Background: Obesity is a major public health disorder associated with multiple co-morbidities. Knee magnetic resonance imaging (MRI) permits visualization of the subcutaneous fat anatomy, which can be correlated to body mass index (BMI) and obesity-related co-morbidities. Purpose: This study intends to validate a method of correlating measurements of subcutaneous fat around the distal femur on axial MR images to BMI and obesity-related co-morbidities. Material and Methods: The most proximal axial slice of each knee MRI was divided into four quadrants. Measurements of the thickest portion of the subcutaneous fat in each quadrant were independently obtained, yielding a value which was assigned the name of the SubCut fat index. The relationship between the SubCut fat index of each quadrant and the patient's BMI was then evaluated. Receiver operating characteristic curves utilizing both the subcutaneous fat in the medial and lateral quadrants as well as BMI were performed with respect to obesity-related co-morbidities. Results: SubCut fat index measurements in all four quadrants and BMI show the strongest correlation (all four, ANOVA P < 0.0001, r = 0.6), with subcutaneous fat measurements of the anterior medial (p < 0.0001) and posterior medial quadrants (P = 0.01). Additionally, BMI and medial quadrants SubCut indices showed strong association with obesity-related co-morbidities including sleep apnea, asthma, diabetes, hypertension, gastroesophageal reflux disease, and osteoporosis. Conclusion: The SubCut fat index, a marker of distal femur subcutaneous fat on axial MRI, correlates with severity of obesity (BI) and associated obesity-related co-morbidities.

Objective: Spinal epidural lipomatosis (EL) represents an excessive deposition of unencapsulated adipose tissue in the spinal canal that can result in chronic back pain in patients who are obese with and without diabetes. We aim to calculate the total volumetric epidural fat on lumbar spine MRI in a predominately obese population and correlate total epidural fat to lower back pain (LBP) and body mass index (BMI). Research design and methods: We developed a program (Fat Finder) to quantify volumetric distribution of epidural fat throughout the lumbar spine. Eleven patients with LBP were imaged using two MRI protocols: Parallel axial slices and conventional clinical protocol. The distribution of epidural fat per level was analyzed and normalized to the spinal canal size. Results: Our sample had an average age of 59.9 years and BMI of 31.57 kg/m 2. EL subgroup consisted of seven patients. The L2-L5 total fat volume was 3477.6 mm 3 (1431.1-5595.9) in the EL group versus 1783.8 mm 3 (815.0-2717.5) in the age-similar non-EL group. A higher percentage of fat volume in the canal was associated with higher LBP scores. The fat percentage was 32.2% among patients with EL versus 15.4% for age-similar non-EL with LBP score of 6.1 and 4.0, respectively. Conclusions: The Fat Finder is a novel volumetric method to quantify epidural lumbar spinal fat. The epidural fat favors the lower spinal segment with direct proportionality between the fat volume and LBP score, independent of BMI.