Disc Bulge Research Articles

Magnetic Resonance Imaging Findings in Lumbosacral Spine among Young Arabic Patients with Back Pain

Lower back pain is a significant health issue that affects approximately 80% of adults. Lumbar disc herniation is a common cause of this pain, and lumbosacral magnetic resonance imaging (MRI) is considered the gold standard for diagnosing disc abnormalities. Due to socioeconomic factors, there has been an increased interest in studying disc herniation among young individuals. This retrospective study involved 72 consecutive Arabic patients (34 females and 38 males) aged between 15 and 30 years, all presenting with lower back pain. The aim was to investigate the magnetic resonance imaging findings of the lumbosacral spine. Our study reveals a high prevalence of disc abnormalities in young patients, with approximately 40 individuals (55.6%) exhibiting varying degrees of disc prolapse and bulging. The older subgroup (ages 23-30) was more significantly affected, with no discernible sex predominance. The L4/L5 disc level was the most commonly involved (40%), and central disc prolapse was identified as the most frequent type, observed in 65% of cases. This study revealed a high prevalence of disc prolapse among individuals aged 15 to 30 years, which may be attributed to factors such as lifting heavy objects, obesity, and fluctuations in physical activity levels, both increased and decreased.

Evaluation of Lumbar Spine on MRI in Young Adults presenting with Chronic Backaches

Objective: This study aimed to establish a correlation between clinical symptoms and MRI findings in individuals with chronic back pain. Methodology: This Descriptive cross-sectional study was conducted over a period of four months after ethical approval in the Radiology department at a Tertiary Care Hospital in Lahore. Acohort of 135 young adults were assessed through a consecutive sampling method and underwent lumbar spine MRI examinations. Results: The pool of participants in the study encompassed 42.2% males and 57.8% females, aged between 18 and 40 years, with an average age of 31.5 years and a standard deviation of 6.06. There were four prominent MRI findings: Lumbar Spondylosis (46%, Disc Degeneration (25%, Disc Bulge (10%), and Disc Desiccation (9%). The study also found significant correlations between these findings and clinical characteristics, with Lumbar Spondylosis linked to lower limb numbness and mobility difficulties, and Disc Bulge correlated with pain duration. Conclusion: The findings underscore the effectiveness of MRI scans in identifying underlying causes of chronic back pain in young adults in Pakistan.

A porohyperelastic scheme targeted at High-Performance Computing frameworks for the simulation of the intervertebral disc

Background and Objective:The finite element method is widely used for studying the intervertebral disc at the organ level due to its ability to model complex geometries. An indispensable requirement for proper modelling of the intervertebral disc is a reliable porohyperelastic framework that captures the elaborate underlying mechanics. The increased complexity of such models requires significant computational power that is available within high-performance computing systems. The objective of this study is to present such a framework, validated both against literature and experiments, aiming to enable intervertebral disc research to benefit from state-of-the-art computational resources. Methods:In the context of this work, we implement a biphasic model that captures the mechanical response of the intricate, tissue-dependent models of the solid phase along with the hydrostatic pressure effects of the fluid phase. The tissue-dependent models involve the hyperelastic ground substance, fibrillar reinforcement, and osmotic swelling. The derived porohyperelastic, staggered scheme is implemented in Alya, a finite element code targeted at high-performance computing applications. The formulation is subsequently verified and validated by comparing the results of consolidation simulations with literature data for simulations and experiments using either generic or patient-specific geometries. Additionally, in-house experiments are replicated, evaluating the model’s ability to simulate alternating loading. Finally, the implementation’s circadian response is compared to previous implementation of similar material models in commercial software. Results:Results align well with experimental and literature findings in terms of disc height reduction (4% error), intradiscal pressure (14% error) and disc bulging. Validating the patient-specific geometry results in 4% and 7% deviation in measuring height loss. Simulations show excellent agreement with in-house experimental results, with less than 1% error regarding height reduction. Finally, the comparison to similar, published, earlier implementation in commercial software unveils excellent agreement of less than 1% error for the water content during circadian simulations. Simulation times are reported at 4 min per circadian cycle in the supercomputer Marenostrum V. Conclusions:This work presents a clear and validated formulation for simulating porohyperelastic materials based on assumptions that comply with the non-linear elasticity theory. The implementation in Alya enables intervertebral disc research to benefit from high-performance computing systems.

