Search Results

miPlatform medical imaging suite v3.0 (miPlaftorm v3.0) is an upgrade of miPlatform medical imaging suite v2.0, previous cleared under K131424. miPlatform v3.0 is an internet-based image management system intended to be used by trained professionals, including but not limited to physicians, nurses and medical technicians. The system is a software package that is used with general purpose computing hardware to acquire, store, distribute, process and display images and associated patient data. The software supports and performs reviewing, communication and storage from the following modalities through DICOM 3.0 standard: CT, MR, NM, US, XA, PET, DX, CR/DR, RF, RT, MG, SC, VL, ES, OP, XC, PT, OT, as well as hospital/radiology information systems and any other information systems that support DICOM 3.0 standards. Non-radiology modalities are not for diagnostic use. For radiology modalities, only FDA cleared monitors shall be used to review images for diagnostic use.

miPlatform ZFP Viewer is offered as extension application to miPlatform medical imaging suite system. This software technology uses HTML5 which allows a browser-enabled device to run the software application, and thus requires no installation (zero foot print). The user is able to access patient images and study reports from a mobile device, such as iPad3, as well as personal computer using Microsoft Windows System, anywhere through a wireless and 3G, 4G network. miPlatform ZFP Viewer has a simple GUI for viewing and includes tools such as zoom, pan, windowing, basic measurement, and 3D visualization functions, including volume rendering and multi-planar reconstruction. Only FDA cleared monitors shall be used to review images for diagnostic use.

miPlatform ZFP Viewer provides wireless and portable access to medical images, in addition to standard intranet or internet access. This device is not intended to replace full workstations and should be used only when there is no access to a workstation. When used on a mobile device, the miPlatform ZFP Viewer is not for diagnostic use.

For primary interpretation and review of mammography images, only use display hardware that is specifically designed for and cleared by the FDA for mammography. MIP/MRP tools are not supported for mammography images for diagnostic use.

miPlatform v3.0 and miPlatform ZFP Viewer is the extension application software of miPlatform medical imaging information system. User can achieve mobile office through the software which is installed in PC, smart mobile phone and other mobile terminals.

• . Understanding and analyzing patient's information and medical image in real time.
• . Processing, diagnosing and sharing images in real time. Note that when used on a mobile device, the miPlatform ZFP Viewer is not for diagnostic use.
• . Support three-dimensional image viewing and processing.
• Support image analysis and real-time data synchronization exchange in real-time conference.

The provided text describes the miPlatform medical imaging suite v3.0 and miPlatform ZFP Viewer, an image management system intended for use by trained professionals to acquire, store, distribute, process, and display medical images. The submission aims to demonstrate substantial equivalence to predicate devices, namely miPlatform Medical Imaging Suite (K131424) and CARESTREAM Vue PACS v11.4 Vue Motion (K132824).

The document details the device's indications for use, technological characteristics, and performance based on non-clinical testing. It explicitly states that performance comparison testing on retrospective images was conducted to demonstrate substantial equivalence. However, it does not provide specific acceptance criteria or detailed results in a quantitative manner. The document asserts that "all tests successfully passed" and "designated individuals performed all verification and validation activities and results demonstrated that the predetermined acceptance criteria were met. The system passed all testing criteria." This indicates a qualitative assessment against internal criteria rather than a formally presented analytical study with specific metrics.

Here's an analysis based on the given text, addressing your questions:

1. Table of Acceptance Criteria and Reported Device Performance:

   The document does not explicitly state quantitative acceptance criteria in the form of specific thresholds (e.g., sensitivity, specificity, accuracy percentages, or error margins). Instead, it broadly claims that the device "passed all testing criteria" and "all tests successfully passed" based on its software requirements specification, design verification, and validation documents.

   The "Performance" section generally states: "Support of the substantial equivalence of the miPlatform v3.0 and miPlatform ZFP Viewer device was provided as a result of software validation, which confirms all features of the miPlatform v3.0 and miPlatform ZFP Viewer device were compliant with the software requirements."

