Three-dimensional volumetric assessment of hard tissue alterations following horizontal guided bone regeneration using a split-thickness flap design: A case series.

OBJECTIVES: To analyze morphological, volumetric, and linear hard tissue changes following horizontal ridge augmentation using a three-dimensional radiographic method. METHODS: As part of a larger ongoing prospective study, 10 lower lateral surgical sites were selected for evaluation. Horizontal ridge deficiencies were treated with guided bone regeneration (GBR) using a split-thickness flap design and a resorbable collagen barrier membrane. Following the segmentation of baseline and 6-month follow-up cone-beam computed tomography scans, volumetric, linear, and morphological hard tissue changes and the efficacy of the augmentation were assessed (expressed by the volume-to-surface ratio). RESULTS: Volumetric hard tissue gain averaged 605.32 ± 380.68 mm3. An average of 238.48 ± 127.82 mm3 hard tissue loss was also detected at the lingual aspect of the surgical area. Horizontal hard tissue gain averaged 3.00 ± 1.45 mm. Midcrestal vertical hard tissue loss averaged 1.18 ± 0.81 mm. The volume-to-surface ratio averaged 1.19 ± 0.52 mm3/mm2. The three-dimensional analysis showed slight lingual or crestal hard tissue resorption in all cases. In certain instances, the greatest extent of hard tissue gain was observed 2-3 mm apical to the initial level of the marginal crest. CONCLUSIONS: With the applied method, previously unreported aspects of hard tissue changes following horizontal GBR could be examined. Midcrestal bone resorption was demonstrated, most likely caused by increased osteoclast activity following the elevation of the periosteum. The volume-to-surface ratio expressed the efficacy of the procedure independent of the size of the surgical area.

Reconstruction of vertical alveolar ridge deficiencies utilizing a high-density polytetrafluoroethylene membrane /clinical impact of flap dehiscence on treatment outcomes: case series/.

OBJECTIVES: The aim of this study was to evaluate the effects of membrane exposure during vertical ridge augmentation (VRA) utilizing guided bone regeneration with a dense polytetrafluoroethylene (d-PTFE) membrane and a tent-pole space maintaining approach by registering radiographic volumetric, linear and morphological changes. METHODS: In 8 cases alveolar ridge defects were accessed utilizing a split-thickness flap design. Following flap elevation VRA was performed with tent-pole space maintaining approach utilizing the combination of a non-reinforced d-PTFE membrane and a composite graft (1:1 ratio of autogenous bone chips and bovine derived xenografts). Three-dimensional radiographic evaluation of hard tissue changes was carried out with the sequence of cone-beam computed tomography (CBCT) image segmentation, spatial registration and 3D subtraction analysis. RESULTS: Class I or class II membrane exposure was observed in four cases. Average hard tissue gain was found to be 0.70 cm3 ± 0.31 cm3 and 0.82 cm3 ± 0.40 cm3 with and without membrane exposure resulting in a 17% difference. Vertical hard tissue gain averaged 4.06 mm ± 0.56 mm and 3.55 mm ± 0.43 mm in case of submerged and open healing, respectively. Difference in this regard was 14% between the two groups. Horizontal ridge width at 9-month follow-up was 5.89 mm ± 0.51 mm and 5.61 mm ± 1.21 mm with and without a membrane exposure respectively, resulting in a 5% difference. CONCLUSIONS: With the help of the currently reported 3D radiographic evaluation method, it can be concluded that exposure of the new-generation d-PTFE membrane had less negative impact on clinical results compared to literature data reporting on expanded polytetrafluoroethylene membranes.

SlicerHeart: An open-source computing platform for cardiac image analysis and modeling.

Cardiovascular disease is a significant cause of morbidity and mortality in the developed world. 3D imaging of the heart's structure is critical to the understanding and treatment of cardiovascular disease. However, open-source tools for image analysis of cardiac images, particularly 3D echocardiographic (3DE) data, are limited. We describe the rationale, development, implementation, and application of SlicerHeart, a cardiac-focused toolkit for image analysis built upon 3D Slicer, an open-source image computing platform. We designed and implemented multiple Python scripted modules within 3D Slicer to import, register, and view 3DE data, including new code to volume render and crop 3DE. In addition, we developed dedicated workflows for the modeling and quantitative analysis of multi-modality image-derived heart models, including heart valves. Finally, we created and integrated new functionality to facilitate the planning of cardiac interventions and surgery. We demonstrate application of SlicerHeart to a diverse range of cardiovascular modeling and simulation including volume rendering of 3DE images, mitral valve modeling, transcatheter device modeling, and planning of complex surgical intervention such as cardiac baffle creation. SlicerHeart is an evolving open-source image processing platform based on 3D Slicer initiated to support the investigation and treatment of congenital heart disease. The technology in SlicerHeart provides a robust foundation for 3D image-based investigation in cardiovascular medicine.

Peripheral gene interactions define interpretable clusters of core ASD genes in a network-based investigation of the omnigenic theory.

According to the recently proposed omnigenic theory, all expressed genes in a relevant tissue are contributing directly or indirectly to the manifestation of complex disorders such as autism. Thus, holistic approaches can be complementary in studying genetics of these complex disorders to focusing on a limited number of candidate genes. Gene interaction networks can be used for holistic studies of the omnigenic nature of autism. We used Louvain clustering on tissue-specific gene interaction networks and their subgraphs exclusively containing autism-related genes to study the effects of peripheral gene interactions. We observed that the autism gene clusters are significantly weaker connected to each other and the peripheral genes in non-neuronal tissues than in brain-related tissues. The biological functions of the brain clusters correlated well with previous findings on autism, such as synaptic signaling, regulation of DNA methylation, or regulation of lymphocyte activation, however, on the other tissues they did not enrich as significantly. Furthermore, ASD subjects with disruptive mutations in specific gene clusters show phenotypical differences compared to other disruptive variants carrying ASD individuals. Our results strengthen the omnigenic theory and can advance our understanding of the genetic background of autism.

Utilizing a novel radiographic image segmentation method for the assessment of periodontal healing following regenerative surgical treatment.

OBJECTIVE: The aim of the current article was to present a radiographic method to determine the surface area of newly formed periodontal attachment, as well as to analyze volumetric and morphologic changes after regenerative periodontal treatment. METHOD AND MATERIALS: In this retrospective study, 11 singular intrabony periodontal defects were selected for minimally invasive surgical treatment and 3D evaluation. 3D virtual models were acquired by the segmentation of pre- and postoperative CBCT scans. This study determined the surface area of baseline periodontal attachment (RSA-A) and defect-involved root surface (RSA-D) on the preoperative 3D models, and the surface area of new periodontal attachment (RSA-NA) on the postoperative models. Finally, cumulative change of periodontal attachment (∆RSA-A) was calculated and Boolean subtraction was applied on pre- and postoperative 3D models to demonstrate postoperative 3D hard tissue alterations. RESULTS: The average RSA-A was 84.39 ± 33.27 mm2, while the average RSA-D was 24.26 ± 11.94 mm2. The average surface area of RSA-NA after regenerative periodontal surgery was 17.68 ± 10.56 mm2. Additionally, ∆RSA-A was determined to assess the overall effects of ridge alterations on periodontal attachment, averaging 15.53 ± 12.47 mm2, which was found to be statistically significant (P = .00149). Lastly, the volumetric hard tissue gain was found to be 33.56 ± 19.35 mm3, whereas hard tissue resorption of 26.31 ± 38.39 mm3 occurred. CONCLUSION: The proposed 3D radiographic method provides a detailed understanding of new periodontal attachment formation and hard tissue alterations following regenerative surgical treatment of intrabony periodontal defects.

CBCT subtraction analysis of 3D changes following alveolar ridge preservation: a case series of 10 patients with 6-months follow-up.

AIM: The purpose of this article is to present a novel method for the CBCT subtraction analysis of 3D changes following alveolar ridge preservation (ARP) with the application of a semi-automatic segmentation workflow and spatial registration. The study hypothesis was that by utilizing our novel approach, better 3D visualization and improved volumetric and linear evaluations of alveolar reconstructive procedures could be achieved following ARP compared with existing methodologies. MATERIALS AND METHODS: Ten surgical sites of 10 partially edentulous patients were treated with a tunneled guided bone regeneration approach for ARP. Spatial registration and a semi-automatic segmentation method were utilized to create 3D digital models of pre- and postoperative CBCT datasets for subtraction analysis. The primary outcome variable of the study was the volumetric difference between pre- and postoperative CBCT scans. Secondary outcome variables were horizontal and vertical linear measurements at the mesial, distal, and middle aspects of the alveolus. RESULTS: Change of hard tissue volume averaged at 0.34 ± 0.99 cm3. The mean change of vertical hard tissue dimension was 5.97 ± 3.18 mm at the mesial, 6.40 ± 3.03 mm at the distal, and 7.01 ± 3.02 mm at the middle aspect of the extraction sites. Horizontal linear changes averaged at 6.19 ± 0.68 mm at the mesial, 6.32 ± 1.52 mm at the distal, and 6.90 ± 1.48 mm at the middle aspects of the extraction sites. CONCLUSION: The digital reconstruction of CBCT datasets with the presented approach may provide a better understanding of the healing mechanisms following ARP. Not only the direct effect on extraction socket healing, but also the indirect positive effect on adjacent teeth can be visualized.

