Artificial neural networks (ANNs) have been used in a wide variety of real-world applications and it emerges as a promising field across various branches of medicine. This review aims to identify the role of ANNs in spinal diseases. Literature were searched from electronic databases of Scopus and Medline from 1993 to 2020 with English publications reported on the application of ANNs in spinal diseases. The search strategy was set as the combinations of the following keywords: “artificial neural networks,” “spine,” “back pain,” “prognosis,” “grading,” “classification,” “prediction,” “segmentation,” “biomechanics,” “deep learning,” and “imaging.” The main findings of the included studies were summarized, with an emphasis on the recent advances in spinal diseases and its application in the diagnostic and prognostic procedures. According to the search strategy, a set of 3,653 articles were retrieved from Medline and Scopus databases. After careful evaluation of the abstracts, the full texts of 89 eligible papers were further examined, of which 79 articles satisfied the inclusion criteria of this review. Our review indicates several applications of ANNs in the management of spinal diseases including (1) diagnosis and assessment of spinal disease progression in the patients with low back pain, perioperative complications, and readmission rate following spine surgery; (2) enhancement of the clinically relevant information extracted from radiographic images to predict Pfirrmann grades, Modic changes, and spinal stenosis grades on magnetic resonance images automatically; (3) prediction of outcomes in lumbar spinal stenosis, lumbar disc herniation and patient-reported outcomes in lumbar fusion surgery, and preoperative planning and intraoperative assistance; and (4) its application in the biomechanical assessment of spinal diseases. The evidence suggests that ANNs can be successfully used for optimizing the diagnosis, prognosis and outcome prediction in spinal diseases. Therefore, incorporation of ANNs into spine clinical practice may improve clinical decision making.

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These findings support the value of the MCID to assess surgical success for the JOABPEQ subscales in patients with LDH. This estimate may be a useful tool in clinical practice.

Study DesignCase-control.PurposeTo determine optimal cut-off value for body mass index (BMI) in predicting surgical success in patients with lumbar spinal canal stenosis (LSCS).Overview of LiteratureBMI is an essential variable in the assessment of patients with LSCS.MethodsWe conducted a prospective study with obese and non-obese LSCS surgical patients and analyzed data on age, sex, duration of symptoms, walking distance, morphologic grade of stenosis, BMI, postoperative complications, and functional disability. Obesity was defined as BMI of ≥30 kg/m2. Patients completed the Oswestry Disability Index (ODI) questionnaire before surgery and 2 years after surgery. Surgical success was defined as ≥30% improvement from the baseline ODI score. Receiver operating characteristic (ROC) analysis was used to estimate the optimal cut-off values of BMI to predict surgical success. In addition, correlation was assessed between BMI and stenosis grade based on morphology as defined by Schizas and colleague in total, 189 patients were eligible to enter the study.ResultsMean age of patients was 61.5±9.6 years. Mean follow-up was 36±12 months. Most patients (88.4%) were classified with grades C (severe stenosis) and D (extreme stenosis). Post-surgical success was 85.7% at the 2-year follow-up. A weak correlation was observed between morphologic grade of stenosis and BMI. Rates of postoperative complications were similar between patients who were obese and those who were non-obese. Both cohorts had similar degree of improvement in the ODI at the 2-year follow-up. However, patients who were non-obese presented significantly higher surgical success than those who were obese. In ROC curve analysis, a cut-off value of ≤29.1 kg/m2 for BMI in patients with LSCS was suggestive of surgical success, with 81.1% sensitivity and 82.2% specificity (area under the curve, 0.857; 95% confidence interval, 0.788–0.927).ConclusionThis study showed that the BMI can be considered a parameter for predicting surgical success in patients with LSCS and can be useful in clinical practice.

