Computer Assisted Detection of Neoplasia During Colonoscopy Evaluation (CADeNCE)
Conditions: Colorectal Neoplasms
Sponsor: VA Puget Sound Health Care System

Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation 
(CADeNCE) 
 
 
Study Protocol 
 
October 8, 2025 
 
NCT05888623 
 
 
 
Jason A Dominitz, MD, MHS 
Executive Director, National Gastroenterology and Hepatology Program (NGHP) 
Director, National Colorectal Cancer Screening Program 
Veterans Health Administration, Washington, DC 
Professor of Medicine, Division of Gastroenterology 
University of Washington School of Medicine, Seattle, WA 
 
Andrew J. Gawron, MD, PhD 
Associate Director for Quality, NGHP 
Professor of Medicine, Division of Gastroenterology 
University of Utah School of Medicine, Salt Lake City, UT 
 
Grace McKee, PhD 
Measurement Science Quality Enhancement Research Initiative  
San Francisco VA Medical Center, San Francisco, CA 
Division of General Internal Medicine,  
University of California School of Medicine, San Francisco, California, USA 
 
Katherine J. Hoggatt, PhD, MPH 
Measurement Science Quality Enhancement Research Initiative  
San Francisco VA Medical Center, San Francisco, CA 
Professor of Medicine, Department of Medicine  
University of California School of Medicine, San Francisco, California 
 
Tonya Kaltenbach, MD, MS, MEd 
Measurement Science Quality Enhancement Research Initiative  
San Francisco VA Medical Center, San Francisco, CA 
Professor of Medicine, Division of Gastroenterology 
University of California School of Medicine, San Francisco, California 
 
 

2 
 
Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation 
(CADeNCE) 
 
 
Contents 
 
 
Description 
 
 
 
 
 
 
 
 
Page Number 
Study protocol version 1.0 
 
 
 
 
 
 
 
3 
Study protocol version 1.1 
 
 
 
 
 
 
 
9 
Study protocol version 2.0 
 
 
 
 
 
 
 
16 
Study protocol version 2.1 
 
 
 
 
 
 
 
22 
 
 

3 
 
Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation (CADeNCE) 
 
Study Protocol Version 1.0 
 
March 6, 2023 
 
  
Evaluation Team: 
Jason A. Dominitz, MD, MHS 
Tonya Kaltenbach, MD, MS, MEd 
Andrew Gawron, MD, PhD 
Grace McKee, PhD 
 
 
 
 
Background: Colonoscopy is a key diagnostic and therapeutic procedure for the prevention of 
colorectal cancer (CRC) incidence and mortality. Central to colonoscopy’s effectiveness is the 
identification and removal of colorectal neoplasia, including adenomatous polyps and sessile 
serrated lesions. The endoscopist’s adenoma detection rate (ADR), classically defined as the 
proportion of screening colonoscopies in which one or more adenomas are detected, has been 
demonstrated to be strongly inversely associated with their patients’ risk of post-colonoscopy 
colorectal cancer. Therefore, improving adenoma detection is a major target of quality 
assurance efforts.  
  
The Veterans Health Administration’s (VA) National Gastroenterology and Hepatology Program 
(NGHP) has embarked on a number of efforts to measure, monitor, and improve colonoscopy 
quality across the VA enterprise. One of these efforts is the VA Endoscopy Quality Improvement 
Program (VA-EQuIP) which is a collaboration between the VA Quality Enhancement Research 
Initiative (QUERI), the Office of Research and Development (ORD) and the NGHP. Investigators 
in the Measurement Science QUERI have developed processes for assessing the ADR of 
individual physicians and facilities through extraction of data from the Corporate Data 
Warehouse (CDW). Through collaboration with the VA Clinical Assessment Reporting and 
Tracking Program (CART), more detailed colonoscopy report information is available for 29 VA 
medical centers, with additional VA facilities expected to be added to the list soon. Overall, the 
VA ADR for colonoscopies of all indications is 47%1, well above the benchmark of 30% for men 
undergoing screening colonoscopy. 
  
In 2021, the FDA approved the first artificial intelligence (AI) system for computer assisted 
detection (CADe) of colorectal neoplasia. These CADe devices project an image on the 
endoscopy monitor (i.e., a bounding box) to alert the endoscopist to the presence of a 
suspected polyp within the colon. Initial studies, including randomized controlled trials, have 
demonstrated that use of CADe systems result in a significant improvement in adenoma 
detection, with a reduction in the miss rate of adenomas (i.e., fewer adenomas are found on a 

4 
 
second colonoscopy when the first colonoscopy was performed with a CADe system compared 
to when the first colonoscopy did not use CADe).2-4 However, more recent studies have not 
demonstrated a clear benefit of these devices.5,6 Moreover, most of the additional adenomas 
that are detected are diminutive polyps, the vast majority of which are thought to be of 
minimal, if any, clinical significance. When multiple adenomas are detected during colonoscopy, 
current guidelines recommend repeating colonoscopy sooner than would otherwise be 
recommended. Also, the CADe systems may have unintended consequences, such as creating 
alert fatigue through false alarms or negatively impacting training of gastroenterology fellows.  
  
Objective: The NGHP planned to formally evaluate the quantitative and qualitative impact and 
outcomes of use of CADe within VA medical centers following the purchase and distribution to 
randomly selected gastrointestinal endoscopy units.   
  
Setting: Veteran Health Administration (VA) Medical Centers 
  
Intervention: As part of ongoing quality assurance efforts, the NGHP purchased 115 Medtronic 
GI Genius® CADe devices in late 2022. All facilities were sorted according to their facility-level 
ADR (for all indications) and categorized as below 30%, 30% to <40% or ≥40%. A random 
number generator was then used to sort the VA medical centers within each of these 3 ADR 
strata. Alternating facilities (i.e., approximately 50%) of facilities within the 2 lower ADR 
stratum were allocated the CADe devices. To assure equitable distribution of the remaining 
CADe devices across the 18 VA Integrated Service Networks (VISNs), the remaining devices 
were offered to randomly selected facilities (all within the ≥40% ADR stratum) such that each 
VISN had 2-3 facilities with CADe devices.  
  
