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CT Perfusion V1.0 is an automatic calculation tool indicated for use in radiology. The device is an image processing software allowing computation of parametric maps from CT Perfusion data and extraction of volumes of interest based on numerical thresholds applied to the aforementioned maps. Computation of mismatch between extracted volumes is automatically provided.

The device is intended to be used by trained professionals with medical imaging education including but not limited to, physicians and medical technicians in the imaging assessment workflow by extraction and communication of metrics from CT Perfusion dataset.

The results of CT Perfusion V1.0 are intended to be used in conjunction with other patient information and, based on professional judgment, to assist the clinician in the medical imaging assessment. Trained professionals are responsible for viewing the full set of native images per the standard of care.

The device does not alter the original image. CT Perfusion V1.0 is not intended to be used as a standalone diagnostic device and shall not be used to take decisions with diagnosis or therapeutic purposes. Patient management decisions should not solely be based on CT Perfusion V1.0 results.

CT Perfusion V1.0 can be integrated and deployed through technical platforms, responsible for transferring, storing, converting formats, notifying of detected image variations and display DICOM of imaqing data.

The CT perfusion V1.0 application can be used to automatically compute qualitative as well as quantitative perfusion maps based on the dynamic (first-pass) effect of a contrast agent (CA). The perfusion application assumes that the input data describes a well-defined and transient signal response following rapid administration of a contrast agent.

Olea Medical proposes CT Perfusion V1.0 as an image processing application, Picture Archiving Communications System (PACS) software module that is intended for use in a technical environment, which incorporates a Medical Image Communications Device (MICD) (21 CFR 892.2020) as its technical platform.

CT Perfusion V1.0 image processing application is designed as a docker installed on a technical platform, a Medical Image Communications Device.

The CT Perfusion V1.0 application takes as input a full CT perfusion (CTP) sequence acquired following the injection of an iodine contrast agent.

By processing these input image series, the application provides the following outputs:

• . Parametric maps.
• Volume 1 and volume 2 segmentation in DICOM format. Fusion of segmented Volume 1 and 2 and CTP map could be provided in PNG and DICOM secondary captures.
• . Mismatch computation:
  • Mismatch volume = Volume 2-Volume 1
  • Mismatch ratio = Volume 2/Volume 1 O
  • Relative Mismatch = (Volume 2-Volume 1)/Volume 2*100. O

The CT Perfusion V1.0 offers automatic volume seqmentations based on a set of maps and thresholds. The user is able to tune/adjust these thresholds and the maps associated to thresholds in the configuration files.

Here's an analysis of the acceptance criteria and study for the CT Perfusion V1.0 device, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

Study Details

1. Sample size used for the test set and the data provenance: Not explicitly stated. The document mentions "all cases" for volume comparison, implying a dataset was used, but the specific number of cases is not provided. The provenance (country of origin, retrospective/prospective) is also not stated.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The study compares the performance of the new device to a predicate device, Olea Sphere V3.0, not to expert-derived ground truth.

3. Adjudication method for the test set: Not applicable, as the comparison is against a predicate device's output rather than an expert-adjudicated ground truth.

4. 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: No. This was not a MRMC comparative effectiveness study involving human readers with and without AI assistance. The study focuses on comparing the new device's output to a predicate device's output.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Yes, this was a standalone comparison of the CT Perfusion V1.0 algorithm's outputs against the Olea Sphere V3.0 algorithm's outputs.

6. The type of ground truth used: The "ground truth" for this study was the output of the predicate device, Olea Sphere V3.0.

7. The sample size for the training set: Not applicable. The document states that "CT Perfusion V1.0 does not contain any AI-based algorithms. All calculations are based on deterministic algorithms." Therefore, there is no training set in the machine learning sense.

8. How the ground truth for the training set was established: Not applicable, as there is no training set for a deterministic algorithm.

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