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Checcucci E, Piana A, Volpi G, Quarà A, De Cillis S, Piramide F, Burgio M, Meziere J, Cisero E, Colombo M, Bignante G, Sica M, Granato S, Verri P, Gatti C, Alessio P, Di Dio M, Alba S, Fiori C, Amparore D, Porpiglia F. Visual extended reality tools in image-guided surgery in urology: a systematic review. Eur J Nucl Med Mol Imaging 2024:10.1007/s00259-024-06699-6. [PMID: 38589511 DOI: 10.1007/s00259-024-06699-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/19/2024] [Indexed: 04/10/2024]
Abstract
PURPOSE The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery. METHODS In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine. RESULTS The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach. CONCLUSIONS AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.
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Affiliation(s)
- Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy.
| | - Alberto Piana
- Department of Urology, Romolo Hospital, Rocca di Neto, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Alberto Quarà
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Mariano Burgio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Juliette Meziere
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Edoardo Cisero
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Marco Colombo
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Gabriele Bignante
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Stefano Granato
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Cecilia Gatti
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Paolo Alessio
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Strada Provinciale 142, km 3,95, Candiolo, Turin, 10060, Italy
| | - Michele Di Dio
- Dept. of Surgery, Division of Urology, SS Annunziata Hospital, Cosenza, Italy
| | - Stefano Alba
- Department of Urology, Romolo Hospital, Rocca di Neto, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
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Amparore D, Checcucci E, Piramide F, Busacca G, Volpi G, De Cillis S, Sica M, Verri P, Piana A, Di Dio M, Fiori C, Porpiglia F. Robotic Vena Cava Thrombectomy with Three-dimensional Augmented Reality Guidance. EUR UROL SUPPL 2024; 62:43-46. [PMID: 38434189 PMCID: PMC10909593 DOI: 10.1016/j.euros.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2024] [Indexed: 03/05/2024] Open
Abstract
Robotic surgery has recently been used for treatment of renal cell carcinoma (RCC) and neoplastic thrombus located in the renal vein or inferior vena cava (IVC). Accurate identification of the thrombus location is crucial, and three-dimensional augmented reality (3D AR) may be valuable in achieving this. We enrolled patients with nonmetastatic RCC and level 0-I venous thrombus (Mayo Clinic classification) for robot-assisted radical nephrectomy and thrombectomy with 3D AR guidance. Five patients were prospectively enrolled; three had a level 0 thrombus and two had a level I thrombus. The mean operative time was 123 ± 15 min, mean IVC clamping time was 9.4 ± 6.8 min, and mean estimated blood loss was 750 ± 150 ml. The AR system allowed precise estimation of the thrombus location in all cases. No intraoperative complications or postoperative Clavien-Dindo grade >2 complications occurred. Use of 3D AR guidance allowed correct estimation of the limits of the thrombus and guided the surgeon in selecting an appropriate surgical strategy.
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Affiliation(s)
- Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | | | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
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Checcucci E, Amparore D, Volpi G, De Cillis S, Piramide F, Verri P, Piana A, Sica M, Gatti C, Alessio P, Quarà A, Burgio M, Colombo M, Busacca G, Mottrie A, Cherullo E, Breda A, Antonelli A, Bollens R, Minervini A, Porter J, Schiavina R, Autorino R, Tewari A, Di Dio M, Fiori C, Porpiglia F. Metaverse Surgical Planning with Three-dimensional Virtual Models for Minimally Invasive Partial Nephrectomy. Eur Urol 2024; 85:320-325. [PMID: 37673751 DOI: 10.1016/j.eururo.2023.07.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/30/2023] [Accepted: 07/19/2023] [Indexed: 09/08/2023]
Abstract
The recent integration of new virtual visualization modalities with artificial intelligence and high-speed internet connection has opened the door to the advent of the metaverse in medicine. In this totally virtual environment, three-dimensional virtual models (3DVMs) of the patient's anatomy can be visualized and discussed via digital avatars. Here we present for the first time a metaverse preoperative clinical case discussion before minimally invasive partial nephrectomy. The surgeons' digital avatars met in a virtual room and participated in a virtual consultation on the surgical strategy and clamping approach before the procedure. Robotic or laparoscopic procedures are then carried out according to the simulated surgical strategy. We demonstrate how this immersive virtual reality experience overcomes the barriers of distance and how the quality of surgical planning is enriched by a great sense of "being there", even if virtually. Further investigation will improve the quality of interaction with the models and among the avatars.
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Affiliation(s)
- Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy.
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy; Department of Urology, OLV Hospital, Aalst, Belgium; ORSI Academy, Melle, Belgium
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy; Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Alberto Piana
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy; Romolo Hospital, Rocca di Neto, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Cecilia Gatti
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy; Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Paolo Alessio
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
| | - Alberto Quarà
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Mariano Burgio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Marco Colombo
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Alex Mottrie
- Department of Urology, OLV Hospital, Aalst, Belgium; ORSI Academy, Melle, Belgium
| | - Edward Cherullo
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
| | - Alberto Breda
- Department of Urology, Fundació Puigvert, Autonomous University of Barcelona, Barcelona, Spain
| | - Alessandro Antonelli
- Urology Unit AUOI Verona, Department of Surgery, Dentistry, Pediatrics and Gynecology, University of Verona, Verona, Italy
| | - Renaud Bollens
- Urology Department, Centre Hospitalier de Wallonie Picarde, Tournai, Belgium
| | - Andrea Minervini
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Unit of Urological Oncologic Minimally-Invasive Robotic Surgery and Andrology, University of Florence, Careggi Hospital, Florence, Italy
| | - James Porter
- Department of Urology, Swedish Medical Group, Seattle, WA, USA
| | - Riccardo Schiavina
- Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
| | - Riccardo Autorino
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
| | - Ashutosh Tewari
- Department of Urology, Icahn School of Medicine, Mount Sinai Hospital, New York, NY, USA
| | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Italy
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Amparore D, De Cillis S, Alladio E, Sica M, Piramide F, Verri P, Checcucci E, Piana A, Quarà A, Cisero E, Manfredi M, Di Dio M, Fiori C, Porpiglia F. Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy. J Endourol 2024. [PMID: 38512711 DOI: 10.1089/end.2024.0057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024] Open
Abstract
Introduction: Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectomy. Although nomograms exist, their retrospective limitations highlight artificial intelligence (AI)'s potential. This study seeks to develop a machine learning algorithm using robot-assisted radical prostatectomy (RARP) data to predict postoperative incontinence, advancing personalized care. Materials and Methods: In this propsective observational study, patients with localized prostate cancer undergoing RARP between April 2022 and January 2023 were assessed. Preoperative variables included age, body mass index, prostate-specific antigen (PSA) levels, digital rectal examination (DRE) results, Gleason score, International Society of Urological Pathology grade, and continence and potency questionnaires responses. Intraoperative factors, postoperative outcomes, and pathological variables were recorded. Urinary continence was evaluated using the Expanded Prostate cancer Index Composite questionnaire, and machine learning models (XGBoost, Random Forest, Logistic Regression) were explored to predict incontinence risk. The chosen model's SHAP values elucidated variables impacting predictions. Results: A dataset of 227 patients undergoing RARP was considered for the study. Post-RARP complications were predominantly low grade, and urinary continence rates were 74.2%, 80.7%, and 91.4% at 7, 13, and 90 days after catheter removal, respectively. Employing machine learning, XGBoost proved the most effective in predicting postoperative incontinence risk. Significant variables identified by the algorithm included nerve-sparing approach, age, DRE, and total PSA. The model's threshold of 0.67 categorized patients into high or low risk, offering personalized predictions about the risk of incontinence after surgery. Conclusions: Predicting postoperative incontinence is crucial for tailoring rehabilitation after RARP. Machine learning algorithm, particularly XGBoost, can effectively identify those variables more heavily, impacting the outcome of postoperative continence, allowing to build an AI-driven model addressing the current challenges in post-RARP rehabilitation.
