ArticleCancers2021
Rethinking a Non-Predominant Pattern in Invasive Lung Adenocarcinoma: Prognostic Dissection Focusing on a High-Grade Pattern.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- CT-based deep learning radiomics predicts micropapillary/solid components in lung adenocarcinoma.Journal of thoracic disease · 2026Article
- Evaluation of high-grade growth patterns in invasive adenocarcinomas manifesting as ground-glass lesions via clinical and qualitative and quantitative computed tomography features.Quantitative imaging in medicine and surgery · 2026Article
- Radiological, Molecular, and Pathological Factors Unite: A Model for Predicting Recurrence-Free Survival in Pathological Stage I Lung Adenocarcinoma.Thoracic cancer · 2026Article
- Development and validation of a computed tomography-based radiomics-clinical model to preoperatively predict high-grade patterns within lung invasive adenocarcinoma.Journal of thoracic disease · 2025Article
- Deciphering the intratumoral histologic heterogeneity of lung adenocarcinoma using radiomics.European radiology · 2025Article
- Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features.Cancer research and treatment · 2025Article
- Predicting pathological grade of stage I pulmonary adenocarcinoma: a CT radiomics approach.Frontiers in oncology · 2024Article
- Minor histological components predict the recurrence of patients with resected stage I acinar- or papillary-predominant lung adenocarcinoma.Frontiers in oncology · 2022Article
- Establishment and validation of a radiological-radiomics model for predicting high-grade patterns of lung adenocarcinoma less than or equal to 3 cm.Frontiers in oncology · 2022Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundPrognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern.
methodsIn this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival.
resultsAmong the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups (
conclusionsThe second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.
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