A doppler-exclusive computational diagnostic framework to enhance conventional 2-D clinical ultrasound with 3-D mitral valve dynamics and cardiac hemodynamics

IF 11.8 1区 医学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Nikrouz Bahadormanesh , Mohamed Abdelkhalek , Zahra Keshavarz-Motamed
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引用次数: 0

Abstract

Mitral valve diseases are prevalent cardiac conditions especially by aging. With their high prevalence, the accessibility, accuracy, and reliability of the diagnostic methods are crucial. Mitral valve dynamics assessment could offer crucial insights into the progression of cardiac deterioration and recovery, significantly influencing patient care, intervention planning, and critical clinical decision-making in scenarios with potentially life-threatening risks. In this study, we developed a Doppler-exclusive computational diagnostic framework to assess mitral valve motion and dynamics as well as cardiac hemodynamics in patients non-invasively and at no risk to the patients. The framework was developed based on transthoracic echocardiogram (TTE) data (N=20), validated against transesophageal echocardiography (TEE) data (N=12) as well as CT data (N=4). In addition, we demonstrated the framework’s diagnostic abilities by providing novel and clinically-relevant analyses and interpretations of clinical data. Based on our findings, patient-specific left ventricular pressure was a strong predictor of stress levels in our cohort of 20 patients, despite being neglected by previous studies. There was a very strong negative correlation between the 3-D finite element-based coaptation area and vena Contracta width (R = -0.8; p < 0.001). Furthermore, the LV conicity index, as the geometrical parameter showing left ventricle dilatation, had a strong positive correlation with end diastolic von Mises stress, used for quantification of leaflet tethering (R = 0.78; p < 0.001). Finally, the patient-specific left ventricular pressure, and the rest length of the chords played a primary role in the biomechanical behavior of the mitral leaflets. The developed framework, while aligned with the current clinical metrics, could provide a strong add-on to the established clinical practice for the diagnosis of mitral valve diseases. Notably, this framework is novel in that it relies solely on standard Doppler ultrasound inputs, requiring no additional imaging or invasive measurements to achieve 3-D assessment. Clinically, the DE-MV-Dyn can be seamlessly applied in routine echocardiography exams to provide clinicians with new patient-specific metrics (e.g., leaflet stress, strain, and dynamic coaptation measures) for improved diagnosis and personalized mitral valve therapy planning.
一个多普勒专属计算诊断框架,以增强传统的二维临床超声与三维二尖瓣动力学和心脏血流动力学
二尖瓣疾病是一种常见的心脏疾病,尤其是由年龄引起的。由于其高患病率,诊断方法的可及性、准确性和可靠性至关重要。二尖瓣动力学评估可以为心脏恶化和恢复的进展提供重要的见解,显著影响患者护理、干预计划和潜在危及生命风险的关键临床决策。在这项研究中,我们开发了一个多普勒专有的计算诊断框架来评估患者的二尖瓣运动和动力学以及心脏血流动力学,无创且对患者没有风险。该框架是基于经胸超声心动图(TTE)数据(N=20)开发的,并通过经食管超声心动图(TEE)数据(N=12)和CT数据(N=4)进行验证。此外,我们通过对临床数据进行新颖的临床相关分析和解释,证明了该框架的诊断能力。根据我们的研究结果,在我们的20例患者队列中,患者特异性左心室压是应激水平的一个强有力的预测因子,尽管以前的研究忽略了这一点。基于三维有限元的贴合面积与收缩静脉宽度呈非常强的负相关(R = -0.8;p <0.001)。此外,作为显示左心室扩张的几何参数,左室圆锥度指数与用于量化小叶栓系的舒张末期von Mises应力有很强的正相关(R = 0.78;p <0.001)。最后,患者特有的左心室压力和二尖瓣的剩余长度在二尖瓣小叶的生物力学行为中起主要作用。开发的框架虽然与当前的临床指标一致,但可以为二尖瓣疾病诊断的既定临床实践提供强有力的补充。值得注意的是,该框架的新颖之处在于,它完全依赖于标准的多普勒超声输入,不需要额外的成像或侵入性测量来实现3-D评估。临床上,DE-MV-Dyn可以无缝应用于常规超声心动图检查,为临床医生提供新的患者特异性指标(如小叶应力、应变和动态适应措施),以改进诊断和个性化二尖瓣治疗计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Medical image analysis
Medical image analysis 工程技术-工程:生物医学
CiteScore
22.10
自引率
6.40%
发文量
309
审稿时长
6.6 months
期刊介绍: Medical Image Analysis serves as a platform for sharing new research findings in the realm of medical and biological image analysis, with a focus on applications of computer vision, virtual reality, and robotics to biomedical imaging challenges. The journal prioritizes the publication of high-quality, original papers contributing to the fundamental science of processing, analyzing, and utilizing medical and biological images. It welcomes approaches utilizing biomedical image datasets across all spatial scales, from molecular/cellular imaging to tissue/organ imaging.
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