Quantitative CT Analysis for Predicting the Behavior of Part-Solid Nodules with Solid Components Less than 6 mm: Size, Density and Shape Descriptors

Abstract

Persistent part-solid nodules (PSNs) with a solid component <6 mm usually represent minimally invasive adenocarcinomas and are significantly less aggressive than PSNs with a solid component ≥6 mm. However, not all PSNs with a small solid component behave in the same way: some nodules exhibit an indolent course, whereas others exhibit more aggressive behavior. Thus, predicting the future behavior of this subtype of PSN remains a complex and fascinating diagnostic challenge. The main purpose of this study was to apply open-source software to investigate which quantitative computed tomography (CT) features may be useful for predicting the behavior of a select group of PSNs. We retrospectively selected 50 patients with a single PSN with a solid component <6 mm and diameter <15 mm. Computerized analysis was performed using ImageJ software for each PSN and various quantitative features were calculated from the baseline CT images. The area, perimeter, mean Feret diameter, linear mass density, circularity and solidity were significantly related to nodule growth (p ≤ 0.031). Therefore, quantitative CT analysis was helpful for predicting the future behavior of a select group of PSNs with a solid component <6 mm and diameter <15 mm.

What’s New on Quantitative CT Analysis as a Tool to Predict Growth in Persistent Pulmonary Subsolid Nodules? A Literature Review

“…In their quantitative analysis, the authors defined growth as an increase by more than 11.3% (i.e., more than the coefficient of repeatability of intraobserver variability) of the linear mass density (LMD), a viable two-dimensional alternative to the mass. Moreover, to determine the nodule growth rate, the authors also calculated the LMD-DT by matching the baseline with the last available follow-up CT. Based on the results obtained in their study, Borghesi et al [29] found that both dimensional (area, perimeter, diameter, LMD) and shape features (circularity and solidity) were significantly related to nodule growth, and the strongest association was observed with circularity and solidity (p < 0.001). Among the clinical features (patient age, sex, smoking habits, oncologic history, emphysema status, and PSN lobe location), only oncologic history (lung or other cancers) was strongly associated with nodule growth (p = 0.007).…”

“…The other four original articles were published in 2019 [27][28][29][30]. Two articles, published by Shi et al [28] and Qi et al [30], focused exclusively on NSNs.…”

“…Two articles, published by Shi et al [28] and Qi et al [30], focused exclusively on NSNs. Among the remaining two articles, while the study of Sun et al [27] included both NSNs and PSNs, the one by Borghesi et al [29] included only PSNs with a solid component less than 6 mm and diameter between 6 and 15 mm.…”

“…Borghesi et al [29] included 50 patients with a single PSN and assessed several quantitative features (dimensional, densitometric, and shape parameters) in order to find useful factors for predicting nodule growth. Nodule segmentation was performed manually using an open-source software package on the largest cross-sectional area of each PSN.…”

“…All studies but one were conducted on Asian patients, and only one included a European (Italian) cohort. Five papers investigated the role of quantitative analysis in NSNs [24][25][26]28,30], while one included both PSNs and NSNs [27] and the remaining paper considered only PSNs with a solid component <6 mm [29].…”