The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions
| العنوان: | The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions |
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| المؤلفون: | Gian Carlo Parenti, Emiliano Loi, Emanuela Scarpi, Melchiore Giganti, Aldo Carnevale, Roberto Galeotti, Anna Sarnelli, Giacomo Feliciani, E. Menghi, Filippo Piccinini, Lorenzo Mellini |
| المساهمون: | Feliciani G., Mellini L., Carnevale A., Sarnelli A., Menghi E., Piccinini F., Scarpi E., Loi E., Galeotti R., Giganti M., Parenti G.C. |
| المصدر: | Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021) Scientific Reports |
| بيانات النشر: | Nature Portfolio, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Adult, Male, medicine.medical_specialty, endocrine system, Support Vector Machine, endocrine system diseases, Science, Testicular Neoplasm, Feature selection, Article, NO, 030218 nuclear medicine & medical imaging, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, Text mining, Lasso (statistics), Testicular cancer, Testicular Neoplasms, Retrospective Studie, medicine, radiomic biomarkers, Humans, testicular lesions, radiomic biomarkers, MR, Retrospective Studies, Multidisciplinary, business.industry, Biomarker, MR, Neoplasms, Germ Cell and Embryonal, medicine.disease, Linear discriminant analysis, testicular lesions, Magnetic Resonance Imaging, Seminoma, Support vector machine, 030220 oncology & carcinogenesis, Medicine, Cancer imaging, Radiology, business, Selection operator, Biomarkers, Human |
| الوصف: | How to differentiate with MRI-based techniques testicular germ (TGCTs) and testicular non-germ cell tumors (TNGCTs) is still under debate and Radiomics may be the turning key. Our purpose is to investigate the performance of MRI-based Radiomics signatures for the preoperative prediction of testicular neoplasm histology. The aim is twofold: (i), differentiating TGCTs and TNGCTs status and (ii) differentiating seminomas (SGCTs) from non-seminomatous (NSGCTs). Forty-two patients with pathology-proven testicular neoplasms and referred for pre-treatment MRI, were retrospectively enrolled. Thirty-two out of 44 lesions were TGCTs. Twelve out of 44 were TNGCTs or other histologies. Two radiologists segmented the volume of interest on T2-weighted images. Approximately 500 imaging features were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) was applied as method for variable selection. A linear model and a linear support vector machine (SVM) were trained with selected features to assess discrimination scores for the two endpoints. LASSO identified 3 features that were employed to build fivefold validated linear discriminant and linear SVM classifiers for the TGCT-TNGCT endpoint giving an overall accuracy of 89%. Four features were employed to build another SVM for the SGCT-SNGCT endpoint with an overall accuracy of 86%. The data obtained proved that T2-weighted-based Radiomics is a promising tool in the diagnostic workup of testicular neoplasms by discriminating germ cell from non-gem cell tumors, and seminomas from non-seminomas. |
| وصف الملف: | ELETTRONICO |
| اللغة: | English |
| تدمد: | 2045-2322 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22e8ac07f57d30ed77f59270aaf3395dTest https://doaj.org/article/87c7383624814cd6abcd80b8bd8ee411Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....22e8ac07f57d30ed77f59270aaf3395d |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20452322 |
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