AJR:169, July 1997 101

Estimation of the Left VentricularEjection Fraction Using a NovelMultiphase, Dark-Blood,Breath-Hold MR ImagingTechnique

Shantanu Sinha1Richard Mather1Usha Sinha1Jonathan Goldin1Gregory Fona row2Hyo-Chun Yoon1

OBJECTIVE. In this paper, we evaluate a recently pro�x)sed dual-phase dark-blood MR se-

quence for estimating the left ventricular ejection fraction, compare Simpson’s method of estinla-

tion of ejection fraction with a model based on the biplane method. assess the reproducibility of

both nlethods, and fiiially. test a semiautomated niethod for contouring the endocardial border.

SUBJECTS AND METHODS. An MR pulse sequence was implen�ented to acquire cardiac

images itt Ifotli diastolic ;uld systolic phases within a single breath-hold. A special magnetization

prepa�ation scheille rendered blood dark while a segmciited acquisition allowed breath-hold scantimes. Five healthy volunteers �md five patients with cardiac disease were imaged. Ejection fractions

were estimated using ( 1 ) long-axis and four-chaniber biplane views with :ui ellipsoid mxlel �uxl (2)

a series of short-axis views in conthination with Simpson’s model. These values of ejection frac-

tions were then compared with values obtained tiom echocardiography.

RESULTS. Estiniates of ejection llactiotls obtained using biplane ellipsoid volume and Simp-

SOIl’S rule methods varied by l4�/ in healthy volunteers. However, for patients with severe car-

dion�yopathy, differences between the values of ejection traction obtained with the two methods

varied by as much as 1 5O�k . Ejection fraction estimates obtained from MR inutges with the hi-

plane ellipsoid ulethod at�l fIonl echocardiography varied by approximately l4�X for all sub-jects. Ejection fraction estiit�ttes obtaitied with the seiniautoinated algoritlini agreed well with

estinlates obtained with ii�anual contours made by experienced radiologists. lntraohserver van-

ability was low for both the short-axis (3(/ ) and biplane (4(/ ) methods. 1-lowever, interobsenver

variability of the biplane n�ethod ( I 2�/ ) exceeded that of the shont-axis method (4�% ). lntenex-

;ti�ination vaniahility (9Y ) was the largest litctor in detenuining the reproducibility of the ejec-

tion fraction estiniates.

CONCLUSION. Breath-hold dark-blood MR inlaging technique with sinlultaneous acqui-

sition of a series of short-axis views during systolic and diastolic Phases pemlits rapid and accu-

rate estimates Of ejection fnactions in healthy subjects and in p�ttients. Model-based biplane MR

iniaging methods are less reliable in patients with global cardion�yopathy. The estinlation of

ejection fractions can he automated using the proposed contouring algonithu� aixl the (lark-blood

short-axis views.

Received May 14, 1996; accepted after revisionJanuary22, 1997.

Presented at the annual meeting of the AmericanRoentgen Ray Society, San Diego, May 1996.

1 Department of Radiological Sciences, UCLA School of

Medicine, Los Angeles, CA 90095-1721. Addresscorrespondence to S. Sinha, Department of RadiologicalSciences, 82-220 CHS, UCLA Medical Center,10833 Le Conte Ave., Los Angeles, CA 90095-1721.

2Department of Cardiology, UCLA School of Medicine,

Los Angeles, CA 90095-1721.

AJR 1997;169:101-1 12

0361-803X/97/1 691- 101

© American Roentgen Ray Society

T he inherent soil-tissue contrast of

MR iniaging conuhined with necent

improvements in hardware and soft-

ware capabilities has significantly increased its

potential as an iniaging technique for non-

invasive assessn�ent of cartliac function. This

increased potential includes detennining left

ventricular v(.)lulfles, ejection fraction, mass,

wall i�otion ahnoniialities, �uid functional mt or-

nlation such as i11yoc�u’dial perfusion in patients

with congenital or acquired heart disease 1 1-41.

Geometry-based methods of estintation of the

left ventricular volume and mass, such as the

single-plane and biphule ellipsoidal niethods.

have leen conventionally used in ech(x.ardiog-

mph)’ (5 . These geometry-based metliids have

also been applied to the assessment of ventnicu-

lat’ volumes 110111 MR imaging in � el’firt to t’e-

duce scan times 161. Though these methods

have the adv;ultage of’ reduced imaging tinles.

they are based 011 the ellipsoidal shell t1�xlel of

the left ventricle, which requires axial symnle-

try ol’ the left ventricle atxut its long axis

throughout the c�trdiac cycle. ;ui assunlptmon of-

ten invalid in patients with ii�yocardial disease.

In contrast, volunle estimates lr’oiii a series of’

short-axis views using Simpson’s rule do not

use any geolnetnc asswnptions :111(1yield accu-

Note-Echo. = echocardiography, N/A � not available.

Sinha et al.

102 AJR:169, July 1997

rate volumes. However, the disadvantage of the

latter technique lies in the relatively longer ac-

quisition times. Each short-axis view requires a

separate acquisition and furthermore, in the esti-

mation of ejection fractions and wall motion ab-

normalities, each view needs to be acquired in

different cardiac phases.

In estimating global cardiac parameters,

contouring of the epicardial and endocardial

borders is an important step. Automated meth-

ods of segmenting the left ventricle and myo-

cardium are desirable not only to reduce the

time and effort that would otherwise be in-

volved in contouring the many images but also

to minimize interobserver and intraobserver

variabilities. Semiautomated methods of myo-

cardial segmentation have been attempted by

various groups, generally using bright-blood

images that depict blood as brighter than

myocardium. The efficacy of segmentation de-

pends essentially on two factors: good blood-

myocardium contrast and uniform blood signal

intensity. Obtaining bright-blood breath-hold

images is relatively easy using a segmented

fast gradient-echo technique, but these images

have variable blood signal intensities that are

dependent on the cardiac phase. Also, blood-

myocardium contrast may be suboptimal in

some images: these images, therefore, are not

always amenable to an automatic contouring

method [4]. Thus, it is desirable to suppress the

blood signal intensity to obtain both high myo-

cardium-blood contrast and uniformity of

blood signal intensity to facilitate automation

of endocardial border detection.

We recently proposed a new scheme to si-

multaneously acquire diastolic and systolic

images of the heart in the same R-R interval

in breath-hold times [7]. This study had four

objectives.

The first objective was to evaluate the ul-

trafast sequence for estimation of the left yen-

tricular ejection fraction using a series of

short-axis slices covering the heart from the

apex to the base (Simpson’s rule).

The second objective was to compare this

geometry-independent method of estimating

ejection fraction with that obtained from a

model-based ellipsoid biplane method. The

latter method involves acquisition of only two

planes so that if this biplane method can be

shown to have accuracy and reproducibility

comparable to those of the Simpson’s rule

method. using the biplane method will repre-

sent a considerable savings in scan time.

