肾脏的多参数功能性MRI -评估测试-重测重复性和不同的手动和自动图像分析策略的效果。

IF 1.3 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Rofo-fortschritte Auf Dem Gebiet Der Rontgenstrahlen Und Der Bildgebenden Verfahren Pub Date : 2025-01-10 DOI:10.1055/a-2480-4885
Cecilia Liang, Isabelle Loster, Stephan Ursprung, Aya Ghoul, Thomas Küstner, Brigitte Gückel, Bernd Kühn, Fritz Schick, Petros Martirosian, Ferdinand Seith
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引用次数: 0

摘要

多参数MRI是一种很有前途的无创肾脏结构和功能成像技术,在临床研究中越来越重要。尽管如此,对于分析获得的图像还没有标准化的建议,需要进一步评估目前推荐的MRI参数的准确性和可重复性。本研究的目的是评估使用不同图像分析策略的功能性肾脏MRI参数的重测重复性。10名健康志愿者接受了两次多参数肾脏MRI检查,包括动脉自旋标记(ASL)、体素内非相干运动(IVIM)扩散加权成像(DWI)、血氧依赖(BOLD)成像、T1和T2制图以及间隔一周的容量测定。通过人工器官分割、ROI分析和基于nnUNet框架的自动分割确定两个肾脏的定量结果。采用受试者内方差系数(wCV)和类内系数(ICC)计算各参数的重测重复性。使用骰子分数评估分割准确性和读者间一致性。结构组织参数(T1, T2)显示wCV(%)在4 ~ 11之间,ICC在0.2 ~ 0.8之间。功能参数(ASL、BOLD和DWI)显示wCV(%)在3 ~ 38之间,ICC在0.0 ~ 0.7之间。在ASL和IVIM灌注测量中观察到测试-重测扫描之间的最大差异(wCV: 17-37%)。与基于roi的图像分析相比,使用人工分割获得的皮质和髓质定量分析显示出更好的重复性。人工和自动分割全肾的重复性相当。所有MR参数均具有合理的重复性。与功能参数相比,结构磁共振参数具有更好的重复性。与人工分割相比,基于roi的图像分析的重复性总体较低。自动分割可以达到与人工分割相当的重复性和可接受的分割精度。·肾脏多参数MRI可实现合理的重测重复性。·与基于roi的分析相比,基于人工分割皮层和髓质的图像分析总体上具有更好的重复性。·肾脏体积自动分割与人工分割相比,在定量图像分析中具有相似的重复性。·Liang C, Loster I, Ursprung S等。肾脏的多参数功能性MRI -评估测试-重测重复性和不同的手动和自动图像分析策略的效果。Fortschr Röntgenstr 2024;DOI 10.1055 / - 2480 - 4885。
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Multiparametric functional MRI of the kidneys - evaluation of test-retest repeatability and effects of different manual and automatic image analysis strategies.

Multiparametric MRI is a promising technique for noninvasive structural and functional imaging of the kidneys that is gaining increasing importance in clinical research. Still, there are no standardized recommendations for analyzing the acquired images and there is a need to further evaluate the accuracy and repeatability of currently recommended MRI parameters. The aim of the study was to evaluate the test-retest repeatability of functional renal MRI parameters using different image analysis strategies.Ten healthy volunteers were examined twice with a multiparametric renal MRI protocol including arterial spin labeling (ASL), diffusion-weighted imaging (DWI) with intravoxel incoherent motion (IVIM), blood-oxygen-dependent (BOLD) imaging, T1 and T2 mapping, and volumetry with an interval of one week. The quantitative results of both kidneys were determined by manual organ segmentation, ROI analysis, and automatic segmentation based on the nnUNet framework. Test-retest repeatability of each parameter was computed using the within-subject coefficient of variance (wCV) and the intraclass coefficient (ICC). Segmentation accuracy and inter-reader agreement were evaluated using the dice score.Structural tissue parameters (T1, T2) showed wCV (%) between 4 and 11 and an ICC between 0.2 and 0.8. Functional parameters (ASL, BOLD and DWI) showed wCV (%) between 3 and 38 and an ICC between 0.0 and 0.7. The highest variances between test-retest scans were observed in perfusion measurements with ASL and IVIM (wCV: 17-37%). Quantitative analysis of the cortex and medulla showed a better repeatability when acquired using manual segmentation compared to ROI-based image analysis. Comparable repeatability was achieved with manual and automatic segmentation of the total kidney.Reasonable repeatability was achieved for all MR parameters. Structural MR parameters showed better repeatability compared to functional parameters. ROI-based image analysis showed overall lower repeatability compared to manual segmentation. Comparable repeatability to manual segmentation as well as acceptable segmentation accuracy could be achieved with automatic segmentation. · Reasonable test-retest repeatability can be achieved with multiparametric MRI of the kidneys.. · Image analysis based on manual segmentation of the cortex and medulla showed overall better repeatability compared to ROI-based analysis.. · Automatic segmentation of kidney volume showed similar repeatability of quantitative image analysis compared to manual segmentation.. · Liang C, Loster I, Ursprung S et al. Multiparametric functional MRI of the kidneys - evaluation of test-retest repeatability and effects of different manual and automatic image analysis strategies. Fortschr Röntgenstr 2024; DOI 10.1055/a-2480-4885.

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