Showing papers on "Lumbar vertebrae published in 2021"

Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?

Abstract: BACKGROUND Vertebral fractures are the most common osteoporotic fractures in older individuals. Recent studies suggest that the performance of artificial intelligence is equal to humans in detecting osteoporotic fractures, such as fractures of the hip, distal radius, and proximal humerus. However, whether artificial intelligence performs as well in the detection of vertebral fractures on plain lateral spine radiographs has not yet been reported. QUESTIONS/PURPOSES (1) What is the accuracy, sensitivity, specificity, and interobserver reliability (kappa value) of an artificial intelligence model in detecting vertebral fractures, based on Genant fracture grades, using plain lateral spine radiographs compared with values obtained by human observers? (2) Do patients' clinical data, including the anatomic location of the fracture (thoracic or lumbar spine), T-score on dual-energy x-ray absorptiometry, or fracture grade severity, affect the performance of an artificial intelligence model? (3) How does the artificial intelligence model perform on external validation? METHODS Between 2016 and 2018, 1019 patients older than 60 years were treated for vertebral fractures in our institution. Seventy-eight patients were excluded because of missing CT or MRI scans (24% [19]), poor image quality in plain lateral radiographs of spines (54% [42]), multiple myeloma (5% [4]), and prior spine instrumentation (17% [13]). The plain lateral radiographs of 941 patients (one radiograph per person), with a mean age of 76 ± 12 years, and 1101 vertebral fractures between T7 and L5 were retrospectively evaluated for training (n = 565), validating (n = 188), and testing (n = 188) of an artificial intelligence deep-learning model. The gold standard for diagnosis (ground truth) of a vertebral fracture is the interpretation of the CT or MRI reports by a spine surgeon and a radiologist independently. If there were any disagreements between human observers, the corresponding CT or MRI images would be rechecked by them together to reach a consensus. For the Genant classification, the injured vertebral body height was measured in the anterior, middle, and posterior third. Fractures were classified as Grade 1 ( 40%). The framework of the artificial intelligence deep-learning model included object detection, data preprocessing of radiographs, and classification to detect vertebral fractures. Approximately 90 seconds was needed to complete the procedure and obtain the artificial intelligence model results when applied clinically. The accuracy, sensitivity, specificity, interobserver reliability (kappa value), receiver operating characteristic curve, and area under the curve (AUC) were analyzed. The bootstrapping method was applied to our testing dataset and external validation dataset. The accuracy, sensitivity, and specificity were used to investigate whether fracture anatomic location or T-score in dual-energy x-ray absorptiometry report affected the performance of the artificial intelligence model. The receiver operating characteristic curve and AUC were used to investigate the relationship between the performance of the artificial intelligence model and fracture grade. External validation with a similar age population and plain lateral radiographs from another medical institute was also performed to investigate the performance of the artificial intelligence model. RESULTS The artificial intelligence model with ensemble method demonstrated excellent accuracy (93% [773 of 830] of vertebrae), sensitivity (91% [129 of 141]), and specificity (93% [644 of 689]) for detecting vertebral fractures of the lumbar spine. The interobserver reliability (kappa value) of the artificial intelligence performance and human observers for thoracic and lumbar vertebrae were 0.72 (95% CI 0.65 to 0.80; p < 0.001) and 0.77 (95% CI 0.72 to 0.83; p < 0.001), respectively. The AUCs for Grades 1, 2, and 3 vertebral fractures were 0.919, 0.989, and 0.990, respectively. The artificial intelligence model with ensemble method demonstrated poorer performance for discriminating normal osteoporotic lumbar vertebrae, with a specificity of 91% (260 of 285) compared with nonosteoporotic lumbar vertebrae, with a specificity of 95% (222 of 234). There was a higher sensitivity 97% (60 of 62) for detecting osteoporotic (dual-energy x-ray absorptiometry T-score ≤ -2.5) lumbar vertebral fractures, implying easier detection, than for nonosteoporotic vertebral fractures (83% [39 of 47]). The artificial intelligence model also demonstrated better detection of lumbar vertebral fractures compared with detection of thoracic vertebral fractures based on the external dataset using various radiographic techniques. Based on the dataset for external validation, the overall accuracy, sensitivity, and specificity on bootstrapping method were 89%, 83%, and 95%, respectively. CONCLUSION The artificial intelligence model detected vertebral fractures on plain lateral radiographs with high accuracy, sensitivity, and specificity, especially for osteoporotic lumbar vertebral fractures (Genant Grades 2 and 3). The rapid reporting of results using this artificial intelligence model may improve the efficiency of diagnosing vertebral fractures. The testing model is available at http://140.113.114.104/vght_demo/corr/. One or multiple plain lateral radiographs of the spine in the Digital Imaging and Communications in Medicine format can be uploaded to see the performance of the artificial intelligence model. LEVEL OF EVIDENCE Level II, diagnostic study.

Ultra-low-dose CT versus radiographs for minor spine and pelvis trauma: a Bayesian analysis of accuracy.

