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syngo.CT Applications is a set of software applications for advanced visualization, measurement, and evaluation for specific body regions.

This software package is designed to support the radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice e.g. in the:

• · Evaluation of perfusion of organs and tumors and myocardial tissue perfusion
• · Evaluation of bone structures and detection of bone lesions
• · Evaluation of CT images of the heart
• · Evaluation of the coronary lesions
• · Evaluation of the mandible and maxilla
• · Evaluation of dynamic vessels and extended phase handling
• · Evaluation of the liver and its intrahepatic vessel structures to identify the vascular territories of sub-vessel systems in the liver
• · Evaluation of neurovascular structures
• Evaluation of the lung parenchyma
• · Evaluation of non-enhanced Head CT images
• · Evaluation of vascular lesions

The syngo.CT Applications are syngo based post-processing software applications to be used for viewing and evaluating CT images provided by a CT diagnostic device and enabling structured evaluation of CT images.

The syngo.CT Applications is a combination of thirteen (13) former separately cleared medical devices which are now handled as features / functionalities within syngo.CT Applications. These functionalities are combined unchanged compared to their former cleared descriptions; however, some minor enhancements and improvements are made for the application syngo.CT Pulmo 3D only.

The provided document is a 510(k) summary for syngo.CT Applications, which is a consolidation of thirteen previously cleared medical devices. The document explicitly states that "The testing supports that all software specifications have met the acceptance criteria" and "The result of all testing conducted was found acceptable to support the claim of substantial equivalence." However, it does not explicitly define specific acceptance criteria (e.g., target accuracy, sensitivity, specificity values) for the device's performance or detail the specific studies that prove these criteria are met. Instead, it relies on the premise that the functionalities remain unchanged from the previously cleared predicate devices, with only minor enhancements to one application (syngo.CT Pulmo 3D).

Therefore, based on the provided text, I cannot fill in precise quantitative values for acceptance criteria or specific study results for accuracy, sensitivity, or specificity. The information provided heavily emphasizes software verification and validation, risk analysis, and adherence to consensus standards, rather than detailing a comparative effectiveness study or standalone performance metrics against a defined ground truth.

Here's a breakdown of the available information and what is missing:

1. Table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

• Sample Size for Test Set: Not specified in the document.
• Data Provenance: Not specified in the document.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):

• Number of Experts: Not specified in the document.
• Qualifications of Experts: Not specified in the document.

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

• Adjudication Method: Not specified in the document.

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:

• MRMC Study Done: No. The document does not mention any MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The submission focuses on the consolidation of existing, cleared applications.
• Effect Size of Improvement: Not applicable, as no MRMC study is reported.

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

• Standalone Study Done: Yes, implicitly. The document states, "The testing supports that all software specifications have met the acceptance criteria," suggesting that the software's performance was verified and validated independent of human interpretation to ensure its functionalities (visualization, measurement, evaluation) behave as intended. However, specific metrics (e.g., accuracy of a measurement tool compared to a gold standard) are not provided. The phrase "algorithm only" might not be fully accurate here given the device is a visualization and evaluation tool for human use, not an autonomous diagnostic AI.

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

• Type of Ground Truth: Not explicitly specified. Given the nature of visualization and evaluation tools, it would likely involve comparisons to known values, measurements, or expert-reviewed datasets, but the document does not detail this.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable/Not specified. The document describes the device as a consolidation of existing, cleared software applications with "minor enhancements and improvements" only to syngo.CT Pulmo 3D. It does not indicate that new machine learning models requiring large training sets were developed for this specific submission; rather, it refers to the performance of existing, cleared applications.

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

• How Ground Truth for Training Set was Established: Not applicable/Not specified, for the same reasons as point 8. The document does not describe a new AI model training process for this submission.

Summary of Device Rationale:

The core of this 510(k) submission is the consolidation of thirteen previously cleared syngo.CT applications into a single "syngo.CT Applications" product. The applicant, Siemens Medical Solutions USA, Inc., states that the functionalities within this combined product are "unchanged compared to their former cleared descriptions" with only "minor enhancements and improvements" in syngo.CT Pulmo 3D (specifically regarding color assignments for lobe borders).

The document asserts that "The performance data demonstrates continued conformance with special controls for medical devices containing software." It also states, "The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results support that all the software specifications have met the acceptance criteria. Testing for verification and validation of the device was found acceptable to support the claims of substantial equivalence."

This implies that the "acceptance criteria" largely revolve around the continued functional performance and adherence to specifications of the already cleared individual applications, plus verification of the minor changes to syngo.CT Pulmo 3D, and the successful integration into a single software package. However, quantitative performance metrics for the device against specific clinical tasks are not provided in this 510(k) summary document, as the submission focuses on the substantial equivalence of the consolidated product to its predicate devices, rather than presenting new clinical efficacy data.

