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 neu...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 cT1ce3,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.展开更多
Objective:The aim of the study was to evaluate three-dimensional virtual models(3DVMs)usefulness in the intraoperative assistance of minimally-invasive partial nephrectomy in highly complex renal tumors.Methods:At our...Objective:The aim of the study was to evaluate three-dimensional virtual models(3DVMs)usefulness in the intraoperative assistance of minimally-invasive partial nephrectomy in highly complex renal tumors.Methods:At our institution cT1-2N0M0 all renal masses with Preoperative Aspects and Dimensions Used for an Anatomical classification score≥10 treated with minimally-invasive partial nephrectomy were considered for the present study.For inclusion a baseline contrast-enhanced computed tomography in order to obtain 3DVMs,the baseline and postoperative serum creatinine as well as estimated glomerular filtration rate values were needed.These patients,in which 3DVMs were used to assist the surgeon in the planning and intraoperative guidance,were then compared with a control group of patients who underwent minimally-invasive partial nephrectomy with the same renal function assessments,but without 3DVMs.Multivariable logistic regression models were used to predict the margin,ischemia,and complication score achievement.Results:Overall,79 patients met the inclusion criteria and were compared with 143 complex renal masses without 3DVM assistance.The 3DVM group showed better postoperative outcomes in terms of baseline-weighted differential estimated glomerular filtration rate(-17.7%vs.-22.2%,p=0.03),postoperative complications(16.5%vs.23.1%,p=0.03),and major complications(Clavien Dindo>III,2.5%vs.5.6%,p=0.03).At multivariable logistic regression 3DVM assistance independently predicted higher rates of successful partial nephrectomy(odds ratio:1.42,p=0.03).Conclusion:3DVMs represent a useful tool to plan a tailored surgical approach in case of surgically complex masses.They can be used in different ways,matching the surgeon's needs from the planning phase to the demolitive and reconstructive phase,leading towards maximum safety and efficacy outcomes.展开更多
文摘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 cT1ce3,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.
文摘Objective:The aim of the study was to evaluate three-dimensional virtual models(3DVMs)usefulness in the intraoperative assistance of minimally-invasive partial nephrectomy in highly complex renal tumors.Methods:At our institution cT1-2N0M0 all renal masses with Preoperative Aspects and Dimensions Used for an Anatomical classification score≥10 treated with minimally-invasive partial nephrectomy were considered for the present study.For inclusion a baseline contrast-enhanced computed tomography in order to obtain 3DVMs,the baseline and postoperative serum creatinine as well as estimated glomerular filtration rate values were needed.These patients,in which 3DVMs were used to assist the surgeon in the planning and intraoperative guidance,were then compared with a control group of patients who underwent minimally-invasive partial nephrectomy with the same renal function assessments,but without 3DVMs.Multivariable logistic regression models were used to predict the margin,ischemia,and complication score achievement.Results:Overall,79 patients met the inclusion criteria and were compared with 143 complex renal masses without 3DVM assistance.The 3DVM group showed better postoperative outcomes in terms of baseline-weighted differential estimated glomerular filtration rate(-17.7%vs.-22.2%,p=0.03),postoperative complications(16.5%vs.23.1%,p=0.03),and major complications(Clavien Dindo>III,2.5%vs.5.6%,p=0.03).At multivariable logistic regression 3DVM assistance independently predicted higher rates of successful partial nephrectomy(odds ratio:1.42,p=0.03).Conclusion:3DVMs represent a useful tool to plan a tailored surgical approach in case of surgically complex masses.They can be used in different ways,matching the surgeon's needs from the planning phase to the demolitive and reconstructive phase,leading towards maximum safety and efficacy outcomes.
