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

Insights into Imaging

Original Article

Ingrid Hofland¹  Leon C. ter Beek²  Joyce Sanders³  Jose G. van den Berg³  Monique Maas⁴  Koen Storck⁴  Natalya Lebedyeva⁴  Ieva Kurilova⁴  Stefano Trebeschi⁵  Eun Kyoung Hong⁵  Kevin B. W. Groot Lipman⁵  Regina G. H. Beets-Tan⁵  Zuhir Bodalal⁵  Nino Bogveradze⁶  Fernando M. Gomez⁷ 

[1] Core Facility Molecular Pathology & Biobank, The Netherlands Cancer Institute, Amsterdam, The Netherlands;Department of Medical Physics, The Netherlands Cancer Institute, Amsterdam, The Netherlands;Department of Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands;Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands;Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands;GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands;Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands;GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands;Department of Radiology, American Hospital Tbilisi, Tbilisi, Georgia;Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands;Hospital Clinic-Hospital Sant Joan de Deu, Barcelona, Spain;

关键词: Colorectal cancer;    Colorectal liver metastasis;    Hypoxia;    MRI;    Radiomics;   

DOI  :  10.1186/s13244-023-01474-x

 received in 2023-02-25, accepted in 2023-06-27,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundTumour 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).MethodsA 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.ResultsRadiomic 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.ConclusionsT2W 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 statementHypoxia 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

【 授权许可】

CC BY   
© The Author(s) 2023

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