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Purpose: To evaluate diagnostic image quality of 3D late gadolinium enhancement (LGE) with high isotropic spatial resolution (∼1.4 mm(3) ) images reconstructed from randomly undersampled k-space using LOw-dimensional-structure Self-learning and Thresholding (LOST). Materials and methods: We prospectively enrolled 270 patients (181 men; 55 ± 14 years) referred for myocardial viability assessment. 3D LGE with isotropic spatial resolution of 1.4 ± 0.1 mm(3) was acquired at 1.5T using a LOST acceleration rate of 3 to 5. In a subset of 121 patients, 3D LGE or phase-sensitive LGE were acquired with parallel imaging with an acceleration rate of 2 for comparison. Two readers evaluated image quality using a scale of 1 (poor) to 4 (excellent) and assessed for scar presence. The McNemar test statistic was used to compare the proportion of detected scar between the two sequences. We assessed the association between image quality and characteristics (age, gender, torso dimension, weight, heart rate), using generalized linear models. Results: Overall, LGE detection proportions for 3D LGE with LOST were similar between readers 1 and 2 (16.30% vs. 18.15%). For image quality, readers gave 85.9% and 80.0%, respectively, for images categorized as good or excellent. Overall proportion of scar presence was not statistically different from conventional 3D LGE (28% vs. 33% [P = 0.17] for reader 1 and 26% vs. 31% [P = 0.37] for reader 2). Increasing subject heart rate was associated with lower image quality (estimated slope = -0.009 (P = 0.001)). Conclusion: High-resolution 3D LGE with LOST yields good to excellent image quality in >80% of patients and identifies patients with LV scar at the same rate as conventional 3D LGE. Level of evidence: 2 J. Magn. Reson. Imaging 2017.
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Clinical Performance of High-Resolution
Late Gadolinium Enhancement Imaging
With Compressed Sensing
Tamer A. Basha, PhD,
Mehmet Akc¸akaya, PhD,
Charlene Liew, MD,
Connie W. Tsao, MD,
Francesca N. Delling, MD,
Gifty Addae, BS,
Long Ngo, PhD,
Warren J. Manning, MD,
and Reza Nezafat, PhD
Purpose: To evaluate diagnostic image quality of 3D late gadolinium enhancement (LGE) with high isotropic spatial
resolution (1.4 mm
) images reconstructed from randomly undersampled k-space using LOw-dimensional-structure
Self-learning and Thresholding (LOST).
Materials and Methods: We prospectively enrolled 270 patients (181 men; 55 614 years) referred for myocardial viability
assessment. 3D LGE with isotropic spatial resolution of 1.4 60.1 mm
was acquired at 1.5T using a LOST acceleration rate
of 3 to 5. In a subset of 121 patients, 3D LGE or phase-sensitive LGE were acquired with parallel imaging with an accelera-
tion rate of 2 for comparison. Two readers evaluated image quality using a scale of 1 (poor) to 4 (excellent) and assessed
for scar presence. The McNemar test statistic was used to compare the proportion of detected scar between the two
sequences. We assessed the association between image quality and characteristics (age, gender, torso dimension, weight,
heart rate), using generalized linear models.
Results: Overall, LGE detection proportions for 3D LGE with LOST were similar between readers 1 and 2 (16.30% vs.
18.15%). For image quality, readers gave 85.9% and 80.0%, respectively, for images categorized as good or excellent.
Overall proportion of scar presence was not statistically different from conventional 3D LGE (28% vs. 33% [P50.17] for
reader 1 and 26% vs. 31% [P50.37] for reader 2). Increasing subject heart rate was associated with lower image quality
(estimated slope 5–0.009 (P50.001)).
Conclusion: High-resolution 3D LGE with LOST yields good to excellent image quality in >80% of patients and identifies
patients with LV scar at the same rate as conventional 3D LGE.
Level of Evidence: 2
J. MAGN. RESON. IMAGING 2017;00:000–000.
Myocardial scar and fibrosis can be imaged using late gad-
olinium enhancement (LGE) cardiac magnetic reso-
nance (MR).
LGE has been utilized in identifying ventricular
tachycardia (VT) substrates, and predicting risk of sudden car-
diac death.
Furthermore, the presence and extent of LGE
or heterogeneous left ventricular (LV) scar strongly predicts
adverse cardiac events including appropriate implantable car-
dioverter defibrillator therapy.
However, challenges in LGE
imaging remain. The right ventricle (RV) can also develop
fibrosis, but this is difficult to detect due to limited spatial
resolution and its thin wall. Similarly, LGE enables imaging of
left atrial (LA) scar and fibrosis in patients with atrial fibrilla-
, however, the low spatial resolution of current LGE
imaging sequences makes it challenging to reliably image LA
scar. Therefore, there is an unmet clinical need to further
improve LGE spatial resolution in a clinically feasible scan
LV LGE imaging is commonly performed using 2D
breath-hold imaging with a slice thickness of 8–10 mm.
3D LGE acquisition is an alternative approach,
View this article online at DOI: 10.1002/jmri.25695
Received Mar 28, 2016, Accepted for publication Feb 15, 2017.
This article was published online on 16 March 2017. An error was subsequently identified. This notice is included in the online and print versions to indicate
that both have been corrected 8 April 2017.
*Address reprint requests to: R.N., Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston, MA, 02215. E-mail:
From the
Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA;
Systems and
Biomedical Engineering Department, University of Cairo, Cairo, Egypt;
Department of Electrical and Computer Engineering, University of Minnesota,
Minneapolis, Minnesota, USA;
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA; and
Department of
Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
C2017 International Society for Magnetic Resonance in Medicine 1
enables imaging with higher spatial resolution for better assess-
ment of LV scar heterogeneity, RV, or LA scar. However, 3D
high-resolution LGE requires long scan times, which has limit-
ed its clinical adoption. For example, in a recent study by
Andreu et al,
the reported 3D LGE scan time was 16.4 67.2
minutes for a spatial resolution of 1.4 31.4 31.4 mm
Besides patient comfort, a long scan time also creates additional
artifacts in 3D LGE, such as difficulty in nulling of healthy
myocardium due to temporal changes in contrast agent concen-
tration. Parallel imaging can reduce the scan time; however, the
acceleration rate is often limited to a factor of 2 because of the
LGE low signal-to-noise ratio (SNR). Compressed sensing (CS)
has been previously used to further reduce the 3D LGE scan
The LOw-dimensional-structure Self-learning and
Thresholding (LOST) reconstruction technique has been
shown to enable 3D LGE acceleration rates up to rate 3.
The combination of parallel imaging and LOST has also been
shown to further the accelerate imaging up to rate 6 in coronary
However, CS-based image reconstructions (eg, LOST)
are not yet commercially available. Image reconstruction there-
fore needs to be performed manually offline, which is not ideal
in clinical settings. Furthermore, prior literature assessing
diagnostic image quality of high-resolution 3D LGE with
accelerated data acquisition and CS reconstruction is lacking.
Materials and Methods
All imaging sequences were implemented on a 1.5T Philips Achieva
(Philips Healthcare, Best, The Netherlands) system with a
32-channel cardiac phased-array receiver coil. The research protocol
was approved by our Institutional Review Board and written
informed consent was obtained from all participants in a HIPAA-
compliant manner.
Patient Study
In this prospective study, we recruited patients referred for clinical
cardiac MR exam with LGE assessment. Indications for imaging
included known or suspected coronary disease, nonischemic cardio-
myopathy, or atrial fibrillation. LGE images were acquired 10–20
minutes after a bolus (2 ml/s) infusion of 0.2 mmol/kg of Gd-DTPA
(Magnevist, Bayer Schering Pharma, Berlin, Germany), or 0.1–0.2
mmol/kg of Gd-BOPTA (MultiHance, Bracco, Rome, Italy). All
patients with estimated glomerular filtration rate (eGFR) between
30–60 mL/min/1.73m
received 0.1 mmol/kg of Gd-BOPTA.
