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ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.

ADAS 3D is indicated for patients with myocardial scar produced by ischemic or non-ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.

ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) for the calculation, quantification and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.

The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established.

ADAS 3D is a stand-alone software tool intended to be used for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography Angiography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D software aids in the non-invasive calculation, quantification of cardiac imaging data to support a comprehensive diagnostic decision-making process for understanding cardiovascular disease.

ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems.

ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support:

• Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart.
• Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure.
• . Calculation, quantification and visualization of corridors of intermediate, signal intensity enhancement in the LV.
• Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA).

Additionally, ADAS 3D imports DICOM CTA images to support:

• Quantification of LV wall thickness.
• Identification and Visualization of other 3D anatomical structures.
• Quantification and visualization of LA wall thickness.
• Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures.

Additionally, ADAS 3D imports DICOM Magnetic Resonance Angiography (MRA) images to support:

• Identification and Visualization of other 3D anatomical structures.
  Additionally, ADAS 3D uses the following machine-learning-based features:

• Standard Initialization of the LV, LA, and Aorta from CTA

• Standard Initialization of the Coronary Arteries from CTA

• Standard Initialization of the LA from CTA

• Standard Initialization of the LV from 2D LGE-MRI and Automatic Slice Alignment ●

• Standard Initialization of the LV from 3D LGE-MRI

• Standard Initialization of the LA from 3D LGE-MRI

Here's a breakdown of the acceptance criteria and study details for the Adas3D Medical S.L. ADAS 3D device, based on the provided text:

Acceptance Criteria and Reported Device Performance

Note: The text explicitly states that four tests did not meet the non-inferiority criteria, but these discrepancies were considered sub-pixel and acceptable.

Study Details

• Sample size used for the test set and the data provenance:

  • Standard Initialization of the Left Chambers and Aorta from CTA: 100 cases (US 62%, OUS 38%)
  • Standard Initialization of the Coronaries from CTA: 100 cases (US 64%, OUS 36%)
  • Standard Initialization the LA from CTA: 100 cases (US 65%, OUS 35%)
  • Automatic Slice Alignment for LV from 2D DE-MRI: 70 cases (US 52%, OUS 48%)
  • Standard Initialization of the LV from 2D DE-MRI: 100 cases (US 52%, OUS 48%)
  • Standard Initialization of the LV from 3D DE-MRI: 100 cases (US 69%, OUS 31%)
  • Standard Initialization of the LA from 3D DE-MRI: 95 cases (US 60%, OUS 35%)

  All data in the test set was selected from hospitals not used in any stage of algorithm development (training). The data provenance for the test set includes imaging from both US and OUS (Outside US) countries. The data was anonymized by the hospitals in compliance with GDPR.

• Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
  The ground truth annotations for the test set were generated by two clinical experts. Their qualifications are not explicitly detailed beyond being "clinical experts independent of the clinical experts who established the ground truth of the training dataset." However, the document states the device is intended for use by "qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images." It can be inferred that these clinical experts possess similar qualifications.

• Adjudication method for the test set:
  The adjudication method for reconciling differences between the two clinical experts for the test set ground truth is not explicitly stated. It only mentions that ground truth was generated by two independent experts.

• 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, a multi-reader, multi-case (MRMC) comparative effectiveness study evaluating human readers with and without AI assistance was not described in the provided text. The study focused on the standalone performance of the AI features.

• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
  Yes, the performance testing described is a standalone (algorithm only) performance evaluation. The study assessed the accuracy of the machine learning features against expert-generated ground truth, rather than measuring improvements in human reader performance with the device. The goal of the device is stated as "to provide a preliminary initialization of the target structure, which would then be subject to further refinement by the user," indicating a standalone assessment of its initialization capability.

• The type of ground truth used:
  The ground truth used for the test set was expert consensus / expert annotation. It was generated using the FDA-cleared ADAS 3D software by two independent clinical experts.

• The sample size for the training set:

  • Standard Initialization of the Left Chambers and Aorta from CTA: 111 DICOM images
  • Standard Initialization of the Coronaries from CTA: 231 DICOM images
  • Standard Initialization the LA from CTA: 136 DICOM images
  • Standard Initialization LV from 2D DE-MRI: 126 DICOM images
  • Standard Initialization of the LV from 3D DE-MRI: 110 DICOM images
  • Standard Initialization of the LA from 3D DE-MRI: 82 DICOM images

• How the ground truth for the training set was established:
  The ground truth annotations for the training dataset were "generated initially by the hospitals' clinical teams and revised by Adas3D Medical's Clinical Team." Adas3D Medical's Clinical Team consists of "highly experienced individuals with knowledge of cardiac anatomy, interpretation of MRI and CT volumes, and the use of ADAS 3D."

