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使用白质消除成像的深度学习重建来描绘用于癫痫神经调节的中央中核。

Delineation of the Centromedian Nucleus for Epilepsy Neuromodulation Using Deep Learning Reconstruction of White Matter-Nulled Imaging.

作者信息

Ryan Megan V, Satzer David, Hu Houchun, Litwiller Daniel V, Rettmann Dan W, Tanabe Jody, Thompson John A, Ojemann Steven G, Kramer Daniel R

机构信息

From the Department of Neurosurgery (M.V.R., D.S., J.A.T., S.G.O., D.R.K.), University of Colorado Anschutz Medical Campus, Aurora, Colorado

From the Department of Neurosurgery (M.V.R., D.S., J.A.T., S.G.O., D.R.K.), University of Colorado Anschutz Medical Campus, Aurora, Colorado.

出版信息

AJNR Am J Neuroradiol. 2025 Sep 2;46(9):1868-1874. doi: 10.3174/ajnr.A8766.

Abstract

BACKGROUND AND PURPOSE

Neuromodulation of the centromedian nucleus (CM) of the thalamus has shown promise in treating refractory epilepsy, particularly for idiopathic generalized epilepsy and Lennox-Gastaut syndrome. However, precise targeting of CM remains challenging. The combination of deep learning reconstruction (DLR) and fast gray matter acquisition T1 inversion recovery (FGATIR) offers potential improvements in visualization of CM for deep brain stimulation (DBS) targeting. The goal of the study was to evaluate the visualization of the putative CM on DLR-FGATIR and its alignment with atlas-defined CM boundaries, with the aim of facilitating direct targeting of CM for neuromodulation.

MATERIALS AND METHODS

This retrospective study included 12 patients with drug-resistant epilepsy treated with thalamic neuromodulation by using DLR-FGATIR for direct targeting. Postcontrast-T1-weighted MRI, DLR-FGATIR, and postoperative CT were coregistered and normalized into Montreal Neurological Institute (MNI) space and compared with the Morel histologic atlas. Contrast-to-noise ratios were measured between CM and neighboring nuclei. CM segmentations were compared between an experienced rater, a trainee rater, the Morel atlas, and the Thalamus Optimized Multi Atlas Segmentation (THOMAS) atlas (derived from expert segmentation of high-field MRI) by using the Sorenson-Dice coefficient (Dice score, a measure of overlap) and volume ratios. The number of electrode contacts within the Morel atlas CM was assessed.

RESULTS

On DLR-FGATIR, CM was visible as an ovoid hypointensity in the intralaminar thalamus. Contrast-to-noise ratios were highest ( < .001) for the mediodorsal and medial pulvinar nuclei. Dice score with the Morel atlas CM was higher (median 0.49, interquartile range 0.40-0.58) for the experienced rater ( < .001) than the trainee rater (0.32, 0.19-0.46) and no different ( = .32) than the THOMAS atlas CM (0.56, 0.55-0.58). Both raters and the THOMAS atlas tended to under-segment the lateral portion of the Morel atlas CM, reflected by smaller segmentation volumes ( < .001). All electrodes targeting CM based on DLR-FGATIR traversed the Morel atlas CM.

CONCLUSIONS

DLR-FGATIR permitted visualization and delineation of CM commensurate with a group atlas derived from high-field MRI. This technique provided reliable guidance for accurate electrode placement within CM, highlighting its potential use for direct targeting.

摘要

背景与目的

丘脑中央中核(CM)的神经调节在治疗难治性癫痫方面已显示出前景,特别是对于特发性全身性癫痫和Lennox-Gastaut综合征。然而,精确靶向CM仍然具有挑战性。深度学习重建(DLR)与快速灰质采集T1反转恢复(FGATIR)相结合,为深部脑刺激(DBS)靶向中CM的可视化提供了潜在的改善。本研究的目的是评估DLR-FGATIR上假定CM的可视化及其与图谱定义的CM边界的对齐情况,以促进CM神经调节的直接靶向。

材料与方法

这项回顾性研究纳入了12例耐药性癫痫患者,他们接受了丘脑神经调节治疗,使用DLR-FGATIR进行直接靶向。将对比增强T1加权MRI、DLR-FGATIR和术后CT进行配准并归一化到蒙特利尔神经病学研究所(MNI)空间,并与莫雷尔组织学图谱进行比较。测量CM与相邻核之间的对比噪声比。通过使用索伦森-迪赛系数(迪赛分数,一种重叠度量)和体积比,比较经验丰富的评分者、实习评分者、莫雷尔图谱和丘脑优化多图谱分割(THOMAS)图谱(源自高场MRI的专家分割)之间的CM分割。评估莫雷尔图谱CM内的电极触点数量。

结果

在DLR-FGATIR上,CM在丘脑板内核中表现为椭圆形低信号。背内侧核和内侧枕核的对比噪声比最高(<.001)。经验丰富的评分者与莫雷尔图谱CM的迪赛分数更高(中位数0.49,四分位间距0.40-0.58)(<.001),高于实习评分者(0.32,0.19-0.46),与THOMAS图谱CM(0.56,0.55-0.58)无差异(=.32)。评分者和THOMAS图谱都倾向于对莫雷尔图谱CM的外侧部分分割不足,这通过较小的分割体积反映出来(<.001)。所有基于DLR-FGATIR靶向CM的电极都穿过了莫雷尔图谱CM。

结论

DLR-FGATIR允许可视化和描绘与源自高场MRI的组图谱相称的CM。该技术为CM内准确的电极放置提供了可靠的指导,突出了其直接靶向的潜在用途。

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