分享:
分享到微信朋友圈
X
特别关注
心脏磁共振左室快速长轴应变预测肥厚型心肌病广泛心肌纤维化的价值
陈梓娴 杨娜 南江 张亚萍 徐磊 雷军强

本文引用格式:陈梓娴, 杨娜, 南江, 等. 心脏磁共振左室快速长轴应变预测肥厚型心肌病广泛心肌纤维化的价值[J]. 磁共振成像, 2025, 16(11): 32-38, 48. DOI:10.12015/issn.1674-8034.2025.11.005.


[摘要] 目的 探究基于心脏磁共振(cardiac magnetic resonance, CMR)电影序列测量的左心室快速长轴应变(fast long-axis strain, FLAS)与肥厚型心肌病(hypertrophic cardiomyopathy, HCM)患者广泛延迟钆增强(late gadolinium enhancement, LGE)的相关性,并与左室整体纵向应变(global longitudinal strain, GLS)对比,评估其对广泛心肌纤维化的预测价值。材料与方法 回顾性分析2017年1月至2021年1月在兰州大学第一医院诊断为HCM的患者131例及年龄、性别匹配的75例正常对照者的临床基线资料与CMR影像数据。根据LGE程度将患者分为广泛LGE组和非广泛LGE组。FLAS参数在左心室两腔及四腔心电影序列测量。采用Pearson相关系数探讨FLAS与LGE程度的相关性;采用单因素和多因素logistic回归分析FLAS与LGE的关联,并通过受试者工作特征(receiver operating characteristic, ROC)曲线评估FLAS对广泛LGE的诊断效能。结果 广泛LGE组患者较非广泛LGE组年龄更小[(52±11)岁vs. (57±13)岁,P=0.025],舒张压更高[(79±10) mmHg vs. (74 ± 12) mmHg,P=0.016],高血压发生率降低,差异具有统计学意义(27.3% vs. 51.7 %,P=0.008)。广泛LGE组FLAS显著低于非广泛LGE组[(-9.24%±2.73%)vs.(-12.41%±2.84%),P<0.001],且LGE程度与FLAS呈中度负相关(r=-0.497,P<0.001)。ROC曲线显示,FLAS识别广泛LGE的AUC为0.802,显著优于GLS(AUC=0.709)及传统CMR参数(LVMi、LVESVi、LVEF及MLVT,AUC分别为0.626、0.703、0.725和0.702)。多因素回归分析进一步证实FLAS是广泛LGE的独立预测因子(OR=1.497,95% CI:1.550~2.663,P<0.001)。结论 FLAS作为一种无需对比剂的新型CMR功能学指标,在识别HCM患者广泛心肌纤维化方面表现出优于GLS及传统参数。其有望成为替代LGE的无创心肌纤维化评估工具,尤其适用于钆对比剂禁忌或肾功能不全的患者。
[Abstract] Objective To investigate the correlation between left ventricular fast long-axis strain (FLAS) measured from cardiac magnetic resonance (CMR) cine sequences and extensive late gadolinium enhancement (LGE) in patients with hypertrophic cardiomyopathy (HCM), and to compare its predictive value for extensive myocardial fibrosis against global longitudinal strain (GLS).Materials and Methods A retrospective analysis was conducted on clinical baseline data and CMR imaging from 131 patients diagnosed with HCM and 75 age- and sex-matched normal controls at the First Hospital of Lanzhou University between January 2017 and January 2021. Patients were divided into extensive LGE and non-extensive LGE groups based on LGE extent. FLAS parameter was measured from the two- and four-chamber left ventricular cine sequences. Pearson correlation analysis was used to explore the relationship between FLAS and LGE extent. Univariate and multivariate logistic regression analyses were employed to assess the association between FLAS and LGE. The diagnostic performance of FLAS for identifying extensive LGE was evaluated using receiver operating characteristic (ROC) curve analysis.Results Patients in the extensive LGE group were younger [(52 ± 11) years vs. (57 ± 13) years, P = 0.025)], had higher diastolic blood pressure [(79 ± 10) mmHg vs. (74 ± 12) mmHg, P = 0.016], and showed a statistically significant lower incidence of hypertension (27.3% vs. 51.7%, P = 0.008) compared to the non-extensive LGE group. FLAS was significantly lower in the extensive LGE group [( -9.24% ± 2.73%) vs. (-12.41% ± 2.84%), P < 0.001)] and a moderate negative correlation was observed between LGE extent and FLAS (r = -0.497, P < 0.001). ROC curve analysis showed that the area under the curve (AUC) for FLAS in identifying extensive LGE was 0.802, which was significantly superior to GLS (AUC = 0.709) and traditional CMR parameters (LVMi, LVESVi, LVEF, and MLVT, with AUCs of 0.626, 0.703, 0.725, and 0.702, respectively). Multivariate regression analysis further confirmed FLAS as an independent predictor of extensive LGE (OR = 1.497, 95% CI: 1.550 to 2.663, P < 0.001).Conclusions As a novel contrast-agent-free CMR functional parameter, FLAS demonstrates superior performance to GLS and traditional parameters in identifying extensive myocardial fibrosis in HCM patients. It holds promise as a non-invasive tool for myocardial fibrosis assessment, serving as an alternative to LGE, especially in patients with contraindications to gadolinium contrast or renal insufficiency.
[关键词] 肥厚型心肌病;心脏磁共振;快速长轴应变;心肌纤维化;延迟钆增强
[Keywords] hypertrophic cardiomyopathy;cardiac magnetic resonance;fast long-axis strain;myocardial fibrosis;late gadolinium enhancement

