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The Q-Collar is a non-invasive device intended to be worn around the neck of athletes aged 13 years and older during sports activities to aid in the protection of the brain from effects associated with repetitive sub-concussive head impacts.

The Q-Collar (Figure 1) is a C-shaped collar intended to be worn around the neck during sports activities. The protuberances located at each end of the device are designed to ensure the correct location of pressure on the neck to provide compressive force to the internal jugular vein (IJV). In order to confirm whether the Q-Collar is properly sized and fits the wearer correctly, an ancillary fitting tool, referred to as the Fit Check (Figure 2), is packaged with the Q-Collar. The Q-Collar and Fit Check are packaged with a carry case (Figure 3) for transport and storage.

The provided text describes the Q-Collar, an external compression device for internal jugular vein compression, and details the studies conducted to support its de novo classification by the FDA. The following information summarizes the acceptance criteria, device performance, and study characteristics.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document details non-clinical bench testing acceptance criteria and results. Clinical studies focused on safety and efficacy in reducing neuroanatomical and neurophysiological changes associated with head impacts rather than specific quantitative performance criteria related to medical imaging.

Human Factors and Usability Testing:

• Acceptance Criteria for Fit Check Tool: Users should be able to correctly use the Fit Check Tool to confirm proper sizing and fit.
  • Reported Performance: (b) (4) out of (b) (4) participants were able to use the Fit Check Tool correctly.
• Acceptance Criteria for Labeling Comprehension (Head Injury Action): Users should understand to seek medical care immediately following a head injury while wearing the Q-Collar, and that the device does not prevent head injury.
  • Reported Performance: (b) (4) out of (b) (4) participants successfully responded to questions related to actions taken after incurring a head injury, indicating understanding that the Q-Collar does not prevent head injury and medical treatment should be sought. (b) (4) participants overlooked the specific instruction "Seek medical care immediately if you experience symptoms of a concussion." and one participant demonstrated negative transfer by stating they would not act differently.

Clinical Efficacy (Pivotal Studies):

• Primary Effectiveness Endpoint (Football Study): Changes in DTI metrics (MD, AD, RD) in whole brain from pre-season to post-season in Q-Collar vs. non-Q-Collar groups.
  • Reported Performance: Significant pre-season to post-season reductions in MD, AD, and RD were found in extensive white matter regions in the no-Collar group (p < (b) (4)), but not in the Collar group (p > (b) (4)). Significant greater RD reductions were shown in the no-Collar group compared to the Collar group (p < (b) (4)) in specific regions. The Q-Collar modulated the relationship between head impact exposure and changes in DTI metrics at higher magnitude exposure levels.
• Primary Effectiveness Endpoint (Soccer Study): Changes in DTI-derived brain networks and fMRI-derived brain network measures (e.g., Cg, L, Q) in whole brain from pre-season to post-season in Q-Collar vs. non-Q-Collar groups.
  • Reported Performance: fMRI-derived graph measures showed significant increase in Cg and change in path length (L) for the no-Collar group, with significant differences between groups for Cg change. DTI-derived graph measures showed significant increases in Q for the no-Collar group. The Q-Collar group showed no significant changes for any graph measure in either DTI or fMRI.

Clinical Safety (Pivotal Studies):

• Primary Safety Endpoint: Incidence of serious adverse events (e.g., syncope, loss of consciousness) associated with the Q-Collar during the sports season.
  • Reported Performance (Football and Soccer Studies): No adverse events or serious adverse events (e.g., syncope, loss of consciousness, etc.) due to device use were reported during either pivotal study.

2. Sample Size and Data Provenance

The provided document does not distinguish between "test set" and "training set" in the context of algorithm development, as the device is a physical product and the studies focus on its physical and physiological effects rather than an AI/ML algorithm. Therefore, the following refers to the sample sizes for the studies conducted.