Upon identification of a potential site, the Gastroenterology Section Chief (or equivalent) at 
that randomly selected site was asked if they were interested in receiving the devices and if all 
endoscopists at their facility would agree to use the device during colonoscopy. The physicians 
were not mandated to use the devices but were asked to notify the NGHP if endoscopists were 
not routinely using the devices so that the devices could be reallocated to other VA facilities 
that would make use of the CADe devices. Upon receiving concurrence from the 
Gastroenterology Section Chief, the devices were installed in all procedure rooms that are 
routinely used for colonoscopy at that facility. The devices were not installed on travel carts for 
emergency procedures. One facility did decline to receive the devices due to concerns that the 
devices would negatively impact efficiency in the endoscopy unit. That facility was replaced 
with another randomly selected VA medical center. Ultimately, 43 VA facilities received and 
installed the 115 CADe devices.  
  
Outcomes: 
1) VA Facility Level 
a) Adenoma detection rate for all indications 
i) The proportion of colonoscopies in which one or more adenomas are found. 
ii) Limit to ages 45-75 years 
iii) Also evaluate for all ages 

5 
 
b) Number of polyps per colonoscopy 
i) Limited to Provation sites 
c) Size of polyps detected 
i) Limited to Provation sites 
ii) Average size 
iii) Categorized as 
(1) 1-5mm 
(2) 6-9mm 
(3) ≥10mm 
d) Surveillance recommendations after colonoscopy  
i) Use health factors for follow-up recommendation after colonoscopy 
ii) Limit to ages 45-65 years 
iii) Repeat colonoscopy interval 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
iv) Resume average risk screening 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
v) No further screening 
vi) No health factor found 
e) Withdrawal time when no maneuvers are performed 
i) Limited to Provation Sites (unless EndoPro comes online) 
f) Withdrawal time, including the performance of maneuvers 
i) Limited to Provation Sites (unless EndoPro comes online) 
g) Total procedure time 
i) When no maneuvers are performed 
ii) When all procedures are included 
h) Bowel preparation quality 
i) Adequate vs. inadequate 
ii) Excellent vs. good vs. fair vs. poor 

6 
 
iii) Boston Bowel Preparation Score 
i) Adenocarcinoma detection rate 
i) The proportion of colonoscopies found to have adenocarcinoma 
 
2) VA Provider Level 
a) Adenoma detection rate for all indications 
i) The proportion of colonoscopies in which one or more adenomas are found. 
ii) Limit to ages 45-75 years 
iii) Also evaluate for all ages 
b) Number of polyps per colonoscopy 
c) Size of polyps detected 
i) Average size 
ii) Categorized as 
(1) 1-5mm 
(2) 6-9mm 
(3) ≥10mm 
d) Surveillance recommendations after colonoscopy  
i) Use health factors for follow-up recommendation after colonoscopy 
ii) Limit to ages 45-65 years 
iii) Repeat colonoscopy interval 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
iv) Resume average risk screening 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
v) No further screening/surveillance 
vi) No recommendation found 
e) Withdrawal time when no maneuvers are performed 
i) Limited to Provation Sites (unless EndoPro comes online) 
f) Withdrawal time, including the performance of maneuvers 

7 
 
i) Limited to Provation Sites (unless EndoPro comes online) 
g) Total procedure time 
i) When no maneuvers are performed  
ii) When all procedures are included 
h) Bowel preparation quality 
i) Adequate vs. inadequate 
ii) Excellent vs. good vs. fair vs. poor 
iii) Boston Bowel Preparation Score 
i) Adenocarcinoma detection rate 
i) The proportion of colonoscopies found to have adenocarcinoma 
j) Qualitative assessment (from survey) 
i) Benefits of CADe 
ii) Negative aspects of CADe 
iii) False positive alerts 
iv) Impact on fellow training 
v) Overall satisfaction with CADe 
 
Database: 
Colonoscopy details are extracted from the Corporate Data Warehouse and, when possible, the 
endoscopy reporting system via the CART database, including: 
1. VA facility  
2. Patient characteristics 
a. Age 
b. Gender 
c. Race 
d. Ethnicity 
3. Colonoscopy indication 
a. Screening 
b. Surveillance 
c. FOBT+ 
d. Other 
e. Unknown 
4. Bowel preparation quality 
a. Adequate vs. inadequate 
b. Aronchick 
c. Boston Bowel Preparation Score 
5. Colonoscopy findings 
a. Adenoma detection 
b. Adenocarcinoma detection 
c. Number of polyps detected 
d. Number of polyps detected according to size 
i. 1-5mm 
ii. 6-9mm 
iii. ≥10mm 

8 
 
e. Withdrawal time 
f. Total procedure time 
6. Follow-up Plans after colonoscopy (using Gap Reminder health factors) 
7. A new variable coding the presence or absence of CADe will be added to each colonoscopy 
based upon the date of installation of the GI Genius CADe device at each facility.  
a. In order to allow for endoscopists to adapt to performing colonoscopy with the 
CADe device, all colonoscopies performed within 21 days of the date of installation 
will be classified as “CADe Training” and will be excluded from the analysis.  
  
 Statistical Methods: 
1. Within facility comparison (pre- vs. post): All outcome variables will be compared between 
the pre-CADe and post-CADe time periods (starting 21 days after CADe installation). We will 
aim for a minimum of 3 months on post-CADe assessment, compared to 6 months of pre-
CADe colonoscopies. 
2. Between facility comparison: The 43 VA facilities that received CADe devices will be 
compared to over 100 VA facilities that did not receive CADe devices.  
3. Categorical variables will be compared using the Chi-square test. 
4. Continuous variables will be compared with the t-test or Wilcoxon rank sums test, as 
appropriate. 
5. To adjust for potential confounders, multivariable models will be constructed.  
a. Logistic regression will be used for dichotomous outcomes (e.g., adenoma detection) 
b. Polytomous logistic regression will be used for ordinal outcomes (e.g., colonoscopy 
surveillance recommendations) 
c. Linear regression will be used for continuous outcomes (e.g., withdrawal time) 
d. Shell tables are provided below, detailing the variables to be included in the models 
  
