Gender differences in spinal mobility during postural changes: a detailed analysis using upright CT.

Lumbar spinal alignment is crucial for spine biomechanics and is linked to various spinal pathologies. However, limited research has explored gender-specific differences using CT scans. The objective was to evaluate and compare lumbar spinal alignment between standing and sitting CT in healthy individuals, focusing on gender differences. 24 young and 25 elderly males (M) and females (F) underwent standing and sitting CT scans to assess lumbar spinal alignment. Parameters measured and compared between genders included lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), lordotic angle (LA), foraminal height (FH), and bony boundary area (BBA). Females showed significantly larger changes in SS and PT when transitioning from standing to sitting (p = .044, p = .038). A notable gender difference was also observed in the L4-S LA among the elderly, with females showing a significantly larger decrease in lordotic angle compared to males (- 14.1° vs. - 9.2°, p = .039*). Females consistently exhibited larger FH and BBA values, particularly in lower lumbar segments, which was more prominent in the elderly group (M vs. F: L4/5 BBA 80.1 mm2 [46.3, 97.8] vs. 109.7 mm2 [74.4, 121.3], p = .019 in sitting). These findings underline distinct gender-related variations in lumbar alignment and flexibility, with a focus on noteworthy changes in BBA and FH in females. Gender differences in lumbar spinal alignment were evident, with females displaying greater pelvic and sacral mobility. Considering gender-specific characteristics is crucial for assessing spinal alignment and understanding spinal pathologies. These findings contribute to our understanding of lumbar spinal alignment and have implications for gender-specific spinal conditions and treatments.

Automated Detection and Segmentation of Bone Metastases on Spine MRI Using U-Net: A Multicenter Study.

OBJECTIVE: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. MATERIALS AND METHODS: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. RESULTS: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. CONCLUSION: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.

Bacterial and Viral Infectious Disease of the Spine.

Spinal infections are a diverse group of diseases affecting different compartments of the spine with variable clinical and imaging presentations. Diagnosis of spinal infections is based on a combination of clinical features, laboratory markers, and imaging studies. Imaging plays a pivotal role in the diagnosis and management of spinal infections. The characteristic imaging manifestations of bacterial and viral infections in the spine are discussed with key teaching points emphasized.

Fast and accurate 3-D spine MRI segmentation using FastCleverSeg.

Accurate and efficient segmenting of vertebral bodies, muscles, and discs is crucial for analyzing various spinal diseases. However, traditional methods are either laborious and time-consuming (manual segmentation) or require extensive training data (fully automatic segmentation). FastCleverSeg, our proposed semi-automatic segmentation approach, addresses those limitations by significantly reducing user interaction while maintaining high accuracy. First, we reduce user interaction by requiring the manual annotation of only two or three slices. Next, we automatically Estimate the Annotation on Intermediary Slices (EANIS) using traditional computer vision/graphics concepts. Finally, our proposed method leverages improved voxel weight balancing to achieve fast and precise volumetric segmentation in the segmentation process. Experimental evaluations on our assembled diverse MRI databases comprising 179 patients (60 male, 119 female), demonstrate a remarkable 25 ms (30 ms standard deviation) processing time and a significant reduction in user interaction compared to existing approaches. Importantly, FastCleverSeg maintains or surpasses the segmentation quality of competing methods, achieving a Dice score of 94%. This invaluable tool empowers physicians to efficiently generate reliable ground truths, expediting the segmentation process and paving the way for future integration with deep learning approaches. In turn, this opens exciting possibilities for future fully automated spine segmentation.

Spinal Manifestations of Skeletal Dysplasia: A Practical Guide for Clinical Diagnosis.

