Download Diagnostic Accuracy of Coronary Computed Tomography

JACC: CARDIOVASCULAR IMAGING
VOL. 3, NO. 5, 2010
© 2010 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
PUBLISHED BY ELSEVIER INC.
ISSN 1936-878X/$36.00
DOI:10.1016/j.jcmg.2009.11.018
Diagnostic Accuracy of Coronary Computed
Tomography Angiography as Interpreted on
a Mobile Handheld Phone Device
Troy M. LaBounty, MD,* Robert J. Kim, MD,* Fay Y. Lin, MD, MA,*
Matthew J. Budoff, MD,‡ Jonathan W. Weinsaft, MD,† James K. Min, MD†
New York, New York; and Torrance, California
O B J E C T I V E S This study assessed the diagnostic performance of coronary computed tomography
angiography (CTA) for the detection and exclusion of significant coronary artery stenosis as remotely
interpreted on a mobile handheld device with dedicated medical imaging software.
B A C K G R O U N D Recent advances in technology now permit remote interpretation of medical imaging
studies on mobile handheld devices, although the diagnostic performance of this approach is unknown.
M E T H O D S We evaluated 102 patients with stable chest pain and both 64-detector row coronary CTA
and quantitative invasive coronary angiography. The diagnostic performance of remote coronary CTA
interpretation was assessed using a mobile handheld device and employing dedicated software. The
coronary CTA studies were examined in an intent-to-diagnose manner for the presence or absence of
coronary artery stenosis ⱖ50% on a per-artery and per-patient level; results were compared with quantitative
invasive coronary angiography. Two blinded imagers independently interpreted coronary CTA studies, with
a third imager achieving consensus for discordance. Coronary CTAs were re-interpreted in random order to
determine interobserver agreement. Finally, coronary CTAs were evaluated on a dedicated 3-dimensional
imaging workstation; results were compared to mobile handheld device findings for intertechnology
agreement.
R E S U L T S The prevalence of significant coronary artery stenosis was 25% (26 of 102) at the
per-patient level and 10% (40 of 405) at the per-artery level. Per-patient and per-artery sensitivity,
specificity, and positive and negative predictive values were: 100% (26 of 26), 78% (59 of 76), 60% (26
of 43), and 100% (59 of 59), respectively; and 95% (38 of 40), 85% (310 of 365), 41% (38 of 93), and 99%
(310 of 312), respectively. At the per-artery level, interobserver, intraobserver, and intertechnology
agreement was 0.74, 0.89, and 0.75, respectively (p ⬍ 0.01 for all).
C O N C L U S I O N S The interpretation of coronary CTA using a mobile handheld device with
dedicated software for medical image evaluation possesses high diagnostic accuracy for detection and
exclusion of significant coronary stenosis. (J Am Coll Cardiol Img 2010;3:482–90) © 2010 by the
American College of Cardiology Foundation
From the *Department of Medicine and †Department of Radiology, Weill Cornell Medical College—New York Presbyterian
Hospital, New York, New York; and the ‡Department of Medicine, Los Angeles Biomedical Research Institute at
Harbor—UCLA, Torrance, California. Dr. Min has a research grant and is on the Speakers’ Bureau for GE Healthcare, has
a research grant from Vital Images, and is a consultant for the Cordis Corporation. Dr. Budoff has research support and is on
the Speakers’ Bureau for GE Healthcare. The MIM Pro software (MIM Vista, Cleveland, Ohio) on the iPhone 3G device
(Apple, Inc., Cupertino, California) is not currently approved for clinical use by the U.S. Food and Drug Administration.
Manuscript received October 26, 2009, accepted November 12, 2009.
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C
oronary computed tomography angiography
(CTA) possesses high diagnostic accuracy
for detection and exclusion of significant
coronary artery stenosis (1–3). Historically,
coronary CTA interpretation has been limited to
dedicated stand-alone 3-dimensional (3D) imaging
workstations, which are expensive and generally unavailable outside performing institutions. Recently,
improvements in mobile handheld device technology
have resulted in enhanced computer processing power,
superior screen resolution, enriched user interfaces,
and improved networking (4). In parallel with these
advances, dedicated software that permits visualization
and post-processing of medical images has been developed. The combination of these hardware and
software improvements creates the potential for novel
platforms that permit remote viewing of medical
imaging studies by mobile handheld devices when
dedicated 3D imaging workstations are not available.