   
 
 

9 
 
Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation (CADeNCE) 
 
Study Protocol Version 1.1 
 
June 3, 2023 
 
 
Evaluation Team: 
Jason A. Dominitz, MD, MHS 
Tonya Kaltenbach, MD, MS, MEd 
Andrew J. Gawron, MD, PhD 
Grace McKee, PhD 
 
 
Summary of major revisions and rationale: 
 
(a) Addition of survey methodology 
(i) To assess the end-user experience (i.e., endoscopists), a Microsoft Office Forms survey 
was developed by NGHP leadership for distribution via email to VA endoscopists 
(b) Addition of study oversight information 
 

10 
 
 
Background: Colonoscopy is a key diagnostic and therapeutic procedure for the prevention of 
colorectal cancer (CRC) incidence and mortality. Central to colonoscopy’s effectiveness is the 
identification and removal of colorectal neoplasia, including adenomatous polyps and sessile 
serrated lesions. The endoscopist’s adenoma detection rate (ADR), classically defined as the 
proportion of screening colonoscopies in which one or more adenomas are detected, has been 
demonstrated to be strongly inversely associated with their patients’ risk of post-colonoscopy 
colorectal cancer. Therefore, improving adenoma detection is a major target of quality 
assurance efforts.  
  
The Veterans Health Administration’s (VA) National Gastroenterology and Hepatology Program 
(NGHP) has embarked on a number of efforts to measure, monitor, and improve colonoscopy 
quality across the VA enterprise. One of these efforts is the VA Endoscopy Quality Improvement 
Program (VA-EQuIP) which is a collaboration between the VA Quality Enhancement Research 
Initiative (QUERI), the Office of Research and Development (ORD) and the NGHP. Investigators 
in the Measurement Science QUERI have developed processes for assessing the ADR of 
individual physicians and facilities through extraction of data from the Corporate Data 
Warehouse (CDW). Through collaboration with the VA Clinical Assessment Reporting and 
Tracking Program (CART), more detailed colonoscopy report information is available for 29 VA 
medical centers, with additional VA facilities expected to be added to the list soon. Overall, the 
VA ADR for colonoscopies of all indications is 47%1, well above the benchmark of 30% for men 
undergoing screening colonoscopy. 
  
In 2021, the FDA approved the first artificial intelligence (AI) system for computer assisted 
detection (CADe) of colorectal neoplasia. These CADe devices project an image on the 
endoscopy monitor (i.e., a bounding box) to alert the endoscopist to the presence of a 
suspected polyp within the colon. Initial studies, including randomized controlled trials, have 
demonstrated that use of CADe systems result in a significant improvement in adenoma 
detection, with a reduction in the miss rate of adenomas (i.e., fewer adenomas are found on a 
second colonoscopy when the first colonoscopy was performed with a CADe system compared 
to when the first colonoscopy did not use CADe).2-4 However, more recent studies have not 
demonstrated a clear benefit of these devices.5,6 Moreover, most of the additional adenomas 
that are detected are diminutive polyps, the vast majority of which are thought to be of 
minimal, if any, clinical significance. When multiple adenomas are detected during colonoscopy, 
current guidelines recommend repeating colonoscopy sooner than would otherwise be 
recommended. Also, the CADe systems may have unintended consequences, such as creating 
alert fatigue through false alarms or negatively impacting training of gastroenterology fellows.  
  
Objective: The NGHP planned to formally evaluate the quantitative and qualitative impact and 
outcomes of use of CADe within VA medical centers following the purchase and distribution to 
randomly selected gastrointestinal endoscopy units.   
  
Setting: Veteran Health Administration (VA) Medical Centers 
  

11 
 
Intervention: As part of ongoing quality assurance efforts, the NGHP purchased 115 Medtronic 
GI Genius® CADe devices in late 2022. All facilities were sorted according to their facility-level 
ADR (for all indications) and categorized as below 30%, 30% to <40% or ≥40%. A random 
number generator was then used to sort the VA medical centers within each of these 3 ADR 
strata. Alternating facilities (i.e., approximately 50%) of facilities within the 2 lower ADR 
stratum were allocated the CADe devices. To assure equitable distribution of the remaining 
CADe devices across the 18 VA Integrated Service Networks (VISNs), the remaining devices 
were offered to randomly selected facilities (all within the ≥40% ADR stratum) such that each 
VISN had 2-3 facilities with CADe devices.  
  
Upon identification of a potential site, the Gastroenterology Section Chief (or equivalent) at 
that randomly selected site was asked if they were interested in receiving the devices and if all 
endoscopists at their facility would agree to use the device during colonoscopy. The physicians 
were not mandated to use the devices but were asked to notify the NGHP if endoscopists were 
not routinely using the devices so that the devices could be reallocated to other VA facilities 
that would make use of the CADe devices. Upon receiving concurrence from the 
Gastroenterology Section Chief, the devices were installed in all procedure rooms that are 
routinely used for colonoscopy at that facility. The devices were not installed on travel carts for 
emergency procedures. One facility did decline to receive the devices due to concerns that the 
devices would negatively impact efficiency in the endoscopy unit. That facility was replaced 
with another randomly selected VA medical center. Ultimately, 43 VA facilities received and 
installed the 115 CADe devices.  
  
Survey: To assess the end-user experience, a Microsoft Forms electronic survey will be 
distributed to VA endoscopists who performed at least 25 colonoscopies between December 1, 
2022 and May 31, 2023. Endoscopists will be invited via email with up to two follow-up 
reminders. Survey questions will address self-reported use of CADe for different colonoscopy 
indications, assessment of the benefits and negative impacts of CADe (e.g., impact on neoplasia 
detection or withdrawal time), and overall impression of CADe. Survey completion will be 
optional.  Only staff gastroenterologists and surgeons will be eligible to complete the survey. 
 
Oversight: This quality assurance evaluation was conducted under the auspices of the VA 
NGHP. Evaluation of the quality of colonoscopy, including the effectiveness of CADe, was 
previously deemed to be quality assurance by the University of Utah and Salt Lake City VA 
Medical Center (IRB_00119922); a continuing review of this IRB with amendment was approved 
for evaluation of AI implementation in 2022.  
 
Outcomes: 
3) VA Facility Level 
a) Adenoma detection rate for all indications 
i) The proportion of colonoscopies in which one or more adenomas are found. 
ii) Limit to ages 45-75 years 
iii) Also evaluate for all ages 
b) Number of polyps per colonoscopy 

12 
 
i) Limited to Provation sites 
c) Size of polyps detected 
i) Limited to Provation sites 
ii) Average size 
iii) Categorized as 
(1) 1-5mm 
(2) 6-9mm 
(3) ≥10mm 
d) Surveillance recommendations after colonoscopy  
i) Use health factors for follow-up recommendation after colonoscopy 
ii) Limit to ages 45-65 years 
iii) Repeat colonoscopy interval 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
iv) Resume average risk screening 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
v) No further screening 
vi) No health factor found 
e) Withdrawal time when no maneuvers are performed 
i) Limited to Provation Sites (unless EndoPro comes online) 
f) Withdrawal time, including the performance of maneuvers 
i) Limited to Provation Sites (unless EndoPro comes online) 
g) Total procedure time 
i) When no maneuvers are performed 
ii) When all procedures are included 
h) Bowel preparation quality 
i) Adequate vs. inadequate 
ii) Excellent vs. good vs. fair vs. poor 
iii) Boston Bowel Preparation Score 

13 
 
i) Adenocarcinoma detection rate 
i) The proportion of colonoscopies found to have adenocarcinoma 
 
4) VA Provider Level 
a) Adenoma detection rate for all indications 
i) The proportion of colonoscopies in which one or more adenomas are found. 
ii) Limit to ages 45-75 years 
iii) Also evaluate for all ages 
b) Number of polyps per colonoscopy 
c) Size of polyps detected 
i) Average size 
ii) Categorized as 
(1) 1-5mm 
(2) 6-9mm 
(3) ≥10mm 
d) Surveillance recommendations after colonoscopy  
i) Use health factors for follow-up recommendation after colonoscopy 
ii) Limit to ages 45-65 years 
iii) Repeat colonoscopy interval 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
iv) Resume average risk screening 
(1) <3 years 
(2) 3 years 
(3) 4 years 
(4) 5 years 
(5) 6 years 
(6) 7 years 
(7) 8 years 
(8) 9 years 
(9) 10 years 
v) No further screening/surveillance 
vi) No recommendation found 
e) Withdrawal time when no maneuvers are performed 
i) Limited to Provation Sites (unless EndoPro comes online) 
f) Withdrawal time, including the performance of maneuvers 
i) Limited to Provation Sites (unless EndoPro comes online) 

14 
 
g) Total procedure time 
i) When no maneuvers are performed  
ii) When all procedures are included 
h) Bowel preparation quality 
i) Adequate vs. inadequate 
ii) Excellent vs. good vs. fair vs. poor 
iii) Boston Bowel Preparation Score 
i) Adenocarcinoma detection rate 
i) The proportion of colonoscopies found to have adenocarcinoma 
j) Qualitative assessment (from survey) 
i) Benefits of CADe 
ii) Negative aspects of CADe 
iii) False positive alerts 
iv) Impact on fellow training 
v) Overall satisfaction with CADe 
 
Database: 
Colonoscopy details are extracted from the Corporate Data Warehouse and, when possible, the 
endoscopy reporting system via the CART database, including: 
1) VA facility  
2) Patient characteristics 
a) Age 
b) Gender 
c) Race 
d) Ethnicity 
3) Colonoscopy indication 
a) Screening 
b) Surveillance 
c) FOBT+ 
d) Other 
e) Unknown 
4) Bowel preparation quality 
a) Adequate vs. inadequate 
b) Aronchick 
c) Boston Bowel Preparation Score 
5) Colonoscopy findings 
a) Adenoma detection 
b) Adenocarcinoma detection 
c) Number of polyps detected 
d) Number of polyps detected according to size 
i) 1-5mm 
ii) 6-9mm 
iii) ≥10mm 
e) Withdrawal time 

15 
 
f) Total procedure time 
6) Follow-up Plans after colonoscopy (using Gap Reminder health factors) 
7) A new variable coding the presence or absence of CADe will be added to each colonoscopy 
based upon the date of installation of the GI Genius CADe device at each facility.  
a) In order to allow for endoscopists to adapt to performing colonoscopy with the CADe 
device, all colonoscopies performed within 21 days of the date of installation will be 
classified as “CADe Training” and will be excluded from the analysis.  
  
 Statistical Methods: 
1) Within facility comparison (pre- vs. post): All outcome variables will be compared between 
the pre-CADe and post-CADe time periods (starting 21 days after CADe installation). We will 
aim for a minimum of 3 months on post-CADe assessment, compared to 6 months of pre-
CADe colonoscopies. 
2) Between facility comparison: The 43 VA facilities that received CADe devices will be 
compared to over 100 VA facilities that did not receive CADe devices.  
3) Categorical variables will be compared using the Chi-square test. 
4) Continuous variables will be compared with the t-test or Wilcoxon rank sums test, as 
appropriate. 
5) To adjust for potential confounders, multivariable models will be constructed.  
a) Logistic regression will be used for dichotomous outcomes (e.g., adenoma detection) 
b) Polytomous logistic regression will be used for ordinal outcomes (e.g., colonoscopy 
surveillance recommendations) 
c) Linear regression will be used for continuous outcomes (e.g., withdrawal time) 
d) Shell tables are provided below, detailing the variables to be included in the models 
 
 
 

16 
 
Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation (CADeNCE) 
 
Study Protocol Version 2.0 
 
August 8, 2023 
 
 
Evaluation Team: 
Jason A. Dominitz, MD, MHS 
Tonya Kaltenbach, MD, MS, MEd 
Andrew J. Gawron, MD, PhD 
Grace McKee, PhD 
Katherine J. Hoggatt, PhD, MPH 
 
 
 
Summary of major revisions: 
 
