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HeartSee K171303 Software for cardiac positron emission tomography (PET) is indicated for determining regional and global absolute rest and stress myocardial perfusion in cc/min/g, Coronary Flow Reserve and their combination into the Coronary Flow Capacity (CFC) Map in patients with suspected or known coronary artery disease (CAD) in order to assist clinical interpretation of PET perfusion images by quantification of their severity.

HeartSee K171303 is intended for use by trained professionals, such as nuclear medicine or nuclear cardiology physicians, or cardiologists with appropriate training and certification. The clinician remains ultimately responsible for the final assessment and diagnosis based on standard practices, clinical judgment and interpretation of PET images or quantitative data.

HeartSee K171303 is a software tool for cardiac positron emission tomography (PET) for determining regional and global absolute rest and stress myocardial perfusion in cc/min/q, Coronary Flow Reserve and their combination into the Coronary Flow Capacity (CFC) Map for facilitating the interpretation of PET perfusion images in patients with suspected ot known coronary artery disease. HeartSee K171303 is intended for use by trained professionals, such as nuclear technicians, nuclear medicine or nuclear cardiology physicians, or cardiologists with appropriate training and certification.

HeartSee contains two fundamental components. First, the software imports cardiac PET images in DICOM format from PET scanners with DICOM output. These images are reoriented to cardiac axes to produce standard tomographic and topographic displays of relative uptake. Second, the K171303 software quantifies absolute rest and stress myocardial perfusion per unit tissue (cc/min/g), Coronary Flow Reserve (CFR) as the stress/rest perfusion ratio and the Coronary Flow Capacity combining CFR and stress perfusion, all on a pixel basis for regional and global values. Archiving output data is supported for clinical diagnostics, quality control and research.

Here's a breakdown of the requested information based on the provided document:

Acceptance Criteria and Device Performance Study

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by demonstrating that K171303 performs "identically" to the predicate device (K143664) for certain metrics and "better" for others.

2. Sample size used for the test set and the data provenance

• Sample Size: 4188 rest and 4188 stress PET perfusion scans.
• Data Provenance: The document does not specify the country of origin of the data. It also does not explicitly state if the data was retrospective or prospective. However, given that the study is comparing performance of two software versions on an existing dataset, it's highly likely to be retrospective analysis of previously acquired patient scans.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not specify the number of experts used to establish the ground truth or their qualifications. The study primarily focuses on the algorithmic output against its predicate and clinical association, rather than expert-derived ground truth for individual scan features.

4. Adjudication method for the test set

The document does not describe an adjudication method for the test set. The comparison is between the outputs of two software versions (K171303 and K143664) and their statistical association with clinical outcomes, not against a consensus-based ground truth adjudicated by experts.

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

A multi-reader multi-case (MRMC) comparative effectiveness study focused on human reader improvement with and without AI assistance was not done or reported in this summary. The study reported here is a direct comparison of two algorithmic software versions (K171303 vs. K143664) and their association with clinical outcomes.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, a standalone (algorithm-only) performance study was done. The entire summary describes the performance of the K171303 software in processing PET scans and generating quantitative values and maps, implicitly comparing it to the K143664 software, also in a standalone manner. The clinical associations are derived from these algorithmic outputs without explicitly evaluating human-in-the-loop performance.

7. The type of ground truth used

The ground truth used for performance evaluation appears to be:

• Algorithmic equivalence: For the quantitative measurements (perfusion, CFR), the ground truth for K171303's accuracy is its identical output to the predicate K143664.
• Outcomes data: For the clinical associations (MACE, reduced death and MI after revascularization), the ground truth is the actual patient outcomes.

8. The sample size for the training set

The document does not specify the sample size for the training set. It describes a "study" involving the analysis of 4188 rest and 4188 stress PET perfusion scans, which serves as the test set for comparison between K171303 and K143664. It is not clear if these scans were also part of a training set, or if an entirely separate training set was used for developing the software versions. Given the explanation of K171303 being "identical" in code to K143664 with the addition of the CFC map, it's plausible that the core algorithms were developed using separate data, and these 4188 scans validate the outputs and the new CFC map's utility.

9. How the ground truth for the training set was established

Since the document does not specify the training set sample size, it also does not detail how the ground truth for any training set was established.

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The cardiac position emission tomography (PET) analysis tool, HeartSee is a software package intended for use by nuclear medicine and nuclear cardiology physicians and technologists to facilitate image interpretation. Archiving of output data will be supported for clinical diagnostics, quality control, and research.

HeartSee is intended for processing of DICOM images, visual analysis and quantification of relative myocardial tracer uptake, and quantification of absolute myocardial blood flow and CFR when applied to diagnostic cardiac PET images in patients with suspected or known coronary artery disease.

The cardiac positron emission tomography (PET) analysis tool HeartSee is a software package intended for use by nuclear medicine and nuclear cardiology physicians and technologists to facilitate image interpretation. Archiving of output data will be supported for clinical diagnostics, quality control, and research.

