(18 days)
Yes
The document explicitly states that the device "uses an artificial intelligence algorithm to analyze images" and describes the training process as "customary in the field of machine learning, deep learning algorithm development".
No
The device is a radiological computer-aided triage and notification software intended to assist in workflow by flagging and communicating suspect cases, not to directly treat or cure a disease.
No
Explanation: 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."
Yes
The device description explicitly states "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." It processes images and provides notifications through software, without mentioning any dedicated hardware components included with the device itself.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze biological samples: In Vitro Diagnostics are designed to examine specimens taken from the human body, such as blood, urine, tissue, etc., to provide information about a person's health.
- This device analyzes medical images: BriefCase-Triage analyzes contrast-enhanced images (radiological data) of the lungs. It does not interact with or analyze biological samples.
- The intended use is workflow triage: The primary purpose of this device is to assist in prioritizing radiological images for review by medical specialists, not to perform a diagnostic test on a biological sample.
Therefore, while it is a medical device that uses AI and image processing, it falls under the category of radiological computer-aided triage software, not an In Vitro Diagnostic.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of contrast-enhanced images that include the lungs in adults or transitional adolescents age 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspect cases of incidental Pulmonary Embolism (iPE) 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 suspect cases. 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 AI 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 alqorithm 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.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
contrast-enhanced images that include the lungs
Anatomical Site
Lungs
Indicated Patient Age Range
adults or transitional adolescents age 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 alqorithm 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 contrast-enhanced images that include the lungs containing Incidental Pulmonary Embolism (iPE) in 498 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. 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: 498 cases
AUC: Not Found
MRMC: Not Found
Standalone Performance: Not Found
Key Results: Primary endpoints were sensitivity and specificity with an 80% performance goal. Sensitivity was 91.7% (95% Cl: 87.5%, 94.9%) and Specificity was 91.4% (95% CI: 87.3%, 94.6%). Secondary endpoints included time-to-notification, with the Briefcase-Triage mean time-to-notification being 40.2 seconds (95% Cl: 36.9-43.5), compared to the predicate's 282 seconds (95% CI: 264-306). NPV was 99.8% (95% Cl: 99.6%- 99.8%) and PPV was 22.2% (95% Cl: 16.1%-29.9%). PLR was 10.7 (95% Cl: 7.2-16.0) and NLR was 0.09 (95% Cl: 0.06-0.14).
Key Metrics
Sensitivity: 91.7% (95% Cl: 87.5%, 94.9%)
Specificity: 91.4% (95% CI: 87.3%, 94.6%)
NPV: 99.8% (95% Cl: 99.6%- 99.8%)
PPV: 22.2% (95% Cl: 16.1%-29.9%)
PLR: 10.7 (95% Cl: 7.2-16.0)
NLR: 0.09 (95% Cl: 0.06-0.14)
Predicate Device(s)
Briefcase-Triage for iPE (K213886)
Reference Device(s)
BriefCase-Triage for RibFx (K243548), EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM (K240291)
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
February 14, 2025
Re: K250248
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: January 27, 2025 Received: January 27, 2025
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 (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's
1
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 https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-
combination-products); 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 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,
Jessica Lamb
Jessica Lamb Assistant Director DHT8B: Division of Radiologic Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K250248
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 contrast-enhanced images that include the lungs in adults or transitional adolescents age 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspect cases of incidental Pulmonary Embolism (iPE) 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 suspect cases. 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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3
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510(k) Summary
Aidoc Medical, Ltd.'s BriefCase-Triage (K250248)
| Submitter: | Aidoc Medical, Ltd.
3 Aminadav St.
Tel-Aviv, Israel |
|----------------------|------------------------------------------------------------------------|
| Phone: | +972-73-7946870 |
| Contact Person: | Amalia Schreier, LL.M |
| Date Prepared: | February 13, 2025 |
| Name of Device: | Briefcase-Triage |
| Classification Name: | Radiological computer-assisted triage and notification software device |
| Regulatory Class: | Class II |
| Product Code: | QAS (21 C.F.R. 892.2080) |
| Predicate Device: | Briefcase-Triage for iPE (K213886) |
| Reference Devices: | BriefCase-Triage for RibFx (K243548) |
| | EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME ASSESSMENT SYSTEM (K240291) |
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 AI 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.
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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 alqorithm 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.
Intended Use / Indications for Use
BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of contrast-enhanced images that include the lungs in adults or transitional adolescents age 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspect cases of incidental Pulmonary Embolism (iPE) 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 suspect cases. 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 iPE and the algorithm analysis module for the predicate BriefCase-Triage for iPE (K213886) are identical in most aspects and differ mostly with respect to their algorithm performance. 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
5
default option for all cases.
A table comparing the key features of the subject and the primary predicate devices is provided below.
| Subject Device | Predicate Device | |
|---|---|---|
| Aidoc Briefcase-Triage for iPE | Aidoc Briefcase-Triage for iPE (K213886) | |
| Intended Use / Indications for Use | BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of contrast-enhanced images that include the lungs in adults or transitional adolescents age 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspect cases of incidental Pulmonary Embolism (iPE) 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 suspect cases. 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. | BriefCase is a radiological computer aided triage and notification software indicated for use in the analysis of contrast-enhanced chest CTs (not dedicated CTPA protocol) in adults or transitional adolescents age 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspect cases of incidental Pulmonary Embolism (IPE) pathologies. The device is intended to be used on single-energy exams only.
