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Prediction of placenta accreta spectrum using texture analysis on coronal and sagittal T2-weighted imaging

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Abstract

Purpose

To separately perform visual and texture analyses of the axial, coronal, and sagittal planes of T2-weighted images and identify the optimal method for differentiating between the normal placenta and placenta accreta spectrum (PAS).

Methods

Eighty consecutive patients (normal group, n = 50; PAS group, n = 30) underwent preoperative MRI. A scoring system (0–2) was used to evaluate the degree of abnormality observed in visual analysis (bulging, abnormal vascularity, T2 dark band, placental heterogeneity). The axial, coronal, and sagittal planes were manually segmented separately to obtain texture features, and seven combinations were obtained: axial; coronal; sagittal; axial and coronal; axial and sagittal; coronal and sagittal; and axial, coronal, and sagittal. Feature selection using the least absolute shrinkage and selection operator method and model construction using a support vector machine algorithm with k-fold cross-validation were performed. AUC was used to evaluate diagnostic performance.

Results

The AUC of visual analysis was 0.75. The model ‘coronal and sagittal’ had the highest AUC (0.98) amongst the seven combinations. The fivefold cross-validation for the model ‘coronal and sagittal’ showed AUCs of 0.85 and 0.97 in training and validation sets, respectively. The AUC of the model ‘coronal and sagittal’ for all subjects was significantly higher than that of visual analysis (0.98 vs. 0.75; p < 0.0001).

Conclusion

The model ‘coronal and sagittal’ can accurately differentiate between the normal placenta and PAS, with a significantly better diagnostic performance than visual analysis. Texture analysis is an optimal method for differentiating between the normal placenta and PAS.

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Abbreviations

PAS:

Placenta accreta spectrum

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Acknowledgements

This study has received funding by JSPS (Japan Society for the Promotion of Science) KAKENHI 18K07742.

Funding

JSPS KAKENHI 18K07742.

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Authors and Affiliations

  1. Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan

    Hainan Ren, Naoko Mori, Shunji Mugikura, Sakiko Kageyama & Kei Takase

  2. Division of Image Statistics, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan

    Shunji Mugikura

  3. Tohoku University School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan

    Hiroaki Shimizu

  4. Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574, Japan

    Masatoshi Saito

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  1. Hainan Ren
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Correspondence to Naoko Mori.

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This study was approved by the Institutional Review Board (IRB) of Tohoku University Hospital, Sendai, Japan.

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Ren, H., Mori, N., Mugikura, S. et al. Prediction of placenta accreta spectrum using texture analysis on coronal and sagittal T2-weighted imaging. Abdom Radiol 46, 5344–5352 (2021). https://doi.org/10.1007/s00261-021-03226-1

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