"Augmented reality" applications in urology: a systematic review

Synchronising a stereoscopic surgical video stream using specular reflection

PURPOSE

A stereoscopic surgical video stream consists of left-right image pairs provided by a stereo endoscope. While the surgical display shows these image pairs synchronised, most capture cards cause de-synchronisation. This means that the paired left and right images may not correspond once used in downstream tasks such as stereo depth computation. The stereo synchronisation problem is to recover the corresponding left-right images. This is particularly challenging in the surgical setting, owing to the moist tissues, rapid camera motion, quasi-staticity and real-time processing requirement. Existing methods exploit image cues from the diffuse reflection component and are defeated by the above challenges.

METHODS

We propose to exploit the specular reflection. Specifically, we propose a powerful left-right comparison score (LRCS) using the specular highlights commonly occurring on moist tissues. We detect the highlights using a neural network, characterise them with invariant descriptors, match them, and use the number of matches to form the proposed LRCS. We perform evaluation against 147 existing LRCS in 44 challenging robotic partial nephrectomy and robotic-assisted hepatic resection video sequences with simulated and real de-synchronisation.

RESULTS

The proposed LRCS outperforms, with an average and maximum offsets of 0.055 and 1 frames and 94.1±3.6% successfully synchronised frames. In contrast, the best existing LRCS achieves an average and maximum offsets of 0.3 and 3 frames and 81.2±6.4% successfully synchronised frames.

CONCLUSION

The use of specular reflection brings a tremendous boost to the real-time surgical stereo synchronisation problem.

The impact of positive surgical margin parameters and pathological stage on biochemical recurrence after radical prostatectomy: A systematic review and meta-analysis

BACKGROUND

To systematically review and perform a meta-analysis on the predictive value of the primary Gleason grade (PGG) at the positive surgical margin (PSM), length of PSM, number of PSMs, and pathological stage of the primary tumor on biochemical recurrence (BCR) in patients with prostate cancer (PCa) after radical prostatectomy (RP).

METHODS

A systematic literature search was performed using electronic databases, including PubMed, EMBASE, Cochrane Library, and Web of Science, from January 1, 2005, to October 1, 2023. The protocol was pre-registered in PROSPERO. Subgroup analyses were performed according to the different treatments and study outcomes. Pooled hazard ratios with 95% confidence intervals were extracted from multivariate analyses, and a fixed or random effect model was used to pool the estimates. Subgroup analyses were performed to explore the reasons for the heterogeneity.

RESULTS

Thirty-one studies that included 50,028 patients with PCa were eligible for this meta-analysis. The results showed that, compared to PGG3, PGG4/5 was associated with a significantly increased risk of BCR. Compared with PSM ≤3 mm, PSM ≥3 mm was associated with a significantly increased risk of BCR. Compared with unifocal PSM, multifocal PSM (mF-PSM) was associated with a significantly increased risk of BCR. In addition, pT >2 was associated with a significantly increased risk of BCR compared to pT2. Notably, the findings were found to be reliable based on the sensitivity and subgroup analyses.

CONCLUSIONS

PGG at the PSM, length of PSM, number of PSMs, and pathological stage of the primary tumor in patients with PCa were found to be associated with a significantly increased risk of BCR. Thus, patients with these factors should be treated differently in terms of receiving adjunct treatment and more frequent monitoring. Large-scale, well-designed prospective studies with longer follow-up periods are needed to validate the efficacy of these risk factors and their effects on patient responses to adjuvant and salvage therapies and other oncological outcomes.

Simulation-based learning in nephrology

Simulation is a technique to replace and amplify real experiences with guided ones that evoke or replicate substantial aspects of the real world in a fully interactive fashion. In nephrology (a particularly complex specialty), simulation can be used by patients, nurses, residents, and attending physicians alike. It allows one to learn techniques outside the stressful environment of care such as central venous catheter placement, arteriovenous fistula management, learning about peritoneal dialysis, or performing a kidney biopsy. Serious games and virtual reality are emerging methods that show promise. Simulation could also be important in relational aspects of working in a team or with the patient. The development of simulation as a teaching tool in nephrology allows for maintaining high-quality training for residents, tailored to their future practice, and minimizing risks for patients. Additionally, this education helps nephrologists maintain mastery of technical procedures, making the specialty attractive to younger generations. Unfortunately, the inclusion of simulation training programmes faces occasional logistical or funding limitations that universities must overcome with the assistance and innovation of teaching nephrologists. The impact of simulation-based teaching on clinical outcomes needs to be investigated in clinical studies.

