About

Kevin K Whitehead, MD, PhD, is an Associate Professor of Pediatrics (Cardiology) at the Children's Hospital of Philadelphia within the Department of Pediatrics. His educational background includes a BSE in Biomedical Engineering from Duke University, magna cum laude, obtained in 1992, a PhD in Bioengineering from the University of Pittsburgh in 1998, and an MD from the University of Pittsburgh in 2000. His research expertise encompasses computational fluid dynamics, in vitro flow phantoms, Fontan hemodynamics, and noninvasive quantification of blood flow. Clinically, he specializes in pediatric cardiology, cardiac MRI, cardiac imaging, and quantification of aortopulmonary collateral flow. His work focuses on advancing understanding and measurement of blood flow dynamics in congenital heart disease, contributing to improved diagnostic and therapeutic strategies.

Research topics

• Internal medicine
• Medicine
• Surgery
• Cardiology

Selected publications

• Rapid Visualization of Valves and Myocardium Using Volume Rendering of 3D Cardiac MRI, 4D Cine, and 4D Flow Images

  Radiology Cardiothoracic Imaging · 2026-02-01

  articleOpen access

  Volume rendering enabled rapid visualization of three-dimensional, four-dimensional cine, and four-dimensional flow cardiac MRI to improve understanding of anatomy and hemodynamics in complex congenital heart disease and to support interventional planning.

  PublisherOA PDFDOI

• Image-based navigated CMRA late after gadobutrol reliably delineates the coronaries in children and adults

  Journal of Cardiovascular Magnetic Resonance · 2026-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• Abstract 4367228: Asymmetric Pulmonary Artery Geometry Drives Branch-Specific Shear Stress Patterns in Repaired Tetralogy of Fallot: A Substudy of the <i>Single Center Cardiac Magnetic Resonance Outcomes Registry – Tetralogy of Fallot</i>

  Circulation · 2025-11-03

  article

  Introduction: In repaired tetralogy of Fallot (rToF), asymmetric remodeling of the pulmonary arteries (PA) leads to branch-specific hemodynamic changes. Geometric factors such as curvature influence wall shear stress (WSS) patterns, with distinct effects between the left (LPA) and right pulmonary arteries (RPA). Oscillatory shear index (OSI), which quantifies directional changes in WSS over the cardiac cycle, is a key marker of disturbed flow. This study investigates how curvature and other geometric factors influence hemodynamics in these two branches. Hypothesis: We hypothesize that geometric features influence PA hemodynamics in a branch-specific manner, with curvature having a stronger association with shear-related metrics in certain regions compared to others. Methods: Patient-specific PA models (n = 22) were reconstructed from cardiac magnetic resonance imaging, and computational fluid dynamics simulations were performed under steady and pulsatile flow conditions with patient-derived boundary conditions. Geometric parameters, including curvature and tortuosity, and hemodynamic metrics, including time-averaged WSS and OSI, were quantified. Spearman correlations assessed branch-specific relationships. Results: In the LPA, curvature showed a strong positive correlation with time-averaged WSS (ρ = 0.56, p = 0.006) and a negative correlation with OSI (ρ = -0.52, p = 0.013), indicating that higher curvature segments exhibit more unidirectional, high-shear flow (Figures 1 and 2) . In contrast, RPA curvature did not correlate significantly with any of the measured hemodynamic variables (all p &gt; 0.28). The LPA curvature was significantly greater than the RPA curvature (p = 0.015). Tortuosity did not show significant correlations with hemodynamics in either branch (p &gt; 0.17), suggesting that curvature is the dominant geometric modulator of wall shear stress (Table 1) . Conclusions: The LPA’s curvature-dependent hemodynamics characterized by significant time-averaged WSS and OSI patterns contrast with the RPA’s lack of such correlations. Anatomically, the RPA’s straighter anatomy minimizes flow disruption whereas the LPA curvature increases flow disruption. This study’s results align with prior studies showing sharper angulation in the LPA post-repair, promoting flow acceleration. Clinically, these findings highlight the importance of branch-specific geometric and hemodynamic assessments in rToF follow-up.

