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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_3592_Библиотеки_им_академика_М_И_Перельмана
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Vascular and Intravascular Imaging Trends, Analysis, and Challenges, Volume 1
https://t.me/medicina_free
Figure 12.3. The workflow of AtheroCloud™ and its components. The tower represents a server in the cloud.
The arrows represent the bidirectional flow of information. (Courtesy of AtheroPoint™, Roseville, CA, USA.)
Figure 12.4. Block diagram for the overall engineering components of the design.
scans stored in the cloud-based server and displaying them on the local
computer screen.
(ii) The business logic layer, which consists of scientific engines for measure-
ment and is physically sitting in the cloud-based server. This layer receives
the ultrasound scans, automatically computes the measurements and displays the measurements on the PC screen.
(iii) The persistence or database layer, is also present in the cloud-based
application server and is used for the storage of digital measurements
and images for later retrieval.
12.3.2 Engineering component design of the AtheroCloud™ 1.0 system
The main block diagram of the proposed system is shown in figure 12.4. The main
components consist of (a) automated cropping, (b) the automated carotid artery
recognition phase, (c) the automated LI/MA detection phase and (d) the automated
cIMT measurement phase. Automated cropping is necessary to avoid interfering
with the patient text information, any cardiac gating signals and peak systolic
velocity waveforms [ 50, 51]. The second step consists of automated far wall
recognition which is based on the hypothesis that far wall intensities are highest in
the image [52]. This is combined with scale-space [13, 41, 53] for far wall region-ofinterest (ROI) estimation all along the carotid artery. The detection step consists of
LI/MA interface estimation using an edge operator [13, 41, 53]. The final LI/MA
edges are then fed into the polyline distance method (PDM) for cIMT measurement
(see appendix A)[39, 40].
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12.3.3 General features of the AtheroCloud™ 1.0 system
AtheroCloud™ 1.0 helps in early diagnosis and monitoring of plaque build-up
through its automated/semi-automated processing of ultrasound scans. The proposed system has the following main features: (i) the ability to measure cIMT in a
reliable, accurate, reproducible and cost-effective manner; (ii) cloud-based
cIMT/IMTV measurement of thin/thick carotid plaques in the Routine mode;
(iii) cloud-based LD/LDVar/SSI measurement in a the Routine mode; (iv) fully
automated or user-interactive (semi-automated by manually placing an ROI as a
rectangular box); (v) the ability to monitor and compare measurement readings over
follow-up time; (vi) the ability to interface with various commercial ultrasound
scanners; (vii) the ability to import the following image formats: DICOM; JPEG,
BMP, PNG, GIF and TIFF; (viii) an inbuilt database patient record system;
(ix) reviewing of patient records/images/reports/; (x) the ability to e-mail a clinical
report; (xi) instant screen/report printing capability; (xii) the ability to process a large
number of ultrasound scans without human interaction for the Pharmaceutical
Trials mode (batch-processing); (xiii) it can read carotid ultrasound image scans
from a CD, local hard-drive, internal network server or external network cloud
server. Overall, it provides a user-friendly means of saving, viewing, emailing and
printing patient reports as well as carotid scans. After analyzing and processing
carotid vascular scans, AtheroCloud™ 1.0 generates a PDF statistical report for
each patient (one patient at a time) or produces a PDF statistical report for the
Pharmaceutical Trial mode (consisting of cIMT readings taken from thousands of
patients). Using the above features, AtheroCloud™ 1.0 can be adapted for advanced
clinical applications.
12.3.4 Two application modes of AtheroCloud™: the Routine mode and Pharma
mode
There are two major modes in which AtheroCloud™ can be used: (a) the Routine
mode and (b) the Pharma Trial mode. In the Routine mode, the measurements are
computed real-time during the patient’s visit, one ultrasound scan at a time, and in
the Pharma trial mode, the batch of carotid ultrasound scans are automatically
processed in real-time one-by-one. Depending upon the physical space (gigabytes to
terrabytes) and server RAM, the system can run large databases; however, we
typically suggest up to a maximum of 10 000 images in the batch mode. An example
of the Routine mode is shown in figure 12.5(a). Once the image is loaded in the
Routine mode, with a click of the button ‘Auto Trace’, the LI/MA interface borders
are computed and the IMT region representing the total plaque area is filled in with
yellow (figure 12.5(a)). An example of the Pharma mode is shown in figure 12.5(b).
