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The aycan mobile software program is used to display medical images for diagnosis from CT and MRI modalities only.

aycan mobile provides wireless and portable access to medical images. This device is not intended to replace full workstations and should be used only when there is no access to a workstation.

This device is not to be used for mammography.

aycan mobile is an App for the Apple iPad. It can be used for receiving and visualization of medical images.

Here's a breakdown of the acceptance criteria and the study information based on the provided text, where available:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for the clinical studies. Instead, it generally states that the device "passed all testing criteria" and that radiologists "confirmed" its capability for diagnostic reading.

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

• Sample Size for Test Set: The document mentions "different CT and MRI studies," but does not specify the exact number of cases or images used in the clinical studies.
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: "Qualified radiologists" performed the studies, but the exact number is not specified.
• Qualifications of Experts: They were "qualified radiologists." No further details on their experience (e.g., years of experience) are provided.

4. Adjudication Method for the Test Set

• The document implies that radiologists individually confirmed the diagnostic capability. There is no mention of a specific adjudication method like 2+1 or 3+1 consensus.

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

• The document describes a clinical study where "qualified radiologists" read "different CT and MRI studies" using aycan mobile. However, it does not describe an MRMC comparative effectiveness study that assesses human readers' improvement with AI vs. without AI assistance. The study described focuses on confirming the diagnostic capability and safety/effectiveness of the aycan mobile device itself.

6. Standalone (Algorithm Only) Performance

• The aycan mobile device is described as an application for displaying medical images for diagnosis. It does not appear to be an AI algorithm in the traditional sense that performs automated detection or analysis. Therefore, a standalone (algorithm only) performance metric would not be applicable, as it's a viewing device used by a human for diagnosis.

7. Type of Ground Truth Used

• The ground truth for the clinical studies was based on the "conclusion" of "qualified radiologists" regarding the diagnostic capability, safety, and effectiveness of the device when reading CT and MRI studies. This suggests expert consensus/opinion as the basis for ground truth. There's no mention of pathology or outcomes data.

8. Sample Size for the Training Set

• Since aycan mobile is a viewing and communication system and not an AI algorithm that requires training, there is no mention of a training set sample size.

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

• As aycan mobile is not an AI algorithm requiring a training set, this information is not applicable and therefore not provided in the document.

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aycan workstation OsiriX PRO is a software device intended for viewing of images acquired from CT, MR, CR, DR, US and other DICOM compliant medical imaging systems when installed on suitable commercial standard hardware.

Images and data can be captured, stored, communicated, processed, and displayed within the system and or across computer networks at distributed locations.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation. For primary diagnosis, post process DICOM "for presentation" images must be used. Mammographic images should only be viewed with a monitor approved by FDA for viewing mammographic images.

It is the User's responsibility to ensure monitor quality, ambient light conditions, and image compression ratios are consistent with clinical application.

The aycan workstation OsinX PRO provides services for review and post processing of diagnostic medical images and information. It conforms to the DICOM 3.0 standard to allow the sharing of medical information with other digital imaging systems. aycan workstation OsiriX PRO runs on Apple Mac OSX systems and provides high performance review, navigation and post processing functionality for multidimensional and multimodality images.

aycan workstation OsiriX PRO is a software device that handles and manipulates digital medical images.

The provided text is a 510(k) Summary for the aycan workstation OsiriX PRO. It outlines the device's characteristics and its substantial equivalence to a predicate device, but it does not contain a detailed study report with specific acceptance criteria and performance data for the device itself.

Here's a breakdown of what can and cannot be extracted from the provided document based on your request:

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

• Acceptance Criteria: Not explicitly stated in terms of measurable performance metrics. The document broadly states "the predetermined acceptance criteria were met" and "The system passed all testing criteria," but the criteria themselves are not defined or quantified.
• Reported Device Performance: Not provided. There are no performance metrics or results (e.g., accuracy, sensitivity, specificity) for the aycan workstation OsiriX PRO.

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: Not mentioned.
• Data Provenance: Not mentioned.

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 mentioned. The document primarily focuses on regulatory approval and device description, not on detailed clinical validation studies.

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

• Not mentioned.

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

• Not mentioned. The document describes the device as a "software device intended for viewing of images acquired from CT, MR, CR, DR, US and other DICOM compliant medical imaging systems." It is a Picture Archiving Communications System (PACS) and an image processing system. There is no indication of AI assistance or a comparative effectiveness study involving human readers.

