Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas
ObjectivesThe aim of this study was to establish and validate a MRI-based radiomics nomogram to predict progression-free survival (PFS) of clival chordoma.MethodsA total of 174 patients were enrolled in the study (train cohort: 121 cases, test cohort: 53 cases). Radiomic features were extracted from...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-12-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.996262/full |
| _version_ | 1811184323969155072 |
|---|---|
| author | Yixuan Zhai Jiwei Bai Yake Xue Mingxuan Li Wenbin Mao Xuezhi Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang |
| author_facet | Yixuan Zhai Jiwei Bai Yake Xue Mingxuan Li Wenbin Mao Xuezhi Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang |
| author_sort | Yixuan Zhai |
| collection | DOAJ |
| description | ObjectivesThe aim of this study was to establish and validate a MRI-based radiomics nomogram to predict progression-free survival (PFS) of clival chordoma.MethodsA total of 174 patients were enrolled in the study (train cohort: 121 cases, test cohort: 53 cases). Radiomic features were extracted from multiparametric MRIs. Intraclass correlation coefficient analysis and a Lasso and Elastic-Net regularized generalized linear model were used for feature selection. Then, a nomogram was established via univariate and multivariate Cox regression analysis in the train cohort. The performance of this nomogram was assessed by area under curve (AUC) and calibration curve.ResultsA total of 3318 radiomic features were extracted from each patient, of which 2563 radiomic features were stable features. After feature selection, seven radiomic features were selected. Cox regression analysis revealed that 2 clinical factors (degree of resection, and presence or absence of primary chordoma) and 4 radiomic features were independent prognostic factors. The AUC of the established nomogram was 0.747, 0.807, and 0.904 for PFS prediction at 1, 3, and 5 years in the train cohort, respectively, compared with 0.582, 0.852, and 0.914 in the test cohort. Calibration and risk score stratified survival curves were satisfactory in the train and test cohort.ConclusionsThe presented nomogram demonstrated a favorable predictive accuracy of PFS, which provided a novel tool to predict prognosis and risk stratification. Our results suggest that radiomic analysis can effectively help neurosurgeons perform individualized evaluations of patients with clival chordomas. |
| first_indexed | 2024-04-11T13:11:30Z |
| format | Article |
| id | doaj.art-525f514a589740cba4db0db17065ea41 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-11T13:11:30Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-525f514a589740cba4db0db17065ea412022-12-22T04:22:35ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-12-011210.3389/fonc.2022.996262996262Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomasYixuan Zhai0Jiwei Bai1Yake Xue2Mingxuan Li3Wenbin Mao4Xuezhi Zhang5Yazhuo Zhang6Yazhuo Zhang7Yazhuo Zhang8Yazhuo Zhang9Beijing Neurosurgical Institute, Capital Medical University, Beijing, ChinaBeijing Neurosurgical Institute, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaBeijing Neurosurgical Institute, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaBeijing Neurosurgical Institute, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaCenter of Brain Tumor, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing, ChinaObjectivesThe aim of this study was to establish and validate a MRI-based radiomics nomogram to predict progression-free survival (PFS) of clival chordoma.MethodsA total of 174 patients were enrolled in the study (train cohort: 121 cases, test cohort: 53 cases). Radiomic features were extracted from multiparametric MRIs. Intraclass correlation coefficient analysis and a Lasso and Elastic-Net regularized generalized linear model were used for feature selection. Then, a nomogram was established via univariate and multivariate Cox regression analysis in the train cohort. The performance of this nomogram was assessed by area under curve (AUC) and calibration curve.ResultsA total of 3318 radiomic features were extracted from each patient, of which 2563 radiomic features were stable features. After feature selection, seven radiomic features were selected. Cox regression analysis revealed that 2 clinical factors (degree of resection, and presence or absence of primary chordoma) and 4 radiomic features were independent prognostic factors. The AUC of the established nomogram was 0.747, 0.807, and 0.904 for PFS prediction at 1, 3, and 5 years in the train cohort, respectively, compared with 0.582, 0.852, and 0.914 in the test cohort. Calibration and risk score stratified survival curves were satisfactory in the train and test cohort.ConclusionsThe presented nomogram demonstrated a favorable predictive accuracy of PFS, which provided a novel tool to predict prognosis and risk stratification. Our results suggest that radiomic analysis can effectively help neurosurgeons perform individualized evaluations of patients with clival chordomas.https://www.frontiersin.org/articles/10.3389/fonc.2022.996262/fullradiomicsnomogramchordomaprognosisprediction |
| spellingShingle | Yixuan Zhai Jiwei Bai Yake Xue Mingxuan Li Wenbin Mao Xuezhi Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang Yazhuo Zhang Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas Frontiers in Oncology radiomics nomogram chordoma prognosis prediction |
| title | Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas |
| title_full | Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas |
| title_fullStr | Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas |
| title_full_unstemmed | Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas |
| title_short | Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas |
| title_sort | development and validation of a preoperative mri based radiomics nomogram to predict progression free survival in patients with clival chordomas |
| topic | radiomics nomogram chordoma prognosis prediction |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.996262/full |
| work_keys_str_mv | AT yixuanzhai developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT jiweibai developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT yakexue developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT mingxuanli developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT wenbinmao developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT xuezhizhang developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT yazhuozhang developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT yazhuozhang developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT yazhuozhang developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas AT yazhuozhang developmentandvalidationofapreoperativemribasedradiomicsnomogramtopredictprogressionfreesurvivalinpatientswithclivalchordomas |