Computed tomography (CT) is widely used for the diagnosis and surgical treatment of spinal pathologies, particularly for pedicle screw placement. However, CT’s limitations, notably radiation exposure, necessitate the development of alternative imaging techniques. Synthetic CT (sCT), which generates CT-like images from existing magnetic resonance imaging (MRI) scans, offers a promising alternative to reduce radiation exposure. This study examines the emerging role of sCT in spinal surgery, focusing on usability, efficiency, and potential impact on surgical outcomes. This qualitative literature review evaluated various sCT generation methods, encompassing traditional atlas-based and bulk-density models, as well as advanced convolutional neural network (CNN) architectures, including U-net, V-net, and generative adversarial network models. The review assessed sCT accuracy and clinical feasibility across different medical disciplines, particularly oncology and surgery, with potential applications in orthopedic, neurosurgical, and spinal surgery. sCT has shown significant promise across various medical disciplines. CNN-based techniques enable rapid and accurate generation of sCT from MRI scans, rendering clinical use feasible. sCT has been used to identify pathologies and monitor disease progression, suggesting that MRI alone may suffice for diagnosis and planning in the future. In spinal surgery, sCTs are particularly useful in visualizing key anatomical features like vertebral dimensions and spinal canal diameter. However, challenges persist, especially in visualizing complex structures and larger spinal regions, like the lumbar spine. Additional limitations include inaccuracies stemming from surgical implants and image variability. The application of sCT technology in spinal surgery holds great promise, improving diagnostics, planning, and treatment outcomes. Although further research is required to improve its precision, it offers a viable alternative to traditional CT in many clinical contexts, with the potential for broader application as the technology matures.

Computed tomography (CT) is widely used for the diagnosis and surgical treatment of spinal pathologies, particularly for pedicle screw placement. However, CT’s limitations, notably radiation exposure, necessitate the development of alternative imaging techniques. Synthetic CT (sCT), which generates CT-like images from existing magnetic resonance imaging (MRI) scans, offers a promising alternative to reduce radiation exposure. This study examines the emerging role of sCT in spinal surgery, focusing on usability, efficiency, and potential impact on surgical outcomes. This qualitative literature review evaluated various sCT generation methods, encompassing traditional atlas-based and bulk-density models, as well as advanced convolutional neural network (CNN) architectures, including U-net, V-net, and generative adversarial network models. The review assessed sCT accuracy and clinical feasibility across different medical disciplines, particularly oncology and surgery, with potential applications in orthopedic, neurosurgical, and spinal surgery. sCT has shown significant promise across various medical disciplines. CNN-based techniques enable rapid and accurate generation of sCT from MRI scans, rendering clinical use feasible. sCT has been used to identify pathologies and monitor disease progression, suggesting that MRI alone may suffice for diagnosis and planning in the future. In spinal surgery, sCTs are particularly useful in visualizing key anatomical features like vertebral dimensions and spinal canal diameter. However, challenges persist, especially in visualizing complex structures and larger spinal regions, like the lumbar spine. Additional limitations include inaccuracies stemming from surgical implants and image variability. The application of sCT technology in spinal surgery holds great promise, improving diagnostics, planning, and treatment outcomes. Although further research is required to improve its precision, it offers a viable alternative to traditional CT in many clinical contexts, with the potential for broader application as the technology matures.