Comparison of microsurgical and endoscopic approaches to removing lumbosacral spine hernias

Degenerative and dystrophic changes of the spine rank first in the number of temporary disability days and second among the reasons for visiting a physician. (1) Disc hernia is a consequence of degenerative and dystrophic changes of the spine representing a local displacement of disc elements outside the disc. Herniated disc bulges are most common in the 30-50-year-old population. This paper describes in detail the aetiology and pathogenesis of intervertebral disc hernia development, provides classifications of degenerative and dystrophic changes of the spine according to Osna, Pfirrmann, and presents the classification of intervertebral hernias of the North American Spine Society. The authors also described the clinical picture: vertebrogenic pain syndrome, radiculopathy, urinary disorders, and cauda equina syndrome were characterised. The aim of the study was to compare the microsurgical technique of herniated discs removal with the endoscopic technique, as well as to identify the advantages and disadvantages of each approach. Using data from both domestic and foreign studies, the authors compared these methods and identified the features of each one of them. As an illustration of the microsurgical method, a detailed analysis of a clinical case of removing an intervertebral hernia of the lumbosacral spine was performed. As materials and methods, the authors used the data of the patient»s medical history and the surgery protocol.

Interventional Pain Management in Degenerative Spine Disorders: A Case Report

Low back pain (LBP) is a common health issue affecting a significant portion of the population, particularly adults aged 35-55 years. Nearly 70-80% of individuals in developed countries experience LBP at some point in their lives. We reported a 54-year-old female presenting with LBP persisting for one year. Her pain predominantly occurs during walking, is limited to 100 meters, and is characterized by gripping sensations in the thigh and calf, exacerbated by positional changes but relieved with rest. Imaging revealed anterior listhesis of the L4 vertebral body relative to L5 (<25%) and multiple bulging discs at various lumbar levels, most notably severe at L4-5 with moderate central and severe bilateral neural foraminal stenosis. The patient underwent Selective Nerve Root Block (SNRB) and facet joint blocks with local anesthetic and steroid medication, resulting in a reduction of pain complaints and decreased leg numbness post-intervention. Understanding and addressing specific spinal pathologies in this case was expected to guide effective treatment strategies to alleviate symptoms and improve patient function.

Navigating Complex Comorbidities: A Case of Behcet?s Syndrome with Lumbar Disc Bulging and Cardiovascular Disease

Navigating Complex Comorbidities: A Case of Behcet?s Syndrome with Lumbar Disc Bulging and Cardiovascular Disease

Artificial Intelligence-Assisted MRI Diagnosis in Lumbar Degenerative Disc Disease: A Systematic Review.

Systematic review. Lumbar degenerative disc disease (DDD) poses a significant global health care challenge, with accurate diagnosis being difficult using conventional methods. Artificial intelligence (AI), particularly machine learning and deep learning, offers promising tools for improving diagnostic accuracy and workflow in lumbar DDD. This study aims to review AI-assisted magnetic resonance imaging (MRI) diagnosis in lumbar DDD and discuss current research for clinical use. A systematic search of electronic databases identified studies on AI applications in MRI-based lumbar DDD diagnosis, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Search terms included combinations of "Artificial Intelligence," "Machine Learning," "Deep Learning," "Low Back Pain," "Lumbar," "Disc," "Degeneration," and "MRI," targeting studies in English from January 1, 2010, to January 1, 2024. Inclusion criteria encompassed experimental and observational studies in peer-reviewed journals. Data extraction focused on study characteristics, AI techniques, performance metrics, and diagnostic outcomes, with quality assessed using predefined criteria. Twenty studies met the inclusion criteria, employing various AI methodologies, including machine learning and deep learning, to diagnose lumbar DDD manifestations such as disc degeneration, herniation, and bulging. AI models consistently outperformed conventional methods in accuracy, sensitivity, and specificity, with performance metrics ranging from 71.5% to 99% across different diagnostic objectives. The algorithm model provides a structured framework for integrating AI into routine clinical practice, enhancing diagnostic precision and patient outcomes in lumbar DDD management. Further research and validation are needed to refine AI algorithms for real-world application in lumbar DDD diagnosis.

