Ultrasound in Med. & Biol., Vol. 40, No. 1, pp. 102–114, 2014Copyright � 2014 World Federation for Ultrasound in Medicine & Biology

Printed in the USA. All rights reserved0301-5629/$ - see front matter

/j.ultrasmedbio.2013.09.007

http://dx.doi.org/10.1016

d Original Contribution

IN VIVO THERMAL ABLATION MONITORING USING ULTRASOUND ECHODECORRELATION IMAGING

SWETHA SUBRAMANIAN,* STEVEN M. RUDICH,y AMEL ALQADAH,* CHANDRA PRIYA KARUNAKARAN,*MAREPALLI B. RAO,z and T. DOUGLAS MAST*

*Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA; yDepartment of Surgery, Wright StateUniversity, Dayton, Ohio, USA; and zDepartment of Environmental Health, University of Cincinnati, Cincinnati, Ohio, USA

(Received 6 March 2013; revised 3 September 2013; in final form 4 September 2013)

AWay, MUSA. E

Abstract—Previous work indicated that ultrasound echo decorrelation imaging can track and quantify changes inecho signals to predict thermal damage during in vitro radiofrequency ablation (RFA). In the in vivo studies re-ported here, the feasibility of using echo decorrelation imaging as a treatment monitoring tool was assessed.RFAwas performed on normal swine liver (N 5 5), and ultrasound ablation using image-ablate arrays was per-formed on rabbit liver implanted with VX2 tumors (N 5 2). Echo decorrelation and integrated backscatterwere computed from Hilbert transformed pulse-echo data acquired during RFA and ultrasound ablation treat-ments. Receiver operating characteristic (ROC) curves were employed to assess the ability of echo decorrelationimaging and integrated backscatter to predict ablation. Area under the ROC curves (AUROC) was determined forRFA and ultrasound ablation using echo decorrelation imaging. Ablation was predicted more accurately usingecho decorrelation imaging (AUROC5 0.832 and 0.776 for RFA and ultrasound ablation, respectively) than usingintegrated backscatter (AUROC5 0.734 and 0.494). (E-mail: doug.mast@uc.edu) � 2014World Federation forUltrasound in Medicine & Biology.

KeyWords: Echo decorrelation imaging, Therapy monitoring, Bulk ultrasound ablation, Radiofrequency ablation.

INTRODUCTION

Thermal ablation is the treatment of choice for unresect-able tumors within the liver, kidneys and other organs(Dupuy et al. 2000; Gervais et al. 2005). Thermalablation involves application of energy at the tumorsite, which causes heating in the tissue and therebyresults in coagulative necrosis of the tumor. Commonthermal ablation methods include radiofrequencyablation (RFA), ultrasound ablation, laser ablation andmicrowave ablation (Caspani et al. 2010; Kennedy et al.2004; Murakami et al. 1995; Rhim and Dodd 1999).RFA has been reported to be effective for the treatmentof unresectable liver tumors clinically (Curley et al.1999; Solbiati et al. 2001; Tateishi et al. 2005), offeringseveral advantages over surgical resection, such asreduced morbidity, cost and hospital stays (Livraghiet al. 2008). Ultrasound ablation methods, includinghigh-intensity focused ultrasound and bulk ultrasound

ddress correspondence to: T. Douglas Mast, 231 Albert SabinL 0586, University of Cincinnati, Cincinnati, OH 45267-0586,-mail: doug.mast@uc.edu

102

ablation, have also been found to have potential for clin-ical applications (Illing et al. 2005; Mast et al. 2005,2011; Yang et al. 1991).

Treatment monitoring and probe placement forthermal ablation can be performed using magnetic reso-nance imaging (MRI) (Hynynen and McDannold 2004),ultrasound (Chiou et al. 2007) or X-ray computed tomog-raphy (Dupuy et al. 2000). Although MRI has been re-ported to have great potential for monitoring thermalablation, being capable of accurate temperature moni-toring and control (Arora et al. 2005; Hynynen andMcDannold 2004; McDannold 2005; Smith et al.2001), use of MRI increases treatment complexity andcost and additionally requires use of MR ablation-compatible ablation tools (Boaz et al. 1998; Vigen et al.2006).

Ultrasound imaging offers a real-time, portable andinexpensive alternative. Ultrasound imaging is currentlyused clinically in RFA for probe placement and treatmentguidance (Chiou et al. 2007). However, ultrasoundimaging by itself offers limited treatment monitoringcapability, tracking only changes in the image brightnessor tissue echogenicity. Often tissue necrosis is not

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 103

visualized because of low contrast between the ablatedand unablated regions or artifacts caused by microbubbleformation at the ablation site, resulting in over- orunder-prediction of treated regions (Cha et al. 2000;Leyendecker et al. 2002; Solbiati et al. 1999).

Methods tracking deformation of ultrasound echoes,such as echo strain imaging (Souchon et al. 2005), elas-tography (Varghese et al. 2002) and acoustic radiationforce imaging (Fahey et al. 2006) have been found tohave potential for treatment monitoring. However, thesemethods are sensitive to errors caused by the formationof microbubble clouds at the ablation site (Leyendeckeret al. 2002; Solbiati et al. 1999) and echo decorrelationcaused by tissue motion, bubble activity and othertissue changes (Chandrasekhar et al. 2006; Miller et al.2002; Varghese et al. 2004).

Echo decorrelation imaging is a real-time pulse-echo method that potentially uses these degradations insignals to map thermal ablation. Heat-induced tissuechanges during thermal ablation are monitored bytracking millisecond-scale changes in echo signals, quan-tified by the local signal decorrelation. These changes inthe echo signals are tracked over the duration of a thermalablation treatment to produce a cumulative echo decorre-lation map. Echo decorrelation imaging has been re-ported to have the potential for predicting tissuedamage during RFA of ex vivo tissue (Mast et al. 2008).However, echo decorrelation imaging is more chal-lenging in vivo because of potential decorrelation arti-facts caused by respiratory motion, cardiac motion andperfusion.

