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The syngo. CT Neuro Perfusion software package is designed to evaluate areas of brain perfusion. The software processes images or volumes that were reconstructed from continuously acquired CT data after the injection of contrast media.

It generates the following result volumes:

• . Cerebral blood flow (CBF)
• Cerebral blood volume (CBV) .
• Local bolus timing (time to start (TTS), time to peak (TTP), time to drain (TTD)) .
• Mean transit time (MTT) .
• o Transit time to the center of the IRF (TMax)
• . Flow extraction product (permeability)
• . Temporal MIP
• . Temporal Average
• . Baseline Volume
• Modified dynamic input data .

The software allows the calculation of mirrored regions of interest and the visual inspection of time attenuation curves. One clinical application is to visualize the apparent blood perfusion and to calculate Hypoperfused Area and Mismatch Ratio in the brain tissue affected by acute stroke.

Areas of decreased perfusion appear as areas of changed signal intensity:

• · Lower signal intensity for CBF and CBV
• · Higher signal intensity for TTP, TTD, MTT, and TMax

A second application is to visualize blood brain barrier disturbances by modeling extra-vascular leakage of blood into the interstitial space. This additional capability may improve the differential diagnosis of brain tumors and may be helpful in therapy monitoring.

The syngo. CT Neuro Perfusion software allows the quantitative evaluation of dynamic CT data of the brain acquired during the injection of a compact bolus of iodinated contrast material. It mainly aids in the early differential diagnosis of acute ischemic stroke. Blood-brain-barrier (BBB) imaging feature supports the diagnostic assessment of brain tumors.

By providing images of e.g. cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and Mean Transit Time (MTT) from one set of dynamic CT images or volumes, syngo.CT Neuro Perfusion allows a quick and reliable assessment of the type and extent of cerebral perfusion disturbances, including fast evaluation of the tissue at risk and non-viable tissue in the brain. The underlying approaches for this application were cleared as part of the predicate device and remain unchanged in comparison to the predicate device

syngo.CT Neuro Perfusion allows simultaneous multi-slice processing and supports the workflow requirements in a stroke workflow. The availability of flow extraction product imaging extends the option to the diagnosis of brain tumors. A listing of device modifications as part of the new software version VB50 of syngo.CT Neuro Perfusion is as follows:

Additional Parameters Hypoperfused Area and Mismatch Ratio:

These parameters are calculated based on NVT (non-viable tissue) and TAR (tissue at risk). Hypoperfused Area is calculated based on the sum of NVT and TAR while the Mismatch Ratio is calculated by dividing Hypoperfused Area by NVT.

The provided text describes the Siemens syngo.CT Neuro Perfusion software, which evaluates brain perfusion from CT data. The new version (VB50) adds "Hypoperfused Area" and "Mismatch Ratio" parameters to aid in acute ischemic stroke assessment.

Here's a breakdown of the acceptance criteria and the study that supports the device, based on the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative "acceptance criteria" for the device's performance in a traditional sense (e.g., "sensitivity must be > X%" or "ICC must be > Y"). Instead, the study aims to demonstrate equivalence of the new parameters with a reference device and high concordance between existing and new parameters in clinical decision-making.

The key performance metrics reported are focused on the concordance of clinical decisions and correlation of volumes between the subject device (syngo.CT Neuro Perfusion VB50, referred to as Package A in the study) and a reference device (iSchemaView RAPID, referred to as Package B in the study).

Note: The document emphasizes that despite some volumetric differences, these did not "impact eligibility for MT" and "high agreement" was achieved in clinical decision-making.

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

• Test Set Sample Size:
  • Mechanical Thrombectomy (MT) group: 62 patients
  • No Mechanical Thrombectomy (NMT) group: 56 patients
  • Total: 118 patients (62 + 56)
• Data Provenance: Retrospective. Patients presenting with Acute Ischemic Stroke (AIS) between January 2017 and December 2018 were screened. The study was conducted at a "single center." The country of origin is not explicitly stated in the provided text.

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

The document does not explicitly describe a separate ground truth establishment process involving a specific number of experts for the test set. The comparison is between the subject device's outputs and a reference device's outputs, as well as the observed clinical outcomes (MT vs. NMT) and adherence to a clinical standard (DEFUSE III criteria).

The "Methodology of the study" mentions evaluating "Individual patient triage between MT and NMT groups... to determine if the final clinical decision, based on a combination of factors, would remain the same regardless of eligibility determined based on perfusion imaging." This implies that actual clinical decisions by medical professionals (whose qualifications are not specified in this document) served as a benchmark in combination with the reference device's analysis.

4. Adjudication Method for the Test Set

The document does not describe an explicit "adjudication method" involving multiple experts resolving discrepancies for the test set results from the devices. Instead, it compares the outputs of two software packages (subject device and reference device) and then assesses the concordance of their outputs, particularly in the context of broader clinical guidelines (DEFUSE III). The focus is on how well the software outputs align with clinical decision-making criteria.

The "concordance" rates are reported based on direct comparison of the outputs and how they align with "go versus no-go" decisions for MT when perfusion criteria alone, and then additional clinical criteria, are considered.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not explicitly described in terms of human readers improving with AI vs. without AI assistance. The study described compares the outputs of two software packages (the subject device and a predicate device) and their alignment with clinical decision-making. It does not measure the improvement of human readers using these tools.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the study described is a standalone performance evaluation of the algorithm. It compares the output parameters (e.g., core infarct volume, hypoperfused area, mismatch ratio) generated by the "syngo.CT Neuro Perfusion" software (Package A) with those generated by the "iSchemaView RAPID" software (Package B). The evaluation focuses on the concordance of the software's outputs with each other and with established clinical guidelines, without directly assessing human-in-the-loop performance.