Skeletal dysplasias are a group of genetic conditions defined by atypical bone or cartilage growth and development. Skeletal abnormalities include short stature, limb deformity, joint contracture, and spinal deformity. Over 90% of disorders have a known genetic mutation that can definitively determine the diagnosis. As patients may present with a primary spinal concern, a careful clinical and radiographic evaluation can allow the physician to develop a working diagnosis to guide additional evaluation. Spinal manifestations include scoliosis and kyphoscoliosis, cervical instability, cervical kyphosis, thoracolumbar kyphosis, spinal stenosis, and atypical vertebral body morphology. An understanding of the affected conditions, prevalence, and natural history of these radiographic findings aids the orthopaedic surgeon in establishing a diagnosis and guides appropriate orthopaedic care.

Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis.

PURPOSE: Improved integration and use of preoperative imaging during surgery hold significant potential for enhancing treatment planning and instrument guidance through surgical navigation. Despite its prevalent use in diagnostic settings, MR imaging is rarely used for navigation in spine surgery. This study aims to leverage MR imaging for intraoperative visualization of spine anatomy, particularly in cases where CT imaging is unavailable or when minimizing radiation exposure is essential, such as in pediatric surgery. METHODS: This work presents a method for deformable 3D-2D registration of preoperative MR images with a novel intraoperative long-length tomosynthesis imaging modality (viz., Long-Film [LF]). A conditional generative adversarial network is used to translate MR images to an intermediate bone image suitable for registration, followed by a model-based 3D-2D registration algorithm to deformably map the synthesized images to LF images. The algorithm's performance was evaluated on cadaveric specimens with implanted markers and controlled deformation, and in clinical images of patients undergoing spine surgery as part of a large-scale clinical study on LF imaging. RESULTS: The proposed method yielded a median 2D projection distance error of 2.0 mm (interquartile range [IQR]: 1.1-3.3 mm) and a 3D target registration error of 1.5 mm (IQR: 0.8-2.1 mm) in cadaver studies. Notably, the multi-scale approach exhibited significantly higher accuracy compared to rigid solutions and effectively managed the challenges posed by piecewise rigid spine deformation. The robustness and consistency of the method were evaluated on clinical images, yielding no outliers on vertebrae without surgical instrumentation and 3% outliers on vertebrae with instrumentation. CONCLUSIONS: This work constitutes the first reported approach for deformable MR to LF registration based on deep image synthesis. The proposed framework provides access to the preoperative annotations and planning information during surgery and enables surgical navigation within the context of MR images and/or dual-plane LF images.

Importance of modifiable non-radiographic functional parameters for adult spinal deformity.

We clarified non-radiographic physical parameters associated with the severity of adult spinal deformity (ASD) using community-dwelling adult volunteers. They were subjected to upright entire spine radiographs for standard radiographic parameters and the number of sagittal modifiers of SRS-Schwab ASD classification (Schwab-SM). Clinical evaluations included isometric muscle strength of trunk extensor (TEX), trunk flexor (TFL), quadriceps femoris (QF), gluteus maximus, and iliopsoas; range of motion (ROM) of hip, knee, ankle, and active back extension (BET); SF36 physical component score (PCS), VAS for back and knee pain, and the degree of ambulatory kyphosis (dTIA). Each muscle strength was calibrated by body weight (BW) and expressed as BW ratio. According to our previous study, dTIA ≥ 7.6° was defined as pathological and dTIA ≤ 3.5° as normal. A final total of 409 female volunteers were included, and their demographics were; age 67.0 ± 5.5 years, Schwab-SM 2.1 ± 1.8, TEX 0.90 ± 0.33BW, TFL 0.48 ± 0.15BW, QF 0.45 ± 0.19BW, PCS 33.5 ± 6.5. Subjects were classified as clinical ASD group (cASD, n = 10) with PCS ≤ 27(mean-1SD) and pathological dTIA, robust group (n = 19) with PCS ≥ 40 (mean + 1SD) and normal dTIA, and the rest (non-cASD, n = 338). Statistical analyses showed significant differences in TEX, TFL, QF, knee extension (KEX), and BET between robust and cASD, and the mean values of robust group (TEX ≥ 1.1BW, TFL ≥ 0.5BW, QF ≥ 0.5BW, KEX ≥ 0° and BET ≥ 14 cm) were used as 'ASD-MJ' index. Subjects with fully achieving ASD-MJ goals showed significantly better radiographic and clinical outcomes than those with unmet goals. In conclusion, upon prescribing conservative or physical therapies for ASD patients, modifiable clinical goals should be clarified, and ASD-MJ could be a benchmark.

