JACC: CARDIOVASCULAR IMAGING
VOL. 7, NO. 9, 2014
ª 2014 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
ISSN 1936-878X/$36.00
PUBLISHED BY ELSEVIER INC.
http://dx.doi.org/10.1016/j.jcmg.2014.04.015
EDITORIAL COMMENT
The Need for Speed Accelerating CMR Imaging Assessment of Cardiac Function* Leon Axel, PHD, MD, Daniel K. Sodickson, PHD, MD
A
ssessment of cardiac function is a corner-
breath-holds, resulting in prolonged examination
stone of the diagnosis and care of patients
times
with heart disease. The use of various imag-
different breath-hold periods.
and
potential
inconsistencies
among
ing methods for measuring cardiac function has
2. The inside of the ventricular wall is rough, due to
become increasingly important in both clinical prac-
the presence of trabeculations and papillary mus-
tice and research. In particular, cardiac magnetic
cles. Although, by convention, these irregular
resonance (CMR) has become the de facto standard
structures are generally included with the cavity, it
for assessment of global cardiac function through
is more difficult to delineate them at end-systole,
measurement of the change in ventricular volumes
potentially introducing a bias into the calculated
over the cardiac cycle and calculation of the associ-
end-systolic volumes and the EF.
ated ejection fraction (EF). This reflects the strengths
3. The frequent presence in cardiac patients of car-
of CMR, including its ability to generate a set of
diac arrhythmias and difficulty with breath-
high-quality tomographic images, synchronized with
holding can lead to associated decreases in image
different phases of the cardiac cycle, with accurately
quality.
known 3-dimensional (3D) spatial relationships, thus
4. The need to interact frequently with CMR analysis
permitting reliable segmentation of the boundary
programs to manually correct errors in automated
contours of the ventricular walls and calculation of
image segmentation introduced by the imaging
the corresponding ventricular volumes. These global
limitations mentioned in the previous text in-
function measurements can be combined in a single
creases the time needed to carry out the analysis
imaging session with the use of other CMR-derived
and decreases its reproducibility.
measures of, for example, regional and functional cardiac anatomy, blood flow, myocardial perfusion, and other tissue characteristics such as signal relaxation times and late gadolinium enhancement. Thus, CMR has long been touted as a sort of “1-stop shop” for cardiac evaluation. However, there are still some important limitations in the use of CMR for measurement of global function and calculation of EF:
In cardiac imaging more than in many other settings, the goal is simultaneous characterization of complex 3D tissue structure and dynamics; therefore, imaging speed is of the essence. Various classes of methodological and technological advances have been brought to bear over the years to accelerate CMR. These include a menagerie of advanced pulse sequences and hardware improvements. The advent of parallel magnetic resonance imaging, in which ar-
1. The relatively long time required to acquire con-
rays of radiofrequency coils are used to gather
ventional CMR data requires that the necessary
essential data simultaneously rather than in a tradi-
volumetric data be pieced together over multiple
tional sequential order, has circumvented previous speed limits, and parallel imaging techniques have played a key role in modern CMR examinations. A
*Editorials published in JACC: Cardiovascular Imaging reflect the views
recent and highly promising addition to the arma-
of the authors and do not necessarily represent the views of JACC:
mentarium of rapid CMR is compressed sensing (CS),
Cardiovascular Imaging or the American College of Cardiology.
which combines incoherently undersampled data
From the Bernard and Irene Schwartz Center for Biomedical Imaging,
acquisition with sparsity-enforcing image recon-
Department of Radiology, New York University School of Medicine, New York, New York. Drs. Axel and Sodickson have contributed to various
struction. CS may be considered as a form of image
patent applications in the area of rapid imaging using compressed
pre-compression, in which time-consuming data
sensing methods.
