[Predictive value of nerve root sedimentation sign in diagnosis of lumbar spinal stenosis].

Objective: To explore the predictive value of the nerve root sedimentation sign in the diagnosis of lumbar spinal stenosis (LSS). Methods: Between January 2019 and July 2021, 201 patients with non-specific low back pain (NS-LBP) who met the selection criteria were retrospectively analyzed. There were 67 males and 134 females, with an age of 50-80 years (mean, 60.7 years). Four intervertebral spaces (L 1, 2, L 2, 3, L 3, 4, L 4, 5) of each case were studied, with a total of 804. The nerve root sedimentation sign was positive in 126 intervertebral spaces, and central canal stenosis was found in 203 intervertebral spaces. Progression to symptomatic LSS was determined by follow-up for lower extremity symptoms similar to LSS, combined with central spinal stenosis. Univariate analysis was performed for gender, age, visual analogue scale (VAS) score for low back pain at initial diagnosis, treatment, dural sac cross-sectional area at each intervertebral space, number of spinal stenosis segments, lumbar spinal stenosis grade, positive nerve root sedimentation sign, and number of positive segments between patients in the progression group and non-progression group, and logistic regression analysis was further performed to screen the risk factors for progression to symptomatic LSS in patients with NS-LBP. Results: All patients were followed up 17-48 months, with an average of 32 months. Of 201 patients with NS-LBP, 35 progressed to symptomatic LSS. Among them, 33 cases also had central spinal stenosis, which was defined as NS-LBP progressing to symptomatic LSS (33 cases in progression group, 168 cases in non-progression group). Univariate analysis showed that CSA at each intervertebral space, the number of spinal stenosis segments, lumbar spinal stenosis grade, whether the nerve root sedimentation sign was positive, and the number of nerve root sedimentation sign positive segments were the influencing factors for the progression to symptomatic LSS ( P<0.05); and further logistic regression analysis showed that positive nerve root sedimentation sign increased the risk of progression of NS-LBP to symptomatic LSS ( OR=8.774, P<0.001). Conclusion: The nerve root sedimentation sign may be associated with the progression of NS-LBP to symptomatic LSS, and it has certain predictive value for the diagnosis of LSS.

Automatic segmentation of dura for quantitative analysis of lumbar stenosis: A deep learning study with 518 CT myelograms.

BACKGROUND: The diagnosis of lumbar spinal stenosis (LSS) can be challenging because radicular pain is not often present in the culprit-level localization. Accurate segmentation and quantitative analysis of the lumbar dura on radiographic images are key to the accurate differential diagnosis of LSS. The aim of this study is to develop an automatic dura-contouring tool for radiographic quantification on computed tomography myelogram (CTM) for patients with LSS. METHODS: A total of 518 CTM cases with or without lumbar stenosis were included in this study. A deep learning (DL) segmentation algorithm 3-dimensional (3D) U-Net was deployed. A total of 210 labeled cases were used to develop the dura-contouring tool, with the ratio of the training, independent testing, and external validation datasets being 150:30:30. The Dice score (DCS) was the primary measure to evaluate the segmentation performance of the 3D U-Net, which was subsequently developed as the dura-contouring tool to segment another unlabeled 308 CTM cases with LSS. Automatic masks of 446 slices on the stenotic levels were then meticulously reviewed and revised by human experts, and the cross-sectional area (CSA) of the dura was compared. RESULTS: The mean DCS of the 3D U-Net were 0.905 ± 0.080, 0.933 ± 0.018, and 0.928 ± 0.034 in the five-fold cross-validation, the independent testing, and the external validation datasets, respectively. The segmentation performance of the dura-contouring tool was also comparable to that of the second observer (the human expert). With the dura-contouring tool, only 59.0% (263/446) of the automatic masks of the stenotic slices needed to be revised. In the revised cases, there were no significant differences in the dura CSA between automatic masks and corresponding revised masks (p = 0.652). Additionally, a strong correlation of dura CSA was found between the automatic masks and corresponding revised masks (r = 0.805). CONCLUSIONS: A dura-contouring tool was developed that could automatically segment the dural sac on CTM, and it demonstrated high accuracy and generalization ability. Additionally, the dura-contouring tool has the potential to be applied in patients with LSS because it facilitates the quantification of the dural CSA on stenotic slices.

Preoperative Adjacent Facet Joint Osteoarthritis Is Associated with the Incidence of Adjacent Segment Degeneration and Low Back Pain after Lumbar Interbody Fusion.