Unsupervised local center of mass based scoliosis spinal segmentation and Cobb angle measurement.

Scoliosis is a medical condition in which a person's spine has an abnormal curvature and Cobb angle is a measurement used to evaluate the severity of a spinal curvature. Presently, automatic Existing Cobb angle measurement techniques require huge dataset, time-consuming, and needs significant effort. So, it is important to develop an unsupervised method for the measurement of Cobb angle with good accuracy. In this work, an unsupervised local center of mass (LCM) technique is proposed to segment the spine region and further novel Cobb angle measurement method is proposed for accurate measurement. Validation of the proposed method was carried out on 2D X-ray images from the Saudi Arabian population. Segmentation results were compared with GMM-Based Hidden Markov Random Field (GMM-HMRF) segmentation method based on sensitivity, specificity, and dice score. Based on the findings, it can be observed that our proposed segmentation method provides an overall accuracy of 97.3% whereas GMM-HMRF has an accuracy of 89.19%. Also, the proposed method has a higher dice score of 0.54 compared to GMM-HMRF. To further evaluate the effectiveness of the approach in the Cobb angle measurement, the results were compared with Senior Scoliosis Surgeon at Multispecialty Hospital in Saudi Arabia. The findings indicated that the segmentation of the scoliotic spine was nearly flawless, and the Cobb angle measurements obtained through manual examination by the expert and the algorithm were nearly identical, with a discrepancy of only ± 3 degrees. Our proposed method can pave the way for accurate spinal segmentation and Cobb angle measurement among scoliosis patients by reducing observers' variability.

Association Between Two Methods of Spinal and Pelvic Analysis Among Children With Cerebral Palsy.

OBJECTIVES: Children with cerebral palsy have weak muscles, which may impair postural adjustments. These postural adjustments are required for gait and dynamic balance during the daily living activities. The aim of this study was to investigate the association between Cobb's angle and Formetric 4D surface topography system in evaluating spinal and pelvic deformity in children with cerebral palsy. METHODS: One hundred children with spastic diplegia (6 to 8 years old) diagnosed as cerebral palsy participated in this study and selected from the Outpatient Clinic of Faculty of Physical Therapy. Digital x- ray and formetric analysis were used to measure spinal deformities and pelvic deviation in children with cerebral palsy. RESULTS: There were positive correlations between Cobb's angle and formetric parameters, including trunk imbalance, lateral deviation, and pelvic tilt. Also, Formetric parameters were significant predictors of Cobb's angle, including trunk imbalance (for a one-degree increase, Cobb's angle increases by 0.227, lateral deviation (for a one-degree increase, Cobb's angle increases by 0.665), and pelvic tilt (for a one-degree increase, Cobb's angle increases by 0.252). CONCLUSION: Formetric 4D surface topography system was effective in evaluating spinal and pelvic deformity in children with cerebral palsy when compared with Digital x-ray.

Comparison of elasticity changes in the paraspinal muscles of adolescent patients with scoliosis treated with surgery and bracing.

