Radiomic signatures from T2W and DWI MRI are predictive of tumour hypoxia in colorectal liver metastases

Author:

Bodalal Zuhir,Bogveradze Nino,ter Beek Leon C.,van den Berg Jose G.,Sanders Joyce,Hofland Ingrid,Trebeschi Stefano,Groot Lipman Kevin B. W.,Storck Koen,Hong Eun Kyoung,Lebedyeva Natalya,Maas Monique,Beets-Tan Regina G. H.,Gomez Fernando M.ORCID,Kurilova Ieva

Abstract

Abstract Background Tumour hypoxia is a negative predictive and prognostic biomarker in colorectal cancer typically assessed by invasive sampling methods, which suffer from many shortcomings. This retrospective proof-of-principle study explores the potential of MRI-derived imaging markers in predicting tumour hypoxia non-invasively in patients with colorectal liver metastases (CLM). Methods A single-centre cohort of 146 CLMs from 112 patients were segmented on preoperative T2-weighted (T2W) images and diffusion-weighted imaging (DWI). HIF-1 alpha immunohistochemical staining index (high/low) was used as a reference standard. Radiomic features were extracted, and machine learning approaches were implemented to predict the degree of histopathological tumour hypoxia. Results Radiomic signatures from DWI b200 (AUC = 0.79, 95% CI 0.61–0.93, p = 0.002) and ADC (AUC = 0.72, 95% CI 0.50–0.90, p = 0.019) were significantly predictive of tumour hypoxia. Morphological T2W TE75 (AUC = 0.64, 95% CI 0.42–0.82, p = 0.092) and functional DWI b0 (AUC = 0.66, 95% CI 0.46–0.84, p = 0.069) and b800 (AUC = 0.64, 95% CI 0.44–0.82, p = 0.071) images also provided predictive information. T2W TE300 (AUC = 0.57, 95% CI 0.33–0.78, p = 0.312) and b = 10 (AUC = 0.53, 95% CI 0.33–0.74, p = 0.415) images were not predictive of tumour hypoxia. Conclusions T2W and DWI sequences encode information predictive of tumour hypoxia. Prospective multicentre studies could help develop and validate robust non-invasive hypoxia-detection algorithms. Critical relevance statement Hypoxia is a negative prognostic biomarker in colorectal cancer. Hypoxia is usually assessed by invasive sampling methods. This proof-of-principle retrospective study explores the role of AI-based MRI-derived imaging biomarkers in non-invasively predicting tumour hypoxia in patients with colorectal liver metastases (CLM). Graphical Abstract

Funder

Maurits en Anna de Kock Stichting

ESR Research Seed Grant

NVIDIA Academic GPU grant

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

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