Abstract: To compare diagnosis performance and effective dose of ultra-low-dose CT (ULD CT) versus radiographs in suspected spinal or pelvic ring or hip fracture for minor trauma. ULD CT, in addition to radiography, was prospectively performed in consecutive patients admitted to the emergency department for minor traumas, during working hours over 2 months. Presence of a recent fracture was assessed by two blind radiologists independently. Sensitivities and specificities were estimated using the best valuable comparator (BVC) as a reference and using a latent class model in Bayesian inference (BLCM). Dosimetric indicators were recorded and effective doses (E) were calculated using conversion coefficient. Eighty areas were analyzed in 69 patients, including 22 dorsal spine, 28 lumbar spine, and 30 pelvic ring/hip. Thirty-six fractures (45%) were observed. Applying the BVC method, depending on location, ULD CT sensitivity was 80 to 100% for reader 1 and 85 to 100% for reader 2, whereas radiographic sensitivity was 60 to 85% for reader 1 and 50 to 92% for reader 2. With BLCM approach for reader 2, ULD CT sensitivity for all locations/dorsal spine/lumbar spine and pelvic ring-hip was 87.1/75.9/84.2/76.9% respectively. Corresponding radiograph sensitivity was 73.8, 54.8, 80.4, and 68.7%. Effective doses of ULD CT were similar to radiographs for dorsal and hip locations whereas for lumbar spine, ULD CT effective dose was 1.83 ± 0.59 mSv compared with 0.96 ± 0.59 mSv (p < 0.001). Sensitivity for fracture detection was higher for ULD CT compared with radiographs with an effective dose comparable to radiographs. • Ultra-low-dose spine and pelvis CT demonstrates better fracture detection when compared with radiographs. • The effective dose of ultra-low-dose spine and pelvis CT scan and radiographs is comparable. • Replacement of radiographs by ULD CT in daily practice for trauma patients is an option to consider and should be evaluated by a randomized trial.

Standardized uptake values of 99mTc-MDP in normal vertebrae assessed using quantitative SPECT/CT for differentiation diagnosis of benign and malignant bone lesions.

Abstract: Quantitative bone SPECT/CT is useful for disease follow up and inter-patient comparison. For bone metastatic malignant lesions, spine is the most commonly invaded site. However, Quantitative studies with large sample size investigating all the segments of normal cervical, thoracic and lumbar vertebrae are seldom reported. This study was to evaluate the quantitative tomography of normal vertebrae using 99mTc-MDP with SPECT/CT to investigate the feasibility of standardized uptake value (SUV) for differential diagnosis of benign and malignant bone lesions. A retrospective study was carried out involving 221 patients (116 males and 105 females) who underwent SPECT/CT scan using 99mTc-MDP. The maximum SUV (SUVmax), mean SUV (SUVmean) and CT values (Hounsfield Unit, HU) of 2416 normal vertebrae bodies, 157 benign bone lesions and 118 malignant bone metastasis foci were obtained. The correlations between SUVmax of normal vertebrae and CT values of normal vertebrae, age, height, weight, BMI of patients were analyzed. Statistical analysis was performed with data of normal, benign and malignant groups corresponding to same sites and gender. The SUVmax and SUVmean of normal vertebrae in males were markedly higher than those in females (P < 0.0009). The SUVmax of each normal vertebral segment showed a strong negative correlation with CT values in both males and females (r = − 0.89 and − 0.92, respectively; P < 0.0009). The SUVmax of normal vertebrae also showed significant correlation with weight, height, and BMI in males (r = 0.4, P < 0.0009; r = 0.28, P = 0.005; r = 0.22, P = 0.026), and significant correlation with weight and BMI in females (r = 0.32, P = 0.009; r = 0.23, P = 0.031). The SUVmax of normal group, benign bone lesion group and malignant bone metastasis foci group showed statistical differences in both males and females. Our study evaluated SUVmax and SUVmean of normal vertebrae, benign bone lesion and malignant bone metastasis foci with a large sample population. Preliminary results proved the potential value of SUVmax in differentiation benign and malignant bone lesions. The results may provide a quantitative reference for clinical diagnosis and the evaluation of therapeutic response in vertebral lesions.

The Effects of Paraspinal Muscle Volume on Physiological Load on the Lumbar Vertebral Column: A Finite-Element Study.

Abstract: Study design Analytical biomechanical study using a finite-element (FE) model. Objective We investigated the effects of paraspinal muscle volume to the physiological loading on the lower lumbar vertebral column using a FE model. Summary of background data The FE model analysis can measure the physiological load on the lumbar vertebral column. Which changes as the surrounding environment changes. In this study, our FE model consisted of the sacrum, lumbar spine (L3-L5), intervertebral discs, facet joints, and paraspinal muscles. Methods Three-dimensional FE models of healthy lumbar spinal units were reconstructed. The physiological loads exerted on the lumbar vertebra column were evaluated by applying different paraspinal muscle volumes (without muscles, 50%, 80%, and 100% of healthy muscle volume). Results As the paraspinal muscle volume increased, the loads exerted on the vertebral column decreased. The mean load on the intervertebral disc was 1.42 ± 0.75 MPa in the model without muscle, 1.393 ± 0.73 MPa in the 50% muscle volume model, 1.367 ± 0.71 MPa in the 80% muscle volume model, and 1.362 ± 0.71 MPa in the 100% muscle volume model. The mean loads exerted on the posterior column of lumbar spine were 11.79 ± 4.70 MPa in the model without muscles, 11.57 ± 4.57 MPa in the model with 50% muscle volume, and 11.13 ± 4.51 MPa in the model with 80% muscle volume, and 10.92 ± 4.33 MPa in the model with 100% muscle volume. The mean pressure on the vertebral body in the model without paraspinal muscle, and with 50%, 80%, and 100% paraspinal muscle volume were 14.02 ± 2.82, 13.82 ± 2.62, 13.65 ± 2.61, and 13.59 ± 2.51 MPa, respectively. Conclusion Using FEM, we observed that the paraspinal muscle volume decreases pressure exerted on the lumbar vertebral column. Based on these results, we believe that exercising to increase paraspinal muscle volume would be helpful for spinal pain management and preventing lumbar spine degeneration.Level of Evidence: N/A.

