Analyzing National Incidences and Predictors of Open Conversion During Minimally Invasive Partial Nephrectomy for cT1 Renal Masses

Klein, Geraldine T.; Wang, Hanzhang; Elshabrawy, Ahmed; Nashawi, Mouhamed; Gourley, Eric; Liss, Michael A.; Kaushik, Dharam; Wu, Shenghui; Rodríguez, Ronald; Mansour, Ahmed M.

doi:10.1089/end.2020.0161

Cited by 6 publications

(1 citation statement)

References 38 publications

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“…Over the decades, various technological innovations have been developed to improve oncological outcomes in laparoscopic and robotic surgery, particularly focused at enhanced intraoperative tumor visualization such as 3D laparoscopic surgery, use of artificial intelligence (AI) based software, deep learning 3D model reconstructions, augmented reality (AR), virtual reality (VR), and mixed reality (MR). The latter is an emerging technology different from virtual and augmented realities as herein it overlays virtual objects that can be manipulated whilst still being anchored to the physical environment [ 13 ]. Usually, creation of AR and MR anatomical models needs dedicated staff such as bioengineers and graphic designers, which may be a real obstacle to the widespread use of these technologies.…”

Section: Introductionmentioning

confidence: 99%

Role and Utility of Mixed Reality Technology in Laparoscopic Partial Nephrectomy: Outcomes of a Prospective RCT Using an Indigenously Developed Software

Gadzhiev

Semenyakin

Morshnev

et al. 2022

Advances in Urology

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Objective. To develop a software for mixed reality (MR) anatomical model creation and study its intraoperative clinical utility to facilitate laparoscopic partial nephrectomy. Materials and Methods. After institutional review board approval, 47 patients were prospectively randomized for LPN into two groups: the control group (24 patients) underwent operation with an intraoperative ultrasound (US) control and the experimental group (23 patients) with smart glasses HoloLens 2 (Microsoft, Seattle, WA, USA). Our team has developed an open-source software package called “HLOIA,” utilization of which allowed to create and use during surgery the MR anatomical model of the kidney with its vascular pedicle and tumor. The study period extended from June 2020 to February 2021 where demographic, perioperative, and pathological data were collected for all qualifying patients. The objective was to assess the utility of a MR model during LPN and through a 5-point Likert scale questionnaire, completed by the surgeon, immediately after LPN. Patient characteristics were tested using the chi-square test for categorical variables and Student’s t-test or Mann–Whitney test for continuous variables. Results. Comparison of the variables between the groups revealed statistically significant differences only in the following parameters: the time for renal pedicle exposure and the time from the renal pedicle to the detection of tumor localization ( p < 0.001 ), which were in favor of the experimental group. The surgeon’s impression of the utility of the MR model by the proposed questionnaire demonstrated high scores in all statements. Conclusions. Developed open-source software “HLOIA” allowed to create the mixed reality anatomical model by operating urologist which is when used with smart glasses has shown improvement in terms of time for renal pedicle exposure and time for renal tumor identification without compromising safety.

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Section: Introductionmentioning

confidence: 99%