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Affiliation(s)
- Daniele Amparore
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Eugenio Alladio
- Department of Chemistry, University of Turin, Turin, Italy
- Centro Regionale Antidoping "A. Bertinaria" of Orbassano (Turin), Turin, Italy
| | - Michele Sica
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Paolo Verri
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Alberto Quarà
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Edoardo Cisero
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, Cosenza, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Turin, Italy
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Piana A, Amparore D, Sica M, Volpi G, Checcucci E, Piramide F, De Cillis S, Busacca G, Scarpelli G, Sidoti F, Alba S, Piazzolla P, Fiori C, Porpiglia F, Di Dio M. Automatic 3D Augmented-Reality Robot-Assisted Partial Nephrectomy Using Machine Learning: Our Pioneer Experience. Cancers (Basel) 2024; 16:1047. [PMID: 38473404 DOI: 10.3390/cancers16051047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/26/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
The aim of "Precision Surgery" is to reduce the impact of surgeries on patients' global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called "ikidney", based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6-13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.
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Affiliation(s)
- Alberto Piana
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Michele Sica
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, 10060 Turin, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Giovanni Busacca
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | | | | | | | - Pietro Piazzolla
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, 10043 Turin, Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, Annunziata Hospital, 87100 Cosenza, Italy
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Amparore D, Sica M, Verri P, Piramide F, Checcucci E, De Cillis S, Piana A, Campobasso D, Burgio M, Cisero E, Busacca G, Di Dio M, Piazzolla P, Fiori C, Porpiglia F. Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy. Technol Cancer Res Treat 2024; 23:15330338241229368. [PMID: 38374643 PMCID: PMC10878218 DOI: 10.1177/15330338241229368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
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.
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Affiliation(s)
- Daniele Amparore
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Michele Sica
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Paolo Verri
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Federico Piramide
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute FPO-IRCCS, Candiolo, Italy
| | - Sabrina De Cillis
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Alberto Piana
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
- Department of Urology, Romolo Hospital, Rocca di Neto (KR), Italy
| | - Davide Campobasso
- Urology Unit, University Hospital of Parma, Parma, Italy
- 2 Level Master Degree Program in Advanced Robotic and Laparoscopic Surgery in Urology, Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi, Italy
| | - Mariano Burgio
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Edoardo Cisero
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Giovanni Busacca
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Michele Di Dio
- Division of Urology, Department of Surgery, Annunziata Hospital, Cosenza, Italy
| | - Pietro Piazzolla
- Department of Management and Production Engineer, Polytechnic University of Turin, Turin, Italy
| | - Cristian Fiori
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
| | - Francesco Porpiglia
- Division of Urology, Dept. of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano (Turin), Italy
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7
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Sica M, Piazzolla P, Amparore D, Verri P, De Cillis S, Piramide F, Volpi G, Piana A, Di Dio M, Alba S, Gatti C, Burgio M, Busacca G, Giordano A, Fiori C, Porpiglia F, Checcucci E. 3D Model Artificial Intelligence-Guided Automatic Augmented Reality Images during Robotic Partial Nephrectomy. Diagnostics (Basel) 2023; 13:3454. [PMID: 37998590 PMCID: PMC10670293 DOI: 10.3390/diagnostics13223454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023] Open
Abstract
More than ever, precision surgery is making its way into modern surgery for functional organ preservation. This is possible mainly due to the increasing number of technologies available, including 3D models, virtual reality, augmented reality, and artificial intelligence. Intraoperative surgical navigation represents an interesting application of these technologies, allowing to understand in detail the surgical anatomy, planning a patient-tailored approach. Automatic superimposition comes into this context to optimally perform surgery as accurately as possible. Through a dedicated software (the first version) called iKidney, it is possible to superimpose the images using 3D models and live endoscopic images during partial nephrectomy, targeting the renal mass only. The patient is 31 years old with a 28 mm totally endophytic right-sided renal mass, with a PADUA score of 9. Thanks to the automatic superimposition and selective clamping, an enucleoresection of the renal mass alone was performed with no major postoperative complication (i.e., Clavien-Dindo < 2). iKidney-guided partial nephrectomy is safe, feasible, and yields excellent results in terms of organ preservation and functional outcomes. Further validation studies are needed to improve the prototype software, particularly to improve the rotational axes and avoid human help. Furthermore, it is important to reduce the costs associated with these technologies to increase its use in smaller hospitals.
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Affiliation(s)
- Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Pietro Piazzolla
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Alberto Piana
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, 87100 Cosenza, Italy;
| | | | - Cecilia Gatti
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
| | - Mariano Burgio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Angelo Giordano
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
| | - Enrico Checcucci
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, 10043 Orbassano, Italy; (D.A.); (P.V.); (S.D.C.); (F.P.); (A.P.); (M.B.); (G.B.); (A.G.); (C.F.); (F.P.); (E.C.)
