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Application of IRIS Three-Dimensional Anatomical Models As Preoperative Surgical Planning Tools in the Management of
Pratik M S Gurung1, Rachel Melnyk2, Tyler Holler2
1Department of Urology, University of Rochester Medical Center, Rochester, New York, USA.
Abstract:
The use of volume-rendered images is gaining popularity in the surgical planning for complex procedures. IRIS™ is an interactive software that delivers three-dimensional (3D) virtual anatomical models. We aimed to evaluate the preoperative clinical utility of IRIS for patients with ≤T2 localized renal tumors who underwent either partial nephrectomy (PN) or radical nephrectomy (RN). Six urologists (four faculty and two trainees) reviewed CT scans of 40 cases over 2 study phases, using conventional two-dimensional (2D) CT alone (Phase-I), followed by the CT + IRIS 3D model (Phase-II). After each review, surgeons reported their decision on performing a PN or an RN and rated (Likert scale) their confidence in completing the procedure as well as how the imaging modality influenced specific procedural decisions. Modifications to the choice of procedure and confidence in decisions between both phases were compared for the same surgeon. Concordance between surgeons was also evaluated. A total of 462 reviews were included in the analysis (231 in each phase). In 64% (95% CI: 58-70%) of reviews, surgeons reported that IRIS achieved a better spatial orientation, understanding of the anatomy, and offered additional information compared with 2D CT alone. IRIS impacted the planned procedure in 20% of the reviews (3.5% changed decision from PN to RN and 16.5% changed from RN to PN). In the remaining 80% of reviews, surgeons' confidence increased from 78% (95% CI: 72-84%) with 2D CT, to 87% (95% CI: 82-92%) with IRIS (p = 0.02); this confidence change was more pronounced in cases with a high RENAL score (p = 0.009). In 99% of the reviews, surgeons rated that the IRIS accurately represented the anatomical details of all kidney components. Application of IRIS 3D models could influence the surgical decision-making process and improve surgeons' confidence, especially for robot-assisted management of complex renal tumors.
