortical layers, including layer V, at an angle typical of slice preparations. At high-magnification imaging using an objective with 1-mm of coverglass correction, resolution was sufficient to resolve dendritic spines on layer V GFP neurons. Functional imaging of blood flow at various neocortical depths is also presented, allowing for quantification of red blood cell flux and velocity. Multiphoton fluorescence lifetime imaging (FLIM) of NADH reveals information on neurometabolism. NADH, an intrinsic fluorescent molecule and ubiquitous metabolic coenzyme, has a lifetime dependent on enzymatic binding. A novel NADH FLIM algorithm is presented that produces images showing spatially distinct NADH fluorescence lifetimes in mammalian brain slices. This program provides advantages over traditional FLIM processing of multi-component lifetime data. We applied this technique to a GFP-GFAP pilocarpine mouse model of temporal lobe epilepsy. Results indicated significant changes in the neurometabolism of astrocytes and neuropil in the cell and dendritic layers of the hippocampus when compared to control tissue. Data obtained with NADH FLIM were subsequently interpreted based on the abnormal activity reported in epileptic tissue. Genuine U.S. Federal Reserve Notes have a consistent, two-component intrinsic fluorescence lifetime. This allows for detection of counterfeit paper money because of its significant differences in fluorescence lifetime when compared to genuine paper money. We used scanning multiphoton laser excitation to sample a ˜4 mm2 region from 54 genuine Reserve Notes. Three types of counterfeit samples were tested. Four out of the nine counterfeit samples fit to a one-component decay. Five out of nine counterfeit samples fit to a two-component model, but are identified as counterfeit due to significant deviations in the longer lifetime component compared to genuine bills.

The effects of deformation, ischemia, and reperfusion on the development of muscle damage during prolonged loading.

PubMed

Loerakker, S; Manders, E; Strijkers, G J; Nicolay, K; Baaijens, F P T; Bader, D L; Oomens, C W J

2011-10-01

Deep tissue injury (DTI) is a severe form of pressure ulcer where tissue damage starts in deep tissues underneath intact skin. In the present study, the contributions of deformation, ischemia, and reperfusion to skeletal muscle damage development were examined in a rat model during a 6-h period. Magnetic resonance imaging (MRI) was used to study perfusion (contrast-enhanced MRI) and tissue integrity (T2-weighted MRI). The levels of tissue deformation were estimated using finite element models. Complete ischemia caused a gradual homogeneous increase in T2 (∼20% during the 6-h period). The effect of reperfusion on T2 was highly variable, depending on the anatomical location. In experiments involving deformation, inevitably associated with partial ischemia, a variable T2 increase (17-66% during the 6-h period) was observed reflecting the significant variation in deformation (with two-dimensional strain energies of 0.60-1.51 J/mm) and ischemia (50.8-99.8% of the leg) between experiments. These results imply that deformation, ischemia, and reperfusion all contribute to the damage process during prolonged loading, although their importance varies with time. The critical deformation threshold and period of ischemia that cause muscle damage will certainly vary between individuals. These variations are related to intrinsic factors, such as pathological state, which partly explain the individual susceptibility to the development of DTI and highlight the need for regular assessments of individual subjects.

Three-dimensional high-resolution second-harmonic generation imaging of endogenous structural proteins in biological tissues.

PubMed Central

Campagnola, Paul J; Millard, Andrew C; Terasaki, Mark; Hoppe, Pamela E; Malone, Christian J; Mohler, William A

2002-01-01

We find that several key endogenous protein structures give rise to intense second-harmonic generation (SHG)-nonabsorptive frequency doubling of an excitation laser line. Second-harmonic imaging microscopy (SHIM) on a laser-scanning system proves, therefore, to be a powerful and unique tool for high-resolution, high-contrast, three-dimensional studies of live cell and tissue architecture. Unlike fluorescence, SHG suffers no inherent photobleaching or toxicity and does not require exogenous labels. Unlike polarization microscopy, SHIM provides intrinsic confocality and deep sectioning in complex tissues. In this study, we demonstrate the clarity of SHIM optical sectioning within unfixed, unstained thick specimens. SHIM and two-photon excited fluorescence (TPEF) were combined in a dual-mode nonlinear microscopy to elucidate the molecular sources of SHG in live cells and tissues. SHG arose not only from coiled-coil complexes within connective tissues and muscle thick filaments, but also from microtubule arrays within interphase and mitotic cells. Both polarization dependence and a local symmetry cancellation effect of SHG allowed the signal from species generating the second harmonic to be decoded, by ratiometric correlation with TPEF, to yield information on local structure below optical resolution. The physical origin of SHG within these tissues is addressed and is attributed to the laser interaction with dipolar protein structures that is enhanced by the intrinsic chirality of the protein helices. PMID:11751336

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Imaging Mass Spectrometry (MALDI-TOF IMS) for Premalignant Gastrointestinal Lesions

PubMed Central

Ko, Kwang Hyun; Kwon, Chang Il; Park, So Hye; Han, Na Young; Lee, Hoo Keun; Kim, Eun Hee

2013-01-01

Imaging mass spectrometry (IMS) is currently receiving large attention from the mass spectrometric community, although its use is not yet well known in the clinic. As matrix-assisted laser desorption/ionization time-of-flight (MALDI)-IMS can show the biomolecular changes in cells as well as tissues, it can be an ideal tool for biomedical diagnostics as well as the molecular diagnosis of clinical specimens, especially aimed at the prompt detection of premalignant lesions much earlier before overt mass formation, or for obtaining histologic clues from endoscopic biopsy. Besides its use for pathologic diagnosis, MALDI-IMS is also a powerful tool for the detection and localization of drugs, proteins, and lipids in tissue. Measurement of parameters that define and control the implications, challenges, and opportunities associated with the application of IMS to biomedical tissue studies might be feasible through a deep understanding of mass spectrometry. In this focused review series, new insights into the molecular processes relevant to IMS as well as other field applications are introduced. PMID:24340253

Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

Correlation between polarization sensitive optical coherence tomography and SHG microscopy in articular cartilage

NASA Astrophysics Data System (ADS)

Zhou, Xin; Ju, Myeong Jin; Huang, Lin; Tang, Shuo

2017-02-01

Polarization-sensitive optical coherence tomography (PS-OCT) and second harmonic generation (SHG) microscopy are two imaging modalities with different resolutions, field-of-views (FOV), and contrasts, while they both have the capability of imaging collagen fibers in biological tissues. PS-OCT can measure the tissue birefringence which is induced by highly organized fibers while SHG can image the collagen fiber organization with high resolution. Articular cartilage, with abundant structural collagen fibers, is a suitable sample to study the correlation between PS-OCT and SHG microscopy. Qualitative conjecture has been made that the phase retardation measured by PS-OCT is affected by the relationship between the collagen fiber orientation and the illumination direction. Anatomical studies show that the multilayered architecture of articular cartilage can be divided into four zones from its natural surface to the subchondral bone: the superficial zone, the middle zone, the deep zone, and the calcified zone. The different zones have different collagen fiber orientations, which can be studied by the different slopes in the cumulative phase retardation in PS-OCT. An algorithm is developed based on the quantitative analysis of PS-OCT phase retardation images to analyze the microstructural features in swine articular cartilage tissues. This algorithm utilizes the depth-dependent slope changing of phase retardation A-lines to segment structural layers. The results show good consistency with the knowledge of cartilage morphology and correlation with the SHG images measured at selected depth locations. The correlation between PS-OCT and SHG microscopy shows that PS-OCT has the potential to analyze both the macro and micro characteristics of biological tissues with abundant collagen fibers and other materials that may cause birefringence.

Neuronal Organization of Deep Brain Opsin Photoreceptors in Adult Teleosts

PubMed Central

Hang, Chong Yee; Kitahashi, Takashi; Parhar, Ishwar S.

2016-01-01

Biological impacts of light beyond vision, i.e., non-visual functions of light, signify the need to better understand light detection (or photoreception) systems in vertebrates. Photopigments, which comprise light-absorbing chromophores bound to a variety of G-protein coupled receptor opsins, are responsible for visual and non-visual photoreception. Non-visual opsin photopigments in the retina of mammals and extra-retinal tissues of non-mammals play an important role in non-image-forming functions of light, e.g., biological rhythms and seasonal reproduction. This review highlights the role of opsin photoreceptors in the deep brain, which could involve conserved neurochemical systems that control different time- and light-dependent physiologies in in non-mammalian vertebrates including teleost fish. PMID:27199680

A six-color four-laser mobile platform for multi-spectral fluorescence imaging endoscopy

NASA Astrophysics Data System (ADS)

Black, John F.; Tate, Tyler; Keenan, Molly; Swan, Elizabeth; Utzinger, Urs; Barton, Jennifer

2015-03-01

The properties of multi-spectral fluorescence imaging using deep-UV-illumination have recently been explored using a fiber-coupled thermal source at 280 nm. The resulting images show a remarkable level of contrast thought to result from the signal being overwhelmingly generated in the uppermost few cell layers of tissue, making this approach valuable for the study of diseases that originate in the endothelial tissues of the body. With a view to extending the technique with new wavelengths, and improving beam quality for efficient small core fiber coupling we have developed a mobile self-contained tunable solid-state laser source of deep UV light. An alexandrite laser, lasing at around 750 nm is frequency doubled to produce 375 nm and then tripled to produce 250 nm light. An optical deck added to the system allows other laser sources to be incorporated into the UV beam-line and a lens system has been designed to couple these sources into a single delivery fiber with core diameters down to 50 microns. Our system incorporates five wavelengths [250 nm, 375 nm, 442 nm (HeCd), 543 nm (HeNe) and 638 nm (diode laser)] as the illumination source for a small diameter falloposcope designed for the study of the distal Fallopian tube origins of high grade serous ovarian cancer. The tunability of alexandrite offers the potential to generate other wavelengths in the 720-800, 360-400 and 240-265 nm ranges, plus other non-linear optical conversion techniques taking advantage of the high peak powers of the laser.

Fluorescence diffuse tomography for tumor detection and monitoring

NASA Astrophysics Data System (ADS)

Balalaeva, Irina V.; Orlova, Anna G.; Shirmanova, Marina V.; Kibraeva, Elena A.; Zagainova, Elena V.; Turchin, Ilya V.

2007-05-01

Strong light scattering and absorption limit visualization of the internal structure of biological tissue. Only special tools for turbid media imaging, such as optical diffuse tomography, enable noninvasive investigation of the internal biological tissues, including visualization and intravital monitoring of deep tumors. In this work the preliminary results of fluorescence diffuse tomography (FDT) of small animals are presented. Using of exogenous fluorophores, targeted specifically at tumor cells, and fluorescent proteins expressed endogenously can significantly increase the contrast of obtained images. Fluorescent compounds of different nature, such as sulphonated aluminium phthalocyanine (Photosens), red fluorescing proteins and CdTe/CdSe-core/shell nanocrystals (quantum dots) were applied. The animal was scanned in the transilluminative configuration by low-frequency modulated light (1 kHz) from Nd:YAG laser with second harmonic generation at the wavelength of 532 nm or semiconductor laser at the wavelength of 655 nm. Photosens was injected intravenously into linear mice with metastazing Lewis lung carcinoma in dose 4 mg/kg. Quantum dots (5x10 -11 M) or protein DsRed2 (1-5x10 -6 M) in glass capsules (inner diameter 2-3 mm) were placed inside the esophagus of 7-day-old hairless rats (18-20 g) to simulate marked tumors. Cells of HEK-293 Phoenix line, transitory transfected with Turbo-RFP protein gene, were injected hypodermically to immunodeficient mice. This work demonstrates potential capabilities of FDT method for detection and monitoring of deep fluorescent-labeled tumors in animal models. Strong advantages of fluorescent proteins and quantum dots over the traditional photosensitizer for FDT imaging are shown.

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo

PubMed Central

Hirai, Yasuharu; Nishino, Eri

2015-01-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. PMID:25761950

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo.

PubMed

Hirai, Yasuharu; Nishino, Eri; Ohmori, Harunori

2015-06-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. Copyright © 2015 the American Physiological Society.

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information.

PubMed

Khushi, Matloob; Edwards, Georgina; de Marcos, Diego Alonso; Carpenter, Jane E; Graham, J Dinny; Clarke, Christine L

2013-02-12

Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes. We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient's clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images. Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934.

Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN.

PubMed

Xu, Xuanang; Zhou, Fugen; Liu, Bo

2018-03-19

Automatic approach for bladder segmentation from computed tomography (CT) images is highly desirable in clinical practice. It is a challenging task since the bladder usually suffers large variations of appearance and low soft-tissue contrast in CT images. In this study, we present a deep learning-based approach which involves a convolutional neural network (CNN) and a 3D fully connected conditional random fields recurrent neural network (CRF-RNN) to perform accurate bladder segmentation. We also propose a novel preprocessing method, called dual-channel preprocessing, to further advance the segmentation performance of our approach. The presented approach works as following: first, we apply our proposed preprocessing method on the input CT image and obtain a dual-channel image which consists of the CT image and an enhanced bladder density map. Second, we exploit a CNN to predict a coarse voxel-wise bladder score map on this dual-channel image. Finally, a 3D fully connected CRF-RNN refines the coarse bladder score map and produce final fine-localized segmentation result. We compare our approach to the state-of-the-art V-net on a clinical dataset. Results show that our approach achieves superior segmentation accuracy, outperforming the V-net by a significant margin. The Dice Similarity Coefficient of our approach (92.24%) is 8.12% higher than that of the V-net. Moreover, the bladder probability maps performed by our approach present sharper boundaries and more accurate localizations compared with that of the V-net. Our approach achieves higher segmentation accuracy than the state-of-the-art method on clinical data. Both the dual-channel processing and the 3D fully connected CRF-RNN contribute to this improvement. The united deep network composed of the CNN and 3D CRF-RNN also outperforms a system where the CRF model acts as a post-processing method disconnected from the CNN.

