A system of predictive scores to evaluate the risk of multilevel noncontiguous spinal fractures in patients with traumatic cervical spine injury.

PURPOSE: To develop a predictive scoring system to identify traumatic cervical spine injury patients at a high risk of having multilevel noncontiguous spinal fractures. METHODS: This 12-year retrospective observational cohort study included 588 traumatic cervical spine-injured patients. Patients were categorized into two groups: patients with multilevel noncontiguous spinal fractures and patients without this remote injury. Potential risk factors were examined using multivariable analysis to derive a predictive risk score from independent predictors. Results are presented as odds ratio with a 95% confidence interval (95% CI). The accuracy of the calculated predicted score was demonstrated by the area under the receiver operating characteristic curve (AuROC). RESULTS: The incidence of noncontiguous fracture among the patients was 17% (100 of 588). The independent risk factors associated with multilevel noncontiguous spinal fractures were motor weakness, intracranial injury, intrathoracic injury, and intraabdominal injury. The AuROC of the prediction score was 0.74 (95% CI 0.69, 0.80). The patients were classified into three groups, low-risk group (score< 1), moderate-risk group (score 1-2.5), and high-risk group (score≥ 3), based on the predicted risk of multilevel noncontiguous spinal fractures. CONCLUSIONS: This tool can potentially help preventing the missed diagnosis of cervical spine injuries with multilevel noncontiguous spinal fractures. CT scans or MRI of the entire spine to investigate remote multilevel noncontiguous spinal fractures may have a role in cervical spine-injured patients who have at least one of the independent risk factors and are strongly suggested for patients with scores in the high-risk group.

Atlas (C1) lateral mass screw placement using the intersection between lateral mass and inferomedial edge of the posterior arch: a cadaveric study.

PURPOSE: To compare the Atlas (C1) lateral mass screw placement between screw trajectories of 0° and 15° medial angulation while using the intersection between lateral mass and inferomedial edge of the posterior arch. METHODS: Forty-eight Atlas lateral masses were prepared and divided into 2 groups: Group 1; screws inserted at 3 mm lateral to the reference point with screw trajectory of 0° angulation(N = 24) and Group 2; those inserted with screw trajectory of 15° medial angulation(N = 24). We evaluated the atlas anatomy, screw purchase and the presence of any breaches using CT scan. RESULTS: The radiographic parameters for Groups 1 and 2 were found statistically different (p-value < 0.05): bilateral intraosseous screw lengths (17.92 ± 1.47 mm. vs. 20.71 ± 2.4 mm.), bilateral screw length (29.92 ± 1.72 mm. vs. 33.13 ± 1.78 mm.), left screw medial angulation (x°) (0.67° ± 0.78° vs.14.17° ± 3.51°), right screw medial angulation (y°) (0.83° ± 1.03° vs.14.25° ± 2.53°) and bilateral screw medial angulation (0.75° ± 0.9° vs. 14.21° ± 2.99°). Twenty-two screws (91.67%) using the 0° medial angulation and nineteen screws (79.17%) using the 15° medial angulation had no cortical violations (Grade 0). However, two screws (8.33%) with 0° medial angulation and five screws (20.83%) with 15° medial angulation had breach less than 2 mm (Grade 1). There were no screws with breach between 2 and 4 mm (Grade 2) or greater than 4 mm. (Grade 3). CONCLUSION: A starting point of 3-mm lateral to the intersection between lateral mass and inferomedial edge of the Atlas posterior arch can be safely and effectively used to insert C1 lateral mass using both 0° and 15° medial angulation.

In vitro elution characteristics of gentamicin-impregnated Polymethylmethacrylate: premixed with a second powder vs. liquid Lyophilization.

