ArticleScientific reports2018
Deciphering Clinicoradiologic Phenotype for Thymidylate Synthase Expression Status in Patients with Advanced Lung Adenocarcinoma Using a Radiomics Approach.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 12 citations in OpenAlex.
- Development and Validation of a Radiomics Nomogram for Liver Metastases Originating from Gastric and Colorectal Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Prediction of tumor response via a pretreatment MRI radiomics-based nomogram in HCC treated with TACE.European radiology · 2021Article
- Are radiomics features universally applicable to different organs?Cancer imaging : the official publication of the International Cancer Imaging Society · 2021Article
- Development of a Radiomics Prediction Model for Histological Type Diagnosis in Solitary Pulmonary Nodules: The Combination of CT and FDG PET.Frontiers in oncology · 2020Article
- A Non-invasive Method to Diagnose Lung Adenocarcinoma.Frontiers in oncology · 2020Article
- Clinical impact of variability on CT radiomics and suggestions for suitable feature selection: a focus on lung cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2019Article
- MRI-based Radiomics nomogram to detect primary rectal cancer with synchronous liver metastases.Scientific reports · 2019Article
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8 authors at 4 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
We aimed to identify predictive clinicoradiologic characteristics of thymidylate synthase (TS) expression status in advanced non-squamous non-small cell lung cancer patients. We reviewed clinicoradiologic features of 169 patients stratified into TS-negative (n = 84) and TS-positive (n = 85) groups, including quantitative CT radiomic features of both primary lung and metastatic lesions from initial CT and PET. Clinical factors including age and smoking history were significantly associated with TS as well as radiomic features. The predictive performance for dichotomizing TS expression status was slightly higher when imaging features of primary lung lesions were added compared to the model based solely on the clinical features, but without statistical significance (10-fold cross-validated AUC = 0.619 and 0.581, respectively; P = 0.425). The predictive performance of clinicoradiologic parameters slightly increased with primary lung lesions only compared to the inclusion of metastatic lesions, but without statistical significance (10-fold cross-validated AUC = 0.619 and 0.554, respectively; P = 0.203). Overall survival was prolonged in the TS-negative group compared to the TS-positive group (P = 0.001). TS-negativity is a potential prognostic biomarker, and our study presents that although CT radiomic features have potential for predicting TS expression status, clinical significance is uncertain. The addition of radiomic features to clinical factors did not show significant improvement in predicting TS-negativity.
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