(52 days)
BriefCase-Triage is a radiological computer-aided triaqe 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 Central Pulmonary Embolism (Central PE).
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 Central 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.
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 manually labeled ("tagged") images. In that process, critical findings were tagged in all CTs in the training data set.
Here's a breakdown of the acceptance criteria and study details for the Aidoc BriefCase-Triage device, based on the provided FDA 510(k) summary:
1. Table of Acceptance Criteria and Reported Device Performance
The FDA 510(k) summary explicitly states the primary performance goals and the achieved results.
| Acceptance Criteria (Performance Goal) | Reported Device Performance |
|---|---|
| Sensitivity ≥ 80% | 89.2% (95% CI: 82.5%, 93.9%) |
| Specificity ≥ 80% | 94.5% (95% CI: 90.3%, 97.2%) |
Note on Secondary Endpoints: While time-to-notification, PPV, NPV, PLR, and NLR were assessed as secondary endpoints, the document does not state explicit acceptance criteria for them, but rather presents them as comparative data or additional performance metrics.
2. Sample Size and Data Provenance
- Test Set Sample Size: 328 cases from unique patients.
- Data Provenance: Retrospective, multi-center study with data from 6 US-based clinical sites. The cases collected for the pivotal dataset were distinct in time or center from the cases used to train the algorithm.
3. Number of Experts and Qualifications for Ground Truth
- Number of Experts: 3 senior board-certified radiologists.
- Qualifications of Experts: Senior board-certified radiologists. (No specific years of experience are detailed, but "senior" implies extensive experience).
4. Adjudication Method for the Test Set
- Adjudication Method: Majority voting among the three senior board-certified radiologists was used to establish the ground truth.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Was an MRMC study done? No, a comparative effectiveness study involving human readers with and without AI assistance (MRMC) was not performed as the primary evaluation for this device. The study compared the algorithm's performance to ground truth, and the device is intended for workflow triage/notification, not as a diagnostic tool replacing human interpretation. The time-to-notification comparison was done between the device and a predicate device (PETN), not human readers.
6. Standalone (Algorithm Only) Performance Study
- Was a standalone study done? Yes. The pivotal study directly evaluated the BriefCase-Triage software's performance (sensitivity and specificity) in identifying Central PE by comparing its output against the established ground truth. This is a standalone performance evaluation.
7. Type of Ground Truth Used
- Type of Ground Truth: Expert consensus (majority voting by three senior board-certified radiologists).
8. Sample Size for the Training Set
- The document states that the algorithm was "trained during software development on images of the pathology." However, the exact sample size for the training set is not specified in the provided text.
9. How Ground Truth for the Training Set Was Established
- Method: "Critical findings were tagged in all CTs in the training data set." This implies manual labeling/tagging of findings by experts. The specific number or qualifications of these "tagging" experts are not detailed, but it's consistent with a machine learning development process.
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Aidoc Medical, Ltd. % John Smith Partner Hogan Lovells U.S. LLP 555 Thirteenth Street NW WASHINGTON, DISTRICT OF COLUMBIA 20004
October 30, 2023
Re: K232751 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: September 8, 2023 Received: September 8, 2023
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.
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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).
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 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-regulatory
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assistance/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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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
See PRA Statement below
510(k) Number (if known)
K232751
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 Central Pulmonary Embolism (Central PE).
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 Central 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 trage/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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510(k) Summary Aidoc Medical, Ltd.'s BriefCase-Triage K232751
Submitter:
| Aidoc Medical, Ltd.3 Aminadav St.Tel-Aviv, IsraelPhone: | +972-73-7946870 |
|---|---|
| Contact Person: | Amalia Schreier, LL.M. |
| Date Prepared: | October 16, 2023 |
| Name of Device: | BriefCase-Triage |
| Classification Name: | Radiological computer-assisted triage and notification softwaredevice |
| Requlatory Class: | Class II |
| Product Code: | QAS (21 C.F.R. 892.2080) |
| Primary Predicate Device: | Rapid PE Triage and Notification (PETN) (K220499) |
| Reference Device: | BriefCase of Pulmonary Embolism (PE) (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 manually
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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 triaqe 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 Central Pulmonary Embolism (Central PE).
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 Central 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.
Comparison of Technological Characteristics
The subject BriefCase-Triage of Central Pulmonary Embolism (Central PE) is substantially similar to primary predicate Rapid PE Triage and Notification (PETN) (K220499) and is similar to reference device BriefCase of Pulmonary Embolism (PE) (K222277), as explained below.
The subject, predicate and the reference devices are radiological computer-aided triage and notification software programs. All devices are artificial intelligence, deep-learning algorithms incorporated in software packages for use with DICOM compliant CT scanners, PACS, and radiology workstations. The subject and the reference devices differ in the fact 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.
All 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. All 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, predicate and reference 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 and reference devices, the subject device neither removes cases from the standard of care reading queue nor de-prioritizes cases. All 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 primary predicate devices is provided below.
