Parallel Processing in Web-Based Interactive Echocardiography Simulators

Medical simulation is a new method of education in medicine. It allows training medical students or practitioners without the need to involve patients and makes them familiar with various kinds of examinations, especially related to medical imaging. Simulators that visualize examinations or operations require large computing power to keep time constraints of output presentation. A common approach to this problem is to use graphics processing units (GPU), but the code is not portable. The method of parallelization of processing is more important in component environments, to allow calculating projections in real time. In this paper parallelization issues in the ultrasound view simulation based on provided computer tomography images are analyzed. The proposed domain decomposition for this problem leads to significant reduction in simulation time and allows obtaining an animated visualization for currently available personal computers with multicore processors. The use of a component environment makes the solution portable and makes it possible to implement a web-based application that is the basis for eTraining. The method for creating animation in real time for such solutions is also analyzed

Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography

Abnormal cerebral accumulation of amyloid-beta peptide (Aβ) is a major hallmark of Alzheimer's disease. Non-invasive monitoring of Aβ deposits enables assessing the disease burden in patients and animal models mimicking aspects of the human disease as well as evaluating the efficacy of Aβ-modulating therapies. Previous in vivo assessments of plaque load have been predominantly based on macroscopic fluorescence reflectance imaging (FRI) and confocal or two-photon microscopy using Aβ-specific imaging agents. However, the former method lacks depth resolution, whereas the latter is restricted by the limited field of view preventing a full coverage of the large brain region. Here, we utilized a fluorescence molecular tomography (FMT)-magnetic resonance imaging (MRI) pipeline with the curcumin derivative fluorescent probe CRANAD-2 to achieve full 3D brain coverage for detecting Aβ accumulation in the arcAβ mouse model of cerebral amyloidosis. A homebuilt FMT system was used for data acquisition, whereas a customized software platform enabled the integration of MRI-derived anatomical information as prior information for FMT image reconstruction. The results obtained from the FMT-MRI study were compared to those from conventional planar FRI recorded under similar physiological conditions, yielding comparable time courses of the fluorescence intensity following intravenous injection of CRANAD-2 in a region-of-interest comprising the brain. In conclusion, we have demonstrated the feasibility of visualizing Aβ deposition in 3D using a multimodal FMT-MRI strategy. This hybrid imaging method provides complementary anatomical, physiological and molecular information, thereby enabling the detailed characterization of the disease status in arcAβ mouse models, which can also facilitate monitoring the efficacy of putative treatments targeting Aβ

Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique's advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson's and Alzheimer's disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance

Advanced Endoscopic Navigation:Surgical Big Data,Methodology,and Applications

随着科学技术的飞速发展，健康与环境问题日益成为人类面临的最重大问题之一。信息科学、计算机技术、电子工程与生物医学工程等学科的综合应用交叉前沿课题，研究现代工程技术方法，探索肿瘤癌症等疾病早期诊断、治疗和康复手段。本论文综述了计算机辅助微创外科手术导航、多模态医疗大数据、方法论及其临床应用：从引入微创外科手术导航概念出发，介绍了医疗大数据的术前与术中多模态医学成像方法、阐述了先进微创外科手术导航的核心流程包括计算解剖模型、术中实时导航方案、三维可视化方法及交互式软件技术，归纳了各类微创外科手术方法的临床应用。同时，重点讨论了全球各种手术导航技术在临床应用中的优缺点，分析了目前手术导航领域内的最新技术方法。在此基础上，提出了微创外科手术方法正向数字化、个性化、精准化、诊疗一体化、机器人化以及高度智能化的发展趋势。【Abstract】Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.X.L. acknowledges funding from the Fundamental Research Funds for the Central Universities. T.M.P. acknowledges funding from the Canadian Foundation for Innovation, the Canadian Institutes for Health Research, the National Sciences and Engineering Research Council of Canada, and a grant from Intuitive Surgical Inc

Intraoperative Quantification of Bone Perfusion in Lower Extremity Injury Surgery

Orthopaedic surgery is one of the most common surgical categories. In particular, lower extremity injuries sustained from trauma can be complex and life-threatening injuries that are addressed through orthopaedic trauma surgery. Timely evaluation and surgical debridement following lower extremity injury is essential, because devitalized bones and tissues will result in high surgical site infection rates. However, the current clinical judgment of what constitutes “devitalized tissue” is subjective and dependent on surgeon experience, so it is necessary to develop imaging techniques for guiding surgical debridement, in order to control infection rates and to improve patient outcome. In this thesis work, computational models of fluorescence-guided debridement in lower extremity injury surgery will be developed, by quantifying bone perfusion intraoperatively using Dynamic contrast-enhanced fluorescence imaging (DCE-FI) system. Perfusion is an important factor of tissue viability, and therefore quantifying perfusion is essential for fluorescence-guided debridement. In Chapters 3-7 of this thesis, we explore the performance of DCE-FI in quantifying perfusion from benchtop to translation: We proposed a modified fluorescent microsphere quantification technique using cryomacrotome in animal model. This technique can measure bone perfusion in periosteal and endosteal separately, and therefore to validate bone perfusion measurements obtained by DCE-FI; We developed pre-clinical rodent contaminated fracture model to correlate DCE-FI with infection risk, and compare with multi-modality scanning; Furthermore in clinical studies, we investigated first-pass kinetic parameters of DCE-FI and arterial input functions for characterization of perfusion changes during lower limb amputation surgery; We conducted the first in-human use of dynamic contrast-enhanced texture analysis for orthopaedic trauma classification, suggesting that spatiotemporal features from DCE-FI can classify bone perfusion intraoperatively with high accuracy and sensitivity; We established clinical machine learning infection risk predictive model on open fracture surgery, where pixel-scaled prediction on infection risk will be accomplished. In conclusion, pharmacokinetic and spatiotemporal patterns of dynamic contrast-enhanced imaging show great potential for quantifying bone perfusion and prognosing bone infection. The thesis work will decrease surgical site infection risk and improve successful rates of lower extremity injury surgery

The role of white matter disconnection in stroke as a predictor of clinical outcome after mechanical thrombectomy.

