Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer
Abstract Background This study aimed to develop a novel analytic approach based on a radiomics model derived from 68Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT for predicting intraprostatic lesions in patients with prostate cancer (PCa). Methods This retrospective study included consecuti...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-09-01
|
| Series: | EJNMMI Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13550-022-00936-5 |
| _version_ | 1828108480655917056 |
|---|---|
| author | Shiming Zang Shuyue Ai Rui Yang Pengjun Zhang Wenyu Wu Zhenyu Zhao Yudan Ni Qing Zhang Hongbin Sun Hongqian Guo Ruipeng Jia Feng Wang |
| author_facet | Shiming Zang Shuyue Ai Rui Yang Pengjun Zhang Wenyu Wu Zhenyu Zhao Yudan Ni Qing Zhang Hongbin Sun Hongqian Guo Ruipeng Jia Feng Wang |
| author_sort | Shiming Zang |
| collection | DOAJ |
| description | Abstract Background This study aimed to develop a novel analytic approach based on a radiomics model derived from 68Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT for predicting intraprostatic lesions in patients with prostate cancer (PCa). Methods This retrospective study included consecutive patients with or without PCa who underwent surgery or biopsy after 68Ga-PSMA-11 PET/CT. A total of 944 radiomics features were extracted from the images. A radiomics model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm with tenfold cross-validation in the training set. PET/CT images for the test set were reviewed by experienced nuclear medicine radiologists. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for the model and radiologists’ results. The AUCs were compared. Results The total of 125 patients (86 PCa, 39 benign prostate disease [BPD]) included 87 (61 PCa, 26 BPD) in the training set and 38 (61 PCa, 26 BPD) in the test set. Nine features were selected to construct the radiomics model. The model score differed between PCa and BPD in the training and test sets (both P < 0.001). In the test set, the radiomics model performed better than the radiologists’ assessment (AUC, 0.85 [95% confidence interval 0.73, 0.97] vs. 0.63 [0.47, 0.79]; P = 0.036) and showed higher sensitivity (model vs radiologists, 0.84 [0.63, 0.95] vs. 0.74 [0.53, 0.88]; P = 0.002). Conclusion Radiomics analysis based on 68Ga-PSMA-11 PET may non-invasively predict intraprostatic lesions in patients with PCa. |
| first_indexed | 2024-04-11T10:47:27Z |
| format | Article |
| id | doaj.art-3b2103da1092410597d89d5b07f83795 |
| institution | Directory Open Access Journal |
| issn | 2191-219X |
| language | English |
| last_indexed | 2024-04-11T10:47:27Z |
| publishDate | 2022-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EJNMMI Research |
| spelling | doaj.art-3b2103da1092410597d89d5b07f837952022-12-22T04:29:00ZengSpringerOpenEJNMMI Research2191-219X2022-09-011211810.1186/s13550-022-00936-5Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancerShiming Zang0Shuyue Ai1Rui Yang2Pengjun Zhang3Wenyu Wu4Zhenyu Zhao5Yudan Ni6Qing Zhang7Hongbin Sun8Hongqian Guo9Ruipeng Jia10Feng Wang11Department of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing UniversityDepartment of Urology, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing UniversityDepartment of Urology, Nanjing First Hospital, Nanjing Medical UniversityDepartment of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical UniversityAbstract Background This study aimed to develop a novel analytic approach based on a radiomics model derived from 68Ga-prostate-specific membrane antigen (PSMA)-11 PET/CT for predicting intraprostatic lesions in patients with prostate cancer (PCa). Methods This retrospective study included consecutive patients with or without PCa who underwent surgery or biopsy after 68Ga-PSMA-11 PET/CT. A total of 944 radiomics features were extracted from the images. A radiomics model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm with tenfold cross-validation in the training set. PET/CT images for the test set were reviewed by experienced nuclear medicine radiologists. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for the model and radiologists’ results. The AUCs were compared. Results The total of 125 patients (86 PCa, 39 benign prostate disease [BPD]) included 87 (61 PCa, 26 BPD) in the training set and 38 (61 PCa, 26 BPD) in the test set. Nine features were selected to construct the radiomics model. The model score differed between PCa and BPD in the training and test sets (both P < 0.001). In the test set, the radiomics model performed better than the radiologists’ assessment (AUC, 0.85 [95% confidence interval 0.73, 0.97] vs. 0.63 [0.47, 0.79]; P = 0.036) and showed higher sensitivity (model vs radiologists, 0.84 [0.63, 0.95] vs. 0.74 [0.53, 0.88]; P = 0.002). Conclusion Radiomics analysis based on 68Ga-PSMA-11 PET may non-invasively predict intraprostatic lesions in patients with PCa.https://doi.org/10.1186/s13550-022-00936-568Ga-PSMA-11PET/CTProstate cancerRadiomics |
| spellingShingle | Shiming Zang Shuyue Ai Rui Yang Pengjun Zhang Wenyu Wu Zhenyu Zhao Yudan Ni Qing Zhang Hongbin Sun Hongqian Guo Ruipeng Jia Feng Wang Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer EJNMMI Research 68Ga-PSMA-11 PET/CT Prostate cancer Radiomics |
| title | Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer |
| title_full | Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer |
| title_fullStr | Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer |
| title_full_unstemmed | Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer |
| title_short | Development and validation of 68Ga-PSMA-11 PET/CT-based radiomics model to detect primary prostate cancer |
| title_sort | development and validation of 68ga psma 11 pet ct based radiomics model to detect primary prostate cancer |
| topic | 68Ga-PSMA-11 PET/CT Prostate cancer Radiomics |
| url | https://doi.org/10.1186/s13550-022-00936-5 |
| work_keys_str_mv | AT shimingzang developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT shuyueai developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT ruiyang developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT pengjunzhang developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT wenyuwu developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT zhenyuzhao developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT yudanni developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT qingzhang developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT hongbinsun developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT hongqianguo developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT ruipengjia developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer AT fengwang developmentandvalidationof68gapsma11petctbasedradiomicsmodeltodetectprimaryprostatecancer |