(147 days)
QDQ
Not Found
Yes
The device description explicitly states that the image analysis unit includes "machine learning components trained to detect calcifications and soft tissue lesions".
No
This device is a reading aid for physicians interpreting mammograms, providing marks and scores to identify suspicious regions for breast cancer. It does not directly treat or diagnose a disease but assists in the diagnostic process.
Yes
The device aids radiologists in the detection and diagnosis of breast cancer by identifying suspicious regions, scoring likelihood of malignancy, and improving diagnostic performance. The description explicitly states its function as "aiding radiologists with the detection and diagnosis of breast cancer in mammograms."
Yes
The device description explicitly states "Transpara™ is a software-only device". While it interacts with external hardware (mammography devices, PACS), the device itself is solely software.
Based on the provided information, the ScreenPoint Transpara™ system is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze biological samples: IVDs are designed to examine specimens taken from the human body, such as blood, urine, tissue, etc., to provide information about a person's health.
- Transpara™ analyzes medical images: Transpara™ operates on mammograms, which are medical images, not biological samples. It processes and interprets these images to aid in the detection of potential abnormalities.
- Intended Use: The intended use clearly states that Transpara™ is a "concurrent reading aid for physicians interpreting screening mammograms." This aligns with image analysis and interpretation, not the analysis of biological specimens.
Therefore, Transpara™ falls under the category of medical image analysis software, not an In Vitro Diagnostic device.
No
The letter does not state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. It only references special controls related to DEN180005.
Intended Use / Indications for Use
The ScreenPoint Transpara™ system is intended for use as a concurrent reading aid for physicians interpreting screening mammograms, 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
mammograms
Anatomical Site
breast
Indicated Patient Age Range
Not Found
Intended User / Care Setting
physicians qualified to read screening mammograms / 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 testset of mammograms acquired from multiple centers in multiple EU countries. This test dataset was not used for training of Transpara™ algorithms and included mammograms of asymptomatic women acquired with devices from four manufacturers: Hologic, GE, Philips and Siemens.
Summary of Performance Studies
Software performance testing:
- Study Type: Stand-alone performance test
- Sample Size: Not explicitly stated, but described as a multi-vendor testset.
- AUC: Not directly applicable to CADe marks for sensitivty/FPR.
- MRMC: Not applicable.
- Standalone Performance: Sensitivity for calcifications was 94.1 (90.6-97.1) with a false positive rate of 0.23 (0.22-0.25) marks per image. For soft tissue lesions sensitivity was 72.0 (67.4-76.5) with a false positive rate of 0.033 (0.028-00.037) marks per image. The Transpara™ Score showed that in the independent testing database 78% of exams with screen-detected cancers fall in category 10.
- Key Results: Transpara™ is effective in the detection of soft lesions and calcifications at an appropriate safety level in mammograms.
Clinical Reader study:
- Study Type: Retrospective, fully-crossed multi-reader multicase (MRMC) study.
- Sample Size: 14 MQSA qualified radiologists read 240 cases twice (100 cancer cases, 40 false positive recalls, 100 normal exams).
- AUC: Average AUC increased from 0.866 (unaided) to 0.886 (aided) (+0.020, 95% CI = 0.010 - 0.030, P=0.0019). For soft tissue lesions, AUC increased from 0.886 to 0.902 (mean difference = +0.016). For calcifications, AUC was 0.878 (unaided) and 0.898 (aided) (mean difference = +0.020).
- MRMC: Yes, study was a MRMC design.
- Standalone Performance: Transpara™ standalone AUC=0.887, which approached the average performance of clinical study radiologists when reading mammograms unaided (0.866). Transpara™ had higher AUC than eleven out of fourteen radiologists, and lower AUC than the other three.
- Key Results: Radiologists significantly improved their detection performance when using Transpara™. Reading time per case was similar.
Key Metrics
- Sensitivity for calcifications: 94.1 (90.6-97.1) (standalone)
- False Positive Rate for calcifications: 0.23 (0.22-0.25) marks per image (standalone)
- Sensitivity for soft tissue lesions: 72.0 (67.4-76.5) (standalone)
- False Positive Rate for soft tissue lesions: 0.033 (0.028-0.037) marks per image (standalone)
- AUC improvement: +0.020, 95% Cl = 0.010 - 0.030, P=0.0019 (reader study)
- Reading Time: Unaided: 146 s, 95% Cl: 143-149 s; Aided: 149 s, 95% Cl: 146-152 s.
Predicate Device(s)
OsteoDetect
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.
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health and Human Services logo on the left, and the FDA logo on the right. The FDA logo is a blue square with the letters "FDA" in white, followed by the words "U.S. Food & Drug Administration" in blue.