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ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.

ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.

ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, radiologists, radiologists, radiologists or trained technicians) for the calculation and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.

The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arthythmias (e.g., ventricular tachycardia) or risk stratification has not been established.

ADAS 3D is a software tool intended to be used for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D is intended for the non-invasive calculation, quantification of cardiac imaging data to support a comprehensive diagnostic decision-making process for understanding cardiovascular disease.

ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems.

ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support:

• Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart.
• Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure.
• Calculation, quantification and visualization of corridors of intermediate, signal intensity enhancement in the LV.
• Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA).

Additionally, ADAS 3D imports DICOM CTA images to support:

• Quantification of LV wall thickness.
• Identification and Visualization of other 3D anatomical structures.
• Quantification and visualization of LA wall thickness.
• Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures.

Additionally, ADAS 3D imports DICOM Magnetic Resonance Angiography (MRA) images to support:

• Identification and Visualization of other 3D anatomical structures.

It is designed to be used by qualified medical professionals (cardiologists, radiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images as part of the comprehensive diagnostic decision-making process.

The provided text is a 510(k) summary for the ADAS 3D device. It outlines changes from a previous version (K212421) but does not contain detailed information about the acceptance criteria or a specific study proving the device meets those criteria, especially in the context of clinical performance or accuracy metrics of the AI algorithms. The summary focuses on comparing the modified device to its predicate and describing the changes.

Therefore, much of the requested information cannot be extracted from this document regarding a study proving the device meets acceptance criteria. However, I can provide what is mentioned about the modifications and the general statement about testing.

Here's an attempt to answer based on the limited information available in the provided text:

Acceptance Criteria and Study for ADAS 3D (K230803)

The provided 510(k) summary details modifications to an existing device (ADAS 3D, K212421) and states that "The modified ADAS 3D device has been subject to design controls including design review, risk analyses, design verification / validation testing in order to ensure its safety and effectiveness. The modifications were assessed using well-established methods to validate that the software fully satisfies system requirements."

However, this document does not provide a specific table of detailed acceptance criteria with numerical performance targets or the results of a specific study demonstrating that the device explicitly meets these criteria for its AI-powered functionalities beyond a general statement of design verification and validation.

Without a dedicated section detailing specific performance metrics and a corresponding study, the table below represents what can be inferred or is missing from the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states that the modifications were "assessed using well-established methods to validate that the software fully satisfies system requirements." However, it 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 any specific performance evaluations.

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

This information is not provided in the 510(k) summary. The document mentions that the device is intended for use by "qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians)." However, it does not detail how ground truth was established for any specific test set related to the modifications.

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

This information is not provided in the 510(k) summary.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study or any effect size for human reader improvement with AI assistance. The Indications for Use explicitly state: "The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making." This indicates the device is for decision support rather than a standalone diagnostic tool, but no human-in-the-loop performance study is detailed here.

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

While the document implies some level of algorithm performance validation through "design verification / validation testing," it does not explicitly describe a standalone performance study with specific metrics for any of the modified functionalities (e.g., accuracy of coronary identification, LV segmentation, or corridor detection).

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

The document does not specify the type of ground truth used for any validation testing of the modified functionalities.

8. The sample size for the training set

The document does not provide any information regarding the sample size used for training the algorithms, nor does it explicitly state that the modifications involved retraining existing AI models or developing new ones from scratch (though "improvements" to existing tools could imply model updates).

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

As no training set information is provided, how its ground truth was established is also not mentioned in this document.

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ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.

ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.

ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, radiologists, radiologists, or trained technicians) for the calculation quantification of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.

The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established.

ADAS 3D is a stand-alone software tool designed for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography Angiography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D software aids in the non-invasive calculation, quantification and visualization of cardiac imaging data to support a comprehensive diagnostic decisionmaking process for understanding cardiovascular disease.

ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems.

ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support:

• Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart.
• Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure.
• Calculation, quantification and visualization of corridors of intermediate, signal intensity enhancement in the LV.
• Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA).

Additionally, ADAS 3D imports DICOM CTA images to support:

• Quantification of LV wall thickness.
• Identification and Visualization of other 3D anatomical structures.
• Quantification and visualization of LA wall thickness.
• Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures.

It is designed to be used by qualified medical professionals (cardiologists, radiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images as part of the comprehensive diagnostic decision-making process.

Here's an analysis of the acceptance criteria and study information for the ADAS 3D device based on the provided text:

Important Note: The provided document is a 510(k) summary for a modified device, ADAS 3D, that adds two new functional features compared to a predicate device (K210850). The summary primarily focuses on demonstrating substantial equivalence of the new features and therefore might not contain all the detailed clinical study information typically found for an initial device clearance.