BACKGROUND: Antibiotic-loaded bone cement, or antibiotic-impregnated polymethylmethacrylate (PMMA), were developed to prevent and treat bone and joint infections. Gentamicin is an antibiotic that is commonly used in combination with PMMA; however, gentamicin powder is hard to obtain in many countries. This study aimed to evaluate the elution characteristics of gentamicin-impregnated PMMA made with lyophilized liquid gentamicin, compared with PMMA; which is made from commercial gentamicin powder. METHODS: The experimental sample was divided into 2 groups: the gentamicin power group (PG-PMMA) and the lyophilized liquid gentamicin group (LG-PMMA). Ten cement spacers were prepared in each group. These were produced by mixing gentamicin powder, or lyophilized liquid gentamicin, with a powder polymer before adding the liquid monomer (2 g of gentamicin and 40 g of PMMA). The volume and surface area of the antibiotic-impregnated cement spacers were 50 cm3 and 110 cm2, respectively. Each spacer was immersed in phosphate-buffered saline, which was changed daily under sterile conditions. The solutions were collected to measure the level of gentamicin using the enzyme multiplied immunoassay technique (EMIT), at days 1, 2, 3, 4, 5, 6, 7, 14, 21, 28, 35 and 42. RESULTS: The collections from both groups had high concentrations of gentamicin on day 1 (113.63 ± 23.42 mg/dL in LG-PMMA and 61.7 ±8.37 mg/dL in PG-PMMA), but experienced a continuous decrease over time. The PMMA spacers from both groups could release gentamicin for up to 6 weeks (3.28 ± 1.17 mg/dL in LG-PMMA and 1.21 ± 0.28 mg/dL in PG-PMMA). However, there were significantly higher levels of gentamicin concentrations in the LG-PMMA group compared to the PG-PMMA group at all time points (P< 0.05). CONCLUSION: Gentamicin-impregnated PMMA made with lyophilized liquid gentamicin had approximately a two times higher rate of antibiotic elution in preliminary in vitro studies, as compared with PMMA made with premixed gentamicin powder.

The aiming device for cervical distractor pin insertion: a proof-of-concept, feasibility study.

BACKGROUND: Restoration of cervical lordosis after anterior discectomy and fusion is a desirable goal. Proper insertion of the vertebral distraction or Caspar pin can assist lordotic restoration by either putting the tips divergently or parallel to the index vertebral endplates. With inexperienced surgeons, the traditional free-hand technique for Caspar pin insertion may require multiple insertion attempts that may compromise the vertebral body and increase radiation exposure during pin localization. Our purpose is to perform a proof-of-concept, feasibility study to evaluate the effectiveness of a pin insertion aiming device for vertebral distraction pin insertion. METHODS: A Smith-Robinson approach and anterior cervical discectomy were performed from C3 to C7 in 10 human cadaveric specimens. Caspar pins were inserted using a novel pin insertion aiming device at C3-4, C4-5, C5-6, and C6-7. The angles between the cervical endplate slope and Caspar pin alignment were measured with lateral cervical imaging. RESULTS: The average Superior Endplate-to-Caspar Pin angle (SE-CP) and the average Inferior Endplate-to-Caspar Pin angle (IE-CP) were 6.2 ± 2.0° and 6.3 ± 2.2° respectively. For the proximal pins, the SE-CP and the IE-CP were 4.0 ± 1.1°and 5.2 ± 2.4° respectively. For the distal pins, the SE-CP and the IE-CP were 7.7 ± 1.4° and 6.2 ± 2.0° respectively. No cervical endplate violations occurred. CONCLUSION: The novel Caspar pin insertion aiming device can control the pin entry points and pin direction with the average SE-CP and average IE-CP of 6.2 ± 2.0° and 6.3 ± 2.2°, respectively. The study shows that the average different angles between the Caspar pin and cervical endplate are less than 7°.

Acute traumatic unilateral cervical C4-C5 facet dislocation in pediatric toddlers.

BACKGROUND: The present study is to highlight the challenges in managing cervical spine injuries in toddlers (less than 4 years of age) without neurological deficit. Cases of unilateral cervical C4-C5 facet dislocation in toddlers are very rare. CASE PRESENTATION: A 3-year-old girl suffered cervical spine injury after a motor vehicle collision with unilateral C4-C5 facet dislocation without neurological deficit. Magnetic resonance imaging (MRI) showed no spinal cord injury, Frankel grade E. Initial management was cervical spine protection. Definite treatment and complication were discussed with the patient's parents before closed reduction maneuver with minerva cast was applied under sedation. The patient showed no complication after closed reduction and the cervical spine had aligned well in radiographs. The minerva cast was removed at 8 weeks, at which point neck muscle stretching rehabilitation program started. At one-year follow up, the child was asymptomatic, had full active cervical motion and good function. In radiographs, the cervical spine had normal alignment and was healed. CONCLUSIONS: Unilateral cervical facet dislocation in toddlers is very rare. Closed reduction maneuver and the minerva cast applied were optional in this case. The parents were highly satisfied with the effective treatment and outcome.

