Thymic Epithelial TumorINTHYMNCT06301945
Artificial Intelligence Prediction Tool in Thymic Epithelial Tumors
An observational study of Thymic Epithelial Tumor and Thymic Carcinoma, run by Erasmus Medical Center at 1 site in Netherlands.
Trial summary
Thymic epithelial tumors are rare neoplasms in the anterior mediastinum. The cornerstone of the treatment is surgical resection. Administration of postoperative radiotherapy is usually indicated in patients with more extensive local disease, incomplete resection and/or more aggressive subtypes, defined by the WHO… Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Thymic Epithelial Tumor, Thymic Carcinoma, Thymoma
- What is being tested?
- Artificial Intelligence Diagnostics and Recurrence Prediction Tool
- How many people
- 1,020 participants
- Where
- 1 siteNetherlands
- Study dates
- 1 Aug 2023to 1 Aug 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 Any age
- All sexes
- Child, Adult, Older adult
Study population: Study Population: This study focuses on individuals diagnosed with thymic epithelial tumors. The study includes patients from three datasets: Erasmus MC (710 patients), Maastro (137 patients), and University Hospital Lyon (181 patients). Additional Information: * Erasmus MC (710 patients): Includes age, gender, and diagnosis information; each patient may have multiple whole slide images. * Maastro (137 patients): Each patient may have multiple whole slide images. * University Hospital Lyon (181 patients): Each patient may have multiple whole slide images.
Who may be able to join
- Participants with specific diagnoses are eligible for inclusion in the study. The eligible diagnoses include various subtypes of thymoma and thymic carcinoma, specifically:
- Thymoma A
- Thymoma AB
- Thymoma B1
- Thymoma B2
- Thymoma B3
Show all 10Show fewer
- Thymic Carcinoma
- Inclusion is based on a consensus diagnosis with a level of agreement less than 70%. This criterion is applied during the training phase of the model.
- Recurrence Criteria:
- Participants with a documented recurrence outcome within a 5-year period are considered eligible for this aspect of the study. This criterion is primarily applied during the validation phase.
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Netherlands1 site, 1 recruiting
- Recruiting
Erasmus MC
Rotterdam, South Holland, 3015 GD
Anna Salut Esteve Domínguez, a.estevedominguez@erasmusmc.nl
About this study
Official title: Artificial Intelligence for Histopathological Classification and Recurrence Prediction of Thymic Epithelial Tumors
Thymic epithelial tumors are rare neoplasms in the anterior mediastinum. The cornerstone of the treatment is surgical resection. Administration of postoperative radiotherapy is usually indicated in patients with more extensive local disease, incomplete resection and/or more aggressive subtypes, defined by the WHO histopathological classification.
In this classification thymoma types A, AB, B1, B2, B3, and thymic carcinoma are distinguished. Studies have shown large discordances between pathologists in subtyping these tumors. Moreover, the WHO classification alone does not accurately predict the risk of recurrence, as within subtypes patients have divergent prognoses.
Read more
The investigators will develop AI models using digital pathology and relevant clinical variables to improve the accuracy of histopathological classification of thymic epithelial tumors, and to better predict the risk of recurrence.
In this multicentric and international project three existing databases will be used from Rotterdam, Maastricht and Lyon. For all models one database will be used to build AI models, and the other two for external validation.
The ultimate goal of this project is to develop AI models that support the pathologist in correctly subtyping thymic epithelial tumors, in order to prevent patients from under- or overtreatment with adjuvant radiotherapy.
- Being tested
- Artificial Intelligence Diagnostics, Recurrence Prediction Tool
- Keywords
- Artificial Intelligence, Digital pathology
- Medical subject headings
- Thymic epithelial tumor, Thymoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence DiagnosticsDiagnostic test
Also called AI Diagnostics, AI Classification
AI Diagnostics uses advanced algorithms for precise histological image analysis to help diagnose disease, including subtype.