12.4 Results: measurements and visualization
12.4.1 Carotid intima–media thickness (cIMT) reading
There are two main factors which affect the speed of the system: (a) the size of the
image to be processed in the cloud and (b) the downloading speed of the internet. For
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Figure 12.5. (a) Routine mode automated tracings (yellow) of the carotid intima–media thickness/variability
region showing the LI and MA borders using AtheroCloud™. (b) Pharma Trial mode automated tracings
(yellow) of the carotid intima–media thickness/variability region showing the LI and MA borders using
AtheroCloud. A constant resolution factor of 0.0625 mm/pixel was adapted for this Pharma batch run.
(Courtesy of AtheroPoint™, Roseville, CA, USA.)
factor (a), the size of the ultrasound image can vary from database to database. In our
database, some images are smaller, e.g. 684 × 504 pixels, and took less than three
seconds for downloading and processing, while for larger images, e.g. 1054 × 772
pixels, it took less than five seconds for downloading and processing. Our average
scan dimension (W × H) over 200 images was 881 × 614 pixels. Our internet speed was
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Table 12.1. cIMT using AtheroCloud™ (Routine mode versus Pharma Trial mode), sonographer readings
and manual readings.
AtheroCloud™ (mm)
Neck side
Left cIMT 0.87 ± 0.20 0.86 ± 0.20 0.90 ± 0.20 0.97 ± 0.26
Right cIMT 0.77 ± 0.20 0.77 ± 0.20 0.79 ± 0.20 0.89 ± 0.29
Routine mode Pharma mode
Sonographer (mm) Manual (mm)
180 Mbps. The average time taken by our system is less than five seconds, which
includes uploading the input ultrasound image to the cloud, processing the image in
the cloud and displaying the result at the user’send.
Table 12.1 shows the mean and standard deviations of computed carotid intima–
media thickness for 200 carotid scans using: (i) the automated AtheroCloud™
software (both in the Routine and Pharma Trial modes), (ii) sonographer readings
and (iii) manual (gold standard) readings. Our observations show that the
AtheroCloud™ mean cIMT readings for both the Routine and Pharma Trial modes
were very similar. This clearly showed that AtheroCloud™ software can be used for
clinical trials with very high reproducibility.
12.4.2 Display of LI/MA interfaces using AtheroCloud™ and manual methods
Using the ‘Validation’ button on the AtheroCloud™ front panel (top right corner),
the user can upload the pair of LI/MA interfaces from AtheroCloud™ and
corresponding manual tracings traced by the expert for comparison. Figure 12.6
shows LI/MA delineations using AtheroCloud™ software (solid line) and manual
expert tracings (dotted line). As can be seen, the LI interface shows a bumper-tobumper position with very slight deviations between AtheroCloud™ and manual
tracings. A similar pattern can be seen for the MA interfaces. Cropped and zoomed
images of AtheroCloud™ and the manual overlay image are shown in figure 12.7.
12.5 Performance evaluation of the AtheroCloud™ system
We evaluated the performance of the AtheroCloud™ system by computing a PoM
that compares AtheroCloud™ readings against the manual (expert) readings. We
used the polyline distance metric [39, 43] for evaluating the performance of the
system. Details on the polyline distance metric can be found in appendix A. The
following statistical analysis was performed between the three sets of readings
(AtheroCloud™, sonographer and manual):
• PoM computation of (i) AtheroCloud™ and (ii) sonographer readings
against manual.
• The CC among the three different methods.
• Bland–Altman plots among the three different methods.
• The CC between cIMT and the age of patients.
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Figure 12.6. (a1), (b1), (c1) and (d1) original carotid artery images. (a2), (b2), (c2) and (d2) LI/MA overlays
using AtheroCloud™ software (solid line) and manual tracings (dotted line), respectively. cIMT readings are
the IMT values for AtheroCloud™ and manual tracings.
• Cumulative distribution of cIMT errors for AtheroCloud™ and sonographer
readings.
• Statistical tests.
Once the AtheroCloud™ displays the final LI/MA borders, these borders undergo
a three-step process. These processes are needed to match the final LI/MA borders
from AtheroCloud™ with manual LI/MA borders traced by the physician. This is
necessary for the performance evaluation of the system. The three-step process is as
follows:
(i) B-spline fitting: We smooth the output results of the LI/MA borders using a
B-spline technique. The LI/MA interfaces consist of 100 equal distance
interpolated points after the B-spline smoothing of the LI/MA interfaces.
(ii) Common support creation: We ensure that the LI/MA automated bounda-
ries and the LI/MA manual boundaries have the same starting and ending
coordinates. For this, we apply a common support (the same length) on
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Figure 12.7. Cropped and zoomed images of AtheroCloud™ (solid line) and manual tracings (dotted line).
LI—white; MA—black.
both the LI/MA boundaries. This ensures consistency between the
measurements.
(iii) Interpolation: Finally, we interpolate the points so they are equidistant,
i.e. the distance between the points is the same.
