IQ-UIP

• K Number: K242467
• Device Name: IQ-UIP
• Manufacturer: Imbio, Inc.
• Date Cleared: 2024-12-19 ( 121 days)
• Product Code: QWO
• Regulation Number: 892.2085

Intended Use

Imbio IQ-UIP is a computer-aided software indicated for use in passively notifying specialists associated with interstitial lung disease (ILD) centers of radiological findings suggestive of radiological usual interstitial pneumonia (UIP) in non-contrast, chest CT scans of adults. Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of Imbio IQ-UIP are used to notify specialists at an ILD center of radiological findings that may be consistent with UIP. These specialists are qualified clinicians experienced in evaluating chest CTs for ILD. Input images originate from within the same hospital network associated with the ILD center. The results of Imbio IQ-UIP are intended to be used in conjunction with additional patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Device Description

Imbio IQ-UIP is a computer-aided software indicated for use in notifying specialists associated with Interstitial Lung Disease (ILD) Centers of radiological findings suggestive of radiological Usual Interstitial Pneumonia (UIP) in non-contrast, chest CT scans of adults. Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The development of the deep learning inference model utilized anonymized, multi-center, retrospective, volumetric chest CT scans from several different, private and public data sources including multiple hospitals, clinical imaging centers, and imaging databases. Chest CT datasets were identified where each dataset represented an individual subject and acquisition. Data was subdivided into "bins" between the two stages of model development roughly 80%:20%: 1) model training and validation (i.e., hyper-parameter tuning) and 2) model testing (i.e. performance assessment). Site independence was maintained for several of the databases with clinical location data labels by randomly assigning each clinic location an integer value between 1 and 1000. Then, increasing from the lowest to highest random integer value, all data sets from a specific clinic location were assigned to the training bin until 80% of the total number of datasets from a database had been assigned to the training bin. The remaining were assigned to the testing bin. The testing data set was locked and quarantined from the datasets used in the device's model training and validation. The results of Imbio IQ-UIP are intended to be used in conjunction with other patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Predicate Devices

DEN220040

Reference Devices

Not Found

AI/ML (Artificial Intelligence / Machine Learning)

Yes
The document explicitly states that the device "uses an artificial intelligence algorithm" and mentions the "development of the deep learning inference model" and "using machine learning, artificial intelligence or other image analysis algorithms."

Therapeutic

No
The device is a computer-aided software that analyzes CT scans to notify specialists of potential radiological findings, for informational purposes only, and is not intended for diagnosis or treatment.

Diagnostic

No
The "Intended Use / Indications for Use" and "Device Description" sections explicitly state: "The device does not alter the original medical image and is not intended to be used as a diagnostic device."

SaMD (Software as a Medical Device)

Yes

The device description explicitly states "Imbio IQ-UIP is a computer-aided software". The summary focuses entirely on the software's function, algorithm, data analysis, and performance metrics, with no mention of associated hardware components being part of the device itself.

IVD (In Vitro Diagnostic)

Based on the provided information, this device is not an IVD (In Vitro Diagnostic).

Here's why:

• IVD Definition: In Vitro Diagnostics are medical devices intended for use in vitro for the examination of specimens, including blood and tissue donations, derived from the human body, solely or principally for the purpose of providing information concerning a physiological or pathological state, or concerning a congenital abnormality, or to determine the safety and compatibility with potential recipients, or to monitor therapeutic measures.
• Imbio IQ-UIP's Intended Use: The intended use clearly states that the device analyzes radiological images (CT scans) and provides notifications and summary reports based on these images. It explicitly states it is not intended to be used as a diagnostic device.
• Nature of the Input: The input is medical imaging data (CT scans), not biological specimens from the human body.
• Purpose: The purpose is to passively notify specialists of potential findings, not to directly diagnose or provide information based on the analysis of biological samples.

Therefore, Imbio IQ-UIP falls under the category of medical imaging software or computer-aided detection/notification software, not In Vitro Diagnostics.

