(73 days)
Yes
The device name "ProFound AI" and the explicit mention of "AI" in the "Mentions AI, DNN, or ML" section confirm the use of artificial intelligence.
No
The device is a computer-assisted detection and diagnosis (CAD) software that helps interpreting physicians identify soft tissue densities and calcifications. It does not directly treat or provide therapy to patients.
Yes
The "Intended Use / Indications for Use" section states that the device is "a computer-assisted detection and diagnosis (CAD) software device." It also mentions assisting physicians in "identifying soft tissue densities and calcifications that may be confirmed or dismissed by the interpreting Physician."
Yes
The device description explicitly states "The ProFound Al® V3.0 device detects malignant soft-tissue densities and calcifications in digital breast tomosynthesis (DBT) images. The ProFound AI V3.0 software allows an interpreting physician..." and the intended use describes it as a "computer-assisted detection and diagnosis (CAD) software device". There is no mention of accompanying hardware components.
No, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In vitro diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections. They are used outside of the body.
- This Device's Function: The ProFound AI® V3.0 software analyzes images (digital breast tomosynthesis exams) taken from within the body. It assists interpreting physicians in reading these images to identify potential abnormalities.
- No Sample Analysis: The device does not process or analyze biological samples. Its input is medical imaging data.
Therefore, based on the provided information, ProFound AI® V3.0 is a medical device that uses AI for image analysis in the field of radiology, specifically for breast imaging, but it does not fit the definition of an In Vitro Diagnostic.
No
The provided text does not contain any explicit statement that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The 'Control Plan Authorized (PCCP)' section states "Not Found".
Intended Use / Indications for Use
ProFound AI® V3.0 is a computer-assisted detection and diagnosis (CAD) software device intended to be used concurrently by interpreting physicians while reading digital breast tomosynthesis (DBT) exams from compatible DBT systems. The system detects soft tissue densities (masses, architectural distortions and calcifications in the 3D DBT slices. The detections and Certainty of Finding and Case Scores assist interpreting physicians in identifying soft tissue densities and calcifications that may be confirmed or dismissed by the interpreting Physician.
Product codes
QDQ
Device Description
The ProFound Al® V3.0 device detects malignant soft-tissue densities and calcifications in digital breast tomosynthesis (DBT) images. The ProFound AI V3.0 software allows an interpreting physician to quickly identify suspicious soft tissue densities and calcifications by marking the detected areas in the tomosynthesis images. When the ProFound AI V3.0 marks are displayed by a user, the marks will appear as overlays on the tomosynthesis images. Each detected finding will also be assigned a "score" that corresponds to the ProFound AI V3.0 algorithm's confidence that the detected finding is a cancer (Certainty of Finding). Certainty of Finding scores are a percentage in range of 0% to indicate CAD's confidence that the finding is malignant. ProFound AI V3.0 also assigns a score to each case (Case Score) as a percentage in range of 0% to 100% to indicate CAD's confidence that the case has malignant findings. The higher the Certainty of Finding or Case Score, the higher the confidence that the detected finding is a cancer or that the case has malignant findings.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
Digital breast tomosynthesis
Anatomical Site
Breast
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Interpreting physicians / Radiologists
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies
ProFound AI V3.0 Hologic Supplemental Standalone Study compared performance of ProFound AI V3.0 with Hologic DBT images to the baseline performance of ProFound AI V2 with Hologic DBT images in terms of case sensitivity, FP rate per 3D volume and Area Under the localized Receiver Operating Characteristic (ROC) Curve (AUC). The conclusion of non-inferiority of the standalone performance of ProFound AI V3.0 with a Hologic DBT screening population compared to the baseline performance of ProFound AI V2 with a Hologic DBT screening population is that the claims established in the original Reader Study described in 0074-6003. PowerLook® Tomo Detection V2 Pivotal Reader Study Clinical Study Report (CSR) (K182373) also apply to ProFound AI V3.0 with Hologic DBT. A paired comparison assessed the performance of ProFound AI V3.0 on Hologic DBT images to the performance of ProFound AI V2.0 on the same set of Hologic DBT images and demonstrated a significant increase in specificity from V2.0 to V3.0.
ProFound AI V3.0 GE Supplemental Standalone Study compared performance of ProFound AI V3.0 with GE DBT images to the baseline performance of ProFound AI V2 with Hologic DBT images in terms of case sensitivity, FP rate per 3D volume and AUC. The conclusion of non-inferiority of the standalone performance of ProFound AI V3.0 with a GE DBT screening population compared to the baseline performance of ProFound AI V2 with a Hologic DBT screening population is that the claims established in the original Reader Study described in 0074-6003, PowerLook® Tomo Detection V2 Pivotal Reader Study Report (CSR) (K182373) also apply to ProFound AI V3.0 with GE DBT. A paired comparison assessed the performance of ProFound AI V3.0 on GE DBT images to the performance of ProFound AI V2.0 on the same set of GE DBT images and demonstrated a significant increase in specificity from V2.0 to V3.0.
