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In the YAG mode (Tango Neo, Tango Reflex Neo, Ultra Q Reflex Neo): -Iridotomy and iridectomy. -Posterior capsulotomy. -Posterior membranectomy.

In the SLT mode (Tango Neo, Tango Reflex Neo) : -Selective Laser Trabeculoplasty (SLT)

These devices are slit lamp based surgical laser instruments designed for use by ophthalmologists in clinics or an outpatient facility in a hospital or surgery. These systems are used to perform both Photodisruption procedures such as posterior capsulotomies, iridotomies, posterior membranectomies in the photodisruptor (YAG mode) and Selective Laser Trabeculoplasty (SLT mode) for the treatment of chronic open angle glaucoma.

All these devices consist of the below main parts: Delivery Head, Microscope and Slit lamp Illumination, Console and Table Top, Joystick fire button, Total solution table, Display unit.

This FDA 510(k) summary does not contain the information required to populate a table of acceptance criteria and reported device performance related to clinical effectiveness. This submission is for an ophthalmic laser system (Tango Neo, Tango Reflex Neo, Ultra Q Reflex Neo) and the FDA has determined that clinical data is not required because the new devices use the same technology and principles as a previously cleared predicate device (Ellex YAG/SLT, K212630).

Therefore, many of the requested fields cannot be filled. However, based on the non-clinical testing performed, we can infer some "acceptance criteria" related to safety and performance specifications, though not in the typical format of clinical outcomes.

Here's a summary of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

As clinical data was not required, there are no specific clinical acceptance criteria or reported clinical device performance metrics in this summary. The "acceptance criteria" are implied by compliance with various safety and performance standards for medical devices and lasers.

2. Sample size 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. As per Section IX, "clinical data is not required" for the substantial equivalence determination. The "tests" mentioned are non-clinical safety and performance tests against standards, not clinical studies with patients.

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

Not applicable, as no clinical ground truth was established for a test set in this submission.

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

Not applicable, as no clinical test set requiring adjudication was used.

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 applicable. This is a laser device, not an AI-assisted diagnostic tool, and no MRMC study was conducted.

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

Not applicable. This is a physical laser device, not a standalone algorithm.

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

Not applicable, as no clinical ground truth was established for a clinical study in this submission. For the non-clinical tests, the "ground truth" is adherence to international and federal safety and performance standards.

8. The sample size for the training set

Not applicable. No AI/ML component requiring a training set is mentioned.

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

Not applicable. No AI/ML component requiring a training set is mentioned.

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In the YAG mode (Tango, Ultra Q, Ultra Q Reflex, Tango Reflex): -Iridotomy and iridectomy. -Posterior capsulotomy. -Posterior membranectomy.

In the SLT mode (Tango, Solo, Tango Reflex): -Selective Laser Trabeculoplasty (SLT)

These devices are slit lamp based surgical laser instruments designed for use by ophthalmologists in clinics or an outpatient facility in a hospital or surgery. These systems are used to perform both Photodisruption procedures such as posterior capsulotomies, iridotomies, posterior membranectomies in the photodisruptor (YAG mode) and Selective Laser Trabeculoplasty (SLT mode) for the treatment of chronic open angle glaucoma.

The provided text is a 510(k) summary for the Ellex YAG/SLT Laser. It describes the device, its indications for use, and a comparison to a predicate device to demonstrate substantial equivalence. It does not contain information about a study that proves the device meets specific acceptance criteria based on performance metrics (e.g., sensitivity, specificity, or accuracy) or a multi-reader, multi-case comparative effectiveness study involving human readers and AI assistance.

The document states: "Since the Ellex YAG/SLT devices use the same technology and principles as the predicate device, clinical data is not required." This means that traditional clinical performance studies (like those that would establish detailed acceptance criteria for diagnostic accuracy or reader improvement) were not conducted or submitted for this 510(k) clearance. The focus of this submission is on demonstrating fundamental safety and technological equivalence to a previously cleared device.

Therefore, I cannot populate the table or answer the specific questions related to acceptance criteria, device performance, sample sizes, ground truth establishment, or clinical study design, as this information is not present in the provided document.

The document primarily covers non-clinical tests (electrical safety, EMC, laser safety, biocompatibility, and software verification/validation) to support the safety and substantial equivalence of the new device to the predicate device.

Key takeaway from the document: The applicant relied on substantial equivalence to a predicate device (Lumenis Selecta Duet, K021550) and extensive non-clinical testing to demonstrate the safety and effectiveness of the Ellex YAG/SLT Laser, rather than conducting new clinical performance studies with specific acceptance criteria that would assess diagnostic or treatment effectiveness in a quantitative manner.

