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The B-Scan module is used for imaging the internal structure of the eye, including the opaque media and posterior pathology, for the purpose of diagnosing pathological or traumatic conditions in the eye. The probe is intended to be used on both adult and pediatric patients that require imaging of the eye.

The B-Scan device is designed as an ultrasound B-Scan, which uses pulsed echo ultrasound to image the structure of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulse signals and provides a graphic display of returning pulse echoes to indicate the various structures.

All of the critical functions of the B-Scan are calculated in the same manner as in the predicate device, B-Scan Plus. The software algorithms for clinically critical functions remain the same as in the predicate device. However, the user interface and the workflow of B-Scan have enhancement to support cybersecurity implementation.

Both the subject device and predicate device are compatible with the Connect Software (K070943, K123349) and 4Sight (K152573). The software improvements in Connect were focused on enhancing features that optimize integration with the personal computer's processing, data storage, display, and printing capabilities.

The energy source for the B-Scan is USB power as in the predicate device, B-Scan Plus.

The software utilized on both the Connect and 4Sight platforms is fundamentally identical in core clinical functions, including image scanning, rendering, IOL calculations, data storage, and report formatting. Additionally, the key features within the B-Scan module do not differ significantly between the two systems, nor do they make an impact on the established clinical workflow.

Track 1 is being followed for this 510(k) submission.

Here's a breakdown of the acceptance criteria and the study details for the B-Scan Ultrasonic Imaging System, based on the provided FDA 510(k) clearance letter:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating pre-defined "acceptance criteria" for a novel device performance. However, we can infer acceptance criteria from the comparison table (Table 2) and the performance data section, where the subject device's performance is either "Same" or "SE" (Substantially Equivalent) to the predicate, or explicitly lists performance metrics.

For quantitative metrics, the "acceptance criteria" for the subject device can be interpreted as performing comparably or within acceptable limits relative to the predicate device, or meeting specific new specifications.

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

The document does not explicitly state a sample size for patients or images used in any clinical or test set. The performance data mostly refers to bench testing and validation against standards.

• The only mention of a "sample" related to performance is "average time recorded across 5 probes" for the image preview time. This refers to hardware units, not patient data.
• Data Provenance: Not applicable, as no external data set or clinical study on patients is described beyond bench tests. The focus is on device specifications and in-house validation.

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

Not applicable. The submission does not describe a study involving expert readers establishing ground truth for a test set of images for diagnostic performance evaluation. The "Performance" section outlines bench tests and compliance with recognized standards.

4. Adjudication Method for the Test Set

Not applicable. Since there's no mention of a clinical test set requiring human expert review to establish ground truth, there is no adjudication method described.

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

No. The document does not describe a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify improvement in human readers with AI assistance. The device is purely an imaging system, and there is no mention of AI assistance for image interpretation.

6. Standalone (Algorithm Only Without Human-in-the-loop Performance)

The device described is an "B-Scan Ultrasonic Imaging System," which is a diagnostic tool that produces images for human interpretation. It does not contain an AI algorithm for standalone diagnostic performance. Its performance is related to image acquisition parameters, accuracy of measurements, and adherence to safety/design standards.

7. Type of Ground Truth Used

For the quantitative performance claims (e.g., Clinical Accuracy Line/Area), the ground truth was established by physical measurements against known standards or calibrated references during bench testing ("Physical Accuracy and Range Test"). For other aspects, the ground truth is adherence to technical specifications, safety standards, and validated manufacturing/reprocessing procedures.

8. Sample Size for the Training Set

Not applicable. This device is an ultrasound imaging system, not an AI-driven diagnostic algorithm that requires a "training set" of data in the typical machine learning sense. The software aspects mentioned are primarily for device control, image rendering, data storage, and report formatting, enhanced for cybersecurity and usability – not for learning from data to perform a diagnostic task.

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

Not applicable, as there is no training set mentioned for an AI algorithm.