1) Refinement of the statistical analysis plan 
a) Dr. Hoggatt was added to the evaluation team to refine the statistical analysis plan.   
2) Refinement of the study outcomes 
a) The VA-EQuIP team developed methods to assess other relevant secondary outcomes 
(e.g., sessile serrated lesion detection) that were added to the evaluation  
b) As Provation MD data was not readily available to assess many of the proposed 
secondary outcomes (e.g., indication, polyp size), evaluation of these outcomes is 
deferred 
 

17 
 
Background:  
Colonoscopy is a key diagnostic and therapeutic procedure for the prevention of colorectal 
cancer (CRC) incidence and mortality. Central to colonoscopy’s effectiveness is the 
identification and removal of colorectal neoplasia, including adenomatous polyps and sessile 
serrated lesions. The endoscopist’s adenoma detection rate (ADR), classically defined as the 
proportion of screening colonoscopies in which one or more adenomas are detected, has been 
demonstrated to be strongly inversely associated with their patients’ risk of post-colonoscopy 
colorectal cancer. Therefore, improving adenoma detection is a major target of quality 
assurance efforts.  
  
The Veterans Health Administration’s (VA) National Gastroenterology and Hepatology Program 
(NGHP) has embarked on a number of efforts to measure, monitor, and improve colonoscopy 
quality across the VA enterprise. One of these efforts is the VA Endoscopy Quality Improvement 
Program (VA-EQuIP) which is a collaboration between the VA Quality Enhancement Research 
Initiative (QUERI), the Office of Research and Development (ORD) and the NGHP. Investigators 
in the Measurement Science QUERI have developed processes for assessing the ADR of 
individual physicians and facilities through extraction of data from the Corporate Data 
Warehouse (CDW). Through collaboration with the VA Clinical Assessment Reporting and 
Tracking Program (CART), more detailed colonoscopy report information is available for 29 VA 
medical centers, with additional VA facilities expected to be added to the list soon. Overall, the 
VA ADR for colonoscopies of all indications is 47%1, well above the benchmark of 30% for men 
undergoing screening colonoscopy. 
  
In 2021, the FDA approved the first artificial intelligence (AI) system for computer assisted 
detection (CADe) of colorectal neoplasia. These CADe devices project an image on the 
endoscopy monitor (i.e., a bounding box) to alert the endoscopist to the presence of a 
suspected polyp within the colon. Initial studies, including randomized controlled trials, have 
demonstrated that use of CADe systems result in a significant improvement in adenoma 
detection, with a reduction in the miss rate of adenomas (i.e., fewer adenomas are found on a 
second colonoscopy when the first colonoscopy was performed with a CADe system compared 
to when the first colonoscopy did not use CADe).2-4 However, more recent studies have not 
demonstrated a clear benefit of these devices.5,6 Moreover, most of the additional adenomas 
that are detected are diminutive polyps, the vast majority of which are thought to be of 
minimal, if any, clinical significance. When multiple adenomas are detected during colonoscopy, 
current guidelines recommend repeating colonoscopy sooner than would otherwise be 
recommended. Also, the CADe systems may have unintended consequences, such as creating 
alert fatigue through false alarms or negatively impacting training of gastroenterology fellows.  
  
Objective:  
The NGHP planned to formally evaluate the quantitative and qualitative impact and outcomes 
of use of CADe within VA medical centers following the purchase and distribution to randomly 
selected gastrointestinal endoscopy units.   
  
 

18 
 
Setting:  
Veteran Health Administration (VA) Medical Centers 
  
Intervention:  
As part of ongoing quality assurance efforts, the NGHP purchased 115 Medtronic GI Genius® 
CADe devices in late 2022. All facilities were sorted according to their facility-level ADR (for all 
indications) and categorized as below 30%, 30% to <40% or ≥40%. A random number generator 
was then used to sort the VA medical centers within each of these 3 ADR strata. Alternating 
facilities (i.e., approximately 50%) of facilities within the 2 lower ADR stratum were allocated 
the CADe devices. To assure equitable distribution of the remaining CADe devices across the 18 
VA Integrated Service Networks (VISNs), the remaining devices were offered to randomly 
selected facilities (all within the ≥40% ADR stratum) such that each VISN had 2-3 facilities with 
CADe devices.  
  
Upon identification of a potential site, the Gastroenterology Section Chief (or equivalent) at 
that randomly selected site was asked if they were interested in receiving the devices and if all 
endoscopists at their facility would agree to use the device during colonoscopy. The physicians 
were not mandated to use the devices but were asked to notify the NGHP if endoscopists were 
not routinely using the devices so that the devices could be reallocated to other VA facilities 
that would make use of the CADe devices. Upon receiving concurrence from facility endoscopy 
leadership, the devices were installed in all procedure rooms that are routinely used for 
colonoscopy at that facility. The devices were not installed on travel carts for emergency 
procedures. One facility did decline to receive the devices due to concerns that the devices 
would negatively impact efficiency in the endoscopy unit. That facility was replaced with 
another randomly selected VA medical center. Ultimately, 43 VA facilities received and installed 
the 115 CADe devices.  
  
Survey: To assess the end-user experience, a Microsoft Forms electronic survey will be 
distributed to VA endoscopists who performed at least 25 colonoscopies between December 1, 
2022 and May 31, 2023. Endoscopists will be invited via email with up to two follow-up 
reminders. Survey questions will address self-reported use of CADe for different colonoscopy 
indications, assessment of the benefits and negative impacts of CADe (e.g., impact on neoplasia 
detection or withdrawal time), and overall impression of CADe. Survey completion will be 
optional.  Only staff gastroenterologists and surgeons will be eligible to complete the survey. 
 
Oversight:  
This quality assurance evaluation was conducted under the auspices of the VA NGHP. 
Evaluation of the quality of colonoscopy, including the effectiveness of CADe, was previously 
deemed to be quality assurance by the University of Utah and Salt Lake City VA Medical Center 
(IRB_00119922); a continuing review of this IRB with amendment was approved for evaluation 
of AI implementation in 2022. This quality assurance evaluation is registered with 
ClinicalTrials.gov (NCT05888623). 
 