The third objective was to assess the repro-

ducibility of left ventricular ejection fraction

measurements obtained using Simpson’s rule

method and the biplane ellipsoid method. The

calculation of the left ventricular ejection

fraction from the short-axis images requires

either manual or computer-assisted outlining

of the endocardial borders. Similarly. the esti-

mation of left ventricular ejection fraction

from the biplane views requires a manual

measurement of certain left ventricular di-

mensions. Both the manual outlining and the

manual measurements are prone to inter- and

intraobserver variabilities.

The fourth objective was to test an en-

docardial border detection algorithm by com-

parison of the ejection fractions derived by the

semiautomated method with those from the

manual contouring by experienced radiolo-

gists. The manual method of contouring the

endocardial borders is both time-consuming

and prone to operator variabilities. The semi-

automated algorithm for contouring the en-

docardial borders was developed in-house

(Sinha 5, unpublished data).

Evaluation of the two methods of ejection

fraction estimation involved comparison with

the clinical technique used at our site for global

cardiac function evaluation-that is, echocardi-

ography. Echocardiography was not taken as a

gold standard because the potential problems

that limit accuracy of ejection fraction estima-

tion using this technique are well known and

are discussed later. Rather. such comparisons

were made essentially because echocardiog-

raphy is the routine clinical method for evaluat-

ing cardiac parameters.

Subjects and Methods

Study Design

The dark-blood dual-phase sequence was used to

acquire cardiac images in five healthy volunteers

(subjects I. 2, 3. 5, and 9) with no history of cardiac

disease. and five cardiac patients (subjects 4, 6. 7. 8,

and 10) from whom informed consent was obtained

(Table I ). The average age for the healthy subjects

was 33 years old. Patients 4 and 10 were suffering

from severe global cardiomyopathy. and patients 6,

7. and 8 had a history of myocardial infarction.

Echocardiography scans were obtained for all

healthy volunteers by an experienced technologist,

and patient echocardiography data were obtained

from the patient’s most recent study. To assess the

reproducibility of the measurements, healthy volun-

teers 1 and 3 were scanned in the MR scanner onthree different occasions.

MR Imaging

ECG-gated cardiac MR images of all subjects

were acquired on a I .5-T MR scanner (Magnetom

Vision; Siemens Medical Systems, Iselin, NJ). Sub-

jects were scanned lying supine with ECG electrodes

on the anterior chest wall. A circularly polarized.

phased array body coil. provided commercially by

Siemens. yielded excellent image quality uniformly

throughout the chest region.Dark-bloodturbo fast low-angle shot (turboFLASH) cardiac

images acquired in breath-hold times has been pro-

posed earlier 18. 9J. However. these sequences per-

mitted acquisition only during diastole and could

not be used for estimating ejection fractions be-

cause such estimations require determination of left

ventricular volumes both in end diastole and in end

systole. We designed a magnetization-prepared seg-

mented turboFLASH sequence to simultaneously

acquire images at these two cardiac phases (end di-

astole and end systole). The details of the sequence

are given in the study by Sinha and Sinha 171 and

are summarized in the following text. The magneti-

zation preparation period consists of two 180#{176}RF

pulses designed to selectively suppress blood signal

(Fig. 1). The first l80� pulse is non-slice-selective

and inverts spins from the entire volume. The see-

ond 180#{176}RF pulse is slice-selective and thus re-

stores the spins in the slice of interest to

equilibrium. Magnetization of the static spins in the

slice is recovered, whereas that of blood flowing

into the slice remains inverted. In the single phase

acquisition during diastole. the signal from blood is

minimized by positioning the acquisitioll window

near the null point (T��ii) of blood (8. 91. In the

present scheme of dual-phase images. however. the

two acquisitions are placed symmetrically about

Tnuti. We have shown earlier. from both theoretic

considerations and experimental observations. that

for typical choice of sequence parameters. blood is

suppressed by a factor of 0.3 of its maximum value

at either acquisition [7]. Furthermore. the sequence

is run in a segmented mode that implies the collec-

tion of several lines of K-space in one acquisition

window. Artifacts from the increased motion of the

heart at systole were niinimized by optimizing the

T��ii i

T�,j

(1)(2)

(3)

Fig. 1.-Sequence diagram for dual-phase dark-blood segmented K-space acquisition (five, seven, nine, 11, or13 lines per segment) shows two acquisitions positioned at end-systolic and end-diastolic cardiac phases withtimings set using equations 1-3. Blood signal is suppressed by positioning two acquisitions symmetrically aroundzero-point crossing of inverted blood magnetization, Tnull’ Pressure wave was not measured but is shown to helpidentify relative time points of acquisition windows. The it pulses refer to 180#{176}RF pulses required for magnetiza-tion preparation, whereas a pulses are RF pulses for segmented gradient echoes. Td = delay of preparation pulsesfrom R-wave, T1= delay between preparation pulses and start offirst acquisition, 2T8� total time of segmentedacquisition, I� = time interval between end of first acquisition and beginning of second. Tes time to end systole,

Ted time to end diastole.

�l 4�

�e 20

�e -20

�-40

I�

slrww._2� �

�- --- �--

�

:��i

VT� or T�

4-912Taq

Time

Fig. 2.-Schematic of phase reordering shows relative position of end-diastolic and end-systolic time points (154phase lines, 11 lines per segment). During each R�R interval, phase-encoding levels shown in one segment (Seg. 1,Seg. 2) are traversed once each in end-diastolic (Ted) and end-systolic (Tes) time points. Note that end-diastolic andend-systolic time points are centered in acquisition windows (2Taq) where low K-space lines are acquired first.

MR Imaging of Left Ventricular Ejection Fraction

AJR:169, July 1997 103

length of the acquisition window (which for a fixed

TR ofthe turboFLASH sequence increases with the

number of K-space lines in the segment). The tim-ings Ii,, the time interval between the end of the

first acquisition and the beginning ofthe second; T�,the interval between the preparation pulses and the

beginning of the first acquisition; and Td’ �e inter-val between the R-wave and the preparation pulses

(Fig. 1) of the sequence, are adjusted by the opera-

tor so that the acquisitions, each of duration 2Taq’

are centered at end systole, I�, and at end diastole,T�, around TraIl’ the time at which the magnetiza-

tion of blood spins goes through zero, according to

the equations:

I� = (Ted _T��) -

1 = Tnull - 2Taq _(I�/ 2),

Td(TesTaq)h1.