acquisition
steps
are
omitted
beforehand
with
894
Axel and Sodickson
JACC: CARDIOVASCULAR IMAGING, VOL. 7, NO. 9, 2014 SEPTEMBER 2014:893–5
Editorial Comment
knowledge that key information will be recovered
associated increased estimates of EF, as might be
robustly in reconstruction. Soon after the seminal
expected from the somewhat lower resolution of
work by Donoho, Candès, and Tao introducing CS
the CS-based imaging used.
appeared in the applied mathematics literature, CS
3. Although the relatively short acquisition time
methods were applied to magnetic resonance imaging
needed for each slice (2 heartbeats) may decrease
by Lustig et al. (1). Since then, interest in CS for
the image-degrading effects of respiratory motion
accelerated
various
or arrhythmias, it will not eliminate them and will
productive combinations with other acceleration
not capture associated real variations in the un-
imaging
has
burgeoned,
techniques such as parallel imaging have been
derlying functional measures.
developed, and numerous practical implementations
4. The computation-intensive nature of iterative CS-
for CMR have been demonstrated. However, despite
based image reconstruction makes it a relatively
vigorous research interest in CS methods, to date
lengthy process. However, as suggested by the
there have been comparatively few evaluations in a
researchers, the use of more powerful specialized
truly clinical setting. The current study is, therefore,
computers, such as graphics processing units, is
a welcome addition to the literature.
likely to make this less of a practical problem. 5. The use of global measurements derived from aortic flow as a reference can be problematic, due
SEE PAGE 882
to the frequent presence of uncontrolled baseline In this issue of iJACC, Vincenti et al. (2) report on a CS-based approach to acquire multislice CMR data in a single breath-hold, together with a 3D model– based
approach
to
calculate
global
function
measures from the resulting dataset. Images were qualitatively assessed for overall quality and the presence of artifacts, and the derived function measurements were validated against comparable results from both standard volume analysis of conventionally acquired CMR data of the ventricles and integrated CMR flow data acquired in the aortic root. The
reported
results
reasonable-looking
image
are
encouraging,
quality
and
with
excellent
agreement of the new functional measurements with those derived from the more conventional approaches. In addition to the time savings of the new approach, the acquisition of complete datasets in a single breath-hold allows for better spatial registration between individual slices, potentially enabling more accurate volume calculations. The model-based volumetric image analysis method used here provides both an attractive 3D display of the underlying ventricular structure and a means of regularizing volume calculations despite a relatively coarse spatial sampling. There are also some limitations of the current study:
offsets in the flow measurements. Although the results of Vincenti et al. (2) are already encouraging, the exploration of CS-based approaches to imaging and image analysis is an active and rapidly expanding area. Although the researchers used a conventional Cartesian-based sampling of the CMR data, non-Cartesian sampling offers potential advantages. For example, radial sampling patterns (3) reduce the impact of aliasing from structures in the outer parts of the field of view (a problem encountered in the current study). Radial acquisitions have been shown to be inherently well suited for robust CS, and they are also compatible with continuous acquisition approaches (e.g., employing golden-angle schemes) (4). CSbased methods may also enable significant speed-up of flow measurements, which could both reduce the time required and make the extension of such imaging
to
more
fully
3D
volumetric
flow
measurements more practical. Other CS-based CMR approaches also have the potential to substantially reduce the deleterious effects of respiratory motion and arrhythmias on the images, and they have even been shown to enable robust characterization of irregular cardiac and respiratory motion patterns together with improved structural and functional assessments (5).
