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Inter-observer delineation variability has a relevant influence on radiomics analysis and is strongly influenced by tumor type. This leads to a reduced number of suitable imaging features.

This study provides proof of concept that molecular information can be derived from standard medical images and shows potential for radiomics as imaging biomarker of HPV status. Advances in knowledge: Radiomics has the potential to identify clinically relevant molecular phenotypes.

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Inhibitors of angiogenesis and radiation induce compensatory changes in the tumor vasculature both during and after treatment cessation. To assess the responses to irradiation and vascular endothelial growth factor-receptor tyrosine kinase inhibition (by the vascular endothelial growth factor tyrosine kinase inhibitor PTK787/ZK222854), mammary carcinoma allografts were investigated by vascular casting; electron, light, and confocal microscopy; and immunoblotting. Irradiation and anti-angiogenic therapy had similar effects on the tumor vasculature. Both treatments reduced tumor vascularization, particularly in the tumor medulla. After cessation of therapy, the tumor vasculature expanded predominantly by intussusception with a plexus composed of enlarged sinusoidal-like vessels containing multiple transluminal tissue pillars. Tumor revascularization originated from preserved ␣-smooth muscle actin-positive vessels in the tumor cortex. Quantification revealed that recovery was characterized by an angiogenic switch from sprouting to intussusception. Up-regulated ␣-smooth muscle actin-expression during recovery reflected the recruitment of ␣-smooth muscle actinpositive cells for intussusception as part of the angioadaptive mechanism. Tumor recovery was associated with a dramatic decrease (by 30% to 40%) in the intratumoral microvascular density, probably as a result of intussusceptive pruning and, surprisingly, with only a minimal reduction of the total microvascular (exchange) area. Therefore, the vascular supply to the tumor was not severely compromised, as demonstrated by hypoxia-inducible factor-1␣ expression. Both irradiation and anti-angiogenic therapy cause a switch from sprouting to intussusceptive angiogenesis, representing an escape mechanism and accounting for the development of resistance, as well as rapid recovery, after cessation of therapy. (Am J Pathol

(2017). Material and methodsData from HNSCC patients (n=121) treated with definitive radiochemotherapy were used for model training. In total, 569 radiomic features were extracted from both contrast enhanced CT and 18F-FDG PET images in the primary tumor region.CT, PET and combined PET/CT radiomic models to assess local tumor control were trained separately. Five feature selection and three classification methods were implemented. The performance of the models was quantified using concordance index (CI) in 5-fold cross-validation in the training cohort. The best models, per image modality, were compared and verified in the independent validation cohort (n=51). The difference in CI was investigated using bootstrapping. Additionally, the observed and radiomics-based estimated probabilities of local tumor control were compared between two risk groups. ResultsThe feature selection using principal component analysis and the classification based on the multivariabale Cox regression with backward selection of the variables resulted in the best models for all image modalities (CICT=0.72, CIPET=0.74, CIPET/CT=0.77). Tumors more homogenous in CT density (decreased GLSZMsize_zone_entropy) and with a focused region of high FDG uptake (higher GLSZMSZLGE) indicated better prognosis. No significant difference in the performance of the models in the validation cohort was observed (CICT=0.73, CIPET=0.71, CIPET/CT=0.73). However, the CT radiomics based model overestimated the probability of tumor control in the poor prognostic group (predicted=68%, observed=56%). ConclusionBoth CT and PET radiomics showed equally good discriminative power for local tumor control modeling in HNSCC. However, CT-based predictions overestimated the local control rate in the poor prognostic validation cohort and thus we recommend to base the local control modeling on the 18F-FDG PET.