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aidoc
Table 1. Key Feature Comparison
| Predicate DeviceRapid PE Triage andNotification (PETN)(K220499) | Reference DeviceBriefCase-Triage forPE triage(K222277) | Subject DeviceAidoc BriefCase-Triage of CentralPulmonaryEmbolism (CentralPE) | |
|---|---|---|---|
| Intended Use /Indications for Use | Rapid PE Triage andNotification (PETN) isa radiologicalcomputer aided triageand notificationsoftware indicated foruse in the analysis ofCTPA images. Thedevice is intended toassist hospitalnetworks and trainedclinicians in workflowtriage by flagging andcommunication ofsuspected positivefindings of centralpulmonary embolism(PE) pathology inadults. The software isonly intended to beused on single-energyexams.Rapid PETN uses anartificial intelligencealgorithm to analyzeimages and highlightcases with detectedfindings on a server orstandalone desktopapplication in parallelto the ongoingstandard of care image | BriefCase is aradiological computeraided triage andnotification softwareindicated for use in theanalysis of CTPAimages in adults ortransitionaladolescents aged 18and older. The deviceis intended toassist hospitalnetworks andappropriately trainedmedical specialists inworkflow triage byflagging andcommunication ofsuspected positivefindings of PulmonaryEmbolism (PE)pathologies.BriefCase uses anartificial intelligencealgorithm to analyzeimages and highlightcases with detectedfindings on astandalone desktopapplication in parallelto the ongoingstandard of care | BriefCase-Triage is aradiological computer-aided triage andnotification softwareindicated for use in theanalysis of CTPAimages in adults ortransitionaladolescents aged 18and older. The deviceis intended to assisthospital networks andappropriately trainedmedical specialists inworkflow triage byflagging andcommunicatingsuspected positivecases of CentralPulmonary Embolism(Central PE).BriefCase-Triage usesan artificial intelligencealgorithm to analyzeimages and highlightcases with detectedfindings in parallel tothe ongoing standardof care imageinterpretation. Theuser is presented withnotifications for caseswith suspected CentralPE findings. |
| Predicate DeviceRapid PE Triage andNotification (PETN)(K220499) | Reference DeviceBriefCase-Triage forPE triage(K222277) | Subject DeviceAidoc BriefCase-Triage of CentralPulmonaryEmbolism (CentralPE) | |
| user is presented withnotifications for caseswith suspectedfindings. Notificationsinclude compressedpreview images thatare meant forinformational purposesonly and not intendedfor diagnostic usebeyond notification.The device does notalter the originalmedical image and isnot intended to beused as a diagnosticdevice.The results of RapidPETN are intended tobe used in conjunctionwith other patientinformation and basedon their professionaljudgment, to assistwithtriage/prioritization ofmedical images.Notified clinicians areresponsible for viewingfull images per thestandard of care.Rapid PETN isvalidated for use onGE, Siemens andToshiba scanners. | The user is presentedwith notification forcases with suspectedfindings. Notificationsinclude compressedpreview images thataremeant for informationalpurposes only andnot intended fordiagnostic usebeyond notification.The device does notalter the originalmedical image and isnot intended to beused as a diagnosticdevice.The results ofBriefCase areintended to be used inconjunction with otherpatient information andbased on theirprofessional judgment,to assist withtriage/prioritization ofmedical images.Notified clinicians areresponsible for viewingfull images per thestandard of care. | compressed previewimages that are meantfor informationalpurposes only and notintended for diagnosticuse beyondnotification.The device does not alterthe original medicalimage and is notintended to be used asa diagnostic device.The results ofBriefCase-Triage areintended to be used inconjunction with otherpatient information andbased on theirprofessional judgment,to assist withtriage/prioritization ofmedical images.Notified clinicians areresponsible for viewingfull images per thestandard of care. | |
| Predicate DeviceRapid PE Triage andNotification (PETN)(K220499) | Reference DeviceBriefCase-Triage forPE triage(K222277) | Subject DeviceAidoc BriefCase-Triage of CentralPulmonaryEmbolism (CentralPE) | |
| User population | Hospital networks andtrained clinicians | Hospital networks andappropriately trainedmedical specialists | Hospital networks andappropriately trainedmedical specialists |
| Anatomical region ofinterest | Chest | Chest | Chest |
| Dataacquisitionprotocol | CTPA | CTPA | CTPA |
| Notification-only,parallel workflow tool | Yes | Yes | Yes |
| Interferencewithstandard workflow | No | No | No |
| Algorithm | Artificial intelligencealgorithm withdatabase of images. | Artificial intelligencealgorithm withdatabase of images. | Artificial intelligencealgorithm withdatabase of images. |
| Structure | - The RapidPETN moduleoperates withinthe integratedRapid Platformand uses thebasic servicessupplied by theRapid PlatformincludingDICOMprocessing, jobmanagement,imagingmoduleexecution andimagingoutput. | - AHS module(imageacquisition);- ACS module(imageprocessing);- Aidoc DesktopApplication forworkflowintegration(Feed/Worklist(alternatenames) andnon-diagnosticImageViewer). | - Integrated withimage routingmodule viaimagecommunicationplatform(ICP) (imageacquisition).- Algorithmmodule (imageprocessing)- Integrated withdesktopapplication forworkflowintegration(feed and non-diagnostic |
| Predicate DeviceRapid PE Triage andNotification (PETN)(K220499) | Reference DeviceBriefCase-Triage forPE triage(K222277) | Subject DeviceAidoc BriefCase-Triage of CentralPulmonaryEmbolism (CentralPE) | |
| ImageViewer). |
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Image /page/8/Picture/0 description: The image shows the logo for "aidoc.". The logo is in a sans-serif font and is a dark blue color, except for a small orange dot at the end. The logo is simple and modern.