A free-breathing electrocardiogram (ECG)-triggered navigator-
gated inversion-recovery gradient echo imaging sequence was used
for all acquisitions. Prior to each scan, a Look-Locker acquisition was
used to select the inversion time to null the LV myocardial signal. To
simplify the clinical protocol, the ECG trigger delay was selected
to be the longest trigger time, thereby accommodating the LGE
sequence acquisition window. For patients with heart rates >80 bpm
(n529), imaging was performed in systole. A respiratory navigator
(2D spiral pencil-beam) placed on the dome of the right hemidiaph-
ragm was used for respiratory motion compensation, utilizing pro-
spective real-time correction. A navigator with fixed scan time was
used to adaptively change the acquisition window throughout the
scan to achieve a fixed navigator efficiency of 60%.
A gradient echo
imaging sequence with the following parameters was used for 3D
LGE: repetition time / echo time (TR/TE) 55.2/2.6 msec, field of
view (FOV) 5320 3320 3100–120 mm
, flip angle 5258. Imag-
ing was performed axially, covering the entire heart. Saturation bands
along the phase-encode direction were used to reduce foldover arti-
facts. A right–left phase-encoding direction was used to reduce respi-
ratory artifacts from the chest wall. The spatial resolution varied from
1.0–1.5 mm
(except for one patient who was imaged with a spatial
resolution of 2 mm
to accommodate for large patient size) with
mean 6standard deviation of 1.4 60.1 mm
In a subset of patients, we also acquired 3D LGE or 3D phase-
sensitive inversion recovery (PSIR) images. These images were
acquired with a uniform undersampling pattern and were recon-
structed on the scanner using Philips SENSE reconstruction imple-
mentation. The ordering of acquisition was randomly changed in
different patients. The typical imaging parameters for 3D LGE were:
spatial resolution 51.5 31.5 33mm
,FOV5320 3320 3100–
120 mm
, flip angle 5258, TR/TE 55.3/2.5 msec, acceleration rate
of 2, and for 3D PSIR LGE: spatial resolution 51.5 31.5 3
,FOV5320 3320 3100–120 mm
, TR/TE 55.7/2.7
msec, flip angle 5158, and acceleration rate of 2. The imaging
parameters for 3D LGE and 3D PSIR LGE were our standard clinical
imaging protocol and were not modified in our study.
LOST Data Acquisition and Reconstruction
3D random undersampling was implemented for the accelerated
A pseudorandom k-space undersampling pattern
was generated by fully sampling a part of the central k-space (corre-
sponding to 15–20% of k
lines and 25% of k
lines), and randomly
discarding the edges. This pattern was stored as a lookup table, and a
profile reordering was performed to sort the selected k
lines based
on their k
and k
location in a radial fashion.
The acceleration rate
was 3 in 150 patients, 4 in 25 patients, 5 in 92 patients, and 6 in
three patients. The acceleration rate was selected by the technologists.
In patients with longer imaging protocols, a higher acceleration rate
was chosen. The total acquisition times were 6:25 minutes for
3-fold accelerated acquisitions and 4 minutes for 5-fold accelerated
acquisitions at a heart rate of 70 bpm. The exact scan time varied
between different subjects to accommodate for changes in imaging
field of view, spatial resolution, and heart rate.
The detailed explanation for the reconstruction algorithm and
parameters has been previously described.
The randomly under-
sampled k-space data are reconstructed using an iterative B
LOST algorithm.
LOST reconstruction uses an initial image esti-
mate to adaptively identify 2D image blocks of similar signal content,
and to generate an adaptive sparse representation for the data. These
blocks are declared to be similar if this distance is less than a prede-
fined fixed threshold. Such similar blocks were then grouped into the
similarity cluster of that voxel. The adaptive sparse representation was
generated by applying a 3D fast Fourier transform (FFT) to each
similarity cluster. Dealiasing of the data was performed via shrinkage
of the 3D FFT coefficients of the similarity clusters. The iterative
-weighted reconstruction approach uses the coil sensitivity infor-
mation for data consistency during the reconstruction. For faster
implementation, coil compression
is applied to these 3D coil
sensitivity maps to compress the 32-channel coil data to 10 “virtual”
Journal of Magnetic Resonance Imaging
2 Volume 00, No. 00
channels. The coil compression was performed only once, prior
to the iterative portion of the algorithm. At every iteration of the
-weighted LOST algorithm: 1) the current combined-coil image
estimate is thresholded using LOST; 2) individual coil images are
generated by the voxel-wise multiplication of the coil sensitivity map
of that coil and the combined image; 3) data consistency is enforced
by replacing the acquired k-space locations with the acquired lines for
each of these individual coil images; and 4) a new combined-coil
image estimate is generated by summing the voxelwise product of the
data-consistent coil images and the complex conjugate of the coil
sensitivity maps across the coil dimension. LOST reconstruction was
implemented in MatLab (MathWorks, Natick, MA), with the
adaptive learning and nonlinear shrinkage portions implemented in
C11. The same reconstruction parameters were used in all cases and
acceleration rates, allowing for fully automated reconstructions.
Automated Reconstruction Framework
A software platform was developed to automate the communica-
tion and data transfer between the scanner and the remote process-
ing units. Figure 1 shows a schematic diagram of these connections
illustrating the sequence of the program workflow. After a scan was
completed, the operator used the program to request the recon-
struction of the scanned data, which initiates the following fully
automated workflow: 1) the program inquires the scanner database
for the scan information including the raw data and the imaging
parameters; 2) the database returns the desired information; 3) raw
data are packaged along with the imaging parameters and recon-
struction options, and are then sent to a remote processing unit for
image reconstruction; 4) during the processing, the program peri-
odically connects with the remote processing unit and updates the
progress of the operation; and 5) upon reconstruction completion,
the reconstructed images are automatically pulled from the remote
processing unit, packaged into a Digital Imaging and Communica-
tions in Medicine (DICOM) format, and then pushed to the scan-
ner database, from where it can also be sent to the hospital Picture
Archiving and Communication System (PACS). In this workflow,
multiple datasets can be sent at the same time or sequentially. All
workflow processes are implemented such that they are performed
in the background and do not block operator interaction with the
scanner console. Before sending the data, the software generates
and attaches a random unique identifier (UID) for the specific
data, and then uses this UID to inquire about progress, retrieve
the results when ready, and push them into the scanner database
with the proper patient and series information to comply
with HIPAA, especially if the remote system is located outside the
imaging facility or using an available web-based cloud computational
system. The operator can choose to have the remote processing occur
on the scanner machine or at a different remote station on the net-
work, or even on a CPU cluster or GPU server on the same network.
In our implementation, a CPU cluster was used for performing the
reconstruction. Once the reconstructed images are available in the
scanner database or in the PACS, they can be viewed and stored
similar to images reconstructed by the vendor reconstruction system.
The software program was developed in MatLab.
Image Analysis
LOST reconstructed 3D LGE images were written into DICOM
format and were used for subjective assessment. In patients with
available clinical 3D LGE or PSIR images, reconstructed images
from the scanner vendor software were available and were used for
assessment. Subjective qualitative assessment was performed by two
independent readers (each with 10 years of experience in interpreting
clinical cardiac MR exams, C.T., F.D.), blinded to patient history.
These readers were not aware of the specifics of the reconstructions;
however, because of variations in contrast and resolution, they could
differentiate between LOST reconstructed images vs. conventional
SENSE reconstruction. To minimize this impact, image assessment
for LOST and SENSE reconstruction were performed in two separate
sessions. Readers reviewed each dataset in Osirix (Pixmeo SARL,
Geneva, Switzerland) and were free to adjust the window leveling.
Both original and multiplanar reformatted images were used for
subjective assessment.
