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Comparisons among radiologist, MR findings and radiomics-clinical models in predicting placenta accreta spectrum
Changyi Guo1, Shunlin Guo2, Chao He3
1The First School of Clinical Medicine of Lanzhou University, Lanzhou, 730000, China.
Objective:
To assess and compare the diagnostic accuracy of radiologist, MR findings, and radiomics-clinical models in the diagnosis of placental implantation disorders.
Methods:
Retrospective collection of MR images from patients suspected of having placenta accreta spectrum (PAS) was conducted across three institutions: Institution I (n = 505), Institution II (n = 67), and Institution III (n = 58). Data from Institution I were utilized to form a training set, while data from Institutions II and III served as an external test set. Radiologist diagnosis was performed by radiologists of varying levels of experience. The interpretation of MR findings was conducted by two radiologists with 10-15 years of experience in pelvic MR diagnosis, following the guidelines for diagnosis. Radiomics analysis extracted features from sagittal T2-weighted images and combined them with prenatal clinical features to construct predictive models. These models were then evaluated for discrimination and calibration to assess their performance.
Results:
As measured by the area under the receiver operating characteristic curve (AUC), the diagnostic efficacy was 0.587 (0.542-0.630) for junior radiologists from Institution I, 0.568 (0.441-0.689) from Institution II, and 0.507 (0.373-0.641) from Institution III. The AUC was 0.623 (0.580-0.666) for senior radiologists from Institution I, 0.635 (0.508-0.749) from Institution II, and 0.632 (0.495-0.755) from Institution III. The diagnostic efficacy of MR findings was 0.648 (0.601-0.695) for Institution I, 0.569 (0.429-0.709) for Institution II, and 0.588 (0.442-0.735) for Institution III. The diagnostic efficacy of the radiomics-clinical model was significantly higher, with an AUC of 0.794 (0.754-0.833) for Institution I, 0.783 (0.664-0.903) for Institution II, and 0.816 (0.704-0.927) for Institution III. The diagnostic efficacy of the Fusion model was significantly higher, with an AUC of 0.867 (0.836-0.899) for Institution I, 0.849 (0.753-0.944) for Institution II, and 0.823 (0.708-0.939) for Institution III.
Conclusion:
The fusion models demonstrated superior diagnostic efficacy compared to radiologists, MR findings, and the radiomics-clinical models. Furthermore, the diagnostic accuracy of PAS was notably higher when utilizing the radiomics-clinical models than when relying solely on radiologist diagnosis or MR findings.
Advances In Knowledge:
Radiomics analysis substantially augments the diagnostic precision in PAS, providing a significant enhancement over conventional radiologist and MRI findings. The diagnostic efficacy of the fusion model is notably superior to that of individual diagnostic modalities.
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