Multiple sclerosis (MS) is a demyelinating and inflammatory disease of the central nervous system (CNS). The demyelination process can be repaired by the generation of a new sheath of myelin around the axon, a process termed remyelination. In MS patients, the demyelination-remyelination cycles are highly dynamic. Over the years, magnetic resonance imaging (MRI) has been increasingly used in the diagnosis of MS and it is currently the most useful paraclinical tool to assess this diagnosis. However, conventional MRI pulse sequences are not specific for pathological mechanisms such as demyelination and remyelination. Recently, positron emission tomography (PET) with radiotracer [11C]PIB has become a promising tool to measure in-vivo myelin content changes which is essential to push forward our understanding of mechanisms involved in the pathology of MS, and to monitor individual patients in the context of clinical trials focused on repair therapies. However, PET imaging is invasive due to the injection of a radioactive tracer. Moreover, it is an expensive imaging test and not offered in the majority of medical centers in the world. In this work, by using multisequence MRI, we thus propose a method to predict the parametric map of [11C]PIB PET, from which we derived the myelin content changes in a longitudinal analysis of patients with MS. The method is based on the proposed conditional flexible self-attention GAN (CF-SAGAN) which is specifically adjusted for high-dimensional medical images and able to capture the relationships between the spatially separated lesional regions during the image synthesis process. Jointly applying the sketch-refinement process and the proposed attention regularization that focuses on the MS lesions, our approach is shown to outperform the state-of-the-art methods qualitatively and quantitatively. Specifically, our method demonstrated a superior performance for the prediction of myelin content at voxel-wise level. More important, our method for the prediction of myelin content changes in patients with MS shows similar clinical correlations to the PET-derived gold standard indicating the potential for clinical management of patients with MS.

中文翻译：

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从多序列 MRI 预测 PET 衍生的髓鞘含量，用于多发性硬化症的个体纵向分析

多发性硬化症 (MS) 是一种中枢神经系统 (CNS) 的脱髓鞘和炎症性疾病。脱髓鞘过程可以通过在轴突周围产生新的髓鞘鞘来修复，这一过程称为髓鞘再生。在 MS 患者中，脱髓鞘-髓鞘再生周期是高度动态的。多年来，磁共振成像 (MRI) 越来越多地用于 MS 的诊断，目前它是评估该诊断的最有用的副临床工具。然而，传统的 MRI 脉冲序列并非特定于病理机制，例如脱髓鞘和髓鞘再生。最近，带有放射性示踪剂 [11C]PIB 的正电子发射断层扫描 (PET) 已成为测量体内髓鞘含量变化的有前途的工具，这对于推进我们对 MS 病理学所涉及的机制的理解以及在上下文中监测个体患者至关重要的临床试验侧重于修复疗法。然而，由于注射了放射性示踪剂，PET 成像具有侵入性。此外，它是一种昂贵的成像测试，世界上大多数医疗中心都没有提供。在这项工作中，通过使用多序列 MRI，我们提出了一种预测 [11C]PIB PET 参数图的方法，我们从中得出了 MS 患者纵向分析中髓鞘含量的变化。该方法基于所提出的条件灵活自注意 GAN（CF-SAGAN），该 GAN 专门针对高维医学图像进行调整，能够在图像合成过程中捕捉空间分离病变区域之间的关系。联合应用草图细化过程和建议的关注 MS 病变的注意力正则化，我们的方法在定性和定量上都优于最先进的方法。具体而言，我们的方法在体素水平预测髓鞘含量方面表现出优异的性能。更重要的是，我们预测 MS 患者髓鞘含量变化的方法显示出与 PET 衍生的金标准相似的临床相关性，表明 MS 患者临床管理的潜力。