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Predicting disease-related MRI patterns of multiple sclerosis through GAN-based image editing
Zeitschrift fur Medizinische Physik ( IF 2 ) Pub Date : 2023-12-23 , DOI: 10.1016/j.zemedi.2023.12.001
Daniel Güllmar , Wei-Chan Hsu , Jürgen R. Reichenbach

Introduction

Multiple sclerosis (MS) is a complex neurodegenerative disorder that affects the brain and spinal cord. In this study, we applied a deep learning-based approach using the StyleGAN model to explore patterns related to MS and predict disease progression in magnetic resonance images (MRI).

Methods

We trained the StyleGAN model unsupervised using T1-weighted GRE MR images and diffusion-based ADC maps of MS patients and healthy controls. We then used the trained model to resample MR images from real input data and modified them by manipulations in the latent space to simulate MS progression. We analyzed the resulting simulation-related patterns mimicking disease progression by comparing the intensity profiles of the original and manipulated images and determined the brain parenchymal fraction (BPF).

Results

Our results show that MS progression can be simulated by manipulating MR images in the latent space, as evidenced by brain volume loss on both T1-weighted and ADC maps and increasing lesion extent on ADC maps.

Conclusion

Overall, this study demonstrates the potential of the StyleGAN model in medical imaging to study image markers and to shed more light on the relationship between brain atrophy and MS progression through corresponding manipulations in the latent space.



中文翻译:

通过基于 GAN 的图像编辑预测多发性硬化症的疾病相关 MRI 模式

介绍

多发性硬化症 (MS) 是一种影响大脑和脊髓的复杂神经退行性疾病。在这项研究中,我们应用基于深度学习的方法,使用 StyleGAN 模型来探索与多发性硬化症相关的模式并预测磁共振图像 (MRI) 中的疾病进展。

方法

我们使用多发性硬化症患者和健康对照的 T 1加权 GRE MR 图像和基于扩散的 ADC 图来无监督地训练 StyleGAN 模型。然后,我们使用经过训练的模型从真实输入数据中重新采样 MR 图像,并通过潜在空间中的操作对其进行修改以模拟 MS 进展。我们通过比较原始图像和处理图像的强度分布,分析了模拟疾病进展的模拟相关模式,并确定了脑实质分数(BPF)。

结果

我们的结果表明,可以通过操纵潜在空间中的 MR 图像来模拟 MS 进展,如 T 1加权和 ADC 图上的脑容量损失以及 ADC 图上的病变范围增加所证明的那样。

结论

总体而言,这项研究证明了 StyleGAN 模型在医学成像中研究图像标记的潜力,并通过对潜在空间进行相应的操作来更多地阐明脑萎缩和多发性硬化症进展之间的关系。

更新日期:2023-12-23
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