Ultrasound in Med. & Biol., Vol. 33, No. 3, pp. 402–407, 2007Copyright © 2007 World Federation for Ultrasound in Medicine & Biology

Printed in the USA. All rights reserved0301-5629/07/$–see front matter

doi:10.1016/j.ultrasmedbio.2006.08.007

● Original Contribution

THE DETERMINATION OF MUSCLE VOLUME WITH A FREEHAND 3DULTRASONOGRAPHY SYSTEM

RENATE WELLER,* THILO PFAU,* MARTA FERRARI,* RHIANNON GRIFFITH,*TIM BRADFORD,* and ALAN WILSON*†

*Structure and Motion Laboratory, The Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield,Hertfordshire, UK; and †Institute of Human Performance, University College London, The Royal National

Orthopaedic Hospital, Brockley Hill, Stanmore, Middlesex, UK

(Received 6 March 2006; revised 14 August 2006; in final form 24 August 2006)

Abstract—Muscle morphology determines muscle function. An objective method to determine muscle volume invivo will facilitate understanding of basic muscle function and will also provide a valuable tool for the clinicianto assess the effectiveness of treatment. In this method-validation study, it is hypothesised that a freehand 3-Dultrasonography system provides a noninvasive method that allows the determination of muscle volume with highaccuracy and precision. To test the hypotheses, repeated measurements were performed (1) on cadaver musclesin situ, (2) isolated muscles and (3) live animals. Volume measurements performed with 3-D ultrasonographywere compared with measurements based on computed tomography and the water displacement method. Theresults of this study showed that 3-D ultrasound provided excellent precision and accuracy in the measurementson the isolated muscles and good precision in vivo. It is concluded that 3-D ultrasonography is an innovativetechnique that allows objective determination of muscle volume in vivo. (E-mail:rweller@rvc.ac.uk) © 2007World Federation for Ultrasound in Medicine & Biology.

Key Words: 3D ultrasonography, Muscle, Volume, Cross-section, Cross-sectional area, Power.

INTRODUCTION

Muscle morphology including volume, fibre length, fibreangle and cross-sectional area greatly influences musclefunction (Lieber and Friden 2000). The physiologicalcross-sectional area of a muscle (PCSA) is proportionalto the force potential of the muscle and is often used tocalculate the maximum muscle forces and the relativecontribution of specific muscles to the total joint torque(Epstein and Herzog 1998). PCSA is calculated as mus-cle volume/fibre length multiplied by cos(fibre angle).These parameters are usually determined by dissection ofcadaver material. Dissections are, however, not alwayspracticable or ethical and data can only be obtained forone muscle length, which may be nonphysiological.

2D ultrasound has been used for measuring cross-sectional area (Reeves et al. 2004) and estimating musclevolume (Esformes et al. 2002). Muscle length and cross-sectional area change with contraction status of the mus-

Address correspondence to: Renate Weller, Department of Vet-erinary Clinical Sciences, The Royal Veterinary College, Hawkshead

Lane, North Mymms, Hatfield, Hertfordshire, AL9 7TA, UK. E-mail:rweller@rvc.ac.uk

402

cle, whereas muscle volume remains the same. To stan-dardise contraction status, as a prerequisite for repeatablelength and cross-sectional area measurements, may beeasy in humans, but is not in animals. Estimation ofmuscle volume based on 2D ultrasound relies on theassumption that a muscle can be presented geometricallyas a stack of symmetrical truncated cones. While thisprovides a good approximation of, e.g., the gastrocne-mius muscle in humans, it does not hold true for manyother muscles.

