(84 days)
Aidoc Briefcase (K190072)
Not Found
Yes
The device description explicitly states, "The PETN module is an AI/ML module." and the intended use section mentions it uses an "artificial intelligence algorithm".
No
The device is a computer-aided triage and notification software for medical images, intended to assist clinicians in workflow triage by flagging suspected positive findings. It does not directly treat or alleviate a disease or condition.
No
The device explicitly states: "The device does not alter the original medical image and is not intended to be used as a diagnostic device." Its purpose is workflow triage, flagging, and communicating suspected findings.
Yes
The device is described as "radiological computer aided triage and notification software" and a "software device." While it processes images from hardware (CTPA scanners), the device itself is solely the software component that analyzes and notifies. There is no mention of accompanying hardware being part of the device submission.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are tests performed on samples taken from the human body (like blood, urine, or tissue) to detect diseases, conditions, or infections.
- Device Function: The Rapid PE Triage and Notification (PETN) device analyzes medical images (CTPA scans) to identify potential findings within the body. It does not analyze samples taken from the body.
- Intended Use: The intended use is to assist in workflow triage and notification based on image analysis, not to provide a diagnosis based on laboratory testing of biological samples.
Therefore, this device falls under the category of medical imaging software or computer-aided detection/triage software, not In Vitro Diagnostics.
No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The "Control Plan Authorized (PCCP)" section is explicitly marked as "Not Found."
Intended Use / Indications for Use
Rapid PE Triage and Notification (PETN) is a radiological computer aided triage and notification software indicated for use in the analysis of CTPA images. The device is intended to assist hospital networks and trained clinicians in workflow triage by flagging and communication of suspected positive findings of central pulmonary embolism (PE) pathology in adults. The software is only intended to be used on single-energy exams.
Rapid PETN uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a server or standalone desktop application 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 Rapid PETN 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. Rapid PETN is validated for use on GE, Siemens and Toshiba scanners.
Product codes (comma separated list FDA assigned to the subject device)
QAS
Device Description
Rapid PETN is a radiological computer-assisted triage and notification software device. The Rapid PETN module is a contrast enhanced CTPA processing module which operates within the integrated Rapid Platform to provide triage and notification of suspected Central Pulmonary Emboli (PE). The PETN module is an AI/ML module. The output of the module is a priority notification to clinicians indicating the suspicion of central PE based on positive findings. The Rapid PETN module uses the basic services supplied by the Rapid Platform including DICOM processing, job management, imaging module execution and imaging output including the notification and compressed image.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CTPA images
Anatomical Site
Central pulmonary embolism (PE) pathology
Indicated Patient Age Range
Adults
Intended User / Care Setting
hospital networks and trained clinicians
Description of the training set, sample size, data source, and annotation protocol
Algorithm development, including development validation, was performed using 600 (Pos:300, Neg:300) CTPA cases from multiple sites. The data was split into 480 (Pos:240, Neg:240) training cases and 120 (Pos:60, Neg:60) development validation cases.
Description of the test set, sample size, data source, and annotation protocol
Final performance validation included 306 CTPA cases with ground truth established by 3 experts using a 2:3 confirmation. The cases were split Male:47%, Female 53% with an age range of 22-95 years. The samples were mixed from GE, Philips, Toshiba and Siemens scanners.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Final device validation included standalone performance validation. This performance validation testing demonstrated the Rapid PETN device provides accurate representation of key processing parameters under a range of clinically relevant perturbations associated with the intended use of the software. Software performance, validation and verification testing demonstrated that the Rapid PETN Module met all design requirements and specifications.
Final performance validation included 306 CTPA cases with ground truth established by 3 experts using a 2:3 confirmation. The primary endpoint passed with Sensitivity = 0.96 (0.92.0.98) and Specificity = 0.89 (0.83.0.93). The cases were split Male:47%, Female 53% with an age range of 22-95 years. The samples were mixed from GE, Philips, Toshiba and Siemens scanners. The secondary endpoint was passed at 2.64 minutes (2.34-4.80 min) processing time, with negligible notification time using wireless and cellular communications.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Sensitivity = 0.96 (0.92.0.98) and Specificity = 0.89 (0.83.0.93).
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Aidoc Briefcase (K190072)
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
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.
