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CAAS Workstation features segmentation of cardiovascular structures, 3D reconstruction of vessel segments and catheter path based on multiple angiographic images, measurement and reporting tools to facilitate the following use:

• Calculate the dimensions of cardiovascular structures;
• Quantify stenosis in coronary vessels;
• Determine C-arm position for optimal imaging of cardiovascular structures;
• Quantify pressure drop in coronary vessels;
• Enhance stent visualization and measure stent dimensions;
  CAAS Workstation is intended to be used by or under supervision of a cardiologist.

CAAS Workstation is an image post-processing software package for advanced visualization and ysis in the field of cardiology or radiology and offers functionality to view X-Ray angiographic images, to segment cardiovascular structures in these images, to analyze and quantify these cardiovascular structures and to present the results in different formats.
CAAS Workstation is a client-server solution intended for usage in a network environment or standalone usage and runs on a PC with a Windows operating system. It can read DICOM X-ray images from a directory, or receive DICOM images from the X-ray or PACS system.
CAAS Workstation is composed out of the following analysis workflows: StentEnhancer and vFFR for calculating dimensions of coronary vessels, quantification of stenosis and calculating the pressure drop and vFFR value based on two 2D X-Ray angiographic images. Semi-automatic contour detection forms the basis for the analyses.
Results can be displayed on the screen, printed or saved in a variety of formats to hard disk, network, PACS system or CD. Results and clinical images with overlay can also be printed as a hardcopy and exported in various electronic formats. The functionality is independent of the type of vendor acquisition equipment.

The provided text describes a 510(k) premarket notification for the CAAS Workstation, a software package for advanced visualization and analysis in cardiology and radiology. However, it does not contain specific details about acceptance criteria or a study proving the device meets those criteria with quantitative performance metrics for AI/ML components.

The document states: "Performance testing demonstrated that the numerical results for the analysis workflows StentEnhancer and vFFR, as already available in predicate device K180019, were comparable." This is a qualitative statement of comparability to a predicate device, not a detailed presentation of acceptance criteria and the results of a study designed to meet them.

Therefore, I cannot fulfill all parts of your request with the provided input. I will outline what can be extracted and note what information is missing.

Summary of Device and Approval:

• Device Name: CAAS Workstation
• Applicant: Pie Medical Imaging B.V.
• FDA K-Number: K232147
• Regulation Name: Angiographic X-Ray System
• Regulatory Class: Class II
• Product Codes: QHA, LLZ
• Predicate Device: CAAS Workstation (K180019) – an earlier version of the same product.
• Basis for Clearance: Substantial Equivalence to the predicate device.

Indications for Use (Key Features):
CAAS Workstation features segmentation of cardiovascular structures, 3D reconstruction of vessel segments and catheter path based on multiple angiographic images, measurement and reporting tools to facilitate the following use:

• Calculate the dimensions of cardiovascular structures;
• Quantify stenosis in coronary vessels;
• Determine C-arm position for optimal imaging of cardiovascular structures;
• Quantify pressure drop in coronary vessels;
• Enhance stent visualization and measure stent dimensions;

Missing Information:

The provided text focuses on the regulatory clearance process through 510(k) substantial equivalence. This pathway often relies on demonstrating that a new device is as safe and effective as a legally marketed predicate device, rather than requiring extensive de novo clinical performance studies with specific acceptance criteria as you've requested for an AI/ML component. The document mentions "Performance testing," but it does not provide the details required to answer your specific questions about acceptance criteria, study design, sample sizes, ground truth establishment, or expert involvement for a new AI/ML model's performance.

The "AI" mentioned appears to refer more to automated image processing algorithms (semi-automatic contour detection, vFFR workflow involving pressure drop quantification, StentEnhancer workflow) rather than a novel, deep learning-based AI/ML algorithm that would typically necessitate the detailed performance study described in your prompt. The emphasis is on comparability of "numerical results" to the predicate, implying validation of existing algorithms, possibly with minor improvements, not a new AI/ML model with distinct performance criteria.

Based on the provided text, here's what can be inferred or explicitly stated, and what remains unknown:

1. A table of acceptance criteria and the reported device performance:

• Acceptance Criteria: Not explicitly stated in quantitative terms in the provided text. The document broadly indicates that "numerical results for the analysis workflows StentEnhancer and vFFR...were comparable" to the predicate. This implies the acceptance criterion was "comparability" to the predicate's performance, but no specific thresholds (e.g., accuracy > X%, ROC AUC > Y) are given.
• Reported Device Performance: No quantitative performance metrics (e.g., sensitivity, specificity, accuracy, precision, recall) are provided in the text. The statement is qualitative: "numerical results...were comparable."

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

• Sample Size: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions reading DICOM X-ray images, but not the source of the test data.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The device is intended for use by or under the supervision of a cardiologist, suggesting expert cardiac imaging knowledge would be relevant, but details about ground truth establishment are absent.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

• Not specified.

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:

• Not described. The focus is on the device's standalone performance compared to a predicate, not on a human-in-the-loop MRMC study.

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

• Yes, implicitly. The "Performance testing demonstrated that the numerical results for the analysis workflows StentEnhancer and vFFR...were comparable" indicates an evaluation of the algorithm's output. This is consistent with a standalone performance assessment, as the comparison is about the output of the software itself.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Not explicitly stated. Given the functionalities (quantifying stenosis, dimensions, pressure drop), the ground truth for these "numerical results" would likely involve comparison against a gold standard derived from established imaging methods, potentially quantitative measurements from calibrated imaging devices, or expert consensus measurements, but the document does not elaborate.