   Without specific metrics or thresholds, a direct table of acceptance criteria vs. reported performance cannot be constructed from the provided text. The document focuses on demonstrating feature parity and compliance with established standards (DICOM, HL7) and internal quality control processes.

2. Sample Size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • Sample Size: The document states that "performance comparison testing on retrospective images" was conducted, but it does not specify the sample size (number of cases or images) used for this test set.
   • Data Provenance: The data used was retrospective. The country of origin of the data is not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   The document does not provide information on the number of experts used or their qualifications for establishing ground truth. The nature of the device (an image management and viewing system) suggests that "ground truth" might pertain to accurate display, processing, and measurement capabilities rather than diagnostic accuracy against a clinical reference standard.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   The document does not specify any adjudication method for the test set.

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:

   • A multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or detailed.
   • The device being reviewed (miPlatform medical imaging suite v3.0, miPlatform ZFP Viewer) is described as an image management and viewing system, not an AI-assisted diagnostic tool. Its functionality includes displaying, processing, and measuring images. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not directly apply to the described function of this particular device. The study described is "performance comparison testing on retrospective images to help demonstrate that the proposed device is substantially equivalent to the predicate devices" in terms of its ability to perform its specified functions.

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

   The term "standalone" in the context of an algorithm's diagnostic performance is also not directly applicable here, as the device is an image management system designed for use by trained professionals, implying human-in-the-loop interaction. The non-clinical testing focused on software validation, functionality, and compliance, not on an algorithm's independent diagnostic interpretation.

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

   The document does not explicitly state the type of ground truth used. Given the device's function (image management, display, basic processing, and measurement), the "ground truth" likely refers to the accuracy of image display, correct implementation of tools (zoom, pan, windowing, measurement), and data synchronization as per DICOM standards, rather than diagnostic outcomes from pathology or long-term clinical follow-up. This "ground truth" would be established through verification against known valid image properties and expected software behavior.

8. The sample size for the training set:

   The document does not mention a training set or any machine learning/AI components that would require a distinct training set. The device is described as a software package for image management and viewing, not a predictive or diagnostic AI algorithm.

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

   Since no training set is mentioned in the context of machine learning, this question is not applicable. The ground truth for the verification and validation of the software's functionality would have been established through a combination of engineering specifications, DICOM standards, and expected behavior documented in the software requirements.

Ask a specific question about this device

miPlatform is an internet-based image management system intended to be used by trained professionals, including but not limited to physicians, nurses and medical technicians.

The system is a software package that is used with general purpose computing hardware to acquire, store, distribute, process and display images and associated data. The software performs digital image processing, analysis, reviewing, communication and storage.

miPlatform supports receiving, sending, printing, storing and displaying studies received from the following modality types via DICOM: CT, MR, NM, US, XA, PET, DX, DR, RF, RT, MG, SC, VL, as well as hospital/radiology information systems and any other information systems that support DICOM 3.0 standard.

miPlatform also supports multidimensional image visualization, measurement and analysis tools, and reporting algorithms. The user interface is designed to follow typical clinical workflow patterns to process, review, validate/edit and analyze digital images. The software supports the following image analysis options:

Vessel Analysis is an option intended for viewing or displaying vascular obstructive disease by providing a non-invasive survey of a patient's coronary or peripheral arteries. Physicians can select any artery to view the following anatomical references: the highlighted vessel in 3D, two rotate-able curved MPR vessel views displayed at angles orthogonal to each other, and cross sections of the vessel. Physicians can manually measure the lumen width to obtain percentage stenosis calculations. In addition, clinicians can manually measure vessel length along the centerline in standard curved MPR views and examine Houndsfield unit or signal intensity statistics.

Coronary Calcium Scoring is an option intended for cardiac scoring from CT image derived measurements, including non-invasive detection and quantification of atherosclerotic plaque. Physicians can use semi-automatic tools in Coronary Calcium Scoring to mark calcified lesions of coronary arteries, and automated computation of Agatston scoring will be performed and presented in a report.

miPlatform supports a real-time image-based conference option with integrated audio/video capability. Multiple users may log into the system and participate in the conference from different locations via internet connection.

