Search Results

The Picker Diffusion-Weighted MR Imaging Package has been designed to image the diffusive mobility of water or other proton-containing molecules. One important clinical application is to visualize the apparent loss of mobility of water molecules in brain tissue affected by acute stroke. Areas of decreased diffusion, as is observed in acute cerebral infarcts, appear as areas of higher image intensity.

Diffusion-weighted MR pulse sequences are more accurate than conventional MRI pulse sequences in identifying the occurrence of acute stroke during the first 24 hours after onset of symptoms.

The Picker Diffusion-Weighted MR Imaging Package does not change the technological characteristics of the Picker MR Systems. This package consists of echo-planar imaging (EPI) single-shot based sequences which have selectable directionality and either fixed or selectable b-values. The sequences are basically spin-echo sequences which have large gradient pulses or lobes before and after the 180° RF refocusing pulse.

The provided document is limited in the information it offers regarding acceptance criteria and detailed study data. This appears to be a 510(k) summary, which often relies on demonstrating substantial equivalence to a predicate device rather than presenting extensive de novo performance studies.

Here's an analysis based on the available text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria (e.g., specific sensitivity, specificity, or image quality metrics) or report performance against such criteria for the new device. Instead, it relies on demonstrating substantial equivalence to predicate devices. The "Performance Specifications" for the new device are listed as "Same" as the predicate device (K954646).

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

The document does not report any specific test set sample size or data provenance (e.g., country of origin, retrospective/prospective) for a study performed directly on the "Picker Diffusion-Weighted MR Imaging Package." The entire submission is based on demonstrating substantial equivalence to previously approved devices.

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

Not Applicable. Since no specific test set study on the new device is described, there's no mention of experts or their qualifications for establishing ground truth. The substantial equivalence argument relies on prior approvals of predicate devices.

4. Adjudication Method for the Test Set

Not Applicable. No test set study for the new device is detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No. The document does not describe an MRMC study or any comparative effectiveness study with or without AI assistance. This device predates the widespread use of AI in medical imaging interpretation, and the focus is on a new imaging sequence.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, implicitly. The device itself is an imaging sequence, not an interpretative algorithm. Its performance is inherent in its ability to generate images that show "areas of decreased diffusion...as areas of higher image intensity" for acute stroke. The claim that "Diffusion-weighted MR pulse sequences are more accurate than conventional MRI pulse sequences in identifying the occurrence of acute stroke during the first 24 hours after onset of symptoms" is a standalone performance claim, but it refers to the class of DWI sequences, not a specific study on this particular Picker package. The documentation does not provide a standalone performance study for this specific package.

7. The Type of Ground Truth Used

For the claim about DWI's accuracy in identifying acute stroke, the ground truth would typically be clinical diagnosis of acute stroke, often confirmed by follow-up imaging, clinical course, or potentially pathology if available, but the document doesn't specify. For the substantial equivalence argument, the "ground truth" is that the predicate devices were deemed safe and effective based on their prior submissions, which would have had their own ground truth methods.

8. The Sample Size for the Training Set

Not Applicable. This device is an MRI sequence, not a machine learning algorithm, so there is no "training set."

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

Not Applicable. As there is no training set, there is no ground truth for it.

Ask a specific question about this device