 

19 
 
Database:  
The VA Corporate Data Warehouse administrative and patient care data will be used to 
temporally link CPT codes for colonoscopy to pathology results to assess detection of neoplasia 
and other study outcomes. Natural language processing (NLP) with full-text indexing searches is 
used to classify pathology (i.e., adenoma, sessile serrated lesion, adenocarcinoma). Validation 
of this method to classify adenomas from the pathology results showed 99.5% 
accuracy.(Gawron et al. unpublished) Separately, colonoscopy data from sites using Provation 
MD software (Provation, Minneapolis, MN) is exported to a national VA database for quality 
assurance purposes. This software includes information on colonoscopy quality, such as 
withdrawal time, indication, bowel preparation quality. Outcomes will be ascertained for 
colonoscopies performed between October 1, 2021 through June 30, 2023.  
 
Outcomes: 
Primary outcome: The primary outcome is the change in ADR from the pre- to post-deployment 
periods from colonoscopies performed with CADe available compared to colonoscopies 
performed where CADe was not available.  
 
Secondary Outcomes: 
1) Adenocarcinoma detection rate 
2) Sessile serrated lesion detection rate 
3) Proportion of colonoscopies where pathology specimens are obtained 
4) Proportion of pathology without adenoma or adenocarcinoma 
a) This serves as a surrogate for false positive lesion detection during use of CADe 
5) Withdrawal time when no maneuvers are performed 
a) Limited to Provation Sites  
b) To assess the negative impact of CADe on procedure time or a possible Hawthorne 
effect. 
6) Provider satisfaction with CADe for colonoscopy 
7) Adenoma detection rate stratified by the endoscopist’s pre-CADe ADR quintile 
 
Additional analyses to be considered (due to data availability): 
1) Bowel preparation quality 
a) Limited to Provation sites  
2) Number of polyps per colonoscopy 
a) Limited to Provation sites  
3) Size of polyps detected 
a) Limited to Provation sites  
4) Advanced neoplasia detection rates 
a) Limited to Provation sites 
5) Surveillance recommendations after colonoscopy  
 
Independent Variables: 
1) VA Facility characteristics 
a) Pre-randomization adenoma detection rate 

20 
 
2) Patient characteristics 
a) Age 
b) Gender 
c) Race 
d) Ethnicity 
e) Rurality 
3) Provider characteristics 
a) Specialty 
b) Sex 
c) Years since completion of medical training 
4) Colonoscopy indication (Provation sites only, if available) 
a) Screening 
b) Surveillance 
c) FOBT+ 
d) Other 
e) Unknown 
5) Bowel preparation quality (Provation sites only, if available) 
a) Adequate vs. inadequate 
b) Aronchick 
c) Boston Bowel Preparation Score 
 
Statistical Methods: 
Colonoscopies performed on the day of CADe installation and the next 5 colonoscopies 
performed by each endoscopist after the date of installation (or matched date for control sites) 
will be excluded as a washout period to minimize training adaptation. For the 26 endoscopists 
who performed colonoscopies at multiple facilities, we will retain only procedures at the facility 
where they performed the largest number of colonoscopies. 
 
Baseline data will be summarized as number (%), mean (± standard deviation) or median 
(interquartile range), as appropriate. For binary outcomes, we will estimate the association of 
CADe on study outcomes using mixed effects logistic regression (PROC GLIMMIX, SAS software, 
Cary, NC) with a random intercept for endoscopist and a random slope (at the endoscopist 
level) for study phase. We will also include fixed effects for group, phase, and a group by phase 
interaction (product term), with colonoscopy serving as the unit of analysis. The group by phase 
interaction is quantified as a ratio of odds ratios, where a coefficient greater than 1 for the 
interaction term (or 0 on the log-odds scale) reflects increased neoplasia detection in the post-
deployment phase versus the pre-deployment phase in the CADe group compared to the non-
CADe group.  We will control for pre-randomization ADR stratum, patient demographics (e.g., 
sex, age, race, ethnicity, and rurality), and endoscopist information (e.g., specialty, sex, years 
since medical degree) in all analyses.  
 
After estimating the association of CADe on adenoma detection, we will assess whether the 
effect was moderated by patient and endoscopist characteristics. We will fit additional models 

21 
 
for each potential moderator, adding a main effect for the moderator and interactions (product 
terms) with group, phase, and group by phase terms as fixed effects. 
 
Withdrawal time information will only be available from the subset of VA facilities that use 
Provation MD software. As withdrawal time in a continuous variable, we will use a linear mixed 
effects regression model with the same predictors as described above. We will include only 
those colonoscopies without an associated pathology report and where cecal intubation was 
complete. 
 
To assess whether the effect of CADe on ADR is moderated by endoscopist ADR quintile, 
endoscopists with at least 100 colonoscopies in the pre- and post-deployment phases each will 
be divided into quintiles based on pre-intervention ADR. The quintile variable will be entered 
into the model described above as a main effect and an interaction (product term) with the 
group, phase, and group by phase terms. 
 
 
 
 
 

22 
 
Computer Assisted Detection of Neoplasia during Colonoscopy Evaluation (CADeNCE) 
 
Study Protocol Version 2.1 
 
September 10, 2025 
 
 
Evaluation Team: 
Jason A. Dominitz, MD, MHS 
Tonya Kaltenbach, MD, MS, MEd 
Andrew J. Gawron, MD, PhD 
Grace McKee, PhD 
Katherine J. Hoggatt, PhD, MPH 
 
 
 
Summary of major revisions: 
 
1) In addition to random intercepts for endoscopist and study phase in the regression models, 
a random intercept for facility was added as this was the unit of randomization 
 
 
 
 

23 
 
Background:  
Colonoscopy is a key diagnostic and therapeutic procedure for the prevention of colorectal 
cancer (CRC) incidence and mortality. Central to colonoscopy’s effectiveness is the 
identification and removal of colorectal neoplasia, including adenomatous polyps and sessile 
serrated lesions. The endoscopist’s adenoma detection rate (ADR), classically defined as the 
proportion of screening colonoscopies in which one or more adenomas are detected, has been 
demonstrated to be strongly inversely associated with their patients’ risk of post-colonoscopy 
colorectal cancer. Therefore, improving adenoma detection is a major target of quality 
assurance efforts.  
  
