Transpara Density 1.0.0

K232096 · Screenpoint Medical B.V. · QIH · Dec 11, 2023 · Radiology

Device Facts

• Record ID: K232096
• Device Name: Transpara Density 1.0.0
• Applicant: Screenpoint Medical B.V.
• Product Code: QIH · Radiology
• Decision Date: Dec 11, 2023
• Decision: SESE
• Submission Type: Traditional
• Regulation: 21 CFR 892.2050
• Device Class: Class 2
• Attributes: AI/ML, Software as a Medical Device

Intended Use

Transpara Density is a software application intended for use with data from compatible digital breast tomosynthesis systems. Transpara Density utilises deep learning artificial intelligence algorithms to automatically determine volumetric breast density (VBD), breast volume, and an ACR BI-RADS 5th Edition breast density category to aid health care professionals in the assessment of breast tissue composition. It is not a diagnostic aid.

Device Story

Software module using deep learning AI to assess breast density in digital mammography (DM) and digital breast tomosynthesis (DBT) images. Inputs: processed (FOR PRESENTATION) mammography images or synthetic 2D DBT images. Operation: AI algorithm automatically calculates volumetric breast density (VBD), breast volume, and ACR BI-RADS 5th Edition category. Output: numerical density values and BI-RADS category provided to radiologists as decision support. Used in clinical screening/diagnostic environments; operated by healthcare professionals. Benefits: provides standardized, objective assessment of breast tissue composition to assist radiologists; not a diagnostic aid. Integrated as an optional feature within the Transpara system; requires embedding in applications handling DICOM communication with PACS.

Clinical Evidence

Bench testing only. Evaluated using 10,804 exams (FFDM/DBT) from multiple vendors. Accuracy: Pearson correlation with physics-based model was 0.935 (VBD) and 0.997 (volume); correlation with MRI was 0.908. Reproducibility: high agreement between views (CC/MLO) and sides (left/right). Agreement with human readers: 800 exams assessed by 8 MQSA-qualified radiologists; overall accuracy 70.8% (kappa 0.74) for 4-category classification and 88.9% (kappa 0.78) for dense vs. non-dense classification. Sensitivity 87.3%, specificity 90.4% for dense vs. non-dense.

Technological Characteristics

Software-only device. Uses deep learning AI algorithms for image analysis. Compatible with DICOM standard. Operates on processed (FOR PRESENTATION) mammography and synthetic 2D DBT images. Moderate level of concern. Complies with IEC 62366-1, ISO 14155, ISO 14971, IEC 62304, and IEC 82304-1 standards.

Indications for Use

Indicated for women undergoing digital mammography or digital breast tomosynthesis exams to aid healthcare professionals in assessing breast tissue composition. Not for diagnostic use.

Regulatory Classification

Identification

A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.

Special Controls

*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).

Predicate Devices

• Volpara Imaging Software (K182310)

Submission Summary (Full Text)

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December 11, 2023

Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, with the word "ADMINISTRATION" underneath.

Screenpoint Medical B.V. % Robin Barwegen Head of Regulatory and Quality Affairs Mercator II, 7th floor, Toernooiveld 300 Nijmegen, Gelderland 6525EC NETHERLANDS

## Re: K232096

Trade/Device Name: Transpara Density 1.0.0 Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management and Processing System Regulatory Class: Class II Product Code: QIH Dated: July 6, 2023 Received: July 13, 2023

## Dear Robin Barwegen:

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.

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).

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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 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-reportingcombination-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.

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 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/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-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely,

# Yanna S. Kang -S

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

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# Indications for Use

510(k) Number (if known) K232096

Device Name Transpara Density 1.0.0

#### Indications for Use (Describe)

Transpara Density is a software application intended for use with data from compatible digital breast tomosynthesis systems. Transpara Density utilises deep learning artificial intelligence algorithms to automatically determine volumetric breast density (VBD), breast volume, and an ACR BI-RADS 5th Edition breast density category to aid health care professionals in the assessment of breast tissue composition. It is not a diagnostic aid.

| Type of Use (Select one or both, as applicable) | |
|---------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
| <div style="display:flex; align-items:center;"><input checked="" type="checkbox"/> Prescription Use (Part 21 CFR 801 Subpart D)</div> | <div style="display:flex; align-items:center;"><input type="checkbox"/> Over-The-Counter Use (21 CFR 801 Subpart C)</div> |

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# K232096

# 510(k) Summary Transpara Density

This 510(k) summary of safety and effectiveness information is prepared in accordance with the requirements of 21 CFR § 807.92.