12.5.1 Precision-of-merit
The PoMs for AtheroCloud™ and sonographer readings were computed against the
gold standard (manual readings). PoM computations were based on the basic
concept of how close the AtheroCloud™ cIMT and sonographer cIMT readings are
against the manual readings. cIMT was computed using the bidirectional concept of
the PDM as shown by HSS [39, 43]. The final derivation of AtheroCloud™’s PoM is
also shown in appendix A and is mathematically expressed as
AtheroCloud
⎡
⎛
=−
⎢
⎜
⎝
⎣
cIMT
−
Manual
cIMT cIMT
AtheroCloud Manual
⎞
⎟
⎠
⎤
⎥
100 . (12.1)
*PoM (%) 100
⎦
Similarly, we can compute the sonographer’s PoM as
where
cIMT
Sono
AtheroCloud
=−
,
cIMT
Manual
⎡
⎛
cIMT cIMT
⎢
⎜
⎝
⎣
and
−
Sono Manual
cIMT
cIMT
⎞
⎟
Manual
Sono
⎠
are the mean cIMTs using
⎤
⎥
100 , (12.2)
*PoM (%) 100
⎦
AtheroCloud™, manual and sonographer readings for the entire database as shown
in equations (A.8) and (A.9). Note that the bars represent the absolute value.
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Table 12.2. PoMs for left, right and combined cIMTs.
Parameters Left cIMT Right cIMT Combined cIMT
AtheroCloud™ when compared against manual
AtheroCloud™’s PoM 95.85% 97.24% 96.50%
Sonographer when compared against manual
Sonographer’s PoM 92.87% 87.31% 90.27%
Table 12.2 shows the PoMs between (i) AtheroCloud™ and manual and (ii)
sonographer and manual for the (a) left, (b) right and (c) combined left and right
cIMTs. We observe that the AtheroCloud ™ ’s PoMs (95.85%, 97.24% and 96.50%)
are much higher compared to the sonographer’s PoMs (92.87%, 87.31% and
90.27%) for left cIMT, right cIMT and combined cIMT. The percentage improvements of PoMs for AtheroCloud™ over the sonographer were 2.98%, 9.93% and
6.23% for left, right and combined cIMTs. The PoMs between AtheroCloud™ and
sonographer for the (a) left, (b) right and (c) combined left and right cIMTs are as
shown in appendix B, table B1.
12.5.2 Coefficient of correlation between the three methods
The basic idea behind CC computation is to test the relationship and measure the
strength of association between the two quantities. The corresponding CCs between
these methods are shown in table 12.3. Our observations show a high degree of CC
between AtheroCloud™ and manual (0.96 (P < 0.0001), 0.97 (P < 0.0001) and 0.97
(P < 0.0001)) for left, right and combined cIMTs, compared to sonographer versus
manual (0.74 (P < 0.0001), 0.65 (P < 0.0001) and 0.69 (P < 0.0001)). The
corresponding improvements in CC were 29.73%, 49.23% and 40.58%, respectively.
These CC scatter plots are shown in figure 12.8 between AtheroCloud™,
sonographer and manual cIMT readings. There are three rows: Row 1 (a1 and
a2) shows correlations between AtheroCloud™ and manual readings. Row 2
(b1 and b2) shows the correlations between sonographer and manual readings.
Row 3 (c1 and c2) shows the correlations between the AtheroCloud™ and
sonographer readings. The percentage improvements of CC for AtheroCloud™
over sonographer were 29.73%, 49.23% and 40.58% for the left, right and combined
cIMTs. The CC between AtheroCloud™ and sonographer readings is as shown in
appendix B, table B2.
12.5.3 Bland–Altman plots between the different methods
Bland–Altman plots show the average bias or the average of the differences between
two readings. The bias can be in the positive difference direction or can be in the
negative difference direction. Here, the differences between the two readings are
plotted against the averages of the two readings. Three horizontal lines are drawn,
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Table 12.3. CCs between the three methods for left, right and combined cIMTs.
Parameters Left cIMT Right cIMT Combined cIMT
Method 1: AtheroCloud™ versus Manual
CC 0.96 0.97 0.97
Method 2: Sonographer versus Manual
CC 0.74 0.65 0.69
where the solid line represents the mean difference. The two dotted lines represent
the limits of agreement, which are defined as the mean difference plus and minus
1.96 times the standard deviation of the differences. The average of the differences
between two readings (i.e. average bias) can be higher in either the positive
difference direction or the negative difference direction. The former represents
that the first quantity readings are greater than the second quantity readings, and the
latter represent that the first quantity readings are smaller than the second quantity
readings.