High-Resolution Intravital Microscopy

PubMed Central

Andresen, Volker; Pollok, Karolin; Rinnenthal, Jan-Leo; Oehme, Laura; Günther, Robert; Spiecker, Heinrich; Radbruch, Helena; Gerhard, Jenny; Sporbert, Anje; Cseresnyes, Zoltan; Hauser, Anja E.; Niesner, Raluca

2012-01-01

Cellular communication constitutes a fundamental mechanism of life, for instance by permitting transfer of information through synapses in the nervous system and by leading to activation of cells during the course of immune responses. Monitoring cell-cell interactions within living adult organisms is crucial in order to draw conclusions on their behavior with respect to the fate of cells, tissues and organs. Until now, there is no technology available that enables dynamic imaging deep within the tissue of living adult organisms at sub-cellular resolution, i.e. detection at the level of few protein molecules. Here we present a novel approach called multi-beam striped-illumination which applies for the first time the principle and advantages of structured-illumination, spatial modulation of the excitation pattern, to laser-scanning-microscopy. We use this approach in two-photon-microscopy - the most adequate optical deep-tissue imaging-technique. As compared to standard two-photon-microscopy, it achieves significant contrast enhancement and up to 3-fold improved axial resolution (optical sectioning) while photobleaching, photodamage and acquisition speed are similar. Its imaging depth is comparable to multifocal two-photon-microscopy and only slightly less than in standard single-beam two-photon-microscopy. Precisely, our studies within mouse lymph nodes demonstrated 216% improved axial and 23% improved lateral resolutions at a depth of 80 µm below the surface. Thus, we are for the first time able to visualize the dynamic interactions between B cells and immune complex deposits on follicular dendritic cells within germinal centers (GCs) of live mice. These interactions play a decisive role in the process of clonal selection, leading to affinity maturation of the humoral immune response. This novel high-resolution intravital microscopy method has a huge potential for numerous applications in neurosciences, immunology, cancer research and developmental biology. Moreover, our striped-illumination approach is able to improve the resolution of any laser-scanning-microscope, including confocal microscopes, by simply choosing an appropriate detector. PMID:23251402

Diffuse fluorescence tomography of exo- and endogenously labeled tumors

NASA Astrophysics Data System (ADS)

Balalaeva, Irina V.; Turchin, Ilya V.; Orlova, Anna G.; Plekhanov, Vladimir I.; Shirmanova, Marina V.; Kleshnin, Michail S.; Fiks, Ilya I.; Zagainova, Elena V.; Kamensky, Vladislav A.

2007-06-01

Strong light scattering and absorption limit observation of the internal structure of biological tissue. Only special tools for turbid media imaging, such as optical diffuse tomography, enable noninvasive investigation of the internal biological tissues, including visualization and intravital monitoring of deep tumors. In this work the preliminary results of diffuse fluorescence tomography (DFT) of small animals are presented. Usage of exogenous fluorophores, targeted specifically at tumor cells, and fluorescent proteins expressed endogenously can significantly increase the contrast of obtained images. Fluorescent compounds of different nature, such as sulphonated aluminium phthalocyanine (Photosens), red fluorescing proteins and CdTe/CdSe-core/shell nanocrystals (quantum dots) were applied. We tested diffuse fluorescence tomography method at model media, in post mortem and in vivo experiments. The animal was scanned in transilluminative configuration by low-frequency modulated light (1 kHz) from Nd:YAG laser with second harmonic generation at wavelength of 532 nm or semiconductor laser at wavelength of 655 nm. Quantum dots or protein DsRed2 in glass capsules (inner diameter 2-3 mm) were placed post mortem inside the esophagus of 7-day-old hairless rats to simulate marked tumors. Photosens was injected intravenously to linear mice with metastazing Lewis lung carcinoma. The reconstruction algorithm, based on Algebraic Reconstruction Technique, was created and tested numerically in model experiments. High contrast images of tumor simulating capsules with DsRed2 concentrations about 10 -6 M and quantum dots about 5x10 -11 M have been obtained. Organ distribution of Photosens and its accumulation in tumors and surrounding tissues of animals has been examined. We have conducted the monitoring of tumors, exogenously labeled by photosensitizer. This work demonstrates potential capabilities of DFT method for intravital detection and monitoring of deep fluorescent-labeled tumors in animal models. The comparative analysis of conventional photosensitizer, fluorescent proteins and quantum dots has been carried out.

Optical coherence tomography and optical coherence domain reflectometry for deep brain stimulation probe guidance

NASA Astrophysics Data System (ADS)

Jeon, Sung W.; Shure, Mark A.; Baker, Kenneth B.; Chahlavi, Ali; Hatoum, Nagi; Turbay, Massud; Rollins, Andrew M.; Rezai, Ali R.; Huang, David

2005-04-01

Deep Brain Stimulation (DBS) is FDA-approved for the treatment of Parkinson's disease and essential tremor. Currently, placement of DBS leads is guided through a combination of anatomical targeting and intraoperative microelectrode recordings. The physiological mapping process requires several hours, and each pass of the microelectrode into the brain increases the risk of hemorrhage. Optical Coherence Domain Reflectometry (OCDR) in combination with current methodologies could reduce surgical time and increase accuracy and safety by providing data on structures some distance ahead of the probe. For this preliminary study, we scanned a rat brain in vitro using polarization-insensitive Optical Coherence Tomography (OCT). For accurate measurement of intensity and attenuation, polarization effects arising from tissue birefringence are removed by polarization diversity detection. A fresh rat brain was sectioned along the coronal plane and immersed in a 5 mm cuvette with saline solution. OCT images from a 1294 nm light source showed depth profiles up to 2 mm. Light intensity and attenuation rate distinguished various tissue structures such as hippocampus, cortex, external capsule, internal capsule, and optic tract. Attenuation coefficient is determined by linear fitting of the single scattering regime in averaged A-scans where Beer"s law is applicable. Histology showed very good correlation with OCT images. From the preliminary study using OCT, we conclude that OCDR is a promising approach for guiding DBS probe placement.

Sensitivity and accuracy of hybrid fluorescence-mediated tomography in deep tissue regions.