#### Submitter 1.

## Manufacturer:

ScreenPoint Medical B.V.

Mercator II, 7th floor

Toernooiveld 300

6525 EC Nijmegen

Netherlands

www.screenpoint-medical.com

# Contact person:

Robin Barwegen

Office: [phone] | [phone]

Mobile: [phone]

Mercator II, 7th floor, Toernooiveld 300, 6525 EC Nijmegen, Netherlands

# Date:

11 December 2023

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#### 2. Device

| Device trade name | Transpara Density |
|---------------------------|----------------------------------------|
| Device | System, Image Processing, Radiological |
| Classification regulation | 21 CFR 892.2050 |
| Panel | Radiology |
| Device class | II |
| Product code | QIH |
| Submission type | Traditional 510(k) |

#### 3. Legally marketed predicate device

| Device trade name | Volpara Imaging Software |
|---------------------------|----------------------------------------|
| Legal Manufacturer | Volpara Health Technologies Limited |
| Device | System, Image Processing, Radiological |
| Classification regulation | 21 CFR 892.2050 |
| Panel | Radiology |
| Device class | II |
| Product code | LLZ |
| Clearance number | K182310 |

#### Device description 4.

Transpara Density is a software module that uses artificial intelligence techniques to assess breast density in mammography (DM) and breast tomosynthesis (DBT) images and provide support to radiologists in this task. The novel methods of Transpara Density, extend the capabilities of computer aided detection systems for mammography by providing radiologists with decision support via the output of density assessment.

The Transpara Density outputs are:

- Density Grade, in accordance with categories defined in the ACR BI-RADS Atlas 5th Edition (A = almost entirely fat; B = scattered fibroglandular densities; C = heterogeneously dense; and D = extremely dense)
- Volumetric Breast Density in % .
- . Breast volume in cm3

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Transpara Density is designed as an optional feature of Transpara. To operate in a clinical environment the software must be embedded in a software application that generates output in standardized formats (e.g. DICOM) and handles communication with external devices (such as PACS systems).

#### 5. Indications for use

Transpara Density is a software application intended for use with data from compatible digital mammography and digital breast tomosynthesis systems. Transpara Density utilizes deep learning artificial intelligence algorithms to automatically determine volumetric breast density (VBD), breast volume, and an ACR BI-RADS 5th Edition breast density category to aid health care professionals in the assessment of breast tissue composition. It is not a diagnostic aid.

# Intended user population

Intended users of Transpara Density are healthcare professionals involved in breast imaging.

## Intended patient population

The device is intended to be used in the population of women having a digital mammogram or digital breast tomosynthesis exam.

## Safety and Effectiveness Concerns

The device labeling contains instructions for use and any necessary cautions and warnings to provide for safe and effective use of the device. Risk management is ensured via a risk analysis, which is used to identify potential hazards and mitigations. These potential hazards are controlled by software means, user instructions, verification and validation testing to ensure that the product meets its intended uses.

#### 6. Predicate device comparison

It can be concluded that the subject device Transpara Density is substantially equivalent to the commercially available predicate device Volpara Imaging Software (K182310). It has the same intended use, intended users, and numeric output as the predicate device. The substantial equivalence comparison table below provides details.

