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The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient-imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume and volume over time. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed.

The Lung Nodule Assessment and Comparison Option application is intended for use as a diagnostic patient-imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed. The user interface and automated tools help to determine growth patterns and compose comparative reviews. The Lung Nodule Assessment and Comparison Option application requires the user to identify a nodule and to determine the type of nodule in order to use the appropriate characterization tool. Lung Nodule Assessment and Comparison Option may be utilized in both diagnostic and screening evaluations supporting Low Dose CT Lung Cancer Screening*.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:

Device Name: Lung Nodule Assessment and Comparison Option (LNA)

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly list quantified acceptance criteria with numerical targets. Instead, it indicates that the device was tested against its defined functional requirements and performance claims, and that it "meets the acceptance criteria and is adequate for its intended use and specifications." The "acceptance criteria" are implied by the verification and validation tests performed to ensure the device's design meets user needs and intended use, and that its technological characteristics claims are met.

However, based on the description of the device's capabilities, we can infer some key performance areas that would have been subject to acceptance criteria:

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

• Test Set Sample Size: The document does not specify a numerical sample size for the internal validation studies conducted by Philips for the LNA application. It states that the LNA application was validated "using real recorded clinical data cases in order to simulate the actual use of the software."
• Data Provenance for Philips' Internal Tests: The text implicitly suggests the data was retrospective, as it refers to "real recorded clinical data cases." The country of origin for these internal test cases is not specified.
• Data Provenance for the Risk Calculator (McWilliams et al. study):
  • Development Data Set: Participants from the Pan-Canadian Early Detection of Lung Cancer Study (PanCan).
  • Validation Data Set: Participants from chemoprevention trials at the British Columbia Cancer Agency (BCCA), sponsored by the U.S. National Cancer Institute.
  • This indicates the data was from Canada (PanCan, BCCA in British Columbia) and supported by the U.S. National Cancer Institute. Both were prospective population-based studies.

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

The document does not specify the number of experts or their qualifications for establishing ground truth specifically for Philips' internal V&V test set. It mentions the LNA application was validated to address "user needs" and simulate "actual use of the software," which implies expert input, but no details are provided.

For the Risk Calculator, the ground truth for malignancy in the McWilliams et al. study was established through tracking the final outcomes of all detected nodules. This likely involved pathology reports and clinical follow-up, adjudicated by clinical experts, but the exact number and qualifications of these experts are not detailed in this summary.

4. Adjudication Method for the Test Set

The document does not describe a specific adjudication method (e.g., 2+1, 3+1) for Philips' internal V&V test set. The validation process involved evaluating each test case for the complete clinical workflow and ensuring the design meets user needs, which might involve expert review, but the formal adjudication protocol is not elaborated upon in this summary.

For the Risk Calculator's underlying study (McWilliams et al.), the "final outcomes of all nodules" suggests a definitive ground truth based on pathology or long-term clinical stability/progression, but the adjudication method for these biological outcomes is not specified within this document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

The document does not report an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The studies described focus on the standalone performance and validation of the LNA application's features and the underlying model for the risk calculator.

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

Yes, standalone performance was evaluated for various features of the LNA application:

• The automatic segmentation capabilities (lungs, lobes, nodules) were validated to be "adequate."
• The automatic measurement calculations (diameters, volume, mean HU) were tested to comply with "defined functionality requirements and performance claims."
• The comparison and matching functionality and "Prefill functionality for the Lung RADS score and the risk prediction" were assured to be "adequate."
• The Risk Calculator tool itself (based on McWilliams et al.) demonstrated standalone predictive performance with "excellent discrimination and calibration, with areas under the receiver-operating-characteristic curve of more than 0.90." This indicates strong standalone performance of the algorithm in predicting malignancy.

7. The Type of Ground Truth Used

• For Philips' Internal V&V: The ground truth appears to be based on "real recorded clinical data cases," implying clinical diagnoses, measurements, and potentially pathology results where applicable, as evaluated against the software's specified functionality and user needs. The specific hierarchy or gold standard used for each feature's ground truth (e.g., expert consensus for segmentation, pathology for nodule type) is not explicitly detailed.
• For the Risk Calculator (McWilliams et al. study): The ground truth for malignancy was established by tracking "the final outcomes of all nodules," which would primarily be pathology results for cancerous nodules and long-term clinical outcome data (stability or benign diagnosis) for non-cancerous ones.

8. The Sample Size for the Training Set

The document does not specify the sample size for the training set used for the LNA application's algorithms, including the segmentation, measurement, and comparison features.

For the Risk Calculator's underlying model (McWilliams et al.):

• The "development data set" (training set) included participants from the Pan-Canadian Early Detection of Lung Cancer Study (PanCan). The exact number of participants or nodules is not provided in this summary but the PanCan study is a large, population-based study.

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

For the Risk Calculator's underlying model (McWilliams et al.):

• The ground truth for the development data set (PanCan study) was established by tracking "the final outcomes of all nodules of any size that were detected on baseline low-dose CT scans." This indicates that the ground truth for malignancy was based on definitive pathological diagnosis or long-term clinical follow-up confirming benignity or stability.

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