scholarly journals Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform

2020 ◽  
pp. 736-748
Author(s):  
Mireia Crispin-Ortuzar ◽  
Marcel Gehrung ◽  
Stephan Ursprung ◽  
Andrew B. Gill ◽  
Anne Y. Warren ◽  
...  
Keyword(s):  
Open Source ◽  
Tumor Heterogeneity ◽  
Spatial Scales ◽  
Three Dimensional ◽  
Patient Specific ◽  
Sampling Location ◽  
Precision Oncology ◽  
Similarity Coefficients ◽  
Tissue Samples ◽  
Manual Intervention

PURPOSE Spatial heterogeneity of tumors is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood because it relies on the accurate coregistration of medical images and tissue biopsies. Tumor molds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice. These hurdles have so far hindered the progress in the area of multiscale integration of tumor heterogeneity data. METHODS We have developed an open-source computational framework to automatically produce patient-specific 3-dimensional–printed molds that can be used in the clinical setting. Our approach achieves accurate coregistration of sampling location between tissue and imaging, and integrates seamlessly with clinical, imaging, and pathology workflows. RESULTS We applied our framework to patients with renal cancer undergoing radical nephrectomy. We created personalized molds for 6 patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.96 for tumor regions and between 0.70 and 0.76 for healthy kidneys. The framework required minimal manual intervention, producing the final mold design in just minutes, while automatically taking into account clinical considerations such as a preference for specific cutting planes. CONCLUSION Our work provides a robust and automated interface between imaging and tissue samples, enabling the development of clinical studies to probe tumor heterogeneity on multiple spatial scales.

scholarly journals 3D-printed moulds for image-guided surgical biopsies: an open source computational platform

2019 ◽  
Author(s):  
Mireia Crispin-Ortuzar ◽  
Marcel Gehrung ◽  
Stephan Ursprung ◽  
Andrew B Gill ◽  
Anne Y Warren ◽  
...  
Keyword(s):  
Open Source ◽  
Spatial Scales ◽  
Patient Specific ◽  
Sampling Location ◽  
Precision Oncology ◽  
Similarity Coefficients ◽  
Tumour Heterogeneity ◽  
Tissue Samples ◽  
3D Printed ◽  
Mould Design

ABSTRACTPURPOSESpatial heterogeneity of tumours is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood, as it relies on the accurate co-registration of medical images and tissue biopsies. tumour moulds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice. These hurdles have so far hindered the progress in the area of multiscale integration of tumour heterogeneity data.METHODSWe have developed an open source computational framework to automatically produce patient-specific 3D-printed moulds that can be used in the clinical setting. Our approach achieves accurate co-registration of sampling location between tissue and imaging, and integrates seamlessly with clinical, imaging and pathology workflows.RESULTSWe applied our framework to patients with renal cancer undergoing radical nephrectomy. We created personalised moulds for five patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.93 for tumour regions, and between 0.70 and 0.76 for healthy kidney. The framework required minimal manual intervention, producing the final mould design in just minutes, while automatically taking into account clinical considerations such as a preference for specific cutting planes.CONCLUSIONOur work provides a robust and automated interface between imaging and tissue samples, enabling the development of clinical studies to probe tumour heterogeneity on multiple spatial scales.

Helical Axis Data Visualization and Analysis of the Knee Joint Articulation

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Ricardo Manuel Millán Vaquero ◽  
Alexander Vais ◽  
Sean Dean Lynch ◽  
Jan Rzepecki ◽  
Karl-Ingo Friese ◽  
...  
Keyword(s):  
Knee Joint ◽  
Lie Algebra ◽  
Degrees Of Freedom ◽  
Spatial Scales ◽  
Three Dimensional ◽  
Patient Specific ◽  
Helical Axis ◽  
Accurate Analysis ◽  
Related Data ◽  
Flexion Extension