For each dataset, the presence of LGE was assessed using a three-
point scale (absent with confidence 50, present with confidence 51,
unable to interpret/inconclusive 52). Furthermore, each dataset was
qualitatively assessed using a four-point ordinal system based on overall
image quality to assess for viability/scar: 1, poor (large artifacts/no con-
fidence in interpreting LGE in >50% of the myocardium); 2, fair
(moderate artifacts/LGE interpretable in 50–70% of the myocardium);
3, good (small artifacts/LGE interpretable in 75–90% of the
myocardium); 4, excellent (no artifacts/LGE interpretable in >90% of
the myocardium).
To assess the potential impact of various patient characteristics on
image quality, we extracted the following parameters for each patient:
age,gender,heartrate,weight,torso dimension (ie, posteroanterior
[back to chest wall] and transverse [right to left]).
Statistical Analysis
We first analyzed data for all subjects with 3D LGE with LOST.
The proportion of the detected LGE presence (“Present with Con-
fidence”) was reported for each reader, as well as the agreement
kappa statistic and 95% confidence interval (CI). Stratification by
acceleration rate was carried out to yield these estimates within
each rate stratum (acceleration rate 3, 4, and 5). We performed
similar analysis for image quality by grouping “good” and
“excellent” image quality in one category and estimating the pro-
portion of “good or excellent” for overall image quality and by
stratification of rate. The kappa statistic was computed. Second, we
analyzed data for the sample of 121 subjects with data from both
sequences (3D LGE with LOST, and conventional 3D LGE). We
FIGURE 1: Integration of the automated reconstruction frame-
work into the clinical workflow: (1) the scanner database is que-
ried for scan raw data and imaging parameters, (2) the
database returns the requested information, (3) raw data are
packed and sent to the Central Processing Unit (CPU) cluster
for LOST reconstruction, (4) progress and results are updated
upon request from the operator, (5) reconstructed images are
pushed to the scanner database, from where they can also be
sent to the hospital PACS.
Basha et al.: High-Resolution LGE With Compressed Sensing
Month 2017 3
also reported the same statistics as in the sample of 270 subjects.
Additionally, we compared the “Present with Confidence” of LGE
between the two sequences using the McNemar test statistic to
account for dependency in the sample (since subjects in this group
were imaged with both sequences). We used SAS software v. 9.4
(Cary, NC) for data management and statistical analysis.
We recruited 270 patients (181 men; 54.9 614.1 years)
who were imaged using high-resolution 3D LGE with
LOST. We also acquired 3D LGE or 3D PSIR images in a
subset of 121 patients. The reconstruction framework
allowed successful automation of image reconstruction in all
cases without the need for any interaction with research sci-
entists on the investigator’s team. Figure 2 shows an example
of 3D LGE with high isotropic resolution, as well as 3D
PSIR LGE image acquired in a 65-year-old-man with a his-
tory of coronary artery disease and ventricular tachycardia.
Improved spatial resolution allows better depiction of
complex scar geometry in the patient. In high-resolution
images, several additional small focal enhancements can be
seen that were not seen in 3D PSIR images due to limited
FIGURE 2: Reformatted 3D LGE images (3D high-resolution LGE with isotropic spatial resolution with LOST rate 5 and 3D PSIR
LGE with nonisotropic spatial resolution) in a 65-year-old man with coronary artery disease, symptomatic nonsustained ventricular
tachycardia, and presyncope referred for evaluation of LV scar. Subendocardial LGE in the left anterior descending coronary distri-
bution can be seen in all images. Additionally, smaller scar in remote areas is visible at different slice locations with significantly
better depiction of scar in 3D high-resolution LGE with isotropic spatial resolution. Smaller areas of scar are not visible in 3D PSIR
LGE with nonisotropic spatial resolution.
FIGURE 3: Reformatted 3D LGE of a 67-year-old man with hypertrophic cardiomyopathy. Focal hypertrophy of the mid inferior
left ventricular septum. High-resolution 3D high-resolution LGE images acquired with LOST rate 3 demonstrate a more detailed
depiction of scar compared with 3D PSIR LGE.
Journal of Magnetic Resonance Imaging
4 Volume 00, No. 00
spatial resolution. The isotropic spatial resolution also allows
reformatting in any desired orientation (as shown) with
identical image quality as the original axial images. Because
of nonisotopic spatial resolution of PSIR LGE, there is
additional partial voluming and lower image quality in
reformatted images. Viability images from a patient with
hypertrophic cardiomyopathy (HCM) are shown in Fig. 3.
The isotropic spatial resolution of accelerated 3D LGE
shows the complex nature of the scar in this patient includ-
ing papillary muscle. While hyperenhancement can be
assessed with 3D PSIR LGE, the visualization of complex
scar and scar patchiness are better seen with high-resolution
3D LGE with isotropic spatial resolution. Figure 4 shows
viability images in a 62-year-old male patient with sarcoido-
sis and LV aneurysms. Higher spatial resolution images
improve detection of hyperenhancement region, as well as
confirm the involvement of the RV.
Table 1 shows the proportions of “Present with Con-
fidence” for the presence of detected LGE in 3D LGE with
LOST; 16.30% and 18.15% for readers 1 and 2, respectively.
These proportions agree well with a kappa statistic of 0.78
(95% CI: 0.68–0.88). These proportions are also similar
when the sample was stratified by acceleration rate (3–5). For
acceleration rate 4, the sample size is small, and compared to
rates 3 and 5, the proportions are smaller. Similar analysis was
carried out for image quality. The proportion of “Good or
Excellent” is high, 85.93% for reader 1, and 80.00% for read-
er 2, with a fair kappa statistic of 0.43 (95% CI 0.22–0.57).
Reader 1 scored 4, 34, 88, and 144 as poor, fair, good, and
excellent, respectively, while reader 2 scored 7, 47, 135, and
81 as poor, fair, good, and excellent, respectively. Stratification
by rate also yielded similar proportions.
Table 2 shows the analysis for the 121 subjects with
data for both 3D LGE with LOST, and conventional 3D
LGE. For reader 1, the overall proportion of “Present with
Confidence” is 28.93% for 3D LGE with LOST, and is not
statistically different from 33.88% for conventional 3D
LGE (P50.157, McNemar test). We stratified this sample
FIGURE 4: Viability images from a 62-year-old man with cardiac sarcoidosis, comparing high-resolution 3D LGE with 1.2 mm
resolution with LOST rate 4 with 3D PSIR LGE with nonisotropic resolution. 3D high-resolution LGE significantly improves visualization
of scar and shows involvement of the RV free wall as well as signal enhancement in the RV papillary muscles and apical LV aneurysm.
Basha et al.: High-Resolution LGE With Compressed Sensing
Month 2017 5
by acceleration rate 3, 4, 5, and found no significant statisti-
cal difference between the two proportions. Numerically,
3D LGE with LOST estimates are slightly less than those of
the conventional 3D LGE overall, and within each stratum
of acceleration rate. The agreement between the two readers
via kappa statistic is high at 0.90 (95% CI: 0.81–0.99) for
“Present with Confidence” for LGE detection. Conventional
3D LGE also yields a high kappa of 0.87 (95% CI: 0.77–
0.96). For image quality, “Good or Excellent” is 85.95% for
reader 1 for 3D LGE with LOST, and 84.30% for conven-
tional 3D LGE (P50.637). For reader 2, there is also no
statistical difference between the two approaches (78.51%
vs. 85.95%, P50.083). The agreement is fair with kappa
of 0.36 (95% CI: 0.15–0.56) for 3D LGE with LOST. For
conventional 3D LGE, the kappa is high 0.80 (95% CI:
The baseline characteristics of the study population
and torso size measurements are shown in Table 3. Increas-
ing subject heart rate, weight, and torso dimension are asso-
ciated negatively with subjective image quality (Table 4),
but only heart rate reached statistical significance.