Although such platforms may enhance point-of-care
for medical imaging studies, the diagnostic performance of medical image interpretation by mobile
handheld devices has not been evaluated to date.
The aim of the present study was to compare the
diagnostic accuracy of remote coronary CTA interpretation using a mobile handheld device to quantitative coronary angiography (QCA) for the detection and exclusion of significant coronary artery
stenosis in chest pain patients without known coronary artery disease (CAD). We assessed the diagnostic performance at the per-patient and per-vessel
level in an intent-to-diagnose fashion, including all
patients and all vessels for final efficacy analysis.
METHODS
We evaluated patients with stable chest pain who
underwent 64-detector row coronary CTA and invasive coronary angiography (ICA) with QCA measurement, as part of the multicenter ACCURACY (Assessment by Coronary Computed Tomographic
Angiography of Individuals Undergoing Invasive
Coronary Angiography) Trial (1). The inclusion criteria of the ACCURACY trial included: age ⱖ18
years; typical or atypical chest pain symptoms; and
referral for a nonemergent ICA. Exclusion criteria
included: established iodinated contrast allergy; baseline renal insufficiency (creatinine ⱖ1.7 mg/dl); resting tachycardia (heart rate ⬎100 beats/min); irregular
heart rhythm; contraindication to beta-blocker,
calcium-channel blocker, or nitroglycerin; pregnancy;
or established history of CAD. The study was performed at 16 centers in the U.S., with approval of the
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Accuracy of Coronary CTA Interpreted on a Mobile Handheld Phone Device
483
institutional review board from each site. Details of
the study design have been previously reported (1).
For the present study, we included 102 patients from
the ACCURACY trial who were randomly selected
from the overall study cohort of 230 patients. The
study was limited to this number based on the storage
capacity of the handheld device.
Coronary CTA image acquisition. Subjects underwent
coronary CTA by a standard protocol (1). Patients
received oral and/or intravenous beta-blockers as
needed to achieve a heart rate ⬍65 beats/min and
were given 0.4-mg sublingual nitroglycerin before
the study. All scans were performed with 64detector CT scanners (Lightspeed VCT, GE
Healthcare, Milwaukee, Wisconsin) using a triplephase contrast protocol: 60-ml iodixanol (GE
Healthcare, Princeton, New Jersey), followed by a
40-ml 50:50 mixture of iodixanol and saline, followed by a 50-ml saline flush. The scan parameters
included 64 ⫻ 0.625 mm collimation, tube voltage
120 mV, 350 to 780 mA, and dose-modulated
retrospective electrocardiogram-gating.
ABBREVIATIONS
Radiation dose reduction algorithms using
AND ACRONYMS
automodulation of tube current and
electrocardiography-modulated imaging
CAD ⴝ coronary artery disease
was performed. After coronary CTA scan
CTA ⴝ computed tomographic
completion, images were reconstructed at
angiography
75% of the R-R interval for the present
ICA ⴝ invasive coronary
angiography
study.
QCA ⴝ quantitative coronary
Image analysis. The coronary CTA images
angiography
were reviewed using MIM Pro software
3D ⴝ 3-dimensional
version 1.0.4 (MIM Vista, Cleveland, Ohio)
on an iPhone 3G device (Apple Inc., Cupertino, California), with a diagonal screen size of 8.9
cm and a screen resolution of 480 ⫻ 320 pixels.
Full-resolution images were transferred over an encrypted 802.11 Wi-Fi network to the handheld device. Each study was transferred and uncompressed on
the device in less than 5 min. As the MIM Pro
software (MIM Vista) used for the present study did
not have post-processing reconstruction capability,
coronary CTA image interpretations were restricted
to axial images at high resolution (0.625-mm in-plane
slice thickness).