An initial cine scout scan was used to detetminethe temporal location of the end-diastolic (T�) and

end-systolic (Tes) �&dftit fr�tfl�S. ThC timings are

referenced to the start of the R-wave trigger. Two ac-

quisition windows, each of a duration of 70 msec

centered around the end-systolic and the end-dia-

stolic time points, serve to acquire the images at the

two phases. Both nequisition windows are within the

same R-R interval (Fig. 1). In each such acquisitionsegment� 11 phase-encodinglthes are acquired. Thesephase tines are sequentially reordered with the cen-

tral K-space lines in the middle of the acquisitionwindow (Fig. 2). The end-diastolic and end-systolic

tune points were centered on the respective acquisi-

tion windows (i.e., on the central K-space lines).The schemejust described works well for spatial

locations from the apex tojust beyond the mid yen-

tricle level. Cardiac motion is more pronounced to-

ward the base of the heart than at the apex [10].This severe motion of the more basal slices results

in loss of myocardia.l signal intensity in the systolic

phase because of saturated spins outside the slice ofinterest moving into the slice. The problem was cir-

cumvented by positioning the preparatory inversionpulses at systole and acquiring the slice in the fol-

lowing R-R interval at the same cardiac phase

during systole. The end-diastolic acquisition isunchanged. The excellent image quality obtainedusing this variation of the pulse sequence is shownin the Results section. This latter scheme, which

stretches each segmented acquisition to two R-R in-

tervals, is used only for the basal slices.The imaging protocol consisted of first acquiring

scout scans to locate the long-axis, short-axis, and

four-chamber views (the long-axis view is equivalentto the vertical long-axis view, and the four-chamberview is equivalent to the horizontal long-axis view).This step was followed by a cine scan in the short-

axis view at the level of the mid ventricle to accu-

rately determine � and I�,j. A direct examination ofthe ECG signal should be sufficient to locate the sys-

tolic and diastolic time points, but our experienceshowed that the cine scans were able to locate more

accurately and consistently the required cardiac

phases. The cine sequence (TR � 12 msec), permit-

(4)

ted acquisitions of 18-22 temporal slices (depending

on the R-R interval of the subject). These multiphase

cine images of the same slice were then examined vi-

sually, and the end-systolic and end-diastolic frames

were identified by the smallest and largest endocar-

dial areas. respectively, of the left ventricular cham-ber. The dual-phase dark-blood images were then

acquired under breath-hold conditions with the two

acquisition window locations determined from the

cine scan and other sequence timings determined

from equations 1-3. Typical values of these timings

are as follows: R-R, 800 msec; T�, 6&) msec; T�,

335 msec; I�, 240 msec; I�, 275 msec; and Td’

I 7 msec. I� and Td were adjusted for each subject toobtain the best blood suppression. The image planes

acquired with the dark-blood sequence were a long-

axis view, a four-chamber view, and a series of con-

tiguous short-axis views from apex to base. Each

breath-hold acquisition yielded images of the sameslice at the two points in the cardiac cycle in l6to apeproximately 21 sec. A pause of 6 to approximately

10 sec was allowed between scans. Optimization of

sequence parameters led to the following choices for

the dual-phase cardiac acquisitions reported here:(I) TRItE of the tUTbOFLASH acquisition, 6.3/3.2

msec; field ofview, 45#{176};(2) number ofK-space linesand segments, 11 (resulting in an acquisition window

of 70 msec); and (3) geometry parameters: slicethickness, 10 mm; field of view, 230-250 mm; spac-

ing, contiguous.

For the purposes of comparison with the tech-

nique most commonly used at present, we also ac-quired bright-blood breath-hold images for onevolunteer with scan parameters similar to those used

for the dark-blood images. Because these imageswere acquired to facilitate a direct comparison withdark- and bright-blood images obtained under simi-

lar conditions and in the same scan time, we used a

segmented breath-hold turboFLASH cine scan.

Echocardiogrophy

Echocardiography was performed on all healthyvolunteers to obtain long-axis and four-chamber

views during end systole and end diastole. All im-

aging was performed on an AlL Ultramark 9 (Ad-

vanced Techniques Laboratory, Bothell, WA) with

a 2.25-MHz phased array transducer. All patients

had echocardiography within I month before theMR imaging study. No patient had therapeutic in-

tervention between the time of echocardiographyand the MR imaging study. In addition, histories

obtained from all patients revealed no significantchange in symptomatology related to their cardio-myopathy between studies.

Left Ventricular Volume Estimation

From MR short-avis images-Simpson’s rulewas used to directly measure the left ventricular vol-

umes from the set of endocardial contours of theshort-axis images. The end-diastolic and end-sys-

tolic chamber volume of the left ventricle were oh-tamed by integrating the areas bound by the

endocardial contours (in the two cardiac phases) and

multiplying by the section thickness. The cardiac

(5)

Sinha et al.

104 AJR:169, July 1997

contours were outlined manually, once for all the

subjects, by two experienced cardiovascular radiolo-gists. In addition, the intraobserver variability was

estimated by each radiologist repeating the manualcontouring of particular studies (three times for each

study). These studies were the repeated MR exami-nations on subjects I and 3. Finally, the contours

were also determined using a semiautomated algo-

rithm (briefly described in the following text).

From the dual-plane MR images-The ventricu-

lar volumes (V) from the long-axis and four-cham-

her images were calculated using the equation [1 11:

(irL� (4A� (4A2V=I- lxi Xl

�6) tjrDi) �jtD2

where L = long-axis length of the ventricle, Al =

cross-sectional area at the mid papillary muscle level

on the long-axis view, DI = diameter at the mid pap-

illary muscle level on the long-axis view, A2 =

cross-sectional area at the mid papillary muscle levelon the four-chamber view, D2 = diameter at the mid

papillary muscle level on the four-chamber view.

Given the geometric constraint, A = ir(D I 2)2, thevolume reduces to the formula:

v= DIXD2X(�

The measurements of Dl , D2, and L for each sub-ject were again performed by the two radiologists

with repeated measurements on the same scans asfor the short-axis views.

Front echocardiography.-Ventricular volumes

were calculated using biplane apical views with a

modified Simpson’s rule approach [1 1]:

V = � � D.D x4s..l �20

where the length L of the ventricle is divided into

20 disks (i = 1 to i = 20) from base to apex with thediameters, Dl and D2, of each disk determined in

two apical views, four-chamber and long-axis.

Morphologic Measurements from MR Images

Manual techniques-Images were transferred

from the MR host computer to a SPARC5 work-station (Sun Microsystems, Mountain View, CA)

for image analysis. Images were displayed en-larged by a factor of 2 to facilitate manual mea-

surement.s. Endocardial borders were traced using

the mouse, and the algorithm calculated the num-

ber of pixels inside the trace. Distance measure-

ments were made subsequent to the user’s clickingat appropriate start and end points.

