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使用 χ 分离对白质和皮质多发性硬化病变进行髓鞘再生定量。

Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions.

机构信息

From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY.

出版信息

Neurology. 2024 Sep 24;103(6):e209604. doi: 10.1212/WNL.0000000000209604. Epub 2024 Aug 30.

DOI:10.1212/WNL.0000000000209604
PMID:39213476
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11362958/
Abstract

BACKGROUND AND OBJECTIVES

Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals.

METHODS

This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models.

RESULTS

Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both < 0.001). Younger age ( < 0.001, = -5.111 × 10), lower disability ( = 0.04, = -2.352 × 10), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], < 0.001; vs secondary progressive 0.0004 [IQR 0.01], < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS ( = 0.015, = -6.686 × 10).

DISCUSSION

χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

摘要

背景与目的

髓鞘和铁在多发性硬化症(MS)病变的再髓鞘化过程中起着至关重要的作用。χ 分离是一种应用于多回波 T2*-数据和 T2 数据的新型生物物理模型,可估计髓鞘和铁对获得的磁化率信号的贡献。我们使用该方法研究了 MS 患者和健康个体的病变和非病变脑区的髓鞘和铁水平。

方法

本前瞻性 MS 队列研究纳入了符合 2017 年 McDonald 标准的 MS 患者和年龄在 18 岁及以上、无其他神经合并症的健康个体。参与者在基线和 2 年后接受 MRI 检查,包括多回波 GRE(T2*)和 FAST(T2)序列。使用 χ 分离,我们生成了髓鞘敏感和铁敏感的磁化率图。在液体衰减反转恢复和磁化准备 2 快速梯度回波图像上分别对脑白质病变(WMLs)、皮质病变(CLs)、周围正常表现的白质(NAWM)和正常表现的灰质进行分割。使用 Wilcoxon 秩和检验进行横截面组间比较,使用 Wilcoxon 符号秩检验进行纵向分析。使用线性回归模型评估与临床结局(疾病表型、年龄、性别、疾病持续时间、用扩展残疾状况量表(EDSS)测量的残疾程度、神经丝轻链水平以及 T2 病变数量和体积)的相关性。

结果

在 168 名 MS 患者(中位数[四分位距(IQR)]年龄 47.0[21.7]岁;101 名女性;6898 个 WMLs,775 个 CLs)和 103 名健康个体(年龄 33.0[10.5]岁,57 名女性)中,108 名和 62 名分别在中位数为 2 年的时间点进行了随访(IQR 0.1;5030 个 WMLs,485 个 CLs)。在基线时,WML 的髓鞘(中位数 0.025[IQR 0.015]ppm)和铁(0.017[0.015]ppm)低于相应的 NAWM(髓鞘 0.030[0.012]ppm;铁 0.019[0.011]ppm;均 < 0.001)。2 年后,髓鞘(0.027[0.014]ppm)和铁均增加(0.018[0.015]ppm;均 < 0.001)。年龄较小( < 0.001, = -5.111×10)、残疾程度较低( = 0.04, = -2.352×10)、缓解复发型表型(RRMS,0.003[0.01]vs原发性进展型 0.002[IQR 0.01], < 0.001;vs继发性进展型 0.0004[IQR 0.01], < 0.001)与再髓鞘化相关。髓鞘的增加与 EDSS 测量的临床改善相关( = 0.015, = -6.686×10)。

讨论

χ 分离是一种应用于多回波 T2*-图像和 T2 图像的新型数学模型,表明年轻的 RRMS 患者,残疾程度较低,具有更高的再髓鞘化能力,与 2 年随访期间的临床残疾相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/22e99abdbf1a/WNL-2023-007770f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/9c42d8a8d931/WNL-2023-007770f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/68a029703807/WNL-2023-007770f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/6f707484da5c/WNL-2023-007770f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/57497ff3c1de/WNL-2023-007770f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/22e99abdbf1a/WNL-2023-007770f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/9c42d8a8d931/WNL-2023-007770f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/f903ea41932c/WNL-2023-007770f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/68a029703807/WNL-2023-007770f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/6f707484da5c/WNL-2023-007770f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/57497ff3c1de/WNL-2023-007770f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0fe/11362958/22e99abdbf1a/WNL-2023-007770f6.jpg

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