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PloS one · 2026

Adenosquamous carcinoma of the lung: Comparative CT and pathological features versus adenocarcinoma and squamous cell carcinoma.

СтатьяСравнительное исследованиеНазвание и аннотация: Перевод в очереди
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Yuan Qianyao, Zhang Dai, Xu Rui, Yao Wenjun, Zhao Hong

Аннотация

OBJECTIVE: Adenosquamous carcinoma (ASC) of the lung, containing both adenocarcinoma (AC) and squamous cell carcinoma (SCC) components, is associated with aggressive behavior and poor prognosis. Due to overlapping imaging features with AC and SCC, its preoperative diagnosis remains challenging. This study aimed to compare CT and pathological characteristics among ASC, AC, and SCC; identify key differentiators.

METHODS: This retrospective study included 27 patients with pathologically confirmed ASC who underwent surgical resection from November 2018 to January 2025. Forty cases each of AC and SCC, matched for age, sex, and smoking history, were selected for comparison. Clinical, radiological, and pathological features were analyzed. Variables with statistical significance (P < 0.05) in univariate analysis were further evaluated using multivariate logistic regression. The discriminatory performance of the models was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS: Compared with SCC, ASC lesions were more peripheral and associated with higher distance ratios (DR), pleural retraction, spiculation, and lymph node metastasis (LNM). Compared with AC, ASC tumors were larger, more often solid, and exhibited lobulation, bronchial cutoff sign, and advanced staging. Among the evaluated analyses, the combined pathology-imaging approach showed the highest discriminatory performance, with AUCs of 0.909 (ASC vs SCC) and 0.900 (ASC vs AC). LNM and DR were more strongly associated with ASC relative to SCC, whereas larger tumor size, ill-defined margins, and advanced stage were more strongly associated with ASC relative to AC.

CONCLUSION: Certain CT imaging features, especially DR and LNM, were associated with ASC and may provide useful information for preoperative radiological assessment and subtype stratification.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты