Department of Neurological Surgery, University of Pittsburgh, UPMC, Pittsburgh, PA, USA.
Department of Neurosurgery, University of Bristol, Southmead Hospital, Bristol, UK.
Neuroimage Clin. 2022;35:103062. doi: 10.1016/j.nicl.2022.103062. Epub 2022 May 28.
Huntington's disease (HD) is a neurodegenerative disorder characterized by motor, psychiatric, and cognitive symptoms. Due to its diverse manifestations, the scientific community has long recognized the need for sensitive, objective, individualized, and dynamic disease assessment tools. We examined the feasibility of Differential Tractography as a biomarker to evaluate correlation of symptom severity and of HD progression at the individual level. Differential tractography is a novel tractography modality that maps pathways with axonal injury characterized by a decrease of anisotropic diffusion pattern. We recruited sixteen patients scanned at 0-, 6-, and 12-month intervals by diffusion MRI scans for differential tractography assessment and correlated its volumetric findings with the Unified Huntington's Disease Rating Scale (UHDRS). Deterministic fiber tracking algorithm was applied. Longitudinal data was modeled using the generalized estimating equation (GEE) model and correlated with UHDRS scores, in addition to Spearman correlation for cross-sectional data. Our results show that volumes of affected pathways revealed by differential tractography significantly correlated with UHDRS scores in longitudinal data (p-value < 0.001), and chronological changes in differential tractography also correlated with the changes in UHDRS (p-value < 0.001). This technique opens new clinical avenues as a clinical translational tool to evaluate presymptomatic and symptomatic gene positive individuals. Our results provide support that differential tractography has the potential to be used as a dynamic imaging biomarker to assess at the individual level in a non-invasive manner, disease progression in HD. Critically important, differential tractography proves to be a quantitative tool for following degeneration in presymptomatic patients, with potential applications in clinical trials.
亨廷顿病（HD）是一种神经退行性疾病，其特征为运动、精神和认知症状。由于其表现多样，科学界早就认识到需要敏感、客观、个体化和动态的疾病评估工具。我们研究了差异束追踪作为评估个体水平的症状严重程度和 HD 进展相关性的生物标志物的可行性。差异束追踪是一种新的束追踪方式，可绘制出具有轴突损伤特征的通路图谱，表现为各向异性扩散模式减少。我们招募了 16 名患者，他们在 0、6 和 12 个月的时间间隔内接受了扩散 MRI 扫描，用于差异束追踪评估，并将其体积发现与统一亨廷顿病评定量表（UHDRS）相关联。应用了确定性纤维追踪算法。纵向数据采用广义估计方程（GEE）模型建模，并与 UHDRS 评分相关联，此外还对横截面数据进行 Spearman 相关分析。我们的结果表明，差异束追踪显示的受影响通路的体积与纵向数据中的 UHDRS 评分显著相关（p 值 < 0.001），并且差异束追踪的时间变化也与 UHDRS 的变化相关（p 值 < 0.001）。该技术为评估有症状和无症状基因阳性个体开辟了新的临床途径，是一种临床转化工具。我们的结果支持差异束追踪有可能成为一种动态成像生物标志物，以非侵入性的方式评估个体水平的 HD 进展。重要的是，差异束追踪证明是一种用于跟踪无症状患者退行性变的定量工具，具有在临床试验中的潜在应用。
