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Optimising performance in clinical capsule endoscopy

Koulaouzidis, Anastasios LU (2020) In Lund University, Faculty of Medicine Doctoral Dissertation Series
Abstract
Video capsule endoscopy (VCE), perfomed by ingesting a small vitamin-sized camera pill, was developed over a
period of a couple of decades and –since its introduction in clinical practice at the dawn of the millennium– has
become an essential tool in the diagnosis and management of small bowel (SB) diseases. At the same time, other
fields such as minimally invasive diagnosis of other parts of the gastointestinal (GI) tract has been or is currently
explored as future applications of this technology. As a pure imaging modality, VCE ‘suffers’ from lack of additional
on-board data that could allow higher diagnostic accurary. This could be either advanced image enhancement or
biochemical sensors that could provide... (More)
Video capsule endoscopy (VCE), perfomed by ingesting a small vitamin-sized camera pill, was developed over a
period of a couple of decades and –since its introduction in clinical practice at the dawn of the millennium– has
become an essential tool in the diagnosis and management of small bowel (SB) diseases. At the same time, other
fields such as minimally invasive diagnosis of other parts of the gastointestinal (GI) tract has been or is currently
explored as future applications of this technology. As a pure imaging modality, VCE ‘suffers’ from lack of additional
on-board data that could allow higher diagnostic accurary. This could be either advanced image enhancement or
biochemical sensors that could provide relevant info. Furthermore, as VCE clips reading remains manual, it is heavily
dependent on the reviewer’s experience. Historically, VCE lesion miss rates have been reported at levels between
6% and 18%. There is also poor agreement on interobserver agreement and subsequent management decisionmaking.
The aim of this thesis was to increase the knowledge and to critically evaluate the importance of existing applications
as well as exploring and developing new applications to optimize use and diagnostic outcomes of VCE in clinical
practice. More specifically, to investigate the correlation between VCE imaging and faecal calprotectin (FC); to
develop a model for prediction of VCE results based on FC levels; to investigate and consolidate existing clinical
data on the utility of Fujinon Intelligent Chromoendoscopy (FICE) in improving delineation and detection rate for
pathological findings in VCE compared to conventional reading; to develop and validate a novel database aiming to
provide a reference for research on the development of medical decision support system (MDSS) for VCE; and to
develop an approach to capsule localisation and to provide estimations of relative movement of the VCE during its
passage through the GI tract.
Results of the studies showed that in patients with strong clinical suspicion of SB inflammation and negative
(conventional) bidirectional endoscopy, VCE should not be limited to patients with elevated biomarkers only.
Moreover, the correlation between FC levels and GI inflammation –as detected by VCE– was moderate and FC=>76
mcg/g may be associated with appreciable SB inflammation on VCE in patients with negative prior diagnostic
workup. Furthemore, FICE seems to perform better for pigmented lesions such as angiectasias, both in lesion
delineation and detection. However, overall using the three FICE modes did not significantly improve detection rate
or the quality of visualization of the most common pathological findings seen on SB VCE. We developed KID, the
first database of VCE images and videos with both graphic and semantic annotations, developed specifically for
MDSS research. KID provides a platform for data sharing and software development. The experiments detailed are
proof-of-principle studies demonstrating the potential for KID to fulfil this role. Moreover, we presented methods for
both 2D and 3D localisation of capsules using visual information alone. Such methods are feasible and have
potential to be of clinical use. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Baatrup, Gunnar, Svendborg
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Capsule endoscopy, small bowel innovation, image improvement, software, localisation, KID, FICE
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
issue
2020:75
pages
81 pages
publisher
Lund University, Faculty of Medicine
defense location
Diagnostiskt centrun, Carl-Bertil Laurells gata 9, Skånes Universitetssjukhus i Malmö
defense date
2020-06-09 09:00:00
ISSN
1652-8220
ISBN
978-91-7619-937-4
language
English
LU publication?