Semiautomated image pux-essing.--Image pro-cessing was performed on a SPARC5 workstationwith image processing tools (median filter, erosion

and dilation morphologic operators) based on the ap-plications software SunVision (an image processing

applications package) (Sun Microsystems). The algo-rithm locates both the endocardial and epicardial bor-

ders but, for the sake of brevity, only the stage

corresponding to the endocardial border detection isdescribed in the following text. The process is similar

to that for detecting the epicardial border. The userinitiates the program forthe isolation ofthe left ventri-

dc by identifying the approximate center of the leftventricle and a region of interest encompassing the

left ventricle. The histogram of the region of interestis displayed on a panel that essentially consists ofthree peaks corresponding to the background (and

blood), myocardium, and fat. On an intensity scale of0-255, typical blood signal intensity is less than 2&,

myocardium signal intensity ranges from 28 to 75,

and fat signal intensity is greater than 75. The user

sets the lower threshold interactively on the histo-

gram. The image is first changed to black and white

so that only pixels with values equal to or less than thelower threshold are set to white and all others are set

to black. The next step is to isolate the region spatially

connected to the center of the left ventricle (the user-defined center). The size of the isolated region is

checked against preset values. and the object is

eroded until the criterion is met. The size criterion

serves to break false connections to large isointense

objects such as the chest wall and liver. Each erosion

is followed by a connectivity operation to isolate the

new area. The connectivity algorithm isolates thestructure in which all pixels are connected to the seed

pixel through their four nearest neighbors. Once the

size criterion is fulfilled, the image is dilated the samenumber oftimes that it was eroded. The dilation is fol-

lowed by a sequential contouring algorithm that iden-tifies the endocardial border pixel that can then be

used for subsequent calculations of ejection fraction.

A 3 x 3 rectangular structuring element is used for the

morphologic operations of both erosion and dilation.

Erosion diminishes the isolated volume, removes sub-volumes that do not fill out the structuring element,

(6) and forces spatial isolation by breaking false connec-

tions. Dilation enlarges the volume and fills holes and

indentations that are smaller than or equal to the struc-turing element. The epicardial surface was also con-

toured by a similar procedure but was not used in anyof our calculations and so is not described here.

Contour refinement-A further refinement to

the contour found in the previous step was incorpo-

rated using the concept of active contours, or“snakes,” which have the ability to conform to dif-

ferent contours within an image [ 12]. We describethe refinement procedure briefly in the following

text. The snake algorithm requires an initial active

contour (a rough approximation to the desired con-tour in the image) to be specified, which in our al-gorithm is the output of the previous stage. The true

border between the myocardium and the left ventri-

cle is automatically estimated by the snake algo-

rithm on the basis of iteratively minimizing the

energy of the active contour. The energy of the con-tour consists of different components such as the in-temal energy, image gradient energy, and externalenergy. The internal energy is defined from the

smoothness and compactness of the contour, the gra-

I0

MR Imaging of Left Ventricular Ejection Fraction

AJR:169, July 1997 105

dient energy is the negative of the sum of the gradi-

ent strengths at cacti contour point. and the external

energy consists �)f any knowledge-based constraints

the user can add to the equation.

Data Analysis

(.Ofll/)(IILsOfl I)(’t1i�e(’!1 (1(1/k- (111(1 hiight-blood tnt-

tiges.-The contours obtained from the semiauto-

niated algorithm followed by the refinement were

analyied as follows: The center of mass was esti-

mated using the border pixels. and intensity gradients

along the radial direction were calculated. Three pixel

points on either side of each border pixel were exani-

ned for the one with the maximum gradient value.

(The border pixel may not be the maxirnuni gradient

pixel because the snake algorithm chooses the con-

tour pixel on the basis of the maxiniurn gradient and

other cotisiderations. I Comparisons were then made

using the histograni distribution of pixel gradient val-

ues for all the border pixels.

Co,tzjaii.oni 1)t’titt’t’!i ili//t’re’tit t(’(/nnques.-Per-centage ofejection fractions (EF) was calculated as:

. EDt: -ESVLF=-- xl()0.

EDV

where EDV is the end-diastolic volume and ESV is

the end-systolic volume of the left ventricle. The

ejection fractions deteriiiined front MR iiaaging.

using the short-;ods images and the biplane method

for all the subjects. were compared with those front

echocaidiography. A sepalate coniparison was also

niade of the ejection fractions detenitined from

echocardiogranis and those determined by the semi-

autontated algorithm front the short-axis MR im-

ages. (‘oniparisons were expiessed is linear

regression plots I.)i the ejection fractions from the

two techniques. A slope close to one for the linear

regression line indicates that the ejection fractions

froii� the tVv() methods coiiipaied well. vhereas a re-

gression coefficient of I indicates a high degree of

correlation between the two data sets.

Reproducibility

Variations in ejection fiactioti estiniations front

MR inlages could potentially arise froiu three dif-

ferent factois: ( I ) interexaiilination variaL)ility and

( 2) intra- and ( 3 ) interobserver s ariation in deter-

mining the left ventricular endocardial llx)rder

( Simpson ‘s rule ) and left ventricular diiiiensions

( biplane aethod). We investigated the contrihu-

tions of these three factors to the reproducibilit) of

ejeCtiOil fraction estintates. 1 ftc f irst factor. inter-

(7 1 exaniination variability . v�as deterntined by scaii-

ning two subjects on three separate occasions s�ith

identical MR protocols. The interexamination

variahilit� was expressed in terms of the average

coefficient of variation of the ejection fraction es-

tintated front the three epetilions. lfiiee uianual

contouring trials sverc lx�rf�i tied on each of tss o

Patients at three different exaiiiiihttions (a total ofsix studies) to evaluate tfte iniraofserver variation

of the left s entricuLir est iilhtt Oil . I�iL ft contouring

trial was separated fiuni the pies bus OOC h� 7 I .4

days to decrease any remnant meiiior� ef fects. In

addition. the iadiologist [)erfornhing the contouring

WdS kept unav�arc of patient deniograpliics. 1 he

interobserver s ariahilit� s� a- deternniicd from the

ejection fraction estinlaies h� the iv�o observers oii

all the studies. The iiti aohsers er ‘. ailat (lit iii theestiniation of ejection fractions using tfie seiiiiau-

tomated algorithiii ssas estiin�iied front three sepa-

rate trials on each of six studies (the sante as the

Oiies used iii estiin�itii1g utti �iohsers er s �ti i�ihifities

by niaiiual contouring ntethotls . li�.aclt stiirf� svas

contoured three tinics using the ‘eniiatitoinated al-

goritliiii b� ()itC ohsei s er s� ith �i stiff iciiiitl� long

tinie inters at betsvccii Lritfs. �\ll cocf ficieiuts of

\�iriiItiO1t 55Ci� expiesseii in teiins of peicenLige of

SD of the mean.

