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17 results on '"Cisero, Edoardo"'

1. Visual extended reality tools in image-guided surgery in urology: a systematic review

Author

Checcucci, Enrico, Piana, Alberto, Volpi, Gabriele, Quarà, Alberto, De Cillis, Sabrina, Piramide, Federico, Burgio, Mariano, Meziere, Juliette, Cisero, Edoardo, Colombo, Marco, Bignante, Gabriele, Sica, Michele, Granato, Stefano, Verri, Paolo, Gatti, Cecilia, Alessio, Paolo, Di Dio, Michele, Alba, Stefano, Fiori, Cristian, Amparore, Daniele, and Porpiglia, Francesco

Published
2024
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3. Outcomes of Cytoreductive Radical Prostatectomy for Oligometastatic Prostate Cancer on Prostate-specific Membrane Antigen Positron Emission Tomography: Results of a Multicenter European Study

Author

Rajwa, Pawel, Robesti, Daniele, Chaloupka, Michael, Zattoni, Fabio, Giesen, Alexander, Huebner, Nicolai A., Krzywon, Aleksandra, Miszczyk, Marcin, Moll, Matthias, Stando, Rafał, Cisero, Edoardo, Semko, Sofiya, Checcucci, Enrico, Devos, Gaëtan, Apfelbeck, Maria, Gatti, Cecilia, Marra, Giancarlo, van den Bergh, Roderick C.N., Goldner, Gregor, Rasul, Sazan, Ceci, Francesco, Dal Moro, Fabrizio, Porpiglia, Francesco, Gontero, Paolo, Bjartell, Anders, Stief, Christian, Heidenreich, Axel, Joniau, Steven, Briganti, Alberto, Shariat, Shahrokh F., and Gandaglia, Giorgio

Published
2024
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5. PSMA PET-targeted Biopsy for Prostate Cancer Diagnosis: Initial Experience From a Multicenter Cohort

Author

Checcucci, Enrico, Bauckneht, Matteo, Cisero, Edoardo, Volpi, Gabriele, Rizzo, Alessio, Zattoni, Fabio, Bianchi, Lorenzo, De Angelis, Mario, Cangemi, Danilo, Heetman, Joris, Farolfi, Andrea, Piramide, Federico, De Cillis, Sabrina, Amparore, Daniele, De Luca, Stefano, Di Dio, Michele, Dal Moro, Fabrizio, Fanti, Stefano, Schiavina, Riccardo, Briganti, Alberto, Fiori, Cristian, Gandaglia, Giorgio, and Porpiglia, Francesco

Published
2024
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6. Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy.

Author

Amparore, Daniele, De Cillis, Sabrina, Alladio, Eugenio, Sica, Michele, Piramide, Federico, Verri, Paolo, Checcucci, Enrico, Piana, Alberto, Quarà, Alberto, Cisero, Edoardo, Manfredi, Matteo, Di Dio, Michele, Fiori, Cristian, and Porpiglia, Francesco

Subjects
MACHINE learning, DIGITAL rectal examination, ARTIFICIAL intelligence, RADICAL prostatectomy, DEEP learning, RETROPUBIC prostatectomy
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. [ABSTRACT FROM AUTHOR]

Published
2024
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7. 70 - Comparative evaluation of perioperative and functional outcomes between aquablation and robot-assisted simple prostatectomy for benign prostatic hyperplasia

Author

Sica, Michele, De Cillis, Sabrina, Amparore, Daniele, De Luca, Stefano, Quarà, Alberto, Checcucci, Enrico, Volpi, Gabriele, Piana, Alberto, Piramide, Federico, Verri, Paolo, Busacca, Giovanni, Cisero, Edoardo, Mandaletti, Martina, Colombo, Marco, Ferrando, Luca, Turcan, Alexandru, Garzena, Valentina, Garino, Davide, Manfredi, Matteo, Fiori, Cristian, and Porpiglia, Francesco