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The 4Sight is a multi-purpose diagnostic ophthalmic ultrasound system intended to make axial length, anterior chamber depth, lens thickness and corneal thickness measurements of the internal structure of the eye.

The 4Sight is a multi-purpose diagnostic ophthalmic ultrasound system intended to make axial length, anterior chamber depth, lens thickness and corneal thickness measurements of the eye and visualize the internal structure of the eye.

Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Ophthalmic

The 4sight device is designed to combine the functionalities of Accutome's A-scan Plus (K123349), B-scan Plus (K070943) and Accupach Pachymeter (K042752) devices into a combined, stand-alone platform. The device performs axial length measurements, corneal thickness measurements and images the internal structure of the eye using these 3 modalities. The 4Sight is a stand-alone system which runs on a Windows 8 platform consisting of a 4Sight control unit, transducers, footswitch, and keyboard.

Here's an analysis of the acceptance criteria and study information provided in the document for the Accutome 4Sight device:

1. Table of Acceptance Criteria and Reported Device Performance

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

• A-scan Physical Accuracy Test: The document does not specify a numerical sample size for this test. It refers to "the A-Scan function on the 4Sight" and "the predicate device," suggesting comparative measurements, but not how many such measurements were taken.
• Pachymetry Comparison Test: The document does not specify a numerical sample size for this test. It refers to "critical parameter results between the two devices," implying multiple comparisons, but the exact number is not provided.
• External Validation Tests: The device was evaluated at 4 different locations. The document does not specify the number of individual cases or patients involved.
• Data Provenance: Not explicitly stated regarding country of origin. The study appears to be prospective for the validation testing, as it involved evaluating the new 4Sight device.

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

• A-scan Physical Accuracy Test: Ground truth was established by "physical distance measured by a mechanical dial indicator." This does not involve human experts in setting the ground truth, but rather a direct physical measurement.
• Pachymetry Comparison Test: Ground truth for this test involved comparing the 4Sight's results to those of the predicate device (Accupach VI) using the "same input test fixture and values." The predicate device likely serves as the reference, which itself would have been validated against a form of ground truth or clinical standard.
• External Validation Tests: "Experienced technicians/ophthalmologists" evaluated the device at 4 different locations. The exact number of experts is not specified beyond "users." Their specific years of experience or training are also not detailed, only that they were "experienced."

4. Adjudication Method for the Test Set

• No explicit adjudication method (e.g., 2+1, 3+1) is mentioned for any of the tests.
• For the External Validation Tests, the qualitative feedback (ratings) from "every user" or "all users" was aggregated to determine if the acceptance criteria were met. This implies a consensus or majority opinion approach rather than a formal adjudication process for discordant interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

• No, a formal MRMC comparative effectiveness study, as typically understood for AI evaluation, was not conducted.
• The document describes a "Pachymetry Comparison Test" and an "A-scan Physical Accuracy Test" that compare the 4Sight to its predicate devices, but this is a device-to-device comparison, not an AI-assisted vs. unassisted human reader comparison.
• The External Validation Tests involved multiple users, but the goal was to assess device usability and safety, not to quantify the effect size of AI on reader performance. There is no mention of "AI" in this context, as the device is an ultrasound system making measurements.

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

• Yes, the performance of the device's measurement algorithms appears to have been evaluated in a standalone manner.
• The A-scan Physical Accuracy Test directly measures the accuracy of the A-scan function against a physical standard.
• The Pachymetry Comparison Test compares the 4Sight's output with that of a predicate device under controlled input conditions, essentially evaluating the algorithm's output.
• The device itself is described as a "stand-alone system."

7. The Type of Ground Truth Used

• A-scan Physical Accuracy Test: Direct physical measurement (physical distance measured by a mechanical dial indicator).
• Pachymetry Comparison Test: Comparison against a predicate device's measurements using the same input. The predicate device's measurements are implicitly treated as the ground truth for this comparison.
• Software Validation: Ground truth was meeting the 317 specified software requirements.
• External Validation Tests: Expert opinion/feedback (ratings from experienced technicians/ophthalmologists) regarding usability and safety.

