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Thalamus Optimized Multi Atlas Segmentation (THOMAS): fast, fully automated segmentation of thalamic nuclei from structural MRI

机译:Thalamus优化多标志性分割(托马斯):来自结构MRI的快速,全自动分割丘脑核

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The thalamus and its nuclei are largely indistinguishable on standard T1 or T2 weighted MRI. While diffusion tensor imaging based methods have been proposed to segment the thalamic nuclei based on the angular orientation of the principal diffusion tensor, these are based on echo planar imaging which is inherently limited in spatial resolution and suffers from distortion. We present a multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging that segments the thalamus into 12 nuclei with computation times on the order of 10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from healthy volunteers and patients with multiple sclerosis by comparing against manual segmentations delineated by a neuroradiologist, guided by the Morel atlas. Segmentation accuracy was very high, with uniformly high Dice indices: at least 0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7 even for small structures such as the habenular, centromedian, and lateral and medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes of the right anteroventral, right ventral posterior lateral, and both right and left pulvinar nuclei were significantly lower in MS patients compared to controls, after adjusting for age, sex and intracranial volume. Lastly, we evaluated the potential of this method for targeting the Vim nucleus for deep brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus segmented from pre-operative data on post-operative data. The locations of the ablated region and active DBS contact corresponded well with the segmented Vim nucleus. Our fast, direct structural MRI based segmentation method opens the door for MRI guided intra-operative procedures like thalamotomy and asleep DBS electrode placement as well as for accurate quantification of thalamic nuclear volumes to follow progression of neurological disorders.
机译:丘脑及其核在标准T1或T2加权MRI上很大地区别。虽然已经提出了基于基于基于的基于基于主扩散张量的角度的核核的方法,但是基于回声平面成像,其在空间分辨率上固有地限制并且遭受变形。我们介绍了一种基于白品 - 无效的MP-RAGE成像的多拟标菌分段技术,将丘脑分段为12个核,在台式电脑上的10分钟的10分钟的计算时间;我们称之为托马斯(丘脑优化的多atlas分段)。通过比较由羊毛地理位置的神经皮层划分的手动分割,对从健康志愿者和多发性硬化患者获得的7T MRI数据严格评估托马斯。分割精度非常高,具有均匀的高骰子指数:至少0.85细胞核大像即使对于较小的结构枕和背中部核和至少0.7,如缰,中央中,并且横向和内侧膝状核。体积相似性索引为较大核的较小核的0.82距离为0.97。体积显示,与对照相比,在调整年龄,性别和颅内体积后,MS患者患者右侧饲养术,右侧腹侧侧向和右侧和左侧脉冲核的体积显着降低。最后,我们通过将Vim核覆盖在术后数据上,通过将Vim核分段覆盖在术后数据上,评估该方法的潜在靶向深脑手术和聚焦超声肌瘤的潜力。消融区域和有源DBS触点的位置与分段的Vim核相对应良好。我们的快速直接的结构MRI基础分割方法为MRI引导术内手术的门打开,如硫肌瘤和睡眠DBS电极放置,以及准确定量丘脑核体积以追随神经系统疾病的进展。

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