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.

Will climate change cause Sargassum beds in temperate waters to expand or contract? Evidence from the range shift pattern of Sargassum.

Understanding the range shift patterns of foundation species (e.g., macroalgae) under future climatic conditions is critical for biodiversity conservation in coastal ecosystems. These predictions are typically made using species distribution models (SDMs), and severe habitat loss has been predicted for most brown algal forests. Nevertheless, some models showed that local adaptation within species can reduce range loss projections. In this study, we used the brown algae Sargassum fusiforme and Sargassum thunbergii, which are distributed in the Northwest Pacific, to determine whether climate change will cause the Sargassum beds in Northwest Pacific temperate waters to expand or contract. We divided S. fusiforme and S. thunbergii into northern and southern lineages, considering the temperature gradients and phylogeographic structures. We quantified the realized niches of the two lineages using an n-dimensional hypervolume. Significant niche differentiation was detected between lineages for both species, suggesting the existence of local adaptation. Based on these results, lineage-level SDMs were constructed for both species. The prediction results showed the different responses of different lineages to climate change. The suitable distribution area for both species was predicted to move northward, retaining part of the suitable habitat at low latitudes (along the East China Sea). Unfortunately, this expansion could not compensate for losing middle-low latitude areas. Our results have important implications for the future management and protection of macroalgae and emphasize the importance of incorporating intraspecific variation into species distribution predictions.

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.

[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.