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基于优化阈值选择的磁化准备快速采集梯度回波(MP-RAGE)序列半自动检测和定量颈动脉斑块内出血

Semi-automatic carotid intraplaque hemorrhage detection and quantification on Magnetization-Prepared Rapid Acquisition Gradient-Echo (MP-RAGE) with optimized threshold selection.

作者信息

Liu Jin, Balu Niranjan, Hippe Daniel S, Ferguson Marina S, Martinez-Malo Vanesa, DeMarco J Kevin, Zhu David C, Ota Hideki, Sun Jie, Xu Dongxiang, Kerwin William S, Hatsukami Thomas S, Yuan Chun

机构信息

University of Washington, Seattle, WA, USA.

Walter Reed National Military Medical Center, Bethesda, MD, USA.

出版信息

J Cardiovasc Magn Reson. 2016 Jul 16;18(1):41. doi: 10.1186/s12968-016-0260-3.

DOI:10.1186/s12968-016-0260-3
PMID:27430263
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4950626/
Abstract

BACKGROUND

Intraplaque hemorrhage (IPH) is associated with atherosclerosis progression and subsequent cardiovascular events. We sought to develop a semi-automatic method with an optimized threshold for carotid IPH detection and quantification on MP-RAGE images using matched histology as the gold standard.

METHODS

Fourteen patients scheduled for carotid endarterectomy underwent 3D MP-RAGE cardiovascular magnetic resonance (CMR) preoperatively. Presence and area of IPH were recorded using histology. Presence and area of IPH were also recorded on CMR based on intensity thresholding using three references for intensity normalization: the sternocleidomastoid muscle (SCM), the adjacent muscle and the automatically generated local median value. The optimized intensity thresholds were obtained by maximizing the Youden's index for IPH detection. Using leave-one-out cross validation, the sensitivity and specificity for IPH detection based on our proposed semi-automatic method and the agreement with histology on IPH area quantification were evaluated.

RESULTS

The optimized intensity thresholds for IPH detection were 1.0 times the SCM intensity, 1.6 times the adjacent muscle intensity and 2.2 times the median intensity. Using the semi-automatic method with the optimized intensity threshold, the following IPH detection and quantification performance was obtained: sensitivities up to 59, 68 and 80 %; specificities up to 85, 74 and 79 %; Pearson's correlation coefficients (IPH area measurement) up to 0.76, 0.93 and 0.90, respectively, using SCM, the adjacent muscle and the local median value for intensity normalization, after heavily calcified and small IPH were excluded.

CONCLUSIONS

A semi-automatic method with good performance on IPH detection and quantification can be obtained in MP-RAGE CMR, using an optimized intensity threshold comparing to the adjacent muscle. The automatically generated reference of local median value provides comparable performance and may be particularly useful for developing automatic classifiers. Use of the SCM intensity as reference is not recommended without coil sensitivity correction when surface coils are used.

摘要

背景

斑块内出血(IPH)与动脉粥样硬化进展及随后的心血管事件相关。我们试图开发一种半自动方法,利用匹配的组织学作为金标准,在MP-RAGE图像上对颈动脉IPH进行检测和定量分析,并确定优化的阈值。

方法

14例计划行颈动脉内膜切除术的患者术前接受了3D MP-RAGE心血管磁共振(CMR)检查。使用组织学记录IPH的存在情况和面积。还基于强度阈值在CMR上记录IPH的存在情况和面积,使用三个强度归一化参考值:胸锁乳突肌(SCM)、相邻肌肉和自动生成的局部中值。通过最大化IPH检测的约登指数来获得优化的强度阈值。使用留一法交叉验证,评估基于我们提出的半自动方法进行IPH检测的敏感性和特异性,以及在IPH面积定量方面与组织学的一致性。

结果

IPH检测的优化强度阈值分别为SCM强度的1.0倍、相邻肌肉强度的1.6倍和中值强度的2.2倍。使用具有优化强度阈值的半自动方法,获得了以下IPH检测和定量性能:敏感性分别高达59%、68%和80%;特异性分别高达85%、74%和79%;在排除严重钙化和小IPH后,使用SCM、相邻肌肉和局部中值进行强度归一化时,IPH面积测量的皮尔逊相关系数分别高达0.76、0.93和0.90。

结论

在MP-RAGE CMR中,通过与相邻肌肉比较使用优化的强度阈值,可以获得一种在IPH检测和定量方面具有良好性能的半自动方法。自动生成的局部中值参考提供了可比的性能,可能对开发自动分类器特别有用。当使用表面线圈时,在没有线圈灵敏度校正的情况下,不建议使用SCM强度作为参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/28716487ff9a/12968_2016_260_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/f08fcae42083/12968_2016_260_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/097177c01449/12968_2016_260_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/db6933aa6cb3/12968_2016_260_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/28716487ff9a/12968_2016_260_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/f08fcae42083/12968_2016_260_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/b36223791dcf/12968_2016_260_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/097177c01449/12968_2016_260_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/db6933aa6cb3/12968_2016_260_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a435/4950626/28716487ff9a/12968_2016_260_Fig5_HTML.jpg

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