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uWS-MI is a software solution intended to be used for viewing, manipulation, and storage of medical images. It supports interpretation and evaluation of examinations within healthcare institutions. It has the following additional indications:

The PET/CT Oncology application is intended to provide tools to display and analyze the follow-up PET/CT data, with which users can do image registration, lesion segmentation, and statistical analysis.

The PET/CT Dynamic Analysis application is intended to display the dynamic PET image data and its associated timeactivity curve.

The PET/CT Brain Analysis (NeuroQ™) application is intended to analyze the brain PET scan, give quantitative results of the relative activity of 240 different brain regions, and make comparison of activity of normal brain regions in AC database.

The PET/CT Cardiac Analysis (ECTbTM) application is intended to provide cardiac short axis reconstruction, browsing function. And it also performs perfusion analysis and cardiac function analysis of the cardiac short axis.

uWS-MI is a comprehensive software solution designed to process, review and analyze PET, CT and PET/CT patient studies. It can transfer images in DICOM 3.0 format over a medical imaging network or import images from external storage devices such as CD/DVDs or flash drives. These images can be functional data, such as PET as well as anatomical datasets, such as CT. It can be at one or more time-points or include one or more time-frames. Multiple display formats including MIP and volume rendering and multiple statistical analysis including mean. maximum and minimum over a user-defined region is supported. A trained, licensed physician can interpret these displayed images as well as the statistics as per standard practice.

The acceptance criteria and study proving device performance are not explicitly detailed in the provided text in the format requested. However, based on the scattered information, I can infer some points and explicitly state what is missing.

The device is uWS-MI, a software solution for viewing, manipulation, and storage of medical images, with specific applications for PET/CT Oncology, PET/CT Dynamic Analysis, PET/CT Brain Analysis (NeuroQ™), and PET/CT Cardiac Analysis (ECTb™).

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed performance study with specific acceptance criteria and detailed quantitative results.

Here's an attempt to extract and synthesize the information based on your requested format:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). However, it mentions "Performance evaluation Report for PET/CT Oncology and Image Fusion" as part of Performance Verification. Details about this report, including the data used, are not provided. Given the nature of a 510(k) summary, the data often comes from internal testing designed to show equivalence, rather than large-scale clinical trials.

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

This information is not provided in the document. Ground truth establishment details are absent.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

A MRMC comparative effectiveness study was not specifically mentioned or detailed. The document focuses on demonstrating substantial equivalence based on features and software verification, and states "No clinical study was required." for general device clearance. The performance of specific applications (NeuroQ™ and ECTb™) leverages their prior clearances, implying that their functionalities, rather than a new comparative effectiveness study of the full uWS-MI system, were reviewed.

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

The device is described as "stand-alone software," and its primary verification listed is "Software Verification and Validation." This suggests that the performance verification would have evaluated the algorithm's output independently, as a standalone system. However, the exact metrics and results of this standalone performance are not explicitly provided beyond the statement of functional equivalence to predicate/reference devices.

7. Type of Ground Truth Used

The type of ground truth used for specific performance evaluations is not explicitly stated. However, considering the device's function as an image post-processing and analysis tool, the ground truth would typically involve:

• Expert consensus or expert readings: For evaluating the accuracy of image analysis, measurements, or lesion segmentation outputs.
• Pathology or clinical outcomes data: For validating the diagnostic accuracy of features, particularly for oncology applications, though "no clinical study was required" suggests this was not the primary method for this 510(k).
• Phantom or synthetic data: For testing algorithm robustness and accuracy in controlled environments.

Since the PET/CT Brain Analysis (NeuroQ™) and PET/CT Cardiac Analysis (ECTb™) applications were cleared previously, their ground truth would have been established during their initial clearances, likely involving expert-derived truth based on clinical images or phantoms.

8. Sample Size for the Training Set

The document does not provide information regarding the sample size of any training set. As a 510(k) for a software device, the focus is often on functional equivalence and verification/validation, rather than detailing the machine learning model training process if such models are embedded.

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

This information is not provided in the document.

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The Siemens Symbia series is intended for use by appropriately trained health care professionals to aid in detecting, localizing, diagnosing, staging of lesions, tumors, disease and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders and cancer. The images produced by the system can also be used by the physician to aid in radiotherapy treatment planning and interventional radiology procedures.

SPECT: The SPECT component is intended to detect or image the distribution of radionuclides in the body or organ (physiology), using the following techniques; Planar imaging, and tomographic imaging for isotopes with energies up to 588 keV.

CT: The CT component is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data (anatomy) from either the same axial plane taken at different angles or spiral planes take at different angles.

SPECT+CT: The SPECT and CT components used together acquire SPECT/CT images can be corrected for attenuation with the CT images, and can be combined (image registration) to merge the patient's physiological (SPECT) and anatomical (CT) images.

Software: the syngo MI Applications software is a display and analysis package intended to aid the clinician in the assessment and quantification of pathologies in images produced from SPECT, PET, CT and other imaging modalities.

The Siemens Symbia systems consist of Single Photon Emission Computed Tomography (SPECT) scanners and integrated hybrid X-Ray Computed Tomography (CT) and SPECT scanners. The SPECT subsystem images and measures the distribution of radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and integrates CT's anatomical detail for precise reference of the location of the metabolic activity. The CT component produces cross-sectional images of the body by computer reconstruction of X-Ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The system can be used as an integrated SPECT and CT modality while also enabling independent functionality of SPECT and CT as standalone diagnostic imaging devices.