  PublisherDOI

• Pulmonary Artery Shear Stress and Oscillatory Shear Index are Associated with Right Ventricular Remodeling in Repaired Tetralogy of Fallot

  Annals of Biomedical Engineering · 2025-07-03 · 2 citations

  articleOpen access

  Abstract Purpose Right ventricular (RV) remodeling in repaired tetralogy of Fallot (rToF) is a multifactorial process that may be affected by downstream hemodynamics. We therefore sought to characterize hemodynamics in the pulmonary arteries (PAs) of rToF patients using cardiovascular magnetic resonance (CMR)-derived computational fluid dynamics (CFD) and to study these variables in association with RV measurements at follow-up. Methods We selected patients with two CMRs who had magnetic resonance angiography (MRA) performed at baseline. The PA was segmented from the main PA (MPA) through the first bifurcation of the left PA (LPA) and right PA (RPA). Both steady and pulsatile simulations were performed. For each vessel, we calculated curvature, tortuosity, and both average (avg) and peak steady WSS (WSS steady ), time-averaged WSS (taWSS), WSS in systole (WSS systole ), and WSS in diastole (WSS diastole ), as well as oscillatory shear index (OSI). We studied these variables in association with RV metrics at follow-up including: RV end-diastolic volume index (RVEDVi), RV end-systolic volume index (RVESVi), RV stroke volume index (RVSVi), and RV ejection fraction (RVEF), as well as the outcome of pulmonic valve replacement (PVR). Results 22 patients met the inclusion criteria. Several focal hemodynamic metrics in the main and branch PAs, including WSS steady , taWSS, WSS systole , WSS diastole, and OSI were associated with RV measurements at follow-up, including RVEDVi, RVESVi, and RVSVi. LPA WSS steady,avg , RPA WSS steady,peak , whole vessel OSI avg , and MPA OSI avg were associated with likelihood of PVR. Conclusion CFD-derived hemodynamic variables in the PAs of rToF patients are associated with both PVR and RV remodeling.

  PublisherOA PDFDOI

• Intravenous immunoglobulin does not reduce burden of late gadolinium enhancement in pediatric patients with myocarditis: A pilot study

  Journal of Cardiovascular Magnetic Resonance · 2025-01-01

  articleOpen access
  PublisherDOI

• Left ventricle to aorta tunnel with unusual right coronary artery origin

  Journal of Cardiovascular Magnetic Resonance · 2025-01-01

  articleOpen access
  PublisherDOI

• Clinical Outcome Prediction Model in Tetralogy of Fallot Without Pulmonary Valve Replacement Using Contraction Fraction From the SCOUT‐TOF Registry

  Journal of the American Heart Association · 2025-05-13 · 3 citations

  articleOpen access

  Background Few large scale prediction models of clinical outcomes in repaired tetralogy of Fallot (rTOF) exist. Further, contraction fraction, a novel parameter indexing stroke volume by mass reflecting myocardial efficiency, has not been studied. The goals of this study were to develop and validate an rTOF prediction model of clinical outcome from a single center, the SCOUT‐TOF (Single Center Outcomes Using Cardiac Magnetic Resonance in Tetralogy of Fallot) registry, using readily available cardiac magnetic resonance parameters and explore novel metrics. Methods and Results We retrospectively reviewed cardiac magnetic resonance parameters of patients with rTOF undergoing cardiac magnetic resonance from 2005 to 2021. Composite outcome 1 (CO1) included death, transplantation, ventricular tachycardia, and pacemaker placement, and composite outcome 2 (CO2) added cardiovascular hospitalizations. An elastic net was used to identify significant variables to enter a best subsets logistic regression. A group of 761 patients with rTOF were studied with a median follow‐up of 4.15 years; 31 and 44 CO1 and CO2 events occurred respectively. Right ventricular (RV) contraction fraction was the most significant predictor for CO1 (area under the curve, 0.72; odds ratio [OR], 0.54; P =0.01) and CO2 (area under the curve, 0.69; OR, 0.60; P =0.01). RV contraction fraction was lower for those met that CO1 and CO2 end points (median 1.84 [1.48–2.39] versus 2.34 [1.72–3.02] and 1.88 [1.51–2.53] versus 2.34 [1.72–3.02] cc×cm 2.7 /g×m 1.4 , P &lt;0.01 respectively). Additional significant predictors for CO1 were indexed RV mass/volume and left ventricular ejection fraction whereas for CO2, left ventricular global function index and left ventricular mass were additional predictors. Conclusions In rTOF, RV contraction fraction, a novel biomarker of ventricular efficiency, may be used to possibly improve risk stratification. In addition, not only RV but left ventricular measures of remodeling should be considered in the follow‐up of these patients.

