skin-subqfat attenuation srinivasan umb 2001

8/2/2019 Skin-SubQFat Attenuation Srinivasan UMB 2001

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● Original Contribution

HIGH-FREQUENCY ULTRASONIC ATTENUATION AND BACKSCATTER

COEFFICIENTS OF IN VIVO NORMAL HUMAN DERMIS AND

SUBCUTANEOUS FAT

BALASUNDAR I. RAJU*‡ and MANDAYAM A. SRINIVASAN†‡

Laboratory for Human and Machine Haptics, *Department of Electrical Engineering and Computer Science,†Department of Mechanical Engineering and ‡Research Laboratory of Electronics, Massachusetts Institute of

Technology, Cambridge, MA, USA

( Received 20 April 2001; in final form 31 July 2001)

Abstract— In vivo attenuation and backscatter coefficients of normal human forearm dermis and subcutaneousfat were determined in the ranges 14 to 50 MHz and 14 to 34 MHz, respectively. Data were collected using threedifferent transducers to ensure that results were independent of the measurement system. Attenuation coefficientwas obtained by computing spectral slopes vs. depth, with the transducers axially translated to minimizediffraction effects. Backscatter coefficient was obtained by compensating recorded backscatter spectra forsystem-dependent effects and, additionally, for one transducer using the reference phantom technique. Goodagreement was seen between the computed attenuation and backscatter results from the different transducers/ methods. The attenuation coefficient of the forearm dermis was well described by a linear dependence with aslope that ranged between 0.08 to 0.39 (median 0.21) dB mm1 MHz1. The backscatter coefficient of thedermis was generally in the range 103 to 101 Sr1 mm1 and showed an increasing trend with frequency. Nosignificant differences in attenuation coefficient slope between the forearm dermis and fat were noted. Within therange of 14 to 34 MHz, the ratio of integrated (average) backscatter of dermis to that of fat ranged from 1.03 to87.1 (median 6.45), indicating significantly higher backscatter for dermis than for fat. Data were also recordedat the fingertip where the attenuation coefficient slope of the dermis was seen to be higher than that at theforearm. (E-mail: [email protected]) © 2001 World Federation for Ultrasound in Medicine & Biology.

Key Words: Ultrasound, Skin, Tissue characterization, Attenuation coefficient, Backscatter coefficient, In vivo,Dermis, Fat, Dermatology, High frequency.

INTRODUCTION

The development of high-frequency ultrasound (US) im-

aging systems has led to numerous applications in der-

matology. Examples of studies include evaluation of

tumors (Edwards et al. 1989; Hoffmann et al. 1992;

Fornage et al. 1993; Harland et al. 1993), scleroderma

(Ihn et al. 1995), psoriasis (Vaillant et al. 1994; Gupta et

al. 1996), burn injuries (Cantrell et al. 1978), study of skin aging (de Rigal et al. 1989; Gniadecka and Jemec

1998) and study of the effects of cosmetics (Levy et al.

1994), to name a few. Although most of the above

studies have used 20-MHz systems, systems operating at

frequencies greater than 20 MHz have also been demon-

strated (Foster et al. 1993; Passmann and Ermert 1996).

The B-scan images of skin produced by such systems

have shown that fine structures, such as veins and hair

follicles, can be visualized (Turnbull et al. 1995; El

Gammal et al. 1999). However, conventional B-scan

images use only the magnitude of envelope and have

limited utility when used for imaging skin tissues. For

instance, earlier studies have shown that, using B-scan

images of skin, it is difficult to distinguish between

benign and malignant lesions (Fornage et al. 1993), be-

tween different types of skin tumors (Fornage et al. 1993;Cammarota et al. 1998), between melanoma and an old

scar (Turnbull et al. 1995), or between tumors and sub-

tumoral inflammatory infiltrate (Hoffmann et al. 1992).

Hence, it becomes important to study if tissue character-

ization methods that attempt to classify tissues based on

their ultrasonic properties, such as frequency-dependent

attenuation and backscatter coefficients, could augment

information obtained through conventional B-scan im-

ages. For example, structural changes in skin due to

changes in pathology (e.g., infiltration of dermal collagen

Address correspondence to: Balasundar Raju, MIT Room36-788, 50 Vassar Street, Cambridge, MA 02139 USA. E-mail: [email protected]

Ultrasound in Med. & Biol., Vol. 27, No. 11, pp. 1543–1556, 2001Copyright © 2001 World Federation for Ultrasound in Medicine & Biology

Printed in the USA. All rights reserved0301-5629/01/$–see front matter

1543



fibers by tumor cells) could result in changes in ultra-

sonic properties that are registered by these methods.

Compared to other tissues, studies that report ultra-

sonic properties of skin or utilize tissue-characterization

techniques for classifying skin tissues are sparse. Of the

studies that have been done so far, Olerud et al. (1987)

showed that both speed and attenuation in skin were di-rectly related to collagen content and inversely related to

water content. Riederer-Henderson et al. (1988) measured

attenuation and speed in excised normal canine skin at 25

and 100 MHz using backscatter and SLAM, respectively.

Using backscatter and SLAM techniques, respectively, For-

ster et al. (1990) and Olerud et al. (1990) found that the

speed and attenuation values for wounded canine skin are

less than that of control skin. Moran et al. (1995) measured

speed, attenuation and backscatter coef ficients from excised

human skin tissues between 20 to 30 MHz. Baldeweck et al.

(1995) measured attenuation coef ficient of excised porcine

skin tissues at 20 MHz. Pan et al. (1998) measured atten-uation and backscatter coef ficients in excised rabbit and

human skin between 20 to 30 MHz and found a decreasing

trend in attenuation coef ficient and a slight increasing trend

in backscatter coef ficient with increasing strain. Guittet et

al. (1999) measured attenuation at 40 MHz for 150 human

volunteers in vivo using a spectral-shift technique and found

a decreasing trend in attenuation coef ficient slope with age.

