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Journal of Medical Signals and Sensors، جلد ۱۴، شماره ۱۰، صفحات ۱۰-۴۱۰۳
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عنوان انگلیسی Predicting the Response of Patients Treated with 177Lu-DOTATATE Using Single-photon Emission Computed Tomography-Computed Tomography Image-based Radiomics and Clinical Features
چکیده انگلیسی مقاله Abstract Background:  In this study, we want to evaluate the response to Lutetium-177 ( 177 Lu)-DOTATATE treatment in patients with neuroendocrine tumors (NETs) using single-photon emission computed tomography (SPECT) and computed tomography (CT), based on image-based radiomics and clinical features. Methods:  The total volume of tumor areas was segmented into 61 SPECT and 41 SPECT-CT images from 22 patients with NETs. A total of 871 radiomics and clinical features were extracted from the SPECT and SPECT-CT images. Subsequently, a feature reduction method called maximum relevance minimum redundancy (mRMR) was used to select the best combination of features. These selected features were modeled using a decision tree (DT), random forest (RF), K-nearest neighbor (KNN), and support vector machine (SVM) classifiers to predict the treatment response in patients. For the SPECT and SPECT-CT images, ten and eight features, respectively, were selected using the mRMR algorithm. Results:  The results revealed that the RF classifier with feature selection algorithms through mRMR had the highest classification accuracies of 64% and 83% for the SPECT and SPECT-CT images, respectively. The accuracy of the classifications of DT, KNN, and SVM for SPECT-CT images is 79%, 74%, and 67%, respectively. The poor accuracy obtained from different classifications in SPECT images (~64%) showed that these images are not suitable for predicting treatment response. Conclusions:  Modeling the selected features of SPECT-CT images based on their anatomy and the presence of extensive gray levels makes it possible to predict responses to the treatment of 177 Lu-DOTATATE for patients with NETs.
کلیدواژه‌های انگلیسی مقاله Lutetium-177-DOTATATE,neuroendocrine tumors,radiomics,single-photon emission computed tomography,single-photon emission computed tomography-computed tomography
نویسندگان مقاله | Baharak Behmanesh
Department of Nuclear Physics, Urmia University, Oroumieh, Iran


| Akbar Abdi-Saray
Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Mohammad Reza Deevband
Department of Nuclear Medicine, School of Medicine, Shohada-e Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Mahasti Amoui
Department of Radiology and Medical Imaging Center, School of Medicine, Shohada-e Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Hamid R Haghighatkhah
Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Ahmad Shalbaf


نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/731
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Original Articles
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