Automatic landmark identification in cone-beam computed tomography.

OBJECTIVE: To present and validate an open-source fully automated landmark placement (ALICBCT) tool for cone-beam computed tomography scans. MATERIALS AND METHODS: One hundred and forty-three large and medium field of view cone-beam computed tomography (CBCT) were used to train and test a novel approach, called ALICBCT that reformulates landmark detection as a classification problem through a virtual agent placed inside volumetric images. The landmark agents were trained to navigate in a multi-scale volumetric space to reach the estimated landmark position. The agent movements decision relies on a combination of DenseNet feature network and fully connected layers. For each CBCT, 32 ground truth landmark positions were identified by 2 clinician experts. After validation of the 32 landmarks, new models were trained to identify a total of 119 landmarks that are commonly used in clinical studies for the quantification of changes in bone morphology and tooth position. RESULTS: Our method achieved a high accuracy with an average of 1.54 ± 0.87 mm error for the 32 landmark positions with rare failures, taking an average of 4.2 second computation time to identify each landmark in one large 3D-CBCT scan using a conventional GPU. CONCLUSION: The ALICBCT algorithm is a robust automatic identification tool that has been deployed for clinical and research use as an extension in the 3D Slicer platform allowing continuous updates for increased precision.

Clinical decision support systems in orthodontics: A narrative review of data science approaches.

Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.

Decision Support Systems in Temporomandibular Joint Osteoarthritis: A review of Data Science and Artificial Intelligence Applications.

With the exponential growth of computational systems and increased patient data acquisition, dental research faces new challenges to manage a large quantity of information. For this reason, data science approaches are needed for the integrative diagnosis of multifactorial diseases, such as Temporomandibular joint (TMJ) Osteoarthritis (OA). The Data science spectrum includes data capture/acquisition, data processing with optimized web-based storage and management, data analytics involving in-depth statistical analysis, machine learning (ML) approaches, and data communication. Artificial intelligence (AI) plays a crucial role in this process. It consists of developing computational systems that can perform human intelligence tasks, such as disease diagnosis, using many features to help in the decision-making support. Patient's clinical parameters, imaging exams, and molecular data are used as the input in cross-validation tasks, and human annotation/diagnosis is also used as the gold standard to train computational learning models and automatic disease classifiers. This paper aims to review and describe AI and ML techniques to diagnose TMJ OA and data science approaches for imaging processing. We used a web-based system for multi-center data communication, algorithms integration, statistics deployment, and process the computational machine learning models. We successfully show AI and data-science applications using patients' data to improve the TMJ OA diagnosis decision-making towards personalized medicine.

PAUF/ZG16B promotes colorectal cancer progression through alterations of the mitotic functions and the Wnt/ß-catenin pathway.

Pancreatic adenocarcinoma upregulated factor (PAUF), also known as ZG16B, was previously found in the secretome of metastatic colorectal cancer cells. Here, we demonstrated the presence of PAUF at the intracellular level and its multiple effects on cancer progression. An initial decline of PAUF expression was observed at early stages of colorectal cancer followed by an increase at the metastatic site. PAUF was located at different cellular compartments: membrane-associated vesicles, endosomes, microtubule-associated vesicles, cell growth cones and the cell nucleus. PAUF loss in two colorectal cancer cell lines caused severe alterations in the cell phenotype and cell cycle, including tetraploidy, extensive genomic alterations, micronuclei and increased apoptosis. An exhaustive analysis of the PAUF interactome using different proteomic approaches revealed the presence of multiple components of the cell cycle, mitotic checkpoint, Wnt pathway and intracellular transport. Among the interacting proteins we found ZW10, a moonlighting protein with a dual function in membrane trafficking and mitosis. In addition, PAUF silencing was associated to APC loss and increased ß-catenin nuclear expression. Altogether, our results suggest that PAUF depletion increases aneuploidy, promotes apoptosis and activates the Wnt/ß-catenin pathway in colorectal cancer cells facilitating cancer progression. In summary, PAUF behaves as a multifunctional protein, with different roles in cancer progression according to the extra- or intracellular expression, suggesting a therapeutic value for colorectal cancer.

