Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations

Cerebral blood flow (CBF) supports brain function and health. Cerebral blood flow is affected by normal brain development, disease, medications use, and other interventions. One method to measure CBF is phase contrast magnetic resonance (PC MR) imaging, a particularly fast and reliable method to mea...

Full description

Saved in:
Bibliographic Details
Main Authors: Eamon K. Doyle, Isabel Torres, Joseph Liu, Abhishek Karnwal, Sudarshan Ranganathan, Bradley J. De Souza, Payal Shah, Bradley S. Peterson, John C. Wood, Matthew Thomas Borzage
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Physiology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2025.1527093/full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850212242804441088
author Eamon K. Doyle
Eamon K. Doyle
Isabel Torres
Isabel Torres
Joseph Liu
Abhishek Karnwal
Sudarshan Ranganathan
Sudarshan Ranganathan
Bradley J. De Souza
Payal Shah
Bradley S. Peterson
John C. Wood
John C. Wood
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
author_facet Eamon K. Doyle
Eamon K. Doyle
Isabel Torres
Isabel Torres
Joseph Liu
Abhishek Karnwal
Sudarshan Ranganathan
Sudarshan Ranganathan
Bradley J. De Souza
Payal Shah
Bradley S. Peterson
John C. Wood
John C. Wood
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
author_sort Eamon K. Doyle
collection DOAJ
description Cerebral blood flow (CBF) supports brain function and health. Cerebral blood flow is affected by normal brain development, disease, medications use, and other interventions. One method to measure CBF is phase contrast magnetic resonance (PC MR) imaging, a particularly fast and reliable method to measure blood flow through major arteries such as the internal carotid (ICA) or vertebral arteries (VA). Unfortunately, sometimes PC MR can be compromised due to errors by the technologist during image acquisition, patient movement, or complex vessel structures. Our goal was to develop mathematical models to estimate CBF for a wide age range of patients whenever 1 or more vessels are not correctly measured. To investigate this, we studied a set of 258 PC MR acquisitions from a group of 196 patients with one or three acquisitions per subject (165 single images, 31 acquisitions of 3 images) ranging in age from 0.4 to 61.3 years (mean [μ] = 13.1, standard deviation [σ] = 12.3). We deliberately excluded measurements from one or more arteries in each volunteer to mimic situations with low image quality. Subsequently, we developed mathematical models to predict the missing data. Our predictive models performed well; across the human lifespan when at least one ICA measurement was available, our normalized root mean squared error values were low (<0.137), our R-squared values were high (>0.91), and we observed high intra-class correlation coefficients (>0.951). In summary, these imputation models are effective in estimating CBF in children and adults.
format Article
id doaj-art-8ce5f6235bdd45bdb8f022ae6e25b6b8
institution OA Journals
issn 1664-042X
language English
publishDate 2025-06-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Physiology
spelling doaj-art-8ce5f6235bdd45bdb8f022ae6e25b6b82025-08-20T02:09:23ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2025-06-011610.3389/fphys.2025.15270931527093Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populationsEamon K. Doyle0Eamon K. Doyle1Isabel Torres2Isabel Torres3Joseph Liu4Abhishek Karnwal5Sudarshan Ranganathan6Sudarshan Ranganathan7Bradley J. De Souza8Payal Shah9Bradley S. Peterson10John C. Wood11John C. Wood12Matthew Thomas Borzage13Matthew Thomas Borzage14Matthew Thomas Borzage15Matthew Thomas Borzage16Department of Radiology, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United StatesDepartment of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesDepartment of Radiology, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United StatesRudi Schulte Research Institute, Santa Barbara, CA, United StatesFetal and Neonatal Institute, Division of Neonatology, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDepartment of Anesthesia Critical Care Medicine, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesFetal and Neonatal Institute, Division of Neonatology, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDivision of Cardiology, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDepartment of Anesthesia Critical Care Medicine, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDivision of Cardiology, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDepartment of Psychiatry, Keck School of Medicine at the University of Southern California, Los Angeles, CA, United StatesDepartment of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesDivision of Cardiology, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesDepartment of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesFetal and Neonatal Institute, Division of Neonatology, Children’s Hospital Los Angeles, Los Angeles, CA, United StatesAlfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Regulatory and Quality Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, United StatesCerebral blood flow (CBF) supports brain function and health. Cerebral blood flow is affected by normal brain development, disease, medications use, and other interventions. One method to measure CBF is phase contrast magnetic resonance (PC MR) imaging, a particularly fast and reliable method to measure blood flow through major arteries such as the internal carotid (ICA) or vertebral arteries (VA). Unfortunately, sometimes PC MR can be compromised due to errors by the technologist during image acquisition, patient movement, or complex vessel structures. Our goal was to develop mathematical models to estimate CBF for a wide age range of patients whenever 1 or more vessels are not correctly measured. To investigate this, we studied a set of 258 PC MR acquisitions from a group of 196 patients with one or three acquisitions per subject (165 single images, 31 acquisitions of 3 images) ranging in age from 0.4 to 61.3 years (mean [μ] = 13.1, standard deviation [σ] = 12.3). We deliberately excluded measurements from one or more arteries in each volunteer to mimic situations with low image quality. Subsequently, we developed mathematical models to predict the missing data. Our predictive models performed well; across the human lifespan when at least one ICA measurement was available, our normalized root mean squared error values were low (<0.137), our R-squared values were high (>0.91), and we observed high intra-class correlation coefficients (>0.951). In summary, these imputation models are effective in estimating CBF in children and adults.https://www.frontiersin.org/articles/10.3389/fphys.2025.1527093/fullinternal carotid artery (ICA)cerebral blood flow (CBF)magnetic resonance imaging (MRI)vertebral artery (VA)phase contrast (PC)
spellingShingle Eamon K. Doyle
Eamon K. Doyle
Isabel Torres
Isabel Torres
Joseph Liu
Abhishek Karnwal
Sudarshan Ranganathan
Sudarshan Ranganathan
Bradley J. De Souza
Payal Shah
Bradley S. Peterson
John C. Wood
John C. Wood
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
Matthew Thomas Borzage
Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
Frontiers in Physiology
internal carotid artery (ICA)
cerebral blood flow (CBF)
magnetic resonance imaging (MRI)
vertebral artery (VA)
phase contrast (PC)
title Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
title_full Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
title_fullStr Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
title_full_unstemmed Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
title_short Imputation models and error analysis for phase contrast MR cerebral blood flow measurements in heterogeneous pediatric and adult populations
title_sort imputation models and error analysis for phase contrast mr cerebral blood flow measurements in heterogeneous pediatric and adult populations
topic internal carotid artery (ICA)
cerebral blood flow (CBF)
magnetic resonance imaging (MRI)
vertebral artery (VA)
phase contrast (PC)
url https://www.frontiersin.org/articles/10.3389/fphys.2025.1527093/full
work_keys_str_mv AT eamonkdoyle imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT eamonkdoyle imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT isabeltorres imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT isabeltorres imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT josephliu imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT abhishekkarnwal imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT sudarshanranganathan imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT sudarshanranganathan imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT bradleyjdesouza imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT payalshah imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT bradleyspeterson imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT johncwood imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT johncwood imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT matthewthomasborzage imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT matthewthomasborzage imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT matthewthomasborzage imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations
AT matthewthomasborzage imputationmodelsanderroranalysisforphasecontrastmrcerebralbloodflowmeasurementsinheterogeneouspediatricandadultpopulations