(103 days)
spineEOS software is indicated for assisting healthcare professionals with preoperative planning of spine surgeries. spineEOS provides access to EOS images with associated 3D datasets and measurements. spineEOS includes surgical planning tools that enable users to define a patient specific surgical strategy.
spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries. EOS images (generated from EOS imaging's acquisition system) and associated 3D datasets are used as inputs of the software. The product manages clinical measurements and allows user to access surgical planning tools to define a patient specific surgical strategy. The product is indicated for adolescent and adult patients.
The provided document is a 510(k) premarket notification for the device spineEOS. It primarily focuses on demonstrating substantial equivalence to a predicate device (K160407 spineEOS) rather than detailing a clinical study with acceptance criteria and performance data for a novel AI/ML-based device.
Therefore, the document does not contain the detailed information required to fully answer the request, specifically relating to a study proving the device meets acceptance criteria for new or modified AI/ML features. The information regarding performance data (Section 7) states that "Nonclinical performance testing performed on the subject device, spineEOS, supports substantial equivalence to the predicate device" and explicitly, "Determination of substantial equivalence is not based on an assessment of clinical performance data."
However, based on the provided text, I can extract information relevant to the comparison for substantial equivalence as presented, and highlight what is missing for a comprehensive answer on acceptance criteria and a study proving performance for a new AI/ML feature.
Here's an attempt to answer the questions based on the available information, noting where data is absent:
1. A table of acceptance criteria and the reported device performance
The document does not provide a table of acceptance criteria for specific performance metrics of a new AI/ML model. Instead, it presents a comparison for substantial equivalence between the modified spineEOS and its predicate (K160407 spineEOS). This comparison focuses on demonstrating that technological differences do not affect safety or effectiveness, not on proving a specific quantitative performance metric against a set acceptance criterion for a novel feature.
Here's a re-interpretation of "acceptance criteria" based on the "Substantially Equivalent?" column in Table 5-1, which represents the justification for equivalence rather than quantitative performance.
| Characteristic | Cleared spineEOS (K160407) | Modified spineEOS | Substantially Equivalent? (Implied Acceptance/Justification) | Reported Device Performance |
|---|---|---|---|---|
| Indications for Use | Using 3D data and models obtained from sterEOS workstation, spineEOS software is indicated for assisting healthcare professionals in viewing, measuring images as well as in preoperative planning of spine surgeries. The device includes tools for measuring spine anatomical components for placement of surgical implants. Clinical judgment and experience are required to properly use the software online. | spineEOS software is indicated for assisting healthcare professionals with preoperative planning of spine surgeries. spineEOS provides access to EOS images with associated 3D datasets and measurements. spineEOS includes surgical planning tools that enable users to define a patient specific surgical strategy. | Yes, the modified spineEOS has the same intended use. Slight rephrasing of indications for use does not raise different safety/effectiveness questions. | Not applicable - assessment is on equivalence of stated use. |
| User Population | Spine surgeons to define and validate the surgical plan. | Spine surgeons and "EOS staff and implant distributors to define and save the optional pre-planning." | Yes, similar. Addition of EOS staff does not affect safety/effectiveness as they have similar account rights and require training. | Not applicable - assessment is on equivalence of user types. |
| Target Population | Patients 7 years or older who need spine surgery (Degenerative, Deformative adult spine, AIS). | Patients 7 years or older who need spine surgery (Degenerative Spine Surgery, Deformative Spine Surgery, AIS). | Yes, same. Slight rephrasing for consistency doesn't change target population. | Not applicable - assessment is on equivalence of patient types. |
| Hardware & Software Requirement | Web browsers (Windows: Chrome 47, Firefox 43, Opera 34; Mac: Chrome 47, Firefox 43, Opera 34, Safari 9). PC: Dual Core 2.4 GHz, 4 GB RAM, integrated graphics. Screen: 1920x1080 minimum. | Web browsers (Windows: Chrome, Firefox, Edge; macOS: Chrome, Firefox, Safari). PC: Dual Core 2.4 GHz, 4 GB RAM, integrated graphics. Screen: 1920x1080 minimum. | Yes, similar. Updates account for web browser evolution; minor changes do not affect safety/effectiveness. | Performance not measured against these specs; rather, the capability to run the software. |
| Tools Available for Planning | Segmental Alignment, Interbody Implant, Osteotomy. | Segmental Alignment, Interbody Implant, Osteotomy, Spondylolisthesis, Rod Curvature Management. | Yes, similar. Fundamental tools unchanged. Introduction of Spondylolisthesis tool (operates on same principle as segmental alignment, just different axis) and Rod Curvature Management does not affect safety/effectiveness. | Functionality of new tools confirmed as per design. No quantitative performance data provided on accuracy or precision of these new tools, only that their introduction does not impact safety/effectiveness because they are based on existing principles. |
| Image Manipulation Functions | 2D/3D display & basic manipulation (zoom, panning, angles measurements). | 2D/3D display & basic manipulation (zoom, panning, distance, and angles measurements). | Yes, same. Addition of distance measurement based on same principle as existing angle measurement; does not affect safety/effectiveness. | Functionality tested, no specific quantitative performance reported. |
2. Sample size used for the test set and the data provenance
The document states "Nonclinical performance testing performed on the subject device, spineEOS, supports substantial equivalence to the predicate device." It also mentions "Validation activities" including "Validation of the multifunctional requirements in terms of design" and "Usability testing".