In this work, we report on in vivo attenuation and

backscatter coef ficients from healthy human dermis and

subcutaneous fat. The reason for the present study and its

contributions are as follows. All the studies so far, except

the study of attenuation coef ficients of the dermis by Guittet

et al. (1999), were done under in vitro conditions using

excised tissues. For tissue characterization methods to be

clinically useful, these methods should be done under in

vivo conditions. The properties of in vitro tissues could

differ from that of in vivo tissues due to reasons such as

changes in skin tension, absence of blood flow, differences

between room and body temperatures (when specimens are

tested at room temperature), and specimen preparation ef-

fects. Until now, backscatter coef ficients of skin tissues

have not been measured under in vivo conditions, and in

vitro measurements of backscatter coef ficients are very few.

Diffuse backscattering is the primary soft tissue-wave in-

teraction responsible for echoes received at the transducer

and, hence, for any images that are generated with US

systems. The backscattered signals depend on size, shape,

acoustical properties and concentration of scatterers (dis-

continuities in acoustic properties) in the tissue, and could

contain potential information about tissue microstructure,

especially when a broad range of frequencies is available.

Therefore, measurements of in vivo backscatter coef ficients

will serve to improve our basic understanding of US-skin

tissue interaction. Next, the studies so far have been re-

stricted to only the layers of the skin; the subcutaneous fat,

which is sometimes considered as a third layer of skin and

referred to as the hypodermis, has not been well studied.

Based on B-scan images, subcutaneous fat is considered

hypoechogenic with respect to dermis, but such a difference

has not been quantified in terms of integrated backscatter

measurements or frequency dependence of backscatter co-

ef ficients. It is necessary to study subcutaneous fat becauseskin lesions such as tumors could extend well beneath the

dermis into the fat (Koh 1991). Previous studies have indi-

cated that, in B-scan images, both subcutaneous fat and skin

tumors appear hypoechogenic with respect to the dermis

and, therefore, there could be ambiguity in determining the

bottom margins of thick tumors that extend beneath the

dermis into the fat. Next, it is also presently unclear whether

ultrasonic properties of skin tissues vary from one location

to another. Unlike other organs like heart, liver etc. that are

localized to one region in the body, the skin covers the

entire body and large variations in properties are possible

because of differences in skin thickness and type (e.g.,glabrous vs. hairy skin), the state of tension, exposure to sun

and environment, as well as work-related usage of certain

parts of the body. By recording data from two grossly

different regions in the body, the fingertip and the dorsal

forearm, we compare in this work, the attenuation coef fi-

cients of the dermis at these two locations. Results in this

study are also compared with existing literature.

MATERIALS AND METHODS

Experimental system

The experimental system consists of a polyvinylidene

diflouride (PVDF) transducer (Panametrics), a pulser/re-

ceiver (Panametrics, Waltham, MA; Model 5900), a digi-

tizing oscilloscope (Tektronix, Beaverton, OR; Model TDS

520C), a three-axis scanning system (Parker-Hannifin/

Compumotor, Cleveland, OH), and a personal computer

(PC) to control mechanical scanning and GPIB-based data

acquisition. Three transducers whose specifications are

shown in Table 1 were used in this study. The transducer

characteristics vary a bit, depending on the excitation level

setting in the Panametrcs pulser that, in this work, was set

to 32 J. The digitizing oscilloscope sampled the backscat-

tered signals at a sampling frequency of 500 MHz. Each

A-scan was an average of several repeated acquisitions (100

for transducers I and II, and 240 for transducer III), which

greatly improved the signal-to-noise ratio (SNR), enabling

even weak signals from subcutaneous fat to be studied.

While recording each A-scan, the vertical scale on the

digitizing oscilloscope was adjusted in real-time by the

controlling program to record strong signals such as surface

reflections free of clipping, as well as weak signals such as

backscatter from subcutaneous fat without quantization ef-

fects. For example, when a full scale of 5 to 5 volts is

set, a weak signal with amplitude of only 25 mV might get

1544 Ultrasound in Medicine and Biology Volume 27, Number 11, 2001



quantized to a value of zero, because of the finite number of

bits. On the other extreme, if the full scale is too low, say

5 mV to 5 mV, the same signal would be recorded withclipping effects. Because there is no a priori way to know

the magnitude of signals to be recorded, the software ad-

justs the scaling on the vertical axis (by trial and error) for

each A-scan to ensure that the signals are being recorded

without too much quantization effect, as well as without

clipping. The transducers were mounted on a three-axis

stage that had encoders on the x- and y-axes that provided

a high lateral positioning accuracy of 1m. Water was used

as a coupling medium between the transducers and tissues.

Although no special attempt was made to maintain the

temperature of water to be constant during a given experi-

ment, the temperature at the start of the experiment was

uniform for all subjects (36°C).

Diffraction elimination and adjustment for

surface curvature

A-scans were collected from 25 independent lateral

locations of the transducers by scanning along x and y in a

5 5 raster format. The area over which the 25 samples

was taken was 1.5 mm2 for transducer I, 3 mm2 for trans-

ducer II, and 1 mm2 for transducer III. To minimize dif-

fraction effects from affecting the results, several axial

translations of the transducer toward the tissue were done

for each lateral location while data were recorded from the

locations of the focal zones of the transducers. Another

consideration in high-resolution, high-frequency character-

ization is that, due to curvature of the skin surface, data

from adjacent locations of the focal zones for any given

axial location of the transducer could correspond to differ-

ent depths from the surface when the transducer is rectilin-

early scanned across the tissue (Fig. 1). In some cases, the

location of the focal zone might even move out of the

surface. This is undesirable when lateral averaging of quan-

tities such as power spectra are done. Hence, at each lateral

location of the transducer, the system first adjusted for the

surface curvature by measuring the time-of-flight from the

surface and then moving the transducer up or down, so that

the surface was at a predetermined distance from the trans-

ducer. Such adjustments still have the problem of oblique

incidence due to surface curvature (i.e., the incident angle

not being 90°). However, because the interaction of waves

with the tissues is more of scattering rather than specularreflections, the effect of oblique incidence should be small

as long as the incident angle is not very different from 90°

(Campbell and Waag 1984). Scanning was first done in the

axial direction to collect data from several locations of the

focal zones in the tissue for a given lateral location, after

which the transducer was moved to the next lateral location,

its height adjusted, the axial scans done, and the procedure

repeated for all lateral locations.

