Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-10-154 ISMRM Abstract

Improving Glioblastoma Classification Using Quantitative Transport Mapping with a Synthetic Tumor Trained Deep Neural Network

Primary: Neuro - Tumors
Secondary: Contrast Mechanisms - Perfusion
470-10-154 · Integrated MRI-Based Approaches for Preoperative Diagnosis, Grading, and Prognostic Prediction of Brain Tumors · Tuesday, 12 May, 4:55 PM–5:50 PM · Traditional Posters | Exhibition Hall
Keywords: DSC & DCE Perfusion Quantitative Transport Mapping Brain Tumor classification Dynamic Contrast-Enhanced MRI Perfusion quantification
Accepted
Dominick Romano1, Alexandra G Roberts 2,3, Benjamin Weppner1,4, Qihao Zhang3, Maneesh John2,3, Renjiu Hu3,5, Gloria C Chiang3, Pascal Spincemaille 3, Yi Wang1,3
1Biomedical Engineering, Cornell University, Ithaca, United States of America
2Electrical & Computer Engineering, Cornell University, Ithaca, United States of America
3Radiology, Weill Cornell Medicine, New York, United States of America
4Department of Radiology, Weill Cornell Medicine, New York, United States of America
5Mechanical & Aerospace Engineering, Cornell University, Ithaca, United States of America
Presenting Author: Alexandra G Roberts

Synopsis

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References

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2. Arevalo-Perez J, Peck KK, Young RJ, Holodny AI, Karimi S, Lyo JK. Dynamic Contrast-Enhanced Perfusion MRI and Diffusion-Weighted Imaging in Grading of Gliomas. J Neuroimaging. Sep-Oct 2015;25(5):792-8. doi:10.1111/jon.12239 [doi]
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7. Romano D, Zhang Q, Roberts AG, et al. Validation of quantitative transport mapping (QTM) with an ex vivo perfused liver model. Magnetic Resonance in Medicine. 2025;94(4):1779-1792. doi:https://doi.org/10.1002/mrm.30581 [doi]
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9. Zhou L, Zhang Q, Spincemaille P, et al. Quantitative transport mapping (QTM) of the kidney with an approximate microvascular network. Magnetic Resonance in Medicine. 2021;85(4):2247-2262. doi:https://doi.org/10.1002/mrm.28584 [doi]
10. Zhang Q, Spincemaille P, Drotman M, et al. Quantitative transport mapping (QTM) for differentiating benign and malignant breast lesion: Comparison with traditional kinetics modeling and semi-quantitative enhancement curve characteristics. Magn Reson Imaging. Feb 2022;86:86-93. doi:10.1016/j.mri.2021.10.039 [doi]
11. Zhou L, Zhang Q, Spincemaille P, et al. Perfusion Quantification Validation on a Numerical Vascular Network of the Kidney: Traditional Kety’s Method vs Quantitative Transport Mapping. ISMRM; 2020:
12. Zhang Q, Chiang G, Nguyen T, Spincemaille P, Wang Y. Glioblastoma grading using perfusion parameters: comparing quantitative transport mapping method and kinetic modeling method. presented at: ISMRM Annual Meeting; https://cds.ismrm.org/protected/21MPresentations/abstracts/3910.html
13. Zhang Q. Estimating Perfusion and Vascular Properties from Medical Images: Quantitative Transport Mapping (QTM). Ph.D. Cornell University; 2023. https://www.proquest.com/dissertations-theses/estimating-perfusion-vascular-properties-medical/docview/2827576793/se-2?accountid=10267
14. D. Romano QZ, M. Sisman, A. Roberts, R. Hu, B. Weppner, T. Nguyen, P. Spincemaille, M. Prince, Y. Wang. Validating Quantitative Transport Mapping (QTM) on a Perfused MRI Liver Phantom. Magnetic Resonance in Medicine; 2024:
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http://echo.ismrm.org/p/ISMRM2026/470-10-154