Cervical spine fracture in diffuse idiopathic skeletal hyperostosis: A bibliometric analysis.

Objective: The study aimed to assess and investigate cervical spine fracture in diffuse idiopathic skeletal hyperostosis and to identify research trends in cervical spine fracture in diffuse idiopathic skeletal hyperostosis in countries around the world using bibliometric analysis. Method: We examined bibliometric data obtained from the Scopus database collection for the periods 1 January 2000 and 1 January 2022. Authors, institutions, nations, publications, keywords, and references were noted and analyzed. The total number of research articles published on the subject of diffuse idiopathic skeletal hyperostosis was used to calculate the amount of research on that subject undertaken in the study period. A sample of the publication data collected from the Scopus database was then analyzed using the Bibliometric program and used to develop a relationship chart using the Bibliometrix and VOSviewer programs. Results: The number of citations was assumed to be a qualitative measure of the publication. We estimated the impact of the research using several metrics, including the H-index, in the bibliometric analysis of authors, geographic areas, institutes, and references. A total of 52 studies related to cervical spine fractures in diffuse idiopathic skeletal hyperostosis were identified. Only 5.12% of those studies were cited in other publications, for a total of 1410 citations in publications by 342 authors, of whom only two authors had published a single study. Co-authorships occurred at 7.273%. Diseases common in elderly males were often studied retrospectively, and "Diffuse Idiopathic Skeletal Hyperostosis" was a frequently mentioned keyword. Conclusion: The findings of this study provide insights into authors, institutions, key publications, and research trends related to diffuse idiopathic skeletal hyperostosis and can potentially serve as a guide for further studies in the field. The bibliometric analysis of cervical spine fractures in patients with diffuse idiopathic skeletal hyperostosis highlights important contributors, influential papers, geographical trends, and study characteristics in this area of research.

Artificial Intelligence Detection of Cervical Spine Fractures Using Convolutional Neural Network Models.

OBJECTIVE: To develop and evaluate a technique using convolutional neural networks (CNNs) for the computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. By leveraging deep learning techniques, the study might potentially lead to improved patient outcomes and clinical decision-making. METHODS: This study obtained 500 lateral radiographic cervical spine x-ray images from standard open-source dataset repositories to develop a classification model using CNNs. All the images contained diagnostic information, including normal cervical radiographic images (n=250) and fracture images of the cervical spine fracture (n=250). The model would classify whether the patient had a cervical spine fracture or not. Seventy percent of the images were training data sets used for model training, and 30% were for testing. Konstanz Information Miner (KNIME)'s graphic user interface-based programming enabled class label annotation, data preprocessing, CNNs model training, and performance evaluation. RESULTS: The performance evaluation of a model for detecting cervical spine fractures presents compelling results across various metrics. This model exhibits high sensitivity (recall) values of 0.886 for fractures and 0.957 for normal cases, indicating its proficiency in identifying true positives. Precision values of 0.954 for fractures and 0.893 for normal cases highlight the model's ability to minimize false positives. With specificity values of 0.957 for fractures and 0.886 for normal cases, the model effectively identifies true negatives. The overall accuracy of 92.14% highlights its reliability in correctly classifying cases by the area under the receiver operating characteristic curve. CONCLUSION: We successfully used deep learning models for computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. This approach can assist the radiologist in screening, detecting, and diagnosing cervical spine fractures.

Cervical sagittal parameters in degenerative cervical spondylolisthesis versus degenerative cervical kyphosis with myeloradiculopathy treated by anterior cervical discectomy and fusion.