8. The sample size for the training set:

• Not specified. The document mentions "semi-automatic contour detection forms the basis for the analyses" for the vFFR workflow, which could imply a training process, but no details are given.

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

• Not specified.

In conclusion, the K232147 FDA clearance document for the CAAS Workstation confirms its regulatory pathway via substantial equivalence to a predicate device. While it mentions "Performance testing" and "comparable numerical results," it does not provide the detailed quantitative acceptance criteria, study methodology, or specific performance metrics that would typically be found in an in-depth clinical validation study for a novel AI/ML device. The information provided is sufficient for a 510(k) submission based on predicate equivalence but lacks the granularity for the specific technical and clinical performance questions asked.

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Standalone software for medical image analysis intended for advanced visualization and quantitative analysis for diagnostic in the field of cardiology by means of segmentation of cardiovascular structures and enabling the analysis of blood flow in the heart and large vessels based on multi-slice, multi-phase and velocity encoded MR images as well as measurement and reporting tools by providing the following functionality:

• Segmentation of cardiovascular structures and calculation of quantitative results ●
• Support signal intensity analysis for the myocardium
• . Quantification of MR parametric maps (such as T1, T2, T2* relaxation)
• Visualization and quantification of blood flow velocity and directions

When the results provided by CAAS MR Solutions are used in a clinical setting to support diagnoses, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS MR Solutions is an image post-processing software package which offers functionality to import DICOM MR images, to segment cardiovascular structures in these images, to visualize and evaluate blood flow in cardiovascular structures, to analyze and quantify these cardiovascular structures and to present the analysis results in different formats.

CAAS MR Solutions is designed as a stand-alone software package to run on a PC with a Windows operating system. It can read DICOM MR images from an accessible file system, hard disk (local directory), or (indirectly) received from the MR or PACS system. CAAS MR Solutions provides the functionality to import the DICOM MR images and to organize the loaded DICOM MR images into patients, studies, and series.

CAAS MR Solutions comprises functionalities for viewing and quantification of cardiovascular MR images, segmentation of cardiovascular structures and calculation of quantitative results, for signal intensity analysis of the myocardium, for quantification of MR parametric maps and for visualization of blood flow velocity and directions.

Results can be displayed on the screen, printed, or saved in a variety of formats to hard disk, network or PACS system. Results and clinical images with overlay can also be printed as a hardcopy and exported in various electronic formats.

The provided text is a 510(k) summary for the device CAAS MR Solutions. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed performance study results with specific acceptance criteria and outcome metrics.

Therefore, I cannot provide the requested information regarding acceptance criteria and performance study details (e.g., sample size, data provenance, expert qualifications, adjudication methods, MRMC study results, standalone performance, ground truth type, training set details) from the provided text.

The document states:

• "The verification and validation of the new strain analysis workflow demonstrated that the results meet the accuracy and reproducibility requirements."
• "Equivalence in numerical results for the analysis workflows already available in the predicate device CAAS MR Solutions (K181825) was demonstrated with regression testing."

However, it does not specify what those accuracy and reproducibility requirements are (i.e., the acceptance criteria), nor does it provide the reported device performance against those criteria in a quantitative manner. Details about the studies (e.g., sample size, ground truth establishment) are also absent.

To answer your request, a detailed performance study report would be needed, which is not part of this 510(k) summary.

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Standalone software for medical intended for advanced visualization and quantitative analysis in adult populations to support physicians with diagnostics by means of enabling segmentation, quantification, review, and reporting of cardiac structures based on multi-dimensional echocardiographic images. Caas Qardia facilitates the following use:

· Segmentation of cardiovascular structures

· Calculation of quantitative indices describing cardiovascular function and structure

When the results provided by Caas Qardia are used in a clinical decision making, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

Caas Qardia is an image post-processing software package for diagraphy, which offers functionality to view echocardiographic images, to segment cardiovascular structures in these images, to analyze and quantify these cardiovascular structures and to present the analysis results in different formats.

Caas Qardia is a web-based solution for diagnostic echocardiography, intended for usage in a network environment or standalone usage. Caas Qardia is composed of the following key analysis features:

• -Study selection (from PACS server or local data)
• -Image viewing
• -Left ventricular ejection fraction analysis
• -Left ventricular strain analysis
• -Cardiac geometric measurements and velocity measurements
• -Reporting
• -Export of results

Results can be displayed on the screen, printed, or saved in a variety of formats to hard disk, network, PACS system or CD. Results and clinical images with overlay can also be printed as a hardcopy and exported in various electronic formats.

Here's a summary of the acceptance criteria and study details for the Caas Qardia device:

Caas Qardia Acceptance Criteria and Performance Study

• The document states these criteria were met for all values.

Here's the additional information about the study:

• Sample size used for the test set and the data provenance: The document does not explicitly state the sample size for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It mentions "clinical images" and "clinical datasets."

• 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 or their qualifications for establishing ground truth. It refers to "manually annotated ED and ES contours" as the comparison for volume and EF, implying expert annotation.

• Adjudication method (e.g., 2+1, 3+1, none) for the test set: The adjudication method is not mentioned.

• 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 MRMC comparative effectiveness study involving human readers with and without AI assistance is described in this document. The performance testing focused on the device's accuracy against manual annotations and predicate device, and inter/intra-observer variability.

• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Yes, the performance testing described for ED/ES volume, EF, and GLS against manually annotated contours, and the comparison with the predicate device, represents standalone (algorithm only) performance.

• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The ground truth for ED and ES volume and EF determination was based on manually annotated ED and ES contours. For Global Longitudinal Strain, it was evaluated by comparing results against the predicate device.

• The sample size for the training set: The document does not specify the sample size for the training set.

• How the ground truth for the training set was established: The document does not provide details on how the ground truth for the training set was established.

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CAAS MR Solutions is a modular software product intended to be used by or under supervision of a cardiologist or radiologist in order to aid in reading and interpreting cardiovascular MR images and to visualize and evaluate blood flow in cardiovascular structures to support clinical decision making.

CAAS MR Solutions features segmentation of cardiovascular structures, enables the analysis of blood flow in the heart and large vessels based on multi-slice, multi-phase and velocity encoded MR images as well as measurement and reporting tools by providing the following functionality:

• Segmentation of cardiovascular structures and calculation of quantitative results
• Support signal intensity analysis for the myocardium ●
• Quantification of MR parametric maps (such as T1, T2, T2* relaxation)
• Visualization and quantification of blood flow velocity and directions

When the results provided by CAAS MR Solutions are used in a clinical setting to support diagnoses, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS MR Solutions is an image post-processing software package which offers functionality to import DICOM MR images, to segment cardiovascular structures in these images, to visualize and evaluate blood flow in cardiovascular structures, to analyze and quantify these cardiovascular structures and to present the analysis results in different formats.

CAAS MR Solutions is designed as a stand-alone software package to run on a PC with a Windows operating system. It can read DICOM MR images from an accessible file system, hard disk (local directory), or (indirectly) received from the MR or PACS system. CAAS MR Solutions provides the functionality to import the DICOM MR images and to organize the found DICOM MR images into patients, studies and series.

CAAS MR Solutions is composed out of analysis workflows of its previously cleared devices: CAAS MRV, CAAS MR Flow and CAAS MR 4D Flow. CAAS MR Solutions comprises their respective functionalities for viewing and quantification of cardiovascular MR images. In addition, CAAS MR Solutions offers new functionality for signal intensity analysis of the myocardium and for MR parametric maps for T1 relaxation. The CAAS MR Solutions product has a moderate level of concern.

Results can be displayed on the screen, printed or saved in a variety of formats to hard disk, network, PACS system or CD. Results and clinical images with overlay can also be printed as a hardcopy and exported in various electronic formats.

Pie Medical Imaging B.V.'s CAAS MR Solutions is a software package for post-processing medical images. This 510(k) summary provides details about its acceptance criteria and the studies conducted to demonstrate its performance.

1. Table of Acceptance Criteria and Reported Device Performance

The FDA summary does not provide a specific table of acceptance criteria with numerical targets. Instead, it states that the device was validated to meet "accuracy and reproducibility requirements" for new functionalities and that "equivalence in numerical results" was demonstrated for existing functionalities.

Therefore, the table below reflects what can be inferred from the provided text, focusing on the categorical nature of the reported performance rather than specific numerical metrics.

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

The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "validation" and "testing" without providing specific dataset details.

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

The document does not specify the number of experts used to establish ground truth for the test set or their qualifications.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method used for the test set.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it provide any effect size related to human reader improvement with or without AI assistance. The focus of this submission is on demonstrating substantial equivalence to predicate devices and meeting internal specifications, not on comparative effectiveness with human readers.

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

The document indicates that the device has standalone functionalities. For example, it states "The validation of the new functionalities for signal intensity analysis workflow and the T1 mapping quantification demonstrated that the results meet the accuracy and reproducibility requirements." This implies that the algorithm's performance on these specific tasks was assessed independently. However, the overall intended use is for aiding a cardiologist or radiologist, implying a human-in-the-loop context for clinical decision-making.

7. The Type of Ground Truth Used

The document does not explicitly state the specific type of "ground truth" used for validation. However, considering the nature of the device (segmentation, quantification of parameters like T1, T2, T2* relaxation, blood flow), it is highly probable that the ground truth for new functionalities would involve:

• Reference standard measurements: Comparison against established reference methods or expert manual measurements for parameters like T1 mapping and signal intensity analysis.
• Clinical consensus: For segmentation tasks, expert consensus on manual or semi-manual delineations would likely serve as a ground truth.

For the functionalities already available in predicate devices, the "equivalence in numerical results" implies comparison against outputs from those already validated predicate devices rather than a direct independent ground truth assessment.

8. The Sample Size for the Training Set

The document does not specify the sample size for the training 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. Given that the device incorporates functionalities from previously cleared devices (CAAS MRV, CAAS MR Flow, CAAS MR 4D Flow), it's possible that some methodologies for establishing ground truth for training data were inherited or adapted from those previous developments. However, this is not detailed in the provided text.

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CAAS Workstation is a modular software product intended to be used by or under supervision of a cardiologist or radiologist in order to aid in reading, co-registering and interpreting cardiovascular X-Ray images to support diagnoses and for assistance during intervention of cardiovascular conditions.

CAAS Workstation features segmentation of cardiovascular structures, 3D reconstruction of vessel segments and catheter path based on multiple angiographic images, measurement and reporting tools to facilitate the following use:

• Calculate the dimensions of cardiovascular structures;
• Quantify stenosis in coronary and peripheral vessels;
• Quantify the motion of the left and right ventricular wall;
• Perform density measurements;
• Determine C-arm position for optimal imaging of cardiovascular structures;
• Enhance stent visualization and measure stent dimensions;
• Quantify pressure drop in coronary vessels;
• Co-registration of angiographic X-Ray images with IVUS and OCT images.
  CAAS Workstation is intended to be used by or under supervision of a cardiologist or radiologist.

