Palo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Psychiatry, Stanford University, Stanford, CA 94305, United States.
Palo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Harvard Medical School, Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA 00215, United States.
Neuroimage Clin. 2018 Mar 16;18:553-559. doi: 10.1016/j.nicl.2018.01.020. eCollection 2018.
Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12 years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies.
颈动脉血运重建（内膜切除术、支架置入术）可预防中风；然而，与该操作相关的栓塞较为常见，导致弥散加权磁共振成像（DWI）易于识别的小的脑损伤。了解这些损伤的临床意义的一个关键障碍一直是缺乏一种统计方法来识别易损脑区。问题是这些损伤小、数量多且不重叠。在这里，我们使用一种新方法，即微损伤收敛分析（CAML）技术，来解决这个问题，这是解剖似然分析（ALE）的扩展。该方法结合了手动损伤追踪、基于已知损伤模式的约束和收敛分析，将易损区域表示为概率性脑图谱。在 12 年的时间里，我们进行了两项研究，一项在活跃的血管外科诊所进行。在对 126 名患者进行的 1.5T MRI 分析中进行了初步研究，随后在另一组 80 名患者的 3T MRI 中进行了交叉验证。在 CAML 中，手动定义损伤并确定中心点。根据手术侧对大脑进行配准，因为这一因素有力地决定了损伤的分布。对每组大脑进行了基于收敛的分析。结果表明，最一致的易损区域是运动和运动前皮质区。两组共同的较小区域包括额外侧前额皮质和内侧顶叶区域。运动皮质的易损性与先前的研究一致，该研究表明这些手术与手部灵巧性的变化有关。CAML 的一致性也证明了这种新方法用于描述具有多灶性病变的患者中微小、弥散、不重叠损伤的可行性。
