(110 days)
Yes
The device description explicitly states that the image analysis unit includes "machine learning components trained to detect calcifications and soft tissue lesions".
No.
The device is described as a "concurrent reading aid for physicians interpreting screening mammograms" and its output is used to "identify regions suspicious for breast cancer and assess their likelihood of malignancy." It does not directly provide therapy or treatment.
Yes
The device aids in the detection and diagnosis of breast cancer by identifying suspicious regions, assessing likelihood of malignancy, and providing an overall score indicating the likelihood of cancer on a mammogram. Therefore, it fits the definition of a diagnostic device.
Yes
The device description explicitly states "Transpara™ is a software-only device". While it interacts with hardware (FFDM systems, PACS, workstations), the device itself, as described, is solely the software component.
Based on the provided information, the ScreenPoint Transpara™ system is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: IVD devices are used to examine specimens derived from the human body (like blood, urine, tissue) to provide information about a patient's health.
- Transpara's Function: Transpara™ analyzes medical images (mammograms) to aid physicians in interpreting those images. It does not analyze biological specimens.
Therefore, Transpara™ falls under the category of a medical device, specifically a software-only device used for image analysis and interpretation, rather than an IVD.
No
The input states "Control Plan Authorized (PCCP) and relevant text Not Found", indicating that the letter does not mention explicit FDA approval or clearance of a PCCP for this device.
Intended Use / Indications for Use
The ScreenPoint Transpara™ system is intended for use as a concurrent reading aid for physicians interpreting screening mammograms from compatible FFDM systems, to identify regions suspicious for breast cancer and assess their likelihood of malignancy. Output of the device includes marks placed on suspicious soft tissue lesions and suspicious calcifications; region-based scores, displayed upon the physician's query, indicating the likelihood that cancer is present in specific regions; and an overall score indicating the likelihood that cancer is present on the mammogram. Patient management decisions should not be made solely on the basis of analysis by Transpara™.
Product codes
QDQ
Device Description
Transpara™ is a software-only device for aiding radiologists with the detection and diagnosis of breast cancer in mammograms. The product consists of a processing server and an optional viewer. The software applies algorithms for recognition of suspicious calcifications and soft tissue lesions, which are trained with large databases of biopsy proven examples of breast cancer, benign lesions and normal tissue. Processing results of Transpara™ can be transmitted to external destinations, such as medical imaging workstations or archives, using the DICOM mammography CAD SR protocol. This allows PACS workstations to implement the interface of Transpara™ in mammography reading applications.
Transpara™ automatically processes mammograms and the output of the device can be used by radiologists concurrently with the reading of mammograms. The user interface of Transpara™ has different functions:
a) Activation of computer aided detection (CAD) marks to highlight locations where the device detected suspicious calcifications or soft tissue lesions. Only the most suspicious soft tissue lesions are marked to achieve a very low false positive rate.
b) Regions can be queried using a pointer for interactive decision support. When the location of the queried region corresponds with a finding of Transpara™ a suspiciousness level of the region computed by the algorithms in the device is displayed. When Transpara™ has identified a corresponding region in another view of the same breast this corresponding region is also displayed to minimize interactions required from the user.
c) Display of the exam based Transpara™ Score which categorizes exams on a scale of 1-10 with increasing likelihood of cancer.
Transpara™ is configured as a DICOM node in a network and receives its input images from another DICOM node, such as a mammography device or a PACS archive. The image analysis unit includes machine learning components trained to detect calcifications and soft tissue lesions and a component to pre-process images in such a way that images from different vendors can be processed by the same algorithms.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
FFDM systems (Full Field Digital Mammography)
Anatomical Site
Breast
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Intended users of Transpara™ are physicians qualified to read screening mammograms.
Use in a healthcare facility or hospital.
Description of the training set, sample size, data source, and annotation protocol
The software applies algorithms for recognition of suspicious calcifications and soft tissue lesions, which are trained with large databases of biopsy proven examples of breast cancer, benign lesions and normal tissue.