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 cleared monitor that meets technical specifications reviewed and accepted by FDA.

miPlatform is an internet-based image management system intended to be used by trained professionals, including but not limited to physicians, nurses and medical technicians.

The system is a software package that is used with general purpose computing hardware to acquire, store, distribute, process and display images and associated data. The software performs digital image processing, analysis, reviewing, communication and storage.

miPlatform supports receiving, sending, printing, storing and displaying studies received from the following modality types via DICOM: CT, MR, NM, US, XA, PET, DX, DR, RF, RT, MG, SC, VL, as well as hospital/radiology information systems and any other information systems that support DICOM 3.0 standard.

miPlatform also supports multidimensional image visualization, measurement and analysis tools, and reporting algorithms. The user interface is designed to follow typical clinical workflow patterns to process, review, validate/edit and analyze digital images. The software supports the following image analysis options: Vessel Analysis and Coronary Calcium Scoring.

miPlatform supports a real-time image-based conference option with integrated audio/video capability.

The provided 510(k) summary for the "miPlatform medical imaging suite" (K131424) primarily focuses on demonstrating substantial equivalence to predicate devices through software validation and performance comparison rather than presenting specific acceptance criteria and a detailed study explicitly proving those criteria were met for standalone performance.

Here's an analysis based on the provided text:

1. Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria for features like "Vessel Analysis" or "Coronary Calcium Scoring." Instead, it relies on general statements about successful passing of tests and compliance with software requirements.

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

The document states: "In addition, we conducted the performance comparison testing on retrospective images to help demonstrate that the proposed device is substantially equivalent to the predicate devices." (Page 3)

• Sample Size for Test Set: Not specified.
• Data Provenance: Retrospective images. The country of origin is not specified.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

Not specified. The document only mentions "physicians" and "clinicians" in the context of using the device's measurement tools. There is no information about experts used to establish a ground truth for testing.

4. Adjudication Method for the Test Set:

Not specified.

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

No MRMC study is mentioned. The document primarily focuses on the device's standalone performance and its equivalence to predicate devices, without discussing AI assistance for human readers.

6. Standalone Performance Study:

Yes, a standalone (algorithm only without human-in-the-loop performance) study was indicated, though details are scarce. The document states:

• "Support of the substantial equivalence of the miPlatform device was provided as a result of software validation, which confirms all features of the miPlatform device were compliant with the software requirements." (Page 3)
• "Testing involved system level functionality test, segmentation accuracy test, measurement accuracy test, interfacing test, usability test, serviceability test, labeling test, as well as the test for risk mitigation method analyzed and implemented in the risk management process." (Page 3)
• "Performance Data from nonclinical Testing: Designated individuals performed all verification and validation activities and results demonstrated that the predetermined acceptance criteria were met. The system passed all testing criteria." (Page 4)

These statements suggest that tests were conducted on the software itself to ensure its functions (segmentation, measurement, etc.) met requirements.

7. Type of Ground Truth Used:

The type of ground truth used for specific features like "Vessel Analysis" (lumen width, percentage stenosis calculation, vessel length, Hounsfield unit/signal intensity statistics) and "Coronary Calcium Scoring" (Agatston scoring) is not explicitly detailed. Given the mention of "segmentation accuracy test" and "measurement accuracy test," it's implied that there were reference measurements or segmentations against which the device's outputs were compared. However, it's not specified if this ground truth came from expert consensus, pathology, or another source.

8. Sample Size for the Training Set:

Not applicable. The document does not mention any machine learning or AI models requiring a training set in the context of the device's primary functions described. The focus is on a Picture Archiving and Communications System (PACS) with analytical tools rather than a predictive AI algorithm.

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

Not applicable, as no training set is mentioned.

Ask a specific question about this device