Common Bile Duct NeoplasmsNCT05147389
Artificial Intelligence for Digital Cholangioscopy Neoplasia Diagnosis
An observational study of Common Bile Duct Neoplasms and Non-Neoplastic Bile Duct Disorder, run by Instituto Ecuatoriano de Enfermedades Digestivas at 6 sites in 4 countries.
Trial summary
Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. To date, there is not a universally accepted DSOC classification. Endoscopists' Intra and interobserver agreements vary widely. Read more about this study
- Who is it for?
- Ages 18 to 79 years
- Conditions the study is for
- Common Bile Duct Neoplasms, Non-Neoplastic Bile Duct Disorder
- What is being tested?
- AI model classification and DSOC endoscopist experts' classification
- How many people
- 170 participants
- Where
- 6 sitesin 4 countries
- Study dates
- 1 Oct 2020to 1 May 2022
- How long will I take part?
- 1 Year
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 79 years
- All sexes
- Adult, Older adult
Study population: Adult patients with indication of DSOC.
Who may be able to join
- Patients referred to our center with an indication of DSOC due to suspicion of CBD tumor or indeterminate CBD stenosis.
- Patients who authorized for recording DSOC procedure for this study.
Who cannot join
- Any clinical condition which makes DSOC inviable.
- Patients with more than one DSOC.
- Low quality of recorded DSOC videos, even for AI model as for the expert endoscopists.
- Lost on a one-year follow-up after DSOC.
- Disagreement between DSOC findings vs. one-year follow-up, even after re-assessment of respective DSOC videos.
Trial locations and contacts
6 sites in 4 countries.
6 sites in 4 countries
United States3 sites
Baylor Saint Luke's Medical Center
Houston, Texas, 77030
Houston Methodist Hospital
Houston, Texas, 77098
Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University
New Brunswick, New Jersey, 08901
Belgium1 site
Department of Advanced Interventional Endoscopy, Universitair Ziekenhuis Brussel (UZB)/Vrije Universiteit Brussel (VUB)
Brussels
Brazil1 site
Serviço de Endoscopía Gastrointestinal do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
São Paulo
About this study
Official title: Clinical Validation of an Artificial Intelligence Software for Digital Cholangioscopy Diagnosis: an Observational Trial
Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. To date, there is not a universally accepted DSOC classification. Endoscopists' Intra and interobserver agreements vary widely. Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools is almost exclusively for intrahepatic CCA (iCCA). Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions.
In Ecuador, the investigators have recently proposed an AI model to classify bile duct lesions during real-time DSOC, which accurately detected malignancy patterns. This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with high DSOC experienced endoscopists.
Read the detailed description
Distinguishing neoplastic from non-neoplastic bile duct lesions is a challenge for clinicians. Magnetic resonance (MR) and biopsy guided by endoscopic retrograde cholangiopancreatography (ERCP) reached a negative predictive value (NPV) around 50%. On the other hand, Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. DSOC could be even better than DSOC-guided biopsy, which is inconclusive in some cases. However, to date, there is no universally accepted DSOC classification for that purpose. Also, endoscopists' Intra and interobserver agreements vary widely. Therefore, a more reproducible system is still needed.
With interesting results, Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools has been developed based on imaging radiomics. Nevertheless, CCA AI resources are almost exclusively for intrahepatic CCA (iCCA), with an endoscopic technique. Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions. Perihilar (pCCA) and distal (dCCA) cholangiocarcinoma as the most typical neoplastic bile duct lesions. Both represent 50-60% and 20-30% of all CCA, including secondary malignancies by local extension (hepatocarcinoma, gallbladder, and pancreas cancer).
A recent Portuguese proof-of-concept study developed an AI tool based on convolutional neuronal networks (CNNs). It let to differentiate between malignant from benign bile duct lesions or normal tissue with very high accuracy. Still, it needs more external validation, including endoscopists' Intra and interobserver agreement comparison. In Ecuador, the investigators recently proposed an AI model to classify bile duct lesions during real-time DSOC, which has been able to detect malignancy pattern in all cases.
This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with six endoscopists with high DSOC experience.