Key Metrics
Specificity (significant increase from V2.0 to V3.0)
Predicate Device(s)
Reference Device(s)
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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March 12, 2021
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iCAD Inc. % Heather Reed Vice President Quality Assurance and Regulatory Affairs 98 Spit Brook Road, Suite 100 NASHUA NH 03062
Re: K203822
Trade/Device Name: ProFound AI® Software V3.0 Regulation Number: 21 CFR 892.2090 Regulation Name: Radiological computer assisted detection and diagnosis software Regulatory Class: Class II Product Code: QDQ Dated: February 16, 2021 Received: February 22, 2021
Dear Heather Reed:
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/cfpmp/bmn.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 devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
1
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,
Michael D. O'Hara
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) K203822
Device Name ProFound AI® Software V3.0
Indications for Use (Describe)
ProFound AI® V3.0 is a computer-assisted detection and diagnosis (CAD) software device intended to be used concurrently by interpreting physicians while reading digital breast tomosynthesis (DBT) exams from compatible DBT systems. The system detects soft tissue densities (masses, architectural distortions and calcifications in the 3D DBT slices. The detections and Certainty of Finding and Case Scores assist interpreting physicians in identifying soft tissue densities and calcifications that may be confirmed or dismissed by the interpreting Physician
| 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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Image /page/3/Picture/0 description: The image is a logo for iCAD. The logo is in dark blue and features the letters "iCAD" in a stylized font. To the right of the letter "D" is a figure of a person with their arms raised above their head. A curved line extends from the bottom of the "D" and wraps around the figure.
510k Summary K203822
Date Prepared: February 16, 2021
Submitter:
iCAD, Inc. 98 Spit Brook Road Suite 100 Nashua, NH 03062
Contact Person:
Heather Reed Vice President, Quality Assurance and Regulatory Affairs Email: hreed@icadmed.com Phone: (603) 309-1945 Fax: (603) 880-3043
Device Name:
| Trade Name: | ProFound AI® Software V3.0 |
|---|---|
| Common Name: | Medical Imaging Software |
| Classification: | Radiological Computer Assisted Detection and Diagnosis Software |
| Product Code: | QDQ |
| Regulation Number: | 21 CFR 892.2090 |
| Review Panel: | Radiology |
Predicate Device:
| 510k Number: | K191994 |
|---|---|
| Manufacturer: | iCAD, Inc. |
| Device Name: | ProFound AI® V2.1 |
Device Description
The ProFound Al® V3.0 device detects malignant soft-tissue densities and calcifications in digital breast tomosynthesis (DBT) images. The ProFound AI V3.0 software allows an interpreting physician to quickly identify suspicious soft tissue densities and calcifications by marking the detected areas in the tomosynthesis images. When the ProFound AI V3.0 marks are displayed by a user, the marks will appear as overlays on the tomosynthesis images. Each detected finding will also be assigned a "score" that corresponds to the ProFound AI V3.0 algorithm's confidence that the detected finding is a cancer (Certainty of Finding). Certainty of Finding scores are a percentage in range of 0% to indicate CAD's confidence that the finding is malignant. ProFound AI V3.0 also assigns a score to each case (Case Score) as a percentage in range of 0% to 100% to indicate CAD's confidence that the case has malignant findings. The higher the Certainty of Finding or Case Score, the higher the confidence that the detected finding is a cancer or that the case has malignant findings.
4
Technical Characteristics:
Lesion Detection
ProFound AI V3.0 software detects soft tissue densities (masses, architectural distortions and asymmetries) and calcifications in the 3D digital breast tomosynthesis images. The ProFound AI algorithm uses deep learning technology to process feature computations and uses pattern recogmition to identify suspicious breast lesions appearing as soft tissue densities or clusters of calcifications. Each detected region in the tomosynthesis data is identified or represented by marking the contour of the lesion in the tomosynthesis slice where it was detected.