Human subjects and tissues

Skin consists of a superficial layer of epidermis and an

underlying layer of dermis. The region beneath the dermisconsists of subcutaneous fat, which is sometimes consid-

Fig. 1. Curvature effects. In ultrasonic tissue characterizationstudies, power spectra from focal zone depths of adjacentlocations are averaged to compute mean spectra. When such aprocedure is applied to high-frequency imaging of skin, due tothe curvature of the surface averaging occurs between data atdifferent depths (top). In some cases, the focal zone locationmight even move out of the surface. Hence, the system adjustsfor this by measuring the time of flight and translating thetransducer up and down (bottom). Then several axial scans areperformed at the same lateral location, followed by lateral scans

to collect data from other locations.

Table 1. Characteristics of the transducers used in this study

TransducerI

(Model PI50)II

(Model PI75)III

(Model PI3005)

Center frequency 28 MHz 30 MHz 44 MHz

6 dB bandwidth 30 MHz 40 MHz 50 MHzF-number 2 4 2

Focal length 12.7 mm 12.7 mm 4 mmDiameter 6.35 mm 3.175 mm 2 mmUseful frequency

range in dermis 14–50 MHz 14–50 MHz 14–55 MHz

The center frequency and 6 dB bandwidths are based on thespectrum of signal reflected from a perfect reflector at the transducer’sfocus. The useful frequency range in dermis is based on spectra of signals backscattered from normal human dermis that have an SNRgreater than 10 dB.

Attenuation and backscatter coef ficients of skin q B. I. RAJU and M. A. SRINIVASAN 1545



ered as a third layer of skin and is referred to as the

hypodermis. In most parts of the body, the epidermis is very

thin compared to the dermis (0.15 mm vs. 1.2 to 1.8 mm),

except at the palms and soles where it is much thicker (0.6 mm). In this study, data were collected from 2 grossly

different locations: the dorsal side of the right forearm

(hairy skin) and the left index fingertip (glabrous skin). Atthe forearm, two body sites, one near the wrist and the other

near the elbow, were studied. The reason for choosing two

sites at the forearm was that, due to their proximity, one of

them could serve as a control for the other. Table 2 sum-

marizes the tissues studied and the subject population. Be-

cause skin condition could depend on the subject’s age, the

present study was restricted to only young adults. The first

transducer was used for all the three body sites to study

differences due to body site. All three transducers were used

to collect data from the forearm wrist region to test system

independencies. In the case of skin regions near the forearm

wrist and elbow, data were collected from 10 locations of

the focal zones (axial scans) starting from 0.3 mm below the

surface up to a depth of 3.0 mm in steps of 0.3 mm, which

covered both the dermis and fat. In the case of the fingertip,

data were recorded from 12 locations of the focal zones

from 0.3 mm up to 1.95 mm in steps of 0.15 mm, which

covered both the epidermis and dermis. Due to reasons

concerning logistics, the same set of subjects was not used

for all the three transducers, but the median ages were about

the same (Table 2). All the subjects that participated in the

fingertip study were right-handed. For each of the experi-

ments done, a second independent repetition at a nearby

region (displaced by a few mm from the original site) was

done to increase the number of independent data sets.

Power spectra computation

After data from all focal zone locations and all lateral

locations were obtained, a time-gate of 128 samples (0.256

s, corresponding to a frequency resolution of about 4

MHz) was applied to select data at the focus of the trans-

ducers. These gated data were truncated by applying a

Hamming window, Fourier-transformed and squared to

compute individual power spectra for all lateral locations

and at all axial locations of the transducer. Although it is

customary to compute the mean of the spectra recorded

from all lateral locations, in this work, it was found that a

trimmed mean wherein the top and bottom 25% of the data

were eliminated was more useful. Such a quantity is less

sensitive to the presence of extreme variations in the data

and will be simply referred to as the mean spectra in this

work. The approach was especially useful in the case of subcutaneous fat, where strongly reflecting fibrous septae

were present occasionally. Figure 2 (a) shows mean spectra

for 10 locations of the focal zones at the forearm of a human

subject obtained with transducer I.

Attenuation estimation

To compute attenuation coef ficients, spectral slopes

in dB mm1 were computed, based on mean spectral

levels from several focal zone locations in the tissue at

the frequencies of interest. To do this computation, one

first needs to identify the extent of tissue in the axial

direction. This was done by plotting “pseudoimages”using the collected data (Fig. 2b). Such images serve to

differentiate grossly different regions, such as the dermis

and fat. In this example, the strongly scattering dermis is

seen to extend about 1.8 mm beneath the surface. To

convert time-of-flight to depth, a speed of sound of 1.5

mm s1 was assumed throughout this study, which is

close to values reported in the literature (Bhagat and

Kerrick 1980; Foster et al. 1984; Moran et al. 1995).

Small discrepancies in speed do not affect the computed

attenuation values (dB mm1) significantly and, hence, a

convenient value of 1.5 mm s1 was used. In general,

most of the subjects had a dermal thickness between 1.3

and 1.8 mm and, hence, the first four focal zone locations

(at 0.3, 0.6, 0.9 and 1.2 mm from the surface) were taken

to correspond to dermis for all subjects. A few subjects

whose forearm dermal thicknesses were less than 1.2 mm

were eliminated from the study a priori so as to maintain

uniformity. The focal zone locations beneath the dermis

were taken to correspond to fat, with care taken to avoid

fibrous septae that were sometimes seen in the pseudo-

images. Figure 2 also demonstrates how the useful fre-

quency range for analysis was chosen. At higher frequen-

cies, the spectra tend to become flat after the noise floor

is reached, especially for signals from the deeper fat

tissues. To have an SNR of at least 10 dB, a frequency

range of 14 to 50 MHz was chosen for the dermis and a

range of 14 to 34 MHz was chosen for fat.

