Publications by authors named "Michele R Aizenberg"

Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).

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Article Synopsis
  • - Designing implants for complex cranial defects is tough, with existing methods mainly relying on convolutional neural networks (CNN) that struggle in clinical settings for real-world issues.
  • - The paper introduces a statistical shape model (SSM) that leverages skull segmentation masks and performs better than CNNs when handling large and intricate cranial defects.
  • - Neurosurgeons find the SSM-generated implants clinically viable after some minor adjustments, and both the datasets and SSM model used in the study are publicly accessible online.
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Article Synopsis
  • Cranial implants are used to repair skull defects from surgeries and typically take a long time to produce, but the AutoImplant II challenge seeks to automate this process for faster availability during surgery.
  • The challenge builds on the first AutoImplant (2020) by including real clinical cases and more synthetic data across three tracks to evaluate different aspects of implant design.
  • Submitted designs were assessed based on their performance using metrics from imaging data and evaluations by a neurosurgeon, showing significant advancements in areas like efficiency and adaptability.
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Background: Growing evidence indicates fractal analysis (FA) has potential as a computational tool to assess tumor microvasculature in glioblastoma (GBM). As fractal parameters of microvasculature have shown to be reliable quantitative biomarkers in brain tumors, there has been similar success in measuring the architecture of tumor tissue using FA in other tumor types. However, evaluating fractal parameters of tissue structure in relation to the microvasculature has not yet been implemented in GBM.

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Purpose: Glioblastoma (GBM) is the most lethal primary brain tumor in adult patients. The disease progression, response to chemotherapy and radiotherapy at initial diagnosis, and prognosis are profoundly associated with the tumor microenvironment, especially the features of tumor-infiltrating immune cells (TII). Recurrent GBM is even more challenging to manage.

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While magnetoencephalography (MEG) has proven to be a valuable and reliable tool for presurgical functional mapping of eloquent cortices for at least two decades, widespread use of this technique by clinicians has remained elusive. This modest application may be attributable, at least in part, to misunderstandings regarding the success rate of such mapping procedures, as well as the primary sources contributing to mapping failures. To address this, we conducted a retrospective comparison of sensorimotor functional mapping success rates in 141 patients with epilepsy and 75 tumor patients from the Center for MEG in Omaha, NE.

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Accurate individual functional mapping of task activations is a potential tool for biomarker discovery and is critically important for clinical care. While structural imaging does not directly map task activation, we hypothesized that structural imaging contains information that can accurately predict variations in task activation between individuals. To this end, we trained a convolutional neural network to use structural imaging (T1-weighted, T2-weighted, and diffusion tensor imaging) to predict 47 different functional MRI task activation volumes across seven task domains.

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The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design.

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Objective: By looking at how the accuracy of preoperative brain mapping methods vary according to differences in the distance from the activation clusters used for the analysis, the present study aimed to elucidate how preoperative functional neuroimaging may be used in such a way that maximizes the mapping accuracy.

Methods: The eloquent function of 19 patients with a brain tumor or cavernoma was mapped prior to resection with both functional MRI (fMRI) and magnetoencephalography (MEG). The mapping results were then validated using direct cortical stimulation mapping performed immediately after craniotomy and prior to resection.

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Purpose: Perfusion and diffusion magnetic resonance imaging (MRI) provide important biomarkers for brain tumor analysis. Our aim was to investigate if regions of increased perfusion or tumor with restricted diffusion on the immediate post-operative MRI examination would be predictive of time to tumor progression in patients with high-grade gliomas.

Materials And Methods: Twenty-three patients with high-grade gliomas were retrospectively analyzed.

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Introduction: Glioblastoma (GBM) is heterogeneous and underlying genomic profiles influence evolution, resistance, and therapeutic responses. While extensive knowledge regarding genomic profiling of primary GBM exists, there remains a lack of understanding of genomic differences in recurrent GBM.

Methods: We used the FoundationOne® comprehensive genomic profiling assay (CGP) to analyze ten matched primary and recurrent GBM.

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There is little data on why glioblastomas (GBM) hemorrhage and how it may affect patient outcomes. The aim of this study was to investigate the mechanisms of hemorrhage in glioblastoma by examining molecular and genetic features by immunohistochemistry (IHC) and mRNA expression profiles in association with imaging and clinical outcomes. An observational retrospective cohort analysis was performed on 43 FFPE GBM tissue samples.

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Epstein-Barr virus-associated smooth muscle tumors (EBV-SMTs) are rare lesions that occur in immunocompromised patients. Dural involvement appears to be less common in organ transplant recipients than in HIV patients. Due to the paucity of reported cases following organ transplantation, the natural history of these lesions is unclear.

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Objective: Primary central nervous system non-Hodgkin lymphoma (PCNSL) is a malignant lymphoma limited to the cranial-spinal axis in the absence of systemic lymphoma. Historically, PCNSL accounts for fewer than 5% of all cases of primary intracranial neoplasms. PCNSL is rare in immunocompetent young adults.

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Gliomas are the most common form of tumor in the CNS and are exceptionally heterogeneous. Accurately characterizing gliomas, in terms of grade and type, is essential for predicting the rate of tumor progression. Histopathological grading and analysis based on biopsied tissue remains the gold standard, but non- and semi-invasive neuroimaging also plays a key role.

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Object: Patients presenting with spinal metastases from unknown primary tumors (UPTs) are rare. The authors reviewed their surgical experience to evaluate outcomes and identify predictors of survival in these patients.

Methods: This study is a retrospective analysis of patients undergoing surgery for metastatic spine disease from UPTs between June 1993 and February 2007 at The University of Texas M.

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Systemic enzyme replacement for Gaucher's disease has not prevented premature death or severe morbidity in patients with a neuronopathic phenotype, because the enzyme does not cross the blood-brain barrier. We used convection-enhanced delivery for regional distribution of glucocerebrosidase in rat and primate brains and examined its safety and feasibility for neuronopathic Gaucher's disease. Rats underwent intrastriatal infusion and were observed and then sacrificed at 14 hours, 4 days, or 6 weeks.

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