(28 days)
Yes
The document explicitly states that the device "uses an artificial intelligence algorithm to analyze images" and mentions "deep learning algorithm development" and "machine learning" in the description of the training set.
No
The device is described as a "radiological computer-aided triage and notification software" intended to "assist workflow triage by flagging and communicating suspected positive cases of Pulmonary Embolism (PE) pathologies." It is clearly stated that the device "does not alter the original medical image and is not intended to be used as a diagnostic device" and notifications are "not intended for diagnostic use beyond notification." Its purpose is to prioritize cases for clinicians, not to treat or directly manage disease.
No
The "Intended Use / Indications for Use" section explicitly states, "The device does not alter the original medical image and is not intended to be used as a diagnostic device." Additionally, it clarifies that notifications are "for informational purposes only and not intended for diagnostic use beyond notification" and that "full images per the standard of care" must be viewed by clinicians for diagnosis.
Yes
The device description explicitly states that Briefcase-Triage is a "radiological computer-assisted triage and notification software device" and that it is "intended to run on a linux-based server in a cloud environment." There is no mention of accompanying hardware components that are part of the device itself.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze biological samples (like blood, urine, tissue) to provide information about a patient's health. The Briefcase-Triage device analyzes medical images (CTPA scans), not biological samples.
- The intended use is for workflow triage and notification based on image analysis. It is explicitly stated that the device "does not alter the original medical image and is not intended to be used as a diagnostic device." While it assists in identifying potential pathologies, it does so by analyzing images, not by performing tests on biological specimens.
Therefore, the Briefcase-Triage device falls under the category of a medical image analysis software, not an In Vitro Diagnostic.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The provided text only indicates "Not Found" for "Control Plan Authorized (PCCP) and relevant text".
Intended Use / Indications for Use
BriefCase-Triage is a radiological computer- aided triage and notification software indicated for use in the analysis of CTPA images, in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive cases of Pulmonary Embolism (PE) pathologies.
Briefcase-Triage uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected PE findings. Notifications include compressed preview images that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Briefcase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
Product codes
QAS
Device Description
Briefcase-Triage is a radiological computer-assisted triage and notification software device. The software is based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.
The Briefcase-Triage receives filtered DICOM Images, and processes them chronologically by running the algorithms on each series to detect suspected cases. Following the Al processing, the output of the algorithm analysis is transferred to an image review software (desktop application). When a suspected case is detected, the user receives a pop-up notification and is presented with a compressed, low-quality, grayscale image that is captioned "not for diagnostic use, for prioritization only" which is displayed as a preview function. This preview is meant for informational purposes only, does not contain any marking of the findings, and is not intended for primary diagnosis beyond notification.
Presenting the users with worklist prioritization facilitates efficient triage by prompting the user to assess the relevant original images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CTPA images
Anatomical Site
Chest
Indicated Patient Age Range
adults or transitional adolescents aged 18 and older.
Intended User / Care Setting
Hospital networks and appropriately trained medical specialists
Description of the training set, sample size, data source, and annotation protocol
The algorithm was trained during software development on images of the pathology. As is customary in the field of machine learning, deep learning algorithm development consisted of training on manually labeled ("tagged") images. In that process, critical findings were tagged in all CTs in the training data set.
Description of the test set, sample size, data source, and annotation protocol
Aidoc conducted a retrospective, blinded, multicenter study with the Briefcase-Triage software to evaluate the software's performance in identifying CTPA images containing Pulmonary Embolism (PE) in 499 cases from 6 US-based clinical sites, compared to the ground truth as determined by three senior board-certified radiologists. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm, as was used for the most recent clearance (K22277). Test pivotal study data was sequestered from algorithm development activities, and use of the data is managed by appropriate Quality Management System procedures.
Summary of Performance Studies
Study Type: Retrospective, blinded, multicenter study
Sample Size: 499 cases
Standalone Performance: Not Found
Key Results:
Sensitivity and specificity exceeded the 80% performance goal. Sensitivity was 94.39% (95% Cl: 90.41%, 97.07%) and Specificity was 94.39% (95% Cl: 91.04%, 96.67%).