3D superimposition of craniofacial imaging-The utility of multicentre collaborations.

Clinical applications of 3D image registration and superimposition have contributed to better understanding growth changes and clinical outcomes. The use of 3D dental and craniofacial imaging in dentistry requires validate image analysis methods for improved diagnosis, treatment planning, navigation and assessment of treatment response. Volumetric 3D images, such as cone-beam computed tomography, can now be superimposed by voxels, surfaces or landmarks. Regardless of the image modality or the software tools, the concepts of regions or points of reference affect all quantitative of qualitative assessments. This study reviews current state of the art in 3D image analysis including 3D superimpositions relative to the cranial base and different regional superimpositions, the development of open source and commercial tools for 3D analysis, how this technology has increased clinical research collaborations from centres all around the globe, some insight on how to incorporate artificial intelligence for big data analysis and progress towards personalized orthodontics.

Decreased Axon Caliber Underlies Loss of Fiber Tract Integrity, Disproportional Reductions in White Matter Volume, and Microcephaly in Angelman Syndrome Model Mice.

Angelman syndrome (AS) is a debilitating neurodevelopmental disorder caused by loss of function of the maternally inherited UBE3A allele. It is currently unclear how the consequences of this genetic insult unfold to impair neurodevelopment. We reasoned that by elucidating the basis of microcephaly in AS, a highly penetrant syndromic feature with early postnatal onset, we would gain new insights into the mechanisms by which maternal UBE3A loss derails neurotypical brain growth and function. Detailed anatomical analysis of both male and female maternal Ube3a-null mice reveals that microcephaly in the AS mouse model is primarily driven by deficits in the growth of white matter tracts, which by adulthood are characterized by densely packed axons of disproportionately small caliber. Our results implicate impaired axon growth in the pathogenesis of AS and identify noninvasive structural neuroimaging as a potentially valuable tool for gauging therapeutic efficacy in the disorder.SIGNIFICANCE STATEMENT People who maternally inherit a deletion or nonfunctional copy of the UBE3A gene develop Angelman syndrome (AS), a severe neurodevelopmental disorder. To better understand how loss of maternal UBE3A function derails brain development, we analyzed brain structure in a maternal Ube3a knock-out mouse model of AS. We report that the volume of white matter (WM) is disproportionately reduced in AS mice, indicating that deficits in WM development are a major factor underlying impaired brain growth and microcephaly in the disorder. Notably, we find that axons within the WM pathways of AS model mice are abnormally small in caliber. This defect is associated with slowed nerve conduction, which could contribute to behavioral deficits in AS, including motor dysfunction.

Three-dimensional quantitative assessment of surgical stability and condylar displacement changes after counterclockwise maxillomandibular advancement surgery: Effect of simultaneous articular disc repositioning.

INTRODUCTION: In this study, we quantitatively assessed 3-dimensional condylar displacement during counterclockwise maxillomandibular advancement surgery (CMMA) with or without articular disc repositioning, focusing on surgical stability in the follow-up period. METHODS: The 79 patients treated with CMMA had cone-beam computed tomography scans taken before surgery, immediately after surgery, and, on average, 15 months postsurgery. We divided the 142 condyles into 3 groups: group 1 (n = 105), condyles of patients diagnosed with symptomatic presurgical temporomandibular joint articular disc displacement who had articular disc repositioning concomitantly with CMMA; group 2 (n = 23), condyles of patients with clinical verification of presurgical articular disc displacement who had only CMMA; and group 3 (n = 14), condyles of patients with healthy temporomandibular joints who had CMMA. Presurgical and postsurgical 3-dimensional models were superimposed using voxel-based registration on the cranial base. Three-dimensional cephalometrics and shape correspondence were applied to assess surgical and postsurgical displacement changes. RESULTS: Immediately after surgery, the condyles moved mostly backward and medially and experienced lateral yaw, medial roll, and upward pitch in the 3 groups. Condyles in group 1 showed downward displacement, whereas the condyles moved upward in groups 2 and 3 (P ≤0.001). Although condylar displacement changes occurred in the 3 groups, the overall surgical procedure appeared to be fairly stable, particularly for groups 1 and 3. Group 2 had the greatest amount of relapse (P ≤0.05). CONCLUSIONS: CMMA has been shown to be a stable procedure for patients with healthy temporomandibular joints and for those who had simultaneous articular disc repositioning surgery.

