Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
563-06-004 ISMRM Abstract

Automating BT-RADS Scoring and Structured MRI Reporting in Post-Treatment Glioma Using Large Language Models

Primary: Neuro - Tumors
Secondary: Analysis Methods - Multi-Modal Learning with LLMs/VLMs
563-06-004 · From Molecular Signatures to Surgical Guidance: Cutting-Edge MRI in Brain Tumor Care · Wednesday, 13 May, 4:55 PM–5:50 PM · Digital Posters Row D
Accepted
Zhi Liu 1
1Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Presenting Author: Zhi Liu

Synopsis

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References

1. Miller, K.D.; Ostrom, Q.T.; Kruchko, C.; Patil, N.; Tihan, T.; Cioffi, G.; Fuchs, H.E.; Waite, K.A.; Jemal, A.; Siegel, R.L.; et al. Brain and Other Central Nervous System Tumor Statistics, 2021. CA. Cancer J. Clin. 2021, 71, 381–406. doi:10.3322/caac.21693. [doi]
2. Weinberg, B.D.; Gore, A.; Shu, H.-K.G.; Olson, J.J.; Duszak, R.; Voloschin, A.D.; Hoch, M.J. Management-Based Structured Reporting of Post-treatment Glioma Response with the Brain Tumor Reporting and Data System. J. Am. Coll. Radiol. JACR 2018, 15, 767–771. doi:10.1016/j.jacr.2018.01.013. [doi]
3. Bhayana, R.; Biswas, S.; Cook, T.S.; et al. From Bench to Bedside With Large Language Models: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2024, 223(3):e2430928. doi:10.2214/AJR.24.30928. [doi]
4. Bhayana, R.; Nanda, B.; Dehkharghanian, T.; et al. Large Language Models for Automated Synoptic Reports and Resectability Categorization in Pancreatic Cancer. Radiology 2024, 311(3):e233117. doi:10.1148/radiol.233117. [doi]
5. Jabal, M.S.; Warman, P.; Zhang, J.; et al. Open-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters. Radiol Artif Intell. 2025;7(3):e240551. doi:10.1148/ryai.240551. [doi]
6. Ramos A, Hilario A. Standardized brain tumor reporting in the multidisciplinary spotlight: pros of the BT-RADS. Eur Radiol. 2024 Oct;34(10):6776-6778. doi: 10.1007/s00330-024-10716-5. Epub 2024 Apr 7. PMID: 38583126. [doi] [pmid]
7. Bhayana R, Jajodia A, Chawla T, et al. Accuracy of Large Language Model-based Automatic Calculation of Ovarian-Adnexal Reporting and Data System MRI Scores from Pelvic MRI Reports. Radiology. 2025;315(1):e241554.
8. Gore A, Hoch MJ, Shu HG, Olson JJ, Voloschin AD, Weinberg BD. Institutional Implementation of a Structured Reporting System: Our Experience with the Brain Tumor Reporting and Data System. Acad Radiol. 2019;26(7):974-980.
9. Pons E, Braun LMM, Hunink MGM, Kors JA. Natural Language Processing in Radiology: A Systematic Review. Radiology 2016;279(2):329–343.
10. Hu, W., Xu, Y., Li, Y., Li, W., Chen, Z., & Tu, Z. (2024, March). Bliva: A simple multimodal llm for better handling of text-rich visual questions. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 3, pp. 2256-2264).

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/563-06-004