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510(k) Data Aggregation
(159 days)
The Pentacam® is designed to take photos of the anterior segment of the cornea, pupil, anterior chamber and lens of the eye. To evaluate:
- · corneal shape,
- · analyze condition of the lens (opaque crystalline lens),
- · analyze the anterior chamber angle,
- · analyze anterior chamber depth,
- · analyze the volume of the anterior chamber,
- · analyze anterior or posterior cortical opacity.
- · analyze the location of cataracts (nuclear, sub capsular and or cortical), using cross slit imaging with densitometry,
- · corneal thickness,
- · axial length,
- · white-to-white distance.
The Pentacam® AXL also performs calculations to assist physicians in determining the power of the intractular lens for implantation.
The Pentacam AXL is designed to take photos of the anterior segment of the eye to measures eye components such as Axial length, Corneal thickness, Anterior chamber depth, Corneal curvature, Corneal cylinder, Corneal cylinder axis and White-to-white-distance. The measured parameters can be used by physicians to calculate the power of the intraocular lens (IOL) implanted during a cataract surgery.
While rotating around the eye. the Pentacam® AXL captures Scheimpflug images of the anterior eye segment through varying axes. The Scheimpflug images created during an examination are transmitted to the connected PC. The axial length of the eye is measured by interferometry.
Scheimpflug images can be captured within maximum two seconds. Up to 138,000 genuine height values are measured and analyzed from the Scheimpflug images.
The Scheimpflug images are the basis for the height data which are used to calculate a mathematical 3D model of the anterior eye segment.
The mathematical 3D model, corrected for eye movements, provides the basis for all subsequent analysis.
The provided text describes the acceptance criteria and study proving that the Pentacam AXL device meets these criteria by demonstrating substantial equivalence to predicate devices (IOL Master 500 and Pentacam).
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria (as implied by comparison to predicate devices) and Reported Device Performance:
The acceptance criteria for the Pentacam AXL are implicitly defined by its agreement with the predicate devices (IOL Master 500 and Pentacam) on various ophthalmic measurements. The study evaluated agreement using mean differences and 95% Limits of Agreement (LoA). The table below summarizes the reported performance for the overall eye population in comparison to IOL Master 500, which serves as the primary benchmark for the new functionalities (like axial length). Similar data exists for other eye populations and for comparison with the original Pentacam for parameters related to Scheimpflug imaging.
Measure | Acceptance Criteria (95% LoA, derived from predicate agreement) | Reported Pentacam AXL Performance (vs. IOL Master 500, Overall Population) |
---|---|---|
Axial Length [mm] | (-0.116; 0.110) | Difference (Mean ± SD): -0.003 ± 0.058 |
Radius Flat Meridian [mm] | (-0.063; 0.111) | Difference (Mean ± SD): 0.024 ± 0.044 |
Radius Steep Meridian [mm] | (-0.077; 0.152) | Difference (Mean ± SD): 0.037 ± 0.058 |
Mean Radius (Rm) [mm] | (-0.045; 0.106) | Difference (Mean ± SD): 0.030 ± 0.038 |
Corneal Cylinder [D] | (-0.99; 0.79) | Difference (Mean ± SD): -0.10 ± 0.45 |
Corneal Cylinder Axis [°] | (-23.0; 30.2) | Difference (Mean ± SD): 3.6 ± 13.6 |
Anterior Chamber Depth [mm] | (-0.14; 0.24) | Difference (Mean ± SD): 0.05 ± 0.10 |
White-to-White Distance [mm] | (-0.57; 0.04) | Difference (Mean ± SD): -0.26 ± 0.16 |
CCT [µm] | (-15; 19) (vs. Pentacam) | Difference (Mean ± SD): 2 ± 9 (vs. Pentacam) |
Note: The acceptance criteria are interpreted as the demonstrated agreement (Limits of Agreement) with the predicate devices, indicating that the Pentacam AXL performs within acceptable ranges compared to established devices. A separate de novo set of acceptance criteria is not explicitly stated, but the study design aims to show non-inferiority/agreement.
2. Sample Size Used for the Test Set and the Data Provenance:
-
Test Set 1 (Pentacam AXL vs. IOL Master 500):
- Sample Size: 80 subject eyes (20 eyes in each of four pre-defined eye populations).
- Data Provenance: Not explicitly stated as country of origin, but described as a clinical study comparing the Pentacam AXL with the IOL Master 500. This implies prospective collection for the purpose of this comparison.
- Four Eye Populations: Normal eyes (phakic, no cataracts/corneal disease), eyes with cataracts, eyes with abnormal corneal shape (post-keratorefractive surgery), and eyes without a natural lens (aphakic/pseudophakic).
-
Test Set 2 (Pentacam AXL vs. Pentacam):
- Sample Size: 138 eyes of 138 patients.
- Data Provenance: Not explicitly stated as country of origin, but described as a second agreement study. This implies prospective collection for the purpose of this comparison.
-
Test Set 3 (In-house Precision Testing):
- Sample Size: 40 eyes of 40 subjects.
- Data Provenance: Described as "In-house Precision Testing," implying internal data collection.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts:
This information is not provided in the document. The study design is a comparison between two devices (Pentacam AXL and predicate devices), rather than an evaluation against a manually established ground truth by experts. The "ground truth" for the test set is effectively the measurements obtained by the predicate devices.
4. Adjudication Method for the Test Set:
This information is not provided. As the study is a direct comparison between device measurements, traditional adjudication methods involving expert review of images for diagnosis or measurement might not be directly applicable in the same way as, for example, a diagnostic AI study. The "adjudication" is implicitly the statistical comparison of measurements from two automated devices.
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 conducted as described in the provided text. The study focused on the agreement between the Pentacam AXL and existing devices (IOL Master 500 and Pentacam) for quantitative ophthalmic measurements. It did not involve assessing human reader performance, either with or without AI assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:
Yes, the studies described are essentially standalone performance evaluations. The Pentacam AXL, an ophthalmic device, directly measures various eye parameters. The evaluations compare these direct device measurements against those from predicate devices or against repeat measurements from the same device (precision study). There is no "human-in-the-loop" aspect to these performance assessments; they assess the device's inherent measurement capabilities.
7. The Type of Ground Truth Used:
The type of ground truth used is comparison to legally marketed predicate devices.
- For axial length, corneal curvature, corneal cylinder, anterior chamber depth, and white-to-white distance, the IOL Master 500 served as the predicate/reference device.
- For central corneal thickness, and corneal shape parameters, the Pentacam Scheimpflug Camera served as the predicate/reference device.
- For the precision study, repeat measurements from the Pentacam AXL itself served as the reference for repeatability and reproducibility.
8. The Sample Size for the Training Set:
The document describes studies for device validation (performance testing), not for training a machine learning algorithm. Therefore, there is no "training set" mentioned or implied for an AI/algorithm in the context of device development as presented here. The Pentacam AXL is a measurement device, and the Scheimpflug images capture process and subsequent analysis are part of its inherent design, not machine learning that requires a separate training set.
9. How the Ground Truth for the Training Set Was Established:
As there is no training set for an AI/algorithm described in this submission, this question is not applicable.
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