Background: Adult spinal deformity, especially sagittal imbalance, is affecting health-related quality-of-life (HRQOL) scores. There is a lack of emphasis in the comparison of cervical sagittal parameters in patients with degenerative cervical spondylolisthesis and degenerative cervical kyphosis. The aim of study is to determine the preoperative and postoperative cervical sagittal parameters in myeloradiculopathic patients with degenerative cervical spondylolisthesis and degenerative cervical kyphosis treated by anterior cervical discectomy and fusion (ACDF). Methods: A retrospective medical records and radiographic study of 30 adult patients were reviewed. Fifteen patients with degenerative cervical spondylolisthesis and 15 patients with degenerative cervical kyphosis have been performed ACDF from 2010-2020. We measured the preoperative and postoperative cervical sagittal parameters: C0-C2 angle, C1-C2 angle, C2-C7 angle, C2-C7 sagittal vertical axis (SVA), T1 slope, neck tilt angle and thoracic inlet angle. Minimum follow-up period was at least 2 years. Results: Patients in degenerative cervical kyphosis group have C2-C7 angle less than degenerative cervical spondylolisthesis group (-14.88±7.32 vs. 9.60±13.60), leading to increase the mismatch between T1 slope and C2-C7 angle in kyphotic group and hyperlordosis of C0-C2 angle and C1-C2 angle (31.13±7.68, 37.88±5.08) compare with spondylolisthesis group (13±10.20, 24.60±10.70). Whereas patients with degenerative cervical spondylolisthesis have C2-C7 SVA (33.22±13.92) more than kyphosis group (13.70±13.60). After surgery, there is significant increase of the C2-C7 angle in the kyphosis group compare before and after surgery (-14.88±7.32 vs. 4.10±11.80). While the spondylolisthesis group has no significantly different parameters compare to before surgery. However, the postoperative cervical sagittal parameters of all patients are within the normal thresholds (T1-Slope minus C2-C7 lordosis <15° and C2-C7 SVA <40 mm). Conclusions: The study demonstrates the difference of sagittal parameters between degenerative cervical spondylolisthesis and kyphosis before and after surgery. ACDF not only provides neural decompressive procedure, but also corrects the regional cervical sagittal parameters.

Current Trends in Artificial Intelligence-Assisted Spine Surgery: A Systematic Review.

This systematic review summarizes existing evidence and outlines the benefits of artificial intelligence-assisted spine surgery. The popularity of artificial intelligence has grown significantly, demonstrating its benefits in computer-assisted surgery and advancements in spinal treatment. This study adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a set of reporting guidelines specifically designed for systematic reviews and meta-analyses. The search strategy used Medical Subject Headings (MeSH) terms, including "MeSH (Artificial intelligence)," "Spine" AND "Spinal" filters, in the last 10 years, and English- from January 1, 2013, to October 31, 2023. In total, 442 articles fulfilled the first screening criteria. A detailed analysis of those articles identified 220 that matched the criteria, of which 11 were considered appropriate for this analysis after applying the complete inclusion and exclusion criteria. In total, 11 studies met the eligibility criteria. Analysis of these studies revealed the types of artificial intelligence-assisted spine surgery. No evidence suggests the superiority of assisted spine surgery with or without artificial intelligence in terms of outcomes. In terms of feasibility, accuracy, safety, and facilitating lower patient radiation exposure compared with standard fluoroscopic guidance, artificial intelligence-assisted spine surgery produced satisfactory and superior outcomes. The incorporation of artificial intelligence with augmented and virtual reality appears promising, with the potential to enhance surgeon proficiency and overall surgical safety.

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

STUDY DESIGN: Systematic review. OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system.

Background: Osteoporotic Vertebral Compression Fracture (OVCF) substantially reduces a person's health-related quality of life. Computer Tomography (CT) scan is currently the standard for diagnosis of OVCF. The aim of this paper was to evaluate the OVCF detection potential of artificial neural networks (ANN). Methods: Models of artificial intelligence based on deep learning hold promise for quickly and automatically identifying and visualizing OVCF. This study investigated the detection, classification, and grading of OVCF using deep artificial neural networks (ANN). Techniques: Annotation techniques were used to segregate the sagittal images of 1,050 OVCF CT pictures with symptomatic low back pain into 934 CT images for a training dataset (89%) and 116 CT images for a test dataset (11%). A radiologist tagged, cleaned, and annotated the training dataset. Disc deterioration was assessed in all lumbar discs using the AO Spine-DGOU Osteoporotic Fracture Classification System. The detection and grading of OVCF were trained using the deep learning ANN model. By putting an automatic model to the test for dataset grading, the outcomes of the ANN model training were confirmed. Results: The sagittal lumbar CT training dataset included 5,010 OVCF from OF1, 1942 from OF2, 522 from OF3, 336 from OF4, and none from OF5. With overall 96.04% accuracy, the deep ANN model was able to identify and categorize lumbar OVCF. Conclusions: The ANN model offers a rapid and effective way to classify lumbar OVCF by automatically and consistently evaluating routine CT scans using AO Spine-DGOU osteoporotic fracture classification system.

