A5087117639- Radiomics and Machine Learning in Medical Imaging
- Glioma Diagnosis and Treatment
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Cancer Immunotherapy and Biomarkers
- Brain Tumor Detection and Classification
- Cancer Genomics and Diagnostics
- Advanced MRI Techniques and Applications
- RNA modifications and cancer
- Immunotherapy and Immune Responses
- Cancer-related molecular mechanisms research
- Medical Imaging and Analysis
- Sarcoma Diagnosis and Treatment
- Brain Metastases and Treatment
- Advanced Neuroimaging Techniques and Applications
- Meningioma and schwannoma management
- AI in cancer detection
- Lung Cancer Treatments and Mutations
- Lung Cancer Diagnosis and Treatment
- Esophageal Cancer Research and Treatment
- MicroRNA in disease regulation
- Ferroptosis and cancer prognosis
- Medical Image Segmentation Techniques
- Head and Neck Cancer Studies
- Extracellular vesicles in disease
The University of Texas MD Anderson Cancer Center
2015-2025
UPMC Hillman Cancer Center
2019-2025
University of Pittsburgh
2020-2025
University of Pittsburgh Medical Center
2019-2024
University Hospitals of Cleveland
2024
University Health System
2024
University School
2024
Case Western Reserve University
2024
University of Pennsylvania
2024
Intel (United States)
2024
Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II III) have highly variable clinical behavior that is not adequately predicted on basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty compounded by interobserver variability in diagnosis. Mutations IDH, TP53, ATRX codeletion chromosome arms 1p 19q (1p/19q codeletion) been implicated as clinically relevant...
Several studies underscore the potential of deep learning in identifying complex patterns, leading to diagnostic and prognostic biomarkers. Identifying sufficiently large diverse datasets, required for training, is a significant challenge medicine can rarely be found individual institutions. Multi-institutional collaborations based on centrally-shared patient data face privacy ownership challenges. Federated novel paradigm data-private multi-institutional collaborations, where model-learning...
Glioblastomas are highly infiltrated by diverse immune cells, including microglia, macrophages, and myeloid-derived suppressor cells (MDSCs). Understanding the mechanisms which glioblastoma-associated myeloid (GAMs) undergo metamorphosis into tumor-supportive characterizing heterogeneity of cell phenotypes within glioblastoma subtypes, discovering new targets can help design efficient immunotherapies. In this study, we performed a comprehensive battery phenotyping, whole-genome microarray...
Purpose To conduct a comprehensive analysis of radiologist-made assessments glioblastoma (GBM) tumor size and composition by using community-developed controlled terminology magnetic resonance (MR) imaging visual features as they relate to genetic alterations, gene expression class, patient survival. Materials Methods Because all study patients had been previously deidentified the Cancer Genome Atlas (TCGA), publicly available data set that contains no linkage identifiers is HIPAA compliant,...
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), American Neuroradiology (ASNR), Medical Image Computing Computer Assisted Interventions (MICCAI) society. Since inception, has been focusing on being a common benchmarking venue for brain glioma segmentation algorithms, with well-curated multi-institutional multi-parametric magnetic resonance imaging (mpMRI) data. Gliomas are most primary malignancies central...
Background Despite recent discoveries of new molecular targets and pathways, the search for an effective therapy Glioblastoma Multiforme (GBM) continues. A newly emerged field, radiogenomics, links gene expression profiles with MRI phenotypes. MRI-FLAIR is a noninvasive diagnostic modality was previously found to correlate cellular invasion in GBM. Thus, our radiogenomic screen has potential reveal novel determinants invasion. Here, we present first comprehensive analysis using quantitative...
To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along clinical genomic markers.
Purpose Interleukin-10 (IL-10) stimulates the expansion and cytotoxicity of tumor-infiltrating CD8+ T cells inhibits inflammatory CD4+ cells. Pegylation prolongs serum concentration IL-10 without changing immunologic profile. This phase I study sought to determine safety antitumor activity AM0010. Patients Methods with selected advanced solid tumors were treated AM0010 in a dose-escalation study, which was followed by renal cell cancer (RCC) dose-expansion cohort. self-administered...
Complete surgical resection is the ideal first-line treatment for most liver malignancies. This goal would be facilitated by an intraoperative imaging method that enables more precise visualization of tumor margins and detection otherwise invisible microscopic lesions. To this end, we synthesized silica-encapsulated surface-enhanced Raman scattering (SERS) nanoparticles (NPs) act as a molecular agent We hypothesized that, after intravenous administration, SERS NPs avidly home to healthy...
We sought to ascertain the immune effector function of pembrolizumab within glioblastoma (GBM) microenvironment during therapeutic window.In an open-label, single-center, single-arm phase II "window-of-opportunity" trial in 15 patients with recurrent (operable) GBM receiving up 2 doses before surgery and every 3 weeks afterward until disease progression or unacceptable toxicities occurred, responses were evaluated tumor.No treatment-related deaths occurred. Overall median follow-up time was...
To correlate tumor blood volume, measured by using dynamic susceptibility contrast material-enhanced T2*-weighted magnetic resonance (MR) perfusion studies, with patient survival and determine its association molecular subclasses of glioblastoma (GBM).
Abstract Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast contrast-enhanced perfusion MRI images build classifier radiomic features obtained from both Ktrans rCBV maps coupled with support vector machines. We achieve an accuracy of 90.82% (area under the curve (AUC) = 89.10%, sensitivity 91.36%, 67 specificity 88.24%, p 0.017) differentiating between...
Background Patients with advanced rare cancers have poor prognosis and few treatment options. As immunotherapy is effective across multiple cancer types, we aimed to assess pembrolizumab (programmed cell death 1 (PD-1) inhibitor) in patients cancers. Methods In this open-label, phase 2 trial, whose tumors had progressed on standard therapies, if available, within the previous 6 months were enrolled nine tumor-specific cohorts a 10th cohort for other histologies. Pembrolizumab 200 mg was...
Despite an aggressive therapeutic approach, the prognosis for most patients with glioblastoma (GBM) remains poor. The aim of this study was to determine significance preoperative MRI variables, both quantitative and qualitative, regard overall progression-free survival in GBM. We retrospectively identified 94 untreated GBM from Cancer Imaging Archive who had pretreatment corresponding patient outcomes clinical information Genome Atlas. Qualitative imaging assessments were based on Visually...
Abstract Purpose: Radiomics is the extraction of multidimensional imaging features, which when correlated with genomics, termed radiogenomics. However, radiogenomic biological validation not sufficiently described in literature. We seek to establish causality between differential gene expression status and MRI-extracted radiomic-features glioblastoma. Experimental Design: Radiogenomic predictions were done using Cancer Genome Atlas Repository Molecular Brain Neoplasia Data glioblastoma...
Abstract Background Immune-checkpoint inhibitors (ICIs) changed the therapeutic landscape of patients with lung cancer. However, only a subset them derived clinical benefit and evidenced need to identify reliable predictive biomarkers. Liquid biopsy is non-invasive repeatable analysis biological material in body fluids promising tool for cancer biomarkers discovery. In particular, there growing evidence that extracellular vesicles (EVs) play an important role tumor progression tumor-immune...
Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age Karnofsky Performance Status (KPS), while very few evaluated the significance of preoperative MR-imaging. However, to date, there is no simple GBM classification that also correlates with a highly genomic signature. Thus, we present for first time biologically relevant, clinically applicable tumor Volume, patient Age, KPS (VAK) can easily non-invasively be determined upon admission.We...