Automatically Diagnosing Disk Bulge and Disk Herniation With Lumbar Magnetic Resonance Images by Using Deep Convolutional Neural Networks: Method Development Study.

Abstract: Background: Disk herniation and disk bulge are two common disorders of lumbar intervertebral disks (IVDs) that often result in numbness, pain in the lower limbs, and lower back pain. Magnetic resonance (MR) imaging is one of the most efficient techniques for detecting lumbar diseases and is widely used for making clinical diagnoses at hospitals. However, there is a lack of efficient tools for effectively interpreting massive amounts of MR images to meet the requirements of many radiologists. Objective: The aim of this study was to present an automatic system for diagnosing disk bulge and herniation that saves time and can effectively and significantly reduce the workload of radiologists. Methods: The diagnosis of lumbar vertebral disorders is highly dependent on medical images. Therefore, we chose the two most common diseases—disk bulge and herniation—as research subjects. This study is mainly about identifying the position of IVDs (lumbar vertebra [L] 1 to L2, L2-L3, L3-L4, L4-L5, and L5 to sacral vertebra [S] 1) by analyzing the geometrical relationship between sagittal and axial images and classifying axial lumbar disk MR images via deep convolutional neural networks. Results: This system involved 4 steps. In the first step, it automatically located vertebral bodies (including the L1, L2, L3, L4, L5, and S1) in sagittal images by using the faster region-based convolutional neural network, and our fourfold cross-validation showed 100% accuracy. In the second step, it spontaneously identified the corresponding disk in each axial lumbar disk MR image with 100% accuracy. In the third step, the accuracy for automatically locating the intervertebral disk region of interest in axial MR images was 100%. In the fourth step, the 3-class classification (normal disk, disk bulge, and disk herniation) accuracies for the L1-L2, L2-L3, L3-L4, L4-L5, and L5-S1 IVDs were 92.7%, 84.4%, 92.1%, 90.4%, and 84.2%, respectively. Conclusions: The automatic diagnosis system was successfully built, and it could classify images of normal disks, disk bulge, and disk herniation. This system provided a web-based test for interpreting lumbar disk MR images that could significantly improve diagnostic efficiency and standardized diagnosis reports. This system can also be used to detect other lumbar abnormalities and cervical spondylosis.

Automated Vertebral Segmentation and Measurement of Vertebral Compression Ratio Based on Deep Learning in X-Ray Images

Abstract: Vertebral compression fracture is a deformity of vertebral bodies found on lateral spine images. To diagnose vertebral compression fracture, accurate measurement of vertebral compression ratio is required. Therefore, rapid and accurate segmentation of vertebra is important for measuring the vertebral compression ratio. In this study, we used 339 data of lateral thoracic and lumbar vertebra images for training and testing a deep learning model for segmentation. The result of segmentation by the model was compared with the manual measurement, which is performed by a specialist. As a result, the average sensitivity of the dataset was 0.937, specificity was 0.995, accuracy was 0.992, and dice similarity coefficient was 0.929, area under the curve of receiver operating characteristic curve was 0.987, and the precision recall curve was 0.916. The result of correlation analysis shows no statistical difference between the manually measured vertebral compression ratio and the vertebral compression ratio using the data segmented by the model in which the correlation coefficient was 0.929. In addition, the Bland–Altman plot shows good equivalence in which VCR values are in the area within average ± 1.96. In conclusion, vertebra segmentation based on deep learning is expected to be helpful for the measurement of vertebral compression ratio.

Novel augmentation technique of percutaneous pedicle screw fixation using hydroxyapatite granules in the osteoporotic lumbar spine: a cadaveric biomechanical analysis

Abstract: Percutaneous pedicle screw (PPS) fixation has been commonly used for various spine surgeries. Rigid PPS fixation is necessary to decrease the incidence of screw loosening in osteoporotic spine. Recently, we have reported biomechanical advantages of augmentation technique using hydroxyapatite (HA) granules for PPS fixation in synthetic bone. However, its biomechanical performance in augmenting PPS fixation for osteoporotic spine has not been fully elucidated. The aim of the present study is to perform a cadaveric biomechanical analysis of PPS fixation augmented with HA granules. Thirty osteoporotic lumbar vertebrae (L1–L5) were obtained from 6 cadavers (3 men and 3 women; age 80 ± 9 years; bone mineral density 73 ± 9 mg/cm3). The maximal pullout strength and maximal insertion torque were compared between the screws inserted into the vertebrae with and without augmentation. In toggle testing, the number of craniocaudal toggle cycles and maximal load required to achieve the 2-mm screw head displacement were also compared. The maximal pullout strength in the screws augmented with HA granules was significantly greater compared to those without augmentation (p < 0.05). The augmentation significantly increased the maximal insertion torque of the screws (p < 0.05). Moreover, the number of toggle cycles and the maximal load required to reach 2 mm of displacement were significantly higher in the augmented screws (p < 0.05). The PPS fixation was significantly enhanced by the augmentation with HA granules in the osteoporotic lumbar spine. The PPS fixation augmented with HA granules might decrease the incidence of screw loosening and implant failure in patients with osteoporotic spine.

Prediction of Incidental Osteoporotic Fractures at Vertebral-Specific Level Using 3D Non-Linear Finite Element Parameters Derived from Routine Abdominal MDCT.

