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This device is intended for automatic labelling, visualization and volumetric quantification of segmentable brain structures and lesions from a set of MR images. Volumetric data may be compared to reference percentile data.

SwiftSight-Brain is a fully automated MR image analysis software that provides automatic labeling, visualization, and volumetric quantification of brain structures from a set of MR images and returns segmented images and morphometric reports. The resulting output is provided in morphometric reports that can be displayed on Picture Archive and Communications Systems (PACS). The high throughput capability makes the software suitable for use in routine patient care as a support tool for clinicians in assessment of structural MRIs.

SwiftSight-Brain provides morphometric measurements based on 3D T1 weighted MRI series. The output of the software includes volumes that have been annotated with color overlays, with each color representing a particular segmented region, and morphometric reports that provide comparison of measured volumes to age and gender-matched reference percentile data. In addition, the adjunctive use of the T2 weighted FLAIR MR series allows for improved identification of some brain abnormalities such as lesions, which are often associated with T2 weighted FLAIR hyperintensities.

SwiftSight-Brain processing architecture includes a proprietary automated internal pipeline that performs segmentation, volume calculation and report generation.

The results are displayed in a dedicated graphical user interface, allowing the user to:

• Browse the segmentations and the measures
• Compare the results of segmented brain structures to a reference healthy population
• Read, download and print a PDF report

Additionally, automated safety measures include automated quality control functions, such as scan protocol verification, which validate that the imaging protocols adhere to system requirements.

Here's a breakdown of the acceptance criteria and study details for SwiftSight-Brain, extracted from the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance for SwiftSight-Brain

1. Table of Acceptance Criteria and Reported Device Performance

For 3D T1 Weighted Images (Brain Structures):

For T2 Weighted FLAIR Images (Brain Lesions):

2. Sample Sizes and Data Provenance

For 3D T1 Weighted Images:

• Test Set Sample Size: 72 cases for accuracy, 72 cases for reproducibility.
• Data Provenance: Subjects were collected from multiple countries, including the United States, the United Kingdom, China, and Germany. The data primarily sourced from U.S. hospitals. Retrospective.
• Specifics: Test dataset included MR images from Philips (54 subjects), Siemens Healthineers (53 subjects), and GE (37 subjects) scanners, using both 1.5T and 3.0T field strengths. Ages ranged from 20s to 90s. Included healthy subjects, mild cognitive impairment patients, Alzheimer's disease patients, and small vessel disease patients.

For T2 Weighted FLAIR Images:

• Test Set Sample Size: 160 cases for accuracy, 85 cases for reproducibility.
• Data Provenance: Subjects were collected from multiple countries, including the United States, Brazil, and Republic of Korea. The data primarily sourced from U.S. hospitals. Retrospective.
• Specifics: Test dataset included MR images from Philips (92 subjects), Siemens Healthineers (65 subjects), and GE (88 subjects) scanners, using both 1.5T and 3.0T field strengths. Ages ranged from 20s to 90s. Included healthy subjects, mild cognitive impairment patients, Alzheimer's disease patients, and small vessel disease patients.

3. Number of Experts and Qualifications for Ground Truth Establishment (Test Set)

• Number of Experts: Two neuroradiologists and one neurologist.
• Qualifications: U.S. based. No specific years of experience or board certifications are mentioned in the provided text, only their specialties.

4. Adjudication Method for the Test Set

The adjudication method for establishing ground truth from the multiple experts is not explicitly stated in the provided text. It mentions that ground truth was "established by the U.S. based two neuroradiologists and one neurologist," but doesn't detail how their individual interpretations were combined (e.g., majority vote, consensus meeting, primary reader with adjudication by others).

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

No MRMC comparative effectiveness study was mentioned in the provided text. The study focused on standalone algorithm performance against expert ground truth. Therefore, no effect size for human readers improving with AI vs. without AI assistance is available from this document.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone (algorithm only) performance study was done. The document describes the evaluation of SwiftSight-Brain's segmentation accuracy and reproducibility by comparing its output directly against expert manual segmentations (ground truth). It does not describe any human-in-the-loop performance evaluation for the clearance.

7. Type of Ground Truth Used

The ground truth for both 3D T1 weighted and T2 weighted FLAIR images was established by expert manual segmentations.

8. Sample Size for the Training Set

The sample size for the training set is not explicitly stated in the provided text. The document mentions that "The subjects upon whom the device was trained and tested include healthy subjects, mild cognitive impairment patients, Alzheimer's disease patients, and small vessle disease patients from young adults to elderlies," but only provides specific numbers for the test sets.

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

The method for establishing ground truth for the training set is not explicitly stated. The document only details how the ground truth for the test set was established (expert manual segmentations by two neuroradiologists and one neurologist).

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