To determine if 4 focal zone locations were suf fi-

cient to accurately compute attenuation coef ficient, two

benchmark experiments were done on forearm skin for

one subject before data collection from all subjects was

done. The first experiment had seven closely spaced

focal zone locations starting from 0.3 mm below the

surface and extending to 1.2 mm in steps of 0.15 mm.

The second had only four focal zone locations in steps of

Table 2. Tissues and subjects used in this study

Body site

Transducer(see

Table 1) Tissues studied

Subjects

n

Ages: range(median) years

Forearm wrist I Dermis and fat 16 2 0–36 (26.5)

II Dermis and fat 16 22–36 (28.5)III Dermis 16 19–36 (24.5)

Forearm elbow I Dermis and fat 13 19–34 (24.5)Left index fingertip I Dermis 18 20–33 (24.5)




0.3 mm. The attenuation coef ficient slopes computed for

the two cases were 0.2241 and 0.2483 dB mm1 MHz1,

respectively, indicating only an 11% higher value for the

case with coarser spacing than for the one with finer

spacing. Hence, it was decided to use the coarser spacing

in the axial direction for all further experiments because

adding additional focal zone locations only increased the

data-acquisition time.

Frequency-dependence of attenuation coef ficient

To determine the frequency-dependence of the at-

tenuation coef ficient, a linear fit of the form ( f ) f

C , as well as a power law fit of the form ( f ) Af n

C were done. Whereas the former was done using linear-

least squares techniques, the latter was done using a

nonlinear optimization method using the optimization

toolbox in Matlab (Mathworks, Natick, MA).

Backscatter coef ficient estimation using compensation

for system-dependent effects

The backscatter coef ficient is defined as the differen-

tial scattering cross-section per unit volume of tissue at an

angle of 180°. Measurement of such a quantity requires

compensating the recorded spectra for the electromechani-

cal response and the focusing properties of the transducer

and for the characteristics of the receiver electronics. In this

work, backscatter coef ficients were computed by two dif-

ferent methods. The first method is similar to that of Mad-

sen (1993), wherein the system-dependent effects are ac-

counted for by accurately modeling the physics of wave

propagation phenomena during the data reduction step,

whereas the second method is the reference phantom

method as described by Zagzebski and coworkers (Yao et

al. 1990; Zagzebski et al. 1993a, 1993b). Other methods for

quantifying backscatter coef ficients of tissues can also be

found in the literature (Sigelmann and Reid 1973;

O’Donnell and Miller 1981; Nicholas et al. 1982; Campbell

and Waag 1983; Lizzi et al. 1983; Chen et al. 1997).

The first method involved computing correctionsusing the known transducer geometries and also record-

ing the signal reflected off a plane reflector at the focus

with known acoustic properties. The following formula

was used to compute the backscatter coef ficient:

Bt f St f

Sr f D f I f , (1)

where St (f) is the mean power spectrum recorded from the

tissue of interest (computed using spectra from several

depths in the same tissue, and compensated for attenuation

within these depths), Sr (f) is the power spectrum of thesignal reflected from a perfect reflector at the focus of the

transducer, D(f) is a diffraction correction term defined

below, and I(f) is a term to account for attenuation by

intervening tissues lying shallower than the tissue of inter-

est. The attenuation coef ficients computed beforehand for

each tissue were used to compensate for attenuation within

the tissue of interest while computing St (f). Such a proce-

dure basically assumes homogeneity in tissue properties for

all the depths making up the tissue of interest. The term I(f)

is an additional term to correct for intervening attenuation;

for example, compensating for attenuation by the dermis

while computing backscatter coef ficients of fat. The diffrac-

tion correction term D(f) is given by:

D f

Smirror

dsS

e jk r r

r r ds

2

R 1

0.63

2

d

d S

e jk r r

r r ds

4

e4 f r r 1

. (2)

The explanation for the terms in the above expression is as

follows: The first term in the numerator represents a surface

integral over the surface of the transducer (denoted by S),

followed by another surface integral over the surface of an

identical transducer placed at a distance equal to twice the

focus (denoted as Smirror). The symbols r and r refer to

position vectors on the surface of the transducer and a

generic point in the integration space, respectively. The

second term R is the intensity reflection coef ficient between

the plane reflector and the coupling medium water. The

third term in the numerator (1/0.63)2 is a factor that ac-

counts for the Hamming window function used in comput-

ing the spectra (Chen et al. 1993). The denominator consists

Fig. 2. (a) Mean power spectra of backscattered signals from 10focal zone locations in the skin (locations indicated in theinset). (b) Pseudoimages based on the collected data. The termpseudo implies that the image is not a usual B-scan imagebecause the lateral stepping distance was greater than the lateralresolution of the system, and also the collected data wereactually 3-D whereas the pseudoimage is plotted as though thedata are 2-D, by laterally combining all the y-scans and all thex-scans together. Such images were used to a priori differen-

tiate between dermis and fat.




of a surface integral over the surface of the transducer

(denoted by S), followed by a volume integral over the

region occupied by the scatterers (denoted by ), modified

by an exponential term that accounts for the attenuation

within the gate [( f ) is the amplitude attenuation coef ficient

of the tissue of interest, and r 1 is the distance up to the start

of gate]. In practice, the computation of these integrals is atime-consuming task when numerical integration tech-

niques are used. In this work, the above integrals were

computed using the angular spectrum method (Goodman

1996), which yields a much faster solution due to the

ef ficient computation of FFTs. The computed diffraction

correction functions were compared with simpler analytical

functions given by Chen et al. (1997) for all three transduc-

ers used in this work (Fig. 3). Good match is seen in terms

of frequency-dependence, but the simpler formulation of

Chen and colleagues slightly underpredicts the diffraction

correction for transducers I and III, both of which were

more focused (f-number 2) than transducer II (f-num-ber 4). In this work, the full diffraction corrections D(f)

as defined above were used because they could be com-

puted and stored a priori.

