心肌间质纤维化的自由呼吸非对比 T1ρ 弥散磁共振成像与细胞外体积分数的比较

IF 4.2 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Qinfang Miao, Sha Hua, Yiwen Gong, Zhenfeng Lyu, Pengfang Qian, Chun Liu, Wei Jin, Peng Hu, Haikun Qi
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引用次数: 0

摘要

背景:心肌纤维化是各种心脏疾病的共同特征。它导致不良的心脏重塑,并与不良的临床预后有关。晚期钆增强(LGE)和细胞外体积分数(ECV)是检测局灶性和弥漫性心肌纤维化的标准磁共振成像技术。然而,这些造影剂增强技术需要使用钆造影剂,不适用于有钆禁忌症的患者。为了避免使用造影剂,我们开发并应用了一种内源性自由呼吸 T1ρ 弥散成像技术(FB-MultiMap),用于诊断疑似心肌病群中的弥漫性心肌纤维化:在模型和 15 名健康受试者中开发了拟议的 FB-MultiMap 技术,可在一次扫描中量化 T2、T1ρ 及其差异(心肌纤维化指数,mFI)。在临床研究中,对 55 名疑似心肌病患者使用 FB-MultiMap、传统本地 T1 映像、LGE 和 ECV 成像进行了成像。使用接收器操作特征曲线(ROC)分析评估了内源性参数对预测心室电压增加的准确性。此外,还分别使用皮尔逊相关系数评估了原生 T1、T1ρ 和 mFI 与 ECV 的相关性:结果:FB-MultiMap 与传统的单独屏气绘图技术在模型和健康受试者身上显示出良好的一致性。就所有患者而言,T1ρ比 mFI 和本机 T1 更能准确预测心血管容量的增加,其曲线下面积(AUC)值分别为 0.91、0.79 和 0.75,并且与心血管容量的相关性更强(相关系数 r:0.72 vs. 0.52 vs. 0.40)。在 47 例 T2 值正常的患者子集中,mFI 的诊断性能明显增强(AUC=0.90,r=0.83),优于 T1ρ 和本地 T1:结论:所提出的自由呼吸 T1ρ 弥散成像技术可在一次扫描中同时量化 T2、T1ρ 和 mFI,在诊断复杂心肌病患者的弥漫性心肌纤维化方面显示出巨大潜力,且无需造影剂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Free-Breathing Non-Contrast T1ρ Dispersion MRI of Myocardial Interstitial Fibrosis in Comparison with Extracellular Volume Fraction.

Background: Myocardial fibrosis is a common feature in various cardiac diseases. It causes adverse cardiac remodeling and is associated with poor clinical outcomes. Late gadolinium enhancement (LGE) and extracellular volume fraction (ECV) are the standard MRI techniques for detecting focal and diffuse myocardial fibrosis. However, these contrast-enhanced techniques require the administration of gadolinium contrast agents, which is not applicable to patients with gadolinium contraindications. To eliminate the need of contrast agents, we develop and apply an endogenous free-breathing T1ρ dispersion imaging technique (FB-MultiMap) for diagnosing diffuse myocardial fibrosis in a cohort with suspected cardiomyopathies.

Methods: The proposed FB-MultiMap technique, enabling T2, T1ρ and their difference (myocardial fibrosis index, mFI) quantification in a single scan was developed in phantoms and 15 healthy subjects. In the clinical study, 55 patients with suspected cardiomyopathies were imaged using FB-MultiMap, conventional native T1 mapping, LGE, and ECV imaging. The accuracy of the endogenous parameters for predicting increased ECV was evaluated using receiver operating characteristic (ROC) curve analysis. In addition, the correlation of native T1, T1ρ, and mFI with ECV was respectively assessed using Pearson correlation coefficients.

Results: FB-MultiMap showed a good agreement with conventional separate breath-hold mapping techniques in phantoms and healthy subjects. Considering all the patients, T1ρ was more accurate than mFI and native T1 for predicting increased ECV, with area under the curve (AUC) values of 0.91, 0.79 and 0.75, respectively, and showed stronger correlation with ECV (correlation coefficient r: 0.72 vs. 0.52 vs. 0.40). In the subset of 47 patients with normal T2 values, the diagnostic performance of mFI was significantly strengthened (AUC=0.90, r=0.83), outperforming T1ρ and native T1.

Conclusion: The proposed free-breathing T1ρ dispersion imaging technique enabling simultaneous quantification of T2, T1ρ and mFI in a single scan has shown great potential for diagnosing diffuse myocardial fibrosis in patients with complex cardiomyopathies without contrast agents.

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来源期刊
CiteScore
10.90
自引率
12.50%
发文量
61
审稿时长
6-12 weeks
期刊介绍: Journal of Cardiovascular Magnetic Resonance (JCMR) publishes high-quality articles on all aspects of basic, translational and clinical research on the design, development, manufacture, and evaluation of cardiovascular magnetic resonance (CMR) methods applied to the cardiovascular system. Topical areas include, but are not limited to: New applications of magnetic resonance to improve the diagnostic strategies, risk stratification, characterization and management of diseases affecting the cardiovascular system. New methods to enhance or accelerate image acquisition and data analysis. Results of multicenter, or larger single-center studies that provide insight into the utility of CMR. Basic biological perceptions derived by CMR methods.
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