Improving Lumbar Disc Bulging Detection in MRI Spinal Imaging: A Deep Learning Approach

Lower back pain is a common ailment that affects many people resulting from various spinal diseases such as disk bulge. Disc bulging, which refers to the narrowing of the intervertebral disc within the spinal canal, can cause lower back pain and lead to lumbar spine stenosis. Deep learning algorithms based on artificial intelligence are indispensable in the field of medicine, enhancing the precision of medical image diagnosis significantly and the ability to process massive amounts of data which contributes to reducing the workload on radiologists and doctors. Therefore, Deep learning techniques have become a more helpful tool to overcome this problem. For this purpose, this study employed the YOLO-v7, YOLOv8m object detection technique to build a model to detect lumbar spine disc discords using MRI data from 291 individuals suffering from lower back pain. The image data utilized for training the model were divided into three segments: 70% for training, 20% for validation, and 10% for testing, and validate the model results according to evaluation metrics. shows the optimal model validated externally utilizing new lumbar spine MRI images and assessment with the radiologist. YOLOv8m achieved a mean average in precision (93.7%), precision (90.5%), recall (79.2%), and F1-score (88.6%), accuracy (89.8%). A deep learning model demonstrated similar agreement to subspecialist radiologists in detecting and classifying lumbar spine stenosis on lumbar spine MRI. By selecting the most suitable YOLO model, doctors can significantly enhance their ability to detect lumbar spine stenosis at an early stage and effectively mitigate potential negative consequences for their patients.

Correlation of Low Back Pain with Pathological Changes of Lumbar Spinal Segment in Young Adults: A Cross-Sectional Study

Abstract: Objectives: The objective of this study was to determine the association of low back pain in young adults with most likely involved spinal level by MRI findings of their lumbar spinal segment. Methods: The current study was conducted on 120 adults aged 25 to 40 years with low back pain. Lumbar spinal Magnetic Resonance Imaging (MRI) of these subjects was collected from Capital Diagnostic Center, Islamabad. Patients with any trauma, spinal surgery or fracture, active malignancy, metabolic bone disease, rheumatoid arthritis or pregnancy were excluded from the study. Disc and non-disc related parameters were evaluated from L1- L5 spinal levels. Further, gender based difference in magnetic resonance imaging findings was also assessed. Results: All the adults with low back pain showed some degree of disc degeneration on Pfirrmann grading system. The disc related MRI findings were more prevalent at lower lumbar spine levels L4-5 & L5-S1. On gender comparison, no significant difference of spinal level was found in males and females. However, it was revealed that males mostly had asymmetrical disc bulge (p = 0.03) and females were having facet joint involvement (p = 0.005). Conclusion: In young adults with low back pain, lower lumbar spinal levels were involved. Disc degeneration was mostly found in lower lumbar spinal levels without any gender difference. However, other underlying factors of low back pain may differ in males and females. Key words: Disc Degeneration, Intervertebral Disc, Lumbar spine, Low back pain, MRI, Young adults

Association of MRI findings with paraspinal muscles fat infiltration at lower lumbar levels in patients with chronic low back pain: a multicenter prospective study

ObjectiveIn chronic low back pain (CLBP), the relationship between spinal pathologies and paraspinal muscles fat infiltration remains unclear. This study aims to evaluate the relationship between MRI findings and paraspinal muscles morphology and fat infiltration in CLBP patients by quantitative MRI.MethodsAll the CLBP patients were enrolled from July 2021 to December 2022 in four medical institutions. The cross-sectional area (CSA) and proton density fat fraction (PDFF) of the multifidus (MF) and erector spinae (ES) muscles at the central level of the L4/5 and L5/S1 intervertebral discs were measured. MRI findings included degenerative lumbar spondylolisthesis (DLS), intervertebral disc degeneration (IVDD), facet arthrosis, disc bulge or herniation, and disease duration. The relationship between MRI findings and the paraspinal muscles PDFF and CSA in CLBP patients was analyzed.ResultsA total of 493 CLBP patients were included in the study (198 females, 295 males), with an average age of 45.68 ± 12.91 years. Our research indicates that the number of MRI findings are correlated with the paraspinal muscles PDFF at the L4/5 level, but is not significant. Moreover, the grading of IVDD is the primary factor influencing the paraspinal muscles PDFF at the L4-S1 level (BES at L4/5=1.845, P < 0.05); DLS was a significant factor affecting the PDFF of MF at the L4/5 level (B = 4.774, P < 0.05). After including age, gender, and Body Mass Index (BMI) as control variables in the multivariable regression analysis, age has a significant positive impact on the paraspinal muscles PDFF at the L4-S1 level, with the largest AUC for ES PDFF at the L4/5 level (AUC = 0.646, cut-off value = 47.5), while males have lower PDFF compared to females. BMI has a positive impact on the ES PDFF only at the L4/5 level (AUC = 0.559, cut-off value = 24.535).ConclusionThe degree of paraspinal muscles fat infiltration in CLBP patients is related to the cumulative or synergistic effects of multiple factors, especially at the L4/L5 level. Although age and BMI are important factors affecting the degree of paraspinal muscles PDFF in CLBP patients, their diagnostic efficacy is moderate.