Abstract: To investigate whether finite element (FE) analysis of the spine in routine thoracic/abdominal multi-detector computed tomography (MDCT) can predict incidental osteoporotic fractures at vertebral-specific level; Baseline routine thoracic/abdominal MDCT scans of 16 subjects (8(m), mean age: 66.1 ± 8.2 years and 8(f), mean age: 64.3 ± 9.5 years) who sustained incidental osteoporotic vertebral fractures as confirmed in follow-up MDCTs were included in the current study. Thoracic and lumbar vertebrae (T5-L5) were automatically segmented, and bone mineral density (BMD), finite element (FE)-based failure-load, and failure-displacement were determined. These values of individual vertebrae were normalized globally (g), by dividing the absolute value with the average of L1-3 and locally by dividing the absolute value with the average of T5-12 and L1-5 for thoracic and lumbar vertebrae, respectively. Mean-BMD of L1-3 was determined as reference. Receiver operating characteristics (ROC) and area under the curve (AUC) were calculated for different normalized FE (Kload, Kdisplacement,K(load)g, and K(displacement)g) and BMD (KBMD, and K(BMD)g) ratio parameter combinations for identifying incidental fractures. Kload, K(load)g, KBMD, and K(BMD)g showed significantly higher discriminative power compared to standard mean BMD of L1-3 (BMDStandard) (AUC = 0.67 for Kload; 0.64 for K(load)g; 0.64 for KBMD; 0.61 for K(BMD)g vs. 0.54 for BMDStandard). The combination of Kload, Kdisplacement, and KBMD increased the AUC further up to 0.77 (p < 0.001). The combination of FE with BMD measurements derived from routine thoracic/abdominal MDCT allowed an improved prediction of incidental fractures at vertebral-specific level.

Assessment of adolescent idiopathic scoliosis from body scanner image by finite element simulations.

Abstract: Adolescent idiopathic scoliosis, is a three-dimensional spinal deformity characterized by lateral curvature and axial rotation around the vertical body axis of the spine, the cause of which is yet unknown The fast progression entails regular clinical monitoring, including X-rays Here we present an approach to evaluate scoliosis from the three-dimensional image of a patient's torso, captured by an ionizing radiation free body scanner, in combination with a model of the ribcage and spine A skeletal structure of the ribcage and vertebral column was modelled with computer aided designed software and was used as an initial structure for macroscopic finite element method simulations The basic vertebral column model was created for an adult female in an upright position The model was then used to simulate the patient specific scoliotic spine configurations The simulations showed that a lateral translation of a vertebral body results in an effective axial rotation and could reproduce the spinal curvatures The combined method of three-dimensional body scan and finite element model simulations thus provide quantitative anatomical information about the position, rotation and inclination of the thoracic and lumbar vertebrae within a three-dimensional torso Furthermore, the simulations showed unequal distributions of stress and strain profiles across the intervertebral discs, due to their distortions, which might help to further understand the pathogenesis of scoliosis

Intraoperative Computed Tomography-Based Navigation with Augmented Reality for Lateral Approaches to the Spine.

Abstract: Background. Lateral approaches to the spine have gained increased popularity due to enabling minimally invasive access to the spine, less blood loss, decreased operative time, and less postoperative pain. The objective of the study was to analyze the use of intraoperative computed tomography with navigation and the implementation of augmented reality in facilitating a lateral approach to the spine. Methods. We prospectively analyzed all patients who underwent surgery with a lateral approach to the spine from September 2016 to January 2021 using intraoperative CT applying a 32-slice movable CT scanner, which was used for automatic navigation registration. Sixteen patients, with a median age of 64.3 years, were operated on using a lateral approach to the thoracic and lumbar spine and using intraoperative CT with navigation. Indications included a herniated disc (six patients), tumors (seven), instability following the fracture of the thoracic or lumbar vertebra (two), and spondylodiscitis (one). Results. Automatic registration, applying intraoperative CT, resulted in high accuracy (target registration error: 0.84 ± 0.10 mm). The effective radiation dose of the registration CT scans was 6.16 ± 3.91 mSv. In seven patients, a control iCT scan was performed for resection and implant control, with an ED of 4.51 ± 2.48 mSv. Augmented reality (AR) was used to support surgery in 11 cases, by visualizing the tumor outline, pedicle screws, herniated discs, and surrounding structures. Of the 16 patients, corpectomy was performed in six patients with the implantation of an expandable cage, and one patient underwent discectomy using the XLIF technique. One patient experienced perioperative complications. One patient died in the early postoperative course due to severe cardiorespiratory failure. Ten patients had improved and five had unchanged neurological status at the 3-month follow up. Conclusions. Intraoperative computed tomography with navigation facilitates the application of lateral approaches to the spine for a variety of indications, including fusion procedures, tumor resection, and herniated disc surgery.

Association of Lumbar Spine Radiographic Changes With Severity of Back Pain-Related Disability Among Middle-aged, Community-Dwelling Women.