1. As the researchers acknowledge, the coarse spatial
In summary, the paper of Vincenti et al. (2)
sampling used here would not be adequate for
provides welcome evidence of some of the potential
assessment of the regional anatomy and function
value of CS CMR for improved cardiac function
of the heart and thus would not eliminate the need
assessment, but it is only the barest beginning. In
for acquiring a conventional set of more closely
fact, there are early indications that a more complete
spaced images.
integration of advanced acceleration methods into toward
everyday imaging practice may be in store, in
decreased estimates of end-diastolic volume and
the form of a new paradigm of rapid, continuous
2. There
were
some
systematic
biases
Axel and Sodickson
JACC: CARDIOVASCULAR IMAGING, VOL. 7, NO. 9, 2014 SEPTEMBER 2014:893–5
Editorial Comment
comprehensive imaging. Such an approach would
enabling increasingly rich characterization of both
be both simpler and more efficient than traditional
structure and function in the human heart.
multiplanar CMR protocols, eliminating “dead time” and
REPRINT REQUESTS AND CORRESPONDENCE: Dr.
allowing extraction of multiple dynamic as well as
Daniel K. Sodickson, Department of Radiology, New
tissue
between
separate
specialized
acquisitions
simultaneously. This
York University School of Medicine, 660 First
approach, enabled by key advances such as CS, would
Avenue, Fourth Floor, Room 407, New York, New
revolutionize
York 10016. E-mail: [email protected].
contrast
parameters
cardiac
imaging
workflow
while
REFERENCES 1. Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 2007;58: 1182–95.
3. Peters DC, Ennis DB, McVeigh ER. High-resolution MRI of cardiac function with projection reconstruction and steady-state free precession. Magn Reson Med 2002;48:82–8.
2. Vincenti G, Monney P, Chaptinel J, et al. Compressed sensing single–breath-hold CMR for fast quantification of LV function, volumes, and mass. J Am Coll Cardiol Img 2014;7: 882–92.
4. Feng L, Grimm R, Block KT, et al. Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med 2013 Oct 18 [E-pub ahead of print].
5. Feng L, Axel L, Latson LA, Xu J, Sodickson DK, Otazo R. Compressed sensing with synchronized cardio-respiratory sparsity for free-breathing cine MRI: initial comparative study on patients with arrhythmias. J Cardiovasc Magn Reson 2014;16 Suppl 1:O17.
KEY WORDS cardiac function, fast imaging, fast LV assessment
895
VOL. 7, NO. 9, 2014
ª 2014 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
ISSN 1936-878X/$36.00
PUBLISHED BY ELSEVIER INC.
http://dx.doi.org/10.1016/j.jcmg.2014.04.015
EDITORIAL COMMENT
The Need for Speed Accelerating CMR Imaging Assessment of Cardiac Function* Leon Axel, PHD, MD, Daniel K. Sodickson, PHD, MD
A
ssessment of cardiac function is a corner-
breath-holds, resulting in prolonged examination
stone of the diagnosis and care of patients
times
with heart disease. The use of various imag-
different breath-hold periods.
and
potential
inconsistencies
among
ing methods for measuring cardiac function has
2. The inside of the ventricular wall is rough, due to
become increasingly important in both clinical prac-
the presence of trabeculations and papillary mus-
tice and research. In particular, cardiac magnetic
cles. Although, by convention, these irregular
resonance (CMR) has become the de facto standard
structures are generally included with the cavity, it
for assessment of global cardiac function through
is more difficult to delineate them at end-systole,
measurement of the change in ventricular volumes
potentially introducing a bias into the calculated
over the cardiac cycle and calculation of the associ-
end-systolic volumes and the EF.
ated ejection fraction (EF). This reflects the strengths
3. The frequent presence in cardiac patients of car-
of CMR, including its ability to generate a set of
diac arrhythmias and difficulty with breath-
high-quality tomographic images, synchronized with
holding can lead to associated decreases in image
different phases of the cardiac cycle, with accurately
quality.
known 3-dimensional (3D) spatial relationships, thus
4. The need to interact frequently with CMR analysis
permitting reliable segmentation of the boundary
programs to manually correct errors in automated
contours of the ventricular walls and calculation of
image segmentation introduced by the imaging
the corresponding ventricular volumes. These global
limitations mentioned in the previous text in-
function measurements can be combined in a single
creases the time needed to carry out the analysis
imaging session with the use of other CMR-derived
and decreases its reproducibility.
