SIR 2024
Office-based Procedures
Laetitia Saccenti, MD (she/her/hers)
Research Fellow
National Institutes of Health
Financial relationships: Full list of relationships is listed on the CME information page.
Tabea Borde, MD, PhD
Clinical Research Fellow
National Institutes of Health
Financial relationships: Full list of relationships is listed on the CME information page.
Hannah Huth, BA
Research Fellow
Center for Interventional Oncology, Radiology, and Imaging Sciences, NIH Clinical Center, NIH, Bethesda, MD, USA
Financial relationships: Full list of relationships is listed on the CME information page.
Lindsey Hazen, Clinical Nurse
Clinical Research Nurse
National Institutes of Health
Disclosure information not submitted.
Sheng Xu, PhD
Staff Scientist
National Institutes of Health Clinical Center
Financial relationships: Full list of relationships is listed on the CME information page.
Ifechi Ukeh, MD
Deputy Chief, Interventional Radiology
National Institutes of Health
Financial relationships: Full list of relationships is listed on the CME information page.
Cali Lubrant, MD
IR staff
National Institutes of Health Clinical Center
Disclosure information not submitted.
Keith M. Horton, MD, RPVI, FSIR (he/him/his)
Associate Professor of Radiology
MedStar Washington Hospital Center/ Georgetown University School of Medicine
Disclosure information not submitted.
Vania Tacher
Disclosure information not submitted.
Bradford J. Wood, MD, FSIR
Director NIH Center for IO, Chief IR
NIH
Financial relationships: Full list of relationships is listed on the CME information page.
To evaluate the accuracy of percutaneous needle insertions using an integrated 3D printed needle-guide for smartphone augmented reality (AR) application
Materials and Methods:
A smartphone cover with an integrated needle guide was designed and custom 3D printed. An AR application for percutaneous needle placement was developed. The fixed needle guide on the smartphone provided a projected needle path, which was implemented and visible in the application. This tool provides the operator the ability to plan the needle path at the patient's bedside and insert the needle along a fixed path with the assistance of the needle fixture and a registration process.
To assess the needle placement accuracy, an abdominal phantom (CIRS 057A) was loaded in “3D slicer” from a previously acquired CT scan. The segmentations of the anatomy and targets were projected through the AR application and registered via fiducial. Two interventional radiologists in training performed 10 punctures of 5 targets with defined entry points, with a 17G needle, using the smartphone needle guide first (n=5) and followed by a free-hand approach without hardware assistance (n=5). Placement accuracy, the distance from needle tip to target center, was evaluated on a post-procedural cone beam CT. Planning time and puncture time were recorded. Results were compared using paired t-tests in R (v.4.3.1).
Results: The mean placement accuracy using the smartphone needle guide was 9.1mm ± 5.1mm, which demonstrated greater accuracy than free-hand (15.4mm ± 5.9mm, p=0.03). Using the smartphone needle guide, the mean planning time was 138s ± 76s, and the mean puncture time was 32s ± 11s. No difference was found when compared to free-hand planning time (107s ± 73s, p=0.46) or free-hand puncture time (19s ± 14s, p=0.09)
Conclusion: An integrated custom smartphone case needle holder with augmented reality application tool demonstrated that needle punctures in a phantom had an accuracy of 9.1mm and were feasible in less than 3 minutes. Preliminary results showed this may be more accurate than a free-hand approach. Future studies will characterize this novel bedside low-resource approach to include more operators, learning curve analysis, and comparison to ultrasound guidance