Published
2024
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8. 64 - Progress of machine-learning algorithm to predict the risk of incontinence after robot-assisted radical prostatectomy: XGBoost

Author

Sica, Michele, Amparore, Daniele, De Cillis, Sabrina, Alladio, Eugenio, Checcucci, Enrico, Volpi, Gabriele, Piana, Alberto, Piramide, Federico, Verri, Paolo, Busacca, Giovanni, Cisero, Edoardo, Mandaletti, Martina, Colombo, Marco, Mesterca, Anca Georgiana, Bignante, Gabriele, Trapella, Giulia, Turcan, Alexandru, Ribolzi, Bianca, Manfredi, Matteo, Fiori, Cristian, and Porpiglia, Francesco

Published
2024
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9. Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy.

Author

Amparore, Daniele, Sica, Michele, Verri, Paolo, Piramide, Federico, Checcucci, Enrico, De Cillis, Sabrina, Piana, Alberto, Campobasso, Davide, Burgio, Mariano, Cisero, Edoardo, Busacca, Giovanni, Di Dio, Michele, Piazzolla, Pietro, Fiori, Cristian, and Porpiglia, Francesco

Subjects
COMPUTER vision, SURGICAL robots, CONVOLUTIONAL neural networks, AUGMENTED reality, MACHINE learning, THREE-dimensional imaging
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. [ABSTRACT FROM AUTHOR]

Published
2024
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10. 89 - Two years after Aquablation for BPH-related LUTS: Functional and endoscopic results of a single center first clinical experience

Author

Amparore, Daniele, De Cillis, Sabrina, Checcucci, Enrico, De Luca, Stefano, Piana, Alberto, Piramide, Federico, Volpi, Gabriele, Sica, Michele, Verri, Paolo, Burgio, Mariano, Zamengo, Davide, Quarà, Alberto, Cisero, Edoardo, Della Corte, Marcello, Busacca, Giovanni, Mesterca, Anca Georgiana, Ortenzi, Michele, Manfredi, Matteo, Fiori, Cristian, and Porpiglia, Francesco

Published
2023
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11. 47 - Detection and management of early complication after robot-assisted radical cystectomy (RARC): Use and role of Tytocare™ telemedicine system in postoperative home care

Author

De Cilis, Sabrina, Amparore, Daniele, Checcucci, Enrico, Piramide, Federico, Piana, Alberto, Volpi, Gabriele, Sica, Michele, Burgio, Mariano, Zamengo, Davide, Cisero, Edoardo, Quarà, Alberto, Busacca, Giovanni, Della Corte, Marcello, Giordano, Angelo, Cidda, Dalia, Mandaletti, Martina, Ortenzi, Michele, Manfredi, Matteo, Fiori, Cristian, and Porpiglia, Francesco

Published
2023
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12. 31 - Different ablative techniques for MRI/real-time ultrasound image fusion guided High Intensity Focused Ultrasound (HIFU): A prospective comparative and functional analysis

Author

De Luca, Stefano, Checcucci, Enrico, Volpi, Gabriele, Piramide, Federico, Amparore, Daniele, De Cillis, Sabrina, Piana, Alberto, Alessio, Paolo, Sica, Michele, Verri, Paolo, Granato, Stefano, Burgio, Mariano, Cisero, Edoardo, Busacca, Giovanni, Manfredi, Matteo, Fiori, Cristian, and Porpiglia, Francesco

Published
2022
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13. V12-02 HOW TO MAXIMIZE ROBOTIC RADICAL PROSTATECTOMY OUTCOMES: SURGICAL AND NEW GENERATION IMAGING TIPS AND TRICKS.