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures.

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial registration, and free-form surface modeling. Firstly cone-beam computed tomography datasets were reconstructed with a semi-automatic segmentation method. Alveolar bone and teeth are separated into different segments, allowing 3D morphology, and localization of periodontal intrabony defects to be assessed. The severity, extent, and morphology of acute and chronic alveolar ridge defects are validated concerning adjacent teeth. On virtual complex tissue models, positions of dental implants can be planned in 3D. Utilizing spatial registration of IOS and CBCT data and subsequent free-form surface modeling, realistic 3D hybrid models can be acquired, visualizing alveolar bone, teeth, and soft tissues. With the superimposition of IOS and CBCT soft tissue, thickness above the edentulous ridge can be assessed about the underlying bone dimensions; therefore, flap design and surgical flap management can be determined, and occasional complications may be avoided.

Modeling Tool for Rapid Virtual Planning of the Intracardiac Baffle in Double-Outlet Right Ventricle.

PURPOSE: Biventricular repair of double-outlet right ventricle (DORV) necessitates the creation of a complex intracardiac baffle. Creation of the optimal baffle design and placement thereof can be challenging to conceptualize, even with 2-dimensional and 3-dimensional images. This report describes a recently developed methodology for creating virtual baffles to inform intraoperative repair. DESCRIPTION: A total of 3 heart models of DORV were created from cardiac magnetic resonance images. Baffles were created and visualized using custom software. EVALUATION: This report demonstrates application of the tool to virtual planning of the baffle for repair of DORV in 3 cases. Models were examined by a multidisciplinary team, on screen and in virtual reality. Baffles could be rapidly created and revised to facilitate planning of the surgical procedure. CONCLUSIONS: Virtual modeling of the baffle pathway by using cardiac magnetic resonance, creation of physical templates for the baffle, and visualization in virtual reality are feasible and may be beneficial for preoperative planning of complex biventricular repairs in DORV. Further work is needed to demonstrate clinical benefit or improvement in outcomes.

Quantitative Imaging Informatics for Cancer Research.

PURPOSE: We summarize Quantitative Imaging Informatics for Cancer Research (QIICR; U24 CA180918), one of the first projects funded by the National Cancer Institute (NCI) Informatics Technology for Cancer Research program. METHODS: QIICR was motivated by the 3 use cases from the NCI Quantitative Imaging Network. 3D Slicer was selected as the platform for implementation of open-source quantitative imaging (QI) tools. Digital Imaging and Communications in Medicine (DICOM) was chosen for standardization of QI analysis outputs. Support of improved integration with community repositories focused on The Cancer Imaging Archive (TCIA). Priorities included improved capabilities of the standard, toolkits and tools, reference datasets, collaborations, and training and outreach. RESULTS: Fourteen new tools to support head and neck cancer, glioblastoma, and prostate cancer QI research were introduced and downloaded over 100,000 times. DICOM was amended, with over 40 correction proposals addressing QI needs. Reference implementations of the standard in a popular toolkit and standalone tools were introduced. Eight datasets exemplifying the application of the standard and tools were contributed. An open demonstration/connectathon was organized, attracting the participation of academic groups and commercial vendors. Integration of tools with TCIA was improved by implementing programmatic communication interface and by refining best practices for QI analysis results curation. CONCLUSION: Tools, capabilities of the DICOM standard, and datasets we introduced found adoption and utility within the cancer imaging community. A collaborative approach is critical to addressing challenges in imaging informatics at the national and international levels. Numerous challenges remain in establishing and maintaining the infrastructure of analysis tools and standardized datasets for the imaging community. Ideas and technology developed by the QIICR project are contributing to the NCI Imaging Data Commons currently being developed.

SlicerVR for Medical Intervention Training and Planning in Immersive Virtual Reality.

Virtual reality (VR) provides immersive visualization that has proved to be useful in a variety of medical applications. Currently, however, no free open-source software platform exists that would provide comprehensive support for translational clinical researchers in prototyping experimental VR scenarios in training, planning or guiding medical interventions. By integrating VR functions in 3D Slicer, an established medical image analysis and visualization platform, SlicerVR enables virtual reality experience by a single click. It provides functions to navigate and manipulate the virtual scene, as well as various settings to abate the feeling of motion sickness. SlicerVR allows for shared collaborative VR experience both locally and remotely. We present illustrative scenarios created with SlicerVR in a wide spectrum of applications, including echocardiography, neurosurgery, spine surgery, brachytherapy, intervention training and personalized patient education. SlicerVR is freely available under BSD type license as an extension to 3D Slicer and it has been downloaded over 7,800 times at the time of writing this article.