Artificial neural networks for the detection of odontoid fractures using the Konstanz Information Miner Analytics Platform.

STUDY DESIGN: An experimental study. PURPOSE: This study aimed to investigate the potential use of artificial neural networks (ANNs) in the detection of odontoid fractures using the Konstanz Information Miner (KNIME) Analytics Platform that provides a technique for computer-assisted diagnosis using radiographic X-ray imaging. OVERVIEW OF LITERATURE: In medical image processing, computer-assisted diagnosis with ANNs from radiographic X-ray imaging is becoming increasingly popular. Odontoid fractures are a common fracture of the axis and account for 10%-15% of all cervical fractures. However, a literature review of computer-assisted diagnosis with ANNs has not been made. METHODS: This study analyzed 432 open-mouth (odontoid) radiographic views of cervical spine X-ray images obtained from dataset repositories, which were used in developing ANN models based on the convolutional neural network theory. All the images contained diagnostic information, including 216 radiographic images of individuals with normal odontoid processes and 216 images of patients with acute odontoid fractures. The model classified each image as either showing an odontoid fracture or not. Specifically, 70% of the images were training datasets used for model training, and 30% were used for testing. KNIME's graphic user interface-based programming enabled class label annotation, data preprocessing, model training, and performance evaluation. RESULTS: The graphic user interface program by KNIME was used to report all radiographic X-ray imaging features. The ANN model performed 50 epochs of training. The performance indices in detecting odontoid fractures included sensitivity, specificity, F-measure, and prediction error of 100%, 95.4%, 97.77%, and 2.3%, respectively. The model's accuracy accounted for 97% of the area under the receiver operating characteristic curve for the diagnosis of odontoid fractures. CONCLUSIONS: The ANN models with the KNIME Analytics Platform were successfully used in the computer-assisted diagnosis of odontoid fractures using radiographic X-ray images. This approach can help radiologists in the screening, detection, and diagnosis of acute odontoid fractures.

Clinical and Radiographic Outcomes of Cervical Disc Replacement Versus Posterior Endoscopic Cervical Decompression: A Matched-Pair Comparison Analysis.

OBJECTIVE: To compare clinical and radiographic outcomes between 2 motion preservation surgeries, cervical disc replacement (CDR) and posterior endoscopic cervical decompression (PECD), for unilateral cervical radiculopathy. METHODS: Between February 2018 and December 2020, 60 patients with unilateral cervical radiculopathy who underwent either CDR or PECD were retrospectively recruited as matched pairs. Clinical outcomes included visual analogue scale (VAS) scores for neck and arm pain, Neck Disability Index (NDI), and satisfaction rates. The radiographic outcome was index level motion. Intraoperative data, complications, and hospital stay were collected. Preoperative and postoperative outcomes were compared. RESULTS: Patients undergoing CDR or PECD were included, with 30 cases in each group. Matched pairs were compared in terms of demographic data and preoperative measurements. CDR was associated with shorter operative times, whereas PECD resulted in less intraoperative blood loss. The total complication rate was 5%. NDI and VAS for neck and arm were significantly improved in both groups, with no significant differences between the 2 groups. Satisfaction rates of good and excellent exceeded 87% in both groups. CDR was superior to PECD in the restoration of disc height. Early postoperative follow-up showed no significant difference in terms of index level motion. PECD demonstrated significantly shorter hospital stays and quicker return-to-work times (p<0.05). CONCLUSION: PECD achieved equivalent clinical and radiologic outcomes compared with CDR when the certain criteria for surgery were met. Both techniques demonstrated the potential to maintain index level motion. Additionally, PECD resulted in less blood loss, shorter hospital stays, and faster return-to-work times. Conversely, CDR offered shorter operative times and better restoration of disc height.

Endoscopic carpal surgery in carpal tunnel syndrome: A systematic review.

