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Diffusion Weighted Imaging is intended for use in generating unique contrast/information about the diffuse mobility of water or other proton containing molecules. Changes in mobility of the apparent diffusion coefficients in tissue can be seen much earlier phase than originally possible with conventional proton density, T1 or T2 weighted imaging. This change indicates neurological anomalies, of which diagnosis of acute stroke is one of the important applications.

Diffusion Weighted Imaging generates contrast/information about the apparent diffusion coefficients that reflect the anisotropic nature of tissue composition (e.g. fiber tracts in brain white matter) that otherwise cannot be visualized by conventional proton density, T1 or T2 weighted imaging.

Sensitivity to diffusion has been induced by applying two identical large magnetic field gradient pulses, socalled diffusion gradients, to the basic (SE or SE-EPI) pulse sequences.

One diffusion gradient is applied before the 180 degree refocussing RF pulse and the second after the 180 degree RF pulse. During imaging static spins will be dephased as a result of the first applied diffusion gradient followed by complete rephasing by the second gradient pulse. If the molecules are moving inbetween the two diffusion gradients, non-complete rephasing will occur, resulting in the diffusion weighting. Diffusion Weighted Imaging (DWI) on the Philips Gyroscan NT systems is offered in the following two optional packages:

• Diffusion package: allowing basic DWI sequences, based on Spin Echo (SE) sequences in combination . with motion reduction techniques.
• Extended Diffusion Package: allowing faster acquisition as DWI is based on Spin Echo Planar ● Imaging (SE-EPI) sequences with motion rechniques. Both Single Shot Diffusion EPI as well as multi-shot Diffusion EPI versions are possible.

The provided 510(k) summary does not contain information about acceptance criteria or a study that proves the device meets those criteria. The document describes the device, its intended use, technological characteristics, and claims substantial equivalence to predicate devices, but it does not present performance data or clinical study results.

Therefore, I cannot provide a table of acceptance criteria and reported device performance or other details about a study.

Here's a breakdown of why the requested information is absent from the provided text:

• Acceptance Criteria and Reported Device Performance: This type of information would typically be presented as quantitative metrics (e.g., sensitivity, specificity, accuracy, signal-to-noise ratio, spatial resolution) with target values and the device's demonstrated achievement of those values. The document only discusses general improvements in detecting neurological anomalies earlier.
• Sample Size and Data Provenance (Test Set): No test set with specific numbers of cases or their origin (country, retrospective/prospective) is mentioned.
• Number of Experts and Qualifications (Ground Truth): There is no mention of experts establishing ground truth or their qualifications.
• Adjudication Method: No adjudication method is described.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: The document does not describe any study comparing human readers with and without AI assistance.
• Standalone Performance Study: While the device itself is a standalone imaging package, the document does not present a standalone performance study with specific metrics. It talks about the capabilities of the diffusion-weighted imaging but not its performance in a structured study.
• Type of Ground Truth Used: The document doesn't specify how the "truth" of neurological anomalies or diffusion coefficient changes would be established for any performance evaluation.
• Sample Size for Training Set: No training set is mentioned as this device is a new imaging sequence for an existing MRI system, not an AI/CAD device that requires a training set.
• How Ground Truth for Training Set was Established: Not applicable as no training set is mentioned.

The document primarily focuses on demonstrating substantial equivalence to predicate devices by highlighting that the new sequences are extensions of existing, approved MRI techniques and do not introduce new safety risks. This is a common approach for 510(k) submissions where the technology is an evolution rather than a completely novel device with entirely new performance metrics to establish.

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