MammoScreen BD

{0} FDA U.S. FOOD &amp; DRUG ADMINISTRATION August 22, 2025 Therapixel Pierre Fillard Chief Scientific Officer 455 Promenade des Anglais Nice, 06200 FRANCE Re: K243685 Trade/Device Name: MammoScreen BD Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: July 23, 2025 Received: July 23, 2025 Dear Pierre Fillard: We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading. If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register. FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act. Under 21 CFR 807.81(a)(3), a new U.S. Food &amp; Drug Administration 10903 New Hampshire Avenue Silver Spring, MD 20993 www.fda.gov {1} K243685 - Pierre Fillard Page 2 premarket notification is required if there is a major change or modification in the intended use of a device, or if there is a change or modification in a device that could significantly affect the safety or effectiveness of the device, e.g., a significant change or modification in design, material, chemical composition, energy source, or manufacturing process. Accordingly, if deviations from the established PCCP result in a major change or modification in the intended use of the device, or result in a change or modification in the device that could significantly affect the safety or effectiveness of the device, then a new premarket notification would be required consistent with section 515C(b)(1) of the Act and 21 CFR 807.81(a)(3). Failure to submit such a premarket submission would constitute adulteration and misbranding under sections 501(f)(1)(B) and 502(o) of the Act, respectively. Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download). Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181). Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050. All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part {2} K243685 - Pierre Fillard Page 3 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems. For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100). Sincerely, **MARJAN NABILI -S** for Yanna Kang, Ph.D. Assistant Director Mammography and Ultrasound Team DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {3} DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration Indications for Use Form Approved: OMB No. 0910-0120 Expiration Date: 07/31/2026 See PRA Statement below. Submission Number (if known) K243685 Device Name MammoScreen BD Indications for Use (Describe) 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. Type of Use (Select one or both, as applicable) ☑ Prescription Use (Part 21 CFR 801 Subpart D) ☐ Over-The-Counter Use (21 CFR 801 Subpart C) # CONTINUE ON A SEPARATE PAGE IF NEEDED. This section applies only to requirements of the Paperwork Reduction Act of 1995. # *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." {4} THERAPIXEL TRANSIER TRENTS # 510(k) Summary # K243685 This 510(k) summary of safety and effectiveness information is prepared in accordance with the requirements of 21 CFR § 807.92. Applicant Information: Therapixel 455 Promenade des Anglais, 06200 Nice France Phone: +33 9 72 55 20 39 Submission Correspondent: Pierre Fillard Chief Scientific Officer Email: pfillard@therapixel.com Phone: +33 6 83 71 28 09 Date Summary Prepared: Nov 20, 2024 # Device Information: Trade Name: MammoScreen® BD Common Name: Breast Density Assessment Software Device Classification Name: Automated radiological image processing software Regulation Number: 21 CFR §892.2050 Regulation Class: Class II Product Code: QIH Submission type: Traditional 510(k) 510(k) number: K243685 # Predicate Device: The predicate device is MammoScreen® BD by Therapixel, cleared under K241561 (Product code QIH). 510(k) submission MammoScreen BD {5} THERAPIXEL TRADING·SERVING·INNOVATION·SERVICES # Device Description: 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. # Indication for Use: 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. ## Intended user population Intended users of MammoScreen BD are physicians interpreting mammograms. ## Intended patient population The device is intended to be used in the population of asymptomatic women undergoing screening mammography who are at least 40 years old. 510(k) submission MammoScreen BD {6} THERAPIXEL TRADING·SERVING·INDICT Predicate device comparison: | | Predicate device (MammoScreen BD – K241561) | Subject device (MammoScreen BD – K243685) | | --- | --- | --- | | Manufacturer | Therapixel | Therapixel | | Regulation number | 892.2050 | 892.2050 | | Product Code | QIH | QIH | | Medical Class Device | Class II | Class II | | Intended Use | 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 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. | | Intended patient population | Asymptomatic women undergoing mammography | Asymptomatic women undergoing mammography | | Intended user population | Interpreting physicians | Interpreting physicians | | Anatomical Location | Breast | Breast | | Design | Software-only device | Software-only device | | Type of artificial intelligence | Supervised Machine Learning | Supervised Machine Learning | | Input | Compatible full-field digital mammography and digital breast tomosynthesis systems (using Synthetic 2D (2DSM)) for Hologic. | Compatible full-field digital mammography and digital breast tomosynthesis systems (using Synthetic 2D (2DSM)) for Hologic and GE. | | Output | Breast density assessment based on ACR BIRADS 5th edition category at the mammogram level. | Breast density assessment based on ACR BIRADS 5th edition category at the mammogram level. | | Support of Hologic Envision system and GE mammograms | Not included | Included | | Inclusion of PCCP | Predetermined Change Control Plan (PCCP) including: | Predetermined Change Control Plan (PCCP) including: | 510(k) submission MammoScreen BD {7} THERAPIXEL TRADING·SERVING·INSURANCE | | • Support of GE mammograms (no re-training required) • Support of Siemens mammograms (retraining required) • Pre-training of backbone using Unsupervised Machine Learning (as opposed to Supervised Machine Learning) | • Support of Siemens mammograms (retraining required) • Pre-training of backbone using Unsupervised Machine Learning (as opposed to Supervised Machine Learning) | | --- | --- | --- | The indication for the use of MammoScreen BD is similar to that of the predicate device. Both devices are intended for concurrent use by physicians interpreting breast images to help them with assessing the breast tissue composition. The devices are not intended as a replacement for the review of a physician or their clinical judgment. The predicate device and the subject device are two software versions of MammoScreen BD. They both rely on the same fundamental scientific technology. The design changes of this new version of MammoScreen BD have been assessed at the software design level and do not raise different questions of safety and effectiveness than the previous version. For both devices, a choice of medical image processing and machine learning techniques are implemented. The system includes 'deep learning' modules for the assessment of the breast tissue composition. These modules are trained with very large databases of annotated mammograms. The overall design of MammoScreen BD is the same than the design of the predicate device. Both versions assess the breast tissue composition in radiological breast images and provide information about the assessment of the breast density category to the user in the same manner. While MammoScreen BD has been evaluated on mammograms acquired with a wider range of systems to accept those, these modifications do not raise different questions about the safety and effectiveness of the device as compared to the predicate device. The devices have the same intended use. The modifications do not raise different questions about the safety and effectiveness of the device as compared to the predicate device. The safety and effectiveness of the device have been evaluated with a similar methodology as for the predicate device. 510(k) submission MammoScreen BD Page 4 of 9 {8} THERAPIXEL TRADING AND CO-OPERATING SYSTEMS # Training dataset De-identified screening mammograms used for training were retrospectively collected from 32,368 patients in 2 different US sites. A detailed description of the training data is available in the Table below: | Total number of studies | 108,775 | | --- | --- | | Density distribution | A: 12.79% B: 34.58% C: 42.94% D: 9.38% Unknown (excluded): 0.31% | | Patient ages | First quartile (Q1): 47.0 Mean: 56.0 Third quartile (Q3): 64.0 | | Patient Race / Ethnicity | White: 49.13% Asian: 7.63% Black or African American: 0.43% Native Hawaiian or Pacific Islander: 0.09% Unknown: 42.72% | | Manufacturer | Hologic: 61.63% GE: 38.37% | # Non-Clinical Performance Testing MammoScreen BD is a software-only device. Tests have been performed in compliance with the following recognized consensus standards: - IEC 62304:2006/A1:2016- Medical device software - Software life-cycle processes - IEC 62366-1:2015+AMD1:2020- Medical devices - Application of usability engineering to medical devices. MammoScreen BD has successfully completed integration and verification testing and beta validation. In addition, potential hazards have been evaluated and mitigated, and have acceptable levels. As for the predicate device, the clinical validation of MammoScreen BD includes a standalone analysis of the software against a ground truth established by consensus among the visual assessment of 5 breast radiologists, results of this latter for Hologic Envision system are reported in Figure 1. 