imaging three-dimensional cardiac function - Walter G. O'Dell, PhD

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438 O’DELL MCCULLOCHAnnu. Rev. Biomed. Eng. 2000.2:431-456. Downloaded from arjournals.annualreviews.orgby UNIVERSITY OF ROCHESTER LIBRARY on 07/27/09. For personal use only.?Ventricular-Cavity Volume Estimatesthat regional and interindividual heterogeneity in wall thickness in diseases suchas hypertrophic cardiomyopathy make meaningful comparisons difficult. Finally,acute changes in wall thickness do not necessarily indicate chronic dysfunctionbecause long-term wall remodeling may act to compensate for mild injury byrestoring wall thickness to normal values, as described by Pouleur et al (36) withLV dilation.The relationship between wall thickening and fiber shortening is also not clear.Wall thickening at various wall depths was shown by Hexeberg et al (30) to correlatenot with fiber shortening or myocardial perfusion in those layers, but withthickening of the entire wall and local wall geometry. McCulloch et al (37) supportedthis conclusion for fiber strains but found that transmural location did havea significant effect on cross-fiber strains.The estimate of the contour location in an image is accurate to within 1–2 mm,typically, with MRI (38). For a 10-mm-thick wall, this error leads to a 10%–20%uncertainty in the thickness estimation. The apparent wall thickness is increasedin planar images that intersect the heart wall at oblique angles to the local surfacenormal, creating a bias in the thickness measurement. Through-plane motion introducesadditional error because the same piece of myocardial tissue is not imagedover time at a fixed cross-sectional location. Both the bias and the through-planemotion artifact can be corrected with 3-D ventricular surface reconstruction byusing data from orthogonal views (see below).Traditionally, the measurement of LV volume by thermodilution techniques (39),projection ventriculography (40), or radionuclide techniques has been subject tosubstantial error, that is, ∼20% (39). Despite many innovations in imaging techniquesand computerized analyses, substantial errors of this order remain in clinicalmeasurements of LV volume. Currently, the task of estimating the volume of theventricular cavity often reduces to defining the cavity boundaries and integratingover the enclosed space. Significant, common sources of error are poorly definedbasal and apical limits of the ventricle, oversimplified geometric models, and uncompensatedimaging artifacts.A common convention is to model the base of the heart as a planar surfacepassing through the mitral valve ring. However, the entirety of the valve planeis not easily imaged with ECG or 2-D CT imaging because the mitral valve isobliquely oriented in the chest cavity. With MRI, it is possible to orient the imagingplane to encompass the entire mitral valve ring, but, because the slice thicknessis typically 5–7 mm, there is a ±2.5- to 3.5-mm discrepancy in the plane’s exactlocation within the slice. Even if accurately imaged at one time, the mitral valvering translates apically ∼10 mm (41) from end-diastole to end-systole; henceit does not remain within a single, fixed short-axis image volume. For a mitralvalve ring that is 25 mm in diameter (area, 491 mm 2 ), a jump from one slicelocation to the next represents an estimated volume change, using Simpson’s rule,
Annu. Rev. Biomed. Eng. 2000.2:431-456. Downloaded from arjournals.annualreviews.orgby UNIVERSITY OF ROCHESTER LIBRARY on 07/27/09. For personal use only.?IMAGING 3-D CARDIAC FUNCTION 439of 2.5–3.4 ml or ∼6.2%–8.5% of the total end-systolic volume (for a representativeend-systolic volume of 40 ml). Similarly, it is difficult to detect the most apicalintracavitary point by using only short-axis images. Both of these sources of errorcan be overcome by incorporating planar image data from the orthogonal, long-axisview.When referenced to 3-D ECG and equilibrium radionuclide angiography,limited-plane 2-D ECG methods were no better than subjective visual estimationfor determining the LV ejection fraction (14). To compensate for the inherentlimitations, some applications use correction factors that are calibrated to match theknown volume errors as tested on postmortem or experimental heart models (40).However, these correction factors are computed for a “typical” heart geometry thatmay not necessarily be appropriate for abnormal or diseased hearts.Poor CNRs and partial-volume effects both contribute to errors in the segmentationof heart contour data, which are magnified in the LV volume estimate. Fora sphere of radius 25 mm, a typical LV minor-axis radius dimension, an error of1 mm (4%) in the estimated radius leads to a volume estimation error of ∼12%.All imaging modalities suffer misregistration of the heart contour data when theimage data are acquired over many heartbeats or different times, as a result ofbeat-to-beat variations in the heart contraction and uncorrected respiration-derivedmotions. With projection images, the contrast silhouette obscures most of the indentationsin the wall (i.e. at the papillary muscle sites), creating an overestimationof the true ventricular dimensions. A comparison between cross-sectional ECG andX-ray ventriculography found that projection imaging leads to an overestimationin ejection fraction of 22% (42).When only a few ventricular surface measurements are available, it is convenientto model the LV surface geometry as an ellipsoid. This simplification allows forrapid calculation of volume but disregards the asymmetry of the actual ventricularsurface, the complexity of the mitral valve plane, and the existence of the papillarymuscles. Elliptical models were initially used with projection ventriculography(40), but are now also used commonly with 2-D ECG data (43). The volume of anellipse is given by:V = 4 3 πab2Surface Modeling with Ellipsoidswhere a is the radius along the major axis and b is the radius of the minor axis.For single-plane projections, Dodge (40) used the formulab = A projπawhere b is the minor axis dimension and A proj is the area of the long-axis projection(making V = 4A2 proj). An analogous formula exists for biplanar data. Ellipsoidal3πa
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