Towards a Multi-Parametric Quantitative Ultrasonic Tissue

Characterization

Roberto J. Lavarello

Laboratorio de Imágenes Médicas, Sección Electricidad y Electrónica

Pontificia Universidad Católica del Perú, San Miguel, Lima 32, Perú

Visión 2015, Universidad San Martín de Porres, Octubre 15, 2015

Example of B-mode of breast images from ultrasound

Constantini et al., JUM, 2006;25:649-659

Which one is malignant (if any)?

Example of B-mode of breast images from ultrasound

Irregular hypoechoic mass with angular margins and

no posterier acoustic features (BI-RADS - 5)

IDC

Hypoechoic mass with circumscribed margins

(BI-RADS - 3) Fibroadenoma

Example of B-mode of breast images from ultrasound

Constantini et al., JUM, 2006;25:649-659

Which one is malignant (if any)?

Example of B-mode of breast images from ultrasound

Hypoechoic mass with angular margins and no

posterier acoustic features (BI-RADS - 4)

Medullary Carcinoma

Irregular hypoechoic mass with spiculated margins and echogenic halo

(BI-RADS - 5) Benign Sclerotic Lesion

Theory

Backscatter Coefficient

Backscatter coefficient (BSC)The BSC (derived from the power spectrum of backscattered data) quantifies the frequency-dependent reflectivity of a medium.

Instrument-dependent (transmitted pulse, diffraction) and attenuation effects are compensated in the BSC estimation

process.

BSC estimation BSCs can be estimated from several adjacent gated RF

data segments using:

|Sm(f)|2 : power spectrum of a gated data line |S0(f)|2 : power spectrum from a reference plate A(f) : attenuation compensation function Gp = (kR2/2F) : focal gain of the transducer γ : pressure reflection coefficient of the reference plate F , A0 : transducer focal distance and surface area L : gate length Jn(·) : n-th order Bessel function

𝐵𝑆𝐶 ( 𝑓 )=2.17 ∙𝐷 (𝐺𝑝 ) ∙ 𝛾2𝐹 2

𝐴0𝐿∙⟨|𝑆𝑚 ( 𝑓 )|2 ⟩|𝑆0 ( 𝑓 )|2 𝐴 ( 𝑓 ) ,

𝐷 (𝐺𝑝)=|𝑒− 𝑖𝐺𝑝 [ 𝐽 0 (𝐺𝑝 )+𝑖 𝐽 1 (𝐺𝑝) ]−1|2 ,

BSC-derived parameter estimation

Two spectral parameters (ESD and EAC) were derived. ESD (in μm) – related to the typical size of scattering

structures. EAC (in mm-3) – proportional to the scatterer number

concentration. The parameter values were obtained by fitting the estimated

BSCs to the theoretical spherical Gaussian model:

L : gate length in mm f: frequency in MHz q: ratio of aperture radius to data block depth

𝐵𝑆𝐶 ( 𝑓 )=2.89 ∙𝐿 ∙𝑞 ∙𝐸𝐴𝐶 𝑓 4 ∙𝐸𝑆𝐷6

[ 1+0.67 ( 𝑓 ∙𝑞 ∙𝐸𝑆𝐷 )2 ]𝑒− 3.04 𝑓 2𝐸𝑆𝐷2

,

Application – Thyroid Cancer

Backscatter Coefficient

R. Lavarello, B. Ridgway, S. Sarwate, and M. Oelze, “Imaging of follicular variant papillary thyroid carcinoma in a rodent model using spectral-based quantitative ultrasound techniques,” in Proceedings of the IEEE International Symposium on Biomedical Imaging, pp. 732-735, 2013.

R. Lavarello, B. Ridgway, S. Sarwate and M. Oelze, “Characterization of thyroid cancer in mouse models using high-frequency quantitative ultrasound techniques,” Ultrasound in Medicine and Biology, vol. 39, no. 2, pp. 2333-2341, December 2013.

Motivation

There is a relatively high prevalence of thyroid nodules in the USA population.Prevalence estimated to be 2-6% with palpation, 19-25%

with ultrasound.

However, thyroid cancer has a low prevalence.Less than 0.1% prevalence according to the SEER

database.