PubMed

Rosenhain, Stefanie; Al Rawashdeh, Wa'el; Kiessling, Fabian; Gremse, Felix

2017-09-01

Fluorescence-mediated tomography (FMT) enables noninvasive assessment of the three-dimensional distribution of near-infrared fluorescence in mice. The combination with micro-computed tomography (µCT) provides anatomical data, enabling improved fluorescence reconstruction and image analysis. The aim of our study was to assess sensitivity and accuracy of µCT-FMT under realistic in vivo conditions in deeply-seated regions. Accordingly, we acquired fluorescence reflectance images (FRI) and µCT-FMT scans of mice which were prepared with rectal insertions with different amounts of fluorescent dye. Default and high-sensitivity scans were acquired and background signal was analyzed for three FMT channels (670 nm, 745 nm, and 790 nm). Analysis was performed for the original and an improved FMT reconstruction using the µCT data. While FRI and the original FMT reconstruction could detect 100 pmol, the improved FMT reconstruction could detect 10 pmol and significantly improved signal localization. By using a finer sampling grid and increasing the exposure time, the sensitivity could be further improved to detect 0.5 pmol. Background signal was highest in the 670 nm channel and most prominent in the gastro-intestinal tract and in organs with high relative amounts of blood. In conclusion, we show that µCT-FMT allows sensitive and accurate assessment of fluorescence in deep tissue regions. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Current advances in molecular imaging: noninvasive in vivo bioluminescent and fluorescent optical imaging in cancer research.

PubMed

Choy, Garry; Choyke, Peter; Libutti, Steven K

2003-10-01

Recently, there has been tremendous interest in developing techniques such as MRI, micro-CT, micro-PET, and SPECT to image function and processes in small animals. These technologies offer deep tissue penetration and high spatial resolution, but compared with noninvasive small animal optical imaging, these techniques are very costly and time consuming to implement. Optical imaging is cost-effective, rapid, easy to use, and can be readily applied to studying disease processes and biology in vivo. In vivo optical imaging is the result of a coalescence of technologies from chemistry, physics, and biology. The development of highly sensitive light detection systems has allowed biologists to use imaging in studying physiological processes. Over the last few decades, biochemists have also worked to isolate and further develop optical reporters such as GFP, luciferase, and cyanine dyes. This article reviews the common types of fluorescent and bioluminescent optical imaging, the typical system platforms and configurations, and the applications in the investigation of cancer biology.

Fiber-bundle-basis sparse reconstruction for high resolution wide-field microendoscopy.

PubMed

Mekhail, Simon Peter; Abudukeyoumu, Nilupaer; Ward, Jonathan; Arbuthnott, Gordon; Chormaic, Síle Nic

2018-04-01

In order to observe deep regions of the brain, we propose the use of a fiber bundle for microendoscopy. Fiber bundles allow for the excitation and collection of fluorescence as well as wide field imaging while remaining largely impervious to image distortions brought on by bending. Furthermore, their thin diameter, from 200-500 µ m, means their impact on living tissue, though not absent, is minimal. Although wide field imaging with a bundle allows for a high temporal resolution since no scanning is involved, the largest criticism of bundle imaging is the drastically lowered spatial resolution. In this paper, we make use of sparsity in the object being imaged to up sample the low resolution images from the fiber bundle with compressive sensing. We take each image in a single shot by using a measurement basis dictated by the quasi-crystalline arrangement of the bundle's cores. We find that this technique allows us to increase the resolution of a typical image taken through a fiber bundle.

Layer-by-layer assembled fluorescent probes in the second near-infrared window for systemic delivery and detection of ovarian cancer

PubMed Central

Dang, Xiangnan; Gu, Li; Qi, Jifa; Correa, Santiago; Zhang, Geran; Belcher, Angela M.; Hammond, Paula T.

2016-01-01

Fluorescence imaging in the second near-infrared window (NIR-II, 1,000–1,700 nm) features deep tissue penetration, reduced tissue scattering, and diminishing tissue autofluorescence. Here, NIR-II fluorescent probes, including down-conversion nanoparticles, quantum dots, single-walled carbon nanotubes, and organic dyes, are constructed into biocompatible nanoparticles using the layer-by-layer (LbL) platform due to its modular and versatile nature. The LbL platform has previously been demonstrated to enable incorporation of diagnostic agents, drugs, and nucleic acids such as siRNA while providing enhanced blood plasma half-life and tumor targeting. This work carries out head-to-head comparisons of currently available NIR-II probes with identical LbL coatings with regard to their biodistribution, pharmacokinetics, and toxicities. Overall, rare-earth-based down-conversion nanoparticles demonstrate optimal biological and optical performance and are evaluated as a diagnostic probe for high-grade serous ovarian cancer, typically diagnosed at late stage. Successful detection of orthotopic ovarian tumors is achieved by in vivo NIR-II imaging and confirmed by ex vivo microscopic imaging. Collectively, these results indicate that LbL-based NIR-II probes can serve as a promising theranostic platform to effectively and noninvasively monitor the progression and treatment of serous ovarian cancer. PMID:27114520

Hyperpolarized Porous Silicon Nanoparticles: Potential Theragnostic Material for ²⁹Si Magnetic Resonance Imaging.

PubMed

Seo, Hyeonglim; Choi, Ikjang; Whiting, Nicholas; Hu, Jingzhe; Luu, Quy Son; Pudakalakatti, Shivanand; McCowan, Caitlin; Kim, Yaewon; Zacharias, Niki; Lee, Seunghyun; Bhattacharya, Pratip; Lee, Youngbok

2018-05-20

Porous silicon nanoparticles have recently garnered attention as potentially-promising biomedical platforms for drug delivery and medical diagnostics. Here, we demonstrate porous silicon nanoparticles as contrast agents for ²⁹Si magnetic resonance imaging. Size-controlled porous silicon nanoparticles were synthesized by magnesiothermic reduction of silica nanoparticles and were surface activated for further functionalization. Particles were hyperpolarized via dynamic nuclear polarization to enhance their ²⁹Si MR signals; the particles demonstrated long ²⁹Si spin-lattice relaxation (T₁) times (~ 25 mins), which suggests potential applicability for medical imaging. Furthermore, ²⁹Si hyperpolarization levels were sufficient to allow ²⁹Si MRI in phantoms. These results underscore the potential of porous silicon nanoparticles that, when combined with hyperpolarized magnetic resonance imaging, can be a powerful theragnostic deep tissue imaging platform to interrogate various biomolecular processes in vivo. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative long term measurements of burns in a rat model using Spatial Frequency Domain Imaging (SFDI) and Laser Speckle Imaging (LSI)

PubMed Central

Ponticorvo, Adrien; Burmeister, David M.; Rowland, Rebecca; Baldado, Melissa; Kennedy, Gordon T.; Saager, Rolf; Bernal, Nicole; Choi, Bernard; Durkin, Anthony J.