The CAAS Workstation is designed as a stand-alone software package to run on a PC with a Windows operating system. It can read DICOM X-ray images from an directory, or received from the X-ray or PACS system. Intravascular images (such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT) in DICOM format can be read from a directory, or received from the intravascular imaging console or PACS system. IVUS images can also be received realtime as a video stream from an intravascular imaging console via a DVI streamer. The CAAS Workstation product has a moderate level of concern.

CAAS Workstation is composed out of the following analysis workflows: QCA, QCA3D, QVA, LVA, RVA, StentEnhancer and IV-LINQ of the previously cleared predicate device CAAS Workstation (K151780) for calculating dimensions of coronary and peripheral vessels and the left and right ventricles, quantification of stenosis, performing density measurements, determination of optimal C-arm position for imaging of vessel segments and functionality to enhance the visualization of a stent and to measure stent dimension. Semi-automatic contour detection forms the basis for the analyses. Functionality to co-register X-ray angiographic imaging techniques (such as IVUS and OCT) is added by means of the analysis module IV-LINQ.

In the newly added vFFR workflow the user can calculate the pressure drop and a vFFR value on coronary vessels. To obtain these values for a specific lesion in a coronary vessel, the user has to start with a QCA3D detection using two angiographic images. In each of these images a classic 2D coronary detection is performed after which a reconstruction of the coronary segment is obtained in 3D space. Based on the 3D reconstruction and the user input of systolic and diastolic aortic root blood pressure drop and the vFFR values can be assessed. The functionality is based on a combination of the QCA3D workflow available in predicate device CAAS Workstation (K151780) and technology available in the predicate device CAAS (K052988).

Results can be displayed on the screen, printed or saved in a variety of formats to hard disk, network, PACS system or CD. Results and clinical images with overlay can also be printed as a hardcopy and exported in various electronic formats. The functionality is independent of the type of vendor acquisition equipment.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in a quantitative table format for the new "quantification of pressure drop in coronary vessels" functionality. Instead, it describes a validation approach and comparative analysis.

However, based on the performance data section, we can infer the acceptance criteria for the new "quantification of pressure drop in coronary vessels" module were related to agreement with known pressure drops and improvement compared to the predicate device K052988.

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

• Test set for existing functions (regression testing): Not explicitly stated, but it's implied that a comprehensive set of test cases was used for regression testing to demonstrate equivalence.
• Test set for "quantification of pressure drop in coronary vessels": A "series of X-ray angiographic datasets with known pressure drops" was used. The exact number of datasets is not specified.
• Data Provenance: Not explicitly stated, but the mention of "known pressure drops" suggests these were either simulated datasets or pre-adjudicated clinical cases where pressure drops were definitively measured (e.g., using a reference standard). The document does not specify country of origin or whether it was retrospective or prospective.

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

• For existing functions: Not stated, as regression testing was used to compare against the previous version of the software.
• For "quantification of pressure drop in coronary vessels": The ground truth was based on "known pressure drops." The document does not specify if experts were involved in establishing these "known pressure drops" or what their qualifications would be. It's possible these were derived from a separate reference standard (e.g., invasive pressure wire measurements) or simulated data.

4. Adjudication Method

• For existing functions: Not applicable, as regression testing compared against the predicate device's output.
• For "quantification of pressure drop in coronary vessels": Not applicable, as the comparison was against "known pressure drops" rather than expert consensus on unknown cases.

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

• No, the document does not describe an MRMC comparative effectiveness study involving human readers with and without AI assistance. The performance evaluation focused on the standalone algorithm's accuracy and comparison to a previous device version.

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

• Yes, the performance evaluation for the "quantification of pressure drop in coronary vessels" was a standalone evaluation of the algorithm. The device calculated pressure drops, which were then compared to "known pressure drops."

7. The Type of Ground Truth Used

• For existing functions: The ground truth for regression testing would be the output of the predicate device (K151780).
• For "quantification of pressure drop in coronary vessels": The ground truth was "known pressure drops." As mentioned, this could refer to measurements from a highly accurate reference standard (e.g., invasive physiological measurements) or carefully constructed simulated data. It does not explicitly state "expert consensus," "pathology," or "outcomes data."

8. The Sample Size for the Training Set

• The document does not explicitly state the sample size used for the training set. The description in the "Performance Data" section refers to validation and verification, implying a test set, rather than a training set for model development. The device is described as an "Angiographic X-ray system," implying traditional software rather than a deep learning AI, though modern software often incorporates machine learning components that require training. Given the context, the "known pressure drops" dataset mentioned is very likely the test set used for validation.

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

• Since a training set size is not provided, the method for establishing its ground truth is also not elaborated upon in the provided text. If the device uses machine learning, information on its training set and ground truth establishment would typically be found in a more detailed technical report.

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CAAS MR 4D Flow is a software product intended to be used by or under supervision of a cardiologist or radiologist in order to visualize and evaluate blood flow in cardiovascular structures based on multi-slice, multi-phase and velocity encoded MR images to support clinical decision making.