Two coronary CTA imagers independently interpreted studies in blinded fashion; a third blinded
reader achieved consensus in cases of discordance. All
3 readers were level III– certified in coronary CTA
performance and interpretation, and each reader had
experience interpreting ⬎1,000 coronary CTA examinations. Coronary CTA imager #1 had experience in
using the particular handheld device for coronary
CTA viewing and had previously interpreted more
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Accuracy of Coronary CTA Interpreted on a Mobile Handheld Phone Device
than 50 studies on the device as part of a separate
study. Coronary CTA imager #2 had no experience
using the handheld device prior to the study. To assess
intraobserver variability, 1 imager blindly reinterpreted
all coronary CTA examinations using the mobile
handheld device in a random order, in blinded fashion, and at a minimum of 4 weeks after initial
interpretation. To assess intertechnology variability, 1
reader blindly interpreted all coronary CTA examinations using a dedicated 3D imaging workstation (AW
4.4 Advantage Workstation with CardIQ software;
GE Healthcare, Milwaukee, Wisconsin) using only
axial images. One blinded, experienced reader interpreted coronary CTA studies using the same dedicated 3D imaging workstation and all necessary postprocessing reconstruction techniques, including axial
images, maximum intensity projections, multiplanar
reformats, cross-section analyses, and volume-rendered
imaging. To minimize recall bias, all studies were re-read
in different sequences and at least 4 weeks apart. All
studies on handheld devices were interpreted while sitting in a variety of lighted rooms, including rooms with
both fluorescent and incandescent lighting.
The coronary CTA studies were assessed for maximal stenosis on a per-patient and per-artery level, and
comparisons were performed between coronary CTA
and QCA for the detection of significant coronary
artery stenosis. The handheld device and software
permitted touch-screen optimization of windowing
and leveling (by moving 2 fingers in the x- and y-axes
on the screen) (Fig. 1), scrolling in the z-axis (by using
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1 finger on a scrollbar on the edge of the screen),
image zooming (by pinching 2 fingers together or
apart on the screen) (Fig. 2), and panning in the x-y
axes (by dragging 1 finger on the screen) (Fig. 3).
Each artery was examined by centering the artery on the
screen and scrolling throughout the arterial course on
axial images, with zoom and windowing at the discretion
of the reader.
Studies were evaluated for the presence of significant coronary artery stenosis, defined as ⱖ50% luminal diameter stenosis, using the most severe stenosis
per vessel (Figs. 4 and 5). Stenosis estimation was
based upon comparisons of the luminal size at the site
of stenosis of greatest severity to the nearest proximal
site with the most normal appearance. Per-artery
evaluation was performed for the left main, left anterior descending, left circumflex (including ramus intermedius), and right coronary arteries. For purposes
of evaluation, the diagonal and septal branches were
considered as part of the left anterior descending
artery. The obtuse marginal, left posterolateral, and
left posterior descending branches were considered as
part of the left circumflex artery. The right ventricular
marginal branches, right posterior descending artery,
and right posterolateral branches were considered part
of the right coronary artery. Each artery was examined
in its entirety, and if any portion of an artery was
considered nonevaluable, the entire artery was considered nonevaluable for the purposes of analysis. All
portions of arteries were included for analysis, irrespective of luminal diameter size.
Figure 1. Adjustment of Window Width and Level by the Mobile Handheld Device
Simultaneously moving 2 fingers (as depicted by the white circles and white arrow) on the screen in the x- and y-axes change the
image windowing. In the example, by moving the fingers down and to the right on the screen, the window width and level changed
from 1,666 and 172 (A) to 1,120 and 345 (B) Hounsfield units (HU), respectively.
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LaBounty et al.
Accuracy of Coronary CTA Interpreted on a Mobile Handheld Phone Device
Figure 2. Demonstration of Imaging Zooming by the Mobile Handheld Device
Simultaneously moving 2 fingers apart (as depicted by the white circles and white arrows) (A) increases the image zoom (B). Pinching
the fingers together decreases the zoom. Abbreviation as in Figure 1.
The ICA studies were performed in a standardized
manner, as previously described, with all studies blindly
interpreted by an independent reader using QCA (1).
Statistical analysis. Analyses were performed to determine the diagnostic performance of coronary CTA as
interpreted by a mobile handheld device as compared
with QCA for the detection and exclusion of ⱖ50%
maximal diameter stenosis. Similar comparisons were
performed using dedicated workstations limited to
axial image review as well as dedicated workstations
using post-processing reconstruction techniques.