Fine needle aspiration (FNA) biopsy remains the most sensitive and accurate test for thyroid nodule malignancy.Due to the statistics above, many FNA biopsies result in

benign diagnosis.

Motivation

Markers derived from conventional ultrasonic methods (echography, Doppler) do not provide sufficient diagnostic accuracy.Sensitivity, specificity and accuracy around 70-80% when

using multiple ultrasound parameters.

Further quantitative information can be derived from ultrasound data.Parameters derived from backscatter coefficients (BSCs)

have shown potential for cancer characterization.

Objective: To explore the usefulness of BSC-derived parameters for characterizing follicular variant papillary thyroid carcinoma (FV-PTC) in a rodent model.

Experimental methods

TRβPV/PV mice (Cheng’s Lab, Center for Cancer Research, NIH) were used as a model for FV-PTC.

13 mice (5 diseased, 8 control) were used in this study.

Ultrasound data were obtained from excised thyroids.In order to avoid effects from intervening tissues.

Data was collected using a 40 MHz, single element transducer.3 mm diameter, f/3

BSCs were obtained from data blocks of 0.5 by 0.5 mm.

Results – QUS images

B-mode (left), ESD (center) and EAC (right) images of a normal (top) and diseased (bottom) mice.

Results – QUS estimates

Scatter plot of ESD vs. EAC for all animals considered in this study.

Thyroid histology images

Normal thyroid FV-PTC

Follicle size

Benign : 40-100 μm

FV-PTC : 60-200 μm

Cells

Benign : ≈ 10 μm

FV-PTC : 15-24 μm

Thyroid histology images

Normal thyroid FV-PTC

Histology images at 40x amplification, showing a higher concentration of cells on the FV-PTC when compared to the normal case.

Results – Extended database

Discussion The estimated BSC-derived parameters were

consistent with the histological appearance of the studied thyroids.

ESD : the dominant structures were small malignant cells for the FV-PTC cases and large follicles for the normal cases.

EAC : the FV-PTC cases had a larger concentration of scatterers than the normal cases.

Statistically significant differences (p<0.05) were observed between the normal and FV-PTC thyroids.

A non-parametric Kruskal-Wallis test was used due to the small population size.

Conclusions

The preliminary experimental results obtained in this work suggest that spectral-based quantitative ultrasonic imaging has the potential for differentiating between normal and malignant thyroid tissues.

Further, these results suggest that quantitative ultrasonic imaging may be sensitive to the changes in tissue architecture resulting from thyroid cancer.

Theory

Attenuation Coefficient

Attenuation can be estimated using pulse-echo data using the spectral log difference (SLD) algorithm.

SLD estimates the attenuation coefficient from estimates of backscattered power spectra in two blocks (proximal and distal) within a region of interest.

Attenuation estimation

The ratio of the power spectra from the distal an proximal blocks can be expressed as

: The function describing the total attenuation effects.

: The backscatter coefficient.

: The mean diffraction correction coefficient

|2 : The power spectrum of the ultrasound data received from a region centered at depth

(1)

Spectral log difference method

By making the assumption that the effective scatterer size is constant so that the BSC varies in the form , the attenuation coefficient can be found from

Problem: How to evaluate the diffraction term in the equation above?

• Reference phantom method

• Analytical expression

Spectral log difference method

Pressure gain factor.: Transducer radius. Focal length.: Distance from the transducer to the sample.

In this work, the analytic expressions derived by Chen et al. were used for diffraction correction.

𝐷𝑠 (𝑟 ,𝜔 )≅ {0.46 ∙𝜋𝑎2

𝑟 2 exp [−0.46𝜋

∙𝐺𝑝2 ∙( 𝑓 𝑙𝑟 −1)

2] ,( 1+𝜋𝐺𝑝

)− 1

< 𝑟𝑓 𝑙

<( 1−𝜋𝐺𝑝

)−1

,

𝜋 𝑎2

𝑟2 ∙1.07 ∙[𝐺𝑝 ∙( 𝑓 𝑙𝑟 −1)]− 2

, otherwise ,

(3)

X.Chen, D. Phillips, K. Schwarz, J. Mottley and K. Parker “The measurement of backscatter from a broadband pulse-echo system - A new formulation,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 44, pp.515-526, 1997

Analytic diffraction correction function

Application – Thyroid Cancer

Attenuation Coefficient

O. Zenteno, B. Ridgway, S. Sarwate, M. Oelze, and R. Lavarello, “Ultrasonic attenuation imaging in a rodent thyroid cancer model,” in Proceedings of the IEEE International Ultrasonics Symposium, pp. 88-91, 2013.O. Zenteno, A. Luchies, M. Oelze, and R. Lavarello, “Improving the quality of attenuation imaging using full angular spatial compounding,” in Proceedings of the IEEE International Ultrasonics Symposium, pp. 2426-2429, 2014.