CAAS MR 4D Flow enables the analysis of blood flow in the heart and large vessels based on multi-slice, multi-phase and velocity encoded MR images by providing the following functionality:
Segmentation of cardiovascular structures;
Visualization of blood flow velocity and directions;
Calculation of quantitative cardiovascular results.
When the results provided by CAAS MR 4D Flow are used in a clinical setting to support diagnoses, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS MR 4D Flow offers functionality to import images; to analyze the behavior of blood flow in vessels and through heart valves in phase-contrast MR (Flow) images semi-automaticative flow analysis on the images, and to present the analysis results in different formats.
The CAAS MR 4D Flow software is designed as a stand-alone software package to run on a PC with a Windows operating system. It can read DICOM MR Images from an accessible file system (CD) and CAAS MR 4D Flow provides the functionality to scan the contents of a specific directory and to organize the found DICOM MR images into patients, studies and logical imagesets.
A phase-contrast MR imageset is necessary for performing 4D Flow analysis. Depending on the specific analysis goals, one or more MR imagesets may be added for reference purposes (phase contrast or cine imagesets).
After the MR images are read, the CAAS MR 4D Flow software provides functionality to perform the following measurements:

• . Extraction (and, if wanted, manual editing) of a 3D mesh of the vessel lumen, based on user input points.
• Visualization of color-coded 3D blood motion vectors originating from one or more user-defined planes in the cardiovascular structure.
• Visualization of color-coded (fixed) streamlines and (animated) pathlines indicating blood movement pattern originating from one or more user-defined planes in the cardiovascular structure.
• Visualization and quantification of blood flow through a pre-defined plane.
  Methods to automatically correct for image artifacts or user errors like aliasing, eddy-currents, movement offset, or incorrect velocity direction indication, are available.
  The results of the analysis will be generated as visual snapshots or animation of 3D blood motion (see above) or quantifications, for example:
• Flow through a plane over time (forward, backward, total)
• Min, max, mean, average, sdev velocity through a plane over time
• Pulse wave velocity over a segment of the vessel
  Results can be displayed in numerical format or (if applicable) as graphs. An analysis can be saved to hard disk to enable re-analysis of the data. Visual results can be exported as animation or bitmap images. A graphic report can be exported in DICOM or PDF format, containing both numerical and also be printed. Numerical results can be exported as text files.

The provided text is a 510(k) summary for the CAAS MR 4D Flow device. It outlines the device's intended use, indications for use, and a comparison to a predicate device (Morpheus HeartScan, K133937) to demonstrate substantial equivalence. However, it does not contain a detailed study report with specific acceptance criteria and performance data for the CAAS MR 4D Flow device itself, nor does it describe sample sizes, ground truth establishment, or human reader effectiveness studies.

Instead, the document states: "Verification and validation of the CAAS MR 4D Flow functionality showed that the system requirements – derived from the intended use and indications for use – as well as risk control measures were implemented correctly and that the device meets its specifications including conformance to the following standards: ISO 14971:2007, Medical devices Application of risk management to medical devices; NEMA PS 3.1 3.20 (2011), Digital Imaging and Communication in Medicine (DICOM); IEC 62304 First edition 2006-05, Medical device software Software life cycle processes; IEC 62336:2007, Medical devices Application of usability engineering to medical devices. The verification and validation results demonstrate the safety and effectiveness of CAAS MR 4D Flow in relation to its intended use and therefore CAAS MR 4D Flow can be considered as safe and effective as its predicate device."

This statement indicates that performance testing was conducted to meet system requirements and relevant standards, but the specifics of those tests, including quantitative acceptance criteria and reported device performance metrics, are not included in this summary. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a standalone performance study.

Therefore, I cannot populate the requested table and answer many of the specific questions about acceptance criteria and study details based solely on the provided text. The information is simply not present here.

Based on the provided text, here's what can be inferred and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Not specified in the document. The document states "Verification and validation of the CAAS MR 4D Flow functionality showed that the system requirements... were implemented correctly and that the device meets its specifications," but no details about the data used for this testing are provided.

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

• Not specified in the document.

4. Adjudication method for the test set:

• Not specified in the document.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:

• Not specified in the document. The document does not describe any human-in-the-loop studies or comparative effectiveness studies involving human readers.

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

• The nature of the "Verification and validation" mentioned suggests standalone testing of the software's functionality, but no specific performance results (e.g., accuracy, precision) are provided. The focus is on meeting system requirements and standards, not on clinical performance metrics typically associated with standalone algorithms like diagnostic accuracy.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Not specified in the document.

8. The sample size for the training set:

• Not applicable / not specified. The document describes a software product for analysis and visualization, implying it might be rule-based or model-based, but does not explicitly mention a "training set" in the context of machine learning. If it does use machine learning components (e.g., for segmentation), details about training data are not provided.

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

• Not applicable / not specified. (See point 8)

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CAAS MRV features segmentation of cardiovascular structures on different types of MR images as well as measurement and reporting tools to facilitate the following use:

· Quantitative functional and regional analyses of the heart ventricles

· Quantification of T2 and T2* relaxation values
CAAS MRV is intended to be used by or under supervision of a cardiologist. When the results provided by CAAS MRV are used in a clinical setting to support diagnosis of cardiovascular conditions, the results assurts of critic to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS MRV is designed as a stand-alone modular software package for viewing and quantification of cardiovascular MR images intended to run on a PC with a Windows operating system. The images for analysis can be read from CD, hard disk or from a PACS system and CAAS MRV provides the functionality to scan the contents of a specific directory and to organize the found DICOM MR images into patients, studies and series.

CAAS MRV contains several analysis workflows of the previously cleared predicate device CAAS MRV (K060941) for quantification of the functional and regional parameters of the heart ventricles. Contour detection performed automatically, semi-automatically or manually forms the bases for the analyses.

