Value of imaging examinations in diagnosing lumbar disc herniation: A systematic review and meta-analysis

Classification of lumbar spine disorders using large language models and MRI segmentation

BACKGROUND

MRI is critical for diagnosing lumbar spine disorders but its complexity challenges diagnostic accuracy. This study proposes a BERT-based large language model (LLM) to enhance precision in classifying lumbar spine disorders through the integration of MRI data, textual reports, and numerical measurements.

METHODS

The segmentation quality of MRI data is evaluated using dice coefficients (cut-off: 0.92) and intersection over union (IoU) metrics (cut-off: 0.88) to ensure precise anatomical feature extraction. The CNN extracts key lumbar spine features, such as lumbar lordotic angle (LLA) and disc heights, which are tokenized as direct scalar values representing positional relationships. A data source of 28,065 patients with various disorders, including degenerative disc disease, spinal stenosis, and spondylolisthesis, is used to establish diagnostic standards. These standards are refined through post-CNN processing of MRI texture features. The BERT-based spinal LLM model integrates these CNN-extracted MRI features and numerical values through early fusion layers.

RESULTS

Segmentation analysis illustrate various lumbar spine disorders and their anatomical changes. The model achieved high performance, with all key metrics nearing 0.9, demonstrating its effectiveness in classifying conditions like spondylolisthesis, herniated disc, and spinal stenosis. External validation further confirmed the model's generalizability across different populations. External validation on 514 expert-validated MRI cases further confirms the model's clinical relevance and generalizability. The BERT-based model classifies 61 combinations of lumbar spine disorders.

CONCLUSIONS

The BERT-based spinal LLM significantly improves the precision of lumbar spine disorder classification, supporting accurate diagnosis and treatment planning.

A Novel Classification of Migrated Lumbar Disk Herniation Based on Magnetic Resonance Imaging and Algorithm Recommendations for Full-Endoscopic Discectomy

STUDY DESIGN

Retrospective clinical study.

OBJECTIVE

The purpose of this study was to establish a novel classification of migrated lumbar disk herniation (LDH) based on magnetic resonance imaging and provide appropriate treatment strategies for each type through algorithms.

SUMMARY OF BACKGROUND DATA

Full-endoscopic lumbar discectomy is a surgical technique that has been developed rapidly in recent years. For migrated LDH, few surgeons currently classify it with multiplanar positioning, and there is no consensus on the choice of treatment strategy. Therefore, we established a new multiplanar classification criteria that can localize the lesions more accurately than previous studies.

METHODS

A total of 263 eligible patients from March 2017 to March 2022 were included. Protrusions for each patient were located based on our classification and the surgical approach was selected according to our algorithms. The clinical symptoms of all patients before surgery, and at 1 day, 1 month, 3 months, 6 months, and 12 months after surgery were collected. Evaluations were performed using visual analogue scale (VAS), Oswestry Disability Index (ODI) and modified MacNab criteria. We used the chi-squared test, one-way analysis of variance (ANOVA), and t-test to compare perioperative results and postoperative 3-month, 6-month, and 12-month follow-up results.

RESULTS

VAS (low back pain) scores were reduced from 5.33 ± 2.67 to 0.73 ± 0.77 (p < 0.001), and VAS (leg pain) scores were reduced from 7.44 ± 2.21 to 0.37 ± 0.51 (p < 0.001). ODI scores improved from 58.46 ± 8.04 to 12.57 ± 2.51 (p < 0.001). According to the modified MacNab criteria, the excellent and good rate reached 92.78% at the 12-month follow-up. Twenty-six patients developed complications, all of which improved after treatment. Recurrence occurred in 13 patients, and four of them underwent secondary surgery.

CONCLUSIONS

This is an innovative classification method using multi-plane positioning, and the algorithm used with it can help surgeons make appropriate choices when using endoscopic technology to treat migrated LDH. Statistical analysis of follow-up data confirmed that this is a safe and effective strategy.

Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images

OBJECTIVES

To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD).

METHODS

A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series.

RESULTS

Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p =  0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044).

CONCLUSION

Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR.

CLINICAL RELEVANCE STATEMENT

To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI.

KEY POINTS

ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.

Imaging of Discogenic and Vertebrogenic Pain

Chronic low back pain is a major source of pain and disability globally involving multifactorial causes. Historically, intervertebral disc degeneration and disruption have been associated as primary back pain triggers of the anterior column, termed "discogenic pain." Recently, the vertebral endplates have been identified as another possible pain trigger of the anterior column. This "endplate-driven" model, defined "vertebrogenic pain," is often interconnected with disc degeneration. Diagnosis of vertebrogenic and discogenic pain relies on imaging techniques that isolate pain generators and exclude comorbid conditions. Traditional methods, like radiographs and discography, are augmented by more sensitive methods, including SPECT, CT, and MRI. Morphologic MRI is pivotal in revealing indicators of vertebrogenic (eg, Modic endplate changes) and discogenic pain (eg, disc degeneration and annular fissures). More advanced methods, like ultra-short-echo time imaging, and quantitative MRI further amplify MRI's accuracy in the detection of painful endplate and disc pathology. This review explores the pathophysiology of vertebrogenic and discogenic pain as well as the impact of different imaging modalities in the diagnosis of low back pain. We hope this information can help identify patients who may benefit from personalized clinical treatment and image-guided therapies.

A Severe Disc Herniation Mimics Spinal Tumor

Lumbar disc herniation (LDH) is prevalent among adults aged 25-55 years who spend a considerable proportion of their time sitting or standing with heavy workloads. We report the case of a 33-year-old male waiter with severe LDH, causing compression of the nerve roots and spinal cord with neurological dysfunction, who presented to a chiropractic clinic. Magnetic resonance imaging (MRI) revealed a radiological differential diagnosis comprising LDH and an epidural mass lesion. To rule out serious pathology, a second MRI with contrast was ordered, which confirmed the diagnosis of severe LDH. Diagnosing large LDH may be challenging, and severe disc herniation often mimics spinal tumors. This study offers insights into the differential diagnosis of LDH and spinal tumors, as well as the design of a treatment strategy for severe LDH in the chiropractic clinic.