Search Results

The software comprising the syngo.MR post-processing applications is post-processing software/applications to be used for viewing and evaluating the designated images provided by a magnetic resonance diagnostic device. All of the software applications comprising the syngo.MR post-processing applications have their own indications for use.

syngo.MR General is a syngo based post-processing software for viewing, manipulating and evaluating MR images.

syngo.MR Cardiology is a syngo based post-processing software for viewing, manipulating and evaluating MR cardiac images.

syngo.MR Neurology is a syngo based post-processing software for viewing, manipulating, and evaluating MR neurological images.

The syngo.MR post-processing applications are synqo based post-processing software/applications to be used for viewing and evaluating' MR images provided by a magnetic resonance diagnostic device and enabling structured evaluation of MR images.

With SMRVB20 there are some new features, improvements and changes within the syngo.MR post-processing applications.

Within syngo.MR General VB20 there are the following new features and improvements:

• Arithmetic tools (new): Addition, Division, Multiplication
• Motion Correction (Elastic) (new): A Motion Correction algorithm can ● be used to perform elastic motion correction for angiography series (pre/post) or within 4D Breast datasets.
• MR Combine feature (new): Composing is also available for axial series. ●
• MR Prostate workflow provides PI-RADS™ v2 reporting (improved) ●
• Harmonized MR Basic workflow (improved): Several basic workflows . for routine reading are consolidated in one MR Basic workflow.
• . MR Neurology workflow: The MR Neurology workflow merges the already cleared workflows of MR Head, MR Neuro Perfusion, and MR Neuro Dynamics.
• Easy Reading Layout in all workflows (improved): All workflows now include a viewing step with Easy Reading Layout.
• Improved result management (improved): Multiple export options for . findings in the interactive Findings details dialog

Within syngo.MR Cardiology VB20 there are the following new features and improvements:

• Volume Quantification Tool (new): Volume Quant provides the . capability to evaluate lesion volumes in the myocardium.
• . Improved Result Distribution (improvement): Segmentation images can be exported as a result series.

Within syngo.MR Neurology VB20 there are the following new features, changes and improvements:

• MR Neuro 3D workflow:
  • Offline BOLD (new): offers the capability to run the GLM ● evaluations on raw BOLD data to generate fMRI statistical maps.
  • . Offline DTI (new): offers the capability to generate TENSOR data together with all other diffusion maps (including b0. ADC. TraceW, FA, AD, RD) from raw diffusion series.
  • DTI evaluation (new): offers quantitative evaluation of diffusion . parameters (FA, RD, AD, ADC, ...) using ROI, VOI, or voxels.
• . Neuro-specific Mean Curve Tool (minor improvement): The application svngo.MR Neuro Dynamics described in K151353 (and cleared August 07, 2015) is only available within syngo.MR Neuro Perfusion (neurospecific Mean Curve Tool), but no longer as a single application.

The syngo.MR Neuro Perfusion Engine Pro, described in K151353 (and cleared August 07, 2015), is therefore obsolete within SMRVB20, as all applications are already part of syngo.MR Neuro Perfusion Engine.

This document describes the safety and effectiveness information supporting the Siemens syngo.MR post-processing applications (syngo.MR General, syngo.MR Cardiology, syngo.MR Neurology), in the context of a 510(k) premarket notification (K163294). The focus is on demonstrating substantial equivalence to previously cleared predicate devices, rather than a standalone clinical study to establish new acceptance criteria. Therefore, several of the requested categories (e.g., sample size for test/training sets, number of experts for ground truth, adjudication method, MRMC study, effect size) are not explicitly described in the provided text because a formal clinical study to prove new performance claims was not performed and not required for a substantial equivalence claim.

The submission focuses on new features and improvements to existing functionalities and does not define new "acceptance criteria" in terms of specific performance metrics (e.g., sensitivity, specificity, AUC) that a new device would need to meet. Instead, acceptance is based on demonstrating that the new features do not raise new questions of safety or effectiveness and that the device as a whole maintains substantial equivalence to its predicate devices, which are already legally marketed.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a substantial equivalence submission for an updated software version rather than a de novo device, specific granular acceptance criteria (e.g., performance metrics like sensitivity, specificity, accuracy) are not defined in the document. The "acceptance criteria" are implicitly met by demonstrating that the new features conform to established safety and performance standards, and that the device's intended use and technological characteristics remain substantially equivalent to its predicate devices.

Acceptance Criteria (Implicitly based on Substantial Equivalence):

• Device functions as intended for viewing, manipulating, and evaluating MR images.
• New features do not introduce new questions of safety or effectiveness.
• Device adheres to relevant industry standards (ISO 14971, IEC 62366-1, IEC 62304, NEMA DICOM).
• Device maintains the same intended use as predicate devices.

Reported Device Performance (Implicit from Features and Conformity):

2. Sample size used for the test set and the data provenance

The document does not describe specific test sets, sample sizes, or data provenance (e.g., country of origin, retrospective/prospective) for a clinical performance study. The evaluation focused on non-clinical data (software verification and validation, risk management, adherence to standards) to support the substantial equivalence claim for the updated software.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable, as no formal clinical test set requiring expert-established ground truth for performance metrics is described in this submission. The validation relies on demonstrating technical performance and equivalence to cleared predicate devices.

4. Adjudication method for the test set

Not applicable, as no formal clinical test set with an adjudication process is described in this submission.

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

Not applicable. This submission is for an update to a post-processing software that provides tools for clinicians, not an AI-assisted diagnostic tool that would typically undergo an MRMC study to show human reader improvement. The document does not describe AI components or MRMC studies.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The document does not explicitly describe a standalone performance study for the algorithms. The "device" itself is software for viewing, manipulating, and evaluating MR images, serving as a tool for clinicians. The focus is on the software's ability to provide these functions accurately and safely as an aid to a human reader, implying a human-in-the-loop interaction for diagnostic purposes.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Not explicitly described in terms of a clinical ground truth for a performance study. The validation relies on technical verification and validation, ensuring the software performs its intended functions correctly and reliably, and that its outputs (e.g., measurements, processed images) are accurate based on engineering specifications and comparison against predicate device capabilities.

8. The sample size for the training set

Not applicable. This document describes an update to post-processing software, not a machine learning or AI model that would typically require a training set. The new features mentioned (e.g., arithmetic tools, motion correction, DTI evaluation) are standard image processing and analysis algorithms rather than models requiring large training datasets.

9. How the ground truth for the training set was established

Not applicable, as no training set for a machine learning model is mentioned.

Summary of Approach:

This 510(k) submission for the syngo.MR post-processing applications focuses on demonstrating substantial equivalence to predicate devices for an updated software version. The "study" proving the device meets its (implicit) acceptance criteria relies on:

• Detailed descriptions of new features and improvements.
• Verification and validation activities to ensure these features function as intended and do not introduce new safety or effectiveness concerns.
• Adherence to recognized industry standards (ISO 14971 for risk management, IEC 62366-1 for usability, IEC 62304 for software life cycle, NEMA DICOM for imaging communication).
• A comparison of intended use and technological characteristics with legally marketed predicate devices (K130749, K151353, K153343, K150843) to affirm that the fundamental equivalence remains.

The absence of specific clinical performance study details (e.g., test set sizes, expert reviews, MRMC studies) is consistent with a 510(k) pathway for software updates that are considered substantially equivalent to existing devices and do not introduce entirely new diagnostic capabilities requiring extensive clinical validation.

Ask a specific question about this device

The software comprising the syngo.MR post-processing applications are post-processing software / applications to be used for viewing and evaluating the designated images provided by a magnetic resonance diagnostic device. All of the software applications comprising the syngo.MR post-processing applications have their own indications for use.

syngo.MR General is a syngo based post-processing software for viewing, manipulating, and evaluating MR images.

syngo.MR Cardiology is a syngo based post-processing software for viewing, manipulating, and evaluating MR cardiac images.

syngo.MR Vascular is a syngo based post-processing software for viewing, manipulating, and evaluating MR vascular images.

syngo.MR General, syngo.MR Cardiology and syngo.MR Vascular are post-processing software / applications to be used for viewing and evaluating MR images provided by a magnetic resonance diagnostic device. syngo.MR General; syngo.MR Cardiology and syngo.MR Vascular is syngo.via-based software that enable structured evaluation of MR images.

syngo.MR General, syngo.MR Cardiology and syngo.MR Vascular comprise the following (please refer to Table 1).