陈梓娴 1   杨娜 1   南江 1   张亚萍 1   徐磊 2   雷军强 1*  

1 兰州大学第一医院(第一临床医学院)放射科,兰州 730000

2 首都医科大学附属北京安贞医院放射科,北京 100029

通信作者:雷军强,E-mail:leijq2011@126.com

作者贡献声明:雷军强设计本研究的方案,对稿件重要内容进行了修改;陈梓娴起草和撰写稿件,获取、分析和解释本研究的数据,获得了甘肃省科技计划项目和兰州大学学生创新创业行动计划项目资助;杨娜、南江、张亚萍获取、分析研究数据、对稿件重要内容进行了修改,其中南江获得了兰州大学第一医院院内基金项目资助;徐磊设计本研究的方案、对稿件重要内容进行了修改、获得了国家重点研发计划项目资助。


基金项目: 国家重点研发计划项目 2022YFE0209800 甘肃省科技计划项目 24JRRA310 兰州大学第一医院院内基金项目 ldyyyy-2023-60 兰州大学学生创新创业行动计划项目 20240060182,20250060215
收稿日期:2025-08-07
接受日期:2025-10-27
中图分类号:R445.2  R541 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2025.11.005
本文引用格式:陈梓娴, 杨娜, 南江, 等. 心脏磁共振左室快速长轴应变预测肥厚型心肌病广泛心肌纤维化的价值[J]. 磁共振成像, 2025, 16(11): 32-38, 48. DOI:10.12015/issn.1674-8034.2025.11.005.

0 引言

       肥厚型心肌病(hypertrophic cardiomyopathy, HCM)是编码心肌肌小节蛋白基因突变的常染色体显性遗传性心肌病,是青少年及青年群体心源性猝死(sudden cardiac death, SCD)的首要病因[1]。其病理特征包括左心室非对称性肥厚、心肌细胞排列紊乱及心肌纤维化[2],约60%~65%的HCM患者存在心肌纤维化[3]。纤维化的发病机制涉及肌节蛋白异常、微循环障碍及机械应力失调,导致胶原异常沉积[4],进而增加电传导异质性和机械离散度,促进折返性心律失常并损害舒张功能,最终引发心力衰竭[5, 6]

       心脏磁共振(cardiac magnetic resonance, CMR)延迟钆增强(late gadolinium enhancement, LGE)是目前评估心肌纤维化的金标准[7]。LGE程度≥左心室(left ventricle, LV)心肌质量15%是HCM患者全因死亡率的独立预测因子,并被指南列为SCD风险分层及植入式心律转复除颤器植入的Ⅱa类推荐指标[2, 8, 9]。然而,LGE需注射钆对比剂,可能诱发肾源性系统性纤维化,且钆剂在脑部长期沉积存在潜在神经毒性[10]。此外,CMR检查成本高、耗时长,限制了其广泛应用。因此,开发无创、高效、可重复的纤维化评估方法对优化HCM管理至关重要。

       心脏磁共振特征追踪技术(CMR feature tracking, CMR-FT)通过分析常规电影序列量化整体纵向应变(global longitudinal strain, GLS)等参数,为评估心肌功能提供新方法[11, 12]。研究表明,GLS与HCM患者的纤维化程度及不良心血管事件(major adverse cardiovascular events, MACE)显著相关[13, 14]。但CMR-FT存在局限性:图像质量影响准确性,心肌曲率异常及乳头肌伪影可导致心内膜识别偏差;纤维化增加机械离散度,加剧应变分析的异质性;不同厂商算法尚未标准化,导致平台间差异,限制临床推广[15]

       左心室快速长轴应变(fast long-axis strain, FLAS)是一种新兴功能学指标,通过测量二尖瓣环与心尖距离变化率评估心肌变形能力,仅需标准长轴电影序列,耗时短且重复性高[16, 17]。研究表明,FLAS与GLS在健康人群及心脏病患者中高度一致[17, 18]。LGE阳性节段常伴纵向应变受损,提示机械形变与纤维化相关[19, 20]

       然而,现有研究均聚焦于“应变-预后”或“应变-心功能”层面,且普遍把LGE简化为“有/无”的二元标签,既未量化纤维化范围,也未在同一HCM队列中系统比较FLAS、GLS及传统心功能参数对广泛 LGE 的预测效能[21, 22]。FLAS是否真正优于GLS、能否在无钆条件下替代LGE,关键证据尚属空白。

       基于此,本研究首次聚焦“FLAS-纤维化”轴心,利用HCM队列系统量化LGE范围,并评估FLAS、GLS与传统心功能参数对“广泛LGE”(≥15% LV心肌质量)的预测效能。我们假设:在不依赖对比剂、无需额外序列的前提下,FLAS能以更高效能识别广泛纤维化,并为钆剂禁忌或肾功能不全患者提供安全、即时的风险分层工具,从而重新定义HCM的影像评估策略。

1 材料与方法

1.1 研究对象

       本研究为回顾性研究,纳入2017年1月至2021年1月在兰州大学第一医院行CMR检查的临床疑诊HCM患者150例及年龄、性别匹配的75例正常对照者。HCM的纳入标准:(1)年龄>18岁;(2)经CMR检查,符合《2014欧洲心脏病学会HCM诊断和管理指南》中诊断标准:左室最大舒张末期室壁厚度≥15 mm或者有家族史左室壁最大厚度≥13 mm[23];(3)均接受CMR和超声心动图检查;(4)临床资料完整。排除标准:(1)合并其他心脏疾病(如冠心病、先天性心脏病及瓣膜病等);(2)继发性左室肥厚疾病(如淀粉样变性、法布里病等);(3)既往有室间隔化学消融或外科手术史;(4)左心室射血分数(left ventricular ejection fraction, LVEF)<50%;(5)CMR图像质量不满足后处理分析要求。最终纳入HCM患者131例,根据LGE程度分为广泛LGE组(LGE≥15%)和非广泛LGE组(无LGE或LGE<15%)(图1)。对照组选取同期我院招募的健康志愿者,纳入标准:(1)年龄>18岁;(2)均接受CMR和心电图检查;(3)无心血管症状及既往病史;(4)心电图未见明显异常,血压、血脂、血糖均在正常范围;(5)经临床综合评估(结合病史询问、体格检查、基础实验室检查及CMR检查结果)排除心血管疾病。排除标准:CMR图像质量不满足后处理分析要求者。本研究遵循《赫尔辛基宣言》,已获得兰州大学第一医院伦理委员会的批准,健康志愿者均签署书面知情同意书,病例组豁免知情同意,批准文号:LDYYLL2025-88。

