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510(k) Data Aggregation
(266 days)
The Clairity Allix5 software device is intended to generate a 5-year risk prediction of breast cancer based on a bilateral screening mammogram. Allix5 provides a prediction of the percentage probability that the individual will receive a diagnosis of breast cancer or develop breast cancer within the 5-year timeframe following the screening mammogram, through analysis of mammography features and characteristics.
Eligible patients do not have a known breast cancer at presentation for their screening mammogram.
Allix5 is not intended to diagnose or detect breast cancer, or to provide care recommendations. Allix5 is not intended to replace or to be used as the sole determinant for clinical decision-making. Allix5 output is intended to be considered after the radiologist has completed the interpretation of the screening mammogram.
Allix5 analyzes full-field digital mammograms or directly acquired 2D images from Hologic Lorad Selenia and Selenia Dimensions Mammography Systems; it does not analyze synthetic-2D images.
Allix5 is a Software as a Medical Device (SaMD) that takes as input two-dimensional screening mammography images acquired from Hologic Selenia Dimensions and Lorad Selenia systems and outputs a percentage probability that the patient will receive a diagnosis of breast cancer or develop breast cancer within the 5-year timeframe. The inputs required by the device are the four directly acquired 2D standard views (RCC, LCC, LMLO, RMLO) from the compatible mammography systems. Allix5 provides an output in the range of 0% - 100%. The Allix5 output is a population-based risk estimate reflecting the expected proportion of women, among those with similar AI-identified mammography features and characteristics, who will receive a diagnosis of or will develop a new breast cancer in the next 5 years. Allix5 outputs a percentage probability estimate of the pure risk of breast cancer based on a patient's screening mammogram, where pure risk is the risk of breast cancer without adjustment for competing causes of mortality. Allix5's risk prediction algorithm was developed using a computer vision-based deep learning model that was trained on screening mammograms across diverse patient populations.
Allix5 is not intended to influence the interpretation of a screening mammogram in terms of detecting or diagnosing disease. Figure 1 illustrates how Allix5 is intended to be utilized within the current patient screening workflow:
The Allix5 device is designed to be integrated into existing clinical information systems that are already part of healthcare provider workflows; it does not have an independent user interface. The Allix5 device receives DICOM files from a PACS and automatically returns the Allix5 output via HL7. In this way, healthcare providers (HCPs) can access the Allix5 output alongside patient history and other relevant clinical data as they consider the patient's overall risk of breast cancer and make recommendations for screening and preventive care. HCPs can compare Allix5 outputs to established risk thresholds, such as those provided by the National Comprehensive Cancer Network (NCCN), when making care recommendations.
Allix5 can analyze only directly-acquired 2-Dimensional screening mammography images, and the compatible mammography systems are as follows:
- Selenia Dimensions from Hologic
- Lorad Selenia from Hologic
Here's a breakdown of the acceptance criteria and the study that proves the Allix5 device meets those criteria, based on the provided text:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance | Comments |
|---|---|---|
| Discrimination (Co-primary Endpoint): Lower limit of 95% CI on AUC(5) in total study population ≥ 0.64 | AUC(5) = 0.70 [95% CI: 0.69, 0.72] | Met. The lower limit (0.69) is above the performance goal. |
| Calibration (Co-primary Endpoint): Modified Greenwood-Nam-D'Agostino (GND) test p-value < 0.025 in total study population | GND Test p-value < 0.0001 (Total Study Population) | Met. The p-value is significantly below 0.025. |
| Discrimination (Secondary Endpoint): Lower limit of 95% CI on AUC(5) in total study population excluding current cancers ≥ 0.64 | AUC(5) = 0.66 [95% CI: 0.66, 0.68] | Met. The lower limit (0.66) is above the performance goal. |
| Calibration (Secondary Endpoint): Modified GND test p-value < 0.025 in total study population excluding current cancers | GND Test p-value = 0.0174 (Excluding Current Cancers) | Met. The p-value is below 0.025. |
| Discrimination (Secondary Endpoint): Lower limit of 95% CI on AUC(5) for White patients in total study population ≥ 0.64 | AUC(5) = 0.73 [95% CI: 0.71, 0.74] | Met. The lower limit (0.71) is above the performance goal. |
| Calibration (Secondary Endpoint): Modified GND test p-value < 0.025 for White patients in total study population | GND Test p-value = 0.0016 (White Patients) | Met. The p-value is below 0.025. |
| Discrimination (Secondary Endpoint): Lower limit of 95% CI on AUC(5) for Black patients in total study population ≥ 0.64 | AUC(5) = 0.67 [95% CI: 0.65, 0.69] | Met. The lower limit (0.65) is above the performance goal. |
| Calibration (Secondary Endpoint): Modified GND test p-value < 0.025 for Black patients in total study population | GND Test p-value = 0.0107 (Black Patients) | Met. The p-value is below 0.025. |
