Weber K A, Wesselink E O, Gutierrez J, Law C S W, Mackey S, Ratliff J, Hu S, Chaudhari A S, Pool-Goudzwaard A, Coppieters M W, Elliott J M, Hancock M, De Leener B
Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, 1070 Arastradero Road, Suite 200, Palo Alto, CA, 94304, USA.
Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Eur Spine J. 2025 Jan;34(1):27-35. doi: 10.1007/s00586-024-08559-1. Epub 2024 Nov 18.
Lumbar paraspinal intramuscular fat (IMF) has emerged as a biological factor in low back pain (LBP). Traditional assessments measure IMF across the entire muscle or at specific levels and may miss key information on the role of IMF in LBP. Despite known variations across the lumbar spine, the three-dimensional (3D) distribution of IMF has not been characterized across people. Here we develop a template-based spatial parametric mapping approach to explore the 3D spatial distribution of lumbar paraspinal IMF.
To generate a lumbar spine template, we used T2-weighted magnetic resonance imaging from 76 people who recently recovered from LBP. We spatially normalized fat probability maps from Gaussian mixture modeling to the template and then calculated group-level spatial parametric maps of IMF and the associations between IMF and age, BMI, and sex.
The template had clear delineation of the neural, vertebral, and muscular structures. We observed muscle-specific and spatially varying 3D patterns of IMF across the lumbar spine along with age-, BMI-, and sex-related associations. For the lumbar multifidus and erector spinae, IMF increased inferiorly and was greatest at the anterior-medial muscle borders, while psoas major IMF was more evenly distributed. The associations between IMF and age, BMI, and sex varied spatially with both positive and negative associations present within an individual muscle.
The developed 3D spatial parametric mapping approach provides a comprehensive assessment of lumbar paraspinal IMF, potentially enhancing our understanding of lumbar spine function and pathology, treatment mechanisms, and the modifiable factors promoting recovery from LBP.
腰椎旁肌内脂肪（IMF）已成为腰痛（LBP）的一个生物学因素。传统评估方法是测量整个肌肉或特定水平的IMF，可能会遗漏IMF在LBP中作用的关键信息。尽管已知腰椎存在差异，但尚未对人群中IMF的三维（3D）分布进行特征描述。在此，我们开发了一种基于模板的空间参数映射方法，以探索腰椎旁IMF的3D空间分布。
为生成腰椎模板，我们使用了76名近期从LBP中康复的患者的T2加权磁共振成像。我们将高斯混合模型生成的脂肪概率图在空间上归一化到模板，然后计算IMF的组水平空间参数图以及IMF与年龄、BMI和性别的关联。
该模板清晰地描绘了神经、椎体和肌肉结构。我们观察到腰椎区域IMF具有特定肌肉且随空间变化的3D模式，以及与年龄、BMI和性别相关的关联。对于腰多裂肌和竖脊肌，IMF在下方增加，在前内侧肌肉边界处最大，而腰大肌的IMF分布更均匀。IMF与年龄、BMI和性别的关联在空间上有所不同，单个肌肉内同时存在正相关和负相关。
所开发的3D空间参数映射方法提供了对腰椎旁IMF的全面评估，可能会增强我们对腰椎功能和病理、治疗机制以及促进LBP恢复的可改变因素的理解。
