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Parametric Response Mapping (PRM) for the detection of chronic lung injury in hematopoietic cell transplant recipients

Award Number: R01HL162661
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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ABSTRACT Chronic lung dysfunction (CLD) is a potentially severe complication of bone marrow transplantation (BMT), particularly prevalent in patients who develop chronic graft versus host disease (GVHD) post-BMT. The development of CLD is associated with a 20%-40% long term survival rate, with the majority of patients diagnosed with CLD only after they have developed significant (and potentially irreversible) lung pathology. There is a critical need to identify CLD earlier in its clinical course, at a stage when treatment may prove beneficial to patients. Parametric response mapping (PRM) is a novel computed tomography (CT) based methodology that when applied to standard CT scans is capable of identifying and quantifying a variety of lung disease subtypes in patients. This technology was initially developed at Michigan Medicine over 10 years ago for patients with chronic obstructive pulmonary disease (COPD). In both single center and multicenter trials, PRM has demonstrated efficacy for the identification of CLD in adult BMT patients. Our central hypothesis is that PRM can identify patients with chronic GVHD who are at high risk for the development of CLD. We propose an observational study to examine PRM in adult and pediatric subjects (≥ 3 years in age) with chronic GVHD post- BMT. To test our hypothesis, we have established 3 specific aims. In the first two, we will examine PRM values at two main time points: at the onset of chronic GVHD (Aim 1) and at the onset of CLD (Aim 2), with CLD defined by standard NIH criteria. In Aim 3, we will develop a machine learning model that will incorporate serologic and pulmonary function test (PFT) biomarkers with PRM values to develop a composite biomarker strategy. Upon completion of our current proposal, we will establish PRM as a predictor of CLD in adult BMT patients. In addition, the PRM, PFT, and serologic data obtained from pediatric BMT patients will provide a data bank for future research in this population. Historically, the ability to identify CLD in pediatric patients has been PFT-dependent, with PFTs technically challenging to conduct in young children. The use of PRM as a diagnostic indicator of CLD in pediatric BMT patients will be a major advance of this proposal. Finally, our proposal takes our PRM methodology forward in adults, allowing us to study the trajectory of lung disease in adult BMT recipients with chronic GVHD, and following the onset of CLD.


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 = $727,648 )
2024	2024	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Lung Diseases Research	000	3	8/16/2024	NON-COMPETING CONTINUATION	$727,648
														Subtotal = $727,648

Issue Date FY: 2023 ( Subtotal = $782,026 )
2023	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Lung Diseases Research	000	2	8/16/2023	NON-COMPETING CONTINUATION	$782,026
														Subtotal = $782,026

Issue Date FY: 2022 ( Subtotal = $870,211 )
2022	2022	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Lung Diseases Research	000	1	8/12/2022	NEW	$870,211
														Subtotal = $870,211

Grand Total All Awards = $2,379,885

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Parametric Response Mapping (PRM) for the detection of chronic lung injury in hematopoietic cell transplant recipients

Award Number: R01HL162661

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

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