P A Boland, P D McEntee, J Cucek, S Erzen, E Niemiec, M Galligan, T Petropoulou, J B Burke, J Knol, R Hompes, J Tuynman, F Aigner, A Arezzo, R A Cahill
{"title":"CLASSICA软件作为医疗器械试验的协议。","authors":"P A Boland, P D McEntee, J Cucek, S Erzen, E Niemiec, M Galligan, T Petropoulou, J B Burke, J Knol, R Hompes, J Tuynman, F Aigner, A Arezzo, R A Cahill","doi":"10.1080/13645706.2025.2540482","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Contemporary methods for detecting cancer in significant rectal neoplasia before transanal excision are suboptimal. Fluorescence angiography (FA) coupled with artificial intelligence (AI) classification methods may add value. This regulated clinical trial stage of the CLASSICA Project will validate the concept using software as medical device.</p><p><strong>Methods/design: </strong>This multi-centre prospective study will validate a real-time AI-driven FA method for the digital detection of rectal cancer in-situ and endoscopic biopsy guidance. Traditional endoscopic biopsies and excision specimen pathology are the comparative standard aiming to enrol up to 127 patients from seven surgical cancer centres across five countries with trans-European data sharing protocols balancing General Data Protection Regulation (GDPR), Good Clinical Practice (GCP) and adherence to FAIR principles.</p><p><strong>Discussion: </strong>This CLASSICA phase builds on prior prospective multi-centre and multidisciplinary collaboration that has already recruited 130 patients demonstrating patient and physician capability for the fundamental technique and enlarging the prior training dataset (n = 200 FA videos). Alongside the development of a secure, online data-sharing platform and clinical-grade medical device software, trial protocols have begun institutional approval processes aiming to determine accuracy and further optimisation.</p><p><strong>Trial details and registration: </strong>The CLASSICA Project is registered with ClinicalTrials.gov [NCT05793554] and is funded by Horizon Europe [Project No.101057321]. CLASSICAPROJECT.EU.</p>","PeriodicalId":18537,"journal":{"name":"Minimally Invasive Therapy & Allied Technologies","volume":" ","pages":"1-6"},"PeriodicalIF":2.0000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Protocol for CLASSICA software as medical device trial.\",\"authors\":\"P A Boland, P D McEntee, J Cucek, S Erzen, E Niemiec, M Galligan, T Petropoulou, J B Burke, J Knol, R Hompes, J Tuynman, F Aigner, A Arezzo, R A Cahill\",\"doi\":\"10.1080/13645706.2025.2540482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Contemporary methods for detecting cancer in significant rectal neoplasia before transanal excision are suboptimal. Fluorescence angiography (FA) coupled with artificial intelligence (AI) classification methods may add value. This regulated clinical trial stage of the CLASSICA Project will validate the concept using software as medical device.</p><p><strong>Methods/design: </strong>This multi-centre prospective study will validate a real-time AI-driven FA method for the digital detection of rectal cancer in-situ and endoscopic biopsy guidance. Traditional endoscopic biopsies and excision specimen pathology are the comparative standard aiming to enrol up to 127 patients from seven surgical cancer centres across five countries with trans-European data sharing protocols balancing General Data Protection Regulation (GDPR), Good Clinical Practice (GCP) and adherence to FAIR principles.</p><p><strong>Discussion: </strong>This CLASSICA phase builds on prior prospective multi-centre and multidisciplinary collaboration that has already recruited 130 patients demonstrating patient and physician capability for the fundamental technique and enlarging the prior training dataset (n = 200 FA videos). Alongside the development of a secure, online data-sharing platform and clinical-grade medical device software, trial protocols have begun institutional approval processes aiming to determine accuracy and further optimisation.</p><p><strong>Trial details and registration: </strong>The CLASSICA Project is registered with ClinicalTrials.gov [NCT05793554] and is funded by Horizon Europe [Project No.101057321]. 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Protocol for CLASSICA software as medical device trial.
Background: Contemporary methods for detecting cancer in significant rectal neoplasia before transanal excision are suboptimal. Fluorescence angiography (FA) coupled with artificial intelligence (AI) classification methods may add value. This regulated clinical trial stage of the CLASSICA Project will validate the concept using software as medical device.
Methods/design: This multi-centre prospective study will validate a real-time AI-driven FA method for the digital detection of rectal cancer in-situ and endoscopic biopsy guidance. Traditional endoscopic biopsies and excision specimen pathology are the comparative standard aiming to enrol up to 127 patients from seven surgical cancer centres across five countries with trans-European data sharing protocols balancing General Data Protection Regulation (GDPR), Good Clinical Practice (GCP) and adherence to FAIR principles.
Discussion: This CLASSICA phase builds on prior prospective multi-centre and multidisciplinary collaboration that has already recruited 130 patients demonstrating patient and physician capability for the fundamental technique and enlarging the prior training dataset (n = 200 FA videos). Alongside the development of a secure, online data-sharing platform and clinical-grade medical device software, trial protocols have begun institutional approval processes aiming to determine accuracy and further optimisation.
Trial details and registration: The CLASSICA Project is registered with ClinicalTrials.gov [NCT05793554] and is funded by Horizon Europe [Project No.101057321]. CLASSICAPROJECT.EU.
期刊介绍:
Minimally Invasive Therapy and Allied Technologies (MITAT) is an international forum for endoscopic surgeons, interventional radiologists and industrial instrument manufacturers. It is the official journal of the Society for Medical Innovation and Technology (SMIT) whose membership includes representatives from a broad spectrum of medical specialities, instrument manufacturing and research. The journal brings the latest developments and innovations in minimally invasive therapy to its readers. What makes Minimally Invasive Therapy and Allied Technologies unique is that we publish one or two special issues each year, which are devoted to a specific theme. Key topics covered by the journal include: interventional radiology, endoscopic surgery, imaging technology, manipulators and robotics for surgery and education and training for MIS.