Introduction: Computer-aided diagnostic systems are emerging in the field of gastrointestinal endoscopy. In this study, we assessed the clinical performance of the computer-aided detection (CADe) of colonic adenomas using a new endoscopic artificial intelligence system. Methods: This was a single-center prospective randomized study including 415 participants allocated into the CADe group (n = 207) and control group (n = 208). All endoscopic examinations were performed by experienced endoscopists. The performance of the CADe was assessed based on the adenoma detection rate (ADR). Additionally, we compared the adenoma miss rate for the rectosigmoid colon (AMRrs) between the groups. Results: The basic demographic and procedural characteristics of the CADe and control groups were as follows: mean age, 54.9 and 55.9 years; male sex, 73.9% and 69.7% of participants; and mean withdrawal time, 411.8 and 399.0 s, respectively. The ADR was 59.4% in the CADe group and 47.6% in the control group (p = 0.018). The AMRrs was 11.9% in the CADe group and 26.0% in the control group (p = 0.037). Conclusion: The colonoscopy with the CADe system yielded an 11.8% higher ADR than that performed by experienced endoscopists alone. Moreover, there was no need to extend the examination time or request the assistance of additional medical staff to achieve this improved effectiveness. We believe that the novel CADe system can lead to considerable advances in colorectal cancer diagnosis.

1.
Zauber
AG
,
Winawer
SJ
,
O’Brien
MJ
,
Lansdorp-Vogelaar
I
,
van Ballegooijen
M
,
Hankey
BF
, et al
.
Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths
.
N Engl J Med
.
2012 Feb 23
;
366
(
8
):
687
96
.
2.
Kaminski
MF
,
Regula
J
,
Kraszewska
E
,
Polkowski
M
,
Wojciechowska
U
,
Didkowska
J
, et al
.
Quality indicators for colonoscopy and the risk of interval cancer
.
N Engl J Med
.
2010 May 13
;
362
(
19
):
1795
803
.
3.
Rex
DK
.
Colonoscopic withdrawal technique is associated with adenoma missrates
.
Gastrointest Endosc
.
2000 Jan
;
51
(
1
):
33
6
.
4.
Liu
A
,
Wang
H
,
Lin
Y
,
Fu
L
,
Liu
Y
,
Yan
S
, et al
.
Gastrointestinal endoscopy nurse assistance during colonoscopy and polyp detection: a PRISMA-compliant meta-analysis of randomized control trials
.
Medicine
.
2020 Aug 21
;
99
(
34
):
e21278
.
5.
Misawa
M
,
Kudo
SE
,
Mori
Y
,
Maeda
Y
,
Ogawa
Y
,
Ichimasa
K
, et al
.
Current status and future perspective on artificial intelligence for lower endoscopy
.
Dig Endosc
.
2021 Jan
;
33
(
2
):
273
84
.
6.
Weigt
J
,
Repici
A
,
Antonelli
G
,
Afifi
A
,
Kliegis
L
,
Correale
L
, et al
.
Performance of a new integrated computer-assisted system (CADe/CADx) for detection and characterization of colorectal neoplasia
.
Endoscopy
.
2022 Feb
;
54
(
02
):
180
4
.
7.
Sakamoto
T
,
Nakashima
H
,
Nakamura
K
,
Nagahama
R
,
Saito
Y
.
Performance of computer-aided detection and diagnosis of colorectal polyps compares to that of experienced endoscopists
.
Dig Dis Sci
.
2021 Aug 17
;
67
(
8
):
3976
83
.
8.
Moher
D
,
Hopewell
S
,
Schulz
KF
,
Montori
V
,
Gøtzsche
PC
,
Devereaux
PJ
, et al
.
CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials
.
Int J Surg
.
2012
;
10
(
1
):
28
55
.
9.
FUJIFILM Europe GmbH
.
ELUXEO Lite Brochure
. [cited 2022 August 8]. Available from: https://fujifilm-endoscopy.com/storage/app/media/products/files/ELUXEO%20Lite%20Brochure.pdf.
10.
Higurashi
T
,
Ashikari
K
,
Tamura
S
,
Takatsu
T
,
Misawa
N
,
Yoshihara
T
, et al
.
