Study Design.: Cross-sectional observational study on the relationship between the degrees of disc degeneration and sagittal alignment in asymptomatic healthy individuals. Objective.: This study sought to determine whether the sagittal spine alignment subtype is related to the prevalence of lumbar disc degeneration. Summary and Background Data.: Sagittal balance and spinopelvic parameters might be risk factors for disc degeneration. Methods.: A total of 70 asymptomatic participants (36 women and 34 men) without regular physical activity were categorized according to the four subtypes of sagittal alignment proposed by Roussouly. All participants underwent magnetic resonance imaging of the lumbar spine (1.5T) and panoramic radiography of the spine. The degree of disc degeneration was graded using T2-weighted images according to the Pfirrmann classification. Spinopelvic parameters and vertebral curvatures were measured on digital panoramic radiographs using Surgimap software. Interobserver analyses for the Pfirrmann classification and spinopelvic parameters were assessed using the weighted Kappa and intraclass correlation coefficient (ICC), respectively. Results.: The Kappa associated with disc degeneration classification was 0.79 (95% confidence intervals 0.72–0.87). The ICCs were excellent, with small confidence intervals for all spinopelvic parameters. The type II group (flat lordosis) showed a higher frequency of degenerated discs at L4-L5 (P = 0.03) than the type IV group (long and curved lumbar spine). No significant differences in disc degeneration were observed among the four subtypes at the other disc levels. We found a negative, moderate correlation between the spinopelvic parameters and the occurrence of disc degeneration in the type II group. Conclusion.: The Roussouly subtype II sagittal alignment is significantly associated with disc degeneration at L4-L5 in asymptomatic young adults. Our results support the hypothesis that spinal sagittal alignment plays a role in early disc degeneration. Level of Evidence: 3

Fat infiltration and atrophy of lumbar muscles are related to spinal degenerative conditions and may cause functional deficits. Spinal alignment exerts biomechanical influence on lumbar intervertebral discs and joints. Our objective was to evaluate if spinopelvic parameters correlate with the lumbar muscle volume and fat infiltration. This is an observational, prospective and cross-sectional study. Ninety-three asymptomatic adult aged 20–40 years were included. Lumbar lordosis (LL), thoracic kyphosis (TK), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), thoracolumbar alignment (TL), sagittal vertical axis (SVA), C2-pelvic angle (CPA), spinosacral angle (SSA), lack of lordosis (PI-LL), L1S1 and T1S1 length were measured on panoramic spine radiographs. Lumbar axial T1-weighted and In- and Out-Phase images were obtained on 1.5T MRI scanner and were used to extract the muscle volumes and fat fractions of multifidus, erector spinae, and psoas. All muscle volumes were higher in men than women (p<0.05). The fat fraction was higher in the multifidus and erector spinae in women (p<0.05). Multifidus volume was weakly correlated with PT (R = 0.22), PI (R = 0.22), LL (R = 0.34) and CPA (R = 0.29). Erectors spinae volume were correlated with CPA (R = 0.21). Psoas volume correlated with TK (R = 0.21), TL (R = 0.27) and SVA (R = -0.23). The lumbar muscle volumes showed a moderated correlation with T1S1 length (R = 0.55 to 0.62). Spinopelvic parameters showed correlation with lumbar muscle volumes but not with muscle fat infiltration on asymptomatic young adults.

Sagittal balance describes the optimal alignment of the spine in the sagittal plane, resulting from the interaction between the spine and lower limbs, via the pelvis. Understanding sagittal balance has gained importance, especially in the last decade, because sagittal imbalance correlates directly with disability and pain. Diseases that alter that balance cause sagittal malalignment and may trigger compensatory mechanisms. Certain radiographic parameters have been shown to be clinically relevant and to correlate with clinical scores in the evaluation of spinopelvic alignment. This article aims to provide a comprehensive review of the literature on the spinopelvic parameters that are most relevant in clinical practice, as well as to describe compensatory mechanisms of the pelvis and lower limbs.