7. The Type of Ground Truth Used

The type of "ground truth" used is a combination of:

• Reference Device Output: The outputs from the iSchemaView RAPID software (K182130) served as a key comparison point for the new parameters, as stated: "Equivalence of the parameters 'Hypoperfused Area' and 'Mismatch Ratio' with the reference device iSchemaView RAPID (K182130) was shown mainly by Bathla et al. 2020."
• Clinical Decision-Making Criteria/Outcomes: The study assessed concordance with "go versus no-go" decisions for Mechanical Thrombectomy (MT) based on perfusion outputs alone, and then incorporating additional neuroimaging eligibility criteria as defined in DEFUSE III (e.g., ASPECTS, site of vessel occlusion). This implies that adherence to established clinical guidelines and actual patient triage decisions served as a form of "ground truth" for clinical utility.
• Absence of Pathology/Direct Outcomes: There is no mention of pathology reports or direct patient outcomes data being used as ground truth for volumetric measurements or delineation of hypoperfused areas.

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size used for the training set for the syngo.CT Neuro Perfusion software. The study presented focuses on the validation of the new parameters (Hypoperfused Area and Mismatch Ratio) in comparison to a reference device and clinical criteria.

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

As no information is provided about a training set, the method for establishing its ground truth is also not described in the document. The text highlights that "The calculation of these values are from already existing parameters NVT (non-viable-tissue) and TAR (tissue at risk) within the commercially available syngo.CT Neuro Perfusion SOMARIS/8 VB20 release (K163284)," suggesting that the core algorithms for NVT and TAR were previously established and cleared, and the new parameters are derived from them.

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The syngo.CT Neuro Perfusion software package is designed to evaluate areas of brain perfusion. The software processes images or volumes that were reconstructed from continuously acquired CT data after the injection of contrast media.

It generates the following result volumes:

• Cerebral blood flow (CBF)
• Cerebral blood volume (CBV)
• Local bolus timing (time to start (TTS), time to peak (TTP), time to drain (TTD))
• Mean transit time (MTT)
• Transit time to the center of the IRF (TMax)
• Flow extraction product (permeability)
• Temporal MIP
• Temporal Average
• Baseline Volume
• Modified dynamic input data

The software also allows the calculation of mirrored regions or volumes of interest and the visual inspection of time attenuation curves. One clinical application is to visualize the apparent blood perfusion and the parameter mismatch in brain tissue affected by acute stroke.

Areas of decreased perfusion appear as areas of changed signal intensity:

• Lower signal intensity for CBF and CBV
• Higher signal intensity for TTP, TTD, MTT, and TMax

A second application is to visualize blood brain barrier disturbances by modeling extra-vascular leakage of blood into the interstitial space. This additional capability may improve the differential diagnosis of brain tumors and be helpful in therapy monitoring.

The syngo. CT Neuro Perfusion software allows the quantitative evaluation of dynamic CT data of the brain acquired during the injection of a compact bolus of iodinated contrast material. It mainly aids in the early differential diagnosis of acute ischemic stroke. Blood-brain-barrier (BBB) imaging also supports the diagnostic assessment of brain tumors.

By providing images of e.g. cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and Mean Transit Time (MTT) from one set of dynamic CT images or volumes, syngo.CT Neuro Perfusion allows a quick and reliable assessment of the type and extent of cerebral perfusion disturbances. The underlying approaches have been validated in extensive clinical studies and have been in routine clinical use for more than 10 vears.

The current syngo.CT Neuro Perfusion implementation allows simultaneous multi-slice processing and supports the workflow requirements in a stroke workflow. The availability of flow extraction product imaging extends the option to the diagnosis of brain tumors.

The provided text does not contain detailed information about the acceptance criteria or a specific study that proves the device meets those criteria. It mainly focuses on the device's substantial equivalence to a predicate device and its indications for use.

However, based on the information available, I can infer some aspects related to non-clinical testing and general acceptance.

Here’s an attempt to structure the answer based on the provided text, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a sample size for a test set or provide details on data provenance (e.g., country of origin, retrospective/prospective study design). The discussion of testing is general and relates to non-clinical software verification and validation.

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 in the document. The filing describes non-clinical testing for software verification and validation rather than a clinical performance study with expert ground truth.

4. Adjudication method 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

A multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned in the provided text. The document describes a software package for post-processing CT data and does not detail studies on human reader performance with or without AI assistance.

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

The document discusses "non clinical tests" for software verification and validation, and states that "all the software specifications have met the acceptance criteria." This implies a form of standalone performance assessment against predefined specifications, but the specifics of how "standalone" this was (e.g., if it involved simulated data or real patient data processed without human intervention for evaluation) are not detailed. It's not a clinical standalone study in the sense of diagnostic accuracy against a ground truth.

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

The document refers to "non clinical tests" and "software specifications" rather than clinical ground truth like pathology or expert consensus from a clinical study. The "ground truth" for these non-clinical tests would likely be the expected output or behavior according to the software's functional requirements and design specifications.

8. The sample size for the training set

The document does not specify a sample size for a training set. The software likely relies on pre-established algorithms for generating perfusion maps, which would have been developed and "trained" (or validated) on various datasets over many years, as indicated by: "The underlying approaches have been validated in extensive clinical studies and have been in routine clinical use for more than 10 years." However, specifics about this device's training set are absent.

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

The document mentions that "The underlying approaches have been validated in extensive clinical studies and have been in routine clinical use for more than 10 years." This suggests that the ground truth for the "training" (or more accurately, the development and historical validation of the underlying algorithms) would have been established through clinical studies, but the specific methods (e.g., expert consensus, correlation with other imaging modalities, or patient outcomes) are not detailed in this 510(k) summary for this particular device.

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