TY - JOUR
T1 - Demographics, Utilization, Workflow, and Outcomes Based on Observational Data From the RSNA-ACR 3D Printing Registry
AU - Wang, Kenneth C.
AU - Ryan, Justin R.
AU - Chepelev, Leonid
AU - Wake, Nicole
AU - Quigley, Edward P.
AU - Santiago, Lumarie
AU - Wentworth, Adam
AU - Alexander, Amy
AU - Morris, Jonathan M.
AU - Fleischmann, Dominik
AU - Ballard, David H.
AU - Ravi, Prashanth
AU - Hirsch, Jeffrey D.
AU - Sturgeon, Gregory M.
AU - Huang, Yu Hui
AU - Decker, Summer J.
AU - von Windheim, Natalia
AU - Pugliese, Robert S.
AU - Hidalgo, Ronald V.
AU - Patel, Pushpak
AU - Colon, Joseb
AU - Thieringer, Florian M.
AU - Rybicki, Frank J.
N1 - Publisher Copyright:
© 2024
PY - 2024/11
Y1 - 2024/11
N2 - Purpose: The aim of this study was to report data from the first 3 years of operation of the RSNA-ACR 3D Printing Registry. Methods: Data from June 2020 to June 2023 were extracted, including demographics, indications, workflow, and user assessments. Clinical indications were stratified by 12 organ systems. Imaging modalities, printing technologies, and numbers of parts per case were assessed. Effort data were analyzed, dividing staff members into provider and nonprovider categories. The opinions of clinical users were evaluated using a Likert scale questionnaire, and estimates of procedure time saved were collected. Results: A total of 20 sites and 2,637 cases were included, consisting of 1,863 anatomic models and 774 anatomic guides. Mean patient ages for models and guides were 42.4 ± 24.5 years and 56.3 ± 18.5 years, respectively. Cardiac models were the most common type of model (27.2%), and neurologic guides were the most common type of guide (42.4%). Material jetting, vat photopolymerization, and material extrusion were the most common printing technologies used overall (85.6% of all cases). On average, providers spent 92.4 min and nonproviders spent 335.0 min per case. Providers spent most time on consultation (33.6 min), while nonproviders focused most on segmentation (148.0 min). Confidence in treatment plans increased after using 3-D printing (P < .001). Estimated procedure time savings for 155 cases was 40.5 ± 26.1 min. Conclusions: Three-dimensional printing is performed at health care facilities for many clinical indications. The registry provides insight into the technologies and workflows used to create anatomic models and guides, and the data show clinical benefits from 3-D printing.
AB - Purpose: The aim of this study was to report data from the first 3 years of operation of the RSNA-ACR 3D Printing Registry. Methods: Data from June 2020 to June 2023 were extracted, including demographics, indications, workflow, and user assessments. Clinical indications were stratified by 12 organ systems. Imaging modalities, printing technologies, and numbers of parts per case were assessed. Effort data were analyzed, dividing staff members into provider and nonprovider categories. The opinions of clinical users were evaluated using a Likert scale questionnaire, and estimates of procedure time saved were collected. Results: A total of 20 sites and 2,637 cases were included, consisting of 1,863 anatomic models and 774 anatomic guides. Mean patient ages for models and guides were 42.4 ± 24.5 years and 56.3 ± 18.5 years, respectively. Cardiac models were the most common type of model (27.2%), and neurologic guides were the most common type of guide (42.4%). Material jetting, vat photopolymerization, and material extrusion were the most common printing technologies used overall (85.6% of all cases). On average, providers spent 92.4 min and nonproviders spent 335.0 min per case. Providers spent most time on consultation (33.6 min), while nonproviders focused most on segmentation (148.0 min). Confidence in treatment plans increased after using 3-D printing (P < .001). Estimated procedure time savings for 155 cases was 40.5 ± 26.1 min. Conclusions: Three-dimensional printing is performed at health care facilities for many clinical indications. The registry provides insight into the technologies and workflows used to create anatomic models and guides, and the data show clinical benefits from 3-D printing.
KW - 3-D printing
KW - anatomic guide
KW - anatomic model
KW - registry
UR - http://www.scopus.com/inward/record.url?scp=85203293793&partnerID=8YFLogxK
U2 - 10.1016/j.jacr.2024.07.019
DO - 10.1016/j.jacr.2024.07.019
M3 - Article
C2 - 39117182
AN - SCOPUS:85203293793
SN - 1546-1440
VL - 21
SP - 1781
EP - 1791
JO - Journal of the American College of Radiology
JF - Journal of the American College of Radiology
IS - 11
ER -