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Image /page/9/Picture/0 description: The image shows the logo for Aidoc. The logo is in blue and consists of the word "aidoc" in a sans-serif font. There is a small orange circle to the right of the "c" in "aidoc". The logo is simple and modern.
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 Central Pulmonary Embolism (Central PE) in 328 cases from unique patients, from 6 US-based clinical sites. The study compared the software's performance to the ground truth, as determined by three senior boardcertified radiologists, using majority voting. The cases collected for the pivotal dataset were all distinct in time or center from the cases used to train the algorithm.
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 89.2% (95% Cl: 82.5%, 93.9%) and specificity was 94.5% (95% CI: 90.3%, 97.2%).
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 Rapid PE Triage and Notification (PETN).
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-
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Triage mean time-to-notification for the subject Central PE triage was 29.3 seconds (95% Cl: 26.8-31.9). The time-to-notification for the predicate Rapid PE Triage and Notification (PETN) was 158.4 seconds (95% Cl: 140.4-288).
| Time -to-notification | N | MeanEstimate | 95% LowerCL | 95% UpperCL | Median | IQR |
|---|---|---|---|---|---|---|
| PredicateRapid PETriage andNotification(PETN)ProcessingTime | 306 | 158.4 | 140.4 | 288 | N/A | N/A |
| BriefCase-Triage +ImageCommunication PlatformTime-To-Notification | 115 | 29.3 | 26.8 | 31.9 | 28.0 | 20.2 |
Table 2. Time-to- Notification Comparison for BriefCase-Triage and Predicate Devices (Seconds)
NPV was 99.2% (95% Cl: 98.7%- 99.5%) and PPV was 52.9% (95% Cl: 38.6%- 66.6%).
PLR was 16.1 (95% Cl: 9.1- 28.7 and NLR was 0.1 (95% Cl: 0.1- 0.2).
Thus, the reported similar time-to-notification data demonstrates that when using the subject BriefCase-Triage for Central PE the clinician may have the same benefit in time saving as with the predicate Rapid PE Triage and Notification (PETN).
As can be seen in Table 3 the mean age of patients whose scans were reviewed for Central PE was 60.3 years, with a standard deviation of 17.4 years. Gender distribution was 44.5% male, and 55.5% female (Table 4). Scanner distribution can also be found in Table 5 below.
| Mean | Std | Min | Median | Max | N | |
|---|---|---|---|---|---|---|
| Age (Years) | 60.3 | 17.4 | 19 | 63 | 90 | 328 |
Table 3. Descriptive Statistics for Age
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| GroundTruthResults | Gender | |||||
|---|---|---|---|---|---|---|
| Male | Female | All | ||||
| N | % | N | % | N | % | |
| Positive | 65 | 19.8% | 64 | 19.5% | 129 | 39.3% |
| Negative | 117 | 35.7% | 82 | 25.0% | 199 | 60.6% |
| All | 182 | 55.5% | 146 | 44.5% | 328 | 100.0% |
Table 4. Frequency Distribution of Gender
Table 5. Frequency Distribution of Manufacturer
| Manufacturer | N | % |
|---|---|---|
| Philips | 99 | 30.2% |
| GE MEDICAL SYSTEMS | 90 | 27.4% |
| SIEMENS | 78 | 23.8% |
| TOSHIBA | 61 | 18.6% |
| Total | 328 | 100% |
Clinical Subgroups and Confounders:
Pathologies present in negative cases: Chronic lung diseases; Heart and vascular; Inflammatory; Oncology; Trauma and None of the above.
Additional Operating Point:
In addition to the default operating point one additional operating point was selected to maximize sensitivity, while maintaining a lower bound 95% confidence interval of 80% for specificity and sensitivity.
AOP1: Sensitivity was 96.9% (95% C1: 92.3%-99.2%) and specificity was 85.9% (95% C1: 80.3%-90.4%).
In summary, performance goals were achieved for the default and one additional operating point. 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 of several minutes.
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Conclusions
The subject BriefCase-Triage of Central Pulmonary Embolism (Central PE), the predicate Rapid PE Triage and Notification (PETN) and the reference BriefCase for PE triage devices are intended to aid in prioritization and triage of radiological images for the indications for suspected positive findings of Pulmonary Embolism (the subject and predicate device specifically aid in Central PE). All 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, gravscale, unannotated preview image. In all 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.
All 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. All 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 of Central Pulmonary Embolism (Central PE) triage is thus substantially equivalent to the predicate Rapid PE Triage and Notification (PETN) and the reference BriefCase for PE triage.
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§ 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.