Abstract #0649

Histology-informed biophysical diffusion MRI model selection for enhanced liver cancer immunotherapy assessment

Francesco Grussu¹, Kinga Bernatowicz¹, Marco Palombo^2,3, Caterina Tozzi¹, Sara Simonetti^4,5, Garazi Serna⁴, Athanasios Grigoriou^1,6, Anna Voronova^1,6, Valezka Garay⁷, Juan Francisco Corral^8,9, Marta Vidorreta¹⁰, Pablo García-Polo García¹¹, Xavier Merino^8,9, Richard Mast^8,9, Núria Roson^8,9, Manuel Escobar^8,9, Maria Vieito^12,13, Rodrigo Toledo¹⁴, Paolo Nuciforo⁴, Elena Garralda¹⁵, and Raquel Perez-Lopez¹

¹Radiomics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ²Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, ³School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom, ⁴Molecular Oncology Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ⁵Prostate Cancer Translational Research Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ⁶Department of Biomedicine, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain, ⁷PET/MR Unit, CETIR-Ascires, Barcelona, Spain, ⁸Department of Radiology, Hospital Universitari Vall d’Hebron, Barcelona, Spain, ⁹Institut de Diagnòstic per la Imatge (IDI), Barcelona, Spain, ¹⁰Siemens Healthineers, Madrid, Spain, ¹¹GE HealthCare, Madrid, Spain, ¹²GU, Sarcoma and Neuroncology Unit, Hospital Universitari Vall d’Hebron, Barcelona, Spain, ¹³Drug Development Unit, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ¹⁴Biomarkers and Clonal Dynamics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ¹⁵Early Clinical Drug Development Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain

Synopsis

Keywords: Microstructure, Modelling, Immunotherapy, Liver, Tumours, Histology

Motivation: Multi-compartment liver diffusion MRI (dMRI) provides innovative markers of intra-cellular fraction (F) and cell size (CS). However, practical implementations for histologically-meaningful F and CS computation in the clinic are still sought.

Goal(s): To deliver a compact approach for F and CS estimation, informing model design with histology.

Approach: We compared 5 implementations of a standard two-compartment model for their ability to provide F and CS estimates that agree with reference biopsies in liver tumours.

Results: The best approach consisted of fitting a single-compartment model of intra-cellular diffusion to high b-value images. This provides promising metrics that stratify the risk of progression in immunotherapy.

Impact: We deliver a clinically-feasible liver diffusion MRI approach for intra-cellular fraction, cell size and density estimation. It consists of fitting a single-compartment model of restricted diffusion to high b-value images, and provides metrics that may inform on cancer immunotherapy response.

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