In this study, a freehand 3D real-time ultrasonogra-phy system that uses a conventional 2D ultrasound ma-chine in conjunction with a six-degree-of-freedom mag-netic sensor to determine the position and orientation ofthe transducer in space during scanning is investigated(Fig. 1). A stack of B-mode ultrasound images is ac-quired by moving the transducer over the object of in-terest in transverse orientation. While the raw image canbe readily displayed as 2D slices, 3D analysis and visu-alisation requires explicitly defined object boundaries,especially when creating 3D surface models. To create a3D rendering of an object from any stack of images, the

object of interest needs first to be identified within the 2D

Muscle volume with 3D ultrasound ● R. WELLER et al. 403

image and its boundary marked. This is called imagesegmentation. Surface rendering is performed by thesoftware by fitting a polygonal mesh, interpolating thegaps between segmented scans. Quantitative analysis forparameters such as area, perimeter, volume and lengthcan be obtained easily when object boundaries are de-fined and the object is rendered in 3D. The major sourcesof error in 3D reconstruction are the scanning procedureitself and the segmentation process postscanning thatoutlines the area of interest. The accuracies of similar 3Dultrasound systems have been assessed in vitro on iso-lated cadaver muscles (Delcker et al. 1999) and on phan-tom measurements (Leotta and Martin 2000; Ferrari et al.2006), but not in situ. Repeatability has been investigatedin vitro (Delcker et al. 1999) and for the rotator cufftendons in humans in situ (Leotta and Martin 2000).

The aim of this study was to evaluate the precisionand accuracy of a 3D ultrasound system for the determi-nation of muscle volume in vitro and in situ. Threeexperiments were designed: (1) on cadaver muscles insitu, (2) on isolated cadaver muscles and (3) in liveanimals. Volume measurements obtained with 3D ultra-sound were compared with those gained from dissectionand computed tomography (CT).

MATERIALS AND METHODS

3D ultrasonography: Technical set-up and scanning pro-cedure

The 3D ultrasound system used in this study con-sisted of a standard ultrasound machine with a 7.5 MHzlinear ultrasound transducer (Ausonics, Impact VFI,BCF Technology Ltd, Livingston, UK) and a six-degree-of-freedom magnetic tracking system (Minibird, Ascen-sion Technology Corporation, Burlington, VT, USA).

Fig. 1. Schematic drawing of a freehand 3D ultrasound system.Position and orientation of the ultrasound transducer aretracked within a calibrated space by a magnetic sensor. Thesedata are integrated with the images acquired with a standardultrasound machine in STRADX, a LINUX-based software

dedicated to 3D ultrasound.

The magnetic tracking system comprises a transmitter,

which generates a magnetic field, and a sensor, whichwas attached to the ultrasound transducer with electricaltape. Metal objects cause distortion of the magnetic field,resulting in errors in position determination, thus, thetransmitter was mounted on a wood and plastic frameand the water bath was put on a wooden table. A Linux-based, dedicated software (STRADX, Medical ImagingGroup, Engineering Department, Cambridge University,Cambridge, UK) was used to integrate the ultrasoundimages with the positional information from the mag-netic tracking device to compute 3D ultrasound imagesin real-time (Fig. 1). Ultrasound images were transferredfrom the ultrasound machine to the computer via a Linuxsupported video acquisition card. Before scanning, thesystem was calibrated following the calibration protocolas recommended by the software developers (Prager etal. 1998). This involved the definition of the shape of theB-mode images (by simply outlining it on the screen),temporal and spatial calibration. Temporal calibrationallows the software to calculate the delay between thegrabbed B-mode ultrasound scans and the incoming po-sitions from the position sensor. It does this by compar-ing the B-scans with the position information from themagnetic tracking device, while the transducer and theattached sensor are moved up and down in a water bath.By maximising the correlation between these two datasources across several seconds of probe movement, tem-poral calibration to within �5 ms is possible. Spatialcalibration is nothing more than the coordinate transfor-mation from the ultrasound scan plane to the receiver ofthe magnetic tracking system. This is achieved by mov-ing the transducer with the attached magnetic sensor in awater bath, involving three angular and three transla-tional movements in relation to the position sensor trans-mitter. The location of the plane being imaged by theprobe is also unknown and must be estimated by thespatial calibration process. Repeating the motions move-ments in three different locations will provide sufficientconstraints for the location of this plane to be deter-mined.