In this article, echo decorrelation imaging is testedin vivo for both RFA and ultrasound ablation treatments.The predictive ability of echo decorrelation imaging is as-sessed by quantitatively comparing echo decorrelationwith gross tissue histology using receiver operating char-acteristic (ROC) curves. For comparison, the integratedultrasound backscatter is also computed (Arthur et al.2005; Zhong et al. 2007), and its predictive ability isassessed in a manner similar to that used to assess echodecorrelation imaging (Mast et al. 2008).

METHODS

Echo decorrelation imaging was tested using pulse-echo data recorded during in vivo RFA and ultrasoundablation experiments. Methods used for the experiments,image formation and data analysis are detailed below forRFA experiments performed in porcine liver and forultrasound ablation experiments performed usingimage-ablate arrays in rabbit liver with a VX2 tumormodel. All animal experiments were performed accord-ing to protocols approved by the University of CincinnatiInstitutional Animal Care and Use Committee.

TheoryThe echo decorrelation imaging algorithm previ-

ously described in Mast et al. (2008) and Mast andSubramanian (2010) is implemented here with someminor changes. Let the function p(r, t) represent apulse-echo frame consisting of a collection of beam-formed echo signals in complex radiofrequency (Hil-bert-transformed) form acquired at time t, where r isthe spatial position vector within the image plane. Thefunction p(r, t1 t) represents a pulse-echo image frameacquired at a later time t 1 t, where t is the inter-frametime.

A spatiotemporal cross-correlation functionbetween the two sequential complex pulse-echo imageframes separated by time t is defined as

R01ðr; tÞ5 hpðr; tÞp�ðr; t1tÞi; (1)

where h$i represents a 2-D convolution with a Gaussianmask

Df ðrÞ

E5 f ðrÞ5e2jrj

2=2s2 ; (2)

where s is a width parameter. Similarly, the autocorrela-tion functions R00(r, t) and R11(r, t) are defined here as

R00ðr; tÞ5���pðr; tÞ��2�

R11ðr; tÞ5���pðr; t1tÞ��2� (3)

respectively, which can be regarded as maps of integratedbackscattered energies at times t and t1t. An integratedbackscatter term can thus be defined as

bðr; tÞ5ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiR00ðr; tÞR11ðr; tÞ

p: (4)

An echo decorrelation map is then defined as

Dðr; tÞ5 2b2ðr; tÞ2��R01ðr; tÞ

��2b2ðr; tÞ1b2ðtÞ

; (5)

where the function b2ðtÞ represents the spatial mean valueof b2(r, t) from eqn (4). The echo decorrelation functionwas normalized by this denominator because normaliza-tion by b2(r, t) alonewas found to cause artifactually highdecorrelation in regions of low echogenicity, whereasnormalization by the function b2ðtÞ caused artifacts inregions of high echogenicity (Mast et al. 2008). Thenormalization in eqn (5) results in a more uniform echodecorrelation map. The resulting echo decorrelationmap is zero in regions where the image is unchangedand maximum in regions where local echo changes aregreatest. Finally, because the echo decorrelation mapdefined by eqn (5) also varies stochastically in time,a temporal running average was employed to provide

104 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

a better estimate of local changes in the scatteringmedium (Mast et al. 2008). The temporal running averageemployed is given by

D r; tið Þ5 12εð ÞD r; ti21ð Þ1εD r; tið Þ; (6)

where ti is the time of the current (ith) echo decorrelationimage frame, and ε is a user-defined parameter (0 , ε ,1) that determines the effective length of temporalaveraging.

Echo decorrelation imaging implementationThe echo decorrelation algorithm described above

was implemented on the pulse-echo data acquired duringRFA and ultrasound ablation. Ultrasound imaging wasperformed with the Iris 2 ultrasound imaging and ablationsystem (Guided Therapy Systems, Mesa, AZ, USA)(Barthe et al. 2004). Throughout each treatment, echosignals were recorded from the Iris system using a 14-bit, PC-based A/D converter (CompuScope CS 14200,Gage Applied Technologies, Montreal, QC, Canada) ata sampling rate of 33.3 MHz and stored. The acquiredechoes were then processed in MATLAB (The Math-Works, Natick, MA, USA) to form B-mode, integratedbackscatter and echo decorrelation images as describedbelow. For each recorded pulse-echo frame pair, echosignals were bandpass filtered using the Gaussian filterdefined by

Gðf Þ5 e2ðf2f0Þ2

2a2 ; (7)

where f0 is the center frequency, and a is the bandwidth.This filter also implicitly performs a Hilbert transform toform analytic echo signals. B-mode (brightness mode)images were obtained by logarithmically scaling theecho envelopes (absolute value of the complex analyticecho signals) jp(r, t)j with a displayed dynamic rangeof 60 dB.

To compute echo decorrelation and integratedbackscatter images, the cross-correlation and autocorre-lation functions R01ðr; tÞ, R00ðr; tÞ and R11ðr; tÞ werecomputed using eqns (1) and (3). Spatial integrationwas implemented with eqn (2), using a Gaussianwindow with width parameter s 5 2.5 mm. The time-and position-dependent echo decorrelation was thencomputed using eqn (5) and smoothed by the runningaverage of eqn (6) with ε 5 0.05. To form cumulativeecho decorrelation maps, the temporal maximum ofthe resulting echo decorrelation was recorded at eachpixel location.

To form integrated backscattered images, the inte-grated backscatter computed using eqn (4) was smoothedtemporally using a running-average smoothing filtersimilar to eqn (6). The relative integrated backscatter

was defined as the decibel-scaled ratio between the cumu-lative integrated backscatter and the integrated back-scatter (IBS) computed before treatment (Mast et al.2008)

IBSðr; tÞ5 10$log10

�bðr; tÞbðr; 0Þ

�; (8)

where b is the integrated backscatter function defined byeqn (4). Relative integrated backscatter maps wereformed from the temporal maxima of IBS(r, t) at eachpixel location. Hybrid integrated backscatter maps wereformed for display by overlaying these relative integratedbackscatter maps on the B-mode image frames.