Description of Acceptance Criteria and Study Proving Device Meets Them

The document describes the modified ADAS 3D device as a software tool for post-processing cardiovascular MR and CTA images to aid in diagnosis and pre-planning for electrophysiology procedures. The two new features are:

• Quantification and visualization of LA wall thickness.
• Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures.

The device's acceptance criteria, for these new features, are centered around the validation of the software's ability to accurately measure and visualize these anatomical parameters.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states: "The two new features (Left Atrial wall thickness and Left Atrial distances measurements) were assessed using synthetic phantoms to validate that the software fully satisfies system requirements."

• Sample Size: Not explicitly stated, as "synthetic phantoms" usually implies a set of simulated data rather than a specific number of patient cases. The number of phantoms used is not provided.
• Data Provenance: Synthetic/simulated data. No specific country of origin is applicable as these are not real patient cases. This was a prospective simulation/validation study of the software's performance on engineered data.

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

This information is not provided in the document for the new features' validation. Since synthetic phantoms were used, the "ground truth" would likely be the known, precisely engineered dimensions within the phantoms themselves, rather than requiring expert consensus on clinical images.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method. This aligns with the use of synthetic phantoms where the ground truth is inherently known and does not require expert adjudication.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done for these new features, nor is any such study mentioned in the context of human readers improving with AI vs. without AI assistance for these specific functionalities. The validation focused on the software's technical accuracy using synthetic data.

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

Yes, implicitly. The validation was conducted using "synthetic phantoms to validate that the software fully satisfies system requirements." This indicates a standalone assessment of the algorithm's performance in measuring the specified parameters without human-in-the-loop interaction for these specific validation steps.

7. The Type of Ground Truth Used

The ground truth for the validation of the new features was based on known, engineered measurements within synthetic phantoms.

8. The Sample Size for the Training Set

The document does not specify the sample size for the training set. This 510(k) summary is for a modification to an already cleared device (K210850) and focuses on the validation of new features, not the creation or re-training of the entire underlying model.

9. 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. This information would likely have been part of the original K210850 submission for the predicate device. For the validation of the new features, the ground truth was inherent in the design of the synthetic phantoms.

Ask a specific question about this device

ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.

ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.

ADAS 3D is indicated to be used only by qualified medical professionals ( cardiologists, radiologists, radiologists, radiologists, or trained technicians) for the calculation and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.

The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias ( e.g., ventricular tachycardia) or risk stratification has not been established.

ADAS 3D is a software-based image processing tool for post-processing cardiovascular enhanced Magnetic Resonance (MRI) images and Computed Tomography Angiography (CTA) images.

ADAS 3D is designed to process DICOM image databases to enable the calculation, quantification and visualization of 3D cardiac imaging data by displaying and quantifying the levels of enhancement. ADAS 3D also enables the visualization of the shape of the cardiac chamber and the adjacent anatomy. After data processing, the data and images can be exported utilizing industry standard for viewing on other systems, including Electrophysiology (EP) navigation systems.

The provided text describes a 510(k) submission for the ADAS 3D device, which is a software-based image processing tool for post-processing cardiovascular MRI and CTA images.

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

Important Note: The provided document is a 510(k) summary for a submission involving clarifications to Indications for Use and Precautions sections of a previously cleared device (ADAS 3D, K191125). It explicitly states: "The ADAS 3D device that is the subject of this Special 510(k) is identical to the ADAS 3D device cleared under (K191125). Only clarifications to the Indications for Use and Precautions sections have been made... These labelling changes do not impact the safety or effectiveness of the device."

This means the current document does not contain a new study demonstrating the device's performance against acceptance criteria. Instead, it relies on the substantial equivalence to the predicate device (K191125), implying that any performance studies were conducted and reviewed during the clearance of K191125.

Therefore, the following answers are based on what might be expected for a device like this, or what we can infer from the description of ADAS 3D's functionalities and the acceptance criteria mentioned for its 3D Corridors Module. The document does not explicitly detail a performance study for K210850 because it's a special 510(k) primarily for labeling changes.

1. Table of acceptance criteria and the reported device performance

The document does not provide a formal table of acceptance criteria for the overall device's performance in K210850, as this submission focuses on labeling changes.

However, for the "3D Corridors Module," the document defines the criteria for what the algorithm must identify as a 3D Corridor. If this were a performance study, these would be the ground truth definitions that the algorithm's output would be compared against. The document does not provide "reported device performance" against these criteria in a quantitative manner (e.g., sensitivity, specificity, accuracy).