Adult rat cortical thickness changes across age and following adolescent intermittent ethanol treatment.

Human studies have established that adolescence is a period of brain maturation that parallels the development of adult behaviors. However, little is known regarding cortical development in the adult rat brain. We used magnetic resonance imaging (MRI) and histology to assess the impact of age on adult Wistar rat cortical thickness on postnatal day (P)80 and P220 as well as the effect of adolescent binge ethanol exposure on adult (P80) cortical thickness. MRI revealed changes in cortical thickness between P80 and P220 that differ across cortical region. The adult P220 rat prefrontal cortex increased in thickness whereas cortical thinning occurred in both the cingulate and parietal cortices relative to young adult P80 rats. Histological analysis confirmed the age-related cortical thinning. In the second series of experiments, an animal model of adolescent intermittent ethanol (AIE; 5.0 g/kg, intragastrically, 20 percent ethanol w/v, 2 days on/2 days off from P25 to P55) was used to assess the effects of alcohol on cortical thickness in young adult (P80) rats. MRI revealed that AIE resulted in region-specific cortical changes. A small region within the prefrontal cortex was significantly thinner whereas medial cortical regions were significantly thicker in young adult (P80) AIE-treated rats. The observed increase in cortical thickness was confirmed by histology. Thus, the rat cerebral cortex continues to undergo cortical thickness changes into adulthood, and adolescent alcohol exposure alters the young adult cortex that could contribute to brain dysfunction in adulthood.

Impact on clinical practice of the implementation of guidelines for the toxicity management of targeted therapies in kidney cancer. The protect-2 study.

BACKGROUND: The impact of such recommendations after their implementation of guidelines has not usually been evaluated. Herein, we assessed the impact and compliance with the Spanish Oncology Genitourinary Group (SOGUG) Guidelines for toxicity management of targeted therapies in metastatic renal cell carcinoma (mRCC) in daily clinical practice. METHODS: Data on 407 mRCC patients who initiated first-line targeted therapy during the year before and the year after publication and implementation of the SOGUG guideline program were available from 34 Spanish Hospitals. Adherence to SOGUG Guidelines was assessed in every cycle. RESULTS: Adverse event (AE) management was consistent with the Guidelines as a whole for 28.7% out of 966 post-implementation cycles compared with 23.1% out of 892 pre-implementation cycles (p = 0.006). Analysis of adherence by AE in non-compliant cycles showed significant changes in appropriate management of hypertension (33% pre-implementation vs. 44.5% post-implementation cycles; p < 0.0001), diarrhea (74.0% vs. 80.5%; p = 0.011) and dyslipemia (25.0% vs. 44.6%; p < 0.001). CONCLUSIONS: Slight but significant improvements in AE management were detected following the implementation of SOGUG recommendations. However, room for improvement in the management of AEs due to targeted agents still remains and could be the focus for further programs in this direction.

Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction.

Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction.

An RGD motif present in cadherin 17 induces integrin activation and tumor growth.

Little is known about the mechanism of integrin activation by cadherin 17 (CDH17). Here we observed the presence of a tri-peptide motif, RGD, in domain 6 of the human CDH17 sequence and other cadherins such as cadherin 5 and cadherin 6. The use of CDH17 RAD mutants demonstrated a considerable decrease of proliferation and adhesion in RKO and KM12SM colon cancer cells. Furthermore, RGD peptides inhibited the adhesion of both cell lines to recombinant CDH17 domain 6. The RGD motif added exogenously to the cells provoked a change in ß1 integrin to an active, high-affinity conformation and an increase in focal adhesion kinase and ERK1/2 activation. In vivo experiments with Swiss nude mice demonstrated that cancer cells expressing the CDH17 RAD mutant showed a considerable delay in tumor growth and liver homing. CDH17 RGD effects were also active in pancreatic cancer cells. Our results suggest that α2ß1 integrin interacts with two different ligands, collagen IV and CDH17, using two different binding sites. In summary, the RGD binding motif constitutes a switch for integrin pathway activation and shows a novel capacity of CDH17 as an integrin ligand. This motif could be targeted to avoid metastatic dissemination in tumors overexpressing CDH17 and other RGD-containing cadherins.

