Efficacy and safety of von Willebrand factor concentrate almost devoid of factor VIII (Wilfactin®) in paediatric patients under 6 years of age with severe von Willebrand disease.

BACKGROUND: Plasma-derived von Willebrand factor (VWF) (Wilfactin®, LFB, France) was developed for prophylaxis and treatment of haemorrhages in both adults and adolescents with von Willebrand disease (VWD). Replacement therapy in paediatric patients is a key element of the clinical trial programme. MATERIAL AND METHODS: Patients aged <6 years with severe VWD were enrolled in a multinational, open-label study to evaluate the in vivo recovery for Wilfactin®, and its efficacy in preventing and treating bleeding episodes and during surgery. Overall haemostatic efficacy based on a 4-point scale was assessed by investigators. The treatment period ≥18 months investigated the long-term safety. RESULTS: Nine patients, including 7 with type 3 VWD were exposed to treatment with Wilfactin® for up to 4.2 years. Recovery of VWF in 7 patients (n=5 type 3, n=1 type 2, n=1 type 1) was 1.8±0.4 IU/dL per IU/kg. Of the 62 bleeds, 89% were controlled with one (73%) or two (16%) infusions of Wilfactin®. The median dose per infusion was 54 IU/kg. A factor VIII dose was co-administered in 1.6% of bleeds. "Excellent"/"Good" haemostatic efficacy was achieved in 90.3% of episodes. Six patients underwent 11 minor surgical interventions. Treatment duration was 1 day (range: 1-6 days) with a dose administered 30-60 minutes before procedure of 56 IU/kg (range: 41-106 IU/kg). Haemostasis was rated as "Excellent" in all surgeries. During 4-year prophylactic treatment in one patient, breakthrough bleeds were reported in 2.2% of infusions. No VWF inhibitors, thromboembolic events or allergic/anaphylactic-type reactions were observed following a total exposure of 770 days. DISCUSSION: The results show that Wilfactin® provides a safe and effective treatment in patients <6 years of age with severe VWD.

Assessment timing and choice of outcome measure in determining treatment response in chronic inflammatory demyelinating polyneuropathy: A post hoc analysis of the PRISM trial.

INTRODUCTION/AIMS: Treatment response and its timing are variable in chronic inflammatory demyelinating polyneuropathy (CIDP). In this study we assessed the variability using multiple outcome measures. METHODS: We performed a post hoc analysis of the PRISM trial, a 24-week prospective, multicenter, single-arm, open-label, phase III study of a 10% intravenous immunoglobulin preparation for CIDP. We ascertained timing of response with primary/secondary outcome measures. RESULTS: At 6 weeks after treatment initiation, 13 of 40 subjects (32.5%) were defined as responders on the primary outcome measure, the adjusted Inflammatory Neuropathy Cause And Treatment (INCAT) scale. This increased to 20 of 41 (48.8%) at 12 weeks and to 32 of 42 (76.2%) at 24 weeks. Use of minimal important difference (MID)-determined amelioration of the inflammatory Rasch-built Overall Disability Scale (I-RODS), or of the Medical Research Council sum score (MRCSS), or of dominant hand-grip strength, in addition to the adjusted INCAT, indicated a sensitivity of 41.7% in identifying adjusted INCAT nonresponders at week 12 who subsequently responded at week 24. Specificity was 60% vs INCAT nonresponders at week 24. Consideration of amelioration of any amplitude on any secondary outcome measure indicated a 75% sensitivity, but only 30% specificity vs adjusted INCAT nonresponders at week 24. DISCUSSION: Immunoglobulin treatment continuation may be justified for up to 24 weeks in CIDP. Additional outcome measures may help in the early treatment stages to predict delayed response on the adjusted INCAT. However, their use is limited by high false-positive rates. More robust, reliable, and relevant outcome measures are needed to detect early improvement in immunoglobulin-treated CIDP.

Continuous Infusion of Factor VIII and von Willebrand Factor in Surgery: Trials with pdFVIII LFB or pdVWF LFB in Patients with Bleeding Disorders.

