Tumor Delineation and Quantitative Assessment of Glucose Metabolic Rate within Histologic Subtypes of Non-Small Cell Lung Cancer by Using Dynamic 18 F Fluorodeoxyglucose PET

• Published in: Radiology Vol. 283; no. 2; pp. 547 - 559
• Main Authors: Meijer, Tineke W H, de Geus-Oei, Lioe-Fee, Visser, Eric P, Oyen, Wim J G, Looijen-Salamon, Monika G, Visvikis, Dimitris, Verhagen, Ad F T M, Bussink, Johan, Vriens, Dennis
• Format: Journal Article
• Language: English
• Published: United States 01.05.2017
• Subjects: Aged; Aged, 80 and over; Biomarkers, Tumor - metabolism; Carcinoma, Non-Small-Cell Lung - diagnostic imaging; Carcinoma, Non-Small-Cell Lung - metabolism; Carcinoma, Non-Small-Cell Lung - pathology; Fluorodeoxyglucose F18 - pharmacokinetics; Glucose - metabolism; Humans; Image Interpretation, Computer-Assisted - methods; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - metabolism; Lung Neoplasms - pathology; Male; Metabolic Clearance Rate; Middle Aged; Molecular Imaging - methods; Neoplasm Staging; Positron-Emission Tomography - methods; Radiopharmaceuticals - pharmacokinetics; Reproducibility of Results; Sensitivity and Specificity
• DOI: 10.1148/radiol.2016160329
• ISSN: 0033-8419

Purpose To assess whether dynamic fluorine 18 ( F) fluorodeoxyglucose (FDG) positron emission tomography (PET) has added value over static F-FDG PET for tumor delineation in non-small cell lung cancer (NSCLC) radiation therapy planning by using pathology volumes as the reference standard and to compare pharmacokinetic rate constants of F-FDG metabolism, including regional variation, between NSCLC histologic subtypes. Materials and Methods The study was approved by the institutional review board. Patients gave written informed consent. In this prospective observational study, 1-hour dynamic F-FDG PET/computed tomographic examinations were performed in 35 patients (36 resectable NSCLCs) between 2009 and 2014. Static and parametric images of glucose metabolic rate were obtained to determine lesion volumes by using three delineation strategies. Pathology volume was calculated from three orthogonal dimensions (n = 32). Whole tumor and regional rate constants and blood volume fraction (V ) were computed by using compartment modeling. Results Pathology volumes were larger than PET volumes (median difference, 8.7-25.2 cm ; Wilcoxon signed rank test, P < .001). Static fuzzy locally adaptive Bayesian (FLAB) volumes corresponded best with pathology volumes (intraclass correlation coefficient, 0.72; P < .001). Bland-Altman analyses showed the highest precision and accuracy for static FLAB volumes. Glucose metabolic rate and F-FDG phosphorylation rate were higher in squamous cell carcinoma (SCC) than in adenocarcinoma (AC), whereas V was lower (Mann-Whitney U test or t test, P = .003, P = .036, and P = .019, respectively). Glucose metabolic rate, F-FDG phosphorylation rate, and V were less heterogeneous in AC than in SCC (Friedman analysis of variance). Conclusion Parametric images are not superior to static images for NSCLC delineation. FLAB-based segmentation on static F-FDG PET images is in best agreement with pathology volume and could be useful for NSCLC autocontouring. Differences in glycolytic rate and V between SCC and AC are relevant for research in targeting agents and radiation therapy dose escalation. RSNA, 2016 Online supplemental material is available for this article.