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D-SPECT is an emission computed tomography system intended to detect the location and distribution of gamma ray radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. The device includes display equipment, patient and equipment supports, component parts, and accessories. D-SPECT is primarily intended for cardiac applications. D-SPECT supports radionuclides within the energy range of 40 -170 keV.

Spectrum Dynamics' D-Spect™ Cardiac Scanner System is a SPECT device, which is designed to perform myocardial perfusion imaging. The device is comprised of a detector head, gantry, and patient chair. Device operation is controlled from an acquisition station console. The system is supported by use of data-transfer accessories (RFID tags), which are attached to the patient's wrist and to the syringe containing the radio-pharmaceutical agent, for patient and syringe positive identification. The cardiac gamma camera is designed such that there are no external moving parts that surround the patient. Detector boards rotate within the closed detector head. The special scanning geometry and detector technology, enable shorter scan times.

The provided document is a 510(k) summary for the D-SPECT System, an emission computed tomography system for cardiac applications. However, it does not contain specific acceptance criteria or an explicit study report detailing the device's performance against such criteria for the purpose of demonstrating substantial equivalence beyond general safety and performance standards.

The document primarily focuses on establishing substantial equivalence to predicate devices (Virgo and Cardiarc) based on similar intended use and technological characteristics, and by demonstrating compliance with recognized general performance and safety standards.

Therefore, the following information cannot be fully provided based on the given text:

1. A table of acceptance criteria and the reported device performance: No specific clinical acceptance criteria (e.g., sensitivity, specificity, accuracy for a particular clinical task) are mentioned, nor are quantitative performance metrics reported against such criteria. The document states that performance tests demonstrate the device can be safely and effectively used, but not how it quantitatively meets specific performance benchmarks.

2. Sample size used for the test set and the data provenance: Only "Sample images from three clinical cases" are mentioned as clinical performance data. This is an extremely small sample and likely not a formal test set for statistical evaluation. Data provenance (country of origin, retrospective/prospective) is not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.

4. Adjudication method for the test set: Not mentioned.

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: An MRMC comparative effectiveness study was not done. The device is a standalone imaging system, not an AI-assisted interpretation tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes the D-SPECT system as producing images through computer reconstruction of data, and these images are then presumably interpreted by human readers. The clinical performance data presented (Sample images from three clinical cases) suggests a qualitative assessment rather than a quantitative standalone performance evaluation with metrics like sensitivity/specificity against a ground truth. The focus is on the device's ability to "produce cross-sectional images" and "detect the location and distribution of gamma ray radionuclides."

7. The type of ground truth used: Not explicitly stated for the "three clinical cases." Given the nature of a SPECT device, ground truth for myocardial perfusion imaging would typically involve a combination of patient symptoms, additional diagnostic tests (e.g., angiography, stress echocardiography), and clinical follow-up. However, this is not detailed in the document.

8. The sample size for the training set: Not mentioned. The document does not describe the use of machine learning that would typically involve a training set. The device is described as operating on "the same basic principle and the same basic technology as other SPECT devices."

9. How the ground truth for the training set was established: Not mentioned, as no training set for a machine learning algorithm is described.

Summary of what can be extracted from the document:

• Device Name: D-Spect™ Cardiac Scanner System
• Intended Use/Indication for Use: "An emission computed tomography system intended to detect the location and distribution of gamma ray radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. Primarily intended for cardiac applications. Supports radionuclides within the energy range of 40 -170 keV."
• Study Design (Clinical Data): "Sample images from three clinical cases using the D-SPECT device." This is an observational presentation, not a formal clinical study with performance metrics.
• Non-Clinical Test Data: The device underwent "extensive safety testing, performance testing, and validation" including:
  • EMC and Safety testing (IEC/EN-60601-1 and IEC/EN 60601-1-2)
  • Testing according to relevant sections of NEMA NU 1 standard (Performance Measurements of Scintillation Cameras)
  • Software validation testing.
• Conclusion from Tests: "The performance tests demonstrate that D-SPECT device may be safely and effectively used myocardial perfusion imaging. The software validation and performance validation tests for scintillation cameras (NEMA NU 1), as well as the clinical images provided, demonstrate that the D-SPECT device meets its design and performance specifications and is substantially equivalent to the predicate devices."

In essence, the 510(k) summary provided here relies on compliance with established safety and performance standards (like NEMA NU 1 for scintillation cameras) and qualitative clinical image review, rather than a detailed clinical study with quantitative acceptance criteria for diagnostic performance.

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