Computed tomography (CT) is widely used for the diagnosis and surgical treatment of spinal pathologies, particularly for pedicle screw placement. However, CT’s limitations, notably radiation exposure, necessitate the development of alternative imaging techniques. Synthetic CT (sCT), which generates CT-like images from existing magnetic resonance imaging (MRI) scans, offers a promising alternative to reduce radiation exposure. This study examines the emerging role of sCT in spinal surgery, focusing on usability, efficiency, and potential impact on surgical outcomes. This qualitative literature review evaluated various sCT generation methods, encompassing traditional atlas-based and bulk-density models, as well as advanced convolutional neural network (CNN) architectures, including U-net, V-net, and generative adversarial network models. The review assessed sCT accuracy and clinical feasibility across different medical disciplines, particularly oncology and surgery, with potential applications in orthopedic, neurosurgical, and spinal surgery. sCT has shown significant promise across various medical disciplines. CNN-based techniques enable rapid and accurate generation of sCT from MRI scans, rendering clinical use feasible. sCT has been used to identify pathologies and monitor disease progression, suggesting that MRI alone may suffice for diagnosis and planning in the future. In spinal surgery, sCTs are particularly useful in visualizing key anatomical features like vertebral dimensions and spinal canal diameter. However, challenges persist, especially in visualizing complex structures and larger spinal regions, like the lumbar spine. Additional limitations include inaccuracies stemming from surgical implants and image variability. The application of sCT technology in spinal surgery holds great promise, improving diagnostics, planning, and treatment outcomes. Although further research is required to improve its precision, it offers a viable alternative to traditional CT in many clinical contexts, with the potential for broader application as the technology matures.

BACKGROUND:Atrial fibrillation (AF) is the most common arrhythmia treated in the emergency department (ED), with primary electrical cardioversion (PEC) the preferred method of rhythm control. Anecdotally, patients undergoing ED procedural sedation (EDPS) for PEC differ from those requiring EDPS for other procedures:they are at higher risk of adverse events, and require fewer drugs and lower doses. We attempt to verify this using an EDPS registry at a Canadian, tertiary care teaching hospital. METHODS:This is a retrospective review of patients that underwent EDPS for the period of June 2006 to September 2014. We compared demographics, medication use and intra-procedural adverse events between those receiving EDPS for PEC for AF compared to that for other indications. We report the asssociation between AEs and predictors using logistic regression. RESULTS:A total of 4867 patients were included, 714 for PEC for AF and 4153 for other indications. PEC patients were more likely male (58.5％vs. 47.1％), older (59.5 years vs. 48.1 years), and less likely to be ASA I (46.6％ vs. 69.0％). PEC patients received smaller doses of propofol and less likely to receive adjuvant analgesic therapy (11.5％ vs. 78.2％). PEC patients were more likely to experience hypotension (27.6％vs. 16.5％) but respiratory AEs (apnea, hypoxia and airway intervention) were not different. CONCLUSION:EDPS for PEC differs from that conducted for other purposes:patients tend to be less healthy, receive smaller doses of medication and more likely to suffer hypotension without an increase in respiratory AEs. These factors should be considered when performing EDPS.

BACKGROUND:This prospective, randomized trial was undertaken to evaluate the utility of adding end-tidal capnometry (ETC) to pulse oximetry (PO) in patients undergoing procedural sedation and analgesia (PSA) in the emergency department (ED). METHODS:The patients were randomized to monitoring with or without ETC in addition to the current standard of care. Primary endpoints included respiratory adverse events, with secondary endpoints of level of sedation, hypotension, other PSA-related adverse events and patient satisfaction. RESULTS:Of 986 patients, 501 were randomized to usual care and 485 to additional ETC monitoring. In this series, 48％ of the patients were female, with a mean age of 46 years. Orthopedic manipulations (71％), cardioversion (12％) and abscess incision and drainage (12％) were the most common procedures, and propofol and fentanyl were the sedative/analgesic combination used for most patients. There was no difference in patients experiencing de-saturation (SaO2<90％) between the two groups; however, patients in the ETC group were more likely to require airway repositioning (12.9％ vs. 9.3％,P=0.003). Hypotension (SBP<100 mmHg or <85 mmHg if baseline <100 mmHg) was observed in 16 (3.3％) patients in the ETC group and 7 (1.4％) in the control group (P=0.048). CONCLUSIONS:The addition of ETC does not appear to change any clinically significant outcomes. We found an increased incidence of the use of airway repositioning maneuvers and hypotension in cases where ETC was used. We do not believe that ETC should be recommended as a standard of care for the monitoring of patients undergoing PSA.