Dataset Information

A Population-Based 3D Atlas of the Pathological Lumbar Spine Segment.

ABSTRACT: The spine is the load-bearing structure of human beings and may present several disorders, with low back pain the most frequent problem during human life. Signs of a spine disorder or disease vary depending on the location and type of the spine condition. Therefore, we aim to develop a probabilistic atlas of the lumbar spine segment using statistical shape modeling (SSM) and then explore the variability of spine geometry using principal component analysis (PCA). Using computed tomography (CT), the human spine was reconstructed for 24 patients with spine disorders and then the mean shape was deformed upon specific boundaries (e.g., by ±3 or ±1.5 standard deviation). Results demonstrated that principal shape modes are associated with specific morphological features of the spine segment such as Cobb's angle, lordosis degree, spine width and height. The lumbar spine atlas here developed has evinced the potential of SSM to investigate the association between shape and morphological parameters, with the goal of developing new treatments for the management of patients with spine disorders.

SUBMITTER: Sciortino V

PROVIDER: S-EPMC9405443 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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A Population-Based 3D Atlas of the Pathological Lumbar Spine Segment.

Sciortino Vincenza V Pasta Salvatore S Ingrassia Tommaso T Cerniglia Donatella D

Bioengineering (Basel, Switzerland) 20220822 8

The spine is the load-bearing structure of human beings and may present several disorders, with low back pain the most frequent problem during human life. Signs of a spine disorder or disease vary depending on the location and type of the spine condition. Therefore, we aim to develop a probabilistic atlas of the lumbar spine segment using statistical shape modeling (SSM) and then explore the variability of spine geometry using principal component analysis (PCA). Using computed tomography (CT), t ...[more]

PMID: 36004933

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Project description:BackgroundAdjacent segment disease (ASDz) is a potential complication following lumbar spinal fusion. A common nomenclature based on etiology and ASDz type does not exist and is needed to assist with clinical prognostication, decision making, and management.Questions/purposesThe objective of this study was to develop an etiology-based classification system for ASDz following lumbar fusion.MethodsWe conducted a retrospective chart review of 65 consecutive patients who had undergone both a lumbar fusion performed by a single surgeon and a subsequent procedure for ASDz. We established an etiology-based classification system for lumbar ASDz with the following six categories: "degenerative" (degenerative disc disease or spondylosis), "neurologic" (disc herniation, stenosis), "instability" (spondylolisthesis, rotatory subluxation), "deformity" (scoliosis, kyphosis), "complex" (fracture, infection), or "combined." Based on this scheme, we determined the rate of ASDz in each etiologic category.ResultsOf the 65 patients, 27 (41.5%) underwent surgery for neurogenic claudication or radiculopathy for adjacent-level stenosis or disc herniation and were classified as "neurologic." Ten patients (15.4%) had progressive degenerative disc pathology at the adjacent level and were classified as "degenerative." Ten patients (15.4%) had spondylolisthesis or instability and were classified as "instability," and three patients (4.6%) required revision surgery for adjacent-level kyphosis or scoliosis and were classified as "deformity." Fifteen patients (23.1%) had multiple diagnoses that included a combination of categories and were classified as "combined."ConclusionThis is the first study to propose an etiology-based classification scheme of ASDz following lumbar spine fusion. This simple classification system may allow for the grouping and standardization of patients with similar pathologies and thus for more specific pre-operative diagnoses, personalized treatments, and improved outcome analyses.

Project description:BackgroundThe United States has been facing a worsening opioid epidemic over the past two decades. The veteran population represents a large and vulnerable group with a higher burden of mental health comorbidities. The purpose of this study was to analyze the impact of lumbar spine surgery on postoperative opioid usage in the United States veteran population.MethodsA retrospective cohort study was conducted using the Veterans Affairs Informatics and Computing Infrastructure database. Patients who underwent lumbar spine surgery were stratified into three groups by their preoperative opioid claims within 365 days of surgery. Postoperative cumulative morphine milligram equivalents (MME) were tracked for each group and the paired Wilcoxon signed rank test was used to compare cumulative preoperative MME (days -365-0) to cumulative postoperative MME (days 91-455).ResultsAt one year, 30.6% of patients in the high preoperative opioid group and 73.1% of patients in the low preoperative opioid group were no longer using opioids. In the opioid naive cohort, 10.0% of patients were still using opioids at one year. Among all patients, median cumulative postoperative MME was significantly less than median cumulative preoperative MME (P<0.001). High preoperative opioid usage of more than 3 claims was most significantly associated with continued postoperative opioid usage (odds ratio 12.55, P<0.001). From 2010 to 2020 the proportion of patients with preoperative opioid claims decreased (58.8% to 34.8%).ConclusionsIn the veteran population, lumbar spine surgery was effective in getting 50% of patients who were on opioids preoperatively to discontinue opioids postoperatively. Even minimal exposure to opioids preoperatively resulted in a 2.69-time increase in risk of being on opioids at one year versus opioid naive patients. This study affirms that despite being a high-risk population, the veteran population has a similar response to lumbar spine surgery as the general population in regards to opioid dependence.