图1  HCM患者入组及LGE分组流程图。HCM:肥厚型心肌病;CMR:心脏磁共振;LVEF:左心室射血分数;LGE:延迟钆增强。
Fig. 1  Flowchart of patient enrollment and LGE-based grouping. HCM: hypertrophic cardiomyopathy; CMR: cardiac magnetic resonance; LVEF: left ventricular ejection fraction; LGE: late gadolinium enhancement.

1.2 仪器与方法

1.2.1 超声心动图

       采用飞利浦EPIQ 7C超声系统进行经胸超声心动图(transthoracic echocardiography, TTE)检查。静息状态下,通过心尖五腔心切面测量左心室流出道峰值流速(Vmax),按ΔP=4Vmax²计算压力梯度。静息ΔP≥30 mmHg即诊断左室流出道梗阻(left ventricular outflow tract obstruction, LVOTO)。若静息ΔP<30 mmHg则行运动负荷试验后复测,运动后ΔP≥30 mmHg仍可诊断梗阻性HCM[23]

1.2.2 CMR图像采集

       采用3.0 T磁共振系统(德国Siemens Skyra)进行CMR检查。使用16通道相控阵体部线圈联合心电门控技术进行信号采集。心脏电影成像采用平衡稳态自由进动(balanced steady-state free precession, bSSFP)序列,扫描标准长轴(二腔心、四腔心、三腔心)切面及8~10层短轴切面(参数:FOV 340 mm×265 mm;体素1.6 mm×1.6 mm×8.0 mm;层间距2 mm;TR 3.3 ms;TE 1.43 ms;翻转角55°~70°可调)。

       静脉注射钆喷酸葡胺(Gd-DTPA,德国拜耳公司)0.2 mmol/kg,10~15 min后行LGE扫描,采用相位敏感反转恢复序列获取四腔心和短轴切面(参数:FOV 370 mm×370 mm;体素1.4 mm×1.4 mm×8.0 mm;层间距2 mm;TR 5.2 ms;TE 1.96 ms;翻转角20°)。

1.3 CMR图像后处理

       采用CVI42软件(Circle cardiovascular imaging,加拿大)分析CMR图像。通过短轴电影序列软件自动识别心内膜及心外膜边界(必要时手动校正),计算LVEF、左心室舒张末期容积指数(left ventricular end diastolic volume index, LVEDVi)、左室收缩末期容积指数(left ventricular end systolic volume index, LVESVi)、左心室心肌质量指数(left ventricular mass index, LVMi)等。在舒张末期短轴电影图像上测量左室舒张末期内径(left ventricular end diastolic diameter, LVEDD)及左心室最大室壁厚度(maximum wall thickness of the left ventricle, MLVT)。

1.3.1 GLS分析

       使用CVI42二维应变模块测量GLS。基于两腔及四腔心长轴电影图像,自动勾画心内外膜边界(手动矫正)后计算GLS值。重复测量3次,取平均值作为最终结果。

1.3.2 FLAS测量

       FLAS的测量参照既往文献所描述的方法进行[21, 24]。在左心室长轴两腔心及四腔心电影序列上,分别于收缩末期和舒张末期测量左室心尖心外膜边界至二尖瓣叶附着点连线中点的距离。FLAS计算公式为:FLAS=[(收缩末期距离-舒张末期距离)/舒张末期距离]×100%。每个切面重复测量3次,最终结果取两切面所测值的平均值(图2)。

图2  FLAS测量示意图。52岁,女,HCM患者。2A:四腔心舒张末期;2B:四腔心收缩末期;2C:两腔心舒张末期;2D:两腔心收缩末期。测得FLAS为-11.5%。FLAS:快速长轴应变;HCM:肥厚型心肌病;CMR:心脏磁共振。
Fig. 2  Schematic diagram of FLAS measurement. A 52-year-old female HCM patient using CMR cine images. 2A: End-diastolic four-chamber view; 2B: End-systolic four-chamber view; 2C: End-diastolic two-chamber view; 2D: End-systolic two-chamber view. The measured FLAS is -11.5%. FLAS: fast long-axis strain; HCM: hypertrophic cardiomyopathy; CMR: cardiac magnetic resonance.