Results

A typical set of four-cltanihcr �uid long-axis

inlages (in end-diastolic �utd end-systolic

phases) using the d;uk-hkxxl sequence is shown

in Figure 3. The distance measurements I) I.

Fig. 3.-Typical dark-blood gated MR images of leftventricle in 40-year-old healthy male volunteer.A. Vertical long-axis view of heart at end diastole. Notetwo ellipsoidal axis lengths, Dl and L, required for cal-

culating ventricular volume according to equation 4.

B, Similar vertical long-axis view at end systole showssystolic thickening of myocardium.C, Horizontal long-axis (or four-chamber) view of leftventricle at end diastole. Lengths L and 02 are shown,

the latter being last of three measurements of axis

lengths required in equation 4.D, Horizontal long-axis view at end systole similar tothat in C.

Sinha et aI.

106 AJR:169, July 1997

Fig. 4.-Short-axis MR images ofheart at different spatial and tempo-ral locations in 37-year-old healthymale volunteer using dark-blood se-quence. Signal-to-noise ratio and ex-tent of blood suppression seen hereare representative of most imagesacquired in 10 subjects.A and B, Images acquired at end dias-tole (A), with most apical image onleft, may be compared with corre-sponding spatial images acquired inend systole (B).C and D, More basal slices are shownat end diastole (C), with correspond-ing images at end systole (D). Mostbasal slice is on right Note clear de-lineation of left ventricle (LV, C) andright ventricle (RV, C) in these basalslices, which undergo large degree ofdistortion during cardiac cycle.

D2. and L required for the volume estimation ments from the four-chamber and long-axis

from the biplane method are also indicated images (Fig. 3). Short-axis images of the

(Fig. 3). The long-axis length of the ventricle, sanse subject covering the entire heart were

L, is taken to be the average of the measure- acquired with the dark-blood dual-phase se-

quence (Fig. 4). Images at each spatial loca-

tion were obtained at end diastole and end

systole in a single breath-hold. The time re-

quired to image the heart froni apex to base

A

AJR:169, July 1997 107

Fig. 5.-Short-axis MR images of leftventricle are shown with endocardialand epicardial contours from semiau-tomated algorithm superimposed aswhite pixels.A and B, End-diastolic images (A) cor-respond to end-systolic images (B).These imageswere acquired atthreespatial locations near mid ventricle

level. Relatively high degree of suc-cess of automatic contouring is facili-tated to large extent by good contrastbetween myocardium and ventricularspace in these dark-blood images.

was 8-l() ruin, including preparation and re-

construction time.

The endocardial and epicardial borders of

the heart, as deteniiined from the semiauto-

mated algorithm. are shown superposed on a

set ofdark-blood cardiac images (Fig. 5). The

semiautoniated algorithni took approximately

6 mm for a series of eight images (eight spa-

tial locations at one cardiac phase). Additional

time (3-5 mm) was required for nianual inter-

ventions for the proper identification of the

epicardial border, which was often contiguous

with isointense liver tissue or muscle of the

chest wall. The endocardial borders (lid not

require any manual intervention because the

myocardium-blood contrast was high and

hence tuore amenable to automated detection.

However. soiite of the ntost apical slices did

register blood as bright: manual editing was

required for these images.

Brmght-hkxxl imiiages of the heart showed

nonunifon�iity of blood signal imitemisity at

5(.)I11C locations and cardiac phases (Fig. 6). An

additional drasvhack was that in the basal

Fig. 6.-Bright-blood MR images nearbase of ventricle.A and B, End-diastolic (A) and end-sys-tolic (B) phases are shown at approxi-mately same location as dark-bloodimages in Figure 4B. Note thatwhereasoverall contrast between myocardiumand blood is high, blood signal intensityis nonuniform. In certain regions, par-ticularfy in posterior wall in systolicphase (arrow, B), distinguishing yen-tricular space from myocardium isdifficult, which leads to errors in en-docardial border detection.

I

V0

20

10

10 20 30 40 50 60 70 80 90 100

Intensity Gradient Strength (arbitrarily assigned units)

I

.1:

EF from MR Short-Axis Imiges EF from MR Images

Using Biplane Method (%)

Sinha et al.

108 AJR:169, July 1997

Fig. 7.-Histogram of pixel intensity gradient values at endocardial border in dark-blood (solid line) and bright-blood (dottedline) images. Histogram shown here is for typicalslice (dark and bright blood) in short-axis view. Gradientvalue atany pixel is maximum absolute value ofgradient along a radial line within three pixels of border pixel identifiedby snakeS algorithm.

slices, the signal intensity of blood was isoin-

tense to that of myocardium, particularly near

the posterior wall (Fig. 6). The spatial location

of these slices corresponds roughly to that of

the dark-blood images in Figure 4B. The histo-

grams of gradient intensity distribution of bor-

der pixels indicate that in typical dark-blood

images, the average gradient values are larger

than those in bright-blood images (Fig. 7).

The average ejection fraction of the five

volunteers was 55% (Table 1). A wide range

of ejection fractions was found for the patients

(most lower than the ejection fraction range in

healthy volunteers) and particularly for the

two patients with severe global cardiomyopa-

thy (subjects 4 and 10 in Table 1). Measure-

ments of left ventricular ejection fraction

estimates from MR short-axis images (manual

contouring) and from echocardiographic im-

ages are compared in Figure 8. A significant

correlation was observed between the two

techniques, although echocardiographic val-

ues were underestimated compared with val-

ues from MR short-axis images (slope of

regression line = 0.68, 2 correlation coeffi-

cient = .88). A similar comparison of ejection

Fig. 8-Ejection fractions (EF) estimated from manualcontouring (by observer 1) of short-axis MR images ofheart using Simpson’s rule compared with estimatesfrom echocardiography. Patient data are shown byfilled circles and volunteer data by open circles. Equa-tion to regression line is given in form of y= (slope) x x

+ (intercept), and coefficient of regression as R2. Slopeof regression line was 0.68 (compared with 1.0 for per-fect agreement shown as dashed line) together withvalue of.88forR2. Inthis graph, y=0.68x+ 18.

Fig. a--Ejection fractions (Efl estimated from biplanemethod, using ellipsoid biplane model (with leftventricularmeasurements by observer 1) applied to cardiac MR im-ages compared with estimates from echocardiography.Patient data are shown by solid circles and volunteer databy open ones. Equation to regression line is given as y =

(slope)xx+(intercept)and coefficientofregression as R2.Value of 0.99 for slope of regression line (compared with1.Ofor line ofidentity [dashedlinej) revealsthattwo meth-

ods agree reasonably well. Significant degree of correla-don was obtained (R = .82). Inthis graph, y=O.93x-2.8.

‘S..

0

aa

ci‘0m�aB.

.� z

B0

EF from MR Short-Axis Images EF from Manual Contouring of

MR Short-Axis Images

mnterexamination Va,IabIIIty of Ejection Fraction Contoured by Observer I

.

