Search Results

The HealthCCSng device is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease.

The HealthCCSng device analyzes routine non-gated, non-contrast CT studies that include the entire heart of adult patients of age 30-85.

The device generates an exact calcium soore and a four coronary artery calcium detection category output representing the estimated quantity of calcium detected together with preview axial images of the detected calcium meant for informational purposes only.

The device output will be available to the radiologist as part of their standard workflow. A list of studies that received a successful algorithm analysis result will also be available for further clinician assessment (such as by a cardiologist, general practitioner etc.).

The HealthCCSng results are not intended to be used on a stand-alone basis for risk attribution, clinical decision-making or otherwise preclude clinical assessment of CT studies.

HealthCCSng product is a software device that automatically estimates the coronary artery calcium category from non-cardiac-gated adult CT scans. The product is aimed to leverage the high utilization of CT scans in the medical care environment (both inpatient and outpatient), including lung cancer screening programs, in order to automatically detect calcification in the coronary arteries of patients in an opportunistic manner.

The HealthCCSng product analyzes cases using an artificial intelligence algorithm for the automated detection and estimation of coronary calcium and outputs a result for review by the clinician. The device works in parallel to and in conjunction with the standard of care workflow. The final diagnosis is made by the clinician after reviewing the scan independently of the software. The device is intended for use by the clinicians as a non-diagnostic analysis software in conjunction with additional patient information and professional judgment.

HealthCCSng receives a non-gated, non-contrast CT study from the storage application, Nanox AI's Imaging Analytics Platform (IMA)/ other platforms. For each CT study received, the software shall validate at least one compliant series in which the entire heart is present and performs an analysis. For each complaint study, the software shall output:

1. Estimated Coronary Calcium Detection, based on the measurement of calcium deposits in the coronary arteries.
2. A corresponding Estimated Coronary Calcium Detection Category, based on the Estimated Coronary Calcium measurements.

The software output will include the following calcium categories:

= 400 | High

For patients in which calcium was detected, the user will be presented with representative key images - all the slices containing the measured coronary calcifications (130 HU and above). On these images, the calcified areas will be annotated.

The following modules compose the HealthCCSng software:

1. Data input and validation: DICOM validation receives imaging study from hosting application and the validation feature assessed the input data (i.e. age, modality, view, etc.) to ensure compatibility for processing by the algorithm.
2. HealthCCSng algorithm: Once a study has been validated, the algorithm analyzes the CT for analysis and quantification.
3. IMA Integration feature: The results of a successful study analysis are provided to the hosting application.
4. Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

The product operates in the following manner:

1. A CT scan is sent to the Image Analytics Platform (IMA).
2. The Image Analytics Platform (IMA) forwards the scan to the HealthCCSng algorithm for analysis.
3. The scan is analyzed, with the following possible results sent back to IMA:
   a. Non-compliant: the scan is not compliant with the input criteria of the product and is therefore not analyzed.
   b. Success -
4. Success A Zero calcium, Low, Medium or High Coronary Calcium Detection has been identified.
5. Success No Category Cause: metal artifact(s) suggestive of known cardiac disease is suspected.
   c. Failure: the scan has been analyzed. An error prevented the device from completing the analysis and therefore there is no output available.

In all cases of success. HealthCCSng will provide key images of visualization of the detected coronary calcium (except for zero category), the category name and the exact score.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

Additional Performance Metric:

• Pearson's Correlation Coefficient (GT vs. HealthCCSng scores): 0.959 (95% CI: [0.9499, 0.9655], p

Ask a specific question about this device

The HealthCCSng device is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. The software generates an estimated coronary artery calcium detection category.

The HealthCCSng device analyzes existing non-cardiac-gated CT studies that include the heart of adult patients above the age of 30. The device generates a three-category output representing the estimated quantity of calcium detected together with preview axial images of the detected calcium meant for informational purposes only. The device output will be available to the radiologist as part of their standard workflow. The HealthCCSng results are not intended to be used on a stand-alone basis for risk attribution, clinical decision-making or otherwise preclude clinical assessment of CT studies.

HealthCCSng product is a software device that automatically estimates the coronary arterv calcium category from non-cardiac-gated adult CT scans. The product is aimed to leverage the high utilization of CT scans in the medical care environment (both inpatient and outpatient), including lung cancer screening programs, in order to automatically detect calcification in the coronary arteries of patients in an opportunistic manner.

Zebra's HealthCCSng product analyzes cases using an artificial intelligence algorithm for the automated detection and estimation of coronary calcium and outputs a result for review by the radiologist. The device works in parallel to and in conjunction with the standard of care workflow. The final diagnosis is made by the radiologist after reviewing the scan independently of the software. The device is intended for use by the radiologists as a non-diagnostic analysis software in conjunction with additional patient information and professional judgment.

HealthCCSng receives a non-cardiac-gated CT study from the storage application, Zebra's Imaging Analytics Platform (IMA). For each CT study received, the software shall validate there is at least one compliant series in which the entire heart is present, and perform an analysis. For each compliant study, the software shall output:

1.Estimated Coronary Calcium Detection, based on the measurement of calcium deposits in the coronary arteries.
2. A corresponding Estimated Coronary Calcium Detection Category, based on the Estimated Coronary Calcium measurement.