We developed and implemented a clinically feasible image
reconstruction framework for accelerated data acquisition
and reconstruction using the LOST technique. The image
quality of 3D LOST-accelerated LGE was evaluated in 270
patients with known or suspected cardiovascular disease
referred for clinical viability assessment. We demonstrated
that using this approach, 3D LGE with high isotropic spa-
tial resolution is clinically feasible with acceptable image
quality in most patients.
Despite the growth in development of CS-based image
reconstruction techniques, there have been very limited
efforts in clinical translation and evaluation.
et al
evaluated CS-based reconstruction for routine neuro-
imaging sequences and found that CS was able to moderate-
ly accelerate certain neuroimaging sequences without severe
loss of clinically relevant information. For those sequences
with coarser spatial resolution and/or at a higher accelera-
tion factor, artifacts degraded the quality of the recon-
structed image to the point where they are of minimal
or no clinical value. Vasanawala et al
showed the feasibility
TABLE 1. Subjective Assessment of 3D LGE With LOST Reconstruction (N 5270) for Two Readers and Inter-
reader Agreement for Images Acquired via Different Acceleration Rates
Hyperenhancement on LGE
Present with
for all rates
Present with
for rate 53
Present with
confidence for
rate 54
Present with
for rate 55
Reader 1 3D LGE with LOST 16.30% 15.33% 8.00% 20.65%
Reader 2 - 3D LGE with LOST 18.15% 16.00% 12.00% 22.83%
Image quality
Good or
excellent for
all rates
Good or
excellent for
rate 53
Good or
excellent for
rate 54
Good or
excellent for
rate 55
Reader 1 - 3D LGE with LOST 85.93% 88.00% 96.00% 79.35%
Reader 2 - 3D LGE with LOST 80.00% 79.33% 96.00% 76.09%
Interreader agreement
Kappa 95% Confidence
3D LGE with LOST Score 0.78 0.68-0.88
3D LGE with LOST Image Quality 0.43 0.29-0.57
Journal of Magnetic Resonance Imaging
6 Volume 00, No. 00
of improved pediatric imaging to achieve higher resolution
and/or faster imaging in 34 patients in a clinical setting. Hsiao
et al
assessed the potential of CS in 4D phase-contrast MRI
for the evaluation of valvular insufficiency and intracardiac
shunts in 34 patients with congenital heart disease and
demonstrated that the CS 4D phase-contrast sequence can
TABLE 2. Subjective Assessment of the Subset of Patients With Both 3D LGE With LOST Reconstruction and
Conventional 3D LGE (N5121) for Two Readers and Interreader Agreement for Images Acquired via Different
Acceleration Rates (3 to 5)
Hyperenhancement on LGE
Present with
for all rates
Present with
for rate 53
Present with
for rate 54
Present with
for rate 55
Reader 1 - 3D LGE with LOST 28.93% 33.33% 7.69% 30.00%
Reader 1 - Conventional 3D LGE 33.88% 35.42% 30.77% 33.33%
P-value Comparison of LOST and
Conventional LGE for Reader 1
0.157 0.739 0.083 0.414
Reader 2 - 3D LGE with LOST 26.45% 29.17% 7.69% 28.33%
Reader 2 - Conventional 3D LGE 31.40% 35.42% 23.08% 30.00%
P-value Comparison of LOST and
Conventional LGE for Reader 2
0.134 0.317 0.157 0.655
Image quality
Good or
Excellent for
All Rates
Good or
Excellent for
Rate 53
Good or
Excellent for
Rate 54
Good or
Excellent for
Rate 55
Reader 1 - 3D LGE with LOST 85.95% 85.42% 100.00% 83.33%
Reader 1 - Conventional 3D LGE 84.30% 85.42% 100.00% 80.00%
P-value Comparison of LOST and
Conventional Image Quality for Reader 1
0.637 1.000 1.000 0.564
Reader 2 - 3D LGE with LOST 78.51% 75.00% 92.71% 78.33%
Reader 2 - Conventional 3D LGE 85.95% 87.50% 100.00% 81.67%
P-value Comparison of LOST and
Conventional Image Quality for Reader 2
0.083 0.109 1.000 0.564
Interreader agreement
95% Confidence
3D LGE with LOST Score 0.90 0.81-0.99
Conventional 3D LGE Score 0.87 0.77-0.96
3D LGE with LOST Image Quality 0.36 0.15-0.56
Conventional 3D LGE Image Quality 0.80 0.65-0.96
McNemar test.
Kappa based on 2 by 2 table present with confidence versus otherwise, good or excellent.
Basha et al.: High-Resolution LGE With Compressed Sensing
Month 2017 7
augment conventional cardiac MR imaging by improving sen-
sitivity for and depiction of hemodynamically significant
shunts and valvular regurgitation. Roujol et al evaluated the
performance of CS-accelerated ECG gated pulmonary vein
MRA in 19 patients with atrial fibrillation.
Mann et al
assessed the utility of CS in quantification of the fat fraction
in 11 patients with type 2 diabetes and concluded that accept-
able image quality can be achieved with acceleration up to a
factor of 3.8.
These exploratory studies demonstrated the
potential and clinical feasibility of the CS-based approach for
accelerated imaging; however, evaluations were only per-
formed in a small and selected number of patients (ie, between
Despite excellent image quality, the long reconstruc-
tion time remains one of the main limitations of this tech-
nique, with a typical reconstruction time of 1 hour for
high-resolution 3D LGE. In our implementation, a 3D vol-
ume reconstructed by zero filling of the undersampled data
will be available immediately after imaging. Because of the
fully sampled center of k-space, we found these images to
be helpful in predicting the image quality of the CS recon-
structed images, and often scar can be seen in these images.
While this workflow does not work on cases where immedi-
ate access to reconstructed data is needed (eg, real-time
MRI), immediate reconstruction is not necessary in our spe-
cific application of 3D LGE. In our clinical practice, images
from each patient are typically evaluated the next day,
allowing sufficient time for image reconstruction for clinical
evaluation. Further research to reduce the reconstruction
time and development of alternative reconstruction techniques
is warranted.
Our study only evaluated the image quality of
isotropic 3D LGE with high resolution in our tertiary care
medical center’s referral population. The clinical impact of
high spatial resolution imaging for different diseases should
be carefully assessed in future studies. Not all patients
may need imaging with high spatial resolution; however, for
some cardiovascular diseases this may be clinically war-
ranted. For example, a higher spatial resolution may allow
better visualization of the LV scar morphology, which may
facilitate assessment for ventricular arrhythmia. In addition,
a volumetric isotropic 3D LGE allows for image reconstruc-
tion in any orientation and multiplanar visualization of the
data, which further improves confidence in detection of scar
by confirming the scar in different views. Further studies are
needed to establish the clinical impact of high-resolution
isotropic 3D LGE. We also found that there were differ-
ences in scoring between the two readers for the LOST
accelerated imaging dataset. While the proportion of good
to excellent quality was similar between the two readers, one
of our reader’s scores were more positive and a majority of
images were scored as excellent.
Image reconstruction for CS is commonly performed
offline, which has hindered evaluation of its various recon-
struction algorithms in a clinical environment. Other stand-
alone reconstruction frameworks have been described. A flexi-
ble real-time MRI reconstruction platform (ie, RTHawks) has
been widely applied in real-time MRI.
A real-time display
and reconstruction system was also developed at the National
Institutes of Health and is widely used for interventional pro-
Recently, a flexible stand-alone MRI image recon-
struction framework
has been developed that provides
additional flexibility for reconstruction and use of cloud com-
puting to facilitate image reconstruction. These reconstruction
platforms are designed mainly for situations where real-time
or immediate reconstruction of MRI data is needed, such as
image guidance or real-time imaging.
