BACKGROUND Ex-vivo cardiovascular magnetic resonance (CMR) imaging has played an important role in the validation of in-vivo CMR characterization of pathological processes. However, comparison between in-vivo and ex-vivo imaging remains challenging due to shape changes occurring between the two states, which may be non-uniform across the diseased heart. A novel two-step process to facilitate registration between ex-vivo and in-vivo CMR was developed and evaluated in a porcine model of chronic myocardial infarction (MI). METHODS Seven weeks after ischemia-reperfusion MI, 12 swine underwent in-vivo CMR imaging with late gadolinium enhancement followed by ex-vivo CMR 1 week later. Five animals comprised the control group, in which ex-vivo imaging was undertaken without any support in the LV cavity, 7 animals comprised the experimental group, in which a two-step registration optimization process was undertaken. The first step involved a heart specific flexible 3D printed scaffold generated from in-vivo CMR, which was used to maintain left ventricular (LV) shape during ex-vivo imaging. In the second step, a non-rigid co-registration algorithm was applied to align in-vivo and ex-vivo data. Tissue dimension changes between in-vivo and ex-vivo imaging were compared between the experimental and control group. In the experimental group, tissue compartment volumes and thickness were compared between in-vivo and ex-vivo data before and after non-rigid registration. The effectiveness of the alignment was assessed quantitatively using the DICE similarity coefficient. RESULTS LV cavity volume changed more in the control group (ratio of cavity volume between ex-vivo and in-vivo imaging in control and experimental group 0.14 vs 0.56, p < 0.0001) and there was a significantly greater change in the short axis dimensions in the control group (ratio of short axis dimensions in control and experimental group 0.38 vs 0.79, p < 0.001). In the experimental group, prior to non-rigid co-registration the LV cavity contracted isotropically in the ex-vivo condition by less than 20% in each dimension. There was a significant proportional change in tissue thickness in the healthy myocardium (change = 29 ± 21%), but not in dense scar (change = - 2 ± 2%, p = 0.034). Following the non-rigid co-registration step of the process, the DICE similarity coefficients for the myocardium, LV cavity and scar were 0.93 (±0.02), 0.89 (±0.01) and 0.77 (±0.07) respectively and the myocardial tissue and LV cavity volumes had a ratio of 1.03 and 1.00 respectively. CONCLUSIONS The pattern of the morphological changes seen between the in-vivo and the ex-vivo LV differs between scar and healthy myocardium. A 3D printed flexible scaffold based on the in-vivo shape of the LV cavity is an effective strategy to minimize morphological changes in the ex-vivo LV. The subsequent non-rigid registration step further improved the co-registration and local comparison between in-vivo and ex-vivo data.

中文翻译：

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使用心脏特异性柔性 3D 打印丙烯酸支架结合非刚性配准，改进了体外和体内心血管磁共振图像的联合配准。

背景离体心血管磁共振（CMR）成像在病理过程的体内CMR表征的验证中发挥了重要作用。然而，由于两种状态之间发生的形状变化，体内和体外成像之间的比较仍然具有挑战性，这在患病心脏中可能是不均匀的。在慢性心肌梗塞 (MI) 的猪模型中开发和评估了一种新的两步过程，以促进体外和体内 CMR 之间的注册。方法 缺血再灌注 MI 后 7 周，12 头猪接受了体内 CMR 成像，钆后期增强，1 周后进行了离体 CMR。对照组有 5 只动物，其中在 LV 腔内没有任何支撑的情况下进行离体成像，实验组有 7 只动物，其中进行了两步配准优化过程。第一步涉及由体内 CMR 生成的心脏特异性柔性 3D 打印支架，用于在体外成像期间保持左心室 (LV) 形状。在第二步中，应用非刚性配准算法来对齐体内和体外数据。在实验组和对照组之间比较体内和体外成像之间的组织尺寸变化。在实验组中，比较了非刚性注册前后的体内和体外数据之间的组织隔室体积和厚度。使用 DICE 相似系数定量评估比对的有效性。结果 LV 腔容积在对照组中变化更大（对照组和实验组的体外和体内成像之间的腔容积比为 0.14 对 0.56，p < 0.0001）并且在对照组（对照组和实验组的短轴尺寸比为 0.38 对 0.79，p < 0.001）。在实验组中，在非刚性共同注册之前，LV 腔在离体条件下各向同性收缩小于 20%。健康心肌的组织厚度有显着的比例变化（变化 = 29 ± 21%），但在致密疤痕中没有（变化 = - 2 ± 2%，p = 0.034）。在该过程的非刚性联合配准步骤之后，心肌、左室腔和疤痕的 DICE 相似系数为 0.93 (±0.02), 0。分别为 89 (±0.01) 和 0.77 (±0.07)，心肌组织和 LV 腔容积之比分别为 1.03 和 1.00。结论 在体内和体外 LV 之间观察到的形态变化模式在疤痕和健康心肌之间有所不同。基于 LV 腔体内形状的 3D 打印柔性支架是一种有效的策略，可以最大限度地减少体外 LV 的形态变化。随后的非刚性注册步骤进一步改进了体内和体外数据之间的共同注册和局部比较。基于 LV 腔体内形状的 3D 打印柔性支架是一种有效的策略，可以最大限度地减少体外 LV 的形态变化。随后的非刚性注册步骤进一步改进了体内和体外数据之间的共同注册和局部比较。基于 LV 腔体内形状的 3D 打印柔性支架是一种有效的策略，可以最大限度地减少体外 LV 的形态变化。随后的非刚性注册步骤进一步改进了体内和体外数据之间的共同注册和局部比较。