BACKGROUND: A plasma-derived factor VIII product (pdFVIII; Factane 100 or 200 IU/mL) and a plasma-derived von Willebrand factor product (pdVWF; Wilfactin 100 IU/mL) are approved for replacement therapy by intravenous bolus injections in hemophilia A (HA) and von Willebrand disease (VWD), respectively. However, in situations requiring intensive treatment, continuous infusion (CI) may be desirable to better control target plasma factor levels. AIM: To evaluate the perioperative hemostatic efficacy and safety of these concentrates administered by CI. METHODS: Three phase III trials were conducted. Adults with HA (FVIII:C < 1%) (studies 1 and 2) or VWD (VWF:RCo < 20%) (Study 3) received a preoperative bolus followed by CI of undiluted concentrate for at least 6 days. Bolus doses and CI rates were based on individual recovery and clearance, respectively. The initial infusion rate had to be higher for 48 hours for HA and 24 hours for VWD patients to anticipate potential fluctuations of factor concentrations during major surgery. Target levels of FVIII:C in HA and VWF:RCo in VWD were 80 and 70 IU/dL, respectively. Efficacy was assessed using a global hemostatic efficacy score. RESULTS: Studies 1, 2, and 3 included 12, 4, and 6 patients, respectively. Efficacy outcomes were excellent/good in all 22 major surgeries including 18 orthopedic procedures. Most daily measured FVIII and VWF levels (92%) were on target. No safety concerns, thrombotic events, or inhibitors were identified. CONCLUSION: pdFVIII and pdVWF administered by CI represent an effective and safe alternative to bolus injections in patients with severe HA or VWD undergoing surgery.

Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain.

Background: The subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients. Objective: This study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1). Methods: We used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles. Results: We successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta. Conclusion: Multi-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.

NousNav: A low-cost neuronavigation system for deployment in lower-resource settings.

PURPOSE: NousNav is a complete low-cost neuronavigation system that aims to democratize access to higher-quality healthcare in lower-resource settings. NousNav's goal is to provide a model for local actors to be able to reproduce, build and operate a fully functional neuronavigation system at an affordable cost. METHODS: NousNav is entirely open source and relies on low-cost off-the-shelf components, which makes it easy to reproduce and deploy in any region. NousNav's software is also specifically devised with the low-resource setting in mind. RESULTS: It offers means for intuitive intraoperative control. The designed interface is also clean and simple. This allows for easy intraoperative use by either the practicing clinician or a nurse. It thus alleviates the need for a dedicated technician for operation. CONCLUSION: A prototype implementation of the design was built. Hardware and algorithms were designed for robustness, ruggedness, modularity, to be standalone and data-agnostic. The built prototype demonstrates feasibility of the objectives.

An international multicenter efficacy and safety study of IqYmune in initial and maintenance treatment of patients with chronic inflammatory demyelinating polyradiculoneuropathy: PRISM study.

This prospective, multicenter, single-arm, open-label phase 3 study aimed to evaluate the efficacy and safety of IqYmune in patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). Patients received one induction dose of 2 g/kg and then seven maintenance doses of 1 g/kg at 3-week intervals. The primary endpoint was the responder rate at the end of study (EOS), defined as an improvement of ≥1 point on the adjusted inflammatory neuropathy cause and treatment (INCAT) disability scale. The responder rate was compared with the responder rate of a historical placebo group (33.3%). Secondary endpoints included changes from baseline to EOS of adjusted INCAT disability score, grip strength, Medical Research Council (MRC) sum score, Rasch-modified MRC sum score, Rasch-built overall disability scale score and the clinical global impression. Forty-two patients, including 23 Ig-naïve and 19 Ig-pre-treated, were included in the efficacy set. The overall response rate at EOS was 76.2% (95% confidence interval [60.5%-87.9%]). The superiority of IqYmune compared to the historical placebo control was demonstrated (P < .0001). The responder rate was numerically higher in Ig-pre-treated than in Ig-naïve patients but confidence intervals were overlapping (84.2% [60.4%-96.6%] vs 69.6% [47.1%-86.8%]). All secondary endpoints confirmed this conclusion. The median time to response was 15 weeks [8.9-19.1 weeks]. A total of 156 adverse events including five serious were considered related to IqYmune, 87.2% were mild. Neither hemolysis nor signs of renal or hepatic impairment were observed. These results demonstrate that IqYmune is an effective and well-tolerated treatment in patients with CIDP.

Pharmacology, Efficacy and Safety of a Triple-Secured Fibrinogen Concentrate in Children Less than or Equal to 12 Years with Afibrinogenaemia.