Backscatter coef ficient estimation using the reference

phantom method

The second method to compute backscatter coef ficient

was based on the use of a reference phantom that has been

previously employed in determining in vivo backscatter

coef ficients of other tissues, such as liver (Zagzebski et al.

1993a; Wear et al. 1995; Lu et al. 1999) and kidney (Wear

et al. 1995). Such a method was used for computing back-scatter coef ficients using data from transducer II. The ref-

erence phantom was obtained from CIRS (Norfolk, VA),

and contained gelatin with randomly distributed spherical

glass beads having a mean size of 82 m and an SD in size

of 3 m. Properties of the scatterers were provided by the

manufacturer: The longitudinal wave speed is 5600 m/s; the

density is 2.5 g mL1; and the Poisson’s ratio is 0.22. The

concentration of scatterers is 8000 particles mL1. The gel

has a longitudinal wave speed of 1529 m s1 and a density

of 1.02 g mL1. The backscatter coef ficient was computed

using the formula:

Bt f St f

Sref f Bref f I f , (3)

where St (f) is the mean power spectrum recorded from

the tissue of interest compensated for attenuation within

the tissue of interest, Sref (f) is the mean power spectrum

recorded from the reference phantom (compensated for

attenuation in the phantom up to the depth at which

spectra were computed and for the transmission loss

through the Saran wrap covering the phantom), Bref (f) is

the backscatter coef ficient of the reference phantom, and

I(f) is the intervening tissue attenuation compensation

term. The quantity Bref (f) was computed according to

Faran’s model (Faran 1951), assuming that the scatterers

are randomly oriented, which leads to only incoherent

scattering contributions. To compute the mean backscat-

tered spectra from the phantom, Sref (f), 800 radiofre-

quency (RF) lines were recorded for averaging purposes

to minimize possible effects of inhomogeneities. The

phantom had a protective Saran-wrap cover, and com-

pensation for nonunity transmission coef ficients at the

water-Saran-phantom interface was computed at the re-

quired frequencies (14 to 50 MHz) using the methods

described in Madsen et al. (1999).

Integrated backscatter

After the backscatter coef ficients were computed,

the integrated backscatter was obtained in the range of 14

to 34 MHz, using the formula:

Integrated backscatter1

f 2

f 1 f 1

f 2

Bt f df (4)

where f 1 14 MHz and f 2 34 MHz. Even though

reliable spectra was available up to 50 MHz for the

dermis, the use of 34 MHz as the upper limit made it

possible to compare dermis and fat tissues.

Statistical tests

To quantify differences in parameters between der-

mis and fat, such as attenuation coef ficient slope and

integrated backscatter, a paired t -test was used.

Fig. 3. Comparison of the diffraction correction term used inthis work (——) with that given by the analytical expressions

of Chen et al. (1997) (— — ).




RESULTS

Figure 4 shows the attenuation coef ficient of the fore-

arm dermis at the wrist obtained using data from all three

transducers. It can be seen that the attenuation coef ficients

based on the different transducers agree well with one

another. To quantify the frequency-dependence, both linear

and power-law fits were done for data from all subjects, for

all three transducers. The linear fit gave a slope that

ranged between 0.08 and 0.39 (median 0.21 dB mm1

MHz1). The power-law fit gave an exponent that ranged

between 0.05 and 3.52 (median 1.06). The goodness of

fit as determined by the correlation coef ficient for both the

linear and power law fits were quite similar (mean correla-

tion coef ficient R2 0.95 for linear fit vs. R2 0.96 for

power law fit). It was also found that the power-law fit gave

fitting parameters that had more variations from one subject

to another than did the linear-fit parameters. Such variations

were found even for repetitions done on a single subject

(not shown), and can be attributed to dif ficulties in fitting

power-law functions within a limited frequency range (Lin

et al. 1987). Hence, within the range 14 to 50 MHz, the

simpler linear frequency-dependence of attenuation coef fi-

cient of the dermis adequately described the results obtained

in this work. The use of a nonzero intercept for curve-fitting

the frequency-dependence is discussed in the next section.

Figure 5a shows the attenuation coef ficient of the

dermis at the three body sites: forearm wrist, forearm el-

bow, and the fingertip obtained using transducer I. In the

case of fingertip dermis, only data up to 26 MHz was used

due to a poorer SNR at higher frequencies. As expected, the

results at the two forearm regions were similar (median 0.21 dB mm1 MHz1 at the wrist and 0.20 dB mm1

MHz1 at the elbow). At the fingertip, however, the atten-

uation coef ficient slope was higher (median 0.33 dB

mm1 MHz1) than that at the other two locations. Figure

5b shows the attenuation coef ficient of subcutaneous fat at

the two forearm regions. The median at the wrist and

elbow were 0.18 and 0.19 dB mm1 MHz1, respectively.

These values are close to that of the dermis, indicating

similarity in attenuation coef ficient slopes between dermis

and fat. Figure 6 shows a histogram of the difference in

attenuation coef ficient slope between dermis and fat com-

puted individually for all subjects (for transducers I and II).A paired t -test gave a p value of 0.61 for the equivalence of

the two means, indicating that there is little difference

between dermis and fat in terms of attenuation coef ficient

slope within the frequency range studied.

Figure 7 shows the backscatter coef ficient of forearm

wrist dermis obtained using all three transducers, as well as

the reference phantom method using data from transducer

II. Good agreement can be seen among these results despite

differences in transducer characteristics. Some discrepan-

cies seen in the plots could be attributed to assumptions

used in computing backscatter coef ficients, as well as using

a slightly different subject population for the three trans-

ducers. The backscatter coef ficients were generally in the

range 103 to 101 Sr1 mm1, and showed an increasing

trend with frequency. Data from these plots were combined

with data from transducer I at the forearm elbow and were

plotted on a log-log scale (Fig. 8). An approximate increase

in slope is seen at higher frequencies, which implies in-

creasing power-law exponents when piece-wise power-law

fits are done. For example, if two power-law fits are done on

the data, one for 14 to 30 MHz and the other for 30 to 50

MHz, the latter would show a larger value for power-law

exponent than the former.