Functionality to quantify T2 and T2* relaxation values is added by means of the analysis module Tissue Mapping. For this specific feature, Medis MR-CT VVA is used as a predicate device. This feature is implemented in MR-CT VVA and is very similar in both control and presentation, to the CAAS MRV feature, and yields the same results.

The quantitative results of CAAS MRV support diagnosis of cardiovascular conditions.

The analysis results are available on screen and can be saved to hard-disk to enable re-analysis of the data. Also, the analysis results can be exported in various electronic formats.

The functionality is independent of the type of vendor acquisition equipment.

Acceptance Criteria and Device Performance for CAAS MRV (K162112)

Note: The provided document is a 510(k) summary, which generally focuses on demonstrating substantial equivalence to predicate devices rather than detailing extensive clinical trials with specific acceptance criteria and outcome metrics for standalone performance or comparative effectiveness. Therefore, some requested information may not be explicitly present and is inferred where possible.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of numerical acceptance criteria. Instead, it describes general validation approaches and claims equivalence rather than specific quantitative performance targets. The "Performance Data" section states that "the quantification of the tissue relaxation values (T2 and T2*) meet the accuracy and reproducibility requirements." However, the specific numerical requirements or the reported accuracy/reproducibility values are not disclosed in this document.

For the purpose of illustrating the expected format, if such a table were present, it might look like this:

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3mensio Workstation enables visualization and measurement of the heart and vessels for:

• · Pre-operational planning and sizing for cardiovascular interventions and surgery
• · Postoperative evaluation
• · Support of clinical diagnosis by quantifying dimensions in coronary arteries
• · Support of clinical diagnosis by quantifying calcifications (calcium scoring) in the coronary arteries

To facilitate the above, the 3mensio Workstation provides general functionality such as:

• · Segmentation of cardiovascular structures
• · Automatic and manual centerline detection
• · Visualization and image reconstruction techniques: 2D review, Volume Rendering, MPR, Curved MPR, Stretched
• CMPR, Slabbing, MIP, AIP, MinIP
• · Measurement and annotation tools
• Reporting tools

The 3mensio Workstation software allows cardiologists, radiologist and clinical specialists to select patient studies from various data sources, view them, and process the images with the help of a comprehensive set of tools. 3mensio Workstation works with all major medical image formats and can access multiple data stores and across networks.

3mensio Workstation can combine 2D scan slices into comprehensive 3D models of the patient, and can display supporting ultrasound and X-ray Angio data. The software accurately represents different types of tissue, making it easier to diagnose anomalies in scans.

3mensio Workstation contains two modules, 3mensio Structural Heart (containing submodule cCTA), and 3mensio Vascular which can be marketed in combination or as separate solutions:
3mensio Structural Heart enables assessment and measurement of differen structures of the heart, e.g. aortic valve, mitral valve and ventricles. It provides analysis of the feasibility of a transapical, transfemoral or subclavian approach to structures for replacement or repair procedures. 3mensio cCTA enables assessment and measurement of the coronary arteries and can help in the quantification of the dimensions of the coronary arteries and of the calcified plaques present in coronary arteries. 3mensio Vascular enables assessment of vessels and can help identify calcifications, aneurysms and other anomalies to quickly and reliably prepare for various types of vascular procedures.

The results can be displayed, printed or saved in a variety of formats to a hard disk, network, PACS system or CD. Results can also be printed as a hardcopy.

The provided document describes the 3mensio Workstation, a software device for visualizing and measuring the heart and vessels. The submission focuses on demonstrating substantial equivalence to predicate devices, particularly for newly added features: 3mensio cCTA Calcium scoring and 3mensio cCTA Coronary vessel measurement.

Here's an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria (e.g., specific accuracy thresholds) for the device's performance. Instead, it relies on demonstrating that the new features are "very similar" in technology and user interface to legally marketed predicate devices and that they produce "the same results" as a comparable module in a predicate.

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

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective) for the studies performed. It only mentions that a "test report comparing the numerical results of the device compared with the predicate devices is also available."

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

The document does not provide any information regarding the number of experts used or their qualifications for establishing ground truth. The nature of the comparison ("producing the same results" as predicate devices) suggests that the ground truth might implicitly be the results generated by the predicate devices, rather than a separate expert-derived ground truth.

4. Adjudication Method

The document does not specify any adjudication method for a test set.

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 was not performed or reported in this document. The submission focuses on technical equivalence to predicate devices, not on demonstrating improved human reader performance with AI assistance.

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

This appears to be a standalone algorithm, as the comparison is made directly between the device's numerical results and those of predicate devices. The document does not describe any human-in-the-loop performance studies, but rather the device's ability to render, segment, and measure cardiovascular structures by itself, similar to the predicate. Specifically, the "3mensio cCTA Calcium scoring" and "3mensio cCTA Coronary vessel measurement" are standalone features being compared to their counterparts in predicate devices. The overall 3mensio Workstation is a software solution for clinicians to use, but the testing reported here refers to the functional equivalence of the algorithms within it.

7. The Type of Ground Truth Used

The ground truth implicitly used for the performance comparison is the results generated by the predicate devices. The document states that the new features "produce the same results" and are "very similar" in technology and GUI interaction to the predicate devices. This indicates that the predicate's output serves as the reference for equivalence.

