ACRIN 6684: Assessment of Tumor Hypoxia in Newly Diagnosed Glioblastoma Using 18F-FMISO PET and MRI.

PurposeStructural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma.Experimental designPrior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival.ResultsFifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59-0.91], nRCBV (AUC = 0.72; 95% CI, 0.56-0.89), and nCBF (AUC = 0.72; 95% CI, 0.56-0.89) were predictive of survival at 1 year.ConclusionsIncreased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079-86. ©2016 AACR

Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma

<div><p>Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma.</p></div

Distribution of study population demographics and imaging parameters by imaging biomarkers in Cohort 1.

<p>¹ 96.7% (No. = 59) of this study population were ever smokers and 96.7% (No. = 59) were White race</p><p>² Other includes B30s, B41s, B70s, CHST, FC01, FC13, LUNG, and STANDARD</p><p>³ Distribution based on the tertile values</p><p>Distribution of study population demographics and imaging parameters by imaging biomarkers in Cohort 1.</p

Entropy ratio between the core and border regions of the tumor is predictive of patient survival.

<p>The tumors in the two prognostic groups (a) did not appear significantly different in the CT scans (b).</p

Cox Proportional Hazards Models for Overall Survival.

<p>Abbreviations: Hazard Ratio, HR; Confidence Intervals, CI.</p><p>Statistically significant hazard ratios (p < 0.05) are shown in bold.</p><p>¹ The imaging features are dichotomized at their respective median values and age is dichotomized at 65 years</p><p>² Each imaging biomarker is analyzed independently in separate univariate models. The unadjusted HRs represent the main effects of each covariate.</p><p>³ Based on forward selection, only two imaging biomarkers are included in the model but excluded age, gender, and stage.</p><p>⁴ Only two imaging biomarkers are included in the model in addition to age, gender, and stage</p><p>Cox Proportional Hazards Models for Overall Survival.</p