- Being tested
- AI model classification, DSOC endoscopist experts' classification
- Keywords
- Artificial Intelligence, Cholangioscopy, Neoplasia
- Medical subject headings
- Common Bile Duct Neoplasms, Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI model classificationDiagnostic test
AIWorks is an artificial intelligence model for real-time cholangioscopic detection of neoplastic and non-neoplastic bile duct lesions. It allows you to choose using a video file or a USB camera input as the detection source. Once the input source has been selected, the software performs real-time detection by surrounding the area of interest (i.e., the area with malignancy features) inside a bounding box. All detections made are displayed on the right side of the screen and can also be reviewed afterwards.
DSOC endoscopist experts' classificationDiagnostic test
Six endoscopists with high DSOC expertise will observe and classify a set of videos among neoplastic or non-neoplastic bile duct lesions following a Bernoulli distribution; blinded to clinical records and should have never attended said patients.
Gastroenterologists from each center, with non-DSOC responsibility, will select DSOC videos and corresponding baseline data. DSOC videos and data will be gathered in one set. Each video represents a full DSOC for a single patient. The patient will be the unit of this study.
The neoplastic bile duct criteria are in accordance with the Robles-Medranda et al and the Mendoza classifications (ie. Irregular mucosa surface, Tortuous and dilated vascularity, Irregular nodulations, Polyps, Ulceration, Honeycomb pattern, etc.). The experts will assess neoplastic bile duct by presence or absence of disaggregated criteria. Likewise, by Boolean logical operators, the statistical software will compute disaggregated answers.
| Study group | Role | What they receive |
|---|---|---|
| Neoplastic bile duct lesions | This group is confirmed by DSOC videos from patients with DSOC-confirmed neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm neoplastic bile duct lesion and the type: pCCA or dCCA, local extension of iCCA, hepatocarcinoma mixed CCA/hepatocarcinoma, gallbladder cancer, pancreas cancer, or any other neoplastic bile duct lesion. Based on follow-up, videos from patients with confirmed non-neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. Receives: Diagnostic Test: AI model classification; Diagnostic Test: DSOC endoscopist experts' classification | |
| Non-neoplastic bile duct lesions | This group is confirmed by DSOC videos from patients with DSOC-confirmed non-neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The non-neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm non-neoplastic bile duct lesion and the type, when available: acute or chronic cholangitis secondary to stones or parasite's location, autoimmune cholestatic liver diseases as autoimmune sclerosant cholangitis, and primary biliary cholangitis. Based on follow-up, videos from patients with confirmed neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. Receives: Diagnostic Test: AI model classification; Diagnostic Test: DSOC endoscopist experts' classification |
What is being measured
The primary outcome is the main question the study is designed to answer.
Neoplastic bile duct diagnosis confirmation after one year follow-up
Cases will be first followed up during one year to confirm or discard neoplastic bile duct lesions. A definite diagnosis of neoplastic bile duct lesion will be based on DSOC-guided biopsy specimen or findings from further indicated procedures, including brush cytology fluoroscopy-guided, endoscopic ultrasound-guided tissue sampling, surgical samples, and even imaging test in the context of a more impaired patient. Finally, the agreement between one-year follow-up (gold standard) vs. AI model and DSOC endoscopist experts' classification will be verified through a 2 x 2 contingency table.
Measured: One year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Dec 2021
- Study start1 Oct 2020
- Primary completion30 Nov 2021
- Study completion1 May 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Common Bile Duct NeoplasmsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 170 participants (actual)
- Target duration
- 1 Year
Sponsor and investigators
- Lead sponsor
- Instituto Ecuatoriano de Enfermedades Digestivas
- Sponsor type
- University, hospital or other
- Collaborators
- The Methodist Hospital Research Institute, University of Sao Paulo, Vrije Universiteit Brussel, Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University, Baylor St. Luke's Medical Center, Universitair Ziekenhuis Brussel
- Responsible party
- Sponsor
- Investigators
- Carlos Robles-Medranda, Principal investigator, Ecuadorian Institute of Digestive Diseases
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05147389
- Sponsor's protocol ID
- IECED-11032021
- Status last verified
- Nov 2022
- First submitted
- 5 Nov 2021
- Last updated
- 17 Nov 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Kahaleh M, Gaidhane M, Shahid HM, Tyberg A, Sarkar A, Ardengh JC, Kedia P, Andalib I, Gress F, Sethi A, Gan SI, Suresh S, Makar M, Bareket R, Slivka A, Widmer JL, Jamidar PA, Alkhiari R, Oleas R, Kim D, Robles-Medranda CA, Raijman I. Digital single-operator cholangioscopy interobserver study using a new classification: the Mendoza Classification (with video). Gastrointest Endosc. 2022 Feb;95(2):319-326. doi: 10.1016/j.gie.2021.08.015. Epub 2021 Aug 31.