1.3.3 LGE定量分析

       采用LGE模块进行定量分析。逐层勾画短轴LGE图像的心内外膜边界,以远端正常心肌信号均值+5SD为阈值自动计算LGE%。结果以LGE质量占左室心肌质量的百分比表示。所有测量分别由一名13年和一名10年心血管影像工作经验的副主任医师和主管技师采用盲法独立完成。

1.4 统计学分析

       采用SPSS 27.0进行统计学分析。计量资料经Kolmogorov-Smirnov检验正态性后,正态分布数据用平均数±标准差表示(独立样本t检验),非正态分布数据用中位数(上下四分位数)表示(Mann-Whitney U检验)。计数资料用频数(%)表示(χ2或Fisher精确检验)。采用Pearson相关系数计算FLAS、GLS和LGE之间的相关性。通过受试者工作特征(receiver operating characteristic, ROC)曲线评估各参数预测广泛LGE的效能,并计算曲线下面积(area under the curve, AUC)确定最佳截断值。不同参数AUC间的比较采用DeLong检验。构建单变量和多变量logistic回归模型(矫正年龄、性别等混杂因素)评估FLAS的预测价值。采用Bland-Altman法评价测量一致性。P<0.05表示差异具有统计学意义。

2 结果

2.1 一般资料

       纳入131例HCM患者(男61.1%,中位年龄56岁)和75名正常对照组(男60.0%,中位年龄53岁)。HCM组收缩压显著高于对照组[126(114,139) mmHg vs. 116(110,125) mmHg,P < 0.001]。根据LGE程度分组:广泛LGE组44例,非广泛LGE组87例。与非广泛LGE组比较,广泛LGE组患者年龄更小[(52±11)岁vs.(57±13)岁,P=0.025],舒张压更高[(79±10) mmHg vs. (74±12) mmHg,P=0.016),高血压发生率显著降低(27.3% vs. 51.7%,P=0.008)。其他临床参数组间差异无统计学意义,见表1

表1  HCM及正常对照组的临床基线资料
Tab. 1  Clinical baseline characteristics of HCM patients and normal controls

2.2 影像学特征

       HCM患者较正常对照组,除LVESVi外,其余影像参数差异均具有统计学意义(P均<0.05)。广泛LGE组MLVT、LVESVi及LVMi均高于非广泛LGE组(P均<0.05),但LVEDVi差异无统计学意义(P=0.113)。广泛LGE组LVEF更低[61.00%(55.25%,64.00%)vs. 66.00% (60.00%,71.00%),P<0.001],LVOTO发生率更低(43.2% vs. 66.7%,P=0.010)。HCM患者整体GLS及FLAS显著低于对照组(P<0.001),且广泛LGE组GLS[(-10.67%±3.27%) vs. (-13.10%±2.99%)]和FLAS[(-9.24%±2.73%) vs. (-12.41%±2.84%)]进一步减低(P<0.001)。SAM组间差异无统计学意义,见表2

表2  HCM及正常对照组的影像参数特征
Tab. 2  Imaging parameter characteristics of HCM patients and normal controls

2.3 FLAS与GLS和LGE程度的相关性

       在LGE阳性的HCM患者中,GLS和FLAS均与LGE程度呈负相关(r=-0.404和-0.497,P<0.001),其中FLAS相关性更强,见图3

图3  GLS(3A)、FLAS(3B)与LGE程度的相关性散点图。HCM:肥厚型心肌病;GLS:左室纵向应变;FLAS:左室快速长轴应变;LGE:延迟钆增强。
Fig. 3  Scatter plots illustrating the correlations of GLS (3A) and FLAS (3B) with LGE extent. HCM: hypertrophic cardiomyopathy; GLS: global longitudinal strain; FLAS: fast long-axis strain; LGE: late gadolinium enhancement.

2.4 CMR参数诊断HCM患者广泛LGE的诊断效能

       ROC曲线分析显示:FLAS在识别广泛LGE方面具有最佳的诊断效能(AUC=0.802,95% CI:0.719~0.885)。FLAS的AUC显著高于GLS(AUC=0.709,P=0.022)、LVMi(AUC=0.626,P<0.001)、LVEF(AUC=0.725,P=0.163)、LVESVi(AUC=0.703,P=0.091)及MLVT(AUC=0.702,P=0.054),但其中仅与GLS和LVMi的差异具有统计学意义。当FLAS以-11.06%作为截断值时,诊断的敏感度为84.1%,特异度为67.8%,见图4

图4  CMR参数诊断HCM患者广泛LGE的ROC曲线。CMR:心脏磁共振;HCM:肥厚型心肌病;ROC:受试者工作特征;FLAS:快速长轴应变;GLS:整体纵向应变;MLVT:左室最大室壁厚度;LVEF:左室射血分数;LVESVi:左室收缩末期容积指数;LVEDVi:左室舒张末期容积指数;LVMi:左室心肌质量指数;AUC:曲线下面积。
Fig. 4  ROC curve of CMR parameters for diagnosing extensive LGE in HCM patients. CMR: cardiac magnetic resonance; HCM: hypertrophic cardiomyopathy; ROC: receiver operating characteristic; FLAS: fast long-axis strain; GLS: global longitudinal strain; MLVT: maximum left ventricular wall thickness; LVEF: left ventricular ejection fraction; LVESVi: left ventricular end-systolic volume index; LVEDVi: left ventricular end-diastolic volume index; LVMi: left ventricular mass index; AUC: area under the curve.

2.5 HCM患者广泛LGE的影响因素

       logistic回归分析结果显示,LVESVi升高(OR=1.252,P=0.002)、LVMi增高(OR=0.934,P=0.001)以及FLAS绝对值降低(OR=1.991,P<0.001)与HCM患者出现广泛LGE显著相关。多因素分析进一步证实,FLAS降低、LVESVi升高及LVMi增高均为发生广泛LGE的独立预测因子(P均<0.001)。其中,FLAS的OR值最高(OR=1.497),提示预测价值最为显著,详见表3

表3  预测HCM患者广泛LGE的单因素和多因素回归分析
Tab. 3  Univariate and multivariate regression analysis for predicting extensive LGE in HCM patients

2.6 测量指标组内及组间一致性评价

       随机选取20例HCM患者评估FLAS和GLS的测量一致性。组内一致性由一名10年CMR经验医师间隔1个月重复测量,组间一致性由另一名3年经验医师盲法测量。所有参数的组间ICC值为0.882~0.983,组内ICC值为0.979~0.987,均大于0.75,一致性良好。

