Preoperative Prediction of New Vertebral Fractures after Vertebral Augmentation with a Radiomics Nomogram

被引:2
|
作者
Jiang, Yang [1 ]
Zhang, Wei [1 ]
Huang, Shihao [2 ]
Huang, Qing [3 ]
Ye, Haoyi [4 ]
Zeng, Yurong [5 ]
Hua, Xin [6 ]
Cai, Jinhui [1 ]
Liu, Zhifeng [4 ]
Liu, Qingyu [1 ]
机构
[1] Sun Yat sen Univ, Affiliated Hosp 7, Dept Radiol, Shenzhen 518000, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 5, Dept Radiol, Zhuhai 519000, Peoples R China
[3] Sun Yat sen Univ, Affiliated Hosp 7, Dept Endocrinol, Shenzhen 518000, Peoples R China
[4] Guangzhou Med Univ, Affiliated Hosp 4, Dept Radiol, Guangzhou, Peoples R China
[5] Huizhou Cent Peoples Hosp, Dept Radiol, Huizhou 516000, Peoples R China
[6] Wenzhou Med Univ, Affiliated Hosp 1, Dept Neurol, Wenzhou 325000, Peoples R China
关键词
osteoporosis; vertebral fracture; vertebral augmentation; prediction; radiomics; BONE-MINERAL DENSITY; COMPRESSION FRACTURES; RISK-FACTORS; MANAGEMENT; SPINE;
D O I
10.3390/diagnostics13223459
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The occurrence of new vertebral fractures (NVFs) after vertebral augmentation (VA) procedures is common in patients with osteoporotic vertebral compression fractures (OVCFs), leading to painful experiences and financial burdens. We aim to develop a radiomics nomogram for the preoperative prediction of NVFs after VA. Data from center 1 (training set: n = 153; internal validation set: n = 66) and center 2 (external validation set: n = 44) were retrospectively collected. Radiomics features were extracted from MRI images and radiomics scores (radscores) were constructed for each level-specific vertebra based on least absolute shrinkage and selection operator (LASSO). The radiomics nomogram, integrating radiomics signature with presence of intravertebral cleft and number of previous vertebral fractures, was developed by multivariable logistic regression analysis. The predictive performance of the vertebrae was level-specific based on radscores and was generally superior to clinical variables. RadscoreL2 had the optimal discrimination (AUC >= 0.751). The nomogram provided good predictive performance (AUC >= 0.834), favorable calibration, and large clinical net benefits in each set. It was used successfully to categorize patients into high- or low-risk subgroups. As a noninvasive preoperative prediction tool, the MRI-based radiomics nomogram holds great promise for individualized prediction of NVFs following VA.
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页数:12
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