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.

This study evaluated PET/CT in the initial work-up of patients with PN. PET/CT increased sensitivity (87%) for detection of metastatic disease when combined with standard CT. In invasive cancer, PET/CT changed the management in 11% of our patients. PET/CT should be considered in the initial work-up of patients with potentially resectable pancreatic lesions.

Purpose Structural 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 (GBM). Experimental Design Prior to start of chemoradiation, GBM patients 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. Results Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pre-treatment 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 pre-treatment 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%CI 0.59 to 0.91), nRCBV (AUC=0.72, 95% CI0.56–0.89) and nCBF (AUC = 0.72, 95%CI 0.56 to 0.89) were predictive of survival at 1 year. Conclusions Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed GBM patients and these important physiological markers can be measured safely and reliably using MRI and 18F-FMISO PET.

Purpose Measurement variance affects the clinical effectiveness of PET-based measurement as a semi-quantitative imaging biomarker for cancer response in individual patients and for planning clinical trials. In this study, we measured test-retest reproducibility of SUV measurements under clinical practice conditions, and recorded recognized deviations from protocol compliance. Methods Instrument performance calibration, display and analyses conformed to manufacture recommendations. Baseline clinical 2-deoxy-2-[F-18]fluoro-D-glucose (FDG)-PET/CT examinations were performed and then repeated at 1 – 7 days. Intended scan initiation uptake period was to repeat the examinations at the same time for each study after injection of 12 mCi FDG tracer. Avidity of uptake was measured in 62 tumors in 21 patients as standardized uptake value for maximum voxel (SUVmax) and for a mean of sampled tumor voxels (SUVmean). Results The range of SUVmax and SUVmean was 1.07–21.47 and 0.91–14.69, respectively. Intraclass correlation coefficient (ICC) between log of SUVmax and log of SUVmean was 0.93 (95% CI: 0.88–0.95) and 0.92 (95% CI: 0.87–0.95), respectively. Correlation analysis failed to show an effect on uptake period variation on SUV measurements between the two examinations, suggesting additional sources of noise. The threshold criteria for relative difference from baseline for the 95% confidence interval were ±49% or ±44% for SUVmax or SUVmean, respectively. Conclusion Variance of SUV for FDG-PET/CT in current clinical practice in a single institution was greater than expected when compared to benchmarks reported under stringent efficacy study settings. Under comparable clinical practice conditions, interpretation of changes in tumor avidity in individuals, and assumptions in planning clinical trials may be affected.

Quantitative imaging using CT, MRI, and PET modalities will play an increasingly important role in the design of oncology trials addressing molecularly targeted, personalized therapies. The advent of molecularly targeted therapies, exemplified by antiangiogenic drugs, creates new complexities in the assessment of response. The Quantitative Imaging Network (QIN) addresses the need for imaging modalities which can accurately and reproducibly measure not just change in tumor size, but changes in relevant metabolic parameters, modulation of relevant signaling pathways, drug delivery to tumor, and differentiation of apoptotic cell death from other changes in tumor volume. This article provides an overview of the applications of quantitative imaging to phase 0 through phase 3 oncology trials. We describe the use of a range of quantitative imaging modalities in specific tumor types including malignant gliomas, lung cancer, head and neck cancer, lymphoma, breast cancer, prostate cancer, and sarcoma. In the concluding section, we discuss potential constraints on clinical trials using quantitative imaging, including complexity of trial conduct, impact on subject recruitment, incremental costs, and institutional barriers. Strategies for overcoming these constraints are presented.