PubMed 34478737Sethi A, Tyberg A, Slivka A, Adler DG, Desai AP, Sejpal DV, Pleskow DK, Bertani H, Gan SI, Shah R, Arnelo U, Tarnasky PR, Banerjee S, Itoi T, Moon JH, Kim DC, Gaidhane M, Raijman I, Peterson BT, Gress FG, Kahaleh M. Digital Single-operator Cholangioscopy (DSOC) Improves Interobserver Agreement (IOA) and Accuracy for Evaluation of Indeterminate Biliary Strictures: The Monaco Classification. J Clin Gastroenterol. 2022 Feb 1;56(2):e94-e97. doi: 10.1097/MCG.0000000000001321.
PubMed 32040050Kahaleh M, Raijman I, Gaidhane M, Tyberg A, Sethi A, Slivka A, Adler DG, Sejpal D, Shahid H, Sarkar A, Martins F, Boumitri C, Burton S, Bertani H, Tarnasky P, Gress F, Gan I, Ardengh JC, Kedia P, Arnelo U, Jamidar P, Shah RJ, Robles-Medranda C. Digital Cholangioscopic Interpretation: When North Meets the South. Dig Dis Sci. 2022 Apr;67(4):1345-1351. doi: 10.1007/s10620-021-06961-z. Epub 2021 Mar 30.
PubMed 33783691Saraiva MM, Ribeiro T, Ferreira JPS, Boas FV, Afonso J, Santos AL, Parente MPL, Jorge RN, Pereira P, Macedo G. Artificial intelligence for automatic diagnosis of biliary stricture malignancy status in single-operator cholangioscopy: a pilot study. Gastrointest Endosc. 2022 Feb;95(2):339-348. doi: 10.1016/j.gie.2021.08.027. Epub 2021 Sep 8.
PubMed 34508767Robles-Medranda C, Oleas R, Sanchez-Carriel M, Olmos JI, Alcivar-Vasquez J, Puga-Tejada M, Baquerizo-Burgos J, Icaza I, Pitanga-Lukashok H. Vascularity can distinguish neoplastic from non-neoplastic bile duct lesions during digital single-operator cholangioscopy. Gastrointest Endosc. 2021 Apr;93(4):935-941. doi: 10.1016/j.gie.2020.07.025. Epub 2020 Jul 22.
PubMed 32707155Robles-Medranda C, Valero M, Soria-Alcivar M, Puga-Tejada M, Oleas R, Ospina-Arboleda J, Alvarado-Escobar H, Baquerizo-Burgos J, Robles-Jara C, Pitanga-Lukashok H. Reliability and accuracy of a novel classification system using peroral cholangioscopy for the diagnosis of bile duct lesions. Endoscopy. 2018 Nov;50(11):1059-1070. doi: 10.1055/a-0607-2534. Epub 2018 Jun 28.
PubMed 29954008Robles-Medranda C, Baquerizo-Burgos J, Alcivar-Vasquez J, Kahaleh M, Raijman I, Kunda R, Puga-Tejada M, Egas-Izquierdo M, Arevalo-Mora M, Mendez JC, Tyberg A, Sarkar A, Shahid H, Del Valle-Zavala R, Rodriguez J, Merfea RC, Barreto-Perez J, Saldana-Pazmino G, Calle-Loffredo D, Alvarado H, Lukashok HP. Artificial intelligence for diagnosing neoplasia on digital cholangioscopy: development and multicenter validation of a convolutional neural network model. Endoscopy. 2023 Aug;55(8):719-727. doi: 10.1055/a-2034-3803. Epub 2023 Feb 13.
PubMed 36781156
Study at a glance
From the registry record, last updated by the sponsor on 17 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Validation of an Artificial Intelligence Software for Digital Cholangioscopy Diagnosis: an Observational Trial
- ClinicalTrials.gov ID
- NCT05147389
- Acronym / sponsor ID
- IECED-11032021
- Keywords
- Artificial Intelligence, Cholangioscopy, Neoplasia
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 170 participants (actual)
- Lead sponsor
- Instituto Ecuatoriano de Enfermedades DigestivasUniversity, hospital or other
- Collaborators
- The Methodist Hospital Research Institute, University of Sao Paulo, Vrije Universiteit Brussel, Advanced Endoscopy Research, Robert Wood Johnson Medical School Rutgers University, Baylor St. Luke's Medical Center, Universitair Ziekenhuis Brussel
- Study start
- 1 Oct 2020 (actual)
- Primary completion
- 30 Nov 2021 (actual)
- Study completion
- 1 May 2022 (actual)
- First posted
- 7 Dec 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. To date, there is not a universally accepted DSOC classification. Endoscopists' Intra and interobserver agreements vary widely. Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools is almost exclusively for intrahepatic CCA (iCCA). Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions.
In Ecuador, the investigators have recently proposed an AI model to classify bile duct lesions during real-time DSOC, which accurately detected malignancy patterns. This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with high DSOC experienced endoscopists.
Detailed description
Distinguishing neoplastic from non-neoplastic bile duct lesions is a challenge for clinicians. Magnetic resonance (MR) and biopsy guided by endoscopic retrograde cholangiopancreatography (ERCP) reached a negative predictive value (NPV) around 50%. On the other hand, Digital single-operator cholangioscopy (DSOC) findings achieve high diagnostic accuracy for neoplastic bile duct lesions. DSOC could be even better than DSOC-guided biopsy, which is inconclusive in some cases. However, to date, there is no universally accepted DSOC classification for that purpose. Also, endoscopists' Intra and interobserver agreements vary widely. Therefore, a more reproducible system is still needed.
With interesting results, Cholangiocarcinoma (CCA) assessment through artificial intelligence (AI) tools has been developed based on imaging radiomics. Nevertheless, CCA AI resources are almost exclusively for intrahepatic CCA (iCCA), with an endoscopic technique. Therefore, more AI tools are necessary for assessing extrahepatic neoplastic bile duct lesions. Perihilar (pCCA) and distal (dCCA) cholangiocarcinoma as the most typical neoplastic bile duct lesions. Both represent 50-60% and 20-30% of all CCA, including secondary malignancies by local extension (hepatocarcinoma, gallbladder, and pancreas cancer).
A recent Portuguese proof-of-concept study developed an AI tool based on convolutional neuronal networks (CNNs). It let to differentiate between malignant from benign bile duct lesions or normal tissue with very high accuracy. Still, it needs more external validation, including endoscopists' Intra and interobserver agreement comparison. In Ecuador, the investigators recently proposed an AI model to classify bile duct lesions during real-time DSOC, which has been able to detect malignancy pattern in all cases.
This research pursues a clinical validation of our AI model for distinguishing between neoplastic and non-neoplastic bile duct lesions, compared with six endoscopists with high DSOC experience.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Target follow-up
- 1 Year
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Neoplastic bile duct lesions | – | Diagnostic Test: AI model classification, Diagnostic Test: DSOC endoscopist experts' classificationThis group is confirmed by DSOC videos from patients with DSOC-confirmed neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm neoplastic bile duct lesion and the type: pCCA or dCCA, local extension of iCCA, hepatocarcinoma mixed CCA/hepatocarcinoma, gallbladder cancer, pancreas cancer, or any other neoplastic bile duct lesion. Based on follow-up, videos from patients with confirmed non-neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. |
| Non-neoplastic bile duct lesions | – | Diagnostic Test: AI model classification, Diagnostic Test: DSOC endoscopist experts' classificationThis group is confirmed by DSOC videos from patients with DSOC-confirmed non-neoplastic bile duct lesions, coming from each participating group. Each DSOC video corresponds to a complete DSOC procedure in a single patient. The non-neoplastic bile duct criteria are in accordance with the two following tools: the Robles-Medranda et al and the Mendoza classification. A further follow will be necessary to confirm non-neoplastic bile duct lesion and the type, when available: acute or chronic cholangitis secondary to stones or parasite's location, autoimmune cholestatic liver diseases as autoimmune sclerosant cholangitis, and primary biliary cholangitis. Based on follow-up, videos from patients with confirmed neoplastic bile duct lesions will be re-assessed and re-classified or finally excluded by an expert blinded to clinical records and who do not participate in videos classification. |
Who may qualify
- Ages
- 18 to 79 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Adult patients with indication of DSOC.