| | Transpara Density | Predicate Device Volpara<br>Imaging Software<br>K182310 | Comments |
|----------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use | Transpara Density is a software application intended for use with data from compatible | VolparaDensity is a software application intended for use with the raw data from digital | Similar from the user perspective. Main outputs for the user are volumetric density and |
| | digital mammography<br>and digital breast<br>tomosynthesis systems.<br>Transpara Density utilizes<br>deep learning artificial<br>intelligence algorithms to<br>automatically determine<br>volumetric breast density<br>(VBD), breast volume,<br>and an ACR BI-RADS 5th<br>Edition breast density<br>category to aid health<br>care professionals in the<br>assessment of breast<br>tissue composition. It is<br>not a diagnostic aid. | breast x-ray systems,<br>including tomosynthesis.<br>VolparaDensity calculates<br>and quantifies<br>a density map and from<br>that determines<br>volumetric breast density<br>as a ratio of<br>fibroglandular tissue and<br>total breast volume<br>estimates. Volpara<br>provides these numerical<br>values along with a BI-<br>RADS breast density 4th<br>or 5th Edition category to<br>aid health care<br>professionals in the<br>assessment of breast<br>tissue composition.<br>VolparaDensity is not an<br>interpretive or diagnostic<br>aid and should be used<br>only as adjunctive<br>information when the<br>final assessment of breast<br>density category is made<br>by an MQSA-qualified<br>interpreting<br>physician. | the BI-RADS 5th Edition<br>density category. These<br>outputs are the same. |
| Intended Users | Health Care Professionals | Health Care Professionals | Same |
| Image Source | Digital mammograms<br>from mammography or<br>tomosynthesis systems<br>(any paddle type) | Digital mammograms<br>from mammography or<br>tomosynthesis systems,<br>including those obtained<br>using with curved<br>paddles. | Same. The subject device<br>is insensitive for paddle<br>shapes because it uses<br>images processed by the<br>manufacturer which are<br>not affected by paddle<br>shape. |
| Input image type | FOR PRESENTATION<br>(processed) images for<br>mammography and<br>Synthetic 2D images for<br>DBT | FOR PROCESSING (raw)<br>images for<br>mammography and the<br>central raw projection<br>image for DBT | The core algorithm for<br>density computation of<br>the subject device has a<br>different design which<br>does not require raw<br>data. |
| Anatomical area | Breast | Breast | Same |
| Assessment Scope | | Volumetric | |
| Image Storage and Report<br>Generation | | Yes<br>Output to the console. | |
| Numeric Output | Volume of Breast<br><br>Volumetric Breast Density | Volume of Breast<br><br>Volumetric Breast Density | Similar, the clinically<br>relevant outputs in<br>practice are the same. |
| | BIRADS 5th Edition Breast<br>Density Category | BIRADS 4th or 5th Edition<br>Breast Density Category | |
| | | Volume of Fibroglandular<br>tissue | |
| | | Average thickness of<br>dense tissue | |
| | | Maximum thickness of<br>dense tissue (and<br>location) | |
| | | Maximum volume of<br>dense tissue above any<br>1cm2 square region | |
| Image Output | None | Density map in DICOM<br>SCI format, for<br>visualization as user<br>specifies. | Density maps are not<br>required in clinical<br>practice |
| Classification | 21 CFR 892.2050 | 21 CFR 892.2050 | Same |
| Software Level of<br>Concern | Moderate | Moderate | Same |

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.

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#### Summary of non-clinical performance data 7.

In the design and development of Transpara Density, ScreenPoint applied the following voluntary FDA recognized standards and guidelines:

| Standard ID | Standard Title | FDA Recognition # |
|-------------------------------------------------------------|------------------------------------------------------------------------------------------|-------------------|
| IEC 62366-1 Edition<br>1.1 2020-06 | Medical devices - Part 1: Application of usability<br>engineering to medical devices | 5-129 |
| ISO 14155 Third<br>edition 2020-07 | Clinical investigation of medical devices for<br>human subjects - Good clinical practice | 2-282 |
| ISO 14971 Third<br>Edition 2019-12 | Medical devices - Application of risk<br>management to medical devices | 5-125 |
| IEC 62304 Edition<br>1.1 2015-06<br>CONSOLIDATED<br>VERSION | Medical Device Software - Software Life Cycle<br>Processes | 13-79 |
| IEC 82304-1: 2016 | Health software - Part 1: General requirements<br>for product safety | 13-97 |

