Kathryn Nightingale

Overview:

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.

Positions:

Theo Pilkington Distinguished Professor of Biomedical Engineering

Biomedical Engineering
Pratt School of Engineering

Professor in the Department of Biomedical Engineering

Biomedical Engineering
Pratt School of Engineering

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Bass Fellow

Biomedical Engineering
Pratt School of Engineering

Education:

B.S. 1989

Duke University

Ph.D. 1997

Duke University

Grants:

A Patient-Adaptive, High MI Abdominal Scanner

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Co Investigator
Start Date
End Date

Improved ultrasound imaging using elevated acoustic output

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

Acoustic Radiation Force Based Hepatic Elasticity Quantification and Imaging

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

Acoustic Radiation Force Impulse (ARFI) Imaging of Cardiac Tissue

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Investigator
Start Date
End Date

Acoustic Radiation Force Impulse (ARFI) Imaging of Cardiac Tissue

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Investigator
Start Date
End Date

Publications:

Uniqueness of shear wave modeling in an incompressible, transversely isotropic (ITI) material.

Five material parameters are required to describe a transversely isotropic (TI) material including two Poisson's ratios that characterize the compressibility of the material. Both Poisson's ratios must be specified to model an incompressible, TI (ITI) material. However, a previous analysis of the procedure used to evaluate the incompressible limit in a two-dimensional (2D) space of Poisson's ratios has shown that elements of the stiffness tensor are not unique in this limit, and that an additional, fourth parameter is required to model these elements for an ITI material. In this study, we extend this analysis to the case of shear wave propagation in an ITI material. Shear wave signals are modeled using analytic Green's tensor methods to express the signals in terms of the phase velocity and polarization vectors of the shear horizontal (SH) and shear vertical (SV) propagation modes. In contrast to the previous result, the current analysis demonstrates that the phase velocity and polarization vectors are independent of the procedure used to evaluate the 2D limit of Poisson's ratios without the need to include an additional parameter. Thus, calculated shear wave signals are unique and can be used for comparison with experimental measurements to determine all three model parameters that characterize an ITI material.
Authors
Rouze, NC; Knight, AE; Nightingale, KR
MLA Citation
Rouze, Ned C., et al. “Uniqueness of shear wave modeling in an incompressible, transversely isotropic (ITI) material.Physics in Medicine and Biology, Sept. 2021. Epmc, doi:10.1088/1361-6560/ac287e.
URI
https://scholars.duke.edu/individual/pub1497537
PMID
34544067
Source
epmc
Published In
Physics in Medicine and Biology
Published Date
DOI
10.1088/1361-6560/ac287e

Full Characterization of in vivo Muscle as an Elastic, Incompressible, Transversely Isotropic Material using Ultrasonic Rotational 3D Shear Wave Elasticity Imaging.

Using a 3D rotational shear wave elasticity imaging (SWEI) setup, 3D shear wave data were acquired in the vastus lateralis of a healthy volunteer. The innate tilt between the transducer face and the muscle fibers results in the excitation of multiple shear wave modes, allowing for more complete characterization of muscle as an elastic, incompressible, transversely isotropic (ITI) material. The ability to measure both the shear vertical (SV) and shear horizontal (SH) wave speed allows for measurement of three independent parameters needed for full ITI material characterization: the longitudinal shear modulus μL, the transverse shear modulus μT, and the tensile anisotropy χE. Herein we develop and validate methodology to estimate these parameters and measure them in vivo, with μL = 5.77 ± 1.00 kPa, μT = 1.93 ± 0.41 kPa (giving shear anisotropy χμ = 2.11 ± 0.92), and χE = 4.67 ± 1.40 in a relaxed vastus lateralis muscle. We also demonstrate that 3D SWEI can be used to more accurately characterize muscle mechanical properties as compared to 2D SWEI.
Authors
Knight, AE; Trutna, CA; Rouze, NC; Hobson-Webb, LD; Caenen, A; Jin, FQ; Palmeri, ML; Nightingale, KR
MLA Citation
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. PP, Aug. 2021. Pubmed, doi:10.1109/TMI.2021.3106278.
URI
https://scholars.duke.edu/individual/pub1494620
PMID
34415833
Source
pubmed
Published In
Ieee Trans Med Imaging
Volume
PP
Published Date
DOI
10.1109/TMI.2021.3106278

On the Relationship between Spatial Coherence and In Situ Pressure for Abdominal Imaging.

Tissue harmonic signal quality has been shown to improve with elevated acoustic pressure. The peak rarefaction pressure (PRP) for a given transmit, however, is limited by the Food and Drug Administration guidelines for mechanical index. We have previously demonstrated that the mechanical index overestimates in situ PRP for tightly focused beams in vivo, due primarily to phase aberration. In this study, we evaluate two spatial coherence-based image quality metrics-short-lag spatial coherence and harmonic short-lag spatial coherence-as proxy estimates for phase aberration and assess their correlation with in situ PRP in simulations and experiments when imaging through abdominal body walls. We demonstrate strong correlation between both spatial coherence-based metrics and in situ PRP (R<sup>2</sup> = 0.77 for harmonic short-lag spatial coherence, R<sup>2</sup> = 0.67 for short-lag spatial coherence), an observation that could be leveraged in the future for patient-specific selection of acoustic output.
Authors
Zhang, B; Pinton, GF; Nightingale, KR
MLA Citation
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.
URI
https://scholars.duke.edu/individual/pub1482143
PMID
33985826
Source
epmc
Published In
Ultrasound in Medicine & Biology
Volume
47
Published Date
Start Page
2310
End Page
2320
DOI
10.1016/j.ultrasmedbio.2021.03.008

Semi-automated weak annotation for deep neural network skin thickness measurement.

