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Chondral Quant is a musculoskeletal post-processing software application that allows assessment of knee cartilage condition based on Magnetic Resonance Imaging (MRI).

The medical device Chondral Quant, software version VA10A, is a musculoskeletal postprocessing application that allows evaluating the status of knee cartilage based on Magnetic Resonance Imaging (MRI).

The software is part of the syngo OpenApps framework and can be used from within syngo.via like any other syngo.via workflow.

Version VA10A is the initial version of this medical device.

Chondral Quant processes a morphological 3D series of the knee joint and performs an automated segmentation of the knee's cartilage. The segmentation may be modified by the user. Chondral Quant will also perform a sub-segmentation of the knee cartilage. Chondral Quant additionally performs volumetry and thickness calculation on the segmented areas. Optionally, it is possible to provide a parametric map as secondary input to Chondral Quant. Commonly, this will be a T2 or T2* map. Chondral Quant will perform a registration of the morphological image and the parametric map and transfer the segmentation to the parametric map.

A statistical evaluation of the mapping results for the 21 sub zones will be additionally provided in this case.

All output will be provided in the form of a table showing statistical evaluation of the assessment (volume and mean, median and standard deviation of thickness and mapping results for every region). Additionally, Chondral Quant will generate output maps (segmentation map, cartilage thickness map) and 3D models of the segmented cartilage (zone model and thickness model). Finally, a PDF report containing the table values and the 3D models will be generated as output.

Alternatively, the application Chondral Quant may also be executed in a "PACS-ready" mode, i.e. fully-automated and without user interaction. The results will be sent to PACS automatically. In this case the series names will be marked with a prefix "AUTO GENERATED" for a clear indication of the automatic mode.

The subject device, Chondral Quant with software VA10A, consists of new and modified features that are similar to what is currently offered on the predicate device. The subject device includes the following modifications in comparison to the predicate device: new body region compared to predicate device:

• -Automatic segmentation and volumetry of the cartilage
• -Thickness calculation

The provided text does not contain detailed acceptance criteria and a study demonstrating how the device met those criteria in a format that allows for a direct population of the requested table. The document primarily focuses on explaining the device's intended use, its features, and justifying its substantial equivalence to a predicate device. It mentions "Nonclinical Tests" and "Solution Validation Summary Report" but does not elaborate on specific performance metrics, acceptance thresholds, or detailed study designs for those tests.

However, based on the available information, I can infer some aspects and highlight what is missing:

Here's an attempt to fill out the information based on the provided text, with explicit notes on what is not available:

1. Table of acceptance criteria and reported device performance:

The document mentions "Verification and validation... have been performed" and "All risk mitigations... and all relevant SSRS/FS requirements... have been tested and verified successfully." However, it does not provide a specific table of acceptance criteria (e.g., minimum accuracy, sensitivity, specificity for cartilage segmentation or volume/thickness calculation) nor does it report the device's performance against such criteria with quantitative measures.

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

• Test set sample size: "more than 100 cases" for 3T MRI systems, "more than 11 cases" for 7T MRI systems, and "more than 9 cases" for 1.5T MRI systems.
• Data provenance: Not specified. The document does not mention the country of origin of the data or whether it was retrospective or prospective.

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. The document does not mention the involvement of experts for establishing ground truth for the test set.

4. Adjudication method for the test set:

• Adjudication method: Not specified. There is no mention of how ground truth was established, let alone an adjudication method.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size:

• MRMC study: No. The document explicitly states: "No clinical tests were conducted for the subject device." Therefore, no MRMC study was performed, and no effect size for human readers improving with AI assistance is reported.

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

• Standalone study: The document implies standalone performance testing was done for the algorithm's functionality and accuracy in segmentation, volumetry, and thickness calculation during non-clinical validation. The text states: "Chondral Quant processes a morphological 3D series of the knee joint and performs an automated segmentation of the knee's cartilage. The segmentation may be modified by the user. Chondral Quant will also perform a sub-segmentation of the knee cartilage. Chondral Quant additionally performs volumetry and thickness calculation on the segmented areas." It also mentions an optional "PACS-ready" mode which is "fully-automated and without user interaction," suggesting a standalone capability. However, specific performance metrics from a standalone study are not provided.

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

• Type of ground truth: Not explicitly stated. Given the nature of cartilage segmentation, volumetry, and thickness calculation, it is highly probable that expert-annotated segmentations or measurements (potentially from radiologists or musculoskeletal specialists) were used as ground truth for comparison. However, the document does not confirm this or specify the methodology for ground truth creation.

8. The sample size for the training set:

• Training set sample size: "more than 31" cases.

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

• Ground truth for training set: Not specified. The document does not detail how the ground truth for the training data (e.g., labeled segmentations of cartilage) was established.

Summary of Missing Information:

The provided FDA 510(k) summary focuses on demonstrating substantial equivalence rather than providing a detailed performance study report with specific acceptance criteria and quantitative results. Key missing information includes:

• Specific quantitative acceptance criteria for segmentation, volumetry, and thickness.
• Quantitative results of the device's performance against these criteria.
• Details on the data provenance (country, retrospective/prospective nature) for test data.
• The number and qualifications of experts involved in establishing ground truth for any test or training sets.
• The methodology for establishing ground truth (e.g., expert consensus, manual annotation rules).
• Any details of reader studies (MRMC or otherwise) due to the statement that no clinical tests were conducted.

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