Radiofrequency ablationRadiofrequency ablation experiments were per-

formed within a normal porcine liver in vivo for N55treatments. The experimental setup for the treatments isillustrated in Figure 1(a). The swine was anesthetized,and its liver was exposed via laparotomy. RFA was per-formed using a 2.0-cm RF needle electrode (LaVeen,Boston Scientific, Boston, MA, USA), which was insertedinto the liver. Treatments were performed in the left,medial and right lobes of the liver. Two grounding padswere placed on the back of the pig. A low-noise 1-mmthermocouple (GKMQSS, Omega Engineering, Stam-ford, CT, USA) was also inserted near the RF needle elec-trode to record local tissue temperature during treatment.For each treatment, the RF needle electrodewas driven byan RF generator (RF 2000B, Radio Therapeutics, Moun-tain View, CA, USA). The power supplied and time dura-tion used for all RFA treatments are outlined in Table 1.

A 192-element, 7-MHz linear ultrasound array (L7,Guided Therapy Systems) was positioned on the porcineliver such that its image plane included the RF needleelectrode and the thermocouple. The ultrasound arrayposition on the liver was marked using an electrocauterydevice. In each acquisition, 384 echo signals, comprisinga pulse-echo image frame pair, were acquired at intervalsof 0.85 6 0.05 s. These echoes were then filtered by theGaussian bandpass filter from eqn (7) with a centerfrequency of 7.36 MHz and a bandwidth of 1 MHz, re-sulting in a pair of complex analytic pulse-echo imageframes with dimensions 42.2 3 30.5 mm2, separated byan inter-frame time of 19.6 ms (inverse of the systemframe rate, 51 Hz). For treatment 1, pre-treatment data(ultrasound imaging only) were acquired immediatelybefore RFA treatment at the same position. To compareecho decorrelation images with and without ablationtreatment, the pre-treatment data were analyzed overa duration equal to the subsequent RFA treatment.

After all treatments were performed, the liver wasexcised and the animal was sacrificed. To maintain tissue

Fig. 1. Experimental configurations. (a) Radiofrequency abla-tion of porcine liver. The ultrasound probe is shown resting onthe liver, with the thermocouple and radiofrequency probeinserted into the liver in the ultrasound image. (b) Ultrasoundablation of rabbit liver, with the probe assembly resting on

the liver.

Table 1. Exposure conditions for N 5 5 in vivo RFAtreatments performed in porcine liver

Treatment Liver lobe Power (W) Duration (s)

1 Left 60 402 Medial 31 1703 Right 25 1754 Left 25 3435 Right 26 165

0 20 40 60 80 100 120 140 1600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Time (s)

Co

rrel

atio

n C

oef

fici

ent

Fig. 2. Representative Pearson product-moment correlationcoefficient of the radiofrequency echo data within the region

of interest for treatment 3.

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 105

shape for accurate registration with B-mode images, theexcised liver lobes were frozen in a 280�C freezer andthen sliced parallel to the image plane as indicated bythe electrocautery marks. Tissue sections were scannedon a flatbed scanner (CanoScan 8800F, Canon, Tokyo,

Japan) at 800-dpi (32-mm) resolution. For direct compar-ison with echo decorrelation and integrated backscatterimages in each case, scanned tissue sections wereoriented and registered to ultrasound images using tissueboundaries and visible probe tracks as spatial references.To test the utility of echo decorrelation and integratedbackscatter imaging in predicting ablation, the treatedregion was segmented based on gross discoloration ofthe tissue (ImageJ, National Institutes of Health, Be-thesda, MD, USA), with all pixels within the lesionboundary defined as ablated and the remainder definedas unablated.

To assess the effect of tissue motion on echo decor-relation imaging, echo decorrelation images were recom-puted using motion gating. To this end, a 5 3 5-mm2

region of interest (ROI) was selected for each trial froman unablated region where minimal echo decorrelationwas observed. The first frames within all acquired framepairs were selected for analysis. The Pearson product-moment correlation was used to compute the correlationcoefficient of the echo signals within the ROI for all theselected frames sequentially. Figure 2 is a representativeplot of Pearson product-moment correlation performedbetween echoes within the ROI for sequentially selectedframes separated by 0.856 0.05 s. The temporal intervalbetween two peaks of the correlation coefficient plot was

Table 2. Exposure conditions for N 5 2 in vivoultrasound ablation experiments performed in rabbit liver

with VX2 tumor

Treatment Liver lobe Intensity (W/cm2) Duration (s)

4 Left 38.5 956 Right 38.5 120

106 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

found to be�6 s. The correlation coefficient plot suggeststhat the pulse-echo frames are correlated for a portion ofthe respiratory cycle and severely uncorrelated for theremainder.

To perform motion gating, echo decorrelation wascomputed using only frame pairs containing selectedframes with correlation coefficients.0.6. This thresholdchoice omitted only the frames that were severely uncor-related because of substantial tissue motion. Similar tothe computations of echo decorrelation without motiongating, a temporal running average was performed usingeqn (6), and cumulative echo decorrelation maps wereformed from the temporal-maximum echo decorrelationat each pixel location.

To assess the ability of echo decorrelation to delin-eate between ablated and unablated regions, paired t-testswas performed between the mean (spatially averaged)cumulative echo decorrelations within the ablated andunablated regions at the end of treatment, with andwithout motion gating. Differences in echo decorrelationwere assessed for statistical significance using the crite-rion p , 0.05. One-tailed p-values were employed toassess the significance of any increase in echo decorrela-tion caused by tissue ablation, as well as any decrease inecho decorrelation caused by motion gating.

The time-dependent measured echo decorrelationduring the RFA treatments was also compared with thetemperature simultaneously measured by thermocouple.As the precise location of the thermocouple was notknown in all cases, for comparison of tissue temperaturewith echo decorrelation, the spatial maximum of therunning-average echo decorrelation was determined ateach time point. The spatial maximum of the echo decor-relation was then temporally interpolated to synchronizewith the temperature recordings from the thermocouple.To determine if echo decorrelation is correlated withtissue temperature, the Pearson correlation coefficientwas computed between the measured temperature andthe log-scaled, spatial-maximum echo decorrelation,using all temporal data points from the five trials. Whenstatistical significance of the correlation between echodecorrelation and tissue temperature was tested, thenumber of independent samples was conservatively esti-mated as the number of temporal data points multipliedby the running-average parameter ε5 0.05 from eqn (6).

