(23 days)
BriefCase-Quantification is a radiological image management and processing system software indicated for use in the analysis of CT exams with contrast, that include the abdominal aorta, in adults or transitional adolescents aged 18 and older.
The device is intended to assist appropriately trained medical specialists by providing the user with the maximum abdominal aortic diameter measurement of cases that include the abdominal aorta (M-AbdAo). BriefCase-Quantification is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas.
The BriefCase-Quantification results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a radiologist. For final clinically approved measurements, please refer to the official radiology report. Clinicians are responsible for viewing full images per the standard of care.
BriefCase-Quantification is a radiological medical image management and processing device. The software consists of a single module based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.
The BriefCase-Quantification receives filtered DICOM Images, and processes them chronologically by running the algorithm on relevant series to measure the maximum abdominal aortic diameter. Following the AI processing, the output of the algorithm analysis is transferred to an image review software (desktop application), and forwarded to user review in the PACS.
BriefCase-Quantification produces a preview image annotated with the maximum diameter measurement. The diameter marking is not intended to be a final output, but serves the purpose of visualization and measurement. The original, unmarked series remains available in the PACS as well. The preview image presents an unofficial measurement which is not final, and the user is instructed to review the full image and any other clinical information before making a clinical decision. The image includes a disclaimer: "Not for diagnostic use. The measurement is unofficial, not final, and must be reviewed by a radiologist."
BriefCase-Quantification is not intended to evaluate post-operative aortas.
Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Acceptance Criteria and Device Performance
| Acceptance Criteria (Performance Goal) | Reported Device Performance |
|---|---|
| Mean Absolute Error (MAE) between ground truth and algorithm measurement below a prespecified goal. | 1.52 mm (95% Cl: 1.20 mm, 1.83 mm) |
| Little to no bias between ground truth and algorithm output. | Mean difference of 0.58 mm |
Study Details
1. A table of acceptance criteria and the reported device performance:
See table above.
2. Sample size used for the test set and the data provenance:
- Sample Size (Test Set): 162 cases
- Data Provenance: Retrospective, from 6 US-based clinical sites (both academic and community centers). The cases were distinct in time and/or center from the training data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: Three (3)
- Qualifications: US board-certified radiologists
4. Adjudication method for the test set:
The text states the ground truth was "as determined by three US board-certified radiologists." It doesn't explicitly specify an adjudication method like 2+1 or 3+1, but implies a consensus or agreement among the three experts formed the ground truth.
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, a multi-reader multi-case (MRMC) comparative effectiveness study of human readers with and without AI assistance was not conducted. The study focused on the standalone performance of the algorithm against a human-established ground truth.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Yes, a standalone study of the algorithm's performance was done. The study evaluated the BriefCase-Quantification software's performance in providing maximum diameter measurements compared to a ground truth established by radiologists.
7. The type of ground truth used:
Expert consensus among three US board-certified radiologists.
8. The sample size for the training set:
The sample size for the training set is not explicitly stated. The text only mentions that the subject device's improved performance is "due to its training on a larger data set" compared to the predicate device, but does not provide a specific number for this larger data set. It also states the test set cases were "distinct in time and/or center from the cases used to train the algorithm."
9. How the ground truth for the training set was established:
The text does not explicitly describe how the ground truth for the training set was established. It only refers to a "larger data set" used for training.
§ 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).