(23 days)
DEMASQ Imaging Software Device™ is a software device that receives medical images and data from various imaqing sources (including but not limited to CT. MR. US, RF units, computed and direct radiographic devices, and secondary capture devices, (scanners, imaging gateways or imaging sources). Images and data can be stored. communicated, processed and displayed within the system or across computer networks at distributed locations.
Only pre-processed DICOM for presentation images can be interpreted for primary image diagnosis in mammography.
Lossy compressed Mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA. Typical users of this system are trained professionals, e.g. physicians, radiologists, nurses, medical technicians, and assistants.
DEMASQ Imaging Software Device™ (DISD) is a user network and or a web-based PACS DICOM viewing software running on an IBM Compatible PC with a Windows 98 SE, Windows NT 4.0 (with SP 5 or later), XP or Vista operating system.
DISD is adapted for, storing, processing, routing and report generating. DISD supports the DICOM standard. To assist interpretation a user-friendly interface will allow the enduser to color, crop, zoom, rotate, measure and save the image. Images can be saved to a desktop or network as a standard file format.
DISD allows users to take full advantage of the radiographic images from digital X-ray and various modalities in order to obtain invaluable mission critical diagnostic data and images.
This 510(k) submission for the DEMASQ Imaging Software Device™ is a declaration of substantial equivalence to predicate devices, rather than a submission for a novel device requiring extensive clinical studies to demonstrate performance against acceptance criteria. Therefore, the information provided focuses on demonstrating similar technological characteristics and intended use to existing, FDA-cleared devices, rather than establishing new performance metrics through a dedicated study.
Based on the provided text, a detailed study proving the device meets specific acceptance criteria, as one would expect for a new diagnostic algorithm or AI product, is not present or described.
Here's an analysis based on the structure requested, noting the absence of certain information:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria: Not explicitly stated as quantifiable performance metrics (e.g., sensitivity, specificity, accuracy) for a diagnostic task. The "acceptance criteria" for this type of device (a PACS/DICOM viewer) are implicitly tied to its ability to perform its stated functions effectively and be substantially equivalent to predicate devices. These functions include:
- Receiving medical images and data from various imaging sources.
- Storing, communicating, processing, and displaying images and data.
- Supporting DICOM standard.
- Providing user-friendly interface for color, crop, zoom, rotate, measure, and save images.
- Allowing full advantage of radiographic images from digital X-ray and various modalities.
Reported Device Performance:
The submission asserts that the DEMASQ Imaging Software Device™ (DISD) has essentially the same technological characteristics, general function, application, and intended use as its predicate devices (INFINITT G3 PACS and XEBRA DICOM IMAGE BROWSER). This claim of substantial equivalence serves as the primary "performance" assertion for this type of device.
| Feature/Criterion (Implicit) | DEMASQ Imaging Software Device™ Performance (Claimed) |
|---|---|
| Technological Equivalence to Predicates | "Essentially the same technological characteristics" as INFINITT G3 PACS (K052545) and XEBRA DICOM IMAGE BROWSER (K071894). |
| Functional Equivalence | "Essentially the same... general function, application, and intended use" as predicates. Includes: advanced reviewing (contrast, magnification), parameter evaluation (pixel values, measurements), remote diagnoses, Ethernet/TCP/IP/DICOM 3.0 data acquisition, Windows UI, internal DICOM 3.0 handling, on-line help. |
| Image Handling & Modalities | Receives medical images and data from CT, MR, US, RF units, computed and direct radiographic devices, and secondary capture devices. Stores, communicates, processes, and displays these within the system or across computer networks. |
| DICOM Compliance | Supports DICOM standard. Internal handling of images in DICOM 3.0 format. DICOM 3.0 radiology image file standards for data acquisition. |
| Image Manipulation Tools | User-friendly interface allows color, crop, zoom, rotate, measure, and save images. |
| Operating System Compatibility | Runs on IBM Compatible PC with Windows 98 SE, Windows NT 4.0 (SP 5+), XP, or Vista. |
| Maneuver to avoid lossy compressed mammography review* | Only pre-processed DICOM for presentation images can be interpreted for primary image diagnosis in mammography. Lossy compressed Mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA. |
*These are limitations/warnings on use, not performance metrics.
2. Sample Size Used for the Test Set and Data Provenance
The provided document describes a 510(k) submission for a Picture Archiving Communications System (PACS) software, which is a medical image viewing and management device. It aims to demonstrate substantial equivalence to existing predicate devices, not to prove the statistical performance of a novel diagnostic algorithm.
Therefore, there is no mention of a specific "test set" of medical images used to evaluate the device's diagnostic performance in the way one would test an AI algorithm. The evaluation focuses on functional comparisons to predicate devices and adherence to standards.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
Since there is no "test set" for diagnostic performance, there is no mention of experts or ground truth establishment related to diagnostic accuracy for this device in the provided text.
The "experts" involved are implied to be "trained professionals, e.g. physicians, radiologists, nurses, medical technicians, and assistants" as typical users who interpret images and information displayed by the system, providing "ample opportunity for competent human intervention." These are users, not experts establishing ground truth for the device's internal performance.
4. Adjudication Method for the Test Set
Given the absence of a test set for diagnostic performance, there is no adjudication method described in the submission.
5. 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
This submission is for a PACS viewing software, not an AI-assisted diagnostic tool. Therefore, no MRMC comparative effectiveness study was done and no effect size for human reader improvement with AI assistance is reported in this document. The device is a "viewer," and human interpretation is still paramount.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is a PACS viewing software, not a standalone diagnostic algorithm. Therefore, no standalone performance study was done for an algorithm without human-in-the-loop performance. The document explicitly states: "A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed."
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
Since there is no diagnostic performance study, no type of ground truth is mentioned as being used to evaluate the device's diagnostic capabilities.
8. The Sample Size for the Training Set
This submission is for a PACS viewing software, not a machine learning algorithm requiring a training set. Therefore, there is no training set mentioned in the provided document.
9. How the Ground Truth for the Training Set Was Established
As there is no training set for an AI algorithm, there is no mention of how ground truth for a training set was established.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).