Glioma is the most common form of brain tumor with a high degree of heterogeneity in imaging characteristics, treatment-response, and survival rate. An important factor causing this heterogeneity is the mutation of isocitrate dehydrogenase (IDH) enzyme. The current clinical gold-standard for identifying IDH mutation status involves invasive procedures that involve risk, may fail to capture intra-tumoral spatial heterogeneity or can be inaccessible in low-resource settings. In this study, we propose a deep learning-based method to non-invasively and pre-operatively determine IDH status of high- and low-grade gliomas by leveraging their phenotypical characteristics from volumetric MRI scans. For this purpose, we propose a 3D Mask R-CNN-based approach to simultaneously detect and segment glioma as well as classify its IDH status - thus obviating the requirement of any separate tumor segmentation step. The network can operate on routinely acquired MRI sequences and is agnostic to glioma grade. It was trained on patient-cases from publicly available datasets ( = 223) and tested on two hold-out datasets acquired from The Cancer Genome Atlas (TCGA; = 62) and Washington University School of Medicine (WUSM; = 261). The model achieved areas under the receiver operating characteristic of 0.83 and 0.87, and areas under the precision-recall curves of 0.78 and 0.79, on the TCGA and WUSM sets, respectively. The model can be used to perform a pre-operative 'virtual biopsy' of gliomas, thus facilitating treatment planning, potentially leading to better overall survival.
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http://dx.doi.org/10.1117/12.2651391 | DOI Listing |
Neuropathology
January 2025
Department of Pathology, Kyorin University Faculty of Medicine, Tokyo, Japan.
The manifestation of glioblastoma, IDH-wildtype (GB) as intracranial hemorrhage (ICH) presents diagnostic and therapeutic challenges. Molecular characteristics, including TERT promoter mutation, EGFR amplification, and chromosome 7 gain/10 loss, were incorporated to diagnose GB in the fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System. When molecular analyses fail to detect low fractions of these genetic alterations, the integrated diagnosis of GB can be enigmatic.
View Article and Find Full Text PDFJ Neurooncol
January 2025
Department of Neurosurgery, NYU Langone Health and NYU Grossman School of Medicine, 530 1st Avenue, Skirball Suite 8R, New York, NY, 10016, USA.
Unlabelled: QUESTIONS AND RECOMMENDATIONS FROM THE PRIOR VERSION OF THESE GUIDELINES WITHOUT CHANGE: TARGET POPULATION: Adult patients (age ≥ 18 years) who have suspected low-grade diffuse glioma.
Question: What are the optimal neuropathological techniques to diagnose low-grade diffuse glioma in the adult?
Recommendation: Level I Histopathological analysis of a representative surgical sample of the lesion should be used to provide the diagnosis of low-grade diffuse glioma. Level III Both frozen section and cytopathologic/smear evaluation should be used to aid the intra-operative assessment of low-grade diffuse glioma diagnosis.
Theranostics
January 2025
Neurooncology Unit, Instituto de Investigación Biomédicas I+12, Hospital Universitario 12 de Octubre, Madrid 28041, Spain.
Glioblastoma IDH wild type (GBM IDH wt) has a poor prognosis and a strongly associated with inflammatory processes. Inflammatory molecules generate positive feedback with tumor cells fueling tumor growth as well as recruitment of immune cells that promote aggressiveness. Although the role of many inflammatory molecules is well known, there are many macromolecules, such as the S100A proteins, whose role is only now beginning to be established.
View Article and Find Full Text PDFMagn Reson Imaging
December 2024
Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland.
Background: Brain tumors exhibit diverse genetic landscapes and hemodynamic properties, influencing diagnosis and treatment outcomes.
Purpose: To explore the relationship between MRI perfusion metrics (rCBV, rCBF), genetic markers, and contrast enhancement patterns in gliomas, aiming to enhance diagnostic accuracy and inform personalized therapeutic strategies. Additionally, other radiological features, such as the T2/FLAIR mismatch sign, are evaluated for their predictive utility in IDH mutations.
World Neurosurg
December 2024
Department of Pathology, Huashan Hospital, Fudan University, Shanghai 200040, China.
Background: The presence of isocitrate dehydrogenase (IDH) mutations and 1p/19q codeletion significantly influences the diagnosis and prognosis of patients with lower-grade gliomas (LGGs). The ability to predict these molecular signatures preoperatively can inform surgical strategies. This study sought to establish an interpretable imaging feature set for predicting molecular signatures and overall survival in LGGs.
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