syngo.MR General: covered single and engines applications syngo.MR Reading enables reading of 2D, 3D and 4D MR data. syngo.MR Composing (optional) is an offline application for creation of full-format images from overlapping MR volume data sets acquired at multiple stages. syngo.MR General Engine (optional) extends syngo.via by adding software for professional and routine MR radiology usage. It includes workflows for dedicated MR examinations that load and structure examination results automatically into layouts including user support to make sure that no data is missed. syngo.MR General Engine contains several MR Radiology Workflows, MR Cardio-Vascular Workflows and MR Basic Evaluation features.

syngo.MR Cardiology: syngo.MR Cardiac 4D Ventricular Function enables 4D ventricular function evaluation and processes MR cine images of the heart and generates quantitative results for physicians in the diagnostic process. syngo.MR Cardiac Flow enables cardiac flow evaluation and processes velocity-encoded MR images to evaluate blood flow dynamics e.g. in the heart and the great vessels. The application generates quantitative results for physicians in the diagnostic process. syngo.MR Cardio Engine contains: - syngo.MR Cardiac 4D Ventricular Function; - syngo.MR Cardiac Flow.

syngo.MR Vascular: syngo.MR Vascular Analysis enables assessment / quantification of general vascular pathologies

The provided text is a 510(k) summary for the syngo.MR Post-Processing Software (Version SMRVA16A), which includes syngo.MR General, syngo.MR Cardiology, and syngo.MR Vascular. This document primarily focuses on establishing substantial equivalence to predicate devices rather than presenting a detailed study with acceptance criteria and a comprehensive performance evaluation of the device itself.

Based on the provided text, the following information can be extracted or deduced regarding the acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or report specific performance metrics for the syngo.MR Post-Processing Software. Instead, it claims substantial equivalence to predicate devices. The "performance" assessment is framed around the device's functionality being similar to or an improvement upon the predicate devices without introducing new safety or effectiveness issues.

2. Sample Size Used for the Test Set and Data Provenance

The document does not describe a specific "test set" in the context of an independent performance study with a defined sample size. The substantial equivalence argument relies on the inherent characteristics of the software and its intended use, which are aligned with already cleared devices. There is no mention of a particular dataset (e.g., patient MR images) being used for a formal performance evaluation to establish acceptance criteria for this specific 510(k) submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts

Since no specific test set and associated ground truth establishment study are described, there is no information on the number or qualifications of experts involved in such a process.

4. Adjudication Method for the Test Set

As there is no described test set requiring ground truth establishment, there is no mention of an adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned. The submission focuses on device equivalence, not on comparing reader performance with and without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No standalone performance study is described. The device is a post-processing software intended for human use (viewing, manipulating, evaluating), implying human-in-the-loop operation.

7. Type of Ground Truth Used

Given the nature of the submission (substantial equivalence for post-processing software), the concept of "ground truth" in the context of, for example, disease detection or quantification accuracy, is not directly addressed through a performance study. The ground truth for this type of device's "performance" is implicitly tied to its ability to display, manipulate, and facilitate evaluation of MR images in a manner consistent with existing, cleared technology, and in compliance with relevant standards.

8. Sample Size for the Training Set

No information is provided regarding a training set or its sample size. This type of software, as described, is not an AI/ML algorithm that typically requires a large training set in the way a diagnostic AI algorithm would. It is a tool for post-processing and visualization.

9. How the Ground Truth for the Training Set was Established

As there is no described training set, there is no information on how its ground truth would have been established.

Summary of Approach in this 510(k):

This 510(k) submission primarily relies on establishing substantial equivalence to existing legally marketed predicate devices. The arguments revolve around:

• Similar Indications for Use: The devices serve similar purposes for viewing and evaluating MR images.
• Similar Technological Characteristics and Functionalities: The core functions of post-processing, viewing, manipulating, and evaluating are comparable to the predicate devices.
• No New Safety or Effectiveness Questions: The changes (e.g., updated platform, enhancements) do not introduce novel risks or raise new concerns.
• Compliance with Standards: Adherence to recognized medical device standards (e.g., ISO 14971:2009 for risk management, IEC, ISO, NEMA standards).

The document does not detail a prospective clinical study or a rigorous retrospective performance study with defined acceptance criteria and statistical analysis to "prove" the device meets those criteria in a quantitative sense as might be typical for a novel diagnostic algorithm. Instead, the proof is an argument of similarity and compliance with established regulatory frameworks for predicate devices.

Ask a specific question about this device