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Spectrum Dynamics Medical's VERITON system is intended for use by trained healthcare professionals to aid in the detection, localization, diagnosis, staging and restaging of lesions, diseases, and organ function. For evaluating diseases and disorders such as cardiovascular disease, neurological disorders, and trauma. System outcomes can be used to plan, guide, and monitor therapy.

SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques: whole body and tomographic imaging.

CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes take at different angles.

SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images. The SPECT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.

The VERITONCT 300/400 Series consist of back - to - back Single Photon Emission Computed Tomography (SPECT) and X-Ray Computed Tomography (CT) scanners. The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates CT's anatomical detail for precise reference of the location of the metabolic activity. CT subsystem produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as standalone diagnostic imaging devices.

All models employ a same software version 2.3.0

The proposed series consists of four variations:

Modifications in VERITON Family include:

Enhanced CZT module's introduction to support an extended energy range

The provided text describes the VERITON CT 300/400 Series Digital SPECT/CT System, a modification of previously cleared devices (VERITON CT 64 and VERITON CT 16). The submission focuses on demonstrating substantial equivalence to the predicate device VERITON CT 16 (K190457).

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document mentions that "All testing has met the acceptance criteria for the proposed device" for various performance metrics, but it does not explicitly list the specific acceptance criteria values for each test. It only states that the tests were conducted against the predicate device's performance.

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

• Sample Size (Clinical Evaluation): The document states "Sample clinical images." It does not specify the number of images or cases used in this clinical evaluation.
• Data Provenance (Clinical Evaluation): The document does not specify the country of origin of the clinical data nor whether it was retrospective or prospective.

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

• Number of Experts: "a board-certified radiologist" (singular).
• Qualifications of Experts: "board-certified radiologist." The document does not provide information on the years of experience of this radiologist.

4. Adjudication Method:

• The document describes a single board-certified radiologist evaluating "sample clinical images" to confirm diagnostic quality. This indicates no formal adjudication method (like 2+1 or 3+1) was used, as it was a single reader assessment.

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

• No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The clinical evaluation involved a single radiologist confirming diagnostic quality, not comparing human readers with and without AI assistance to measure an effect size.

6. Standalone Performance Study:

• Yes, a standalone performance was done for several technical aspects. The document describes "non-clinical performance evaluations" using "a variety of test methods and phantoms" to characterize the performance of the device's functionality. This included areas like energy resolution, count rate linearity, uniformity, system resolution, and lesion detectability. These tests assess the algorithm's direct output on controlled inputs (phantoms) or simulated conditions, rather than human-in-the-loop performance.

7. Type of Ground Truth Used:

• For Non-Clinical Performance Tests (Standalone): The ground truth would typically be established by the characteristics of the phantoms used and the expected physical and mathematical properties of the SPECT/CT system being tested. These are objective measures based on known inputs.
• For Clinical Evaluation: The ground truth for this simple evaluation was the expert opinion/assessment of diagnostic quality by a board-certified radiologist. It doesn't mention more definitive ground truths like pathology or long-term clinical outcomes.

8. Sample Size for the Training Set:

• The document does not provide any information regarding the sample size of a training set. Given that the device is presented as a modification of existing systems, and the focus is on hardware/software modifications and demonstrating equivalence, it's possible that a new, extensive training set was not required if the underlying algorithms are largely unchanged. However, the document does not clarify this.

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

• Since there is no information on a training set, there is also no information on how its ground truth was established.

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TruSPECT is intended for acceptance, display, storage, and processing of images for detection of radioisotope tracer uptakes in the patient's body. The device using various processing modes supported by the various clinical applications and various features designed to enhance image quality. The emission computerized tomography data can be coupled with registered and/or fused CT/MR scans and with physiological signals in order to depict, localize, and/or quantify the distribution of radionuclide tracers and anatomical structures in scanned body tissue for clinical diagnostic purposes. The acquired tomographic image may undergo emission-based attenuation correction.

Visualization tools include segmentation, colour coding, and polar maps. Analysis tools include Quantitative Perfusion SPECT (QPS), Quantitative Gated SPECT (QGS) and Quantitative Blood Pool Gated SPECT (QBS) measurements, Multi Gated Acquisition (MUGA) and Heart-to-Mediastinum activity ratio (H/M).