Abstract: Importance Previous studies, using mostly cross-sectional data, provide conflicting evidence of an association between lumbar spine radiographic changes and the severity of back pain–related disability. Such conflicting evidence may be associated with widely unnecessary diagnostic imaging of the lumbar spine. Objective To examine both cross-sectional and longitudinal associations between lumbar spine radiographic changes and the severity of back pain–related disability among middle-aged, community-dwelling women. Design, Setting, and Participants This population-based prospective cohort study used data from the Chingford 1000 Women Study. Analyses included data collected from year 6 (1994-1996; physical activity was measured), year 9 (1997-1999; treated as baseline), and year 15 (2003-2005), with a total length of follow-up for longitudinal analyses of 6 years. Data were analyzed from April 17 to November 3, 2020. Exposures Primary exposure was lumbar spine radiographic changes, defined using the Kellgren-Lawrence (K-L) grade. Secondary exposures were defined using presence of osteophytes and disc space narrowing. The composite score combined the number of lumbar spine segments with definite changes detected on radiographic images (ie, radiographic changes) (K-L grade ≥2, which means at least definite osteophyte and possible narrowing of disc space are present; osteophyte and disc space narrowing grade ≥1, which means at least mild or definite changes are present). Main Outcomes and Measures Self-reported back pain–related disability measured in years 9 and 15 assessed by the St Thomas disability questionnaire. Results Among 650 women (mean [SD] age, 61.3 [5.9] years) in cross-sectional analyses and 443 women (mean [SD] age, 60.6 [6.0] years) in longitudinal analyses, there was no evidence to support an association between higher number of lumbar segments with radiographic changes (K-L grade, osteophytes, and disc space narrowing) and more severe back pain–related disability (eg, cross-sectional analyses using the K-L grade; 1 segment vs 0 segment: adjusted odds ratio, 1.22 [95% CI, 0.76-1.96]). No interactions were found of an association between lumbar spine radiographic changes and the severity of back pain–specific disability with age, body mass index, or smoking status. Conclusions and Relevance In this cohort of middle-aged, community-dwelling women, there was no evidence to support an association between a higher number of lumbar segments with radiographic changes (K-L grade, osteophytes, and disc space narrowing) and more severe back pain–related disability cross-sectionally or over time. These findings provide further evidence against routinely using diagnostic imaging of the lumbar spine.

Proximal junctional kyphosis is a rebalancing spinal phenomenon due to insufficient postoperative thoracic kyphosis after adolescent idiopathic scoliosis surgery

Abstract: Many authors tried to explain proximal junctional kyphosis (PJK) after adolescent idiopathic scoliosis (AIS) surgery by looking for risk factors. Latest publications focus on sagittal alignment. Each healthy adolescent has a specific thoracic kyphosis (TK) depending on their pelvic parameters and lumbar lordosis (LL). The objective of this work is to determine if the difference between TK at follow-up (TKFU) and the patient-specific TK (PSTK) plays a role in PJK occurrence after AIS surgery. The secondary objective was to find other risk factors. We analyzed retrospectively 570 thoracic AIS who underwent a posterior thoracic fusion from nine centers. The series was separated in two groups: with and without PJK. PSTK was calculated with the formula PSTK = 2(PT + LL-PI). TK Gap was the difference between TKFU and PSTK. Logistic regression was utilized to test the impact of TK Gap and other known risk factors on PJK occurrence. Univariate analysis showed 15 factors significantly different between the groups. In a multivariate analysis, three factors had a strong significant influence on PJK: TKFU, TK Gain and TK Gap. Four additional factors affected the rate of PJK: Posterior translation on two rods, preoperative TK, preoperative LL and number of instrumented vertebrae. PJK is related to the insufficient TK at follow-up, compared to the specific TK that every patient should have according to their pelvic parameters. PJK incidence is significantly reduced by a strong gain in TK and a thoracic selective fusion which leaves the proximal lumbar vertebrae free. Diagnostic: individual cross-sectional studies with consistently applied reference standard and blinding

Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.

Abstract: Background The referral process for consultation with a spine surgeon remains inefficient, given a substantial proportion of referrals to spine surgeons are nonoperative. Objective To develop a machine-learning-based algorithm which accurately identifies patients as candidates for consultation with a spine surgeon, using only magnetic resonance imaging (MRI). Methods We trained a deep U-Net machine learning model to delineate spinal canals on axial slices of 100 normal lumbar MRI scans which were previously delineated by expert radiologists and neurosurgeons. We then tested the model against lumbar MRI scans for 140 patients who had undergone lumbar spine MRI at our institution (60 of whom ultimately underwent surgery, and 80 of whom did not). The model generated automated segmentations of the lumbar spinal canals and calculated a maximum degree of spinal stenosis for each patient, which served as our biomarker for surgical pathology warranting expert consultation. Results The machine learning model correctly predicted surgical candidacy (ie, whether patients ultimately underwent lumbar spinal decompression) with high accuracy (area under the curve = 0.88), using only imaging data from lumbar MRI scans. Conclusion Automated interpretation of lumbar MRI scans was sufficient to correctly determine surgical candidacy in nearly 90% of cases. Given that a significant proportion of referrals placed for spine surgery evaluation fail to meet criteria for surgical intervention, our model could serve as a valuable tool for patient triage and thereby address some of the inefficiencies within the outpatient surgical referral process.

Hounsfield unit value on CT as a predictor of cage subsidence following stand-alone oblique lumbar interbody fusion for the treatment of degenerative lumbar diseases.

Abstract: BACKGROUND To investigate the correlation between vertebral Hounsfield unit (HU) values and cage subsidence in patients treated with stand-alone (SA) OLIF. METHODS A retrospective review of collected data was performed on 76 patients who underwent SA OLIF. We utilized the HU value for lumbar bone mineral density (BMD) obtained on preoperative CT. The vertebral HU values of patients with subsidence were compared to those without subsidence. The correlation between cage subsidence and clinical score was investigated. RESULTS Sixteen patients (21.1%) had at least radiographic evidence of interbody cage subsidence. The average cage subsidence was 2.5 ± 1.3 mm (range 0.9-4.8 mm). There were no significant differences in sex, BMI, preoperative diagnoses, or fused level (p > 0.05); however, there were significant differences between the cage subsidence group and the nonsubsidence group in age, average of the lowest T-score, and average HU value, including for the L1 vertebrae, L1-L4 horizontal plane, and L1-L4 sagittal plane (p < 0.05). The average HU value of the L1-L4 horizontal plane showed a more predictable AUC of 0.909 (95% CI, 0.834-0.984; P < 0.001) compared with the average of the lowest T-score following an AUC of 0.791 (95% CI, 0.674-0.909; P < 0.001). Based on logistic regression analysis, the average HU value of the L1-L4 horizontal plane (OR, 0.912; 95% CI, 0.861-0.966; P = 0.002) was an independent factor influencing cage subsidence. CONCLUSIONS Patients with lower average HU values of the lumbar vertebrae are at a much higher risk of developing cage subsidence after SA OLIF. Measurement of preoperative HU values on preexisting CT scans could be rapid, simple and feasible.

