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基于磁共振成像的疑似胎盘植入谱系疾病孕妇轴向和矢状位影像组学研究

Magnetic Resonance Imaging-Based Radiomics of Axial and Sagittal Orientation in Pregnant Patients with Suspected Placenta Accreta Spectrum.

作者信息

Do Quyen N, Lewis Matthew A, Herrera Christina L, Owen David, Spong Catherine Y, Fei Baowei, Lenkinski Robert E, Twickler Diane M, Xi Yin

机构信息

Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA (Q.N.D., M.A.L., B.F., R.E.L., D.M.T., Y.X.).

Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA (Q.N.D., M.A.L., B.F., R.E.L., D.M.T., Y.X.).

出版信息

Acad Radiol. 2025 Mar;32(3):1500-1505. doi: 10.1016/j.acra.2024.09.045. Epub 2024 Oct 4.

Abstract

RATIONALE AND OBJECTIVES

Placenta accreta spectrum (PAS) is associated with significant morbidity and mortality. Current radiomic analysis of PAS magnetic resonance (MR) images is often performed on a single imaging plane. However, depending on the chosen imaging plane, radiomic features extracted from the same patient may vary due to the differing orientations and anatomical contexts, potentially leading to inconsistent results. In this study, we applied region of interest (ROI)-based radiomic analysis on axial and sagittal MR images in pregnant patients at high risk for PAS. Our objective was to compare MR textural features extracted from these imaging planes and to correlate these findings with surgical outcomes, aiming to enhance the accuracy of PAS diagnosis and treatment planning.

MATERIALS AND METHODS

This is a retrospective review of MR images of pregnancies with prenatally suspected PAS. Volumetric placental, uterus, and internal os of the cervix regions of interest (ROI) were manually segmented on axial and sagittal MR images for each patient. Radiomic features were extracted following the image biomarker standardization initiative guideline. Agreement in features extracted from axial and sagittal images were assessed using Spearman's rank correlation coefficient.

RESULTS

Of the 101 pregnant patients that met the study inclusion criteria, 65 underwent cesarean hysterectomy for PAS. 77 percent of the radiomics features had strong Spearman rank correlations (>0.8) between axial and sagittal images, indicating that these imaging planes provide similar radiomics information. The diagnostic performance of features extracted from axial and sagittal planes was quantified under the receiver operating characteristics curve (AUC). We found that axial and sagittal planes have similar performance for the prediction of hysterectomy. Shape elongation, Placental Location within the Uterus (PLU), and heterogeneity features were significant predictors for hysterectomy regardless of the imaging plane.

CONCLUSION

Our study found that radiomics features extracted from axial and sagittal MR image plane in the same patient have excellent agreement and strong correlation. We identified several features present in both axial and sagittal images that were predictive in detecting PAS-suspected patient who required hysterectomy. These features may represent the underlying placental pathophysiology.

摘要

原理与目的

胎盘植入谱系(PAS)与严重的发病率和死亡率相关。目前对PAS磁共振(MR)图像的放射组学分析通常在单个成像平面上进行。然而,根据所选的成像平面,从同一患者提取的放射组学特征可能因不同的方向和解剖背景而有所不同,这可能导致结果不一致。在本研究中,我们对PAS高危孕妇的轴向和矢状面MR图像应用了基于感兴趣区域(ROI)的放射组学分析。我们的目的是比较从这些成像平面提取的MR纹理特征,并将这些发现与手术结果相关联,旨在提高PAS诊断和治疗计划的准确性。

材料与方法

这是一项对产前疑似PAS的妊娠MR图像的回顾性研究。为每位患者在轴向和矢状面MR图像上手动分割胎盘、子宫和宫颈内口区域的体积感兴趣区(ROI)。按照图像生物标志物标准化倡议指南提取放射组学特征。使用Spearman等级相关系数评估从轴向和矢状面图像提取的特征的一致性。

结果

在符合研究纳入标准的101名孕妇中,65名因PAS接受了剖宫产子宫切除术。77%的放射组学特征在轴向和矢状面图像之间具有强Spearman等级相关性(>0.8),表明这些成像平面提供了相似的放射组学信息。在接受者操作特征曲线(AUC)下对从轴向和矢状面提取的特征的诊断性能进行了量化。我们发现轴向和矢状面在预测子宫切除术方面具有相似的性能。无论成像平面如何,形状伸长、胎盘在子宫内的位置(PLU)和异质性特征都是子宫切除术的重要预测因素。

结论

我们的研究发现,从同一患者的轴向和矢状面MR图像平面提取的放射组学特征具有极好的一致性和强相关性。我们确定了轴向和矢状面图像中均存在的几个特征,这些特征在检测需要子宫切除术的疑似PAS患者中具有预测性。这些特征可能代表潜在的胎盘病理生理学。

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本文引用的文献

1
Magnetic resonance imaging improves diagnosis of placenta accreta spectrum requiring hysterectomy compared to ultrasound.
Am J Obstet Gynecol MFM. 2024 Mar;6(3):101280. doi: 10.1016/j.ajogmf.2024.101280. Epub 2024 Jan 10.
3
Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.
J Magn Reson Imaging. 2023 May;57(5):1533-1540. doi: 10.1002/jmri.28403. Epub 2022 Aug 16.
4
CascadeNet for hysterectomy prediction in pregnant women due to placenta accreta spectrum.
Proc SPIE Int Soc Opt Eng. 2022 Feb-Mar;12032. doi: 10.1117/12.2611580. Epub 2022 Apr 4.
5
Automatic Segmentation of Uterine Cavity and Placenta on MR Images Using Deep Learning.
Proc SPIE Int Soc Opt Eng. 2022 Feb-Mar;12036. doi: 10.1117/12.2613286. Epub 2022 Apr 4.
9
Deep learning and radiomics analysis for prediction of placenta invasion based on T2WI.
Math Biosci Eng. 2021 Jul 16;18(5):6198-6215. doi: 10.3934/mbe.2021310.
10
Prediction of placenta accreta spectrum using texture analysis on coronal and sagittal T2-weighted imaging.
Abdom Radiol (NY). 2021 Nov;46(11):5344-5352. doi: 10.1007/s00261-021-03226-1. Epub 2021 Jul 30.

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