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心肌动态灌注成像的绝对碘浓度:在 3D 打印动态心脏模型中提高对狭窄后缺血的检测。

Absolute iodine concentration for dynamic perfusion imaging of the myocardium: improved detection of poststenotic ischaemic in a 3D-printed dynamic heart phantom.

机构信息

Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Klinikum rechts der Isar, Ismaninger Str. 22, 81675, Munich, Germany.

Chair of Biomedical Physics, Department of Physics, School of Natural Sciences, Technical University of Munich, Garching, Germany.

出版信息

Eur Radiol Exp. 2022 Oct 31;6(1):51. doi: 10.1186/s41747-022-00304-x.

DOI:10.1186/s41747-022-00304-x
PMID:36310190
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9618471/
Abstract

BACKGROUND

To investigate the detection capabilities of myocardial perfusion defects of dual-energy computed tomography (CT) technology using time-resolved iodine-based maps for functional assessment of coronary stenosis in a dynamic heart phantom.

METHODS

An anatomical heart model was designed using a three-dimensional (3D) printing technique. The lumen of the right coronary artery was reduced to 25% of the original areal cross-section. Scans were acquired with a 64-slice dual-layer CT equipment using a perfusion protocol with 36 time points. For distinguishing haemodynamically affected from unaffected myocardial regions, conventional and spectral mean transit time (MTT) parameter maps were compared. A dose reduction technique was simulated by using a subset of time points of the time attenuation curves (TACs).

RESULTS

The tracer kinetic modeling showed decreased errors on fit parameters from conventional to spectral TACs (42% reduction for A and 40% for λ). Three characteristic regions (highly, moderately, and not affected by the simulated stenosis) can be distinguished in all spectral perfusion maps. The best distinction was observed on MTT maps. An area under the curve (AUC) value of 1.00 for the voxel-wise differentiation of haemodynamically affected tissue was achieved versus a 0.89 AUC for conventional MTT maps. By temporal under-sampling, a dose reduction of approximately 78% from 19 to 4.3 mSv was achieved with a 0.96 AUC.

CONCLUSION

Dual-energy CT can provide time-resolved iodine density data, which enables the calculation of absolute quantitative perfusion maps with decreased fitting errors, improving the accuracy for poststenotic myocardial ischaemic detection in a 3D-printed heart phantom.

摘要

背景

使用基于碘的双能 CT 技术时间分辨碘图检测心肌灌注缺损,以评估动态心脏模型中冠状动脉狭窄的功能。

方法

使用三维(3D)打印技术设计解剖心脏模型。右冠状动脉管腔减少到原始截面积的 25%。使用灌注协议采集 64 层双层 CT 设备的 36 个时间点的扫描。为了区分受血流动力学影响和不受影响的心肌区域,比较了常规和光谱平均通过时间(MTT)参数图。通过使用时间衰减曲线(TAC)的时间点子集模拟剂量减少技术。

结果

示踪动力学建模显示,常规 TAC 到光谱 TAC 的拟合参数误差降低(A 降低 42%,λ 降低 40%)。在所有光谱灌注图中都可以区分三个特征区域(高度、中度和不受模拟狭窄影响)。MTT 图的区分效果最好。实现了基于体素的心动组织区分的曲线下面积(AUC)值为 1.00,而常规 MTT 图的 AUC 值为 0.89。通过时间欠采样,从 19 次减少到 4.3 次 mSv 可实现大约 78%的剂量减少,AUC 值为 0.96。

结论

双能 CT 可提供时间分辨碘密度数据,从而能够计算具有降低拟合误差的绝对定量灌注图,提高在 3D 打印心脏模型中检测后狭窄性心肌缺血的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/af9ca2109252/41747_2022_304_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/a05b0732c102/41747_2022_304_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/da812ddfdc64/41747_2022_304_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/1cf091af4b30/41747_2022_304_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/0b06f62ccda4/41747_2022_304_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/e389ac5c32df/41747_2022_304_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/af9ca2109252/41747_2022_304_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/a05b0732c102/41747_2022_304_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/da812ddfdc64/41747_2022_304_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/1cf091af4b30/41747_2022_304_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/0b06f62ccda4/41747_2022_304_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/e389ac5c32df/41747_2022_304_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5852/9618471/af9ca2109252/41747_2022_304_Fig6_HTML.jpg

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