A comparative study of breed differences in the anatomical configuration of the equine vertebral column

Abstract: The importance of the equine thoracolumbar vertebral column in orthopaedic disorders is well recognized and diagnostic imaging becomes more feasible, but little is known about variations in the anatomical configuration within breeds. In this descriptive post-mortem study, anatomical variations in three widely differing breeds: Warmblood horses, Shetland ponies and semi-feral Konik horses are described. The caudal cervical (C), thoracic (T), lumbar (L) and sacral (S) regions of the vertebral column of 30 Warmblood horses, 29 Shetland ponies and 18 Konik horses were examined using computed tomography and visualized by volume rendering. Homologous/morphologic variations in the caudal cervical area were frequently seen in Warmblood horses (43%), which was significantly more than in the other breeds (p < 0.001). The as standard described equine formula of 18 T, 6 L and 5 S vertebrae was seen in 78% of Konik horses, but only in 53% Warmblood horses and 38% Shetland ponies, which was significantly different (p < 0.05). Overall, Shetland ponies showed a higher tendency of thoracoization, lumbarization and more variations in the number of vertebrae and pairs of ribs. Ankylosed intertransverse joints (ITJs) between transverse processes of the lumbar vertebrae were most common between the second last and last lumbar vertebra and prevalence was significantly higher in Shetland ponies (61%), than in Warmblood horses (38%) and Konik horses (7%) (p < 0.0001). Cranial to the second last lumbar vertebra there were fewer ITJs ankylosed (14%) in Warmblood horses (p < 0.0095), and this decrease in number of ankylosed ITJs was different compared to the change in ankylosed ITJs in Shetland ponies (p < 0.005). ITJs occurred asymmetrically in 15% (12/77) of the cases. A limitation of the study was that clinical data of the horses were only incompletely available, precluding any conclusions about the potential clinical implications of anatomical variations. Knowledge of variation in osseous anatomy of the equine thoracolumbar vertebral column is important for the interpretation of diagnostic imaging. To assess the functional importance and clinical relevance of this variation, follow-up studies are necessary.

Age estimation by evaluation of osteophytes in thoracic and lumbar vertebrae using postmortem CT images in a modern Japanese population

Abstract: Estimation of age at death is important in forensic investigations of unknown remains. There have been several reports on applying the degree of osteophyte formation—an age-related change in the vertebral body—for age estimation; however, this method is not yet established. This study investigated a method for age estimation of modern Japanese individuals using osteophytes measured on CT images. The sample included 250 cadavers (125 males) aged 20–95 years. The degree of osteophyte formation was evaluated as score O (0–5 points), and the degree of fusion of the osteophytes between the upper and lower vertebrae was evaluated as score B (0–2 points). Age estimation equations were developed using regression analyses with seven variables, determined by scores O and B, and the equation with the smallest standard error of estimate (SEE) was obtained when the number of vertebrae with score O ≥ 2 was used as the explanatory variable. Age estimation with SEE of about 10 years was possible even when partial vertebrae with a high degree of osteophyte formation were used, showing its potential for practical application. The cutoff value for age estimation was established using the receiver operating characteristic curve analysis, wherein good results were obtained for all variables (area under the curve ≥ 0.8). The combination of the estimation equation and the cutoff value can narrow the range of age estimates.

Gorham-Stout Disease with Multiple Bone Involvement-Challenging Diagnosis of a Rare Disease and Literature Review.

Abstract: Gorham-Stout disease is a rare disorder, which may result in a poor prognosis. This disease, a rare lymphangiomatosis, is defined by progressive bone disappearance due to massive unicentric and multicentric osteolysis. Osteolytic lesions of the spine and pleura effusion are poor prognostic factors. Herein, we will present a case where the onset of disease occurred at the age of 18 with asthenia, myalgia, and major bone pain, followed by incomplete motor deficiency in the lower limbs and, later, in the upper limbs. Imaging studies (CT scan and MRI) of the patient revealed osteolytic lesions (cervical and thoracic vertebrae, rib, and clavicle) and a pathological fracture of the C7 vertebra. Surgical procedures undertaken involved replacing the affected vertebrae with bone grafting and prosthesis. The investigations performed allowed for the exclusion of inflammation, thyroid or parathyroid disease, lymphoma, neoplasia, or autoimmune disorders. A bone marrow biopsy showed osteolysis, the replacement of bone tissues with connective tissue, and chronic non-specific inflammation. The evolution was negative with almost complete osteolysis of the left clavicle, the emergence of new osteolysis areas in the lumbar vertebrae, pelvic bones, and the bilateral proximal femur, splenic nodules, chylothorax, and associated major neurological deficits. Unfortunately, this negative evolution resulted in the patient’s death a year after onset.