We present processing methods and visualization techniques for accurately characterizing and interpreting kinematical data of flexion–extension motion of the knee joint based on helical axes. We make use of the Lie group of rigid body motions and particularly its Lie algebra for a natural representation of motion sequences. This allows to analyze and compute the finite helical axis (FHA) and instantaneous helical axis (IHA) in a unified way without redundant degrees of freedom or singularities. A polynomial fitting based on Legendre polynomials within the Lie algebra is applied to provide a smooth description of a given discrete knee motion sequence which is essential for obtaining stable instantaneous helical axes for further analysis. Moreover, this allows for an efficient overall similarity comparison across several motion sequences in order to differentiate among several cases. Our approach combines a specifically designed patient-specific three-dimensional visualization basing on the processed helical axes information and incorporating computed tomography (CT) scans for an intuitive interpretation of the axes and their geometrical relation with respect to the knee joint anatomy. In addition, in the context of the study of diseases affecting the musculoskeletal articulation, we propose to integrate the above tools into a multiscale framework for exploring related data sets distributed across multiple spatial scales. We demonstrate the utility of our methods, exemplarily processing a collection of motion sequences acquired from experimental data involving several surgery techniques. Our approach enables an accurate analysis, visualization and comparison of knee joint articulation, contributing to the evaluation and diagnosis in medical applications.

scholarly journals SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization

2020 ◽  
pp. 299-309 ◽  
Author(s):  
Fan Zhang ◽  
Thomas Noh ◽  
Parikshit Juvekar ◽  
Sarah F. Frisken ◽  
Laura Rigolo ◽  
...  
Keyword(s):  
Open Source ◽  
Diffusion Tensor ◽  
Intraoperative Imaging ◽  
Time Integration ◽  
Three Dimensional ◽  
High Grade Glioma ◽  
Patient Specific ◽  
Imaging Data ◽  
3D Slicer ◽  
Research Software

PURPOSE We present SlicerDMRI, an open-source software suite that enables research using diffusion magnetic resonance imaging (dMRI), the only modality that can map the white matter connections of the living human brain. SlicerDMRI enables analysis and visualization of dMRI data and is aimed at the needs of clinical research users. SlicerDMRI is built upon and deeply integrated with 3D Slicer, a National Institutes of Health–supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. Integration with 3D Slicer provides many features of interest to cancer researchers, such as real-time integration with neuronavigation equipment, intraoperative imaging modalities, and multimodal data fusion. One key application of SlicerDMRI is in neurosurgery research, where brain mapping using dMRI can provide patient-specific maps of critical brain connections as well as insight into the tissue microstructure that surrounds brain tumors. PATIENTS AND METHODS In this article, we focus on a demonstration of SlicerDMRI as an informatics tool to enable end-to-end dMRI analyses in two retrospective imaging data sets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor analysis, advanced multifiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI. RESULTS We illustrate the ability of SlicerDMRI to perform both conventional and advanced dMRI analyses as well as to enable multimodal image analysis and visualization. We provide an overview of the clinical rationale for each analysis along with pointers to the SlicerDMRI tools used in each. CONCLUSION SlicerDMRI provides open-source and clinician-accessible research software tools for dMRI analysis. SlicerDMRI is available for easy automated installation through the 3D Slicer Extension Manager.

scholarly journals A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package

2018 ◽  
Vol 140 (2) ◽  
Author(s):  
Hongzhi Lan ◽  
Adam Updegrove ◽  
Nathan M. Wilson ◽  
Gabriel D. Maher ◽  
Shawn C. Shadden ◽  
...  
Keyword(s):  
Open Source ◽  
Computer Aided Design ◽  
Three Dimensional ◽  
User Interaction ◽  
Solid Modeling ◽  
Patient Specific ◽  
Cardiovascular Modeling ◽  
Software Interface ◽  
Open Source Software Package ◽  
3D Solid

Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid–structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.

scholarly journals Applications of 3D Bioprinted-Induced Pluripotent Stem Cells in Healthcare

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Soja Saghar Soman ◽  
Sanjairaj Vijayavenkataraman
Keyword(s):  
Disease Modeling ◽  
Three Dimensional ◽  
Induced Pluripotent Stem Cell ◽  
Drug Efficacy ◽  
Patient Specific ◽  
Precision Oncology ◽  
Human Tissues ◽  
3D Bioprinting ◽  
3D Print ◽  
Induced Pluripotent

