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NeuroLF is a positron emission tomography system that is used to detect and display the distribution of positron-emitting radionuclides within parts of the human body to assist in diagnosis, therapeutic planning, and therapeutic outcome assessment. The NeuroLF seat is intended to properly position the patient for PET imaging of the neck or head with the NeuroLF.

The NeuroLF is a small aperture Positron Emission Tomography (PET) scanner that produces images of the distribution of positron-emitting isotopes from parts of a subject that are put into the aperture for medical diagnostic purposes. The NeuroLF System comprises the Scanning Unit and the Patient Positioning System (NeuroLF Seat). The circular opening in the scanner head has an effective inner diameter of 260mm and is designed such that the entire brain fits within the scanner's field of view (FoV). With a length of an axial FoV of 163mm, the NeuroLF is designed to capture a single image. The NeuroLF scanner head consists of an octagonal detector, which is composed of 8 detector module contains a total of 384 Lutetium Yttrium Orthosilicate (LYSO) Crystals. The software of the NeuroLF System integrates the equipment, allows acquisition, reconstruction and export of tomographic images. It also allows the user to detect the current state of the running system. The device shall only be used with patients whose weight is lower than 200kg (440lb). There are three different versions of the NeuroLF; 10 mm (NeuroLF Basic), 15 mm (NeuroLF Pro) and 20 mm (NeuroLF Advanced). The number corresponds to the length of the LYSO crystals in the detector modules. The absorption probability of gamma radiation is proportional to the volume of scintillating material in the scanner and therefore the highest absorption probability is to be expected from the 20 mm detectors. The longer the LYSO crystals the higher the sensitivity of the device, therefore in clinical use the acquisition time or the activity in the field of view could be reduced.

The NeuroLF system, a positron emission tomography (PET) scanner, has been cleared for marketing based on its substantial equivalence to a legally marketed predicate device (BBX-PET Scanner, K210450). The clearance is supported by various performance tests demonstrating its compliance with predetermined specifications and applicable standards.

Here's a breakdown of the acceptance criteria and the study information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document doesn't explicitly lay out quantitative acceptance criteria for all aspects in a consolidated table, but rather compares specific performance metrics between the subject device (NeuroLF) and the predicate device, or states compliance with general requirements. However, based on the "Performance Data Specifications" section and the NEMA NU-2:2018 standard for PET systems, we can infer some criteria and reported performance.

Justification of Equivalence: The document states that the NeuroLF's detectors and fields of view are similar to the predicate, with a longer axial FoV for NeuroLF. While its crystal pitch is larger, the use of a single layer of scintillators is noted to facilitate correct gamma absorption location. These differences are deemed to "not affect the indications, only the performance," suggesting that the performance differences are within acceptable clinical variability or represent improvements. Specifically, the clinical effectiveness section concludes with "Same or better as predicate."

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

• Sample Size for Test Set:
  • Bench Performance Testing: The document does not specify a "sample size" in terms of number of units tested. Performance was tested on the NeuroLF System. The testing was performed according to NEMA NU-2:2018 standard, which dictates specific phantoms and procedures.
  • Clinical Effectiveness: "Sample images from four clinical cases using the NeuroLF System were provided."
• Data Provenance: The document does not explicitly state the country of origin for the clinical cases or whether they were retrospective or prospective. It only mentions that Positrigo AG provided the images. Given that Positrigo AG is based in Switzerland, it's plausible the data originated there, but this is not confirmed.

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

The document mentions "Sample images from four clinical cases" for clinical effectiveness and that this "supported the clinical effectiveness of the NeuroLF system." However, it does not specify the number of experts used to establish ground truth or their qualifications for these four clinical cases. The ground truth for these cases is implicitly the clinical images themselves being representative of appropriate PET imaging for the stated indications for use.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the clinical images used in the clinical effectiveness assessment.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not done. The document focuses on showing the device's performance against NEMA standards and the predicate device's general capabilities, and provides a small number of clinical images as anecdotal evidence of clinical effectiveness. It does not assess the improvement of human readers with or without AI assistance, as AI assistance in image interpretation is not an explicit claim or feature described in the provided text.

6. Standalone Performance Study

Yes, a standalone performance study was done for the algorithm (the PET system itself). This is described under "Performance Testing - Bench," where "The performance of the NeuroLF System has been tested by Positrigo AG according to NEMA NU-2:2018." This involved objective physical performance measurements of the device without human interpretation studies to assess its imaging capabilities.

7. Type of Ground Truth Used

• Bench Performance Testing: The ground truth for bench testing (e.g., spatial resolution, sensitivity) is established by the NEMA NU-2:2018 standard, which dictates the use of specific phantoms and measurement techniques to determine objective physical performance parameters.
• Clinical Effectiveness: The ground truth for the four clinical cases is implicitly the clinical images themselves, which are presented as demonstrating the device's capability to produce images for diagnostic assistance, therapeutic planning, and outcome assessment. There is no mention of pathology, outcomes data, or expert consensus being explicitly used to establish ground truth for these specific cases beyond the images' clinical utility.

8. Sample Size for the Training Set

The document does not mention a training set in the context of device performance or software development. The NeuroLF is a PET scanner, and its primary function is image acquisition and reconstruction based on physical principles, not a machine learning model that requires a "training set" in the conventional sense of AI/ML. The software itself undergoes verification and validation, but not typically with a separate "training set" like an AI algorithm would.

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

As no training set is mentioned or applicable in the context of this device description (which is a physical PET scanner with image reconstruction software, not an AI/ML diagnostic tool), this information is not provided.

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