Correctly calculating skin stiffness with ultrasound shear wave elastography techniques requires an accurate measurement of skin thickness. We developed and compared two algorithms, a thresholding method and a deep learning method, to measure skin thickness on ultrasound images. Here, we also present a framework for weakly annotating an unlabeled dataset in a time-effective manner to train the deep neural network. Segmentation labels for training were proposed using the thresholding method and validated with visual inspection by a human expert reader. We reduced decision ambiguity by only inspecting segmentations at the center A-line. This weak annotation approach facilitated validation of over 1000 segmentation labels in 2 hours. A lightweight deep neural network that segments entire 2D images was designed and trained on this weakly-labeled dataset. Averaged over six folds of cross-validation, segmentation accuracy was 57% for the thresholding method and 78% for the neural network. In particular, the network was better at finding the distal skin margin, which is the primary challenge for skin segmentation. Both algorithms have been made publicly available to aid future applications in skin characterization and elastography.
Authors
Jin, FQ; Knight, AE; Cardones, AR; Nightingale, KR; Palmeri, ML
MLA Citation
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.
URI
https://scholars.duke.edu/individual/pub1481738
PMID
33971769
Source
pubmed
Published In
Ultrason Imaging
Volume
43
Published Date
Start Page
167
End Page
174
DOI
10.1177/01617346211014138

Prostate Cancer Detection Using 3-D Shear Wave Elasticity Imaging.

Transrectal ultrasound (TRUS) B-mode imaging provides insufficient sensitivity and specificity for prostate cancer (PCa) targeting when used for biopsy guidance. Shear wave elasticity imaging (SWEI) is an elasticity imaging technique that has been commercially implemented and is sensitive and specific for PCa. We have developed a SWEI system capable of 3-D data acquisition using a dense acoustic radiation force (ARF) push approach that leads to enhanced shear wave signal-to-noise ratio compared with that of the commercially available SWEI systems and facilitates screening of the entire gland before biopsy. Additionally, we imaged and assessed 36 patients undergoing radical prostatectomy using 3-D SWEI and determined a shear wave speed threshold separating PCa from healthy prostate tissue with sensitivities and specificities akin to those for multiparametric magnetic resonance imaging fusion biopsy. The approach measured the mean shear wave speed in each prostate region to be 4.8 m/s (Young's modulus E = 69.1 kPa) in the peripheral zone, 5.3 m/s (E = 84.3 kPa) in the central gland and 6.0 m/s (E = 108.0 kPa) for PCa with statistically significant (p < 0.0001) differences among all regions. Three-dimensional SWEI receiver operating characteristic analyses identified a threshold of 5.6 m/s (E = 94.1 kPa) to separate PCa from healthy tissue with a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC) of 81%, 82%, 69%, 89% and 0.84, respectively. Additionally, a shear wave speed ratio was assessed to normalize for tissue compression and patient variability, which yielded a threshold of 1.11 to separate PCa from healthy prostate tissue and was accompanied by a substantial increase in specificity, PPV and AUC, where the sensitivity, specificity, PPV, NPV and AUC were 75%, 90%, 79%, 88% and 0.90, respectively. This work illustrates the feasibility of using 3-D SWEI data to detect and localize PCa and demonstrates the benefits of normalizing for applied compression during data acquisition for use in biopsy targeting studies.
Authors
Morris, DC; Chan, DY; Palmeri, ML; Polascik, TJ; Foo, W-C; Nightingale, KR
MLA Citation
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.
URI
https://scholars.duke.edu/individual/pub1478493
PMID
33832823
Source
pubmed
Published In
Ultrasound Med Biol
Volume
47
Published Date
Start Page
1670
End Page
1680
DOI
10.1016/j.ultrasmedbio.2021.02.006

Research Areas:

Acoustics
Active learning
Biomechanical Phenomena
Biomechanics
Blood
Blood-Brain Barrier
Catheter Ablation
Computer Simulation
Contrast Media
Diagnostic Imaging
Elasticity
Elasticity Imaging Techniques
Equipment Design
Fatty Liver
Finite Element Analysis
Image Processing, Computer-Assisted
Imaging, Three-Dimensional
Liver
Liver Cirrhosis, Experimental
Muscle, Skeletal
Palpation
Phantoms, Imaging
Prostate
Skin
Transducers
Ultrasonic Therapy
Ultrasonics
Ultrasonography
Ultrasonography, Interventional
Ultrasonography, Mammary
Urine
Viscosity
Water