510(k) submission MammoScreen BD {9} THERAPIXEL TRADING·MEDIA·PUBLIC Accuracy = 85.40 with CI = [82.00, 88.40] Cohen's Kappa (quadratic) = 89.54 with CI = [86.88, 91.69] Cohen's Kappa (linear) = 83.75 with CI = [79.85, 87.00] Accuracy = 93.00 with CI = [90.80, 95.20] Cohen's Kappa (quadratic) = 86.00 with CI = [81.36, 90.25] Cohen's Kappa (linear) = 86.00 with CI = [81.36, 90.25]  Figure 1 - (Left) Confusion matrix comparing the performance of MammoScreen-BD against the radiologist consensus assessment of breast density for the four-class BI-RADS breast density task on Hologic Envision. (Right) Confusion matrix comparing the performance of MammoScreen BD against the radiologist consensus assessment of breast density for the binary task. The number of exams within each bin is shown in parentheses.  The performance testing results indicate that the version MammoScreen BD algorithm does not pose any concerns regarding safety or effectiveness on a wider range of mammogram system. MammoScreen BD behaves equally well on CC and MLO views (Figure 2) and between different age groups and breast thicknesses.  Figure 2 - Contingency matrix comparing the breast density assessment (four-class BI-RADS breast density) of MammoScreen BD on CC and MLO views of the same patient (Hologic Envision). Individual assessments for CC (left) and MLO (right) are given. The number of exams within each bin is shown in parentheses.   Additionally, it was established that MammoScreen BD is non-inferior to the targeted performance. 510(k) submission MammoScreen BD {10} THERAPIXEL TRADING INSTITUTE FOR THE THERAPIXEL The standalone performance testing carried out to validate the device is summarized in what follows: | | Hologic | Hologic Envision | GE | | --- | --- | --- | --- | | Statistics tests for primary objective | Superiority in standalone performance for density assignment of MammoScreen BD compared to a pre-determined reference value (KappaReference = 0.85). | | | | Primary endpoint | No change from previous clearance. Quadratically weighted Cohen's kappa between the density assessment of MammoScreen BD and the established ground truth. Kappa quadratic = 89.03 [95% CI: 87.43 – 90.56] | Quadratically weighted Cohen's kappa between the density assessment of MammoScreen BD and the established ground truth. Kappa quadratic = 89.54 [95% CI: 86.88 – 91.69] | Quadratically weighted Cohen's kappa between the density assessment of MammoScreen BD and the established ground truth. Kappa quadratic = 93.19 [95% CI: 90.50 – 94.92] | | Acceptance criteria | The one-sided p-value for the test H0: Kappa ≤ 0.85 is less than the significance level (α=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. | | | | Number of included patients | 922 | 500 | 376 | | Number of included studies | 1,155 | 500 | 490 | | Age distribution | Range: [40 – 90] First quartile (Q1): 50.0 Mean: 58.5 Third quartile (Q3: 66.0 • Age < 55: 570 • 55 ≤ Age < 65: 308 • Age ≥ 65: 269 | Range: [36 – 86] First quartile (Q1): 48.0 Mean: 56.0 Third quartile (Q3): 65.0 • Age < 55: 234 • 55 ≤ Age < 65: 130 • Age ≥ 65: 136 | Range: [31 -86] First quartile (Q1): 47.0 Mean: 57.2 Third quartile (Q3): 67.0 • Age < 55: 234 • 55 ≤ Age < 65: 130 • Age ≥ 65: 136 | | Race and Ethnicity distribution | White: 273 Asian: 102 Black or African American: 88 American indian or alaska native: 4 Native Hawaiian or pacific islander: 4 | Asian: 6 White: 401 Black or African American: 40 Hispanic: 23 Not Hispanic: 388 | Asian: 48 White: 48 Black: 41 Other (including American Indian, Alaska Native, Native Hawaiian or Other Pacific Islander): 83 Hispanic: 88 | | Considered subgroups | Age | | | | | Age < 55: A(53), B(182), C(239), D(96) 55 ≤ Age < 65: A(26), B(115), C(129), D(38) Age ≥ 65: A(34), B(138), C(83), D(14) | Age < 55: A(21), B(73), C(103), D(37) 55 ≤ Age < 65: A(14), B(59), C(52), D(4) Age ≥ 65: A(15), B(68), C(45), D(8) | Age < 55: A(9), B(44), C(118), D(37) 55 ≤ Age < 65: A(15), B(73), C(41), D(9) Age ≥ 65: A(18), B(83), C(41), D(4) | | | Race | | | | | Asian: A(2), B(52), C(61), D(17) White: A(59), B(176), C(137), D(34) | Asian: A(0), B(2), C(2), D(2) White: A(42), B(163), C(159), D(37) | Asian: A(1), B(31), C(28), D(8) White: A(11), B(17), C(21), D(7) Black: A(8), B(21), C(16), D(3) Other: A(9), B(59), C(48), D(10) | 510(k) submission MammoScreen BD {11} THERAPIXEL TRADING OIL &amp; REACT | | Black: A(20), B(32), C(34), D(9) Other: A(1), B(3), C(4), D(0) | Black: A(3), B(16), C(18), D(3) Hispanic: A(1), B(8), C(12), D(2) Not Hispanic: A(39), B(160), C(148), D(41) | Hispanic: A(5), B(13), C(11), D(3) | | --- | --- | --- | --- | | | Data provenance | | | | | USA: A(85), B(269), C(241), D(63) EU: A(28), B(169), C(214), D(86) | USA: A(50), B(200), C(200), D(50) | USA: A(38), B(155), C(139), D(31) EU: A(4), B(45), C(61), D(19) | | | Breast thickness | | | | | Thick. < 50: A(7), B(80), C(145), D(87) 50 ≤ Thick. < 70: A(43), B(272), C(252), D(58) Thick. ≥ 70: A(63), B(86), C(58), D(4) | Thick. < 50: A(4), B(25), C(47), D(28) 50 ≤ Thick. < 70: A(25), B(104), C(115), D(20) Thick. ≥ 70: A(21), B(71), C(38), D(2) | Thick. < 50: A(33), B(135), C(142), D(46) 50 ≤ Thick. < 70: A(4), B(51), C(49), D(3) Thick. ≥ 70: A(5), B(14), C(9), D(1) | | Truthing process | The reference standard for breast density value was established by majority rule among the assessment of 5 breast radiologists with at least 10 years of experience in breast imaging interpretation. | | | | Independence of test data from training data | Data sources are separated into the training/tuning group and the test group. Sources in the training/tuning group may only be used for model training and tuning. Sources in the test group may only be used for external validation of the model’s performances on unseen data (i.e., from sources entirely left out during training and tuning). Data used for the standalone performance testing only belongs to the test group. | | | # Predetermined Change Control Plan (PCCP) MammoScreen BD is powered by machine-learning neural architectures. Therapixel will make future algorithm improvements under a PCCP. The plan describes the future modifications, assesses their impact, and a modification protocol details how data management, re-training, performance evaluation and update procedures will be handled. The table below lists the anticipated modifications. | | Modification #1 Support of Siemens Mammograms (retraining required) | Modification #2 Pre-training of backbone using Unsupervised Machine Learning (as opposed to Supervised Machine Learning) | | --- | --- | --- | | Data used for development and modifications, representing the target population | Siemens, FFDM Siemens, 2DSM. | No new data collection is foreseen for this change. | | Statistics tests for primary objective | Superiority in standalone performance for density assignment of MammoScreen BD compared to a pre-determined reference value (Kappa reference = 0.85). | | 510(k) submission MammoScreen BD {12} THERAPIXEL TRANSPORT AND LABORATORY | Primary endpoints | Quadratically weighted Cohen’s kappa between the density assessment of MammoScreen and the established ground truth | | --- | --- | | Acceptance criteria | Lower bound of the 95% confidence interval > 0.85 | | Validation activities | Upon demonstration of the superiority through the standalone performance testing, changes will be documented in a minor release amending: • The Algorithm test protocol and results documents • The Device Label, including the User Guide | | Communication plan | Upcoming updates are communicated through advisory notices sent by email at least 2 weeks before deployment. Advisory notices contain: • The new version identification, • A summary of the change, • The schedule for the application of the change, • Statement that the Support team will contact the customer and/or user for acceptance, training or scheduling of the change, if necessary, • A link to access the updated User Guide, where the changes mentioned are reflected. Users may decide to opt out of the update during the 2-week notice period. MammoScreen BD does not have its own user interface. The new labelling for MammoScreen BD will be available on the compatible third-party software once the update is activated. | | Characterization of the device before and after implementation of changes | The device will be accessible to more centers, and thus to more woman. Prevents obsolescence of MammoScreen BD. Better representation of breast tissue diversity leading to higher overall performances and a better generalization on unseen data. | | Monitoring, detection, and response to deviations in device performance | Therapixel monitors customer sites. The distribution of breast density assessment obtained is determined on a representative screening distribution, which serves as a Reference Distribution. Device monitoring compares breast density assessment in real conditions to the reference distribution and alerts of any deviations. The investigation can result in a field-safety notice, a Medical Device Report. | # Conclusions Performance testing results demonstrated that the device is safe and effective. Therapixel has applied a risk management process following FDA-recognized standards to identify, evaluate, and mitigate all known hazards related to MammoScreen BD. All identified risks are effectively mitigated, and it can be concluded that the residual risk is outweighed by the benefits. Considering all data in this submission, the data provided in these 510(k) supports the safe and effective use of MammoScreen BD for its indications for use and substantial equivalence to the predicate device. 510(k) submission MammoScreen BD