HeartSee contains two fundamental components. First, the software can import cardiac PET images in DICOM format from any camera manufacturer. These images can be reoriented to cardiac axes to produce standard tomographic and topographic displays of relative uptake. A trained, licensed physician can interpret these processed images as per standard practice.

Second, the CFR software can quantify absolute myocardial blood flow per unit tissue (cc/min/gm) in stress and rest PET cardiac images and quantitatively assess the coronary flow reserve (CFR).

To compute coronary flow reserve (CFR) - the ratio of increased blood flow (stress) to baseline blood flow (rest) – three inputs are required: integrated arterial activity in the early part after bolus injection, average myocardial activity in the late part after bolus injection, and correction factors for partial volume effects of the PET scanner. The first number comes from a region of interest (ROI) drawn in the thoracic aorta or left atrium on images taken soon after radionuclide bolus administration. The second number comes from the topographic maps of myocardial uptake acquired later after radiotracer injection. The third number varies by PET camera and will be initialized in a user preference file.

HeartSee is a software package that uses standard, industrial computing hardware and applications.

This device is HeartSee, a cardiac PET analysis software.

Please note that the provided document is a 510(k) summary, which often provides less granular detail on study designs compared to full study reports or publications. Therefore, some information may not be explicitly available and will be noted as such.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly state formal acceptance criteria with numerical thresholds. Instead, it relies on demonstrating substantial equivalence to predicate devices (K090178 and K113754). This typically means the new device performs similarly well or not worse than the predicates.

However, the document mentions specific validation studies for its two main functionalities:

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

• Test Set Sample Size: 82 patients.
• Data Provenance: The document does not explicitly state the country of origin. It mentions data from patients with coronary artery disease and "cardiac PET images acquired at our institution." Given the contact information for K. Lance Gould, M.D. at the University of Texas Medical School at Houston, it is highly likely the data is from the USA.
• Retrospective or Prospective: The wording "MBF from 82 patients processed by the new algorithm was compared to MBF previously calculated by an independent algorithm" suggests that the data was retrospective, as the "previously calculated" values imply existing data.

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

The ground truth for the quantitative component (MBF and CFR) was established by an "independent algorithm" (presumably cfrQuant, predicate K113754), not directly by human experts in the sense of adjudication. Therefore, the concept of "number of experts" for establishing this specific ground truth isn't applicable in the traditional sense here.

For the visual interpretation component, the document states: "A trained, licensed physician can interpret these processed images as per standard practice." This implies standard clinical practice where a single (or multiple, depending on practice) trained, licensed physician would interpret the images. However, no specific number of experts or their qualifications for a formal ground truth establishment for this visual component are detailed in the 510(k) summary.

4. Adjudication Method for the Test Set

For the quantitative component (MBF and CFR), the adjudication method was a comparison against a "previously calculated" value from an "independent algorithm" (predicate K113754). This is a direct algorithmic comparison, not a human adjudication method like 2+1 or 3+1.

For the visual interpretation component, no specific adjudication method is described within the context of a validation study for the 510(k) submission.

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

No, an MRMC comparative effectiveness study involving human readers with and without AI assistance is not described in this 510(k) summary. The validation focused on the standalone performance of the algorithm and its correlation with a predicate algorithm.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, a standalone performance study was done for the quantitative components (MBF and CFR). The study directly compared the HeartSee algorithm's output for MBF and CFR to the output of an "independent algorithm" (the predicate device, cfrQuant). The correlations (r=0.99) demonstrate the standalone performance of the HeartSee algorithm.

7. The Type of Ground Truth Used

• For MBF and CFR Quantification: The ground truth was "previously calculated" values from an "independent algorithm" (the predicate device, cfrQuant). This can be classified as a form of algorithmic reference standard or established method comparison.
• For Visual Interpretation/Image Reorientation: The implied ground truth relies on standard clinical practice and expert interpretation, but a formal ground truth definition for a validation study is not detailed.

8. The Sample Size for the Training Set

The 510(k) summary does not provide information on the sample size used for the training set for the HeartSee device. This type of detail is often not included in 510(k) summaries.

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

The 510(k) summary does not provide information on how the ground truth for the training set was established, as it does not describe the training process or dataset.

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The cfrQuant coronary flow reserve (CFR) quantification software quantifies blood flow in the myocardial wall of the heart's left ventricle based on positron emission tomography (PET) images of radionuclide tracer distribution.

The product is intended for use by trained professionals, such as nuclear technicians and nuclear medicine or nuclear cardiology physicians. The clinician remains ultimately responsible for the final assessment and diagnosis based on standard practices and visual interpretation of all PET data.

The software accepts cardiac PET images of either N-13 ammonia or Rb-82 tracer uptake during two physiologic states: baseline (rest) and increased blood flow (stress). A mathematical model computes absolute myocardial perfusion (flow per mass of tissue, or cc/min/gm) at rest and stress. The ratio of stress-to-rest flow is termed the coronary flow reserve (CFR). Visual displays of absolute flow and CFR as well as their numeric quantification are presented to aid diagnostic interpretation of myocardial PET images.

