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510(k) Data Aggregation
(169 days)
The separately-licensed Lung Analysis option is intended for the review and analysis of thoracic CT images for the purposes of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume over time. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed.
Lung Analysis aids in measuring and characterizing lung nodules. The interface and automated tools help to efficiently determine growth patterns and compose comparative reviews. Lung Analysis is intended for the review and analysis of thoracic CT images for the purposes of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume over time. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed. The Lung Analysis Software requires the user to identify a nodule and to determine whether it is a GGO or solid nodule in order to use the appropriate characterization tool.
The Lung Analysis software from Vital Images, Inc. (K151283) had its performance evaluated through non-clinical tests including phantom testing and external validation.
1. Table of Acceptance Criteria and Reported Device Performance:
The document provided details on phantom testing results for GGO volume, diameter, and mean CT attenuation measurements. Specific acceptance criteria values were not explicitly stated for all tests. However, for GGO volume measurements, the results were reported as "within acceptable" ranges.
| Test Case Name | Parameters (Reported) | Type | Status |
|---|---|---|---|
| GGO volume accuracy & precision: Siemens 64-CT scanner | GGO volume: Bias (Absolute error, APNE), Precision (PRC) | Phantom dataset (Passed) | Passed |
| GGO volume accuracy & precision: Philips 16-CT scanner | GGO volume: Bias (Absolute error, APNE), Precision (PRC) | Phantom dataset (Passed) | Passed |
| GGO volume accuracy & precision: Toshiba AQ1 320-CT scanner | GGO volume: Bias (Absolute error, APNE), Precision (PRC) | Phantom dataset (Passed) | Passed |
| Intra-reader & inter-reader variability of GGO volume measurements (patient-based) | Intra-reader agreement & Inter-reader agreement: CCCinter, TDI, Coverage Probability | Patient-based dataset (Passed) | Passed |
| GGO longest diameter measurement accuracy & precision: Toshiba AQ1 320-CT scanner | Longest diameter: Bias (Absolute error), Absolute percentage normalized error (APNE), Precision (within-nodule standard deviation, wSD) | Phantom dataset (Passed) | Passed |
| GGO mean attenuation measurement accuracy & precision: Toshiba AQ-One CT scanner | Mean attenuation: Bias (Absolute error), Absolute percentage normalized error (APNE), Precision (within-nodule standard deviation, wSD) | Phantom dataset (Passed) | Passed |
Summary of Measurement Accuracy for GGO Volume on Toshiba CT scanner (100mAs):
| GGO Ref. diameter | Bias APE% | Precision PRC% |
|---|---|---|
| 5mm | 15.04% | 24.74% |
| 8mm | 16.15% | 11.85% |
| 10mm | 5.49% | 3.24% |
| 12mm | 2.98% | 3.38% |
Note: The document states these results "may vary for other CT scanner types or CT manufacturers and for other acquisition conditions."
2. Sample Size Used for the Test Set and Data Provenance:
The document mentions "phantom datasets" and "patient-based datasets" for testing. However, it does not specify the exact sample sizes (number of phantoms or patients/cases) for these test sets. The provenance of the data (country of origin, retrospective or prospective) is not provided.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
The document mentions "experienced medical professionals" for external validation but does not specify the exact number of experts or their detailed qualifications (e.g., "radiologist with 10 years of experience").
4. Adjudication Method for the Test Set:
The document does not specify any adjudication method (e.g., 2+1, 3+1). It only mentions that "intra-reader and inter-reader agreement" was evaluated for GGO volume measurements on patient-based datasets.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
A MRMC comparative effectiveness study was not performed to evaluate how much human readers improve with AI vs. without AI assistance. The document focuses on the performance of the software itself and its validation against existing datasets and phantom models.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
Yes, a standalone performance evaluation of the algorithm appears to have been conducted through the phantom testing. The "accuracy and precision of the GGO volume measurements after semi-automatic segmentation and before manual editing" indicates an algorithm-only measurement phase.
7. The Type of Ground Truth Used:
The ground truth used for phantom testing was based on "anthropomorphic lung phantoms with synthetic nodules," which provides a controlled and known ground truth for volume and dimensional measurements. For patient-based datasets, the ground truth for reproducibility (intra-reader and inter-reader agreement) appears to have been established by human experts, as indicated by "User-edited GGOs" in the table. However, the ultimate ground truth for lesion characterization (e.g., pathology, outcomes data) is not specified.
8. The Sample Size for the Training Set:
The document does not provide information on the sample size used for the training set.
9. How the Ground Truth for the Training Set Was Established:
The document does not provide information on how the ground truth for the training set was established.
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