2017-01-01

The current standard for diagnosis of burn severity and subsequent wound healing is through clinical examination, which is highly subjective. Several new technologies are shifting focus to burn care in an attempt to help quantify not only burn depth but also the progress of healing. While accurate early assessment of partial thickness burns is critical for dictating the course of treatment, the ability to quantitatively monitor wound status over time is critical for understanding treatment efficacy. SFDI and LSI are both non-invasive imaging modalities that have been shown to have great diagnostic value for burn severity, but have yet to be tested over the course of wound healing. In this study, a hairless rat model (n=6, 300-450g) was used with a four pronged comb to create four identical partial thickness burns (superficial n=3 and deep n=3) that were used to monitor wound healing over a 28 day period. Weekly biopsies were taken for histological analysis to verify wound progression. Both SFDI and LSI were performed weekly to track the evolution of hemodynamic (blood flow and oxygen saturation) and structural (reduced scattering coefficient) properties for the burns. LSI showed significant changes in blood flow from baseline to 220% in superficial and 165% in deep burns by day 7. In superficial burns, blood flow returned to baseline levels by day 28, but not for deep burns where blood flow remained elevated. Smaller increases in blood flow were also observed in the surrounding tissue over the same time period. Oxygen saturation values measured with SFDI showed a progressive increase from baseline values of 66% to 74% in superficial burns and 72% in deep burns by day 28. Additionally, SFDI showed significant decreases in the reduced scattering coefficient shortly after the burns were created. The scattering coefficient progressively decreased in the wound area, but returned towards baseline conditions at the end of the 28 day period. Scattering changes in the surrounding tissue remained constant despite the presence of hemodynamic changes. Here we show that LSI and SFDI are capable of monitoring changes in hemodynamic and scattering properties in burn wounds over a 28 day period. These results highlight the potential insights that can be gained by using noninvasive imaging technologies to study wound healing. Further development of these technologies could be revolutionary for wound monitoring and studying the efficacy of different treatments. PMID:28220508

Radiation dosimetry of the fibrin-binding probe 64Cu-FBP8 and its feasibility for positron emission tomography imaging of deep vein thrombosis and pulmonary embolism in rats

PubMed Central

Blasi, Francesco; Oliveira, Bruno L; Rietz, Tyson A; Rotile, Nicholas J; Day, Helen; Naha, Pratap C; Cormode, David P; Izquierdo-Garcia, David; Catana, Ciprian; Caravan, Peter

2016-01-01

The diagnosis of deep venous thromboembolic disease is still challenging despite the progress of current thrombus imaging modalities and new diagnostic algorithms. We recently reported the high target uptake and thrombus imaging efficacy of the novel fibrin-specific positron emission tomography probe 64Cu-FBP8. Here, we tested the feasibility of 64Cu-FBP8-PET to detect source thrombi and culprit emboli after deep vein thrombosis and pulmonary embolism (DVT-PE). To support clinical translation of 64Cu-FBP8, we performed a human dosimetry estimation using time-dependent biodistribution in rats. Methods Sprague-Dawley rats (n=7) underwent ferric chloride application on the femoral vein to trigger thrombosis. Pulmonary embolism was induced 30 min or 2 days after deep vein thrombosis by intrajugular injection of a preformed blood clot labeled with 125I-Fibrinogen. PET imaging was performed to detect the clots, and single-photon emission tomography (SPECT) was used to confirm in vivo the location of the pulmonary emboli. Ex vivo gamma-counting and histopathology were used to validate the imaging findings. Detailed biodistribution was performed in healthy rats (n=30) at different time-points after 64Cu-FBP8 administration to estimate human radiation dosimetry. Longitudinal whole-body PET/MR imaging (n=2) was performed after 64Cu-FBP8 administration to further assess radioactivity clearance. Results 64Cu-FBP8-PET imaging detected the location of lung emboli and venous thrombi after DVT-PE, revealing significant differences in uptake between target and background tissues (P<0.001). In vivo SPECT imaging and ex vivo gamma-counting confirmed the location of the lung emboli. PET quantification of the venous thrombi revealed that probe uptake was greater in younger clots than in older ones, a result confirmed by ex vivo analyses (P<0.001). Histopathology revealed an age-dependent reduction of thrombus fibrin content (P=0.006), further supporting the imaging findings. Biodistribution and whole-body PET/MR imaging showed rapid, primarily renal, body clearance of 64Cu-FBP8. The effective dose was estimated to be 0.021 mSv/MBq for male and 0.027 mSv/MBq for female, supporting the feasibility of using 64Cu-FBP8 in human trials. Conclusions We showed that 64Cu-FBP8-PET is a feasible approach to image DVT-PE, and that radiogenic adverse health effects should not limit the clinical translation of 64Cu-FBP8. PMID:25977464

Using deep learning in image hyper spectral segmentation, classification, and detection

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Su, Zhenyu

2018-02-01

Recent years have shown that deep learning neural networks are a valuable tool in the field of computer vision. Deep learning method can be used in applications like remote sensing such as Land cover Classification, Detection of Vehicle in Satellite Images, Hyper spectral Image classification. This paper addresses the use of the deep learning artificial neural network in Satellite image segmentation. Image segmentation plays an important role in image processing. The hue of the remote sensing image often has a large hue difference, which will result in the poor display of the images in the VR environment. Image segmentation is a pre processing technique applied to the original images and splits the image into many parts which have different hue to unify the color. Several computational models based on supervised, unsupervised, parametric, probabilistic region based image segmentation techniques have been proposed. Recently, one of the machine learning technique known as, deep learning with convolution neural network has been widely used for development of efficient and automatic image segmentation models. In this paper, we focus on study of deep neural convolution network and its variants for automatic image segmentation rather than traditional image segmentation strategies.

Photoacoustic imaging of hepatocellular carcinoma targeting gold nanoshells (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhou, Quan; Chen, Yan; Li, Zhao; Zhou, Juan; Duan, Xiyu; Wang, Thomas D.

2017-02-01

Plasmonic gold nanoshell (GNS) probe penetrates into tumors for deep imaging, enables superior photoacoustic contrast. Glypican-3 (GPC3) specific peptide (Kd = 71 nM) conjugated gold nanoshell (λabs=770nm) was used to detect HCC xenograft tumors in mice with photoacoustic imaging. This targeting probe demonstrated tumor uptake after 1 hr and cleared in 12 hrs. Images at a mean (±SD) depth of 9.7±1.4 mm from 0 to 2.1 cm beneath the skin revealed increased PA signal from tumors. Highest tumor uptake and tumor to normal tissue ratio occurred at 2 hrs post injection (T/B = 4.45±0.22, n = 8). Molecular targeting GNS showed potential as a simple, effective and rapid technique for noninvasive in vivo monitoring HCC tumor growth and GPC3 expression.

