Cargando…

Comparison of Comprehensive Morphological and Radiomics Features of Subsolid Pulmonary Nodules to Distinguish Minimally Invasive Adenocarcinomas and Invasive Adenocarcinomas in CT Scan

OBJECTIVE: To investigative the diagnostic performance of the morphological model, radiomics model, and combined model in differentiating invasive adenocarcinomas (IACs) from minimally invasive adenocarcinomas (MIAs). METHODS: This study retrospectively involved 307 patients who underwent chest comp...

Descripción completa

Detalles Bibliográficos
Autores principales:	Qiu, Lu, Zhang, Xiuping, Mao, Haixia, Fang, Xiangming, Ding, Wei, Zhao, Lun, Chen, Hongwei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8765579/ https://www.ncbi.nlm.nih.gov/pubmed/35059308 http://dx.doi.org/10.3389/fonc.2021.691112

Ejemplares similares

Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact
por: Jiang, Yining, et al.
Publicado: (2021)

An integrated nomogram combined semantic-radiomic features to predict invasive pulmonary adenocarcinomas in subjects with persistent subsolid nodules
por: Wu, Fu-Zong, et al.
Publicado: (2022)

A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules
por: Wu, Yun-Ju, et al.
Publicado: (2021)

Thin-slice computed tomography enables to classify pulmonary subsolid nodules into pre-invasive lesion/minimally invasive adenocarcinoma and invasive adenocarcinoma: a retrospective study
por: Li, Min, et al.
Publicado: (2023)

Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules
por: Oikonomou, Anastasia, et al.
Publicado: (2019)

CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction
por: Li, Xiaohu, et al.
Publicado: (2020)

Establishment and validation a prediction model for discrimination of invasive adenocarcinomas for patients with peripheral pulmonary subsolid nodules
por: Pan, Wen-Biao, et al.
Publicado: (2022)

Differentiation of persistent pulmonary subsolid nodules with a solid component smaller than 6 mm: to be invasive adenocarcinoma or not to be?
por: Lee, Jong Hyuk, et al.
Publicado: (2020)

Radiomic analysis of pulmonary ground-glass opacity nodules for distinction of preinvasive lesions, invasive pulmonary adenocarcinoma and minimally invasive adenocarcinoma based on quantitative texture analysis of CT
por: Li, Wei, et al.
Publicado: (2018)

Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning
por: Shen, Tianle, et al.
Publicado: (2021)

Quantitative CT Analysis of Pulmonary Ground-Glass Opacity Nodules for the Distinction of Invasive Adenocarcinoma from Pre-Invasive or Minimally Invasive Adenocarcinoma
por: Son, Ji Ye, et al.
Publicado: (2014)

Predicting the invasiveness of lung adenocarcinomas appearing as ground-glass nodule on CT scan using multi-task learning and deep radiomics
por: Wang, Xiang, et al.
Publicado: (2020)

Prediction of subsolid pulmonary nodule growth rate using radiomics
por: Ma, Zong Jing, et al.
Publicado: (2023)

Assessing invasiveness of subsolid lung adenocarcinomas with combined attenuation and geometric feature models
por: de Margerie-Mellon, Constance, et al.
Publicado: (2020)

Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
por: Digumarthy, Subba R., et al.
Publicado: (2019)

Distinct tumor bacterial microbiome in lung adenocarcinomas manifested as radiological subsolid nodules
por: Ma, Yi, et al.
Publicado: (2021)

Stage I lung adenocarcinoma: the value of quantitative CT in differentiating pathological subtypes and predicting growth of subsolid nodules
por: Xu, Xianqun, et al.
Publicado: (2017)

A CT-based nomogram for predicting the risk of adenocarcinomas in patients with subsolid nodule according to the 2021 WHO classification
por: Song, Qilong, et al.
Publicado: (2022)

Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma
por: Xu, Fangyi, et al.
Publicado: (2020)