The Veterans Health Administration’s (VA) National Gastroenterology and Hepatology Program 
(NGHP) has embarked on a number of efforts to measure, monitor, and improve colonoscopy 
quality across the VA enterprise. One of these efforts is the VA Endoscopy Quality Improvement 
Program (VA-EQuIP) which is a collaboration between the VA Quality Enhancement Research 
Initiative (QUERI), the Office of Research and Development (ORD) and the NGHP. Investigators 
in the Measurement Science QUERI have developed processes for assessing the ADR of 
individual physicians and facilities through extraction of data from the Corporate Data 
Warehouse (CDW). Through collaboration with the VA Clinical Assessment Reporting and 
Tracking Program (CART), more detailed colonoscopy report information is available for 29 VA 
medical centers, with additional VA facilities expected to be added to the list soon. Overall, the 
VA ADR for colonoscopies of all indications is 47%1, well above the benchmark of 30% for men 
undergoing screening colonoscopy. 
  
In 2021, the FDA approved the first artificial intelligence (AI) system for computer assisted 
detection (CADe) of colorectal neoplasia. These CADe devices project an image on the 
endoscopy monitor (i.e., a bounding box) to alert the endoscopist to the presence of a 
suspected polyp within the colon. Initial studies, including randomized controlled trials, have 
demonstrated that use of CADe systems result in a significant improvement in adenoma 
detection, with a reduction in the miss rate of adenomas (i.e., fewer adenomas are found on a 
second colonoscopy when the first colonoscopy was performed with a CADe system compared 
to when the first colonoscopy did not use CADe).2-4 However, more recent studies have not 
demonstrated a clear benefit of these devices.5,6 Moreover, most of the additional adenomas 
that are detected are diminutive polyps, the vast majority of which are thought to be of 
minimal, if any, clinical significance. When multiple adenomas are detected during colonoscopy, 
current guidelines recommend repeating colonoscopy sooner than would otherwise be 
recommended. Also, the CADe systems may have unintended consequences, such as creating 
alert fatigue through false alarms or negatively impacting training of gastroenterology fellows.  
  
Objective:  
The NGHP planned to formally evaluate the quantitative and qualitative impact and outcomes 
of use of CADe within VA medical centers following the purchase and distribution to randomly 
selected gastrointestinal endoscopy units.   
  
 

24 
 
Setting:  
Veteran Health Administration (VA) Medical Centers 
  
Intervention:  
As part of ongoing quality assurance efforts, the NGHP purchased 115 Medtronic GI Genius® 
CADe devices in late 2022. All facilities were sorted according to their facility-level ADR (for all 
indications) and categorized as below 30%, 30% to <40% or ≥40%. A random number generator 
was then used to sort the VA medical centers within each of these 3 ADR strata. Alternating 
facilities (i.e., approximately 50%) of facilities within the 2 lower ADR stratum were allocated 
the CADe devices. To assure equitable distribution of the remaining CADe devices across the 18 
VA Integrated Service Networks (VISNs), the remaining devices were offered to randomly 
selected facilities (all within the ≥40% ADR stratum) such that each VISN had 2-3 facilities with 
CADe devices.  
  
Upon identification of a potential site, the Gastroenterology Section Chief (or equivalent) at 
that randomly selected site was asked if they were interested in receiving the devices and if all 
endoscopists at their facility would agree to use the device during colonoscopy. The physicians 
were not mandated to use the devices but were asked to notify the NGHP if endoscopists were 
not routinely using the devices so that the devices could be reallocated to other VA facilities 
that would make use of the CADe devices. Upon receiving concurrence from facility endoscopy 
leadership, the devices were installed in all procedure rooms that are routinely used for 
colonoscopy at that facility. The devices were not installed on travel carts for emergency 
procedures. One facility did decline to receive the devices due to concerns that the devices 
would negatively impact efficiency in the endoscopy unit. That facility was replaced with 
another randomly selected VA medical center. Ultimately, 43 VA facilities received and installed 
the 115 CADe devices.  
  
Survey: To assess the end-user experience, a Microsoft Forms electronic survey will be 
distributed to VA endoscopists who performed at least 25 colonoscopies between December 1, 
2022 and May 31, 2023. Endoscopists will be invited via email with up to two follow-up 
reminders. Survey questions will address self-reported use of CADe for different colonoscopy 
indications, assessment of the benefits and negative impacts of CADe (e.g., impact on neoplasia 
detection or withdrawal time), and overall impression of CADe. Survey completion will be 
optional.  Only staff gastroenterologists and surgeons will be eligible to complete the survey. 
 
Oversight:  
This quality assurance evaluation was conducted under the auspices of the VA NGHP. 
Evaluation of the quality of colonoscopy, including the effectiveness of CADe, was previously 
deemed to be quality assurance by the University of Utah and Salt Lake City VA Medical Center 
(IRB_00119922); a continuing review of this IRB with amendment was approved for evaluation 
of AI implementation in 2022. This quality assurance evaluation is registered with 
ClinicalTrials.gov (NCT05888623). 
 
 

25 
 
Database:  
The VA Corporate Data Warehouse administrative and patient care data will be used to 
temporally link CPT codes for colonoscopy to pathology results to assess detection of neoplasia 
and other study outcomes. Natural language processing (NLP) with full-text indexing searches is 
used to classify pathology (i.e., adenoma, sessile serrated lesion, adenocarcinoma). Validation 
of this method to classify adenomas from the pathology results showed 99.5% accuracy.7 
Separately, colonoscopy data from sites using Provation MD software (Provation, Minneapolis, 
MN) is exported to a national VA database for quality assurance purposes. This software 
includes information on colonoscopy quality, such as withdrawal time, indication, bowel 
preparation quality. Outcomes will be ascertained for colonoscopies performed between 
October 1, 2021 through June 30, 2023.  
 
Outcomes: 
Primary outcome: The primary outcome is the change in ADR from the pre- to post-deployment 
periods from colonoscopies performed with CADe available compared to colonoscopies 
performed where CADe was not available.  
 