Diffusion Tensor Imaging of Heterotopia: Changes of Fractional Anisotropy during Radial Migration of Neurons

PubMed Central

Kim, Jinna

2010-01-01

Purpose Diffusion tensor imaging provides better understanding of pathophysiology of congenital anomalies, involving central nervous system. This study was aimed to specify the pathogenetic mechanism of heterotopia, proved by diffusion tensor imaging, and establish new findings of heterotopia on fractional anisotropy maps. Materials and Methods Diffusion-weighted imaging data from 11 patients (M : F = 7 : 4, aged from 1 to 22 years, mean = 12.3 years) who visited the epilepsy clinic and received a routine seizure protocol MRI exam were retrospectively analyzed. Fractional anisotropy (FA) maps were generated from diffusion tensor imaging of 11 patients with heterotopia. Regions of interests (ROI) were placed in cerebral cortex, heterotopic gray matter and deep gray matter, including putamen. ANOVA analysis was performed for comparison of different gray matter tissues. Results Heterotopic gray matter showed signal intensities similar to normal gray matter on T1 and T2 weighted MRI. The measured FA of heterotopic gray matter was higher than that of cortical gray matter (0.236 ± 0.011 vs. 0.169 ± 0.015, p < 0.01, one way ANOVA), and slightly lower than that of deep gray matter (0.236 ± 0.011 vs. 0.259 ± 0.016, p < 0.01). Conclusion Increased FA of heterotopic gray matter suggests arrested neuron during radial migration and provides better understanding of neurodevelopment. PMID:20499428

Double-excitation fluorescence spectral imaging: eliminating tissue auto-fluorescence from in vivo PPIX measurements

NASA Astrophysics Data System (ADS)

Torosean, Sason; Flynn, Brendan; Samkoe, Kimberley S.; Davis, Scott C.; Gunn, Jason; Axelsson, Johan; Pogue, Brian W.

2012-02-01

An ultrasound coupled handheld-probe-based optical fluorescence molecular tomography (FMT) system has been in development for the purpose of quantifying the production of Protoporphyrin IX (PPIX) in aminolevulinic acid treated (ALA), Basal Cell Carcinoma (BCC) in vivo. The design couples fiber-based spectral sampling of PPIX fluorescence emission with a high frequency ultrasound imaging system, allowing regionally localized fluorescence intensities to be quantified [1]. The optical data are obtained by sequential excitation of the tissue with a 633nm laser, at four source locations and five parallel detections at each of the five interspersed detection locations. This method of acquisition permits fluorescence detection for both superficial and deep locations in ultrasound field. The optical boundary data, tissue layers segmented from ultrasound image and diffusion theory are used to estimate the fluorescence in tissue layers. To improve the recovery of the fluorescence signal of PPIX, eliminating tissue autofluorescence is of great importance. Here the approach was to utilize measurements which straddled the steep Qband excitation peak of PPIX, via the integration of an additional laser source, exciting at 637 nm; a wavelength with a 2 fold lower PPIX excitation value than 633nm.The auto-fluorescence spectrum acquired from the 637 nm laser is then used to spectrally decouple the fluorescence data and produce an accurate fluorescence emission signal, because the two wavelengths have very similar auto-fluorescence but substantially different PPIX excitation levels. The accuracy of this method, using a single source detector pair setup, is verified through animal tumor model experiments, and the result is compared to different methods of fluorescence signal recovery.

Correlative two-photon and serial block face scanning electron microscopy in neuronal tissue using 3D near-infrared branding maps.

PubMed

Lees, Robert M; Peddie, Christopher J; Collinson, Lucy M; Ashby, Michael C; Verkade, Paul

2017-01-01

Linking cellular structure and function has always been a key goal of microscopy, but obtaining high resolution spatial and temporal information from the same specimen is a fundamental challenge. Two-photon (2P) microscopy allows imaging deep inside intact tissue, bringing great insight into the structural and functional dynamics of cells in their physiological environment. At the nanoscale, the complex ultrastructure of a cell's environment in tissue can be reconstructed in three dimensions (3D) using serial block face scanning electron microscopy (SBF-SEM). This provides a snapshot of high resolution structural information pertaining to the shape, organization, and localization of multiple subcellular structures at the same time. The pairing of these two imaging modalities in the same specimen provides key information to relate cellular dynamics to the ultrastructural environment. Until recently, approaches to relocate a region of interest (ROI) in tissue from 2P microscopy for SBF-SEM have been inefficient or unreliable. However, near-infrared branding (NIRB) overcomes this by using the laser from a multiphoton microscope to create fiducial markers for accurate correlation of 2P and electron microscopy (EM) imaging volumes. The process is quick and can be user defined for each sample. Here, to increase the efficiency of ROI relocation, multiple NIRB marks are used in 3D to target ultramicrotomy. A workflow is described and discussed to obtain a data set for 3D correlated light and electron microscopy, using three different preparations of brain tissue as examples. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantification of tissue texture with photoacoustic spectrum analysis

NASA Astrophysics Data System (ADS)

Wang, Xueding; Xu, Guan; Meng, Zhuo-Xian; Lin, Jiandie; Carson, Paul

2014-05-01

Photoacoustic (PA) imaging is an emerging technology that could map the functional contrasts in deep biological tissues in high resolution by "listening" to the laser induced thermoelastic waves. Almost all of the current studies in PA imaging are focused on the intensity of the PA signals as an indication of the optical absorbance of the biological tissues. Our group has for the first time demonstrated that the frequency domain power distribution of the broadband PA signals encode the texture information within the regions-of-interest (ROI). Following the similar method of ultrasound spectral analysis (USSA), photoacoustic spectrum analysis (PASA) could evaluate the relative concentrations and, more importantly, the dimensions of microstructures of the optically absorbing materials in biological tissues, including lipid, collagen, water and hemoglobin. By providing valuable insights into tissue pathology, PASA should benefit basic research and clinical management of many diseases, and may help achieve eventual "noninvasive biopsy". In this work, taking advantage of the optical absorption contrasts contributed by lipid and hemoglobin at 1200-nm and 532-nm wavelengths respectively, we investigated the capability of PASA in identifying histological changes corresponding to fat accumulation livers through the study on ex vivo and in situ mouse models. The PA signals from the mouse livers were acquired using our PA and US dual-modality imaging system, and analyzed in the frequency domain. After quantifying the power spectrum by fitting it to a first order model, three spectral parameters, including the intercept, the midband fit and the slope, were extracted and used to differentiate fatty livers from normal livers. The comparison between the PASA parameters from the normal and the fatty livers supports our hypotheses that PASA can quantitatively identify the microstructure changes in liver tissues for differentiating normal and fatty livers.

Confocal microscopy for astrocyte in vivo imaging: Recycle and reuse in microscopy

PubMed Central

Pérez-Alvarez, Alberto; Araque, Alfonso; Martín, Eduardo D.

2013-01-01

In vivo imaging is one of the ultimate and fundamental approaches for the study of the brain. Two-photon laser scanning microscopy (2PLSM) constitutes the state-of-the-art technique in current neuroscience to address questions regarding brain cell structure, development and function, blood flow regulation and metabolism. This technique evolved from laser scanning confocal microscopy (LSCM), which impacted the field with a major improvement in image resolution of live tissues in the 1980s compared to widefield microscopy. While nowadays some of the unparalleled features of 2PLSM make it the tool of choice for brain studies in vivo, such as the possibility to image deep within a tissue, LSCM can still be useful in this matter. Here we discuss the validity and limitations of LSCM and provide a guide to perform high-resolution in vivo imaging of the brain of live rodents with minimal mechanical disruption employing LSCM. We describe the surgical procedure and experimental setup that allowed us to record intracellular calcium variations in astrocytes evoked by sensory stimulation, and to monitor intact neuronal dendritic spines and astrocytic processes as well as blood vessel dynamics. Therefore, in spite of certain limitations that need to be carefully considered, LSCM constitutes a useful, convenient, and affordable tool for brain studies in vivo. PMID:23658537

Alternative techniques for high-resolution spectral estimation of spectrally encoded endoscopy

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Duan, Lian; Javidi, Tara; Ellerbee, Audrey K.