Description of the test set, sample size, data source, and annotation protocol
Validation testing consisted of determining stand-alone performance of the algorithms in Transpara™ using a multi-vendor test-set of mammograms acquired from multiple centers. This test dataset was not used for training of Transpara™ algorithms and included mammograms of asymptomatic women acquired with devices from five manufacturers: Hologic, GE, Philips, Siemens, and Fujifilm.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Software performance testing:
Verification testing consisted of software unit testing, software integration testing and software system testing. The verification test showed that the software application satisfied the software requirements.
Validation testing consisted of determining stand-alone performance of the algorithms in Transpara™ using a multi-vendor test-set of mammograms acquired from multiple centers. This test dataset was not used for training of Transpara™ algorithms and included mammograms of asymptomatic women acquired with devices from five manufacturers: Hologic, GE, Philips, Siemens, and Fujifilm. Validation testing confirmed that algorithm performance has improved in comparison to Transpara 1.3.0 for the four manufacturers for which the device was already cleared and that for Fujifilm a similar performance is achieved.
Based on results of verification and validation tests it is concluded that Transpara™ is effective in the detection of soft lesions and calcifications at an appropriate safety level in mammograms acquired with mammography devices for which the software has been validated.
Summary of clinical tests:
A pivotal reader study was conducted with the predicate device Transpara 1.3.0. This study provided evidence for safety and effectiveness of Transpara™.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2090 Radiological computer-assisted detection and diagnosis software.
(a)
Identification. A radiological computer-assisted detection and diagnostic software is an image processing device intended to aid in the detection, localization, and characterization of fracture, lesions, or other disease-specific findings on acquired medical images (e.g., radiography, magnetic resonance, computed tomography). The device detects, identifies, and characterizes findings based on features or information extracted from images, and provides information about the presence, location, and characteristics of the findings to the user. The analysis is intended to inform the primary diagnostic and patient management decisions that are made by the clinical user. The device is not intended as a replacement for a complete clinician's review or their clinical judgment that takes into account other relevant information from the image or patient history.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the image analysis algorithm, including a description of the algorithm inputs and outputs, each major component or block, how the algorithm and output affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide improved assisted-read detection and diagnostic performance as intended in the indicated user population(s), and to characterize the standalone device performance for labeling. Performance testing includes standalone test(s), side-by-side comparison(s), and/or a reader study, as applicable.
(iii) Results from standalone performance testing used to characterize the independent performance of the device separate from aided user performance. The performance assessment must be based on appropriate diagnostic accuracy measures (
e.g., receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Devices with localization output must include localization accuracy testing as a component of standalone testing. The test dataset must be representative of the typical patient population with enrichment made only to ensure that the test dataset contains a sufficient number of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, concomitant disease, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals of the device for these individual subsets can be characterized for the intended use population and imaging equipment.(iv) Results from performance testing that demonstrate that the device provides improved assisted-read detection and/or diagnostic performance as intended in the indicated user population(s) when used in accordance with the instructions for use. The reader population must be comprised of the intended user population in terms of clinical training, certification, and years of experience. The performance assessment must be based on appropriate diagnostic accuracy measures (
e.g., receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Test datasets must meet the requirements described in paragraph (b)(1)(iii) of this section.(v) Appropriate software documentation, including device hazard analysis, software requirements specification document, software design specification document, traceability analysis, system level test protocol, pass/fail criteria, testing results, and cybersecurity measures.
(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use.
(ii) A detailed description of the device instructions for use, including the intended reading protocol and how the user should interpret the device output.
(iii) A detailed description of the intended user, and any user training materials or programs that address appropriate reading protocols for the device, to ensure that the end user is fully aware of how to interpret and apply the device output.
(iv) A detailed description of the device inputs and outputs.
(v) A detailed description of compatible imaging hardware and imaging protocols.
(vi) Warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality or for certain subpopulations), as applicable.(vii) A detailed summary of the performance testing, including test methods, dataset characteristics, results, and a summary of sub-analyses on case distributions stratified by relevant confounders, such as anatomical characteristics, patient demographics and medical history, user experience, and imaging equipment.
0
December 10, 2019
Image /page/0/Picture/1 description: The image contains the logos of the Department of Health & Human Services and the Food and Drug Administration (FDA). The Department of Health & Human Services logo is on the left, and the FDA logo is on the right. The FDA logo includes the text "U.S. Food & Drug Administration".