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy; (P.P.); (G.V.); (C.G.)
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Di Dio M, Barbuto S, Bisegna C, Bellin A, Boccia M, Amparore D, Verri P, Busacca G, Sica M, De Cillis S, Piramide F, Zaccone V, Piana A, Alba S, Volpi G, Fiori C, Porpiglia F, Checcucci E. 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. Diagnostics (Basel) 2023; 13:2320. [PMID: 37510065 PMCID: PMC10377834 DOI: 10.3390/diagnostics13142320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/02/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
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.
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Affiliation(s)
- Michele Di Dio
- Division of Urology, Department of Surgery, SS Annunziata Hospital, 87100 Cosenza, Italy
| | - Simona Barbuto
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Claudio Bisegna
- Division of Urology, Department of Surgery, SS Annunziata Hospital, 87100 Cosenza, Italy
| | - Andrea Bellin
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Mario Boccia
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Daniele Amparore
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Giovanni Busacca
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Vincenzo Zaccone
- Division of Urology, Department of Surgery, SS Annunziata Hospital, 87100 Cosenza, Italy
| | - Alberto Piana
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
- Romolo Hospital, 88821 Rocca di Neto, Italy
| | | | - Gabriele Volpi
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, 10060 Candiolo, Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Enrico Checcucci
- Department of Oncology, Division of Urology, San Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
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Pecoraro A, Amparore D, Checcucci E, Piramide F, Carbonaro B, De Cillis S, Granato S, Sica M, Campi R, Fiori C, Porpiglia F. Three-dimensional virtual models assistance predicts higher rates of "successful" minimally invasive partial nephrectomy: an Institutional analysis across the available trifecta definitions. World J Urol 2023; 41:1093-1100. [PMID: 37022496 DOI: 10.1007/s00345-023-04310-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 01/22/2023] [Indexed: 04/07/2023] Open
Abstract
PURPOSE 3D virtual models (3DVMs) are nowadays under scrutiny to improve partial nephrectomy (PN) outcomes. Five different Trifecta definitions have been proposed to optimize the framing of "success" in the PN field. Our aim is to analyze if the use of 3DVMs could impact the success rate of minimally invasive PN (mi-PN), according to the currently available definitions of Trifecta. MATERIALS AND METHODS At our Institution 250 cT1-2N0M0 renal masses patients treated with mi-PN were prospectively enrolled. Inclusion criteria were the availability of contrast-enhanced CT, baseline and postoperative serum creatinine, and eGFR. These patients were then compared with a control group of 710 patients who underwent mi-PN with the same renal function assessments, but without 3DVMs. Multivariable logistic regression (MLR) models were used to predict the trifecta achievement according to the different trifecta definitions. RESULTS Among the definitions, Trifecta rates ranged between 70.8% to 97.4% in the 3DVM group vs. 56.8% to 92.8% in the control group (all p values < 0.05). 3DVMs showed better postoperative outcomes in terms of ΔeGFR, ( - 16.6% vs. - 2.7%, p = 0.03), postoperative complications (15%, vs 22.9%, p = 0.002) and major complications (Clavien Dindo > 3, 2.8% vs 5.6%, p = 0.03). At MLR 3DVMs assistance independently predicted higher rates of successful PN across all the available definitions of Trifecta (OR: 2.7 p < 0.001, OR:2.0 p = 0.0008, OR:2.8 p = 0.02, OR 2.0 p = 0.003). CONCLUSIONS The 3DVMs availability was found to be the constant predictive factor of successful PN, with a twofold higher probability of achieving Trifecta regardless of the different definitions available in Literature.
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Affiliation(s)
- Angela Pecoraro
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy.
- European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands.
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
- European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands
| | - Enrico Checcucci
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Beatrice Carbonaro
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Sabrina De Cillis
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Stefano Granato
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Michele Sica
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Riccardo Campi
- European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands
- Department of Urology, Careggi Hospital, University of Florence, Florence, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
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DE Luca S, Checcucci E, Piramide F, Russo F, Alessio P, Garrou D, Peretti D, Sica M, Volpi G, Piana A, DE Cillis S, Amparore D, Manfredi M, Fiori C, Porpiglia F. MRI/real-time ultrasound image fusion guided high-intensity focused ultrasound: a prospective comparative and functional analysis of different ablative techniques. Minerva Urol Nephrol 2023; 75:172-179. [PMID: 36286396 DOI: 10.23736/s2724-6051.22.04853-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2023]
Abstract
BACKGROUND The aim of this paper was to compare safety and functional outcomes of total, hemi and focal ablation by the latest focal high-intensity focused ultrasound (HIFU) device. METHODS This is a prospective study including patients with low to intermediate-risk PCa treated with HIFU by Focal One® device from 11/2018 to 3/2020. Before the treatment all patients underwent mp-magnetic resonance imaging (MRI) and subsequent MRI/transrectal ultrasound (TRUS) fusion and standard biopsy. Patients were stratified according to the type of ablation: total, hemi- or focal ablation. Functional data (IPSS, Quality of Life [QoL], IIEF-5, maximum flow [Qmax] and post void residual [PVR] at flowmetry) were assessed preoperatively and at 1, 3, 6 and 12 months after treatment. Moreover, the urinary symptoms reported by patients at IPSS questionnaire were divided in "irritative" and "obstructive" and compared. RESULTS One hundred patients were enrolled. Median prostate volume and lesion diameter were 46 (IQR 25-75) mL and 10 (IQR 6-13) mm. 15, 50 and 35 patients underwent total, hemi- and focal ablation, respectively. No differences were found between them except for operative time (lower in the focal group, P<0.01). Significant lower incidence of irritative symptoms was identified in the focal group compared to the others (P<0.05 at 1 and 3 months of follow-up). No differences were found among the baseline status and the postoperative assessment in terms of obstructive IPSS items, IIEF-5, QoL, Qmax and PVR (all P value>0.05). CONCLUSIONS Our study suggests that patients' specific HIFU tailoring with the MRI/real-time TRUS Guidance by Focal One® device is able to minimize the side effects of treatment.
