Background Clinical TNM staging is based on a qualitative assessment of features defining T descriptors and has been found suboptimal for predicting prognosis of patients with MPM. Previous work suggests that volumetric CT (VOLCT) is prognostic and, if found practical and reproducible, could improve clinical MPM classification. Methods Six North American institutions electronically submitted clinical, pathologic and imaging data on patients with stages I-IV MPM to an established multicenter database and biostatistical center (BC). Two reference radiologists, blinded to clinical data, independently reviewed scans, calculated clinical TNM stage by standard criteria, performed semi-automated tumor volume calculations using commercially available software, and submitted the findings to BC. Study endpoints included feasibility of a multi-institutional VOLCT network, concordance of independent VOLCT assessments and association of VOLCT with pathologic T classification. Results Of 164 submitted cases, 129 were evaluated by both reference radiologists. Discordant clinical staging of most cases confirmed the inadequacy of current criteria. The overall correlation between VOLCT estimates was good (Spearman Corr. = 0.822), but some were significantly discordant. Root-cause analysis of the most discordant estimates identified four common sources of variability. Despite these limitations, median tumor volume estimates were similar within subgroups of cases representing each pathological T descriptor, and increased monotonically for each reference pathologist with increasing pathological T status. Conclusions Good correlation between VOLCT estimates obtained for most cases reviewed by two independent radiologists, and qualitative association of VOLCT with pathological T status combine to encourage further study. Identified sources of user error will inform design of a follow-on prospective trial to more formally assess inter-observer variability of VOLCT and its potential contribution to clinical MPM staging.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.