Prediction of mediastinal lymph node metastasis based on 18F-FDG PET/CT imaging using support vector machine in non-small cell lung cancer.
Objective: The purpose of this study was to develop a classification method based on support vector machine (SVM) to improve the diagnostic performance of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) to detect the lymph node (LN) metastasis in non-small cell...
| Publicado en: | European Radiology Vol. 31; no. 6; pp. 3983 - 3993 |
|---|---|
| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=150343604&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 150343604 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Jun2021 vid: 31 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 150343604 147212563 150343604 NLM33201286 150343604 10.1007/s00330-020-07466-5 NLM33201286 150343604 ppf: 3983 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Prediction of mediastinal lymph node metastasis based on 18F-FDG PET/CT imaging using support vector machine in non-small cell lung cancer. aug: au: Yin, Guotao Song, Yingchao Li, Xiaofeng Zhu, Lei Su, Qian Dai, Dong Xu, Wengui affil: Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi Distinct, 300060, Tianjin City, People's Republic of China sug: subj: Carcinoma, Non-Small-Cell Lung Lung Neoplasms Carcinoma, Non-Small-Cell Lung Pathology Lung Neoplasms Pathology Neoplasm Metastasis Tomography, Emission-Computed Retrospective Design Lymph Nodes Lymph Nodes Pathology Fludeoxyglucose F 18 Neoplasm Staging Scales ab: Objective: The purpose of this study was to develop a classification method based on support vector machine (SVM) to improve the diagnostic performance of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) to detect the lymph node (LN) metastasis in non-small cell lung cancer (NSCLC).Method: Two hundred nineteen lymph nodes (37 metastatic) from 71 patients were evaluated in this study. SVM models were developed with 7 LN features. The area under the curve (AUC) and accuracy of 9 models were compared to select the best model. The best SVM model was simplified on the basis of the feature weights and value distribution to further suit the clinical application.Results: The maximum, minimum, and mean accuracy of the best model was 91.89% (68/74, 95% CI 83.11~96.54%), 66.22% (49/74, 95% CI 54.85~75.98%), and 80.09% (59,266/74,000, 95% CI 70.27~89.19%), respectively, with an AUC of 0.94, 0.66, and 0.81, respectively. The best SVM model was finally simplified into a score rule: LNs with scores more than 3.0 were considered as malignant ones, whereas LNs with scores less than 1.5 tended to be benign ones. For the LNs with scores within a range of 1.5-3.0, metastasis was suspected.Conclusion: An SVM model based on 18F-FDG PET/CT images was able to predict the metastatic LNs for patients with NSCLC. The ratio of the maximum of standard uptake value of LNs to aortic arch played a major role in the model. After simplification, the model could be transferred into a scoring method which may partly help clinicians determine the clinical staging of patients with NSCLC relatively easier.Key Points: • The SVM model based on 18F-FDG PET/CT features may help clinicians to make a decision for metastatic mediastinal lymph nodes in patients with NSCLC. • The SURblood plays a major role in the SVM model. • The score rule based on the SVM model simplified the complexity of the model and may partly help clinicians determine the clinical staging of patients with NSCLC relatively easier. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|