Certainty of Finding Scores
Certainty of Finding scores are relative scores assigned to each detected region and a Case Score is assigned to each case regardless of the number of detected regions. Certainty of Finding and Case Scores are computed by the ProFound AI algorithm and represent the algorithm's confidence that a specific finding or case is malignant. The scores are represented on a 0% to 100% scale. Higher scores represent a higher algorithm confidence that a finding or case is malignant. Lower scores represent a lower algorithm confidence that a finding or case is malignant. The scores are based on a population with 50% prevalence of cancer and should be interpreted as the probability of the finding or case correctly being identified as malignant in a population of 50% cancers and 50% non-cancers. The scores serve as a guide to interpreting physicians to aid in determining if a suspicious finding or case needs further work-up. These scores are not intended to be the clinically used "probability of malignancy". Certainty of Finding and Case Scores are not calibrated to the prevalence in the intended use population or to the prevalence in the pivotal reader study outlined in the Assessment of Non-Clinical Performance Data section, and consequently, the Certainty of Finding and Case Scores are in general higher than the actual probability of malignancy in an intended use population with less than 50% prevalence. These scores represent a relative level of concern or level of suspicion because they do not represent an absolute clinical probability of malignancy.
Case Score
Each tomosynthesis study is assigned a Case Scores are the CAD algorithm's confidence that a study contains a malignant finding. Case Scores are represented on a 0%-100% scale. Higher Case Scores represent a higher confidence that the case contains a malignant finding. Lower Case Scores represent a lower confidence that the case contains a malignant finding.
Supported Digital Breast Tomosynthesis Systems
The following Digital Breast Tomosynthesis systems have been tested and are compatible with ProFound AI V3.0 software:
- Hologic Selenia Dimensions/ 3Dimensions (Standard Resolution)
- GE Senographe Essential with SenoClaire ●
- GE Senographe Pristina ●
- Siemens Inspiration both Standard and Empire Reconstruction ●
5
- Siemens Revelation both Standard and Empire Reconstruction ●
Intended Use / "Indications for Use"
ProFound Al® V3.0 is a computer-assisted detection and diagnosis (CAD) software device intended to be used concurrently by interpreting physicians while reading digital breast tomosynthesis (DBT) exams from compatible DBT systems. The system detects soft tissue densities (masses, architectural distortions and asymmetries) and calcifications in the 3D DBT slices. The detections and Certainty of Finding and Case Scores assist interpreting physicians in identifying soft tissue densities and calcifications that may be confirmed or dismissed by the interpreting Physician.
| Comparison with Predicate Device: | |||
|---|---|---|---|
| ----------------------------------- | -- | -- | -- |
| | UNMODIFIED Device
ProFound™ AI V2.1 | MODIFIED Device
ProFound™ AI V3.0 |
|--------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Manufacturer | iCAD, Inc. | iCAD, Inc. |
| Classification Name | Radiological Computer Assisted
Detection and Diagnosis Software | Radiological Computer Assisted
Detection and Diagnosis Software |
| Regulation Number | 21 CFR 892.2090 | 21 CFR 892.2090 |
| Product Code | QDQ | QDQ |
| 510(k) # | K191994 | Pending |
| Intended Use / Indication for
Use | ProFound™ AI V2.1 is a
computer-assisted detection and
diagnosis (CAD) software device
intended to be used concurrently
by interpreting physicians while
reading digital breast
tomosynthesis (DBT) exams from
compatible DBT systems. The
system detects soft tissue
densities (masses, architectural
distortions and asymmetries) and
calcifications in the 3D DBT
slices. The detections and
Certainty of Finding and Case
Scores assist interpreting
physicians in identifying soft
tissue densities and calcifications
that may be confirmed or
dismissed by the interpreting
Physician. | ProFound AI® V3.0 is a
computer-assisted detection and
diagnosis (CAD) software device
intended to be used concurrently
by interpreting physicians while
reading digital breast
tomosynthesis (DBT) exams from
compatible DBT systems. The
system detects soft tissue
densities (masses, architectural
distortions and asymmetries) and
calcifications in the 3D DBT
slices. The detections and
Certainty of Finding and Case
Scores assist interpreting
physicians in identifying soft
tissue densities and calcifications
that may be confirmed or
dismissed by the interpreting
Physician. |
| End User | Radiologists | Radiologists |
| Patient Population | Symptomatic and asymptomatic
women
undergoing mammography. | Symptomatic and asymptomatic
women
undergoing mammography. |
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| | UNMODIFIED Device
ProFound™ AI V2.1 | MODIFIED Device
ProFound™ AI V3.0 |
|---------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Mode of Action | Image processing device intended
to aid in the detection,
localization, and characterization
of soft tissue densities (masses,
architectural distortions
and asymmetries) and
calcifications in the 3D DBT
slices. | Image processing device intended
to aid in the detection,
localization, and characterization
of soft tissue densities (masses,
architectural distortions
and asymmetries) and
calcifications in the 3D DBT
slices. |
| Image Source Modalities | Digital breast tomosynthesis
slices | Digital breast tomosynthesis
slices |
| Output Device | Softcopy Workstation | Softcopy Workstation |
| Deployment | Standalone computer | Standalone computer |
| Supported Digital Breast
Tomosynthesis Systems | ProFound AI V2 Software:
• Hologic Selenia
Dimensions/3Dimensions
• GE Senographe Esssential
with SenoClaire
• GE Senographe Pristina
ProFound AI V2.1 Software:
• Siemens Inspiration both
Standard and Empire
Reconstruction
• Siemens Revelation both
Standard and Empire
Reconstruction | Profound AI V3.0 Software:
• Hologic Selenia
Dimensions/3Dimensions
• GE Senographe Esssential
with SenoClaire
• GE Senographe Pristina
ProFound AI V2.1 Software:
• Siemens Inspiration both
Standard and Empire
Reconstruction
• Siemens Revelation both
Standard and Empire
Reconstruction |
Summary of Indications for Use:
The "Indications for Use" remain unchanged from the Predicate UNMODIFIED Device ProFound AI V2.1.