Ultrasound ablationUltrasound ablation and imaging were performed

using a 3-mm-diameter, 32-element miniaturizedimage-ablate array probe on a rabbit liver with implantedVX2 tumors for N 5 2 treatments, within a series ofin vivo experiments described previously (Mast et al.2011). VX2 tumor fragments were implanted in separateliver lobes 11 d before the experiment was performed. At

the time of the ablation experiments, the tumors hadgrown to about 1 cm in diameter.

For the ablation experiments, the rabbit was anesthe-tized and its liver exposed. The image-ablate array wasinserted into a balloon through which cooling waterwas circulated. The probe assembly was placed on theliver lobe surface proximal to the VX2 tumor and fixedby a 3-D positioning arm, as illustrated in Figure 1(b).Acoustic coupling was implemented between the probeand liver surface using phosphate-buffered saline andconfirmed using ultrasound imaging from the image-ablate array. Continuous-wave, 4.8-MHz ultrasoundwas fired from the entire 32-element array in an unfo-cused beam with spatial-average, temporal-averageintensity 38.5 W/cm2. Treatment cycles, consisting of8.5 s continuous-wave sonication followed by 1.5 s ofimaging by the same array, were repeated for exposuredurations of 1.5–2.0 min. The exposure conditions usedfor the ultrasound ablation treatments are outlined inTable 2.

In each acquisition 32 echo signals were acquired ata frame rate of 16 Hz. The echoes were then filtered by theGaussian bandpass filter from eqn (7) with a centerfrequency of 4.8 MHz and a bandwidth of 0.3 MHz toform complex analytic echo signals. To assess the effectof disturbances such as tissue motion on echo decor-relation imaging, pre-treatment pulse-echo data weresimilarly acquired immediately before each ablation treat-ment, at the same probe position. Cumulative echo decor-relation images were computed from pre-treatment datawith durations matching the corresponding ablationtreatments.

Echo decorrelation and integrated backscatter werecomputed using eqns (4) and (5) from consecutiveframes of pulse-echo data, with an inter-frame time of60 ms, obtained during the 1.5-s quiescent periodsbetween each sonication cycle. A temporal runningaverage was performed using eqn (6).

After the treatments were completed, the animalwas sacrificed. The liver was then excised, sectionedalong the image plane at the array location and stainedwith triphenyl tetrazolium chloride (TTC) vital stain.Tissue sections were scanned and registered in a mannersimilar to the RFA treatments. Tissue sections weresegmented, mapping regions of treatment based on the

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 107

local TTC uptake and registered to ultrasound imagesusing visible tissue boundaries and anatomic landmarks.

To test whether echo decorrelation imaging coulddelineate between the ablated and unablated regions inthe ultrasound ablation experiments, a paired t-test wasperformed between mean cumulative echo decorrelationvalues for the ablated and unablated regions (N 5 2trials).

Receiver operating curve analysisTo test prediction of ablation by echo decorrelation

imaging and integrated backscatter, for both RFA andultrasound ablation, ROC curves were employed(Krzanowski and Hand 2009; Mast et al. 2008). In thisanalysis, treatment outcomes were predicted using echodecorrelation and integrated backscatter thresholds, sothat all the spatial points exceeding a threshold werepredicted to be ablated, and the remainder, unablated.By pixel-by-pixel comparison of cumulative echo decor-relation and integrated backscatter images with corre-sponding segmented tissue maps, prediction successwas determined for each pixel as a function of thethreshold. ROC curves, defined as the true-positive rate(sensitivity) versus the false-positive rate (1 2 speci-ficity), were then plotted for prediction of ablation.Area under the ROC curve (AUROC) was determinedto assess the utility of echo decorrelation and integratedbackscatter in predicting ablation. An AUROC of 1 indi-cates that the treated region was classified perfectly,whereas an AUROC of 0.5 means that the classificationwas no better than chance.

The positive (PPV) and negative (NPV) predictivevalues were computed for all decorrelation and integratedbackscatter thresholds. The PPV indicates the proportionof positive outcomes (local tissue ablation) that werecorrectly classified, whereas the NPV indicates theproportion of negative outcomes (tissue locally unab-lated) that were correctly classified. Optimal decorrela-tion and integrated backscatter thresholds for predictionof local ablation were selected by using the thresholdsyielding equal PPVs and NPVs.

Assessment of prediction success was performed forboth RFA and ultrasound ablation by testing the signifi-cance of the AUROC statistic using a general model forthe AUROC standard error (Hanley and McNeil 1982).In this analysis, effective sample sizes for each treatmentoutcome were conservatively estimated from theGaussian window size used for the computation of echodecorrelation and integrated backscatter. For this calcula-tion, the windows were considered independent when thespatial cross-correlation coefficient of two Gaussianwindows, as defined in eqn (2), was below 0.5. Thedistance between window centers for a correlation coeffi-cient of 0.5 is 2

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi2logð2Þsp

. The effective number of treat-

ment outcomes in each spatial region (ablated andunablated) was determined based on the maximumhexagonal packing density, which is given by p=

ffiffiffiffiffi12

punit-diameter circles per unit-area rectangle. Similarly,to compare predictions using echo decorrelation withthose using integrated backscatter, the significance ofAUROC differences between echo decorrelation and inte-grated backscatter was also computed for both RFA andultrasound ablation.

RESULTS

In Figure 3 are hybrid echo decorrelation maps,comprising echo decorrelation and B-mode images, forall (N5 5) in vivo RFA treatments. For each case, hybridecho decorrelation maps at the end of RFA treatment atthe same location are provided. Similar hybrid imagesfor integrated backscatter at the end of RFA treatmentare provided as well. Also provided are the correspondingsegmented tissue sections, with the segmented ablatedregions enclosed by dashed black lines. Qualitatively,higher echo decorrelation and integrated backscatter isobserved in the ablated regions, whereas relatively lowerecho decorrelation and integrated backscatter is observedin the unablated regions.