• Pilot Hockey Study:
  • Q-Collar group: n=7
  • Control group: n=8
  • Provenance: Not explicitly stated, but implies U.S. given FDA context. Prospective.
• Pilot Football Study:
  • Q-Collar group: n=31
  • Control group: n=30
  • Provenance: Not explicitly stated, but implies U.S. Prospective.
• Pilot Soccer Study:
  • Q-Collar group: n=(b) (4)
  • Control group: n=(b) (4)
  • Provenance: Not explicitly stated, but implies U.S. Prospective longitudinal.
• Pivotal Football Study (2018-1123):
  • Q-Collar group: n=(b) (4) high school male football athletes
  • Control group: n=(b) (4) high school male football athletes
  • Provenance: Not explicitly stated, but implies U.S. Prospective longitudinal.
• Pivotal Soccer Study (2018-1123):
  • Q-Collar group: n=(b) (4) high school female soccer athletes
  • Control group: n=(b) (4) high school female soccer athletes
  • Provenance: Not explicitly stated, but implies U.S. Prospective longitudinal.

3. Number of Experts and Qualifications for Ground Truth

The studies described do not involve a traditional "ground truth" derived from expert consensus for medical image interpretation or diagnosis. Instead, the "ground truth" or primary outcome measures are objective, quantitative changes in DTI and fMRI metrics. These metrics are derived from advanced imaging techniques and statistical analyses performed by researchers. The expertise required would be in neuroimaging physics, data analysis, and interpretation, typically performed by trained radiologists, neuroradiologists, or neuroscientists.

• Number of Experts: Not specified for establishing ground truth/interpretation of imaging data. The studies imply standard research practices where imaging data is processed and analyzed by trained personnel using established protocols.
• Qualifications of Experts: Not explicitly stated but would typically involve researchers with expertise in Diffusion Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI), neuroanatomy, and statistical analysis of neuroimaging data.

4. Adjudication Method for the Test Set

Adjudication methods like 2+1 or 3+1 typically apply to subjective expert reviews (e.g., classifying medical images). Since the clinical efficacy endpoints for the Q-Collar studies rely on quantitative changes in DTI and fMRI metrics derived from image processing and statistical analysis, there is no mention of an adjudication method by human readers. The assessment is based on objective measurements and statistical significance.

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

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done. The studies compared groups of individuals wearing the Q-Collar versus control groups, assessing the effect of the device itself on neuroimaging outcomes, not the performance of human readers with or without AI assistance.

6. Standalone (Algorithm Only) Performance

No standalone (algorithm only) performance study was conducted. The Q-Collar is a physical device, and its performance is evaluated based on its effects on human physiology and brain changes, not as an AI algorithm that generates predictions or interpretations.

7. Type of Ground Truth Used

The "ground truth" in the pivotal clinical studies was based on:

• Quantitative Imaging Surrogates: Changes in Diffusion Tensor Imaging (DTI) metrics (Mean Diffusivity (MD), Axial Diffusivity (AD), Radial Diffusivity (RD), Fractional Anisotropy (FA)) and functional MRI (fMRI)-derived brain network measures (e.g., global clustering coefficient (Cg), characteristic path length (L), modularity (Q)) from pre-season to post-season. These are objective imaging biomarkers interpreted as indicators of neuroanatomical and neurophysiological changes.
• Head Impact Data: Measured by accelerometer devices affixed behind the ear, quantifying linear accelerations and rotational velocities of the head, used as a covariate.
• Safety Outcomes: Incidence of serious adverse events (e.g., syncope, loss of consciousness), which are directly observed clinical outcomes reported by participants or medical staff.

It's important to note the limitations stated by the sponsor: "The use of imaging studies as a future indicator of brain injury has not been validated" and "These changes in DTI have not been validated as a measure of brain injury or linked to clinical outcomes." Also, for fMRI, "The metrics used in the study were not those that were pre-specified, lending to uncertainty in the results."

8. Sample Size for the Training Set

Not applicable. This device is a physical product, not an AI/ML algorithm that requires a training set for model development. The sample sizes listed in section 2 refer to participants in clinical trials.

9. How Ground Truth for the Training Set Was Established

Not applicable, as no training set for an AI/ML algorithm was involved. The "ground truth" for the clinical studies (i.e., the outcome measures) was established through scientifically rigorous methods of data acquisition (MRI scans, accelerometer data) and subsequent quantitative analysis by researchers in the field.

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