measures of, for example, regional and functional cardiac anatomy, blood flow, myocardial perfusion, and other tissue characteristics such as signal relaxation times and late gadolinium enhancement. Thus, CMR has long been touted as a sort of “1-stop shop” for cardiac evaluation. However, there are still some important limitations in the use of CMR for measurement of global function and calculation of EF:
In cardiac imaging more than in many other settings, the goal is simultaneous characterization of complex 3D tissue structure and dynamics; therefore, imaging speed is of the essence. Various classes of methodological and technological advances have been brought to bear over the years to accelerate CMR. These include a menagerie of advanced pulse sequences and hardware improvements. The advent of parallel magnetic resonance imaging, in which ar-
1. The relatively long time required to acquire con-
rays of radiofrequency coils are used to gather
ventional CMR data requires that the necessary
essential data simultaneously rather than in a tradi-
volumetric data be pieced together over multiple
tional sequential order, has circumvented previous speed limits, and parallel imaging techniques have played a key role in modern CMR examinations. A
*Editorials published in JACC: Cardiovascular Imaging reflect the views
recent and highly promising addition to the arma-
of the authors and do not necessarily represent the views of JACC:
mentarium of rapid CMR is compressed sensing (CS),
Cardiovascular Imaging or the American College of Cardiology.
which combines incoherently undersampled data
From the Bernard and Irene Schwartz Center for Biomedical Imaging,
acquisition with sparsity-enforcing image recon-
Department of Radiology, New York University School of Medicine, New York, New York. Drs. Axel and Sodickson have contributed to various
struction. CS may be considered as a form of image
patent applications in the area of rapid imaging using compressed
pre-compression, in which time-consuming data
sensing methods.
acquisition
steps
are
omitted
beforehand
with
894
Axel and Sodickson
JACC: CARDIOVASCULAR IMAGING, VOL. 7, NO. 9, 2014 SEPTEMBER 2014:893–5
Editorial Comment
knowledge that key information will be recovered
associated increased estimates of EF, as might be
robustly in reconstruction. Soon after the seminal
expected from the somewhat lower resolution of
work by Donoho, Candès, and Tao introducing CS
the CS-based imaging used.
appeared in the applied mathematics literature, CS
3. Although the relatively short acquisition time
methods were applied to magnetic resonance imaging
needed for each slice (2 heartbeats) may decrease
by Lustig et al. (1). Since then, interest in CS for
the image-degrading effects of respiratory motion
accelerated
various
or arrhythmias, it will not eliminate them and will
productive combinations with other acceleration
not capture associated real variations in the un-
imaging
has
burgeoned,
techniques such as parallel imaging have been
derlying functional measures.
developed, and numerous practical implementations
4. The computation-intensive nature of iterative CS-
for CMR have been demonstrated. However, despite
based image reconstruction makes it a relatively
vigorous research interest in CS methods, to date
lengthy process. However, as suggested by the
there have been comparatively few evaluations in a
researchers, the use of more powerful specialized
truly clinical setting. The current study is, therefore,
computers, such as graphics processing units, is
a welcome addition to the literature.
