A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer
Objective: To explore the potential imaging biomarkers for predicting Traditional Chinese medicine (TCM) deficiency and excess syndrome in prostate cancer (PCa) patients by radiomics approach based on MR imaging. Methods: A total of 121 PCa patients from 2 centers were divided into 1 training cohort...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023104506 |
| _version_ | 1797383863500013568 |
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| author | Yongsheng Zhang Huan Yang Zhiping Li Chen Gao Yin Chen Yasheng Huang Xianjie Yue Chang Shu Yuguo Wei Feng Cui Maosheng Xu |
| author_facet | Yongsheng Zhang Huan Yang Zhiping Li Chen Gao Yin Chen Yasheng Huang Xianjie Yue Chang Shu Yuguo Wei Feng Cui Maosheng Xu |
| author_sort | Yongsheng Zhang |
| collection | DOAJ |
| description | Objective: To explore the potential imaging biomarkers for predicting Traditional Chinese medicine (TCM) deficiency and excess syndrome in prostate cancer (PCa) patients by radiomics approach based on MR imaging. Methods: A total of 121 PCa patients from 2 centers were divided into 1 training cohort with 84 PCa patients and 1 validation cohort with 37 PCa patients. The PCa patients were divided into deficiency and excess syndrome group according to TCM syndrome differentiation. Radiomic features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging and apparent diffusion coefficient images originated from diffusion-weighted imaging. A radiomic signature was constructed after reduction of dimension in training group by the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator. The performance of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results: The radiomic scores of PCa with TCM excess syndrome group were statistically higher than those of PCa with TCM deficiency syndrome group among T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models. The area under ROC curves for T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models were 0.824, 0.824, 0.847 in the training cohort and 0.759, 0.750, 0.809 in the validation cohort, respectively. The apparent diffusion coefficient imaging model had the best discrimination in separating patients with TCM excess syndrome and deficiency syndrome, and its accuracy was 0.788, 0.778 in the training and validation cohort, respectively. The calibration curve demonstrated that there was a high consistency between the prediction of radiomic scores and the actual classification of TCM's deficiency and excess syndrome in PCa. Conclusion: The radiomic signature based on MR imaging can be performed as a non-invasive, potential approach to discriminate TCM deficiency syndrome from excess syndrome in PCa, in which apparent diffusion coefficient imaging model has the best diagnostic efficiency. |
| first_indexed | 2024-03-08T21:27:08Z |
| format | Article |
| id | doaj.art-520a0633171a4512ac49dd6a34fcd3ed |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-08T21:27:08Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-520a0633171a4512ac49dd6a34fcd3ed2023-12-21T07:35:58ZengElsevierHeliyon2405-84402023-12-01912e23242A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancerYongsheng Zhang0Huan Yang1Zhiping Li2Chen Gao3Yin Chen4Yasheng Huang5Xianjie Yue6Chang Shu7Yuguo Wei8Feng Cui9Maosheng Xu10Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Acupuncture and Moxibustion, Community Health Service of Xiaohehushu District, Hangzhou, 310005, ChinaDepartment of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, 310006, ChinaDepartment of Urology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Urology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Pathology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaAdvanced Analytics, Global Medical Service, GE Healthcare, Hangzhou, 310007, ChinaDepartment of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310007, ChinaDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, 310006, China; Corresponding authors.Objective: To explore the potential imaging biomarkers for predicting Traditional Chinese medicine (TCM) deficiency and excess syndrome in prostate cancer (PCa) patients by radiomics approach based on MR imaging. Methods: A total of 121 PCa patients from 2 centers were divided into 1 training cohort with 84 PCa patients and 1 validation cohort with 37 PCa patients. The PCa patients were divided into deficiency and excess syndrome group according to TCM syndrome differentiation. Radiomic features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging and apparent diffusion coefficient images originated from diffusion-weighted imaging. A radiomic signature was constructed after reduction of dimension in training group by the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator. The performance of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results: The radiomic scores of PCa with TCM excess syndrome group were statistically higher than those of PCa with TCM deficiency syndrome group among T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models. The area under ROC curves for T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models were 0.824, 0.824, 0.847 in the training cohort and 0.759, 0.750, 0.809 in the validation cohort, respectively. The apparent diffusion coefficient imaging model had the best discrimination in separating patients with TCM excess syndrome and deficiency syndrome, and its accuracy was 0.788, 0.778 in the training and validation cohort, respectively. The calibration curve demonstrated that there was a high consistency between the prediction of radiomic scores and the actual classification of TCM's deficiency and excess syndrome in PCa. Conclusion: The radiomic signature based on MR imaging can be performed as a non-invasive, potential approach to discriminate TCM deficiency syndrome from excess syndrome in PCa, in which apparent diffusion coefficient imaging model has the best diagnostic efficiency.http://www.sciencedirect.com/science/article/pii/S2405844023104506Prostate cancerTCM syndromeMagnetic resonance imagingRadiomic |
| spellingShingle | Yongsheng Zhang Huan Yang Zhiping Li Chen Gao Yin Chen Yasheng Huang Xianjie Yue Chang Shu Yuguo Wei Feng Cui Maosheng Xu A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer Heliyon Prostate cancer TCM syndrome Magnetic resonance imaging Radiomic |
| title | A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer |
| title_full | A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer |
| title_fullStr | A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer |
| title_full_unstemmed | A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer |
| title_short | A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer |
| title_sort | radiomics approach based on mr imaging for classification of deficiency and excess syndrome of traditional chinese medicine in prostate cancer |
| topic | Prostate cancer TCM syndrome Magnetic resonance imaging Radiomic |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023104506 |
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