The coronary flow reserve (CFR) quantification (cfrQuant) system is a software package intended for use by nuclear medicine and nuclear cardiology physicians and technologists to perform clinical quantitative analysis on cardiac positron emission tomography (PET) image data. Archiving of output data will be supported for clinical diagnostics, quality control, and research.

cfrQuant calculates absolute myocardial blood flow in cc/min/g using a twodimensional topographical map of PET tracer uptake and an integrated arterial input value. Absolute myocardial flow is calculated from a mathematical flow model validated using microspheres in animals (see Yoshida, Mullani and Gould in J Nuc Med 37:1701, 1996).

To compute CFR, three inputs are required: integrated arterial activity in the early part after bolus injection, average myocardial activity in the late part after bolus injection, and correction factors for partial volume effects of the PET scanner. The first number comes from a region of interest (ROI) drawn in the thoracic aorta or left atrium on images taken soon after radionuclide bolus administration. The second number comes from the topographic maps of myocardial uptake produced by the Positron CARDIAC software. The third number varies by PET camera and will be initialized in a user preference file.

Here's a breakdown of the acceptance criteria and study information for the cfrQuant device, based on the provided text. Unfortunately, the provided document is a 510(k) summary and FDA letter, which primarily focuses on regulatory approval and substantial equivalence to predicate devices, rather than detailed performance studies and acceptance criteria as one might find in a full clinical study report. Therefore, some information is not explicitly stated or is inferred.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly state quantitative acceptance criteria or a formal table of reported device performance metrics against those criteria. The device is cleared based on demonstrating substantial equivalence to predicate devices. The core "performance" is its ability to quantify absolute myocardial blood flow and coronary flow reserve (CFR) using established mathematical models.

However, the technology's validation is mentioned:

• Acceptance Criteria (Inferred from description): The software should accurately calculate absolute myocardial blood flow in cc/min/g and coronary flow reserve (CFR) based on PET tracer uptake and arterial input, using a mathematical flow model validated with microspheres.
• Reported Device Performance:
  • "cfrQuant calculates absolute myocardial blood flow in cc/min/g using a two-dimensional topographical map of PET tracer uptake and an integrated arterial input value."
  • "Absolute myocardial flow is calculated from a mathematical flow model validated using microspheres in animals (see Yoshida, Mullani and Gould in J Nuc Med 37:1701, 1996)."
  • "The ratio of stress-to-rest flow is termed the coronary flow reserve (CFR). Visual displays of absolute flow and CFR as well as their numeric quantification are presented to aid diagnostic interpretation of myocardial PET images."

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

The provided document does not specify a distinct "test set" sample size or data provenance (country, retrospective/prospective) for a performance validation study of cfrQuant itself.

The primary evidence referenced for the underlying mathematical model's validity is a publication: "Yoshida, Mullani and Gould in J Nuc Med 37:1701, 1996." This publication describes validation using microspheres in animals, not human test sets for the cfrQuant software.

For 510(k) submissions, the focus is often on demonstrating equivalency to existing cleared devices rather than extensive new clinical performance studies, especially for software that implements a known scientific model.

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

Given the lack of a specific "test set" described for cfrQuant's performance validation, this information is not applicable or not provided. The ground truth for the underlying mathematical model's validation was established in animals using microspheres, which is a direct physiological measurement, rather than human expert consensus.

4. Adjudication Method for the Test Set

Not applicable as no specific human-read test set and adjudication process are described for cfrQuant's performance validation.

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

No, the document does not mention an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated for cfrQuant.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is inherently an "algorithm only" tool for quantification. Its performance, as described, is the output of its calculations. The reference to the "mathematical flow model validated using microspheres in animals" (Yoshida, Mullani and Gould, 1996) serves as the standalone validation of the core algorithm's underlying principle.

The cfrQuant system is described as a "software package intended for use by nuclear medicine and nuclear cardiology physicians and technologists to perform clinical quantitative analysis." While physicians use the output, the calculation itself is standalone.

7. The Type of Ground Truth Used

For the underlying mathematical model that cfrQuant implements, the ground truth was microspheres in animals. This is a direct physiological measurement of blood flow, considered a gold standard in such preclinical studies.

8. The Sample Size for the Training Set

Not applicable or not provided. This device is based on a pre-established mathematical model, not a machine learning model that requires a "training set" in the conventional sense. The "training" of the model itself would have occurred during its initial development and validation, as referenced by the Yoshida et al. publication.

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

Not applicable in the typical machine learning sense. The ground truth for the validation of the mathematical model was established using microsphere injection in animals with subsequent direct physiological measurement of blood flow. This provides a direct, highly accurate "ground truth" for the flow calculations made by the model.

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