The system also includes reporting tools for formatting findings and user selected areas of interest. It is capable of processing and displaying the acquired in traditional formats, as well as in three-dimensional renderings, and in various forms of animated sequences, showing kinetic attributes of the imaged organs.

TruSPECT is based on Windows operating system. Due to special customer requirements and the clinical focus the TruSPECT can be configured with different combinations of Windows OS based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

TruSPECT is a processing workstation primarily intended for, but not limited to cardiac application can be integrated with the D-SPECT cardiac scanner system or used as a standalone post-processing station.

The TruSPECT is a Nuclear Medicine Software system designed for nuclear medicine images' post processing and further review procedures for detection of the radioisotope tracer uptake in the patient's body. Thus, using a variety of post processing features oriented to specific clinical applications.

SUMO Workflow enables visual evaluation and assessment of the sympathetic innervation system of the heart by quantification of uptake ratios between regions of interest, identifying discreet uptake areas of AdreViewtm (lobenguane 123 Injection) or similar agents within the heart. The results generated by the SUMO workflow can be displayed on the D-SPECT processing station and additionally, can be exported to EP systems. It can also be used by the physician to aid in ablation treatment planning by electrophysiologists.

D-SPECT Dynamic CFR is a workflow for visualization, and quantification of specific areas of attention. It is capable of processing and displaying the acquired information in traditional formats, as well as in three-dimensional renderings, and in various forms of animated sequences, showing kinetic attributes of the imaged organs providing quantitative blood flow measurements of SPECT images. The application provides visualization and measurement tools for both qualitative and quantitative visualization and input data evaluation. It provides automated and manual tools for orientation and segmentation of the myocardium. The software calculates myocardial blood flow measurements and provides tools, such as a database comparison workflow, to the clinician to evaluate these outcomes.

TruSPECT CT based Attenuation Correction (CTAC) is an application that removes soft tissue artifacts from SPECT images. The goal is to minimize the impact of attenuation to provide more consistent and reliable reading images. The CT Attenuation Correction (CTAC) uses a second form of imaging (CT) to develop a density map of each patient and correct the SPECT image accordingly.

TruCorr enhances the user's ability to visualize the acquired information (by way of a single clear image) - thus optimizing what would otherwise be a disjointed visual comparison. It is an Emission Based attenuation correction application using the deep learning model which was trained to directly estimate attenuation corrected SPECT images from non-attenuation corrected ones without the use of any anatomical images.

This document describes the TruSPECT Radiological Image Processing Station (K212230), which is a modification to the D-SPECT® Processing and Reviewing Workstation (K160120). The key modification is the TruCorr application, an image attenuation correction method that integrates pre-trained neural networks in the iteration reconstruction process.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in a tabular format. However, it mentions that the "performance testing for the AI-based algorithm for iteration reconstruction process to control image attenuation have been evaluated and demonstrates algorithm's performance and uses test datasets of representative clinical exams." The evaluation method involved a 5-point Likert scale by experts.

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

• Sample Size: The document refers to "test datasets of representative clinical exams" but does not specify the exact number of cases or images.
• Data Provenance: Not explicitly stated. It mentions "representative clinical exams," suggesting real-world patient data, but the country of origin or whether it was retrospective or prospective is not provided.

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

• Number of Experts: Not explicitly stated, but it mentions "experienced NM Physicists and Physicians." The plural form indicates more than one expert.
• Qualifications of Experts: "experienced NM Physicists and Physicians." No specific years of experience are provided.

4. Adjudication Method for the Test Set

The document states that "experienced NM Physicists and Physicians... were used as ground truth. The NM Physicists and Physicians also performed the algorithm evaluation. They reviewed the results and scored them using a 5-point Likert scale." This implies an expert-driven evaluation, but a specific adjudication method like "2+1" or "3+1" is not mentioned. It could be that experts individually scored the images, or they reached a consensus for the ground truth and then individually evaluated the algorithm's output.

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

• There is no mention of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study being done to quantify the improvement of human readers with AI assistance versus without AI assistance. The evaluation focused on the algorithm's standalone performance as assessed by experts.

