Kathryn Nightingale, PhD

Theo Pilkington Distinguished Professor of Biomedical Engineering
Professor in the Department of Biomedical Engineering
Member of the Duke Cancer Institute
Bass Fellow
Address: 277 Hudson Hall Annex
Durham, NC 27708
Phone: (919) 660-5175
Email: kathy.nightingale@duke.edu

Research Interests

The goals of our laboratory are to investigate and improve ultrasonic imaging methods for clinically-relevant problems. We do this through theoretical, experimental, and simulation methods. The main focus of our recent work is the development of novel, acoustic radiation force impulse (ARFI)-based elasticity imaging methods to generate images of the mechanical properties of tissue, involving interdisciplinary research in ultrasonics and tissue biomechanics. We have access to the engineering interfaces of several commercial ultrasound systems which allows us to design, rapidly prototype, and experimentally demonstrate custom sequences to explore novel beamforming and imaging concepts. We employ FEM modeling methods to simulate the behavior of tissues during mechanical excitation, and we have integrated these tools with ultrasonic imaging modeling tools to simulate the ARFI imaging process. We maintain strong collaborations with the Duke University Medical Center where we work to translate our technologies to clinical practice. The ARFI imaging technologies we have developed have served as the basis for commercial imaging technologies that are now being used in clinics throughout the world.  We are also studying the risks and benefits of increasing acoustic output energy for specific clinical imaging scenarios, with the goal of improving ultrasonic image quality in the difficult-to-image patient.

Publications

Geoghegan, Rory, et al. “Methods of monitoring thermal ablation of soft tissue tumors - A comprehensive review.Medical Physics, vol. 49, no. 2, Feb. 2022, pp. 769–91. Epmc, doi:10.1002/mp.15439.

Caenen, Annette, et al. “Assessing cardiac stiffness using ultrasound shear wave elastography.Physics in Medicine and Biology, vol. 67, no. 2, Jan. 2022. Epmc, doi:10.1088/1361-6560/ac404d.

Knight, Anna E., et al. “Full Characterization of in vivo Muscle as an Elastic, Incompressible, Transversely Isotropic Material Using Ultrasonic Rotational 3D Shear Wave Elasticity Imaging.Ieee Trans Med Imaging, vol. 41, no. 1, Jan. 2022, pp. 133–44. Pubmed, doi:10.1109/TMI.2021.3106278.

Rouze, Ned C., et al. “Uniqueness of shear wave modeling in an incompressible, transversely isotropic (ITI) material.Physics in Medicine and Biology, vol. 66, no. 21, Oct. 2021. Epmc, doi:10.1088/1361-6560/ac287e.

Zhang, Bofeng, et al. “On the Relationship between Spatial Coherence and In Situ Pressure for Abdominal Imaging.Ultrasound in Medicine & Biology, vol. 47, no. 8, Aug. 2021, pp. 2310–20. Epmc, doi:10.1016/j.ultrasmedbio.2021.03.008.

Morris, D. Cody, et al. “Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging.Ultrasound Med Biol, vol. 47, no. 7, July 2021, pp. 1670–80. Pubmed, doi:10.1016/j.ultrasmedbio.2021.02.006.

Chan, Derek Y., et al. “Deep Convolutional Neural Networks for Displacement Estimation in ARFI Imaging.Ieee Trans Ultrason Ferroelectr Freq Control, vol. 68, no. 7, July 2021, pp. 2472–81. Pubmed, doi:10.1109/TUFFC.2021.3068377.

Jin, Felix Q., et al. “Semi-automated weak annotation for deep neural network skin thickness measurement.Ultrason Imaging, vol. 43, no. 4, July 2021, pp. 167–74. Pubmed, doi:10.1177/01617346211014138.