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| ISO 15223-1 Fourth<br>Edition 2021-07 | Medical devices - Symbols to be used with<br>medical device labels labelling and information<br>to be supplied - Part 1: General requirements | 5-134 |
|--------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------|-------|
| ISO 20417 First<br>edition 2021-04<br>Corrected version<br>2021-12 | Medical devices – Information to be supplied by<br>the manufacturer | 5-135 |

The following quidance documents were used to support this submission:

- Guidance for Industry and FDA Staff Guidance for the Content of Premarket ● Submissions for Software Contained in Medical Devices (Issued on May 11, 2005)
- Guidance for Industry and Food and Drug Administration Staff Computer-● Assisted Detection Devices Applied to Radiology Images and Radiology Device Data - Premarket Notification [510(k)] Submissions (Issued on July 3, 2012)
- Guidance for Industry and FDA Staff - Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device Data in Premarket notification [510(k)] Submissions (Issued on July 3, 2012)
- . Guidance for Industry and Food and Drug Administration Staff - The 510(k) Program: Evaluating Substantial Equivalence in Premarket Notifications [510(k)] (Issued on July 28, 2014)
- Guidance for Industry and Food and Drug Administration Staff Unique Device ● Identification: Direct Marking of Devices (Issued on November 17, 2017)
- . Guidance for Industry and Food and Drug Administration Staff - Technical Performance Assessment of Quantitative Imaging in Radiological Device Premarket Submissions (Issued on June 16, 2022)

Transpara Density is a software-only device. The level of concern for the device is determined as Moderate Level of Concern.

# Non-clinical performance tests

Verification testing was conducted, which consisted of software unit testing, software integration testing and software system testing. The verification tests showed that the software application satisfied the software requirements.

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Transpara Density was evaluated by tests covering accuracy, reproducibility, consistency, and agreement with visual assessment by healthcare professionals involved in breast imaging.

# Test data

The test data used for the evaluation of the automated density algorithm included exams from 10,804 women with ages ranging from 40-92. The dataset includes FFDM (10,804 exams) and DBT (833 exams) from multiple vendors including GE (26%), Siemens (16%), Hologic (37%) and Fujifilm (21%). All exams contained at least the four standard views (left and right MLO/CC). The test data was not used for algorithm training and was not accessible to members of the research and development team.

Data originated from multiple clinical centers located in the US, the UK, Turkey, and five countries in the EU (the Netherlands, Sweden, Germany, Spain, Belgium, Italy), Data collection sites are representative for reqular breast cancer screening and diagnostic assessment in hospitals.

Characteristics of the test set, i.e. Density Grade distribution, were evaluated and compared to those reported in literature, confirming that the test set is representative of the target population in the intended use.

## Accuracy

Volumetric breast density (VBD) and breast volume (BV) should be in agreement with measurements obtained using a validated physics based model described in the literature (van Engeland 2006). https://doi.org/10.1109/TMI.2005.862741). Performance was tested with a dataset of 5,468 exams. The Pearson correlation between VBD computed with Transpara Density and the physics model was 0.935 [95% Cl: 0.931 - 0.938]. For breast volume the Pearson correlation coefficient was 0.997.

VBD obtained with Transpara Density was also compared to volumetric measurements based on breast MRI studies in the same patients, for exams acquired within a short time frame. Using a dataset of 190 exams, the Pearson correlation coefficient was 0.908 [95% Cl: 0.878 - 0.931].

Results show that Transpara Density provides accurate estimates of VBD compared to breast MRI and a physics based model.

## Reproducibility

VBD computed in MLO and CC views of the same breast should be similar. In a comparison performed using 10,804 exams. Transpara Density has a Pearson correlation coefficient of 0.947 [95% Cl: 0.945 - 0.948] and a mean absolute deviation of 1.22% [95%

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CI: 1.19% - 1.24%] between CC and MLO views. Minor deviations may be explained by differences in breast positioning.

Using the same dataset, a comparison was also made of VBD computed in the right and left breast of the same patient. The Pearson correlation coefficient was 0.953 [95% Cl: 0.951 - 0.955] with a mean absolute deviation of 1.14% [95% CI: 1.10% - 1.17%] between the left and right breast.