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

• Yes, a standalone performance evaluation was done. The "performance testing for the AI-based algorithm... have been evaluated" and "NM Physicists and Physicians also performed the algorithm evaluation. They reviewed the results and scored them..." This indicates the algorithm's output was evaluated directly.

7. The Type of Ground Truth Used

• Expert Consensus/Manual Assessment: The ground truth for the test set was established by "experienced NM Physicists and Physicians" who "manually accessed" the clinical exams.

8. The Sample Size for the Training Set

• The document states that the TruCorr deep learning model "was trained to directly estimate attenuation corrected SPECT images from non-attenuation corrected ones without the use of any anatomical images." However, the sample size for the training set is not provided. It mentions the use of "nonadaptive machine learning algorithms trained with clinical and/or artificial data," suggesting a combination of real and synthetic data.

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

• The document implies that the "pre-trained neural networks" for TruCorr were trained to estimate "attenuation corrected SPECT images from non-attenuation corrected ones." While it doesn't explicitly state how the "ground truth" for the training set was established, for a deep learning model to generate "attenuation corrected SPECT images," the training data would typically consist of pairs of non-attenuated and corresponding accurately attenuated SPECT images. This typically involves either:
  • Images that have undergone a known, reliable attenuation correction method (e.g., CTAC) used as the target for the AI.
  • Simulated data where the true attenuation is known.
  • Expert-defined "ideal" attenuation correction.

The text does not detail this process but refers to "clinical and/or artificial data" being used for training.

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The Spectrum Dynamics Medical's VERITON™ CT is intended for use by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging of lesions, disease and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders and trauma. The system output can be used for planning, guiding, and monitoring therapy.

SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques; whole body and tomographic imaging.

CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes take at different angles. The CT part is indicated for pediatric and adult patients.

SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.

VERITON® CT consists of Single Photon Emission Computed Tomography (SPECT) scanners and integrated X-Ray Computed Tomography (CT). The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates the CT's anatomical details for precise reference of the location of the metabolic activity. The CT component produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as stand- alone diagnostic imaqing devices.

The provided text describes the VERITON™ CT whole body SPECT/CT system, a medical imaging device. The document focuses on establishing substantial equivalence to a predicate device rather than detailing an AI/machine learning component. As such, information regarding AI-specific criteria, human reader improvement with AI, standalone algorithm performance, or ground truth establishment for AI training/testing is not present.

However, I can extract information related to the performance testing and clinical evaluation of the SPECT/CT system itself.

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

The document broadly states: "All testing has met the acceptance criteria for the proposed device." Specific quantitative acceptance criteria are not explicitly listed in a table format within the provided text. The areas evaluated included:

• Energy resolution
• Count rate linearity
• Uniformity
• System resolution
• Lesion detectability

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

• Sample Size: Not specified for the clinical image evaluation. The text mentions "Sample clinical images."
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: One
• Qualifications: "a board-certified radiologist"

4. Adjudication method for the test set:

• Adjudication Method: Not applicable or not specified beyond a single expert's evaluation. There's no mention of a consensus or pluralistic adjudication process (e.g., 2+1, 3+1).

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:

• MRMC Study: No. The device is a SPECT/CT system, not an AI-powered diagnostic tool for aiding human readers. The clinical evaluation mentioned was to confirm diagnostic quality of the images produced by the device, not a comparative effectiveness study involving human readers with/without AI assistance.
• Effect Size: Not applicable.

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

• Standalone Performance: Not applicable in the context of an AI algorithm. The device itself is a standalone imaging system. The performance testing described (energy resolution, count rate linearity, etc.) assesses the standalone performance of the SPECT/CT system.

7. The type of ground truth used:

• Type of Ground Truth: For the clinical evaluation, the "diagnostic quality" of images was confirmed by a board-certified radiologist. This can be interpreted as expert opinion/consensus (from a single expert in this case) on the diagnostic utility of the images produced by the device, rather than a definitive "ground truth" for specific pathology or outcomes.
  For the non-clinical performance evaluations (e.g., energy resolution, uniformity), the ground truth would be based on established physics principles and industry standards, often using phantoms.

