(247 days)
The SPINEDESIGN™ Spine Surgery Planning application is a mobile medical application to assist healthcare professionals in planning orthopedic surgeries. The device allows service providers to perform spine related measurements of the images in the preoperative planning of orthopedic spinal surgery and includes tools for measuring anatomical components for placement of surgical implants. Clinical judgment and experience are required to properly use the software. This software is for orthopedic planning only; not for primary image viewing.
SPINEDESIGN™ Spine Surgery Planning is a preoperative planning tool that allows surgeons to determine measurements from patient radiographs and plan spinal surgery. The SPINEDESIGNTM Spine Surgery Planning application is compatible with the off-the-shelf Apple® iPad® and functions as an image communications and storage device. The subject software application is designed for iOS 6.0 and higher versions, on iPad® 2, or newer devices, and uses several standard frameworks through Xcode. For Adolescent Idiopathic Scoliosis (AIS) cases, the software application will also determine the Lenke classification based on the patient's measurements, and allow the surgeon to enter the Risser grade into the application. At a high level, the SPINEDESIGN™ Spine Surgery Planning application is a pre-surgical planning tool that provides surgeons an additional method for performing measurements and planning spinal surgeries by uploading radiographs and performing calculations at his/her convenience. SPINEDESIGN™ Spine Surgery Planning application is not intended for diagnostic purposes.
The SPINEDESIGN™ Spine Surgery Planning application is a software-only medical device. The provided text details the software's verification and validation testing to demonstrate substantial equivalence to a predicate device.
Here's an analysis of the acceptance criteria and study information:
1. Table of Acceptance Criteria and Reported Device Performance
The general acceptance criteria for the software were that "All verification and validation testing met the predetermined acceptance criteria." However, specific numerical acceptance criteria (e.g., accuracy, precision) for the "Predicate to Subject Measurement Comparison Test" are not explicitly stated in the document.
| Test Category | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Traceability Matrix | (Implicit: Demonstrates all software requirements are traceable to design and testing) | Met (All V&V testing met predetermined criteria) |
| Software Validation (including code review) | (Implicit: Software functions as intended, no critical defects) | Met (All V&V testing met predetermined criteria) |
| User Acceptance Testing (UAT) | (Implicit: Users can effectively utilize the software for its intended purpose) | Met (All V&V testing met predetermined criteria) |
| Predicate to Subject Measurement Comparison Test | (Implicit: Measurements taken by the subject device are comparable to the predicate) | Met (All V&V testing met predetermined criteria) |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the sample size used for the "Predicate to Subject Measurement Comparison Test" or for the User Acceptance Testing. There is no information provided regarding the data provenance (e.g., country of origin, retrospective or prospective nature) for the test sets.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not provided in the document. The document refers to a "Predicate to Subject Measurement Comparison Test" which implies a comparison against the predicate device's measurements, not necessarily a ground truth established by experts.
4. Adjudication Method for the Test Set
The adjudication method is not specified. Given the nature of a "Predicate to Subject Measurement Comparison Test," it's more likely a direct numerical comparison rather than an expert adjudication process.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A multi-reader multi-case (MRMC) comparative effectiveness study was not performed and is not mentioned. The study primarily focused on software verification and validation, as well as a comparison of measurements against a predicate device.
6. Standalone (Algorithm Only) Performance
Yes, a standalone performance assessment was conducted through the "Software Verification and Validation Testing" and specifically a "Predicate to Subject Measurement Comparison Test." These tests evaluate the algorithms and functionality of the software itself, distinct from its use by a human operator in a clinical setting.
7. Type of Ground Truth Used
The "ground truth" for the "Predicate to Subject Measurement Comparison Test" was implicitly derived from the measurements obtained from the predicate device, Nemaris, Inc., Surgimap Spine (K111019). The document doesn't indicate the use of expert consensus, pathology, or outcomes data as a ground truth for testing the subject device's measurements.
8. Sample Size for the Training Set
The document does not specify a training set sample size. This is a software application for planning and measurement, not a machine learning model that typically undergoes a distinct training phase. Therefore, the concept of a "training set" in the context of predictive algorithms is likely not applicable here.
9. How the Ground Truth for the Training Set Was Established
As there is no mention of a training set, the establishment of ground truth for such a set is not applicable and therefore not described 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).