BriefCase uses an artificial intelligence algorithm to analyze images and flag suspect cases on a standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for suspect cases. 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 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 | Lungs | Chest |
| | Subject Device | Predicate Device |
| | Aidoc Briefcase-Triage for iPE | Aidoc Briefcase-Triage for iPE (K213886) |
| Data acquisition protocol | Contrast-enhanced images that include the lungs | Contrast enhanced chest CTs (not dedicated CTPA protocol) |
| 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
● Contrast-enhanced images that include the lungs
● Single and dual energy exams
● Scans performed on adults/ transitional adolescents ≥ 18 years of age.
● Slice thickness; 0.5 - 5.0 mm axial.
Exclusion Criteria
● All studies that have an inadequate field of view. | Inclusion Criteria:
● Contrast-enhanced chest CTs (not dedicated CTPA protocol
● Single energy exams
● Scans performed with a 64-slice or greater number of detectors
● Scans performed on adults/transitional adults ≥ 18 years of age
● Slice thickness; 0.5 - 3.0 mm axial
Exclusion Criteria
● All studies that are technically inadequate, including studies with motion artifacts, severe metal artifacts, or inadequate field of view |
| Additional Operating Points | 4 Additional Operating Points | N/A |
| Algorithm | Artificial intelligence algorithm with database of images. | Artificial intelligence algorithm with database of images. |
| Structure | - 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) | - AHS module ( image acquisition);
- ACS module (image processing);
- Aidoc Desktop Application for workflow integration (Feed/Worklist (alternate names) and non-diagnostic Image Viewer). |
Table 1. Key Feature Comparison
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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 contrast-enhanced images that include the lungs containing Incidental Pulmonary Embolism (iPE) in 498 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. 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 91.7% (95% Cl: 87.5%, 94.9%) and Specificity was 91.4% (95% CI: 87.3%, 94.6%).
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-Triage iPE.
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 iPE triage was 40.2 seconds (95% Cl: 36.9-43.5). The time-to-notification for the predicate iPE was 282 seconds (95% CI: 264-306).
| Time -to-notification | Mean
Estimate
(seconds) | N | 95% Lower
CL | 95% Upper
CL | Median |
|-----------------------------------------------------------------------------|-------------------------------|-----|-----------------|-----------------|--------|
| Predicate K213886 Processing
Time | 282.63 | 264 | 264 | 306 | 300 |
| Briefcase-Triage + Image
Communication Platform Time-
To-Notification | 40.2 | 243 | 36.9 | 43.5 | 37.5 |
Table 2. Time-to- notification comparison for Briefcase-Triage devices (Seconds)
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Thus, the reported similar time-to-notification data demonstrates that when using the subject Briefcase-Triage for iPE the clinician may have the same benefit in time saving as with the predicate Briefcase-Triage for iPE.
NPV was 99.8% (95% Cl: 99.6%- 99.8%) and PPV was 22.2% (95% Cl: 16.1%-29.9%).
PLR was 10.7 (95% Cl: 7.2-16.0) and NLR was 0.09 (95% Cl: 0.06-0.14).
As can be seen in Table 3 the mean age of patients whose scans were reviewed for iPE was 61.7 years, with a standard deviation of 17.2 years. Gender distribution was 48.5% male, and 51.5% female (Table 4). Scanner distribution can also be found in Table 5 below.
Table 3. Descriptive Statistics for Age
| Mean | Std | Min | Median | Max | N | |
|---|---|---|---|---|---|---|
| Age | ||||||
| (Years) | 61.7 | 17.2 | 18 | 63 | 90 | 498 |
Table 4. Frequency Distribution of Gender *
| Ground
Truth
| Results | Gender | All | ||||
|---|---|---|---|---|---|---|
| N | % | N | % | N | % | |
| Positive | 113 | 23 | 126 | 25.7 | 239 | 48.7 |
| Negative | 140 | 28.5 | 112 | 22.8 | 252 | 51.3 |
| All | 253 | 51.5 | 238 | 48.5 | 491 | 100 |
- 7 cases were unknown for gender, 5 negative and 2 positive.
Table 5. Frequency Distribution of Manufacturer
| Manufacturer | N | % |
|---|---|---|
| GE MEDICAL SYSTEMS | 139 | 27.9% |
| Philips | 97 | 19.5% |
| SIEMENS | 164 | 32.9% |
| TOSHIBA | 98 | 19.7% |
| Total | 498 | 100% |
Clinical Subgroups and Confounders:
Pathologies present in negative cases: Inflammatory; Oncology; Trauma; Heart & vascular; Chronic diseases and None of the above.
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Additional Operating Points:
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 while maintaining a lower bound 95% confidence interval of 80% for sensitivity and spectively:
| Operating Points | Sensitivity % (95% CI) | Specificity % (95% CI) |
|---|---|---|
| AOP1 | 93.4% (95% CI: 89.4%-96.2%) | 89.9% (95% CI: 85.5%-93.3%) |
| AOP2 | 90.9% (95% CI: 90.5%-94.2%) | 92.6% (95% CI: 88.7%-95.5%) |
| AOP3 | 90.5% (95% CI: 86.0%-93.8%) | 94.9% (95% CI: 91.5%-97.3%) |
| AOP4 | 87.1% (95% CI: 82.2%-91.1%) | 96.1% (95% CI: 93.0%-98.1%) |
Table 6. Additional Operating Points
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 iPE and the predicate Briefcase-Triage for iPE (K213886) are intended to aid in prioritization and triage of radiological images for the indications for suspected positive findings of incidental pulmonary embolism pathologies. Both devices are software packages consisting of deep learning Al 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 technological characteristics of both devices are identical with the exception of additional operating points and minor changes in inclusion and exclusion criteria. These differences do not raise new questions of safety and effectiveness. The subject Briefcase-Triage device for iPE is thus substantially equivalent to the primary predicate Briefcase-Triage for iPE (K213886).