The temporal evolution of echo decorrelation duringRFA treatment is illustrated by Figure 4. Figure 4(a) is thehybrid echo decorrelation map plotted at 40 s into pre-treatment, matching the duration of RFA treatment 1. InFigure 4(b–f) are the hybrid echo decorrelation mapsplotted after 20, 25, 30, 35 and 40 s of RFA treatment,in the same image plane where the pre-treatment datawere acquired. Although echo decorrelation was minimalin the ablated region, echo decorrelation caused by tissuemotion was elevated near the liver lobe boundaries duringpre-treatment. As RFA treatment progressed, echo decor-relation increased in the ablated region. Echo decorrela-tion caused by tissue motion similarly increased;however, it was largely concentrated at the liver lobeboundaries.

For the ultrasound ablation trials, the hybrid echodecorrelation maps formed during at the end of pre-treatment imaging and at the end of ultrasound ablationtreatment are provided in Figure 5. Also provided arethe corresponding segmented tissue sections, withsegmented ablated regions enclosed by dashed blacklines. The B-mode ultrasound images, produced duringultrasound ablation using the 32-element image-ablatearray, were of low resolution compared with thoseproduced with the 192-element L7 diagnostic arrayused for RFA experiments. At the end of pre-treatmentimaging, some echo decorrelation is observed in theecho decorrelation images, possibly as a result of tissuemotion. Similarly, Figure 6 provides the hybrid

Fig. 3. Hybrid echo decorrelation and integrated backscatter images for all radiofrequency ablation treatments. (a) Echodecorrelation at end of treatment. (b) Integrated backscatter at end of treatment. (c) Tissue sections corresponding to theultrasound image plane, with the ablated region enclosed by dashed black lines. Results for treatments 1 through 5 are

illustrated in rows (1) through (5), respectively.

108 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

Fig. 4. Hybrid echo decorrelation images for radiofrequency ablation treatment 1. (a) After 40 s of pre-treatment. (b)After 20 s of treatment. (c) After 25 s of treatment. (d) After 30 s of treatment. (e) After 35 s of treatment. (f) After

40 s of treatment.

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 109

integrated backscatter maps formed at the end of pre-treatment imaging and at the end of each ultrasoundablation treatment, along with corresponding segmentedtissue sections.

Mean cumulative echo decorrelations in the ablatedand unablated regions for all RFA treatments are outlinedin Table 3. Figure 7(a) illustrates the means and standarddeviations of the cumulative echo decorrelation in theablated and unablated regions of the tissue at the endof RFA treatment, with and without motion gating.For RFA, the mean cumulative echo decorrelation in theablated region (0.1032 6 0.0624) was significantlygreater than that in the unablated region (0.0231 60.0198) at the end of treatment (t 5 3.3497, p 50.0143). With motion gating, the mean echo decorrelationin the unablated region (0.0129 6 0.0109) at the end oftreatment was significantly reduced (t 5 2.5249, p 50.0325). The mean cumulative echo decorrelation in theablated region at the end of treatment was also signifi-cantly reduced (t 5 2.7072, p 5 0.0268) relative to theungated case (0.05456 0.0308). Still, after motion gating,the mean cumulative echo decorrelation in the ablatedregion was significantly greater than that in the unablatedregion (t 5 4.0148, p 5 0.008), with a greater relativedifference compared with the non-gated case.

For the RFA case for which pre-treatment imageswere available, the mean cumulative echo decorrelationin the ablated region at the end of treatment (0.0654)was substantially greater than the mean cumulativeecho decorrelation (0.0209) in the same region after 40s of pre-treatment imaging. The mean cumulative echodecorrelation in the unablated region at the end of treat-ment (0.0174) was only marginally greater than themean cumulative echo decorrelation (0.0161) after pre-treatment imaging of the same 40-s duration.

For ultrasound ablation, Figure 7(b) illustrates themeans and standard deviations of the cumulative echo de-correlation in the ablated and unablated tissue regions atthe end of pre-treatment imaging and at the end of abla-tion treatment for each case. The mean cumulative echodecorrelations in the ablated and unablated regions ofthe tissue for all treatments are outlined in Table 4.Similar to the RFA trials, the mean cumulative echo de-correlation at the end of ablation treatment was greaterin the ablated region (0.06376 0.0048) than in the unab-lated region (0.0333 6 0.0026), yielding a statisticallysignificant difference (t 5 19.46, p 5 0.0163). Atthe end of pre-treatment imaging, the mean cumulativeecho decorrelation within the ablated region (0.0445 60.0300) was greater than that in the unablated region

Fig. 5. Echo decorrelation images for all ultrasound treatments. (a) End of pre-treatment imaging. (b) End of the ultra-sound ablation treatment. (c) Tissue sections corresponding to the ultrasound image plane, with the ablated region en-

closed by dashed black lines. Results for treatments 4 and 6 are provided in rows (1) and (2), respectively.

110 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

(0.0176 6 0.0079), yielding a statistically insignificantdifference (t 5 1.7228, p 5 0.1674). The mean cumula-tive echo decorrelation at the end of treatment wasgreater in the ablated region compared with the meancumulative echo decorrelation in the same region afterpre-treatment imaging of matching duration, but thisdifference was not statistically significant (t 5 1.0743,p 5 0.2386). Similarly, the mean echo decorrelation inthe unablated region at the end of treatment was notsignificantly higher than that at the end of pre-treatment imaging (t 5 4.2015, p 5 0.0744).