0
Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: a symbol on the left and the FDA acronym with the full name of the agency on the right. The symbol on the left is a stylized representation of a human figure, while the FDA acronym is in a blue square. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
iSchemaView Inc. % Mr. James Rosa SVP Regulatory and Quality 1120 Washington Ave., Ste 200 GOLDEN CO 80401
May 17, 2022
Re: K220499
Trade/Device Name: Rapid PE Triage and Notification (PETN) Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: April 13, 2022 Received: April 14, 2022
Dear Mr. Rosa:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmp/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 requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
1
https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about 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, 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 Ouality Center for Devices and Radiological Health
Enclosure
2
Indications for Use
510(k) Number (if known)
K220499
Device Name Rapid PE Triage and Notification (PETN)
Indications for Use (Describe)
Rapid PE Triage and Notification (PETN) is a radiological computer aided triage and notification software indicated for use in the analysis of CTPA images. The device is intended to assist hospital networks and trained clinicians in workflow triage by flagging and communication of suspected positive findings of central pulmonary embolism (PE) pathology in adults. The software is only intended to be used on single-energy exams.
Rapid PETN uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a server or standalone desktop application 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 Rapid PETN are intended to be used in conjunction with other patient information and based on ther professional judgment, to assist with trage/proritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care. Rapid PETN is validated for use on GE, Siemens and Toshiba scanners.
| 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
510(k) Summary
iSchemaView, Inc.'s Rapid PE Triage and Notification (PETN)
This document contains the 510(k) summary for the iSchemaView Rapid PETN. The content of this summary is based on the requirements of 21 CFR Section 807.92(c).
Applicant Name and Address:
| Name: | iSchemaView, Inc. |
|---|---|
| Address: | 1120 Washington St., Suite 200 |
| Golden, CO 80401 | |
| Official Contact: | Jim Rosa |
| Phone: (303) 704-3374 | |
| Email: rosa@ischemaview.com |
February 12, 2022 Summary Preparation Date:
Device Name and Classification:
| Trade Name: | Rapid PE Triage and Notification (PETN) |
|---|---|
| Common Name: | PACS – Picture Archiving Communications |
| System | |
| Classification: | II |
| Product Code: | Primary: QAS |
| Regulation No: | 21 C.F.R. §892.2080 |
| Classification Panel: | Radiology Devices |
Predicate Devices:
The iSchemaView Rapid PETN is claimed to be substantially equivalent to the following legally marketed predicate devices:
Aidoc Briefcase (K190072)
Device Description:
Rapid PETN is a radiological computer-assisted triage and notification software device. The Rapid PETN module is a contrast enhanced CTPA processing module which operates within the integrated Rapid Platform to provide triage and notification of suspected Central Pulmonary Emboli (PE). The PETN module is an AI/ML module. The output of the module is a priority notification to clinicians indicating the suspicion of central PE based on positive findings. The Rapid PETN module uses the basic services supplied by the Rapid Platform including DICOM processing, job management, imaging module execution and imaging output including the notification and compressed image.
4
Indications for Use:
Rapid PE Triage and Notification (PETN) is a radiological computer aided triage and notification software indicated for use in the analysis of CTPA images. The device is intended to assist hospital networks and trained clinicians in workflow triage by flagging and communication of suspected positive findings of central pulmonary embolism (PE) pathology in adults. The software is only intended to be used on single-energy exams.
Rapid PETN uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a server or standalone desktop application 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 Rapid PETN 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. Rapid PETN is validated for use on GE, Siemens and Toshiba scanners.
Technological Characteristics and Substantial Equivalence:
Rapid PETN does not raise new questions of safety or effectiveness compared to the previously cleared Briefcase (K190072). Both devices are radiological computer-aided triage and notification software applications for use with CTPA input. There are minor differences in intended use and technical characteristics with the predicate device; however, with the minor change excluding the ICH claims, the clinical use for Rapid PETN is the same as the CTPA indication for the predicate with no additional risk. Thus, the Rapid PETN software is substantially equivalent.