3 讨论

       本研究基于CMR电影序列测量FLAS,系统探讨了FLAS与HCM患者广泛LGE(≥15%)之间的定量关系,并通过对比分析评估其诊断价值。研究结果显示:(1)在识别广泛LGE方面,FLAS的诊断效能显著优于GLS及其他传统CMR参数(MLVT、LVEF、LVESVi、LVMi);(2)广泛LGE组患者的FLAS值显著降低,且FLAS与LGE程度呈中度负相关,其相关性强度高于GLS;(3)多因素分析表明,FLAS是广泛LGE的独立预测因子,具有重要的临床价值诊断。本研究首次在HCM人群中明确建立了FLAS与广泛LGE之间的定量关联,并证实FLAS在识别广泛LGE方面诊断性能优于GLS。

3.1 FLAS与GLS在评估心肌纤维化中诊断效能对比

       既往研究表明左室GLS异常与心肌纤维化密切相关。超声心动图研究证实,在LVEF保留阶段,GLS和节段应变即可早期识别心功能异常,并对LGE改变具有预测价值[13, 19]。HU等[13]发现GLS与纤维化程度呈显著相关(r=0.337),并可预测5年SCD风险。BOGARAPU等[25]在儿童HCM中进一步证实CMR-FT测得的GLS诊断LGE的敏感度和特异度高达91%和89%。然而,本研究结果显示,FLAS在鉴别广泛LGE方面表现出更优的性能:其AUC值、敏感度及特异度均优于GLS,且与LGE程度呈更强的负相关。这一发现明确了FLAS在HCM心肌纤维化评估中的优势。

       该优势源于FLAS的技术特性与HCM病理改变之间更高的适配性。从技术层面看[26, 27],GLS依赖专业后处理软件及心内膜勾画的精确性;而HCM患者常存在左室壁肥厚、心肌结构紊乱,易导致心内膜边界识别偏差,影响GLS测量准确性。FLAS仅需追踪三个空间点即可完成评估,无需心内膜勾画,显著降低操作变异性和对图像质量的依赖,提高了测量的稳定性和可重复性。从病理机制看[4],HCM心肌纤维化的本质是左心室细胞外基质蛋白的异常沉积,降低心肌顺应性,并通过改变心肌应力分布损害纵向收缩功能。FLAS直接反映整体纵向应力变化,对纤维化所致的功能异常捕捉更为直接敏感;而GLS受较多技术噪声干扰,其敏感性在一定程度上被削弱。因此,FLAS在评估HCM广泛心肌纤维化方面效能优于GLS,可视为其技术优势与HCM特定病理特征相结合的理想结果。

       需要强调的是,HCM患者的LGE程度受多种因素影响,如MLVT、LVMi、LVOTO、病程、NT-proBNP、基因突变等[28, 29, 30]。因此,FLAS在不同表型和疾病阶段的诊断效能仍需通过多中心前瞻性研究进一步验证。

3.2 FLAS预测HCM患者广泛心肌纤维化的临床意义

       多项研究证实左室LGE程度是HCM患者不良心血管事件的独立预测因子[2, 8, 31]。LIU等[32]发现LGE负荷每增加10%,SCD风险升高1.8倍。当LGE≥15%时,即使传统低危患者SCD风险仍增加2倍[33]。2020年美国心脏协会指南推荐LGE阳性患者每12~18个月复查CMR以评估纤维化进展[13, 34]。但现有LGE技术存在明显局限:需注射钆对比剂、扫描耗时长且依赖患者屏气配合。因此,开发无需对比剂、快速扫描且能准确识别高危纤维化的新型影像标志物,对优化HCM危险分层具有重要临床价值。

       FLAS作为新兴的整体纵向应变参数,在心血管疾病评估中展现出独特价值。研究表明,FLAS不仅在缺血性心脏病中具有诊断和预后价值[17, 24],在非缺血性心肌病中也显示出增量价值[35, 36]。WANG等[37]发现FLAS鉴别心脏淀粉样变性与HCM的准确性优于GLS;SCHUSTER等[38]证实FLAS预测心肌梗死后MACE的预测效能与GLS相当;ARENJA等[39]指出FLAS降低是非缺血性扩张型心肌病MACE的独立预测因子。本研究首次系统建立HCM患者FLAS与广泛LGE的定量关系,为无创评估心肌纤维化的提供了新依据。这一发现对对比剂使用受限患者尤其重要。未来研究可进一步探索FLAS在HCM风险分层和治疗决策中的应用价值。

       FLAS相比传统应变分析具有显著优势:(1)操作简便,仅需追踪三个空间点即可完成评估,摆脱了对专业软件的依赖;(2)不受心内膜勾画质量限制,有效克服了CMR-FT在HCM应用中的技术难点;(3)特别适合临床新手使用。本研究结果显示,正常FLAS参考值为(-17.94%±1.83%)与既往研究结果(-17.2%±2.7%)高度吻合[37]。同时,该参数表现出优秀的观察者内与观察者间重现性,为其未来的临床应用奠定了坚实的可重复性基础。

       FLAS具有突出的多模态兼容性,不仅适用于CMR,还可用于超声心动图和冠状动脉CT血管造影(coronary CT angiography, CCTA)。AURICH等[40]证实超声FLAS的诊断效能与基于斑点追踪的GLS相当;AQUINO等[41]发现CCTA-FLAS可独立预测经导管主动脉瓣置换术患者的死亡率。这些研究表明,FLAS 具备跨影像技术的应用潜力,未来需要重点验证其多模态一致性。

