The functional analysis of the left atrium (LA) is important for evaluating
cardiac health and understanding diseases like atrial fibrillation. Cine MRI is
ideally placed for the detailed 3D characterisation of LA motion and
deformation, but it is lacking appropriate acquisition and analysis tools. In
this paper, we present Analysis for Left Atrial Displacements and Deformations
using unsupervIsed neural Networks, \textit{Aladdin}, to automatically and
reliably characterise regional LA deformations from high-resolution 3D Cine
MRI. The tool includes: an online few-shot segmentation network (Aladdin-S), an
online unsupervised image registration network (Aladdin-R), and a strain
calculations pipeline tailored to the LA. We create maps of LA Displacement
Vector Field (DVF) magnitude and LA principal strain values from images of 10
healthy volunteers and 8 patients with cardiovascular disease (CVD). We
additionally create an atlas of these biomarkers using the data from the
healthy volunteers. Aladdin is able to accurately track the LA wall across the
cardiac cycle and characterize its motion and deformation. The overall DVF
magnitude and principal strain values are significantly higher in the healthy
group vs CVD patients: $2.85 \pm 1.59~mm$ and $0.09 \pm 0.05$ vs $1.96 \pm
0.74~mm$ and $0.03 \pm 0.04$, respectively. The time course of these metrics is
also different in the two groups, with a more marked active contraction phase
observed in the healthy cohort. Finally, utilizing the LA atlas allows us to
identify regional deviations from the population distribution that may indicate
focal tissue abnormalities. The proposed tool for the quantification of novel
regional LA deformation biomarkers should have important clinical applications.
The source code, anonymized images, generated maps and atlas are publicly
available: this https URL

使用自动化工具 Aladdin 从高分辨率三维 Cine MRI 图像中可靠地表征左心房（LA）区域变形的无监督神经网络，生成 LA 位移矢量场和主应变数值图，发现健康组与心血管疾病（CVD）患者之间在位移幅值和主应变数值上有显著差异，并利用 LA 图谱识别个体与整体分布不一致的区域异常，该工具具有重要的临床应用潜力。