The Bland–Altman plots of cIMT measurements using AtheroCloud™ software
against (a) manual cIMT readings and (b) sonographer cIMT readings is shown in
figure 12.9. This shows the average bias or the average of the differences between
two cIMT readings. It can be observed that the bias is higher in the positive
difference direction for AtheroCloud™ and manual reading. Higher bias in the
positive difference direction shows that AtheroCloud™ cIMT readings are greater
than the manual cIMT readings. We also observe that the bias is higher in the
negative difference direction for AtheroCloud™ and sonographer cIMT measurements. Higher bias in the negative difference direction shows that AtheroCloud™
cIMT readings are smaller than the sonographer cIMT readings. The results show a
high degree of agreement between AtheroCloud™ and manual readings compared
to sonographer and manual cIMT readings.
12.5.4 Coefficient of correlation between age and cIMT
In this study, we have analyzed the relationship between age of the patient and cIMT
using three different methods (AtheroCloud™, sonographer and manual). Figure
12.10 shows the scatter diagram showing a mild correlation between age and cIMT
readings. Panels (a1), (b1) and (c1) show a correlation between age and left cIMT
using the three methods and panels (a2), (b2) and (c2) show correlation between age
and right cIMT using three methods, AtheroCloud™, manual and sonographer
readings, respectively. The CC between age and left cIMT readings using
AtheroCloud™, manual and sonographer readings were 0.27, 0.28 and 0.38,
respectively. The correlation of age and right cIMT reading using AtheroCloud™,
manual and sonographer readings were 0.30, 0.29 and 0.37, respectively. Thus, the
CC was moderate and mild for both the left and right cIMTs, but right carotid was
slightly higher compared to the left.
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Figure 12.8. Scatter diagram showing a correlation between AtheroCloud, sonographer and manual cIMT
readings. (a1), (b1) and (c1) show correlations between AtheroCloud™ and manual, sonographer and manual,
and AtheroCloud™ and manual for left cIMT, and (a2), (b2) and (c2) show correlations for the above
combinations for right cIMT readings, respectively.
12.5.5 Cumulative distribution of cIMT errors and LI/MA errors
The basic idea behind plotting cumulative distribution is to determine the percentage
of the population that lies above (or below) a particular cIMT threshold value. The
cumulative frequency is computed by adding each reading to the sum of its
predecessor. Cumulative distribution plots show how well the system is behaving.
The combined cumulative distributions of cIMT error curves for (i) AtheroCloud™
versus manual, (ii) sonographer versus manual, and (iii) AtheroCloud™ versus
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Figure 12.9. Bland–Altman plot of cIMT measurements using AtheroCloud™ software against (a) manual
cIMT readings and (b) sonographer cIMT readings.
sonographer are shown in figure 12.11. Keeping the cIMT error threshold as 10% of
the cIMT thickness (i.e. nearly 0.11 mm), we observed that 91.15%, 68.31% and
53.91% of the population met the error threshold criteria for three error curves.
About 23% of the patients’ cIMT was more accurate in AtheroCloud™ compared to
the sonographer reading. The mean and standard deviation of the LI error and the
MA error between AtheroCloud™ and manual readings were 0.0649 ± 0.0368 mm
and 0.0673 ± 0.0362 mm, respectively.
12.5.6 Statistical tests
Statistical tests are performed to measure the reliability and stability of the system. It
helps us to determine whether there is enough evidence to accept the null hypothesis.
The null hypothesis is an assumption that the two readings are related to each other.
All statistical analyses were performed using MedCalc software (Osteen, Belgium). The
two-tailed z-test, chi-squared test and Mann–Whitney test with a standard normal
distribution at the level of significance 0.05 were performed. The two-tailed z-test is
generally used when there are more than 30 readings. The chi-squared test is used to
determine whether there is a significant relationship between the two quantities.
Finally, the Mann–Whitney test was used to identify the significance difference
between the variables.
Table 12.4 shows the results of the two-tailed z-test, chi-squared test and Mann–
Whitney test between AtheroCloud™ and manual for left (< 0.2888, < 0.0001 and =
0.1419) and right (< 0.4795, = 0.0002 and = 0.4321) cIMT, respectively. The results
of the two-tailed z-test, chi-squared test and Mann–Whitney test between
AtheroCloud™ and sonographer for left and right cIMT were (< 0.0023,
< 0.0001 and = 0.0046) and (< 0.0001, < 0.0001 and = 0.0014), respectively. The
negative z-score conveys that the corresponding raw result is below (less than) the
mean. These statistical analyses were performed to demonstrate the positive
relationships of AtheroCloud™ cIMT against manual and sonographer cIMT and
were found to be statistically significant. The normality of each continuous variable
group was further confirmed by the Kolmogorov–Smirnov (KS)-test.
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