  PublisherDOI

• Image-based navigation with ferumoxytol improves reliability of whole heart acquisition in children and adults

  Journal of Cardiovascular Magnetic Resonance · 2025-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• A unique pediatric case of left ventricular fatty infiltration with excessive trabeculations sparing the right heart

  Journal of Cardiovascular Magnetic Resonance · 2025-01-01

  articleOpen access
  PublisherDOI

• Cardiovascular magnetic resonance imaging traits associated with adverse right ventricular remodeling in repaired tetralogy of Fallot: A Single Center Outcomes Using cardiovascular magnetic resonance in Tetralogy of Fallot study

  Journal of Cardiovascular Magnetic Resonance · 2025-01-01 · 1 citations

  articleOpen access

  Deterioration of right ventricular (RV) function in repaired tetralogy of Fallot (rToF) is poorly understood. Cardiovascular magnetic resonance (CMR) is used for monitoring, but its analysis is user-dependent and time-consuming. We sought to automate the analysis of CMR using machine learning and to identify imaging traits associated with adverse RV remodeling in the natural history of rToF. A longitudinal cohort of rToF patients underwent CMR at the Children’s Hospital of Philadelphia. The nnU-Net method was used to train a machine learning model to segment the left ventricular (LV) blood pool, LV myocardium, and RV blood pool from two-dimensional short-axis CMR images. Conventional and novel measures were calculated and studied in association with remodeling rates using multivariable linear regression. Remodeling rates were calculated as ((Variable scan2 − Variable scan1 )/years between scans) for the variables end-diastolic volume index (EDVi), end-systolic volume index (ESVi), stroke volume index (SVi), ejection fraction (EF), and peak systolic dV/dt. The cohort was comprised of 758 patients, of whom 152 had 2 analyzable scans. Thirty-six patients underwent pulmonic valve replacement (PVR) between scans. Compared to patients with no intervention (representing the natural history of rToF), patients with PVR had significantly lower remodeling rates for RVEDVi, RVESVi, RVSVi, and absolute peak systolic RV dV/dt, while RVEF and left-sided metrics did not differ between groups. In 116 patients without PVR between scans, RV remodeling rates were negatively associated with baseline LV mass index, LVEDVi, LVSVi, and absolute peak systolic LV dV/dt. We demonstrated that rToF patients with two CMR scans and PVR have significant differences in and opposite directions of RV remodeling rates compared to those with no intervention. We also showed that several left-sided measures of structure and function were associated with RV remodeling rates, indicating the importance of baseline LV measurements in characterizing future risk of adverse RV remodeling.

  PublisherDOI

Recent grants

• NIH Grant K23HL089647

  NIH · $692k · 2015

Frequent coauthors

• Mark A. Fogel

  Children's Hospital of Philadelphia

  285 shared

• Matthew Harris

  Columbia University Irving Medical Center

  112 shared

• Ajit P. Yoganathan

  Georgia Institute of Technology

  97 shared

• Matthew A. Harris

  Children's Hospital of Philadelphia

  80 shared

• Marc S. Keller

  80 shared

• Stephen M. Paridon

  65 shared

• Matthew J. Gillespie

  Children's Hospital of Philadelphia

  59 shared

• David M. Biko

  Children's Hospital of Philadelphia

  55 shared

Labs

• Kevin K Whitehead LaboratoryPI