Our study has several limitations. We did not perform a
direct comparison between 3D and 2D LGE imaging, where
the latter is the current clinical standard at many medical cen-
ters. Currently, all patients imaged for LV viability at our
TABLE 3. Baseline Characteristics of the Study Popu-
lation (N5270)
Baseline patient characteristics N5270
Age years (range) 55 (18-85)
Male subjects 181 (66.7%)
Heart rate (/min) 66 613
Weight (kg) 83 615
Chest posteroanterior
dimension (cm)
23.1 63.4
Chest transverse
dimension (cm)
35.3 63.6
TABLE 4. Relationship Between Subjective Average
Qualitative Image Assessment Scores and Patient
Patient Factors Change in mean of
average image score
per unit change in
patient factor
Heart rate -0.009 (0.003) 0.001
Weight -0.003 (0.003) 0.323
Chest AP
-0.012 (0.015) 0.421
Chest transverse
-0.027 (0.015) 0.064
Slope estimate and standard error from multivariable generalized
linear model.
Journal of Magnetic Resonance Imaging
8 Volume 00, No. 00
medical center are imaged using 3D LGE. The spatial resolu-
tion varied between different patients to accommodate patient
size and heart rate. Due to the inherent denoising in CS, we
cannot directly perform SNR or CNR measurements. We
used fixed image reconstruction parameters for all studies and
did not optimize the parameters based on acceleration rate.
In conclusion, 3D LGE with LOST yields good to
excellent image quality in >80% of patients and identifies
patients with LV scar at the same rate as conventional 3D
LGE. High isotropic spatial resolution (1–1.4 mm
) detects
smaller scar and enables multiplanar reconstruction of 3D
LGE to facilitate scar visualization.
Contract grant sponsor: National Institutes of Health (NIH);
contract grant numbers: R01EB008743, R01HL129185-01,
R01HL127015, R21HL127650, NIH K99HL111410 and
R00HL111410 (to M.A.); Contract grant sponsor: American
Heart Association (AHA); contract grant number:
We thank Sophie Berg, Kraig V. Kissinger, and Beth Goddu
for patient recruitment and scanning.
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Journal of Magnetic Resonance Imaging
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... In cardiovascular magnetic resonance (CMR) imaging, static cardiac imaging techniques, such as late gadolinium enhancement (LGE) (Kellman and Arai, 2012;Kellman et al., 2002;Akçakaya et al., 2012;Basha et al., 2017), mapping (Kellman and Hansen, 2014;Messroghli et al., 2017;Aherne et al., 2020), or three-dimensional (3-D) whole heart coronary angiography (Munoz et al., 2020;Greil et al., 2017;Cruz et al., 2017;Forman et al., 2014) are increasingly being performed to qualitatively and quantitatively assess the cardiac anatomy and function. It is important to acquire the data during the phase of the cardiac cycle with least motion, called a resting phase (RP), especially mid-or end-diastolic (ED) phases (Kramer et al., 2020;Isma'eel et al., 2009;Kramer et al., 2013), or in patients with a fast heart rate during the end-systolic (ES) phase. ...
Static cardiac imaging such as late gadolinium enhancement, mapping, or 3-D coronary angiography require prior information, e.g., the phase during a cardiac cycle with least motion, called resting phase (RP). The purpose of this work is to propose a fully automated framework that allows the detection of the right coronary artery (RCA) RP within CINE series. The proposed prototype system consists of three main steps. First, the localization of the regions of interest (ROI) is performed. Second, the cropped ROI series are taken for tracking motions over all time points. Third, the output motion values are used to classify RPs. In this work, we focused on the detection of the area with the outer edge of the cross-section of the RCA as our target. The proposed framework was evaluated on 102 clinically acquired dataset at 1.5T and 3T. The automatically classified RPs were compared with the reference RPs annotated manually by a expert for testing the robustness and feasibility of the framework. The predicted RCA RPs showed high agreement with the experts annotated RPs with 92.7% accuracy, 90.5% sensitivity and 95.0% specificity for the unseen study dataset. The mean absolute difference of the start and end RP was 13.6 ± 18.6 ms for the validation study dataset (n=102). In this work, automated RP detection has been introduced by the proposed framework and demonstrated feasibility, robustness, and applicability for static imaging acquisitions.
... Real-time imaging has the potential to reduce respiratory motion artifacts by acquiring data of each cardiac phase in a single shot, enables shorter breath-hold times or fully free-breathing imaging, but sacrifices spatiotemporal resolution. Compressed sensing is an emergent technique playing a pivotal role in CMR acquisition acceleration comprehensively, covering cine imaging (10,11), late gadolinium enhancement imaging (12,13), and magnetic resonance (MR) angiography (14,15). Recently, real-time cine imaging with compressed sensing (RTCSCine) was used to acquire cine images during free breathing. ...
Full-text available
Background: Free-breathing cardiac cine magnetic resonance imaging (MRI) comparable to the traditional breath-hold 2D segmented cine imaging (SegBH) is clinically required for cardiac function and strain analysis. This study is to assess the feasibility and accuracy of a free-breathing cardiac cine technique (RTCSCineMoCo) combined with highly accelerated real-time acquisition, compressed sensing, and fully automated non-rigid motion correction for left ventricular (LV) function and strain analysis, using SegBH as the reference and comparing with free-breathing single-shot real-time compressed sensing cine imaging (RTCSCine) without motion correction. Methods: A total of 67 patients scheduled for clinical cardiac MRI were included. Cine images were acquired using three techniques (SegBH, RTCSCineMoCo, RTCSCine) consecutively at 3.0 T. LV functional parameters, including ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), stroke volumes (SV), and LV mass (LVM) were measured and compared. Strain parameters including global radial (GRS), circumferential (GCS), and longitudinal (GLS) strain as well as corresponding time to peak strain (TPS) were computed by magnetic resonance (MR) feature tracking and compared. Subgroup analyses were performed according to heart rate (HR), left ventricular ejection fraction (LVEF), and etiology. Results: All quantitative parameters of LV function and strain measured by RTCSCineMoCo (r≥0.766) and RTCSCine (r≥0.712) showed strong correlations with SegBH (all P<0.001). LV functional parameters were not statistically different between RTCSCineMoCo and SegBH (all P>0.05), but an overestimation of LV end-systolic volume (LVESV) and underestimation of LVEF and LVM were observed using RTCSCine (all P<0.001). GRS, GCS, and GLS by RTCSCineMoCo and RTCSCine were significantly different than those by SegBH (all P<0.05). All TPS values by RTCSCineMoCo showed no significant differences (all P>0.05) compared with SegBH, but TPS in longitudinal directions (TPSL) by RTCSCine was significantly different (P=0.011). There were no significant differences for GRS or GCS between RTCSCineMoCo and SegBH in patients with HR <70 bpm or LVEF <50%. GRS by RTCSCineMoCo showed similar results compared to SegBH in patients with pulmonary hypertension. Conclusions: RTCSCineMoCo is a promising method for robust free-breathing cardiac cine imaging, yielding more precise quantitative analytic results for LV function compared with RTCSCine. RTCSCineMoCo mildly underestimated GRS, GCS, and GLS, but showed smaller bias compared to RTCSCine in LV strain analysis.
... 3D LGE can now achieve isotropic resolution of 1.3-1.4 mm from ∼7 min scans (45)(46)(47), while 3D T1-and T2-mapping techniques with 1.5-1.6 mm isotropic resolution from ∼10 min scans have been recently demonstrated (48-50). These approaches are promising for the detection of smaller patchy lesions which might be present in CS. ...
Full-text available
The diagnosis of cardiac sarcoidosis (CS) remains challenging. While only a small fraction of patients with systemic sarcoidosis present with clinically symptomatic CS, cardiac involvement has been associated with adverse outcomes, such as ventricular arrhythmia, heart block, heart failure and sudden cardiac death. Despite the clinical relevance of having an early and accurate diagnosis of CS, there is no gold-standard technique available for the assessment of CS. Non-invasive PET and MR imaging have shown promise in the detection of different histopathological features of CS. More recently, the introduction of hybrid PET-MR scanners has enabled the acquisition of these hallmarks in a single scan, demonstrating higher sensitivity and specificity for CS detection and risk stratification than with either imaging modality alone. This article describes recent developments in hybrid PET-MR imaging for improving the diagnosis of CS and discusses areas of future development that could make cardiac PET-MRI the preferred diagnostic tool for the comprehensive assessment of CS.