November 21, 2018
ScreenPoint Medical BV % Dr. Nico Karssemeijer CEO Stationsplein 26 Nijmegen, 6512 AB NETHERLANDS
Re: K181704
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 17, 2018 Received: October 19, 2018
Dear Dr. Karssemeijer:
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 mav, 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 avare 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
1
requirements, including, but not limited to: registration and listing (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/CombinationProducts/GuidanceRegulatoryInformation/ucm597488.html; good manufacturing practice requirements as set forth in the quality systems (OS) 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 http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). 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 (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
Michael D.'Hara For
Robert Ochs, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K181704
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, 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™.
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) |
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510(k) Summary Transpara™
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 BV
Stationsplein 26
6512 AB Nijmegen
The Netherlands
Contact person:
Nico Karssemeijer
Office: +31 24 2020027 | +31 24 2020020
Mobile: +31 6 13508596
Stationsplein 26, 6512AB, Nijmegen, The Netherlands
Date:
November 18, 2018
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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 | OsteoDetect |
|---|---|
| Legal Manufacturer | Imagen Technologies, Inc. |
| Device | Radiological Computer Assisted Detection and Diagnosis Software |
| Classification regulation | 21 CFR 892.2090 |
| Panel | Radiology |
| Device class | II |
| Product code | QBS |
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.
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:
5
- 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, 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.
Intended patient population
The device is intended to be used in the population of women undergoing screening mammography.
Warnings and precautions
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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™ is similar to that of the predicate device. Both devices are intended to be used by clinicians interpreting radiological images, 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 indication for use of Transpara™ and the predicate device differ in the disease specific findings the devices detect, the type of medical images the devices process, and the intended patient population. However, these differences do not raise new questions regarding safety and effectiveness of the device when used as labeled.
The overall design of Transpara™ is similar to that of the predicate device. Differences in technological characteristics of Transpara™ and the predicate device 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:
| 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 | Evaluation of automatic class III | |
| designation for OsteoDetect - Decision | ||
| summary with special controls | N/A |
The following guidance 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)
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- . 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™ 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 purpose of the verification test was to assure 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 testset of mammograms acquired from multiple centers in multiple EU countries. This test dataset was not used for training of Transpara™ algorithms and included mammograms of asymptomatic women acquired with devices from four manufacturers: Hologic, GE, Philips and Siemens. Sensitivity and specificity of the CADe marks for detection of malignant calcification groups and soft tissue lesions were determined with 95% confidence intervals obtained by bootstrapping. Sensitivity for calcifications was 94.1 (90.6-97.1) with a false positive rate of 0.23 (0.22-0.25) marks per image. For soft tissue lesions sensitivity was 72.0 (67.4-76.5) with a false positive rate of 0.033 (0.028-0.037)marks per image.
The Transpara™ Score indicates the likelihood that a mammographically visible cancer is present in an exam. The score combines the results of the Transpara™ algorithms. The score is calibrated in such a way that the number of screening mammograms in each category is approximately equal. The figure shows that in the independent testing database 78% of exams with screen-detected cancers fall in category 10, while very few occur in the lowest categories (Fig. 1)
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Image /page/8/Figure/2 description: The image is a bar graph showing the percentage of cancers for different Transpara scores. The x-axis represents the Transpara score, ranging from 1 to 10, and the y-axis represents the percentage of cancers, ranging from 0 to 100. The bar for a Transpara score of 10 is significantly higher than the others, reaching nearly 80 percent, while the other scores are below 10 percent.
Figure1: The Transpara™ Score indicates the likelihood that a mammographically visible cancer is present in an exam. The graph shows that in the testing database over 78% of exams with category 10, while very few occur in the lowest categories.
Transpara™ operates on "FOR PRESENTATION' images from different manufacturers. Since manufacturers use different processing algorithms, which may evolve over time or have flavors which can be selected by the user, the performance of the Transpara™ detection algorithms should not be affected by differences in image processing methods applied by manufacturers. In addition, algorithms should be able to work with images that have a different pixel spacing. Stability tests have been performed to verify that performance of Transpara™ remains stable when processing and pixel spacing varies.
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 has been conducted to determine whether the performance of radiologists in detecting breast cancer in mammograms increases when they use the Transpara™, compared to when they read mammograms unaided. The primary effectiveness endpoint of the study is a significant increase of area under the ROC (AUC). The following quidance document was used to design and conduct the study:
- 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)
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In the study, both conditions are tested with a balanced fully-crossed multi-reader multicase (MRMC) retrospective study. Study outcomes are comparisons of area under the receiver operating characteristic curve, sensitivity and specificity, and reading time.
In the study fourteen MQSA qualified radiologists read 240 cases twice, once with and once without Transpara™, with a washout period of one month or more in between. The reader study was conducted in the United States. The study set contained digital mammograms of asymptomatic women that were retrospectively collected at two clinical centers using Lorad Selenia (Hologic) and Mammomat Inspiration devices. The selected cases consisted of series of consecutive samples. The study set included 100 cases with cancer, 40 false positive recalls from screening, and 100 normal exams.
