(72 days)
syngo.MR Spectroscopy is a post-processing application to analyze and evaluate MR spectroscopy data. It provides evaluation of MR Single Voxel Spectroscopy (SVS) data and MR Chemical Shift Imaging (CSI) data with workflow guidance to support the diagnostic process.
syngo.MR Spectroscopy includes the possibility of an integrated reading of MR images and spectroscopy data for spectroscopy exams and focuses on ease-of-use by reducing complexity. A novel fit-algorithm reduces the need for manual data processing and offers the user reproducible evaluation results. When interpreted by a trained physician, these results provide information that may assist in diagnosis.
The post-processing tool fits and displays spectra and provides intuitive representations of the metabolic profile. The calculation and display of predefined results such as spectral maps, and metabolite images is provided. The evaluation can be adapted by the customer via protocol modification and task configurations. Interactive reading of spectroscopy exams is supported by side-by-side display of MR images and spectroscopy results, and synchronized display.
syngo.MR Spectroscopy is a syngo.via-based MR spectroscopy data viewing, processing and reading software. This software allows MR spectroscopic data evaluation in a structured way. It is a reading application supporting convenient reading of MR Single Voxel Spectroscopy (SVS) data and MR Chemical Shift Imaging (CSI) data of body regions which have been acquired for in-vivo examinations of the cell metabolism of tissue and organs.
The medical device syngo.MR Spectroscopy comprises syngo.MR Spectro SVS, svngo.MR Spectro CSI and syngo.MR Spectro Extension.
- syngo.MR Spectro SVS: provides evaluation of MR Single Voxel Spectroscopy -(SVS) data with comprehensive workflow guidance.
- syngo.MR Spectro CSI: provides evaluation of MR Chemical Shift Imaging (CSI) data with comprehensive workflow guidance. syngo.MR Spectro CSI includes the possibility of an integrated reading of MR images and CSI spectroscopy data for prostate exams.
- syngo.MR Spectro Extension: provides access to advanced parameters, which allow the advanced user to configure the post processing and display of spectro results according to his / her personal needs. Both Single Voxel Spectroscopy (SVS) and Chemical Shift Imaging (CSI) data are supported.
syngo.MR Spectro Engine bundles the above three packages for post-processing for purchase separately or as part of the syngo.MR Spectro Engine.
Here's an analysis of the Siemens syngo.MR Spectroscopy 510(k) submission, focusing on acceptance criteria and supporting studies, based on the provided text:
Important Note: The provided document is a 510(k) summary for a medical device. 510(k) submissions primarily focus on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria through detailed clinical studies in the same way a PMA (Pre-Market Approval) or some other device types might. Therefore, the information regarding "acceptance criteria" and "studies proving the device meets the acceptance criteria" will be interpreted in the context of a 510(k) submission, which emphasizes functional equivalence and safety/effectiveness data primarily against a predicate.
Description of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria
Overview:
The Siemens syngo.MR Spectroscopy device is a post-processing application for analyzing and evaluating MR spectroscopy data. Its 510(k) submission primarily establishes substantial equivalence to legally marketed predicate devices rather than presenting a de novo set of performance acceptance criteria and a detailed clinical trial to prove them. The "acceptance criteria" here are implicitly related to demonstrating that its functionalities (viewing, processing, and reading software for SVS and CSI data, including a novel fit-algorithm) are safe, effective, and similar to the predicate devices, not raising new questions of safety or effectiveness. The "study" largely consists of verification and validation testing, risk management, and conformance to standards to support this claim of substantial equivalence.
1. Table of Acceptance Criteria and Reported Device Performance:
Given the nature of this 510(k) summary, explicit, quantifiable clinical "acceptance criteria" are not presented in the same way one might find for a diagnostic accuracy study. Instead, the submission focuses on functional equivalence, safety, and effectiveness. The "reported device performance" is largely described qualitatively and through adherence to engineering and quality standards.