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The Eye Prime is intended for ophthalmic imaging when the following conditions are present or suspected:
•Cataracts
•Retinal Detachment (separation of the retina from the middle coat of the eyeball)
•Orbital Lesions
•Tumors
•Foreign Bodies
•Inflammation
•Vascular Irregularities

The Eye Prime is a new, diagnostic ophthalmic ultrasound Track 1 device. Its function is to perform B-mode ultrasound scans. The system consists of 1) A console which supports 12 and 18MHz Posterior B scan probes and Anterior B- Scan. Ultrasound Bio-microscopy (UBM) probes with either 35 or 50MHz transducers. 2) A laptop which performs the image processing requirements of the system; provides the user interface for operating the device and viewing the resultant images. The laptop also provides data storage, export, archiving and networking for the device and includes the connection for footswitch.

The provided text describes the Eye Prime device, which is an ophthalmic ultrasound system. However, the document provided does not contain information about acceptance criteria, device performance metrics, sample sizes, expert adjudication, or clinical study results (MRMC or standalone) for the Eye Prime device itself.

The document primarily focuses on establishing "substantial equivalence" of the Eye Prime device to a predicate device (Eye Cubed Version 4) based on similar indications for use, technological characteristics, and safety testing. It explicitly states in Section IX: "Since the Eye Prime device uses the same technology and principles as the predicate device, clinical data is not required." This implies that no specific clinical study was conducted for the Eye Prime to prove its performance against acceptance criteria in the way a new, non-substantially equivalent device might.

Therefore, I cannot fulfill all parts of your request with the provided information. I can, however, extract details about the acceptance criteria assumed by demonstrating substantial equivalence, and other relevant information present in the document.

Here's a breakdown of what can and cannot be provided based on the input:

Acceptance Criteria and Device Performance

Since no specific performance metrics or acceptance criteria for the Eye Prime device itself are reported, we can infer that the acceptance criteria for this 510(k) submission were likely focused on demonstrating equivalence in safety and general performance characteristics to the predicate device, rather than specific diagnostic accuracy metrics.

Table of Performance (Based on "Substantial Equivalence" claim):

Study Details for Demonstrating Substantial Equivalence:

The "study" here is implicitly non-clinical testing and comparison to a predicate device rather than a traditional clinical trial proving diagnostic accuracy.

1. Sample sizes used for the test set and data provenance:

   • Test Set (Non-clinical): Not applicable in the context of a clinical test set from patient data. The "test set" here refers to the extensive non-clinical and engineering tests performed (e.g., electrical safety, acoustic output, biocompatibility, software verification/validation).
   • Data Provenance: Not specified for any patient data. The submission relies on adherence to standards and engineering tests. The information doesn't specify if any phantom or ex-vivo data was used for "measurement accuracy" validation, nor its origin.

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

   • Not applicable/Not mentioned. No "ground truth" based on expert clinical assessment of images is established or used for performance evaluation in this 510(k) summary, as it explicitly states clinical data was not required. The "truth" in this context is adherence to engineering and safety standards.

3. Adjudication method for the test set:

   • Not applicable/Not mentioned. There was no clinical test set requiring adjudication.

4. 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. The document explicitly states "Since the Eye Prime device uses the same technology and principles as the predicate device, clinical data is not required." This implies no MRMC study or any clinical study of human-in-the-loop performance was performed or submitted.

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

   • The Eye Prime is a diagnostic ultrasound system, not an AI algorithm. Its "performance" refers to its ability to generate images and measurements. The document claims "Measurement accuracy Eye Prime System has been verified and has been found to be equivalent in measurement accuracy to Eyecubed Version 4." This implies some form of standalone technical testing (e.g., using phantoms or calibrated measurements) was done to verify accuracy, but specific metrics, methods, or details are not provided beyond this statement.

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

   • For the non-clinical tests (e.g., electrical safety, acoustic output, biocompatibility), the "ground truth" is defined by the requirements of the relevant international and national safety and performance standards (e.g., IEC 60601 series, ISO 10993, NEMA UD2).
   • For "measurement accuracy," the "ground truth" would likely be based on calibrated measurements using known physical standards or phantoms, rather than clinical ground truth (pathology, expert consensus). The details are not provided.

7. The sample size for the training set:

   • Not applicable. The Eye Prime is a hardware ultrasound system with associated software for image processing and user interface. This is not an AI/ML device that requires a training set in that sense. Its design and verification are based on engineering principles and established medical device development processes.

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

   • Not applicable, as there is no "training set" in the context of an AI/ML algorithm.

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