The value of preoperative neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and red blood cell distribution width in predicting positive surgical margin after laparoscopic radical prostatectomy

BACKGROUND

Prostate cancer (PCa) is one of the most common malignant tumors in men, and laparoscopic radical prostatectomy (LRP) is commonly used to treat localized and advanced PCa. Positive surgical margin (PSM) is one of the most frequent problems faced by surgeons.

AIMS

This study aimed to explore the value of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and red blood cell distribution width (RDW) in predicting PSM after LRP.

METHODS AND RESULTS

Three hundred and twenty patients with PCa were admitted and underwent LRP in Beijing Chaoyang Hospital from January 2017 to June 2023. Patients were randomly divided into a training set (225 cases) and a validation set (95 cases) in a 7:3 ratio. NLR, PLR, and RDW were significantly higher in the PSM group than in the negative surgical margins (NSM) group. In addition, the NLR, PLR, and RDW values correlated with clinical T stage, Gleason score, and seminal vesicle invasion in the PSM group. In training set, ROC curve analysis revealed that the optimal cutoff values of NLR, PLR, and RDW for predicting postoperative PSM in PCa were 2.31, 115.40, and 12.85%, respectively. Multivariate Logistic regression analysis showed NLR and RDW were the clinical independent predictors. The area under the curve (AUC, 0.770, 95% CI 0.709-0.831) for postoperative PSM was the highest when a combination of the three parameters was used, with sensitivity and specificity of 62.5% and 85.2%, respectively. In validation set, the AUC values for NLR, PLR, RDW and the three markers combined were 0.708, 0.675, 0.723, and 0.780, respectively. Correlation analysis showed that in the PSM group, NLR was positively correlated with PLR and RDW, and PLR was positively correlated with RDW. By contrast, in the NSM group, a positive association was only found between NLR and PLR.

CONCLUSIONS

Higher preoperative NLR, PLR, and RDW values were associated with postoperative PSM. Additionally, the three markers combined may be useful to predict PSM.

Early introduction of simulation in the medical curriculum: the MedInTo perspective

Despite the increasing body of evidence supporting the use of simulation in medicine, a question remains: when should we introduce it into the medical school's curriculum? We present the experience and future perspectives of the MD program in Medicine and Surgery of University of Turin-MedInTo. Since its launch, MedInTo has been dedicated to integrating innovative teaching approaches at the early stages into the medical curriculum. Herewith, we describe a case-based approach for our activities, which includes the utilization of simulation for emergency medical care training for students and the integration of virtual and augmented reality technology. Dedicated surgical training activities using virtual-augmented reality and life-like simulator for students are also described.

Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy

OBJECTIVES

The research's purpose is to develop a software that automatically integrates and overlay 3D virtual models of kidneys harboring renal masses into the Da Vinci robotic console, assisting surgeon during the intervention.

INTRODUCTION

Precision medicine, especially in the field of minimally-invasive partial nephrectomy, aims to use 3D virtual models as a guidance for augmented reality robotic procedures. However, the co-registration process of the virtual images over the real operative field is performed manually.

METHODS

In this prospective study, two strategies for the automatic overlapping of the model over the real kidney were explored: the computer vision technology, leveraging the super-enhancement of the kidney allowed by the intraoperative injection of Indocyanine green for superimposition and the convolutional neural network technology, based on the processing of live images from the endoscope, after a training of the software on frames from prerecorded videos of the same surgery. The work-team, comprising a bioengineer, a software-developer and a surgeon, collaborated to create hyper-accuracy 3D models for automatic 3D-AR-guided RAPN. For each patient, demographic and clinical data were collected.

RESULTS

Two groups (group A for the first technology with 12 patients and group B for the second technology with 8 patients) were defined. They showed comparable preoperative and post-operative characteristics. Concerning the first technology the average co-registration time was 7 (3-11) seconds while in the case of the second technology 11 (6-13) seconds. No major intraoperative or postoperative complications were recorded. There were no differences in terms of functional outcomes between the groups at every time-point considered.

CONCLUSION

The first technology allowed a successful anchoring of the 3D model to the kidney, despite minimal manual refinements. The second technology improved kidney automatic detection without relying on indocyanine injection, resulting in better organ boundaries identification during tests. Further studies are needed to confirm this preliminary evidence.

Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy: A feasibility and accuracy study

Objective

To evaluate the accuracy of our new three-dimensional (3D) automatic augmented reality (AAR) system guided by artificial intelligence in the identification of tumour's location at the level of the preserved neurovascular bundle (NVB) at the end of the extirpative phase of nerve-sparing robot-assisted radical prostatectomy.

Methods

In this prospective study, we enrolled patients with prostate cancer (clinical stages cT1c-3, cN0, and cM0) with a positive index lesion at target biopsy, suspicious for capsular contact or extracapsular extension at preoperative multiparametric magnetic resonance imaging. Patients underwent robot-assisted radical prostatectomy at San Luigi Gonzaga Hospital (Orbassano, Turin, Italy), from December 2020 to December 2021. At the end of extirpative phase, thanks to our new AAR artificial intelligence driven system, the virtual prostate 3D model allowed to identify the tumour's location at the level of the preserved NVB and to perform a selective excisional biopsy, sparing the remaining portion of the bundle. Perioperative and postoperative data were evaluated, especially focusing on the positive surgical margin (PSM) rates, potency, continence recovery, and biochemical recurrence.

Results

Thirty-four patients were enrolled. In 15 (44.1%) cases, the target lesion was in contact with the prostatic capsule at multiparametric magnetic resonance imaging (Wheeler grade L2) while in 19 (55.9%) cases extracapsular extension was detected (Wheeler grade L3). 3D AAR guided biopsies were negative in all pathological tumour stage 2 (pT2) patients while they revealed the presence of cancer in 14 cases in the pT3 cohort (14/16; 87.5%). PSM rates were 0% and 7.1% in the pathological stages pT2 and pT3 (<3 mm, Gleason score 3), respectively.

Conclusion

With the proposed 3D AAR system, it is possible to correctly identify the lesion's location on the NVB in 87.5% of pT3 patients and perform a 3D-guided tailored nerve-sparing even in locally advanced diseases, without compromising the oncological safety in terms of PSM rates.

Evaluation of augmented reality technology in global urologic surgery

BACKGROUND

The COVID-19 pandemic drastically reduced opportunities for surgical skill sharing between high-income and low to middle-income countries. Augmented reality (AR) technology allows mentors in one country to virtually train a mentee in another country during surgical cases without international travel. We hypothesize that AR technology is an effective live surgical training and mentorship modality.

METHODS

Three senior urologic surgeons in the US and UK worked with four urologic surgeon trainees across the continent of Africa using AR systems. Trainers and trainees individually completed post-operative questionnaires evaluating their experience.

RESULTS

Trainees rated the quality of virtual training as equivalent to in-person training in 83% of cases (N = 5 of 6 responses). Trainers reported the technology's visual quality as "acceptable" in 67% of cases (N = 12 of 18 responses). The audiovisual capabilities of the technology had a "high" impact in the majority of the cases.

CONCLUSION

AR technology can effectively facilitate surgical training when in-person training is limited or unavailable.

Urology: a trip into metaverse

PURPOSE

Metaverse is becoming an alternative world in which technology and virtual experiences are mixed with real life, and it holds the promise of changing our way of living. Healthcare is already changing thanks to Metaverse and its numerous applications. In particular, Urology and urologic patients can benefit in many ways from Metaverse.

METHODS

A non-systematic literature review identified recently published studies dealing with Metaverse. The database used for this review was PubMed, and the identified studies served as the base for a narrative analysis of the literature that explored the use of Metaverse in Urology.

RESULTS

Virtual consultations can enhance access to care and reduce distance and costs, and pain management and rehabilitation can find an incredible support in virtual reality, reducing anxiety and stress and improving adherence to therapy. Metaverse has the biggest potential in urologic surgery, where it can revolutionize both surgery planning, with 3D modeling and virtual surgeries, and intraoperatively, with augmented reality and artificial intelligence. Med Schools can implement Metaverse in anatomy and surgery lectures, providing an immersive environment for learning, and residents can use this platform for learning in a safe space at their own pace. However, there are also potential challenges and ethical concerns associated with the use of the metaverse in healthcare.

CONCLUSIONS

This paper provides an overview of the concept of the metaverse, its potential applications, challenges, and opportunities, and discusses the implications of its development in Urology.

Study on the postoperative visual function recovery of children with concomitant exotropia based on an augmented reality plasticity model

Objective

This study aimed to investigate the clinical application effect of an augmented reality (AR) plasticity model on the postoperative visual function recovery of children with concomitant exotropia.