MR Imaging ExaminationSubject 1 Subject 2

Biplane (%) Short Axis (%) Biplane (%) Short Axis (%)

Numberl

Number2

Number3

%SD

62

67

66

3

66

61

55

10

67

57

52

13

58

50

49

9

lntraobserver Varlablllty of EjectIon Fraction for Observer I

Exam. Subj.

Trial 1 (%) Trial 2 (%) Trial 3 (%) SD (%)

BiplaneShortAxis

.

BiplaneShortAxis

.

BiplaneShortAxis

.

BiplaneShortAxis

1

2

3

4

5

6

1

1

1

3

3

3

62

67

66

67

57

52

66

61

55

58

50

49

59

68

69

61

54

53

62

58

55

56

51

48

67

70

73

64

60

50

63

63

53

56

49

48

6

3

5

5

5

3

3

4

2

2

2

2

MR Imaging of Left Ventricular Ejection Fraction

AJR:169, July 1997 109

Fig. 10.-Ejection fraction (EF) estimates from corn-puter-generated contours of short-axis MR imagescompared with those from echocardiography. Patientdata are shown by filled circles and volunteer data byopen circles. Equation to regression line is given as y= (slope) x x + (intercept), and coefficient of regres-sion as R2. Value of 0.65 for slope of regression line(compared with 1.0 for line of identity shown asdashedline), together with value of .85 for R 2, revealsresults closely parallel to those shown in Figure 9. Inthis graph, y= 0.65x + 18.8.

Fig. 11.-Ejection fraction (EF) estimates obtained from semiautomated contouring of MR short-axis images com-pared with those from manually contoured (observer 1) short-axis images. Patient data are shown by filled circlesand volunteer data by open circles. Line ofidentity is indicated by dashed line. Equation to re9ression line is given asy= (slope) x X+ (intercept), and coefficient of regression as R2. Hi9h degree of correlation (R’ = .98) and near perfectagreement(slope of regression line = 1.07) indicate good reliability of semiautomated contouring process comparedwith manual contouring by experienced radiologists. In this graph, y= 1.Olx- 2.07.

Note-Exam. = examination, Subj. = subject.

fraction estimates from the biplane MR imag-

ing method with those from echocardio-

graphic images reveal both a significant

correlation and a closer agreement of the esti-

mates (Fig. 9) (slope of regression line = 0.93,

2 = .82). Results of the regression analysis

of ejection fraction estimates obtained from

MR short-axis images (semiautomated con-

touring) compared with those from echocar-

diographic images closely paralleled those

obtained for the manually contoured data (Fig.

10) (slope of regression line = 0.65, 2 .85).

A direct comparison of the ejection fraction

estimates from short-axis MR images pro-

cessed by the manual versus the semlauto-

mated method revealed a high degree of

correlation and agreement (Fig. 1 1) (slope of

regression line = I .07, 2 .98).

An examination of the estimates of ejection

fraction from three independent scans each on

two of the subjects using the biplane and Simp-

son’s rule methods revealed that the average

value of the percentage of SD caused by inter-

examination variability was about 9% for both

methods of ejection fraction estimation (Ta-

ble 2). The results of the contouring by ob-

server 1 are given in Table 2; similar results

were obtained by observer 2. The intraob-

server variability (for observer 1) was esti-

mated as the percentage of SD ofthe mean left

ventricular ejection fraction obtained from

three trials each on six scans (Table 3). Again,

as in the case of the interexarnination variabil-

ity, the results of observer 2 closely tracked

those of observer 1 and therefore are not listed

here. The average percentages of SD of ejec-

tion fraction estimates caused by intraobserver

variability (averaged for both observers) were

4.5% for the biplane method and 2.5% for the

short-axis images. Figures 12A and l2B are

comparisons of the ejection fractions obtained

by the two observers for all the subjects. The

I..Ii

0a

I

II

0aC

aC

Ejection Fraction, Observer 2 (%)

A

Ejection Fraction, Observer 2 (%)

B

Sinha et al.

110 AJR:169, July 1997

Fig. 12.-lnterobserver variability in usingshort-axis and biplane methods to estimateejection fractions. Patient data are shownby filled circles and volunteer data by opencircles. Une of identity is indicated bydashed line. Equation to regression line isgiven as y= (slope) x x+ (intercept), and co-efficient of regression as R2.A, Ejection fractions obtained bytwo observ-ers using same short-axis images. Note highdegree of correlation (slope = 1.0, R2 = .96)between estimates obtained by two observ-ers, indicating low interobserver variabilitywhen using short-axis images. In this graph,y= 1.Ox+ 0.18.B, Ejection fraction obtained bytwo observ-ers using biplane method. Note lack ofagreement and degree of scatter, indicatedby slope of 0.63 and R2 of .46 between val-ues of ejection fraction estimates. In thisgraph. y=0.63x+21.

slope of the regression lines and the coeffi-

cients of correlation are 1 .0 and .96, respec-

tively, for the short-axis images, whereas for

the biplane method these values are 0.63 and

.46, respectively. The interobserver variabili-

ties are 12% and 4% for the biplane and Simp-

son’s rule methods, respectively. The

intraobserver variability in the estimates of

ejection fraction using the semiautomated at-

gorithm, averaged over all six studies (three

trails each), was approximately 3%.

Discussion

Cine MR imaging provides reliable and

reproducible measurements of left ventricu-

lar ejection fraction and left ventricular myo-

cardial mass [1-4]. However, cine images

acquired with conventional gradient-echo se-

quences require scan times of 10-20 mm.

Recently, a breath-hold segmented cine se-

quence yielding bright-blood images has

been proposed and evaluated for reproduc-

ibility of left ventricular volume estimations

[4, 13]. However, the bright-blood tech-

niques suffer from variable blood signal in-

tensity through the cardiac cycle as seen in

Figure 6 (e.g., image at the right in Fig. 6A

compared with the corresponding dark-blood

images in Fig. 4). Such nonuniformity of

blood signal intensity can lead to problems

when using semiautomated algorithms to

outline the endocardial border [4]. The reason

for the variable signal intensity of the left

ventricle is that blood registers bright on cine

images because it is flowing at varying rates

within the ventricle compared with a relatively

static myocardium. However, slow-flowing

blood near the myocardiat wall (especially in

the diastolic phase) may have a reduced sig-

nat intensity and may often be difficult to

distinguish from the myocardium in bright-

blood images because it is subject to the

same saturation effects that render the myo-

cardium hypointense compared with the rap-

idly flowing blood. The new sequence

proposed here overcomes this problem by

suppressing the left ventricular blood signal

by a preparation scheme. Furthermore, the

interval between the preparation pulses and

the collection of data allows enough time

even for the slow-moving blood present

within the slice to move out of the slice and

be replaced by dark blood. In conjunction

with a phased array surface coil, the sequence

yields images with good blood-to-myocar-

dium contrast and high signal-to-noise ratio.