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Affiliation(s)
- Stefano DE Luca
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Enrico Checcucci
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Federico Piramide
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy -
| | - Filippo Russo
- Department of Radiology, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Paolo Alessio
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Diletta Garrou
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy
| | - Dario Peretti
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Michele Sica
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Gabriele Volpi
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Sabrina DE Cillis
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy
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Checcucci E, De Cillis S, Amparore D, Volpi G, Piramide F, Piana A, Sica M, Zamengo D, Manfredi M, Fiori C, Piazzolla P, Porpiglia F. Improving the safety of robotic surgery with a new artificial intelligence-based system. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)01430-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Morelli M, Spinelli M, Sciorio C, Spirito L, Geretto P, Gemma L, Frediani L, Sica M, Guerrer C, Cito G, Manassero A, Lombardi G, De Cobelli O, Sampogna G. Does the time from spinal cord injury affect the sperm retrieval rate in testicular sperm extraction? Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)00720-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Volpi G, Checcucci E, Amparore D, De Cillis S, Piramide F, Piana A, Sica M, Verri P, Burgio M, Zamengo D, Meziere J, Cisero E, Della Corte M, Mesterca A, Mandaletti M, Giordano A, Pini F, Sterrantino A, Manfredi M, Fiori C, Porpiglia F. The application of artificial intelligence guided 3D automatic augmented-reality biopsy allows to improve the oncological safety of the nerve sparing phase during robotic prostatectomy. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)00524-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Amparore D, Piana A, Busacca G, De Cillis S, Piramide F, Checcucci E, Volpi G, Verri P, Sica M, Meziere J, Zamengo D, Manfredi M, Fiori C, Porpiglia F. The role of three-dimensional virtual models to plan a minimal surgical impact robot assisted partial nephrectomy for the treatment of small renal masses. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)01396-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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De Cillis S, De Luca S, Amparore D, Checcucci E, Piramide F, Piana A, Volpi G, Sica M, Verri P, Meziere J, Zamengo D, Quarà A, Cisero E, Busacca G, Colombo M, Cidda D, Gatti C, Sterrantino A, Ortenzi M, Manfredi M, Fiori C, Porpiglia F. Lower Urinary Tract Symptoms (LUTS) after Aquablation for the treatment of Benign Prostatic Hyperplasia (BPH): Evaluation of symptoms category (filling versus voiding phase) prevalence rates. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)00077-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Piana A, Amparore D, Busacca G, Alessio P, Checcucci E, Piramide F, De Cillis S, Volpi G, Verri P, Sica M, Burgio M, Bellin A, Manfredi M, Fiori C, Porpiglia F. 3D augmented reality robotic-assisted segmental ureterectomy with buccal mucosa graft for the repair of upper complex ureteral strictures. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)01450-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Amparore D, De Cillis S, Checcucci E, De Luca S, Piana A, Piramide F, Volpi G, Sica M, Verri P, Burgio M, Zamengo D, Quarà A, Cisero E, Della Corte M, Busacca G, Mesterca A, Ortenzi M, Sterrantino A, Manfredi M, Fiori C, Porpiglia F. Functional and endoscopic results up to two years after Aquablation for BPH-related LUTS: A single centre first clinical experience. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)01167-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Amparore D, Piramide F, Checcucci E, Piana A, Volpi G, De Cillis S, Verri P, Granato S, Sica M, Quarà A, Busacca G, Colombo M, Bellin A, Manfredi M, Fiori C, Porpiglia F. 3D Augmented reality for neoplastic venous thrombus identification during robotic radical nephrectomy for RCC: A new tool for intraoperative guidance. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)01404-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Olivero A, Liu K, Checchucci E, Liu L, Ma L, Wang G, Mantica G, Tappero S, Amparore D, Sica M, Fiori C, Huang Q, Niu S, Wang B, Ma X, Hou X, Porpiglia F, Terrone C, Zhang X. Adrenocortical carcinoma with venous tumor invasion: is there a role for mini-invasive surgery? Langenbecks Arch Surg 2023; 408:17. [PMID: 36625975 DOI: 10.1007/s00423-023-02765-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 11/22/2022] [Indexed: 01/11/2023]
Abstract
OBJECTIVE This study aims to investigate early oncologic outcomes in patients with adrenocortical carcinoma (ACC) with venous invasion (VI) treated using both open and mini-invasive approaches. PATIENTS AND MATERIALS We conducted a retrospective analysis of 4 international referral center databases, including all the patients undergoing adrenalectomy for ACC with VI from January 2007 to March 2020. According to CT scan or MRI, the tumor thrombus was classified into four levels: (1) adrenal vein invasion; (2) renal vein invasion; (3) infra-hepatic Inferior vena cava (IVC); and (4) retro-hepatic IVC. In addition, we divided our patients into patients who had undergone open surgery and mini-invasive surgery. RESULTS We identified 20 patients with a median follow-up of 12 months. The median tumor size was 110mm. ENSAT stage was II in 4 patients, III in 13 patients, and IV in 3 patients. Tumor thrombus extended in the adrenal vein (n=5), renal vein (n=1), infra-hepatic IVC (n=9), or into the retro-hepatic IVC (n=5). Ten patients were treated with a mini-invasive approach. The patient treated with an open approach reported a more aggressive disease. The two groups did not differ in surgical margins, surgical time, blood losses, complications, and length of stay. The prognosis resulted worse in the patient undergoing open. Kaplan-Meier analysis indicated a difference in OS for the patients stratified by ENSAT stage (Log-rank p=0.011); we also reported a difference in DFS for patients stratified for thrombus extension (p=0.004) and ENSAT stage (p<0.001). CONCLUSION The DFS of patients with VI from ACC is influenced by the staging and the extension of the venous invasion; the staging influences the OS. The mini-invasive approach seems feasible in selected patients; however, further studies investigating the oncological outcomes are needed. A mini-invasive approach for adrenal tumors with venous invasion is an explorable option in very selected patients.
