Radiomics-based tumor phenotype determination based on medical imaging and tumor microenvironment in a preclinical setting.
Radiother Oncol
; 169: 96-104, 2022 04.
Article
em En
| MEDLINE
| ID: mdl-35192909
ABSTRACT
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 (AUCValid) and F1-score. Furthermore, we analyzed correlations between TME- and MRI features using the Spearman correlation coefficient ρ.RESULTS:
TME and MRI-derived features showed good performance (AUCValid,TME = 0.72, AUCValid,MRI = 0.85, AUCValid,Combined=0.85) individual tumor phenotype prediction. We found correlation coefficients of ρ=-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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Microambiente Tumoral
/
Neoplasias de Cabeça e Pescoço
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Radiother Oncol
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Alemanha