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iCare ALTIUS CW is a Medical Device Software indicated for the review, processing and analysis of ophthalmic medical images, for the review of video, clinical and diagnostic data, measurements and reports, generated by ophthalmic medical devices or documentation system through computerized networks, to support trained healthcare professionals in the diagnosis and monitoring of several eye pathologies.

iCare ALTIUS CW is a cloud-based software application with a web-based interface able to:

• review medical ophthalmic images, including videos,
• digitally process images,
• review diagnostic data, clinical information and reports,
  from ophthalmic diagnostic instruments. CW does not perform automated image analysis but provides advanced imaging manipulation tools.
  CW allows to review and process diagnostic data and multiple images with different formats (e.g. PDFS, JPEG, ...) and provides the following features:
• image manipulation filters such as zooming, changing brightness and contrast and gamma, RGB filtering,
• side-by-side image comparison (detached or synchronized mode) with different layouts,
• advanced imaging tools, such as flicker between different pictures and mosaics of several images,
• review and print reports generated by ophthalmic devices.
  CW integrates with PACS software systems, which provide the medical images and reports, to be analysed by the CW. The patient data and medical images exchange between CW and PACS is done through computerized networks using secured network communication.
  The web-based interface of CW is designed to be used through a desktop PC or a laptop using keyboard and mouse (further details in the technical requirements section).
  The User Interface is available in the languages required by the applicable regulatory requirement of the country where the device is placed on the market.

The iCare ALTIUS CW device is a Medical Device Software indicated for the review, processing, and analysis of ophthalmic medical images, video, clinical and diagnostic data, measurements, and reports generated by ophthalmic medical devices or documentation systems. It aims to support trained healthcare professionals in the diagnosis and monitoring of various eye pathologies.

The provided text does not contain detailed acceptance criteria or a comprehensive study report with specific performance metrics and statistical results. It describes the device, its intended use, and states that "Software Verification and Validation Testing" was conducted, and "documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, 'Content of Premarket Submissions for Device Software Functions.'" However, it does not specify what those acceptance criteria were, what the reported device performance against those criteria was, or provide the specifics of the study methodology (e.g., sample sizes, ground truth establishment, expert qualifications, etc.).

Therefore, I cannot fully answer your request based on the provided input.

However, I can extract the available information and highlight what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample size for test set: Not specified.
• Data provenance: Not specified.

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

• Number of experts: Not specified.
• Qualifications of experts: Not specified.

4. Adjudication method for the test set

• Adjudication method: Not specified.

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

• MRMC study: Not specified. The device description states, "CW does not perform automated image analysis but provides advanced imaging manipulation tools," suggesting it's primarily a viewing and processing platform rather than an AI-driven diagnostic tool in the typical sense that would necessitate an MRMC study comparing AI-assisted vs. unassisted human performance in diagnosis or detection. The capabilities listed (zooming, brightness, contrast, comparison, flickering, mosaic, cup-to-disc ratio annotation) are image manipulation and viewing tools.

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

• Standalone study: Not specified. As noted above, the device is described as a tool to "support trained healthcare professionals" and "does not perform automated image analysis." Thus, a standalone algorithm performance evaluation would not be applicable in the same way it would for an autonomous AI diagnostic system.

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

• Type of ground truth: Not specified.

8. The sample size for the training set

• Sample size for training set: Not specified. Given that the device "does not perform automated image analysis," it's unlikely to have a "training set" in the context of a machine learning algorithm.

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

• Method for establishing ground truth: Not applicable based on the device description.

