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CC BY-NC-ND 4.0 · Endosc Int Open 2024; 12(02): E227-E230
DOI: 10.1055/a-2226-0755
Innovation forum

Cloud technology and capsule endoscopy: A single-center users’ experience of remote online video analysis and reporting

Conor Costigan 
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
2   Trinity Academic Gastroenterology Group, Trinity College Dublin, Dublin, Ireland (Ringgold ID: RIN8809)
,
Caroline Walker
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
2   Trinity Academic Gastroenterology Group, Trinity College Dublin, Dublin, Ireland (Ringgold ID: RIN8809)
,
Jim O'Connell
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
2   Trinity Academic Gastroenterology Group, Trinity College Dublin, Dublin, Ireland (Ringgold ID: RIN8809)
,
Emmanuel Omallao
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
,
Thilagaraj Manoharan
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
,
Niamh Eagle
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
,
Yvonne Bailey
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
,
Fintan O'Hara
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
2   Trinity Academic Gastroenterology Group, Trinity College Dublin, Dublin, Ireland (Ringgold ID: RIN8809)
,
Deirdre Mc Namara
1   Gastroenterology, Tallaght University Hospital, Dublin, Ireland (Ringgold ID: RIN57976)
2   Trinity Academic Gastroenterology Group, Trinity College Dublin, Dublin, Ireland (Ringgold ID: RIN8809)
› Author AffiliationsTechnology provided. No monetary grant awarded
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Abstract

Background and study aims Telemedicine has progressed significantly in recent years, with newer, more integrated information technology systems improving healthcare delivery. The development of the world’s first cloud-based capsule platform could allow safe and timely virtual analysis of videos from a network of linked hospital centers. We aimed to assess the efficacy of Medtronic’s PillCam Remote Reader System.

Methods PillCam remote reader technical data were collected from the capsule endoscopy (CE) database over 8 months. User-reported performance was collect using an online survey. Outcomes included overall procedure success, video-upload/report-download rates and speeds, encryption/decryption rates, and user/reader satisfaction.

Results Data from 377 studies encompassing seven different readers was collected (318 small bowel capsules, 59 colon capsules). Overall procedure success was 100% (all videos reported). Two upload delays occurred (< 24 hours). There were no encryption/decryption errors. Seven of seven respondents felt it easy to access and use vs one of seve for the old system. Six of seven respondents felt department efficiency increased. Benefits included off-site reading and multisite-conferences. Issues included offsite difficulty accessing other hospital systems.

Conclusions PillCam remote reader is a reliable, secure, and effective capsule analysis platform and should be incorporated into any CE service development plan.

Keywords

Endoscopy Small Bowel - Capsule endoscopy - Training - Quality and logistical aspects - Image and data processing, documentatiton


Publication History

Received: 30 June 2023

Accepted after revision: 04 December 2023

Accepted Manuscript online:
11 December 2023

Article published online:
15 February 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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  • References

  • 1 Idan G, Meron G, Glukhovsky A. et al. Wireless capsule endoscopy. Nature 2000; 405: 417
    CrossrefPubMedSearch in Google Scholar
  • 2 Eliakim R, Yassin K, Niv Y. et al. Prospective multicentre performance evaluation of the second-generation colon capsule compared with colonoscopy. Endoscopy 2009; 41: 1026-1031
    Thieme ConnectPubMedSearch in Google Scholar
  • 3 Spada C, Hassan C, Munoz-Navas M. et al. Second-generation colon capsule endoscopy compared with colonoscopy. Gastrointest Endosc 2011; 74: 581-589.e1
    CrossrefPubMedSearch in Google Scholar
  • 4 Spada C, Pasha SF, Gross SA. et al. Accuracy of first- and second-generation colon capsules in endoscopic detection of colorectal polyps: a systematic review and meta-analysis. Clin Gastroenterol Hepatol 2016; 14: 1533-1543
    CrossrefPubMedSearch in Google Scholar
  • 5 Kjølhede T, Ølholm AM, Kaalby L. et al. Diagnostic accuracy of capsule endoscopy compared with colonoscopy for polyp detection: systematic review and metanalyses. Endoscopy 2021; 53: 713-721
    Thieme ConnectPubMedSearch in Google Scholar
  • 6 Spada C, Hassan C, Galmiche JP. et al. Colon capsule endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Guideline. Endoscopy 2012; 44: 527-536
    Thieme ConnectPubMedSearch in Google Scholar
  • 7 Spada C, Hassan C, Bellini D. et al. Imaging alternatives to colonoscopy: CT colonography and colon capsule. European Society of Gastrointestinal Endoscopy 5 (ESGE) and European Society of Gastrointestinal and Abdominal Radiology (ESGAR) Guideline – Update 2020. Endoscopy 2020; 52: 1127-1141
    CrossrefPubMedSearch in Google Scholar
  • 8 Pennazio M, Rondonotti E, Despott EJ. et al. Small-bowel capsule endoscopy and device-assisted enteroscopy for diagnosis and treatment of small-bowel disorders: European Society of Gastrointestinal Endoscopy (ESGE) Guideline-Update 2022. Endoscopy. Endoscopy 2023; 55: 58-95
    Thieme ConnectPubMedSearch in Google Scholar
  • 9 Mascarenhas Saraiva MJ, Afonso J, Ribeiro T. et al. Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network. BMJ Open Gastroenterology 2021; 8: e000753
    CrossrefPubMedSearch in Google Scholar