8. The sample size for the training set:

• Sample Size for Training Set: Not applicable. The document does not describe an AI/machine learning component that would require a distinct training set. The device is a traditional medical imaging system.

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

• Ground Truth for Training Set: Not applicable, as there is no described AI/machine learning training set.

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The Spectrum Dynamics Medical's VERITON™ CT is intended for use by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging of lesions, disease and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders and trauma. The system output can be used for planning, guiding, and monitoring therapy.

SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques; whole body and tomographic imaging.

CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes take at different angles. The CT part is indicated for pediatric and adult patients.

SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.

VERITON™ CT consists of Single Photon Emission Computed Tomography (SPECT) scanners and integrated X-Ray Computed Tomography (CT). The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates the CT's anatomical details for precise reference of the location of the metabolic activity. The CT component produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as stand- alone diagnostic imaging devices.

The provided text describes the VERITON™ CT whole body SPECT/CT system, a medical imaging device. However, it does not contain detailed information about specific acceptance criteria for a study, nor does it present a detailed study proving the device meets those criteria in the format requested.

The document discusses "Performance testing" and "Summary of Non-Clinical Testing" which state that "All testing has met the acceptance criteria for the proposed device." It also mentions a "Summary of Clinical Testing" where a radiologist evaluated sample images for diagnostic quality.

Based on the information provided, I can only generate a partial answer, focusing on the available details and explicitly stating when information is missing.

Here's the breakdown of what can be extracted:

1. A table of acceptance criteria and the reported device performance
   • The document states that "All testing has met the acceptance criteria for the proposed device" for areas like energy resolution, count rate linearity, uniformity, system resolution, and lesion detectability. However, the specific numerical or descriptive acceptance criteria and the reported device performance values are not provided.

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

   • Sample Size: Not specified for non-clinical testing. For clinical testing, it states "Sample clinical images" which implies an unspecified number, likely small, and not a statistically defined test set.
   • Data Provenance: Not specified.

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

   • Number of Experts: "a board-certified radiologist" (one expert).
   • Qualifications: "board-certified radiologist." Specific experience (e.g., "10 years of experience") is not mentioned.

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

   • Adjudication Method: "None" or not applicable, as only one radiologist was used for evaluation.

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

   • MRMC Study: No, there is no indication of an MRMC comparative effectiveness study involving human readers with and without AI assistance. This device is an imaging system, not explicitly a standalone AI diagnostic tool.

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

   • Standalone Performance: The document describes the device (VERITON™ CT system) performance and capabilities. It doesn't detail an "algorithm only" performance separate from the integrated system. The clinical "evaluation" involved a human radiologist reviewing images produced by the system.

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

   • Ground Truth: For clinical evaluation, the ground truth was established by a "board-certified radiologist" confirming "diagnostic quality." This points to expert opinion/evaluation rather than a definitive "ground truth" like pathology for specific disease detection accuracy. For non-clinical testing, phantoms were used, but the specific "ground truth" for e.g. "lesion detectability" in phantoms is inherent to the phantom design.

8. The sample size for the training set

   • Training Set Sample Size: Not applicable/not specified. The document describes a medical imaging device, not a machine learning model that would typically have a separate training set.

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

   • Training Set Ground Truth Establishment: Not applicable, as there's no mention of a traditional "training set" for a machine learning model.

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VERITON™ NM is a Nuclear Medicine (NM) imaging system, intended to perform general nuclear medicine imaging procedures for the detection of radioisotope tracer uptake in a patient's body, using a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality.

Scanning modes include whole body and tomographic (static, dynamic and multi-gated) mode, while acquisition types include single and multi-isotope single-photon imaging-enhancement features include gating by way of physiological signals and real-time automatic body contouring.

The VERITON™ NM system is a medical device intended for use by appropriately-trained healthcare professionals to aid in the detection, localization and diagnosis of diseases and organ function, for the evaluation of diseases, trauma, abnormalities and disorders. System output can be used by a physician for planning, guiding, and monitoring therapy.

SPECT: To detect or image the distribution of radionuclides in the body or organ, using the following techniques: whole body imaging and tomographic imaging.