Screenpoint Medical B.V. % Umar Waqas, Ph.D. Regulatory Officer Mercator II, 7th floor, Toernooiveld 300 6525 EC Nijmegen, Gelderland THE NETHERLANDS
Re: K192287
Trade/Device Name: Transpara™ Regulation Number: 21 CFR 892.2090 Regulation Name: Radiological computer assisted detection and diagnosis software Regulatory Class: Class II Product Code: QDQ Dated: October 30, 2019 Received: November 1, 2019
Dear Dr. Waqas:
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 (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 located 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.
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 803) for
1
devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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 (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
For
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
2
Indications for Use
510(k) Number (if known) K192287
Device Name Transpara
Indications for Use (Describe)
The ScreenPoint Transpara™ system is intended for use as a concurrent reading aid for physicians interpreting screening mammograms from compatible FFDM systems, to identify regions suspicious for breast cancer and assess their likelihood of malignancy. Output of the device includes marks placed on suspicious and suspicious calcifications; region-based scores, displayed upon the physician's query, indicating the likelihood that cancer is present in specific regions, and an overall score indicating the likelihood that cancer is present on the mammogram. Patient management decisions should not be made solely on the basis of analysis by Transpara™.
| Type of Use (Select one or both, as applicable) | ||
|---|---|---|
| X 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 rouio inotructiono grob yigting dato gother and maintain the doto nooded and comploto |
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.
Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2020 See PRA Statement below.
3
510(k) Summary Transpara™ K192287
This 510(k) summary of safety and effectiveness information is prepared in accordance with the requirements of 21 CFR § 807.92.
1. Submitter
Manufacturer:
ScreenPoint Medical B.V.
Mercator II, 7th floor
Toernooiveld 300
6525 EC Nijmegen
Netherlands
Contact person:
Umar Waqas
Office: +31 24 3030045 | +31 24 2020020
Mobile: +31 6 44077104
Mercator II, 7th floor, Toernooiveld 300, 6525 EC Nijmegen, Netherlands
Date:
December 10, 2019
4
2. Device
| Device trade name | Transpara™ |
|---|---|
| Device | Radiological Computer Assisted Detection and |
| Diagnosis Software | |
| Classification regulation | 21 CFR 892.2090 |
| Panel | Radiology |
| Device class | II |
| Product code | QDQ |
| Submission type | Traditional 510(k) |
3. Legally marketed predicate device
| Device trade name | Transpara™ 1.3.0 (K181704) |
|---|---|
| Legal Manufacturer | ScreenPoint Medical B.V. |
| Device | Radiological Computer Assisted Detection and |
| Diagnosis Software | |
| Classification regulation | 21 CFR 892.2090 |
| Panel | Radiology |
| Device class | II |
| Product code | QDQ |
4. Device description
Transpara™ is a software-only device for aiding radiologists with the detection and diagnosis of breast cancer in mammograms. The product consists of a processing server and an optional viewer. The software applies algorithms for recognition of suspicious calcifications and soft tissue lesions, which are trained with large databases of biopsy proven examples of breast cancer, benign lesions and normal tissue. Processing results of Transpara™ can be transmitted to external destinations, such as medical imaging workstations or archives, using the DICOM mammography CAD SR protocol. This allows PACS workstations to implement the interface of Transpara™ in mammography reading applications.
5
Transpara™ automatically processes mammograms and the output of the device can be used by radiologists concurrently with the reading of mammograms. The user interface of Transpara™ has different functions:
- a) Activation of computer aided detection (CAD) marks to highlight locations where the device detected suspicious calcifications or soft tissue lesions. Only the most suspicious soft tissue lesions are marked to achieve a very low false positive rate.
- b) Regions can be queried using a pointer for interactive decision support. When the location of the queried region corresponds with a finding of Transpara™ a suspiciousness level of the region computed by the algorithms in the device is displayed. When Transpara™ has identified a corresponding region in another view of the same breast this corresponding region is also displayed to minimize interactions required from the user.
- c) Display of the exam based Transpara™ Score which categorizes exams on a scale of 1-10 with increasing likelihood of cancer.