Rationale: Mechanical thrombectomy is a promising approach to acute treatment in large vessel occlusion (LVO) ischemic stroke. This technique has shown to be safe and effective when performed both in early and late-window trials. Several clinical and mainly volumetric, radiological features are used as prognostic factors for functional outcome and patient eligibility. However, emerging evidence supports the idea that lesion topography is strongly associated with prognosis and functional brain recovery. The aim of this study is to examine the role of clinical (i.e. mRS and NIHSS) vs. standard volume-based lesion (i.e. ASPECTS, core, penumbra and final lesion volume) vs. topological radiological (i.e. white matter structural disconnection) features, in patients eligible for acute mechanical thrombectomy. Materials and methods: We selected a group of patients (n=50) who underwent acute mechanical thrombectomy over 47 months, from January 2018 to November 2021, and occurred at the Stroke Unit and Clinica Neurologica of the Hospital of Padova. They were studied with the modified Rankin Scale (mRS) and the National Institutes of Health Stroke Scale (NIHSS) both at admission (pre) and at discharge (post), then, again with the mRS at 90 days from the acute event. The lesions were manually segmented on structural MRI and CT scans using the program ITK-SNAP. Four models were performed through a linear regression analysis. Specifically, we computed a baseline clinical model (M1) based on demographics, pre-stroke mRS and admission NIHSS. Then we added commonly used (standard) radiological parameters of lesion or perfusion damage (core, penumbra, ASPECTS) (M2). Therefore, we added information about the white matter structural disconnection to clinical variables (M3). Finally, we tested a baseline clinical +early recovery model (M4), which included age, pre-mRS, admission NIHSS, and post-mRS. The lesions were normalized in atlas space and displayed to study their distribution and structural disconnections (SDC). Results: The mean baseline mRS was 0.48±0.90, while the mean 90-day mRS was 2.18±1.81. The linear regression analysis showed a significant positive correlation between 90-day mRS and clinical variables (pre-mRS, NIHSS at presentation, post-mRS), while radiological variables (ASPECTS, core, and penumbra volume) did not seem to be associated with functional outcome. The results of the ANOVA analysis showed that, between the four models tested, M4 (including age, pre-mRS, NIHSS at presentation, and post-mRS as independent variables) was the one providing the highest adjusted R-squared [Adj.R-squared=0.614] and explained 62% of the variance in outcome prediction. At a voxel-wise level, we found a significant positive correlation between brain recovery (Delta 90-day mRS-pre-mRS) and damage, affecting predominantly the left corticospinal tract and the corresponding structural white matter disconnection (SDC), which also extended to the cingulum and, bilaterally, to the callosal commissure. Conclusion: In our sample, acute clinical status represents the most valuable prognostic factor. Interestingly, while radiological (i.e. volumetric and semi-quantitative) features, such as ASPECTS, core, and penumbra volume, did not show any significant correlation with 90-day mRS, structural white matter disconnection and lesion topography, in particular of the left corticospinal tract, were associated with a poorer recovery after endovascular treatment. These results could have important future implications in pre-treatment patients’ selection and in post-treatment post stroke rehabilitation.​Rationale: Mechanical thrombectomy is a promising approach to acute treatment in large vessel occlusion (LVO) ischemic stroke. This technique has shown to be safe and effective when performed both in early and late-window trials. Several clinical and mainly volumetric, radiological features are used as prognostic factors for functional outcome and patient eligibility. However, emerging evidence supports the idea that lesion topography is strongly associated with prognosis and functional brain recovery. The aim of this study is to examine the role of clinical (i.e. mRS and NIHSS) vs. standard volume-based lesion (i.e. ASPECTS, core, penumbra and final lesion volume) vs. topological radiological (i.e. white matter structural disconnection) features, in patients eligible for acute mechanical thrombectomy. Materials and methods: We selected a group of patients (n=50) who underwent acute mechanical thrombectomy over 47 months, from January 2018 to November 2021, and occurred at the Stroke Unit and Clinica Neurologica of the Hospital of Padova. They were studied with the modified Rankin Scale (mRS) and the National Institutes of Health Stroke Scale (NIHSS) both at admission (pre) and at discharge (post), then, again with the mRS at 90 days from the acute event. The lesions were manually segmented on structural MRI and CT scans using the program ITK-SNAP. Four models were performed through a linear regression analysis. Specifically, we computed a baseline clinical model (M1) based on demographics, pre-stroke mRS and admission NIHSS. Then we added commonly used (standard) radiological parameters of lesion or perfusion damage (core, penumbra, ASPECTS) (M2). Therefore, we added information about the white matter structural disconnection to clinical variables (M3). Finally, we tested a baseline clinical +early recovery model (M4), which included age, pre-mRS, admission NIHSS, and post-mRS. The lesions were normalized in atlas space and displayed to study their distribution and structural disconnections (SDC). Results: The mean baseline mRS was 0.48±0.90, while the mean 90-day mRS was 2.18±1.81. The linear regression analysis showed a significant positive correlation between 90-day mRS and clinical variables (pre-mRS, NIHSS at presentation, post-mRS), while radiological variables (ASPECTS, core, and penumbra volume) did not seem to be associated with functional outcome. The results of the ANOVA analysis showed that, between the four models tested, M4 (including age, pre-mRS, NIHSS at presentation, and post-mRS as independent variables) was the one providing the highest adjusted R-squared [Adj.R-squared=0.614] and explained 62% of the variance in outcome prediction. At a voxel-wise level, we found a significant positive correlation between brain recovery (Delta 90-day mRS-pre-mRS) and damage, affecting predominantly the left corticospinal tract and the corresponding structural white matter disconnection (SDC), which also extended to the cingulum and, bilaterally, to the callosal commissure. Conclusion: In our sample, acute clinical status represents the most valuable prognostic factor. Interestingly, while radiological (i.e. volumetric and semi-quantitative) features, such as ASPECTS, core, and penumbra volume, did not show any significant correlation with 90-day mRS, structural white matter disconnection and lesion topography, in particular of the left corticospinal tract, were associated with a poorer recovery after endovascular treatment. These results could have important future implications in pre-treatment patients’ selection and in post-treatment post stroke rehabilitation

Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

The cerebellum plays a key role in movement control and in cognition and cerebellar involvement is described in several neurodegenerative diseases. While conventional magnetic resonance imaging (MRI) is widely used for brain and cerebellar morphologic evaluation, advanced MRI techniques allow the investigation of cerebellar microstructural and functional characteristics. Volumetry, voxel-based morphometry, diffusion MRI based fiber tractography, resting state and task related functional MRI, perfusion, and proton MR spectroscopy are among the most common techniques applied to the study of cerebellum. In the present review, after providing a brief description of each technique's advantages and limitations, we focus on their application to the study of cerebellar injury in major neurodegenerative diseases, such as multiple sclerosis, Parkinson's and Alzheimer's disease and hereditary ataxia. A brief introduction to the pathological substrate of cerebellar involvement is provided for each disease, followed by the review of MRI studies exploring structural and functional cerebellar abnormalities and by a discussion of the clinical relevance of MRI measures of cerebellar damage in terms of both clinical status and cognitive performance

Understanding the Contributions of Alzheimer’s Disease & Cardiovascular Risks to Cerebral Small Vessel Disease Manifest as White Matter Hyperintensities on Magnetic Resonance Imaging (MRI)

Introduction: Alzheimer’s Diseases (AD) & cerebral small vessel disease associated with cardiovascular risk factors (cSVD) frequently coexist, differentially affecting both imaging and clinical features associated with aging and dementia. We hypothesized that Magnetic Resonance Imaging (MRI) can be used in novel ways to identify relative contributions of AD & cardiovascular risks to cSVD and brain atrophy, generating new biomarkers & insights into mixed disease states associated with cognitive decline and dementia. Methods: Three experiments were conducted to address the overarching hypothesis. First, we visually rated the clinical MRI of 325 participants from a community-based cross-sectional sample to elucidate the relative association of age, AD (visualized as hippocampal atrophy) and cSVD (visualized as white matter hyperintensities; WMH) with global brain atrophy in experiment 1. In experiment 2, we analyzed cross-sectional MRI scans from 62 participants from the University of Kentucky Alzheimer’s Disease Center (UKADC) with available clinical data on cardiovascular risk and cerebrospinal fluid (CSF) beta-amyloid levels as a marker of AD. Voxel wise regression was used to examine the association of white matter hyperintensities with AD and/or cardiovascular risk (hypertension). Experiment 3, examined longitudinal MRI changes in WMH volumes in 377 participants from the Alzheimer’s Disease Neuroimaging Initiative 2 (ADNI 2). Subjects were categorized into three groups based on WMH volume change, including those that demonstrated regression (n=96; 25.5%), stability (n=72; 19.1%), and progression (n=209; 55.4%) of WMH volume over time. Differences in brain atrophy measures and cognitive testing among the three group were conducted. Results: In the first experiment, logistic regression analysis demonstrated that a 1-year increase in age was associated with global brain atrophy (OR = 1.04; p = .04), medial temporal lobe atrophy (MTA; a surrogate of AD) (OR = 3.7; p \u3c .001), and WMH as surrogate of cSVD (OR = 8.80; p \u3c .001). Both MTA and WMH were strongly associated with global brain atrophy in our study population, with WMH showing the strongest relationship after adjusting for age. In the second experiment, linear regression as well as mediation and moderation analyses demonstrated significant main effects of hypertension (HTN; the strongest risk factor associated with cSVD) and CSF Aβ 1-42 (a surrogate of AD) on WMH volume, but no significant HTN×CSF Aβ 1-42 interaction. Further exploration of the independence of HTN and Aβ using a voxelwise analysis approach, demonstrated unique patterns of WM alteration associated with either hypertension or CSF Aβ 1-42, confirming that both independently contribute to WMH previously classified as cSVD. Extending this work into a longitudinal model rather than focusing on purely cross-sectional associations, we demonstrated that spontaneous WMH regression is common, and that such regression is associated with a reduced rate of global brain atrophy (p = 0.012), and improvement in memory function over time (p = 0.003). Conclusion: These data demonstrate that both AD and cSVD frequently coexist in the same brain, contributing differentially to alterations in brain structure, subcortical white matter injury, and cognitive function. These effects can be disentangled using MRI, and while we currently lack therapeutic interventions to halt or reverse AD, the dynamic WMH change evident in our data clearly suggests that the ability to reverse cSVD exists today