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Densitas densityai™ is a software application intended for use with compatible full field digital mammography and digital breast tomosynthesis systems. Densityai™ provides an ACR BI-RADS Atlas 5th Edition breast density category to aid interpreting physicians in the assessment of breast tissue composition. Densitas densityai™ produces adjunctive information. It is not a diagnostic aid.

Densitas densityai™ is a standalone software application that automatically analyzes "for presentation" data from digital breast x-ray systems, including digital breast tomosynthesis exams, to assess breast tissue composition. The software processes the data according to proprietary algorithms and generates a Breast Density Grade in accordance with the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) 5th edition density classification scale. Densitas densityai™ data output is packaged for viewing on a mammography workstation or PACS as a DICOM mammography Structured Report or Secondary Capture. Output may also be transmitted to a RIS. Densitas densityai™ reports are configured to provide the following data based on the BI-RADS 5th edition breast density classification grade: For each patient: DENSITAS breast density grade (BDG).

Here's a summary of the acceptance criteria and study details for the densitas densityai™ device, based on the provided FDA 510(k) summary:

1. Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state pre-defined acceptance criteria (e.g., minimum accuracy percentages). Instead, it presents the device's performance metrics, implying that these results were deemed acceptable for substantial equivalence. The performance is assessed by comparing the device's breast density classifications against expert radiologist consensus.

Table of Performance for densitas densityai™ (all scan types)

Additionally, other performance aspects were assessed through internal testing:

• Reliability: Measured by Pearson's Correlation Coefficient for percent density, dense breast area, and total area measurements between left and right breasts.
• Accuracy: Validated for percent density and total area measurements.
• Reproducibility: Measured by Pearson's Correlation Coefficient by running the algorithm twice over the same images.
• Inverse Relationship with Age: Pearson's Correlation Coefficient between percent density and age.

2. Sample Size and Data Provenance

• Test Set Sample Size: n=796 cases
• Data Provenance: Not explicitly stated regarding country of origin or whether it was retrospective/prospective. The description says "a large dataset that spanned all compatible scanner types," which implies diversity, but specifics are missing.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Four expert radiologists.
• Qualifications: "Expert radiologists" is stated, but no specific experience (e.g., years of experience, subspecialty certification) is detailed in the provided document.

4. Adjudication Method

• The ground truth was established by a "consensus assessment of four expert radiologists' independent readings." This implies an adjudication method where their individual readings were combined to form a single reference standard, but the specific consensus rule (e.g., majority vote, specific tie-breaking) is not described.

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

• No MRMC comparative effectiveness study was explicitly mentioned. The study focused on the standalone performance of the AI device compared to expert consensus, not on how human readers' performance improved with AI assistance.

6. Standalone Performance

• Yes, a standalone performance study was done. The results presented in the tables (Kappa, Accuracy) directly assess the algorithm's performance in categorizing breast density against the expert radiologist consensus without human intervention.

7. Type of Ground Truth Used

• Expert Consensus: The ground truth for the validation study was established through "a consensus assessment of four expert radiologists' independent readings of overall breast composition." This falls under expert consensus.

8. Sample Size for the Training Set

• The document does not specify the sample size for the training set. It only describes the validation testing.

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

• The document does not provide details on how the ground truth for the training set was established. Since the training set size isn't mentioned, neither are the methods for its ground truth. The information provided focuses solely on the validation/test set.

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DM-Density is a software application intended for use with compatible full field digital mammography systems. DM-Density calculates percent breast density defined as the ratio of fibroglandular tissue to total breast area estimates. DM-Density provides these numerical values for each breast as well as a density category to aid interpreting physicians in the assessment of breast tissue composition. DM-Density produces adjunctive information. It is not a diagnostic aid.

DM-Density is a standalone software application that automatically analyzes "for presentation" full field digital mammograms to calculate breast tissue composition. The software processes full field digital mammograms according to proprietary algorithms and generates a Breast Density Grade in accordance with the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) density classification scales. DM-Density has been validated on Hologic's Selenia Dimensions and Lorad Selenia systems. DM-Density data output is packaged for viewing on a mammography workstation or PACS as a DICOM mammography Structured Report or Secondary Capture. Output may also be transmitted to a RIS.

Here's a breakdown of the acceptance criteria and study information for DM-Density, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not provide specific numerical thresholds for "acceptance" (e.g., Pearson's correlation coefficient > 0.9, Kappa > 0.8). It only states that testing was performed "in accordance with Densitas' design control processes" and that "DM-Density product specifications have been met."

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

The exact sample size for each specific test (Reliability, Accuracy, Reproducibility, Inverse relationship to age) is not explicitly stated in the provided document.

• Data Provenance: The data used for reproducibility testing was from "subjects who had two mammograms acquired on compatible mammography acquisition systems within a two year time period." The document doesn't specify the country of origin, but it does mention that DM-Density has been validated on Hologic's Selenia Dimensions and Lorad Selenia systems.

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

• Number of Experts: "Expert radiologist visual assessments" were used for validation, but the exact number of experts is not specified.
• Qualifications of Experts: They are referred to generally as "expert radiologists." No further details on their specific experience (e.g., years of experience, subspecialty) are provided.

4. Adjudication Method for the Test Set

The adjudication method for establishing ground truth from the expert radiologists is not explicitly stated. It mentions "expert radiologist visual assessments," but doesn't specify if it was a consensus, majority vote, or other method.

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

• Was an MRMC study done? No, the document states, "There was no human clinical testing required to support the medical device." This indicates that no MRMC study involving human readers and AI assistance was conducted or reported.

6. Standalone (Algorithm Only) Performance Study

• Was a standalone study done? Yes, the described performance testing (Reliability, Accuracy, Reproducibility, Inverse Relationship to Age) assesses the DM-Density software's performance as a standalone algorithm without human intervention.
  • The "Accuracy" assessment specifically states "validating DM-Density percent density and total area measurements" and "validating the Breast Density Grade assessments to known Breast Density Grade assessments using the Kappa statistic," which are direct measures of the algorithm's performance against derived ground truth.

7. Type of Ground Truth Used

• For Accuracy (Breast Density Grade): "expert radiologist visual assessments of mammography density" were used to establish "known Breast Density Grade assessments." This indicates expert consensus or individual expert assessment as ground truth for density categories.
• For Accuracy (Percent Density) and Reliability: The ground truth for percent density, dense breast area, and total area measurements is implied to be a carefully measured value derived from the same images, likely through a reference method or manual segmentation, which the algorithm is then compared against. The document doesn't explicitly state the method for this specific ground truth, but it's not pathology or outcomes data.

8. Sample Size for the Training Set

The sample size for the training set is not provided in the document. The document refers to "proprietary algorithms" but does not detail their development or the data used for training.

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

The document does not provide information on how the ground truth for the training set was established. It only discusses "proprietary algorithms" and validation testing.

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