8. The Sample Size for the Training Set

The document does not specify any sample size for a training set. This is consistent with the nature of the submission, which is for equivalence based on functional similarity to predicates, rather than a de novo submission for a novel AI algorithm requiring extensive training data validation.

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

Since no training set is described, information on how its ground truth was established is not provided.

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CAAS Workstation is a modular software product intended to be used by or under supervision of a cardiologist or radiologist in order to aid in reading, co-registering and interpreting cardiovascular X-Ray images to support diagnoses and for assistance during intervention of cardiovascular conditions.

CAAS Workstation features segmentation of cardiovascular structures, 3D reconstruction of vessel segments and catheter path based on multiple angiographic images, measurement and reporting tools to facilitate the following use:

• Calculate the dimensions of cardiovascular structures;
• Quantify stenosis in coronary and peripheral vessels;
• Quantify the motion of the left and right ventricular wall;
• Perform density measurements;
• Determine C-arm position for optimal imaging of cardiovascular structures;
• Enhance stent visualization and measure stent dimensions;
• Co-registration of angiographic X-Ray images with IVUS and OCT images.

CAAS Workstation is intended to be used by or under supervision of a cardiologist or radiologist. When the results provided by CAAS Workstation are used in a clinical setting to support diagnoses and for assistance during intervention of cardiovascular conditions, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS Workstation is designed as a stand-alone modular software product for viewing and quantification of X-ray angiographic images intended to run on a PC with a Windows operating system. CAAS Workstation contains the analysis modules QCA, QCA3D, QVA, LVA, RVA and StentEnhancer of the previously cleared predicate device CAAS Workstation (K133993) for calculating dimensions of coronary and peripheral vessels and the left and right ventricles, quantification of stenosis, performing density measurements, determination of optimal C-arm position for imaging of vessel segments and functionality to enhance the visualization of a stent and to measure stent dimension. Semi-automatic contour detection forms the basis for the analyses.

Functionality to co-register X-ray angiographic images and intravascular imaging techniques (such as intravascular ultrasound and optical coherence tomography) is added by means of the analysis module IV-LINQ. With co-registration a common frame of intravascular imaging techniques with X-ray angiographic images is provided using a three-dimensional model. This functionality is based on the Volcano Angio-IVUS Mapping system (K060483).

In the IV LINQ workflow the user has to select two angiographic X-ray images in DICOM format. The user indicates a catheter path starting at the imaging tip. This path can be optimized manually by adding, deleting or moving control point on the drawn path. After the catheter path is drawn in both angiographic X-ray images, a 3D reconstruction of the catheter path is calculated.

The user then has to select one IVUS or OCT dataset in DICOM format or the data is streamed from the intravascular imaging console with a DVI streamer. The IVUS or OCT pullback must be acquired using a motorized pullback device. After the 3D catheter path from X-ray angiographic images is calculated and the IVUS or OCT pullback is loaded, IV-LINQ co-registers each IVUS or OCT frame with a position on the 3D catheter path using a distance mapping algorithm. On intravascular images diameter and area measurements can be performed.

The quantitative results of CAAS Workstation support diagnosis and intervention of cardiovascular conditions. The analysis results are available on screen, and can be exported in various electronic formats. The functionality is independent of the type of vendor acquisition equipment.

The provided text describes the CAAS Workstation and its regulatory submission. It mentions performance data and validation efforts but does not provide explicit acceptance criteria in a table format, nor does it detail a specific study with quantitative results proving adherence to such criteria.

However, I can extract the information provided regarding the device's validation and testing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table of acceptance criteria with corresponding performance metrics. Instead, it offers a general statement about performance:

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

The document does not specify the sample size used for any test sets, nor does it provide information on the data provenance (e.g., country of origin, retrospective or prospective) for training or testing.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

The document does not specify the number of experts used to establish ground truth or their qualifications for any part of the testing.

4. Adjudication Method for the Test Set:

The document does not mention any adjudication method used for a test set.

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

The document does not mention a Multi Reader Multi Case (MRMC) comparative effectiveness study being done, nor does it provide any effect size for human reader improvement with or without AI assistance.

6. Standalone Performance Study:

The document implies a standalone performance for the algorithm through statements like "System testing showed that the system requirements were implemented correctly" and "proper functioning of the algorithms is validated." However, it does not explicitly detail a dedicated standalone study with specific metrics. The focus is on the software's functionality and accuracy of its calculations.

7. Type of Ground Truth Used:

The document describes "validation approaches" and "proper functioning of the algorithms," and "accuracy and reproducibility requirements" for length measurements. This suggests the ground truth was likely established through:

• Reference measurements or calculations for quantitative aspects (e.g., vessel dimensions, stenosis quantification).
• Comparison to accepted standards or methods for qualitative aspects or algorithmic outputs.

However, the document does not explicitly state the specific type of ground truth used (e.g., expert consensus, pathology, outcomes data).

8. Sample Size for the Training Set:

The document does not provide any information regarding the sample size used for the training set.

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

As no training set size is provided, the document does not explain how ground truth for a training set was established.

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CAAS A-Valve has been developed to support the interventionalist during or in preparation of treatment of the aortic root. Based on angiographic X-ray images an analysis is performed: To assist in C-arm projection selection to optimize visualization during treatment; To calculate dimensions of the aortic root corrected for out-of-plane magnification and foreshortening errors; To provide an objective and reproducible grading method for aortic regurgitation based on time versus density curves extracted from an aortogram. The software is used by or under supervision of a cardiologist. When the results provided by CAAS A-Valve are used in a clinical setting to support diagnoses or for assistance during intervention of cardiovascular conditions, the results are explicitly not to be regarded as the sole, irrefutable basis for clinical decision making.