To compare VBD and DG for DM and DBT acquisitions a dataset of 433 exams was used in which images of both modalities were available. The Pearson correlation coefficient in this comparison was 0.912 [95% Cl: 0.904 - 0.920], with a mean absolute deviation of 1.68% [95% C1: 1.57% - 1.78%] between VBD values on FFDM and DBT acquisitions. There was a high agreement in the four category DG values for DM and DBT with a quadratically weighted kappa of 0.810 [95% Cl: 0.787 - 0.835].

## Agreement with human readers

A study was performed with 400 digital mammography and 400 digital breast tomosynthesis examinations from 800 women with a median age of 56, originating from multiple clinical centers and representative for screening and diagnostic assessment procedures. Breast tissue composition in these examinations was independently assessed by eight MQSA-qualified radiologists according to the ACR BI-RADS Atlas 5th Edition. A panel majority vote was computed for each exam to serve as a reference standard in a comparison with the automated breast density grades determined by Transpara Density. Ties in the panel majority-vote were resolved by taking the majority vote of the three most experienced radiologists in the panel. Five exams were excluded from analysis because of non-compliant DICOM headers which caused a failure of the density measurement.

Agreement was assessed by computing accuracy using 4x4 and 2x2 (for non-dense (a+b) and dense (c+d) confusion matrices (figure 1 and figure 2). Also, Cohen's quadratically weighted kappa was calculated to measure the inter-rater agreement for categorical items. Overall the accuracy was 70.8% [95% Cl: 67.6% - 73.9%] [Cohen's weighted kappa = 0.74 [95% Cl: 0.70 - 0.79] for the four breast density categories (a-b-c-d), and 88.9% [95% C1: 86.6% - 90.9%] [Cohen's weighted kappa = 0.78 [95% C1: 0.72 - 0.84]] for the dense vs non-dense assessment.

For dense vs. non-dense classification, Transpara Density has a sensitivity of 87.3% [95% CI: 83.6% - 90.3%], and a specificity of 90.4% [95% CI: 87.2% - 92.9%].

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Image /page/11/Figure/0 description: This image is a table showing the PMV (Predicted Mean Vote) of radiologists according to the BIRADS-V (Breast Imaging Reporting and Data System) classification. The rows represent the Transpara Density, labeled a through d, and the columns represent the radiologists' PMV, also labeled a through d. For example, the cell at row 'a' and column 'b' has a value of 75, while the cell at row 'c' and column 'c' has a value of 239.

Agreement 70.8% (67.6% - 73.9% ), K = 0.743 (0.698 - 0.785)

Fig. 1 Confusion matrix between Transpara Density and PMV for the four breast density categories (a-b-c-d).

Image /page/11/Figure/3 description: This image is a confusion matrix that shows the performance of radiologists' PMV according to BIRADS-V. The matrix compares non-dense and dense categories for both Transpara Density and Radiologists' PMV. The matrix shows that there were 376 true positives for non-dense, 331 true positives for dense, 48 false positives, and 40 false negatives.

Agreement 88.9% (86.6% - 90.9% ), K = 0.778 (0.717 - 0.839)

Fig. 2 Confusion matrix between Transpara Density and PMV for the two breast density categories (non-dense (a+b) vs dense (c+d)).

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## Compatibility

Compatibility with multiple vendors was demonstrated for the Breast Density score: GE, Siemens, Hologic and Fujifilm. For VBD and BV compatibility with GE, Siemens and Hologic was demonstrated.

#### Conclusions 8.

The data presented in this 510(k) includes all required information to support the review by FDA. Performance tests have shown that Transpara Density delivers results that are in high agreement with the visual assessment done by radiologists and that standalone performance requirements were met. Agreement was found between the majority vote of a panel of eight MQSA-qualified radiologists and Transpara Density in classifying dense from non-dense breasts. Standalone performance tests demonstrated that requirements were met.

ScreenPoint has applied a risk management process in accordance with FDA recognized standards to identify, evaluate, and mitigate all known hazards related to Transpara Density. 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 this 510(k) application supports the safe and effective use of Transpara Density for its indications for use and substantial equivalence to the predicate device.