K Number
K090811
Date Cleared
2009-08-27

(155 days)

Product Code
Regulation Number
892.1200
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The inSPira HD™ is intended to produce images depicting the anatomical distributions of single photon emitting radioisotopes within the human body for interpretation by medical personnel for anatomy that can be imaged in the 21cm field of view, primarily brain.

Device Description

The InSPira HD™ is a mobile single photon computed tomography system comprised of focused collimators to acquire volumetric x-ray data primary of the head and neck. This system is intended to be utilized by appropriately trained healthcare professionals to image and measure the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body. With the exception of an x-ray source, materials and construction are equivalent to the CereTom and are compliant with CISPR11, IEC 60601-1 and associated collateral standards and applicable sections of 21CFR Subchapter J.

AI/ML Overview

The provided text does not contain detailed information about acceptance criteria for a study, devices' performance against those criteria, or a comprehensive study report with sample sizes, ground truth establishment, or expert qualifications.

The document is a 510(k) summary for the NeuroLogica Corporation InSPira HD™ and primarily focuses on establishing "substantial equivalence" of the device to previously cleared predicate devices. It describes the device, its intended use, and similarities and differences to predicate devices, but not a clinical study designed to test performance against pre-defined acceptance criteria with statistical rigor.

Therefore, many of the requested sections cannot be filled from the provided text.

Here's what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance:

  • Cannot be provided: The document is a 510(k) submission for "substantial equivalence" and does not present acceptance criteria or detailed device performance metrics from a specific study. Instead, it discusses the device's technical specifications and how they compare to predicates (e.g., better reconstructed resolution/sensitivity for brain-sized anatomy compared to one predicate), but these are not framed as acceptance criteria with numerical targets and achieved performance.

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

  • Cannot be provided: The document does not describe a clinical study with a test set of data.

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

  • Cannot be provided: No information regarding experts or ground truth establishment for a test set is present.

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

  • Cannot be provided: No adjudication method is mentioned as there's no described test set or expert review process.

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:

  • Cannot be provided: The device is a "Single photon emission computed tomography system" (SPECT) and not an AI/CAD device for which MRMC studies are typically performed. The document does not describe any human-in-the-loop or AI assistance effectiveness study.

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

  • Cannot be provided: The device is a hardware imaging system, not an algorithm, so stand-alone algorithm performance is not applicable or discussed.

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

  • Cannot be provided: No ground truth establishment is described in the context of a performance study.

8. The sample size for the training set:

  • Cannot be provided: The document does not describe a training set as it's not a machine learning/AI device, but rather a hardware imaging system.

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

  • Cannot be provided: Not applicable for this type of device and submission.

In summary: The provided text is a regulatory submission focused on demonstrating substantial equivalence for a SPECT imaging system, not a performance study report with the specific details requested.

§ 892.1200 Emission computed tomography system.

(a)
Identification. An emission computed tomography system is a device intended to detect the location and distribution of gamma ray- and positron-emitting radionuclides in the body and produce cross-sectional images through computer reconstruction of the data. This generic type of device may include signal analysis and display equipment, patient and equipment supports, radionuclide anatomical markers, component parts, and accessories.(b)
Classification. Class II.