AI-Based Stool Image Analysis for Colorectal Neoplasia Risk Assessment (FECAL-AI)
2026년 7월 28일 업데이트: Servicio de Salud Metropolitano Sur Oriente
FECAL-AI: Prospective Observational Validation of AI-Based Stool Image Analysis Against Quantitative Fecal Immunochemical Testing for Colorectal Neoplasia Risk Assessment
This prospective observational substudy evaluates the association between artificial intelligence-derived features from stool images analyzed using the FAEX Health digital platform and fecal immunochemical test results in adults undergoing colorectal cancer screening or diagnostic evaluation.
Participants will capture stool images using a mobile application.
The primary analysis will compare AI-derived image outputs with quantitative FIT values and FIT positivity.
Secondary exploratory analyses will assess associations with colonoscopy and histopathological findings when these results are available.
The platform will be used exclusively for research and will not provide diagnoses, replace clinical evaluation, or influence medical decisions.
연구 개요
상태
상태
모병
정황
정황
개입 / 치료
개입 / 치료
상세 설명
This is a substudy of the project "Estrategia de prevención secundaria de cáncer colorrectal en personas mayores a 18 años." The substudy evaluates the FAEX Health digital platform, which applies artificial intelligence algorithms to stool images for non-diagnostic research and validation.
Participants will capture images of their stools using the FAEX Health mobile application. The images will be coded and analyzed using computational algorithms designed to identify visual characteristics such as color, consistency, and possible visible blood.
The primary objective is to evaluate the association and discriminatory performance of AI-derived stool image features for quantitative fecal immunochemical test results and FIT positivity. Secondary exploratory objectives are to assess associations between these image features and colonoscopic and histopathological findings among participants for whom these results are available.
The AI-derived results will not be returned to participants or treating clinicians and will not be used to determine whether colonoscopy or any other clinical procedure is performed. The findings may inform future studies evaluating stool image analysis as a potential triage strategy when FIT is unavailable or declined; however, the present study does not evaluate the platform as a replacement for FIT.
Personal identifiers will not be stored together with stool images. Access to coded study information will be restricted to authorized researchers, and study data will be managed according to applicable ethical, legal, and confidentiality requirements.
연구 유형
연구 유형
관찰
등록 (추정된)
등록
250
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 연락처
연구 연락처
- 이름: Erik Manriquez Alegria, MD
- 전화번호: +56988232111
- 이메일: erik.manriquez.alegria@gmail.com
연구 연락처 백업
- 이름: Felipe Quezada Diaz, MD
- 전화번호: +56934651992
- 이메일: ffquezad@gmail.com
연구 장소
-
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Santiago Metropolitan
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Santiago, Santiago Metropolitan, 칠레, 8207257
- 모병
- Hospital Sotero Del Rio
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연락하다:
- Erik Manriquez Alegria, MD
- 전화번호: +56988232111
- 이메일: erik.manriquez.alegria@gmail.com
-
연락하다:
- Felipe Quezada Diaz, MD
- 전화번호: +56934651992
- 이메일: ffquezad@gmail.com
-
-
참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
해당 없음
샘플링 방법
비확률 샘플
연구 인구
Adults receiving care at Hospital Dr. Sótero del Río who are undergoing colorectal cancer screening or diagnostic evaluation and have a quantitative fecal immunochemical test planned or completed.
Eligible participants will prospectively submit stool images through the FAEX Health mobile application.
AI-derived image features will be compared primarily with matched quantitative FIT results and FIT positivity.
Colonoscopy and histopathology findings will be evaluated as secondary exploratory outcomes when available.
AI results will not be returned to participants or clinicians and will not influence clinical management.
설명
Inclusion Criteria:
- Age 18 years or older.
- Referred for screening or diagnostic colonoscopy at Hospital Dr. Sótero del Río.
- Quantitative fecal immunochemical testing planned or completed within 30 days before or after stool image submission.
- Able to submit at least one stool image using the FAEX Health mobile application, independently or with assistance.
- Able and willing to provide written informed consent.
Exclusion Criteria:
- Unable or unwilling to provide written informed consent.
- Previous enrollment in the study.
- Unable to complete stool-image capture, even with assistance.