Software: System application software is a display and analysis package intended to aid the clinician in the assessment and quantification of pathologies taken from SPECT, CT and other imaging modalities.

Spectrum Dynamics VERITON™ NM system is a single photon emission computing tomography system (SPECT) intended for detection of radioisotope tracer uptake in the body and to produce cross-sectional images through computer reconstruction of the data.

The system uses a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality. The system may utilize various modalities to create attenuation corrected images along with functional and anatomical mapping imaging (localization, registration and fusion).

The VERITON™ NM system may include signal analysis and display equipment, patient and equipment supports, components and accessories. The system may include data and image processing to produce images in a variety of trans-axial and reformatted planes. The images can also be post processed to obtain additional images, imaging planes, analysis results and uptake quantitation. The system may be used for patients of all ages.

Here's a breakdown of the acceptance criteria and study information for the VERITON™ NM, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a direct table of specific numerical acceptance criteria and reported device performance for the VERITON™ NM. Instead, it states that:

• "All testing results have met the predetermined acceptance values."
• "Mathematical and physics analysis were performed to demonstrate that each performance metric/claim was successfully verified and substantiated."
• "The device has successfully completed all design control testing per our quality system. No new hazards were identified and no unexpected test results were obtained."

The document mentions that testing was conducted according to NEMA NU-1:2012. This standard specifies performance measurements for gamma cameras, and compliance implies meeting the criteria within that standard for the tested parameters.

Evaluated Areas (Implied Performance Metrics):

• Energy resolution
• Count rate linearity
• Uniformity
• System resolution
• Lesion detectability

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

The document explicitly states that the non-clinical performance evaluation testing "used a variety of test methods and phantoms appropriate for the performance metric/claim that was to be tested and evaluated."

• Sample Size for Test Set: Phantoms were used. The specific number or types of phantoms used for each test are not detailed in this summary.
• Data Provenance: This was an in-vitro (phantom-based) and non-clinical study. Therefore, there is no patient data or country of origin mentioned.

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

Not applicable, as the testing was performed using phantoms and engineering analysis, not human interpretation of patient data in an AI context. The "ground truth" for these tests would be the known physical properties and configurations of the phantoms.

4. Adjudication Method for the Test Set:

Not applicable, as the testing involved physical measurements and analysis against predetermined engineering and performance standards (NEMA NU-1:2012), not human adjudication of image interpretation.

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

No, an MRMC comparative effectiveness study was not conducted. This document describes non-clinical performance testing of the imaging system itself, not a study of human reader performance with or without AI assistance.

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

While the device includes "System application software is a display and analysis package intended to aid the clinician," the performance testing described here focuses on the imaging system's technical specifications and image quality using phantoms. It does not explicitly detail a standalone performance study of the algorithm's diagnostic capabilities on patient data. The summary is primarily about the hardware and core imaging performance.

7. Type of Ground Truth Used:

For the non-clinical performance testing, the ground truth was based on the known physical properties and configurations of the phantoms used, as well as established metrological standards (e.g., NEMA NU-1:2012).

8. Sample Size for the Training Set:

Not applicable. This document describes validation testing of the VERITON™ NM system, which is an imaging device (hardware and associated software), not an AI algorithm that requires a "training set" in the context of machine learning model development.

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

Not applicable, as there was no "training set" in the machine learning sense.

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The D-SPECT® Cardiac Scanner is an emission computed tomography system intended for detection of radioisotope tracer uptake in the patient's body and produce cross-sectional images through computer reconstruction of the data. The system uses a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality. The scanning modes include planar mode (Static, Multi-gated and Dynamic) and tomographic mode (Static, Multi-gated and Dynamic). The acquisition types include single and multi-isotope/multi peak frame/list mode single-photon imaging. The imaging-enhancement features include gating by physiological signals, real-time body movement control, and low count rate (low dose) acquisition without loss of image quality.

The D-SPECT® Cardiac Scanner may consist and display equipment contain data and image processing software to produce images in a variety of trans-axial and reformatted planes. To perform analysis and uptake quantitation and to apply the appropriate filters. The system utilizes combined images for attenuation corrected imaging as well as functional and anatomical mapping imaging (localization, registration and fusion).

