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510(k) Data Aggregation
(266 days)
MammoScreen BD
MammoScreen® BD is a software application intended for use with compatible full-field digital mammography and digital breast tomosynthesis systems. MammoScreen BD evaluates the breast tissue composition to provide an ACR BI-RADS 5th Edition breast density category. The device is intended to be used in the population of asymptomatic women undergoing screening mammography who are at least 40 years old.
MammoScreen BD only produces adjunctive information to aid interpreting physicians in the assessment of breast tissue composition. It is not a diagnostic software.
Patient management decisions should not be made solely based on analysis by MammoScreen BD.
MammoScreen BD is a software-only device (SaMD) using artificial intelligence to assist radiologists in the interpretation of mammograms. The purpose of the MammoScreen BD software is to automatically process a mammogram to assess the density of the breasts.
MammoScreen BD processes the 2D-mammograms standard views (CC and/or MLO of FFDM and/or the 2DSM from the DBT) to assess breast density.
For each examination, MammoScreen BD outputs the breast density following the ACR BI-RADS 5th Edition breast density category.
MammoScreen BD outputs can be integrated with compatible third-party software such as MammoScreen Suite. Results may be displayed in a web UI, as a DICOM Structured Report, a DICOM Secondary Capture Image, or within patient worklists by the third-party software.
MammoScreen BD takes as input a folder with images in DICOM formats and outputs breast density assessment in a form of a JSON file.
Note that the MammoScreen BD outputs should be used as complementary information by radiologists while interpreting breast density. Patient management decisions should not be made solely on the basis of analysis by MammoScreen BD, the medical professional interpreting the mammogram remains the sole decision-maker.
Here's a breakdown of the acceptance criteria and the study that proves MammoScreen BD meets them, based on the provided FDA 510(k) clearance letter:
Acceptance Criteria and Device Performance Study
The study primarily focuses on the standalone performance of MammoScreen BD in assessing breast density against an expert consensus Ground Truth. The key metric for performance is the quadratically weighted Cohen's Kappa (${\kappa}$).
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Primary Objective: Superiority in standalone performance for density assignment of MammoScreen BD compared to a pre-determined reference value (${\kappa_{\text{reference}} = 0.85}$). | Hologic: ${\kappa_{\text{quadratic}} = 89.03}$ [95% CI: 87.43 – 90.56] |
| Acceptance Criteria (Statistical): The one-sided p-value for the test $H_0: \kappa \leq 0.85$ is less than the significance level ($\alpha=0.05$) AND the lower bound of the 95% confidence interval for Kappa $> 0.85$, indicating that the observed weighted Kappa is statistically significantly greater than 0.85. | Hologic Envision: ${\kappa_{\text{quadratic}} = 89.54}$ [95% CI: 86.88 – 91.69] |
| GE: ${\kappa_{\text{quadratic}} = 93.19}$ [95% CI: 90.50 – 94.92] |
All reported Kappa values exceed the reference value of 0.85, and their 95% confidence intervals' lower bounds are also above 0.85, satisfying the acceptance criteria.
2. Sample Size and Data Provenance
Test Set:
- Hologic (original dataset): 922 patients / 1,155 studies
- Hologic Envision (new system for subject device): 500 patients / 500 studies
- GE (new system for subject device): 376 patients / 490 studies
Data Provenance:
- Hologic (original dataset):
- USA: 658 studies (distributed as A:85, B:269, C:241, D:63)
- EU: 447 studies (distributed as A:28, B:169, C:214, D:86)
- Hologic Envision: USA: 500 studies (distributed as A:50, B:200, C:200, D:50)
- GE:
- USA: 359 studies (distributed as A:38, B:155, C:139, D:31)
- EU: 129 studies (distributed as A:4, B:45, C:61, D:19)
All data for the test sets appears to be retrospective, as it's stated that the "Data used for the standalone performance testing only belongs to the test group" and is distinct from the training data.
3. Number of Experts and Qualifications for Ground Truth
- Number of Experts: 5 breast radiologists
- Qualifications: At least 10 years of experience in breast imaging interpretation.
4. Adjudication Method for the Test Set
The ground truth was established by majority rule among the assessment of the 5 breast radiologists. This implies a 3-out-of-5 or more agreement for a given breast density category to be assigned as ground truth.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
There is no mention of an MRMC comparative effectiveness study being performed to assess how much human readers improve with AI vs. without AI assistance. The study focuses solely on the standalone performance of the AI algorithm. The device is described as "adjunctive information to aid interpreting physicians," but its effect on radiologist performance isn't quantified in this document.
6. Standalone Performance (Algorithm Only)
Yes, a standalone performance study was explicitly conducted. The results for the quadratically weighted Cohen's Kappa presented in the table above (89.03 for Hologic, 89.54 for Hologic Envision, and 93.19 for GE) are all for the algorithm's performance only ("MammoScreen BD against the radiologist consensus assessment").
7. Type of Ground Truth Used
The ground truth used was expert consensus based on the visual assessment of 5 breast radiologists.
