Related Experiment Video
Updated: Dec 13, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
The Growth Rate of Subsolid Lung Adenocarcinoma Nodules at Chest CT
Constance de Margerie-Mellon1, Long H Ngo1, Ritu R Gill1
1From the Departments of Radiology (C.d.M.M., R.R.G., A.C.M.F., B.H.H., A.A.B.), General Medicine (L.H.N.), and Pathology (A.O., M.A.M., P.A.V.), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Mass (L.H.N.); and Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (B.H.H.).
Abstract:
Background Confirming that subsolid adenocarcinomas show exponential growth is important because it would justify using volume doubling time to assess their growth. Purpose To test whether the growth of lung adenocarcinomas manifesting as subsolid nodules at chest CT is accurately represented by an exponential model. Materials and Methods Patients with lung adenocarcinomas manifesting as subsolid nodules surgically resected between January 2005 and May 2018, with three or more longitudinal CT examinations before resection, were retrospectively included. Overall volume (for all nodules) and solid component volume (for part-solid nodules) were measured over time. A linear mixed-effects model was used to identify the growth pattern (linear, exponential, quadratic, or power law) that best represented growth. The interactions between nodule growth and clinical, CT morphologic, and pathologic parameters were studied. Results Sixty-nine patients (mean age, 70 years ± 9 [standard deviation]; 48 women) with 74 lung adenocarcinomas were evaluated. Overall growth and solid component growth were better represented by an exponential model (adjusted R = 0.89 and 0.95, respectively) than by a quadratic model (r = 0.88 and 0.93, respectively), a linear model (r = 0.87 and 0.92, respectively), or a power law model (r = 0.82 and 0.93, respectively). Faster overall volume growth was associated with a history of lung cancer (P < .001), a baseline nodule volume less than 500 mm3 (P = .03), and histologic findings of invasive adenocarcinoma (P < .001). The median volume doubling time of noninvasive adenocarcinoma was significantly longer than that of invasive adenocarcinoma (939 days [interquartile range, 588-1563 days] vs 678 days [interquartile range, 392-916 days], respectively; P = .01). Conclusion The overall volume growth of adenocarcinomas manifesting as subsolid nodules at chest CT was best represented by an exponential model compared with the other tested models. This justifies the use of volume doubling time for the growth assessment of these nodules. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuriyama and Yanagawa in this issue.

