Anant Bs Tewari
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Anant Bs Tewari has a total of 19 co-authors. Here are the top co-authors by number of shared publications:
- Braden Miller
Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA 22903, USA
1 shared publication - Christopher R. Good
Virginia Spine Institute
1 shared publication - Colin M. Haines
Department of Surgery, Virginia Spine Institute, Reston, VA, USA
1 shared publication - David A. Boyd
Antimicrobial Resistance & Nosocomial Infections, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
1 shared publication - David Moore
Focused Ultrasound Foundation, Charlottesville, VA 22903, USA
1 shared publication - Ehsan Jazini
Department of Surgery, Virginia Spine Institute, Reston, VA, USA
1 shared publication
Latest Publications
- 5 February 2025
- Published by Wolters Kluwer Health in Clinical Orthopaedics and Related Research
- Vol. 483 (5) , 808-819
CORR Synthesis: What Is the Impact of Frailty on Postoperative Complications After Spinal Surgery?
- 5 February 2025
- Published by Wolters Kluwer Health in Clinical Orthopaedics and Related Research
- Vol. 483 (5) , 808-819
CORR Synthesis: What Is the Impact of Frailty on Postoperative Complications After Spinal Surgery?
- Open Access
- 23 October 2024
- Published by University of St. Augustine for Health Sciences Library in Journal of Innovation in Health Sciences Education
- Vol. 1 (3) , 34-48
The Four Domains Model of Artificial Intelligence in Surgical Education: Adapting Applications to Trainee Level
Since the inception of modern medicine, surgical trainees have benefitted from coaching and feedback from senior surgeons. In the high-demand operating room environment, granular feedback is often limited by time constraints. Artificial intelligence (AI) represents a novel frontier in surgical education in that it may be able to provide reliable, objective, and comprehensive feedback in an automated manner. While prior studies have given broad overviews of AI in surgical training, there has been no study to our knowledge that has codified the myriad applications and offered guidance for which applications best suit trainees at various levels of surgical education. We aim to describe four key domains under which surgical training AI applications can be classified. We define which applications would best suit junior, intermediate, and experienced surgeons by matching their educational needs. The four domains include: enhanced simulation (realistic and safe training environment), real time visual cues (guidance
- 23 October 2024
- Published by University of St. Augustine for Health Sciences Library in Journal of Innovation in Health Sciences Education
- Vol. 1 (3) , 34-48
Open AccessThe Four Domains Model of Artificial Intelligence in Surgical Education: Adapting Applications to Trainee Level
Since the inception of modern medicine, surgical trainees have benefitted from coaching and feedback from senior surgeons. In the high-demand operating room environment, granular feedback is often limited by time constraints. Artificial intelligence (AI) represents a novel frontier in surgical education in that it may be able to provide reliable, objective, and comprehensive feedback in an automated manner. While prior studies have given broad overviews of AI in surgical training, there has been no study to our knowledge that has codified the myriad applications and offered guidance for which applications best suit trainees at various levels of surgical education. We aim to describe four key domains under which surgical training AI applications can be classified. We define which applications would best suit junior, intermediate, and experienced surgeons by matching their educational needs. The four domains include: enhanced simulation (realistic and safe training environment), real time visual cues (guidance
- Open Access
- 6 April 2024
- Published by MDPI AG in Tomography
- Vol. 10 (4) , 533-542
Transcutaneous Ablation of Lung Tissue in a Porcine Model Using Magnetic-Resonance-Guided Focused Ultrasound (MRgFUS)
Focused ultrasound (FUS) is a minimally invasive treatment that utilizes high-energy ultrasound waves to thermally ablate tissue. Magnetic resonance imaging (MRI) guidance may be combined with FUS (MRgFUS) to increase its accuracy and has been proposed for lung tumor ablation/debulking. However, the lungs are predominantly filled with air, which attenuates the strength of the FUS beam. This investigation aimed to test the feasibility of a new approach using an intentional lung collapse to reduce the amount of air inside the lung and a controlled hydrothorax to create an acoustic window for transcutaneous MRgFUS lung ablation. Eleven pigs had one lung mechanically ventilated while the other lung underwent a controlled collapse and subsequent hydrothorax of that hemisphere. The MRgFUS lung ablations were then conducted via the intercostal space. All the animals recovered well and remained healthy in the week following the FUS treatment. The location and size of the ablations were confirmed one week post-treatment via MRI, necropsy, and histological analysis. The animals had almost no side effects and the skin burns were completely eliminated after the first two animal studies, following technique refinement. This study introduces a novel methodology of MRgFUS that can be used to treat deep lung parenchyma in a safe and viable manner.
- 6 April 2024
- Published by MDPI AG in Tomography
- Vol. 10 (4) , 533-542
Open AccessTranscutaneous Ablation of Lung Tissue in a Porcine Model Using Magnetic-Resonance-Guided Focused Ultrasound (MRgFUS)
Focused ultrasound (FUS) is a minimally invasive treatment that utilizes high-energy ultrasound waves to thermally ablate tissue. Magnetic resonance imaging (MRI) guidance may be combined with FUS (MRgFUS) to increase its accuracy and has been proposed for lung tumor ablation/debulking. However, the lungs are predominantly filled with air, which attenuates the strength of the FUS beam. This investigation aimed to test the feasibility of a new approach using an intentional lung collapse to reduce the amount of air inside the lung and a controlled hydrothorax to create an acoustic window for transcutaneous MRgFUS lung ablation. Eleven pigs had one lung mechanically ventilated while the other lung underwent a controlled collapse and subsequent hydrothorax of that hemisphere. The MRgFUS lung ablations were then conducted via the intercostal space. All the animals recovered well and remained healthy in the week following the FUS treatment. The location and size of the ablations were confirmed one week post-treatment via MRI, necropsy, and histological analysis. The animals had almost no side effects and the skin burns were completely eliminated after the first two animal studies, following technique refinement. This study introduces a novel methodology of MRgFUS that can be used to treat deep lung parenchyma in a safe and viable manner.
- Open Access
- 10 January 2022
- Published by SAGE Publications in Global Spine Journal
- Vol. 13 (7) , 2047-2052
Augmented Reality-Assisted Spine Surgery: An Early Experience Demonstrating Safety and Accuracy with 218 Screws
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.
- 10 January 2022
- Published by SAGE Publications in Global Spine Journal
- Vol. 13 (7) , 2047-2052
Open AccessAugmented Reality-Assisted Spine Surgery: An Early Experience Demonstrating Safety and Accuracy with 218 Screws
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.