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Affiliation(s)
- Alberto Olivero
- Department of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
- Department of Urology, Policlinico San Martino Hospital, University of Genoa, Genoa, Italy.
| | - Kan Liu
- Department of Urology, Chinese PLA General Hospital, Beijing, China
| | - Enrico Checchucci
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Lei Liu
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Lulin Ma
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Guoliang Wang
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Guglielmo Mantica
- Department of Urology, Policlinico San Martino Hospital, University of Genoa, Genoa, Italy
| | - Stefano Tappero
- Department of Urology, Policlinico San Martino Hospital, University of Genoa, Genoa, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Michele Sica
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Quingbo Huang
- Department of Urology, Chinese PLA General Hospital, Beijing, China
| | - Shaoxi Niu
- Department of Urology, Chinese PLA General Hospital, Beijing, China
| | - Baojun Wang
- Department of Urology, Chinese PLA General Hospital, Beijing, China.
| | - Xin Ma
- Department of Urology, Chinese PLA General Hospital, Beijing, China
| | - Xiaofei Hou
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Carlo Terrone
- Department of Urology, Policlinico San Martino Hospital, University of Genoa, Genoa, Italy
| | - Xu Zhang
- Department of Urology, Chinese PLA General Hospital, Beijing, China
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Pecoraro A, Peretti D, Tian Z, Aimar R, Niculescu G, Alleva G, Piana A, Granato S, Sica M, Amparore D, Checcucci E, Manfredi M, Karakiewicz P, Fiori C, Porpiglia F. Treatment of Ureteral Stent-Related Symptoms. Urol Int 2023; 107:288-303. [PMID: 34818261 DOI: 10.1159/000518387] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 06/22/2021] [Indexed: 11/19/2022]
Abstract
BACKGROUND The aim of the study was to assess the effectiveness of the main classes of drugs used at reducing morbidity related to ureteric stents. SUMMARY After establishing a priori protocol, a systematic electronic literature search was conducted in July 2019. The randomized clinical trials (RCTs) selection proceeded in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and was registered (PROSPERO ID 178130). The risk of bias and the quality assessment of the included RCTs were performed. Ureteral Stent Symptom Questionnaire (USSQ), International Prostate Symptom Score (IPSS), and quality of life (QoL) were pooled for meta-analysis. Mean difference and risk difference were calculated as appropriate for each outcome to determine the cumulative effect size. Fourteen RCTs were included in the analysis accounting for 2,842 patients. Alpha antagonist, antimuscarinic, and phosphodiesterase (PDE) inhibitors significatively reduced all indexes of the USSQ, the IPSS and QoL scores relative to placebo. Conversely, combination therapy (alpha antagonist plus antimuscarinic) showed in all indexes of the USSQ, IPSS, and QoL over alpha antagonist or antimuscarinic alone. On comparison with alpha blockers, PDE inhibitors were found to be equally effective for urinary symptoms, general health, and body pain parameters, but sexual health parameters improved significantly with PDE inhibitors. Finally, antimuscarinic resulted in higher decrease in all indexes of the USSQ, the IPSS, and QoL relative to alpha antagonist. KEY MESSAGE Relative to placebo, alpha antagonist alone, antimuscarinics alone, and PDE inhibitors alone have beneficial effect in reducing stent-related symptoms. Furthermore, there are significant advantages of combination therapy compared with monotherapy. Finally, PDE inhibitors are comparable to alpha antagonist, and antimuscarinic seems to be more effective than alpha antagonist alone.
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Affiliation(s)
- Angela Pecoraro
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Dario Peretti
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Zhe Tian
- Cancer Prognostics and Health Outcomes Unit, University of Montreal Hospital Center, Montreal, Québec, Canada
| | - Roberta Aimar
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Gabriel Niculescu
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Giorgio Alleva
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Stefano Granato
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Michele Sica
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Enrico Checcucci
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Pierre Karakiewicz
- Cancer Prognostics and Health Outcomes Unit, University of Montreal Hospital Center, Montreal, Québec, Canada
| | - Cristian Fiori
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department of Oncology, School of Medicine, San Luigi Hospital, University of Turin, Turin, Italy
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21
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Lastrucci V, Puglia M, Pacifici M, Rusconi F, Buscemi P, Alderotti G, Sica M, Belli G, Berti E, Voller F. Predictors of delayed vaccination in infants born in Tuscany, Italy: an area based cohort study. Eur J Public Health 2022. [DOI: 10.1093/eurpub/ckac129.392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
Timely vaccination is essential to protect infants from vaccine-preventable diseases. The aim of the study was to evaluate the determinants of vaccination timeliness for hexavalent (HEXA) and measles-mumps-rubella (MMR) vaccines.
Methods
The study is part of the PREHMO project funded by Tuscany Region, Italy. Data on the 2017 and 2018 full birth cohorts of Tuscany (N = 41,493) were retrieved from the Birth Registry and linked to those of the Vaccine Registry up to 24 months after birth. Sociodemographic and at birth characteristics of mothers and infants were retrieved. The primary outcome was the timeliness of HEXA 1st and 3rd doses, and MMR 1st dose. Timeliness was defined as the administration of the dose a day after the period recommended by the vaccination schedule. Multiple logistic regression models were performed.
Results
For all the vaccines considered, a significantly increased risk of delayed vaccination was observed in preterm infants and in infants born in hospital of second level of newborn care, while infants conceived by assisted reproductive technologies and first-born infants showed a significantly decreased risk for delayed vaccination. Multiple births, small for gestational age status, maternal unemployment, and rural residence were significantly associated with an increased risk of delayed HEXA-1 vaccination (OR 1.31, 95%CI 1.13-1.51; OR 1.12, 95%CI 1.03-1.22; OR 1.06, 95%CI 1.01-1.13; and OR 1.1, 95%CI 1.03-1.16). As for MMR vaccination, a low maternal education was significantly associated with high risk of delay (OR 1.12, 95%CI 1.06-1.18), while rural residence, maternal foreign nationality and female sex were significantly associated with a decreased risk of delay (OR 0.91, 95%CI 0.87-0.96; OR 0.82, 95%CI 0.78-0.87; and OR 0.95, 95%CI 0.91-0.99).
Conclusions
Several common and vaccine-specific predictors of vaccination timeliness were identified. Strategies to improve a timely vaccination should take into account these predictors.
Key messages
• Several maternal and infants factors may influence vaccination timeliness of routine immunization in childhood.
• Tailored vaccination strategies are needed to improve vaccination timeliness in infants at high-risk of delayed vaccination.
