Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, Colorado, USA.
J Magn Reson Imaging. 2023 Jul;58(1):189-197. doi: 10.1002/jmri.28471. Epub 2022 Oct 25.
Healthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA).
To quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA.
Retrospective study.
Fourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren-Lawrence [KL] grade: 0; final KL grade: 3 over the 10-year study).
FIELD STRENGTH/SEQUENCE: 3.0-T and 14.1-T, biomechanics-based displacement-encoded imaging, fast spin echo, multi-slice multi-echo T2 mapping.
We studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades.
Multiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold at α = 0.05.
Gradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (R = 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not.
Spatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early-stage degeneration.
1 TECHNICAL EFFICACY: Stage 1.
健康的关节软骨在厚度上呈现出由不同的带区模式定义的结构梯度，这在几种疾病的发病机制中可能会被打乱。使用定量 MRI 数据对纹理模式进行分析，可能会识别出与早期骨关节炎（OA）相关的健康或退化组织的结构梯度。
定量分析 MRI 数据的空间梯度和模式，并探索新的候选生物标志物来预测 OA 的早期严重程度。
回顾性研究。
14 名接受全膝关节置换手术的志愿者（8 名男性/2 名女性/4 名未知，平均年龄±标准差：68.1±9.6 岁）和 10 名来自 OA 倡议（OAI）的放射学 OA 发病患者（2 名男性/8 名女性，平均年龄±标准差：57.7±9.4 岁；初始 Kellgren-Lawrence [KL] 分级：0；10 年研究结束时的最终 KL 分级：3）。
磁场强度/序列：3.0-T 和 14.1-T，基于生物力学的位移编码成像，快速自旋回波，多切片多回波 T2 映射。
我们研究了接受全膝关节置换手术的志愿者的软骨外植体的结构和应变，或进展性 OA 的 OAI 患者的软骨结构。我们计算了定量 MRI 测量值（例如 T2）垂直于软骨表面的空间梯度，以增强带区变化。我们将梯度值与组织学 OA 严重程度、常规弛豫率和/或 KL 分级进行比较。
混合效应模型残差与组织学确定的 OA 严重程度之间关系的多参数线性回归，显著性阈值为α=0.05。
个体弛豫率和生物力学测量的梯度与 OA 严重程度显著相关，优于常规弛豫率和应变指标。在人体外植体中，分析空间梯度与 OA 严重程度的相关性最强（R=0.627）。OAI 数据的 T2 空间梯度可识别单个人的放射学（KL 分级 2）OA 严重程度的变化，而单独的常规 T2 则不行。
定量 MRI 数据的空间梯度可能会提高非侵入性成像对早期退变的预测能力。
1 技术功效：第 1 阶段。