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

The CT Oncology application is intended to support fast-tracking routine diagnostic oncology, staging, and follow-up, by providing a tool for the user to perform the segmentation and volumetric evaluation of suspicious lesions in lung or liver.
The CT Colon Analysis application is intended to provide the user a tool to enable easy visualization and efficient evaluation of CT volume data sets of the colon.
The CT Dental application is intended to provide the user a tool to reconstruct panoramic and paraxial views of jaw.
The CT Lung Density Analysis application is intended to segment pulmonary, lobes, and airway, providing the user quantitative parameters, structure information to evaluate the lung and airway.
The CT Lung Nodule application is intended to provide the user a tool for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies.
The CT Vessel Analysis application is intended to provide a tool for viewing, manipulating, and evaluating CT vascular images.
The Inner view application is intended to perform a virtual camera view through hollow structures (cavities), such as vessels.
The CT Brain Perfusion application is intended to calculate the parameters such as: CBV, CBF, etc. in order to analyze functional blood flow information about a region of interest (ROI) in brain.
The CT Heart application is intended to segment heart and extract coronary artery. It also provides analysis of vascular stenosis, plaque and heart function.
The CT Calcium Scoring application is intended to identify calcifications and calculate the calcium score.
The CT Dynamic Analysis application is intended to support visualization of the CT datasets over time with the 3D/4D display modes.
The CT Bone Structure Analysis application is intended to provide visualization and labels for the ribs and spine, and support batch function for intervertebral disk.
The CT Liver Evaluation application is intended to provide processing and visualization for liver segmentation and vessel extraction. It also provides a tool for the user to perform liver separation and residual liver segments evaluation.

uWS-CT is a comprehensive software solution designed to process, review and analyze CT 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, as well as anatomical datasets. 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 provided document, a 510(k) summary for the uWS-CT software, does not contain detailed information about specific acceptance criteria and the results of a study proving the device meets these criteria in the way typically required for AI/ML-driven diagnostics.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (uWS-CT K173001) and several reference devices for its various CT analysis applications. It lists the functions of the new and modified applications (e.g., CT Lung Density Analysis, CT Brain Perfusion, CT Heart, CT Calcium Scoring, CT Dynamic Analysis, CT Bone Structure Analysis, CT Liver Evaluation) and compares them to those of the predicate and reference devices, indicating that their functionalities are "Same."

While the document states that "Performance data were provided in support of the substantial equivalence determination" and lists "Performance Evaluation Report" for various CT applications, it does not provide the specifics of these performance evaluations, such as:

• Acceptance Criteria: What specific numerical thresholds (e.g., accuracy, sensitivity, specificity, Dice score for segmentation) were set for each function?
• Reported Device Performance: What were the actual measured performance values?
• Study Design Details: Sample size, data provenance, ground truth establishment methods, expert qualifications, adjudication methods, or results of MRMC studies.

The document explicitly states:

• "No clinical study was required." (Page 16)
• Software Verification and Validation was provided, including hazard analysis, SRS, architecture description, environment description, and cyber security documents. However, these are general software development lifecycle activities and not clinical performance studies.

Therefore, based solely on the provided text, I cannot fill out the requested table or provide the detailed study information. The document suggests that the performance verification was focused on demonstrating functional equivalence rather than presenting quantitative performance metrics against pre-defined acceptance criteria in a clinical context.

Summary of what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance: This information is not provided in the document. The document states "Performance Evaluation Report" for various applications were submitted, but the content of these reports (i.e., the specific acceptance criteria and the results proving they were met) is not included in this 510(k) summary.

2. Sample size used for the test set and the data provenance: This information is not provided. The document states "No clinical study was required." The performance evaluations mentioned are likely internal verification and validation tests whose specifics are not detailed here.

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. Given that "No clinical study was required," it's unlikely a formal multi-expert ground truth establishment process for a clinical test set, as typically done for AI/ML diagnostic devices, was undertaken for this submission in a publicly available manner.

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: This information is not provided. The document explicitly states "No clinical study was required."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document states this is a "software solution intended to be used for viewing, manipulation, and storage of medical images" that "supports interpretation and evaluation of examinations within healthcare institutions." The listed applications provide "a tool for the user to perform..." or "a tool for the review and analysis..." which implies human-in-the-loop use. Standalone performance metrics are not provided.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): This information is not provided.

8. The sample size for the training set: This information is not provided. The document is a 510(k) summary for a software device, not a detailed technical report on an AI/ML model's development.

9. How the ground truth for the training set was established: This information is not provided.

In conclusion, the supplied document is a regulatory submission summary focused on demonstrating substantial equivalence based on intended use and technological characteristics, rather than a detailed technical report of performance studies for an AI/ML device with specific acceptance criteria and proven results. For this type of information, one would typically need access to the full 510(k) submission, which is not publicly available in this format, or a peer-reviewed publication based on the device's clinical performance.

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