Reading was performed using a setting similar to a screening procedure in the United States. All readers completed the reading sessions as scheduled following the study protocol. There were no adverse events reported in the clinical reader study.
Statistical analysis of the MRMC study was done using analysis of variance models that take repeated measures into account.
Results showed that radiologists significantly improved their detection performance when using Transpara™, with the average AUC increasing from 0.866 to 0.886 (+0.020, 95% Cl = 0.010 - 0.030, P=0.0019). (Figure 2). Per reader, the changes in AUC ranged from -0.3% to +5.4%, being higher with Transpara™ for twelve out of the fourteen radiologists (equal AUC for one reader and decrease of 0.3% with Transpara™ for another).
Image /page/9/Figure/7 description: The image contains two plots. The plot on the left is a Receiver Operating Characteristic (ROC) curve comparing the sensitivity and 1-specificity of an unaided model versus a model with Transpara. Both models have an AUC of 0.866. The plot on the right is a scatter plot comparing the AUC of the unaided model versus the model with Transpara, with each point representing a different AUC-Wilcoxon value. The points are clustered around the diagonal line, indicating that the two models have similar performance.
Figure 2. Average ROC performance of the readers under both reading conditions (left), and AUC performance of the individual readers in aided and unaided condition (right). In the ROC plot to mputed with the BI-RADS ≥3 criterion is shown.
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Analysis by lesion type was performed by only including the True and False positive exams of the given type in the evaluation. Performance was higher with Transpara™ whether reading cases with soft tissue lesions or reading cases with calcifications. For soft tissue lesions, the AUC increased from 0.886 to 0.902 (mean difference = +0.016, standard error = 0.007), while for calcifications, the AUC was 0.878 in the unaided and 0.898 in the aided mode (mean difference = +0.020, standard error = 0.012).
On average, reading time per case was similar in the unaided sessions (146 s, 95% Cl: 143-149 s) and the sessions with Transpara™ (149 s, 95% Cl: 146-152 s). Reading time increased for nine out of fourteen radiologists (range 0.5-10%) while it decreased for five (range 0.3%-22%)
The standalone breast cancer detection performance of Transpara™ was observed to approach the average performance of the clinical study radiologists when reading mammograms unaided (radiologists' AUC = 0.866 versus Transpara™ AUC=0.887). Compared to each individual radiologist, Transpara™ had higher AUC (range 1.5-9.3%) than eleven out of the fourteen radiologists, and lower AUC than the other 3 (range 1.7-4.7%).
Image /page/10/Figure/5 description: The image contains two ROC curves comparing the performance of radiologists and a stand-alone Transpara system. The left plot shows the ROC curves for multiple radiologists, labeled as Radiologist 1, Radiologist 2, Radiologist 3, and Radiologist 14, along with the Stand-alone Transpara system. The right plot compares the ROC curves of the unaided performance (0.866) with the Stand-alone Transpara system (0.887), also indicating the operating point for the unaided performance.
Figure 3. Comparison of ROC curves between the radiologists (reading mammograms unaided, left individual radiologists, right shows the average of the 14 radiologists) and Transpara™ as a stand-alone. Radiologists' operating points at BI-RADS 3 thresholds are indicated with the circle markers. Op. pt. iindicates the mean operating point of the radiologists.
Discussion
The primary endpoint of the clinical study was met. With the use of device AUC of the readers increase significantly (p=0.0019). Secondary descriptive analyses show that the
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impact of Transpara™ on radiologists' performance depends negligibly on lesion type, image type and used workflow, while there is not an increase in reading time.
In conclusion, study results provide evidence for safety and effectiveness of Transpara™. With use of the device it is likely that false positives and false negatives are reduced. A decrease in false positives and false negative was also found in the clinical test performed with the predicate device, in a study with similar design. Therefore, the outcome of the clinical study supports substantial equivalence of Transpara™ with the predicate device.
9. Conclusions
The data presented in this 510(k) includes all required information to support the review by FDA. Non-clinical and clinical performance tests demonstrate that Transpara™ is safe and effective.
One difference with the predicate device is a difference in the indications for use, because it detects different disease specific findings in different radiological images. The risks associated with use of the device are comparable because they are both intended to be used in a similar same way as aid for the clinician. Main risks are related to false positives and false negatives of the devices and these are mitigated by special controls defined in DEN180005.
Results of the primary analysis of the clinical test demonstrate that use of Transpara™ improves detection of breast cancer in mammograms. Hypothesis testing was not prespecified for secondary analyses. Descriptively, improvement was observed to depend negligibly on lesion type and reading time was not observed to increase with the use of Transpara™. In addition, sensitivity of the readers tended to increase with the use of Transpara™ without decreasing specificity. Finally, in standalone testing, Transpara™ breast cancer detection performance was observed to approach the average performance of the clinical study radiologists when reading mammograms unaided.
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.