Objective Maintaining the occipito-axial (O–C2) angle following occipitocervical fusion is crucial to prevent postoperative complications. Although automated O–C2 measurement has been reported, practical methods that provide rapid results for routine practice remain limited. This study aimed to develop a deep learning model using the YOLO (You Only Look Once) object detection algorithm to automatically identify anatomical landmarks and rapidly calculate the O–C2 angle.
Methods A retrospective analysis was conducted using cervical spine radiographs from 2 independent facilities. The internal dataset comprised 574 lateral cervical radiographs from 271 patients for model development, while the external validation dataset included 100 radiographs from 100 patients. Model performance was evaluated against manual measurements by 3 expert raters.
Results The model demonstrated excellent detection performance, achieving perfect metrics for the hard palate (F1 score: 1.00) and high performance for the occipital bone (F1 score: 0.97), anteroinferior corner of C2 (F1 score: 0.99), and posteroinferior corner of C2 (F1 score: 0.99). For O–C2 angle estimation, the mean absolute error was 2.35° and root mean squared error was 2.98°, with an accuracy of 94.7% for determining the presence or absence of the O–C2 angle (i.e., whether all 4 anatomical landmarks were simultaneously detected). Bland-Altman analysis revealed minimal bias (0.57°; 95% confidence interval, -0.06° to 1.12°) with limits of agreement from -5.19° to 6.33°. Inference time was approximately 0.14 s per image.
Conclusion Our deep learning model enables rapid and accurate O–C2 angle measurement on lateral cervical radiographs, demonstrating performance comparable to expert raters and potential clinical utility.
Objective Paravertebral foramen screws (PVFSs) have been developed for better pullout strength than lateral mass screws do and lower the risk of vertebral artery and nerve injury than do pedicle screws. While the original method involves insertion using lateral fluoroscopy, its reliability may be limited. This report is the first to assess the accuracy of PVFS insertion under navigation. Given the inherent inaccuracies associated with navigation systems, the authors propose and evaluate a novel stepwise method of inserting PVFSs, called stepwise PVFS with a focus on achieving the correct screw tip location for good cortical bone purchase.
Methods The authors conducted a retrospective analysis of 12 patients (78 screws) who underwent cervical spine fixation with stepwise PVFS under O-arm navigation between October 2022 and February 2024. The accuracy of screw placement was evaluated using postoperative computed tomography (CT) scans.
Results A total of 78 PVFSs were inserted in 5 men and 7 women, with an average age of 75 years (range, 52–85 years). The mean follow-up period was 471 days (range, 47–834 days). There were no adverse events related to screw insertion. Postoperative CT scans revealed that 70 screws (90%) were placed in the ideal position. Among the 8 screws that did not achieve the ideal position, 4 had lateral deviation (located in a lateral mass), whereas the other 4 were too short. There were no cases of screw loosening at the final follow-up.
Conclusion The present study demonstrates that the stepwise PVFS method under navigation guidance achieves higher accuracy in PVFS placement compared with conventional fluoroscopy-guided PVFS, as reported in previous studies.
The study of genetic alterations and molecular biology in central nervous system (CNS) tumors has improved the accuracy of estimations of patient prognosis and tumor categorization. Therefore, the updated 2021 World Health Organization (WHO) classification includes various diagnostic genes, molecules, and pathways for diagnosis, as well as histological findings. These findings are expected both to have diagnostic applications and to facilitate new targeted therapies that target tumor-specific genetic changes and molecular biology. Intramedullary spinal cord tumors (IMSCTs) are rare CNS tumors that are difficult to treat because they occur in eloquent areas. Although the genetic underpinnings of IMSCTs remain unclear compared to their intracranial counterparts, the genetic characteristics of these tumors are gradually being revealed. Here, we describe the major changes in the new 2021 WHO classification and review the major types of IMSCTs, with an emphasis on their clinical features and genetic alterations.
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Objective The purpose of this study is to find the clinical and radiographic characteristics of traumatic craniocervical junction (CCJ) injuries requiring occipitocervical fusion (OC fusion) for early diagnosis and surgical intervention.
Methods We retrospectively reviewed 12 patients with CCJ injuries presenting to St. Michaels Hospital in Toronto who underwent OC fusion and looked into the following variables; (1) initial trauma data on emergency room arrival, (2) associated injuries, (3) imaging characteristics of computed tomography (CT) scan and magnetic resonance imaging (MRI), (4) surgical procedures, surgical complications, and neurological outcome.
Results All patients were treated as acute spinal injuries and underwent OC fusion on an emergency basis. Patients consisted of 10 males and 2 females with an average age of 47 years (range, 18–82 years). All patients sustained high-energy injuries. Three patients out of 6 patients with normal BAI (basion-axial interval) and BDI (basion-dens interval) values showed visible CCJ injuries on CT scans. However, the remaining 3 patients had no clear evidence of occipitoatlantal instability on CT scans. MRI clearly described several findings indicating occipitoatlantal instability. The 8 patients with normal values of ADI (atlantodens interval interval) demonstrated atlantoaxial instability on CT scan, however, all MRI more clearly and reliably demonstrated C1/2 facet injury and/or cruciate ligament injury.
Conclusion We advocate measures to help recognize CCJ injury at an early stage in the present study. Occipitoatlantal instability needs to be carefully investigated on MRI in addition to CT scan with special attention to facet joint and ligament integrity.
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