OBJECTIVE: To date, the use of a fibrinogen concentrate (FC) administered in children with inherited fibrinogen deficiency is poorly documented. Treatment modalities may differ from those of adults. The aim of this study was to investigate the pharmacokinetics (PK), efficacy (bleeding/surgery) and safety of a triple-secured FC (FibCLOT, LFB, France) in young patients aged of 12 years or less. METHODS: This was a prospective, non-comparative, multicentre, phase 2-3 study. Estimated PK parameters were based on population PK modelling. Target fibrinogen levels were 1.2 and 1.0 g/L for major and minor events, respectively. In vivo recovery (IVR) was calculated at study entry to tailor the dose. RESULTS: Sixteen afibrinogenaemia patients were treated with FC: 12 included in the PK study (6 aged ≤ 6 years and 6 aged 7-12 years). IVR at 1 hour post-infusion (geometric mean [coefficient of variation]) was 1.91 [20%] mg/dL per mg/kg and results were similar between the two age groups (1.87 [14%]) and (1.96 [27%]) with no statistical differences. Estimated half-life (t 1/2) was 49.0 hours [12%] with no observed differences between groups (46.6 hours [10%] and 51.6 hours [12%]). Overall efficacy was rated as excellent/good in 96.9% of 32 bleeds and in 100% of 11 surgeries. Most of the events (39/43, 90.7%) were managed with one infusion. There was no serious adverse drug reaction. CONCLUSION: Individually tailored dosing was efficacious in children who exhibited a lower IVR and shorter t 1/2 than those previously reported in adolescent and adult patients emphasising the importance of individualised dose optimisation.

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

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.

White matter tracing combined with electric field simulation - A patient-specific approach for deep brain stimulation.

OBJECTIVE: Deep brain stimulation (DBS) in zona incerta (Zi) is used for symptom alleviation in essential tremor (ET). Zi is positioned along the dentato-rubro-thalamic tract (DRT). Electric field simulations with the finite element method (FEM) can be used for estimation of a volume where the stimulation affects the tissue by applying a fixed isolevel (VDBS). This work aims to develop a workflow for combined patient-specific electric field simulation and white matter tracing of the DRT, and to investigate the influence on the VDBS from different brain tissue models, lead design and stimulation modes. The novelty of this work lies in the combination of all these components. METHOD: Patients with ET were implanted in Zi (lead 3389, n = 3, voltage mode; directional lead 6172, n = 1, current mode). Probabilistic reconstruction from diffusion MRI (dMRI) of the DRT (n = 8) was computed with FSL Toolbox. Brain tissue models were created for each patient (two homogenous, one heterogenous isotropic, one heterogenous anisotropic) and the respective VDBS (n = 48) calculated from the Comsol Multiphysics FEM simulations. The DRT and VDBS were visualized with 3DSlicer and superimposed on the preoperative T2 MRI, and the common volumes calculated. Dice Coefficient (DC) and level of anisotropy were used to evaluate and compare the brain models. RESULT: Combined patient-specific tractography and electric field simulation was designed and evaluated, and all patients showed benefit from DBS. All VDBS overlapped the reconstructed DRT. Current stimulation showed prominent difference between the tissue models, where the homogenous grey matter deviated most (67 < DC < 69). Result from heterogenous isotropic and anisotropic models were similar (DC > 0.95), however the anisotropic model consistently generated larger volumes related to a greater extension of the electric field along the DBS lead. Independent of tissue model, the steering effect of the directional lead was evident and consistent. CONCLUSION: A workflow for patient-specific electric field simulations in combination with reconstruction of DRT was successfully implemented. Accurate tissue classification is essential for electric field simulations, especially when using the current control stimulation. With an accurate targeting and tractography reconstruction, directional leads have the potential to tailor the electric field into the desired region.

SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research.

Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow. Core SlicerDMRI functionality includes diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMRI quantification. SlicerDMRI supports clinical DICOM and research file formats, is open-source and cross-platform, and can be installed as an extension to 3D Slicer (www.slicer.org). More information, videos, tutorials, and sample data are available at dmri.slicer.org Cancer Res; 77(21); e101-3. ©2017 AACR.

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

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.

Cross-View Neuroimage Pattern Analysis in Alzheimer's Disease Staging.