Scoliosis is a three-dimensional spinal deformity, and paraspinal muscles play an important role as stabilizers of the spinal curve. In this prospective study, we compared elasticity changes in the paraspinal muscles of adolescent patients with scoliosis after surgery or bracing. Elasticity was measured on the concave and convex sides of the paraspinal muscles at the apex of the curve at the beginning of treatment and 6 and 12 months after treatment. Twenty-six patients with correction surgery (n = 15) or bracing (n = 11) were included. At initial evaluation, the Cobb angle was larger in the surgery group (72.3 ± 20.2° in surgery vs. 30.6 ± 5.1° in brace, p < 0.001). The estimated mean elasticity value of the paraspinal muscles was lower in the surgery group at baseline on the convex side (15.8 vs. 22.8 kPa, p = 0.037) and 6 months on both the concave (12.1 vs. 22.7 kPa, p = 0.004) and convex (13.4 vs. 23.8 kPa, p = 0.005) sides. There was a significant stiffness decrease from baseline to 6 months on the concave side in the surgery group (5.9 kPa, p = 0.025). However, the elasticity change recovered at 12 months without significant differences between the two groups.

Automatic image registration on intraoperative CBCT compared to Surface Matching registration on preoperative CT for spinal navigation: accuracy and workflow.

INTRODUCTION: Spinal navigation solutions have been slower to develop compared to cranial ones. To facilitate greater adoption and use of spinal navigation, the relatively cumbersome registration processes need to be improved upon. This study aims to validate a new solution for automatic image registration and compare it to a traditional Surface Matching method. METHOD: Adult patients undergoing spinal surgery requiring navigation were enrolled after providing consent. A registration matrix-Universal AIR (= Automatic Image Registration)-was placed in the surgical field and used for automatic registration based on intraoperative 3D imaging. A standard Surface Matching method was used for comparison. Accuracy measurements were obtained by comparing planned and acquired coordinates on the vertebrae. RESULTS: Thirty-nine patients with 42 datasets were included. The mean accuracy of Universal AIR registration was 1.20 ± 0.42 mm, while the mean accuracy of Surface Matching registration was 1.94 ± 0.64 mm. Universal AIR registration was non-inferior to Surface Matching registration. Post hoc analysis showed a significantly greater accuracy for Universal AIR registration. In Surface Matching, but not automatic registration, user-related errors such as incorrect identification of the vertebral level were seen. CONCLUSION: Automatic image registration for spinal navigation using Universal AIR and intraoperative 3D imaging provided improved accuracy compared to Surface Matching registration. In addition, it minimizes user errors and offers a standardized workflow, making it a reliable registration method for navigated spinal procedures.

Top 25 Most Cited Articles on Intraoperative Computer Tomography-Guided Navigation in Spine Surgery.

BACKGROUND: In recent years, the use of intraoperative computer tomography-guided (CT-guided) navigation has gained significant popularity among health care providers who perform minimally invasive spine surgery. This review aims to identify and analyze trends in the literature related to the widespread adoption of CT-guided navigation in spine surgery, emphasizing the shift from conventional fluoroscopy-based techniques to CT-guided navigation. METHODS: Articles pertaining to this study were identified via a database review and were hierarchically organized based on the number of citations. An "advanced document search" was performed on September 28th, 2022, utilizing Boolean search operator terms. The 25 most referenced articles were combined into a primary list after sorting results in descending order based on the total number of citations. RESULTS: The "Top 25" list for intraoperative CT-guided navigation in spine surgery cumulatively received a total of 2742 citations, with an average of 12 new citations annually. The number of citations ranged from 246 for the most cited article to 60 for the 25th most cited article. The most cited article was a paper by Siewerdsen et al., with 246 total citations, averaging 15 new citations per year. CONCLUSIONS: Intraoperative CT-guided navigation is 1 of many technological advances that is used to increase surgical accuracy, and it has become an increasingly popular alternative to conventional fluoroscopy-based techniques. Given the increasing adoption of intraoperative CT-guided navigation in spine surgery, this review provides impactful evidence for its utility in spine surgery.

Three-dimensional spine reconstruction from biplane radiographs using convolutional neural networks.