The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images.

This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net's segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Analysis of Finger Photo Pulse Plethysmography and Body Composition among Low Back Pain Subjects with Lumbar Disc Degenerative Diseases Diagnosed by MRI Analysis

Lumbar disc degenerative disc disease, accompanied by back pain, is a prominent health concern in society. The purpose of the study was to investigate the connection of arterial stiffness and body composition in the patients suffering low back pain with lumbar disc degenerative disorders. A comparative study was performed on 197 patients, both male and female, between the ages of 30 and 70, who were experiencing low back pain. These patients have undergone magnetic resonance imaging of the lumbosacral region to evaluate the intervertebral disc's nucleus and annulus as well as its signal intensity and height. The Pfirrmann grading method was used to determine the extent of disc degeneration. The statistical analysis revealed no significant link between overall body fat and stiffness index in disc bulging and nerve compression groups. However, the group experiencing nerve compression demonstrated a statistically significant association between visceral fat and reflection index in individuals who were overfat and obese. In addition, there was a notable correlation between PWV and the reflection index of the disc bulging groups. So, whole body fat and PWV had a different impact on disc degeneration. The PWV has a robust positive correlation with both the stiffness index and reflection index. The presence of subcutaneous fat and vascular stiffness may not have any impact on low back pain in patients with disc bulging and nerve compression. Early identification of vascular stiffness and study of body composition serve as initial measures to avoid the progression of disc degeneration.

Clinical efficacy and imaging analysis of oblique lateral lumbar interbody fusion in the treatment of different types of lumbar intervertebral foramen stenosis

PurposeTo analyze and study the clinical efficacy and imaging indexes of oblique lateral lumbar interbody fusion (OLIF) in the treatment of lumbar intervertebral foramen stenosis(LFS) caused by different causes.Method33 patients with LFS treated with OLIF from January 2018 to May 2022 were reviewed. Oswestry Dysfunction Index (ODI) and visual analogue scale (VAS) were calculated before and after operation. Segmental lordotic angle (SLA), lumbar lordotic angle (LLA) and segmental scoliosis angle (SSA), disc height (DH), posterior disc height (PDH), lateral disc height (LDH), foraminal height (FH), foramen width (FW) and foraminal cross-sectional area (FSCA) were measured before and after operation.ResultThe VAS and ODI after operation were significantly improved as compared with those before operation. Compared with pre-operation, the DH, PHD increased by 67.6%, 94.6%, LDH increased by 107.4% (left), 101.7% (right), and FH increased by 30.2% (left), 34.5% (right). The FSCA increased by 93.1% (left), 89.0% (right), and the FW increased by 137.0% (left), 149.6% (right). The postoperative SSA was corrected by 74.5%, the postoperative SLA, LLA were corrected by 70.2%, 38.1%, respectively. All the imaging indexes were significantly improved (p < 0.01).ConclusionThe clinical efficacy and imaging data of OLIF in the treatment of LFS caused by low and moderate lumbar spondylolisthesis, intervertebral disc bulge and reduced intervertebral space height, degenerative lumbar scoliosis, articular process hyperplasia or dislocation have been well improved. OLIF may be one of the better surgical treatments for LFS caused by the above conditions.

Clinical correlation of Magnetic Resonance Imaging (MRI) with symptom complex in prolapsed intervertebral disc disease in the patients of Tertiary Care Hospital, Kharian.

