(107 days)
CoLumbo is an image post-processing and measurement software tool that provides quantitative spine measurements from previously-acquired DICOM lumbar spine Magnetic Resonance (MR) images for users' review, analysis, and interpretation. It provides the following functionality to assist users in visualizing, measuring and documenting out-of-range measurements:
- Feature segmentation;
- Feature measurement;
- Threshold-based labeling of out-of-range measurement; and
- Export of measurement results to a written report for user's revise and approval.
CoLumbo does not produce or recommend any type of medical diagnosis or treatment. Instead, it simply helps users to more easily identify and classify features in lumbar MR images and compile a report. The user is responsible for confirming/modifying settings, reviewing and verifying the software-generated measurements, inspecting out-of-range measurements, and approving draft report content using their medical judgment and discretion.
The device is intended to be used only by hospitals and other medical institutions.
Only DICOM images of MRI acquired from lumbar spine exams of patients aged 18 and above are considered to be valid input. CoLumbo does not support DICOM images of patients that are pregnant, undergo MRI scan with contrast media, or have post-operational complications, tumors, infections.
CoLumbo is a medical device (software) for viewing and interpreting magnetic resonance imaging (MRI) of the lumbar spine. The software is a quantitative imaging tool that assists radiologists and neuro- and spine surgeons ("users") to identify and measure lumbar spine features in medical images and record their observations in a report. The users then confirm whether the out-of-range measurements represent any true abnormality versus a spurious finding, such as an artifact or normal variation of the anatomy. The segmentation and measurements are classified using "modifiers" based on rule-based algorithms and thresholds set by each software user and stored in the user's individualized software settings. The user also identifies and classifies any other observations that the software may not annotate.
The purpose of CoLumbo is to provide information regarding common spine measurements confirmed by the user and the pre-determined thresholds confirmed or defined by the user. Every feature annotated by the software, based on the user-defined settings, must be reviewed and affirmed by the user before the measurements of these features can be stored and reported. The software semi-automatically initiates adjustable measurements resulting from segmentation. Segmentations are not intended to be a final output but serve the purpose of visualization and calculating measurements. The device outputs are intended to be a starting point for a clinical workflow and should not be interpreted or used as a diagnosis. The user is responsible for confirming segmentation and all measurement outputs. The output is an aid to the clinical workflow of measuring patient anatomy and should not be misused as a diagnosis tool.
User-confirmed/defined settings control the sensitivity of the software for labelling measurements in an image. The user (not the software) controls the threshold for identifying outof-range measurements, and, in every case once an out-of-range measurement is identified, the user must confirm or reject its presence. The software facilitates this process by annotating or drawing contours (segmentations) around features of the relevant anatomy and displaying measurements based on these contours. The user maintains control of the process by inspecting the segmentation, measurements and annotations upon which the measurements are based. The user may also examine other features of the imaging not annotated by the software to form a complete impression and diagnostic judgment of the overall state of disease, disorder, or trauma.
Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document focuses on demonstrating substantial equivalence to a predicate device rather than presenting specific quantitative acceptance criteria with corresponding performance metrics in a defined table for a new device. However, the performance assessment study served to validate the software's outputs against expert ground truth.
| Performance Metric Category | Acceptance Criteria (Implied) | Reported Device Performance (as validated) |
|---|---|---|
| Feature Segmentation & Measurement Accuracy | CoLumbo's automated segmentations and measurements should accurately reflect the true anatomical features and their dimensions in lumbar spine MRI. | The standalone software performance assessment study compared CoLumbo's outputs (segmentations and measurements) without radiologist editing, against ground truth established by three radiologists. The study "demonstrates continued conformance for medical devices containing software." |
| Threshold-based Labeling Accuracy | The device should correctly identify and label "out-of-range" measurements based on user-defined thresholds. | Performance was validated as part of the standalone software performance assessment study, demonstrating agreement with expert ground truth on segmentations and measurements. |
| Software Functionality & Reliability | The software should perform its stated functions (segmentation, measurement, labeling, reporting) reliably and according to its design. | Software design verification testing was performed, and the device complies with voluntary conformance standards (IEC 62304, IEC 82304-1, ISO 14971, IEC 62366-1, ISO 20417). |
| Cybersecurity | The device should be secure against unauthorized access, modifications, misuse, or denial of use. | Vulnerability assessment and penetration testing demonstrated satisfactory security performance with no critical and high-risk vulnerabilities. |
2. Sample Size for Test Set and Data Provenance:
- Sample Size for Test Set: 100 MR image studies for 100 patients.
- Data Provenance: The standalone software performance assessment study was conducted in the U.S. The data included patients of different ages and racial groups. It's implicitly retrospective as it involved "previously-acquired DICOM lumbar spine Magnetic Resonance (MR) images."
3. Number of Experts and Qualifications for Ground Truth:
- Number of Experts: 3 radiologists.
- Qualifications of Experts: Not explicitly stated beyond "radiologists."
4. Adjudication Method for Test Set:
- The ground truth was "defined by 3 radiologists." The specific adjudication method (e.g., 2+1, 3+1, none) is not specified. It is simply stated that the ground truth was defined by them, implying a consensus or individual determination by each that forms the basis of the ground truth.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly stated as being performed. The study described is a "standalone software performance assessment study," comparing algorithm output directly to ground truth. There is no mention of human readers using the AI and then comparing their performance to human readers without AI assistance.
6. Standalone (Algorithm Only) Performance Study:
- Yes, a standalone performance study was conducted. It was explicitly called a "clinical data based standalone software performance assessment study." This study compared "the CoLumbo software outputs without any editing by a radiologist to the ground truth."
7. Type of Ground Truth Used:
- Expert Consensus/Opinion: The ground truth was "defined by 3 radiologists on segmentations and measurements."
8. Sample Size for Training Set:
- The sample size for the training set is not provided in the document. The document focuses on the performance validation study (test set).
9. How Ground Truth for Training Set Was Established:
- How the ground truth for the training set was established is not provided in the document.
§ 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).