Infiltrative CardiomyopathyNCT05108168
Analysis of Clinical featuRes and Echocardiographic Characteristics for Diagnosis of Infiltrative cardiomyopaThy (ACREDIT): Retrospective Multi-center Observational Study
An observational study of Infiltrative Cardiomyopathy, run by Yonsei University at 1 site in South Korea.
Trial summary
This study sought to develop an algorithm by collecting echocardiographic image information and related clinical information capable of quantitatively evaluating changes of the myocardium through machine learning. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Infiltrative Cardiomyopathy
- How many people
- 500 participants
- Where
- 1 siteSouth Korea
- Study dates
- 4 Jan 2021to 31 Dec 2021
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: It is important to obtain as large image data as possible to develop an algorithm capable of diagnosing various infiltrative myocardial diseases. Infiltrative cardiomyopathy is a rare disease, and it was reported that the prevalence of cardiac amyloidosis in Korea was 1.91 per 100,000 in 2015.2 In the case of other diseases, there has been no report of the prevalence in Korea, but reports from an overseas report that cardiac sarcoidosis is 2.2 per 100,000, 8 and Fabry disease is 0.9 to 2.5 per 100,000. 9,10 Securing enough data that can be learned to improve machine learning accuracy is not easy because of the scarcity of invasive cardiomyopathy. Furthermore, it is difficult to confirm the disease. Therefore, it is necessary to review and obtain clinical information and echocardiographic image data of as many confirmed patients as possible. This study is a retrospective observational study, and the expected number of target subjects is about 500.
Who may be able to join
- Selection criteria for screening (1) 18 years old or older (2) Patients with infiltrative cardiomyopathy (the diagnostic name for each of the following diseases) or systemic disease (such as amyloidosis, multiple myeloma, sarcoidosis) (3) Search Period: January 1, 2010-December 31, 2020
- Criteria for enrolling patients
- Patients who are satisfied with at least one of each definition are selected.
- Cardiac amyloidosis1,5,11,12 I. 'Definite': Positive myocardial biopsy (Congo-Red positive) II. 'Probable': One of the following imaging findings along with a positive biopsy of tissues other than myocardium A. Positive DPD / PYP scan Grade 2-3 cardiac uptake B. Echocardiography Symmetrical increase in LV and RV wall thickness Dilated LA and RA Granular appearance of myocardium Pericardial effusion Decreased or normal RQS complex voltage despite increased LV wall thickness C. Cardiac magnetic resonance imaging Diffuse subendocardial late Gd-enhancement Elevated native T1 and ECV value III. 'Possible': Two or more of the above imaging findings are satisfied without biopsy findings, and it is suitable for the diagnosis according to all clinical findings
- ② Cardiac sarcoidosis13,14,15,16 I. 'Definite': If all of the following are satisfied A. Noncaseating, multinucleated giant cell granuloma surrounded by bands of dense collagen fibers in endomyocardial biopsy B. Compatible clinical presentation C. Exclusion of other causes of granulomatous inflammation II. 'Probable': Two or more of the following findings along with a positive biopsy of tissues other than myocardium A. Electrocardiogram High-grade atrioventricular block (including complete atrioventricular block) or fatal ventricular arrhythmia (e.g., sustained ventricular tachycardia and ventricular fibrillation) B. Echocardiography Variable focal LV wall thinning (frequently at the basal septum, lateral wall) Focal wall motion abnormalities do not match coronary artery territory C. Cardiac magnetic resonance imaging Patch, basal and lateral LV wall late Gd-enhancement D. Positron Emission Tomography - Computed Tomography Focal increased FDG-uptake IV. 'Possible': Two or more of the above imaging findings are satisfied without biopsy findings, and it is suitable for the diagnosis according to all clinical findings
- Hemochromatosis 17 I. 'Definite': Positive myocardial biopsy Iron deposits within the myocyte II. 'Probable': Non-myocardial tissue biopsy positive or iron overload clinical evidence (such as hereditary hemochromatosis, transfusion-dependent anemia) and the following imaging findings A. Echocardiography Dilated LV with global systolic dysfunction B. Cardiac magnetic resonance imaging Low T2* value of myocardium
Show all 10Show fewer
- Etc
- ① Fabry disease18,19 I. 'Definite': Positive myocardial biopsy Enlarged myocytes with clusters of concentric glycolipid (myelinoid bodies) within lysosomes II. 'Probable': A-galactosidase A screening test and X-linked genetic test positive, along with the following echocardiographic findings A. Echocardiography Symmetrical increase in LV and RV wall thickness
- ② Danon disease20 I. 'Definite': Positive for genetic testing or biopsy of myocardial tissue, along with the following echocardiographic findings Symmetrical increase in LV and/or RV wall thickness Decreased LV systolic function
- ③ Cardiac oxalosis1 I. 'Definite': Positive myocardial biopsy II. 'Probable': The following echocardiographic findings along with a history of massive transfusion or positive biopsy of tissues other than myocardium Symmetrical increase in LV and RV wall thickness Patchy, echodense speckled reflection
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
South Korea1 site, 1 recruiting
- Recruiting
Yonsei University Health System, Severance Hospital, Division of Cardiology
Seoul
Hyuk-jae Chang, +82 2-2228-8460, hjchang@yuhs.ac
About this study
This study sought to develop an algorithm by collecting echocardiographic image information and related clinical information capable of quantitatively evaluating changes of the myocardium through machine learning. Moreover, the researchers investigate the usefulness of an algorithm for early diagnosis and differential diagnosis of infiltrative cardiomyopathy.
