MRI of the Placenta Accreta Spectrum (PAS) Disorder: Radiomics Analysis Correlates With Surgical and Pathological Outcome
Abstract
Background: Placenta accreta spectrum (PAS) in women with previous cesarean delivery has become increasingly prevalent. Depending on the severity, patient management may involve cesarean hysterectomy. Purpose: To investigate textural analyses as the radiomics in MRI of the placenta in predicting the PAS requiring cesarean hysterectomy in a high‐risk population. Study Type: Retrospective. Population: Sixty‐two women with prior cesarean delivery referred for MRI because of sonographic suspicion for PAS. Field Strength/Sequence: 1.5T with T 1 W, T 2 W, and diffusion‐weighted imaging (DWI). Assessment: Two reviewers independently evaluated MR images based on five established PAS variables. Placental regions of interest (ROIs) were generated on T 2 W, DWI, and an apparent diffusion coefficient (ADC) map, based on definitions of areas of placenta in proximity to and remote from previous surgical incision sites. Statistical Tests: Reader agreement was assessed by simple kappa and prevalence adjusted bias adjusted kappa (PABAK). T‐tests and chi‐square analyses between the primary outcome (hysterectomy vs. no hysterectomy) were performed. Thirteen Haralick texture features calculated from gray‐level co‐occurrence matrixes were extracted from manually drawn placental ROIs within each of three MR acquisitions. Univariate and multivariable logistic regression were used to assess the association with cesarean hysterectomy. Results: Of 62 pregnancies at risk for PAS, 40 required cesarean hysterectomy (65%), with excellent correlation between need for hysterectomy and pathology confirmation of PAS in the hysterectomy specimen [κ = 0.82 (0.62, 1)]. Reader agreement was fair to moderate. Of the 13 Haralick variables within each of three acquisition groups, significant differences (P < 0.05) were seen in 22 of 39 parameters comparing placental ROIs in proximity to incision scar(s) to those ROIs remote from scar. A stepwise selection algorithm indicated that the combination of T 2 W Fcm.sum.var, ADC Fcm.diff.entr, and DWI Fcm.energy gave the highest leave‐one‐out‐AUC of 0.80 (0.68, 0.91). Data Conclusion: Assessment of PAS severity is subjective and dependent on radiologist expertise. We identified textural features on placental MR images in the region of the prior uterine scar that differentiated pregnancies requiring cesarean hysterectomy based on clinical suspicion of PAS from those that did not, suggesting predictive capabilities of these objective radiomics features. Level of Evidence: 3 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:936–946.
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Previous work showed that ROIs of the placenta proximal and remote to the prior Caesarean section scar had significant differences in radiomic feature distribution, associated with undergoing caesarean hysterectomy for PAS.
“The segmentation protocol was informed by a previous work where ROIs of the placenta proximal and remote to the prior Caesarean section scar showed significant differences in the distribution of radiomic features, which were associated with undergoing caesarean hysterectomy for PAS [13].”
From Radiomics-based prediction of FIGO grade for placenta accreta spectrum (2023) · cites this paper as [13]
Several studies have applied radiomics to MR images in PAS and found radiomic features useful in aiding diagnosis and predicting clinical outcomes such as massive obstetric haemorrhage.
“Several studies have applied radiomics to MR images in PAS and found radiomic features were useful in aiding diagnosis and predicting clinical outcomes such as massive obstetric haemorrhage [12, 13].”
From Radiomics-based prediction of FIGO grade for placenta accreta spectrum (2023) · cites this paper as [13]
Previous studies have used radiomic features to predict clinical outcomes such as undergoing caesarean hysterectomy and blood loss.
“Previous studies have used radiomic features to predict clinical outcomes such as undergoing caesarean hysterectomy and blood loss [13, 37]”
From Radiomics-based prediction of FIGO grade for placenta accreta spectrum (2023) · cites this paper as [13]
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References 37 · Cited by 61
- Authors
- Do, Q. N., Lewis, M. A., Xi, Y., Madhuranthakam, A. J., Happe, S. K., Dashe, J. S., Lenkinski, R. E., Khan, A., & Twickler, D. M.
- Affiliations
- The University of Texas Southwestern Medical Center (US)
- Corresponding author
- Twickler, Diane M.
- ORCID
- Venue
- Journal of Magnetic Resonance Imaging
- Publisher
- Wiley
- Published
- 2019-08-09
- Volume
- 51
- Issue
- 3
- Pages
- 936-946
- ISSN
- 1053-1807 (ISSN-L)
- 1522-2586
- OpenAlex
- W2968662911
- Cited by
- 61
- References
- 37
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 8 · 2023: 15 · 2022: 11 · 2021: 10 · 2020: 1 · 2019: 2
- FWCI
- 6.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Magnetic Resonance Imaging (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Maternal and fetal healthcare
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Health Sciences › Medicine › Obstetrics and Gynecology › Uterine Myomas and Treatments
- Keywords
- placenta accreta spectrum, cesarean hysterectomy, radiomics, texture analysis, GLCM texture features, gray level co-occurrence matrix, diffusion-weighted imaging, apparent diffusion coefficient, previous cesarean section, uterine scar, placental MRI, surgical outcome prediction, reader agreement, high-risk pregnancy
- MeSH terms
- Female, Humans, Hysterectomy, Magnetic Resonance Imaging, Placenta Accreta, Pregnancy, Retrospective Studies, Diffusion Magnetic Resonance Imaging
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