Secondary Outcomes: 
1) Adenocarcinoma detection rate 
2) Sessile serrated lesion detection rate 
3) Proportion of colonoscopies where pathology specimens are obtained 
4) Proportion of pathology without adenoma or adenocarcinoma 
a) This serves as a surrogate for false positive lesion detection during use of CADe 
5) Withdrawal time when no maneuvers are performed 
a) Limited to Provation Sites  
b) To assess the negative impact of CADe on procedure time or a possible Hawthorne 
effect. 
6) Provider satisfaction with CADe for colonoscopy 
7) Adenoma detection rate stratified by the endoscopist’s pre-CADe ADR quintile 
 
Additional analyses to be considered (due to data availability): 
1) Bowel preparation quality 
a) Limited to Provation sites  
2) Number of polyps per colonoscopy 
a) Limited to Provation sites  
3) Size of polyps detected 
a) Limited to Provation sites  
4) Advanced neoplasia detection rates 
a) Limited to Provation sites 
5) Surveillance recommendations after colonoscopy  
 
Independent Variables: 
1) VA Facility characteristics 
a) Pre-randomization adenoma detection rate 

26 
 
2) Patient characteristics 
a) Age 
b) Gender 
c) Race 
d) Ethnicity 
e) Rurality 
3) Provider characteristics 
a) Specialty 
b) Sex 
c) Years since completion of medical training 
4) Colonoscopy indication (Provation sites only, if available) 
a) Screening 
b) Surveillance 
c) FOBT+ 
d) Other 
e) Unknown 
5) Bowel preparation quality (Provation sites only, if available) 
a) Adequate vs. inadequate 
b) Aronchick 
c) Boston Bowel Preparation Score 
 
Statistical Methods: 
Colonoscopies performed on the day of CADe installation and the next 5 colonoscopies 
performed by each endoscopist after the date of installation (or matched date for control sites) 
will be excluded as a washout period to minimize training adaptation. For the 26 endoscopists 
who performed colonoscopies at multiple facilities, we will retain only procedures at the facility 
where they performed the largest number of colonoscopies. 
 
Baseline data will be summarized as number (%), mean (± standard deviation) or median 
(interquartile range), as appropriate. For binary outcomes, we will estimate the association of 
CADe on study outcomes using mixed effects logistic regression (PROC GLIMMIX, SAS software, 
Cary, NC) with random intercepts for facility and endoscopist and random slopes (at the facility 
and endoscopist level) for study phase. We will also include fixed effects for group, phase, and a 
group by phase interaction (product term), with colonoscopy serving as the unit of analysis. The 
group by phase interaction is quantified as a ratio of odds ratios, where a coefficient greater 
than 1 for the interaction term (or 0 on the log-odds scale) reflects increased neoplasia 
detection in the post-deployment phase versus the pre-deployment phase in the CADe group 
compared to the non-CADe group.  We will control for pre-randomization ADR stratum, patient 
demographics (e.g., sex, age, race, ethnicity and rurality), and endoscopist information (e.g., 
specialty, sex, years since medical degree) in all analyses.  
 
After estimating the association of CADe on adenoma detection, we will assess whether the 
effect was moderated by patient and endoscopist characteristics. We will fit additional models 

27 
 
for each potential moderator, adding a main effect for the moderator and interactions (product 
terms) with group, phase, and group by phase terms as fixed effects. 
 
Withdrawal time information will only be available from the subset of VA facilities that use 
Provation MD software. As withdrawal time in a continuous variable, we will use a linear mixed 
effects regression model with the same predictors as described above. We will include only 
those colonoscopies without an associated pathology report and where cecal intubation was 
complete. 
 
To assess whether the effect of CADe on ADR is moderated by endoscopist ADR quintile, 
endoscopists with at least 100 colonoscopies in the pre- and post-deployment phases each will 
be divided into quintiles based on pre-intervention ADR. The quintile variable will be entered 
into the model described above as a main effect and an interaction (product term) with the 
group, phase, and group by phase terms. 
 
 

28 
 
 
References: 
1. 
Gawron AJ, Yao Y, Gupta S, et al. Simplifying Measurement of Adenoma Detection Rates 
for Colonoscopy. Dig Dis Sci. Sep 2021;66(9):3149-3155. doi:10.1007/s10620-020-06627-2 
2. 
Hassan C, Spadaccini M, Iannone A, et al. Performance of artificial intelligence in 
colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. 
Gastrointest Endosc. Jan 2021;93(1):77-85 e6. doi:10.1016/j.gie.2020.06.059 
3. 
Repici A, Badalamenti M, Maselli R, et al. Efficacy of Real-Time Computer-Aided 
Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. Aug 
2020;159(2):512-520 e7. doi:10.1053/j.gastro.2020.04.062 
4. 
Wallace MB, Sharma P, Bhandari P, et al. Impact of Artificial Intelligence on Miss Rate of 
Colorectal Neoplasia. Gastroenterology. Jul 2022;163(1):295-304 e5. 
doi:10.1053/j.gastro.2022.03.007 
5. 
Ladabaum U, Shepard J, Weng Y, Desai M, Singer SJ, Mannalithara A. Computer-aided 
Detection of Polyps Does Not Improve Colonoscopist Performance in a Pragmatic 
Implementation Trial. Gastroenterology. Mar 2023;164(3):481-483 e6. 
doi:10.1053/j.gastro.2022.12.004 
6. 
Levy I, Bruckmayer L, Klang E, Ben-Horin S, Kopylov U. Artificial Intelligence-Aided 
Colonoscopy Does Not Increase Adenoma Detection Rate in Routine Clinical Practice. Am J 
Gastroenterol. Nov 1 2022;117(11):1871-1873. doi:10.14309/ajg.0000000000001970 
7. 
Gawron AJ, McKee G, Dominitz JA, Yao Y, Whooley M, Kaltenbach T. Validation of a 
National Pathology Database for Colonoscopy Quality Reporting and Assurance. Clin 
Gastroenterol Hepatol. Apr 2025;23(5):866-868 e1. doi:10.1016/j.cgh.2024.08.017