Summary of what is known:

• Device Name: iCare ALTIUS CW
• Regulatory Status: K234076, Class II, Product Code NFJ
• Indications for Use: Review, process, and analyze ophthalmic medical images, video, clinical and diagnostic data, measurements, and reports to support healthcare professionals in diagnosis and monitoring of eye pathologies.
• Key Features: Image manipulation (zoom, pan, brightness, contrast, gamma, RGB filtering), side-by-side comparison, advanced imaging tools (flicker, mosaic), review/print reports, cup-to-disc ratio annotation.
• Core Functionality: Cloud-based software providing advanced imaging manipulation tools; it does not perform automated image analysis.
• Performance Data Provided: "Software Verification and Validation Testing" was conducted, and documentation complied with FDA guidance and IEC 62304.
• Conclusion: The device is substantially equivalent to the predicate (FORUM, K213527), and differences (absence of purely database features, measurements only in dimensionless units for cup-to-disc, mosaic and flickering features, different system architecture) have no effect on safety and effectiveness.

What is explicitly missing from the provided text to fully answer the request:

• Specific quantitative or qualitative acceptance criteria.
• Detailed results of the verification and validation testing against those criteria.
• Any information regarding clinical studies, test set sizes, ground truth establishment, expert qualifications, or adjudication methods.
• Information about training sets or AI performance metrics, as the device explicitly states it does not perform automated image analysis.

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CALLISTO eye Software is a software device intended for remote control of ophthalmic surgical microscopes of OPMI Lumera family and RESCAN 700, and display images of the anterior and posterior segment of the eye.

CALLISTO eye Software is indicated as graphical guidance aid to insert, align, position, and register an intraocular lens (IOL) including toric IOLs, limbal relaxing incisions, and capsulorhexis during anterior segment surgical procedures.

CALLISTO eye software operates as an adjunct to the ZEISS's family of ophthalmic surgical microscopes to process surgery videos and OCT data (B-Scan images). Specifically, the subject device has the functionality to be connected to an OCT camera (such as in RESCAN 700 (K180229)), a phaco machine (such as in QUATERA 700 (K212241), as well as MIMPS (such as FORUM (K213527).

CALLISTO eye Software must be installed on a computer with a touchscreen; this Panel PC (ORPC) is offered as an accessory. The current model of the ORPC is the CALLISTO eye Panel PC Model II. OPRC function and configuration has been modified since the last CALLISTO eye 510(k) by upgrading electronics components to accommodate lifecycle management needs.

CALLISTO eye 3.7.2 has the same functionalities as CALLISTO eye 3.6 (K180858). These functionalities include patient data management and transmission via DICOM protocol, interfaces to ZEISS's ophthalmic microscopes with/without OCT camera (RESCAN 700) and assists with overlay function for markerless marking to support IOL alignment.

Additional functionalities unique to CALLISTO eye 3.7.2 are inclusion of changes occurring from software version 3.6 to 3.7.1 and additional support of language packages, bug fixes, cybersecurity enhancements and interoperability abilities with a phaco system (OUATERA 700).

The subject device, CALLISTO eye 3.7.2, provides connectivity to the following surgical microscopes from ZEISS:

• . OPMI LUMERA 700 with Integrated Data Injection System (IDIS)
• OPMI LUMERA T with External Data Injection System (EDIS) ●
• OPMI LUMERA I with External Data Injection System (EDIS) .
• OPMI LUMERA 700 with OCT camera (RESCAN700)
• ARTEVO 800 with 3D monitor cart (3DIS) .
• ARTEVO 800 with OCT camera (RESCAN700) .

The software can acquire photo and videos from all surgical microscope listed above and can remote control these microscopes apart from the OPMI LUMERA T and I.

All OPMI LUMERA family surgical microscopes have been covered by the predicate device CALLISTO eye 3.6 (K180858). With the subject device the range of supported surgical microscopes was extended to the ARTEVO 800 with and without RESCAN700 as principal successor of the OPMI LUMERA 700.

The intended use and indications for use of OPMI LUMERA and ARTEVO 800 are identical and the microscopes can be applied for the same surgical procedure.

CALLISTO eye allows the connection and remote control of a surgical microscope with or without OCT Camera and thus operates as an adjunct to the family of ZEISS surgical microscopes. Functionalities such as light intensity, camera parameters, start/stop recording, zoom, focus, diaphragm, start/stop OCT scanning, etc. of the surgical microscope, including the configuration of the foot control panel and handgrips, can be accessed and managed by the user in CALLISTO eye.