Key inclusion criteria (2 listed)
- Patients referred to our center with an indication of DSOC due to suspicion of CBD tumor or indeterminate CBD stenosis.
- Patients who authorized for recording DSOC procedure for this study.
Key exclusion criteria (5 listed)
- Any clinical condition which makes DSOC inviable.
- Patients with more than one DSOC.
- Low quality of recorded DSOC videos, even for AI model as for the expert endoscopists.
- Lost on a one-year follow-up after DSOC.
- Disagreement between DSOC findings vs. one-year follow-up, even after re-assessment of respective DSOC videos.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI model classificationAIWorks is an artificial intelligence model for real-time cholangioscopic detection of neoplastic and non-neoplastic bile duct lesions. It allows you to choose using a video file or a USB camera input as the detection source. Once the input source has been selected, the software performs real-time detection by surrounding the area of interest (i.e., the area with malignancy features) inside a bounding box. All detections made are displayed on the right side of the screen and can also be reviewed afterwards. | Diagnostic test | Neoplastic bile duct lesions, Non-neoplastic bile duct lesions |
| DSOC endoscopist experts' classificationSix endoscopists with high DSOC expertise will observe and classify a set of videos among neoplastic or non-neoplastic bile duct lesions following a Bernoulli distribution; blinded to clinical records and should have never attended said patients. Gastroenterologists from each center, with non-DSOC responsibility, will select DSOC videos and corresponding baseline data. DSOC videos and data will be gathered in one set. Each video represents a full DSOC for a single patient. The patient will be the unit of this study. The neoplastic bile duct criteria are in accordance with the Robles-Medranda et al and the Mendoza classifications (ie. Irregular mucosa surface, Tortuous and dilated vascularity, Irregular nodulations, Polyps, Ulceration, Honeycomb pattern, etc.). The experts will assess neoplastic bile duct by presence or absence of disaggregated criteria. Likewise, by Boolean logical operators, the statistical software will compute disaggregated answers. | Diagnostic test | Neoplastic bile duct lesions, Non-neoplastic bile duct lesions |
Primary outcome
Neoplastic bile duct diagnosis confirmation after one year follow-up
Time frame: One year
Cases will be first followed up during one year to confirm or discard neoplastic bile duct lesions. A definite diagnosis of neoplastic bile duct lesion will be based on DSOC-guided biopsy specimen or findings from further indicated procedures, including brush cytology fluoroscopy-guided, endoscopic ultrasound-guided tissue sampling, surgical samples, and even imaging test in the context of a more impaired patient. Finally, the agreement between one-year follow-up (gold standard) vs. AI model and DSOC endoscopist experts' classification will be verified through a 2 x 2 contingency table.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Nov 2022.
- Background: PubMed 34478737Kahaleh M, Gaidhane M, Shahid HM, Tyberg A, Sarkar A, Ardengh JC, Kedia P, Andalib I, Gress F, Sethi A, Gan SI, Suresh S, Makar M, Bareket R, Slivka A, Widmer JL, Jamidar PA, Alkhiari R, Oleas R, Kim D, Robles-Medranda CA, Raijman I. Digital single-operator cholangioscopy interobserver study using a new classification: the Mendoza Classification (with video). Gastrointest Endosc. 2022 Feb;95(2):319-326. doi: 10.1016/j.gie.2021.08.015. Epub 2021 Aug 31.
