Radiomics-based tumor phenotype determination based on medical imaging and tumor microenvironment in a preclinical setting

被引:19
|
作者
Mueller, Johannes [1 ,2 ,3 ]
Leger, Stefan [1 ,2 ,4 ,5 ,6 ,7 ,8 ]
Zwanenburg, Alex [1 ,2 ,4 ,5 ,6 ,7 ,8 ]
Suckert, Theresa [1 ,2 ,9 ,10 ]
Luehr, Armin [1 ,2 ,11 ]
Beyreuther, Elke [1 ,2 ,12 ]
von Neubeck, Claere [1 ,2 ,13 ]
Krause, Mechthild [1 ,2 ,3 ,4 ,5 ,6 ,7 ,8 ,14 ]
Loeck, Steffen [1 ,2 ,7 ,14 ]
Dietrich, Antje [1 ,2 ,9 ,10 ]
Buetof, Rebecca [1 ,2 ,4 ,5 ,6 ,7 ,8 ,14 ]
机构
[1] Tech Univ Dresden, Helmholtz Zentrum Dresden Rossendorf, OncoRay Natl Ctr Radiat Res Oncol, Fac Med, Dresden, Germany
[2] Tech Univ Dresden, Helmholtz Zentrum Dresden Rossendorf, Univ Hosp Carl Gustav Carus, Dresden, Germany
[3] Helmholtz Zentrum Dresden Rossendorf, Inst Radiooncol OncoRay, Dresden, Germany
[4] Natl Ctr Tumor Dis NCT, Partner Site Dresden, Dresden, Germany
[5] German Canc Res Ctr, Dresden, Germany
[6] Tech Univ Dresden, Fac Med, Fetscherstr 74, D-01307 Dresden, Germany
[7] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Dresden, Germany
[8] Helmholtz Assoc Helmholtz Zentrum Dresden Rossend, Dresden, Germany
[9] German Canc Consortium DKTK, Partner Site Dresden, Dresden, Germany
[10] German Canc Res Ctr, Heidelberg, Germany
[11] TU Dortmund Univ, Dept Phys, Med Phys & Radiotherapy, Dortmund, Germany
[12] Helmholtz Zentrum Dresden Rossendorf, Inst Radiat Phys, Dresden, Germany
[13] Univ Duisburg Essen, Dept Particle Therapy, Univ Hosp Essen, Duisburg, Germany
[14] Tech Univ Dresden, Fac Med, Dept Radiotherapy & Radiat Oncol, Dresden, Germany
关键词
Head and neck; Preclinical; Radiomics; Tumor microenvironment; Hypoxia; PRIMARY RADIOCHEMOTHERAPY; PROSPECTIVE TRIAL; FDG-PET; HYPOXIA; CANCER; PARAMETERS; HEAD; MRI; RADIOTHERAPY; EXPRESSION;
D O I
10.1016/j.radonc.2022.02.020
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background and purpose: Radiomics analyses have been shown to predict clinical outcomes of radiotherapy based on medical imaging-derived biomarkers. However, the biological meaning attached to such image features often remains unclear, thus hindering the clinical translation of radiomics analysis. In this manuscript, we describe a preclinical radiomics trial, which attempts to establish correlations between the expression of histological tumor microenvironment (TME)- and magnetic resonance imaging (MRI)-derived image features. Materials & Methods: A total of 114 mice were transplanted with the radioresistant and radiosensitive head and neck squamous cell carcinoma cell lines SAS and UT-SCC-14, respectively. The models were irradiated with five fractions of protons or photons using different doses. Post-treatment T1-weighted MRI and histopathological evaluation of the TME was conducted to extract quantitative features pertaining to tissue hypoxia and vascularization. We performed radiomics analysis with leave-one-out cross validation to identify the features most strongly associated with the tumor's phenotype. Performance was assessed using the area under the curve (AUC(Valid)) and F1-score. Furthermore, we analyzed correlations between TME- and MRI features using the Spearman correlation coefficient rho. Results: TME and MRI-derived features showed good performance (AUC(Valid, TME) = 0.72, AUC(Valid, MRI) = 0.85, AUC(Valid, Combined) = 0.85) individual tumor phenotype prediction. We found correlation coefficients of rho = -0.46 between hypoxia-related TME features and texture-related MRI features. Tumor volume was a strong confounder for MRI feature expression. Conclusion: We demonstrated a preclinical radiomics implementation and notable correlations between MRI- and TME hypoxia-related features. Developing additional TME features may help to further unravel the underlying biology. (c) 2022 The Authors. Published by Elsevier B.V.
引用
收藏
页码:96 / 104
页数:9
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