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01-12-2024 | Trigeminal Neuralgia | Research

A nomogram based on radiomics and clinical information to predict prognosis in percutaneous balloon compression for the treatment of trigeminal neuralgia

Authors: Keyu Chen, Ji Wu, Hao Mei, Yuankun Cai, Songshan Chai, Lei shen, Jingyi Yang, Dongyuan Xu, Shiyu Zhao, Pucha Jiang, Jincao Chen, Nanxiang Xiong

Published in: Neurosurgical Review | Issue 1/2024

Abstract

Objective

To develop a clinical-radiomics nomogram based on clinical information and radiomics features to predict the prognosis of percutaneous balloon compression (PBC) for the treatment of trigeminal neuralgia (TN).

Methods

The retrospective study involved clinical data from 149 TN patients undergoing PBC at Zhongnan Hospital, Wuhan University from January 2018 to January 2022. The free open-source software 3D Slicer was used to extract all radiomic features from the intraoperative X-ray balloon region. The relationship between clinical information and TN prognosis was analyzed by univariate logistic analysis and multivariate logistic analysis. Using R software, the optimal radiomics features were selected using the least absolute shrinkage and selection operator (Lasso) algorithm. A prediction model was constructed based on the clinical information and radiomic features, and a nomogram was visualized. The performance of the clinical radiomics nomogram in predicting the prognosis of PBC in TN treatment was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

Results

A total of 149 patients were eventually included. The clinical factors influencing the prognosis of TN in univariate analysis were compression severity score and TN type. The lasso algorithm Max-Relevance and Min-Redundancy(mRMR) was used to select two predictors from 13 morphology-related radiomics features, including elongation and surface-volume ratio. A total of 4 predictors were used to construct a prediction model and nomogram. The AUC was 0.886(95% confidence interval (CI), 0.75 to 0.96), indicating that the model’s good predictive ability. DCA demonstrated the nomogram’s high clinical applicability.

Conclusion

Clinical-radiomics nomogram constructed by combining clinical information and morphology-related radiomics features have good potential in predicting the prognosis of TN for PBC treatment. However, this needs to be further studied and validated in several independent external patient populations.

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Title: A nomogram based on radiomics and clinical information to predict prognosis in percutaneous balloon compression for the treatment of trigeminal neuralgia
Authors: Keyu Chen
Ji Wu
Hao Mei
Yuankun Cai
Songshan Chai
Lei shen
Jingyi Yang
Dongyuan Xu
Shiyu Zhao
Pucha Jiang
Jincao Chen
Nanxiang Xiong
Publication date: 01-12-2024
Publisher: Springer Berlin Heidelberg
Keyword: Trigeminal Neuralgia
Published in: Neurosurgical Review / Issue 1/2024
Print ISSN: 0344-5607
Electronic ISSN: 1437-2320
DOI: https://doi.org/10.1007/s10143-024-02339-7

Keynote webinar | Spotlight on medication adherence

Springer Medicine

A nomogram based on radiomics and clinical information to predict prognosis in percutaneous balloon compression for the treatment of trigeminal neuralgia

Abstract

Objective

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objective

Methods

Results

Conclusion

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