Augmented Reality to Guide Selective Clamping and Tumor Dissection During Robot-assisted Partial Nephrectomy: A Preliminary Experience

Schiavina, Riccardo; Bianchi, Lorenzo; Chessa, F.; Barbaresi, U.; Cercenelli, Laura; Lodi, Simone; Gaudiano, Caterina; Bortolani, Barbara; Angiolini, A.; Bianchi, Federico; Ercolino, Amelio; Casablanca, Carlo; Molinaroli, Enrico; Porreca, Angelo; Golfieri, Rita; Diciotti, Stefano; Marcelli, Emanuela; Brunocilla, Eugenio

doi:10.1016/j.clgc.2020.09.005

Cited by 38 publications

(20 citation statements)

References 29 publications

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“…Mean operating times and blood loss in this study were 110 min and 180 ml, respectively, similar to those reported in a case series by Schiavina et al. in which, amongst 15 patients, they were 135 min and 140 ml 84 …”

Section: Resultssupporting

confidence: 90%

The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review

Bollen

Awad

Langridge

et al. 2022

Robotics Computer Surgery

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Background This systematic review aims to critically appraise the intraoperative use of augmented and mixed reality technology to improve surgical outcomes. Method A literature search of PubMed, Scopus, Cochrane Central Register of Controlled Trials, http://ClinicalTrials.gov and WHO ICTRP was performed in accordance with Cochrane Handbook for Systematic Reviews of Interventions. Results This review included 94 studies on 2473 patients, comprising 78 studies on augmented reality and 16 on mixed reality. This technology has seen broad intraoperative application. Augmented and mixed reality can reduce operative duration, blood loss, and the duration of inpatient care. Current evidence shows that they achieve this most in percutaneous surgery. Conclusions Augmented and mixed reality technology improve surgical outcomes by increasing navigational speed and reducing navigational error intraoperatively. However, they have technical limitations which are the subject of ongoing research. Further studies are necessary to define how this technology is best applied intraoperatively. Systematic Review Registration: PROSPERO CRD42020205892.

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Section: Resultssupporting

confidence: 90%

The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review

Bollen

Awad

Langridge

et al. 2022

Robotics Computer Surgery

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“…Patients scheduled for PN underwent laparoscopic or robot‐assisted PN, carried out by four surgeons with extensive experience in both centers (>100 procedures for each technique). Laparoscopic PN and robot‐assisted PN were carried out with the transperitoneal approach in the case of anterior or complex renal masses 13–16 . However, the retroperitoneal approach was carried out in the case of posterior tumors 17 …”

Section: Methodsmentioning

confidence: 99%

Percutaneous ablation or minimally invasive partial nephrectomy for cT1a renal masses? A propensity score‐matched analysis

et al. 2021

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Objective Local tumor ablation to treat small renal mass is increasing. The aim of the present study was to compare oncologic outcomes among patients with T1 renal mass treated with partial nephrectomy and local tumor ablation. Methods To reduce the inherent differences between patients undergoing laparoscopic or robot‐assisted partial nephrectomy (n = 405) and local tumor ablation (n = 137), we used a 1:1 propensity score‐matched analysis. Local tumor ablation consisted of radiofrequency ablation and cryoablation. Disease‐free survival, overall survival and other causes mortality‐free survival rates were estimated using the Kaplan–Meier method. Multivariable logistic regression and competing‐risk regression models were used to identify predictors of complications, recurrence and other causes mortality, respectively. Results Partial nephrectomy had higher disease‐free survival estimates, as compared with local tumor ablation (92.8% vs 80.4% at 5 years, P = 0.02), with no significant difference between radiofrequency ablation and cryoablation (P = 0.9). Ablation showed comparable overall survival estimates to partial nephrectomy (91% vs 95.8% at 5 years, P = 0.6). The 5‐year recurrence rates were 7.9% versus 23.8% for patients aged ≤70 years, and 2.5% versus 11.9% for patients aged >70 years treated with partial nephrectomy and ablation, respectively; the 5‐year other causes mortality rates were 0% and 2.2% for patients treated with partial nephrectomy and ablation aged ≤70 years, and 3% versus 10.9% for patients aged >70 years treated with partial nephrectomy and ablation, respectively. At multivariable analysis, ablation was associated with fewer complications (odds ratio 0.41; P = 0.01). At competing risks analysis, age (hazard ratio 0.96) and ablation (hazard ratio 4.56) were independent predictors of disease recurrence (all P ≤ 0.008). Conclusions Local tumor ablation showed a higher risk of recurrence and lower risk of complications compared with partial nephrectomy, with comparable overall survival rates.

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“…Here we follow the common framework for which AI includes methods such as Machine Learning and Deep Learning. AI tools can help PCa diagnosis in many aspects, such as in prostate gland volume segmentation, lesion segmentation, detection, and characterization [12,13], and it has also been developed for applications in robotic surgery both for prostate cancer [14] and kidney cancer [15], digital pathology, and genomics [16]. However, one of the most challenging tasks is to accurately stage lesions aggressiveness, in particular classifying between not clinically significant tumors and clinically significant PCa.…”

Section: Ai In Pca Characterizationmentioning

confidence: 99%

Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data

Corradini

Brizi

Gaudiano

et al. 2021

Cancers

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Many efforts have been carried out for the standardization of multiparametric Magnetic Resonance (mp-MR) images evaluation to detect Prostate Cancer (PCa), and specifically to differentiate levels of aggressiveness, a crucial aspect for clinical decision-making. Prostate Imaging—Reporting and Data System (PI-RADS) has contributed noteworthily to this aim. Nevertheless, as pointed out by the European Association of Urology (EAU 2020), the PI-RADS still has limitations mainly due to the moderate inter-reader reproducibility of mp-MRI. In recent years, many aspects in the diagnosis of cancer have taken advantage of the use of Artificial Intelligence (AI) such as detection, segmentation of organs and/or lesions, and characterization. Here a focus on AI as a potentially important tool for the aim of standardization and reproducibility in the characterization of PCa by mp-MRI is reported. AI includes methods such as Machine Learning and Deep learning techniques that have shown to be successful in classifying mp-MR images, with similar performances obtained by radiologists. Nevertheless, they perform differently depending on the acquisition system and protocol used. Besides, these methods need a large number of samples that cover most of the variability of the lesion aspect and zone to avoid overfitting. The use of publicly available datasets could improve AI performance to achieve a higher level of generalizability, exploiting large numbers of cases and a big range of variability in the images. Here we explore the promise and the advantages, as well as emphasizing the pitfall and the warnings, outlined in some recent studies that attempted to classify clinically significant PCa and indolent lesions using AI methods. Specifically, we focus on the overfitting issue due to the scarcity of data and the lack of standardization and reproducibility in every step of the mp-MR image acquisition and the classifier implementation. In the end, we point out that a solution can be found in the use of publicly available datasets, whose usage has already been promoted by some important initiatives. Our future perspective is that AI models may become reliable tools for clinicians in PCa diagnosis, reducing inter-observer variability and evaluation time.

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Augmented Reality to Guide Selective Clamping and Tumor Dissection During Robot-assisted Partial Nephrectomy: A Preliminary Experience

Cited by 38 publications

References 29 publications

The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review

The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review

Percutaneous ablation or minimally invasive partial nephrectomy for cT1a renal masses? A propensity score‐matched analysis

Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data

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