Geometric and volumetric relationship between human lumbar vertebrae and "Black-bone" MRI-based models.

Abstract: Background This study will examine the differences between human lumbar vertebrae, three-dimensional (3D) scans of these bones, 3D models based on 'Black-bone' magnetic resonance imaging (MRI) scans, and 3D-printed models. Materials and methods 3D mesh models were created from the "Black-bone" MRI data from two cadaveric human spines, and then 3D printed. Four models were analysed and compared: anatomic bones, 3D-scanned models, MRI models and 3D-printed models. Results There was no significant difference between when comparing the average of all measurements between all model types (p = 0.81). The mean dice coefficient was 0.91 (SD 0.016) and the mean Hausdorff distance was 0.37 mm (SD 0.04 mm) when comparing the MRI model to the 3D-scanned model. The mean volumes for the MRI model and the 3D scanned model were 10.42 and 10.04 ml (p = 0.085), respectively. Conclusions The 'Black-bone' MRI could be a valid radiation-free alternative to computed tomography for the 3D printing of lumbar spinal biomodels.

Bone density optimized pedicle screw instrumentation improves screw pull-out force in lumbar vertebrae.

Abstract: Pedicle screw instrumentation is performed in the surgical treatment of a wide variety of spinal pathologies. A common postoperative complication associated with this procedure is screw loosening. ...

Role of the Lumbosacral Transition Vertebra and Vertebral Lamina in the Pathogenesis of Lumbar Disc Herniation.

Abstract: Objective To investigate the prevalence of lumbosacral transition vertebrae (LSTVs) in both the normal population and the lumbar disc herniation (LDH) population and to determine the risk factors for LDH. Methods Between January 2019 and September 2020, all patients aged 18-39 years and underwent an anteroposterior (AP) X-ray of the lumbar vertebrae were retrospective reviewed in our institution. Those patients who were diagnosed with LDH were eligible for inclusion in the LDH group. During the same period, those patients admitted to our hospital who underwent an anteroposterior X-ray of the lumbar spine and had not been diagnosed with LDH were included in the control group. Those patients with disease that might affect the lumbar anatomy were excluded from both groups. The type of LSTV was classified according to the Castellvi classification. The height of the lumbar vertebral lamina was evaluated through the h/H index. The inter- and intra-observer reliability was evaluated by one senior radiologist and one senior orthopedist using intraclass correlation coefficient (ICC). The association between the LSTV and the herniation level was also investigated. Binary logistic regression was used to explore the association of different factors between the LDH group and the control group. Results Two hundred LDH patients (115 male and 85 female) and 200 individuals (108 male and 92 female) were investigated retrospectively. The prevalence of LSTVs was 71.5% (n = 143) in the LDH group and 34.0% (n = 68) in the control group. The most frequent LSTV types were type Ib and type IIa. The inter- and intra-observer ICCs of the measurement of "h/H" index and the classification of LSTV were all "excellent" (ICC > 0.90). The median h/H index in the control group was significantly higher than that in the LDH group (0.28 (0.26, 0.31) vs 0.34 (0.31, 0.37), P = 0.000). The distribution of the Castellvi classification in the L4/5 and L5/S1 herniation patients was significantly different (P = 0.048). LSTVs, BMI and the h/H index were closely associated with LDH, with odds ratios of 3.06 (95% CI: 2.12-4.43), 1.23 (95% CI: 1.13-1.33) and 0.09 (95% CI: 0.05-0.15), respectively. The incidence of L4/5 disc herniation in patients with an LSTV was significantly more common than that in patients with L5/S1 disc herniation (P = 0.048). Conclusion The prevalence of LSTVs was 34.0% in the control group and 71.5% in the LDH group; LSTVs and BMI were positively correlated with LDH, and h/H was negatively correlated with LDH.

Providing Epidemiological Data in Lumbar Spine Imaging Reports Did Not Affect Subsequent Utilization of Spine Procedures: Secondary Outcomes from a Stepped-Wedge Randomized Controlled Trial.

Abstract: Objective To evaluate the effect of inserting epidemiologic information into lumbar spine imaging reports on subsequent non-surgical and surgical procedures involving the thoracolumbosacral spine and sacroiliac (SI) joints. Design Analysis of secondary outcomes from the Lumbar Imaging with Reporting of Epidemiology (LIRE) pragmatic stepped-wedge randomized trial. Setting Primary care clinics within four integrated healthcare systems in the United States. Subjects 238,886 patients aged ≥18 years who received lumbar diagnostic imaging between 2013-2016. Methods Clinics were randomized to receive text containing age- and modality-specific epidemiologic benchmarks indicating the prevalence of common spine imaging findings in people without low back pain, inserted into lumbar spine imaging reports (the "LIRE intervention"). The study outcomes were receiving (1) any non-surgical lumbosacral or sacroiliac spine procedure (lumbosacral epidural steroid injection, facet joint injection, or facet joint radiofrequency ablation; or sacroiliac joint injection) or (2) any surgical procedure involving the lumbar, sacral, or thoracic spine (decompression surgery or spinal fusion or other spine surgery). Results The LIRE intervention was not significantly associated with subsequent utilization of non-surgical lumbosacral or sacroiliac spine procedures (odds ratio [OR]=1.01, 95% confidence interval [CI] 0.93-1.09; p = 0.79) or any surgical procedure (OR = 0.99, 95 CI 0.91-1.07; p = 0.74) involving the lumbar, sacral, or thoracic spine. The intervention was also not significantly associated with any individual spine procedure. Conclusions Inserting epidemiologic text into spine imaging reports had no effect on non-surgical or surgical procedure utilization among patients receiving lumbar diagnostic imaging.