Read the detailed description
- Study Design: Multicenter Retrospective Observational Study
- Study method: If the above selection criteria are met, the index visit echocardiographic images which were performed immediately before or closest to the time of hospitalization for final diagnosis, echocardiographic images of the pre-visit and post-visit from the final diagnosis, and clinical information will be obtained. Chest X-ray, electrocardiogram, and echocardiography images are extracted in raw DICOM format and then analyzed in the core lab (Severance hospital). The characteristics of patients with infiltrative cardiomyopathy are identified through the collection of relevant clinical information, and a method for non-invasive early diagnosis and differential diagnosis of infiltrative cardiomyopathy is developed.
- Quantative analysis of echocardiographic images using Radiomics
- Radiomics is a method of extracting a large number of quantitative image features (300-500 features such as shape, entropy, volume, etc.) from non-invasive medical images (CT, MRI, etc.) and statistically analyzing the features. Its value has been demonstrated through the studies for prediction of breast cancer recurrence and lesion classification.
- Using the open source platform PyRadiomics19, we extract the radiomic characteristics for brightness (Energy, Entropy, Mean, Median, etc.) and texture (Gray Level Co-occurrence Matrix Contrast, Difference Variance, Maximal Correlation Coefficient, etc.) from the set region of interest.
- The differences between infiltrative cardiomyopathy and normal control are identified using clinical information and radiomics features extracted from echocardiography at the time of the diagnosis visit. The algorithms to distinguish the disease will be developed using machine learning methods such as support vector machine classifier.
- Conditions
- Infiltrative Cardiomyopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| infiltrative cardiomyopathy | infiltrative cardiomyopathy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity
Sensitivity (True Positive Rate) refers to the proportion of those who have the infiltrative cardiomyopathy that received a positive result on the diagnostic algorythm by machine learning.
Measured: until June 30, 2022
Specificity
Specificity refers to the proportion of those who do not have the infiltrative cardiomyopathy that received a negative result on the test.
Measured: until June 30, 2022
Area under the curve of the receiver operation characteristics
Measured: until June 30, 2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Nov 2021
- Study start4 Jan 2021
- Primary completion16 Dec 2021 (estimated)
- Study completion31 Dec 2021 (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 Infiltrative CardiomyopathyStudies of the same condition, open and under way.
- More trials run by Yonsei UniversityThe 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
- Retrospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Yonsei University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Hyuk-jae Chang, Principal investigator, Yonsei University Health System, Severance Hospital, Division of Cardiology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05108168
- Sponsor's protocol ID
- 4-2020-1278
- Status last verified
- Oct 2021
- First submitted
- 24 Oct 2021
- Last updated
- 4 Nov 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Seward JB, Casaclang-Verzosa G. Infiltrative cardiovascular diseases: cardiomyopathies that look alike. J Am Coll Cardiol. 2010 Apr 27;55(17):1769-79. doi: 10.1016/j.jacc.2009.12.040.
PubMed 20413025van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts HJWL. Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res. 2017 Nov 1;77(21):e104-e107. doi: 10.1158/0008-5472.CAN-17-0339.
PubMed 29092951
Study at a glance
From the registry record, last updated by the sponsor on 4 Nov 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Analysis of Clinical featuRes and Echocardiographic Characteristics for Diagnosis of Infiltrative cardiomyopaThy (ACREDIT): Retrospective Multi-center Observational Study
- ClinicalTrials.gov ID
- NCT05108168
- Acronym / sponsor ID
- 4-2020-1278
- Conditions
- Infiltrative Cardiomyopathy
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Yonsei UniversityUniversity, hospital or other
- Study start
- 4 Jan 2021 (actual)
- Primary completion
- 16 Dec 2021 (estimated)
- Study completion
- 31 Dec 2021 (estimated)
- First posted
- 4 Nov 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.
This study sought to develop an algorithm by collecting echocardiographic image information and related clinical information capable of quantitatively evaluating changes of the myocardium through machine learning. Moreover, the researchers investigate the usefulness of an algorithm for early diagnosis and differential diagnosis of infiltrative cardiomyopathy.
Detailed description
- Study Design: Multicenter Retrospective Observational Study
- Study method: If the above selection criteria are met, the index visit echocardiographic images which were performed immediately before or closest to the time of hospitalization for final diagnosis, echocardiographic images of the pre-visit and post-visit from the final diagnosis, and clinical information will be obtained. Chest X-ray, electrocardiogram, and echocardiography images are extracted in raw DICOM format and then analyzed in the core lab (Severance hospital). The characteristics of patients with infiltrative cardiomyopathy are identified through the collection of relevant clinical information, and a method for non-invasive early diagnosis and differential diagnosis of infiltrative cardiomyopathy is developed.