Nonevaluable arteries were examined in an intent-todiagnose fashion, including all patients and all vessels
for the final efficacy analysis. Arteries in which portions of the vessels were considered nonevaluable by
expert coronary CTA imagers were considered as
having ⱖ50% diameter stenosis. A secondary analysis
was performed that excluded arteries and patients in
which portions of the arteries were deemed nonevaluable. Patients in whom coronary CTA demonstrated at least 1 nonevaluable artery but in whom a
ⱖ50% stenosis was noted in separate evaluable artery
were included in the latter analysis.
Comparisons between groups were performed with
McNemar and Fisher exact tests for paired and
nonpaired categorical variables, respectively. Kappa
tests were used to compare intraobserver, interobserver, and intertechnology agreement. To determine
the 95% confidence intervals for proportions, the
efficient-score method was used. SPSS version 17.0
(SPSS Inc., Chicago, Illinois) was used for all analyses. A 2-tailed p value ⬍0.05 was deemed significant.
RESULTS
The study cohort included 102 stable chest pain
patients who underwent coronary CTA before nonemergent ICA. Patient demographics are listed in
Table 1. A total of 3 arteries from 3 patients could not
be evaluated by QCA; these were excluded from
further analysis, and the remaining 405 arteries were
included in the study. Significant coronary artery
stenosis at the 50% threshold was observed by QCA
in 26 of 102 (26%) patients and 40 of 405 (10%)
arteries, with significant coronary artery stenosis in the
left main, left anterior descending, left circumflex, and
right coronary arteries in 1%, 11%, 12%, and 16% of
patients, respectively.
On coronary CTA, 17 of 405 (4%) arteries from 12
patients were considered nonevaluable by expert coronary CTA imagers. Significant coronary artery stenosis was observed in separate evaluable arteries in 7 of
these patients, resulting in 5 patients where the presence or absence of significant CAD could not be
determined at the per-patient level. The frequency of
nonevaluable arteries was 0%, 2%, 4%, and 11% for
the left main, left anterior descending, left circumflex,
and right coronary arteries, respectively.
Using dedicated workstations, there were 10 arteries deemed nonevaluable for analysis on axial image
review (p ⫽ 0.07 vs. handheld device), and 10 arteries
deemed nonevaluable after use of post-processing reconstruction techniques (p ⫽ 0.19 vs. handheld device).
Diagnostic performance. The diagnostic performance
of coronary CTA as interpreted by a remote mobile
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Figure 3. Demonstration of Panning by the Mobile Handheld Device
Moving a single finger on the device screen (as depicted by the white circles and white arrow) (A) pans the selected image and permits
manual centering within the image plane (B).
handheld device in comparison to QCA is provided in
Tables 2 and 3. For the primary intent-to-diagnose
analyses, all nonevaluable arteries on coronary CTA
were assumed to exhibit significant coronary artery
stenosis. Secondary analyses were performed with
nonevaluable arteries excluded; if at least 1 artery was
nonevaluable but significant CAD was identified in
other arteries, the patient was included in the perpatient analysis. Per-patient and per-artery analyses
revealed high sensitivity and negative predictive values,
with moderate and fair specificity and positive predictive values, respectively.
Our coronary CTA imager #1 had prior experience
using the handheld device to interpret coronary CTA
studies, whereas coronary CTA imager #2 had no
prior experience. The sensitivity of each coronary
CTA imager was identical (100% [26 of 26] for
each, p ⫽ 1.0), whereas coronary CTA imager #1
had higher specificity (78% [59 of 76] vs. 64% [49
of 76], p ⫽ 0.01). The negative predictive value
was identical between readers (100% [59 of 59]
vs. 100% [49 of 49], p ⫽ 1.0), with no significant
difference in the positive predictive value (60%
[26 of 43] vs. 49% [26 of 53], p ⫽ 0.31).
Figure 4. Mild Coronary Artery Stenosis
Example of mild plaque (arrows) with ⬍50% luminal stenosis involving the proximal left anterior descending artery on both a workstation
computer (A) and on the handheld device (B). The window width and level were 800 and 100 Hounsfield units for both, respectively.
LaBounty et al.
Accuracy of Coronary CTA Interpreted on a Mobile Handheld Phone Device
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Figure 5. Severe Coronary Artery Stenosis
Example of an occluded proximal left anterior descending coronary artery (arrows) on both a workstation computer (A) and on the
handheld device (B). The window width and level were 800 and 100 Hounsfield units for both, respectively.