A stack of 2D ultrasound images was acquired bymoving the ultrasound transducer over the length of themuscle in transverse orientation at a steady speed. Ac-quisition rate was set to 25 frames per second. In objectswhose diameter was less than the length of the transducer(6 cm), a single sweep was sufficient; in bigger objects,two or more parallel sweeps were necessary to cover thewhole width of the muscle. In the post scanning process,the software allows for placement of dividing planes, sothat areas overlapping on adjacent sweeps would only beaccounted for once in the segmentation and, hence, in themeasurements (Fig. 2). Segmentation was performedmanually by drawing around the perimeter of the object

of interest in each 2D ultrasound image. Length, cross-

e is the

404 Ultrasound in Medicine and Biology Volume 33, Number 3, 2007

sectional area and volume were then measured with thebuilt-in measurement features of the software. All scanswere performed by the same operator.

Experiment 1: In situ cadaver measurementsTwo dog cadavers (female, skeletally mature Grey-

hounds), euthanized for reasons unrelated to the study,were used in this experiment. The cadavers had beenfrozen within 3 h of death and were left to defrost atroom temperature for 24 h before the experiment. Ultra-sonographic images were acquired of the vastus lateralis,the biceps femoris, the semitendinosus and the semi-membranosus muscles of each side. The cadavers wereput in lateral recumbency on a wooden table within thecalibrated area. The area of interest was cleaned withwater and detergent and coupling gel was applied toensure optimal transducer contact. The origin and inser-tion of each muscle were identified and its outline wasmarked with a piece of string to assist orientation. Eachmuscle was scanned twice and the postscanning segmen-tation was repeated twice to assess the repeatability ofthe system at each level.

Experiment 2: Measurements on isolated muscleThe accuracy of the system was assessed by com-

paring the measurements based on 3D ultrasound with

Fig. 2. Multisweep technique: the diameter of the object(a) Shows the outline of the scan as three parallel overlsquare representing a single B-mode ultrasound image; bare discarded from segmentation; two dividing planes sep(b) Shows a series of three images, the cyan line ouoverlapping areas on adjacent sweeps. (c) Shows the w

structure. The object in this pictur

measurements obtained with CT and the water displace-

ment method. After the in situ experiment was com-pleted, the vastus lateralis, the biceps femoris, the semi-membranosus and the semitendinosus were removedfrom both hindlimbs and the 3D ultrasound was repeatedwith the muscles placed in a water bath. The volumes ofthe muscles were also measured with the water displace-ment method by submerging them in water in a cali-brated measuring cylinder. In a third step, the volume ofthe isolated muscles was determined by performing a CTscan (Picker 5000, Philips Medical, Reigate, Surrey, UK)with a slice thickness of 5 mm and an index of 5 mm.Segmentation and surface rendering of the CT imageswas performed in Mimics (Materialise Inc., Technolo-gielaan, Leuven, Belgium).

Experiment 3: Live animalsIn this experiment, the use of the system with re-

gards to repeatability and practical consideration in livedogs was tested. These experiments complied with legalrequirements and the institutional requirements and wereapproved by the Royal Veterinary College’s ethics com-mittee.

Two live dogs (female, skeletally mature, one short-haired Labrador and one long-haired Australian Shep-herd) were used in this experiment. The dogs were askedto lay in lateral recumbency on a wooden table with their

est is larger than the length of the ultrasound transducer.stacks of B-mode ultrasound images, with each white

ares are B-mode images between parallel swipes, whichhe stacks to identify overlapping areas for segmentation.the area of interest and the thatched area indicating

object in 3D after surface rendering of the segmentedbiceps femoris muscle of a dog.

of interappinglue squarate ttlining

hole

hindlimb within the calibrated area. The outline of the

Muscle volume with 3D ultrasound ● R. WELLER et al. 405

muscles was identified by palpation. The skin over thequadriceps and hamstring muscles was cleaned with wa-ter and detergent and coupling gel applied. Two 3Dtransverse ultrasound scans were acquired for each mus-cle and the segmentation process was repeated twice oneach scan.