Computed ROC curves for the prediction of ablationare provided for both the RFA and ultrasound ablationexperiments in Figure 8. The AUROC for RFA exposureswas 0.8328 using echo decorrelation (p , 10213) and0.7336 using integrated backscatter (p 5 4.7 3 1029)for prediction of ablation. The AUROC for ultrasoundexposures was 0.7761 using echo decorrelation (p 50.0047) and 0.4944 using integrated backscatter (p 50.5156) for prediction of ablation. Although these AUROCstatistics indicate comparable prediction performance forboth sets of experiments for echo decorrelation imaging,statistical significance for the ultrasound exposures islower because of the smaller effective sample size, witha conservative estimate of 19 independent predictions oftreatment outcome, compared with 214 independentpredictions for RFA exposures. AUROC values were

significantly higher for ablation prediction using echo de-correlation imaging than for prediction using integratedbackscatter, for both RFA (p 5 0.0020) and ultrasoundablation (p 5 0.0041) cases.

Optimal echo decorrelation thresholds for ablationprediction, corresponding to equal PPVs and NPVs,were 0.1555 for RFA and 0.0096 for ultrasound ablation.The PPVand NPVat the optimum decorrelation thresholdwere 0.750 for RFA and 0.730 for ultrasound ablation.Optimal integrated backscatter thresholds for ablationprediction were 14.80 dB for RFA and 7.92 dB for ultra-sound ablation. The corresponding PPV and NPV at theoptimal integrated backscatter thresholds were 0.730for RFA and 0.318 for ultrasound ablation.

Figure 9 is a scatter plot of the thermocouple-measured tissue temperature versus the spatial-maximum,running-average, log-scaled echo decorrelation, measuredsimultaneously throughout the RFA treatments. Thisscatter plot indicates a non-linear relationship betweenecho decorrelation and tissue temperature. Although thereis an apparent monotonically increasing relationshipbetween echo decorrelation and tissue temperature, therate of increase in echo decorrelation is not the same forall treatments. However, the instantaneous tissue temp-erature and echo decorrelation were correlated across alltreatments with high statistical significance (r 5 0.3227,p 5 5.19 3 10223). The modest correlation between

Fig. 6. Integrated backscatter images for all ultrasound treatments. (a) End of pre-treatment imaging. (b) End of the ultra-sound treatment. (c) Tissue sections corresponding to the ultrasound image plane, with the ablated region enclosed by

dashed black lines. Results for treatment numbers 4 and 6 are provided in rows (1) and (2), respectively.

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 111

echodecorrelation and temperaturemaybepartially causedby the lack of precise knowledge of the thermocouple loca-tion. Also, non-thermal factors such as gas activity andtissue motion may cause substantial echo decorrelation,complicating any relationship between local echo decorre-lation and tissue temperature.

DISCUSSION

Echo decorrelation imaging has previously been re-ported to have potential for monitoring thermal ablationin vitro (Mast et al. 2008). The feasibility of ultrasoundecho decorrelation imaging as a treatment monitoring

Table 3. Results for N 5 5 in vivo radiofrequencyablation treatments in porcine liver

Treatment

Mean cumulative echo decorrelation

End treatment End treatment (gated)

Unablated Ablated Unablated Ablated

1 0.0174 0.0654 0.0096 0.04072 0.0511 0.1054 0.0269 0.07053 0.0026 0.0550 0.0017 0.04574 0.0094 0.0808 0.0045 0.01755 0.0351 0.2095 0.0217 0.0979

Mean 0.0231 0.1032 0.0129 0.0545Standard deviation 0.0198 0.0624 0.0109 0.0308

tool for in vivo thermal ablation and its possible limita-tions are discussed below.

Possible causes of echo decorrelation during thermalablation may include the structural changes, vaporizationand dissolution of gas that occur in tissue during coagula-tive necrosis. In the case of ultrasound ablation, anotherpossible source of echo decorrelation is bubble activityassociated with acoustic cavitation. Performing thermalablation in vivo introduces possible sources of artifactualecho decorrelation, including unsteady perfusion, tissuemotion and respiration-induced tissue motion.

Respiratory tissue motion is an important sourceof error for ultrasound-based treatment monitoringmethods, including echo decorrelation imaging. The rela-tive importance of tissue motion as a source of artifactualecho decorrelation can be assessed from the motiongating test reported here. For thermal monitoring ofin vivo RFA, motion gating significantly reduced themean cumulative echo decorrelation in both ablated andunablated regions. However, with or without motiongating, the mean cumulative echo decorrelation in theablated region was significantly greater than that in theunablated region. This suggests that for the imagingconfiguration employed here, with pulse-echo imageframes separated by about 20 ms, ablation-inducedecho decorrelation dominated any artifactual decorrela-tion caused by tissue motion alone. Uncertainty caused

a

b

Fig. 7. Bar graphs illustrating the means and standard devia-tions of cumulative echo decorrelation in ablated and unablatedregions. (a) Decorrelation at the end of radiofrequency ablationtreatment, with and without motion gating. (b) Decorrelation forultrasound ablation, at the end of pre-treatment imaging and at

the end of ultrasound ablation treatment.

a

b

Fig. 8. Receiver operating characteristic curves for accuracy ofablation prediction: (a) radiofrequency ablation; (b) ultrasound

112 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

by tissue motion could be reduced by use of a higherimaging frame rate, potentially eliminating the need formotion gating.

Table 4. Results for N 5 2 in vivo ultrasound ablationtreatments in rabbit liver with VX2 tumor

Treatment

Mean cumulative echo decorrelation

Pre-treatment End treatment

Unablated Ablated Unablated Ablated

1 0.0231 0.0657 0.0352 0.06702 0.0120 0.0233 0.0315 0.0603

Mean 0.0176 0.0445 0.0333 0.0637Standard deviation 0.0079 0.0300 0.0026 0.0048

ablation.

The ROC curves (Fig. 8) plotted for both RFA andultrasound ablation are indicative of the ability of echodecorrelation imaging to classify ablated and unablatedtissue regions. The relatively high AUROC values foundfor both ultrasound ablation and RFA, together with thehigh positive and negative predictive values obtained atoptimum echo decorrelation thresholds, indicate theutility of echo decorrelation for prediction of local abla-tion. AUROC values for ultrasound ablation, although

Fig. 9. Scatter plot of spatial maximum, temporal running-average echo decorrelation map versus simultaneousthermocouple-measured tissue temperature for all time points

from five radiofrequency ablation trials.