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document for K210850 does not describe a new performance study, thus no test set sample size or data provenance is provided. Any such information would have been part of the original K191125 submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

No new performance study in K210850, so this information is not provided. The definitions for the "3D Corridors Module" are given algorithmically, not as expert-established ground truth from a study within this document.

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

No new performance study in K210850, so this information is not provided.

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

The document does not describe an MRMC comparative effectiveness study for K210850. The device is a post-processing tool intended to "support the visualization and analysis" and "support qualified medical professionals for clinical decision making," implying assistance, but no comparative effectiveness study with human readers is detailed here.

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

This document does not describe a standalone performance study for K210850. The device itself is software-only (standalone software application), but performance evaluation of its outputs against a ground truth is not presented here.

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

For the "3D Corridors Module," the ground truth definition is algorithmic based on specific criteria (BZ region, HT region, CS region, minimum length). If a performance study were done, the algorithm's output would be compared against these predefined algorithmic criteria or against expert delineations following these criteria. The document does not specify which type of ground truth was used in any prior studies, or if such studies specifically used expert consensus, pathology, or outcomes data to validate the clinical significance of these algorithmic definitions. Indeed, the Indications for Use state, "The clinical significance of using ADAS 3D to identify arrhythmia substrates... has not been established."

8. The sample size for the training set

No details on training set size are provided in K210850.

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

No details on training set ground truth establishment are provided in K210850.

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ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease.

ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D.

ADAS 3D is indicated to be used only by qualified medical professionals for the visualization and analysis of cardiac images. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making.

ADAS 3D is not intended to identify regions for catheter ablation or treatment of arrhythmias.

ADAS 3D is a software-based image processing tool for post-processing cardiovascular enhanced Magnetic Resonance (MRI) images and Computed Tomography Angiography (CTA) images.

ADAS 3D is designed to process DICOM image databases to enable the calculation, quantification and visualization of 3D cardiac imaging data by displaying and quantifying the levels of enhancement. ADAS 3D also enables the visualization of the cardiac chamber and the adjacent anatomy. After data processing, the data and images can be exported utilizing industry standard formats for viewing on other system, including Electrophysiology (EP) navigation system.

The provided document is a 510(k) summary for the ADAS 3D device. It identifies a predicate device (MR-CT VVA, K140587) and discusses the substantial equivalence of ADAS 3D based on intended use, indications for use, and performance, including non-clinical and clinical data.

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or a direct performance table for ADAS 3D against such criteria. Instead, it relies on comparison to a predicate device and states that "clinical data was used to test and validate this software as described in section 18 of this submission to support this premarket notification and to establish the decision concerning adequate safety and performance of the predicate device." It concludes that ADAS 3D is "substantially equivalent to the listed legally marketed predicate devices."

Therefore, the reported device performance is implicitly considered to be equivalent to the predicate device, MR-CT VVA (K140587), and to generally meet the safety and performance standards for a radiological image processing system.

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

The document states that "Clinical data was used to test and validate this software as described in section 18 of this submission." However, Section 18 is not included in the provided text, so the specific sample size for the test set and the data provenance (e.g., country of origin, retrospective or prospective) cannot be determined from the given information.

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

This information is also not present in the provided text. The document mentions that the device is "intended to be used by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians)," but it does not specify how many or with what qualifications experts were involved in establishing ground truth for the validation studies.

4. Adjudication method

The adjudication method for the test set is not mentioned in the provided document.

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

The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was conducted to measure human reader improvement with or without AI assistance. The focus is on the software's ability to provide visualization and quantification to support clinical decision-making, rather than directly improving human reader performance metrics.

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

The document describes ADAS 3D as a "software-based image processing tool" for "calculation, quantification and visualization of 3D cardiac imaging data." It identifies specific functions like "Left Ventricle Layer Computation," "Enhancement Quantification algorithm," and "3D Corridor Detection Algorithm." These descriptions strongly suggest that standalone algorithm performance was evaluated, as the software performs these calculations and visualizations independently. The output then "supports" qualified medical professionals, implying the algorithm runs without a "human-in-the-loop" for its primary processing functions.

7. The type of ground truth used

The specific type of ground truth used for its clinical validation is not explicitly stated in the provided text. The device processes MR and CT images and focuses on identifying and quantifying myocardial scar and 3D corridors of border zone tissue. Therefore, the ground truth would likely involve expert consensus interpretations of complex cardiac imaging, potentially correlated with other clinical data or pathology where available, but this is not confirmed in the document.

8. The sample size for the training set

The document does not provide any information regarding the sample size used for the training set for the ADAS 3D algorithms.

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

The document does not provide any information regarding how the ground truth for the training set was established.

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