Purposes
To investigate the value of nomograms based on clinical prognostic factors (CPF),
intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and MRI-derived
radiomics in predicting recurrence and disease-free survival (DFS) after concurrent
chemoradiotherapy (CCRT) for locally advanced cervical cancer (LACC).
Methods
Retrospective analysis of data from 115 patients with ⅠB-ⅣA cervical cancer who underwent
CCRT and had been followed up consistently. All patients were randomized 2:1 into
training and validation groups. Pre-treatment IVIM-DWI parameters (ADC-value, D-value,
D*-value and f-value) and pre- and post-treatment three-dimensional radiomics parameters
(from axial T2WI) of primary lesions were measured. The LASSO algorithm and Logistic regression
analysis were used to filter texture features and calculate radiomics score (Rad-score).
Multivariate Logistic and Cox regression analysis was used to construct nomograms
to predict recurrence and DFS for patients with LACC after CCRT respectively, with
internal and external validation.
Results
External beam radiotherapy dose, f-value, pre-treatment and post-treatment Rad-score
were independent prognostic factors for recurrence and DFS in patients with cervical
cancer, forming Model1 and Model2, with OR values of 0.480, 1.318, 3.071, 3.200 and
HR values of 0.322, 3.372, 5.138, 7.204. The area under the curve (AUC) of Model1
for predicting recurrence of cervical cancer was 0.977, with internal and external
validation C-indexes of 0.977 and 0.962. The AUC for Model2 predicting disease-free
survival (DFS) at 1, 3, and 5 years was 0.895, 0.888 and 0.916 respectively, with
internal and external C-indexes of 0.860 and 0.892. The decision curves analysis and
clinical impact curves further indicate the high predictive efficiency and stability
of nomograms.
Conclusion
The nomograms based on clinical, IVIM-DWI and radiomics parameters have high clinical
value in predicting recurrence and DFS of patients with LACC after CCRT and can provide
a reference for prognostic assessment and individualized treatment of cervical cancer
patients.
Key Words
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Article info
Publication history
Published online: August 30, 2022
Accepted:
August 1,
2022
Received in revised form:
July 31,
2022
Received:
July 7,
2022
Identification
Copyright
© 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