- Study images and clinical data cannot be reliably linked using the assigned study code.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
그룹/코호트 수
1
코호트 및 개입
그룹/코호트그룹/코호트 |
개입 / 치료개입 / 치료 |
|---|---|
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Prospective Stool Image, FIT and Colonoscopy Cohort
Adults participating in colorectal cancer screening or diagnostic evaluation who submit stool images through the FAEX Health mobile application.
AI-derived stool image outputs will be compared primarily with quantitative fecal immunochemical test results and FIT positivity.
Colonoscopy and histopathology findings will be evaluated as secondary exploratory outcomes when available.
AI-derived results will not be returned to participants or clinicians and will not influence clinical decisions.
|
Participants capture stool images using the FAEX Health mobile application.
Coded images are analyzed using artificial intelligence algorithms to derive visual features and a prespecified patient-level output or score.
The AI-derived output is used exclusively for research and is compared primarily with quantitative FIT results and FIT positivity, with secondary comparisons against colonoscopy and histopathology when available.
The output is not used to provide a diagnosis or guide clinical management.
|
연구는 무엇을 측정합니까?
주요 결과 측정
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Correlation Between AI-Derived Stool Image Score and Quantitative FIT (faecal immunochemical test) Concentration
기간: Within 90 days of stool image submission
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Correlation coefficient between the prespecified patient-level AI-derived stool image score and quantitative fecal immunochemical test concentration among participants with analyzable matched data, reported with a 95% confidence interval.
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Within 90 days of stool image submission
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2차 결과 측정
2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Area Under the ROC Curve for FIT Positivity
기간: Within 90 days of stool image submission
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Area under the receiver operating characteristic curve of the prespecified AI-derived stool image score for classifying participants as FIT positive or FIT negative according to the locally established FIT threshold, reported with a 95% confidence interval.
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Within 90 days of stool image submission
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Sensitivity and Specificity of the AI-Derived Stool Image Score for FIT Positivity/Negativity
기간: Within 90 days of stool image submission
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Sensitivity and Specificity of a prespecified AI-derived stool image score threshold for identifying participants with a positive/negative FIT result, reported as a percentage with a 95% confidence interval.
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Within 90 days of stool image submission
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Area Under the ROC Curve for Colonoscopy-Detected Colorectal Neoplasia
기간: Within 90 days of stool image submission
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Area under the receiver operating characteristic curve of the AI-derived stool image score for identifying colorectal neoplasia detected at colonoscopy, with histopathological confirmation when available.
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Within 90 days of stool image submission
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
수사관
수사관
- 수석 연구원: Erik Manriquez Alegria, MD, Hospital Sotero Del Rio
간행물 및 유용한 링크
연구에 대한 정보 입력을 담당하는 사람이 자발적으로 이러한 간행물을 제공합니다. 이것은 연구와 관련된 모든 것에 관한 것일 수 있습니다.
일반 간행물
- Collins GS, Moons KGM, Dhiman P, Riley RD, Beam AL, Van Calster B, Ghassemi M, Liu X, Reitsma JB, van Smeden M, Boulesteix AL, Camaradou JC, Celi LA, Denaxas S, Denniston AK, Glocker B, Golub RM, Harvey H, Heinze G, Hoffman MM, Kengne AP, Lam E, Lee N, Loder EW, Maier-Hein L, Mateen BA, McCradden MD, Oakden-Rayner L, Ordish J, Parnell R, Rose S, Singh K, Wynants L, Logullo P. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ. 2024 Apr 16;385:e078378. doi: 10.1136/bmj-2023-078378.
- Lee JW, Woo D, Kim KO, Kim ES, Kim SK, Lee HS, Kang B, Lee YJ, Kim J, Jang BI, Kim EY, Jo HH, Chung YJ, Ryu H, Park SK, Park DI, Yu H, Jeong S; IBD Research Group of KASID and Crohn's and Colitis Association in Daegu-Gyeongbuk (CCAiD). Deep Learning Model Using Stool Pictures for Predicting Endoscopic Mucosal Inflammation in Patients With Ulcerative Colitis. Am J Gastroenterol. 2025 Jan 1;120(1):213-224. doi: 10.14309/ajg.0000000000002978. Epub 2024 Jul 25.
- Sounderajah V, Guni A, Liu X, Collins GS, Karthikesalingam A, Markar SR, Golub RM, Denniston AK, Shetty S, Moher D, Bossuyt PM, Darzi A, Ashrafian H; STARD-AI Steering Committee. The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence. Nat Med. 2025 Oct;31(10):3283-3289. doi: 10.1038/s41591-025-03953-8. Epub 2025 Sep 15.
