Schwenderling L, Heinrich F, Hansen C. Augmented reality visualization of automated path planning for percutaneous interventions: a phantom study.
Int J Comput Assist Radiol Surg 2022;
17:2071-2079. [PMID:
35737284 PMCID:
PMC9515049 DOI:
10.1007/s11548-022-02690-4]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/25/2022] [Indexed: 11/24/2022]
Abstract
PURPOSE
Insertion point identification is a major challenge for percutaneous interventions. Planning in 2D slice image data is time-consuming and inefficient. Automated path planning can help to overcome these challenges. However, the setup of the intervention room is difficult to consider. In addition, transferring the insertion point to the skin is often prone to error. Therefore, a visualization for an automated path planning was implemented.
METHODS
A condition-based automated path planning was calculated with path length, distance to risk structures and insertion angle. The results were displayed on a phantom using projector-based augmented reality (AR) with an access point selection using the insertion needle. Two variants of the insertion visualization and three target displays were evaluated in a user study.
RESULTS
A visualization of insertion points with a representation of the path quality resulted in a choice of safer paths, compared with no insertion point display or no coding of the path quality. A representation of the target was preferred in the final survey, but did not perform better. A target display separate from the insertion point visualization reduced interferences between visualizations.
CONCLUSION
A projector-based AR visualization of automated path planning results supports insertion point identification for percutaneous interventions. A display of the path quality enables the choice of safe access paths especially for unexperienced users. Further research is needed to identify clinical benefits and applicability.
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