Methods

Between September 2019 and October 2021, 28 patients with concomitant exotropia who visited Shenzhen Children's Hospital (9 male and 19 female) were enrolled in this study. The average age of the patients was 6.4 ± 1.8 years. Postoperative rehabilitation training was conducted using a personalized AR binocular visual perception plasticity model developed based on the patient's examination results. After 1 month, 3 months, and 6 months of training, the patients returned to the hospital for examinations of perceptual eye position, static zero-order stereopsis, dynamic first-order fine stereopsis, and dynamic second-order coarse stereopsis to compare the changes in eye position control and stereovision function.

Results

After 6 months of eye position training, the horizontal perception eye position of the 28 patients was significantly lower than that before training. The difference in eye position at the first and third months compared with that before training was not statistically significant (1st month: z = -2.255, p = 0.024 > 0.017; 3rd month: z = -2.277, p = 0.023 > 0.017; 6th month: z = -3.051, p = 0.002 < 0.017). The difference in vertical perceptual eye position after training compared with that before training was not statistically significant (1st month: z = -0.252, p = 0.801 > 0.017; 3rd month: z = -1.189, p = 0.234 > 0.017; 6th month: z = -2.225, p = 0.026 > 0.017). The difference in 0.8-m static zero-order stereopsis before and after training was not statistically significant (1st month: z = -2.111, p = 0.035 > 0.017; 3rd month: z = -1.097, p = 0.273 > 0.017; 6th month: z = -1.653, p = 0.098 > 0.017). The 1.5-m static zero-order stereopsis was improved after 1 month, 3 months, and 6 months of training compared with that before training (1st month: z = -3.134, p = 0.002 < 0.017; 3rd month: z = -2.835, p = 0.005 < 0.017; 6th month: z = -3.096, p = 0.002 < 0.017). Dynamic first-order fine stereopsis and dynamic second-order coarse stereopsis were measured in the 28 patients before and after training. Patients 1 and 18 had no dynamic first-order fine stereopsis before training, but both regained dynamic stereopsis after 1 month, 3 months, and 6 months of training. Patient 16 had no dynamic first-order fine stereopsis or dynamic second-order coarse stereopsis before training, but first-order and second-order stereopsis had been reconstructed after 1 month, 3 months, and 6 months of training.

Conclusion

Concomitant exotropia surgery improved the basic problem of eye position at the ocular muscle level, but the patient's perceptual eye position and visual function defects at the brain visual level remained. This might partly explain the poor postoperative clinical effect. The AR plasticity model can improve patients' horizontal perceptual eye position and multi-dimensional stereoscopic function, and its clinical effect warrants further study.

Artificial Intelligence-Based Hyper Accuracy Three-Dimensional (HA3D®) Models in Surgical Planning of Challenging Robotic Nephron-Sparing Surgery: A Case Report and Snapshot of the State-of-the-Art with Possible Future Implications

Recently, 3D models (3DM) gained popularity in urology, especially in nephron-sparing interventions (NSI). Up to now, the application of artificial intelligence (AI) techniques alone does not allow us to obtain a 3DM adequate to plan a robot-assisted partial nephrectomy (RAPN). Integration of AI with computer vision algorithms seems promising as it allows to speed up the process. Herein, we present a 3DM realized with the integration of AI and a computer vision approach (CVA), displaying the utility of AI-based Hyper Accuracy Three-dimensional (HA3D^®) models in preoperative planning and intraoperative decision-making process of challenging robotic NSI. A 54-year-old Caucasian female with no past medical history was referred to the urologist for incidental detection of the right renal mass. Preoperative contrast-enhanced abdominal CT confirmed a 35 × 25 mm lesion on the anterior surface of the upper pole (PADUA 7), with no signs of distant metastasis. CT images in DICOM format were processed to obtain a HA3D^® model. RAPN was performed using Da Vinci Xi surgical system in a three-arm configuration. The enucleation strategy was achieved after selective clamping of the tumor-feeding artery. Overall operative time was 85 min (14 min of warm ischemia time). No intra-, peri- and post-operative complications were recorded. Histopathological examination revealed a ccRCC (stage pT1aNxMx). AI is breaking new ground in medical image analysis panorama, with enormous potential in organ/tissue classification and segmentation, thus obtaining 3DM automatically and repetitively. Realized with the integration of AI and CVA, the results of our 3DM were accurate as demonstrated during NSI, proving the potentialities of this approach for HA3D^® models' reconstruction.