Induced pluripotent stem cell (iPSC) technology and advancements in three-dimensional (3D) bioprinting technology enable scientists to reprogram somatic cells to iPSCs and 3D print iPSC-derived organ constructs with native tissue architecture and function. iPSCs and iPSC-derived cells suspended in hydrogels (bioinks) allow to print tissues and organs for downstream medical applications. The bioprinted human tissues and organs are extremely valuable in regenerative medicine as bioprinting of autologous iPSC-derived organs eliminates the risk of immune rejection with organ transplants. Disease modeling and drug screening in bioprinted human tissues will give more precise information on disease mechanisms, drug efficacy, and drug toxicity than experimenting on animal models. Bioprinted iPSC-derived cancer tissues will aid in the study of early cancer development and precision oncology to discover patient-specific drugs. In this review, we present a brief summary of the combined use of two powerful technologies, iPSC technology, and 3D bioprinting in health-care applications.

scholarly journals Single-cell analysis of hepatoblastoma identifies distinct tumor cell signatures that predict susceptibility to chemotherapy using patient-specific tumor spheroids

2021 ◽  
Author(s):  
Hanbing Song ◽  
Simon Bucher ◽  
Katherine Rosenberg ◽  
Margaret Tsui ◽  
Deviana Burhan ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Tumor Heterogeneity ◽  
Single Cell Analysis ◽  
Primary Liver Cancer ◽  
Patient Specific ◽  
Precision Oncology ◽  
Cell Of Origin ◽  
Specific Tumor ◽  
Transcriptomic Signature

Pediatric hepatoblastoma (HB) is the most common primary liver cancer in infants and children. Studies of HB that focus exclusively on tumor cells demonstrate sparse somatic mutations and a common cell of origin, the hepatoblast, across patients. In contrast to the homogeneity these studies would suggest, HB tumors have a high degree of heterogeneity that can portend poor prognosis. In this study, we used single- cell genomic techniques to analyze resected human pediatric HB specimens. This study establishes that tumor heterogeneity can be defined by the relative proportions of five distinct subtypes of tumor cells. Notably, patient-derived HB spheroid cultures predict differential responses to treatment based on the transcriptomic signature of each tumor, suggesting a path forward for precision oncology for these tumors. Collectively, these results define HB tumor heterogeneity with single-cell resolution and demonstrate that patient-derived spheroids can be used to evaluate responses to chemotherapy.

Confocal laser microscopy of impregnated central nervous system tissue

1988 ◽  
Vol 46 ◽  
pp. 94-95
Author(s):  
J.N. Turner ◽  
M. Siemens ◽  
D. Szarowski ◽  
D.N. Collins
Keyword(s):  
Electron Microscopy ◽  
Central Nervous System ◽  
Nervous System ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Confocal Laser ◽  
High Contrast ◽  
Central Nervous System Tissue ◽  
Tissue Samples ◽  
Reflected Light

A classic preparation of central nervous system tissue (CNS) is the Golgi procedure popularized by Cajal. The method is partially specific as only a few cells are impregnated with silver chromate usualy after osmium post fixation. Samples are observable by light (LM) or electron microscopy (EM). However, the impregnation is often so dense that structures are masked in EM, and the osmium background may be undesirable in LM. Gold toning is used for a subtle but high contrast EM preparation, and osmium can be omitted for LM. We are investigating these preparations as part of a study to develop correlative LM and EM (particularly HVEM) methodologies in neurobiology. Confocal light microscopy is particularly useful as the impregnated cells have extensive three-dimensional structure in tissue samples from one to several hundred micrometers thick. Boyde has observed similar preparations in the tandem scanning reflected light microscope (TSRLM).

scholarly journals Integrated multi-modality image-guided navigation for neurosurgery: open-source software platform using state-of-the-art clinical hardware

