Suppr超能文献

基于单序列快速自旋回波 T2 加权 Dixon 序列的定性及定量分析对良恶性椎体压缩性骨折的鉴别诊断。

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence.

机构信息

Department of Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.

Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.

出版信息

Eur Radiol. 2021 Dec;31(12):9418-9427. doi: 10.1007/s00330-021-07947-1. Epub 2021 May 26.

Abstract

OBJECTIVES

To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple readers and different quantitative methods.

METHODS

From July 2014 to June 2020, 95 consecutive patients with spine MRI performed prior to cementoplasty for acute VCFs were retrospectively included. VCFs were categorized as benign (n = 63, mean age = 76 ± 12 years) or malignant (n = 32, mean age = 63 ± 12 years) with a best valuable comparator as a reference. Qualitative analysis was independently performed by four radiologists by categorizing each VCF as either benign or malignant using only the image sets provided by FSE T2-weighted Dixon sequences. Quantitative analysis was performed using two different regions of interest (ROI1-2) and three methods (signal drop, fat fraction (FF) from ROIs, FF maps). Diagnostic performance was compared using ROC curves analyses. Interobserver agreement was assessed using kappa statistics and intraclass correlation coefficients (ICC).

RESULTS

The qualitative diagnostic performance ranged from area under the curve (AUC) = 0.97 (95% CI: 0.91-1.00) to AUC = 0.99 (95% CI: 0.95-1.0). The quantitative diagnostic performance ranged from AUC = 0.82 (95% CI: 0.73-0.89) to AUC = 0.97 (95% CI: 0.91-0.99). Pairwise comparisons showed no statistical difference in diagnostic performance (all p > 0.0013, Bonferroni-corrected p < 0.0011). All five cases with disagreement among the readers were correctly diagnosed at quantitative analysis using ROI2. Interobserver agreement was excellent for both qualitative and quantitative analyses.

CONCLUSIONS

A single FSE T2-weighted Dixon sequence can be used to differentiate benign and malignant VCF with high diagnostic performance using both qualitative and quantitative analyses, which can provide complementary information.

KEY POINTS

• Qualitative analysis of a single FSE T2-weighted Dixon sequence yields high diagnostic performance and excellent observer agreement for differentiating benign and malignant compression fractures. • The same FSE T2-weighted Dixon sequence allows quantitative assessment with high diagnostic performance. • Quantitative data can readily be extracted from the FSE T2-weighted Dixon sequence and may provide complementary information to the qualitative analysis, which may be useful in doubtful cases.

摘要

目的

使用多位读者和不同的定量方法,确定并比较单张矢状位快速自旋回波(FSE)T2 加权 Dixon 序列在区分良性和恶性椎体压缩性骨折(VCF)中的定性和定量诊断性能。

方法

本回顾性研究纳入了 2014 年 7 月至 2020 年 6 月期间因急性 VCF 而行骨水泥成形术的 95 例连续患者。VCF 分为良性(n=63,平均年龄 76±12 岁)或恶性(n=32,平均年龄 63±12 岁),最佳有价值的比较器作为参考。定性分析由四位放射科医生独立进行,他们仅使用 FSE T2 加权 Dixon 序列提供的图像集,将每个 VCF 分类为良性或恶性。定量分析使用两个不同的感兴趣区(ROI1-2)和三种方法(信号下降、来自 ROI 的脂肪分数(FF)、FF 图)进行。使用 ROC 曲线分析比较诊断性能。使用kappa 统计和组内相关系数(ICC)评估观察者间一致性。

结果

定性诊断性能的曲线下面积(AUC)范围为 0.97(95%CI:0.91-1.00)至 AUC = 0.99(95%CI:0.95-1.0)。定量诊断性能的 AUC 范围为 0.82(95%CI:0.73-0.89)至 AUC = 0.97(95%CI:0.91-0.99)。两两比较显示,所有定量分析方法的诊断性能均无统计学差异(所有 p > 0.0013,Bonferroni 校正 p < 0.0011)。读者间存在 5 例不一致的病例,在使用 ROI2 进行定量分析时均得到正确诊断。定性和定量分析的观察者间一致性均为优秀。

结论

单张 FSE T2 加权 Dixon 序列可用于区分良性和恶性 VCF,定性和定量分析均具有较高的诊断性能,可提供互补信息。

关键点

  1. 单张 FSE T2 加权 Dixon 序列的定性分析在区分良性和恶性压缩性骨折方面具有较高的诊断性能和出色的观察者间一致性。

  2. 相同的 FSE T2 加权 Dixon 序列可进行定量评估,具有较高的诊断性能。

  3. 定量数据可从 FSE T2 加权 Dixon 序列中轻松提取,并可为定性分析提供补充信息,在有疑问的情况下可能有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee1c/8589814/08239e02c7ab/330_2021_7947_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验