Computational Biomedicine – 3D tumour mould

The technique is currently being developed in both Ovarian and Renal cancer.

Computational Biomedicine - 3D tumour mould as part of ICM

3D-printed moulds of renal tumours for image-guided tissue sampling in the clinical setting. Crispin-Ortuzar, M. et al, 2019.

Summary: To address intra-tumoural heterogeneity in renal clear cell carcinoma we have started to develop a novel method to link imaging (MRI) data to digital pathology data, by developing an image guided 3D-printed tumour mould. By tightly integrating our approach into the workflows of clinical trials, our methodology will enable the creation of large spatially-matched multiscale datasets including radiomics, genomics and histology data.

Radiogenomics Analysis of Intratumor Heterogeneity in a Patient With High-Grade Serous Ovarian Cancer. Weigelt, B, et al., JCO Precision Oncology, June 2019.

In this study we use lesion-specific three-dimensional (3D) molds for phenotypic image-guided tumor sampling to ensure spatial colocation of imaging, histology, and genomic data, critical for understanding tumor biology. Phenotypic imaging maps of heterogeneity (ie, imaging habitats) of two HGSOC sites were obtained by combining perfusion, diffusion, and metabolic maps derived from multiparametric imaging. We evaluated if this phenotypic imaging-based heterogeneity reflects the underlying histologic and/or genetic heterogeneity of the tumor.


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