Clinical trial NCT06328075: Artificial Intelligence to Assist the Echocardiographic Identification of Transthyretin Cardiac Amyloidosis
Official title: Artificial Intelligence to Assist the Echocardiographic Identification of Transthyretin Cardiac Amyloidosis
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Amyloid Cardiomyopathy
Transthyretin Amyloid Cardiomyopathy
Transthyretin Cardiac Amyloidosis
Keywords: echocardiography
artificial intelligence
Transthyretin Amyloid Cardiomyopathy
Lead sponsor: Bichat Hospital
Sponsor class: OTHER
Collaborators: name: Bichat Hospital
name: Bioquantis
First posted: 2024-03-25
Enrollment: 15000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The ATTR-CM cohort will be recruited in referral tertiary centers for cardiac amyloidosis The Control cohort will be recruited in the same centers from patients presenting an indication for transthoracic echocardiography as part of cardiological follow-up

Brief summary: The goal of this study is to develop an algorithm using artificial intelligence (AI) to assist identification of potential ATTR-CM cases using routine transthoracic echocardiography.

The main questions it aims to answer are:

* is the algorithm able to diagnose ATTR-CM
* is the algorithm able to diagnose different types of ATTR-CM (ATTRv, ATTRwt)

This is a non interventional study. Participant' echocardiographies will be, after deidentification, used to train, valid and test the algorithm.

Detailed description: Transthyretin (TTR) amyloidosis is a serious systemic disease affecting multiple target organs including the peripheral nervous system, heart, and kidney. In the absence of treatment, the median survival for symptomatic forms with cardiac involvement is 3 to 4 years.

In recent years, new treatments have proven their effectiveness in transthyretin amyloidosis, making it possible to slow the progression of neuropathy and cardiac damage. These treatments seem particularly effective when they are initiated at an early stage of the disease.

It is therefore necessary to establish the diagnosis as early as possible in order to benefit the most from the treatment. However, during the clinical examination, the electrocardiogram or the routine echocardiography, the signs evoking cardiac amyloidosis are not specific. The initial diagnosis is therefore often difficult, missed or delayed and the median time between the first symptoms and the initiation of treatment is approximately 3 years.

It is therefore the initial phase of diagnosis that must be improved in a sufficiently sensitive and specific manner to detect potential cases early while avoiding unnecessary examinations in the event of a low probability.

The objective of the study is to develop and validate a tool to assist the screening of cardiac transthyretin amyloidosis, from standard echocardiography, without the need for active participation of the cardiologist in the diagnostic process. This diagnostic contribution will allow the cardiologist to evoke the diagnosis of cardiac amyloidosis and to consider additional explorations.

Eligibility criteria: ATTR-CM patients:

Inclusion Criteria:

* Cardiac transthyretin amyloidosis diagnosed on the classic criteria:

  1. Absence of monoclonal immunoglobulin AND
  2. Presence of a bisphosphonate scintigraphy with enhancement in the cardiac area OR

  2-Presence of a cardiac biopsy showing transthyretin (Congo red positive) cardiac amyloidosis (demonstrated either by immunostaining or by mass spectrometry) OR 3-Presence of a peripheral biopsy showing transthyretin amyloidosis (see above) associated with cardiac infiltration (parietal thickness \>12mm without other cause of cardiac hypertrophy)
* No opposition to research

Non-inclusion criteria:

* Another cause of cardiac amyloidosis: AL AA amyloidosis...
* Mixed heart disease with associated presence of non-amyloid heart disease (ischemic heart disease, dilated, etc.)

Control patients:

Inclusion criteria:

* Indication for transthoracic echocardiography as part of cardiological follow-up
* Patient affiliated with social security
* Patient's agreement to participate in the research and signature of the consent form.
* Technical conditions of the examination and echogenicity allowing acquisition of good quality echocardiographic images, allowing post processing

Non-inclusion criteria:

* Presence of cardiac amyloidosis as defined above
* Presence of transthyretin amyloidosis even without demonstrated cardiac involvement
* Patient monitored for asymptomatic transthyretin mutation
* Minor patient or patient unable to give their consent (unconscious patient, under guardianship)

Primary outcomes:
measure: Building and validating the diagnostic performance metrics curves of the AI algorithm to diagnose ATTR-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics of the AI algorithm to diagnose ATTR-CM :
timeFrame: year 1
Secondary outcomes:
measure: Building and validating the diagnostic performance metrics of the AI algorithm to diagnose ATTRwt-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics of the AI algorithm to diagnose ATTRv-V122I-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics of the AI algorithm to diagnose ATTRv-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics of the AI algorithm to differentiate ATTR-CM from LV hypertrophy (LVH) :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics curves of the AI algorithm to diagnose ATTRwt-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics curves of the AI algorithm to diagnose ATTRv-V122I-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics curves of the AI algorithm to diagnose ATTRv-CM :
timeFrame: year 1
measure: Building and validating the diagnostic performance metrics curves of the AI algorithm to differentiate ATTR-CM from LV hypertrophy (LVH) :
timeFrame: year 1
Other outcomes:
Locations:
city: Paris
country: France
facility: Bichat
Study officials:
affiliation: Bichat Hospital
name: Gabriel Steg, MD, PhD
role: STUDY_CHAIR
References: