Purpose of review: The endplates form the interface between the rigid vertebral bodies and compliant intervertebral discs. Proper endplate function involves a balance between conflicting biomechanical and nutritional demands. This review summarizes recent data that highlight the importance of proper endplate function and the relationships between endplate dysfunction, adjacent disc degeneration, and axial low back pain. Recent findings: Changes to endplate morphology and composition that impair its permeability associate with disc degeneration. Endplate damage also associates with disc degeneration, and the progression of degeneration may be accelerated and the chronicity of symptoms heightened when damage coincides with evidence of adjacent bone marrow lesions. Summary: The endplate plays a key role in the development of disc degeneration and low back pain. Clarification of the mechanisms governing endplate degeneration and developments in clinical imaging that enable precise evaluation of endplate function and dysfunction will distinguish the correlative vs. causative nature of endplate damage and motivate new treatments that target pathologic endplate function.

OBJECTIVEFrailty is a clinical state of increased vulnerability due to age-associated decline and has been well established as a perioperative risk factor. Geriatric patients have a higher risk of frailty, higher incidence of brain cancer, and increased postoperative complication rates compared to nongeriatric patients. Yet, literature describing the effects of frailty on short- and long-term complications in geriatric patients is limited. In this study, the authors evaluate the effects of frailty in geriatric patients receiving cranial neurosurgery for a primary CNS neoplasm.METHODSThe authors conducted a retrospective cohort study of geriatric patients receiving cranial neurosurgery for a primary CNS neoplasm between 2010 and 2017 by using the Nationwide Readmission Database. Demographics and frailty were queried at primary admission, and readmissions were analyzed at 30-, 90-, and 180-day intervals. Complications of interest included infection, anemia, infarction, kidney injury, CSF leak, urinary tract infection, and mortality. Nearest-neighbor propensity score matching for demographics was implemented to identify nonfrail control patients with similar diagnoses and procedures. The analysis used Welch two-sample t-tests for continuous variables and chi-square test with odds ratios.RESULTSA total of 6713 frail patients and 6629 nonfrail patients were identified at primary admission. At primary admission, frail geriatric patients undergoing cranial neurosurgery had increased odds of developing acute posthemorrhagic anemia (OR 1.56, 95% CI 1.23–1.98; p = 0.00020); acute infection (OR 3.16, 95% CI 1.70–6.36; p = 0.00022); acute kidney injury (OR 1.32, 95% CI 1.07–1.62; p = 0.0088); urinary tract infection prior to discharge (OR 1.97, 95% CI 1.71–2.29; p < 0.0001); acute postoperative cerebral infarction (OR 1.57, 95% CI 1.17–2.11; p = 0.0026); and mortality (OR 1.64, 95% CI 1.22–2.24; p = 0.0012) compared to nonfrail geriatric patients receiving the same procedure. In addition, frail patients had a significantly increased inpatient length of stay (p < 0.0001) and all-payer hospital cost (p < 0.0001) compared to nonfrail patients at the time of primary admission. However, no significant difference was found between frail and nonfrail patients with regard to rates of infection, thromboembolism, CSF leak, dural tear, cerebral infarction, acute kidney injury, and mortality at all readmission time points.CONCLUSIONSFrailty may significantly increase the risks of short-term acute complications in geriatric patients receiving cranial neurosurgery for a primary CNS neoplasm. Long-term analysis revealed no significant difference in complications between frail and nonfrail patients. Further research is warranted to understand the effects and timeline of frailty in geriatric patients.

Background There is an interplay between the intervertebral disc (IVD) and the adjacent bone marrow that may play a role in the development of IVD degeneration and might influence chronic lower back pain (CLBP). Purpose To apply novel quantitative MRI techniques to assess the relationship between vertebral bone marrow fat (BMF) and biochemical changes in the adjacent IVD. Study Type Prospective. Subjects Forty‐six subjects (26 female and 20 male) with a mean age of 47.3 ± 12.0 years. Field Strength/Sequence 3 T MRI; a combined T1ρ and T2 mapping pulse sequence and a 3D spoiled gradient recalled sequence with six echoes and iterative decomposition of water and fat with echo asymmetry and least‐squares estimation (IDEAL) reconstruction algorithm. Assessment Using quantitative MRI, the vertebral BMF fraction was measured as well as the biochemical composition (proteoglycan and collagen content) of the IVD. Furthermore, clinical Pfirrmann grading, Oswestry disability index (ODI), and visual analog scale (VAS) was assessed. Statistical Tests Mixed random effects models accounting for multiple measurements per subject were used to assess the relationships between disc measurements and BMF. Results The relationships between BMF (mean) and T1ρ/T2 (mean and SD) were significant, with P < 0.05. Significant associations (P < 0.001) were found between clinical scores (Pfirrmann, ODI, and VAS) with T1ρ/T2 (mean and SD). BMF mean was significantly related to ODI (P = 0.037) and VAS (P = 0.043), but not with Pfirrmann (P = 0.451). In contrast, BMF SD was significantly related to Pfirrmann (P = 0.000) but not to ODI (P = 0.064) and VAS (P = 0.13). Data Conclusion Our study demonstrates significant associations between BMF and biochemical changes in the adjacent IVD, both assessed by quantitative MRI; this may suggest that the conversion of hematopoietic bone marrow to fatty bone marrow impairs the supply of available nutrients to cells in the IVD and may thereby accelerate disc degeneration. Level of Evidence: 2 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:1219–1226.

Background: Bone marrow fat (BMF) fraction quantification in vertebral bodies is used as a novel imaging biomarker to assess and characterize chronic lower back pain. However, manual segmentation of vertebral bodies is time consuming and laborious. Purpose: ( 1 ) Develop a deep learning pipeline for segmentation of vertebral bodies using quantitative water-fat MRI. ( 2 ) Compare BMF measurements between manual and automatic segmentation methods to assess performance. Materials and Methods: In this retrospective study, MR images using a 3D spoiled gradient-recalled echo (SPGR) sequence with Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) reconstruction algorithm were obtained in 57 subjects (28 women, 29 men, mean age, 47.2 ± 12.6 years). An artificial network was trained for 100 epochs on a total of 165 lumbar vertebrae manually segmented from 31 subjects. Performance was assessed by analyzing the receiver operating characteristic curve, precision-recall, F1 scores, specificity, sensitivity, and similarity metrics. Bland-Altman analysis was used to assess performance of BMF fraction quantification using the predicted segmentations. Results: The deep learning segmentation method achieved an AUC of 0.92 (CI 95%: 0.9186, 0.9195) on a testing dataset ( n = 24 subjects) on classification of pixels as vertebrae. A sensitivity of 0.99 and specificity of 0.80 were achieved for a testing dataset, and a mean Dice similarity coefficient of 0.849 ± 0.091. Comparing manual and automatic segmentations on fat fraction maps of lumbar vertebrae ( n = 124 vertebral bodies) using Bland-Altman analysis resulted in a bias of only −0.605% (CI 95% = −0.847 to −0.363%) and agreement limits of −3.275% and +2.065%. Automatic segmentation was also feasible in 16 ± 1 s. Conclusion: Our results have demonstrated the feasibility of automated segmentation of vertebral bodies using deep learning models on water-fat MR (Dixon) images to define vertebral regions of interest with high specificity. These regions of interest can then be used to quantify BMF with comparable results as manual segmentation, providing a framework for completely automated investigation of vertebral changes in CLBP.

No abstract