| Discrimination (Subgroup) - Patients with Breast Implants: Lower limit of 95% CI on AUC(5) ≥ 0.64 | AUC(5) = 0.73 [95% CI: 0.59, 0.87] | Not Demonstrated. The 95% CI contains 0.64 due to large uncertainty. |
| Calibration (Subgroup) - Patients with Breast Implants: Modified GND test p-value < 0.025 | GND Test p-value = 0.1153 (Patients with Breast Implants) | Not Demonstrated. The p-value is > 0.025. |
| Calibration (Subgroup) - Asian patients: Modified GND test p-value < 0.025 | GND Test p-value = 0.1830 (Asian Patients) | Not Demonstrated. The p-value is > 0.025. |
| Calibration (Subgroup) - Age < 50: Modified GND test p-value < 0.025 | GND Test p-value = 0.0498 (Age < 50) | Not Demonstrated. The p-value is > 0.025. |
| Calibration (Subgroup) - Age ≥ 65: Modified GND test p-value < 0.025 | GND Test p-value = 0.5202 (Age ≥ 65) | Not Demonstrated. The p-value is > 0.025. |
| Reproducibility Study #1 (Simulated repeated screening mammography): Acceptable ICC, mean absolute risk difference, CoV, and SEM | Mean ICC = 98%, Mean absolute risk difference = 0.008 (median 0.002), Mean CoV = 17.5%, Mean SEM = 0.0024 | Met. Reported to be within acceptable standards. |
| Reproducibility Study #2 (Alternative image selection within same exam): ICC values > 0.75, acceptable mean absolute difference | ICC values ranging from 0.83 to 0.92 (above 0.75), Mean absolute difference = 0.0043 | Met. Reported to be acceptable. |
Study Details
1. Sample Sizes for the Test Set and Data Provenance
- Sample Size (Pivotal Study - Test Set): 77,511 exams from 44,112 patients.
- Data Provenance: Retrospective, multi-site. Collected from five clinical validation sites in the United States:
- Emory University Hospital Midtown in Atlanta, Georgia
- Solis Mammography at Baylor Scott & White All Saints Medical Center in Fort Worth, Texas
- Solis Mammography Bedford at Lisa Trent Breast Center in Bedford, Texas
- University of California, Davis Health Ellison Ambulatory Care Center in Sacramento, California
- University of California, Davis Folsom Clinic in Folsom, California
- This data was independent of the data used for algorithm training and tuning.
2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
- The document does not explicitly state the number or specific qualifications of human experts used to establish the ground truth for the test set.
- Instead, the ground truth for the test set was established based on clinical outcomes data: "Ground truth for breast cancer occurrence within five years after the index screening mammogram was based on biopsy-proven breast cancer. Ground truth for breast cancer not occurring within five years after the index screening mammogram was based on subsequent mammography and/or lack of evidence of a biopsy-proven breast cancer within the required time frame."
3. Adjudication Method for the Test Set
- The document does not describe an adjudication method involving multiple human readers for establishing the ground truth of the test set.
- The ground truth was established through a defined protocol using biopsy results and subsequent imaging or lack thereof, which inherently incorporates medical record data.
4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No, an MRMC comparative effectiveness study was not done.
- The study focuses solely on the standalone performance of the Allix5 algorithm in predicting breast cancer risk. There is no mention of human readers or AI assistance for human readers in the described clinical performance study.
5. Standalone (Algorithm Only) Performance Study
- Yes, a standalone study was done. The entire pivotal clinical study described evaluates the Allix5 device's performance as an algorithm only, without human-in-the-loop interaction. The endpoints (discrimination via AUC and calibration via GND test) are direct measures of the algorithm's predictive capabilities.
6. Type of Ground Truth Used
- The ground truth used was primarily based on outcomes data and pathology reports:
- Positive Cases: Biopsy-proven breast cancer within 5 years of the index screening mammogram.
- Negative Cases: No biopsy-proven breast cancer within 5 years AND a subsequent negative screening/diagnostic mammogram or biopsy 5 years or more after the index exam; OR biopsy-proven cancer more than 5 years after the index exam WITH an earlier negative screening/diagnostic mammogram at or after 5 years.
- The document also describes a methodology to account for censored time to breast cancer onset, resulting in a "probability of being breast cancer positive" as the ground truth, which could be categorized as "positive," "negative," or "ambiguous."
7. Sample Size for the Training Set
- Training Dataset: 365,916 exams.
8. How the Ground Truth for the Training Set Was Established
- Similar to the test set, the ground truth for the training set was established using clinical data records from each site.
- Cancer Positive Outcome: Biopsy-proven breast cancer within five years after the index screening mammogram.
- Cancer Negative Outcome: Subsequent mammography and/or lack of evidence of a biopsy-proven breast cancer within the required time frame (5 years after the index screening mammogram).
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