The software output will include the following calcium categories:

| Estimated Coronary Calcium
Detection | Corresponding Estimated Coronary Calcium
Detection Category |
|-----------------------------------------|----------------------------------------------------------------|
| 0-99 | Low |
| 100-399 | Medium |
| ≥400 | High |

For patients in which calcium was detected, the user will be presented with representative images - all the slices containing the measured coronary calcifications (130 HU and above). On these images, the calcified areas will be annotated (with an option for the user to toggle on and off the annotation).

The following modules compose the HealthCCSng software:

Data input and validation: Following retrieval of a study, the validation feature assessed the input data (i.e. age, modality, view, etc.) to ensure compatibility for processing by the algorithm.

HealthCCSng algorithm: Once a study has been validated, the algorithm analyzes the CT for analysis and quantification.

IMA Integration feature: The study analysis and the results of a successful study analysis is provided to IMA.

Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for HealthCCSng:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: 447 anonymized CT chest cases.
• Data Provenance: Retrospective study from two healthcare institutions, composed of multiple clinical sites. The specific country of origin is not mentioned.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Number of Experts: Three radiologists.
• Qualifications: The document does not specify the qualifications (e.g., years of experience, subspecialty) of these radiologists.

4. Adjudication Method for the Test Set

• Adjudication Method: "Majority agreement of two of three radiologists" was used to determine the ground truth category. This is a 2-out-of-3 majority consensus method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? The document describes a standalone performance study comparing the device's output to ground truth. It does not mention a comparative effectiveness study involving human readers with and without AI assistance to measure an effect size.

6. Standalone (Algorithm Only) Performance

• Was a standalone study done? Yes, the document explicitly states: "The HealthCCSng software device performance was validated in a stand-alone retrospective study for its overall agreement compared to the established ground truth..."

7. Type of Ground Truth Used

• Type of Ground Truth: Expert consensus. Specifically, the "ground truth category was determined by the majority agreement of two of three radiologists."

8. Sample Size for the Training Set

• The document does not specify the sample size for the training set. It only details the validation (test) set.

9. How the Ground Truth for the Training Set Was Established

• The document does not specify how the ground truth for the training set was established. It only describes the ground truth establishment for the validation (test) set. It's common for training data ground truth to be established through expert annotations, but the method is not stated here.

Ask a specific question about this device

The HealthCCS Device is intended for use as a non-invasive post-processing software that can be used to evaluate calcified plaques in the coronary arteries, which may be a risk factor for coronary artery disease. The software can be used to generate reports of the total risk category of coronary calcium. This information can then be used by a physician for further analysis and treatment. The HealthCCS Device analyses pre-existing heart or chest ECG-Gated Triggered CT scans. The Device is indicated for use only on patients whose age at the CT scan was taken, was above 20 years old. This device generates a 4-category Agatston-equivalent risk score, and the patient management, especially for the patient with the score from 0-10, will depend on the physician's own judgment. It may require further testing to evaluate the appropriate clinical management.

The HealthCCS Device is an automatic non-invasive post processing tool that uses cardiac CT images to identify and quantify calcification in the coronary arteries, known to be a risk factor for coronary disease. HealthCCS Device quantifies calcification on non-contrast cardiac computed tomography (CT) scans. HealthCCS Device calculates the amount of identified calcification and reports the risk category of coronary calcium. This information can then be used by a physician for further analysis and treatment.

The provided document describes the HealthCCS device, a non-invasive post-processing software for evaluating calcified plaques in coronary arteries. Here's a breakdown of the acceptance criteria and the study that proves the device meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The document explicitly states the overall acceptance criterion as "adequate overall agreement" and "adequate agreement per category." It then reports the achieved performance against these criteria.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: 249 studies.
• Data Provenance: The document states a "retrospective performance study." No specific country of origin is mentioned for the data, but the applicant's address is Israel.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

• Number of Experts: 3 radiologists.
• Qualifications of Experts: Not specified in the document beyond "radiologists." No information on their years of experience or subspecialty focus is provided.

4. Adjudication Method for the Test Set

The ground truth was established by "3 radiologists using the Kodak Carestream PACS device (K053347)." This implies a consensus or majority rule approach, but the specific adjudication method (e.g., 2+1, 3+1) is not explicitly stated. It seems to be a form of expert consensus derived from their use of a reference device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

• A formal MRMC comparative effectiveness study comparing human readers with and without AI assistance was not described. The study described focused on the agreement between the HealthCCS device's categorization and the ground truth established by radiologists using a reference PACS device. It was a comparison of the AI's output against human-derived ground truth, not an assessment of human performance improvement with AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Yes, the performance study described is essentially a standalone (algorithm only) performance study. The HealthCCS device's output (4-level risk categorization) was directly compared to the ground truth established by the radiologists. There was no human-in-the-loop component described for this performance evaluation.

7. The Type of Ground Truth Used

• Expert Consensus (using a reference device): The ground truth was established by "3 radiologists using the Kodak Carestream PACS device (K053347)." This indicates that the radiologists performed the calcification scoring using a legally marketed device, and their determinations served as the "ground truth" for comparison.

8. The Sample Size for the Training Set

• The document does not specify the sample size used for the training set. It only details the performance validation study (test set).

9. How the Ground Truth for the Training Set Was Established

• The document does not provide information on how the ground truth for the training set was established. The focus is solely on the validation of the device's performance using a test set. However, a CNN-based probability threshold is mentioned, implying that the model was trained on data with ground truth about what constitutes coronary arterial calcification.

Ask a specific question about this device