Dual-energy CT-based radiomics for predicting invasiveness of lung adenocarcinoma appearing as ground-glass nodules
por: Zheng, Yuting, et al.
Publicado: (2023)

Development and Validation a Nomogram Incorporating CT Radiomics Signatures and Radiological Features for Differentiating Invasive Adenocarcinoma From Adenocarcinoma In Situ and Minimally Invasive Adenocarcinoma Presenting as Ground-Glass Nodules Measuring 5-10mm in Diameter
por: Shi, Lili, et al.
Publicado: (2021)

Comparison and Fusion of Deep Learning and Radiomics Features of Ground-Glass Nodules to Predict the Invasiveness Risk of Stage-I Lung Adenocarcinomas in CT Scan
por: Xia, Xianwu, et al.
Publicado: (2020)

Incidental, subsolid pulmonary nodules at CT: etiology and management
por: Seidelman, Jessica L., et al.
Publicado: (2013)

Analysis of CT morphologic features and attenuation for differentiating among transient lesions, atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive and invasive adenocarcinoma presenting as pure ground-glass nodules
por: Qi, Lin, et al.
Publicado: (2019)

Radiomics as a non-invasive adjunct to Chest CT in distinguishing benign and malignant lung nodules
por: Selvam, Minmini, et al.
Publicado: (2023)

A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans
por: Alilou, Mehdi, et al.
Publicado: (2021)

Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction
por: Sun, Yingli, et al.
Publicado: (2020)

Corrigendum: Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma
por: Xu, Fangyi, et al.
Publicado: (2020)

Radiomics-based analysis of CT imaging for the preoperative prediction of invasiveness in pure ground-glass nodule lung adenocarcinomas
por: Feng, Hui, et al.
Publicado: (2023)

Diameter of the Solid Component in Subsolid Nodules on Low-Dose Unenhanced Chest Computed Tomography: Measurement Accuracy for the Prediction of Invasive Component in Lung Adenocarcinoma
por: Ahn, Hyungwoo, et al.
Publicado: (2018)

Factors distinguishing invasive from pre-invasive adenocarcinoma presenting as pure ground glass pulmonary nodules
por: Yang, Huan-Huan, et al.
Publicado: (2020)

Diagnosis of Serosal Invasion in Gastric Adenocarcinoma by Dual-Energy CT Radiomics: Focusing on Localized Gastric Wall and Peritumoral Radiomics Features
por: Yang, Li, et al.
Publicado: (2022)

Value of (18)F-FDG PET/CT-based radiomics model to distinguish the growth patterns of early invasive lung adenocarcinoma manifesting as ground-glass opacity nodules
por: Shao, Xiaonan, et al.
Publicado: (2020)

CT Radiomics Combined With Clinicopathological Features to Predict Invasive Mucinous Adenocarcinoma in Patients With Lung Adenocarcinoma
por: Zhang, Junjie, et al.
Publicado: (2023)

Development of a novel nomogram-based model incorporating 3D radiomic signatures and lung CT radiological features for differentiating invasive adenocarcinoma from adenocarcinoma in situ and minimally invasive adenocarcinoma
por: Ren, He, et al.
Publicado: (2022)

Diagnostic Efficacy of CT Radiomic Features in Pulmonary Invasive Mucinous Adenocarcinoma
por: Sheng, Aizhu, et al.
Publicado: (2022)

CT-Based Radiomic Analysis for Preoperative Prediction of Tumor Invasiveness in Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodule
por: Kao, Tzu-Ning, et al.
Publicado: (2022)

Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing
por: Xing, Xudong, et al.
Publicado: (2021)

Computed tomography-based radiomics machine learning models for prediction of histological invasiveness with sub-centimeter subsolid pulmonary nodules: a retrospective study
por: Zhang, Haochuan, et al.
Publicado: (2023)

Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study
por: Wu, Guangyao, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_esosoff26enrj8fsm9ehu0p279