(148 days)
The TraumaCad Mobile Release 1.0 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 1.0 allows surqeons 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 reqularly updated library of digital templates from leading manufacturers. TraumaCad Mobile Release 1.0 supports DICOM and enables the importing and exporting of image files from a central PACS system, or Quentry (Class I device reqistered by Brainlab AG in the FDA).
TraumaCad Mobile Release 1.0 is the web based version of the predicate device TraumaCad 2.0 (cleared by the FDA on March 19, 2008). The TraumaCad Mobile Release 1.0 has the same basic functionality and intended use as the predicate device, but is now available as a web based version on additional platforms. The differences between the device and the predicate device do not impact on substantial equivalence.
TraumaCad Mobile Release 1.0 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 1.0 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 is not intended for use on mobile phones. Use of TraumaCad Mobile 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.
In order to access TraumaCad Mobile, the user needs to browse to a specific URL and enter the system via username and password. A Web Application will be available in the iTunes store that will automatically open the browser with the correct URL. The application can be downloaded from iTunes for free but cannot be used without receiving a license to ensure the use by appropriate healthcare professionals.
The program features full PACS integration and an extensive reqularly updated library of digital templates from leading manufacturers. TraumaCad Mobile supports DICOM and enables the importing and exporting image files from a central PACS system or from Quentry.
The provided document describes the 510(k) premarket notification for TraumaCad Mobile Release 1.0. This device is a web-based version of the previously cleared TraumaCad 2.0 and is intended for assisting healthcare professionals in preoperative planning of orthopedic surgery.
The document does not explicitly state "acceptance criteria" and "reported device performance" in a formal table format as requested. Instead, it focuses on demonstrating substantial equivalence to a predicate device (TraumaCad 2.0) through functional testing, comparison of technological characteristics, and usability testing. The "acceptance criteria" can be inferred from the successful outcome of these tests, implying that the new device performs "as well as or better than the legally marketed predicate device."
Here's an analysis of the study and information provided:
1. Table of Acceptance Criteria and Reported Device Performance:
The document doesn't provide a specific table of quantitative acceptance criteria with numerical performance targets and reported values. Instead, it asserts that the TraumaCad Mobile Release 1.0 performs comparably to its predicate device, TraumaCad 2.0, across its shared functionalities.
| Acceptance Criteria (Inferred from testing) | Reported Device Performance (TraumaCad Mobile Release 1.0) |
|---|---|
| Functional Equivalence to Predicate Device: | |
| - Marker detection accuracy | Same expected results as TraumaCad 2.0 |
| - Calibration result accuracy | Same expected results as TraumaCad 2.0 |
| - Template positioning accuracy | Same expected results as TraumaCad 2.0 |
| - Image selection from Quentry/PACS | Successfully performed |
| - Image calibration | Successfully performed |
| - Implant selection | Successfully performed |
| - Evaluation of LLD and offset changes | Successfully performed |
| - Changing implant properties | Successfully performed |
| - Use of measurement tools | Successfully performed |
| - Saving results to Quentry/PACS | Successfully performed |
| Safety and Effectiveness: | Successfully demonstrated through non-clinical testing |
| Risk Mitigation: | New risk control measures implemented and deemed effective for the mobile environment |
| System Stability/Reliability: | Passed unit, system/integration, and acceptance tests including security, negative testing, error handling, stress testing, platform testing, workflow testing, functional testing, multi-user/external access testing, data integrity testing, compatibility testing, load testing, regression testing, and hazard mitigation testing. |
| Usability: (Inferred from Usability Testing) | Successfully performed preoperative planning on various Hip X-rays, with familiar workflow for users of the predicate device. |
2. Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: The document does not specify a numerical sample size for the test set (number of cases or images). It mentions "various medical images from a range of cases" and "various Hip X-rays" for usability testing.
- Data Provenance: The document implies the use of existing digital images from PACS systems or Quentry. The country of origin is not explicitly stated. The nature of the study appears to be retrospective as it uses pre-obtained digital images for testing the software's functionality and comparison.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
- The document does not explicitly state the number of experts used to establish ground truth or their specific qualifications (e.g., radiologist with X years of experience).
- It states that "Clinical judgment and experience are required to properly use the software" as part of its indications for use, implying that healthcare professionals with relevant expertise would interpret the results.
- The testing compared the results of TraumaCad Mobile with TraumaCad 2.0, suggesting the "ground truth" for the comparison was based on the performance of the predicate device, which would have been validated by experts previously.
4. Adjudication Method for the Test Set:
- The document does not describe a formal adjudication method (e.g., 2+1, 3+1).
- The comparison involved running tests in parallel on TraumaCad Mobile and the predicate device TraumaCad 2.0 and observing if they yielded "the same expected results." This implies a direct comparison rather than an expert consensus adjudication on individual cases.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No, an MRMC comparative effectiveness study was not explicitly described. The study focused on demonstrating substantial equivalence between TraumaCad Mobile and its predicate device, TraumaCad 2.0.
- While usability testing involved test participants (who may be healthcare professionals and potentially users of the predicate device), the document does not present data on how much human readers improve with AI (TraumaCad Mobile) vs. without AI assistance (presumably manual planning or planning with the predicate device) in a formal MRMC study design to determine an effect size.
6. Standalone Performance:
- Yes, a standalone (algorithm only without human-in-the-loop performance) evaluation was effectively performed for the core algorithms. The document states: "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." And "Testing included the main functions such as: Marker detection, Calibration result and Templates positioning. The test shows that the predicate device TraumaCad and TraumaCad Mobile have the same expected results in all of the tests." This suggests that the inherent algorithmic performance for these functions was compared in a standalone manner.
- However, the device is explicitly indicated for "assisting healthcare professionals," meaning human-in-the-loop is part of its intended use. The usability testing further underscores the interaction with humans.
7. Type of Ground Truth Used:
- The ground truth for the functional comparison testing was primarily based on the expected results from the predicate device (TraumaCad 2.0). The document states that the new device and the predicate device "have the same expected results in all of the tests."
- For the initial validation of the predicate device (TraumaCad 2.0) and the underlying algorithms, it is highly probable that expert consensus (e.g., orthopedic surgeons, radiologists) and potentially comparison against surgical outcomes data or pathology (if applicable for certain measurements) would have been used. However, for this specific 510(k), the ground truth is anchored to the performance of the already-cleared predicate device.
8. Sample Size for the Training Set:
- The document does not provide any information regarding a training set sample size. This is because TraumaCad Mobile Release 1.0 is largely a porting of existing, already-trained algorithms from TraumaCad 2.0 to new platforms (web-based, iPad, Mac). It's not a new machine learning algorithm that requires a separate training phase with new data. The document explicitly states: "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."
9. How the Ground Truth for the Training Set Was Established:
- As there's no mention of a new training set for TraumaCad Mobile 1.0, there's no information on how its ground truth would have been established.
- For the original TraumaCad 2.0 and its algorithms (from which TraumaCad Mobile's algorithms are derived), the ground truth for training (if machine learning was involved, which is not explicitly stated in this document but is common for such systems) would typically be established through expert consensus by orthopedic surgeons or radiologists, potentially using manually annotated anatomical landmarks, measurements, or templating results validated against surgical outcomes or physical measurements.
§ 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).