2015-09-01

Spectrally encoded endoscopy (SEE) is a minimally invasive optical imaging modality capable of fast confocal imaging of internal tissue structures. Modern SEE systems use coherent sources to image deep within the tissue and data are processed similar to optical coherence tomography (OCT); however, standard processing of SEE data via the Fast Fourier Transform (FFT) leads to degradation of the axial resolution as the bandwidth of the source shrinks, resulting in a well-known trade-off between speed and axial resolution. Recognizing the limitation of FFT as a general spectral estimation algorithm to only take into account samples collected by the detector, in this work we investigate alternative high-resolution spectral estimation algorithms that exploit information such as sparsity and the general region position of the bulk sample to improve the axial resolution of processed SEE data. We validate the performance of these algorithms using bothMATLAB simulations and analysis of experimental results generated from a home-built OCT system to simulate an SEE system with variable scan rates. Our results open a new door towards using non-FFT algorithms to generate higher quality (i.e., higher resolution) SEE images at correspondingly fast scan rates, resulting in systems that are more accurate and more comfortable for patients due to the reduced image time.

Laser speckle imaging in the spatial frequency domain

PubMed Central

Mazhar, Amaan; Cuccia, David J.; Rice, Tyler B.; Carp, Stefan A.; Durkin, Anthony J.; Boas, David A.; Choi, Bernard; Tromberg, Bruce J.

2011-01-01

Laser Speckle Imaging (LSI) images interference patterns produced by coherent addition of scattered laser light to map subsurface tissue perfusion. However, the effect of longer path length photons is typically unknown and poses a limitation towards absolute quantification. In this work, LSI is integrated with spatial frequency domain imaging (SFDI) to suppress multiple scattering and absorption effects. First, depth sensitive speckle contrast is shown in phantoms by separating a deep source (4 mm) from a shallow source (2 mm) of speckle contrast by using a high spatial frequency of illumination (0.24 mm−1). We develop an SFD adapted correlation diffusion model and show that with high frequency (0.24 mm−1) illumination, doubling of absorption contrast results in only a 1% change in speckle contrast versus 25% change using a planar unmodulated (0 mm−1) illumination. Similar absorption change is mimicked in vivo imaging a finger occlusion and the relative speckle contrast change from baseline is 10% at 0.26 mm−1 versus 60% at 0 mm−1 during a finger occlusion. These results underscore the importance of path length and optical properties in determining speckle contrast. They provide an integrated approach for simultaneous mapping of blood flow (speckle contrast) and oxygenation (optical properties) which can be used to inform tissue metabolism. PMID:21698018

In vivo imaging of inducible tyrosinase gene expression with an ultrasound array-based photoacoustic system

NASA Astrophysics Data System (ADS)

Harrison, Tyler; Paproski, Robert J.; Zemp, Roger J.

2012-02-01

Tyrosinase, a key enzyme in the production of melanin, has shown promise as a reporter of genetic activity. While green fluorescent protein has been used extensively in this capacity, it is limited in its ability to provide information deep in tissue at a reasonable resolution. As melanin is a strong absorber of light, it is possible to image gene expression using tyrosinase with photoacoustic imaging technologies, resulting in excellent resolutions at multiple-centimeter depths. While our previous work has focused on creating and imaging MCF-7 cells with doxycycline-controlled tyrosinase expression, we have now established the viability of these cells in a murine model. Using an array-based photoacoustic imaging system with 5 MHz center frequency, we capture interleaved ultrasound and photoacoustic images of tyrosinase-expressing MCF-7 tumors both in a tissue mimicking phantom, and in vivo. Images of both the tyrosinase-expressing tumor and a control tumor are presented as both coregistered ultrasound-photoacoustic B-scan images and 3-dimensional photoacoustic volumes created by mechanically scanning the transducer. We find that the tyrosinase-expressing tumor is visible with a signal level 12dB greater than that of the control tumor in vivo. Phantom studies with excised tumors show that the tyrosinase-expressing tumor is visible at depths in excess of 2cm, and have suggested that our imaging system is sensitive to a transfection rate of less than 1%.

The structure of the insertions of the tendons of biceps brachii, triceps and brachialis in elderly dissecting room cadavers.

PubMed Central

Benjamin, M; Newell, R L; Evans, E J; Ralphs, J R; Pemberton, D J

1992-01-01

The terminal portions of the tendon of brachialis, and the distal tendons of biceps brachii and triceps, were compared by routine histology. All tendons came from elderly dissecting room cadavers. There were pronounced quantitative differences between the 3 tendons in (1) the thickness of the attachment-zone fibrocartilage, (2) the thickness of cortical calcified tissue, and (3) the percentage of bone to marrow. There was significantly more uncalcified fibrocartilage at the attachment of biceps than at the other sites, reflecting greater range of movement of the tendon at this site. The thickness of cortical calcified tissue and the percentage of bone to marrow were significantly greater at the attachment of brachialis than either biceps or triceps. The large quantities of bone at the attachment of brachialis may be related more to the importance of the coronoid process in buttressing the elbow joint than to any special requirement for large amounts of calcified tissue at the tendon attachment. Near its attachment zone, the biceps tendon splits into superficial and deep laminae that are distinct from the macroscopic subdivision of this tendon. It is suggested that the lamination may facilitate the movements of pronation and supination. In support of this, the deep portion of the superficial lamina contained fibrocartilage where it rubbed against the attachment-zone of the deep lamina. In one body, the fibrocartilage of the biceps attachment-zone was subject to degenerative changes, including cell clumping and matrix fissuring. Images Fig. 2 Fig. 3 PMID:1506288

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

Dual-Modality Optical/PET Imaging of PARP1 in Glioblastoma.