Echo decorrelation imaging for monitoring thermal ablation d S. SUBRAMANIAN et al. 113

statistically significant for RFA, had less predictive powerthan echo decorrelation. In the case of ultrasound abla-tion, integrated backscatter predicted ablation no betterthan chance. In both RFA and ultrasound cases, AUROCvalues for echo decorrelation imaging were significantlygreater than those for integrated backscatter. This isconsistent with previous results on prediction of ex vivotissue ablation by RFA (Mast et al. 2008).

An important future step toward clinical thermalablation monitoring is implementation of echo decorrela-tion imaging in real time. The high positive and negativepredictive values obtained for both RFA and ultrasoundablation indicate the potential of echo decorrelationimaging for real-time prediction of heat-induced thermaldamage, with applications in thermal ablation monitoringand control. Computation of echo decorrelation imagesrequires only a few arithmetical and filtering operationsapplied to beamformed ultrasound echo signals, compa-rable to the processing performed by current imagingsystems for conventional B-mode and color Dopplerimaging. Thus, implementation of real-time echo decor-relation imaging on clinical pulse-echo scanners wouldrequire no additional hardware and relatively modestsoftware modifications.

As thermal ablation is an intrinsically 3-D problemrequiring precision for the destruction of a tumor in itsentirety, a 3-D treatment guidance and monitoringmodality is desirable. Because echo decorrelation imagesare computed directly from the same pulse-echo dataused for 3-D B-mode imaging, this method can poten-tially be implemented on any 3-D ultrasound imagingsystem with sufficiently high frame rate with low compu-tational cost. This would ultimately allow detailed real-time 3-D monitoring and control of any clinical thermalablation procedure.

CONCLUSIONS

The results obtained indicate the utility of echo de-correlation imaging for predicting tissue thermal damageduring in vivo thermal ablation. Significantly higher meancumulative echo decorrelation was observed in ablatedtissue regions compared with unablated regions for bothRFA and ultrasound ablation treatments, indicating theability of echo decorrelation to delineate between ablatedand unablated regions. For in vivo RFA, motion gatingreduced the mean echo decorrelation significantly.However, with or without motion gating, the mean cumu-lative echo decorrelation was significantly greater in theablated than in the unablated region. This result suggeststhat echo decorrelation can delineate between ablated andunablated regions in the presence of motion-related arti-facts. Higher AUROC values were obtained for bothRFA and ultrasound ablation using echo decorrelationimaging than using relative integrated backscatter,despite limitations including tissue motion and the lowresolution of the image-ablate array used for ultrasoundablation. Together, these results indicate the feasibilityof echo decorrelation imaging as a tool for monitoringin vivo thermal ablation.

Acknowledgments—This research was supported by NIH Grants R01CA158439 and R21 EB008483.

REFERENCES

Arora D, Cooley D, Perry T, Guo J, Parker D, Skliar M, Roemer R.Thermal dose control of ultrasound therapies using MR thermom-etry images: An in-vitro phantom study. In: Proceedings, IEEEAmerican Control Conference, Portland, OR, 8–10 June2005:405–410.

Arthur RM, Straube WL, Trobaugh JW, Moros EG. Non-invasive esti-mation of hyperthermia temperatures with ultrasound. Int J Hyper-thermia 2005;216:589–600.

Barthe P, Slayton M, Jaeger P, Makin I, Gallagher L, Mast T, Runk M,Faidi W. Ultrasound therapy system and ablation results utilizingminiature imaging/therapy arrays. In: Proceedings, IEEE Ultra-sonics Symposium, San Juan, Puerto Rico, 22–25 October2004;3:1792–1795.

Boaz T, Lewin J, Chung Y, Duerk J, Clampitt M, Haaga J. MR moni-toring of MR-guided radiofrequency thermal ablation of normalliver in an animal model. J Magn Reson Imaging 1998;81:64–69.

Caspani B, Ierardi AM, Motta F, Cecconi P, Fesce E, Belli L. Smallnodular hepatocellular carcinoma treated by laser thermal ablationin high risk locations: preliminary results. Eur Radiol 2010;209:2286–2292.

Cha CH, Lee FT, Gurney JM, Markhardt BK, Warner TF, Kelcz F,Mahvi DM. CT versus sonography for monitoring radiofrequencyablation in a porcine liver. AJR Am J Roentgenol 2000;1753:705–711.

Chandrasekhar R, Ophir J, Krouskop T, Ophir K. Elastographic imagequality vs. tissue motion in vivo. Ultrasound Med Biol 2006;326:847–855.

Chiou SY, Liu JB, Needleman L. Current status of sonographicallyguided radiofrequency ablation techniques. J Ultrasound Med2007;264:487–499.

Curley SA, Izzo F, Delrio P, Ellis LM, Granchi J, Vallone P, Fiore F,Pignata S, Daniele B, Cremona F. Radiofrequency ablation of unre-sectable primary and metastatic hepatic malignancies: Results in123 patients. Ann Surg 1999;2301:1.

114 Ultrasound in Medicine and Biology Volume 40, Number 1, 2014

Dupuy DE, Zagoria RJ, Akerley W, Mayo-Smith WW, Kavanagh PV,Safran H. Percutaneous radiofrequency ablation of malignanciesin the lung. AJR Am J Roentgenol 2000;1741:57–59.

Fahey BJ, Hsu SJ,Wolf PD, Nelson RC, Trahey GE. Liver ablation guid-ance with acoustic radiation force impulse imaging: Challenges andopportunities. Phys Med Biol 2006;5115:3785–3808.

Gervais DA, McGovern FJ, Arellano RS, McDougal WS, Mueller PR.Radiofrequency ablation of renal cell carcinoma: Part 1. Indications,results, and role in patient management over a 6-year period andablation of 100 tumors. AJR Am J Roentgenol 2005;1851:64–71.

Hanley JA, McNeil BJ. The meaning and use of the area under a receiveroperating characteristic (ROC) curve. Radiology 1982;143:29–36.

