Hypoxia results from an imbalance between oxygen supply and consumption. It is a common phenomenon in solid malignant tumors such as head and neck cancer. As hypoxic cells are more resistant to therapy, tumor hypoxia is an indicator for poor prognosis. Several techniques have been developed to measure tissue oxygenation. These are the Eppendorf O2 polarographic needle electrode, immunohistochemical analysis of endogenous (e.g., hypoxia-inducible factor-1α (HIF-1a)) and exogenous markers (e.g., pimonidazole) as well as imaging methods such as functional magnetic resonance imaging (e.g., blood oxygen level dependent (BOLD) imaging, T1-weighted imaging) and hypoxia positron emission tomography (PET). Among the imaging modalities, only PET is sufficiently validated to detect hypoxia for clinical use. Hypoxia PET tracers include 18F-fluoromisonidazole (FMISO), the most commonly used hypoxic marker, 18F-flouroazomycin arabinoside (FAZA), 18Ffluoroerythronitroimidazole (FETNIM), 18F-2-nitroimidazolpentafluoropropylacetamide (EF5) and 18F-flortanidazole (HX4). As technical development provides the opportunity to increase the radiation dose to subregions of the tumor, such as hypoxic areas, it has to be ensured that these regions are stable not only from imaging to treatment but also through the course of radiotherapy. The aim of this review is therefore to characterize the behavior of tumor hypoxia during radiotherapy for the whole tumor and for subregions by using hypoxia PET tracers, with focus on head and neck cancer patients.
This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.
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