A comprehensive computational model of myocardial blood flow

摘要（非专业术语）患者有各种形状、大小和年龄，有各种各样的生活方式、活动水平和期望。医疗干预没有系统地考虑到这些因素。心脏病是我们这个时代最常见的主要疾病，心脏病患者就是一个很好的例子。他们经常在心脏的几根血管中出现狭窄和堵塞。医生对病人影响的评估通常是不准确的，而且是基于医学成像，而医学成像通常不善于评估变窄对血流的影响。不同血管的几种变窄的累积效应尤其成问题。为了解决这些问题，我们小组开发了一个模型，可以预测特定动脉狭窄的影响。这个提议的挑战是扩展我们的数学模型来预测心脏所有主要动脉的血液流动。这将使医生能够计划最有效的治疗（如球囊血管成形术或支架植入术，以打开动脉），使患者受益最大，并发症风险最小，费用最少。我们建议通过有效的诊断（所有受影响冠状动脉的虚拟FFR）来优化护理，以提供患者特异性预测和基于证据的干预-冠状动脉血运重建，通常通过经皮冠状动脉介入治疗，在阳性FFR（<0.80）的指导下。生理指标对于个体做出正确的治疗决定至关重要。对于患有冠状动脉疾病的患者，分数血流储备（FFR），即使用压敏金属丝测量狭窄血管的血流限制，已被证明比简单地在医学图像（血管造影）上对解剖狭窄程度进行视觉评估更成功，因为人眼是不准确的。一般来说，对于特定病变，FFR值为0.80已被证实为有用的阈值，低于该值治疗是有价值的，高于该值治疗很少或没有益处。我们已经开发了从医学图像（血管造影）计算FFR的跟踪记录。几乎所有患有严重冠状动脉疾病的患者（英国每年25万例）都要进行血管造影，而使用压力线的ffr则没有。因此，我们的FFR模型有可能省去插入压力线的需要，但更重要的是为那些根本没有压力线的患者提供FFR。目前，我们可以准确地模拟成像良好的冠状动脉的FFR。其他系统已经开发出来，但我们的系统结合了临床参数，允许个性化的值。第二位导师Morris博士对我们的系统进行了改进，当与压力导线一起使用时，可以计算冠状动脉的血流量。绝对血流比压力梯度更可能与心肌灌注、症状和因血运重建引起的改善相关。

Abstract (Lay terminology)Patients come in all shapes, sizes and ages, with a wide variety of lifestyles, activity levels and expectations. Medical interventions do not take these factors into account in a systematicway. Patients with heart disease, the most common major illness of our time, are a case in point. They frequently have narrowings and blockages in several blood vessels in the heart.Doctors' assessments of effect upon the patient are often inaccurate, and based upon medical imaging, which is often not good at assessing the effect of narrowings upon blood flow. Thecumulative effect of several narrowings in different vessels is particularly problematic. To solve these problems, in our group we have developed a model which can predict the impactof a narrowing in a particular artery. The challenge in this proposal is to extend our mathematical model to predict the blood flow through all the major arteries of the heart. Thiswill enable doctors to plan the most effective treatment (such as balloon angioplasty or stenting, to open up the arteries) with maximum benefit to the patient, minimum risk ofcomplications, and least expense. We propose optimising care through effective diagnosis (virtual FFRs in all affected coronary arteries), to provide patient-specific prediction andevidence-based intervention -coronary revascularisation, usually by percutaneous coronary intervention, guided by a positive FFR (<0.80).BackgroundPhysiological measures are of critical importance to make the right therapeutic decisions for individuals. For patients with coronary artery disease, fractional flow reserve (FFR), ameasure of the restriction of blood flow through a narrowed vessel using a pressure-sensitive wire, has proved more successful than simply making a visual assessment of the degree ofanatomical narrowing on medical images (the angiogram) because the human eye is inaccurate. In general, an FFR value of 0.80 has been validated as useful threshold at a givenlesion, below which treatment is valuable, and above which it confers little or no benefit. We have developed a track record in the computational estimation of FFR from medicalimages (angiograms). Angiograms are obtained on almost all patients with severe coronary disease, (250,000 in the UK p.a.) whereas FFRs, using a pressure wire, are not. Therefore ourFFR models have the potential to dispense with the need for inserting the pressure wire, but more importantly provide an FFR for patients who otherwise would not have one at all. Wecan currently accurately model FFR in a well imaged coronary artery. Other systems have been developed, but ours incorporates clinical parameters to allow personalised values. Thesecond supervisor, Dr Morris, has adapted our system, when used with a pressure wire, to calculate volumetric coronary artery blood flow. Absolute flow rather than pressure gradientsis arguably more relevant to myocardial perfusion, symptoms and improvement due to revascularisation.