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Study design: Systematic review and meta-analysis. Aim: The purpose of this study was to compare the safety and accuracy of the C2 pedicle versus C2 pars screws placement and free-hand technique versus navigation for upper cervical fusion patients. Methods: Databases searched included PubMed, Scopus, Web of Science, and Cochrane Library to identify all papers published up to April 2020 that have evaluated C2 pedicle/pars screws placement accuracy. Two authors individually screened the literature according to the inclusion and exclusion criteria. The accuracy rates associated with C2 pedicle/pars were extracted. The pooled accuracy rate estimated was performed by the CMA software. A funnel plot based on accuracy rate estimate was used to evaluate publication bias. Results: From 1123 potentially relevant studies, 142 full-text publications were screened. We analyzed data from 79 studies involving 4431 patients with 6026 C2 pedicle or pars screw placement. We used the Newcastle-Ottawa Scale (NOS) to evaluate the quality of studies included in this review. Overall, funnel plot and Begg's test did not indicate obvious publication bias. The pooled analysis reveals that the accuracy rates were 93.8% for C2 pedicle screw free-hand, 93.7% for pars screw free-hand, 92.2% for navigated C2 pedicle screw, and 86.2% for navigated C2 pars screw (all, P value < 0.001). No statistically significant differences were observed between the accuracy of placement C2 pedicle versus C2 pars screws with the free-hand technique and the free-hand C2 pedicle group versus the navigated C2 pedicle group (all, P value > 0.05). Conclusion: Overall, there was no difference in the safety and accuracy between the free-hand and navigated techniques. Further well-conducted studies with detailed stratification are needed to complement our findings.

Study DesignCross-sectional.PurposeTo examine the relationship between magnetic resonance imaging (MRI) morphology stenosis grades and preoperative walking ability in patients with lumbar canal stenosis (LCS).Overview of LiteratureNo previous study has analyzed the correlation between MRI morphology stenosis grades and walking ability in patients with LCS.MethodsThis prospective study included 98 consecutive patients with LCS who were candidates for surgery. Using features identified in T2-weighted axial magnetic, stenosis type was determined at the maximal stenosis level, and only trefoil and triangle stenosis grade types were considered because of sufficient sample size. Intraobserver and interobserver reliability were assessed by calculating weighted kappa coefficients. Symptom severity was evaluated via the Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ). Walking ability was assessed using the Self-Paced Walking Test (SPWT) and JOABPEQ subscales. Demographic characteristics, SPWT scores, and JOABPEQ scores were compared between patients with trefoil and triangle stenosis types.ResultsThe mean patient age was 58.1 (standard deviation, 8.4) years. The kappa values of the MRI morphology stenosis grade types showed a perfect agreement between the stenosis grade types. The trefoil group (n=53) and triangle group (n=45) showed similar preoperative JOABPEQ subscale scores (e.g., low back pain, lumbar function, and mental health) and were not significantly different in age, BMI, duration of symptoms, or lumbar stenosis levels (all p>0.05); however, trefoil stenosis grade type was associated with a decreased walking ability according to the SPWT and JOABPEQ subscale scores.ConclusionsThese findings suggest preoperative walking ability is more profoundly affected in patients with trefoil type stenosis than in those with triangle type stenosis.

Background Patients with Marfan syndrome commonly require spinal deformity surgery. The purpose of this case report is to present a rare thoracotomy complication. We present the management of such a patient. Case summary In a known case of Marfan syndrome, an 18-year-old Persian man was admitted to our hospital with scoliosis. The patient underwent radiological examinations, and thoracic scoliosis of 70° was diagnosed. A right thoracotomy for anterior spinal fusion from the sixth rib and posterior spinal fusion were performed successfully. Two months later, he was readmitted because of winging of the right scapula due to serratus anterior palsy. Electromyography and nerve conduction velocity confirmed long thoracic nerve injury. Conservative treatment was provided. Ultimately, the patient recovered completely in the last follow-up visit 6 months after the surgery. Discussion This is the first report of ipsilateral winged scapula after thoracotomy. Attention needs to be paid to surgical techniques in patients with Marfan syndrome.