The D-SPECT® Cardiac Scanner is intended for use by the appropriately trained healthcare professionals to aid in detecting, localizing and diagnosing of (but not limited) cardiac or individual organs diseases. The system output can be used for planning, guiding, and monitoring therapy.

Spectrum Dynamics D-SPECT® Cardiac Scanner System is a single photon emission computing tomography system intended for detection of radioisotope tracer uptake in the body and produce cross-sectional images through computer reconstruction of the data.

The device uses a variety of scanning modes supported by various acquisition types and imaging features designed to enhance image quality. System's scanning modes include planar mode (Static, Multi-Gated and Dynamic) and tomographic mode (Static, Multi-Gated and Dynamic). The acquisition types include single and multi-isotope/multi peak frame/list mode single-photon imaging. The imaging-enhancement features include gating by physiological signals, real-time body movement control. The device may proceed a low count rate (low dose) acquisition without loss of image quality. The device may utilize variate modalities to create attenuation corrected images along with functional and anatomical mapping imaging (localization, registration and fusion).

The device is a high performance and compact Single Photon Emission Computed Tomography system intended for imaging of the breast and additional small organs in order to aid in the evaluation of lesions.

The system detectors support radionuclides within the energy range of 40 -170 Kev.

D-SPECT® Cardiac Scanner System comprising detector head, gantry, patient supports, uninterruptible power supply (UPS), image display and processing equipment, gating and real-time body movement control tools, interconnecting cables and related appurtenances.

The device is available in two models, D-SPECT with nine detectors configuration and the D-SPECT L with six detectors configuration.

D-SPECT® Cardiac Scanner System consist integrated signal analysis and display equipment or may use an FDA cleared D-SPECT® Processing and Reviewing Workstation (K160120) for image processing.

The provided text describes the D-SPECT® Cardiac Scanner System, an emission computed tomography system. However, the document does not contain explicit acceptance criteria and a detailed study report proving the device meets those criteria with specific performance metrics.

The text mentions "All testing results are met the predetermined acceptance values" but does not elaborate on what these values are or the specific results. It also states "The device efficacy and safety as well as the performance specifications remain the same," referring to a previous 510(k) cleared device (K110507). Without the original K110507 submission or a more detailed current submission, specific acceptance criteria and performance data are unavailable in this document.

Therefore, many of the requested details cannot be extracted directly from the provided text.

Here is what can be inferred or stated based on the text provided:

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

This information is not explicitly stated in the provided document. The document mentions: "All testing results are met the predetermined acceptance values." and "The device efficacy and safety as well as the performance specifications remain the same." This implies that the device's performance matches or exceeds the criteria established for the predicate device (K110507) and potentially international standards, but the specific metrics are not provided.

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

This information is not available in the provided text. The document refers to "performance validation testing" but does not specify details about patient data, sample sizes, or provenance.

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):

This information is not available in the provided text. The document mentions the device is intended for use by "appropriately trained healthcare professionals," but it doesn't describe any studies involving experts establishing ground truth.

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

This information is not available in the provided text.

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:

This information is not available in the provided text. The device described is a SPECT imaging system, not an AI-assisted diagnostic tool, so an MRMC study comparing AI assistance would not be directly relevant to its fundamental performance.

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

This device is an imaging system, not an algorithm in the typical sense of a standalone AI diagnostic tool. Its "performance" refers to the quality of the images it produces and its ability to detect radioisotope uptake. The document indicates that "performance validation testing conducted according to NEMA NU-1:2012," which are standards for performance measurements of SPECT systems. This would refer to the technical performance of the device itself.

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

This information is not explicitly stated in the provided text. For SPECT imaging systems, ground truth for performance testing typically involves phantoms with known activity distributions to assess resolution, sensitivity, uniformity, etc., and potentially clinical correlation for certain aspects of image quality, but the document does not specify the method used.

8. The sample size for the training set:

This information is not applicable/available. The D-SPECT Cardiac Scanner System is a hardware imaging device that uses reconstruction algorithms, but the text does not describe an AI/machine learning component that would require a "training set" in the context of device performance claims.

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

This information is not applicable/available for the reasons stated above.

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