Search Results

CoverScan is a medical image management and processing software package that allows the display, analysis and postprocessing of DICOM compliant medical images and MR data.

CoverScan provides both viewing and analysis capabilities to ascertain quantified metrics of multiple organs such as the heart, lungs, liver, spleen, pancreas and kidney.

CoverScan provides measurements in different organs to be used for the assessment of longitudinal and transversal relaxation time and rate (T1, SR-T1, cT1, T2), fat content (proton density fat fraction or PDFF) and metrics of organ function (e.g., left ventricular ejection fraction and lung fractional area change on deep inspiration).

These metrics derived from the interpreted by a licensed physician, vield information that may assist in diagnosis, clinical management and monitoring of patients.

CoverScan is not intended for asymptomatic screening. This device is intended for use with Siemens 1.5T MRI scanners.

CoverScan is a post-processing software system comprised of several software modules. It uses acquired MR data to produce metrics of quantified tissue characteristics of the heart, lungs, liver, kidneys, pancreas and spleen.

Metrics produced by CoverScan can be used by licensed physicians in a clinical setting for the purposes of assessing multiple organs.

The provided documentation describes the CoverScan v1 device, which is a medical image management and processing software. While it mentions internal verification and validation testing, and that product specifications were met, it does not explicitly state specific quantitative acceptance criteria or detailed results of a study proving the device meets those criteria, especially in a comparative effectiveness context (MRMC).

The document primarily focuses on establishing substantial equivalence to predicate devices through a qualitative comparison of intended use, technological characteristics, and performance features. It indicates that "bench testing included functional verification to ensure software installation, licensing, labeling, and feature functionality all met design requirements" and that "The accuracy and precision of device measurements was assessed using purpose-built phantoms and in-vivo acquired data from volunteers." However, it does not provide the specific quantitative results of these assessments against defined acceptance criteria.

Therefore, much of the requested information cannot be directly extracted from the provided text. I will explain what information is available and highlight what is missing.

Here's an attempt to structure the information based on the provided text, with clear indications where the information is not present:

Acceptance Criteria and Device Performance Study (CoverScan v1)

The provided document indicates that CoverScan v1 underwent internal verification and validation testing to confirm it met product specifications and its overall ability to meet user needs was validated. However, specific, quantitative acceptance criteria for metrics like accuracy, sensitivity, specificity, etc., are not explicitly defined in the provided text. Similarly, the reported numerical device performance against such criteria is not detailed. The document broadly states that "The accuracy and precision of device measurements was assessed using purpose-built phantoms and in-vivo acquired data from volunteers."

Missing Information: A detailed table of acceptance criteria with numerical targets and the corresponding reported device performance values.

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

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

• Test Set Sample Size: The document mentions "in-vivo acquired data from volunteers" and that "Volunteers participating in the performance testing were representative of the intended patient population." However, the specific number of cases or volunteers used in the test set is not provided.
• Data Provenance: The document does not explicitly state the country of origin of the data or whether it was retrospective or prospective. It only mentions "in-vivo acquired data from volunteers," implying prospectively collected data for assessment, but this is not explicitly stated.

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 text indicates that the device produces quantitative metrics that are "interpreted by a licensed physician" to "assist in diagnosis, clinical management and monitoring of patients." However, it does not describe how ground truth was established for the performance testing, nor the number or qualifications of experts involved in that process.

4. Adjudication method for the test set

This information is not provided in the document. There is no mention of an adjudication process (e.g., 2+1, 3+1, none) for the test set's ground truth.

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

The document does not indicate that a MRMC comparative effectiveness study was performed. The device is described as a "post-processing software system" that provides "quantified metrics" and does not describe AI assistance for human readers in a diagnostic workflow. The primary method of performance assessment mentioned is the accuracy and precision of the measurements themselves using phantoms and volunteer data, not reader performance.

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

The performance testing described involves the device generating quantitative metrics. The phrase "The accuracy and precision of device measurements was assessed" suggests a standalone performance assessment of the algorithm's output (measurements) against some reference (phantoms, in-vivo data). While the final interpretation is by a physician, the core performance reported relates to the device's ability to produce these measurements consistently and accurately, which aligns with a standalone assessment of the algorithms.

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

The ground truth for the "accuracy and precision of device measurements" was established using:

• Purpose-built phantoms: These phantoms "containing vials with different relaxation times corresponding to the physiological ranges of tissue values." This provides a known, controlled physical ground truth.
• In-vivo acquired data from volunteers: For this type of data, the text does not specify how ground truth was established (e.g., through other validated methods, clinical outcomes, or expert consensus on a final diagnosis based on all available information). It only mentions that the studies "covering a range of physiological values for cT1, T1 and PDFF."

8. The sample size for the training set

This information is not provided in the document. The document describes CoverScan v1 as software that takes acquired MR data and processes it; it does not detail any machine learning training processes or associated datasets.

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

As there is no mention of a specific training set in the provided text, the method for establishing its ground truth is also not described. The document implies that the device is a measurement and processing tool rather than a machine learning model that requires a dedicated training set.

Ask a specific question about this device