Incorporating 3-dimensional models in online articles.

INTRODUCTION: The aims of this article are to introduce the capability to view and interact with 3-dimensional (3D) surface models in online publications, and to describe how to prepare surface models for such online 3D visualizations. METHODS: Three-dimensional image analysis methods include image acquisition, construction of surface models, registration in a common coordinate system, visualization of overlays, and quantification of changes. Cone-beam computed tomography scans were acquired as volumetric images that can be visualized as 3D projected images or used to construct polygonal meshes or surfaces of specific anatomic structures of interest. The anatomic structures of interest in the scans can be labeled with color (3D volumetric label maps), and then the scans are registered in a common coordinate system using a target region as the reference. The registered 3D volumetric label maps can be saved in .obj, .ply, .stl, or .vtk file formats and used for overlays, quantification of differences in each of the 3 planes of space, or color-coded graphic displays of 3D surface distances. RESULTS: All registered 3D surface models in this study were saved in .vtk file format and loaded in the Elsevier 3D viewer. In this study, we describe possible ways to visualize the surface models constructed from cone-beam computed tomography images using 2D and 3D figures. The 3D surface models are available in the article's online version for viewing and downloading using the reader's software of choice. These 3D graphic displays are represented in the print version as 2D snapshots. Overlays and color-coded distance maps can be displayed using the reader's software of choice, allowing graphic assessment of the location and direction of changes or morphologic differences relative to the structure of reference. The interpretation of 3D overlays and quantitative color-coded maps requires basic knowledge of 3D image analysis. CONCLUSIONS: When submitting manuscripts, authors can now upload 3D models that will allow readers to interact with or download them. Such interaction with 3D models in online articles now will give readers and authors better understanding and visualization of the results.

Euclidean and Shape-Based Analysis of the Dynamic Mitral Annulus in Children using a Novel Open-Source Framework.

BACKGROUND: The dynamic shape of the normal adult mitral annulus has been shown to be important to mitral valve function. However, annular dynamics of the healthy mitral valve in children have yet to be explored. The aim of this study was to model and quantify the shape and major modes of variation of pediatric mitral valve annuli in four phases of the cardiac cycle using transthoracic echocardiography. METHODS: The mitral valve annuli of 100 children and young adults with normal findings on three-dimensional echocardiography were modeled in four different cardiac phases using the SlicerHeart extension for 3D Slicer. Annular metrics were quantified using SlicerHeart, and optimal normalization to body surface area was explored. Mean annular shapes and the principal components of variation were computed using custom code implemented in a new SlicerHeart module (Annulus Shape Analyzer). Shape was regressed over metrics of age and body surface area, and mean shapes for five age-stratified groups were generated. RESULTS: The ratio of annular height to commissural width of the mitral valve ("saddle shape") changed significantly throughout age for systolic phases (P < .001) but within a narrow range (median range, 0.20-0.25). Annular metrics changed statistically significantly between the diastolic and systolic phases of the cardiac cycle. Visually, the annular shape was maintained with respect to age and body surface area. Principal-component analysis revealed that the pediatric mitral annulus varies primarily in size (mode 1), ratio of annular height to commissural width (mode 2), and sphericity (mode 3). CONCLUSIONS: The saddle-shaped mitral annulus is maintained throughout childhood but varies significantly throughout the cardiac cycle. The major modes of variation in the pediatric mitral annulus are due to size, ratio of annular height to commissural width, and sphericity. The generation of age- and size-specific mitral annular shapes may inform the development of appropriately scaled absorbable or expandable mitral annuloplasty rings for children.

