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Prima is a software application that is intended for use in receiving, processing, manipulating, displaying, printing, and archiving mammography images as well as other medical images and data (e.g. US and MR). Images and data can be stored, communicated, and displayed within the system or across computer systems. Prima provides various image processing and measurement tools to facilitate the interpretation of mammography x-ray, breast tomosynthesis, and other multimodality DICOM medical images and enable diagnosis. Lossy compressed mammographic 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 the FDA.

Prima is typically used by trained professionals, including radiologists, oncologists, surgeons, technologists and clinicians and may provide information to be used for screening and diagnostic procedures.

Prima is a software application that is intended for use in receiving, processing, manipulating, displaying, printing, and archiving mammography images as well as other medical images and data (e.g. US and MR). Images and data can be stored, communicated, and displayed within the system or across computer systems. Prima provides various image processing and measurement tools to facilitate the interpretation of mammography x-ray, breast tomosynthesis, and other multimodality DICOM medical images and enable diagnosis. Lossy compressed mammographic 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 the FDA.

Prima is typically used by trained professionals, including radiologists, oncologists, surgeons, technologists and clinicians and may provide information to be used for screening and diagnostic procedures.

The provided text is a 510(k) summary for a Picture Archiving and Communication System (PACS) software called "Prima." It declares substantial equivalence to predicate devices but does not contain information about specific acceptance criteria, performance studies, or clinical trial data as requested. The summary mentions that the performance of the software was tested in accordance with Hologic's design control procedures to demonstrate intended performance and that testing was successfully conducted, and demonstrates that Prima meets all of its functional requirements and specifications. However, it does not provide details about these tests.

Therefore, I cannot fulfill your request for the specific acceptance criteria and study details. The document focuses on regulatory equivalence rather than detailed performance metrics.

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CURVE IMAGE is an internet-based, image management software (PACS) that enables dental offices to keep records of hard and soft tissue charts in a form of digital images. The system uses a Web-based interface and includes acquisition, editing and storage of digital images. Images and data can be stored, communicated, processed and displayed within the system or across computer networks at distributed locations. Images can be acquired from standard dental imaging devices, or can be uploaded directly from the user's computer. Images can be edited (e.g., zoomed, contrast, rotated, etc.), as well as exported. The system is designed to provide images for diagnostic use.

Curve Image is a web-based dental practice image management system that provides Internet access to an image library for each patient in a practice. It also provides tools for dental practices to manipulate patient images and both acquire and upload new images in industry standard formats. Images can be annotated and tagged, and are available for both diagnostic and non-diagnostic use. All of these actions are performed from a secure website, after entering user credentials, similar to other commonly used online applications. The system can be accessed by the user via an internet connection and does not require any software installation on the user's computer.

Curve Image may be sold as a stand-alone product, or may be bundled with a suite of web applications to form a comprehensive dental practice management application called HERO.

The provided text describes a 510(k) submission for the "Curve Image" dental PACS system. However, the document does not contain specific acceptance criteria, performance metrics (like sensitivity, specificity, accuracy), sample sizes for test or training sets, details on expert ground truth establishment, or clinical study results typical for AI/ML device evaluations.

The document focuses on demonstrating substantial equivalence to predicate devices by comparing intended use, environment of use, performance characteristics, and technological characteristics. This type of submission relies on the similar nature of the device to already-cleared devices, rather than a clinical trial demonstrating new performance.

Therefore, many of the requested sections regarding acceptance criteria and study details cannot be filled from the provided text.

Here's an analysis of what information is available:

1. A table of acceptance criteria and the reported device performance

• Acceptance Criteria: Not explicitly stated in terms of performance metrics (e.g., sensitivity, specificity, F1 score, AUC). The "acceptance criteria" for this 510(k) is implicitly demonstrating substantial equivalence to the predicate devices through a comparison of features and capabilities, and successful non-clinical testing.
• Reported Device Performance:
  • Non-Clinical Testing Summary: "Curve Dental, Inc. has conducted extensive non-clinical and validation testing of the Curve Image system, as a PACS system that is capable of providing reliable post-processing and display of images for dental applications. All of the different components of the Curve Image software have been stress tested to ensure that the system as a whole provides all the capabilities necessary to operate in a manner substantially equivalent to the predicate devices."
  • Tests performed included:
    • Product Risk Assessment
    • Software modules verification tests
    • Software validation test

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

• Not provided. This document does not detail specific image datasets used for a "test set" in the context of clinical performance evaluation. The non-clinical testing is described generally as "software modules verification tests" and "software validation test" without specifying sample sizes for images or data.
• The device is a PACS system, so it manages images from "standard dental imaging devices" or uploads from the user's computer, implying a wide range of potential data, but not a specific test set.

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)

• Not applicable. This information is not relevant to a 510(k) submission for a PACS system that acts as an image management tool, not an AI diagnostic aid requiring expert-established ground truth for its own diagnostic performance. The device is for "diagnostic use" by dental professionals, but it doesn't perform automated diagnosis itself.

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

• Not applicable. See point 3.