PCCP (Predetermined Change Control Plan) Authorized

No
The letter does not mention the FDA reviewing, approving, or clearing a Predetermined Change Control Plan (PCCP) for this specific device.

Overview

Intended Use / Indications for Use

Imbio IQ-UIP is a computer-aided software indicated for use in passively notifying specialists associated with interstitial lung disease (ILD) centers of radiological findings suggestive of radiological usual interstitial pneumonia (UIP) in non-contrast, chest CT scans of adults. Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device.

The results of Imbio IQ-UIP are used to notify specialists at an ILD center of radiological findings that may be consistent with UIP. These specialists are qualified clinicians experienced in evaluating chest CTs for ILD. Input images originate from within the same hospital network associated with the ILD center. The results of Imbio IQ-UIP are intended to be used in conjunction with additional patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Product codes

QWO

Device Description

Imbio IQ-UIP is a computer-aided software indicated for use in notifying specialists associated with Interstitial Lung Disease (ILD) Centers of radiological findings suggestive of radiological Usual Interstitial Pneumonia (UIP) in non-contrast, chest CT scans of adults.

Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device.

The development of the deep learning inference model utilized anonymized, multi-center, retrospective, volumetric chest CT scans from several different, private and public data sources including multiple hospitals, clinical imaging centers, and imaging databases. Chest CT datasets were identified where each dataset represented an individual subject and acquisition. Data was subdivided into "bins" between the two stages of model development roughly 80%:20%: 1) model training and validation (i.e., hyper-parameter tuning) and 2) model testing (i.e. performance assessment). Site independence was maintained for several of the databases with clinical location data labels by randomly assigning each clinic location an integer value between 1 and 1000. Then, increasing from the lowest to highest random integer value, all data sets from a specific clinic location were assigned to the training bin until 80% of the total number of datasets from a database had been assigned to the training bin. The remaining were assigned to the testing bin. The testing data set was locked and quarantined from the datasets used in the device's model training and validation.

The results of Imbio IQ-UIP are intended to be used in conjunction with other patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Mentions image processing

Not Found

Mentions AI, DNN, or ML

Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation.
The development of the deep learning inference model utilized anonymized, multi-center, retrospective, volumetric chest CT scans from several different, private and public data sources including multiple hospitals, clinical imaging centers, and imaging databases.
The device supports referral of findings related to fibrotic lung diseases using machine learning, artificial intelligence or other image analysis algorithms.

Input Imaging Modality

non-contrast, chest CT scans

Anatomical Site

Lung/Chest

Indicated Patient Age Range

Adults > 22 years old

Intended User / Care Setting

Specialists associated with interstitial lung disease (ILD) centers.
Qualified clinicians experienced in evaluating chest CTs for ILD.
Input images originate from within the same hospital network associated with the ILD center.

Description of the training set, sample size, data source, and annotation protocol

The development of the deep learning inference model utilized anonymized, multi-center, retrospective, volumetric chest CT scans from several different, private and public data sources including multiple hospitals, clinical imaging centers, and imaging databases. Data was subdivided into "bins" between the two stages of model development roughly 80%:20%: 1) model training and validation (i.e., hyper-parameter tuning) and 2) model testing (i.e. performance assessment). Site independence was maintained for several of the databases with clinical location data labels by randomly assigning each clinic location an integer value between 1 and 1000. Then, increasing from the lowest to highest random integer value, all data sets from a specific clinic location were assigned to the training bin until 80% of the total number of datasets from a database had been assigned to the training bin.

Description of the test set, sample size, data source, and annotation protocol

The remaining [20% of data sets] were assigned to the testing bin. The testing data set was locked and quarantined from the datasets used in the device's model training and validation.
These data were collected from 804 individual patient images.
Five experts, U.S. board-certified radiologists ("truthers") practicing within the United States performed ground truthing of the performance datasets. Each truther had a minimum of 5+ years experience evaluating chest CTs for ILDs and a clinical familiarity with using the ATS/ERS/JRS/ALAT diagnostic categories for UIP pattern. None of the enrolled truthers were involved in the development of the algorithm/device in any way, thus ensuring independence of testing and training data or other activities.

Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)

Software Validation:

• Integration, Regression, and Algorithm Validation Testing
• Design Verification
• Unit Testing
• Standalone Performance Assessment

Summary Data:

• Sample size: 804 individual patient images
• AUC ROC: 96.6 [95.4, 97.7]
• PPV: 77.9 [73.3, 82.8]
• Specificity: 91.5 [89.2, 93.7]
• Sensitivity: 90.2 [86.2, 94.3]

The prevalence of radiological UIP+ pattern in the standalone performance assessment cohort was 193/804 = 24.0%.
Positive and negative predictive values were estimated for various prevalences expected to be encountered by the device.

Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)

AUC ROC: 96.6 [95.4, 97.7]
PPV: 77.9 [73.3, 82.8]
Specificity: 91.5 [89.2, 93.7]
Sensitivity: 90.2 [86.2, 94.3]

Predicate Device(s)

DEN220040

Reference Device(s)

Not Found

Predetermined Change Control Plan (PCCP) - All Relevant Information

Not Found

Regulation Number and Section

N/A

Summary

0

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Imbio. Inc. William Mclain QA/RA Manager 1015 Glenwood Avenue Floor 4 Minneapolis, Minnesota 55405

December 19, 2024

Re: K242467

Trade/Device Name: IQ-UIP Regulation Number: 21 CFR 892.2085 Regulation Name: Radiology software for referral of findings related to fibrotic lung disease Regulatory Class: Class II Product Code: QWO Dated: November 18, 2024 Received: November 18, 2024

Dear William Mclain:

We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"

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(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 (OS) 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.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatory

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assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely,

Jessica Lamb

Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

Submission Number (if known)

K242467

Device Name

IQ-UIP

Indications for Use (Describe)

Imbio IQ-UIP is a computer-aided software indicated for use in passively notifying specialists associated with interstitial lung disease (ILD) centers of radiological findings suggestive of radiological usual interstitial pneumonia (UIP) in non-contrast, chest CT scans of adults. Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device.

The results of Imbio IQ-UIP are used to notify specialists at an ILD center of radiological findings that may be consistent with UIP. These specialists are qualified clinicians experienced in evaluating chest CTs for ILD. Input images originate from within the same hospital network associated with the ILD center. The results of Imbio IQ-UIP are intended to be used in conjunction with additional patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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K242467 510(k) Summary-IQ UIP

Submission Owner and Correspondent

Imbio, Inc. 1015 Glenwood Avenue Floor 4 Minneapolis, MN 55405 Contact: William McLain Phone: [phone] E-Mail: [e-mail]

Other submissions correspondents: Lauren Keith, Director of Engineering, [e-mail] and Kai Ludwig, Senior Imaging Scientist, [e-mail]

Date Summary Prepared

November 18, 2024

Device Trade Name

IQ-UIP

Device Common Name

Radiology Software For Referral Of Findings Related To Fibrotic Lung Disease

Device Classification Name

Radiology Software For Referral Of Findings Related To Fibrotic Lung Disease 21 CFR 892.2085 QWO

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Legally Marketed Device To Which The Device Is Substantially Equivalent

The IQ-UIP Software is substantially equivalent to the Imvaria, Inc Fibresolve authorized under DEN220040.

Description of the Device

lmbio IQ-UIP is a computer-aided software indicated for use in notifying specialists associated with Interstitial Lung Disease (ILD) Centers of radiological findings suggestive of radiological Usual Interstitial Pneumonia (UIP) in non-contrast, chest CT scans of adults.

Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device.