Figure 9 shows the backscatter coef ficients of the

dermis and fat at the two forearm regions obtained using

data from transducer I. Results from the two regions match

well for both dermis and for fat. Within the range 14 to 34

MHz, backscatter coef ficient of fat showed a slight increas-

ing trend followed by a slight decreasing trend. The results

for fat also showed more variations than for dermis; the

reasons for this could be attributed primarily to the occa-

sional presence of strongly scattering fibrous septae in the

fat. To compare the backscatter levels of the dermis and fat,

a histogram of the differences in integrated backscatter (14

to 34 MHz) between the two was plotted (Fig. 10). All of

the values were positive, indicating higher integrated back-

scatter for dermis compared to fat. A paired t -test gave a p

value 0 for the hypothesis that the two means are the

same. The ratio of integrated backscatter of dermis to that of

fat computed for all data ranged from 1.03 to 87.1 (median

Fig. 4. In vivo attenuation coef ficients of the forearm dermis(wrist) in the range 14 to 50 MHz based on the three transduc-ers. The markers indicate the median and the error bars indicate

the full range of data. The tick marks on the error bars indicatethe 25th and the 75th percentile points. The three curves aredisplaced slightly along the x-axis to make them more legibleand the frequencies indicated on the x-axis are the actual values

at which the attenuation coef ficients were computed.




value was 6.45), indicating that, within 14 to 34 MHz,

dermis on the average backscatters about 6 times stronger

than fat.

DISCUSSION

Summary of results

In this work, attenuation and backscatter coef fi-

cients from healthy human dermis and subcutaneous fat

were determined using humans under in vivo conditions.

Attenuation coef ficients of dermis in the range 14 to 50

MHz at the forearm wrist region were computed using

data from three transducers, which showed good agree-

ment with one another. Backscatter coef ficients of der-

mis at the same location were also computed by com-

pensating recorded backscatter spectra for the system-

dependent effects and, additionally, for one transducer

using the reference phantom method. The computed

backscatter coef ficients based on the four methods

agreed well with one another. Comparison of attenuation

and backscatter coef ficients between the dermis and fat

at the forearm region was done. Attenuation coef ficients

of the dermis at two locations, fingertip and forearm, were

also compared. Table 3 presents a summary of the results.

Although the initial aim was to study all the three

layers (epidermis, dermis, and fat) at both the forearm and

fingertip regions, only a subset of these tissues could be

studied, the reasons for which are as follows. First, for

tissue characterization studies, the thickness of the tissue

being investigated should be suf ficient to compute power

spectra over a windowed region free of surface and inter-

Fig. 5. In vivo attenuation coef ficient of (a) the dermis at threebody sites; and (b) subcutaneous fat at two body sites. Themarkers indicate the median and the error bars indicate the fullrange of data. The tick marks on the error bars indicate the 25thand the 75th percentile points. Individual curves are slightlydisplaced along the x-axis to improve legibility. Data at fre-quencies higher than 26 MHz in the case of fingertip dermis,and higher than 34 MHz in the case of subcutaneous fat, were

not used due to poorer SNR at these frequencies.

Fig. 6. Histogram of difference in attenuation-coef ficient slopebetween the dermis and subcutaneous fat. All data obtainedusing transducer I at both forearm wrist and elbow regions andtransducer II at forearm wrist regions were used to create thehistogram. On the average, little difference is seen between thedermis and fat in terms of attenuation-coef ficient slope within

the range of frequencies studied.




face echoes. To compute the attenuation coef ficients, sev-

eral such windows at successive depths are required. At the

frequencies and pulse lengths used in this study, the epider-

mis at the forearm region was too thin to fit this criterion.

Fig. 7. In vivo backscatter coef ficients of the dermis at the forearmwrist location in the range 14 to 50 MHz. The markers indicate the

median and the error bars indicate the full range of data. The tick marks on the error bars indicate the 25th and the 75th percentilepoints. Individual curves are slightly displaced along the x-axis toimprove legibility. The backscatter coef ficients were computed forthe three transducers by compensating backscattered spectra forsystem-dependent effects and, additionally, for transducer II, using

the reference phantom method.

Fig. 9. Backscatter coef ficient of (a) the dermis and (b) fat atthe two forearm regions obtained with transducer I. Markersand error bars indicate median and full range of data, respec-tively. The tick marks on the error bars indicate the 25th and the75th percentile points. Individual curves are slightly displaced

along the x-axis to improve legibility.Fig. 8. Comparison of in vivo backscatter coef ficient of dermisfrom this study with literature data (in vitro). Data from Moran etal. (1995) is based on a power-law fit mentioned in their study.




Next, although it was initially thought that the epidermis at

the fingertip could be studied due to its increased thickness,

the inhomogenities within the layer itself, such as the pres-

ence of a sharp interface at the stratum corneum-viable

epidermis border, made it dif ficult to select homogeneous

regions and, therefore, the fingertip epidermis could not be

reliably studied from a tissue-characterization perspective.

The presence of such imhomogeneities noted in this study

is consistent with earlier studies of US imaging of skin

(Murakami and Miki 1989; El Gammal et al. 1999). Next,

subcutaneous fat at the fingertip region could not be studied

because the signals from this tissue were too weak and close

to the noise floor level. Thus, in this work, the forearm

dermis, the forearm subcutaneous fat, and the fingertip

dermis were the three tissues studied. Furthermore, because

the fingertip epidermis was not studied, the backscatter

coef ficient of the fingertip dermis could not be computed

because the intervening attenuation due to the epidermis

could not be determined reliably.

