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regularization of the embedding controlled by the
parameter e.
The resulting equation of the motion for the level-set
function F(x,t) is:
+ Ñ - Ñ = 0
¶
¶j e j b j g K
t
74
2.4. Image and data analysis
In each subject, for each gravity level (phase 1, 1 Gz;
phase 2, 1.8 Gz; phase 3, 0 Gz) images relevant to one
complete cardiac cycle were selected and analyzed
applying the modified level set model. For each frame,
endocardial LV contour was detected and LV area
measured as pixel counts. The reliability of the semiautomated
contour identification was assessed by visual
inspection during the analysis by an expert operator, by
superimposing the detected contours on the original image,
and allowing algorithm’s parameters adjustment. LV
function curves were obtained by plotting the area over
time, and LV parameters were extracted: end-diastolic
(EDA) and end-systolic (ESA) areas, respectively as the
maximum and the minimum of the area in the cardiac
cycle; fractional area change (FAC%) as EDA-ESA
normalized by EDA; atrial filling (AF), as the increase of
LV area following the atrial contraction.
One-way analysis of variance for repeated measures
was applied to test significant differences (p<0.05) in LV
parameters due to different gravity conditions.
3. Results
A total of 418 frames were analyzed: endocardial
contours judged as reliable by an expert observer were
automatically detected in 89% (371/418) of the processed
frames, while the remaining 11% (47/418) needed further
manual adjustment of the algorithm parameters. Local
failures in the detection were associated with open mitral
valves inclusion and apex or lateral wall
misidentification, due to poor image quality. In figure 2
an example of the semi-automatically detected LV cavity
contour is shown. The processing time was about 30
seconds per frame.
Figure 2. Example of an automatically detected LV
endocardial contour superimposed to the original image
at 1 Gz
In figure 3, the LV area versus time curves obtained
during different Gz loads in one subject are shown. A
reduction in LV area during 2Gz was visible, together
with its increase during 0 Gz, compared to normogravity.
Table 1 shows the mean results in LV parameters
obtained for the whole population, presented as
percentages in respect to normogravity, i.e. to be assumed
as 100%. Expected modifications in LV area with
different gravity were found: at 1.8 Gz, end-diastolic
(EDA) and end-systolic (ESA) areas were significantly
reduced of 10.7±5.4% and 21.6±11.1% respectively,
compared to 1 Gz values, while they were increased of
11.2±5.4% and 11.1±6% during 0 Gz. Fractional area
change (FAC% ) was augmented of 20.9±29.1% at 1.8
Gz, while it remained unchanged at 0 Gz, compared with
1 Gz values. Furthermore, LV filling due to atrial
contraction (AF) was increased at 0 Gz of 39±35.6%.
Table 1. Mean results, obtained in 7 subjects, of LV
parameters (mean±SD), expressed as percentage in
respect to phase 1 (1Gz) (*: p<0.05 in respect with 1Gz).
EDA ESA FAC% AF
1.8 Gz 91.7±8.5* 84.2±19.4* 120.9±29.1* 126±46.6
0 Gz 111.2±5.4* 111.1±6.0* 100.7±8.9 139±35.6*
Figure 3. LV area (in pixels) over time at different
gravity conditions (see legend in the figure).
4. Discussion
The results of this study confirmed that acute changes
in venous return and cardiac loading conditions are
1 frame # 16
pixel counts
2500
8500
1 Gz
2 Gz
0 Gz
75
induced by different gravity loads during parabolic
flight.
The resulting variations in cardiac chambers size can
be tracked using 2-D echocardiography. To analyze 2-
D echocardiographic images, a rapid, accurate and
reproducible method for calculating LV dimensions is
highly desirable. In clinical practice, LV area is usually
calculated by manually tracing the endocardial contours
but this technique is time-consuming and operatordependant.
Compared to this conventional technique, the applied
algorithm, based on level set method, is faster and
semi-automatic, requiring parameter’s initialization on
only one frame of the cardiac cycle. The endocardial
detection was then automatic for the entire cineloop, by
taking the estimated contour as initial condition for the
contour detection of the following frame. In this way,
the analysis can be extended to the whole cardiac cycle,
instead of being limited to the telediastolic and
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