PURPOSE: The purpose of this study was to develop and evaluate a deep learning network for three-dimensional reconstruction of the spine from biplanar radiographs. METHODS: The proposed approach focused on extracting similar features and multiscale features of bone tissue in biplanar radiographs. Bone tissue features were reconstructed for feature representation across dimensions to generate three-dimensional volumes. The number of feature mappings was gradually reduced in the reconstruction to transform the high-dimensional features into the three-dimensional image domain. We produced and made eight public datasets to train and test the proposed network. Two evaluation metrics were proposed and combined with four classical evaluation metrics to measure the performance of the method. RESULTS: In comparative experiments, the reconstruction results of this method achieved a Hausdorff distance of 1.85 mm, a surface overlap of 0.2 mm, a volume overlap of 0.9664, and an offset distance of only 0.21 mm from the vertebral body centroid. The results of this study indicate that the proposed method is reliable.

Automatic Assessment of Ultrasound Curvature Angle for Scoliosis Detection Using 3-D Ultrasound Volume Projection Imaging.

OBJECTIVE: Scoliosis is a spinal deformation in which the spine takes a lateral curvature, generating an angle in the coronal plane. The conventional method for detecting scoliosis is measurement of the Cobb angle in spine images obtained by anterior X-ray scanning. Ultrasound imaging of the spine is found to be less ionising than traditional radiographic modalities. For posterior ultrasound scanning, alternate indices of the spinous process angle (SPA) and ultrasound curve angle (UCA) were developed and have proven comparable to those of the traditional Cobb angle. In SPA, the measurements are made using the spinous processes as an anatomical reference, leading to an underestimation of the traditionally used Cobb angles. Alternatively, in UCA, more lateral features of the spine are employed for measurement of the main thoracic and thoracolumbar angles; however, clear identification of bony features is required. The current practice of UCA angle measurement is manual. This research attempts to automate the process so that the errors related to human intervention can be avoided and the scalability of ultrasound scoliosis diagnosis can be improved. The key objective is to develop an automatic scoliosis diagnosis system using 3-D ultrasound imaging. METHODS: The novel diagnosis system is a three-step process: (i) finding the ultrasound spine image with the most visible lateral features using the convolutional RankNet algorithm; (ii) segmenting the bony features from the noisy ultrasound images using joint spine segmentation and noise removal; and (iii) calculating the UCA automatically using a newly developed centroid pairing and inscribed rectangle slope method. RESULTS: The proposed method was evaluated on 109 patients with scoliosis of different severity. The results obtained had a good correlation with manually measured UCAs (R2=0.9784 for the main thoracic angle andR2=0.9671 for the thoracolumbar angle) and a clinically acceptable mean absolute difference of the main thoracic angle (2.82 ± 2.67°) and thoracolumbar angle (3.34 ± 2.83°). CONCLUSION: The proposed method establishes a very promising approach for enabling the applications of economic 3-D ultrasound volume projection imaging for mass screening of scoliosis.

A rare skeletal dysplasia in the etiology of severe scoliosis: Diaphanospondylodysostosis.

Diaphanospondylodysostosis is a rare genetic skeletal disorder caused by biallelic variants in the BMPER gene. The term, diaphanospondylodysostosis, includes ischiospinal dysotosis, which was previously known as a distinct entity with milder clinical features. The clinical phenotype of diaphanospondylodysostosis is quite variable with mortality in early postnatal life in some patients. Main clinical and radiographic features are narrow thorax, vertebral segmentation defects, rib anomalies, ossification defects of vertebrae, ischium and sacrum, and renal cysts. In this study, we report on a 14-year-old girl patient with diaphanospondylodysostosis harbouring a novel BMPER mutation. The patient presented with severe scoliosis and severely hypoplastic/aplastic distal phalanges of the fingers and toes, findings yet hitherto not described in this syndrome.

Lateral bone ridge expansion and internal tissue replacement for vertebral body growth in Pacific bluefin tuna Thunnus orientalis.