Comparison of the diagnostic performance of NBI, Laser-BLI and LED-BLI: a randomized controlled noninferiority trial
.
Surg Endosc
.
2022
;
36
(
10
):
7577
87
.
11.
Tanaka
S
,
Saitoh
Y
,
Matsuda
T
,
Igarashi
M
,
Matsumoto
T
,
Iwao
Y
, et al
.
Evidence-based clinical practice guidelines for management of colorectal polyps
.
J Gastroenterol
.
2021 Apr
;
56
(
4
):
323
35
.
12.
Lai
EJ
,
Calderwood
AH
,
Doros
G
,
Fix
OK
,
Jacobson
BC
.
The Boston bowel preparation scale: a valid and reliable instrument for colonoscopy-oriented research
.
Gastrointest Endosc
.
2009
;
69
(
3
):
620
5
.
13.
The Paris endoscopic classification of superficial neoplastic lesions: esophagus, stomach, and colon: November 30 to December 1, 2002
..
Gastrointest Endosc
.
2003 Dec
;
58
(
6 Suppl
):
S3–
43
.
14.
Japanese Society for Cancer of the Colon and Rectum
.
Japanese classification of colorectal, appendiceal, and anal carcinoma: the 3d English edition [secondary publication]
.
J Anus Rectum Colon
.
2019
;
3
(
4
):
175
95
.
15.
Sano
Y
,
Tanaka
S
,
Kudo
SE
,
Saito
S
,
Matsuda
T
,
Wada
Y
, et al
.
Narrow-band imaging (NBI) magnifying endoscopic classification of colorectal tumors proposed by the Japan NBI Expert Team
.
Dig Endosc
.
2016 Jul
;
28
(
5
):
526
33
.
16.
Saito
Y
,
Oka
S
,
Kawamura
T
,
Shimoda
R
,
Sekiguchi
M
,
Tamai
N
, et al
.
Colonoscopy screening and surveillance guidelines
.
Dig Endosc
.
2021 May
;
33
(
4
):
486
519
.
17.
Winawer
SJ
,
Zauber
AG
.
The advanced adenoma as the primary target of screening
.
Gastrointest Endosc Clin North America
.
2002
;
12
:
1
9
.
18.
Hassan
C
,
Spadaccini
M
,
Iannone
A
,
Maselli
R
,
Jovani
M
,
Chandrasekar
VT
, et al
.
Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis
.
Gastrointest Endosc
.
2021 Jan
;
93
(
1
):
77
85.e6
.
19.
Kanda
Y
.
Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics
.
Bone Marrow Transpl
.
2013 Mar
;
48
(
3
):
452
8
.
20.
Rex
DK
,
Schoenfeld
PS
,
Cohen
J
,
Pike
IM
,
Adler
DG
,
Fennerty
BM
, et al
.
Quality indicators for colonoscopy
.
Am J Gastroenterol
.
2015 Jan
;
110
(
1
):
72
90
.
21.
Corley
DA
,
Jensen
CD
,
Marks
AR
,
Zhao
WK
,
Lee
JK
,
Doubeni
CA
, et al
.
Adenoma detection rate and risk of colorectal cancer and death
.
N Engl J Med
.
2014 Apr 3
;
370
(
14
):
1298
306
.
22.
Kaminski
MF
,
Wieszczy
P
,
Rupinski
M
,
Wojciechowska
U
,
Didkowska
J
,
Kraszewska
E
, et al
.
Increased rate of adenoma detection associates with reduced risk of colorectal cancer and death
.
Gastroenterology
.
2017
;
153
(
1
):
98
105
.
23.
Floer
M
,
Meister
T
.
Endoscopic improvement of the adenoma detection rate during colonoscopy: where do we stand in 2015
.
Digestion
.
2016
;
93
(
3
):
202
13
.
24.
Bowel preparation before colonoscopy
..
Gastrointest Endosc
.
2015 Apr
;
81
(
4
):
781–
94
.
25.
Pohl
H
,
Bensen
SP
,
Toor
A
,
Gordon
SR
,
Levy
LC
,
Berk
B
, et al
.
