(39 days)
The TraumaCad Mobile Release 2.0 program is indicated for assisting healthcare professionals in preoperative planning of orthopedic surgery. The device allows for overlaying of prosthesis templates on radiological images, and includes tools for performing measurements on the image and for positioning the template. Clinical judgment and experience are required to properly use the software is not for primary image interpretation. The software is not for use on mobile phones.
TraumaCad Mobile Release 2.0 allows surgeons to evaluate digital images while performing various pre-operative surgical planning and evaluation of images. This software application enables surgeons to plan operations on screen, execute measurements, and facilitate the film-less orthopedic practice. The program features full PACS integration and an extensive regularly updated library of digital templates from leading manufacturers. TraumaCad Mobile Release 2.0 supports DICOM and enables the importing and exporting of image files from a central PACS system, or Quentry (Class I device registered by Brainlab AG in the FDA). TraumaCad Mobile Release 2.0 is the web based version of the predicate device TraumaCad 2.0 (cleared by the FDA on March 19, 2008). The TraumaCad Mobile Release 2.0 has the same basic functionality as the predicate device, but is now available as a web based version on additional platforms. TraumaCad Mobile Release 2.0 is a web based device that can be used on PCs, Mac, or iPad 3, 4 or 5 (Air) and interacts with a PACS system or Quentry. No installation is required. TraumaCad Mobile Release 2.0 provides web based access and should only be used on computers and iPads that are already qualified for wireless use in a clinical setting. TraumaCad Mobile Release 2.0 is not intended for use on mobile phones. Use of TraumaCad Mobile Release 2.0 for planning on a tablet is not to replace planning on a workstation. Use on a tablet is only for situations when a workstation is not available.
This document, a 510(k) summary for TraumaCad Mobile Release 2.0, provides information on comparative testing but does not explicitly define acceptance criteria for performance metrics or present a formal study proving the device meets acceptance criteria. Instead, it focuses on demonstrating substantial equivalence to predicate devices through various tests.
Here's a breakdown of the provided information, addressing your questions where possible:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not specify formal "acceptance criteria" with quantitative thresholds (e.g., minimum accuracy, maximum error). Instead, it states that "the test shows that the predicate device TraumaCad 2.0 and TraumaCad Mobile have the same expected results in all of the tests" when comparing marker detection, calibration results, and template positioning. This implies an internal acceptance criterion of equivalence to the predicate device.
| Parameter/Character Tested | Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|---|
| Marker detection | Same expected results as predicate device TraumaCad 2.0 | Achieved same expected results as predicate device TraumaCad 2.0 |
| Calibration result | Same expected results as predicate device TraumaCad 2.0 | Achieved same expected results as predicate device TraumaCad 2.0 |
| Templates positioning | Same expected results as predicate device TraumaCad 2.0 | Achieved same expected results as predicate device TraumaCad 2.0 |
| Usability | Simulated clinical environment, pre-operative planning, and functional testing demonstrates satisfactory performance | Testing performed on Hip and Knee procedures; primary operating functions tested in a clinical environment; most participants familiar with predicate device workflow. Implied satisfactory usability. |
| Non-clinical testing | Safety and effectiveness demonstrated for defined indications of use, performs as well as or better than predicate device | Successful non-clinical testing demonstrates safety and effectiveness and performance as well as or better than the legally marketed predicate device. |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document repeatedly mentions "various medical images from a range of cases," "various Hip X-rays," and "various knee images." However, no specific numerical sample size for the test set is provided.
- Data Provenance: The images are described as "pre-obtained digital images via PACS system or via Quentry." This suggests retrospective data collected from typical clinical archives. There is no information about the country of origin of the data.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
The document does not specify the number of experts used to establish ground truth or their qualifications. The tests involved comparing the subject device's results to those of the predicate device (TraumaCad 2.0), implying the predicate device's output or methods serve as a form of reference, but not explicitly a human-established ground truth for each case.
4. Adjudication Method for the Test Set
The document does not describe an explicit adjudication method (e.g., 2+1, 3+1). The testing involved "comparing TraumaCad 2.0 on a PC device and TraumaCad Mobile on an iPad device," suggesting a direct comparison of outputs rather than an independent expert adjudication process for each case.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study and Effect Size
No MRMC comparative effectiveness study is reported. The focus is on the device's functional equivalence to the predicate, not on how human readers' performance improves with or without the AI assistance of TraumaCad Mobile.
6. Standalone (Algorithm Only) Performance Study
The reported testing focuses on the device's functionality, including "Marker detection, Calibration result and Templates positioning," and compares these directly to the predicate device's performance. This implies a form of standalone performance evaluation in the sense that the device's algorithms are being assessed for their output equivalence to an established system without necessarily involving human interpretation as the primary outcome being measured. The product is described as "assisting healthcare professionals," so while the tests evaluate the algorithm's output, it's within the context of a human-in-the-loop workflow.
7. Type of Ground Truth Used
The "ground truth" implicitly used for the functional tests such as marker detection, calibration, and template positioning is the output generated by the predicate device, TraumaCad 2.0. For usability, the "ground truth" would be the successful completion of tasks and overall user satisfaction, observed during the simulated clinical environment testing. There is no mention of pathology or outcomes data being used as ground truth for these specific tests.
8. Sample Size for the Training Set
The document does not provide any information regarding the sample size used for the training set. It mentions that "The algorithms contained on TraumaCad Mobile are the same as those that are in the predicate device TraumaCad 2.0 that have been extensively tested," suggesting that the underlying algorithms were developed and likely trained prior to this specific device iteration, possibly with data associated with TraumaCad 2.0.
9. How the Ground Truth for the Training Set Was Established
Since no specific training set information is provided, how the ground truth for an (unspecified) training set was established is not detailed. The statement about the algorithms being the same as in the predicate device (TraumaCad 2.0) suggests that any previous ground truth establishment for those algorithms would have occurred during the development and testing of TraumaCad 2.0.
§ 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).