Objective: To assess the clinical correlation of MRI with the symptoms of prolapsed intervertebral disc disease in the patients of Tertiary Care Hospital, Kharian. Study Design: Cross Sectional study. Setting: Tertiary Care Hospital, Kharian. Period: February 2022 to August 2022. Methods: The patients with age range 18 to 50 years, visiting hospital with complaint of low back pain and radicular pain were included in this study. Physical and neurological examination was conducted followed by MRI. The symptoms were correlated with MRI findings through correlation analysis with p&lt;0.05 as significant. Results: The mean age was 38.09 ± 8.4 years with majority (54.6%) of patients in age range 41 to 50 years. The male patients (69.3%) and hard labor workers (59.3%) were more effected. Protrusion was the most prevalent type (60%). SLR was significantly associated with disc bulge and protrusion (p&lt;0.001). The loss of power (56.6%) had significant correlation with disc protrusion (p &lt; 0.001). Majority (55.3%) of the cases comprised of nerve root compression with more (47.3%) and significant prevalence in protrusion (p &lt; 0.001). The multiple nerve root involvement had significant association with disc extrusion (p&lt;0.001). Conclusion: MRI is a good means of indicating disease level in prolapsed intervertebral disc disease. However, some of the clinical symptoms show high association with the radiological findings, whereas, some are not good indicators.

Anatomic, Image-based Classification of Diseased Lumbar Spinal Motion-Segment-Preliminary Clinical Report

Background: Multiple minimally invasive spine approaches and techniques have been developed in recent years. While the disease processes affecting the spinal motion-segment (SMS) have remained largely the same, surgical treatment options have changed radically and not necessarily in an organized fashion. This is inevitable given the rapid evolution of the technology. The current image-based diagnostic techniques, also evolving, have helped us appreciate the disease Patho anatomy in minute detail. A comprehensive classification method accounting for all anatomical participants in the spinal motion-segment pathology, tailored to treatment options, is necessary. Out of the many valid options, a spine surgeon should be able to choose a single surgical approach that is most appropriate for the Patho anatomy of his/her patient’s disease. We feel that our classification system will help the spine surgeon make that important decision consistently, with minimal risk of leaving behind a significant lesion, or disrupting a structure which is not a participant in the disease process. Furthermore, universal acceptance of this classification system will make it easier for spine surgeons to communicate with each other and meaningfully compare the results of the various surgical approaches. Purpose of the Study: To develop a comprehensive, treatment-orientated classification of lumbar spinal motion-segment disease. Materials and Methods: Contributors to spinal motion-segment disease - intervertebral disc, facet joint, ligamentum flavum and mal-alignment were identified. The degrees of abnormalities in each of these entities were coded, and the codes were entered in a table from which the possible combinations of pathologic processes were generated. Study of 57 lumbar MRI images (217 spinal motion-segments) was carried out to determine the prevalence of various combinations of the motion-segment disease. Pre- and post-operative MRI-based spinal motion-segment classifications were performed to evaluate the clinical application of this classification system in 15 patients. Results: This classification presents 494 possible combinations of the spinal motion-segment disease. Many of the combinations are only theoretical possibilities without clinical significance. Normal motion-segments, D0 A0 L0 F0 , represented 33.3% of the total motion-segments; D1 A0 L0 F0 was 8.8%, representing bulging disc, normal alignment, ligamentum flavum and facet joint. D2 A0 L0 F2 was 6.9% representing intraannular disc herniation, normal alignment, mildly thickened ligamentum flavum, and hypertrophied superior articular process of the facet joint. 6.4% was D1 A0 L1 F3 representing bulging disc, mildly hypertrophic ligamentum and hypertrophied facet joint. Clinical application of the classification revealed: Accurate anatomic classification; immediate post-operative classification changes which correlate with patient’s symptoms; pre-operative, immediate post-operative and late post-operative classifications which correlate with patient’s symptoms and accurately demonstrate post-operative remodeling of the motion-segment, especially after disc surgery, and accurate; and anatomic documentation of pre- and post op classifications of interlaminar endoscopic decompression. Conclusion: A treatment-orientated, standardized classification of spinal motion-segment disease is necessary considering current multiple treatment options and availability of sophisticated pre-operative imaging techniques. Such a classification will allow standardization of treatment options for various combinations of the pathological processes. With the emergence of new technologies surgical options can be upgraded based on a standardized classification. This in turn will help minimize confusion for those who want to learn and facilitate growth in the minimally invasive technology. The preliminary results of clinical application of the classification showed it to be a very accurate patho-anatomic representation; immediate post-operative classification change reflected clinical improvement post-operatively; and precise representation of post-operative remodeling of the motion-segment one to two years post-operatively. The precision of this classification allows accurate communication regarding the pathology, between providers across the globe, and more accurate comparison of results of different surgical interventions.