8. The Sample Size for the Training Set

• The document does not describe the development of an AI algorithm that would require a "training set." The 4Sight device is described as combining functionalities and algorithms from existing predicate devices (A-scan Plus, B-scan Plus, Accupach Pachymeter).
• The software modifications were primarily for integrating these functionalities into a single standalone unit and graphical interface, not for developing new measurement algorithms that would typically rely on training data. Therefore, the concept of a training set as applied to AI/ML is not relevant here.

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

• As the device does not appear to employ new AI/ML algorithms requiring a training set in the conventional sense, this information is not applicable and therefore not provided in the document. The algorithms for critical functions were stated to be "exactly the same as in the predicate devices."

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An AccuTip Cover is applied over the tip of a handheld tonometer prior to performing tonometry. The tip cover is used for protection of the patient's eye and the instrument tip.

The AccuTip Cover is intended to be used in conjunction with a handheld tonometer by trained individuals experienced in taking intraocular pressure measurements.

The AccuTip Cover is a non-sterile, sanitized, single use latex disposable. It is used to cover the tip of a handheld tonometer.

Here's a breakdown of the acceptance criteria and the studies mentioned for the AccuTip Cover, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document does not specify the sample size used for the test set in any of the studies (Verification, Comparison, Validation, Disinfection, or Aging testing).

The document does not explicitly state the country of origin of the data. Given Accutome, Inc. is located in Malvern, PA, USA, and the FDA correspondence, it's highly probable the studies were conducted in the USA.

The studies described are prospective in nature, as they involve testing the AccuTip Cover under various conditions to demonstrate its performance and safety.

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

The document does not mention the use of external experts or the establishment of "ground truth" in the context of expert consensus for any of the studies. The evaluation criteria appear to be based on internal design specifications, historical predicate device performance, and established standards.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) for the test set. The evaluations appear to be straightforward comparisons against predetermined criteria.

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 done. This type of study is typically relevant for interpretative diagnostic devices or AI-assisted systems, which the AccuTip Cover, a physical tonometer tip cover, is not. The document does not discuss AI or human reader improvement.

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

A standalone study was not done. The AccuTip Cover is a passive physical device, not an algorithm.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

The "ground truth" for the studies performed for the AccuTip Cover is derived from different sources depending on the test:

• Verification Testing: Internal design inputs and outputs.
• Comparison Test: Performance of the legally marketed predicate device (Ocu-Lab Ocu-Film Tip Cover).
• Validation Testing: Specified intended use and method of application.
• High Level Disinfection Validation: Pre-determined acceptance criteria for bioburden and sterility assurance level, likely based on established microbiological standards.
• Aging Testing: Pre-determined acceptance criteria for integrity and defects, likely based on material science and device longevity standards.
• Biocompatibility: Compliance with established international (EN/ISO 10993) and national (FDA G95-1) biocompatibility standards.

In essence, the "ground truth" is a combination of engineering specifications, performance relative to a predicate, and compliance with recognized industry standards.

8. The Sample Size for the Training Set:

There is no mention of a "training set" in the document. This concept is applicable to machine learning or AI models, which are not relevant to the AccuTip Cover.

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

As there is no training set, this question is not applicable.

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This instrument is used for measuring the axial length, anterior chamber depth and lens thickness of the eye. It also is used for calculating the optical power of the IOL to be implanted during cataract surgery.

The Accutome A-Scan Plus Connect device is designed as a biometer, which uses pulsed echo ultrasound to measure the axial length, and the location of other structures of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulses, and provides a one-dimensional display of returning pulse echoes, with positive peaks to indicate the location of ocular structures. The distance between peaks can be measured.

The new A-Scan Plus Connect model uses the personal computer as the main computing vehicle and display instead of the dedicated computer/display of the predicate device. The software modifications in the Connect model are those necessary to interface the processing, data storage, display, and printing capabilities of the personal computer.