       本研究证实,HCM患者在LVEF保留阶段即已出现FLAS和GLS显著降低,符合“纵向应变较LVEF更早反映心功能损害”的理论[42, 43]。HCM病理进程通常始于舒张功能障碍,晚期才出现LVEF下降。最新研究将LVEF 50%~60%界定为“低正常”状态,与心血管死亡风险相关[44, 45]。本研究发现LVEF<51%可能提示广泛LGE,但其诊断准确性不及FLAS。这些结果再次验证了纵向应变参数在评估心肌纤维化方面较传统指标具有额外价值。

3.3 研究的局限性与展望

       本研究存在以下局限:(1)样本量有限,且为单中心回顾性设计,未来需扩大样本并在多中心中验证;(2)未分析FLAS与心肌细胞外容积分数(extracellular volume fraction, ECV)的相关性;(3)目前缺乏随访数据,需进一步开展随访研究以评估FLAS的预后价值。

       基于以上局限,未来研究可从以下三方面展开:首先,开展多中心研究,纳入不同临床表型(如梗阻性与非梗阻性)、不同遗传背景(如携带或不携带致病基因突变)及不同疾病阶段的HCM患者,系统验证FLAS在广泛人群中的诊断效能与泛化性;其次,应进一步获取可反映HCM患者心肌间质纤维化程度的指标ECV,分析FLAS与ECV之间的关联,从而更全面评估FLAS在表征心肌微观结构改变方面的潜在价值;最后,建立3~5年长期随访队列,以主要不良心血管事件为终点,通过Cox回归模型评估FLAS的预后预测价值,并探索其与HCM Risk-SCD评分联合应用是否能提升风险分层的准确性。

4 结论

       FLAS在识别HCM患者广泛LGE方面优于GLS及其他传统参数。这种无需对比剂的CMR标志物具有操作简便、可重复性好等优势,特别适用于钆对比剂禁忌患者。FLAS为HCM心肌纤维化评估提供了安全可靠的无创替代方案,在临床风险分层中展现出重要应用价值。