Vertebral Bone Quality Score as a Predictor of Adjacent Segment Disease After Lumbar Interbody Fusion.

With lumbar spine fusion being one of the most commonly performed spinal surgeries, investigating common complications such as adjacent segment disease (ASD) is a high priority. To the authors' knowledge, there are no previous studies investigating the utility of the preoperative magnetic resonance imaging-based vertebral bone quality (VBQ) score in predicting radiographic and surgical ASD after lumbar spine fusion. We aimed to investigate the predictive factors for radiographic and surgical ASD, focusing on the predictive potential of the VBQ score. A single-center retrospective analysis was conducted of all patients who underwent 1-3 level lumbar or lumbosacral interbody fusion for lumbar spine degenerative disease between 2014 and 2021 with a minimum 12 months of clinical and radiographic follow-up. Demographic data were collected, along with patient medical, and surgical data. Preoperative MRI was assessed in the included patients using the VBQ scoring system to identify whether radiographic ASD or surgical ASD could be predicted. A total of 417 patients were identified (mean age, 59.8 ± 12.4 years; women, 54.0%). Eighty-two (19.7%) patients developed radiographic ASD, and 58 (13.9%) developed surgical ASD. A higher VBQ score was a significant predictor of radiographic ASD in univariate analysis (2.4 ± 0.5 vs 3.3 ± 0.4; P < .001) and multivariate analysis (odds ratio, 1.601; 95% CI, 1.453-1.763; P < .001). For surgical ASD, a significantly higher VBQ score was seen in univariate analysis (2.3 ± 0.5 vs 3.3 ± 0.4; P < .001) and served as an independent risk factor in multivariate analysis (odds ratio, 1.509; 95% CI, 1.324-1.720; P < .001). We also identified preoperative disk bulge and preoperative existence of adjacent segment disk degeneration to be significant predictors of both radiographic and surgical ASD. Furthermore, 3-level fusion was also a significant predictor for surgical ASD. The VBQ scoring system might be a useful adjunct for predicting radiographic and surgical ASD.

In subjects with chronic low back pain, does neuropathia exclusively correlated to neuronal compression? A correlation study of PainDETECT questionnaire and corresponding MRI and X-ray findings

IntroductionUnderstanding the complex nature of low back pain (LBP) is crucial for effective management. The PainDETECT questionnaire is a tool that distinguishes between neuropathic (NeP), nociceptive (NoP), and ambiguous pain. This study aimed to investigate the relationship between pain classification and lumbar intervertebral degenerative parameters obtained from imaging.MethodsA cohort study was conducted involving 279 patients, aged 18 years and above, who completed PainDETECT questionnaires and underwent lumbar MRI and/or X-ray scans.ResultsThe study included 102 patients with NoP, 78 with ambiguous pain, and 99 with NeP. The NeP group had lower mean age (58.21 vs. 53.63, p < 0.05) and higher mean numerical rating scale score (7.9 vs. 5.9, p < 0.001) compared to the NoP group. A negative correlation was found between PainDETECT scores and pelvic incidence (τ = − 0.177, p = 0.043). The NeP group exhibited significantly higher severity of foraminal stenosis (U = 18.962, p = 0.002), spinal stenosis (U = 14.481, p = 0.005), and Pfirrmann grade (U = 14.221, p = 0.028) compared to the NoP group. A higher proportion of NeP patients had intervertebral disk bulge (96% vs. 78% vs. 78%, p = 0.002) and high-intensity zones (51% vs. 41% vs. 19%, p < 0.001) compared to those with NoP and ambiguous pain.ConclusionNeP, as determined by the PainDETECT questionnaire, is associated with more severe neural compression, increased presence of discogenic disease and inflammatory disk severity, and decreased pelvic incidence. This pioneering study establishes a connection between pathological findings and pain categorization, providing clinicians with valuable guidance for formulating tailored management plans and reducing the need for unnecessary pharmacotherapy, imaging, and non-targeted surgical interventions.

