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比较椭圆公式和基于体素分割法计算子宫肌瘤体积时的异常数据

Outlier data in volume calculations of uterine fibroids comparing ellipsoid formula and voxel-based segmentation.

作者信息

Bérczi Viktor, Turtóczki Kolos György, Fazekas Szuzina, Dolla-Takács Anna, Stollmayer Róbert, Kaposi Pál Novák, Kalina Ildikó, Budai Bettina Katalin

机构信息

Medical Imaging Centre, Semmelweis University, 2 Korányi Sándor St, Budapest, H-1083, Hungary.

出版信息

BMC Med Imaging. 2025 May 16;25(1):165. doi: 10.1186/s12880-025-01672-7.

DOI:10.1186/s12880-025-01672-7
PMID:40380106
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12082917/
Abstract

BACKGROUND

The ellipsoidal formula is the most common method used to determine the volume of fibroids on MR images. Labor-intensive manual segmentation provides the opportunity to measure the volume of a given lesion on a voxel basis. The aim of this study is to compare the volume of the uterine fibroid calculated using voxel-based segmentation and the ellipsoid formula.

METHODS

In this study, pretreatment MRI scans of patients who underwent uterine artery embolization due to symptomatic fibroids were retrospectively collected between 2016 and 2022. The volume data of the largest fibroids was determined by segmentation (group S) as the reference standard. In addition, the largest diameters of the fibroids in three planes (D1/D2/D3) were also measured and the volumes were also estimated by using the ellipsoidal formula (D1D2D3*0.5233) (group E). The interobserver reproducibility of the diameter measurements was tested. The volume values (median, IQR) were compared; in addition, the differences between the segmented and ellipsoidal volumes were recorded. Statistical analysis was performed using the Kruskal-Wallis test, Wilcoxon's two-sided signed rank test, intraclass correlation (ICC) analysis, and Bland-Altman plots.

RESULTS

Pretreatment MRI scans of 113 patients were identified. Fibroids where the interobserver difference of diameter-based ellipsoidal volumes reached 30% were excluded resulting in 99 patients in the final dataset. The volumes of group S and group E showed no significant differences with 134.1 (257.3) cm and 133.5 (269.1) cm, respectively, with an average difference of 3.47 cm (0.25%; p = 0.377). The agreement between the two methods was excellent (ICC = 0.979), without difference across fibroid locations. In 46 cases (46.5%), group S values were larger, and in 53 fibroids (53.5%), group E volume values were larger. However, volume difference was outside the ± 20% range in 21 cases (21.2%) and outside the ± 30% range in 10 cases (10.1%); the largest difference was approximately 56.5% (156.5 cm).

CONCLUSIONS

The ellipsoid formula-based and the voxel-based volume calculation showed no significant difference for the group as a whole. However, there was a difference of > 20% in 21.2% of cases and > 30% in 10.1% of cases. In the era of personalized medicine, it is not only the average difference between the two methods that need to be considered but also cases where there is a 20% or 30% difference in results should be highlighted, as these may change the treatment plan in individual cases. This methodology should also be tested for other tumor-type volume calculations.

摘要

背景

椭圆公式是在磁共振成像(MRI)上确定子宫肌瘤体积最常用的方法。劳动强度大的手动分割提供了在体素基础上测量给定病变体积的机会。本研究的目的是比较使用基于体素的分割法和椭圆公式计算的子宫肌瘤体积。

方法

在本研究中,回顾性收集了2016年至2022年间因症状性子宫肌瘤接受子宫动脉栓塞术患者的术前MRI扫描图像。将通过分割确定的最大肌瘤的体积数据(S组)作为参考标准。此外,还测量了肌瘤在三个平面上的最大直径(D1/D2/D3),并使用椭圆公式(D1D2D3*0.5233)估算体积(E组)。测试了观察者间直径测量的可重复性。比较体积值(中位数,四分位间距);此外,记录分割体积和椭圆体积之间的差异。使用Kruskal-Wallis检验、Wilcoxon双侧符号秩检验、组内相关(ICC)分析和Bland-Altman图进行统计分析。

结果

确定了113例患者的术前MRI扫描图像。排除观察者间基于直径的椭圆体积差异达到30%的肌瘤,最终数据集有99例患者。S组和E组的体积分别为134.1(257.3)cm³和133.5(269.1)cm³,无显著差异,平均差异为3.47 cm³(0.25%;p = 0.377)。两种方法之间的一致性极佳(ICC = 0.979),不同肌瘤位置无差异。在46例(46.5%)中,S组值更大,在53个肌瘤(53.5%)中,E组体积值更大。然而,21例(21.2%)的体积差异超出±20%范围,10例(10.1%)超出±30%范围;最大差异约为56.5%(156.5 cm³)。

结论

基于椭圆公式和基于体素的体积计算在总体上无显著差异。然而,21.2%的病例差异>20%,10.1%的病例差异>30%。在个性化医疗时代,不仅要考虑两种方法之间的平均差异,还应突出结果差异达20%或30%的病例,因为这些可能会改变个别病例的治疗方案。这种方法也应在其他肿瘤类型的体积计算中进行测试。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0e8/12082917/53a56e78ac8d/12880_2025_1672_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0e8/12082917/f578c003622c/12880_2025_1672_Fig4_HTML.jpg
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