Hynynen K, McDannold N. MRI guided and monitored focused ultra-sound thermal ablation methods: A review of progress. Int J Hyper-thermia 2004;207:725–737.

Illing RO, Kennedy JE, Wu F, Ter Haar GR, Protheroe AS, Friend PJ,Gleeson FV, Cranston DW, Phillips RR, Middleton MR. The safetyand feasibility of extracorporeal high-intensity focused ultrasound(HIFU) for the treatment of liver and kidney tumours in a Westernpopulation. Br J Cancer 2005;938:890–895.

Kennedy JE, Wu F, Ter Haar GR, Gleeson FV, Phillips RR,Middleton MR, Cranston D. High-intensity focused ultrasound forthe treatment of liver tumours. Ultrasonics 2004;421:931–935.

KrzanowskiWJ, HandDJ. ROC curves for continuous data. Boca Raton,FL: Chapman & Hall CRC; 2009.

Leyendecker JR, Dodd GD, Halff GA, McCoy VA, Napier DH,Hubbard LG, Chintapalli KN, Chopra S, Washburn WK,Esterl RM, Cigarroa FG, Kohlmeier RE, Sharkey FE. Sonographi-cally observed echogenic response during intraoperative radiofre-quency ablation of cirrhotic livers. AJR Am J Roentgenol 2002;1785:1147–1151.

Livraghi T, Meloni F, Di Stasi M, Rolle E, Solbiati L, Tinelli C, Rossi S.Sustained complete response and complications rates after radiofre-quency ablation of very early hepatocellular carcinoma in cirrhosis:Is resection still the treatment of choice? Hepatology 2008;471:82–89.

Mast TD, Barthe PG, Makin IRS, Slayton MH, Karunakaran CP,Burgess MT, Alqadah A, Rudich SM. Treatment of rabbit livercancer in vivo using miniaturized image-ablate ultrasound arrays.Ultrasound Med Biol 2011;3710:1609–1621.

Mast TD, Makin IRS, Faidi W, Runk MM, Barthe PG, Slayton MH.Bulk ablation of soft tissue with intense ultrasound: Modeling andexperiments. J Acoust Soc Am 2005;1184:2715–2724.

Mast TD, Pucke DP, Subramanian SE, Bowlus WJ, Rudich SM,Buell JF. Ultrasound monitoring of in vitro radio frequency ablationby echo decorrelation imaging. J Ultrasound Med 2008;2712:1685–1697.

Mast TD, Subramanian S. Analytic and numerical modeling of ultra-sonic B-scan and echo decorrelation imaging. Proc Meet Acoust2010;9:020003.

McDannold N. Quantitative MRI-based temperature mapping based onthe proton resonant frequency shift: Review of validation studies. IntJ Hyperthermia 2005;216:533–546.

Miller NR, Bamber JC, Meaney PM. Fundamental limitations of nonin-vasive temperature imaging by means of ultrasound echo strain esti-mation. Ultrasound Med Biol 2002;2810:1319–1333.

Murakami R, Yoshimatsu S, Yamashita Y, Matsukawa T, Takahashi M,Sagara K. Treatment of hepatocellular carcinoma: Value of percuta-neous microwave coagulation. AJR Am J Roentgenol 1995;1645:1159–1164.

Rhim H, Dodd GD. Radiofrequency thermal ablation of liver tumors.J Clin Ultrasound 1999;275:221–229.

Smith NB, Merrilees NK, Hynynen K, Dahleh M. Control system for anMRI compatible intracavitary ultrasound array for thermal treatmentof prostate disease. Int J Hyperthermia 2001;173:271–282.

Solbiati L, Goldberg SN, Ierace T, DellanoceM, Livraghi T, Gazelle GS.Radio-frequency ablation of hepatic metastases: Postproceduralassessment with a US microbubble contrast agent—Early experi-ence. Radiology 1999;2113:643–649.

Solbiati L, Livraghi T, Goldberg SN, Ierace T, Meloni F, Dellanoce M,Cova L, Halpern EF, Gazelle GS. Percutaneous radio-frequencyablation of hepatic metastases from colorectal cancer: Long-termresults in 117 patients. Radiology 2001;2211:159–166.

Souchon R, Bouchoux G, Maciejko E, Lafon C, Cathignol D,Bertrand M, Chapelon JY. Monitoring the formation of thermallesions with heat-induced echo-strain imaging: A feasibility study.Ultrasound Med Biol 2005;312:251–259.

Tateishi R, Shiina S, Teratani T, Obi S, Sato S, Koike Y, Fujishima T,Yoshida H, Kawabe T, OmataM. Percutaneous radiofrequency abla-tion for hepatocellular carcinoma: An analysis of 1000 cases. Cancer2005;1036:1201–1209.

Varghese T, Techavipoo U, Zagzebski JA, Lee FT. Impact of gasbubbles generated during interstitial ablation on elastographicdepiction of in vitro thermal lesions. J Ultrasound Med 2004;234:535–544.

Varghese T, Zagzebski JA, Lee FT. Elastographic imaging ofthermal lesions in the liver in vivo following radiofrequencyablation: Preliminary results. Ultrasound Med Biol 2002;2811:1467–1473.

Vigen KK, Jarrard J, Rieke V, Frisoli J, Daniel BL, Pauly KB. In vivoporcine liver radiofrequency ablation with simultaneous MRtemperature imaging. J Magn Reson Imaging 2006;234:578–584.

Yang R, Reilly CR, Rescorla FJ, Faught PR, Sanghvi NT, Fry FJ,Franklin TD Jr, Lumeng L, Grosfeld JL. High-intensity focusedultrasound in the treatment of experimental liver cancer. ArchSurg 1991;126:1002–1009. discussion 1009–1010.

Zhong H, Wan MX, Jiang YF, Wang SP. Monitoring imaging of lesionsinduced by high intensity focused ultrasound based on differentialultrasonic attenuation and integrated backscatter estimation. Ultra-sound Med Biol 2007;331:82–94.