Transpara™ is configured as a DICOM node in a network and receives its input images from another DICOM node, such as a mammography device or a PACS archive. The image analysis unit includes machine learning components trained to detect calcifications and soft tissue lesions and a component to pre-process images in such a way that images from different vendors can be processed by the same algorithms.
5. Indications for use
Transpara™ is a software medical device for use in a healthcare facility or hospital with the following indications for use:
The ScreenPoint Transpara™ system is intended for use as a concurrent reading aid for physicians interpreting screening mammograms from compatible FFDM systems, to identify regions suspicious for breast cancer and assess their likelihood of malignancy. Output of the device includes marks placed on suspicious soft tissue lesions and suspicious calcifications; region-based scores, displayed upon the physician's query, indicating the likelihood that cancer is present in specific regions; and an overall score indicating the likelihood that cancer is present on the mammogram. Patient management decisions should not be made solely on the basis of analysis by Transpara™.
Intended user population
Intended users of Transpara™ are physicians qualified to read screening mammograms.
6
Intended patient population
The device is intended to be used in the population of women undergoing screening mammography.
Warnings and precautions
Transpara™ is an adjunct tool and not intended to replace a physicians' own review of a mammogram. Decisions should not be made solely based on analysis by Transpara™.
6. Predicate device comparison
The indication for use of Transpara™1.5.0 is the same as that of the predicate device. Both devices are intended to be used by clinicians interpreting mammograms, to help them with localizing and characterizing abnormalities. The devices are both intended to be used concurrently with the reading of images and are not intended as a replacement for the review of a clinician or their clinical judgement.
The overall design of Transpara™1.5.0 is similar to that of the predicate device. The main differences in technological characteristics of Transpara™ 1.5.0 and the predicate device are algorithmic improvements leading to better detection performance. Additionally, the 1.5.0 version now supports Fujifilm modalities. These changes do not raise different questions of safety and effectiveness.
7. Summary of non-clinical performance data
In the design and development of Transpara™, ScreenPoint applied the following voluntary FDA recognized standards and guidelines:
| Standard ID | Standard Title | FDA Recognition # |
|---|---|---|
| ISO 14971:2007 | Medical Devices - Application Of Risk | |
| Management To Medical Devices | 5-40 | |
| IEC 62304:2015 | Medical Device Software - Software Life - | |
| Cycle Processes | 13-79 | |
| DEN180005 | Decision summary with special controls | |
| for class II radiology device |
The following guidance documents were used to support this submission:
7
- . Guidance for Industry and FDA Staff - Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (Issued on May 11, 2005)
- 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 - Premarket Approval (PMA) and Premarket Notification [510(k)] Submissions (Issued on July 3, 2012)
Software performance testing
Transpara™1.5.0 is a software-only device. The level of concern for the device is determined as Moderate Level of Concern.
Verification testing consisted of software unit testing, software integration testing and software system testing. The verification test showed that the software application satisfied the software requirements.
Validation testing consisted of determining stand-alone performance of the algorithms in Transpara™ using a multi-vendor test-set of mammograms acquired from multiple centers. This test dataset was not used for training of Transpara™ algorithms and included mammograms of asymptomatic women acquired with devices from five manufacturers: Hologic, GE, Philips, Siemens, and Fujifilm. Validation testing confirmed that algorithm performance has improved in comparison to Transpara 1.3.0 for the four manufacturers for which the device was already cleared and that for Fujifilm a similar performance is achieved.
Based on results of verification and validation tests it is concluded that Transpara™ is effective in the detection of soft lesions and calcifications at an appropriate safety level in mammograms acquired with mammography devices for which the software has been validated.
8. Summary of clinical tests
A pivotal reader study was conducted with the predicate device Transpara 1.3.0. This study provided evidence for safety and effectiveness of Transpara™
9. Conclusions
The data presented in this 510(k) includes all required information to support the review by FDA. Standalone performance tests demonstrate that Transpara™ 1.5.0 achieves better detection performance compared to the predicate device.
8
ScreenPoint has applied a risk management process in accordance with FDA recognized standards to identify, evaluate, and mitigate all known hazards related to Transpara™. These hazards may occur when accuracy of diagnosis is potentially affected, causing either false-positives or false-negatives. 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) supports the safe and effective use of Transpara™ for its indications for use and substantial equivalence to the predicate device.