Purpose
To investigate the noninvasive prediction model for new fractures after percutaneous
vertebral augmentation (PVA) based on radiomics signature and clinical parameters.
Methods
Data from patients who were diagnosed with osteoporotic vertebral compression fracture
(OVCF) and treated with PVA in our hospital between May 2014 and April 2019 were retrospectively
analyzed. Radiomics features were extracted from T1-weighted magnetic resonance imaging
(MRI) of the T11-L5 segments taken before PVA. Different radiomics models was developed
by using linear discriminant analysis (LDA), multilayer perceptron (MLP), and stochastic
gradient descent (SGD) classifiers. A nomogram was constructed by integrating clinical
parameters and Radscore that calculated by the best radiomics model. The model performance
was quantified in terms of discrimination, calibration and clinical usefulness.
Result
Four clinical parameters and 16 selected radiomics features were used for model development.
The clinical model showed poor discrimination capability with area under the curves
(AUCs) yielding of 0.522 in the training dataset and 0.517 in the validation dataset.
The LDA, MLP and SGD classifier-based radiomics model had achieved AUCs of 0.793,
0.810, and 0.797 in the training dataset, and 0.719, 0.704, and 0.725 in the validation
dataset, respectively. The nomogram showed the best performance with AUCs achieving
0.810 and 0.754 in the training and validation datasets, respectively. The decision
curve analysis demonstrated the net benefit of the nomogram was higher than that of
other models.
Conclusion
Our findings indicate that combining clinical features with radiomics features from
pre-augmentation T1-weighted MRI can be used to develop a nomogram that can predict
new fractures in patients after PVA.
Key Words
Abbreviations:
AUC (area under the receiver operating characteristic curves), BMI (body mass index), BMD (bone mineral density), DXA (Dual X-ray absorptiometry), LDA (linear discriminant analysis), MLP (multilayer perceptron), MRI (magnetic resonance imaging), NSF (new symptomatic fracture), OVCF (osteoporotic vertebral compression fracture), PKP (percutaneous kyphoplasty), PVP (percutaneous vertebroplasty), PVA (percutaneous vertebral augmentation), QCT (quantitative computed tomography), ROI (region of interest), SGD (stochastic gradient descent), TBS (trabecular bone score)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: July 29, 2022
Accepted:
June 26,
2022
Received in revised form:
June 25,
2022
Received:
April 6,
2022
Identification
Copyright
© 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.