The A-Scan Plus connect control unit is an interface between the ultrasonic probe and a personal computer. It consists of a microprocessor based printed circuit board, with USB connections, enclosed in a plastic case.

The energy source for the A-Scan Plus Connect is USB power from the personal computer instead of the AC to DC adapter used to power the predicate device.

Here's a summary of the acceptance criteria and study details for the Accutome A-Scan Plus Connect, based on the provided document:

Acceptance Criteria and Device Performance

• Ultrasound measurements for all eye types within 0.05mm.
• IOL calculation results for all formulas within one decimal place. | All of the data met the established acceptance criteria:
• Ultrasound measurements for all eye types were within 0.05mm.
• IOL calculation results for all formulas were within one decimal place. |
  | Internal Validation Tests: All operations and features fully functional, no errors or deficiencies in patient information, and usability deemed superior to the predicate device. | All operations and features were fully functional. There were no errors or deficiencies in the patient information. The usability was judged to be superior to the predicate device. |
  | External Validation Tests: Safety, functionality, and usability evaluated with a rating scale (1-5, 5=best). No ratings of 1 or 2 in any tests, with a high average rating for specific attributes and an overall rating of 5. | Safety was ranked 5 by every user. The average rating for the 9 specific attributes enumerated was 4.8. The "Overall Rating" of the device was 5 by all users. There were no ratings of 1 or 2 in any of the tests. |

Study Details

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

   • Physical Accuracy Test: Not explicitly stated, but implies a comparison of measurements from a test fixture.
   • Data Comparison Test: Not explicitly stated, but involved measuring "all eye types" and performing "all formulas" for IOL calculations on an input test fixture.
   • Internal Validation Tests: The test plan consisted of 83 specific evaluations, most requiring multiple actions/observations. The sample size refers to the number of evaluations rather than patient data.
   • External Validation Tests: 29 different patients were evaluated. The data provenance is not explicitly stated in terms of country of origin, nor is it specified as retrospective or prospective, though the nature of "evaluating patients" suggests a prospective approach.

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

   • External Validation Tests: 3 different experienced technicians/ophthalmologists. Their specific qualifications (e.g., years of experience) are not detailed beyond "experienced." One user had detailed experience with the predicate device, and two with a competitive biometer.

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

   • No adjudication method is described for resolving discrepancies, as the criteria were based on ratings given by users.

4. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done:

   • No, a formal MRMC comparative effectiveness study as typically understood in AI/medical imaging (comparing reader performance with and without AI assistance) was not done. The external validation involved multiple users but focused on device usability and functionality relative to a predicate, rather than comparing human reader diagnostic accuracy with and without AI.

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

   • The "Physical Accuracy Test" and "Data Comparison Test" can be considered standalone algorithm performance tests, as they directly compare the device's measurements and calculations to physical standards or expected outputs from a test fixture, without direct human input into the measurement generation.

6. The type of ground truth used:

   • Physical Accuracy Test: Physical distance measured by a mechanical dial indicator.
   • Data Comparison Test: Established criteria for ultrasound measurements (within 0.05mm) and IOL calculation results (within one decimal place) based on a test fixture.
   • Internal Validation Tests: Proper operation and usability, validated against the defined test plan and expected performance.
   • External Validation Tests: User ratings from experienced technicians/ophthalmologists regarding safety, functionality, and usability.

7. The sample size for the training set:

   • The document does not describe a training set for the A-Scan Plus Connect itself, as it is presented as having "software algorithms for clinically critical functions... exactly the same as in the predicate device." Therefore, it's not a new algorithm requiring a separate training set.

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

   • Not applicable, as no new training set for the A-Scan Plus Connect is described. The device's clinical critical functions are based on algorithms identical to the predicate device.

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The UBM Plus is designed for imaging the internal structure of the eye including opaque media and anterior segment pathology, for the purpose of diagnosing pathological or traumatic conditions in the eye.