Experimental setup

A weakly focused (f/3) single element transducer with central frequency of 40 MHz and focal length of 9 mm was selected.

Extracted thyroid lobes were placed in a tank of 0.9% saline solution for ultrasound scanning using a micro positioning system.

Several ROIs of 0.6 by 0.6 mm where distributed over the sample with an overlap of 87.5%.

Histopatologic result blind ultrasound image analysis was performed to avoid biasing.

Sample attenuation images

Distribution of attenuation estimates

Mean/STD: 1.32 ± 0.20 dB/(MHz·cm)

P-values: • C-cell vs. all: p<= 0.0034• PTC vs. FV-PTC: p = 0.0176

Discussion

The estimated mean values are consistent with:• Independent insertion loss measurements obtained from

mice (1.19 ± 0.26 dB/MHz·cm).• Reports of attenuation in human thyroids (0.9

dB/MHz·cm to 1.8 dB/MHz·cm).

Attenuation coefficient slope estimates has potential for thyroid characterization.

• But high variance may compromise their diagnostic value…

Discussion – angular compounding

Discussion – angular compounding

Attenuation images from a two-region phantom. Background and inclussion attenuation coefficient slopes were measured to be 0.5 and 1 dB/cm/MHz, respectively. Estimation variance was reduced by 89% using angular compounding.

Application – Thyroid Cancer

Towards Human Studies

J. Rouyer, T. Cueva, T. Yamamoto, A. Portal and R. Lavarello, “In vivo estimation of attenuation and backscatter coefficients from human thyroids,” IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, submitted, 2015.J. Rouyer, T. Cueva, A. Portal, T. Yamamoto, and R. Lavarello, “Attenuation coefficient estimation of the healthy human thyroid in vivo,” Physics Procedia, vol. 70, pp. 1139-1143, 2015.T. Cueva, J. Rouyer, A. Portal, T. Yamamoto, and R. Lavarello, “Feasibility of quantitative backscatter imaging of human thyroids in vivo,” in Proceedings of the IEEE International Ultrasonics Symposium, accepted for publication, 2015.

Data Acquisition and Processing

Data Acquisition and Processing

Attenuation and Backscatter Coefficients

QUS Images in vivo

Conclusions

 Quantitative ultrasonic attenuation imaging allows some discrimination among four studied thyroid cancer animal models:

• c-cell adenoma from normal and malignant groups• Both malignant groups ( i.e., FV-PTC vs. PTC )

Attenuation coefficient slope estimates in conjunction with other techniques (i.e., BSC-based parameters, angular compounding) may have the potential to improve ultrasound-based tissue characterization.

Acknowledgements

M.Sc. In Digital Signal and Image Processing

Between 2010 and 2014, students from the M.Sc. Program in DSP from PUCP have:Performed 12 internships in universities and research centers in

Europe and North America (USA and Canada)Published more than 20 articles in indexed, peer-reviewed

proceedings of international conferences as first authorsPublished three publications in indexed, peer reviewed journals as

first authorsObtained more than 20 awards and scholarships from the PUCP

Graduate School, the Peruvian goverment, and the Fulbright program

DSP Program students – international activities

9th IEEE International Symposium on Biomedical Imaging, Barcelona, España, May 2012

DSP Program students – international activities

IEEE International Ultrasonics Symposium, Dresden, Alemania, October 2012

DSP Program students – international activities

12th International Tissue Elasticity Conference, Lingfield, Inglaterra, October 2013

DSP Program students – international activities

 11th IEEE EMBS Summer School on Biomedical Imaging, Esmerald Coast, Brittany, June 2014

DSP Program students – international activities

IEEE International Ultrasonics Symposium, Chicago, EE.UU., September 2014

Thanks!!!