| Acceptance Criteria (Inferred from 510(k) Framework) | Reported Device Performance (from 510(k) Summary) |
|---|---|
| Functional Equivalence to Predicate Devices: | |
| - Ability to view, process, and read MR SVS data. | Provides evaluation of MR SVS data with comprehensive workflow guidance. |
| - Ability to view, process, and read MR CSI data. | Provides evaluation of MR CSI data with comprehensive workflow guidance. |
| - Integrated reading of MR images and spectroscopy data. | Includes the possibility of an integrated reading of MR images and CSI spectroscopy data for prostate exams (syngo.MR Spectro CSI) and general spectroscopy exams (Intended Use section). |
| - Support for post-processing and display of spectra. | Fits and displays spectra, provides intuitive representations of the metabolic profile, calculation and display of predefined results (spectral maps, metabolite images). |
| - Workflow guidance and ease-of-use. | Offers comprehensive workflow guidance, focuses on ease-of-use by reducing complexity, simplifies workflows, improved algorithm, intuitive processing capabilities. |
| - Reproducible evaluation results. | Novel fit-algorithm reduces manual data processing and offers reproducible evaluation results. |
| Safety and Effectiveness: | |
| - No new questions of safety or effectiveness. | "Siemens is of the opinion that syngo.MR Spectroscopy does not raise new questions of safety or effectiveness." |
| - Conformance to applicable standards. | Conforms to "applicable FDA recognized and international IEC, ISO, and NEMA standards." |
| - Mitigation of potential hazards. | Risk management via risk analysis (ISO 14971:2007), identified hazards controlled via software development, verification/validation testing. |
| - Operation by healthcare professionals. | Operators are healthcare professionals familiar with and responsible for evaluating and post-processing MR images. |
| Technological Characteristics: | |
| - Improved algorithm for post-processing. | Features an "improved algorithm." |
| - Advanced parameter access/configurability. | syngo.MR Spectro Extension provides access to advanced parameters for configuring post-processing and display. |
2. Sample Size Used for the Test Set and Data Provenance:
The 510(k) summary does not explicitly state a specific sample size for a test set of patient data. It mentions "verification and validation testing" as part of the risk management and development process. This typically involves testing with various datasets, but the specific number or characteristics of these datasets are not detailed in this public summary.
Regarding data provenance: The document does not specify the country of origin or whether the data used in internal verification/validation was retrospective or prospective.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:
The 510(k) summary does not provide details on the number or qualifications of experts used to establish ground truth for any specific test set. The focus is on the software's post-processing capabilities and the output it provides to a "trained physician" for interpretation, rather than on a direct comparison of its diagnostic output against a 'ground truth' established by experts.
4. Adjudication Method for the Test Set:
Since specific details about a test set and ground truth establishment by experts are not provided, an adjudication method like 2+1 or 3+1 is not mentioned in the summary.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
A MRMC comparative effectiveness study is not reported in this 510(k) summary. The submission focuses on the standalone performance and functional equivalence of the software rather than a human-in-the-loop study to quantify improvement with AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:
Yes, a standalone evaluation of the algorithm's performance is implied through the description of its functionality and reproducibility. The summary states: "A novel fit-algorithm reduces the need for manual data processing and offers the user reproducible evaluation results." This indicates that the algorithm itself has been evaluated for its ability to process data, fit spectra, and produce consistent outputs independently of human interaction during the fitting process itself. However, explicit quantitative metrics for this standalone performance (e.g., accuracy of fit, consistency metrics) are not provided in this summary. The ultimate interpretation of these results is still by a human physician - When interpreted by a trained physician, these results provide information that may assist in diagnosis.
7. Type of Ground Truth Used:
The summary does not explicitly describe the type of ground truth used for evaluating the device, as its primary claim is substantial equivalence and functional improvement of post-processing. Given that it's a post-processing tool whose output is interpreted by physicians, the "truth" might internally relate to the accurate and reproducible quantification of metabolite peaks/ratios as expected by spectroscopy experts, or consistency with known physiological states. However, it's not tied to pathology, outcomes data, or expert consensus in a formally described validation study within this document.
8. Sample Size for the Training Set:
The 510(k) summary does not disclose the sample size used for the training set. Modern "AI" in medical devices often involves machine learning, which requires training data. While the summary mentions a "novel fit-algorithm," it does not specify if this algorithm involved machine learning requiring a distinct training set, or if it refers to a more traditional algorithmic approach.
9. How the Ground Truth for the Training Set Was Established:
As the 510(k) summary does not mention a specific training set or its sample size, it also does not describe how ground truth for a 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).