- Zhong H, Hou C, Huang Z, Chen X, Zou Y, Zhang H, Wang T, Wang L, Huang X, Xiang Y, Zhong M, Hu M, Xiong D, Wang L, Zhang Y, Luo Y, Guan Y, Xia M, Liu X, Yang J, Gan T, Wei W, Chen H, Gong H. A clinical pilot trial of an artificial intelligence-driven smart phone application of bowel preparation for colonoscopy: a randomized clinical trial. Scand J Gastroenterol. 2025 Jan;60(1):116-121. doi: 10.1080/00365521.2024.2443520. Epub 2024 Dec 22.
- Ramprasad C, Saini D, Del Carmen H, Krasnovsky L, Chandra R, Mcgregor R, Shinohara RT, Eaton E, Gummadi M, Mehta S, Lewis JD. Text Message System for the Prediction of Colonoscopy Bowel Preparation Adequacy Before Colonoscopy: An Artificial Intelligence Image Classification Algorithm Based on Images of Stool Output. Gastro Hep Adv. 2024 Sep 19;4(2):100556. doi: 10.1016/j.gastha.2024.09.011. eCollection 2025.
- Katsoula A, Paschos P, Haidich AB, Tsapas A, Giouleme O. Diagnostic Accuracy of Fecal Immunochemical Test in Patients at Increased Risk for Colorectal Cancer: A Meta-analysis. JAMA Intern Med. 2017 Aug 1;177(8):1110-1118. doi: 10.1001/jamainternmed.2017.2309.
- Rahman F, Trivedy M, Rao C, Akinlade F, Mansuri A, Aggarwal A, Laskaratos FM, Rajendran N, Banerjee S. Faecal Immunochemical Testing to Detect Colorectal Cancer in Symptomatic Patients: A Diagnostic Accuracy Study. Diagnostics (Basel). 2023 Jul 10;13(14):2332. doi: 10.3390/diagnostics13142332.
- Bailey JA, Weller J, Chapman CJ, Ford A, Hardy K, Oliver S, Morling JR, Simpson JA, Humes DJ, Banerjea A. Faecal immunochemical testing and blood tests for prioritization of urgent colorectal cancer referrals in symptomatic patients: a 2-year evaluation. BJS Open. 2021 Mar 5;5(2):zraa056. doi: 10.1093/bjsopen/zraa056.
- D'Souza N, Georgiou Delisle T, Chen M, Benton S, Abulafi M; NICE FIT Steering Group. Faecal immunochemical test is superior to symptoms in predicting pathology in patients with suspected colorectal cancer symptoms referred on a 2WW pathway: a diagnostic accuracy study. Gut. 2021 Jun;70(6):1130-1138. doi: 10.1136/gutjnl-2020-321956. Epub 2020 Oct 21.
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
연구 시작
2026년 5월 8일
기본 완료 (추정된)
기본 완료
2026년 12월 1일
연구 완료 (추정된)
연구 완료
2026년 12월 1일
연구 등록 날짜
최초 제출
최초 제출
2026년 7월 28일
QC 기준을 충족하는 최초 제출
QC 기준을 충족하는 최초 제출
2026년 7월 28일
처음 게시됨 (실제)
처음 게시됨
2026년 7월 31일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
마지막 업데이트 게시됨
2026년 7월 31일
QC 기준을 충족하는 마지막 업데이트 제출
QC 기준을 충족하는 마지막 업데이트 제출
2026년 7월 28일
마지막으로 확인됨
마지막으로 확인됨
2026년 7월 1일
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
기타 연구 ID 번호
- HSR-FAEX-CRC-FIT-2026
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
아니요
IPD 계획 설명
Individual participant data will not be made publicly available or routinely shared with external researchers.
The dataset includes coded clinical information and potentially sensitive stool images, and access is restricted by participant consent, ethics approval, applicable data-protection requirements, and the research data-sharing agreement between Hospital Dr. Sótero del Río and Faex Health.
Study findings will be reported in aggregate and de-identified form.
Any future external secondary use would require separate institutional, ethical, legal, and data-sharing approvals.
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
아니
미국 FDA 규제 기기 제품 연구
아니
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .