(99 days)
ct42 is intended to be used for viewing, post-processing and quantitative evaluation of cardiovascular computed tomography (CT) images in a Digital Imaging and Communications in Medicine (DICOM) Standard format. It enables; Importing Cardiac CT Images in DICOM format Supporting clinical diagnostics by qualitative analysis of the cardiac CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including multi-planner reconstructions of the images. Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac CT images, specifically distance, area, volume and mass Supporting clinical diagnostics by using area and volume measurements for measuring LV function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac CT images. Supporting clinical diagnostics by quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores. It shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process. ct42 is a software application that can be used as a stand-alone product or in a networked environment. The target population for the ct42 is not restricted, however the image acquisition by a cardiac CT scanner may limit the use of the device for certain sectors of the general public. ct42 shall not be used to view or analyze images of any part of the body except the cardiac CT images acquired from a cardiovascular CT scanner.
ct42 is a dedicated software application for evaluating cardiovascular images in a DICOM Standard format. The software can be used as a stand-alone product that can be integrated into a hospital or private practice environment. ct42 has a graphical user interface which allows users to qualitatively and quantitatively analyze cardiac CT images for volume/mass, and calcium scoring. It provides a comprehensive set of tools for the analysis of Cardiovascular Computed Tomography (CT) images.
Here's an analysis of the provided text regarding the acceptance criteria and study for the ct42 Cardiac Computed Tomography (CT) Software:
Note: The provided document is a 510(k) Summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed performance study with acceptance criteria in the manner one might find in a clinical trial report. As such, some requested information (like specific numerical acceptance criteria and a detailed study proving the device meets those criteria) is not explicitly present in the provided text. The document states that "The successful non-clinical testing demonstrates the safety and effectiveness of the ct42 when used for the defined indications for use and demonstrates that the device for which the 510(k) is submitted performs as well as or better than the legally marketed predicate device."
Acceptance Criteria and Reported Device Performance
The document does not explicitly state numerical acceptance criteria in a table format with corresponding reported performance for the ct42 software. Instead, it relies on demonstrating equivalence to a predicate device (Ziosoft - Cardiac Function Analysis & Calcium Scoring, K083446) by possessing similar features and functionalities. The "Conclusion" section indirectly serves as the statement of meeting acceptance, asserting that "ct42... demonstrates that the device... performs as well as or better than the legally marketed predicate device."
Here's a table based on the "Device Comparison Table" provided, highlighting the features where equivalence is drawn, which implicitly serve as the "acceptance criteria" for functionality:
| Acceptance Criteria (Feature/Functionality) | Reported Device Performance (ct42) |
|---|---|
| Post processes ECG gated - Cardiac CT images | YES |
| Image viewer functionality | YES |
| Left ventricular ejection fraction | YES |
| End diastolic volume | YES |
| End systolic volume | YES |
| Stroke volume | YES |
| Cardiac output | YES |
| Cardiac Index | YES |
| Wall thickness | YES |
| Wall thickness ratio | YES |
| Wall movement | YES |
| Volume Curve | YES |
| Calcium Scoring | YES |
| Evaluates calcified plaque in the coronary arteries | YES |
| Agatston calcium score | YES |
| Volume calcium score | YES |
| Calcium mass/density calculations | YES (calculates mass) |
| DICOM compliant | YES |
Additional Information on the Study:
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Sample size used for the test set and the data provenance:
- Sample Size: Not explicitly stated in the provided 510(k) summary. The document mentions "non-clinical testing" and testing "according to the specifications that are documented in a Master Software Test Plan," but specific details about the number of cases or images in the test set are absent.
- Data Provenance: Not specified. It's unclear if the data was retrospective or prospective, or its country of origin.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. The document does not detail how ground truth was established for any testing.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not specified.
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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:
- No. The document presents a substantial equivalence claim based on feature comparison and non-clinical software testing. It does not describe a MRMC comparative effectiveness study involving human readers and AI assistance. The device itself is a software application for viewing, post-processing, and quantitative evaluation, implying it's a tool for human professionals, but no study on human performance improvement is mentioned.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The submission focuses on "non-clinical testing" to demonstrate safety and effectiveness and equivalence to a predicate device. This implies testing the algorithm's functionality and accuracy in various measurements (distance, area, volume, mass, calcium scoring) in a standalone manner, but the specifics of how this was done (e.g., comparing algorithm outputs to known truths or another software's output) are not detailed. The term "standalone" performance in the context of an FDA submission for this type of device usually refers to the accuracy of its quantitative measurements rather than a human-like diagnostic output.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Not explicitly stated. Given the nature of the device (quantitative measurements for cardiac CT), ground truth for accuracy testing would typically involve comparisons to:
- Manual measurements by experts (expert consensus)
- Measurements from another validated software/method
- Perhaps in some cases, correlation with pathology or invasive measurements, though this is less common for software functionality claims.
- The document does not detail which of these, if any, were used.
- Not explicitly stated. Given the nature of the device (quantitative measurements for cardiac CT), ground truth for accuracy testing would typically involve comparisons to:
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The sample size for the training set:
- Not applicable/Not mentioned. The provided document is for a traditional 510(k) submission for ct42. It describes a software application for quantitative analysis of CT images. It does not indicate that this device utilizes machine learning or AI models that would require a distinct "training set" in the modern sense. The "testing" mentioned refers to traditional software validation and verification.
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How the ground truth for the training set was established:
- Not applicable, as no training set (for machine learning) is implied or mentioned for this device.
§ 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).