Recurrence Prediction ToolDiagnostic test
This AI tool evaluates thymic tumour data and other clinical data and calculates the risk of recurrence, with the aim of analysing whether there is an association with specific subtypes of thymic epithelial tumours and clinical data.
| Study group | Role | What they receive |
|---|---|---|
| Patients with TET | Patients diagnosed with the following TET subtypes:
* Thymoma Type A
* Thymoma Type AB
* Thymoma Type B1
* Thymoma Type B2
* Thymoma Type B3
* Thymic Carcinoma Receives: Diagnostic Test: Artificial Intelligence Diagnostics | |
| Recurrence | Patients with thymic epithelial tumors who have experienced recurrence. Receives: Diagnostic Test: Recurrence Prediction Tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
WP1 - Databases/Data Pre-processing
The EMC-dataset includes 179 TET-patients classified by experienced TET-pathologists. Cases with good agreement between pathologists will be used for training AI-models. Evaluation includes digitized pathology slides assessed by an international expert-panel. The MUMC-database (137 patients) and CHUL-database (181 patients) provide additional data, including clinical variables. Relevant factors include age, gender, tumor volume, stage, completeness of resection, autoimmune disorders, and treatment details.
Measured: M1-M18
Secondary outcomes (1)
WP2 - Deep Learning-Model for TET Classification and Recurrence Prediction
This outcome aims to create an AI-framework with two principal goals. First, investigate TET-subtypes using four different models emphasizing cell type, morphological structures, and a combination. Second, classify patients based on recurrence outcome within 5 years. An ablation study will be conducted with state-of-the-art deep learning classifiers (ResNet, Inception).
Measured: M6-M32
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Mar 2024
- Study start1 Aug 2023
- Primary completion1 Aug 2027 (estimated)
- Study completion1 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Thymic Epithelial TumorStudies of the same condition, open and under way.
- More trials run by Erasmus Medical CenterThe sponsor's other registered studies.
- 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,020 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Erasmus Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- Maastro Clinic, The Netherlands, Hospices Civils de Lyon
- Responsible party
- Principal investigator, Anna Salut Esteve Domínguez, Erasmus Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06301945
- Sponsor's protocol ID
- Maastro Clinic
- Other IDs
- 72725524
- Acronym
- INTHYM
- Status last verified
- Mar 2024
- First submitted
- 4 Mar 2024
- Last updated
- 27 Mar 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Wolf JL, van Nederveen F, Blaauwgeers H, Marx A, Nicholson AG, Roden AC, Strobel P, Timens W, Weissferdt A, von der Thusen J, den Bakker MA. Interobserver variation in the classification of thymic lesions including biopsies and resection specimens in an international digital microscopy panel. Histopathology. 2020 Nov;77(5):734-741. doi: 10.1111/his.14167. Epub 2020 Sep 24.
PubMed 32506527Molina TJ, Bluthgen MV, Chalabreysse L, de Montpreville VT, de Muret A, Dubois R, Hofman V, Lantuejoul S, le Naoures C, Mansuet-Lupo A, Parrens M, Piton N, Rouquette I, Secq V, Girard N, Marx A, Besse B. Impact of expert pathologic review of thymic epithelial tumours on diagnosis and management in a real-life setting: A RYTHMIC study. Eur J Cancer. 2021 Jan;143:158-167. doi: 10.1016/j.ejca.2020.11.011. Epub 2020 Dec 11.
PubMed 33316754
Study at a glance
From the registry record, last updated by the sponsor on 27 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence for Histopathological Classification and Recurrence Prediction of Thymic Epithelial Tumors
- ClinicalTrials.gov ID
- NCT06301945
- Acronym / sponsor ID
- INTHYM / Maastro Clinic
- Keywords
- Artificial Intelligence, Digital pathology
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,020 participants (estimated)
- Lead sponsor
- Erasmus Medical CenterUniversity, hospital or other
- Collaborators
- Maastro Clinic, The Netherlands, Hospices Civils de Lyon
- Study start
- 1 Aug 2023 (actual)
- Primary completion
- 1 Aug 2027 (estimated)
- Study completion
- 1 Aug 2027 (estimated)
- First posted
- 8 Mar 2024 (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.
Thymic epithelial tumors are rare neoplasms in the anterior mediastinum. The cornerstone of the treatment is surgical resection. Administration of postoperative radiotherapy is usually indicated in patients with more extensive local disease, incomplete resection and/or more aggressive subtypes, defined by the WHO histopathological classification.
In this classification thymoma types A, AB, B1, B2, B3, and thymic carcinoma are distinguished. Studies have shown large discordances between pathologists in subtyping these tumors. Moreover, the WHO classification alone does not accurately predict the risk of recurrence, as within subtypes patients have divergent prognoses.
The investigators will develop AI models using digital pathology and relevant clinical variables to improve the accuracy of histopathological classification of thymic epithelial tumors, and to better predict the risk of recurrence.
