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The IOLMaster 700 is intended for biometric measurements and visualization of ocular structures. The measurements and visualization assist in the determination of the appropriate power and type of intraocular lens. The IOLMaster 700 measures:

• · Lens thickness
• · Corneal curvature and thickness
• · Axial length
• · Anterior chamber depth
• · Pupil diameter
• · White-to-white distance (WTW)

The IOLMaster 700 is a non-invasive optical biometry instrument for visualization and measurement of ocular structures. The IOLMaster 700 is the latest generation device in the IOLMaster series. The version of the IOLMaster 700 that is the subject of this submission is a modified version of the IOLMaster 700 cleared under K170171.

Here's a breakdown of the acceptance criteria and study details for the IOLMaster 700 device, based on the provided FDA 510(k) summary.

It's important to note that this document is for a 510(k) submission, which primarily aims to demonstrate substantial equivalence to a predicate device. Therefore, the "acceptance criteria" discussed are largely about demonstrating comparability or non-inferiority to the predicate device and established clinical methods, rather than setting absolute performance thresholds for a novel device. The study design reflects this goal.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) for a modified device, the "acceptance criteria" are not explicitly stated as numerical targets in the same way they might be for a de novo device. Instead, the performance data aims to demonstrate that the new features (Total Keratometry and Posterior Corneal Surface measurements) are either:

• Interchangeable with conventional methods for normal eyes.
• Perform better than or comparably to existing history-free approximation methods (like Haigis-L) for post-LVC eyes, especially when historical data is unavailable.
• And that repeatability and reproducibility are comparable to the conventional keratometry.

The reported performance is summarized in the "Results" sections of the clinical studies. For the purpose of this table, I will infer the acceptance criteria from the conclusions drawn by the manufacturer regarding comparability and suitability.

2. Sample Sizes and Data Provenance

• Test Set (Clinical Data):

  • Normal Eyes (Study IOLM71): 142 normal eyes (without previous surgery or pathologies except cataract), 738 measurements. (Provenance: Raw data collected prospectively, non-significant risk clinical study at three sites, described as "normal eyes = without prior Laser Vision Correction").
  • Normal Eyes (Study IOLMaster 2017-01909): 32 non-cataract eyes (281 measurements) and 31 cataract eyes (278 measurements). (Provenance: Prospective, monocentric, non-significant risk clinical R&R study, one eye per patient).
  • Post-LVC Eyes (Study HamburgLVC): 30 eyes, 60 measurements (one pre- and one post-operative measurement for each eye). 29 myopic LASIK, 1 hyperopic LASIK. (Provenance: Prospective, single-site clinical study, one eye per patient).
  • Post-LVC Eyes (Study IOLMaster 2017-01909): 30 post-LVC eyes, 267 measurements. (Provenance: Prospective, monocentric, non-significant risk clinical R&R study, one eye per patient).
  • Country of Origin: Not explicitly stated, but the mention of "HamburgLVC" suggests Germany for at least one study site. The applicant "Carl Zeiss Meditec AG" is based in Germany.

• Training Set: Not explicitly mentioned in this 510(k) summary, as the device improvements are primarily related to algorithms for new measurement calculations (Total Keratometry, Posterior Cornea Surface) derived from existing OCT technology, rather than an AI/ML model that requires explicit "training" in the traditional sense. The software verification and validation are for the overall product, and bench testing with "test targets of known curvatures" was used for accuracy and repeatability of the new measurement calculations.

3. Number of Experts and their Qualifications for Ground Truth

• Not applicable in the context of this 510(k). This device is a measurement instrument. The ground truth for the performance of the measurements is based on:
  • Bench testing with "test targets of known curvatures."
  • Comparison to existing, established clinical measurement methods (conventional keratometry, Gullstrand model, Clinical History Method for post-LVC eyes).
  • The "experts" involved would be the clinicians conducting the clinical studies and presumably validating the established methods used for comparison. The document does not specify the number or qualifications of these clinicians beyond them being study site personnel.

4. Adjudication Method for the Test Set

• Not applicable. This study is focused on the performance of a measurement device. There is no subjective interpretation being adjudicated. The measurements are quantitative.

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

• No. This is not an imaging device where human readers interpret and then AI assists in that interpretation. It is a biometric measurement device. The studies compare the device's measurements to established measurement methods.

6. Standalone (Algorithm Only) Performance

• Yes, implicitly. The device itself performs the measurements for Total Keratometry and Posterior Corneal Surface (via its software algorithm). The performance data (Table 1, Figure 1, Figure 2, Tables 2, 3) represent the output of the device's algorithms. There isn't a human-in-the-loop component for these specific measurements; the device generates the numbers. The clinical data then validates these algorithm outputs against established clinical practices.

7. Type of Ground Truth Used

• For Accuracy/Deviation:
  • Known Reference Standards: Bench testing used "test targets of known curvatures."
  • Established Clinical Methods/Models:
    • Conventional keratometry and the Gullstrand model (for normal eyes).
    • Clinical History Method (CHM) for post-LVC eyes, which is considered the "gold standard" when historical data is available.
• For Repeatability & Reproducibility:
  • Multiple measurements on the same patients/eyes using the device itself across different scans, and sometimes different devices/operators.

8. Sample Size for the Training Set

• Not applicable / Not stated. This 510(k) describes a device that utilizes "Spectral domain interferometry (OCT principle)" and "Swept source laser" to obtain biometric measurements. The improvements are primarily algorithmic enhancements to interpret these optical measurements for new parameters (TK, PCS). It's not described as a machine learning model that undergoes a distinct "training set" phase in the typical AI/ML sense. Bench testing and clinical data validate the performance of these algorithms.

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

• Not applicable / Not stated as there is no explicitly defined "training set" for an AI/ML model. The underlying physics and algorithms are based on established optical principles (OCT, interferometry). The validation data compares the device's output to established clinical measurement techniques and physical standards.

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