Attenuation coef ficient measurements

Previous work by Riederer-Henderson et al. (1988) at

25 and 100 MHz indicated that the attenuation coef ficient in

skin might have a power-law type of dependence. Moran et

al. (1995) also reported a power-law type of dependence of

dermal and epidermal attenuation coef ficients with fre-

quency within the range 20 to 30 MHz, but if a simplerlinear fit could have modeled the data well enough was not

mentioned in their work. Work by Pan et al. (1998) showed

that attenuation coef ficients in human skin at 20 and 30

MHz were 5.5 and 8.4 dB mm1, respectively, from which

a power-law exponent, assuming (f) Af n, could be

obtained to be n 1.04. Other researchers have assumed a

linear frequency-dependence while computing attenuation

coef ficients for the dermis (Baldeweck et al. 1995; Guittet

et al. 1999). In this work, although power-law fits were

analyzed, no advantage in using them over simpler linear

frequency-dependence was seen in the range 14 to 50 MHz

for the dermis. It should also be noted that, even if apower-law-dependence is truly present, a large BW and

computation of attenuation coef ficients at several indepen-

dent frequencies within this BW are needed to accurately

determine the appropriate parameters (Lin et al. 1987).

Thus, over the frequency range analyzed, a linear frequen-

cy-dependence adequately described the attenuation coef fi-

cient of the dermis.

A surprising result from this study is that the attenu-

ation coef ficient slopes of the dermis and subcutaneous fat

are similar. This is different from earlier results by Guittet

et al. (1999), where a lower value of attenuation coef ficient

slope was reported for subcutaneous fat. The reason for thisdifference is not clear, but it can be noted that the applica-

bility of the spectral-shift method used in their studies

becomes more limited when the bandwidth of the signals

starts to change with depth. In their case, a bandwidth equal

to that obtained at the focus on a steel plate reflector was

used for all depths, in which case an underestimation of the

attenuation coef ficient slope could occur if the bandwidth is

actually smaller than the one used. The results in this work

show a decreasing trend in the bandwidth of the signals

backscattered from deeper fat layers compared to the shal-

lower dermis (Fig. 2a). Another reason could be due to the

Fig. 10. Histogram of difference in integrated backscatter be-

tween the dermis and fat in the range 14 to 34 MHz. All dataobtained using transducer I at both forearm wrist and elbowregions and transducer II at forearm wrist were used to create

the histogram.

Table 3. Summary of results from this work

Tissue

Attenuation coef ficient slope(dB mm1 MHz)1;

Range (Median)

Integrated backscatter (14–34 MHz)

103 Sr1 mm1;

Range (Median)

Forearm dermis 0.081–0.388 (0.211) 1.57–47.7 (8.52)Forearm fat 0.037–0.399 (0.184) 0.06–14.6 (1.60)Fingertip dermis 0.088–0.524 (0.331) –

The forearm results include data from both the wrist and the elbow regions.




different frequency ranges used. In this work, the useful

frequency for subcutaneous fat was chosen to be 14 to 34

MHz so as to avoid noise from biasing the results, whereas

the values reported by Guittet et al. (1999) were at a center

frequency of 40 MHz. A histogram of differences in atten-

uation coef ficient slopes between the dermis and fat com-

puted in this work showed that, on the average, there is little

difference between the two tissues (Fig. 6).

The results in this work support the possibility that

attenuation coef ficients of the dermis could depend on the

location in the body. The values at the fingertip were found

to be higher than that at the forearm. Possible reasons are

differences in skin tension at the two locations and differ-

ences in the underlying collagen structure at the two loca-

tions (Pan et al. 1998). Further studies involving data col-

lection from several body sites are needed to establish

regional variations in ultrasonic properties of skin.

When analyzing the frequency-dependence of the

attenuation coef ficient of the forearm dermis, a nonzero

intercept was used in both the linear and power-law

models. This is consistent with the data shown in Fig. 5,

wherein an extrapolation of the attenuation coef ficients

of dermis would lead to negative y-intercepts. Such

negative intercepts imply an increase in recorded signal

levels at lower frequencies, and can be attributed to

increases in backscatter coef ficients within the region

analyzed. Estimation of attenuation coef ficients with in

vivo backscattered data requires the assumption that

backscatter coef ficients are constant with depth within

the region analyzed. When such a condition does not

exist, the computed attenuation coef ficients may not be

true attenuation coef ficients inherent to the tissues, but

can only serve as a relative measure between different

tissues. Several researchers have used such assumptions:

Guittet et al. (1999) for skin, Wilson et al. (1994) for

vascular tissues, and Lu et al. (1999) for liver, to name a

few. Examples of fitting frequency-dependence curves

for attenuation coef ficients with nonzero intercepts can

also be found in the literature (Bamber and Hill 1981;

Huisman et al. 1998). Under these conditions, the mea-

sured backscatter coef ficients are also only averages over

the ROI (e.g., in the case of dermis, over the range 0.3 to

1.2 mm beneath the surface). It is also worthwhile to note

that, if changes in backscatter coef ficients from one

depth to another within the ROI are relatively frequency-

independent, then the frequency-dependence of attenua-

tion is not affected except for a shift along the y-axis.

Thus, the computed linear slope would be independent

of any frequency-independent changes in backscatter

coef ficients over the region analyzed.

Figure 11 shows the comparison of the results of

computed attenuation coef ficient slopes from this work with

that found in the literature. To be consistent with other

methods, only the attenuation-coef ficient slope (with the

intercept removed) was used in comparing with literature

data. It is to be noted that the previous in vivo results by

Guittet et al. (1999) were based on a spectral-shift method,

whereas the results here were based on a spectral-difference

method and a good agreement between the two could be

seen despite differences in methodology. Figure 12 shows a

Fig. 11. Comparison of in vivo attenuation coef ficients of the dermis from this study with literature data.




comparison of attenuation-coef ficient slopes of fat esti-

mated in this work with that found in the literature.