Impact of variables on diagnostic performance. Additional analyses were performed to assess the impact of
specific variables on study interpretability and the
diagnostic performance (Table 4). No differences in
diagnostic performance of coronary CTA as interpreted by the mobile handheld device were noted for
patients with higher coronary artery calcium scores or
body mass index; however, both a heart rate ⱕ65
beats/min (p ⬍ 0.01) and intrascan heart rate variability ⬍10 beats/min (p ⫽ 0.03) were associated with a
significant increase in study interpretability, as well as
improved or a trend toward improved specificity.
Comparison between interpretation techniques.
There was good interobserver agreement between the
coronary CTA imagers, and very good intraobserver
agreement (Table 5). Intertechnology agreement
comparing interpretation on the mobile handheld
device to the dedicated 3D imaging workstation demonstrated good agreement.
Table 1. Baseline Patient Demographics
Age, yrs
Male sex, %
Body mass index, kg/m2
57 ⫾ 9
60
32 ⫾ 6
A comparison of the diagnostic performance between coronary CTA interpreted on the handheld
device and interpretations using a dedicated workstation demonstrates that both axial-only and complete
post-processing image reconstruction result in higher
specificity and positive predictive values, although the
differences were not statistically significant (Table 6).
DISCUSSION
This study represents the first evaluation of the diagnostic performance of remote medical image interpretation via a mobile handheld device with dedicated
Table 2. Diagnostic Accuracy of Coronary CTA Interpretation
on a Handheld Device: Patient-Based Analysis
Estimate (%)
95% CI (%)
n
Sensitivity
100
84–100
26/26
Specificity
78
66–86
59/76
PPV
60
44–75
26/43
NPV
100
92–100
59/59
25/25
Analysis of all patients
(N ⫽ 102)
Analysis limited to
evaluable patients
(n ⫽ 97)
Heart rate, beats/min
55 ⫾ 6
Sensitivity
100
83–100
Heart rate variability, beats/min
3 (3–5)
Specificity
82
71–90
59/72
PPV
66
49–80
25/38
NPV
100
92–100
59/59
Diabetes, %
25
Hyperlipidemia, %
76
Hypertension, %
63
Any history of tobacco use, %
55
Positive family history, %
84
Percentage or mean with standard deviation provided. As the heart rate
variability does not have a normal distribution, it is provided as a median and
interquartile range.
Diagnostic accuracy provided for detection of ⱖ50% luminal coronary artery
stenosis by quantitative coronary angiography. Nonevaluable arteries were
deemed to have significant coronary artery stenosis for analysis of all patients
in the primary intent-to-diagnose analysis; the secondary analysis excluded
patients with nonevaluable arteries in which significant coronary artery
disease could not be established or excluded.
CI ⫽ confidence interval; CTA ⫽ computed tomographic angiography;
PPV ⫽ positive predictive value; NPV ⫽ negative predictive value.
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Table 3. Diagnostic Accuracy of Coronary CTA Interpretation
on a Handheld Device: Artery-Based Analysis
Estimate (%)
95% CI (%)
n
Sensitivity
95
82–99
38/40
Specificity
85
81–88
310/365
PPV
41
31–52
38/93
NPV
99
97–100
310/312
Sensitivity
94
79–99
32/34
Specificity
88
84–91
310/354
PPV
42
31–54
32/76
NPV
99
97–100
310/312
Analysis of All Arteries
(N ⫽ 405)
Analysis Limited to
Evaluable Arteries
(n ⫽ 388)
Diagnostic accuracy provided for detection of ⱖ50% luminal coronary artery
stenosis by quantitative coronary angiography. Nonevaluable arteries were
deemed to have significant coronary artery stenosis for analysis of all arteries
in the primary intent-to-diagnose analysis; the secondary analysis was limited
to evaluable arteries.
Abbreviations as in Table 2.
medical imaging software. We employed coronary
CTA examinations from the prospective multicenter
ACCURACY trial, which included individuals with
chest pain syndrome without known CAD. Our
results demonstrate high diagnostic sensitivity and
negative predictive value for a mobile handheld device
to detect and exclude significant coronary artery stenosis, albeit with lower specificity and positive predictive values. These results demonstrate diagnostic performance characteristics that are on par with other
noninvasive imaging modalities (such as stress echocardiography and myocardial perfusion scintigraphy).