yes
id
c571aae8-bc68-4c6c-9e3e-d0d4ca11b37d
date added to LUP
2020-05-11 13:01:25
date last changed
2020-05-25 09:41:15
@phdthesis{c571aae8-bc68-4c6c-9e3e-d0d4ca11b37d,
  abstract     = {{Video capsule endoscopy (VCE), perfomed by ingesting a small vitamin-sized camera pill, was developed over a<br>
period of a couple of decades and –since its introduction in clinical practice at the dawn of the millennium– has<br>
become an essential tool in the diagnosis and management of small bowel (SB) diseases. At the same time, other<br>
fields such as minimally invasive diagnosis of other parts of the gastointestinal (GI) tract has been or is currently<br>
explored as future applications of this technology. As a pure imaging modality, VCE ‘suffers’ from lack of additional<br>
on-board data that could allow higher diagnostic accurary. This could be either advanced image enhancement or<br>
biochemical sensors that could provide relevant info. Furthermore, as VCE clips reading remains manual, it is heavily<br>
dependent on the reviewer’s experience. Historically, VCE lesion miss rates have been reported at levels between<br>
6% and 18%. There is also poor agreement on interobserver agreement and subsequent management decisionmaking.<br>
The aim of this thesis was to increase the knowledge and to critically evaluate the importance of existing applications<br>
as well as exploring and developing new applications to optimize use and diagnostic outcomes of VCE in clinical<br>
practice. More specifically, to investigate the correlation between VCE imaging and faecal calprotectin (FC); to<br>
develop a model for prediction of VCE results based on FC levels; to investigate and consolidate existing clinical<br>
data on the utility of Fujinon Intelligent Chromoendoscopy (FICE) in improving delineation and detection rate for<br>
pathological findings in VCE compared to conventional reading; to develop and validate a novel database aiming to<br>
provide a reference for research on the development of medical decision support system (MDSS) for VCE; and to<br>
develop an approach to capsule localisation and to provide estimations of relative movement of the VCE during its<br>
passage through the GI tract.<br>
Results of the studies showed that in patients with strong clinical suspicion of SB inflammation and negative<br>
(conventional) bidirectional endoscopy, VCE should not be limited to patients with elevated biomarkers only.<br>
Moreover, the correlation between FC levels and GI inflammation –as detected by VCE– was moderate and FC=&gt;76<br>
mcg/g may be associated with appreciable SB inflammation on VCE in patients with negative prior diagnostic<br>
workup. Furthemore, FICE seems to perform better for pigmented lesions such as angiectasias, both in lesion<br>
delineation and detection. However, overall using the three FICE modes did not significantly improve detection rate<br>
or the quality of visualization of the most common pathological findings seen on SB VCE. We developed KID, the<br>
first database of VCE images and videos with both graphic and semantic annotations, developed specifically for<br>
MDSS research. KID provides a platform for data sharing and software development. The experiments detailed are<br>
proof-of-principle studies demonstrating the potential for KID to fulfil this role. Moreover, we presented methods for<br>
both 2D and 3D localisation of capsules using visual information alone. Such methods are feasible and have<br>
potential to be of clinical use.}},
  author       = {{Koulaouzidis, Anastasios}},
  isbn         = {{978-91-7619-937-4}},
  issn         = {{1652-8220}},
  keywords     = {{Capsule endoscopy; small bowel innovation; image improvement; software; localisation; KID; FICE}},
  language     = {{eng}},
  number       = {{2020:75}},
  publisher    = {{Lund University, Faculty of Medicine}},
  school       = {{Lund University}},
  series       = {{Lund University, Faculty of Medicine Doctoral Dissertation Series}},
  title        = {{Optimising performance in clinical capsule endoscopy}},
  url          = {{https://lup.lub.lu.se/search/files/79440714/Anastasios_Koulaouzidis_ALL.pdf}},
  year         = {{2020}},
}