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510(k) Data Aggregation
(109 days)
Calcium scoring of calibrated CT images to provide quantitative measures of calcium content in the coronary arteries and aorta. The software is intended to be used under the supervision of trained physicians to monitor progression of vascular calcium which may be useful in the prognosis of Cardiovascular disease.
N-Vivo™ Calcium Score is a calibrated software program for non-invasive identification and quantification of calcified plaques in the coronary arteries and aorta using CT images. The software runs on a standard PC with basic image processing, database and reporting functions.
N-Vivo™ may be used to monitor progression of calcium which may be useful in the prognosis of cardiovascular disease.
A software package operating on a PC which facilitates non-invasive measurements of vascular calcified plaques. The device provides Agaston, Volume and Mass Scores using Phantom Calibrated CT images.
The key features include:
- Hybrid calibration with external phantom and invivo blood pool reference. .
- 사 Plaque definition which include statistical and calibrated thresholds for a calcium mass measurement.
- . Artery trace which segments regions of the heart that include the coronary arteries and aorta.
- . Automated identification, quantification, and scoring of vascular calcium.
- 내 PC workstation with web browser based interface which includes database, Dicom reports, Serial graphs and QA module.
The provided text is a 510(k) summary for the N-Vivo Calcium Score device, a software package for calcium scoring from CT images. It does not contain a detailed study description with specific acceptance criteria or an explicit comparative effectiveness study. The document focuses on establishing substantial equivalence to previously marketed devices.
However, based on the information provided, we can infer some details and highlight what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state acceptance criteria or provide a table of performance metrics. It mainly focuses on the device description and its intended use. The closest statement regarding performance is: "The calibration and software analysis improves the performance of calcium measurements from reconstructed CT images." However, no specific data demonstrating this improvement or against a defined acceptance criterion is provided.
2. Sample Size Used for the Test Set and Data Provenance
This information is not provided in the document.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
This information is not provided in the document.
4. Adjudication Method for the Test Set
This information is not provided in the document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A multi-reader multi-case (MRMC) comparative effectiveness study, which would involve human readers improving with AI vs. without AI assistance, is not mentioned or described in this document. The focus is on the device's ability to provide quantitative measures, not on its impact on human reader performance.
6. Standalone Performance Study
While the device's function is standalone (algorithm-only), a detailed standalone performance study with specific metrics and results against a ground truth is not explicitly described in this document. The statement "The calibration and software analysis improves the performance of calcium measurements" implies a standalone capability, but without specific study details.
7. Type of Ground Truth Used
The document states that the device provides "Agaston, Volume and Mass Scores using Phantom Calibrated CT images" and uses "Hybrid calibration with external phantom and invivo blood pool reference." This suggests that phantom-based calibration and potentially in-vivo biological references are used to establish a form of ground truth for the measurements. However, the exact nature of the ground truth for an independent test set (e.g., pathology, clinical outcomes) is not detailed. It implies a focus on accuracy of measurement against calibrated standards rather than diagnostic accuracy against a clinical outcome.
8. Sample Size for the Training Set
This information is not provided in the document.
9. How the Ground Truth for the Training Set Was Established
This information is not provided in the document. However, similar to point 7, it can be inferred that phantom-based calibration and in-vivo blood pool references played a role in the development and refinement (training) of the algorithms.
In summary, the 510(k) summary provided is a high-level overview establishing substantial equivalence. It lacks the detailed study information typically found in a clinical validation report, including specific acceptance criteria, sample sizes, expert qualifications, adjudication methods, and detailed performance metrics.
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