... To successfully reconstruct an image, CS requires the image to be sparse in some domain (e.g., wavelet, finite difference, etc.) and the undersampling artifacts to be incoherent in the sparse domain (Figure 4) (45). CS has enabled many applications, including removing the need for patient breathholding in 2D (46) or 3D cine imaging (47), accelerating parametric mapping acquisitions (48), acquiring 3D LGE images (49,50), acquiring 3D MR angiography images (51)(52)(53)(54)(55), or acquiring higher dimensional CMR images such as 5D cardiac images (x, y, z spatial dimensions + respiratory motion + cardiac motion) (30,(56)(57)(58)(59)(60). CS has also recently been cleared by the United States Food and Drug Administration (FDA), allowing it to be used and tested in larger clinical settings (61)(62)(63). ...
Full-text available
Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging’s (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple “features” such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.
... )[28][29][30]. ...
Full-text available
Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.
Full-text available
Aim The purpose of this study was to investigate the clinical application of Compressed SENSE accelerated single-breath-hold LGE with 3D isotropic resolution compared to conventional LGE imaging acquired in multiple breath-holds. Material & Methods This was a retrospective, single-center study including 105 examinations of 101 patients (48.2 ± 16.8 years, 47 females). All patients underwent conventional breath-hold and 3D single-breath-hold (0.96 × 0.96 × 1.1 mm ³ reconstructed voxel size, Compressed SENSE factor 6.5) LGE sequences at 1.5 T in clinical routine for the evaluation of ischemic or non-ischemic cardiomyopathies. Two radiologists independently evaluated the left ventricle (LV) for the presence of hyperenhancing lesions in each sequence, including localization and transmural extent, while assessing their scar edge sharpness (SES). Confidence of LGE assessment, image quality (IQ), and artifacts were also rated. The impact of LV ejection fraction (LVEF), heart rate, body mass index (BMI), and gender as possible confounders on IQ, artifacts, and confidence of LGE assessment was evaluated employing ordinal logistic regression analysis. Results Using 3D single-breath-hold LGE readers detected more hyperenhancing lesions compared to conventional breath-hold LGE ( n = 246 vs. n = 216 of 1,785 analyzed segments, 13.8% vs. 12.1%; p < 0.0001), pronounced at subendocardial, midmyocardial, and subepicardial localizations and for 1%–50% of transmural extent. SES was rated superior in 3D single-breath-hold LGE (4.1 ± 0.8 vs. 3.3 ± 0.8; p < 0.001). 3D single-breath-hold LGE yielded more artifacts (3.8 ± 1.0 vs. 4.0 ± 3.8; p = 0.002) whereas IQ (4.1 ± 1.0 vs. 4.2 ± 0.9; p = 0.122) and confidence of LGE assessment (4.3 ± 0.9 vs. 4.3 ± 0.8; p = 0.374) were comparable between both techniques. Female gender negatively influenced artifacts in 3D single-breath-hold LGE ( p = 0.0028) while increased heart rate led to decreased IQ in conventional breath-hold LGE ( p = 0.0029). Conclusions In clinical routine, Compressed SENSE accelerated 3D single-breath-hold LGE yields image quality and confidence of LGE assessment comparable to conventional breath-hold LGE while providing improved delineation of smaller LGE lesions with superior scar edge sharpness. Given the fast acquisition of 3D single-breath-hold LGE, the technique holds potential to drastically reduce the examination time of CMR.
Myocardial inflammation occurs following activation of the cardiac immune system, producing characteristic changes in the myocardial tissue. Cardiovascular magnetic resonance is the non-invasive imaging gold standard for myocardial tissue characterization, and is able to detect image signal changes that may occur resulting from inflammation, including edema, hyperemia, capillary leak, necrosis, and fibrosis. Conventional cardiovascular magnetic resonance for the detection of myocardial inflammation and its sequela include T2-weighted imaging, parametric T1- and T2-mapping, and gadolinium-based contrast-enhanced imaging. Emerging techniques seek to image several parameters simultaneously for myocardial tissue characterization, and to depict subtle immune-mediated changes, such as immune cell activity in the myocardium and cardiac cell metabolism. This review article outlines the underlying principles of current and emerging cardiovascular magnetic resonance methods for imaging myocardial inflammation.
The introduction of compressed sensing to increase imaging speed has been a major innovation in the field of MRI. Compressed sensing enables reconstructing MR images from undersampled data by exploiting image sparsity, and the power of sparsity-enforcing reconstruction has been demonstrated in various applications with a substantial clinical impact. This chapter presents an overview of compressed sensing and its application in rapid MRI. The compressed sensing theory will first be briefly reviewed. The conditions required for successful implementation of compressed sensing and how these requirements can be implemented in MRI are discussed. This chapter also covers combinations of compressed sensing with parallel imaging, which can form a synergistic reconstruction framework to exploit joint multicoil sparsity for further improved image quality. The clinical applications of compressed sensing in MRI are then summarized. Finally, existing challenges of compressed sensing MRI and potential solutions are discussed.
Magnetic resonance imaging (MRI) is a versatile modality that can generate high‐resolution images with a variety of tissue contrasts. However, MRI is a slow technique and requires long acquisition times, which increase with higher temporal and spatial resolution and/or when multiple contrasts and large volumetric coverage is required. In order to speedup MR data acquisition, several approaches have been introduced in the literature. Most of these techniques acquire less data than required and exploit intrinsic redundancies in the MR images to recover the information that was not sampled. This article presents a review of MR acquisition and reconstruction methods that have exploited redundancies in the temporal, spatial, and contrast/parametric dimensions to accelerate image data acquisition, focusing on cardiac and abdominal MR imaging applications. The review describes how each of these dimensions has been separately exploited for speeding up MR acquisition to then discuss more advanced techniques where multiple dimensions are exploited together for further reducing scan times. Finally, future directions for multidimensional image acceleration and remaining technical challenges are discussed. Evidence Level 5 Technical Efficacy 1
Purpose Clinical guidelines recommend the use of bright-blood late gadolinium enhancement (BR-LGE) for the detection and quantification of regional myocardial fibrosis and scar. This technique, however, may suffer from poor contrast at the blood-scar interface, particularly in patients with subendocardial myocardial infarction. The purpose of this study was to assess the clinical performance of a two-dimensional black-blood LGE (BL-LGE) sequence, which combines free-breathing T1-rho-prepared single-shot acquisitions with an advanced non-rigid motion-compensated patch-based reconstruction. Materials and methods Extended phase graph simulations and phantom experiments were performed to investigate the performance of the motion-correction algorithm and to assess the black-blood properties of the proposed sequence. Fifty-one patients (37 men, 14 women; mean age, 55 ± 15 [SD] years; age range: 19–81 years) with known or suspected cardiac disease prospectively underwent free-breathing T1-rho-prepared BL-LGE imaging with inline non-rigid motion-compensated patch-based reconstruction at 1.5T. Conventional breath-held BR-LGE images were acquired for comparison purposes. Acquisition times were recorded. Two readers graded the image quality and relative contrasts were calculated. Presence, location, and extent of LGE were evaluated. Results BL-LGE images were acquired with full ventricular coverage in 115 ± 25 (SD) sec (range: 64–160 sec). Image quality was significantly higher on free-breathing BL-LGE imaging than on its breath-held BR-LGE counterpart (3.6 ± 0.7 [SD] [range: 2–4] vs. 3.9 ± 0.2 [SD] [range: 3–4]) (P <0.01) and was graded as diagnostic for 44/51 (86%) patients. The mean scar-to-myocardium and scar-to-blood relative contrasts were significantly higher on BL-LGE images (P < 0.01 for both). The extent of LGE was larger on BL-LGE (median, 5 segments [IQR: 2, 7 segments] vs. median, 4 segments [IQR: 1, 6 segments]) (P < 0.01), the method being particularly sensitive in segments with LGE involving the subendocardium or papillary muscles. In eight patients (16%), BL-LGE could ascertain or rule out a diagnosis otherwise inconclusive on BR-LGE. Conclusion Free-breathing T1-rho-prepared BL-LGE imaging with inline motion compensated reconstruction offers a promising diagnostic technology for the non-invasive assessment of myocardial injuries.