The Briefcase-Triage mean time-to-notification for the subject PE triage was 26.42 seconds (95% C1: 25.3-27.54). The time-to-notification for the predicate PE was 78 seconds (95% CI 73.6-82.3).
NPV was 98.96% (95% CI: 98.21%- 99.4%) and PPV was 74.79% (95% CI: 64.80%- 82.7%). PLR was 16.81 (95% Cl: 10.43- 27.09) and NLR was 0.059 (95% Cl: 0.034- 0.103).
Additional Operating Points:
AOP1: Sensitivity was 99.53% (95% Cl: 97.42%- 99.99%) and Specificity was 86.67% (95% Cl: 82.16%-90.39%).
AOP2: Sensitivity was 97.66% (95% Cl: 94.63%-99.24%) and Specificity was 91.93% (95% Cl: 88.14%-94.82%.
AOP3: Sensitivity was 91.59% (95% C1: 87.03%- 94.94%) and Specificity was 96.49% (95% C1: 93.64%-98.3%).
AOP4: Sensitivity was 85.98% (95% C1: 80.6%-90.34%) and Specificity was 98.25% (95% C1: 95.95%-99.43%).
Key Metrics
Sensitivity: 94.39% (95% Cl: 90.41%, 97.07%)
Specificity: 94.39% (95% Cl: 91.04%, 96.67%)
NPV: 98.96% (95% CI: 98.21%- 99.4%)
PPV: 74.79% (95% CI: 64.80%- 82.7%)
PLR: 16.81 (95% Cl: 10.43- 27.09)
NLR: 0.059 (95% Cl: 0.034- 0.103)
Predicate Device(s)
Briefcase-Triage (PE triage, K222277)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2080 Radiological computer aided triage and notification software.
(a)
Identification. Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.(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 notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm 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 effective triage (
e.g., improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(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 intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of 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 for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
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Aidoc Medical, Ltd. % John Smith Partner Hogan Lovells US LLP 555 Thirteenth Street NW Washington, District of Columbia 20004
July 12, 2024
Re: K241727
Trade/Device Name: BriefCase-Triage Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: QAS Dated: June 14, 2024 Received: June 14, 2024
Dear John Smith:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
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Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-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.
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
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Indications for Use
Submission Number (if known)
Device Name
BriefCase-Triage
Indications for Use (Describe)
Briefcase-Triage is a radiological computer- aided triage and notification software indicated for use in the analysis of CTPA images, in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspected positive cases of Pulmonary Embolism (PE) pathologies.
Briefcase-Triage uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected PE findings. Notifications include compressed preview images that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Briefcase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
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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K241727 510(k) Summary Aidoc Medical, Ltd.'s Briefcase-Triage
Submitter:
| Aidoc Medical, Ltd.
92 Yigal Alon St.
Tel-Aviv, Israel
| Phone: | +972-73-7946870 |
|---|---|
| Contact Person: | Amalia Schreier, LL.M |
| Date Prepared: | July 11, 2024 |
| Name of Device: | Briefcase-Triage |
| Classification Name: | Radiological computer-assisted triage and notification software |
| device | |
| Regulatory Class: | Class II |
| Product Code: | QAS (21 CFR 892.2080) |
| Primary Predicate Device: | Briefcase-Triage (PE triage, K222277) |
Device Description
Briefcase-Triage is a radiological computer-assisted triage and notification software device. The software is based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.
The Briefcase-Triage receives filtered DICOM Images, and processes them chronologically by running the algorithms on each series to detect suspected cases. Following the Al processing, the output of the algorithm analysis is transferred to an image review software (desktop application). When a suspected case is detected, the user receives a pop-up notification and is presented with a compressed, low-quality, grayscale image that is captioned "not for diagnostic use, for prioritization only" which is displayed as a preview function. This preview is meant for informational purposes only, does not contain any marking of the findings, and is not intended for primary diagnosis beyond notification.
Presenting the users with worklist prioritization facilitates efficient triage by prompting the user to assess the relevant original images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.
The algorithm was trained during software development on images of the pathology. As is customary in the field of machine learning, deep learning algorithm development consisted of training on
4
manually labeled ("tagged") images. In that process, critical findings were tagged in all CTs in the training data set.
