Browsing by Subject "accuracy"
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Item Open Access Accuracy and efficiency of image-guided radiation therapy (IGRT) for preoperative partial breast radiosurgery.(Journal of radiosurgery and SBRT, 2020-01) Yoo, Sua; O'Daniel, Jennifer; Blitzblau, Rachel; Yin, Fang-Fang; Horton, Janet KObjective
To analyze and evaluate accuracy and efficiency of IGRT process for preoperative partial breast radiosurgery.Methods
Patients were initially setup with skin marks and 5 steps were performed: (1) Initial orthogonal 2D kV images, (2) pre-treatment 3D CBCT images, (3) verification orthogonal 2D kV images, (4) treatment including mid-treatment 2D kV images (for the final 15 patients only), and (5) post-treatment orthogonal 2D kV or 3D CBCT images. Patient position was corrected at each step to align the biopsy clip and to verify surrounding soft tissue positioning.Results
The mean combined vector magnitude shifts and standard deviations at the 5 imaging steps were (1) 0.96 ± 0.69, (2) 0.33 ± 0.40, (3) 0.05 ± 0.12, (4) 0.15 ± 0.17, and (5) 0.27 ± 0.24 in cm. The mean total IGRT time was 40.2 ± 13.2 minutes. Each step was shortened by 2 to 5 minutes with improvements implemented. Overall, improvements in the IGRT process reduced the mean total IGRT time by approximately 20 minutes. Clip visibility was improved by implementing oblique orthogonal images.Conclusion
Multiple imaging steps confirmed accurate patient positioning. Appropriate planning and imaging strategies improved the effectiveness and efficiency of the IGRT process for preoperative partial breast radiosurgery.Item Open Access Augmented Reality in Spine Surgery Narrative Review: Seeing is Believing(Operative Techniques in Orthopaedics, 2023-12-01) Charles, AJ; Luo, E; Arango, A; Rowe, D; Goodwin, CR; Erickson, MMIn recent years, augmented reality (AR) has emerged as a promising technology in spine surgery. Its benefits are numerous, including enhanced surgical accuracy, improved anatomic approximation, and uninterrupted visualization. It has proven particularly valuable in spinal fusion, allowing for meticulous planning of screw trajectories and precise alignment of screws, plates, and implants, resulting in low complication rates. Additionally, AR reduces radiation exposure by minimizing the need for intraoperative fluoroscopy. The technology has also been utilized for surgical education and training, enabling real-time feedback through telementoring. However, challenges exist. Discomfort and wearability issues are reported with current AR models, and the need for 3D image rendering prolongs procedure time. Accuracy is compromised in patients with larger body habitus, necessitating improvements in calibration to individual anatomies. Cost is another significant challenge as it requires advanced imaging capabilities in operating rooms, along with expenses for AR hardware, software, training, and personnel. Ongoing research is necessary to evaluate the sustained benefits and potential complications of AR in spine surgery. While AR demonstrates advantages in terms of patient outcomes and surgical accuracy, continued optimization is essential to enhance accessibility and success in spine surgery and orthopaedic surgery as a whole.Item Open Access Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study.(JMIR perioperative medicine, 2022-10) Bardia, Amit; Deshpande, Ranjit; Michel, George; Yanez, David; Dai, Feng; Pace, Nathan L; Schuster, Kevin; Mathis, Michael R; Kheterpal, Sachin; Schonberger, Robert BBackground
The automated acquisition of intraoperative patient temperature data via temperature probes leads to the possibility of producing a number of artifacts related to probe positioning that may impact these probes' utility for observational research.Objective
We sought to compare the performance of two de novo algorithms for filtering such artifacts.Methods
In this observational retrospective study, the intraoperative temperature data of adults who received general anesthesia for noncardiac surgery were extracted from the Multicenter Perioperative Outcomes Group registry. Two algorithms were developed and then compared to the reference standard-anesthesiologists' manual artifact detection process. Algorithm 1 (a slope-based algorithm) was based on the linear curve fit of 3 adjacent temperature data points. Algorithm 2 (an interval-based algorithm) assessed for time gaps between contiguous temperature recordings. Sensitivity and specificity values for artifact detection were calculated for each algorithm, as were mean temperatures and areas under the curve for hypothermia (temperatures below 36 C) for each patient, after artifact removal via each methodology.Results
A total of 27,683 temperature readings from 200 anesthetic records were analyzed. The overall agreement among the anesthesiologists was 92.1%. Both algorithms had high specificity but moderate sensitivity (specificity: 99.02% for algorithm 1 vs 99.54% for algorithm 2; sensitivity: 49.13% for algorithm 1 vs 37.72% for algorithm 2; F-score: 0.65 for algorithm 1 vs 0.55 for algorithm 2). The areas under the curve for time × hypothermic temperature and the mean temperatures recorded for each case after artifact removal were similar between the algorithms and the anesthesiologists.Conclusions
The tested algorithms provide an automated way to filter intraoperative temperature artifacts that closely approximates manual sorting by anesthesiologists. Our study provides evidence demonstrating the efficacy of highly generalizable artifact reduction algorithms that can be readily used by observational studies that rely on automated intraoperative data acquisition.