The research on staging of pre-symptomatic and prodromal phase of neurological disorders, e.g., Alzheimer's disease (AD), is essential for prevention of dementia. New strategies for AD staging with a focus on early detection, are demanded to optimize potential efficacy of disease-modifying therapies that can halt or slow the disease progression. Recently, neuroimaging are increasingly used as additional research-based markers to detect AD onset and predict conversion of MCI and normal control (NC) to AD. Researchers have proposed a variety of neuroimaging biomarkers to characterize the patterns of the pathology of AD and MCI, and suggested that multi-view neuroimaging biomarkers could lead to better performance than single-view biomarkers in AD staging. However, it is still unclear what leads to such synergy and how to preserve or maximize. In an attempt to answer these questions, we proposed a cross-view pattern analysis framework for investigating the synergy between different neuroimaging biomarkers. We quantitatively analyzed nine types of biomarkers derived from FDG-PET and T1-MRI, and evaluated their performance in a task of classifying AD, MCI, and NC subjects obtained from the ADNI baseline cohort. The experiment results showed that these biomarkers could depict the pathology of AD from different perspectives, and output distinct patterns that are significantly associated with the disease progression. Most importantly, we found that these features could be separated into clusters, each depicting a particular aspect; and the inter-cluster features could always achieve better performance than the intra-cluster features in AD staging.

Using 3D Modeling Techniques to Enhance Teaching of Difficult Anatomical Concepts.

RATIONALE AND OBJECTIVES: Anatomy is an essential component of medical education as it is critical for the accurate diagnosis in organs and human systems. The mental representation of the shape and organization of different anatomical structures is a crucial step in the learning process. The purpose of this pilot study is to demonstrate the feasibility and benefits of developing innovative teaching modules for anatomy education of first-year medical students based on three-dimensional (3D) reconstructions from actual patient data. MATERIALS AND METHODS: A total of 196 models of anatomical structures from 16 anonymized computed tomography datasets were generated using the 3D Slicer open-source software platform. The models focused on three anatomical areas: the mediastinum, the upper abdomen, and the pelvis. Online optional quizzes were offered to first-year medical students to assess their comprehension in the areas of interest. Specific tasks were designed for students to complete using the 3D models. RESULTS: Scores of the quizzes confirmed a lack of understanding of 3D spatial relationships of anatomical structures despite standard instruction including dissection. Written task material and qualitative review by students suggested that interaction with 3D models led to a better understanding of the shape and spatial relationships among structures, and helped illustrate anatomical variations from one body to another. CONCLUSIONS: The study demonstrates the feasibility of one possible approach to the generation of 3D models of the anatomy from actual patient data. The educational materials developed have the potential to supplement the teaching of complex anatomical regions and help demonstrate the anatomical variation among patients.

In vivo Exploration of the Connectivity between the Subthalamic Nucleus and the Globus Pallidus in the Human Brain Using Multi-Fiber Tractography.

The basal ganglia is part of a complex system of neuronal circuits that play a key role in the integration and execution of motor, cognitive and emotional function in the human brain. Parkinson's disease is a progressive neurological disorder of the motor circuit characterized by tremor, rigidity, and slowness of movement. Deep brain stimulation (DBS) of the subthalamic nucleus and the globus pallidus pars interna provides an efficient treatment to reduce symptoms and levodopa-induced side effects in Parkinson's disease patients. While the underlying mechanism of action of DBS is still unknown, the potential modulation of white matter tracts connecting the surgical targets has become an active area of research. With the introduction of advanced diffusion MRI acquisition sequences and sophisticated post-processing techniques, the architecture of the human brain white matter can be explored in vivo. The goal of this study is to investigate the white matter connectivity between the subthalamic nucleus and the globus pallidus. Two multi-fiber tractography methods were used to reconstruct pallido-subthalamic, subthalamo-pallidal and pyramidal fibers in five healthy subjects datasets of the Human Connectome Project. The anatomical accuracy of the tracts was assessed by four judges with expertise in neuroanatomy, functional neurosurgery, and diffusion MRI. The variability among subjects was evaluated based on the fractional anisotropy and mean diffusivity of the tracts. Both multi-fiber approaches enabled the detection of complex fiber architecture in the basal ganglia. The qualitative evaluation by experts showed that the identified tracts were in agreement with the expected anatomy. Tract-derived measurements demonstrated relatively low variability among subjects. False-negative tracts demonstrated the current limitations of both methods for clinical decision-making. Multi-fiber tractography methods combined with state-of-the-art diffusion MRI data have the potential to help identify white matter tracts connecting DBS targets in functional neurosurgery intervention.