- Background: PubMed 32040050Sethi A, Tyberg A, Slivka A, Adler DG, Desai AP, Sejpal DV, Pleskow DK, Bertani H, Gan SI, Shah R, Arnelo U, Tarnasky PR, Banerjee S, Itoi T, Moon JH, Kim DC, Gaidhane M, Raijman I, Peterson BT, Gress FG, Kahaleh M. Digital Single-operator Cholangioscopy (DSOC) Improves Interobserver Agreement (IOA) and Accuracy for Evaluation of Indeterminate Biliary Strictures: The Monaco Classification. J Clin Gastroenterol. 2022 Feb 1;56(2):e94-e97. doi: 10.1097/MCG.0000000000001321.
- Background: PubMed 33783691Kahaleh M, Raijman I, Gaidhane M, Tyberg A, Sethi A, Slivka A, Adler DG, Sejpal D, Shahid H, Sarkar A, Martins F, Boumitri C, Burton S, Bertani H, Tarnasky P, Gress F, Gan I, Ardengh JC, Kedia P, Arnelo U, Jamidar P, Shah RJ, Robles-Medranda C. Digital Cholangioscopic Interpretation: When North Meets the South. Dig Dis Sci. 2022 Apr;67(4):1345-1351. doi: 10.1007/s10620-021-06961-z. Epub 2021 Mar 30.
- Results publication: PubMed 34508767Saraiva MM, Ribeiro T, Ferreira JPS, Boas FV, Afonso J, Santos AL, Parente MPL, Jorge RN, Pereira P, Macedo G. Artificial intelligence for automatic diagnosis of biliary stricture malignancy status in single-operator cholangioscopy: a pilot study. Gastrointest Endosc. 2022 Feb;95(2):339-348. doi: 10.1016/j.gie.2021.08.027. Epub 2021 Sep 8.
- Results publication: PubMed 32707155Robles-Medranda C, Oleas R, Sanchez-Carriel M, Olmos JI, Alcivar-Vasquez J, Puga-Tejada M, Baquerizo-Burgos J, Icaza I, Pitanga-Lukashok H. Vascularity can distinguish neoplastic from non-neoplastic bile duct lesions during digital single-operator cholangioscopy. Gastrointest Endosc. 2021 Apr;93(4):935-941. doi: 10.1016/j.gie.2020.07.025. Epub 2020 Jul 22.
- Results publication: PubMed 29954008Robles-Medranda C, Valero M, Soria-Alcivar M, Puga-Tejada M, Oleas R, Ospina-Arboleda J, Alvarado-Escobar H, Baquerizo-Burgos J, Robles-Jara C, Pitanga-Lukashok H. Reliability and accuracy of a novel classification system using peroral cholangioscopy for the diagnosis of bile duct lesions. Endoscopy. 2018 Nov;50(11):1059-1070. doi: 10.1055/a-0607-2534. Epub 2018 Jun 28.
- Derived from this study: PubMed 36781156Robles-Medranda C, Baquerizo-Burgos J, Alcivar-Vasquez J, Kahaleh M, Raijman I, Kunda R, Puga-Tejada M, Egas-Izquierdo M, Arevalo-Mora M, Mendez JC, Tyberg A, Sarkar A, Shahid H, Del Valle-Zavala R, Rodriguez J, Merfea RC, Barreto-Perez J, Saldana-Pazmino G, Calle-Loffredo D, Alvarado H, Lukashok HP. Artificial intelligence for diagnosing neoplasia on digital cholangioscopy: development and multicenter validation of a convolutional neural network model. Endoscopy. 2023 Aug;55(8):719-727. doi: 10.1055/a-2034-3803. Epub 2023 Feb 13.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Carlos Robles-Medranda principal investigator
Ecuadorian Institute of Digestive Diseases
6 sites in 4 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Common Bile Duct Neoplasms and Non-Neoplastic Bile Duct Disorder, run by Instituto Ecuatoriano de Enfermedades Digestivas at 6 sites in 4 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 17 Nov 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 6 sites in United States, Belgium, Brazil, Ecuador. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Neoplastic bile duct diagnosis confirmation after one year follow-up (time frame: One year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05147389, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Nov 2022.