CAAS A-Valve is a stand-alone software application, intended to run on a PC with a Windows operating system. The images for analysis can be read from a directory or from an X-ray system or PACS through a command line interface. The results can be displayed on the screen, printed or saved in a variety of formats to a hard disk, network, PACS system or CD. Results and clinical images with overlay can also be printed as a hardcopy. CAAS A-Valve consists of two separate workflows, Optimal Projection and qRA (quantitative Regurgitation Analysis). With CAAS A-Valve - Optimal Projection, angiographic images of the aortic root can be analyzed to determine a good projection for visualization of the aortic root and to perform basic measurements. As input for analysis, two angiographic images of the aortic root can be selected. On both images the contour of the aortic root is defined manually by the user. The 2D aortic root contours in each image are used to generate a 3D reconstruction of the aortic root. By indicating the right coronary cusp in both projections the software determines the recommended projection (PRL projection). This projection can be used to acquire an aortogram with the cusps in a line and all cusps visible. Additionally it is possible to perform diameter and length measurements based on the 3D reconstruction. The Optimal Projection workflow is 510(k) cleared under K113076. CAAS A-Valve - qRA is used to determine aortic regurgitation (also referred to as aortic insufficiency). This is done based on a multi-frame image showing the aortic root and the left ventricle while contrast liquid is injected in the aorta during the X-ray acquisition; also known as an aortogram. The user draws the contour of the aortic root and the left ventricle and indicates the basal plane. Next a static background, which is obtained from the images before contrast injection, is subtracted resulting in an image sequence in which the intensities correlate to the amount of contrast liquid. Based on this image sequence combined with the user input, time versus contrast density curves are calculated and visualized for both the aortic root and the left ventricle. The ratio between the area under the curve of the aortic root and the area under the curve of the left ventricle represents the amount of contrast liquid flowing from the aortic root to the left ventricle and is a measure for regurgitation. Additionally a dynamic color map is shown for the left ventricle. This color map is achieved by showing the accumulative area under the curve at each image frame as a movie with the same frame rate as used during the acquisition of the multi-frame image. CAAS A-Valve is designed for use in clinical practice to support the physician during or in preparation of treatment of the aortic root.

The acceptance criteria and study details for the CAAS A-Valve device are outlined below, focusing on the information available in the provided text.

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics in a pass/fail format. Instead, it describes what was verified and validated. The "Performance Data" section states that "System requirements - derived from the intended use and indications for use - as well as risk control measures are verified by System Testing. Additionally numerical accuracy and reproducibility is verified and validated for the following analysis results."

Based on this, the table below infers acceptance criteria from the verified and validated analysis results, and the reported performance is that these criteria were met, leading to a conclusion of safety and effectiveness.

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

The document does not specify the exact "sample size used for the test set" or the "data provenance (e.g., country of origin of the data, retrospective or prospective)". It generally refers to "System Testing," "numerical accuracy," and "reproducibility" being verified and validated but provides no specific numbers of cases or origin details.

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

The document does not specify the "number of experts used to establish the ground truth for the test set" or their "qualifications". It mentions that the software is used by or under the supervision of a cardiologist, suggesting expert involvement in clinical use, but not specifically for establishing ground truth in testing. The process for defining aortic root contours is described as "defined manually by the user," implying clinician input.

4. Adjudication Method

The document does not specify any "adjudication method" (e.g., 2+1, 3+1, none) for the test set.

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

The document does not mention a "multi-reader multi-case (MRMC) comparative effectiveness study" or any "effect size of how much human readers improve with AI vs without AI assistance." The device's role is described as "to support the interventionalist" and "to provide an objective and reproducible grading method," suggesting assistance rather than a comparative AI vs. human study for improvement.

6. Standalone Performance Study

Yes, a standalone performance study was implicitly done. The "Performance Data" section states that "System requirements... as well as risk control measures are verified by System Testing. Additionally numerical accuracy and reproducibility is verified and validated for the following analysis results." This indicates that the algorithm's output for Optimal C-arm projection, dimensions, time versus density curves, and aortic regurgitation grade was tested for accuracy and reproducibility on its own.

7. Type of Ground Truth Used

The type of ground truth used is primarily based on expert definition/manual input (user-defined contours) and numerical accuracy/reproducibility verification against established methods or expected values.

• For Optimal Projection: "On both images the contour of the aortic root is defined manually by the user. The 2D aortic root contours in each image are used to generate a 3D reconstruction of the aortic root. By indicating the right coronary cusp in both projections the software determines the recommended projection (PRL projection)."
• For Quantitative Regurgitation Analysis (qRA): "The user draws the contour of the aortic root and the left ventricle and indicates the basal plane." The calculated time versus density curves and the ratio for regurgitation are then compared to a "grading method for aortic regurgitation" that is stated to be "objective and reproducible."

This suggests that the ground truth for validating the device's calculations and determinations relies on initial manual inputs (expert-defined contours) and the ability of the system to consistently and accurately derive quantitative results from these inputs, aligning with established clinical understanding or other validated methods for measurement and grading.

8. Sample Size for the Training Set

The document does not specify the "sample size for the training 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." Given the descriptions, it's possible that the "training set" (if any, as it's not explicitly mentioned as a machine learning model) would also rely on expert input for defining anatomical landmarks and confirming measurements, similar to how the test set's ground truth is implied to be established. However, this is speculative as no specific details are given.

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