Attenuation- and Entropy-Based Habitat Imaging for High-Risk Features in Lung Adenocarcinoma Presenting as a Part-Solid Nodule on CT: A Multicenter Study.

Abstract

<b>BACKGROUND.</b> Prior studies using habitat imaging for lung nodule characterization have been limited by intermixing of nodule types, insufficient handling of lesion heterogeneity, and incomplete consideration of high-risk histologic features. <b>OBJECTIVE.</b> To predict high-risk features within lung adenocarcinoma presenting as part-solid nodules on low-dose CT (LDCT) using habitat imaging incorporating attenuation and entropy measurements. <b>METHODS.</b> This retrospective study included 781 patients (median age, 58 years; 266 men, 515 women) with 781 resected adenocarcinomas manifesting as part-solid nodules on LDCT from July 2018 to December 2025. Patients from one center formed a training set (n=578) and from three other centers an external test set (n=203). The outcome was high-risk adenocarcinoma, defined as poorly differentiated invasive adenocarcinoma or invasive adenocarcinoma with visceral pleural invasion, spread through air spaces, lymphovascular invasion, or lymph node metastases. K-means clustering was used to determine optimal nodule subregions for maps of attenuation and entropy (reflecting local heterogeneity); attenuation and entropy subregions were integrated to form habitats. Habitat volumes and volume ratios (relative to whole-nodule volumes) were determined. A model incorporating demographic and conventional CT features was constructed by multivariable logistic regression analysis. AUCs were compared using DeLong test. <b>RESULTS.</b> The optimal number of clusters for both attenuation and entropy was 2 (attenuation threshold, -447 HU; entropy threshold, 4.201), yielding four habitats (high-attenuation high-entropy, high-attenuation low-entropy, low-attenuation high-entropy, low-attenuation low-entropy). In the external test set, AUC for high-risk adenocarcinoma was significantly greater (p<.05) for high-attenuation low-entropy habitat volume (0.863) than for conventional CT features (nodule diameter, solid-component diameter, consolidation-to-tumor ratio, whole-nodule volume) (0.693-0.809), other habitat features (0.614-0.842), and the conventional model (comprising sex, solid-component diameter, and whole-nodule volume; 0.810). High-attenuation low-entropy habitat volume had sensitivity, specificity, PPV, and NPV of 86.4%, 68.6%, 43.2%, and 94.8%, respectively, in the external test set. An executable software application for the final analytic pipeline and corresponding source code were made publicly available (https://github.com/mzi969/Habitat-Imaging-High-Risk-LUADs). <b>CONCLUSION.</b> The high-attenuation low-entropy habitat volume outperformed conventional CT features in predicting high-risk histologic characteristics of adenocarcinoma. <b>CLINICAL IMPACT.</b> Habitat imaging could inform noninvasive risk stratification and clinical decision-making for part-solid nodules encountered during lung cancer screening.