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Affiliation(s)
- V Lastrucci
- Meyer Children's Hospital Epidemiology Unit, , Firenze, Italy
- Department of Health Science, University of Florence , Firenze, Italy
| | - M Puglia
- Epidemiologic Observatory, Regional Health Agency of Tuscany , Firenze, Italy
| | - M Pacifici
- Epidemiologic Observatory, Regional Health Agency of Tuscany , Firenze, Italy
| | - F Rusconi
- Maternal and Child Department, Local Health Unit Toscana Nord Ovest , Pisa, Italy
| | - P Buscemi
- Department of Health Science, University of Florence , Firenze, Italy
| | - G Alderotti
- Meyer Children's Hospital Epidemiology Unit, , Firenze, Italy
| | - M Sica
- Meyer Children's Hospital Epidemiology Unit, , Firenze, Italy
| | - G Belli
- Neonatal Intensive Care Unit, Local Health Unit Toscana Centro , Firenze, Italy
| | - E Berti
- Neonatal Intensive Care Unit, Meyer Children's Hospital , Firenze, Italy
| | - F Voller
- Epidemiologic Observatory, Regional Health Agency of Tuscany , Firenze, Italy
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22
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Piramide F, Amparore D, Checcucci E, Piana A, Volpi G, De Cillis S, Verri P, Granato S, Sica M, Burgio M, Carbonaro B, Busacca G, Mesterca G, Gatti C, Pini F, Bellin A, Manfredi M, Fiori C, Porpiglia F. Optimizing the neoplastic venous thrombus identification during robotic radical nephrectomy thanks to 3D augmented reality guidance. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01192-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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23
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Piramide F, Amparore D, Checcucci E, Piana A, Volpi G, De Cillis S, Verri P, Granato S, Sica M, Burgio M, Busacca G, Mesterca A, Gatti C, Pini F, Bellin A, Manfredi M, Fiori C, Porpiglia F. 3D Augmented reality guidance in identification of neoplastic venous thrombus during robotic radical nephrectomy. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)02173-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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24
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Pecoraro A, Amparore D, Piramide F, Verri P, Checcucci E, De Cillis S, Piana A, Sica M, Piscitello S, Burgio M, Meziere J, Zamengo D, Quarà A, Della Corte M, Busacca G, Colombo M, Mandaletti M, Manfredi M, Fiori C, Porpiglia F. 3D virtual models assistance predicts higher rates of “successful” minimally-invasive partial nephrectomy: an institutional analysis across the available trifecta definitions. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01181-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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25
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Amparore D, De Cillis S, Checcucci E, Manfredi M, Volpi G, Meziere J, Piana A, Piramide F, Sica M, Verri P, Granato S, Piscitello S, Quarà A, Della Corte M, Fiori C, Kadner G, Schulman C, Porpiglia F. Application of temporary implantable nitinol device (ITIND) for the treatment of lower urinary tract symptoms due to BPH: long term results of an international multicenter prospective study. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01165-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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26
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Fiori C, Checcucci E, Stura I, De Cillis S, Amparore D, Piramide F, Piana A, Volpi G, Granato S, Verri P, Sica M, Piscitello S, Ola L, Meziere J, Zamengo D, Cisero E, Della Corte M, Manfredi M, Giuseppe M, Porpiglia F. Identify patients candidate for extended pelvic lymph- node dissection during radical prostatectomy based on target biopsy findings only: Internal validation of novel nomogram. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)02144-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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De Cillis S, De Luca S, Amparore D, Checcucci E, Piana A, Piramide F, Volpi G, Sica M, Verri P, Piscitello S, Burgio M, Quarà A, Pini F, Mandaletti M, Giordano A, Cidda D, Mesterca A, Manfredi M, Fiori C, Porpiglia F. Salvage robot-assisted radical prostatectomy in patient underwent primary HIFU: A tertiary care center experience. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)02145-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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28
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Amparore D, Piramide F, Checcucci E, De Cillis S, Piana A, Volpi G, Verri P, Granato S, Sica M, Meziere J, Busacca G, Cisero E, Colombo M, Mandaletti M, Ortenzi M, Cidda D, Bellin A, Cattaneo G, Manfredi M, Fiori C, Porpiglia F. Identification of renal perfusion areas with a mathematical algorithm to increase the precision of selective clamping during robot-assisted partial nephrectomy. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)02236-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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29
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Amparore D, Piramide F, Checcucci E, De Cillis S, Piana A, Volpi G, Sica M, Verri P, Granato S, Burgio M, Ola L, Zamengo D, Della Corte M, Busacca G, Colombo M, Mandaletti M, Cossu M, Mesterca A, Manfredi M, Fiori C, Porpiglia F. A new technology to optimize selective clamping during 3D guided robotic partial nephrectomy: Is it feasible to precisely establish the perfusion areas of the organ? EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)02165-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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30
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Checcucci E, Alladio E, Manfredi M, Amparore D, De Cillis S, Piramide F, Volpi G, Piana A, Sica M, Verri P, Piscitello S, Ola L, Zamengo D, Cisero E, Della Corte M, Pini F, Giordano A, Fiori C, De Luca S, Porpiglia F. Standard prostate biopsy combined with target biopsy in biopsy naïve patients: does it has an additional role when compared with radical prostatectomy specimens? results of a prospective randomized clinical trial. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01175-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
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31
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Checcucci E, Piazzolla P, Manfredi M, Amparore D, Piana A, De Cillis S, Piramide F, Volpi G, Sica M, Granato S, Burgio M, Ola L, Meziere J, Della Corte M, Cisero E, Colombo M, Gatti C, Fiori C, Porpiglia F. Artificial intelligence based system to alert the surgeon of active bleeding during robotic prostatectomy: a feasibility preliminary study. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01168-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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32
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Manfredi M, Sica M, Checcucci E, Amparore D, Silvestri T, Piramide F, De Cillis S, Piana A, Volpi G, Granato S, Ola L, Zamengo D, Meziere J, Cisero E, Poggio M, Cidda D, Giordano A, Fiori C, Celia A, Porpiglia F. Y-pouch ileal neobladder after robot-assisted radical cystectomy: preliminary results of two italian tertiary centers. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01117-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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33