       全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。

[1]
MARON B J, DESAI M Y, NISHIMURA R A, et al. Diagnosis and evaluation of hypertrophic cardiomyopathy JACC state-of-the-art review[J]. J Am Coll Cardiol, 2022, 79(4): 372-389. DOI: 10.1016/j.jacc.2021.12.002.
[2]
OMMEN S R, MITAL S, BURKE M A, et al. 2020 AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: executive summary: a report of the American college of cardiology/American heart association joint committee on clinical practice guidelines[J/OL]. Circulation, 2020, 142(25): e533-e557 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/33215938/. DOI: 10.1161/CIR.0000000000000938.
[3]
HABIB M, ADLER A, FARDFINI K, et al. Progression of myocardial fibrosis in hypertrophic cardiomyopathy: a cardiac magnetic resonance study[J]. JACC Cardiovasc Imaging, 2021, 14(5): 947-958. DOI: 10.1016/j.jcmg.2020.09.037.
[4]
SCHLITTLER M, PRAMSTALLER P P, ROSSINI A, et al. Myocardial fibrosis in hypertrophic cardiomyopathy: a perspective from fibroblasts[J/OL]. Int J Mol Sci, 2023, 24(19): 14845 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/37834293/. DOI: 10.3390/ijms241914845.
[5]
RAPHAEL C E, MITCHELL F, KANAGANAYAGAM G S, et al. Cardiovascular magnetic resonance predictors of heart failure in hypertrophic cardiomyopathy: the role of myocardial replacement fibrosis and the microcirculation[J/OL]. J Cardiovasc Magn Reson, 2021, 23(1): 26 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/33685501/. DOI: 10.1186/s12968-021-00720-9.
[6]
LUMISH H S, LIANG L W, HASEGAWA K, et al. Prediction of worsening heart failure in hypertrophic cardiomyopathy using plasma proteomics[J]. Heart, 2023, 109(24): 1837-1843. DOI: 10.1136/heartjnl-2023-322644.
[7]
LISI M, CAMELI M, MANDOLI G E, et al. Detection of myocardial fibrosis by speckle-tracking echocardiography: from prediction to clinical applications[J]. Heart Fail Rev, 2022, 27(5): 1857-1867. DOI: 10.1007/s10741-022-10214-0.
[8]
HANNEMAN K. The clinical significance of cardiac MRI late gadolinium enhancement in hypertrophic cardiomyopathy[J]. Radiology, 2022, 302(2): 307-308. DOI: 10.1148/radiol.2021212214.
[9]
AQUARO G D, TODIERE G, BARISON A, et al. Prognostic role of the progression of late gadolinium enhancement in hypertrophic cardiomyopathy[J/OL]. Am J Cardiol, 2024, 211: 199-208 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/37949342/. DOI: 10.1016/j.amjcard.2023.11.003.
[10]
IYAD N, AHMAD M S, ALKHATIB S G, et al. Gadolinium contrast agents- challenges and opportunities of a multidisciplinary approach: Literature review[J/OL]. Eur J Radiol Open, 2023, 11: 100503 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/37456927/. DOI: 10.1016/j.ejro.2023.100503.
[11]
XU J, YANG W J, ZHAO S H, et al. State-of-the-art myocardial strain by CMR feature tracking: clinical applications and future perspectives[J]. Eur Radiol, 2022, 32(8): 5424-5435. DOI: 10.1007/s00330-022-08629-2.
[12]
PEZESHKI P S, GHORASHI S M, HOUSHMAND G, et al. Feature tracking cardiac magnetic resonance imaging to assess cardiac manifestations of systemic diseases[J]. Heart Fail Rev, 2023, 28(5): 1189-1199. DOI: 10.1007/s10741-023-10321-6.
[13]
HU X, BAO Y W, ZHU Y, et al. Predicting left ventricular myocardial fibrosis in patients with hypertrophic cardiomyopathy by speckle tracking automated functional imaging[J]. Ultrasound Med Biol, 2023, 49(5): 1309-1317. DOI: 10.1016/j.ultrasmedbio.2023.01.020.
[14]
HIEMSTRA Y L, DEBONNAIRE P, BOOTSMA M, et al. Global longitudinal strain and left atrial volume index provide incremental prognostic value in patients with hypertrophic cardiomyopathy[J/OL]. Circ Cardiovasc Imaging, 2017, 10(7): e005706 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/28679523/. DOI: 10.1161/CIRCIMAGING.116.005706.
[15]
YANG W J, XU J, ZHU L Y, et al. Myocardial strain measurements derived from MR feature-tracking: influence of sex, age, field strength, and vendor[J]. JACC Cardiovasc Imaging, 2024, 17(4): 364-379. DOI: 10.1016/j.jcmg.2023.05.019.
[16]
LENG S, TAN R S, ZHAO X D, et al. Fast long-axis strain: a simple, automatic approach for assessing left ventricular longitudinal function with cine cardiovascular magnetic resonance[J]. Eur Radiol, 2020, 30(7): 3672-3683. DOI: 10.1007/s00330-020-06744-6.
[17]
SIRY D, RIFFEL J, SALATZKI J, et al. A head-to-head comparison of fast-SENC and feature tracking to LV long axis strain for assessment of myocardial deformation in chest pain patients[J/OL]. BMC Med Imaging, 2022, 22(1): 159 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/36064332/. DOI: 10.1186/s12880-022-00886-3.
[18]
LI Y J, XU Y W, TANG S Q, et al. Left atrial function predicts outcome in dilated cardiomyopathy: fast long-axis strain analysis derived from MRI[J]. Radiology, 2022, 302(1): 72-81. DOI: 10.1148/radiol.2021210801.
[19]
WABICH E, DORNIAK K, ZIENCIUK-KRAJKA A, et al. Segmental longitudinal strain as the most accurate predictor of the patchy pattern late gadolinium enhancement in hypertrophic cardiomyopathy[J]. J Cardiol, 2021, 77(5): 475-481. DOI: 10.1016/j.jjcc.2020.11.004.
[20]
MEINDL C, PAULUS M, POSCHENRIEDER F, et al. Patients with acute myocarditis and preserved systolic left ventricular function: comparison of global and regional longitudinal strain imaging by echocardiography with quantification of late gadolinium enhancement by CMR[J]. Clin Res Cardiol, 2021, 110(11): 1792-1800. DOI: 10.1007/s00392-021-01885-0.
[21]
RIFFEL J H, ANDRE F, MAERTENS M, et al. Fast assessment of long axis strain with standard cardiovascular magnetic resonance: a validation study of a novel parameter with reference values[J/OL]. J Cardiovasc Magn Reson, 2015, 17(1): 69 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/26253220/. DOI: 10.1186/s12968-015-0171-8.
[22]
YANG F Y, WANG J, LI Y C, et al. The prognostic value of biventricular long axis strain using standard cardiovascular magnetic resonance imaging in patients with hypertrophic cardiomyopathy[J/OL]. Int J Cardiol, 2019, 294: 43-49 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/31405582/. DOI: 10.1016/j.ijcard.2019.08.010.
[23]
MEMBERS A F, ELLIOTT P M, ANASTASAKIS A, et al. 2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: the Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC)[J]. Eur Heart J, 2014, 35(39): 2733-2779. DOI: 10.1093/eurheartj/ehu284.
[24]
SCHUSTER A, BACKHAUS S J, STIERMAIER T, et al. Fast manual long-axis strain assessment provides optimized cardiovascular event prediction following myocardial infarction[J]. Eur Heart J Cardiovasc Imaging, 2019, 20(11): 1262-1270. DOI: 10.1093/ehjci/jez077.
[25]
BOGARAPU S, PUCHALSKI M D, EVERITT M D, et al. Novel cardiac magnetic resonance feature tracking (CMR-FT) analysis for detection of myocardial fibrosis in pediatric hypertrophic cardiomyopathy[J]. Pediatr Cardiol, 2016, 37(4): 663-673. DOI: 10.1007/s00246-015-1329-8.
[26]
LIM C, BLASZCZYK E, RIAZY L, et al. Quantification of myocardial strain assessed by cardiovascular magnetic resonance feature tracking in healthy subjects-influence of segmentation and analysis software[J]. Eur Radiol, 2021, 31(6): 3962-3972. DOI: 10.1007/s00330-020-07539-5.
[27]
FEISST A, KUETTING D L R, DABIR D, et al. Influence of observer experience on cardiac magnetic resonance strain measurements using feature tracking and conventional tagging[J/OL]. IJC Heart Vasc, 2018, 18: 46-51 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/29876503/. DOI: 10.1016/j.ijcha.2018.02.007.
[28]
LI Y M, LIU J, CAO Y K, et al. Predictive values of multiple non-invasive markers for myocardial fibrosis in hypertrophic cardiomyopathy patients with preserved ejection fraction[J/OL]. Sci Rep, 2021, 11(1): 4297 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/33619345/. DOI: 10.1038/s41598-021-83678-z.
[29]
MAHRHOLDT H, SEITZ A. Refining the prognostic value of LGE in hypertrophic cardiomyopathy: presence, extent, and location-what's next?[J]. JACC Cardiovasc Imaging, 2023, 16(9): 1178-1180. DOI: 10.1016/j.jcmg.2023.04.002.
[30]
ASFOUR I, KARIM S, TABRAIZ S A, et al. Late gadolinium enhancement and electrocardiographic associations in hypertrophic cardiomyopathy[J/OL]. Ann Noninvasive Electrocardiol, 2025, 30(4): e70077 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/40464065/. DOI: 10.1111/anec.70077.
[31]
KIAOS A, DASKALOPOULOS G N, KAMPERIDIS V, et al. Quantitative late gadolinium enhancement cardiac magnetic resonance and sudden death in hypertrophic cardiomyopathy: a meta-analysis[J]. JACC Cardiovasc Imaging, 2024, 17(5): 489-497. DOI: 10.1016/j.jcmg.2023.07.005.
[32]
LIU J, ZHAO S H, YU S Q, et al. Patterns of replacement fibrosis in hypertrophic cardiomyopathy[J]. Radiology, 2022, 302(2): 298-306. DOI: 10.1148/radiol.2021210914.
[33]
TODIERE G, NUGARA C, GENTILE G, et al. Prognostic role of late gadolinium enhancement in patients with hypertrophic cardiomyopathy and low-to-intermediate sudden cardiac death risk score[J]. Am J Cardiol, 2019, 124(8): 1286-1292. DOI: 10.1016/j.amjcard.2019.07.023.
[34]
TEDESCHI E, CARANCI F, GIORDANO F, et al. Gadolinium retention in the body: what we know and what we can do[J]. Radiol Med, 2017, 122(8): 589-600. DOI: 10.1007/s11547-017-0757-3.
[35]
GRÜTZEDIEK K, FISCHER R, KURIO G, et al. Rapid MRI assessment of long-axis strain to indicate systolic dysfunction in patients with sickle cell disease[J]. J Magn Reson Imag, 2023, 58(5): 1499-1506. DOI: 10.1002/jmri.28623.
[36]
MĖLINYTĖ-ANKUDAVIČĖ K, MARCINKEVIČIENĖ K, GALNAITIENĖ G, et al. Potential prognostic impact of left-ventricular global longitudinal strain in analysis of whole-heart myocardial mechanics in nonischemic dilated cardiomyopathy[J]. Int J Cardiovasc Imaging, 2024, 40(9): 1941-1949. DOI: 10.1007/s10554-024-03184-x.
[37]
WANG F Q, DENG Y, LI S J, et al. CMR left ventricular strains beyond global longitudinal strain in differentiating light-chain cardiac amyloidosis from hypertrophic cardiomyopathy[J/OL]. Front Cardiovasc Med, 2023, 10: 1108408 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/37206101/. DOI: 10.3389/fcvm.2023.1108408.
[38]
SCHUSTER A, HOR K N, KOWALLICK J T, et al. Cardiovascular magnetic resonance myocardial feature tracking: concepts and clinical applications[J/OL]. Circ Cardiovasc Imaging, 2016, 9(4): e004077 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/27009468/. DOI: 10.1161/CIRCIMAGING.115.004077.
[39]
ARENJA N, RIFFEL J H, FRITZ T, et al. Diagnostic and prognostic value of long-axis strain and myocardial contraction fraction using standard cardiovascular MR imaging in patients with nonischemic dilated cardiomyopathies[J]. Radiology, 2017, 283(3): 681-691. DOI: 10.1148/radiol.2016161184.
[40]
AURICH M, FUCHS P, MÜLLER-HENNESSEN M, et al. Unidimensional longitudinal strain: a simple approach for the assessment of longitudinal myocardial deformation by echocardiography[J]. J Am Soc Echocardiogr, 2018, 31(6): 733-742. DOI: 10.1016/j.echo.2017.12.010.
[41]
AQUINO G J, DECKER J A, SCHOEPF U J, et al. Feasibility of coronary CT angiography-derived left ventricular long-axis shortening as an early marker of ventricular dysfunction in transcatheter aortic valve replacement[J/OL]. Radiol Cardiothorac Imaging, 2022, 4(3): e210205 [2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/35833168/. DOI: 10.1148/ryct.210205.
[42]
BRANN A, MILLER J, ESHRAGHIAN E, et al. Global longitudinal strain predicts clinical outcomes in patients with heart failure with preserved ejection fraction[J]. Eur J Heart Fail, 2023, 25(10): 1755-1765. DOI: 10.1002/ejhf.2947.
[43]
NAGUEH S F, KHAN S U. Left atrial strain for assessment of left ventricular diastolic function: focus on populations with normal LVEF[J]. JACC Cardiovasc Imaging, 2023, 16(5): 691-707. DOI: 10.1016/j.jcmg.2022.10.011.
[44]
CHOI Y J, KIM H K, HWANG I C, et al. Prognosis of patients with hypertrophic cardiomyopathy and low-normal left ventricular ejection fraction[J]. Heart, 2023, 109(10): 771-778. DOI: 10.1136/heartjnl-2022-321853.
[45]
ZHAO X L, LUO K, MA H H, et al. Influence of heart failure phenotypes on prognosis of patients with hypertrophic cardiomyopathy[J/OL]. Heart Lung, 2025, 74: 12-18[2025-08-06]. https://pubmed.ncbi.nlm.nih.gov/40554115/. DOI: 10.1016/j.hrtlng.2025.05.015.

上一篇 心脏磁共振晚期钆增强的左心室熵与心肌纤维化影像标志物在射血分数保留型心衰患者中的相关性及诊断价值的研究
下一篇 四维血流心脏磁共振评估儿童室性期前收缩心室血流动力学特征及其对负荷程度的预测价值
  
诚聘英才 | 广告合作 | 免责声明 | 版权声明
联系电话:010-67113815
京ICP备19028836号-2