ArticleCancers2022
CT-Based Radiomic Analysis for Preoperative Prediction of Tumor Invasiveness in Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodule.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 26 citations in OpenAlex.
- Radiomic model with SHAP-based interpretability for predicting invasiveness of pure ground-glass nodules: a retrospective study based on high-resolution computed tomography (HRCT) volumetric datasets.Journal of cardiothoracic surgery · 2026Article
- Predicting Invasiveness of Lung Adenocarcinoma from Chest CT with Few-shot Vision-Language Ternary Classification Model.NPJ digital medicine · 2025Article
- The impact of preoperative percutaneous transthoracic needle biopsy on pleural recurrence in clinically early-stage non-small cell lung cancer.Journal of thoracic disease · 2025Article
- Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground-Glass Nodules Based on AI-Extracted Radiomic Features.Thoracic cancer · 2025Article
- Predicting Visceral Pleural Invasion in Resected Lung Adenocarcinoma via Computed Tomography.Cancers · 2025Article
- Assessment of intratumor heterogeneity for preoperatively predicting the invasiveness of pulmonary adenocarcinomas manifesting as pure ground-glass nodules.Quantitative imaging in medicine and surgery · 2025Article
- Radiomics of Vascular Structures in Pulmonary Ground-glass Nodules: A Predictor of InvasivenessCurrent medical imaging · 2025Article
- Nomogram integrating clinical-radiological and radiomics features for differentiating invasive from non-invasive pulmonary adenocarcinomas presenting as ground-glass nodules.American journal of cancer research · 2025Article
- CT-based radiomic consensus clustering association with tumor biological behavior in clinical stage IA adenocarcinoma: a retrospective study.Translational lung cancer research · 2024Article
- Prediction of the Benign or Malignant Nature of Pulmonary Pure Ground-Glass Nodules Based on Radiomics Analysis of High-Resolution Computed Tomography Images.Tomography (Ann Arbor, Mich.) · 2024Article
- Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule.Journal of thoracic disease · 2024Article
- The identification of hub genes associated with pure ground glass nodules using weighted gene co-expression network analysis.BMC pulmonary medicine · 2024Article
- Correlation between Radiological Characteristics, PET-CT and Histological Subtypes of Primary Lung Adenocarcinoma-A 102 Case Series Analysis.Medicina (Kaunas, Lithuania) · 2024Article
- [Value of CT Quantitative Parameters in Prediction of Pathological Types of Lung Ground Glass Nodules].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024Article
- The value of intratumoral and peritumoral radiomics features in differentiating early-stage lung invasive adenocarcinoma (≤3 cm) subtypes.Translational cancer research · 2024Article
- Predicting the Invasiveness of Pulmonary Adenocarcinomas in Pure Ground-Glass Nodules Using the Nodule Diameter: A Systematic Review, Meta-Analysis, and Validation in an Independent Cohort.Diagnostics (Basel, Switzerland) · 2024Review
- Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.La Radiologia medica · 2024Article
- A nomogram for predicting invasiveness of lung adenocarcinoma manifesting as pure ground-glass nodules: incorporating subjective CT signs and histogram parameters based on artificial intelligence.Journal of cancer research and clinical oncology · 2023Article
- Effective Invasiveness Recognition of Imbalanced Data by Semi-Automated Segmentations of Lung Nodules.Biomedicines · 2023Article
- Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
It remains a challenge to preoperatively forecast whether lung pure ground-glass nodules (pGGNs) have invasive components. We aimed to construct a radiomic model using tumor characteristics to predict the histologic subtype associated with pGGNs. We retrospectively reviewed clinicopathologic features of pGGNs resected in 338 patients with lung adenocarcinoma between 2011-2016 at a single institution. A radiomic prediction model based on forward sequential selection and logistic regression was constructed to differentiate adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma. The study cohort included 133 (39.4%), 128 (37.9%), and 77 (22.8%) patients with AIS, MIA, and invasive adenocarcinoma (acinar 55.8%, lepidic 33.8%, papillary 10.4%), respectively. The majority (83.7%) underwent sublobar resection. There were no nodal metastases or tumor recurrence during a mean follow-up period of 78 months. Three radiomic features-cluster shade, homogeneity, and run-length variance-were identified as predictors of histologic subtype and were selected to construct a prediction model to classify the AIS/MIA and invasive adenocarcinoma groups. The model achieved accuracy, sensitivity, specificity, and AUC of 70.6%, 75.0%, 70.0%, and 0.7676, respectively. Applying the developed radiomic feature model to predict the histologic subtypes of pGGNs observed on CT scans can help clinically in the treatment selection process.
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