Cap-assisted colonoscopy and detection of Adenomatous Polyps (CAP) study: a randomized trial
.
Endoscopy
.
2015 Oct
;
47
(
10
):
891
7
.
26.
Wu
J
,
Hu
B
.
The role of carbon dioxide insufflation in colonoscopy: a systematic review and meta-analysis
.
Endoscopy
.
2012
;
44
(
02
):
128
36
.
27.
Yoshida
N
,
Inoue
K
,
Tomita
Y
,
Kobayashi
R
,
Hashimoto
H
,
Sugino
S
, et al
.
An analysis about the function of a new artificial intelligence, CAD EYE with the lesion recognition and diagnosis for colorectal polyps in clinical practice
.
Int J Colorectal Dis
.
2021 Oct
;
36
(
10
):
2237
45
.
28.
Kumar
S
,
Thosani
N
,
Ladabaum
U
,
Friedland
S
,
Chen
AM
,
Kochar
R
, et al
.
Adenoma miss rates associated with a 3-minute versus 6-minute colonoscopy withdrawal time: a prospective, randomized trial
.
Gastrointest Endosc
.
2017
;
85
(
6
):
1273
80
.
29.
Kawamura
T
,
Oda
Y
,
Kobayashi
K
,
Matsuda
K
,
Kida
M
,
Tanaka
T
, et al
.
Colonoscopy withdrawal time and adenoma detection rate: a Japanese multicenter analysis
.
J Gastroenterol Hepatol Res
.
2017
;
6
(
1
):
2273
8
.
30.
Wallace
MB
,
Sharma
P
,
Bhandari
P
,
East
J
,
Antonelli
G
,
Lorenzetti
R
, et al
.
Impact of artificial intelligence on miss rate of colorectal neoplasia
.
Gastroenterology
.
2022 Jul
;
163
(
1
):
295
304.e5
.
31.
Kamba
S
,
Tamai
N
,
Saitoh
I
,
Matsui
H
,
Horiuchi
H
,
Kobayashi
M
, et al
.
Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial
.
J Gastroenterol
.
2021 Aug
;
56
(
8
):
746
57
.
32.
Kudo
SE
,
Kouyama
Y
,
Ogawa
Y
,
Ichimasa
K
,
Hamada
T
,
Kato
K
, et al
.
Depressed colorectal cancer: a new paradigm in early colorectal cancer
.
Clin Transl Gastroenterol
.
2020 Dec
;
11
(
12
):
e00269
.
33.
Kudo
SE
,
Misawa
M
,
Mori
Y
,
Hotta
K
,
Ohtsuka
K
,
Ikematsu
H
, et al
.
Artificial intelligence-assisted system improves endoscopic identification of colorectal neoplasms
.
Clin Gastroenterol Hepatol
.
2020
;
18
(
8
):
1874
81.e2
.
34.
Chino
A
,
Yamamoto
N
,
Kato
Y
,
Morishige
K
,
Ishikawa
H
,
Kishihara
T
, et al
.
The frequency of early colorectal cancer derived from sessile serrated adenoma/polyps among 1858 serrated polyps from a single institution
.
Int J Colorectal Dis
.
2016
;
31
(
2
):
343
9
.
35.
Saiki
H
,
Nishida
T
,
Yamamoto
M
,
Hayashi
S
,
Shimakoshi
H
,
Shimoda
A
, et al
.
Frequency of coexistent carcinoma in sessile serrated adenoma/polyps and traditional serrated adenomas removed by endoscopic resection
.
Endosc Int Open
.
2016
;
4
(
4
):
E451
8
.
36.
WHO Classification of Tumours Editorial Board
.
Digestive system tumours
. 5th ed.
Geneva
:
WHO classification of tumours. World Health Organization
;
2019
.
Vol. 8
. p.
163
9
.
37.
Ito
R
,
Ikematsu
H
,
Murano
T
,
Shinmura
K
,
Kojima
M
,
Kumahara
K
, et al
.
Diagnostic ability of Japan Narrow-Band Imaging Expert Team classification for colorectal lesions by magnifying endoscopy with blue laser imaging versus narrow-band imaging
.
Endosc Int Open
.
2021 Feb
;
09
(
02
):
E271
7
.
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