Backscatter coef ficient measurements

This work seems to be the first one where in vivo

backscatter coef ficients are being reported for dermis and

subcutaneous fat. Only few in vitro data are available and a

comparison is shown in Fig. 8. Differences between the

present results and previous studies can be attributed to

genuine differences between in vivo and in vitro tissues,

specimen preparation effects or differences in skin proper-

ties between forearm and other body sites used for the other

studies. To mathematically describe the frequency-depen-

dence of backscatter coef ficients, a power-law fit has been

used for many tissues because backscatter coef ficients typ-

ically tend to increase with frequency. In the case of the

dermis, the backscatter coef ficient computed in this study

does not show such a simple behavior but, rather, increas-

ingly stronger dependence at higher frequencies within the

range 14 to 50 MHz. Such a behavior could result due to

scattering from multiple populations of scatterers in the

dermis. The dermis consists of a network of collagen fibers

whose sizes approximately increase with depth. At the

papillary layer closer to the surface, the fibers are 0.3 to 3

m in size whereas, at the deeper reticular layer, the sizes

are coarser and 10 to 40 m in size (Brown 1972). Scat-

tering at lower frequencies (14 to 30 MHz) could be dom-

inated by the larger-sized collagen fibers, giving rise to a

smaller power-law exponent, and scattering at higher fre-

quencies (30 to 50 MHz) could be dominated by a high

density of small-sized collagen fibers giving rise to a more

Rayleigh-type scattering with a higher value of power-law

exponent. This is broadly consistent with the anatomical

structure of the dermis. If a bimodal distribution of scatter-

ers is assumed for the dermis, previous methods developed

to estimate scatterer sizes from measured backscattered

spectra could be used to estimate mean scatterer sizes for

these two populations, after suitably filtering the data to

select relevant frequency ranges (Lizzi et al. 1987; Insana et

al. 1990). Such analyses have been useful in determining

scatterer sizes in kidney (Insana and Brown 1993), liver

(Lizzi et al. 1987, 1988) and the eye (Lizzi et al. 1987). The

application of such methods to skin tissues will be the

subject of future work. The possibility of complex fre-

quency-dependence of backscatter coef ficient, such as

the presence of resonance patterns, also exists if there

is regularity in the size of scatterers. Such resonance

patterns were not found (even on a single-subject

basis, results not shown) in this study, most probably

due to wide variations in the sizes of the scattering

structures in dermis. Conventional B-scans typically

show that subcutaneous fat is hypoechoic compared to

the dermis, but such a difference has not been quan-

tified previously. The present results indicate that,

within the range 14 to 34 MHz, the integrated (aver-

age) backscatter of the dermis is about 6 times larger

than that of fat (median of ratio of integrated back-

scatter of dermis and that of fat was 6.45). In conven-

tional B-scans, such a difference could get more ex-

aggerated when the compensation for intervening at-

tenuation is based on a smaller value of 0.5 dB cm1

MHz1 typical of soft tissues than the value of 2 dB

cm1 MHz1 for dermis.

Limitations

Effect of epidermis. In this work, while computing

backscatter coef ficients of dermis and fat tissues, com-

Fig. 12. Comparison of in vivo attenuation coef ficients of fat from this study with literature data.




pensation for intervening attenuation was done by as-

suming that the attenuation coef ficient of epidermis is the

same as that of the dermis. The effect of making such an

assumption can be estimated to first order from the in

vitro data of attenuation coef ficients of the epidermis and

the dermis by Moran et al. (1995). From their results, at

a frequency of 26 MHz, the ratio in attenuation between

epidermis and dermis for a round-trip distance of 0.3 mm

(approximately twice the epidermal thickness at the fore-

arm) is calculated to be 0.93 dB or a factor of about 1.24.

This indicates that the backscatter coef ficients of thedermis and fat reported in this work could be lower than

the true value by about 24%. Efforts to determine atten-

uation and backscatter coef ficients of the epidermis at the

fingertip were not successful with the present system due

to the presence of gross inhomogeneities in the epider-

mis. Figure 13 shows B-scan images of the fingertip of

two subjects. Notable is the presence of an interface

below the surface and above the dermis, most probably

corresponding to the transition from the stratum corneum

to the viable epidermis (El Gammal et al. 1999). Al-

though it is possible to separate the sublayers in B-scan

images, efforts to separate them for tissue characteriza-tion were not successful with the present system due to

finite pulse length and the requirement of several win-

dows free of interfaces within each layer to compute

attenuation (and therefore backscatter) coef ficients. The

epidermis is best studied using much higher frequency

systems (e.g., 100 MHz) with shorter pulses.

Hydration effects. Because water is used as a cou-

pling medium in the experiments, hydration effects are

possible during the time of the experiment (about 6 min).

The effect of the hydration on the attenuation and back-

scatter coef ficients cannot be quantified at present but, pre-

sumably due to the barrier function of the stratum corneum

in the epidermis (Kligman 1964), such effects are limited to

only the superficial layers in the skin, and the dermis and fat

are not affected very much. Such effects can also be re-

duced in future studies by using a faster imaging system.

Implications to tissue characterization and future work

At present, excision-biopsy is the “gold standard” for

analysis of skin lesions such as suspected skin tumors. This

is a time-consuming and expensive practice, especially be-

cause the majority of skin lesions are benign. High-fre-

quency US is a promising technique for evaluating skin due

to its ability to penetrate deep tissues (several mm), its low

cost and noninvasiveness. Tissue characterization parame-

ters such as attenuation and backscatter coef ficients have

the potential to aid classification and differentiation be-

tween normal and abnormal skin tissues, as well as between

healthy and malignant tissues. The computation of suchparameters for healthy skin tissues in vivo is an important

step in that direction. Future studies would deal with the

evaluation of such parameters for specific skin lesions.

Moreover, other parameters such as speckle statistics,

Doppler, and elasticity may have the potential for providing

useful information for the evaluation of skin lesions, and are

worth being investigated in further studies. The epidermis

could also be studied using much higher frequency systems.

Acknowledgements—The work reported here was partly supported byNIH grant NS33778 and by a Grant-in-Aid of Research from the

National Academy of Sciences through Sigma Xi.

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