Dopamine transporter (DAT) imaging is commonly used for monitoring Parkinson's disease (PD), where striatal DAT uptake amount is computed to assess PD severity. However, DAT imaging has a high cost and the risk of radiance exposure and is not available in general clinics. Recently, MRI patch of the nigral region has been proposed as a safer and easier alternative. This paper proposes a symmetric regressor for predicting the DAT uptake amount from the nigral MRI patch. Acknowledging the symmetry between the right and left nigrae, the proposed regressor incorporates a paired input-output model that simultaneously predicts the DAT uptake amounts for both the right and left striata. Moreover, it employs a symmetric loss that imposes a constraint on the difference between right-to-left predictions, resembling the high correlation in DAT uptake amounts in the two lateral sides. Additionally, we propose a symmetric Monte-Carlo (MC) dropout method for providing a fruitful uncertainty estimate of the DAT uptake prediction, which utilizes the above symmetry. We evaluated the proposed approach on 734 nigral patches, which demonstrated significantly improved performance of the symmetric regressor compared with the standard regressors while giving better explainability and feature representation. The symmetric MC dropout also gave precise uncertainty ranges with a high probability of including the true DAT uptake amounts within the range.

翻译：多巴胺转运体（DAT）成像常用于监测帕金森病（PD），通过计算纹状体DAT摄取量评估帕金森病严重程度。然而，DAT成像成本高、存在辐射暴露风险，且未在普通诊所普及。近期，黑质区MRI补丁被提出作为一种更安全、更便捷的替代方案。本文提出一种对称回归器，用于从黑质MRI补丁预测DAT摄取量。考虑到左右黑质的对称性，该回归器采用配对输入输出模型，可同时预测左右纹状体的DAT摄取量。此外，它采用对称损失函数对左右侧预测差异施加约束，以模拟两侧DAT摄取量的高度相关性。进一步地，我们提出对称蒙特卡洛（MC）丢弃法，通过利用上述对称性为DAT摄取预测提供丰富的置信度估计。我们在734个黑质补丁上评估了该方法，结果表明对称回归器相较于标准回归器性能显著提升，同时具有更好的可解释性和特征表示能力。对称MC丢弃法还能提供精确的置信区间，且该区间以高概率包含真实的DAT摄取量。