Diagnostic Performance of a Next-Generation Virtual/Augmented Reality Headset: A Pilot Study of Diverticulitis on CT

Next-generation virtual/augmented reality (VR/AR) headsets may rival the desktop computer systems that are approved for clinical interpretation of radiologic images, but require validation for high-resolution low-luminance diagnoses like diverticulitis. The primary aim of this study is to compare diagnostic performance for detecting diverticulitis on CT between radiologists using a headset versus a desktop. The secondary aim is to survey participating radiologists about the usage of both devices. This pilot study retrospectively included 110 patients (mean age 64 ± 14 years, 62 women) who had abdomen/pelvis CT scans for which the report mentioned the presence or absence of diverticulitis. Scans were dichotomized and matched by time, for a total of 55 cases with diverticulitis and 55 controls with no diverticulitis. Six radiologists were oriented to the VR/AR headset (Apple Vision Pro) and viewer app (Visage Ease VP) using ten scans. They each scored 100 unknown scans on a 6-level scale for diverticulitis (1 = no diverticulitis, 6 = diverticulitis) on the headset and then on a desktop. Time per case was recorded. Finally, they completed a survey using 5-level scales about the ease of use of the headset and viewer app (1 = difficult, 5 = easy), about their experience with the headset (1 = bad, 5 = good), and about their preference between devices (1 = desktop, 5 = headset). Summary statistics and multi-reader multi-case ROC curves were calculated. The AUC (and 95% confidence interval) for diverticulitis was 0.93 (0.88-0.97) with the headset and 0.94 (0.91-0.98) with the desktop (p = 0.40). The median (and first-third quartiles) of time per case was 57 (41-76) seconds for the headset and 31 (22-64) seconds for the desktop (p < 0.001). Average survey scores ranged from 3.3 to 5 for ease of use, from 3 to 4.7 for experience, and from 2.2 to 3.3 for preference. Diagnostic performance for detecting diverticulitis on CT was similar between the next-generation VR/AR headset and desktop. Ease of use, experience, and preference varied across different aspects of the devices and among radiologists.

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Publication Details

Journal
Journal of Imaging Informatics in Medicine
Published
2024-11-04
DOI
https://doi.org/10.1007/s10278-024-01292-7
Citations
2
Primary Topic
Diverticular Disease and Complications
Type
article
Field-Weighted Citation Impact
1.15

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article

Diagnostic Performance of a Next-Generation Virtual/Augmented Reality Headset: A Pilot Study of Diverticulitis on CT

Julie Y. An, Luke Wojdyla, P. Murphy, Kathryn J. Fowler et al.
2 citations
Journal of Imaging Informatics in Medicine
Diverticular Disease and Complications
1.15
article

Diagnostic Performance of a Next-Generation Virtual/Augmented Reality Headset: A Pilot Study of Diverticulitis on CT

Julie Y. An, Luke Wojdyla, P. Murphy, Kathryn J. Fowler, Aman Khurana, Chris Longhurst, Thomas W. Loehfelm, Adam C. Searleman
article en
2 citations

Abstract

Next-generation virtual/augmented reality (VR/AR) headsets may rival the desktop computer systems that are approved for clinical interpretation of radiologic images, but require validation for high-resolution low-luminance diagnoses like diverticulitis. The primary aim of this study is to compare diagnostic performance for detecting diverticulitis on CT between radiologists using a headset versus a desktop. The secondary aim is to survey participating radiologists about the usage of both devices. This pilot study retrospectively included 110 patients (mean age 64 ± 14 years, 62 women) who had abdomen/pelvis CT scans for which the report mentioned the presence or absence of diverticulitis. Scans were dichotomized and matched by time, for a total of 55 cases with diverticulitis and 55 controls with no diverticulitis. Six radiologists were oriented to the VR/AR headset (Apple Vision Pro) and viewer app (Visage Ease VP) using ten scans. They each scored 100 unknown scans on a 6-level scale for diverticulitis (1 = no diverticulitis, 6 = diverticulitis) on the headset and then on a desktop. Time per case was recorded. Finally, they completed a survey using 5-level scales about the ease of use of the headset and viewer app (1 = difficult, 5 = easy), about their experience with the headset (1 = bad, 5 = good), and about their preference between devices (1 = desktop, 5 = headset). Summary statistics and multi-reader multi-case ROC curves were calculated. The AUC (and 95% confidence interval) for diverticulitis was 0.93 (0.88-0.97) with the headset and 0.94 (0.91-0.98) with the desktop (p = 0.40). The median (and first-third quartiles) of time per case was 57 (41-76) seconds for the headset and 31 (22-64) seconds for the desktop (p < 0.001). Average survey scores ranged from 3.3 to 5 for ease of use, from 3 to 4.7 for experience, and from 2.2 to 3.3 for preference. Diagnostic performance for detecting diverticulitis on CT was similar between the next-generation VR/AR headset and desktop. Ease of use, experience, and preference varied across different aspects of the devices and among radiologists.

Journal of Imaging Informatics in MedicineVol. 38(5)
University of San Diego (US), UC San Diego Health System (US), University of California San Diego (US)
University of California, San Diego
Openalex Percentile: Top 20%
Diverticular Disease and Complications
1.15
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