In our study, we noted differences in the diagnostic
accuracy of coronary CTA interpretation when comparing 2 coronary CTA imagers with different levels
of familiarity with the mobile handheld technology. In
particular, coronary CTA imager #1 had previously
used the device for another study evaluating coronary
CTA images in a different study population that
consisted of 50 cases and had extensive experience
using the particular device for additional applications.
In contrast, coronary CTA imager #2 had never
previously used the mobile handheld device for either
medical image viewing or for other applications.
These differences were associated with a reduced
specificity with the less-experienced coronary CTA
imager #2. The interobserver agreement was lower
than the intraobserver agreement, which is consistent
with these findings. Despite these differences, both
readers’ interpretations demonstrated very high sensitivity and negative predictive value, suggesting that the
“learning curve” of this mobile handheld device is
generally rapid and easy. Nevertheless, future studies
evaluating the length of the “learning curve” of coronary CTA interpretation on mobile handheld devices
should be performed.
The current version of the medical image viewing
software was limited to review and processing of axial
images alone; 3D post-processing was unavailable. In
contrast, prior studies evaluating the diagnostic accuracy of coronary CTA for detection and exclusion of
Table 4. Patient-Based Diagnostic Accuracy Stratified by Specific Variables
Calcium Score (HU)
<400
>400
Interpretability
91% (67/74)
82% (23/28)
Sensitivity
100% (20/20)
Specificity
76% (41/54)
82% (18/22)
<35
>35
Body Mass Index (kg/m2)
Interpretability
84% (58/69)
Sensitivity
100% (20/20)
Specificity
71% (35/49)
Heart Rate (beats/min)
Interpretability
<65
100% (6/6)
97% (32/33)
100% (6/6)
89% (24/27)
>65
p Value
0.30
1.0
0.76
p Value
0.10
1.0
0.09
p Value
⬍0.01
92% (88/96)
33% (2/6)
Sensitivity
100% (25/25)
100% (1/1)
1.0
Specificity
82% (58/71)
20% (1/5)
⬍0.01
>10
p Value
Heart Rate Variability (beats/min)
Interpretability
<10
91% (86/95)
57% (4/7)
Sensitivity
100% (25/25)
100% (1/1)
1.0
Specificity
80% (56/70)
50% (3/6)
0.12
In these per-patient analyses, all patients were included, with nonevaluable arteries assumed to represent significant coronary artery stenosis.
HU ⫽ Hounsfield units.
0.03
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Table 5. Artery-Based Interobserver, Intraobserver, and
Intertechnology Agreement
Agreement, % (n)
Kappa
p Value
Interobserver
89% (365/408)
0.74
⬍0.01
Intraobserver
96% (392/408)
0.89
⬍0.01
Intertechnology
92% (376/408)
0.75
⬍0.01
Intertechnology represents comparison between a reader on a handheld device
and repeat subsequent interpretation on a dedicated workstation by the same
reader using axial images only. For all cases, arteries were designated as
nonevaluable, ⬍50% maximal stenosis, or ⱖ50% maximal stenosis.
coronary artery stenosis have used dedicated imaging
workstations capable of 3D post-processing techniques and have included interpretation using not only
axial images, but also oblique images, multiplanar
reformations, maximum intensity projections, and
volume-rendered surface-shaded displays. Indeed,
current scientific guidelines encourage the use of
multiple 3D post-processing techniques when interpreting coronary CTA studies (5). A recent comparison of the diagnostic accuracy of these different
techniques reported a sensitivity and specificity of
91% and 88% for axial images; in comparison, 3D
oblique maximum intensity projections and multiplanar reformations had similar sensitivity, but
higher specificity (6). As such, future iterations of
medical image viewing software with 3D postprocessing capability may result in slightly different
results than what we observed in the current study.
When compared to the diagnostic accuracy of
coronary CTA interpreted on dedicated workstations (both analysis limited to axial images and
analysis using post-processing techniques), there
was a nonsignificant trend to reduced specificity
using the handheld device. Nevertheless, the findings of the present analysis suggest that currentgeneration remote handheld device medical image
review restricted to the axial plane does permit
interpretation with high sensitivity and negative
predictive value, and can be thus useful for detection and exclusion of significant coronary artery
stenosis.