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Claps F, Pavan N, d’Altilia N, Maggi M, Checcucci E, Napolitano L, Morlacco A, Tafuri A, Palumbo C, Mazzon G, Del Giudice F, Campi R, Signorini C, Boeri L, Giannarini G, Esperto F, Tulone G, Finati M, Sica M, La Rocca R, Bignù C, Celentano G, Falagario U, Traunero F, Panunzio A, Zucchi A, Sciarra A, Liguori G, Busetto G, Bartoletti R, Simonato A, Minervini A, Papalia R, Scarpa R, Serni S, Montanari E, Carmignani L, Celia A, Volpe A, Antonelli A, Dal Moro F, Mirone V, Porpiglia F, Tubaro A, Cormio L, Carrieri G, Trombetta C. Predictors of residual tumor at re-staging transurethral resection for high-risk non-muscle invasive bladder cancer: insights from a large multi-institutional collaboration. EUR UROL SUPPL 2022. [DOI: 10.1016/s2666-1683(22)01227-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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34
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Fiori C, Checcucci E, Stura I, Amparore D, De Cillis S, Piana A, Granato S, Volpi G, Sica M, Piramide F, Verri P, Manfredi M, De Luca S, Autorino R, Migliaretti G, Porpiglia F. Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only. Prostate Cancer Prostatic Dis 2022:10.1038/s41391-022-00565-y. [PMID: 35750851 DOI: 10.1038/s41391-022-00565-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/16/2022] [Accepted: 06/10/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Nowadays a tool able to predict the risk of lymph-node invasion (LNI) in patients underwent target biopsy (TB) only before radical prostatectomy (RP) is still lacking. Our aim is to develop a model based on mp-MRI and target biopsy (TB) alone able to predict the risk of LNI. METHODS We retrospectively extracted data of patients with preoperative positive mp-MRI and TB only who underwent RARP with ePLND from April 2014 to March 2020. A logistic regression model was performed to evaluate the impact of pre- and intra-operative factors on the risk of LNI. Model discrimination was assessed using an area under (AUC) the ROC curve. A nomogram, and its calibration plot, to predict the risk of LNI were generated based on the logistic model. A validation of the model was done using a similar cohort. RESULTS 461 patients were included, of which 52 (11.27) had LNI. After logistic regression analysis and multivariable model DRE, PI-RADS, seminal vesicle invasion, PSA and worst GS at I and II target lesions were significant predictors of LNI. The AUC was 0.74 [0.67-0.81] 95% CI. The calibration plot shows that our model is very close to the ideal one which is in the 95% CI. After the creation of a visual nomogram, the cut-off to discriminate between the risk or not of LNI was set with Youden index at 60 points that correspond to a risk of LNI of 7%. The model applied on a similar cohort shown a LH+ of 2.58 [2.17-2.98] 95% CI. CONCLUSIONS Our nomogram for patients undergoing MRI-TB only takes into account clinical stage, SVI at MRI, biopsy Gleason pattern and PSA and it is able to identify patients with risk of LNI when a score higher than 7% is achieved.
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Affiliation(s)
- Cristian Fiori
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Enrico Checcucci
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy. .,Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy.
| | - Ilaria Stura
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano Granato
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Gabriele Volpi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Michele Sica
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Federico Piramide
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Paolo Verri
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano De Luca
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | | | - Giuseppe Migliaretti
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
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35
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Checcucci E, Manfredi M, De Cillis S, Amparore D, Piramide F, Piana A, Volpi G, Sica M, Verri P, Granato S, Piscitello S, Burgio M, Luciano O, Carbonaro B, Zamengo D, Quarà A, Della Corte M, Dibilio E, Alessio P, Pecoraro A, Sturia I, Migliaretti G, Fiori C, De Luca S, Porpiglia F. PD17-11 COMPARISON BETWEEN TARGET VS TARGET PLUS STANDARD BIOPSY FOR PROSTATE CANCER DIAGNOSIS IN BIOPSY NAÏVE PATIENTS: A RANDOMIZED CONTROLLED TRIAL. J Urol 2022. [DOI: 10.1097/ju.0000000000002555.11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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De Luca S, Checcucci E, Piramide F, Amparore D, Volpi G, De Cillis S, Piana A, Alessio P, Pecoraro A, Sica M, Verri P, Granato S, Burgio M, Ola L, Quarà A, Manfredi M, Fiori C, Porpiglia F. A prospective comparative and functional analysis of different ablative techniques for MRI/real-time ultrasound image fusion guided High Intensity Focused Ultrasound (HIFU). Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00395-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Amparore D, Piramide F, Pecoraro A, Checcucci E, De Cillis S, Piana A, Verri P, Granato S, Sica M, Burgio M, Carbonaro B, Manfredi M, Fiori C, Porpiglia F. Colored perfusion areas-based 3D virtual models: The Rainbow Kidney as a new tool to optimize the clamping strategy during robot-assisted partial nephrectomy. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)01340-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Checcucci E, Manfredi M, De Cillis S, Amparore D, Piramide F, Piana A, Volpi G, Sica M, Verri P, Granato S, Burgio M, Ola L, Carbonaro B, Zamengo D, Quarà A, Della Corte M, Busacca G, Alessio P, Pecoraro A, Stura I, Migliaretti G, Fiori C, De Luca S, Porpiglia F. Target vs. target plus standard biopsy in naïve patients: Results of a prospective randomized controlled trial. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00538-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Pecoraro A, Knipper S, Palumbo C, Rosiello G, Luzzago S, Deuker M, Tian Z, Shariat S, Saad F, Briganti A, Kapoor A, De Cillis S, Piana A, Piramide F, Sica M, Amparore D, Checcucci E, Manfredi M, Fiori C, Porpiglia F, Karakiewicz P. The effect of age on cancer-specifc mortality in T1a stage renal cell carcinoma patients: A population-based study across all treatment’s modalities. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00151-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Amparore D, Piramide F, Pecoraro A, Verri P, Checcucci E, De Cillis S, Piana A, Volpi G, Sica M, Granato S, Piscitello S, Zamengo D, Quarà A, Manfredi M, Fiori C, Porpiglia F. Optimizing selective clamping during 3-D guided robotic partial nephrectomy: The application of a mathematical tool to precisely establish the perfusion areas of the organ. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00419-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Checcucci E, Alladio E, De Cillis S, Granato S, Amparore D, Piana A, Piramide F, Volpi G, Sica M, Verri P, Piscitello S, Carbonaro B, Meziere J, Zamengo D, Della Corte M, Pecoraro A, Cattaneo G, Di Dio M, Manfredi M, Porpiglia F. Ten-year outcome of a prospective randomised trial comparing laparoscopic versus robot-assisted radical prostatectomy. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)01247-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Amparore D, Piramide F, Pecoraro A, Verri P, Checcucci E, De Cillis S, Piana A, Volpi G, Granato S, Sica M, Bellin A, Cattaneo G, Manfredi M, Fiori C, Porpiglia F. ICON3D technology: The intraoperative display for hyper-accuracy 3D models in laparoscopic partial nephrectomy. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)01322-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Amparore D, Piramide F, Checcucci E, Verri P, Pecoraro A, De Cillis S, Piana A, Volpi G, Sica M, Piscitello S, Burgio M, Alessio P, Busacca G, Della Corte M, Bellin A, Cattaneo G, Manfredi M, Fiori C, Porpiglia F. Intraoperative touchless gesture interaction with 3D virtual models during laparoscopic partial nephrectomy: Pilot experience with ICON3D technology. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00434-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Checcucci E, Manfredi M, Sica M, Amparore D, De Cillis S, Volpi G, Granato S, Carbonaro B, Piramide F, Meziere J, Verri P, Piana A, Poggio M, Cossu M, Fiori C, Porpiglia F. Robot-assisted-radical-cystectomy with total intracorporeal Y neobladder: Analysis of postoperative complications and functional outcomes with urodynamics findings. Eur J Surg Oncol 2021; 48:694-702. [PMID: 34949495 DOI: 10.1016/j.ejso.2021.12.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 11/25/2021] [Accepted: 12/10/2021] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES To describe our robotic Y intracorporeal neobladder (ICNB) technique and to report its post-operative complications and urodynamics (UD) findings. SUBJECTS and Methods: In this prospective study we enrolled patients affected by MIBC (T1-T4N0-N1M0) from 01/2017 to 06/2021 at our Centers. All the patients underwent robotic radical cystectomy (RARC) with Y-ICNB reconfiguration. Early and late complications were collected and classified according to Clavien-Dindo. Continence and potency at 1, 3, 6 and 12 months were evaluated. At the 3rd month of follow-up patients underwent UD. Finally, in a retrospective match paired analysis the functional outcomes of Y RARC patients were compared with a cohort of open Y radical cystectomy. RESULTS 45 patients were enrolled. Overall 30-day complications were observed in 25 (55,5%) patients and 30 to 90-days complications in 4 (8,9%). 9 patients (20%) had Clavien ≥3 complications. UDs revealed median neobladder capacity of 268 cc, with a median compliance of 13 ml/cm H20; the voiding phase showed a voiding volume and a post void residual (PVR) of 154 cc and 105 cc respectively. At 12 months of follow-up 4.4%, 15.5% and 4.4% of the patients experienced urge, stress and mix urinary incontinence respectively. The comparison between Y RARC and Y open RC revealed a higher neobladder capacity with open approach (p = 0.049) with subsequent better findings during the voiding phase in terms of maximum flow (p = 0.002), voiding volume (p = 0.001) and PVR (p = 0.01). Focusing on continence recovery, a slight trend in favor of RARC was shown without reaching the statistical significance. CONCLUSIONS Robotic Y-ICNB is feasible and safe as shown by the low rate of postoperative complications. Satisfying UD functional outcomes are achievable, both during filling and voiding phase.
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Affiliation(s)
- Enrico Checcucci
- Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy; Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy.
| | - Matteo Manfredi
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Michele Sica
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Daniele Amparore
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Sabrina De Cillis
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Gabriele Volpi
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Stefano Granato
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Beatrice Carbonaro
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Federico Piramide
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Juliette Meziere
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Paolo Verri
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Alberto Piana
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Massimiliano Poggio
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Marco Cossu
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Cristian Fiori
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
| | - Francesco Porpiglia
- Department of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy
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Porpiglia F, Amparore D, Checcucci E, Pecoraro A, Alessio P, Piana A, Piramide F, Volpi G, De Cillis S, Sica M, Granato S, Burgio M, Zamengo D, Poggio M, Manfredi M, Fiori C. ERAS protocol for minimizing the morbidity of robot-assisted radical cystectomy: A tertiary center experience. EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)02261-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Porpiglia F, Checcucci E, Pecoraro A, De Cillis S, Amparore D, Piramide F, Piana A, Piscitello S, Volpi G, Alessio P, Sica M, Granato S, Ola L, Zamengo D, Cattaneo G, Manfredi M, Fiori C. Is 3D technology able to reduce positive surgical margins during robot-assisted radical prostatectomy? EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)02231-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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Fiori C, Checcucci E, De Cillis S, Amparore D, Volpi G, Piramide F, Sica M, Piscitello S, Burgio M, Carbonaro B, Zamengo D, Cossu M, Manfredi M, Bollito E, Stura I, Migliaretti G, Porpiglia F. Target only vs target plus standard biopsy in naïve patients: analysis of detection rate and comparison with radical prostatectomy specimens. EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)00907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Enrico C, Rosati S, De Cillis S, Vagni M, Giordano N, Amparore D, Manfredi M, De Luca S, Cattaneo G, Pecoraro A, Alessio P, Volpi G, Piana A, Piramide F, Sica M, Verri P, Fiori C, Balestra G, Popriglia F. Evaluation of multiple prebiopsy variables via artificial intelligence with Fuzzy Logic Algorithms: a step forward in prediction of targeted biopsy outcomes. EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)00786-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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Porpiglia F, Amparore D, Piramide F, Checcucci E, Verri P, Alessio P, Pecoraro A, De Cillis S, Piana A, Volpi G, Sica M, Burgio M, Ola L, Mézière J, Bellin A, Piazzolla P, Manfredi M, Vezzetti E, Fiori C. Automatic 3D augmented reality robot assisted partial nephrectomy with indocyanine green guidance: a pilot study. EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)00730-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Passera R, De Luca S, Fiori C, Bollito E, Alessio P, Checcucci E, Amparore D, Pecoraro A, Volpi G, De Cillis S, Piana A, Piramide F, Sica M, Granato S, Zamengo D, Cattaneo G, Manfredi M, Donato Franco R, Montorsi F, Porpiglia F. The role of artificial intelligence and machine learning techniques to define the role of PSA levels and prostate cancer gene 3 score in prostate cancer diagnosis. EUR UROL SUPPL 2021. [DOI: 10.1016/s2666-1683(21)00788-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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