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Purpose: To determine the limits of agreement of hepatic fat fraction and R2* relaxation rate quantified with accelerated magnetic resonance (MR) imaging reconstructed with combined compressed sensing and parallel imaging compared with conventional fully sampled acquisitions. Materials and methods: Eleven subjects with type 2 diabetes and a healthy control subject were recruited with the approval of the Newcastle and North Tyneside 2 ethics committee and written consent. Undersampled data at ratios of 2.6×, 2.9×, 3.8×, and 4.8× were prospectively acquired in addition to fully sampled data by using five gradient echoes per repetition time at 3.0 T. Fat fraction maps were calculated by using combined compressed sensing and parallel imaging (CS-PI) reconstruction and Bland-Altman analysis performed to assess bias and 95% limits of agreement. Inter- and intrarater analysis was performed for quantitative fat fraction and R2* relaxation rate, and image quality was assessed with a four-point scale by two independent observers. Results: The fat fractions from the accelerated acquisitions had 95% limits of agreement of 1.2%, 1.2%, 1.1%, and 1.5%, respectively, with no bias. When compared with the intra- and interrater 95% limits of agreement (0.7% and 0.8%), acceleration of up to 3.8× did not greatly degrade the fat fraction measurements. No or minimal artifact was detected at 2.6× and 2.9× accelerations, moderate artifact was detected at 3.8× acceleration, and substantial artifact was detected at 4.8× acceleration. Conclusion: Prospective undersampling and CS-PI reconstruction of liver fat fractions can be used to accelerate liver fat fraction measurements. The fat fractions and image quality produced were acceptable up to a factor of 3.8×, thereby shortening the required breath-hold duration from 17.7 seconds to 4.7 seconds.
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Non-invasive depiction of conducting channels (CCs) is gaining interest for its usefulness in ventricular tachycardia (VT) ablation. The best imaging approach has not been determined. We compared characterization of myocardial scar with late-gadolinium enhancement cardiac magnetic resonance using a navigator-gated 3D sequence (3D-GRE) and conventional 2D imaging using either a single shot inversion recovery steady-state-free-precession (2D-SSFP) or inversion-recovery gradient echo (2D-GRE) sequence. We included 30 consecutive patients with structural heart disease referred for VT ablation. Preprocedural myocardial characterization was conducted in a 3 T-scanner using 2D-GRE, 2D-SSFP and 3D-GRE sequences, yielding a spatial resolution of 1.4 × 1.4 × 5 mm, 2 × 2 × 5 mm, and 1.4 × 1.4 × 1.4 mm, respectively. The core and border zone (BZ) scar components were quantified using the 60% and 40% threshold of maximum pixel intensity, respectively. A 3D scar reconstruction was obtained for each sequence. An electrophysiologist identified potential CC and compared them with results obtained with the electroanatomic map (EAM). We found no significant differences in the scar core mass between the 2D-GRE, 2D-SSFP, and 3D-GRE sequences (mean 7.48 ± 6.68 vs. 8.26 ± 5.69 and 6.26 ± 4.37 g, respectively, P = 0.084). However, the BZ mass was smaller in the 2D-GRE and 2D-SSFP than in the 3D-GRE sequence (9.22 ± 5.97 and 9.39 ± 6.33 vs. 10.92 ± 5.98 g, respectively; P = 0.042). The matching between the CC observed in the EAM and in 3D-GRE was 79.2%; when comparing the EAM and the 2D-GRE and the 2D-SSFP sequence, the matching decreased to 61.8% and 37.7%, respectively. 3D scar reconstruction using images from 3D-GRE sequence improves the overall delineation of CC prior to VT ablation. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email:
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To investigate the feasibility of accelerated electrocardiogram (ECG)-triggered contrast enhanced pulmonary vein magnetic resonance angiography (CE-PV MRA) with isotropic spatial resolution using compressed sensing (CS). Nineteen patients (59±13 y, 11 M) referred for MR were scanned using the proposed accelerated free breathing ECG-triggered 3D CE-PV MRA sequence (FOV=340×340×110 mm3, spatial resolution=1.5×1.5×1.5 mm3, acquisition window=140 ms at mid diastole and CS acceleration factor=5) and a conventional first-pass breath-hold non ECG-triggered 3D CE-PV MRA sequence. CS data were reconstructed offline using low-dimensional-structure self-learning and thresholding reconstruction (LOST) CS reconstruction. Quantitative analysis of PV sharpness and subjective qualitative analysis of overall image quality were performed using a 4-point scale (1: poor; 4: excellent). Quantitative PV sharpness was increased using the proposed approach (0.73±0.09 vs. 0.51±0.07 for the conventional CE-PV MRA protocol, p<0.001). There were no significant differences in the subjective image quality scores between the techniques (3.32±0.94 vs. 3.53±0.77 using the proposed technique). CS-accelerated free-breathing ECG-triggered CE-PV MRA allows evaluation of PV anatomy with improved sharpness compared to conventional non-ECG gated first-pass CE-PV MRA. This technique may be a valuable alternative for patients in which the first pass CE-PV MRA fails due to inaccurate first pass timing or inability of the patient to perform a 20-25 seconds breath-hold.
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This document is an update to the 2008 publication of the Society for Cardiovascular Magnetic Resonance (SCMR) Board of Trustees Task Force on Standardized Protocols. Since the time of the original publication, 3 additional task forces (Reporting, Post-Processing, and Congenital Heart Disease) have published documents that should be referred to in conjunction with the present document. The section on general principles and techniques has been expanded as more of the techniques common to CMR have been standardized. There is still a great deal of development in the area of tissue characterization/mapping, so these protocols have been in general left as optional. The authors hope that this document continues to standardize and simplify the patient-based approach to clinical CMR. It will be updated at regular intervals as the field of CMR advances.
Magnetic resonance imaging (MRI) is one of the most dynamic and safe imaging techniques available in the clinic today. However, MRI acquisitions tend to be slow, limiting patient throughput and limiting potential indications for use while driving up costs. Compressed sensing (CS) is a method for accelerating MRI acquisition by acquiring less data through undersampling of k-space. This has the potential to mitigate the time-intensiveness of MRI. The limited body of research evaluating the effects of CS on MR images has been mostly positive with regards to its potential as a clinical tool. Studies have successfully accelerated MRI with this technology, with varying degrees of success. However, more must be done before its diagnostic efficacy and benefits are clear. Studies involving a greater number radiologists and images must be completed, rating CS based on its diagnostic efficacy. Also, standardized methods for determining optimal imaging parameters must be developed.
