AI4CMR v1.0

AI4MedImaging Medical Solutions S.A.
AI4CMR v1.0 Model Card
Product Details
Model Identifier
Manufacturer
AI4MedImaging Medical Solutions S.A.
Product
AI4CMR v1.0
Version
Unknown
Date Cleared
07/22/2022
FDA Submission No.
Category
MIMPS
Model Characteristics
Inclusion Criteria
Cardiovascular images: multi-phase, multi-slice acquired from MRI scanners
Exclusion Criteria
Unknown
Instructions for Use
Not available
Indications for Use
Indication of Use
AI4CMR software is designed to report cardiac function measurements (ventricle volumes, ejection fraction, indices etc.) from 1.5T and 3T magnetic resonance (MR) scanners. AI4CMR uses artificial intelligence to automatically segment and quantify the different cardiac measurements. Its results are not intended to be used on a stand-alone basis for clinical decision-making. The user incorporating AI4CMR into their DICOM application of choice is responsible for implementing a user interface.
Intended User
Clinicians
Age
Unknown
Anatomy
Chest
Modality
MR
Output
● Anatomy and tissue segmentation ● LV/RV stroke volume ● LV/RV cardiac output ● LV/RV ejection fraction ● LV/RV end-diastolic volume ● LV/RV end-systolic volume
Details on Training Data Sets
Details on Training Data Sets
No. of Cases
Unknown
Age Range (Years)
Unknown
Sex (%)
  • Female: Unknown
  • Male: Unknown
  • Unknown: Unknown
Output
Unknown
Race (%)
  • White: Unknown
  • Black or African American: Unknown
  • American Indian or Alaska Native: Unknown
  • Asian: Unknown
  • Native Hawaiian or Other Pacific Islander: Unknown
  • Unknown: Unknown
Ethnicity (%)
  • Hispanic or Latino: Unknown
  • Not Hispanic or Latino: Unknown
  • Unknown: Unknown
Geographic Region (%)
  • USA: Unknown
  • International: Unknown
  • Unknown: Unknown
Scanner Manufacturer(s)
Unknown
Scanner Model(s)
Unknown
Model Performance
Study Type
Performance Testing Type
Both
Standalone Model Performance
Reference Standard (Ground Truth)
Interpretation by Reviewing Clinician
No. of Cases
15
Age Range (Years)
42 - 77
Sex (%)
  • Female: Unknown
  • Male: Unknown
  • Unknown: Unknown
Race (%)
  • White: Unknown
  • Black or African American: Unknown
  • American Indian or Alaska Native: Unknown
  • Asian: Unknown
  • Native Hawaiian or Other Pacific Islander: Unknown
  • Unknown: Unknown
Ethnicity (%)
  • Hispanic or Latino: Unknown
  • Not Hispanic or Latino: Unknown
  • Unknown: Unknown
Geographic Region (%)
  • USA: Unknown
  • International: Unknown
  • Unknown: Unknown
Output
Unknown
Scanner Manufacturer(s)
GE;Philips;Siemens
Scanner Model(s)
Unknown
No. of Sites
Unknown
Model Accuracy
Unknown
Model Sensitivity
Not provided
Model Specificity
Not provided
Reader Study Performance
No. of Readers
Unknown
No. of Cases
146
No. of Sites
Unknown
Output
Diseased: 60% Non-diseased: 40%
Age Range (Years)
17 - 85
Sex (%)
Male: 77
Race (%)
  • White: Unknown
  • Black or African American: Unknown
  • American Indian or Alaska Native: Unknown
  • Asian: Unknown
  • Native Hawaiian or Other Pacific Islander: Unknown
  • Unknown: Unknown
Ethnicity (%)
  • Hispanic or Latino: Unknown
  • Not Hispanic or Latino: Unknown
  • Unknown: Unknown
Geographic Region (%)
  • USA: Unknown
  • International: Unknown
  • Unknown: Unknown
Scanner Manufacturer(s)
GE;Philips;Siemens
Scanner Model(s)
Unknown
Model Accuracy
Unknown
Model Sensitivity
Not provided
Model Specificity
Not provided
Model Limitations, Warnings, & Precautions
Model Limitations, Warnings, & Precautions
Supported Scanner Manufacturer(s)
Unknown
Slice Thickness
Unknown
Contrast Use
Unknown
MRI Field Strength
Unknown
Reconstruction Kernel Used
Unknown
Alternative Choices
Alternative Choices
Previous Version(s)
Unknown
Contact Information
Contact Information
Point of Contact Name
Unknown
Email
Unknown
Additional Details
Related Use Cases
Unknown
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