Author

Piramide, Federico, Amparore, Daniele, Checcucci, Enrico, De Cillis, Sabrina T., Piana, Alberto, Volpi, Gabriele, Sica, Michele, Verri, Paolo, Burgio, Mariano, Meziere, Juliette, Busacca, Giovanni, Cisero, Edoardo, Marsero, Luca, Quarà, Alberto, Colombo, Marco, Mandaletti, Martina, Garzena, Valentina, Ribolzi, Bianca S., Manfredi, Matteo, and Fiori, Cristian

Subjects
RETROPUBIC prostatectomy, RADICAL prostatectomy, ROBOTICS
Published
2024
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14. MP49-20 POTENTIAL OF A COMBINED PSA-ZINC URINARY TEST FOR THE DETECTION OF PROSTATE CANCER.

Author

De Cillis, Sabrina Titti, Occhipinti, Sergio, Amparore, Daniele, Manfredi, Matteo, Checcucci, Enrico, Piana, Alberto, Piramide, Federico, Volpi, Gabriele, Sica, Michele, Verri, Paolo, Granato, Stefano, Quara', Alberto, Cisero, Edoardo, Busacca, Giovanni, Ortenzi, Michele, Colombo, Marco, Mesterca, Anca Georgiana, Gatti, Cecilia, Sterrantino, Andrea, and Garino, Davide

Subjects
PROSTATE cancer, EARLY detection of cancer, PROSTATE cancer patients
Published
2024
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15. V06-03 ROBOT-ASSISTED RENAL ARTERY ANEURYSM REMOVAL WITH 3D-PERFUSION MODELS ASSISTANCE.

Author

Amparore, Daniele, Piramide, Federico, Verri, Paolo, Barbuto, Simona, Checcucci, Enrico, De Cillis, Sabrina Titti, Piana, Alberto, Volpi, Gabriele, Michele, Sica, Burgio, Mariano, Meziere, Juliette, Quarà, Alberto, Busacca, Giovanni, Cisero, Edoardo, Marsero, Luca, Mandaletti, Martina, Gatti, Cecilia, Ortenzi, Michele, Ferrando, Luca, and Trapella, Giulia

Subjects
RENAL artery, ANEURYSMS, SURGICAL & topographical anatomy, PREOPERATIVE risk factors
Published
2024
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16. PD11-09 THE ADDED VALUE OF IMPLEMENTING PERFUSION VOLUMES IN THE COMPARISON OF DIFFERENT GENERATIONS OF 3D VIRTUAL MODELS FOR ROBOTIC PARTIAL NEPHRECTOMY(RAPN) PLANNING.

Author

Amparore, Daniele, Piramide, Federico, Manfredi, Matteo, Checcucci, Enrico, De Cillis, Sabrina Titti, Piana, Alberto, Volpi, Gabriele, Sica, Michele, Verri, Paolo, Burgio, Mariano, Quara', Alberto, Busacca, Giovanni, Cisero, Edoardo, Colombo, Marco, Mandaletti, Martina, Mesterca, Anca Georgiana, Gatti, Cecilia, Rosi, Francesco, Ribolzi, Bianca Sabrina, and Di Dio, Michele

Subjects
NEPHRECTOMY, PERFUSION, ROBOTICS, SURGICAL equipment, VORONOI polygons
Published
2024
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17. PD02-04 COMPARATIVE STUDY ABOUT EFFICACY ASSESSMENT OF TYTOCARE TELEMEDICINE SYSTEM FOR HOME-TELEMONITORING OF PATIENTS UNDERGOING RADICAL CYSTECTOMY.

Author

Amparore, Daniele, De Cillis, Sabrina Titti, Manfredi, Matteo, Checcucci, Enrico, Piana, Alberto, Piramide, Federico, Volpi, Gabriele, Sica, Michele, Verri, Paolo, Meziere, Juliette, Quara', Alberto, Cisero, Edoardo, Busacca, Giovanni, Colombo, Marco, Mandaletti, Martina, Sterrantino, Andrea, Garzena, Valentina, Trapella, Giulia, Ziani, Nadia, and Maria Venezia, Alessandro Enrico

Subjects
CYSTECTOMY, TELEMEDICINE, ILEAL conduit surgery, COMPARATIVE studies, URINARY diversion
Published
2024
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