Background: To investigate the detection of intervertebral disc (IVD) composition aging-related changes using T2 and T1ρ relaxometry in vivo in asymptomatic young adults. Methods: We recruited ninety asymptomatic and young adults (42 men and 48 women) between 20 and 40 years old. T2 and T1ρ lumbar spine mappings were acquired using 1.5 T magnetic resonance imaging (MRI) scanner. Two independent observers manually segmented 450 lumbar discs in all slices. They also performed sub region segmentation of annulus fibrosus (AF) and nucleus pulposus (NP) at the central MRI sagittal slices. Results: There was no difference between men and women for T2 (P=0.37) or T1ρ relaxometry (P=0.97). There was a negative correlation between age (20–40 years) and IVD T2 relaxation time of the whole disc (r=−0.30, P<0.0001), NP (r=−0.20 to −0.51, P<0.05) and posterior AF (r=−0.21 to −0.31, P<0.05) at all lumbar disc levels. There was no statistical correlation between aging and IVD T1ρ relaxation both for NP and AF. Conclusions: T2 relaxometry detected gradual IVD dehydration in the first two decades of adulthood. We observed no significant variation of T1ρ or volumetry with aging in our study group. Our results suggest that T2 mapping may be more appropriate to detect early IVD aging changes.

Intervertebral disk biochemical composition could be accessed in vivo by T1ρ and T2 relaxometry. We found no studies in the literature comparing different segmentation methods for data extraction using these techniques. Our aim was to compare different manual segmentation methods used to extract T1ρ and T2 relaxation times of intervertebral disks from MR imaging. Seven different methods of partial-disk segmentation techniques were compared with whole-disk segmentation as the reference standard. Sagittal T1ρ and T2 maps were generated by using a 1.5T MR imaging scanner in 57 asymptomatic volunteers 20-40 years of age. Two hundred eighty-five lumbar disks were separated into 2 groups: nondegenerated disk (Pfirrmann I and II) and degenerated disk (Pfirrmann III and IV). In whole-disk segmentation, the disk was segmented in its entirety on all sections. Partial-disk segmentation methods included segmentation of the disk into 6, 5, 4, 3, and 1 sagittal sections. Circular ROIs positioned in the nucleus pulposus and annulus fibrosus were also used to extract T1ρ and T2, and data were compared with whole-disk segmentation In the nondegenerated group, segmentation of ≥5 sagittal sections showed no statistical difference with whole-disk segmentation. All the remaining partial-disk segmentation methods and circular ROIs showed different results from whole-disk segmentation (P < .001). In the degenerated disk group, all methods were statistically similar to whole-disk segmentation. All partial-segmentation methods, including circular ROIs, showed strong linear correlation with whole-disk segmentation in both the degenerated and nondegenerated disk groups. Manual segmentation showed strong reproducibility for T1ρ and T2 and strong linear correlation between partial- and whole-disk segmentation. Absolute T1ρ and T2 values extracted from different segmentation techniques were statistically different in disks with Pfirrmann grades I and II.

Chronic constriction injury (CCI) of the sciatic nerve is a peripheral nerve injury widely used to induce mononeuropathy. This study used machine learning methods to identify the best gait analysis parameters for evaluating peripheral nerve injuries. Twenty-eight male Wistar rats (weighing 270±10 g), were used in the present study and divided into the following 4 groups: CCI with 4 ligatures around the sciatic nerve (CCI-4L; n=7), a modified CCI model with 1 ligature (CCI-1L; n=7), a sham group (n=7), and a healthy control group (n=7). All rats underwent gait analysis 7 and 28 days postinjury. The data were evaluated using Kinovea and WeKa software (machine learning and neural networks). In the machine learning analysis of the experimental groups, the pre-swing (PS) angle showed the highest ranking in all 3 analyses (sensitivity, specificity, and area under the receiver operating characteristics curve using the Naive Bayes, k-nearest neighbors, radial basis function classifiers). Initial contact (IC), step length, and stride length also performed well. Between 7 and 28 days after injury, there was an increase in the total course time, step length, stride length, stride speed, and IC, and a reduction in PS and IC-PS. Statistically significant differences were found between the control group and experimental groups for all parameters except speed. Interactions between time after injury and nerve injury type were only observed for IC, PS, and IC-PS. PS angle of the ankle was the best gait parameter for differentiating nonlesions from nerve injuries and different levels of injury.