PubMed

Carlucci, Giuseppe; Carney, Brandon; Brand, Christian; Kossatz, Susanne; Irwin, Christopher P; Carlin, Sean D; Keliher, Edmund J; Weber, Wolfgang; Reiner, Thomas

2015-12-01

The current study presents [(18)F]PARPi-FL as a bimodal fluorescent/positron emission tomography (PET) agent for PARP1 imaging. [(18)F]PARPi-FL was obtained by (19)F/(18)F isotopic exchange and PET experiments, biodistribution studies, surface fluorescence imaging, and autoradiography carried out in a U87 MG glioblastoma mouse model. [(18)F]PARPi-FL showed high tumor uptake in vivo and ex vivo in small xenografts (< 2 mm) with both PET and optical imaging technologies. Uptake of [(18)F]PARPi-FL in blocked U87 MG tumors was reduced by 84 % (0.12 ± 0.02 %injected dose/gram (%ID/g)), showing high specificity of the binding. PET imaging showed accumulation in the tumor (1 h p.i.), which was confirmed by ex vivo phosphor autoradiography. The fluorescent component of [(18)F]PARPi-FL enables cellular resolution optical imaging, while the radiolabeled component of [(18)F]PARPi-FL allows whole-body deep-tissue imaging of malignant growth.

Using glow stick chemistry for biological imaging.

PubMed

Tseng, Jen-Chieh; Bailey, Dyane; Tupper, Tanya; Kung, Andrew L

2014-08-01

This study describes an imaging strategy based on glow stick chemistry to non-invasively image oxidative stress and reactive oxygen species (ROS) production in living animals. Upon stimulation, phagocytes produce toxic levels of ROS to kill engulfed microorganisms. The mitochondrial respiratory chain continually generates low levels of superoxide (O2·(-)) that serve as a source for generation of downstream ROS, which function as regulatory signaling intermediaries. A ROS-reacting substrate, 2-methyl-6-[4-methoxyphenyl]-3,7-dihydroimidazo[1,2-a]pyrazin-3-one hydrochloride, was used as the chemical energy donor for generating energy transfer luminescence in phagosomes and mitochondria. Using targeted photoluminescent dyes with specific subcellular localization that serve as chemical energy recipients, our imaging data demonstrate proof-of-concept for using glow stick chemistry to visualize ROS production associated with phagocytosis and mitochondrial respiration in living mice. Glow stick imaging is a complementary hybrid of chemiluminescence and photoluminescence imaging, capable of generating red or far-red emission for deep tissue imaging.

Evaluating the Feasibility of Acoustic Radiation Force Impulse Shear Wave Elasticity Imaging of the Uterine Cervix With an Intracavity Array: A Simulation Study

PubMed Central

Feltovich, Helen; Homyk, Andrew D.; Carlson, Lindsey C.; Hall, Timothy J.

2015-01-01

The uterine cervix softens, shortens, and dilates throughout pregnancy in response to progressive disorganization of its layered collagen microstructure. This process is an essential part of normal pregnancy, but premature changes are associated with preterm birth. Clinically, there are no reliable noninvasive methods to objectively measure cervical softening or assess cervical microstructure. The goal of these preliminary studies was to evaluate the feasibility of using an intracavity ultrasound array to generate acoustic radiation force impulse (ARFI) excitations in the uterine cervix through simulation, and to optimize the acoustic radiation force (ARF) excitation for shear wave elasticity imaging (SWEI) of the tissue stiffness. The cervix is a unique soft tissue target for SWEI because it has significantly greater acoustic attenuation (α = 1.3 to 2.0 dB·cm−1·MHz−1) than other soft tissues, and the pathology being studied tends to lead to an increase in tissue compliance, with healthy cervix being relatively stiff compared with other soft tissues (E ≈ 25 kPa). Additionally, the cervix can only be accessed in vivo using a transvaginal or catheter-based array, which places additional constraints on the excitation focal characteristics that can be used during SWEI. Finite element method (FEM) models of SWEI show that larger-aperture, catheter-based arrays can utilize excitation frequencies up to 7 MHz to generate adequate focal gain up to focal depths 10 to 15 mm deep, with higher frequencies suffering from excessive amounts of near-field acoustic attenuation. Using full-aperture excitations can yield ~40% increases in ARFI-induced displacements, but also restricts the depth of field of the excitation to ~0.5 mm, compared with 2 to 6 mm, which limits the range that can be used for shear wave characterization of the tissue. The center-frequency content of the shear wave particle velocity profiles ranges from 1.5 to 2.5 kHz, depending on the focal configuration and the stiffness of the material being imaged. Overall, SWEI is possible using catheter-based imaging arrays to generate adequate displacements in cervical tissue for shear wave imaging, although specific considerations must be made when optimizing these arrays for this shear wave imaging application. PMID:24081254

Radiolabeled Peptide Scaffolds for PET/SPECT - Optical in Vivo Imaging of Carbohydrate-Lectin Interactions

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

Deutscher, Susan

2014-09-30

The objective of this research is to develop phage display-selected peptides into radio- and fluoresecently- labeled scaffolds for the multimodal imaging of carbohydrate-lectin interactions. While numerous protein and receptor systems are being explored for the development of targeted imaging agents, the targeting and analysis of carbohydrate-lectin complexes in vivo remains relatively unexplored. Antibodies, nanoparticles, and peptides are being developed that target carbohydrate-lectin complexes in living systems. However, antibodies and nanoparticles often suffer from slow clearance and toxicity problems. Peptides are attractive alternative vehicles for the specific delivery of radionuclides or fluorophores to sites of interest in vivo, although, because ofmore » their size, uptake and retention may be less than antibodies. We have selected high affinity peptides that bind a specific carbohydrate-lectin complex involved in cell-cell adhesion and cross-linking using bacteriophage (phage) display technologies (1,2). These peptides have allowed us to probe the role of these antigens in cell adhesion. Fluorescent versions of the peptides have been developed for optical imaging and radiolabeled versions have been used in single photon emission computed tomography (SPECT) and positron emission tomography (PET) in vivo imaging (3-6). A benefit in employing the radiolabeled peptides in SPECT and PET is that these imaging modalities are widely used in living systems and offer deep tissue sensitivity. Radiolabeled peptides, however, often exhibit poor stability and high kidney uptake in vivo. Conversely, optical imaging is sensitive and offers good spatial resolution, but is not useful for deep tissue penetration and is semi-quantitative. Thus, multimodality imaging that relies on the strengths of both radio- and optical- imaging is a current focus for development of new in vivo imaging agents. We propose a novel means to improve the efficacy of radiolabeled and fluorescently labeled peptides, including our lectin/carbohydrate- targeting peptides, by displaying the targeting epitopes on small ~29 amino acid cyclic plant protein scaffolds known as cyclotides. Cyclotides are extremely stable molecules with long serum half-lives and low kidney uptake (7). More than one copy of the peptide can be engineered into the cyclotide loops, thus increasing the avidity of the peptide construct for its target.« less

Corrosion-Fatigue Assessment Program

DTIC Science & Technology

2008-03-31

22 Figure 3.2.1-4 Deep -focus image of Specimen 598-7 – Crack 1...at Feature #2 .........................22 Figure 3.2.1-5 Deep -focus image of Specimen 598-7 – Crack 2 at Feature #5 .........................23...Figure 3.2.1-6 Deep -focus image of Specimen 598-7 – Crack 3 at Feature #3 .........................23 Figure 3.2.1-7 Deep -focus image of Specimen 598-7