Extended reality for procedural planning and guidance in structural heart disease - a review of the state-of-the-art

Extended reality (XR), which encompasses virtual, augmented and mixed reality, is an emerging medical imaging display platform which enables intuitive and immersive interaction in a three-dimensional space. This technology holds the potential to enhance understanding of complex spatial relationships when planning and guiding cardiac procedures in congenital and structural heart disease moving beyond conventional 2D and 3D image displays. A systematic review of the literature demonstrates a rapid increase in publications describing adoption of this technology. At least 33 XR systems have been described, with many demonstrating proof of concept, but with no specific mention of regulatory approval including some prospective studies. Validation remains limited, and true clinical benefit difficult to measure. This review describes and critically appraises the range of XR technologies and its applications for procedural planning and guidance in structural heart disease while discussing the challenges that need to be overcome in future studies to achieve safe and effective clinical adoption.

Health Information Technology Usability Evaluation Scale (Health-ITUES) and User-Experience Questionnaire (UEQ) for 3D Intraoperative Cognitive Navigation (ICON3DTM) System for Urological Procedures

Backgound and objectives: In recent years, the adoption of 3D models for surgical planning and intraoperative guidance has gained a wide diffusion. The aim of this study was to evaluate the surgeons' perception and usability of ICON3D^TM platform for robotic and laparoscopic urological surgical procedures. Materials and Methods: During the 10th edition of the Techno-Urology Meeting, surgeons and attendees had the opportunity to test the new ICON3D^TM platform. The capability of the user to manipulate the model with hands/mouse, the software usability, the quality of the 3D model's reproduction, and the quality of its use during the surgery were evaluated with the Health Information Technology Usability Evaluation Scale (Health-ITUES) and the User-Experience Questionnaire (UEQ). Results: Fifty-three participants responded to the questionnaires. Based on the answers to the Health-ITUES questionnaire, ICON3D^TM resulted to have a positive additional value in presurgical/surgical planning with 43.4% and 39.6% of responders that rated 4 (agree) and 5 (strongly agree), respectively. Regarding the UEQ questionnaire, both mouse and infrared hand-tracking system resulted to be easy to use for 99% of the responders, while the software resulted to be easy to use for 93.4% of the responders. Conclusions: In conclusion, ICON3D^TM has been widely appreciated by urologists thanks to its various applications, from preoperative planning to its support for intraoperative decision-making in both robot-assisted and laparoscopic settings.

Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery

Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instruments are clearly visible in AR. Superimposition of a 3D model on top of the surgical stream, including the instruments, can result in a potentially hazardous surgical situation. We demonstrate real-time instrument detection during AR-guided robot-assisted partial nephrectomy and show the generalization of our algorithm to AR-guided robot-assisted kidney transplantation. We developed an algorithm using deep learning networks to detect all nonorganic items. This algorithm learned to extract this information for 65 927 manually labeled instruments on 15 100 frames. Our setup, which runs on a standalone laptop, was deployed in three different hospitals and used by four different surgeons. Instrument detection is a simple and feasible way to enhance the safety of AR-guided surgery. Future investigations should strive to optimize efficient video processing to minimize the 0.5-s delay currently experienced. General AR applications also need further optimization, including detection and tracking of organ deformation, for full clinical implementation.

A survey of augmented reality methods to guide minimally invasive partial nephrectomy

INTRODUCTION

Minimally invasive partial nephrectomy (MIPN) has become the standard of care for localized kidney tumors over the past decade. The characteristics of each tumor, in particular its size and relationship with the excretory tract and vessels, allow one to judge its complexity and to attempt predicting the risk of complications. The recent development of virtual 3D model reconstruction and computer vision has opened the way to image-guided surgery and augmented reality (AR).

OBJECTIVE

Our objective was to perform a systematic review to list and describe the different AR techniques proposed to support PN.

MATERIALS AND METHODS

The systematic review of the literature was performed on 12/04/22, using the keywords "nephrectomy" and "augmented reality" on Embase and Medline. Articles were considered if they reported surgical outcomes when using AR with virtual image overlay on real vision, during ex vivo or in vivo MIPN. We classified them according to the registration technique they use.