The accuracy of muscle volume measurements with3D ultrasound depends on the number of segmentedframes per length unit and thus depends on the frame rateof the system and on the speed with which the transduceris moved over the object. The magnitude of the change inaccuracy depends on the uniformity of the cross-sec-tional area of the muscle over its length. If the object ofinterest is a regular cylinder with a uniform cross-sec-tional area over its whole length, it would be enough tosegment the first and the last frame of the whole scan toobtain an accurate measurement. Muscles, however, donot have a uniform cross-sectional area and ideally, thespace between segmented frames should be as small aspossible; this, however, increases the time required forpostprocessing. To assess the influence of number offrames per unit length, one isolated muscle was seg-mented every 5, 10, 20 and 50 mm.

Data analysisThe accuracy of the system was evaluated in ca-

daver muscles by comparing 3D ultrasound measure-ments with measurements obtained from the water dis-placement method and CT scans. For 3D ultrasound, themean of the repeat scans and segmentation was used forcomparison. The measurements obtained by the threedifferent methods were compared by determining the95% limits of agreement between each pair of methods(Bland and Altman 1986). The 95% limits of agreementwere determined by calculating the difference betweeneach pair of measurements and then calculating the av-erage and the standard deviation of all of these differ-ences (within-subject standard deviation sw). To calcu-late the upper 95% limit of agreement, 1.96 � sw wasadded to the average difference and, to calculate thelower 95% limit of agreement, 1.96 � sw was subtractedfrom the average difference. If the differences are nor-mally distributed and independent of the magnitude ofthe measurement, 95% of the differences should fallwithin the width of the 95% limits of agreement. Nor-mality was assessed with a Kolmogorov-Smirnov testand the relationship between the mean of the measure-ments and the difference was determined by calculatingthe Pearson correlation coefficient. Precision of the 3Dultrasound measurements was assessed for the in situmeasurements, the measurements on isolated musclesand on the live dogs by determining the repeatabilitycoefficient. The repeatability coefficient is defined as

��2�*1.96 *sw or 2.77 *sw. The difference between two

measurements for the same subject is expected to be lessthan 2.77 sw for 95% of pairs of observations (Bland andAltman 1986). The precision was assessed at two levels,the segmentation and the scanning procedures. For theassessment of the precision of the scanning procedure,the average of the two segmentation measurements wasused. The standard error se of sw was estimated bysw ⁄��2n�m�1��, where n is the number of muscles andm the number of repeat measurements; hence se

� sw ⁄��2�8�2�1�� � sw ⁄4.

RESULTS

Technical considerationsThe procedure was well tolerated by the live dogs.

Clipping was not necessary in the cadaver Greyhoundsand in the long-haired Australian Shepherd; in the La-brador (shorter, but thicker hair), however, the fur had tobe clipped to ensure images of sufficient quality. Thor-ough cleansing and generous application of coupling gelwas necessary to maintain transducer contact.

Thorough anatomical knowledge is needed to iden-tify the outline of the muscles and the muscle borderswere more readily identified in the live dogs than in thecadaver dogs. This is thought to be due to the loss ofmuscle tone and the effect of freezing and defrosting.

An overlap of adjacent scans of about a third of thewidth of the scans was necessary to ensure coverage ofthe whole muscle (Fig. 2). The sweeps had to be paralleland the transducer orthogonal to the skin surface tomaintain sufficient overlap at all times. Lack of overlapresulted in gaps in the 3D-rendered muscle and, hence, ininaccuracies in the measurement of the muscle volume.The biceps femoris and vastus lateralis muscles requiredthree sweeps, semimembranosus and semitendinosus twosweeps. In the postscanning process, dividing planeswere placed so that areas overlapping on adjacent sweepswould only be accounted for once in the segmentationand, hence, in the measurements (Fig. 2). This includedthe identification of the invalid scans when the trans-ducer was returned to the starting position in betweensweeps. This was facilitated by moving the transducerclearly away from the muscle.

