431-01-014 / 431-01-014 ISMRM Abstract

Edema Geometry as a Quantitative Diagnostic and Prognostic Radiosignature Distinguishing Brain Metastases from Gliomas

Primary: Neuro - Tumors

Secondary: Analysis Methods - Classification and Prediction

431-01-014 · From Microstructure to Metabolism: Next-Generation MRI for Brain Tumors · Tuesday, 12 May, 8:20 AM–9:56 AM · Roof Terrace

Keywords: Glioma MRI Brain Tumor Segmentation Brain Metastasis Edema

Accepted

Neha Yadav¹, Vivek Tiwari ²

¹Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Berhampur, Odisha, India

²Indian Institute of Science Education and Research (IISER) Berhampur, Odisha, India

Presenting Author: Vivek Tiwari

Synopsis

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References

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2. Ramakrishnan, D., Jekel, L., Chadha, S., Janas, A., Moy, H., Maleki, N., Sala, M., Kaur, M., Petersen, G.C., Merkaj, S., et al. (2024). A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Sci Data 11, 254. https://doi.org/10.1038/s41597-024-03021-9 [doi]

3. Rudie, J.D., Saluja, R., Weiss, D.A., Nedelec, P., Calabrese, E., Colby, J.B., Laguna, B., 1005 Mongan, J., Braunstein, S., Hess, C.P., et al. (2024). The University of California San 1006 Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset. 1007 Radiol Artif Intell 6. https://doi.org/10.1148/ryai.230126. [doi]

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5. Bakas S, Akbari H, Sotiras A, Bilello M, Rozycki M, Kirby J, Freymann J, Farahani K, and Davatzikos C. (2017). Data from: Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection [Data Set]. Preprint https://doi.org/doi:10.7937/K9/TCIA.2017.GJQ7R0EF [doi]

6. Bakas, S., Sako, C., Akbari, H., Bilello, M., Sotiras, A., Shukla, G., Rudie, J.D., Flores Santamaria N., Fathi Kazerooni, A., Pati, S., et al. (2021). Multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients from the University of Pennsylvania Health System (UPENN-GBM) (Version 2) [Data] set]. Preprint, https://doi.org/10.7937/TCIA.709X-DN49 [doi]

7. Adewole, M., Rudie, J.D., Gbadamosi, A., Zhang, D., Raymond, C., Ajigbotoshso, J., Toyobo, O., Aguh, K., Omidiji, O., Akinola R., et al. (2024). Expanding the Brain Tumor Segmentation (BraTS) data to include African Populations (BraTS-Africa) (version 1) [Dataset]. The Cancer Imaging Archive. https://doi.org/https://doi.org/10.7937/v8h6-8×67 [doi]

8. Calabrese, E., Villanueva-Meyer, J., Rudie, J., Rauschecker, A., Baid, U., Bakas, S., 990 Cha, S., Mongan, J., and Hess, C. (2022). The University of California San Francisco 991 Preoperative Diffuse Glioma MRI (UCSF-PDGM) (Version 4) [Dataset]. Preprint, 992 https://doi.org/10.7937/tcia.bdgf-8v37 https://doi.org/10.7937/tcia.bdgf-8v37 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/431-01-014