The extent of blood suppression varied

among the subjects, and in some slices the

intensity of the suppressed blood appeared

nonuniform (Fig. 4). Nonuniformity of blood

signal intensity may arise from the fact that

not all the blood in the slice of interest has

been replaced by inverted blood from out-

side the imaging plane. The extent of this re-

placement depends on several factors such as

the thickness of the reinverted slice, velocity

of blood, cardiac phase, and spatial location.

However, even in the worst case, the blood

suppression was sufficient to permit unam-

biguous detection of the myocardial border.

Contrast between the blood and the myo-

cardium can be quantified in terms of the in-

tensity gradient at the endocardial border

pixels. The semiautomated algorithm used

here (and in general most such algorithms)

uses the detection of intensity discontinuities

between homogenous regions to identify the

edges. Larger values of the intensity gradient

will thus result in a greater reliability of seg-

menting the endocardial border using auto-

mated techniques, which was the motivation

behind comparing the gradients of pixels on

the endocardial border for dark- and bright-

blood images. The histogram in Figure 7

shows the average gradient strengths of the

border pixels to be higher for the dark-blood

images than for the bright-blood images and

quantitatively indicates that dark-blood im-

ages have an increased blood-to-myocardium

contrast over bright-blood images. A draw-

back of imaging the heart at only two phases,

such as at end diastole and end systole as in

our scheme, may be an inability to assess par-

ticular cardiac conditions such as diastolic

dysfunction or asynergic contraction that ap-

pear normal at end systole.

The superiority of Simpson’s technique

over the biplane technique is well established,

but our rationale for investigating the model-

based biplane method is as follows. The se-

quence discussed in this paper does permit left

ventricular function estimations in relatively

short scan times using the more accurate Simp-

son’s technique. To cover the entire heart,

eight to 10 breath-holds are necessary-one

breath-hold for each spatial location. Al-

though this pace is not demanding for volun-

teers, conceivably some patients will not be

able to perform these eight to 10 breath-holds.

Using the biplane method instead of Simp-

son’s method requires only two breath-holds,

thereby making the procedure less demand-

ing. We investigated the differences in left

ventricular estimation between the Simpson’s

and the biplane methods to quantify the

amount of error in the latter method, using the

proposed sequence. Thus, although accurate

measurements may not be possible using the

biplane method, that method may still enable

MR Imaging of Left Ventricular Ejection Fraction

AJR:169, July 1997 111

quick left ventricular function estimates to be

made in even very sick patients, which until

now was not possible with MR imaging.

However. maximum deviations from true es-

timates of ejection fraction occur in sick pa-

tients because the ellipsoid model is not

strictly valid in such cases. Simpson’s method

will be the protocol of choice in all subjects

capable of eight to 10 breath-holds, and the

biplane method can be used only in patients

who have difficulty holding their breath.

The normalized average difference (in per-

centage) between ejection fraction estimations

from the biplane method and from short-axis

images was about 15% excluding the two pa-

tients with severe cardiomyopathy. The aver-

age value of this quantity for the two patients

was approximately 150%. The large discrep-

ancy for the two patients was due to the fail-

ure of the geometry-based model in those

cases. Thus, it would not be feasible to accu-

rately calculate ejection fractions in patients

with global cardiomyopathy using the biplane

method, but that method could be used in such

patients to obtain an approximate figure.

However, the biplane method can be used to

obtain ejection fractions with sufticient accu-

racy in patients with. for example. history of

myocardial infarction (subjects 6, 7, and 8 in

Table 1 ). The regression plots in Figures 8-10

show a significant correlation between ejec-

tion fractions obtained from MR imaging and

from echocardiography techniques. The better

agreement between ejection fl-actions esti-

mated from echocardiography and from the

MR imaging biplane method is not surprising

because in both cases similar geometric as-

sumptions were involved in the calculation of

the let’t ventricular volumes. A comparison of

ejection fraction estimates from echocardiog-

raphy and front MR imaging using Simpson’s

rule revealed that the estimates from the former

were consistently less than those from MR

imaging for both manual (Fig. 8) and auto-

mated (Fig. 10) contouring. Ejection fraction

estimates from short-axis MR images are

more accurate because the echocardiography

estimate is based on the geometric assump-

tion of elliptical ventricular cross section that

is suboptimal for the precise measurement of

left ventricular dimensions. Potential maccu-

racies do exist in ejection fraction estimations

from short-axis images, arising mainly from

errors in locating the end points of the left

ventricle both at the base and at the apex.

However, because the calculation of the ejec-

tion fraction involves a subtraction of these

measurements made at systole froni those

made at diastole, this particular error is likely

to be smaller than that arising from the geo-

metric assumptions in the biplane method.

Another potential source of error is the tempo-

ral resolution of the images. In gradient-echo

imaging protocols, the temporal resolution

can be as small as 12 msec, but the ultrafast

segmented technique implemented in this

study uses an acquisition window of 70 msec.

Because the motion of the heart is most pro-

nounced at systole, the end-systolic volume

will depend on the duration of the acquisition

window. However, an acquisition window of

about 60-msec duration can still be used for

the accurate depiction of the end-systolic vol-

umes [4]. Our study uses an acquisition win-

dow of 70 msec, but this duration is likely to

be reduced in the future with the use of shorter

gradient-rise times, a hardware improvement

that is being made increasingly more available

in clinical scanners.

The correlation coefficients and slope of the

regression lines were similar for the plots in

Figures 8 and 10. Such similarity of behavior

was again reflected in the excellent correlation

(with a slope of 1.07) between the ejection

fraction values obtained from the manual and

from the semiautomatic methods (Fig. 1 1).

This finding is encouraging because it implies

that the left ventricular contours generated by

the sentiautomated algorithm agree closely

with the contours generated by the expert. An

automated or semiautomated technique is criti-

cal for a clinical implementation of left yen-

tricular function estimates in a time-efficient

manner. As indicated in the introduction. the

success of the semiautomated method depends

on the robustness of the algorithm, the signal

intensity and contrast-to noise ratio of the left

ventricle and myocardium, and the signal ho-

mogeneity of both blood and myocardium.

The comparison of the dark-blood technique

with the equivalent bright-blood scheme

shows an improvement of both contrast be-

tween left ventricle and myocardium and the

homogeneity of the blood signal. The signal-

to-noise ratio of the images was significantly

enhanced by the use of the phased array sur-

face coil compared with the body coil. Cer-

tainly the improved signal-to-noise ratio is not

an advantage of our sequence alone. but the

combination of the improved contrast. homo-

geneity (using dark-blood sequences). and in-

creased signal-to-noise ratio (from the use of

the phased array coil) resulted in an ability to

easily contour the left ventricle both manually

and with the computer.