RESULTS

We found 16 articles describing an AR technique during MIPN procedures that met the eligibility criteria. A moderate to high risk of bias was recorded for all the studies. We classified registration methods into three main families, of which the most promising one seems to be surface-based registration.

CONCLUSION

Despite promising results, there do not exist studies showing an improvement in clinical outcomes using AR. The ideal AR technique is probably yet to be established, as several designs are still being actively explored. More clinical data will be required to establish the potential contribution of this technology to MIPN.

Three-dimensional Model-assisted Minimally Invasive Partial Nephrectomy: A Systematic Review with Meta-analysis of Comparative Studies

CONTEXT

Use of three-dimensional (3D) guidance for nephron-sparing surgery (NSS) has increased in popularity, especially for laparoscopic and robotic approaches. Different 3D visualization modalities have been developed as promising new tools for surgical planning and intraoperative navigation.

OBJECTIVES

To summarize and evaluate the impact of 3D models on minimally invasive NSS in terms of perioperative, functional, and oncological outcomes.

EVIDENCE ACQUISITION

A systematic literature search was conducted in December 2021 using the Medline (PubMed), Embase (Ovid), Scopus, and Web of Science databases. The protocol was registered on PROSPERO (CRD42022300948). The search strategy used the PICOS (Population, Intervention, Comparison, Outcome, Study design) criteria and article selection was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias and the quality of the articles included were assessed. A dedicated data extraction form was used to collect the data of interest. Meta-analysis was performed using the Mantel-Haenszel method for binary outcomes, with results summarized as the odds ratio (OR), and the inverse variance method for continuous data, with results reported as the mean difference (MD). All effect estimates are reported with the 95% confidence interval (CI) and p ≤ 0.05 was considered statistically significant. All analyses were performed using R software and the meta package.

EVIDENCE SYNTHESIS

The initial electronic search identified 450 papers, of which 17 met the inclusion criteria and were included in the analysis. Use of 3D technology led to a significant reduction in the global ischemia rate (OR 0.22, 95% CI 0.07-0.76; p = 0.02) and facilitated more frequent enucleation (OR 2.54, 95% CI 1.36-4.74; p < 0.01) and less frequent opening of the collecting system (OR 0.36, 95% CI 0.15-0.89; p = 0.03) and was associated with less blood loss (MD 23.1 ml, 95% CI 31.8-14.4; p < 0.01). 3D guidance for NSS was associated with a significant reduction in the transfusion rate (OR 0.20, 95% CI 0.07-0.56; p < 0.01). There were no significant differences in rates of conversion to radical nephrectomy, minor and major complications, change in glomerular filtration rate, or surgical margins (all p > 0.05).

CONCLUSIONS

3D guidance for NSS is associated with lower rates of detriment and surgical injury to the kidney. Specifically, a lower amount of nontumor renal parenchyma is exposed to ischemia or sacrificed during resection, and opening of the collecting system is less frequent. However, use of 3D technology does not lead to significant improvements in oncological or functional outcomes.

PATIENT SUMMARY

We reviewed the use of three-dimensional tools for minimally invasive surgery for partial removal of the kidney in patients with kidney cancer. The evidence suggests that these tools have benefits during surgery, but do not lead to significant improvements in cancer control or functional outcomes for patients.

Performance and Usability Evaluation of an Extended Reality Platform to Monitor Patient’s Health during Surgical Procedures

An extended-reality (XR) platform for real-time monitoring of patients’ health during surgical procedures is proposed. The proposed system provides real-time access to a comprehensive set of patients’ information, which are made promptly available to the surgical team in the operating room (OR). In particular, the XR platform supports the medical staff by automatically acquiring the patient’s vitals from the operating room instrumentation and displaying them in real-time directly on an XR headset. Furthermore, information regarding the patient clinical record is also shown upon request. Finally, the XR-based monitoring platform also allows displaying in XR the video stream coming directly from the endoscope. The innovative aspect of the proposed XR-based monitoring platform lies in the comprehensiveness of the available information, in its modularity and flexibility (in terms of adaption to different sources of data), ease of use, and most importantly, in a reliable communication, which are critical requirements for the healthcare field. To validate the proposed system, experimental tests were conducted using instrumentation typically available in the operating room (i.e., a respiratory ventilator, a patient monitor for intensive care, and an endoscope). The overall results showed (i) an accuracy of the data communication greater than 99 %, along with (ii) an average time response below ms, and (iii) satisfying feedback from the SUS questionnaires filled out by the physicians after intensive use.