Image acquisition took about 5 min per muscle,including identification of the muscle outline. Speed ofthe transducer movement was approximately 3 cm/s.Time for postprocessing was largely dependent on thenumber of frames used for segmentation and, hence, onthe length of the muscle and on the number of frames permuscle unit. In the example of the canine semimembra-nosus muscle, the volume measurement decreased whenincreasing the distance between segmented frames and,hence, decreasing the total number of segmented frames:

the volume was measured at 111 mL when segmenting

406 Ultrasound in Medicine and Biology Volume 33, Number 3, 2007

every 5 mm, 108 mL when segmenting every 10 mm, 97mL when segmenting every 20 mm and 64 mL whensegmenting every 50 mm, over a whole muscle length of220 mm. For the subsequent accuracy and precisionstudies, frames every 5 mm were segmented.

Accuracy of the 3D ultrasound system in isolated mus-cles

The differences in volume measurements between3D ultrasound, CT and water displacement methods werenormally distributed and did not correlate significantlywith the magnitude of measurements. Table 1 lists theminimum, maximum, average, standard deviation of thedifferences and upper and lower limits of agreement foreach pair of methods. The best agreement was found for3D ultrasound and the water displacement method, witha width of the 95% limits of agreement of 8 mL. Theleast agreement was found for CT and the water dis-placement method, with a width of the 95% limits ofagreement of 17 mL.

Precision of 3D ultrasoundTables 2 and 3 list the repeatability coefficients for

the segmentation and the whole scanning process forcadaver muscles in situ, for isolated muscles and for liveanimals. The differences between repeat scans/segmen-tations were normally distributed and independent of themagnitude of the measurement. The repeatability coeffi-cients for the whole scanning process are generally larger

Table 1. Comparison of volume measurements in isolatedmuscles based on 3D ultrasound (3D US), computed

tomography (CT), and water displacement method (WD)

Meandifference

Standarddeviation of the

differences

Lower 95%limit of

agreement

Upper 95%limit of

agreement

3D US and CT 3.33 4.37 �5.24 17.143D US and WD �1.38 2.37 �6.02 3.27CT and WD 4.70 4.89 �4.87 14.28

The mean difference, the standard deviation of the differences andthe upper 95% and lower 95% limits of agreement of the differencesare listed. All measurements are in mL.

Table 2. Precision of the segmentation process in cadavermuscles in situ, isolated muscles and in live dogs

SegmentationAverage

differenceStandarddeviation

Repeatabilitycoefficient

In situ cadaver muscles 1.08 0.48 1.32Isolated muscles 0.39 0.31 0.86Live dogs 0.58 0.33 0.92

The table lists the average, the standard deviation of the differencesand the repeatability coefficient. All measurements are in mL.

than those associated with the segmentation processalone. This is not surprising, since the scanning processincorporates the segmentation process. The smallest re-peatability coefficients were found for the isolated mus-cles, the largest for the cadaver muscles in situ. Therepeatability coefficients for the live animal were smallerthan those found in the in situ cadaver muscles. Thelargest repeatability coefficient observed was under 5mL, which equates to less than 5% when looking at thesmallest muscle scanned in this study. The standard errorfor the within-subject standard deviation was below 0.12mL for the segmentation process and below 0.4 mL forthe whole scanning process.

DISCUSSION

The freehand 3D ultrasound system evaluated inthis study proved to be as accurate and precise as con-ventional dissection-based methods, such as the waterdisplacement method or tomographic imaging methods(in this study, CT), for the measurement of muscle vol-ume. However, the accuracy and precision required dif-fers with the research question asked and it has to bedecided for each study whether or not the accuracy andprecision of the system is sufficient.

The system is noninvasive and was well-toleratedby the animals, which makes it a valuable tool to gainmuscle data for, e.g., computer modeling or to assess theeffect of physiotherapeutic treatment regimes in livesubjects.