The development of the deep learning inference model utilized anonymized, multi-center, retrospective, volumetric chest CT scans from several different, private and public data sources including multiple hospitals, clinical imaging centers, and imaging databases. Chest CT datasets were identified where each dataset represented an individual subject and acquisition. Data was subdivided into "bins" between the two stages of model development roughly 80%:20%: 1) model training and validation (i.e., hyper-parameter tuning) and 2) model testing (i.e. performance assessment). Site independence was maintained for several of the databases with clinical location data labels by randomly assigning each clinic location an integer value between 1 and 1000. Then, increasing from the lowest to highest random integer value, all data sets from a specific clinic location were assigned to the training bin until 80% of the total number of datasets from a database had been assigned to the training bin. The remaining were assigned to the testing bin. The testing data set was locked and quarantined from the datasets used in the device's model training and validation.

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The results of Imbio IQ-UIP are intended to be used in conjunction with other patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Indication for Use

Imbio IQ-UIP is a computer-aided software indicated for use in passively notifying specialists associated with interstitial lung disease (ILD) centers of radiological findings suggestive of radiological usual interstitial pneumonia (UIP) in non-contrast, chest CT scans of adults. Imbio IQ-UIP uses an artificial intelligence algorithm to analyze images and identify positive findings on a worklist application separate from and in parallel to the standard of care radiological image interpretation. Identification of positive findings include summary reports with a clinical guideline reference for the definition of UIP pattern that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device.

The results of Imbio IQ-UIP are used to notify specialists at an ILD center of radiological findings that may be consistent with UIP. These specialists are qualified clinicians experienced in evaluating chest CTs for ILD. Input images originate from within the same hospital network associated with the ILD center. The results of Imbio IQ-UIP are intended to be used in conjunction with additional patient information and based on the user's professional judgment, to assist with the review of medical images. Notified clinicians are responsible for viewing full image series and making final clinical determinations.

Technological Characteristics

The following table demonstrates the technical characteristics comparing the proposed to the predicate device.