Potentially, the manual interactions in-

volved in the semiautomatic niethod could

lead to observer-dependent variations in left

ventricular ejection fraction estimation. The

manual interactions involved are identifica-

tion of a seed point within the left ventricle

and tracing a region of interest encompassing

the left ventricle and the ittyocardiunt, and se-

lection of an intensity threshold separating left

ventricle blood from myocardium. We tested

the variation (arising from the manual inter-

ventions) in the estimation of ejection fraction

using the semiautontated algorithm. The in-

traobserver variability of approximately 3%

was small and close to that obtained using

manual contouring by experienced radiolo-

gists. The results showed that the semiauto-

mated algorithm can be used successfully in a

routine clinical setting.

Intraobserver variability was small (4%

and 3% for the biplane and short-axis methods,

respectively). This small variability shows that

reproducibility cannot be improved signifi-

cantly by having the san�e observer make the

nteasurements on two or more occasions and

then take the mean of these nteasurements.

The larger variability in the biplane method is

expected because small errors in the distance

determinations ofthe biplane method can give

rise to large errors in left ventricular volume

calculations. However, the ntain difference in

the two niethods was seen in the interobserver

variabilities (Fig. 1 2). The interobserver van-

ability was high for the biplane method be-

cause each observer had to make subjective

estimations of the locations of various cardiac

landmarks on the four-chamber and long-axis

images (Dl, D2. and L in Fig. 3). Conversely.

the contouring of the endocardial borders on

the short-axis images was much less subjec-

tive, especially with the improved myocar-

dium-to-blood signal intensity contrast of the

present sequence. The large interobserver

variability of the biplane method shows that it

can be used only in clinical situations in

which scan time is at a premium. In such

cases, the measurement reproducibility can

be improved by having five or six experts

perform the measurenients twice and then

taking the mean of all the measurements. Be-

cause only three distance measurements must

be made per examination, such repeated mea-

surements by different experts may be a time-

efficient clinically feasible alternative to the

short-axis method. We did not attempt to

sentiautomate the measurements required to

estimate left ventricular ejection fraction

front the biplane method. It is intrinsically

harder to semiautomate these nteasurements

compared with contouring the endocardial

borders from short-axis images because the

algorithm will have to be designed to recog-

Sinha et al.

112 AJR:169, July 1997

nize landmarks (Fig. 3). Semiautomation may

decrease the interobserver variability (com-

pared with completely manual methods) in es-

timating left ventricular ejection fraction from

biplane methods.

The interexamination variability showed

that when a subject is studied on several occa-

sions, with the different examinations read by

the same observer, the estimate of ejection

fractions may vary by approximately 9% for

the healthy heart (for both the biplane and

Simpson’s rule methods). Keeping this factor

in mind is important when attempting to detect

changes in ejection fraction, as in a follow-up

study. The interexamination variability is the

most significant source of variation in deter-

mining left ventricular ejection fractions from

serial short-axis images from the dark-blood

breath-hold sequence and was similar to that

reported earlier for MR short-axis images from

spin-echo and gradient-echo imaging and from

echocardiography [2, 14].

Interexamination variability has contnibu-

tions that are biologic and technical in origin

[2, 1 1, 14]. Physiologic differences depend on

various factors, such as the ventricular after-

load, hydration state, heart rate, and blood

pressure, that cannot be controlled easily.

Technical factors include the data acquisition

method and analysis. In data acquisition, sev-

eral factors may limit reproducibility, such as

the thickness of imaging planes, acquisition

plane positioning, and temporal location and

resolution of the imaging planes. As men-

tioned previously, one of the potential sources

of error in estimating the ejection fractions is

the temporal resolution of the MR images

limited by the acquisition window duration.

Because the present scheme also requires po-

sitioning of the end-systolic and end-diastolic

acquisition windows, we undertook a study

of the interexamination variability. For the

biplane plane method, small errors in slice po-

sitioning required for the generation of the

four-chamber and short-axis images in re-

peated MR examinations may lead to a larger

contribution from technical variability to the

total interexamination variance. It is surpris-

ing that the variability of ejection fractions

determined from the biplane and from the

short-axis methods was in the same range.

This similar variability may reflect the fact

that biologic variability contributes signifi-

cantly to the reproducibility of repeated stud-

ies [14]. All the MR imaging was carried out

with the same protocols for scout images, and

a radiologist prescribed the four-chamber and

short-axis views on the basis of the scout im-

ages. In other studies unrelated to this one [2,

1 1, 14], interexamination variabilities in the

same range of 10% were estimated using both

MR imaging (spin- and gradient-echo se-

quences) and echocardiography. These meth-

ods are significantly different from the present

method (especially echocardiography) so that

common technical contributions to variability

cannot explain the same range of interexami-

nation variabilities found across all these stud-

ies. The biologic factor is common to all these

techniques, which leads us to conclude that it

is the major source of interexamination van-

ability. In fact, the biologic factor has been

identified as a major contributor by other

studies also [2, 14]. However, the contribution

from technical sources, as detailed previously,

cannot be discounted. The determination of

the interexamination variabilities will help set

a range beyond which changes in left ventric-

ular function can be considered significant.

Reproducibility may be improved by in-

corporating a repeated examination and tak-

ing the average of two such examinations

[2]. This procedure was not clinically feasi-

ble when using spin-echo or gradient-echo

sequences. However, with the ultrafast se-

quences, it is clinically possible to actually

have two separate examinations covering

the heart from apex to base. Furthermore,

the use of thinner slices will improve accu-

racy and reproducibility. Again, the use of

ultrafast sequences will permit the acquisi-

tion of a larger number of thinner imaging

sections in reasonable scan times.

In conclusion, this paper reports our pre-

liminary feasibility study on the use of the

dual-phase, dark-blood serial short-axis im-

ages acquired by the present imaging scheme

to yield reproducible estimates of the ejection

fraction in a limited number of both patients

and healthy volunteers. The suppression of

blood in the left ventricle in combination with

the high signal-to-noise ratio obtained with

the phased array surface coil permits auto-

mated contouring of the endocardial borders.

The estimation of ejection fraction by apply-

ing the Simpson’s method to the short-axis

images is more reliable than the biplane

method; the latter is not suitable for patients

with global cardiomyopathy because of the

invalidity of the assumptions in the geometric

model in these cases. The proposed semiauto-

mated algorithm can be successfully imple-

mented to automate the estimation of ejection

fractions from dank-blood dual-phase images.

The speed of the acquisition of the images

coupled with the potential to automate their

segmentation and analysis suggests the possi-

bility of implementing this technique on a

routine clinical basis for evaluating global left

ventricle function.

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