In contrast to other 3D ultrasound systems, thefreehand approach allows the scanning of larger objectsby combining multiple sweeps. Since most muscles’diameter exceeds the length of ultrasound transducers,this is of considerable advantage, especially in musculo-skeletal research.

Repeatability was found to be better in isolatedmuscles compared with muscles in situ; while scanningisolated muscles in a water bath can be performed inparallel sweeps at equal height, when scanning musclesin situ, the transducer has to follow the contour of themuscle while maintaining sufficient overlap between

Table 3. Precision of the scanning process in cadavermuscles in situ, isolated muscles and in live dogs

Scanning procedureAverage

differenceStandarddeviation

Repeatabilitycoefficient

In situ cadaver muscles 1.76 1.78 4.94Isolated muscles 0.52 0.49 1.36Live dogs 0.83 1.10 3.04

The table lists the average, the standard deviation of the differencesand the repeatability coefficient. All measurements are in mL.

scans and parallel orientation of the transducer. In situ

Muscle volume with 3D ultrasound ● R. WELLER et al. 407

muscle measurements in live dogs were more repeatablethan in cadaver dogs. This was largely due to the fact thatthe borders of the muscles were more distinct in the liveanimals compared with the cadaver muscles and, hence,were more easily identified during scanning and segmen-tation. Autolysis of the soft tissues separating the differ-ent muscles during freezing and defrosting of the cadav-ers might account for this.

To be able to use 3D ultrasound for volume measure-ments, the muscle borders have to be visible over theirwhole length. This limits its use, firstly, to muscles that arewithin the depth of penetration of the transducer and, sec-ondly, to muscles with clearly identifiable borders. Thelatter can pose a problem if muscles are partly fused to othermuscles, or insert on not very well-defined aponeuroses.

The presented method allows the measurement ofcross-sectional area at each level along the muscle ten-don unit. Determination of cross-sectional area also al-lows for the calculation of the stress experienced by themuscle/tendon at each level and, hence, is important inunderstanding pathogenesis of injuries (Lieber and Fri-den 2000; 2001). In the live animal, in particular, it canbe difficult to keep the transducer orientated orthogo-nally to the long axis of the muscle tendon unit at alltimes and distortion of the cross-section can occur. Byreslicing the image stack at an orthogonal angle, theimages can be resampled and the true cross-sectionalarea measured.

The length of the muscle tendon unit as a whole aswell as the exact location of the muscle-tendon junctioncan also be determined, which provides information of-ten essential for, e.g., the correct placement of electro-myelography electrodes.

The freehand system presented in the study com-bines a magnetic tracking device with a clinically usedultrasound machine, but other authors have shown thatthe system can also be used in conjunction with anoptical motion analysis system to track the ultrasoundtransducer in space. Since motion analysis systems areinstalled in most gait laboratories and ultrasound ma-chines are commonly used in hospitals, the system can berelatively inexpensive. The time required for setting-upand calibrating the system before scanning and process-ing of the data after the scan makes the system tootime-consuming (and hence expensive) to be used within

a clinical setting at the present time. The permanent

installation of a 3D ultrasound set-up reduces the time,but requires the purchase of a dedicated ultrasound ma-chine and the availability of space that can be perma-nently occupied by the system. Further advancement inautomated image segmentation might lead to a decreasein the time needed for postprocessing in the future andmay lead to the development of time-efficient systemsthat will find more widespread use within clinical set-tings.

CONCLUSION

Objective measurement techniques with high accuracyand precision are a prerequisite of evidence-based medi-cine, both in research and in clinical work. 3D ultrasonog-raphy provides such a technique for the assessment ofmuscle volume and has furthermore the advantage of beingnoninvasive and relatively inexpensive.

Acknowledgments—The authors thank Karin Jespers and Christina vonScheven for help with data collection, Anna Wilson and Emma Tole forhelp with the manuscript and the BBSRC and the German Science Foun-dation for funding (DFG Emmy Noether Program WE 2180/1 to 1).

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