Thursday, July 3, 2025 7/3/2025

Robust Clinical Translation of CT Imaging Biomarker in COPD for EBV Patient Selection

Award Number: R01HL153964
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/01/2021
PERIOD OF PERFORMANCE END DATE: 03/31/2025

Group Awards By:

View Award Description

Robust Clinical Translation of CT Imaging Biomarker in COPD for EBV Patient Selection - PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD), which includes conditions such as emphysema, is the fourth leading cause of death in the United States. Although progression of COPD can be slowed through lifestyle changes, the disease is incurable. New treatment/management options emerged recently when the FDA approved endobronchial valves (EBV) as a Breakthrough Device for the treatment of severe COPD. EBVs provide a new treatment pathway but their implantation is associated with morbidity and mortality risks. In addition, not every patient who undergoes implantation has demonstrated the expected benefits from the device. Trial data indicate that imaging data can be used to help identify patients in whom an EBV will be effective, showing specifically that effectiveness increases in patients with heterogeneous COPD with complete fissures in the targeted lobes. The EBV is officially indicated for “severe emphysema in regions of the lung that have little to no collateral ventilation,” but interpretation of these criteria is imprecise and qualitative. The goal of this proposal is to develop more unified, robust, and quantitative criteria that will more successfully identify patients that are likely to respond to EBV implantation. The three most predictive variables identified by clinical trials to date have been the degree of severity of COPD, the heterogeneity of COPD between adjacent lobes and fissure completeness, all of which can be assessed by CT imaging. However, quantification of COPD severity can be confounded by the CT acquisition and reconstruction parameter selections used in the imaging protocol. These can also affect the ability to assess fissure completeness. In addition, traditional measures of COPD severity (i.e. Emphysema score) do not distinguish lung destruction from airtrapping, which may be important in assessing whether a patient is a good candidate for an EBV. In this proposal, we will investigate methods to standardize CT imaging data that would allow for more robust quantitative image analysis and apply the resulting methods to develop a more robust criteria for patient selection for the application of EBV devices. Therefore, our Specific Aims are: (1) To develop methods for robust, quantitative CT estimates of lung density and the Fissure Integrity Score (FIS). This will involve the application of methods to account for differences in CT scanners and acquisition/reconstruction parameters as well as machine learning methods to more accurately assess lung fissure integrity; (2) To develop and test an EBV predictive model using improved measures. Using the improved estimates of lung density and FIS from aim 1, we will develop and test a predictive model that distinguishes EBV responders from non-responders; and (3) To extend the EBV Prediction Model to incorporate additional biomarkers. We will extend the EBV scoring model by investigating other biomarkers that may provide complementary information, such as distinguishing airtrapping from COPD and an assessment of lung vascularity. We evaluate the ability of this extended model to improve our ability to distinguish EBV responders from non-responders.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $668,617 )
2024	2024	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	001	4	6/24/2024	NON-COMPETING CONTINUATION	$54,582
2024	2024	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	000	4	3/29/2024	NON-COMPETING CONTINUATION	$614,035
														Subtotal = $668,617

Issue Date FY: 2023 ( Subtotal = $682,261 )
2023	2023	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	000	3	4/17/2023	NON-COMPETING CONTINUATION	$682,261
														Subtotal = $682,261

Issue Date FY: 2022 ( Subtotal = $673,505 )
2022	2022	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	001	2	6/14/2022	NON-COMPETING CONTINUATION	$67,353
2022	2022	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	000	2	3/16/2022	NON-COMPETING CONTINUATION	$606,152
														Subtotal = $673,505

Issue Date FY: 2021 ( Subtotal = $687,505 )
2021	2021	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90095	LOS ANGELES	USA	Lung Diseases Research	000	1	3/25/2021	NEW	$618,754
2021	2021	UNIVERSITY OF CALIFORNIA, LOS ANGELES	10889 WILSHIRE BLVD STE 700	LOS ANGELES	CA	90024	LOS ANGELES	USA	Lung Diseases Research	001	1	7/2/2021	NEW	$68,751
														Subtotal = $687,505

Grand Total All Awards = $2,711,888

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Robust Clinical Translation of CT Imaging Biomarker in COPD for EBV Patient Selection

Award Number: R01HL153964

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 04/01/2021

PERIOD OF PERFORMANCE END DATE: 03/31/2025

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer