(182 days)
JointPoint is an image-processing software indicated to assist in the positioning of total hip replacement components. It is intended to assist in precisely positioning total hip replacement components intra-operatively by measuring their positions relative to the bone structures of interest provided that the points of interest can be identified from radiology images.
JointPoint is also indicated for assisting healthcare professionals in preoperative analysis of orthopedic surgery in Total Hip Replacement, Total Knee Replacement, and Intertrochanteric Fracture Reduction. 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. The software is not for primary image interpretation. The software is not for use on mobile phones.
JointPoint is a non-invasive software system intended to provide preoperative templating for orthopaedic procedures and intraoperative data for total hip arthroplasties (THA). The JointPoint software is a client/server based software product wherein a primary server software component and database store user, patient and case information and a client software package is installed on user devices such as laptops or tablets. The two software components communicate with each other over the internet in a fully HIPAA compliant manner. The medical aspects of the software can function on the laptop or tablet alone, without the user of the internet, so that the system will still function in an OR that does not have internet connectivity.
The provided text describes the JointPoint device, an image-processing software intended to assist in the positioning of total hip replacement components and for preoperative analysis of orthopedic surgery. The document confirms that the device has undergone performance testing to establish substantial equivalence to predicate devices, but it does not explicitly provide a table of acceptance criteria or detailed results of a specific study proving the device meets those criteria.
However, by carefully extracting information, we can infer some details about the testing performed.
Here's a breakdown of the available information based on your requested points:
1. Table of Acceptance Criteria and Reported Device Performance
A specific table of acceptance criteria with corresponding performance metrics is not explicitly provided in the document. The document generally states that "Testing performed on this device demonstrates that JointPoint is substantially equivalent to the predicate devices" and mentions "Performance testing of the JointPoint system included the FDA recommended verification and validation testing."
It vaguely describes two types of testing:
- Software verification testing: "performed in the laboratory to evaluate setup, accuracy and functionality of the system in supporting orthopedic procedures."
- Validation testing: "performed using clinical data to compare the templated versus actual size of the implants in order to validate the system's pre-operative intended use, as well as, cadaver data to validate the system's intra-operative intended uses."
Without specific numerical targets or results, a formal table cannot be constructed from the given text.
2. Sample size used for the test set and the data provenance
- Test Set Sample Size: Not explicitly stated. The document refers to "clinical data" and "cadaver data" for validation testing but does not provide the number of cases or images.
- Data Provenance:
- Clinical Data: Used for pre-operative intended use validation. The country of origin is not specified. It is implied to be retrospective as it compares "templated versus actual size of the implants," suggesting outcomes were known.
- Cadaver Data: Used for intra-operative intended use validation. The country of origin is not specified. It is implied to be prospective in nature, as it simulates intra-operative use.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- The document does not provide information on the adjudication method used for the test set.
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
- The document does not mention an MRMC comparative effectiveness study or any effect size related to human reader improvement with AI assistance. The device's indications for use emphasize "assisting" healthcare professionals, but no study details are provided to quantify this assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- The document implies standalone testing was done as part of "software verification testing ... to evaluate setup, accuracy and functionality of the system." Also, the validation testing comparing "templated versus actual size of the implants" and using "cadaver data" suggests evaluating the algorithm's performance in predicting or measuring. However, it's not explicitly labeled as a "standalone" study in the detailed sense of comparing its performance to a ground truth in isolation from human input. The device is not for primary image interpretation and requires clinical judgment, suggesting it's designed as a human-in-the-loop system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- For the pre-operative intended use validation, the ground truth was "actual size of the implants," which likely corresponds to outcomes data (i.e., surgical records or measurements of the implants used).
- For the intra-operative intended use validation using cadaver data, the exact type of ground truth is not specified but would likely involve direct measurements on the cadaver or from high-precision imaging, serving as a reference.
8. The sample size for the training set
- The document does not provide information on the sample size used for the training set.
9. How the ground truth for the training set was established
- The document does not provide information on how the ground truth for the training set was established.
§ 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).