Temporomandibular joint condylar changes following maxillomandibular advancement and articular disc repositioning.

PURPOSE: To evaluate condylar changes 1 year after bimaxillary surgical advancement with or without articular disc repositioning using longitudinal quantitative measurements in 3-dimensional (3D) temporomandibular joint (TMJ) models. METHODS: Twenty-seven patients treated with maxillomandibular advancement (MMA) underwent cone-beam computed tomography before surgery, immediately after surgery, and at 1-year follow-up. All patients underwent magnetic resonance imaging before surgery to assess disc displacements. Ten patients without disc displacement received MMA only. Seventeen patients with articular disc displacement received MMA with simultaneous TMJ disc repositioning (MMA-Drep). Pre- and postsurgical 3D models were superimposed using a voxel-based registration on the cranial base. RESULTS: The location, direction, and magnitude of condylar changes were displayed and quantified by graphic semitransparent overlays and 3D color-coded surface distance maps. Rotational condylar displacements were similar in the 2 groups. Immediately after surgery, condylar translational displacements of at least 1.5 mm occurred in a posterior, superior, or mediolateral direction in patients treated with MMA, whereas patients treated with MMA-Drep presented more marked anterior, inferior, and mediolateral condylar displacements. One year after surgery, more than half the patients in the 2 groups presented condylar resorptive changes of at least 1.5 mm. Patients treated with MMA-Drep presented condylar bone apposition of at least 1.5 mm at the superior surface in 26.4%, the anterior surface in 23.4%, the posterior surface in 29.4%, the medial surface in 5.9%, or the lateral surface in 38.2%, whereas bone apposition was not observed in patients treated with MMA. CONCLUSIONS: One year after surgery, condylar resorptive changes greater than 1.5 mm were observed in the 2 groups. Articular disc repositioning facilitated bone apposition in localized condylar regions in patients treated with MMA-Drep.

SKELETAL POINT REPRESENTATIONS WITH GEOMETRIC DEEP LEARNING.

Skeletonization has been a popular shape analysis technique that models both the interior and exterior of an object. Existing template-based calculations of skeletal models from anatomical structures are a time-consuming manual process. Recently, learning-based methods have been used to extract skeletons from 3D shapes. In this work, we propose novel additional geometric terms for calculating skeletal structures of objects. The results are similar to traditional fitted s-reps but but are produced much more quickly. Evaluation on real clinical data shows that the learned model predicts accurate skeletal representations and shows the impact of proposed geometric losses along with using s-reps as weak supervision.

Modeling Longitudinal Optical Coherence Tomography Images for Monitoring and Analysis of Glaucoma Progression.

Glaucoma causes progressive visual field deterioration and is the leading cause of blindness worldwide. Glaucomatous damage is irreversible and greatly impacts quality of life. Therefore, it is critically important to detect glaucoma early and closely monitor progression to preserve functional vision. Glaucoma is routinely monitored in the clinical setting using optical coherence tomography (OCT) for derived measures such as the thickness of important visual structures. There is not a consensus of what measures represent the most relevant biomarkers of glaucoma progression. Further, despite the increasing availability of longitudinal OCT data, a quantitative model of 3D structural change over time associated with glaucoma does not exist. In this paper we present an algorithm that will perform hierarchical geodesic modeling at the imaging level, considering 3D OCT images as observations of structural change over time. Hierarchical modeling includes subject-wise trajectories as geodesics in the space of diffeomorphisms and population level (glaucoma vs control) trajectories are also geodesics which explain subject-wise trajectories as deviations from the mean. Our preliminary experiments demonstrate a greater magnitude of structural change associated with glaucoma compared to normal aging. Our algorithm has the potential application in patient-specific monitoring and analysis of glaucoma progression as well as a statistical model of population trends and population variability.

Hierarchical Geodesic Polynomial Model for Multilevel Analysis of Longitudinal Shape.

