TOMTEC-ARENA TTA2

• K Number: K150122
• Device Name: TOMTEC-ARENA TTA2
• Manufacturer: TOMTEC IMAGING SYSTEMS, GMBH
• Date Cleared: 2015-02-13 ( 24 days)
• Product Code: LLZ
• Regulation Number: 892.2050
• Type: Traditional
• Panel: RA
• Reference & Predicate Devices: K132544 , K110667

Intended Use

Indications for use of TomTec-Arena software are quantification and reporting of cardiovascular, fetal, and abdominal structures and function of patients with suspected disease to support the physicians in the diagnosis.

Device Description

TomTec-Arena™ is a clinical software package for reviewing, quantifying and reporting digital medical data. The software is compatible with different TomTec Image-Arena™ platforms and TomTec-Arena Server®, their derivatives or third party platforms.

Platforms enhance the workflow by providing the database, import, export and other services. All analyzed data and images will be transferred to the platform for archiving, reporting and statistical quantification purposes.

TomTec-Arena™ TTA2 consists of the following optional modules:

• Image-Com
• 4D LV-Analysis and 4D LV-Function
• 4D RV-Function
• 4D Cardio-View
• 4D MV-Assessment
• Echo-Com
• 2D Cardiac-Performance Analysis
• 2D Cardiac-Performance Analysis MR
• 4D Sono-Scan
• Reporting
• Worksheet
• TomTec-Arena Client

AI/ML Overview

The provided text does not contain detailed acceptance criteria or a study that explicitly proves the device meets those criteria. Instead, it describes a substantial equivalence submission for the TomTec Arena TTA2, a picture archiving and communications system.

The document focuses on demonstrating that the new device is substantially equivalent to previously marketed predicate devices (TomTec-Arena 1.0 and Image-Arena 4.5). It outlines changes made to the device, primarily bug fixes, operability enhancements, and feature changes (repackaging or new appearance of existing technology).

It explicitly states: "Substantial equivalence determination of this subject device was not based on clinical data or studies." This means that a detailed clinical performance study with defined acceptance criteria for the device's diagnostic performance was not conducted as part of this submission for determining substantial equivalence.

While non-clinical performance data (software testing and validation) was performed according to internal company procedures, the acceptance criteria for this testing are not explicitly stated in a quantifiable manner within the provided text, beyond "expected results and acceptance (pass/fail) criteria have been defined in all test protocols."

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, and ground truth establishment cannot be extracted from the provided text.

Here is a summary of what can be extracted:

1. A table of acceptance criteria and the reported device performance:

   • Acceptance Criteria: Not explicitly stated in quantifiable terms for the device's diagnostic performance. The document mentions "expected results and acceptance (pass/fail) criteria have been defined in all test protocols" for internal software testing.
   • Reported Device Performance:
     • All automated tests were reviewed and passed.
     • Feature complete test completed without deviations.
     • Functional tests are completed.
     • Measurement verification is completed without deviations.
     • All non-verified bugs have been evaluated and are rated as minor deviations and deferred to the next release.
     • The overall product concept was clinically accepted and supports the conclusion that the device is as safe as effective, and performs as well as or better than the predicate device.
     • The Risk-Benefit Assessment concludes that the benefit is superior to the risk, and the risk is low.
     • The data are sufficient to demonstrate compliance with essential requirements covering safety and performance.
     • The claims made in the device labeling are substantiated by clinical data (via literature review).

2. Sample size used for the test set and the data provenance: Not applicable, as no clinical study with a test set was detailed. Non-clinical software testing involved various test cases but the sample size (number of test cases) and their provenance are not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no clinical study with a test set requiring expert ground truth was detailed.

4. Adjudication method for the test set: Not applicable.

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. The device is a "Picture archiving and communications system" and "Image Review and Quantification Software," not explicitly an AI-assisted diagnostic device, and no MRMC study was mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The focus is on software functionality and equivalence to predicate devices, not AI algorithm performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For non-clinical software testing, the "ground truth" would be the expected output of the software functions based on established specifications and requirements. For the "clinical acceptance" mentioned, it refers to a literature review, implying published clinical data served as the basis for concluding safety and effectiveness relative to predicate devices and general medical standards.

8. The sample size for the training set: Not applicable, as this is not an AI/ML device with a training set.

9. How the ground truth for the training set was established: Not applicable.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).