Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation
Background: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis.Method...
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Frontiers Media S.A.
2019-06-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fendo.2019.00403/full |
| _version_ | 1811227733285404672 |
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| author | Yanghua Fan Min Hua Anna Mou Miaojing Wu Xiaohai Liu Xinjie Bao Renzhi Wang Ming Feng |
| author_facet | Yanghua Fan Min Hua Anna Mou Miaojing Wu Xiaohai Liu Xinjie Bao Renzhi Wang Ming Feng |
| author_sort | Yanghua Fan |
| collection | DOAJ |
| description | Background: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis.Methods: In total, 158 patients with acromegaly were randomized into the primary cohort (n = 100) and validation cohort (n = 58). The consistency of the tumor was classified as soft or firm according to the neurosurgeon's evaluation. The critical radiomics features were determined using the elastic net feature selection algorithm, and the radiomics signature was constructed. The most valuable clinical characteristics were then selected based on the multivariable logistic regression analysis. Next, a radiomics model was developed using the radiomics signature and clinical characteristics, and 30 patients with acromegaly were recruited for multicenter validation of the radiomics model. The model's performance was evaluated based on the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, and other associated classification measures. Its calibration, discriminating capacity, and clinical usefulness were also evaluated.Results: The radiomics signature established according to four radiomics features screened in the primary cohort exhibited excellent discriminatory capacity in the validation cohort. The radiomics model, which incorporated both the radiomics signature and Knosp grade, displayed favorable discriminatory capacity and calibration, and the AUC was 0.83 (95% confidence interval, 0.81–0.85) and 0.81 (95% confidence interval, 0.78–0.83) in the primary and validation cohorts, respectively. Furthermore, compared with the clinical characteristics, the as-constructed radiomics model is more effective in prediction of the tumor consistency in patients with acromegaly. Moreover, the multicenter validation and decision curve analysis suggested that the radiomics model was clinically useful.Conclusions: This radiomics model can assist neurosurgeons in predicting tumor consistency in patients with acromegaly before surgery and facilitates the determination of individualized therapeutic schemes. |
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| language | English |
| last_indexed | 2024-04-12T09:46:39Z |
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| series | Frontiers in Endocrinology |
| spelling | doaj.art-67297103b86f40458c63f45b307b5c1e2022-12-22T03:37:56ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922019-06-011010.3389/fendo.2019.00403467339Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective ValidationYanghua Fan0Min Hua1Anna Mou2Miaojing Wu3Xiaohai Liu4Xinjie Bao5Renzhi Wang6Ming Feng7Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaSchool of Electrical Engineering and Automation, East China Jiaotong University, Nanchang, ChinaDepartment of Radiology, Sichuan Provincial People's Hospital, Sichuan Academy of Medical Sciences, Chengdu, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaBackground: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis.Methods: In total, 158 patients with acromegaly were randomized into the primary cohort (n = 100) and validation cohort (n = 58). The consistency of the tumor was classified as soft or firm according to the neurosurgeon's evaluation. The critical radiomics features were determined using the elastic net feature selection algorithm, and the radiomics signature was constructed. The most valuable clinical characteristics were then selected based on the multivariable logistic regression analysis. Next, a radiomics model was developed using the radiomics signature and clinical characteristics, and 30 patients with acromegaly were recruited for multicenter validation of the radiomics model. The model's performance was evaluated based on the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, and other associated classification measures. Its calibration, discriminating capacity, and clinical usefulness were also evaluated.Results: The radiomics signature established according to four radiomics features screened in the primary cohort exhibited excellent discriminatory capacity in the validation cohort. The radiomics model, which incorporated both the radiomics signature and Knosp grade, displayed favorable discriminatory capacity and calibration, and the AUC was 0.83 (95% confidence interval, 0.81–0.85) and 0.81 (95% confidence interval, 0.78–0.83) in the primary and validation cohorts, respectively. Furthermore, compared with the clinical characteristics, the as-constructed radiomics model is more effective in prediction of the tumor consistency in patients with acromegaly. Moreover, the multicenter validation and decision curve analysis suggested that the radiomics model was clinically useful.Conclusions: This radiomics model can assist neurosurgeons in predicting tumor consistency in patients with acromegaly before surgery and facilitates the determination of individualized therapeutic schemes.https://www.frontiersin.org/article/10.3389/fendo.2019.00403/fullacromegalytumor consistencymagnetic resonance imagingradiomicsROC |
| spellingShingle | Yanghua Fan Min Hua Anna Mou Miaojing Wu Xiaohai Liu Xinjie Bao Renzhi Wang Ming Feng Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation Frontiers in Endocrinology acromegaly tumor consistency magnetic resonance imaging radiomics ROC |
| title | Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation |
| title_full | Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation |
| title_fullStr | Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation |
| title_full_unstemmed | Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation |
| title_short | Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation |
| title_sort | preoperative noninvasive radiomics approach predicts tumor consistency in patients with acromegaly development and multicenter prospective validation |
| topic | acromegaly tumor consistency magnetic resonance imaging radiomics ROC |
| url | https://www.frontiersin.org/article/10.3389/fendo.2019.00403/full |
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