Longitudinal analysis is a core aspect of many medical applications for understanding the relationship between an anatomical subject's function and its trajectory of shape change over time. Whereas mixed-effects (or hierarchical) modeling is the statistical method of choice for analysis of longitudinal data, we here propose its extension as hierarchical geodesic polynomial model (HGPM) for multilevel analyses of longitudinal shape data. 3D shapes are transformed to a non-Euclidean shape space for regression analysis using geodesics on a high dimensional Riemannian manifold. At the subject-wise level, each individual trajectory of shape change is represented by a univariate geodesic polynomial model on timestamps. At the population level, multivariate polynomial expansion is applied to uni/multivariate geodesic polynomial models for both anchor points and tangent vectors. As such, the trajectory of an individual subject's shape changes over time can be modeled accurately with a reduced number of parameters, and population-level effects from multiple covariates on trajectories can be well captured. The implemented HGPM is validated on synthetic examples of points on a unit 3D sphere. Further tests on clinical 4D right ventricular data show that HGPM is capable of capturing observable effects on shapes attributed to changes in covariates, which are consistent with qualitative clinical evaluations. HGPM demonstrates its effectiveness in modeling shape changes at both subject-wise and population levels, which is promising for future studies of the relationship between shape changes over time and the level of dysfunction severity on anatomical objects associated with disease.

Geodesic Logistic Analysis of Lumbar Spine Intervertebral Disc Shapes in Supine and Standing Positions.

Non-specific lower back pain (LBP) is a world-wide public health problem that affects people of all ages. Despite the high prevalence of non-specific LBP and the associated economic burdens, the pathoanatomical mechanisms for the development and course of the condition remain unclear. While intervertebral disc degeneration (IDD) is associated with LBP, there is overlapping occurrence of IDD in symptomatic and asymptomatic individuals, suggesting that degeneration alone cannot identify LBP populations. Previous work has been done trying to relate linear measurements of compression obtained from Magnetic Resonance Imaging (MRI) to pain unsuccessfully. To bridge this gap, we propose to use advanced non-Euclidean statistical shape analysis methods to develop biomarkers that can help identify symptomatic and asymptomatic adults who might be susceptible to standing-induced LBP. We scanned 4 male and 7 female participants who exhibited lower back pain after prolonged standing using an Open Upright MRI. Supine and standing MRIs were obtained for each participant. Patients reported their pain intensity every fifteen minutes within a period of 2 h. Using our proposed geodesic logistic regression, we related the structure of their lower spine to pain and computed a regression model that can delineate lower spine structures using reported pain intensities. These results indicate the feasibility of identifying individuals who may suffer from lower back pain solely based on their spinal anatomy. Our proposed spinal shape analysis methodology have the potential to provide powerful information to the clinicians so they can make better treatment decisions.

DENTALMODELSEG: FULLY AUTOMATED SEGMENTATION OF UPPER AND LOWER 3D INTRA-ORAL SURFACES.

In this paper, we present a deep learning-based method for surface segmentation. This technique consists of acquiring 2D views and extracting features from the surface such as the normal vectors. The rendered images are analyzed with a 2D convolutional neural network, such as a UNET. We test our method in a dental application for the segmentation of dental crowns. The neural network is trained for multi-class segmentation, using image labels as ground truth. A 5-fold cross-validation was performed, and the segmentation task achieved an average Dice of 0.97, sensitivity of 0.98 and precision of 0.98. Our method and algorithms are available as a 3DSlicer extension.

SlicerSALT: From Medical Images to Quantitative Insights of Anatomy.

Three-dimensional (3D) shape lies at the core of understanding the physical objects that surround us. In the biomedical field, shape analysis has been shown to be powerful in quantifying how anatomy changes with time and disease. The Shape AnaLysis Toolbox (SALT) was created as a vehicle for disseminating advanced shape methodology as an open source, free, and comprehensive software tool. We present new developments in our shape analysis software package, including easy-to-interpret statistical methods to better leverage the quantitative information contained in SALT's shape representations. We also show SlicerPipelines, a module to improve the usability of SALT by facilitating the analysis of large-scale data sets, automating workflows for non-expert users, and allowing the distribution of reproducible workflows.