- Sample Size for Test Set: This information is not provided. The document makes no mention of a specific dataset size for evaluating the performance of the claimed features, especially for any new AI/ML components. Given the "nonclinical performance" and "not based on clinical performance data" statements, it's highly likely that a traditional "test set" in the context of an AI/ML study (i.e., a set of patient cases to evaluate algorithm performance) was not part of this 510(k) submission.
- Data Provenance: This information is not provided. (e.g., country of origin, retrospective or prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not provided. Since the submission states "Determination of substantial equivalence is not based on an assessment of clinical performance data," it's unlikely that such an expert-adjudicated ground truth dataset, typical for AI/ML device evaluations, was used. The focus was on demonstrating that the modified features (like the new Spondylolisthesis tool) function as intended and do not introduce new safety concerns compared to the predicate, rather than on proving diagnostic or measurement accuracy against a gold standard.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided.
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
No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Determination of substantial equivalence is not based on an assessment of clinical performance data." The core of this 510(k) is demonstrating substantial equivalence based on technological comparisons and nonclinical performance (e.g., software verification and validation activities), not an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not explicitly provided. The document mentions "Validation of the multifunctional requirements in terms of design" and "Usability testing." The product, spineEOS, is presented as a tool "assisting healthcare professionals," implying a human-in-the-loop model for its primary use ("clinical judgment and experience are required to properly use the software"). There's no separate mention of a "standalone" algorithm-only performance evaluation, especially one related to diagnostic accuracy without human input.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Since the submission states it's not based on clinical performance data and focuses on substantial equivalence via nonclinical V&V, the concept of "ground truth" in the context of clinical accuracy (e.g., expert consensus, pathology) for performance claims is not applicable or provided. The "ground truth" for the V&V activities would be the design specifications and requirements.
8. The sample size for the training set
This information is not provided. The document does not describe the specific AI/ML algorithms used or their training. The changes highlighted (like the new Spondylolisthesis tool) are additions to existing functionality, and the filing focuses on their technological equivalence and safety, not on a new AI/ML model requiring a training dataset.
9. How the ground truth for the training set was established
This information is not provided, as there is no mention of a training set for an AI/ML model for this submission.
Summary of what the document does provide regarding performance and validation:
- Nonclinical performance testing: This includes design input review, unit testing, software integration, system integration, validation of multifunctional requirements in terms of design, and usability testing.
- Safety & Effectiveness Argument: The core argument is that the modified device, including new tools like "Spondylolisthesis" and "Rod Curvature Management," operates on principles similar to existing cleared functionalities (e.g., segmental alignment tool), and therefore does not raise new questions of safety or effectiveness.
- No Clinical Performance Data: The submission explicitly states that "Determination of substantial equivalence is not based on an assessment of clinical performance data." This significantly limits the type of "acceptance criteria" and "study" information available, as it implies a focus on V&V of software functionality and comparison to predicate rather than a clinical trial proving new performance claims.
§ 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).