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NEUROSCAPE is a PACS image management software intended for use with general purpose computing hardware to acquire and process images and data throughout a clinical environment. Data and images are acquired through DICOM compliant imaging devices and modalities. The system is used in hospitals, imaging centers and radiologist practices by medically trained professionals.

NEUROSCAPE accepts data from existing MRI systems, allows the selection of regions of interest as defined by a trained professional and provides a measurement of the areas or volumes associated with such selected regions. These measurements are normally used by the practitioner as an aid in the assessment of ischemic cerebral stroke patients.

NEUROSCAPE is fully integrated with most existing medical image visualization applications. The system is a multi-platform software running on any Windows or Linux operating systems.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations.

NEUROSCAPE is a medical software which helps in making informed decisions about the choice of treatment following an Ischemic Cerebral Stroke.

NEUROSCAPE enables an optimized visualization of images created by Magnetic Resonance Imaging (MRI). The device is capable of making instantaneous multi-parametric image analyses for displaying critical information such as the extent and the significance of the cerebral lesions. By providing an estimate of the lesion volume in the brain, informed decisions about whether a patient may be an appropriate candidate for thrombolytic treatment can be made.

Additionally, the display of high-definition diffusion and perfusion images and of their size change by bilinear interpolation provides the operator with an overall view of all the images, which can be efficiently and instantaneously compared. NEUROSCAPE generates a medical report, which incorporates all performed images data calculations.

The system includes the following features:

• Image Loading; .
• Image Saving:
• Image Viewing;
• Image Manipulation;
• Image Analysis; and .
• Image Processing.

The provided 510(k) summary for NEUROSCAPE does not contain specific acceptance criteria or a detailed study that proves the device meets such criteria in the way a modern regulatory submission for AI/ML-driven medical devices typically would.

NEUROSCAPE is described as a PACS image management software that aids in visualizing and analyzing MRI images for ischemic cerebral stroke. Its primary functionalities involve image loading, viewing, manipulation, processing, and analysis (specifically for lesion volume estimation) and generating medical reports.

Here's an analysis based on the provided text, highlighting the absence of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not present in the provided document. The submission focuses on substantial equivalence to a predicate device (Nordic Image Control and Evaluation (nICE) Software) rather than defining specific performance metrics and demonstrating their achievement. There are no quantitative measures of accuracy, sensitivity, specificity, or volume measurement deviation.

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

This information is not present. The document mentions "extensive validation testing" but does not provide details on the test set's size, characteristics, or provenance.

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

This information is not present. There is no mention of ground truth establishment for a test set, nor the involvement of experts in that process.

4. Adjudication Method

This information is not present. There is no mention of any adjudication method for a test set.

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

This information is not present. The document does not describe any MRMC study comparing human readers with and without AI assistance. The device is presented as an aid to professionals rather than a standalone diagnostic tool or a tool for improving human reader performance in a controlled study.

6. Standalone (Algorithm Only) Performance Study

This information is not present. While the device performs "multi-parametric image analyses for displaying critical information such as the extent and the significance of the cerebral lesions" and provides "an estimate of the lesion volume," the document does not include a standalone performance study report for these analytical capabilities, independent of a human operator. The focus is on its function as a PACS system providing tools for assessment by a "trained professional."

7. Type of Ground Truth Used

This information is not present. Since no specific performance study with a test set is detailed, the type of ground truth used to validate any measurements or analyses is not mentioned.

8. Sample Size for the Training Set

This information is not present. As an image analysis and PACS software, it's not explicitly stated that NEUROSCAPE uses machine learning in the modern sense that would typically involve a "training set." The functionality described sounds more like rule-based image processing and measurement tools.

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

This information is not present for the same reasons as point 8.

Summary of what is present:

• Predicate Device: Nordic Image Control and Evaluation (nICE) Software (K063539).
• Intended Use: PACS image management software to acquire and process images/data, specifically aiding in the assessment of ischemic cerebral stroke patients by providing measurements of areas/volumes associated with selected regions on MRI images.
• Testing Mentioned: "Extensive validation testing" of the NEUROSCAPE system as a PACS system capable of reliable post-processing and display of MRI images. It states "all of the different components... have been stress tested to ensure that the system as a whole provides all the capabilities necessary to operate safely and effectively."
• Safety & Effectiveness Conclusion: Based on the comparison of intended use and technological characteristics, it is substantially equivalent to the predicate and "raises no new safety or effectiveness issues."

Conclusion:

The provided 510(k) summary is a traditional submission focused on substantial equivalence to a predicate PACS device. It describes the device's functions and intended use, but it lacks the detailed performance study information, acceptance criteria, and ground truth establishment methods typically found in submissions for AI/ML-driven devices, especially those making quantitative claims about accuracy or aiding in diagnosis. The "testing" mentioned is high-level and refers to stress testing for system functionality rather than clinical performance metrics.

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