Pairwise Latent Semantic Association for Similarity Computation in Medical Imaging.

Retrieving medical images that present similar diseases is an active research area for diagnostics and therapy. However, it can be problematic given the visual variations between anatomical structures. In this paper, we propose a new feature extraction method for similarity computation in medical imaging. Instead of the low-level visual appearance, we design a CCA-PairLDA feature representation method to capture the similarity between images with high-level semantics. First, we extract the PairLDA topics to represent an image as a mixture of latent semantic topics in an image pair context. Second, we generate a CCA-correlation model to represent the semantic association between an image pair for similarity computation. While PairLDA adjusts the latent topics for all image pairs, CCA-correlation helps to associate an individual image pair. In this way, the semantic descriptions of an image pair are closely correlated, and naturally correspond to similarity computation between images. We evaluated our method on two public medical imaging datasets for image retrieval and showed improved performance.

The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery.

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) tractography reconstruction of white matter pathways can help guide brain tumor resection. However, DTI tracts are complex mathematical objects and the validity of tractography-derived information in clinical settings has yet to be fully established. To address this issue, we initiated the DTI Challenge, an international working group of clinicians and scientists whose goal was to provide standardized evaluation of tractography methods for neurosurgery. The purpose of this empirical study was to evaluate different tractography techniques in the first DTI Challenge workshop. METHODS: Eight international teams from leading institutions reconstructed the pyramidal tract in four neurosurgical cases presenting with a glioma near the motor cortex. Tractography methods included deterministic, probabilistic, filtered, and global approaches. Standardized evaluation of the tracts consisted in the qualitative review of the pyramidal pathways by a panel of neurosurgeons and DTI experts and the quantitative evaluation of the degree of agreement among methods. RESULTS: The evaluation of tractography reconstructions showed a great interalgorithm variability. Although most methods found projections of the pyramidal tract from the medial portion of the motor strip, only a few algorithms could trace the lateral projections from the hand, face, and tongue area. In addition, the structure of disagreement among methods was similar across hemispheres despite the anatomical distortions caused by pathological tissues. CONCLUSIONS: The DTI Challenge provides a benchmark for the standardized evaluation of tractography methods on neurosurgical data. This study suggests that there are still limitations to the clinical use of tractography for neurosurgical decision making.

Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders.

Multimodal neuroimaging is increasingly used in neuroscience research, as it overcomes the limitations of individual modalities. One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders. Multimodal neuroimaging computing enables the visualization and quantitative analysis of the alterations in brain structure and function, and has reshaped how neuroscience research is carried out. Research in this area is growing exponentially, and so it is an appropriate time to review the current and future development of this emerging area. Hence, in this paper, we review the recent advances in multimodal neuroimaging (MRI, PET) and electrophysiological (EEG, MEG) technologies, and their applications to the neuropsychiatric disorders. We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.

Multimodal neuroimaging computing: the workflows, methods, and platforms.

The last two decades have witnessed the explosive growth in the development and use of noninvasive neuroimaging technologies that advance the research on human brain under normal and pathological conditions. Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices. Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information. We review the current workflows and methods for multimodal neuroimaging computing, and also demonstrate how to conduct research using the established neuroimaging computing packages and platforms.

Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer's disease.

The accurate diagnosis of Alzheimer's disease (AD) is essential for patient care and will be increasingly important as disease modifying agents become available, early in the course of the disease. Although studies have applied machine learning methods for the computer-aided diagnosis of AD, a bottleneck in the diagnostic performance was shown in previous methods, due to the lacking of efficient strategies for representing neuroimaging biomarkers. In this study, we designed a novel diagnostic framework with deep learning architecture to aid the diagnosis of AD. This framework uses a zero-masking strategy for data fusion to extract complementary information from multiple data modalities. Compared to the previous state-of-the-art workflows, our method is capable of fusing multimodal neuroimaging features in one setting and has the potential to require less labeled data. A performance gain was achieved in both binary classification and multiclass classification of AD. The advantages and limitations of the proposed framework are discussed.