Sheng Xu1, Venkatesh Krishnasamy1, Elliot Levy1, Ming Li1, Zion Tsz Ho Tse2, Bradford John Wood1. 1. 1 Department of Radiology and Imaging Sciences, National Institutes of Health, Clinical Center, 9000 Rockville Pike, Bldg 10, Rm 1C351, Bethesda, MD 20892. 2. 2 Medical Robotics Laboratory, University of Georgia, College of Engineering, Athens, GA.
Abstract
OBJECTIVE: In CT-guided intervention, translation from a planned needle insertion angle to the actual insertion angle is estimated only with the physician's visuospatial abilities. An iPhone app was developed to reduce reliance on operator ability to estimate and reproduce angles. MATERIALS AND METHODS: The iPhone app overlays the planned angle on the smartphone's camera display in real-time based on the smartphone's orientation. The needle's angle is selected by visually comparing the actual needle with the guideline in the display. If the smartphone's screen is perpendicular to the planned path, the smartphone shows the Bull's-Eye View mode, in which the angle is selected after the needle's hub overlaps the tip in the camera. In phantom studies, we evaluated the accuracies of the hardware, the Guideline mode, and the Bull's-Eye View mode and showed the app's clinical efficacy. A proof-of-concept clinical case was also performed. RESULTS: The hardware accuracy was 0.37° ± 0.27° (mean ± SD). The mean error and navigation time were 1.0° ± 0.9° and 8.7 ± 2.3 seconds for a senior radiologist with 25 years' experience and 1.5° ± 1.3° and 8.0 ± 1.6 seconds for a junior radiologist with 4 years' experience. The accuracy of the Bull's-Eye View mode was 2.9° ± 1.1°. Combined CT and smart-phone guidance was significantly more accurate than CT-only guidance for the first needle pass (p = 0.046), which led to a smaller final targeting error (mean distance from needle tip to target, 2.5 vs 7.9 mm). CONCLUSION: Mobile devices can be useful for guiding needle-based interventions. The hardware is low cost and widely available. The method is accurate, effective, and easy to implement.
OBJECTIVE: In CT-guided intervention, translation from a planned needle insertion angle to the actual insertion angle is estimated only with the physician's visuospatial abilities. An iPhone app was developed to reduce reliance on operator ability to estimate and reproduce angles. MATERIALS AND METHODS: The iPhone app overlays the planned angle on the smartphone's camera display in real-time based on the smartphone's orientation. The needle's angle is selected by visually comparing the actual needle with the guideline in the display. If the smartphone's screen is perpendicular to the planned path, the smartphone shows the Bull's-Eye View mode, in which the angle is selected after the needle's hub overlaps the tip in the camera. In phantom studies, we evaluated the accuracies of the hardware, the Guideline mode, and the Bull's-Eye View mode and showed the app's clinical efficacy. A proof-of-concept clinical case was also performed. RESULTS: The hardware accuracy was 0.37° ± 0.27° (mean ± SD). The mean error and navigation time were 1.0° ± 0.9° and 8.7 ± 2.3 seconds for a senior radiologist with 25 years' experience and 1.5° ± 1.3° and 8.0 ± 1.6 seconds for a junior radiologist with 4 years' experience. The accuracy of the Bull's-Eye View mode was 2.9° ± 1.1°. Combined CT and smart-phone guidance was significantly more accurate than CT-only guidance for the first needle pass (p = 0.046), which led to a smaller final targeting error (mean distance from needle tip to target, 2.5 vs 7.9 mm). CONCLUSION: Mobile devices can be useful for guiding needle-based interventions. The hardware is low cost and widely available. The method is accurate, effective, and easy to implement.
Authors: Rachel Hecht; Ming Li; Quirina M B de Ruiter; William F Pritchard; Xiaobai Li; Venkatesh Krishnasamy; Wael Saad; John W Karanian; Bradford J Wood Journal: Cardiovasc Intervent Radiol Date: 2020-01-08 Impact factor: 2.740