Role of MRI in detection of lumber spine pathologies using 1.5 tesla (MRI)

Background: This study investigates the diagnostic accuracy of MRI in detecting various lumbar spine pathologies in patients with lower back pain. Lower back pain (LBP) is a prevalent issue affecting 80%–85% of the population during their lifetime, contributing significantly to global disability. LBP is nonspecific in 95% of cases but can stem from underlying pathologies such as disc herniation, spinal stenosis, infection, inflammation, tumours, or fractures. Objective: To emphasize the importance of magnetic resonance imaging (MRI) in patients suspected of lumbar spinal examinations. Methods and material: The research focused on adult patients with radicular syndrome, spinal stenosis, spinal tumours, spinal fractures, spinal infection/inflammation, disc herniation, spondylolisthesis, spondylolysis, ankylosing spondylitis, disc displacement, osteoporotic fractures, and other degenerative disc diseases. Utilizing a 1.5 Tesla MRI machine, the descriptive, cross-sectional observational study spanned one year and included 150 patients. Results: revealed that diffuse disc bulge (87.33%) and disc protrusion (87.33%) were the most common pathologies, followed by partial desiccation (34.67%), neural foramina stenosis (16.00%), spondylosis (1.33%), osteoporosis (12.00%), spinal haemorrhage (2.00%), osteophyte spurs (29.33%), and sclerotic changes (3.33%). Discussion and Conclusion: The study's discussion highlighted notable findings, including a higher prevalence of lumbar spine abnormalities in females (51.33%) and a substantial association with a history of lower back pain (40.00%). The conclusion underscores the significance of MRI in diagnosing lumbar spine pathologies, with specific attention to the prevalence of disc bulge and protrusion in the studied population.

Cervical Multifidus and Longus Colli Ultrasound Differences among Patients with Cervical Disc Bulging, Protrusion and Extrusion and Asymptomatic Controls: A Cross-Sectional Study.

The aim of this study was to analyze the differences in morphological and histological features of the cervical multifidus (CM) and longus colli (LC) muscles among patients with cervical disc bulging, protrusion, or extrusion. Fifteen patients with cervical disc bulging (20% male, mean age: 48.5, standard deviation (SD) 7.5 years), fifteen with cervical disc protrusion (6% male, mean age: 43, SD 7.8 years), and fifteen with cervical disc extrusion (40% male, mean age: 44, SD 8 years) diagnosed via clinical and imaging findings participated in this study. Additionally, fifteen asymptomatic controls (40% male, mean age: 40.4, SD 9.7 years) were also included. The following ultrasound measurements, cross-sectional area (CSA), anterior-posterior distance (APD), lateral dimension (LD), and mean echo-intensity (EI) of the CM and LC at C5-C6 level were examined by an assessor blinded to the subject's condition. The results revealed no group ×side significant differences among the groups (p > 0. 00625). However, group effects were found for APD and MEI of the CM (p = 0.006 and p < 0.001, respectively) and CSA, APD and MEI of the LC (all, p < 0.001). The LD of the LC muscle and the APD and LD of the CM were negatively associated with related disability (p < 0.01; p < 0.05 and p < 0.01, respectively), and pain intensity was negatively associated with LC APD and LD (both p < 0.05). These results suggest that US can be used to detect bilateral morphological changes in deep cervical flexors and extensors to discriminate patients with cervical disc alterations.

Development of a Machine Learning Algorithm to Correlate Lumbar Disc Height on X-rays with Disc Bulging or Herniation.

Lumbar disc bulging or herniation (LDBH) is one of the major causes of spinal stenosis and related nerve compression, and its severity is the major determinant for spine surgery. MRI of the spine is the most important diagnostic tool for evaluating the need for surgical intervention in patients with LDBH. However, MRI utilization is limited by its low accessibility. Spinal X-rays can rapidly provide information on the bony structure of the patient. Our study aimed to identify the factors associated with LDBH, including disc height, and establish a clinical diagnostic tool to support its diagnosis based on lumbar X-ray findings. In this study, a total of 458 patients were used for analysis and 13 clinical and imaging variables were collected. Five machine-learning (ML) methods, including LASSO regression, MARS, decision tree, random forest, and extreme gradient boosting, were applied and integrated to identify important variables for predicting LDBH from lumbar spine X-rays. The results showed L4-5 posterior disc height, age, and L1-2 anterior disc height to be the top predictors, and a decision tree algorithm was constructed to support clinical decision-making. Our study highlights the potential of ML-based decision tools for surgeons and emphasizes the importance of L1-2 disc height in relation to LDBH. Future research will expand on these findings to develop a more comprehensive decision-supporting model.