Search Results

The Fujifilm Digital Mammography System, Aspire HD (FDR MS-1000), generates full-field digital mammography images that can, as other full-field digital mammography systems, be used for screening and diagnosis of breast cancer and is intended for use in the same clinical applications as traditional screen-film mammography systems.

The Aspire HD is an integrated FFDM system combining an X-ray system made by Siemens with Fujifilm's a-Se detector and Acquisition Workstation (AWS). The Aspire HD creates digital mammography images by direct capture of x-ray energy using the a-Se detector is a Fujifilm design utilizing an exclusive dual layer a-Se scintillator with Direct Optical switching circuitry to acquire image data and transfer images to the AWS for automated post processing, technologist preview and QC, and subsequent transmission to hard copy printers, diagnostic workstations and archiving systems. The Aspire HD provides automated compression and one AEC mode.

The Aspire HD Acquisition Workstation (FDR 1000AWS) includes an off the shelf personal computer, the application software, either Microsoft Vista or Windows 7 Operating System, a Smegapixel portrait type monitor, and a hub. The hub transmits signals between the personal computer and control cabinet, and between the personal computer and exposure stand.

The AWS display primarily consists of three windows:

• Patient Information Input window .
• Exposure Menu Selection window t
• . Study window.

The user may switch between these windows depending on the operation being performed. The X-ray control panel, which controls and observes the exposure stand, is always displayed in the lower part of each window. This allows setting the exposure conditions and confirming the radiation conditions on a single view.

Here's an analysis of the provided text regarding the FUJIFILM Aspire HD Full-Field Digital Mammography X-ray System, focusing on the acceptance criteria and the study that proves the device meets them.

It's important to note that the provided documents are a 510(k) Summary and the FDA's Substantial Equivalence letter. These documents typically focus on demonstrating equivalence to a predicate device rather than presenting a detailed clinical study with explicit acceptance criteria and corresponding performance metrics for an AI algorithm. Since this device is a digital mammography system itself and not an AI-based diagnostic tool, the interpretation below will reflect the information provided for such a system.

Acceptance Criteria and Device Performance

The provided text does not contain a typical "acceptance criteria table" with specific quantitative metrics (e.g., sensitivity, specificity, AUC) and corresponding reported performance values that would be expected for an AI diagnostic device. Instead, for a digital mammography system, the "acceptance criteria" are implied by demonstrating substantial equivalence to predicate devices through technical comparisons and a qualitative clinical image attribute review.

Implicit Acceptance Criteria and Reported Performance (for a digital mammography system):

Study Details

1. Sample size used for the test set and the data provenance:

   • Sample Size: Six (6) image sets of screening and diagnostic cases.
   • Data Provenance: Not explicitly stated, but clinical cases are implied. The country of origin and whether the data was retrospective or prospective are not mentioned.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: "independent mammographic radiologists" (number not specified, but plural indicating more than one).
   • Qualifications: "independent mammographic radiologists." Specific experience (e.g., 10 years) is not detailed.

3. Adjudication method for the test set:

   • The document states an "image attribute review was conducted by independent mammographic radiologists." The specific adjudication method (e.g., 2+1, 3+1) is not provided. It seems to have been a collective review or consensus among the independent radiologists.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, an MRMC comparative effectiveness study involving AI assistance was not done. This document pertains to a device (mammography system), not an AI algorithm intended to assist human readers. The clinical review was to assess the image quality of the Aspire HD system itself, not its impact on human reader performance with or without AI.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • No, this is not applicable. The Aspire HD is a full-field digital mammography X-ray system, not a standalone algorithm. The "performance" being assessed is the system's ability to produce diagnostically acceptable mammographic images.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The "ground truth" for the image attribute review was based on the expert opinion/consensus of independent mammographic radiologists regarding the "sufficiently acceptable quality for mammographic use" of the images. It was not based on pathology or outcomes data in the typical sense of a diagnostic accuracy study.

7. The sample size for the training set:

   • Not applicable. This document describes a medical imaging device (hardware and integrated software for image acquisition), not a machine learning model that relies on a "training set" in the context of AI. The system itself undergoes design and engineering, but doesn't have a data-driven "training set" like an AI algorithm would.

8. How the ground truth for the training set was established:

   • Not applicable, as there is no "training set" for this device in the context of AI development.

Ask a specific question about this device