The following table summarizes and compares data on the Briefcase (K190072) to the Rapid PETN that is the subject of this Traditional 510(k) submission.
| Parameter | K190072 - Predicate Device | Rapid PETN – Subject Device |
|---|---|---|
| Product Code | QAS | QAS |
| Regulation | 21 CFR §892.2080 | 21 CFR §892.2080 |
| Intended Use/ | ||
| Indications for | ||
| Use | BriefCase is a radiological computer | |
| aided triage and notification software | ||
| indicated for use in the analysis of | ||
| non-enhanced head CT and CTPA | ||
| images. The device is intended to | ||
| assist hospital networks and trained | ||
| radiologists in workflow triage by | ||
| flagging and communication of | ||
| suspected positive findings of | ||
| Intracranial Hemorrhage (ICH) and | ||
| Pulmonary Embolism (PE) | ||
| pathologies. For the PE pathology, | ||
| the software is only intended to be | ||
| used on single-energy exams. | Rapid PE Triage and Notification (PETN) | |
| is a radiological computer aided triage and | ||
| notification software indicated for use in | ||
| the analysis of CTPA images. The device | ||
| is intended to assist hospital networks and | ||
| trained clinicians in workflow triage by | ||
| flagging and communication of suspected | ||
| positive findings of central pulmonary | ||
| embolism (PE) pathology in adults. The | ||
| software is only intended to be used on | ||
| single-energy exams. |
Rapid PETN uses an artificial intelligence
algorithm to analyze images and highlight
cases with detected findings on a server or |
| Parameter | K190072 - Predicate Device | Rapid PETN – Subject Device |
| | 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 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 viewing full images
per the standard of care. | standalone desktop application 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 Rapid PETN 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. Rapid PETN is validated for use on
GE, Siemens and Toshiba scanners. |
| User | Radiologist | Radiologist, Clinician |
| Basic PACS
Functions | Software package which interfaces
to a PACS or allows viewing within
the application | Same |
| Computer Platform | PC | Server or Workstation |
| Software | AI/ML | AI/ML |
| DICOM Compliance | Yes, using CT and CTPA | Yes, using CTPA |
| Segmentation | No, Device does not mark,
annotate, or direct users' attention
to a specific location in the original
image | No, Device does not mark, annotate, or
direct users' attention to a specific location
in the original image |
| Preview Images | Presentation of a small,
compressed, black and white
preview image that is labeled "Not
for diagnostic use"; The device
operates in parallel with the
standard of care, which remains
the default option for all cases. | Presentation of a small, compressed, black
and white preview image that is labeled "Not
for diagnostic use"; The device operates in
parallel with the standard of care, which
remains the default option for all cases. |
| Alteration of
original image | No | No |
| Removal of cases from
workflow queue | No | No |
5
6
AI/ML Module Development:
Algorithm development, including development validation, was performed using 600 (Pos:300, Neg:300) CTPA cases from multiple sites. The data was split into 480 (Pos:240, Neg:240) training cases and 120 (Pos:60, Neg:60) development validation cases. The optimal design performance for the final solution showed a Sensitivity = 0.98 and Specificity = 0.97. The development data included the following distributions:
| Table 1: Age Distribution for Development & Training | ||||
|---|---|---|---|---|
| PE status | Mean age | Median age | Min age | Max age |
| Positive (N=300) | 63 | 64 | 22 | 93 |
| Negative (N=300) | 51 | 51 | 17 | 89 |
| Table 2: Gender Distribution for Development & Training | |||
|---|---|---|---|
| PE status | Female | Male | Unknown |
| Positive (N=300) | 52% | 47% | 70 |
8
| Age | Measure | N | Estimate | Lower 95%
CI | Upper 95%
CI |
|-----|-------------|----|----------|-----------------|-----------------|
| | Specificity | 66 | 0.924 | 0.835 | 0.967 |
| Mfr | Measure | N | Estimate | Lower 95% CI | Upper 95% CI |
|---|---|---|---|---|---|
| GE | Sensitivity | 41 | 0.976 | 0.874 | 0.996 |
| GE | Specificity | 51 | 0.882 | 0.766 | 0.945 |
| TOSHIBA | Sensitivity | 21 | 0.952 | 0.773 | 0.992 |
| TOSHIBA | Specificity | 58 | 0.966 | 0.883 | 0.990 |
| SIEMENS | Sensitivity | 16 | 0.938 | 0.717 | 0.989 |
| SIEMENS | Specificity | 43 | 0.860 | 0.727 | 0.934 |
Table 3: Scanner Brand
Table 4: Slice Thickness
| Slice Thickness | Measure | N | Estimate | Lower 95%
CI | Upper 95%
CI |
|-----------------|-------------|-----|----------|-----------------|-----------------|
|