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An MRI radiomics nomogram improves the accuracy in identifying eligible candidates for fertility-preserving treatment in endometrioid adenocarcinoma.
Yan, Bi-Cong; Ma, Feng-Hua; Li, Ying; Fan, Yan-Feng; Huang, Zhi-Long; Ma, Xiao-Liang; Wen, Xue-Ting; Qiang, Jin-Wei.
Afiliación
  • Yan BC; Department of Diagnostic and Interventional Radiology, Shanghai Jiaotong University Affiliated Sixth People's Hospital 600 Yi Shan Road, Shanghai 200233, China.
  • Ma FH; Department of Radiology, Jinshan Hospital, Fudan University 1508 Longhang Road, Shanghai 201508, China.
  • Li Y; Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University 128 Shenyang Road, Shanghai 200090, China.
  • Fan YF; Department of Radiology, Jinshan Hospital, Fudan University 1508 Longhang Road, Shanghai 201508, China.
  • Huang ZL; Department of Diagnostic and Interventional Radiology, Shanghai Jiaotong University Affiliated Sixth People's Hospital 600 Yi Shan Road, Shanghai 200233, China.
  • Ma XL; Department of Diagnostic and Interventional Radiology, Shanghai Jiaotong University Affiliated Sixth People's Hospital 600 Yi Shan Road, Shanghai 200233, China.
  • Wen XT; Department of Radiology, Jinshan Hospital, Fudan University 1508 Longhang Road, Shanghai 201508, China.
  • Qiang JW; Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University 128 Shenyang Road, Shanghai 200090, China.
Am J Cancer Res ; 12(3): 1056-1068, 2022.
Article en En | MEDLINE | ID: mdl-35411235
It is difficult to identify eligible candidates for fertility-preserving treatment (FPT) among endometrioid adenocarcinoma (EAC) and atypical hyperplasia (AH) patients. Therefore, new approaches for improving the accuracy of candidate selection are warranted. From December 2014 to January 2020, 236 EAC/AH patients (age <50 and premenopausal) were retrospectively reviewed and randomly divided into the primary group (n=158) and validation group 1 (n=78). From February 2020 to December 2021, 51 EAC/AH patients were prospectively enrolled and formed the validation group 2. From the primary group, 385 features were extracted using pyradiomics from multiparameter magnetic resonance imaging (MRI) (including T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences) and 13 radiomics features were selected using a least absolute shrinkage and selection operator. A clinical model based on clinical information (myometrial invasion on MRI and tumor grade in curettage) and a radiomics nomogram by integrating clinical information with the radiomics features was developed to identify eligible candidates of FPT. For identifying eligible candidates of FPT, the areas under the receiver operating characteristic curve (AUCs) were 0.63 (95% confidence interval [CI]: 0.53-0.73) in the primary group, and 0.62 (95% CI: 0.45-0.78) and 0.69 (95% CI: 0.53-0.86) in validation groups 1 and 2, respectively, for the clinical model; were 0.86 (95% CI: 0.80-0.93) in the primary group, and 0.82 (95% CI: 0.71-0.93) and 0.94 (95% CI: 0.87-1.0) in validation groups 1 and 2, respectively, for the radiomics nomogram. With the help of radiomics nomogram, the treatment decision determined from the clinical model was revised in 45 EAC/AH patients. The net reclassification index (NRI) was 0.80 and integrated discrimination improvement (IDI) was 0.17, indicating that the nomogram could improve the accuracy in identifying eligible EAC/AH candidates for FPT.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Am J Cancer Res Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Am J Cancer Res Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos