Study Design Prospective cohort study. Objectives In spine surgery, accurate screw guidance is critical to achieving satisfactory fixation. Augmented reality (AR) is a novel technology to assist in screw placement and has shown promising results in early studies. This study aims to provide our early experience evaluating safety and efficacy with an Food and Drug Administration-approved head-mounted (head-mounted device augmented reality (HMD-AR)) device. Methods Consecutive adult patients undergoing AR-assisted thoracolumbar fusion between October 2020 and August 2021 with 2 -week follow-up were included. Preoperative, intraoperative, and postoperative data were collected to include demographics, complications, revision surgeries, and AR performance. Intraoperative 3D imaging was used to assess screw accuracy using the Gertzbein-Robbins (G-R) grading scale. Results Thirty-two patients (40.6% male) were included with a total of 222 screws executed using HMD-AR. Intraoperatively, 4 (1.8%) were deemed misplaced and revised using AR or freehand. The remaining 218 (98.2%) screws were placed accurately. There were no intraoperative adverse events or complications, and AR was not abandoned in any case. Of the 208 AR-placed screws with 3D imaging confirmation, 97.1% were considered clinically accurate (91.8% Grade A, 5.3% Grade B). There were no early postoperative surgical complications or revision surgeries during the 2 -week follow-up. Conclusions This early experience study reports an overall G-R accuracy of 97.1% across 218 AR-guided screws with no intra or early postoperative complications. This shows that HMD-AR-assisted spine surgery is a safe and accurate tool for pedicle, cortical, and pelvic fixation. Larger studies are needed to continue to support this compelling evolution in spine surgery.
OBJECTIVE The analysis of sagittal alignment by measuring spinopelvic parameters has been widely adopted among spine surgeons globally, and sagittal imbalance is a well-documented cause of poor quality of life. These measurements are time-consuming but necessary to make, which creates a growing need for an automated analysis tool that measures spinopelvic parameters with speed, precision, and reproducibility without relying on user input. This study introduces and evaluates an algorithm based on artificial intelligence (AI) that fully automatically measures spinopelvic parameters. METHODS Two hundred lateral lumbar radiographs (pre- and postoperative images from 100 patients undergoing lumbar fusion) were retrospectively analyzed by board-certified spine surgeons who digitally measured lumbar lordosis, pelvic incidence, pelvic tilt, and sacral slope. The novel AI algorithm was also used to measure the same parameters. To evaluate the agreement between human and AI-automated measurements, the mean error (95% CI, SD) was calculated and interrater reliability was assessed using the 2-way random single-measure intraclass correlation coefficient (ICC). ICC values larger than 0.75 were considered excellent. RESULTS The AI algorithm determined all parameters in 98% of preoperative and in 95% of postoperative images with excellent ICC values (preoperative range 0.85–0.92, postoperative range 0.81–0.87). The mean errors were smallest for pelvic incidence both pre- and postoperatively (preoperatively −0.5° [95% CI −1.5° to 0.6°] and postoperatively 0.0° [95% CI −1.1° to 1.2°]) and largest preoperatively for sacral slope (−2.2° [95% CI −3.0° to −1.5°]) and postoperatively for lumbar lordosis (3.8° [95% CI 2.5° to 5.0°]). CONCLUSIONS Advancements in AI translate to the arena of medical imaging analysis. This method of measuring spinopelvic parameters on spine radiographs has excellent reliability comparable to expert human raters. This application allows users to accurately obtain critical spinopelvic measurements automatically, which can be applied to clinical practice. This solution can assist physicians by saving time in routine work and by avoiding error-prone manual measurements.
The study design is retrospective, multi-surgeon, single-center review. The objective is to evaluate complication rates, revision rates, and accuracy grading for robotic-guided S2 alar-iliac (S2AI) screws. Sixty-five consecutive patients underwent S2AI fixation (118 screws) as part of a posterior spine fusion using robotic-guidance. Screws were placed percutaneously in 14 cases and 51 were placed in an open fashion by three board-certified spine surgeons using the Mazor core technology robotic systems (Mazor X, n = 42; Mazor XSE, n = 23). Medical charts were retrospectively reviewed for revisions and complications. All patients were followed for 90 days or greater. Postoperative CT scans were obtained in 22 of the 51 patients, allowing for 46 screws to be reviewed by an independent neuroradiologist who graded the screws for accuracy. There were no intraoperative or postoperative complications associated with S2AI screw placement. There were no revisions found to be related to the S2AI screw placement. All 46 screws evaluated with postoperative CT scans were reported as being at the highest level of accuracy, grade A, with a breach distance of 0 mm (no breach). The robotic-guided technique for S2AI screw placement is a reliable method to achieving pelvic fixation with low complication and revision rates. In addition, a high degree of accuracy can be achieved without relying on visible and tactile landmarks needed for the freehand technique or the additional radiation associated with fluoroscopic-guidance.
Introduction. Degenerative disc disease is a common cause of chronic low back pain. Surgical intervention is an invasive treatment associated with high costs. There is growing interest in regenerative medicine as a less invasive but direct disc treatment for chronic discogenic low back pain. Objective. To evaluate clinical improvement of primary discogenic low back pain with intradiscal injection of autologous bone marrow aspirate concentrate (BMAC). Study Design. Prospective cohort study. Setting. Single, multiphysician center. Patients. 32 adult patients undergoing intradiscal injection of autologous BMAC for the treatment of primary discogenic low back pain. Interventions. Intradiscal injection of autologous BMAC. Main Outcome Measures. Primary outcome measure is visual analog back pain scale (VAS back pain). Secondary outcome measures include ODI, VAS leg pain, and EQ-5D-5L scores. Outcomes were compared from baseline to 1 year. Results. Thirty-two patients (56.3% male) with a mean age of 45.9 years were enrolled, giving 92 treated levels. Mean VAS back and leg pain scores improved from 5.4 to 3.0 ( p < 0.001 ) and 2.8 to 1.3 ( p = 0.005 ), respectively. Mean ODI scores decreased from 33.5 to 21.1 ( p < 0.001 ), and EQ-5D-5L scores improved from 0.69 to 0.78 ( p = 0.001 ). Using established MCID values, 59.4% had clinically significant improvement in VAS back pain, 43.8% in VAS leg pain, and 56.3% in ODI scores. Conclusion. Intradiscal injection of autologous BMAC significantly improved low back pain, disability, and quality of life at one year. This study suggests that intradiscal BMAC has the potential to be an effective nonsurgical treatment for chronic discogenic low back pain.
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