Reliability of the Path of the Sciatic Nerve, Congruence between Patients' History and Medical Imaging Evidence of Disc Herniation and Its Role in Surgical Decision Making

Mostofi, Keyvan; Khouzani, Reza Karimi

doi:10.4184/asj.2015.9.2.200

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…However, inconsistencies between the symptoms and the degree of nerve root compression seen on conventional MRI are continually observed. In addition, some studies reported symptom-free people with nerve root compression 4 . Therefore, it is difficult to use MRI to understand the cause of the pain and numbness.…”

mentioning

confidence: 99%

Microstructural changes are coincident with the improvement of clinical symptoms in surgically treated compressed nerve roots

Wu¹,

Liang²,

Chen³

et al. 2017

Sci Rep

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Diffusion tensor imaging (DTI) has been widely used to visualize peripheral nerves, but the microstructure of compressed nerve roots can be assessed using DTI. However, there are no data regarding the association among microstructural changes evaluated using DTI, the symptoms assessed using the Oswestry Disability Index (ODI) and the duration of symptoms after surgery in patients with lumbar disc herniation (LDH). Thirty patients with unilateral radiculopathy were investigated using DTI. The changes in the mean fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) values as well as the correlation between these changes and the severity and duration of the clinical symptoms were investigated before and at least one month after surgery. The FA values were significantly increased after surgical treatment (p < 0.0001). Both the ADC and ODI values were noticeably decreased (p < 0.0001). A strong positive correlation between the preoperative and postoperative DTI parameters (p < 0.0001) as well as between the preoperative ODI and postoperative ODI/ODI changes (p < 0.0001) were found. In addition, there was a significant positive correlation between the changes in the DTI parameters and changes in the ODI (p < 0.0001). This preliminary study suggests it may be possible to use DTI to diagnose, quantitatively evaluate and follow-up patients with LDH.

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mentioning

confidence: 99%

Microstructural changes are coincident with the improvement of clinical symptoms in surgically treated compressed nerve roots

Wu¹,

Liang²,

Chen³

et al. 2017

Sci Rep

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“…However, these paradoxes are much less in cervical spine than lumbar spine [4]. The most frequent causes are lumbosacral transitional vertebrae and conjoined nerve root in lumbosacral area [5,7].…”

Section: Discussionmentioning

confidence: 99%

Reliability of cervical radiculopathy, its congruence between patient history and medical imaging evidence of disc herniation and its role in surgical decision

Mostofi¹,

Khouzani

2016

Eur J Orthop Surg Traumatol

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“…Despite advances in imaging technology, the accuracy of X-ray-based diagnostic imaging for LDBH remains questionable [15]. Literature reviews have even noted discrepancies between imaging findings and clinical parameters [16]. Additionally, there is a lack of standardized methods for interpreting the lumbar X-ray images of patients with LDBH.…”

Section: Introductionmentioning

confidence: 99%

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

Lin,

Chang,

Hsiao

et al. 2024

Diagnostics

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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.

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Reliability of the Path of the Sciatic Nerve, Congruence between Patients' History and Medical Imaging Evidence of Disc Herniation and Its Role in Surgical Decision Making

Cited by 8 publications

References 11 publications

Microstructural changes are coincident with the improvement of clinical symptoms in surgically treated compressed nerve roots

Microstructural changes are coincident with the improvement of clinical symptoms in surgically treated compressed nerve roots

Reliability of cervical radiculopathy, its congruence between patient history and medical imaging evidence of disc herniation and its role in surgical decision

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

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