Intended Use / Indications for Use
BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of CTPA images in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspected positive cases of Pulmonary Embolism (PE) pathologies.
BriefCase-Triage uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected PE findings. Notifications include compressed preview images that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of BriefCase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
Summary of Technological Characteristics
The subject Briefcase-Triage for PE and the algorithm analysis module for the primary predicate Briefcase-Triage for PE (K222277) are identical in most aspects and differ with respect to their algorithm performance, due to training the subject device on a larger data set and additional operating points have been added to the pivotal study endpoints. In addition, the SW architecture was changed to separate the image communication platform from the Briefcase-Triage SW. The subject device consists of only the algorithm analysis module which can be integrated with image communication platforms that meet the Briefcase-Triage input and output requirements.
Both the primary predicate and subject devices are radiological computer-aided triage and notification software programs. Both devices are artificial intelligence, deep-learning algorithms incorporated in software packages for use with DICOM compliant CT scanners, PACS, and radiology workstations.
Both devices are intended to aid in triage and prioritization of radiological images and utilize the same design of deep learning algorithm trained on medical images. Both devices are intended to provide the specialists with notifications and unannotated, compressed, low-quality, and grayscale preview images of suspect studies for the purpose of preemptive triage.
The subject and predicate Briefcase-Triage devices raise the same types of safety and effectiveness questions, namely, accurate triage of findings within the processed study. It is important to note that, like the predicate, the subject device neither removes cases from the standard of care reading queue nor de-prioritized cases. Both devices operate in parallel with the standard of care, which remains the default option for all cases. A table comparing the key features of the subject and the
5
| | Predicate Device
Aidoc Briefcase-Triage for PE
(K222277) | Subject Device
Aidoc Briefcase-Triage for PE |
|------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use /
Indications for
Use | BriefCase is a radiological computer
aided triage and notification software
indicated for use in the analysis of
CTPA images in adults or transitional
adolescents aged 18 and older. The
device is intended to assist hospital
networks and appropriately trained
medical specialists in workflow triage
by flagging and communication of
suspected positive findings of
Pulmonary Embolism (PE)
pathologies. | Briefcase-Triage is a radiological
computer- aided triage and notification
software indicated for use in the analysis
of CTPA images, in adults or transitional
adolescents aged 18 and older. The
device is intended to assist hospital
networks and appropriately trained
medical specialists in workflow triage by
flagging and communicating suspected
positive cases of Pulmonary Embolism
(PE) pathologies. |
| | BriefCase uses an artificial
intelligence algorithm to analyze
images and highlight cases with
detected findings on a standalone
desktop application in parallel to the
ongoing standard of care image
interpretation. The user is presented
with notifications for cases with
suspected PE findings. Notifications
include compressed preview images
that are meant for informational
purposes only and not intended for
diagnostic use beyond notification.
The device does not alter the original
medical image and is not intended to
be used as a diagnostic device. | Briefcase-Triage uses an artificial
intelligence algorithm to analyze images
and highlight cases with detected findings
in parallel to the ongoing standard of care
image interpretation. The user is
presented with notifications for cases with
suspected findings. Notifications include
compressed preview images that are
meant for informational purposes only,
and not intended for diagnostic use
beyond notification. The device does not
alter the original medical image and is not
intended to be used as a diagnostic
device. |
| | The results of BriefCase are intended
to be used in conjunction with other
patient information and based on their
professional judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for | The results of Briefcase-Triage are
intended to be used in conjunction with
other patient information and based on
their professional judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for
viewing full images per the standard of
care. |
| | Predicate Device | Subject Device |
| | Aidoc Briefcase-Triage for PE (K222277) | Aidoc Briefcase-Triage for PE |
| | viewing full images per the standard of care. | |
| User population | Hospital networks and appropriately trained medical specialists | Hospital networks and appropriately trained medical specialists |