CALLISTO eye Software is an assistance, information system to support ophthalmic surgical procedures. It provides an interface to other devices to facilitate the:

• Display and recording of video data provided by ZEISS surgical microscopes (OPMI) .
• Display of assistance functions (graphical guidance templates) and device information (cockpits) to aid the surgeon in the implantation of intra ocular lenses; e.g., used for the alignment for toric intraocular lenses.
• . Display and recording of OCT image data provided by ZEISS RESCAN 700
• Display and exchange data with the ZEISS OUATERA 700 phacoemulsification and vitrectorny system .
• . Retrieval and storage of patient data from and to the FORUM MIMPS system
• . Configuration of ZEISS surgical microscopes, including the assignment of functions to OPMI handgrips and foot control panel

The provided text is a 510(k) summary for the Carl Zeiss Meditec AG's CALLISTO eye (Software Version 3.7.2). It primarily focuses on demonstrating substantial equivalence to a predicate device (CALLISTO eye, Software Version 3.6) rather than detailing specific acceptance criteria and a study to prove meeting those criteria in the context of diagnostic performance.

The document discusses functional equivalence and safety, but not performance metrics like sensitivity, specificity, or accuracy for a diagnostic task. The device is described as an "assistance system" providing "non-diagnostic video documentation and image capture" and "graphical guidance aid." Therefore, the typical diagnostic performance acceptance criteria and study design (like MRMC studies) are not applicable here.

However, I can extract information related to the device's functional performance and the verification/validation activities performed, which serve as proof that the device meets its functional specifications.

Here's a breakdown based on the provided text, addressing the points where information is available or noting its absence:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is not a diagnostic device with performance metrics like sensitivity/specificity, the "acceptance criteria" are related to its functional specifications and safety. The "reported device performance" refers to the successful verification and validation of these functions.

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

Not applicable or not specified in the context of a "test set" for diagnostic performance. The document describes software verification and validation, which typically involves internal testing against specifications and requirements, often using simulated data, test cases, and potentially real (but de-identified) operational data. The document does not specify a "test set" in the sense of clinical study data with provenance.

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. As a non-diagnostic assistance system, there is no "ground truth" to establish for diagnostic outcomes in the context of the device's stated functions. The validation focuses on whether the software performs its intended functions correctly (e.g., displays images, provides graphical guidance correctly).

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

Not applicable, as there's no diagnostic ground truth being established via expert adjudication.

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 MRMC comparative effectiveness study was done or mentioned. The device's indications for use emphasize "graphical guidance aid" and "assistance system," not a primary diagnostic tool. The submission states, "Animal and Clinical testing was not conducted."

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

This concept is not directly applicable. The CALLISTO eye software is designed as an "assistance, information system to support ophthalmic surgical procedures" with "graphical guidance aid." Its function is inherently human-in-the-loop, providing information to the surgeon. Standalone performance for a predictive or diagnostic algorithm is not its purpose. The document details "software verification activities" and "validation," which confirm the software's functional correctness.

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

For the functional validation of this device, the "ground truth" would be the expected correct behavior of the software according to its design specifications and user requirements. This is established through:

• Design specifications: The software behaving as programmed.
• User requirements: The software meeting the needs of trained clinical personnel for guidance and control.

There is no mention of external clinical ground truth like pathology or outcomes data in this submission for assessing the device's inherent performance.

8. The sample size for the training set

Not applicable. This device is described as software that provides graphical guidance and remote control, not a machine learning or AI algorithm that is "trained" on a dataset for diagnostic or predictive tasks in the conventional sense described by these questions.

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

Not applicable, as there is no "training set" for an AI model mentioned in the submission. The "ground truth" for the software's functional correctness is simply its design specifications and user requirements, as verified and validated through software testing.

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