Objective: Endoscopic carpal tunnel release has become increasingly popular and has shown the advantage of early recovery of hand function with minimal morbidity. In this systematic review, we aimed to summarize the currently available data and describe the reported advantages and disadvantages of endoscopic carpal tunnel surgery for treating carpal tunnel syndrome. Methods: In this study, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, which is a set of reporting requirements for systematic reviews and meta-analyses. The search strategy with MeSH terms was "MeSH (carpal tunnel syndrome) AND (endoscopic)" Filters: in the last 5 years, English-on February 27th, 2022. A total of 131 articles fulfilled the first screening criteria. A detailed analysis of those articles identified 39 that matched the criteria, of which 14 were considered appropriate for this analysis after applying the complete inclusion and exclusion criteria. Results: A total of 14 studies met the eligibility criteria. Analysis of those studies found that all types of portals in endoscopic carpal tunnel release reduced postoperative pain at a short-term follow-up. There was no evidence to suggest the superiority of the single- or two-portal techniques in terms of outcomes. In terms of pain relief, symptom resolution, patient satisfaction, duration to return to work, and adverse events, this early use of endoscopic carpal tunnel release produced satisfactory outcomes. Further studies comparing the number of portals are needed. Conclusion: Endoscopic carpal tunnel surgery for treating carpal tunnel syndrome is effective and both single- and dual-portal techniques provide advantages in terms of early recovery and minimal morbidity.

An invasive squamous cell carcinoma of the ankle: a case report.

One to ten percent of all squamous carcinomas are invasive squamous cell carcinomas (ISCC), a rare variation of the disease. According to a recent literature review, less than 25 cases have been reported in the foot and ankle, making it especially uncommon in those areas. Case presentation: The authors present the case of a male patient, 60 years old, who presented with a progressive mass on his left ankle for 2 years with a history of healed burns in that area. The ISCC was diagnosed using histopathology after which he underwent a marginal excision biopsy and split-thickness skin grafting. Wide-marginal excision and split-thickness skin grafting were done. It was noted that the graft had taken well and that there were clear tumour margins postoperatively. The skin graft was almost completely incorporated. No tumour cells were reported on the margins during the postoperative histopathology. Clinical discussion: This case highlights a successful outcome of the patient improved at the 12-month follow-up, and he expressed a high degree of satisfaction with the treatment. Conclusion: ISCC of the lower extremities is a rare disease that almost never affects the ankle and is frequently treated inappropriately since it mimics chronic wounds. It is important to have an index of suspicion in patients with a history of chronic irritation to the area of interest. Surgery is the primary option if ICCS is detected. Clear tumour margins are important, and, if done well, excision should be curative.

Automatic Detection, Classification, and Grading of Lumbar Intervertebral Disc Degeneration Using an Artificial Neural Network Model.

BACKGROUND AND OBJECTIVES: Intervertebral disc degeneration (IDD) is a common cause of symptomatic axial low back pain. Magnetic resonance imaging (MRI) is currently the standard for the investigation and diagnosis of IDD. Deep learning artificial intelligence models represent a potential tool for rapidly and automatically detecting and visualizing IDD. This study investigated the use of deep convolutional neural networks (CNNs) for the detection, classification, and grading of IDD. METHODS: Sagittal images of 1000 IDD T2-weighted MRI images from 515 adult patients with symptomatic low back pain were separated into 800 MRI images using annotation techniques to create a training dataset (80%) and 200 MRI images to create a test dataset (20%). The training dataset was cleaned, labeled, and annotated by a radiologist. All lumbar discs were classified for disc degeneration based on the Pfirrmann grading system. The deep learning CNN model was used for training in detecting and grading IDD. The results of the training with the CNN model were verified by testing the grading of the dataset using an automatic model. RESULTS: The training dataset of the sagittal intervertebral disc lumbar MRI images found 220 IDDs of grade I, 530 of grade II, 170 of grade III, 160 of grade IV, and 20 of grade V. The deep CNN model was able to detect and classify lumbar IDD with an accuracy of more than 95%. CONCLUSION: The deep CNN model can reliably automatically grade routine T2-weighted MRIs using the Pfirrmann grading system, providing a quick and efficient method for lumbar IDD classification.

Full-Endoscopic Lumbar Discectomy Approach Selection: A Systematic Review and Proposed Algorithm.