PurposeTo develop and validate a respiratory motion compensation method for free-breathing cardiac cine imaging.MethodsA free-breathing navigator-gated cine steady-state free precession acquisition (Cine-Nav) was developed which preserves the equilibrium state of the net magnetization vector, maintains the high spatial and temporal resolutions of standard breath-hold (BH) acquisition, and images entire cardiac cycle. Cine image data is accepted only from cardiac cycles occurring entirely during end-expiration. Prospective validation was performed in 10 patients by obtaining in each three complete ventricular image stacks with different respiratory motion compensation approaches: (1) BH, (2) free-breathing with 3 signal averages (3AVG), and (3) free-breathing with Cine-Nav.ResultsThe subjective image quality score (1 = worst, 4 = best) for Cine-Nav (3.8 ± 0.4) was significantly better than for 3AVG (2.2 ± 0.5, P = 0.002), and similar to BH (4.0 ± 0.0, P = 0.13). The blood-to-myocardium contrast ratio for Cine-Nav (6.3 ± 1.5) was similar to BH (5.9 ± 1.6, P = 0.52) and to 3AVG (5.6 ± 2.5, P = 0.43). There were no significant differences between Cine-Nav and BH for the ventricular volumes and mass. In contrast, there were significant differences between 3AVG and BH in all of these measurements but right ventricular mass.Conclusion Free-breathing cine imaging with Cine-Nav yielded comparable image quality and ventricular measurements to BH, and was superior to 3AVG. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.
To expand the open source Gadgetron reconstruction framework to support distributed computing and to demonstrate that a multinode version of the Gadgetron can be used to provide nonlinear reconstruction with clinically acceptable latency. The Gadgetron framework was extended with new software components that enable an arbitrary number of Gadgetron instances to collaborate on a reconstruction task. This cloud-enabled version of the Gadgetron was deployed on three different distributed computing platforms ranging from a heterogeneous collection of commodity computers to the commercial Amazon Elastic Compute Cloud. The Gadgetron cloud was used to provide nonlinear, compressed sensing reconstruction on a clinical scanner with low reconstruction latency (eg, cardiac and neuroimaging applications). The proposed setup was able to handle acquisition and 11 -SPIRiT reconstruction of nine high temporal resolution real-time, cardiac short axis cine acquisitions, covering the ventricles for functional evaluation, in under 1 min. A three-dimensional high-resolution brain acquisition with 1 mm(3) isotropic pixel size was acquired and reconstructed with nonlinear reconstruction in less than 5 min. A distributed computing enabled Gadgetron provides a scalable way to improve reconstruction performance using commodity cluster computing. Nonlinear, compressed sensing reconstruction can be deployed clinically with low image reconstruction latency. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.
Left atrial fibrosis is prominent in patients with atrial fibrillation (AF). Extensive atrial tissue fibrosis identified by delayed enhancement magnetic resonance imaging (MRI) has been associated with poor outcomes of AF catheter ablation. To characterize the feasibility of atrial tissue fibrosis estimation by delayed enhancement MRI and its association with subsequent AF ablation outcome. Multicenter, prospective, observational cohort study of patients diagnosed with paroxysmal and persistent AF (undergoing their first catheter ablation) conducted between August 2010 and August 2011 at 15 centers in the United States, Europe, and Australia. Delayed enhancement MRI images were obtained up to 30 days before ablation. Fibrosis quantification was performed at a core laboratory blinded to the participating center, ablation approach, and procedure outcome. Fibrosis blinded to the treating physicians was categorized as stage 1 (<10% of the atrial wall), 2 (≥10%-<20%), 3 (≥20%-<30%), and 4 (≥30%). Patients were followed up for recurrent arrhythmia per current guidelines using electrocardiography or ambulatory monitor recording and results were analyzed at a core laboratory. Cumulative incidence of recurrence was estimated by stage at days 325 and 475 after a 90-day blanking period (standard time allowed for arrhythmias related to ablation-induced inflammation to subside) and the risk of recurrence was estimated (adjusting for 10 demographic and clinical covariates). Atrial tissue fibrosis estimation by delayed enhancement MRI was successfully quantified in 272 of 329 enrolled patients (57 patients [17%] were excluded due to poor MRI quality). There were 260 patients who were followed up after the blanking period (mean [SD] age of 59.1 [10.7] years, 31.5% female, 64.6% with paroxysmal AF). For recurrent arrhythmia, the unadjusted overall hazard ratio per 1% increase in left atrial fibrosis was 1.06 (95% CI, 1.03-1.08; P < .001). Estimated unadjusted cumulative incidence of recurrent arrhythmia by day 325 for stage 1 fibrosis was 15.3% (95% CI, 7.6%-29.6%); stage 2, 32.6% (95% CI, 24.3%-42.9%); stage 3, 45.9% (95% CI, 35.5%-57.5%); and stage 4, 51.1% (95% CI, 32.8%-72.2%) and by day 475 was 15.3% (95% CI, 7.6%-29.6%), 35.8% (95% CI, 26.2%-47.6%), 45.9% (95% CI, 35.6%-57.5%), and 69.4% (95% CI, 48.6%-87.7%), respectively. Similar results were obtained after covariate adjustment. The addition of fibrosis to a recurrence prediction model that includes traditional clinical covariates resulted in an improved predictive accuracy with the C statistic increasing from 0.65 to 0.69 (risk difference of 0.05; 95% CI, 0.01-0.09). Among patients with AF undergoing catheter ablation, atrial tissue fibrosis estimated by delayed enhancement MRI was independently associated with likelihood of recurrent arrhythmia. The clinical implications of this association warrant further investigation.
To evaluate the feasibility of three-dimensional (3D) single breath-hold late gadolinium enhancement (LGE) of the left ventricle (LV) using supplemental oxygen and hyperventilation and compressed-sensing acceleration. Breath-hold metrics [breath-hold duration, diaphragmatic/LV position drift, and maximum variation of R wave to R wave (RR) interval] without and with supplemental oxygen and hyperventilation were assessed in healthy adult subjects using a real-time single shot acquisition. Ten healthy subjects and 13 patients then underwent assessment of the proposed 3D breath-hold LGE acquisition (field of view = 320 × 320 × 100 mm(3), resolution = 1.6 × 1.6 × 5.0 mm(3), acceleration rate of 4) and a free-breathing acquisition with right hemidiaphragm navigator (NAV) respiratory gating. Semiquantitative grading of overall image quality, motion artifact, myocardial nulling, and diagnostic value was performed by consensus of two blinded observers. Supplemental oxygenation and hyperventilation increased the breath-hold duration (35 ± 11 s to 58 ± 21 s; P < 0.0125) without significant impact on diaphragmatic/LV position drift or maximum variation of RR interval (both P > 0.01). LGE images were of similar quality when compared with free-breathing acquisitions, but with reduced total scan time (85 ± 22 s to 35 ± 6 s; P < 0.001). Supplemental oxygenation and hyperventilation allow for prolonged breath-holding and enable single breath-hold 3D accelerated LGE with similar image quality as free breathing with NAV. Magn Reson Med, 2013. © 2013 Wiley Periodicals, Inc.
To deploy clinically, a combined parallel imaging compressed sensing method with coil compression that achieves a rapid image reconstruction, and assess its clinical performance in contrast-enhanced abdominal pediatric MRI. With Institutional Review Board approval and informed patient consent/assent, 29 consecutive pediatric patients were recruited. Dynamic contrast-enhanced MRI was acquired on a 3 Tesla scanner using a dedicated 32-channel pediatric coil and a three-dimensional SPGR sequence, with pseudo-random undersampling at a high acceleration (R = 7.2). Undersampled data were reconstructed with three methods: a traditional parallel imaging method and a combined parallel imaging compressed sensing method with and without coil compression. The three sets of images were evaluated independently and blindly by two radiologists at one siting, for overall image quality and delineation of anatomical structures. Wilcoxon tests were performed to test the hypothesis that there was no significant difference in the evaluations, and interobserver agreement was analyzed. Fast reconstruction with coil compression did not deteriorate image quality. The mean score of structural delineation of the fast reconstruction was 4.1 on a 5-point scale, significantly better (P < 0.05) than traditional parallel imaging (mean score 3.1). Fair to substantial interobserver agreement was reached in structural delineation assessment. A fast combined parallel imaging compressed sensing method is feasible in a pediatric clinical setting. Preliminary results suggest it may improve structural delineation over parallel imaging.J. Magn. Reson. Imaging 2013. © 2013 Wiley Periodicals, Inc.