Project description:ObjectivesUndiagnosed osteoporosis may lead to severe complications after spinal surgery. This study aimed to construct and validate a radiomic signature based on CT scans to screen for lumbar spine osteoporosis.MethodsUsing a stratified random sample method, 386 vertebral bodies were randomly divided into a training set (n = 270) and a test set (n = 116). A total of 1040 radiomics features were automatically retracted from lumbar spine CT scans using the 3D slicer pyradiomics module, and a radiomic signature was created. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the Hounsfield and radiomics signature models were calculated. The AUCs of the two models were compared using the DeLong test. Their clinical usefulness was assessed using a decision curve analysis.ResultsTwelve features were chosen to establish the radiomic signature. The AUCs of the radiomics signature and Hounsfield models were 0.96 and 0.88 in the training set and 0.92 and 0.84 in the test set, respectively. According to the DeLong test, the AUCs of the two models were significantly different (p < 0.05). The radiomics signature model indicated a higher overall net benefit than the Hounsfield model, as determined by decision curve analysis.ConclusionsThe CT-based radiomic signature can differentiate patients with/without osteoporosis prior to lumbar spinal surgery. Without additional medical cost and radiation exposure, the radiomics method may provide valuable information facilitating surgical decision-making.Key points• The goal of the study was to evaluate the efficacy of a radiomics signature model based on routine preoperative lumbar spine CT scans in screening osteoporosis. • The radiomics signature model demonstrated excellent prediction performance in both the training and test sets. • This radiomics method may provide valuable information and facilitate surgical decision-making without additional medical costs and radiation exposure.

Project description:BackgroundBiomechanical investigations of spinal motion preserving implants help in the understanding of their in vivo behavior. In this study, we hypothesized that the lumbar spine with implanted total spinal segment replacement (TSSR) would exhibit decreased dynamic stiffness and more rapid energy absorption compared to native functional spinal units under simulated physiologic motion when tested with the pendulum system.MethodsFive unembalmed, frozen human lumbar functional spinal units were tested on the pendulum system with axial compressive loads of 181 N, 282 N, 385 N, and 488 N before and after Flexuspine total spinal segment replacement implantation. Testing in flexion, extension, and lateral bending began by rotating the pendulum to 5°; resulting in unconstrained oscillatory motion. The number of rotations to equilibrium was recorded and bending stiffness (N-m/°) was calculated and compared for each testing mode.ResultsThe total spinal segment replacement reached equilibrium with significantly fewer cycles to equilibrium compared to the intact functional spinal unit at all loads in flexion (p<0.011), and at loads of 385 N and 488 N in lateral bending (p<0.020). Mean bending stiffness in flexion, extension, and lateral bending increased with increasing load for both the intact functional spinal unit and total spinal segment replacement constructs (p<0.001), with no significant differences in stiffness between the intact functional spinal unit and total spinal segment replacement in any of the test modes (p>0.18).ConclusionsLumbar functional spinal units with implanted total spinal segment replacement were found to have similar dynamic bending stiffness, but absorbed energy at a more rapid rate than intact functional spinal units during cyclic loading with an unconstrained pendulum system. Although the effects on clinical performance of motion preserving devices is not fully known, these results provide further insight into the biomechanical behavior of this device under approximated physiologic loading conditions.

Dataset Information

A Population-Based 3D Atlas of the Pathological Lumbar Spine Segment.

Publications

A Population-Based 3D Atlas of the Pathological Lumbar Spine Segment.

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