2021 ◽  
Author(s):  
Jonathan Shapey ◽  
Thomas Dowrick ◽  
Rémi Delaunay ◽  
Eleanor C. Mackle ◽  
Stephen Thompson ◽  
...  
Keyword(s):  
Skull Base ◽  
Open Source ◽  
Open Source Software ◽  
Skull Base Surgery ◽  
Patient Specific ◽  
Software Platform ◽  
Image Guided ◽  
Phantom Model ◽  
Technical Requirements ◽  
Navigated Ultrasound

Abstract Purpose Image-guided surgery (IGS) is an integral part of modern neuro-oncology surgery. Navigated ultrasound provides the surgeon with reconstructed views of ultrasound data, but no commercial system presently permits its integration with other essential non-imaging-based intraoperative monitoring modalities such as intraoperative neuromonitoring. Such a system would be particularly useful in skull base neurosurgery. Methods We established functional and technical requirements of an integrated multi-modality IGS system tailored for skull base surgery with the ability to incorporate: (1) preoperative MRI data and associated 3D volume reconstructions, (2) real-time intraoperative neurophysiological data and (3) live reconstructed 3D ultrasound. We created an open-source software platform to integrate with readily available commercial hardware. We tested the accuracy of the system’s ultrasound navigation and reconstruction using a polyvinyl alcohol phantom model and simulated the use of the complete navigation system in a clinical operating room using a patient-specific phantom model. Results Experimental validation of the system’s navigated ultrasound component demonstrated accuracy of $$<4.5\,\hbox {mm}$$ < 4.5 mm and a frame rate of 25 frames per second. Clinical simulation confirmed that system assembly was straightforward, could be achieved in a clinically acceptable time of $$<15\,\hbox {min}$$ < 15 min and performed with a clinically acceptable level of accuracy. Conclusion We present an integrated open-source research platform for multi-modality IGS. The present prototype system was tailored for neurosurgery and met all minimum design requirements focused on skull base surgery. Future work aims to optimise the system further by addressing the remaining target requirements.

scholarly journals Numerical computation of blood flow for a patient-specific hemodialysis shunt model

2021 ◽  
Author(s):  
Surabhi Rathore ◽  
Tomoki Uda ◽  
Viet Q. H. Huynh ◽  
Hiroshi Suito ◽  
Toshitaka Watanabe ◽  
...  
Keyword(s):  
Stokes Equations ◽  
Three Dimensional ◽  
Arteriovenous Shunt ◽  
Navier Stokes ◽  
Patient Specific ◽  
Stabilized Finite Element ◽  
Computed Tomography Scanning ◽  
Outflow Boundary ◽  
Stage Renal Disease ◽  
End Stage

AbstractHemodialysis procedure is usually advisable for end-stage renal disease patients. This study is aimed at computational investigation of hemodynamical characteristics in three-dimensional arteriovenous shunt for hemodialysis, for which computed tomography scanning and phase-contrast magnetic resonance imaging are used. Several hemodynamical characteristics are presented and discussed depending on the patient-specific morphology and flow conditions including regurgitating flow from the distal artery caused by the construction of the arteriovenous shunt. A simple backflow prevention technique at an outflow boundary is presented, with stabilized finite element approaches for incompressible Navier–Stokes equations.

scholarly journals Application of subject-specific adaptive mechanical loading for bone healing in a mouse tail vertebral defect

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angad Malhotra ◽  
Matthias Walle ◽  
Graeme R. Paul ◽  
Gisela A. Kuhn ◽  
Ralph Müller
Keyword(s):  
Mechanical Loading ◽  
Bone Defect ◽  
Bone Healing ◽  
Three Dimensional ◽  
Patient Specific ◽  
Dependent Manner ◽  
Micro Computed Tomography ◽  
Computed Tomography Images ◽  
Bone Defect Healing ◽  
Subject Specific

AbstractMethods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to clinical bone defect healing scenarios, where mechanical loading can become patient-specific and more efficacious. This is achieved by accounting for initial bone defect conditions and spatio-temporal healing, both being factors that are always unique to the patient.

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