likely to make this less of a practical problem. 5. The use of global measurements derived from aortic flow as a reference can be problematic, due
SEE PAGE 882
to the frequent presence of uncontrolled baseline In this issue of iJACC, Vincenti et al. (2) report on a CS-based approach to acquire multislice CMR data in a single breath-hold, together with a 3D model– based
approach
to
calculate
global
function
measures from the resulting dataset. Images were qualitatively assessed for overall quality and the presence of artifacts, and the derived function measurements were validated against comparable results from both standard volume analysis of conventionally acquired CMR data of the ventricles and integrated CMR flow data acquired in the aortic root. The
reported
results
reasonable-looking
image
are
encouraging,
quality
and
with
excellent
agreement of the new functional measurements with those derived from the more conventional approaches. In addition to the time savings of the new approach, the acquisition of complete datasets in a single breath-hold allows for better spatial registration between individual slices, potentially enabling more accurate volume calculations. The model-based volumetric image analysis method used here provides both an attractive 3D display of the underlying ventricular structure and a means of regularizing volume calculations despite a relatively coarse spatial sampling. There are also some limitations of the current study:
offsets in the flow measurements. Although the results of Vincenti et al. (2) are already encouraging, the exploration of CS-based approaches to imaging and image analysis is an active and rapidly expanding area. Although the researchers used a conventional Cartesian-based sampling of the CMR data, non-Cartesian sampling offers potential advantages. For example, radial sampling patterns (3) reduce the impact of aliasing from structures in the outer parts of the field of view (a problem encountered in the current study). Radial acquisitions have been shown to be inherently well suited for robust CS, and they are also compatible with continuous acquisition approaches (e.g., employing golden-angle schemes) (4). CSbased methods may also enable significant speed-up of flow measurements, which could both reduce the time required and make the extension of such imaging
to
more
fully
3D
volumetric
flow
measurements more practical. Other CS-based CMR approaches also have the potential to substantially reduce the deleterious effects of respiratory motion and arrhythmias on the images, and they have even been shown to enable robust characterization of irregular cardiac and respiratory motion patterns together with improved structural and functional assessments (5).
1. As the researchers acknowledge, the coarse spatial
In summary, the paper of Vincenti et al. (2)
sampling used here would not be adequate for
provides welcome evidence of some of the potential
assessment of the regional anatomy and function
value of CS CMR for improved cardiac function
of the heart and thus would not eliminate the need
assessment, but it is only the barest beginning. In
for acquiring a conventional set of more closely
fact, there are early indications that a more complete
spaced images.
integration of advanced acceleration methods into toward
everyday imaging practice may be in store, in
decreased estimates of end-diastolic volume and
the form of a new paradigm of rapid, continuous
2. There
were
some
systematic
biases
Axel and Sodickson
JACC: CARDIOVASCULAR IMAGING, VOL. 7, NO. 9, 2014 SEPTEMBER 2014:893–5
Editorial Comment
comprehensive imaging. Such an approach would
enabling increasingly rich characterization of both
be both simpler and more efficient than traditional
structure and function in the human heart.
multiplanar CMR protocols, eliminating “dead time” and
REPRINT REQUESTS AND CORRESPONDENCE: Dr.
allowing extraction of multiple dynamic as well as
Daniel K. Sodickson, Department of Radiology, New
tissue
between
separate
specialized
acquisitions
simultaneously. This
York University School of Medicine, 660 First
approach, enabled by key advances such as CS, would
Avenue, Fourth Floor, Room 407, New York, New
revolutionize
York 10016. E-mail: [email protected].
contrast
parameters
cardiac
imaging
workflow
while
REFERENCES 1. Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 2007;58: 1182–95.
3. Peters DC, Ennis DB, McVeigh ER. High-resolution MRI of cardiac function with projection reconstruction and steady-state free precession. Magn Reson Med 2002;48:82–8.
2. Vincenti G, Monney P, Chaptinel J, et al. Compressed sensing single–breath-hold CMR for fast quantification of LV function, volumes, and mass. J Am Coll Cardiol Img 2014;7: 882–92.
4. Feng L, Grimm R, Block KT, et al. Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med 2013 Oct 18 [E-pub ahead of print].
5. Feng L, Axel L, Latson LA, Xu J, Sodickson DK, Otazo R. Compressed sensing with synchronized cardio-respiratory sparsity for free-breathing cine MRI: initial comparative study on patients with arrhythmias. J Cardiovasc Magn Reson 2014;16 Suppl 1:O17.
KEY WORDS cardiac function, fast imaging, fast LV assessment
895