| Characteristic | Predicate: Fibresolve
(DEN220040) | Proposed: IQ-UIP | Similarities or
Differences |
|------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| FDA Clearance | DEN220040 | TBD | -- |
| Clearance Date | 01/12/2024 | TBD | -- |
| Product Code | QWO | QWO | Same |
| Characteristic | Predicate: Fibresolve
(DEN220040) | Proposed: IQ-UIP | Similarities or
Differences |
| Class | II | II | Same |
| Regulation | 892.2085 | 892.2085 | Same |
| Software | Device is software only | Device is software only | Same |
| Software
Documentation
Level | Moderate | Basic | Documentation is similar
and differences are due to
updated FDA guidance. |
| Indications for
Use | Fibresolve is a software-only device
that receives and analyzes lung
computed tomography (CT) imaging
data in order to provide a diagnostic
subtype classification in suspected
cases of interstitial lung disease
(ILD). The device supplements the
standard-of-care workflow by
providing a qualitative, diagnostic
classification output of imaging
findings based on machine learning
pattern recognition, in order to
provide adjunctive information as
part of a referral pathway to an
appropriate Multidisciplinary
Discussion (MDD) or as part of an
MDD. Specifically, the tool is used
to serve as an adjunct in the
diagnosis of idiopathic pulmonary
fibrosis (IPF) prior to invasive
testing. The results of Fibresolve are
intended to be used only by
clinicians qualified in the care of
lung disease, specifically in caring
for patients with ILD, in conjunction
with the patient's clinical history,
symptoms, and other diagnostic
tests, as well as the clinician's
professional judgment.
The input to Fibresolve is a DICOM-
compliant lung CT scan. Clinical
case eligibility includes the
following criteria:
Age > 22 years old.
Pulmonary symptoms suggestive of
possible ILD including IPF. | Imbio IQ-UIP is a computer-aided
software indicated for use in
passively notifying specialists
associated with interstitial lung
disease (ILD) centers of
radiological findings suggestive of
radiological usual interstitial
pneumonia (UIP) in non-contrast,
chest CT scans of adults. Imbio IQ-
UIP uses an artificial intelligence
algorithm to analyze images and
identify positive findings on a
worklist application separate from
and in parallel to the standard of
care radiological image
interpretation. Identification of
positive findings include summary
reports with a clinical guideline
reference for the definition of UIP
pattern that are meant for
informational purposes only. The
device does not alter the original
medical image and is not intended
to be used as a diagnostic device.
The results of Imbio IQ-UIP are
used to notify specialists at an ILD
center of radiological findings that
may be consistent with UIP. These
specialists are qualified clinicians
experienced in evaluating chest
CTs for ILD. Input images originate
from within the same hospital
network associated with the ILD
center. The results of Imbio IQ-UIP
are intended to be used in
conjunction with additional patient
information and based on the
user's professional judgment, to
assist with the review of medical | Similarities
• Referral software for
findings suggestive of
a pre-specified
clinical fibrotic lung
condition
• Uses artificial
intelligence to
analyze chest/lung CT
images
• Used by clinicians
qualified in the care
of lung disease
• Operates in parallel to
standard of care
workflow
• Provide qualitative
diagnostic subtype
classification for
cases suspected of
interstitial lung
disease
• Limited to analysis of
imaging data and
should not be used
in-lieu of full patient
evaluation or relied
upon to make or
confirm diagnosis |
| Characteristic | Predicate: Fibresolve
(DEN220040) | Proposed: IQ-UIP | Similarities or
Differences |
| | | images. Notified clinicians are
responsible for viewing full image
series and making final clinical
determinations. | Differences:
• IQ-UIP reports
viewable on
dedicated worklist
application separate
from standard-of-
care. |
| Technical
Method | The device supports referral of
findings related to fibrotic lung
diseases using machine learning,
artificial intelligence or other
image analysis algorithms. | The device supports referral of
findings related to fibrotic lung
diseases using machine
learning, artificial intelligence or
other image analysis algorithms. | Same |
| Target Area | The device operates on
radiological images of the
human body. | The device operates on
radiological images of the
human body. | Same |
| Anatomical Site | Lung/Chest | Lung/Chest | Same |
| Intended User
Population | Clinicians qualified in care of lung
disease | Clinicians qualified in care of lung
disease | Same |
| Patient
Population | Adults > 22 years old and with
pulmonary symptoms suggestive of
possible ILD including IPF. | Adults > 22 years old | Similarities:
• Adults > 22 years old

Differences:
• Fibresolve's patient
population is limited
to those adults with
pulmonary symptoms
suggestive of possible
ILD including IPF.
• IQ-UIP patient
population would
include the same
patient population as
those indicated for
Fibresolve but may
also include others
who have undergone a
chest CT for other
symptoms. |
| Communication
with Patient | Does not communicate images
to patients. | Does not communicate images
to patients. | Same |
| Characteristic | Predicate: Fibresolve
(DEN220040) | Proposed: IQ-UIP | Similarities or
Differences |
| Alteration of
original image | No | No | Same |
| Viewing | Unknown | Referral report viewable on
dedicated worklist application
accessible by the intended users. | IQ-UIP reports viewable on
dedicated worklist
application separate from
standard-of-care. |

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Software Validation

The IQ-UIP Software was subject to the following testing in association with software validation:

• . Integration, Regression, and Algorithm Validation Testing
• . Design Verification
• Unit Testing .
• . Standalone Performance Assessment

Summary Data

For primary endpoints, the device's AUC ROC is 96.6 [95.4, 97.7] and PPV is 77.9 [73.3, 82.8].

For secondary endpoints, the device's specificity is 91.5 [89.2, 93.7] and sensitivity is 90.2 [86.2, 94.3].

These data were collected from 804 individual patient images.

The prevalence of radiological UIP+ pattern in the standalone performance assessment cohort was 193/804 = 24.0%.

Positive and negative predictive values were estimated for various prevalences expected to be encountered by the device.

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Demographic data are presented in the following table.

Data Bin	Datasets	Percentage of Total (%)
Gender
Male	437	54.4%
Female	300	37.3%
N/A	67	8.3%
Age (years)