Summary of Technological Characteristic
The technological characteristics of Modified Device, ProFound AI V3.0 remain unchanged from Unmodified Device ProFound AI V2.1 as the predicate. Per 21 CFR 892.2090, both devices are radiological computer assisted detection and diagnostic software intended to aid in the detection, localization, and characterization of disease specific findings on acquired medical images. The outputs of both devices serve as a secondary or concurrent read and not a primary read. The output is used to inform the interpreting physician (who themselves make the primary diagnostic and patient management decisions) and will not replace the clinical expertise and judgment of the clinical user.
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The difference in technological characteristics of ProFound AI V3.0 and the predicate device are software improvements leading to improved specificity for GE and Hologic modalities. These changes do not raise different questions of safety and effectiveness.
General 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 this device. Risk management is ensured via a risk analysis which is used to identify and mitigate potential hazards. Any potential hazards are controlled via software development, verification and validation testing. In addition, general controls of the FD&C Act, and special controls established for Radiological Computer Assisted Detection and Diagnosis Software are in place to further mitigate any safety and or effectiveness risks.
Assessment of Non-Clinical Performance Data
ProFound AI V3.0 has been verified and validated according to iCAD's design control processes. All supporting documentation has been included in this 510(k) Premarket Notification. Verification activity included unit, integration, and regression testing was performed. Lastly, ProFound AI V3.0 is deployed on a DICOM platform that has been successfully tested for clinical network integration.
Hologic DBT Non-clinical Validation Testing:
ProFound AI V3.0 Hologic Supplemental Standalone Study compared performance of ProFound AI V3.0 with Hologic DBT images to the baseline performance of ProFound AI V2 with Hologic DBT images in terms of case sensitivity. FP rate per 3D volume and Area Under the localized Receiver Operating Characteristic (ROC) Curve (AUC).
The conclusion of non-inferiority of the standalone performance of ProFound AI V3.0 with a Hologic DBT screening population compared to the baseline performance of ProFound AI V2 with a Hologic DBT screening population is that the claims established in the original Reader Study described in 0074-6003. PowerLook® Tomo Detection V2 Pivotal Reader Study Clinical Study Report (CSR) (K182373) also apply to ProFound AI V3.0 with Hologic DBT.
A paired comparison assessed the performance of ProFound AI V3.0 on Hologic DBT images to the performance of ProFound AI V2.0 on the same set of Hologic DBT images and demonstrated a significant increase in specificity from V2.0 to V3.0.
GE DBT Non-clinical Validation Testing:
ProFound AI V3.0 GE Supplemental Standalone Study compared performance of ProFound AI V3.0 with GE DBT images to the baseline performance of ProFound AI V2 with Hologic DBT images in terms of case sensitivity, FP rate per 3D volume and AUC.
The conclusion of non-inferiority of the standalone performance of ProFound AI V3.0 with a GE DBT screening population compared to the baseline performance of ProFound AI V2 with a Hologic DBT screening population is that the claims established in the original Reader Study described in 0074-6003, PowerLook® Tomo Detection V2 Pivotal Reader Study Report (CSR) (K182373) also apply to ProFound AI V3.0 with GE DBT.
8
A paired comparison assessed the performance of ProFound AI V3.0 on GE DBT images to the performance of ProFound AI V2.0 on the same set of GE DBT images and demonstrated a significant increase in specificity from V2.0 to V3.0.
Conclusion:
Based upon the information presented in this submission, it is concluded that ProFound AI V3.0 is substantially equivalent to the named predicate device.