University Hospitals Coventry and Warwickshire NHS Trust, UK.
University of Chicago, IL.
Spine (Phila Pa 1976). 2022 Mar 1;47(5):E187-E195. doi: 10.1097/BRS.0000000000004159.
Retrospective, randomized, radiographic study assessing age-related changes (ARCs) on lumbar magnetic resonance imaging (MRI) using an ensemble method.
This study proposed to develop a novel reporting method to calculate a predicted "age estimate" for the ARC seen on lumbar MRI.
Lumbar MRI reports include pathological findings but usually not the prevalence data of common findings which has been shown to decrease the need for narcotics in the management of non-specific lower back pain (NSLBP). Comparing the normal age estimation for lumbar spine degenerative changes/ARC on MRI and comparing this to the patient's real age may improve patient outcome in the management of NSLBP.
A total of 60 lumbar MRI were taken from patients aged between 0 and 100 years. Lumbar MRI features reported as associated with age on review of the literature were measured on each MRI and statistically evaluated for correlation with age. Factors found to be associated were then entered into an ensemble model consisting of several machine learning techniques. The resulting ensemble model was then tested to predict age for a further 10 random lumbar MRI scans. One further lumbar MRI was then assessed for observer variability.
Features that correlated with age were disc signal intensity, the appearance of paravertebral and psoas muscle, disc height, facet joint size, ligamentum flavum thickness, Schmorl nodes, Modic changes, vertebral osteophytes, and high-intensity zones. With the ensemble model, 80% of estimated spinal age were within 11 years of the subjects' physical age.
It would appear that the intervertebral discs, and many other structures that are subjected to loading in and around the lumbar spine change their lumbar MRI appearance in a predictable way with increasing age. ARC on lumbar MRI can be assessed to predict an "expected age" for the subject.Level of Evidence: 2.
回顾性、随机、放射影像学研究，使用集成方法评估腰椎磁共振成像（MRI）的年龄相关变化（ARC）。
本研究提出开发一种新的报告方法，以计算腰椎 MRI 上 ARC 的预测“年龄估计”。
腰椎 MRI 报告包括病理发现，但通常不包括常见发现的流行数据，这已被证明可以减少非特异性下腰痛（NSLBP）管理中对麻醉剂的需求。比较腰椎脊柱退行性变化/ARC 的正常年龄估计值与患者的实际年龄，可能会改善 NSLBP 管理中患者的预后。
共对 60 例年龄在 0 至 100 岁之间的患者进行了腰椎 MRI 检查。对文献回顾中报告与年龄相关的腰椎 MRI 特征进行了测量，并进行了统计学评估，以确定与年龄的相关性。然后将相关的因素输入到一个集成模型中，该模型由几种机器学习技术组成。然后对另外 10 例随机腰椎 MRI 扫描进行了该集成模型的测试，以预测年龄。然后对另一个腰椎 MRI 进行了观察者变异性评估。
与年龄相关的特征是椎间盘信号强度、椎旁和腰大肌的外观、椎间盘高度、小关节大小、黄韧带厚度、Schmorl 结节、Modic 改变、椎体骨赘和高信号区。使用集成模型，80%的估计脊柱年龄与受试者的实际年龄相差不超过 11 年。
似乎椎间盘以及许多其他在腰椎周围和周围承受负荷的结构，其腰椎 MRI 外观会随着年龄的增长以可预测的方式发生变化。可以评估腰椎 MRI 上的 ARC，以预测受试者的“预期年龄”。
2。