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

• The device described is a PACS workstation, not an AI algorithm. Its function is to display and process images for human interpretation, explicitly stating, "A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed." Therefore, a standalone algorithm-only performance study would not be applicable or relevant to this device's stated function.

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

• Not mentioned.

8. The sample size for the training set

• Not mentioned. As this is not an AI/ML algorithm that typically requires a training set, this information is not expected.

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

• Not mentioned. (See point 8)

Summary of available information regarding acceptance criteria and study:

The document states:

• "As required by the risk analysis, designated individuals performed all verification and validation activities and results demonstrated that the predetermined acceptance criteria were met. The system passed all testing criteria." (K103546, P. 2)

This indicates that internal verification and validation were conducted, and the device met its internal acceptance criteria. However, the specific details of these criteria, the study design, sample sizes, ground truth establishment, or any performance metrics are not included in this 510(k) summary. The summary focuses on demonstrating substantial equivalence to a predicate device based on its functional characteristics and intended use, rather than a detailed performance study like what would be expected for a diagnostic AI device.

Ask a specific question about this device

aycan Workstation OsiriX is a software device intended for viewing of images acquired from CT, MR, CR, DR, US and other DICOM compliant medical imaging systems when installed on suitable commercial standard hardware.

Images and data can be captured, stored, communicated, processed, and displayed within the system and or across computer networks at distributed locations.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation. For primary diagnosis, post process DICOM "for presentation" images must be used. Mammographic images should only be viewed with a monitor approved by FDA for viewing mammographic images.

It is the User's responsibility to ensure monitor quality, ambient light conditions, and image compression ratios are consistent with clinical application.

The aycan Workstation OsiriX provides services for review and post processing of diagnostic medical images and information. It conforms to the DICOM 3.0 standard to allow the sharing of medical information with other digital imaging systems. aycan workstation OsiriX runs on Apple Mac OSX systems and provides high performance review, navigation and post processing functionality for multidimensional and multimodality images.

The provided document is a 510(k) summary for the aycan Workstation OsiriX. It primarily focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and intended use. The document does not contain the specific details required to answer all parts of your request about acceptance criteria and a detailed study proving performance.

Here's what can be extracted and what is missing:

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

• Acceptance Criteria: The document states, "As required by the risk analysis, designated individuals performed all verification and validation activities and results demonstrated that the predetermined acceptance criteria were met. The system passed all testing criteria."
• Reported Device Performance: The document generally states that the device "provides high performance review, navigation and post processing functionality for multidimensional and multimodality images." However, specific quantitative or qualitative performance metrics against defined acceptance criteria are not provided.

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

• This information is not provided in the document.

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)

• This information is not provided in the document.

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

• This information is not provided in the document.

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 MRMC study or any information about AI assistance and human reader improvement is not mentioned in the document. The device is a "Picture Archiving Communications System", not an AI-powered diagnostic tool, so such a study would not be expected.

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

• The document implies human intervention, stating, "A physician, providing ample opportunity for competent human intervention interarets images and information being displayed and printed." Given that it's a PACS workstation, standalone algorithmic performance for diagnosis is not its primary function, and no such study is mentioned.

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

• This information is not provided in the document.

8. The sample size for the training set

• This information is not provided in the document. The device is a workstation, and the concept of a "training set" in the context of an AI/ML algorithm doesn't directly apply here.

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

• This information is not provided in the document, as it's not relevant to the type of device described.

Summary of what the document focuses on:

The 510(k) summary primarily demonstrates the substantial equivalence of the aycan Workstation OsiriX to a predicate device (IQ-SYSTEM PACS SYSTEM K062488). This is achieved by:

• Categorizing the device: As a "Picture Archiving Communications System" and "system, image processing, radiological" (Product code LLZ).
• Describing intended use: For viewing, capturing, storing, communicating, processing, and displaying images from various DICOM-compliant medical imaging systems.
• Highlighting technological characteristics: It's a software device conforming to DICOM 3.0, running on Apple Mac OSX, and providing review and post-processing functionality. It explicitly states it does not contact the patient or control life-sustaining devices.
• Stating compliance: It notes that appropriate verification and validation activities were performed, and predetermined acceptance criteria were met.
• Providing warnings/limitations: Regarding lossy compressed mammographic images, digitized film screen images, and the user's responsibility for monitor quality and ambient light.

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