(261 days)
ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.
ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.
ADAS 3D is indicated to be used only by qualified medical professionals for the visualization and analysis of cardiac images. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.
ADAS 3D is not intended to identify regions for catheter ablation or treatment of arrhythmias.
ADAS 3D is a software-based image processing tool for post-processing cardiovascular enhanced Magnetic Resonance (MRI) images and Computed Tomography Angiography (CTA) images.
ADAS 3D is designed to process DICOM image databases to enable the calculation, quantification and visualization of 3D cardiac imaging data by displaying and quantifying the levels of enhancement. ADAS 3D also enables the visualization of the cardiac chamber and the adjacent anatomy. After data processing, the data and images can be exported utilizing industry standard formats for viewing on other system, including Electrophysiology (EP) navigation system.
The provided document is a 510(k) summary for the ADAS 3D device. It identifies a predicate device (MR-CT VVA, K140587) and discusses the substantial equivalence of ADAS 3D based on intended use, indications for use, and performance, including non-clinical and clinical data.
1. Table of acceptance criteria and the reported device performance
The document does not explicitly state quantitative acceptance criteria or a direct performance table for ADAS 3D against such criteria. Instead, it relies on comparison to a predicate device and states that "clinical data was used to test and validate this software as described in section 18 of this submission to support this premarket notification and to establish the decision concerning adequate safety and performance of the predicate device." It concludes that ADAS 3D is "substantially equivalent to the listed legally marketed predicate devices."
Therefore, the reported device performance is implicitly considered to be equivalent to the predicate device, MR-CT VVA (K140587), and to generally meet the safety and performance standards for a radiological image processing system.
2. Sample size used for the test set and the data provenance
The document states that "Clinical data was used to test and validate this software as described in section 18 of this submission." However, Section 18 is not included in the provided text, so the specific sample size for the test set and the data provenance (e.g., country of origin, retrospective or prospective) cannot be determined from the given information.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is also not present in the provided text. The document mentions that the device is "intended to be used by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians)," but it does not specify how many or with what qualifications experts were involved in establishing ground truth for the validation studies.
4. Adjudication method
The adjudication method for the test set is not mentioned in the provided document.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, if so, what was the effect size of how much human readers improve with AI vs without AI assistance
The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was conducted to measure human reader improvement with or without AI assistance. The focus is on the software's ability to provide visualization and quantification to support clinical decision-making, rather than directly improving human reader performance metrics.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
The document describes ADAS 3D as a "software-based image processing tool" for "calculation, quantification and visualization of 3D cardiac imaging data." It identifies specific functions like "Left Ventricle Layer Computation," "Enhancement Quantification algorithm," and "3D Corridor Detection Algorithm." These descriptions strongly suggest that standalone algorithm performance was evaluated, as the software performs these calculations and visualizations independently. The output then "supports" qualified medical professionals, implying the algorithm runs without a "human-in-the-loop" for its primary processing functions.
7. The type of ground truth used
The specific type of ground truth used for its clinical validation is not explicitly stated in the provided text. The device processes MR and CT images and focuses on identifying and quantifying myocardial scar and 3D corridors of border zone tissue. Therefore, the ground truth would likely involve expert consensus interpretations of complex cardiac imaging, potentially correlated with other clinical data or pathology where available, but this is not confirmed in the document.
8. The sample size for the training set
The document does not provide any information regarding the sample size used for the training set for the ADAS 3D algorithms.
9. How the ground truth for the training set was established
The document does not provide any information regarding how the ground truth for the training set was established.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).