The UBM Plus device is designed as a high frequency ultrasound B-Scan, which uses pulsed echo ultrasound to image the anterior segment of the eye. It utilizes a noncontact probe via a contact Scleral shell to generate and receive the ultrasound pulses, and provides a graphic display of returning pulse echoes to indicate the various structures.

The UBM Plus device's performance data and acceptance criteria are outlined in the provided text.

1. Table of Acceptance Criteria and Reported Device Performance:

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The instrument is used for measuring the corneal thickness of the eye.
Intended Use: Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Ophthalmic, A-mode (P=previously cleared by FDA).

The PachPen device is designed as an ultrasound pachymeter which uses pulsed echo ultrasound to measure the corneal thickness of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulses, and provides a numeric display of returning pulse echoes to indicate the thickness of the cornea.

This document is a 510(k) summary for the PachPen Pachymeter, an ultrasound device for measuring corneal thickness. As such, it is a submission for regulatory clearance and does not contain a detailed study report with acceptance criteria and device performance data in the structured format requested.

The document confirms the device's substantial equivalence to a predicate device (AccuPach V Pachymeter K042752), which is the basis for its regulatory clearance. However, it does not provide the specific performance data from a clinical or technical study proving the device meets an explicit set of acceptance criteria.

Therefore, many of the requested fields cannot be directly populated from the provided text.

Here's an attempt to answer based on the available information and highlighting what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Self-correction: The document does not explicitly state acceptance criteria or report specific performance metrics for the PachPen device. Its clearance is based on substantial equivalence to a predicate device. For a full study report, these details would be necessary.

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

• Sample Size: Not specified.
• Data Provenance: Not specified. Since it's a 510(k) summary for substantial equivalence, the data likely relates to the technical specifications and comparison with the predicate device, rather than a large clinical study directly evaluating the new device's performance against ground truth in human subjects.

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

• Not applicable/Not specified in this document. The submission is for substantial equivalence to an existing device, rather than a de novo clinical validation requiring expert-established ground truth for a new diagnostic claim.

4. Adjudication method for the test set

• Not applicable/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

• No. This device is an ultrasound pachymeter, a measurement tool, not an AI-assisted diagnostic imaging system for human interpretation. Therefore, an MRMC study related to AI assistance is not relevant or mentioned.

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

• Yes, in a sense. The PachPen Pachymeter is a standalone device designed to provide a numeric measurement. Its performance would be evaluated as a standalone instrument, but not in the context of an "algorithm only" in the way AI or image processing algorithms are typically described.

7. The type of ground truth used

• Not explicitly stated for the PachPen device. For a pachymeter, ground truth for accuracy studies would typically involve:
  • Phantom measurements: Using phantoms with precisely known thicknesses.
  • Comparative measurements: Against a highly accurate reference standard pachymeter or other established measurement method.
  • Histology/Pathology (less common for in-vivo devices): Ex-vivo tissue measurements.

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device that requires a training set.

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

• Not applicable. This is not an AI/machine learning device.

Summary of what the document does provide:

• Device Description: The PachPen is an ultrasound pachymeter that uses pulsed echo ultrasound with an eye-contact probe to measure corneal thickness.
• Indications for Use: Measuring the corneal thickness of the eye.
• Predicate Device: AccuPach V Pachymeter (K042752).
• Regulatory Clearance Basis: Substantial equivalence to the predicate device.
• Transducer: A-mode 10.5 MHz, which is the same as used in the predicate device.
• Regulatory Class: Class II, under "Ultrasonic pulsed echo imaging system" (21 CFR 892.1650).

Key Takeaway: This 510(k) summary is a regulatory filing demonstrating substantial equivalence, not a detailed technical or clinical study report. It relies on the predicate device's established performance, rather than presenting new, detailed performance data for the PachPen itself.

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The instrument is used for measuring the axial length, anterior chamber depth and lens thickness of the eye. It also is used for calculating the optical power of the IOL to be implanted during cataract surgery.