Polymorph segmentation representation for medical image computing.

BACKGROUND AND OBJECTIVE: Segmentation is a ubiquitous operation in medical image computing. Various data representations can describe segmentation results, such as labelmap volumes or surface models. Conversions between them are often required, which typically include complex data processing steps. We identified four challenges related to managing multiple representations: conversion method selection, data provenance, data consistency, and coherence of in-memory objects. METHODS: A complex data container preserves identity and provenance of the contained representations and ensures data coherence. Conversions are executed automatically on-demand. A graph containing the implemented conversion algorithms determines each execution, ensuring consistency between various representations. The design and implementation of a software library are proposed, in order to provide a readily usable software tool to manage segmentation data in multiple data representations. A low-level core library called PolySeg implemented in the Visualization Toolkit (VTK) manages the data objects and conversions. It is used by a high-level application layer, which has been implemented in the medical image visualization and analysis platform 3D Slicer. The application layer provides advanced visualization, transformation, interoperability, and other functions. RESULTS: The core conversion algorithms comprising the graph were validated. Several applications were implemented based on the library, demonstrating advantages in terms of usability and ease of software development in each case. The Segment Editor application provides fast, comprehensive, and easy-to-use manual and semi-automatic segmentation workflows. Clinical applications for gel dosimetry, external beam planning, and MRI-ultrasound image fusion in brachytherapy were rapidly prototyped resulting robust applications that are already in use in clinical research. The conversion algorithms were found to be accurate and reliable using these applications. CONCLUSIONS: A generic software library has been designed and developed for automatic management of multiple data formats in segmentation tasks. It enhances both user and developer experience, enabling fast and convenient manual workflows and quicker and more robust software prototyping. The software's BSD-style open-source license allows complete freedom of use of the library.

Validation of MRI to TRUS registration for high-dose-rate prostate brachytherapy.

PURPOSE: The objective of this study was to develop and validate an open-source module for MRI to transrectal ultrasound (TRUS) registration to support tumor-targeted prostate brachytherapy. METHODS AND MATERIALS: In this study, 15 patients with prostate cancer lesions visible on multiparametric MRI were selected for the validation. T2-weighted images with 1-mm isotropic voxel size and diffusion weighted images were acquired on a 1.5T Siemens imager. Three-dimensional (3D) TRUS images with 0.5-mm slice thickness were acquired. The investigated registration module was incorporated in the open-source 3D Slicer platform, which can compute rigid and deformable transformations. An extension of 3D Slicer, SlicerRT, allows import of and export to DICOM-RT formats. For validation, similarity indices, prostate volumes, and centroid positions were determined in addition to registration errors for common 3D points identified by an experienced radiation oncologist. RESULTS: The average time to compute the registration was 35 ± 3 s. For the rigid and deformable registration, respectively, Dice similarity coefficients were 0.87 ± 0.05 and 0.93 ± 0.01 while the 95% Hausdorff distances were 4.2 ± 1.0 and 2.2 ± 0.3 mm. MRI volumes obtained after the rigid and deformable registration were not statistically different (p > 0.05) from reference TRUS volumes. For the rigid and deformable registration, respectively, 3D distance errors between reference and registered centroid positions were 2.1 ± 1.0 and 0.4 ± 0.1 mm while registration errors between common points were 3.5 ± 3.2 and 2.3 ± 1.1 mm. Deformable registration was found significantly better (p < 0.05) than rigid registration for all parameters. CONCLUSIONS: An open-source MRI to TRUS registration platform was validated for integration in the brachytherapy workflow.

dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM.

Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number of quantitative analysis methods being proposed. The Digital Imaging and Communications in Medicine (DICOM) standard is widely adopted for image and metadata in radiology. dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion of the data stored in commonly used research formats into the standard DICOM representation. dcmqi source code is distributed under BSD-style license. It is freely available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer. Installation and usage instructions are provided in the GitHub repository at https://github.com/qiicr/dcmqi Cancer Res; 77(21); e87-90. ©2017 AACR.

Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

PLUS: open-source toolkit for ultrasound-guided intervention systems.

A variety of advanced image analysis methods have been under the development for ultrasound-guided interventions. Unfortunately, the transition from an image analysis algorithm to clinical feasibility trials as part of an intervention system requires integration of many components, such as imaging and tracking devices, data processing algorithms, and visualization software. The objective of our paper is to provide a freely available open-source software platform-PLUS: Public software Library for Ultrasound-to facilitate rapid prototyping of ultrasound-guided intervention systems for translational clinical research. PLUS provides a variety of methods for interventional tool pose and ultrasound image acquisition from a wide range of tracking and imaging devices, spatial and temporal calibration, volume reconstruction, simulated image generation, and recording and live streaming of the acquired data. This paper introduces PLUS, explains its functionality and architecture, and presents typical uses and performance in ultrasound-guided intervention systems. PLUS fulfills the essential requirements for the development of ultrasound-guided intervention systems and it aspires to become a widely used translational research prototyping platform. PLUS is freely available as open source software under BSD license and can be downloaded from http://www.plustoolkit.org.

Open-source surface mesh-based ultrasound-guided spinal intervention simulator.

PURPOSE:    Ultrasound is prevalent in image-guided therapy as a safe, inexpensive, and widely available imaging modality. However, extensive training in interpreting ultrasound images is essential for successful procedures. An open-source ultrasound image simulator was developed to facilitate the training of ultrasound-guided spinal intervention procedures, thereby eliminating the need for an ultrasound machine from the phantom-based training environment. METHODS:    Anatomical structures and surgical tools are converted to surface meshes for data compression. Anatomical data are converted from segmented volumetric images, while the geometry of surgical tools is available as a surface mesh. The pose of the objects are either constants or coming from a pose-tracking device. Intersection points between the surface models and the ultrasound scan lines are determined with a binary space partitioning tree. The scan lines are divided into segments and filled with gray values determined by an intensity calculation accounting for material properties, reflection, and attenuation parameters defined in a configuration file. The scan lines are finally converted to a regular brightness-mode ultrasound image. RESULTS:    The simulator was tested in a tracked ultrasound imaging system, with a mock transducer tracked with an Ascension trakSTAR electromagnetic tracker, on a spine phantom. A mesh model of the spine was created from CT data. The simulated ultrasound images were generated at a speed of 50 frames per second, and a resolution of [Formula: see text] pixels, with 256 scan lines per frame, on a PC with a 3.4 GHz processor. A human subject trial was conducted to compare the learning performance of novice trainees, with real and simulated ultrasound, in the localization of facet joints of a spine phantom. With 22 participants split into two equal groups, and each participant localizing 6 facet joints, there was no statistical difference in the performance of the two groups, indicating that simulated ultrasound could indeed replace the real ultrasound in phantom-based ultrasonography training for spinal interventions. CONCLUSIONS:    The ultrasound simulator was implemented and integrated into the open-source Public Library for Ultrasound (PLUS) toolkit.

SlicerRT: radiation therapy research toolkit for 3D Slicer.

PURPOSE: Interest in adaptive radiation therapy research is constantly growing, but software tools available for researchers are mostly either expensive, closed proprietary applications, or free open-source packages with limited scope, extensibility, reliability, or user support. To address these limitations, we propose SlicerRT, a customizable, free, and open-source radiation therapy research toolkit. SlicerRT aspires to be an open-source toolkit for RT research, providing fast computations, convenient workflows for researchers, and a general image-guided therapy infrastructure to assist clinical translation of experimental therapeutic approaches. It is a medium into which RT researchers can integrate their methods and algorithms, and conduct comparative testing. METHODS: SlicerRT was implemented as an extension for the widely used 3D Slicer medical image visualization and analysis application platform. SlicerRT provides functionality specifically designed for radiation therapy research, in addition to the powerful tools that 3D Slicer offers for visualization, registration, segmentation, and data management. The feature set of SlicerRT was defined through consensus discussions with a large pool of RT researchers, including both radiation oncologists and medical physicists. The development processes used were similar to those of 3D Slicer to ensure software quality. Standardized mechanisms of 3D Slicer were applied for documentation, distribution, and user support. The testing and validation environment was configured to automatically launch a regression test upon each software change and to perform comparison with ground truth results provided by other RT applications. RESULTS: Modules have been created for importing and loading DICOM-RT data, computing and displaying dose volume histograms, creating accumulated dose volumes, comparing dose volumes, and visualizing isodose lines and surfaces. The effectiveness of using 3D Slicer with the proposed SlicerRT extension for radiation therapy research was demonstrated on multiple use cases. CONCLUSIONS: A new open-source software toolkit has been developed for radiation therapy research. SlicerRT can import treatment plans from various sources into 3D Slicer for visualization, analysis, comparison, and processing. The provided algorithms are extensively tested and they are accessible through a convenient graphical user interface as well as a flexible application programming interface.