- Quantative analysis of echocardiographic images using Radiomics
- Radiomics is a method of extracting a large number of quantitative image features (300-500 features such as shape, entropy, volume, etc.) from non-invasive medical images (CT, MRI, etc.) and statistically analyzing the features. Its value has been demonstrated through the studies for prediction of breast cancer recurrence and lesion classification.
- Using the open source platform PyRadiomics19, we extract the radiomic characteristics for brightness (Energy, Entropy, Mean, Median, etc.) and texture (Gray Level Co-occurrence Matrix Contrast, Difference Variance, Maximal Correlation Coefficient, etc.) from the set region of interest.
- The differences between infiltrative cardiomyopathy and normal control are identified using clinical information and radiomics features extracted from echocardiography at the time of the diagnosis visit. The algorithms to distinguish the disease will be developed using machine learning methods such as support vector machine classifier.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| infiltrative cardiomyopathy | – | –infiltrative cardiomyopathy |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- It is important to obtain as large image data as possible to develop an algorithm capable of diagnosing various infiltrative myocardial diseases. Infiltrative cardiomyopathy is a rare disease, and it was reported that the prevalence of cardiac amyloidosis in Korea was 1.91 per 100,000 in 2015.2 In the case of other diseases, there has been no report of the prevalence in Korea, but reports from an overseas report that cardiac sarcoidosis is 2.2 per 100,000, 8 and Fabry disease is 0.9 to 2.5 per 100,000. 9,10 Securing enough data that can be learned to improve machine learning accuracy is not easy because of the scarcity of invasive cardiomyopathy. Furthermore, it is difficult to confirm the disease. Therefore, it is necessary to review and obtain clinical information and echocardiographic image data of as many confirmed patients as possible. This study is a retrospective observational study, and the expected number of target subjects is about 500.
Key inclusion criteria (10 listed)
- Selection criteria for screening (1) 18 years old or older (2) Patients with infiltrative cardiomyopathy (the diagnostic name for each of the following diseases) or systemic disease (such as amyloidosis, multiple myeloma, sarcoidosis) (3) Search Period: January 1, 2010-December 31, 2020
- Criteria for enrolling patients
- ② Cardiac sarcoidosis13,14,15,16 I. 'Definite': If all of the following are satisfied A. Noncaseating, multinucleated giant cell granuloma surrounded by bands of dense collagen fibers in endomyocardial biopsy B. Compatible clinical presentation C. Exclusion of other causes of granulomatous inflammation II. 'Probable': Two or more of the following findings along with a positive biopsy of tissues other than myocardium A. Electrocardiogram High-grade atrioventricular block (including complete atrioventricular block) or fatal ventricular arrhythmia (e.g., sustained ventricular tachycardia and ventricular fibrillation) B. Echocardiography Variable focal LV wall thinning (frequently at the basal septum, lateral wall) Focal wall motion abnormalities do not match coronary artery territory C. Cardiac magnetic resonance imaging Patch, basal and lateral LV wall late Gd-enhancement D. Positron Emission Tomography - Computed Tomography Focal increased FDG-uptake IV. 'Possible': Two or more of the above imaging findings are satisfied without biopsy findings, and it is suitable for the diagnosis according to all clinical findings
- Etc
- ① Fabry disease18,19 I. 'Definite': Positive myocardial biopsy Enlarged myocytes with clusters of concentric glycolipid (myelinoid bodies) within lysosomes II. 'Probable': A-galactosidase A screening test and X-linked genetic test positive, along with the following echocardiographic findings A. Echocardiography Symmetrical increase in LV and RV wall thickness
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.
Primary outcome
Sensitivity
Time frame: until June 30, 2022
Sensitivity (True Positive Rate) refers to the proportion of those who have the infiltrative cardiomyopathy that received a positive result on the diagnostic algorythm by machine learning.
Specificity
Time frame: until June 30, 2022
Specificity refers to the proportion of those who do not have the infiltrative cardiomyopathy that received a negative result on the test.
Area under the curve of the receiver operation characteristics
Time frame: until June 30, 2022
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Nov 2021.
- Background: PubMed 20413025Seward JB, Casaclang-Verzosa G. Infiltrative cardiovascular diseases: cardiomyopathies that look alike. J Am Coll Cardiol. 2010 Apr 27;55(17):1769-79. doi: 10.1016/j.jacc.2009.12.040.
- Background: PubMed 29092951van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts HJWL. Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res. 2017 Nov 1;77(21):e104-e107. doi: 10.1158/0008-5472.CAN-17-0339.
- 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. This study is not recruiting at the moment.
Hyuk-jae Chang principal investigator
Yonsei University Health System, Severance Hospital, Division of Cardiology
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 Infiltrative Cardiomyopathy, run by Yonsei University at 1 site in South Korea.
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: status not confirmed, as of the sponsor's last update on 4 Nov 2021. 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 South Korea. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Hyuk-jae Chang (+82 2-2228-8460, hjchang@yuhs.ac), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity (time frame: until June 30, 2022). The study lists 3 primary outcomes in all. 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 NCT05108168, 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 4 Nov 2021.