Search Results

CDM Insights is a post-processing image analysis software that assists trained healthcare practitioners in viewing. analyzing, and evaluating MR brain images of adults > 45 years of age.

CDM Insights provides the following functionalities:

• Automated segmentation and quantitative analysis of individual brain structures and white matter hyperintensities
• Quantitative comparison of brain structures and derived values with normative data from a healthy population
• Presentation of results for reporting that includes numerical values as well as visualization of these results

CDM Insights is automated post-processing medical device software that is used by radiologists, neurologists, and other trained healthcare practitioners familiar with the post-processing of magnetic resonance images. It accepts DICOM images using supported protocols and performs: automatic segmentation and quantification of brain structures and lesions, automatic post-acquisition analysis of diffusionweighted magnetic resonance imaging (DWI) data, and comparison of derived image metrics from multiple time-points.

The values for a given patient are compared against age-matched percentile data from a population of healthy reference subjects. White matter hyperintensities can be visualized and quantified by volume. Output of the software provides numerical values and derived data as graphs and anatomical images with graphical color overlays.

CDM Insights output is provided in standard DICOM format as a DICOMencapsulated PDF report.

The provided text describes the acceptance criteria and the study that proves the device (CDM Insights) meets these criteria. Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sizes and Data Provenance

• Test Set Sample Size:
  • Accuracy of segmentation: 60 cases for brain region and WMH segmentation accuracy.
  • Repeatability: 121 healthy individuals.
  • Reproducibility: Over 1500 unique subjects.
  • Accuracy of percentiles: Almost 2000 test scans.
• Data Provenance: The data included scans acquired on different scanner models from multiple manufacturers. It included scans from a group of cognitively healthy individuals and a mix of individuals with disorders (Alzheimer's disease, mild cognitive impairment, frontotemporal dementia, multiple sclerosis). Data were obtained from 13 different source cohorts, with 7 of these based in the USA. The text indicates that information was available on race or ethnicity for the majority of individuals, with more than 20% non-white and more than 5% Hispanic. The studies included both retrospective (existing scans) and potentially some prospective components (implied by "repeated MRI scans" for repeatability) but primarily seems based on existing datasets.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not explicitly stated as a number, but referred to as "US board-certified neuroradiologists."
• Qualifications of Experts: US board-certified neuroradiologists. Their years of experience are not specified.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1). It states "tested against a gold standard of US board-certified neuroradiologists," implying their consensus or individual expert delineation as the ground truth.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided text does not mention a multi-reader, multi-case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance. The study focuses on the standalone performance of the algorithm.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done. The performance metrics (Dice scores, visual ratings) are presented for the algorithm's output directly against expert-established ground truth, without a human-in-the-loop component described in these performance tests.

7. Type of Ground Truth Used

The ground truth used for accuracy assessments (segmentation and cortical surfaces) was established by expert consensus/delineation (a "gold standard of US board-certified neuroradiologists").

8. Sample Size for the Training Set

The "almost 2000 test scans" for percentile accuracy are explicitly stated to be "independent of training scans used to derive percentiles." However, the sample size for the training set itself is not specified in this document.

9. How Ground Truth for Training Set Was Established

The document states that the percentiles were "used to derive percentiles," implying that the training set was used to construct the normative data. However, the method for establishing ground truth within that training set (e.g., for segmentation, if those were part of the training) is not detailed. It's implied that the normative data itself serves as the "ground truth" for the percentile comparisons.

Ask a specific question about this device

The CDMx-H is intended for dental radiographic examination and diagnosis of the teeth, jaw and oral structure by using scanned dental x-ray images sent through the digital x-ray sensor.

Not Found

The provided document is a 510(k) clearance letter from the FDA for a device named CDMx-H. It states that the device is "substantially equivalent" to legally marketed predicate devices. Unfortunately, this document does not contain the specific acceptance criteria, performance data, or details about the studies conducted to demonstrate its performance.

The FDA 510(k) clearance process primarily focuses on substantial equivalence to a predicate device, meaning it has the same intended use and technological characteristics, or if the technological characteristics are different, that the differences do not raise new questions of safety and effectiveness and that the device is as safe and effective as the predicate device. It does not typically require the submission of detailed performance studies in the same way a PMA (Premarket Approval) might.

Therefore,Based on the provided text, I cannot extract the information required to populate the table and answer your questions directly. The document is solely an FDA clearance letter and does not include the details of the studies conducted to establish the device's performance against specific acceptance criteria.

To answer your request, I would need access to the actual 510(k) summary or the full submission document, which would detail the testing and performance data.

Ask a specific question about this device

Ask a specific question about this device

A software package and instrument interface that is used for quantitative analyses of high performance liquid chromatography (HPLC) test kits.

The CDM makes use of a 486 IBM compatible computer and a separate communications interface. The system accepts signals from a detector, integrates the chromatograms, identifies reference peaks and performs calculations of percent area. In addition, the CDM can control pumps and an automated sampler and store quality control data.

The provided document describes the Bio-Rad Laboratories Clinical Data Management (CDM) system, which is a software package and instrument interface used for quantitative analyses of high-performance liquid chromatography (HPLC) test kits. The study described aims to establish substantial equivalence of the CDM to existing predicate devices, specifically the Hewlett-Packard 3392A Reporting Integrator and, for analytical comparison, the Shimadzu CR501.

Acceptance Criteria and Reported Device Performance

The acceptance criterion implicitly is comparability to the existing Shimadzu CR501 integrator for analytical sensitivity and accuracy across various HPLC tests. The device performance is deemed acceptable if the results (standard deviation, coefficient of variation, correlation coefficient, y-intercept, and slope) are comparable to those obtained with the CR501.

1. Sample sizes used for the test set and the data provenance:

The document does not explicitly state the sample sizes (e.g., number of specimens or chromatograms) used for the analytical comparison. It mentions "each of the following five tests" and provides sensitivity and accuracy data for various analytes within these tests. The data provenance is not specified, but it implies a laboratory setting where these HPLC tests were performed. It is a retrospective analysis of the device's performance against a comparative device rather than a prospective clinical study involving patient data.

2. 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):

This study is an analytical comparison of two laboratory instruments (integrators) for quantitative analysis. The "ground truth" here is the quantitative analytical results obtained by a well-established and accepted method (Shimadzu CR501 integrator). Therefore, there were no human experts establishing a "ground truth" in the diagnostic sense (like radiologists interpreting images). The accuracy is measured against the output of the reference instrument.

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

Not applicable. This is an analytical device comparison, not a diagnostic study requiring adjudication of expert interpretations.

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:

Not applicable. This is not an AI-assisted diagnostic study or an MRMC study. It's a comparison of two analytical instruments.

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

Yes, this study represents a standalone comparison of the CDM system's performance (algorithm-driven integration and calculation) against another standalone instrument (CR501 integrator). There is no "human-in-the-loop performance" in evaluating the integrators' quantitative outputs. The humans operate the HPLC systems, but the comparison is on the data processing output.

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

The "ground truth" is established by the analytical measurements and calculations performed by the well-accepted and commercially available Shimadzu CR501 integrator. This is an analytical reference standard rather than a clinical ground truth like pathology or expert consensus. The assumption is that the CR501 provides accurate and precise measurements.

7. The sample size for the training set:

Not applicable. This document describes a performance evaluation of a device, not the development or training of a machine learning algorithm. The CDM is a "Clinical Data Management System" that performs calculations, integration, and control, rather than a learning AI system requiring a specific training set as understood in modern AI.

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

Not applicable, as there is no mention of a training set for an AI algorithm.

Ask a specific question about this device