Discriminating nodular pulmonary alveolar proteinosis from lung adenocarcinoma with radiomic model and multimodal model

Background: Pulmonary alveolar proteinosis (PAP) typically manifests as diffuse lung disease, while nodular PAP presenting as pulmonary nodules is extremely rare and often radiologically indistinguishable from early-stage lung adenocarcinoma (LUAD). Objectives: This study aims to establish an accurate diagnostic algorithm to prevent unnecessary invasive procedures in patients with nodular PAP. Design: This study was a retrospective, single-center study. Methods: This study enrolled 16 pathologically confirmed nodular PAP patients and 52 early-stage LUAD patients, systematically comparing their clinical characteristics and biochemical markers. A radiomics model was developed based on CT imaging features, followed by a multimodal model incorporating significant clinical and biochemical discriminators. Results: The nodular PAP cohort demonstrated a 3:5 male-to-female ratio, equivalent distribution of solitary versus multiple nodules, and nodule diameters spanning 3–28 mm. Nodular PAP patients were significantly younger (mean 51.4 vs 67.0 years, p < 0.001), had higher body mass index (BMI, 25.8 ± 2.5 vs 23.7 ± 2.8 kg/m², p < 0.01), and lower lactate dehydrogenase levels (LDH, 188.44 ± 26.71 vs 214.79 ± 56.84 U/L, p = 0.01) compared to LUAD patients. The radiomic model achieved an AUC (area under the curve) of 0.91, while the multimodal model combining clinical and biochemical features showed similar performance (AUC = 0.97). Conclusion: This study provides the characterization of nodular PAP and establishes radiomic and multimodal diagnostic models with similar accuracy, which are reliable tools to make a differential diagnosis between nodular PAP and LUAD and to prevent unnecessary surgery.