Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
563-03-003 ISMRM Abstract

Microstructure characterisation of brain tumours by VERDICT MRI: a benchmark of deep learning methods

Primary: Analysis Methods - Classification and Prediction
Secondary: Diffusion - Microstructure
563-03-003 · Image Classification for Brain Cancer · Wednesday, 13 May, 1:40 PM–2:35 PM · Digital Posters Row D
Keywords: Diffusion Modeling Microstructure Deep learning Brain tumor Model fitting
Accepted
Matteo Figini 1, Zheng Yu2, Marco Palombo3,4,5, Michele Bailo6,7, Antonella Castellano6,8, Daniel C Alexander1, Eleftheria Panagiotaki1
1Hawkes Institute, Department of Computer Science, University College London, London, United Kingdom
2Department of Computer Science, University College London, London, United Kingdom
3CUBRIC, Cardiff University, Cardiff, United Kingdom
4School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
5Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
6Vita-Salute San Raffaele University, Milan, Italy
7Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
8Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy
Presenting Author: Matteo Figini

Synopsis

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References

1. 1. O’Connor, J.P.B.; Rose, C.J; Waterton, J.C.; Carano, R.A.D. ; Parker, G. J. M.; Jackson, A. Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome. Clinical Cancer Research 2015, 212:249–257.
2. 2. Messina, C; Bignone, E.; Bruno, E.; Bruno, F.; Nazarian, E.; Reginelli, A.; Calandri, S.; Tagliafico, A.; Ulivieri, A.; Guglielmi, G., Sconfienza, L. DiffusionWeighted Imaging in Oncology: An Update. Eur Radiol Exp 2020, 4(1):55.
3. 3. Drake-Perez, M.; Boto, J.; Fitsiori, F.; Lovblad, R.; Vargas, R. T. Clinical applications of diffusion weighted imaging in neuroradiology. Insights Imaging 2018, 9(4):535–547.
4. 4. Panagiotaki, E.; Walker-Samuel, S.; Siow, B.; Johnson, S.P.; Rajkumar, V.; Pedley, R.B.; Lythgoe, M.F.; Alexander, D.C. Noninvasive quantification of solid tumor microstructure using VERDICT MRI. Cancer Res 2014, 74:1902-1912, doi:10.1158/0008-5472.Can-13-2511. [doi]
5. 5. Figini M, Castellano A, Bailo M, Callea M, Cadioli M, Bouyagoub S, Palombo M, Pieri V, Mortini P, Falini A, Alexander DC, Cercignani M, Panagiotaki E. Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology. Cancers (Basel) 2023 Apr 27;15(9):2490
6. 6. Grussu, F.; Battiston, M.; Palombo, M.; Schneider, T.; Gandini Wheeler-Kingshott, C.A.M.; Alexander, D.C. Deep learning model fitting for diffusion-relaxometry: a comparative study. bioRxiv 2020, 10.1101/2020.10.20.347625, 2020.2010.2020.347625 [doi]
7. 7. Tian, Q.; Bilgic, B.; Fan, Q.; Liao, C.; Ngamsombat, C.; Hu, Y.; Witzel, T.; Setsompop, K.; Polimeni, J.R.; Huang, S.Y. DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning. NeuroImage 2020, 219:117017, doi:https://doi.org/10.1016/j.neuroimage.2020.117017. [doi]
8. 8. Barbieri, S.; Gurney-Champion, O.J.; Klaassen, R.; Thoeny, H.C. Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI. Magnetic Resonance in Medicine 2020, 83:312-321.
9. 9. de Almeida Martins, J.P.; Nilsson, M.; Lampinen, B.; Palombo, M.; While, P.T.; Westin, C.-F.; Szczepankiewicz, F. Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter. NeuroImage 2021, 244:118601
10. 10. Figini, M.; Palombo, M.; Bailo, M.; Callea, M.; Mortini, P.; Falini, A.; Alexander, D.C.; Cercignani, M.; Castellano, A.; Panagiotaki, E.; Accelerated Glioma characterization with VERDICT MRI: a comparison between deep learning and non-linear least squares fitting. Proc. Intl. Soc. Mag. Reson. Med. 2024, 32:
11. 11. Sen, S.; Singh, S.; Pye, H.; Moore, C. M.; Whitaker, H. C.; Punwani, S.; Atkinson, D. ; Panagiotaki, E.; Slator, P. J.P. ssVERDICT: Self-supervised verdict-mri for enhanced prostate tumor characterization. Mag. Reson. Med. 2024, 92:2181–2192.

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http://echo.ismrm.org/p/ISMRM2026/563-03-003