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

• No. This type of study is not mentioned or undertaken for this device. The Curve Image system is a PACS, not an AI diagnostic tool designed to assist human readers directly in interpretation (beyond displaying images clearly and providing basic manipulation tools).

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

• Not applicable. The device is a Picture Archiving and Communications System (PACS); it is not an AI algorithm performing diagnostic tasks. Its performance is related to its functionalities as an image management system.

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

• Not applicable. For a PACS system, the "ground truth" would relate to its ability to accurately store, retrieve, display, and manipulate images, which is assessed through software validation and verification, not against clinical ground truth like pathology for specific diagnoses.

8. The sample size for the training set

• Not provided. The device is not an AI/ML system that undergoes "training" in the traditional sense on a dataset. It's a software application.

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

• Not applicable. See point 8.

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The PetaVision is a device that provides one or more capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images. The software components provide functions for performing operations related to Image manipulation, enhancement, compression or quantification. And Images may be acquired from imaging devices such as CR, CT, MR and other devices. This device is not intended for mammographic applications.

PetaVision™ is PACS (Picture Archiving and Communication System) software for radlologist and physician doctor. By use of PetaVision™ enables images such as xray and scans to be stored electronically and viewed on screens. Doctors and other health professional can access and compare images at the touch of a button Also, PetaVision™ is a device that provides one or more capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images. The software components provide functions for performing operations related to image manipulation, enhancement, compression or quantification. And Images may be acquired from imaging devices such as CR, CT, MR and other devices.

The provided text is a 510(k) summary for the PetaVision PACS device. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance studies against specific acceptance criteria. Therefore, much of the requested information regarding acceptance criteria, study design, and performance metrics is not available in this document.

Here's an analysis of the provided information concerning the acceptance criteria and study, with clear indication of what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: Specific, measurable acceptance criteria (e.g., image display accuracy, processing speed, data transfer rates, system uptime, error rates). Quantitative performance results against such criteria.

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

Not provided. The document does not describe any specific test set of medical images or patient data used for evaluating the PetaVision device.

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

Not applicable/Not provided. Since no specific test set or clinical evaluation is described, there's no mention of experts establishing ground truth for such a test. The device is a Picture Archiving and Communication System (PACS) and its primary function is display and management, not diagnostic interpretation in itself.

4. Adjudication Method for the Test Set

Not applicable/Not provided. As no test set is detailed, no adjudication method is mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No. This document does not describe an MRMC comparative effectiveness study. PACS systems typically do not undergo MRMC studies in the same way diagnostic AI algorithms do, as their primary function is infrastructure (display, storage, transfer) rather than direct diagnostic interpretation assistance. The efficacy claim is based on substantial equivalence to an existing PACS.

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

Yes, implicitly. The device itself, PetaVision, is a standalone software system. Its function is to perform operations related to image manipulation, enhancement, compression, transfer, display, and storage without direct human intervention in the execution of these underlying software functions. However, its overall utility is in supporting human radiologists and physicians. No performance study of the algorithm in isolation (e.g., measuring its success rate in image acquisition or display) is detailed in this summary. Instead, the focus is on the functions it provides.

7. The Type of Ground Truth Used

Not applicable/Not provided. As no specific evaluation of diagnostic performance against objective ground truth (e.g., pathology, outcomes data) is presented, the concept of "ground truth" as it pertains to diagnostic accuracy is not relevant here. The device's "ground truth" would be its ability to correctly perform its stated functions (e.g., display an image accurately as originally acquired), but this is not explicitly detailed as a ground truth in the context of a performance study in this summary.

8. The Sample Size for the Training Set

Not applicable/Not provided. PetaVision is described as a Picture Archiving and Communication System (PACS) software. It is not an AI/ML algorithm that requires a "training set" in the conventional sense for learning patterns or making diagnostic predictions. Its functionality is based on established DICOM standards and imaging processing techniques.

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

Not applicable/Not provided. As stated above, this device is not an AI/ML algorithm requiring a training set with established ground truth.

Summary of Device and Study as Per Provided Text:

The PetaVision is a Picture Archiving and Communication System (PACS) software designed to acquire, transfer, display, store, and digitally process medical images from various modalities (CR, CT, MR, etc.). It facilitates image manipulation, enhancement, compression, and quantification. It is not intended for mammographic applications.

The study described here is a 510(k) premarket notification aiming to demonstrate substantial equivalence to a predicate device, the MEDIFACE PACS (K010259). The document concludes that PetaVision is safe and effective and substantially equivalent to the predicate device based on the information provided in the premarket notification. This type of submission relies on comparing design, indications for use, technological characteristics, and performance data (if available) to an already cleared device, rather than conducting a de novo clinical performance study against specific acceptance criteria.

The submission does not provide details on specific performance metrics, sample sizes for test sets, data provenance, expert qualifications for ground truth, adjudication methods, or results of MRMC or standalone performance studies against defined acceptance criteria. It primarily focuses on defining the device's functions and claiming equivalence to a predicate PACS system.

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