| Anatomical region of interest | Chest | Chest |
| Data acquisition protocol | CTPA | CTPA |
| Notification-only (/notification alerts), parallel workflow tool | Yes | Yes |
| Images format | DICOM | DICOM |
| Interference with standard workflow | No. No cases are removed from desktop app or deprioritized | No. No cases are removed from desktop app or deprioritized |
| Inclusion/Exclusion criteria for clinical performance testing | Inclusion criteria CTPA protocols. Single Energy or Dual Energy exams Performed on CT scanners with 64 or greater number of detectors Scans performed on adults/transitional adults ≥ 18 years of age Slice thickness; 0.5 mm to 3.0 mm axial slices | Inclusion criteria CTPA protocols. Single Energy or Dual Energy exams Performed on CT scanners with 64 or greater number of detectors Scans performed on adults/transitional adults ≥ 18 years of age Slice thickness; 0.5 mm to 3.0 mm axial slices |
| | Predicate Device
Aidoc Briefcase-Triage for PE
(K222277) | Subject Device
Aidoc Briefcase-Triage for PE |
| | Exclusion Criteria All studies that are technically inadequate, including studies with motion artifacts, severe metal artifacts, sub-optimal bolus timing or an inadequate field of view. | Exclusion Criteria All studies that are technically inadequate, including studies with motion artifacts, severe metal artifacts, sub-optimal bolus timing or an inadequate field of view. |
| Algorithm | Artificial intelligence algorithm with database of images. | Artificial intelligence algorithm with database of images. |
| Structure | AHS module ( image acquisition); ACS module (image processing); Aidoc Desktop Application for workflow integration (Feed/Worklist (alternate names) and non-diagnostic Image Viewer). | Integrated with image routing module via image communication platform (ICP) (image acquisition). Algorithm module (image processing) Integrated with desktop application for workflow integration (feed and non-diagnostic Image Viewer). |
Table 1. Key Feature Comparison
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7
Performance Data
Pivotal Study Summary
Aidoc conducted a retrospective, blinded, multicenter study with the Briefcase-Triage software to evaluate the software's performance in identifying CTPA images containing Pulmonary Embolism (PE) in 499 cases from 6 US-based clinical sites, compared to the ground truth as determined by three senior board-certified radiologists. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm, as was used for the most recent clearance (K22277). Test pivotal study data was sequestered from algorithm development activities, and use of the data is managed by appropriate Quality Management System procedures.
Primary endpoints were sensitivity and specificity with an 80% performance goal. Secondary endpoints were Briefcase-Triage time-to-notification compared to the predicate device. Positive Predictive Value (PPV), Negative Predictive Value (NPV), Positive Likelihood Ratio (PLR), and Negative Likelihood Ratio (NLR) were also assessed.
Primary Endpoint
Sensitivity and specificity exceeded the 80% performance goal. Sensitivity was 94.39% (95% Cl: 90.41%, 97.07%) and Specificity was 94.39% (95% Cl: 91.04%, 96.67%).
8
Secondary Endpoint
In addition, the time-to-notification metric observed for the Briefcase-Triage software, when integrated with a compatible image communication platform, was compared to the equivalent metric of the predicate devices. The Briefcase-Triage time-to-notification includes the time to get the DICOM exam, de-identify it, upload it to the cloud, analyze and send a notification on a positive suspect case back to the desktop application.
The Briefcase-Triage time-to-notification was measured for all True Positive cases (i.e., identified as positive both by the reviewers as well as the Briefcase-Triage device) and is given in Table 2 below. The Table also displays the same metric reported for the predicate Briefcase-Triaqe PE.
The time-to-notification results obtained for the subject Briefcase-Triage device show comparability with the primary predicate with regard to time savings to the standard of care review. The Briefcase-Triage mean time-to-notification for the subject PE triage was 26.42 seconds (95% C1: 25.3-27.54). The time-to-notification for the predicate PE was 78 seconds (95% CI 73.6-82.3).
| Time -to-notification | Mean
Estimate
(seconds) | N | 95% Lower
CL | 95% Upper
CL | Median | IQR |
|----------------------------------------------------------------------------------|-------------------------------|-----|-----------------|-----------------|--------|-------|
| Predicate K222277
Processing Time | 78.0 | 499 | 73.6 | 82.3 | 64.5 | 53.2 |
| Briefcase-Triage +
Image
Communication
Platform
Time-To-Notification | 26.42 | 499 | 25.3 | 27.54 | 23.81 | 14.74 |
Table 2. Time-to- notification comparison for Briefcase-Triage devices (Seconds)
NPV was 98.96% (95% CI: 98.21%- 99.4%) and PPV was 74.79% (95% CI: 64.80%- 82.7%). PLR was 16.81 (95% Cl: 10.43- 27.09) and NLR was 0.059 (95% Cl: 0.034- 0.103).
