A5101869004- Lung Cancer Diagnosis and Treatment
- Lung Cancer Treatments and Mutations
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging and Pathology Studies
- Lung Cancer Research Studies
- Pleural and Pulmonary Diseases
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Tracheal and airway disorders
- Cancer Immunotherapy and Biomarkers
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Cancer Genomics and Diagnostics
- Advanced X-ray and CT Imaging
- Salivary Gland Tumors Diagnosis and Treatment
- Gastric Cancer Management and Outcomes
- Galectins and Cancer Biology
- COVID-19 diagnosis using AI
- RNA modifications and cancer
- AI in cancer detection
- Neurological disorders and treatments
- Parkinson's Disease Mechanisms and Treatments
- Ferroptosis and cancer prognosis
- Immune cells in cancer
- Esophageal Cancer Research and Treatment
- Circular RNAs in diseases
- Actinomycetales infections and treatment
Tongji University
2016-2025
Shanghai Pulmonary Hospital
2016-2025
Dalian Medical University
2024-2025
Chongqing Medical University
2024-2025
Second Affiliated Hospital of Chongqing Medical University
2024-2025
Thoracic Surgery Foundation
2017-2022
<h3>Importance</h3> There is a lack of studies exploring the performance deep learning survival neural network in non–small cell lung cancer (NSCLC). <h3>Objectives</h3> To compare performances DeepSurv, with tumor, node, and metastasis staging system prediction test reliability individual treatment recommendations provided by network. <h3>Design, Setting, Participants</h3> In this population-based cohort study, learning–based algorithm was developed validated using consecutive cases newly...
// Yijiu Ren 1, * , Chenyang Dai Hui Zheng 1 Fangyu Zhou Yunlang She Gening Jiang Ke Fei Ping Yang 2 Dong Xie Chang Chen Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School Medicine, Shanghai, People’s Republic China Division Epidemiology, Health Sciences Research, Mayo Clinic, Rochester, MN, USA These authors contributed equally to this work Correspondence to: Chen, email: changchenc@hotmail.com Xie, kongduxd@163.com Keywords: lung cancer, distant...
Background Radiomics-based biomarkers enable the prognostication of resected non–small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized patients with NSCLC. Materials Methods In this retrospective study, six signatures were constructed NSCLC who underwent resection between January 2011 December 2013 at...
Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non–small cell lung cancer (NSCLC). Purpose To develop a deep learning signature N2 metastasis prediction and prognosis stratification in NSCLC. Materials Methods In this retrospective study conducted from May 2020 to October population with NSCLC, an internal cohort was adopted establish signature. Subsequently, predictive efficacy biologic basis proposed were investigated external cohort....
BackgroundThis study, based on multicentre cohorts, aims to utilize computed tomography (CT) images construct a deep learning model for predicting major pathological response (MPR) neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC) and further explore the biological basis under its prediction.Methods274 patients undergoing curative surgery after NSCLC at 4 centres from January 2019 December 2021 were included divided into training cohort, an internal validation external...
Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop deep learning signature based on positron emission tomography/computed tomography predict ONM clinical stage N0 NSCLC. An internal cohort (n = 1911) is included construct the (DLNMS). Subsequently, an external 355) and prospective 999) are utilized fully validate predictive performances DLNMS. Here, we show areas under receiver operating...
Objectives To develop and validate a nomogram to estimate the pretest probability of malignancy in Chinese patients with solid solitary pulmonary nodule (SPN). Materials Methods A primary cohort 1798 pathologically confirmed SPNs after surgery was retrospectively studied at five institutions from January 2014 December 2015. based on independent prediction factors malignant SPN developed. Predictive performance also evaluated using calibration curve area under receiver operating...
// Yunlang She 1,* , Lilan Zhao Chenyang Dai 1 Yijiu Ren Junyan Zha Huikang Xie 2 Sen Jiang 3 Jingyun Shi Shunbin 4 Weirong 5 Bing Yu 6 Gening Ke Fei Yongbing Chen 7 and Chang Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School Medicine, Shanghai, P.R. China Pathology, Radiology, The Affiliated Wujiang Hospital Nantong University, Jiangsu, Sixth People's Fenghua Zhejiang, Second Soochow * These authors have contributed equally to this work Correspondence to:...
This study aimed to investigate the relationship between lymph node micrometastasis and histologic patterns of adenocarcinoma, with a particular focus on their joint effect prognosis. We retrospectively reviewed 235 patients stage I adenocarcinoma from January 2009 December 2009. Lymph was evaluated by immunohistochemical staining for cytokeratin (AE1/AE3) thyroid transcription factor-1. A logistic regression model applied confirm predictive factors micrometastasis. Survival analysis...
Abstract OBJECTIVES As evidence has proven that sublobar resection is oncologically contraindicated by tumour spread through air spaces (STAS), its preoperative recognition vital in customizing surgical strategies. We aimed to assess the value of radiomics predicting STAS stage I lung adenocarcinoma. METHODS retrospectively reviewed patients with adenocarcinoma, who accepted curative our institution between January 2011 and December 2013. Using ‘PyRadiomics’ package, 88 features were...
To investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA).Preoperative image findings were consecutively evaluated 317 resected IMA from January 2011 to December 2015. The long-term assessed by univariate analysis. independent prognostic factors identified multivariate Cox regression analyses. comparison of was investigated using Kaplan-Meier method propensity scores. Furthermore, impact based on different...
Robust imaging biomarkers are needed for risk stratification in stage I lung adenocarcinoma patients order to select optimal treatment regimen. We aimed construct and validate a radiomics nomogram predicting the disease-free survival (DFS) of with resected adenocarcinoma, further identifying candidates benefit from adjuvant chemotherapy (ACT).Using approach, we analyzed 554 patients' computed tomography (CT) images three multicenter cohorts. Prognostic features were extracted selected using...