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 wi...
| Publicado en: | Minimally Invasive Therapy & Allied Technologies Vol. 34; no. 6; pp. 441 - 447 |
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| Autores principales: | , , , , , , , , , , , , , |
| Formato: | pictorial protocol tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Dec2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189706708&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189706708 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13645706 J4S jtl: Minimally Invasive Therapy & Allied Technologies issn: 13645706 maglogo: Y pubinfo: dt: Dec2025 vid: 34 iid: 6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 189706708 187517141 189706708 189706708 10.1080/13645706.2025.2540482 189706708 ppf: 441 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Protocol for CLASSICA software as medical device trial. aug: au: Boland, PA McEntee, PD Cucek, J Erzen, S Niemiec, E Galligan, M Petropoulou, T Burke, JB Knol, J Hompes, R Tuynman, J Aigner, F Arezzo, A Cahill, RA affil: UCD Centre for Precision Surgery, School of Medicine, University College Dublin, Dublin, Ireland sug: subj: Software Utilization Software Design Artificial Intelligence Utilization Rectal Neoplasms Diagnosis Algorithms Utilization Guideline Adherence Evaluation Patient Safety Evaluation Clinical Trials ab: 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 pubtype: Academic Journal doctype: pictorial protocol tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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