Single level posterolateral lumbar fusion in a New Zealand White rabbit (Oryctolagus cuniculus) model: Surgical anatomy, operative technique, autograft fusion rates, and perioperative care.

Abstract: Introduction The posterolateral lumbar fusion (PLF) New Zealand White (NZW) (Oryctolagus cuniculus) rabbit model is a long-standing surgical technique for the preclinical evaluation of materials for spinal fusion. A detailed understanding of lumbar spine anatomy and perioperative care requirements of rabbits is imperative for correct execution of the model both scientifically and ethically. This study describes the preoperative procedures and surgical techniques used in single level PLF in a NZW rabbit model as it pertains to the animal husbandry, lumbar spine anatomy, anesthesia, surgical approach, and perioperative care of rabbits in a research setting. Materials and methods We describe the surgical technique and perioperative patient care for single level PLF in a NZW rabbit model. Medical records from a single research facility were retrospectively reviewed for adult NZW rabbits that underwent single level PLF (L4-L5) between January 2016 and December 2019. The number of lumbar vertebrae per rabbit, fusion rates at 12 weeks using iliac crest autograft and complications are reported. Skeletal maturity was confirmed by preoperative fluoroscopic and radiographic documented closure of hindlimb physes. Results The PLF rabbit surgical model and perioperative patient care is described. PLF was performed in 868 adult female entire NZW rabbits. The majority of rabbits had seven lumbar vertebrae (620/868; 71.4%), followed by six (221/868; 25.5%), and eight (27/868; 3.1%). Fusion rates at 12 weeks for PLF using iliac crest autograft as assessed by manual palpation and radiographic assessment was 76.9% and 70.0%, respectively. Postoperative complications included occasional partial autograft site wound dehiscence due to self-trauma. Conclusions For PLF rabbit models, a detailed understanding of the surgical technique, rabbit lumbar anatomy including number of lumbar vertebrae, and dietary and husbandry requirements of rabbits, is essential for execution of the model and animal welfare.

Association of Continuous Vertebral Bone Bridges and Bone Mineral Density with the Fracture Risk in Patients with Diffuse Idiopathic Skeletal Hyperostosis.

Abstract: Study Design Cross-sectional study. Purpose To examine whether the number of continuous vertebral bone bridges and bone mineral density (BMD) influence the fracture risk in diffuse idiopathic skeletal hyperostosis (DISH) patients. Overview of Literature Bone bridges connecting through the intervertebral body in DISH create long lever arms that can increase the risk of fractures from minor trauma. DISH patients have a BMD that is higher than or comparable to those of age-matched healthy subjects. Methods We examined the computed tomography scans from the thoracic vertebra to the sacrum used to diagnose DISH in 140 patients (98 men and 42 women; average age, 78.6 years). We compared patients who did (n=52) and did not have (n=88) fractures at the continuous vertebral bodies fused by bone bridges. The relationship between the vertebral fractures and the maximum number of vertebrae that are bony cross-linked with contiguous adjacent vertebrae (max VB) from the thoracic vertebra to the sacrum or from the lumbar vertebra to the sacrum and proximal femur BMD were analyzed using a logistic regression model. Results We found that after adjusting for the confounding factors, higher max VB, both from the thoracic vertebrae to the sacrum and the lumbar vertebrae to the sacrum, was associated with a higher risk of vertebral fractures. This difference was statistically significant. The risk was higher when only the lumbar vertebrae to the sacrum was considered (thoracic vertebrae to the sacrum: odds ratio, 1.21; p<0.05; lumbar vertebrae to the sacrum: odds ratio, 2.78; p<0.01). Moreover, low proximal femur BMD in DISH patients raises the fracture risk (odds ratio, 0.47; p<0.01). Conclusions Many continuous vertebral bone bridges, especially those that extend to the lumbar spine and low proximal femur BMD, are risk factors for fracture in DISH patients.

Simplified Universal Grading of Lumbar Spine MRI Degenerative Findings: Inter-Reader Agreement of Non-Radiologist Spine Experts.

Abstract: OBJECTIVE 1) To describe a simplified multidisciplinary grading system for the most clinically relevant lumbar spine degenerative changes. 2) To measure the inter-reader variability among non-radiologist spine experts in their use of the classification system for interpretation of a consecutive series of lumbar spine magnetic resonance imaging (MRI) examinations. METHODS ATS multidisciplinary and collaborative standardized grading of spinal stenosis, foraminal stenosis, lateral recess stenosis, and facet arthropathy was developed. Our institution's picture archiving and communication system was searched for 50 consecutive patients who underwent non-contrast MRI of the lumbar spine for chronic back pain, radiculopathy, or symptoms of spinal stenosis. Three fellowship-trained spine subspecialists from neurosurgery, orthopedic surgery, and physiatry interpreted the 50 exams using the classification at the L4-L5 and L5-S1 levels. Inter-reader agreement was assessed with Cohen's kappa coefficient. RESULTS For spinal stenosis, the readers demonstrated substantial agreement (κ = 0.702). For foraminal stenosis and facet arthropathy, the three readers demonstrated moderate agreement (κ = 0.544, and 0.557, respectively). For lateral recess stenosis, there was fair agreement (κ = 0.323). CONCLUSIONS A simplified universal grading system of lumbar spine MRI degenerative findings is newly described. Use of this multidisciplinary grading system in the assessment of clinically relevant degenerative changes revealed moderate to substantial agreement among non-radiologist spine physicians. This standardized grading system could serve as a foundation for interdisciplinary communication.