The provided document is a 510(k) Pre-market Notification from Siemens Medical Solutions, USA, Inc. to the FDA for their Symbia 6.5 device. This document primarily focuses on establishing substantial equivalence to a predicate device (Symbia 6.0) rather than presenting a detailed clinical study for a novel AI/software component, which is what the prompt's questions imply by asking for "human readers improve with AI vs without AI assistance" or "stand alone (i.e. algorithm only without human-in-the-loop performance)."

The document discusses updates to the Symbia device, including upgraded software and the integration of commercially marketed CT software and a viewing application. The "syngo MI Applications software" is described as a display and analysis package intended to aid clinicians. However, the performance testing section does not describe a clinical study of an AI algorithm in the way the prompt specifies. Instead, it focuses on physical performance characteristics of the SPECT/CT system, specifically quantitative accuracy using phantoms, and refers to electrical, mechanical, and radiation safety standards.

Therefore, many of the requested details about acceptance criteria and study design for an AI-powered diagnostic device are not present in this document. The document describes performance testing for a medical imaging system, not a specific AI-driven diagnostic or assistive algorithm for image interpretation that would involve human readers or ground truth established by experts.

Given the information provided in the document:

Acceptance Criteria and Reported Device Performance

The acceptance criteria and performance reported relate to the quantitative accuracy of the SPECT system, not a specific AI diagnostic algorithm.

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syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite syngo.via integrates Radiology Information Systems (RIS) to enable customer specific workflows. The predicate device, syngo.via allows for the use of a variety of advanced applications (clinical applications) These applications are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo.via medical device. syngo.via has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and post processing algorithms compared to the above mentioned predicate devices. syngo.via is based on Windows. Due to special customer requirements and the clinical focus syngo.via can be configured in the same way as the predicate device with different combinations of syngo- or Windows based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

Here's an analysis of the provided 510(k) summary regarding acceptance criteria and supporting studies:

This 510(k) pertains to "syngo.via," a PACS system. Based on the document, this 510(k) is for enhanced functionalities of syngo.via, making it an update or extension of a previously cleared device (K123375). The key here is that it's not a new AI algorithm designed for a
specific diagnostic task with associated performance metrics. Instead, it seems to be primarily a software platform update that integrates functionalities already present in other cleared Siemens products.

Therefore, the typical structure for reporting AI/CADe/CADx device performance (sensitivity, specificity, AUROC, etc.) involving a test set, ground truth, and expert readers is not applicable in this submission. The "acceptance criteria" discussed are likely related to software verification and validation, adherence to standards, and demonstrating substantial equivalence to existing devices with similar functionalities.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned above, this 510(k) is for an enhanced PACS system and does not present specific diagnostic performance metrics. The "performance" is primarily demonstrated through compliance with standards and equivalence to predicate devices. There are no explicit quantitative acceptance criteria for diagnostic performance in terms of sensitivity, specificity, etc., as it's not a new diagnostic algorithm.

The "performance" described is in terms of:

• Software Functionality: Viewing, manipulation, communication, and storage of medical images.
• Integration: HL7-/DICOM-compatible RIS workflow.
• Technological Characteristics: Runs on Windows OS, supports DICOM images, image data compression (lossless and lossy).
• Imaging Algorithms (inherited/similar to predicates): MPR, MIP, MinIP, VRT, SSD, Digitally Reconstructed Radiograph, Editor functionality, Registration, Region Growing, Quantitative measurements.
• Automatic Spine Labeling (inherited/similar to predicates): Anatomy Labeling of Vertebra bodies, automatically suggested labels with manual override.

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

The document does not describe a "test set" in the context of diagnostic performance evaluation (e.g., a set of medical images used to evaluate an algorithm's diagnostic accuracy). The testing performed was software verification and validation testing at Unit, Integration, and System levels, as per IEC 62304. This type of testing uses various software inputs and configurations to ensure functional correctness, rather than a diagnostic image dataset. No specific sample size of images or data provenance (country, retrospective/prospective) is provided because it's not relevant for this type of submission.

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

Not applicable. There was no diagnostic "test set" requiring expert ground truth for diagnostic accuracy evaluation.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. There was no diagnostic "test set" requiring expert ground truth or adjudication.

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 510(k) does not present an MRMC study comparing human reader performance with and without AI assistance, as it is a PACS system enhancement, not a new AI-powered diagnostic tool.

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

Not applicable. This is not a standalone diagnostic algorithm. syngo.via is a platform for viewing, manipulation, communication, and storage of medical images, intended to "support the physician in diagnosis and treatment planning." The functionalities described (like automatic spine labeling) are features within this broader platform, and their performance is indicated as being similar to those from previously cleared predicate devices.

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

Not applicable. As there was no diagnostic test set in the traditional sense, there was no ground truth for diagnostic accuracy established through expert consensus, pathology, or outcomes data. The "ground truth" for the software's functional performance would be defined by the software requirements and design specifications, verified through testing procedures.

8. The sample size for the training set

Not applicable. This 510(k) does not describe a new AI algorithm that requires a training set. The enhanced functionalities are stated to have "similar technological characteristics as the predicate device" and incorporate "imaging and post processing algorithms compared to the above mentioned predicate devices." This implies that any underlying algorithms for features like "Automatic Spine Labeling" are either existing, well-established, or derived from components previously cleared, rather than newly developed and trained models.

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

Not applicable, as there is no mention of a training set for a new algorithm in this 510(k) submission.

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