STUDY DESIGN: A systematic review of the literature to develop an algorithm formulated by key opinion leaders. OBJECTIVE: This study aimed to analyze currently available data and propose a decision-making algorithm for full-endoscopic lumbar discectomy for treating lumbar disc herniation (LDH) to help surgeons choose the most appropriate approach [transforaminal endoscopic lumbar discectomy (TELD) or interlaminar endoscopic lumbar discectomy (IELD)] for patients. SUMMARY OF BACKGROUND DATA: Full-endoscopic discectomy has gained popularity in recent decades. To our knowledge, an algorithm for choosing the proper surgical approach has never been proposed. MATERIALS AND METHODS: A systematic review of the literature using PubMed and MeSH terms was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Patient samples included patients with LDH treated with full-endoscopic discectomy. The inclusion criteria were interventional research (randomized and nonrandomized trials) and observation research (cohort, case-control, case series). Exclusion criteria were case series and technical reports. The criteria used for selecting patients were grouped and analyzed. Then, an algorithm was generated based on these findings with support and reconfirmation from key expert opinions. Data on overall complications were collected. Outcome measures included zone of herniation, level of herniation, and approach (TELD or IELD). RESULTS: In total, 474 articles met the initial screening criteria. The detailed analysis identified the 80 best-matching articles; after applying the inclusion and exclusion criteria, 53 articles remained for this review. CONCLUSIONS: The proposed algorithm suggests a TELD for LDH located in the foraminal or extraforaminal zones at upper and lower levels and for central and subarticular discs at the upper levels considering the anatomic foraminal features and the craniocaudal pathology location. An IELD is preferred for LDH in the central or subarticular zones at L4/L5 and L5/S1, especially if a high iliac crest or high-grade migration is found.

An Unusual Chordoma of the Odontoid Process: A Case Report and Literature Review.

The aim of this study is to present a rare case of chordoma in the odontoid process in which the tumor involved the odontoid process and compressed the spinal cord at the craniocervical junction. We report on the effectiveness and successful outcome of anterior microscopic tumor resection combined with posterior occipitocervical fixation and review the current standard treatment. A 39-year-old man presented with sudden dyspnea and quadriparesis caused by an unknown tumor compression at C2. Radiographic examination revealed a large destructive mass at C2 and heterogeneous enhancement. The patient received urgent surgical intervention by microscopic-assisted anterior tumor resection and posterior spinal fixation from the occiput to the C5 level. The pathohistologic reports for cytokeratins, epithelial membrane antigen, and S-100 protein were positive. The final diagnosis was chordoma of the odontoid process. At the 2-year follow-up, the patient's condition had improved, and a postoperative MRI showed no indication of tumor regrowth. Chordoma of the odontoid process or C2 body is very rare. The current standard management is wide tumor resection to prevent recurrence. The combined approach of anterior tumor resection with microscopic assistance and posterior stabilization of the occiput to C5 is the optimal treatment for this condition.

Can acute radiculopathy be caused by upper lumbar hemorrhagic synovial cyst spinal compression in the elderly?

INTRODUCTION AND IMPORTANCE: Acute radiculopathy caused by upper lumbar synovial cysts is rare. They generally present with a slow development of symptoms resulting from spinal canal involvement. Intracyst hemorrhagic synovial cysts are extremely uncommon and can manifest as radicular pain, radiculopathy or even cauda equina compression syndrome. CASE PRESENTATION: A 71-year-old woman with acute back and radicular leg pain presented with worsening symptoms after receiving 1 week of therapy to the left lower limb without trauma. Magnetic resonance imaging (MRI) showed a hemorrhagic synovial intracyst at L2-L3 on the front of the left inter-facet joint which was identified as the cause of the acute back pain and radiculopathy which required surgical removal. Post-surgery, the patient followed the rehabilitation program instructions and attended all scheduled follow-up visits. The patient was asymptomatic at the one-year follow-up. CLINICAL DISCUSSION: Synovial cysts are commonly associated with degenerative changes that occur with aging, although the specific cause is unknown. Surgical removal of an upper lumbar synovial cyst gives better results than non-surgical treatments if the symptoms persist or recurrent. CONCLUSION: For recurrent symptomatic upper lumbar spine synovial cysts (L2-L3), surgery is usually the best option. Surgical removal of an upper lumbar synovial cyst can result in full relief of acute symptoms and reduction of neurologic deficits.

A Preliminary Report on Augmented Reality Assisted Carpal Tunnel Release.

Augmented reality (AR) refers to the use of technology to enhance a real-world environment by computer generated visual, auditory, haptic, somatosensory and/or olfactory stimuli. We developed an augmented reality-assisted surgery (ARAS) for carpal tunnel syndrome (CTS). It generates a virtual image of the operative field that the surgeon can view. This enhances the operative experience. We report the use of ARAS in performing limited open carpal tunnel release. Level of Evidence: Level V (Therapeutic).