8. Sample Size for the Training Set
- Total number of studies: 108,775
- Total number of patients: 32,368
9. How the Ground Truth for the Training Set was Established
The document states that the training modules are "trained with very large databases of annotated mammograms." While "annotated" implies ground truth was established, the specific method for establishing ground truth for the training set is not detailed in the provided text. It only specifies the ground truth establishment method for the test set (majority rule of 5 radiologists). It's common for training data to use various methods for annotation, which might differ from the rigorous expert consensus used for the test set.
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(124 days)
MammoScreen BD
MammoScreen® BD is a software application intended for use with compatible full field digital mammography and digital breast tomosynthesis systems. MammoScreen BD evaluates the breast tissue composition to provide an ACR BI-RADS 5th Edition breast density category. The device is intended to be used in the population of asymptomatic women undergoing screening mammography who are at least 40 years old.
MammoScreen BD only produces adjunctive information to aid interpreting physicians in the assessment of breast tissue composition. It is not a diagnostic software.
Patient management decisions should not be made solely based on analysis by MammoScreen BD.
MammoScreen BD is a software-only device (SaMD) using artificial intelligence to assist radiologists in the interpretation of mammograms. The MammoScreen BD software is to automatically process a mammogram to assess the density of the breasts.
For each examination, MammoScreen BD outputs the breast density in accordance with the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) Atlas 5th Edition breast density categories "A" through "D".
MammoScreen BD takes as input a folder with images in DICOM formats and outputs a breast density assessment in a form of a JSON file. MammoScreen BD outputs can be integrated with compatible third-party software such as the MammoScreen Web-UI interface, PACS viewer (using DICOM Structured Report or DICOM Secondary Capture SOP Class UIDs), patient worklists, or within reporting software.
Here is a detailed breakdown of the acceptance criteria and study information for MammoScreen BD, based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
The primary acceptance criteria for the initial clearance of MammoScreen BD were related to the accuracy and agreement with ground truth established by radiologists for classifying breast density into four BI-RADS categories.
| Acceptance Criteria (from PCCP section for future modifications) | Primary Objective Reported Device Performance (4-class task) | Primary Objective Reported Device Performance (Binary task) |
|---|---|---|
| Quadratic Kappa on GE mammograms superior to 0.85 | Quadratic Cohen's Kappa: 89.03 (95% CI: 87.43 - 90.56) | Quadratic Cohen's Kappa: 84.50 (95% CI: 81.46, 87.36) |
| Linear Kappa, Accuracy, and Density Bins (A, B, C, D) | Accuracy: 84.68 (95% CI: 82.68, 86.67) | Accuracy: 92.29 (95% CI: 90.82, 93.77) |
Note: The document explicitly states "Acceptance criteria of the updated device" under the PCCP for future modifications. While the document does not explicitly state the acceptance criteria for the initial clearance in a separate section, the reported performance metrics (Quadratic Cohen's Kappa and Accuracy for both 4-class and binary classification) are implicitly the metrics against which the device's performance was judged for its initial clearance, demonstrating its effectiveness based on comparison to the ground truth.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: 922 women/exams. (Total of 922 exams with 4 views each).
- Data Provenance: Retrospectively collected from two US screening centers and one French screening center.
- 52.6% of cases (485 patients) originated from the USA.
- 47.4% of cases (437 patients) originated from France.
- The provenance did not intersect any clinical centers used for algorithm development, mitigating a center-induced bias.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: 5 breast radiologists.
- Qualifications of Experts: The document specifies "5 breast radiologists" but does not provide details on their years of experience or specific board certifications.
4. Adjudication Method for the Test Set
- Adjudication Method: "Consensus among the visual assessment of 5 breast radiologists." The exact method (e.g., majority vote, sequential review with tie-breaking) is not explicitly detailed beyond "consensus."
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No, a multi-reader multi-case (MRMC) comparative effectiveness study evaluating human readers with AI assistance versus without AI assistance was not conducted or reported in this document. The study focuses on the standalone performance of the AI algorithm against expert consensus.
6. Standalone (Algorithm Only) Performance Study
- Yes, a standalone performance study was conducted. The "Primary Objectives" and "Performance Data" sections directly evaluate "the accuracy and the reproducibility of MammoScreen BD algorithm in assessing the breast density category" in terms of agreement with the ground truth established by the consensus of 5 radiologists.
- For the 4-class task, the algorithm achieved a quadratic Cohen's kappa of 89.03 and an accuracy of 84.68%.
- For the binary classification task (dense vs. non-dense), the algorithm achieved a quadratic Cohen's kappa of 84.50 and an accuracy of 92.29%.
7. Type of Ground Truth Used
- Type of Ground Truth: Expert Consensus. Specifically, "ground truth (GT) established by consensus among the visual assessment of 5 breast radiologists."
8. Sample Size for the Training Set
- Sample Size for Training Set: 32,368 patients, comprising 108,775 studies.
9. How Ground Truth for the Training Set Was Established
- The document states that the training data was derived from "De-identified screening mammograms... retrospectively collected from 32,368 patients in 2 different US sites."
- It does not explicitly state how the ground truth for the training set was established. It only describes the density distribution (A: 12.79%, B: 34.58%, C: 42.94%, D: 9.38%) within the training data, implying these were pre-existing labels. It's common for such labels to be derived from radiologist reports or existing clinical records, but the specific method of ground truth establishment for the training set is not detailed.
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