(49 days)
Advanced Lung Analysis II is intended to provide an optimized non-invasive application to measure abnormalities in the lung (for example, nodules, lesions, etc.) from a set of Computed Tomography (CT) images.
The software is designed to support the physician in confirming the presence or absence of physician identified lung lesions (e.g. nodules). The software allows measurement of volume over time using a consistent standardized measurement protocol, thus providing an estimation of the volume doubling time. ALA II software allows analysis and displays statistics for nodule characterization all the different nodule types.
ALA II optional Digital Contrast Agent (DCA) module is an automated highlight feature for the visual identification of possible lesions. Digital Contrast Agent (DCA) is a 3D filter that produces images that highlight spherical (S) and cylindrical (C) anatomical regions, such as nodules, cysts, scars, and vessels. Images are made available to the physician to aid in characterization of suspicious nodules and thus, the patient management care decision process.
ALA II provides to physician with additional information, meant to complement diagnosis based on classical techniques.
CT Advanced Lung Analysis (ALA 2 / ALA II) is a post processing analysis software package designed to assist radiologists and other clinicians in the evaluation and assessment of nodules and other lesions in the lung.
Advanced Lung Analysis II provides an effective solution for providing quick analysis and measurements to help differentiate the radiologist's findings during the primary read. The software assesses and measures all lung nodule types, including measuring volume and their changes over time. Following a C1 scan, the user clicks on a specific nodule and the software automatically calculates and displays a 3-dimensional volume and rendering of the nodule as well as the associated measurements. Advanced Lung Analysis II also offers functionality for quick comparisons between the current and previous patient procedures.
The Digital Contrast Agent (DCA) option will further compliment the Radiologist's diagnostic capability by highlighting spherical (S) and cylindrical (C) anatomical regions, such as nodules, cysts, scars. and vessels.
ALA II and DCA are software options that operate on the GE family of LightSpeed multi-slice CT scanners. Advantage Workstation 4.2 (or higher), and GE PACS systems.
Here's an analysis of the provided 510(k) summary, specifically focusing on the acceptance criteria and study details for the Advanced Lung Analysis II device:
Important Note: The provided 510(k) summary (K042694) for "Advanced Lung Analysis II" does not contain specific details about acceptance criteria, a dedicated study proving device performance against those criteria, or quantitative performance metrics. This 510(k) relies heavily on demonstrating substantial equivalence to predicate devices (Advanced Lung Analysis I and LungCare CT) by stating that "The Advanced Lung Analysis II docs not result in any new potential safety risks and performs as well as devices currently on the market."
Therefore, much of the requested information (like specific acceptance criteria, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, and detailed ground truth establishment methods for training and test sets) is not present within this document. The summary focuses on product description, indications for use, and a general statement of equivalence.
Acceptance Criteria and Device Performance
Since explicit acceptance criteria and corresponding reported performance are not detailed in the provided 510(k) summary, this section is largely based on the general statements made about the device's function and equivalence.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Inferred from Indications of Use and Equivalence Statement) | Reported Device Performance (Inferred from Equivalence Statement) |
|---|---|
| Accuracy in measuring lung abnormalities (nodules, lesions): Specifically, measuring volume and changes over time using a consistent standardized measurement protocol, and estimating volume doubling time. | "performs as well as devices currently on the market" (Predicate devices: Advanced Lung Analysis I and LungCare CT, which are presumed to fulfill this criterion). |
| Ability to support physicians in confirming presence/absence of identified lung lesions. | "performs as well as devices currently on the market" (Predicate devices). |
| Ability to analyze and display statistics for different nodule types. | "performs as well as devices currently on the market" (Predicate devices). |
| Effectiveness of Digital Contrast Agent (DCA) module in highlighting spherical and cylindrical anatomical regions (e.g., nodules, cysts, scars, vessels). | "performs as well as devices currently on the market" (Predicate devices). |
| No new potential safety risks compared to predicate devices. | Controlled by "Software Development, Validation and Verification Process" and "Adherence to industry and international standards." Implied to have no new risks given clearance. |
Study Details (Based on available information in the 510(k) summary)
The 510(k) summary does not describe a specific clinical or performance study with quantitative results to prove the device meets acceptance criteria. Instead, it relies on demonstrating substantial equivalence to previously cleared predicate devices (Advanced Lung Analysis I and LungCare CT) and mentions general "Software Development, Validation and Verification Process" and adherence to standards.
2. Sample size used for the test set and the data provenance:
* Sample size for test set: Not specified in the document.
* Data provenance: Not specified in the document (e.g., country of origin, retrospective or prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
* Not specified in the document. The general statement refers to the device assisting "radiologists and other clinicians," but details about expert involvement in a test set are absent.
4. Adjudication method for the test set:
* Not specified in the document.
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:
* No MRMC study is mentioned or detailed in the provided 510(k) summary. The document does not provide any data or discussion on human reader improvement with or without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
* No standalone performance study is mentioned or detailed in the provided 510(k) summary. The device is described as "designed to assist radiologists and other clinicians," implying a human-in-the-loop context.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
* Not specified in the document. The document refers to "physician identified lung lesions" in its indications, suggesting that clinical interpretation is central, but how ground truth was formally established for any testing is not described.
8. The sample size for the training set:
* Not specified in the document.
9. How the ground truth for the training set was established:
* Not specified in the document.
Summary of Missing Information:
It is crucial to re-emphasize that this 510(k) summary primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a standalone performance study with detailed acceptance criteria and empirical evidence. Therefore, most of the quantitative and methodological details typically found in such a study are absent from this document. The "study" mentioned is the overall "Software Development, Validation and Verification Process" and "Adherence to industry and international standards," which are general quality control measures rather than a specific performance evaluation study with the requested metrics.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).