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Clinicoradiologic features and evolutionary characteristics of pulmonary focal mucinous adenocarcinomas across
Xue-Feng Jiang1, Hui Gan2, Ting Fu1
1Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Background:
Pulmonary focal mucinous adenocarcinomas (MAs) (≤3 cm) frequently present with non-specific computed tomography (CT) features, posing diagnostic difficulties. This study aimed to identify the clinicoradiologic features of pulmonary focal MAs for early diagnosis.
Methods:
A total of 211 patients with 211 confirmed MAs were retrospectively enrolled from two centers between November 2012 and November 2025. Thirty-one (26.5%) of 117 subsolid mucinous adenocarcinomas (SS-MAs) and 20 (21.3%) of 94 solid mucinous adenocarcinomas (S-MAs) underwent follow-up CT. The clinical data and initial and follow-up CT findings were evaluated and compared between these two subtypes to identify significant differences.
Results:
Both SS-MAs and S-MAs mainly distributed in the lower lobes (62.4%, 62.9%) and subpleural zones (75.2%, 76.3%) (each P>0.05). Compared to patients with S-MAs, females (74.4% vs. 52.1%) and non-smokers (84.6% vs. 71.3%) were more common in those with SS-MAs. Compared to S-MAs, more SS-MAs had an ill-defined boundary (62.4% vs. 20.2%) and patchy appearance (43.6% vs. 24.5%), but fewer had lobulation (16.2% vs. 47.9%) and spiculation (8.5% vs. 38.3%) (each P<0.05). During follow-up, the S-MAs showed a higher cumulative incidence of volume doubling and a shorter volume doubling time (VDT) [336.5 (254.1-401.2) vs. 470.8 (400.8-566.3) days] than SS-MAs (each P<0.05). In addition to a significant increase in size and density of the SS-MA and S-MA in progression, the solid components in SS-MAs significantly increased in size and their boundary became increasingly well-defined (each P<0.05). However, the boundary of most SS-MAs remained ill-defined, and the density of S-MAs was consistently negative.
Conclusions:
Focal SS-MAs and S-MAs are two distinct radiologic phenotypes, and understanding their respective evolutionary characteristics is helpful for early diagnosis.