We used a mobile handheld phone device for this
study, which possesses a screen resolution of 480 ⫻
320 pixels. This small screen may theoretically influence diagnostic performance. Further, the number of
shades of gray that can be discerned by the mobile
handheld device has not been reported by the manufacturer, and any screen with finite grayscale discrimination that is less than the approximately 4,000
shades of gray of the CT Hounsfield unit scale may
theoretically influence diagnostic performance. In our
study, we noted that the intertechnology agreement
was high between the mobile handheld device and the
dedicated 3D imaging workstation. Given differences
in screen resolution, bit depth and grayscales on
different mobile handheld devices, it remains unknown whether the device used in this study differs
from other handheld devices with respect to diagnostic accuracy. Future studies should be performed to
evaluate these differences.
Stratification of patients by coronary artery calcium
score and body mass index did not result in differences
in coronary CTA study interpretability or diagnostic
performance. In contrast, heart rates ⬎65 beats/min
and heart rate variability ⱖ10 beats per coronary CTA
scan were associated with a significant reduction in
study interpretability; whereas the diagnostic sensitivity was unaffected, the specificity was poorer for
patients with faster heart rates and greater heart rate
variability. In our study population, the number of
patients with poorly controlled or highly variable heart
rates was low, emphasizing the importance of patient
selection and pre-medication with beta-blockers in
coronary CTA examinations. Further, we employed
prospectively acquired data from the multicenter ACCURACY trial, which restricted enrollment to those
individuals without known CAD in whom a decision
to perform invasive coronary angiography had already
been made. The ACCURACY study cohort, as is
reflected in the present study, identified an intermediate prevalence of significant coronary artery stenosis.
As such, the diagnostic performance of the mobile
Table 6. Comparative Diagnostic Performance by Coronary CTA Interpretation Technique
Handheld Device % (n)
Workstation With Axial
Images Only % (n)
p Value
Workstation With Post-Processing
Techniques % (n)
p Value
Sensitivity
100 (26/26)
92 (24/26)
0.50
100 (26/26)
1.0
Specificity
78 (59/76)
87 (66/76)
0.07
86 (65/76)
0.15
PPV
60 (26/43)
71 (24/34)
0.47
70 (26/37)
0.48
NPV
100 (59/59)
97 (66/68)
0.50
100 (65/65)
1.0
Patient-based analysis was used for detection of maximal luminal coronary artery stenosis of ⱖ50% by coronary CTA in comparison to quantitative coronary
angiography. Nonevaluable arteries were deemed to have significant coronary artery stenosis for analysis of all patients in the primary intent-to-diagnose analysis.
The p values for comparisons to handheld device are shown.
Abbreviations as in Table 2.
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handheld device technology in other study cohorts—
such as those with known CAD or with alternate
prevalence of significant coronary artery stenosis—
remains unknown.
Finally, we employed beta software for interpretation of coronary CTA studies on a mobile handheld
device. Although an application for this software has
been submitted to the U.S. Food and Drug Administration, it is not currently approved for coronary CTA
interpretation and our present results should be interpreted as proof-of-concept pending their approval.
To enhance point-of-care for individuals undergoing medical imaging studies, remote access to
medical images has expanded beyond dedicated 3D
imaging workstations. Numerous potential solutions have been developed that include off-site 3D
imaging workstations with dedicated broadband
access, thin-client servers, and more recently, mobile handheld devices. Contemporary advances in the
field of mobile handheld technology now permit
viewing and processing of medical images anywhere
an Internet connection exists, which may permit
sharing of studies for consultation with additional
readers and which may enable remote medical
image evaluation if on-site readers are unavailable.
These developments carry the potential of improving
the efficiency of diagnostic imaging evaluation, given
the potentially expanded access to medical images.
Further, the effects of medical image viewing via
remote mobile device technology may influence patient factors such as medical compliance and lifestyle
modification, as these images may be easily demonstrated to patients. Future studies should be performed
to examine the clinical utility of mobile handheld
devices in relation to workflow and patient care.
Importantly, the handheld device was limited to
review of axial images, and the ability to perform 3D
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Reprint requests and correspondence: Dr. Troy M.
LaBounty, Weill Cornell Medical College—New York
Presbyterian Hospital, Starr Pavilion 4th Floor, 520
East 70th Street, New York, New York 10021. E-mail:
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Key Words: computed
tomography y angiography y
coronary artery disease.