The AccuSonic A-Scan device is designed as a biometer, which uses pulsed echo ultrasound to measure the axial length, and the location of other structures of the eye. It utilizes an eye-contact probe to generate and receive the ultrasound pulses, and provides a one-dimensional display of returning pulse echoes, with positive peaks to indicate the location of ocular structures. The distance between peaks can be measured.

The provided 510(k) summary for the AccuSonic A-Scan device primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a detailed study with specific acceptance criteria and performance data in the format typically used for AI/ML device evaluations.

This submission is for an ultrasound biometer, a physical device that measures ocular structures. It precedes the widespread use and regulatory requirements for AI/ML-driven medical devices. Therefore, the information typically found in such reports (like sample size for test/training sets, ground truth establishment for AI, MRMC studies, etc.) is not applicable in this context. The 510(k) process for devices like this primarily relies on performance specifications, safety testing, and comparison to already cleared devices.

Here's a breakdown of the requested information based on the provided document and the limitations of an A-scan biometer submission from 2003:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics in a single table as would be expected for a modern AI/ML device study. Instead, the "performance" is implicitly tied to its "substantially equivalent" claim to predicate devices. For an A-scan biometer, key performance aspects would relate to accuracy, precision, and reproducibility of measurements (axial length, anterior chamber depth, lens thickness). These are typically verified through internal testing and comparison to reference standards or predicate devices.

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

• Not Applicable / Not Provided: The document does not describe a clinical "test set" in the context of an AI/ML algorithm. For a physical device like an A-scan, performance is typically validated through engineering tests, phantom studies, and comparison to predicate devices, rather than a separate clinical test set to evaluate an algorithm's output. Clinical validation might involve a small number of patients, but this is not detailed here.

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

• Not Applicable / Not Provided: Ground truth in the context of algorithmic performance is not relevant for this device's submission. The "ground truth" for an A-scan biometer's measurements would be the actual physical dimensions of the structures being measured, verified by precise physical standards or other highly accurate measurement methods, not expert consensus on image interpretation.

4. Adjudication method for the test set

• Not Applicable / Not Provided: Adjudication methods are typically employed in studies where human interpretation or labeling of data is involved, especially for AI/ML model training or evaluation. This is not
  relevant to the performance evaluation described for the AccuSonic A-Scan.

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 is a submission for a physical diagnostic ultrasound device (biometer), not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not applicable and was not performed.

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

• Not Applicable: There is no "algorithm only" performance reported in the context of AI for this device. The device itself is the standalone measurement system. Its performance is its ability to accurately measure ocular dimensions.

7. The type of ground truth used

• Inferred: Physical/Reference Standards: For an A-scan biometer, the ground truth would typically be established by:
  • High-precision physical phantoms: Known dimensions are measured by the device and compared to the phantom's actual dimensions.
  • Comparison to highly accurate predicate devices: Measurements obtained by the new device are compared to those from an already validated predicate device on the same subjects or phantoms.
  • Cadaveric eyes or animal eyes: In some cases, direct measurements on excised eyes could serve as ground truth.
    These methods ensure the device's measurements correlate accurately with physical reality.

8. The sample size for the training set

• Not Applicable / Not Provided: This device is not an AI/ML algorithm, so it doesn't have a "training set" in that sense. The device's design and calibration are based on engineering principles and physical laws of ultrasound.

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

• Not Applicable: As there is no AI/ML training set, the concept of establishing ground truth for it is not relevant.

In summary: The provided document is a 510(k) summary for a traditional medical device (ultrasound biometer) from 2003. Its primary purpose is to show "substantial equivalence" to existing cleared devices rather than providing detailed performance metrics from an AI/ML study. Therefore, many of the requested categories related to AI/ML device evaluation are not applicable or not explicitly detailed in this type of regulatory submission. The performance is assessed based on the device's ability to produce measurements comparable to those of already cleared predicate devices.

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