Vertebral growth is an essential developmental process to support the expansion of the vertebrate body. In teleosts, the lateral side of the vertebral bodies develops to form different structures among species in the late stages of vertebral growth, although lateral structures are not apparent in the early stages. Lateral structures are one of the structural features that determine the diversity of teleost vertebrae. However, explanations for the formation of lateral structures are conflicting because few reports have investigated the growth of teleost vertebral bodies. To clarify the growth process, we analyzed the morphological changes in the vertebral body of Pacific bluefin tuna Thunnus orientalis at different developmental stages using micro-computed tomography (CT) scans. The micro-CT scans showed that the vertebral centrum formed a plate-like ridge on the lateral side along the cranial-caudal direction and extended laterally with increasing thickness. Simultaneously, the proximal region of the lateral ridges became porous as the vertebrae grew to form bone marrow cavities. Furthermore, we used histological observations to describe the relationship between these morphological changes and osteoblast and osteoclast activities. Osteoblasts accumulated on the distal edges of the lateral ridges, whereas osteoclasts were distributed in the bone marrow cavities. These observations suggest that bone resorption occurs proximally to form bone marrow cavities in addition to bone synthesis at the edges of the lateral ridges. The bone marrow cavities were occupied by blood vessels, extracellular matrix, and adipocytes, and the internal tissue composition changed to increase the area of adipose tissue. Because the ratio of bone volume decreases in large vertebrae, bone formation and resorption are regulated to separate the external cortical and internal trabecular bones to support the vertebrae. This study is the first to report the formation of lateral structures and can be applied to similar lateral structures in the vertebrae of other teleost species.

Instrumentation failure following pediatric spine deformity growth-sparing surgery using traditional growing rods or vertical expandable prosthetic titanium ribs.

BACKGROUND: Instrumentation failure (IF) is a major complication associated with growth-sparing surgery for pediatric spinal deformities; however, studies focusing on IF following each surgical procedure are lacking. We aimed to evaluate the incidence, timing, and rates of unplanned return to the operating room (UPROR) associated with IF following each surgical procedure in growth-sparing surgeries using traditional growing rods (TGRs) and vertical expandable prosthetic titanium ribs (VEPTRs). METHODS: We reviewed 1,139 surgical procedures documented in a Japanese multicenter database from 2015 to 2017. Of these, 544 TGR and 455 VEPTR procedures were included for evaluation on a per-surgery basis. IF was defined as the occurrence of an implant-related complication requiring revision surgery. RESULTS: The surgery-based incidences of IF requiring revision surgery in the TGR and VEPTR groups were 4.3% and 4.0%, respectively, with no significant intergroup difference. Remarkably, there was a negative correlation between IF incidence per surgical procedure and the number of lengthening surgeries in both groups. In addition, rod breakage in the TGR group and anchor-related complications in the VEPTR group tended to occur relatively early in the treatment course. The surgery-based rates of UPROR due to IF in the TGR and VEPTR groups were 2.0% and 1.5%, respectively, showing no statistically significant difference. CONCLUSIONS: We found that IF, such as anchor related-complications and rod breakage, occurs more frequently earlier in the course of lengthening surgeries. This finding may help in patient counseling and highlights the importance of close postoperative follow-up to detect IF and improve outcomes.

Image-Guided Spine Surgery.

The realm of spine surgery is undergoing a transformative shift, thanks to the integration of image-guided navigation technology. This innovative system seamlessly blends real-time imaging data with precise location tracking. While the indispensable expertise of experienced spine surgeons remains irreplaceable, navigation systems bring a host of valuable advantages to the operating room. By offering a comprehensive view of the surgical anatomy, these systems empower surgeons to conduct procedures with accuracy, while minimizing radiation exposure for both patients and medical professionals. Moreover, image-guided navigation paves the way for integration of other state-of-the-art technologies, such as augmented reality and robotics. These innovations promise to further revolutionize the field, providing greater precision and expanding the horizons of what is possible in the world of spinal procedures. This article explores the evolution, classification, and impact of image-guided spine surgery, underscoring its pivotal role in enhancing efficacy and safety while setting the stage for the incorporation of future technological advancements.