基于室间隔自动提取和T2*参数图的地中海贫血患者心脏铁沉积测量方法

Thalassemia is a kind of hereditary hematonosis. Cardiovascular magnetic resonance (CMR) T2* is the method of choice for the assessment of myocardial iron, which is needed to detect iron early and guide chelation therapy in hospital. It is highly importmant for estalish a fully automated myocardial iron concentration (MIC) measurements for the major thalassemia. Barriers to CMR T2* assessment exist. The T2* map, which reflects the spatial distribution of MIC, cannot be efficiently and accurately caculated due to the impact from noise. There is no reliable and easy-to-implement interventricular septum extraction method for the whole cardiac T2* measurement which indicates the total MIC and has been shown to be more reproducibile..In this project, we plan to extend the nonlocal means algorithm to myocardial T2* mapping introducing a novel distance measure to include similarities between exponential decay curves based on a noise correction model for T2* relaxometry. After that, we will use the multi-atlas registration and level sets, using KL distance and local neighborhood information, for the myocardium extraction.By combination of the classical image segmentation methods(thresholding, local fuzzy clustering, connected region labeled and etc), we will segmente the interventricular septum taking spatiallocationinto account to exclude the pixels which are likely affected by the partial volume effect for calculating the representive T2* value. .This project would provide improved, reliable and easy-to-implement T2* measurment methods for the quantificaiton of MIC, and improve the therapy management of beta-thalassemia major patients.

地中海贫血症是一种严重危害人类健康的血液遗传病，利用心脏磁共振T2*参数方法准确地测量心脏铁沉积对于指导与监控地贫患者的除铁治疗具有重要的临床意义。这就急切地需要建立一种全自动的心脏铁沉积测量方法，然而目前尚无不受噪声影响的反映心铁空间分布的T2*图和室间隔区域自动提取模型。.本课题拟采用基于磁共振弛豫衰减曲线距离约束的非局部均值滤波和噪声补偿模型以快速精确去除非零背景噪声对T2*估计的影响进而准确求解T2*图；并在此基础上拟采用基于多图谱配准和基于KL距离加权和局部邻域信息的CV模型融合分割方法以实现左心室全心肌组织自动提取，结合经典的形态学操作、局部模糊聚类、阈值分割等方法自动提取右心室血池，最后利用解剖位置信息提取室间隔区域以计算室间隔区域的代表性T2*值。.本项目研究将为临床地贫患者提供一种全自动心脏铁沉积测量模型，辅助临床医生对地贫患者进行铁含量分级诊断和除铁治疗。

地中海贫血病是全球最大的单基因遗传病之一。地中海贫血患者长期输血使其生长发育接近正常和防止骨骼病变，可以改善他们的生活并延长他们的生命，然而定期输血容易造成含铁血黄素沉着症，损伤肝脏、心脏和胰腺组织，进而导致病发率和死亡率增加。临床上，一般是给予铁螯合剂治疗以便去除身体内多余的铁，但是由于其化学毒性，治疗时会伴随着并发症。准确地测量和控制人体的铁含量对诊断和评估铁螯合剂治疗具有重要的意义。研究表明，磁共振R2*(1/T2*)参数与铁浓度有很好的相关性，室间隔区域不易受到脂肪、肝脏、肺等组织敏感性的影响，其T2*值可以表示心脏的铁浓度。本项目研究基于磁共振T2*的精确心铁测量，经过三年的研究，本项目实现了预期目标。本项目(1)完成了R2*图的精确测量方法研究，即提出一种基于自适应正则化的R2*参数拟合方法，能够直接从噪声图像计算得到准确的R2*图，需要进一步拓展到心脏图像。(2)完成了全自动心肌组织的提取，采用圆形霍夫变换、带空间信息约束的模糊C均值、基于局部邻域信息和熵加权的高斯约束CV模型来提取黑血磁共振图像的左心室心肌组织，利用基于2D梯度算子和多尺度的活动形状模型分割亮血磁共振图像的左心室心肌组织，消除了观察者主观性的影响。(3)结合解剖位置信息、形态学操作和阈值分割等方法提取室间隔区域，结果表明该方法具有较高的精确性和可重复性。(4)磁共振成像的质量与参数测量结果密切相关，项目组对成像方法和降低成像噪声进行了初步研究，在视觉上提高了图像质量，对利用磁共振成像辅助医生进行疾病的诊断具有重要的意义。以上研究成果为临床提供了简单易用的心铁浓度测量方法，为指导和监控地中海贫血治疗提供了可靠的依据。