A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning
A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning
复制标题
用于预测重构和治疗计划的法洛四联症右心室统计模型
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
N. Ayache
中科院分区：
文献类型：
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作者：
Tommaso Mansi;S. Durrleman;B. Bernhardt;Maxime Sermesant;H. Delingette;Ingmar Voigt;P. Lurz;A. Taylor;J. Blanc;Y. Boudjemline;X. Pennec;N. Ayache
法洛四联症修复后的患者常伴有慢性肺动脉瓣关闭不全和右心室极度扩张。为了减少风险因素，必须重新植入新的肺动脉瓣。然而，由于RV形状和病理演变的变异性很大，确定再次介入的最佳时机是一项临床挑战。本研究旨在量化生长和再结晶对舒张末期RV解剖结构的区域影响。最终目标是在临床变量中确定形状的预测因子，以建立预测RV重塑的统计模型。所提出的方法依赖于基于电流和LDDMM算法的前向模型来估计18个患者的无偏模板和朝向每个个体形状的变形。进行横截面多变量分析以评估体表面积、三尖瓣和经二尖瓣瓣膜置换对RV形状的影响，发现具有统计学意义的变形模式与临床相关。典型相关分析产生了一个生成模型，成功地测试了两个新的患者。
Patients with repaired Tetralogy of Fallot commonly suffer from chronic pulmonary valve regurgitations and extremely dilated right ventricle (RV). To reduce risk factors, new pulmonary valves must be re-implanted. However, establishing the best timing for re-intervention is a clinical challenge because of the large variability in RV shape and in pathology evolution. This study aims at quantifying the regional impacts of growth and regurgitations upon the end-diastolic RV anatomy. The ultimate goal is to determine, among clinical variables, predictors for the shape in order to build a statistical model that predicts RV remodelling. The proposed approach relies on a forward model based on currents and LDDMM algorithm to estimate an unbiased template of 18 patients and the deformations towards each individual shape. Cross-sectional multivariate analyses are carried out to assess the effects of body surface area, tricuspid and transpulmonary valve regurgitations upon the RV shape, The statistically significant deformation modes were found clinically relevant. Canonical correlation analysis yielded a generative model that was successfully tested on two new patients.