STUDY DESIGN: A retrospective cohort study. PURPOSE: To analyze the association between preoperative adjacent facet joint osteoarthritis (FJOA) and outcomes of lumbar interbody fusion (LIF). OVERVIEW OF LITERATURE: Whether preoperative adjacent FJOA is associated with the incidence of radiological adjacent segment degeneration (RASD) and low back pain (LBP) relief after lumbar fusion remains unknown. METHODS: The study included patients who underwent LIF. The demographic characteristics and radiographic and surgical data were collected and evaluated. The included patients were divided into control group and FJOA group based on the preoperative adjacent facet joint Pathria grade. Preoperative and last follow-up LBP Visual Analog Scale (VAS) score, leg pain (LP) VAS, Oswestry Disability Index (ODI) and RASD were evaluated and compared. The improvement rates in VAS and ODI were calculated and compared between the two groups. Logistic regression was used to analyze the risk factors of LBP relief and incidence of RASD. RESULTS: In total, 197 patients (control group, 86; FJOA group, 111) were included, and the median follow-up was 46 months. The VAS and ODI in both groups significantly improved after surgery. At the last follow-up, the FJOA group had higher VAS and lower VAS improvement rates of LBP than the control group (p<0.05). However, no significant difference in the LP VAS and ODI was found between the two groups. The incidence of RASD in the FJOA group was significantly higher than that in the control group (48.6% vs. 30.2%, p=0.034). Multivariate logistic regression analysis showed that preoperative adjacent FJOA was significantly associated with LBP relief (odds ratio [OR], 0.691; 95% confidence interval [CI], 0.498-0.958) and the postoperative incidence of RASD (OR, 1.406; 95% CI, 1.020-1.939). CONCLUSIONS: The preoperative FJOA in the adjacent segments was significantly associated with LBP following LIF. Patients with preoperative FJOA were more likely to have RASD following lumbar fusion surgery.

Effect of spinal-pelvic sagittal balance on the clinical outcomes after lumbar fusion surgery.

BACKGROUND: Spinal-pelvic sagittal balance is important for maintaining energy-efficient posture in normal and diseased states.Few reports to date have evaluated the effect of spinal-pelvic sagittal balance on clinical outcomes after lumbar interbody fusion in patients with lumbar degenerative diseases (LDD). METHODS: A total of 303 patients treated with posterior lumbar interbody fusion surgery for lumbar degenerative disease from January 2012 to December 2019 were enrolled in this retrospective study according to the inclusion criteria. Preoperative and postoperative spinal-pelvic sagittal parameters including pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS) and lumbar lordosis (LL) of the patients were evaluated and compared. 163 patients whose postoperative PI-LL ≤ 10° were divided into the spinal-pelvic match group (Group M), while 140 patients were divided into the spinal-pelvic mismatch group (Group MM). Preoperative and postoperative Oswestry Disability Index (ODI) and Visual Analog Scale (VAS) for back pain of both groups were compared. RESULTS: There was no significant difference between the two groups in demographic and surgical data, except for blood loss in surgery. LL, PI, PT and SS of the patients at final follow-up were all statistically different from the preoperative values in the two groups(P < 0.05). There was no significant difference in LL, PI, PT and SS between the two groups before surgery. At the final follow-up, LL, PI and PT differed significantly between the two groups(P < 0.05). Compared with the preoperative results, ODI and VAS of low back in both groups decreased significantly at the final follow-up (P < 0.05). Significant differences in VAS and ODI were found between the two groups at the final follow-up (P < 0.05). The improvement rates of VAS and ODI of Group M are both significantly higher than Group MM. Regression analysis showed that age and spinal-pelvic match had significant effects on the improvement of patients' low back pain at the final follow-up. CONCLUSIONS: lumbar interbody fusion can significantly improve the prognosis of patients with LDD. In terms of outcomes with an average follow-up time of more than 2 years, the spinal-pelvic match has a positive effect on patients' quality of life and the release of low back pain.

Gene correlation network analysis to identify regulatory factors in sciatic nerve injury.

BACKGROUND: Sciatic nerve injury (SNI), which frequently occurs under the traumatic hip and hip fracture dislocation, induces serious complications such as motor and sensory loss, muscle atrophy, or even disabling. The present work aimed to determine the regulating factors and gene network related to the SNI pathology. METHODS: Sciatic nerve injury dataset GSE18803 with 24 samples was divided into adult group and neonate group. Weighted gene co-expression network analysis (WGCNA) was carried out to identify modules associated with SNI in the two groups. Moreover, differentially expressed genes (DEGs) were determined from every group, separately. Subsequently, co-expression network and protein-protein interaction (PPI) network were overlapped to identify hub genes, while functional enrichment and Reactome analysis were used for a comprehensive analysis of potential pathways. GSE30165 was used as the test set for investigating the hub gene involvement within SNI. Gene set enrichment analysis (GSEA) was performed separately using difference between samples and gene expression level as phenotype label to further prove SNI-related signaling pathways. In addition, immune infiltration analysis was accomplished by CIBERSORT. Finally, Drug-Gene Interaction database (DGIdb) was employed for predicting the possible therapeutic agents. RESULTS: 14 SNI status modules and 97 DEGs were identified in adult group, while 15 modules and 21 DEGs in neonate group. A total of 12 hub genes was overlapping from co-expression and PPI network. After the results from both test and training sets were overlapped, we verified that the ten real hub genes showed remarkably up-regulation within SNI. According to functional enrichment of hub genes, the above genes participated in the immune effector process, inflammatory responses, the antigen processing and presentation, and the phagocytosis. GSEA also supported that gene sets with the highest significance were mostly related to the cytokine-cytokine receptor interaction. Analysis of hub genes possible related signaling pathways using gene expression level as phenotype label revealed an enrichment involved in Lysosome, Chemokine signaling pathway, and Neurotrophin signaling pathway. Immune infiltration analysis showed that Macrophages M2 and Regulatory T cells may participate in the development of SNI. At last, 25 drugs were screened from DGIdb to improve SNI treatment. CONCLUSIONS: The gene expression network is determined in the present work based on the related regulating factors within SNI, which sheds more light on SNI pathology and offers the possible biomarkers and therapeutic targets in subsequent research.