In this multicentric and international project three existing databases will be used from Rotterdam, Maastricht and Lyon. For all models one database will be used to build AI models, and the other two for external validation.
The ultimate goal of this project is to develop AI models that support the pathologist in correctly subtyping thymic epithelial tumors, in order to prevent patients from under- or overtreatment with adjuvant radiotherapy.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients with TET | – | Diagnostic Test: Artificial Intelligence DiagnosticsPatients diagnosed with the following TET subtypes: * Thymoma Type A * Thymoma Type AB * Thymoma Type B1 * Thymoma Type B2 * Thymoma Type B3 * Thymic Carcinoma |
| Recurrence | – | Diagnostic Test: Recurrence Prediction ToolPatients with thymic epithelial tumors who have experienced recurrence. |
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- Study Population: This study focuses on individuals diagnosed with thymic epithelial tumors. The study includes patients from three datasets: Erasmus MC (710 patients), Maastro (137 patients), and University Hospital Lyon (181 patients). Additional Information: * Erasmus MC (710 patients): Includes age, gender, and diagnosis information; each patient may have multiple whole slide images. * Maastro (137 patients): Each patient may have multiple whole slide images. * University Hospital Lyon (181 patients): Each patient may have multiple whole slide images.
Key inclusion criteria (10 listed)
- Participants with specific diagnoses are eligible for inclusion in the study. The eligible diagnoses include various subtypes of thymoma and thymic carcinoma, specifically:
- Thymoma A
- Thymoma AB
- Thymoma B1
- Thymoma B2
Key exclusion criteria (0 listed)
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 |
|---|---|---|
| Artificial Intelligence DiagnosticsAlso: AI Diagnostics, AI ClassificationAI Diagnostics uses advanced algorithms for precise histological image analysis to help diagnose disease, including subtype. | Diagnostic test | Patients with TET |
| Recurrence Prediction ToolThis AI tool evaluates thymic tumour data and other clinical data and calculates the risk of recurrence, with the aim of analysing whether there is an association with specific subtypes of thymic epithelial tumours and clinical data. | Diagnostic test | Recurrence |
Primary outcome
WP1 - Databases/Data Pre-processing
Time frame: M1-M18
The EMC-dataset includes 179 TET-patients classified by experienced TET-pathologists. Cases with good agreement between pathologists will be used for training AI-models. Evaluation includes digitized pathology slides assessed by an international expert-panel. The MUMC-database (137 patients) and CHUL-database (181 patients) provide additional data, including clinical variables. Relevant factors include age, gender, tumor volume, stage, completeness of resection, autoimmune disorders, and treatment details.
1 secondary outcome
WP2 - Deep Learning-Model for TET Classification and Recurrence Prediction
Time frame: M6-M32
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Mar 2024.
- Background: PubMed 32506527Wolf JL, van Nederveen F, Blaauwgeers H, Marx A, Nicholson AG, Roden AC, Strobel P, Timens W, Weissferdt A, von der Thusen J, den Bakker MA. Interobserver variation in the classification of thymic lesions including biopsies and resection specimens in an international digital microscopy panel. Histopathology. 2020 Nov;77(5):734-741. doi: 10.1111/his.14167. Epub 2020 Sep 24.
- Background: PubMed 33316754Molina TJ, Bluthgen MV, Chalabreysse L, de Montpreville VT, de Muret A, Dubois R, Hofman V, Lantuejoul S, le Naoures C, Mansuet-Lupo A, Parrens M, Piton N, Rouquette I, Secq V, Girard N, Marx A, Besse B. Impact of expert pathologic review of thymic epithelial tumours on diagnosis and management in a real-life setting: A RYTHMIC study. Eur J Cancer. 2021 Jan;143:158-167. doi: 10.1016/j.ejca.2020.11.011. Epub 2020 Dec 11.
- Individual participant dataSharing planned: No
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Thymic Epithelial Tumor and Thymic Carcinoma, run by Erasmus Medical Center at 1 site in Netherlands.
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 10 inclusion and 0 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: looking for participants now, as of the sponsor's last update on 27 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Anna Salut Esteve Domínguez (0107043491, a.estevedominguez@erasmusmc.nl), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
WP1 - Databases/Data Pre-processing (time frame: M1-M18). 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 NCT06301945, which also lists 2 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 27 Mar 2024.