Thus, the reported similar time-to-notification data demonstrates that when using the subject Briefcase-Triage for PE the clinician may have the same benefit in time saving as with the predicate Briefcase-Triage for PE.
As can be seen in Table 3 the mean age of patients whose scans were reviewed for PE was 62.1 years, with a standard deviation of 17.3 years. Gender distribution was 48% male, and 51% female (Table 4). Scanner distribution can also be found in Table 5 below.
9
Table 3. Descriptive Statistics for Age
| Mean | Std | Min | Median | Max | N | |
|---|---|---|---|---|---|---|
| Age | ||||||
| (Years) | 62.1 | 17.3 | 18 | 64 | 90 | 499 |
Table 4. Frequency Distribution of Gender *
| Ground Truth
| Results | Gender | |||||
|---|---|---|---|---|---|---|
| Female | Male | All | ||||
| N | % | N | % | N | % | |
| Positive | 100 | 20.0% | 113 | 22.6% | 213 | 42.6% |
| Negative | 154 | 30.8% | 127 | 25.4% | 281 | 56.2% |
| All | 254 | 50.8% | 240 | 48.0% | 494 | 98.8% |
- 5 cases were unknown for gender, 4 negative and 1 positive. * 1 case was excluded
Table 5. Frequency Distribution of Manufacturer
| Manufacturer | N | % |
|---|---|---|
| SIEMENS | 201 | 40.3% |
| GE | 100 | 20.0% |
| Canon | 99 | 19.8% |
| Philips | 99 | 19.8% |
| Total | 499 | 100% |
Clinical Subgroups and Confounders:
Pathologies present in negative cases: Fully negative; Heart & vascular; Chronic Lung diseases; Inflammatory; Trauma; Oncology and None of the above.
Additional Operating Points:
10
In addition to the default operating point that was selected to maximize both sensitivity and specificity, four additional operating points (AOP) were selected to maximize specificity or sensitivity while maintaining a lower bound 95% confidence interval of 80% for sensitivity and specificity respectively:
AOP1:
Sensitivity was 99.53% (95% Cl: 97.42%- 99.99%) and Specificity was 86.67% (95% Cl: 82.16%-90.39%).
AOP2:
Sensitivity was 97.66% (95% Cl: 94.63%-99.24%) and Specificity was 91.93% (95% Cl: 88.14%-94.82%.
AOP3: Sensitivity was 91.59% (95% C1: 87.03%- 94.94%) and Specificity was 96.49% (95% C1: 93.64%-98.3%).
AOP4: Sensitivity was 85.98% (95% C1: 80.6%-90.34%) and Specificity was 98.25% (95% C1: 95.95%-99.43%).
In summary, performance goals were achieved for the default and four additional operating points. Combined with the comparison results of time-to-notification metric with the predicate device, these data establish the achievement by the subject Briefcase-Triage of preemptive triage in the range of several minutes.
Conclusions
The subject Briefcase-Triage for PE and the predicate Briefcase-Triage for PE (K222277) are intended to aid in prioritization and triage of radiological images for the indications for suspected positive findings of Pulmonary Embolism (PE) pathologies. Both devices are software packages consisting of deep learning AI algorithms that process images and produce analysis results, which are displayed to the user by a prioritization alert and a compressed, low-quality, grayscale, unannotated preview image. In both devices, the labeling clearly states that the devices are not for diagnostic use and instructs the user to further evaluate and diagnose based only on the original images in the local PACS.
Both devices operate in parallel to the standard of care workflow in the sense that they do not change the original image, do not provide any marking on the output preview, do not remove images from the standard of care FIFO queue and do not de-prioritize cases, thus not disturbing standard interpretation of the images. Both devices notify the radiologist of time-sensitive critical cases within the range of several minutes, and thus contribute similarly to the standard of care workflow turnaround time reduction through preemptive triage.
The subject Briefcase-Triage device for PE is thus substantially equivalent to the primary predicate Briefcase-Triage for PE (K222277).