DOI:10.2214/AJR.07.2066
AJR 2007; 189:240-245
© American Roentgen Ray Society
Fast High-Spatial-Resolution MRI of the Ankle with Parallel Imaging Using GRAPPA at 3 T
Jan Stefan Bauer1,2,
Suchandrima Banerjee1,3,
Tobias D. Henning1,
Roland Krug1,
Sharmilla Majumdar1,3 and
Thomas M. Link1
1 Department of Radiology, University of California at San Francisco, San
Francisco, CA.
2 Present address: Department of Radiology, Institut für
Röntgendiagnostik, Technische Universität München, Ismaninger
Str. 22, 81675 München, Germany.
3 UCSF & UCB Joint Graduate Group in Bioengineering, Berkeley, CA.
Received February 19, 2007;
accepted after revision March 26, 2007.
J. S. Bauer and S. Banerjee equally contributed to this study.
Address correspondence to J. S. Bauer
(jansbauer{at}gmail.com).
Abstract
OBJECTIVE. The purpose of our study was to compare an
autocalibrating parallel imaging technique at 3 T with standard acquisitions
at 3 and 1.5 T for small-field-of-view imaging of the ankle.
MATERIALS AND METHODS. MRI of the ankle was performed in three fresh
human cadaver specimens and three healthy volunteers. Axial and sagittal
T1-weighted, axial fat-saturated T2-weighted, and coronal
intermediate-weighted fast spin-echo sequences, as well as a fat-saturated
spoiled gradient-echo sequence, were acquired at 1.5 and 3 T. At 3 T, reduced
data sets were reconstructed using a generalized autocalibrating partially
parallel acquisition (GRAPPA) technique, with a scan time reduction of
approximately 44%. All images were assessed by two radiologists independently
concerning image quality. The signal-to-noise ratio (SNR) and
contrast-to-noise ratio (CNR) were measured in every data set. In the cadaver
specimens, macroscopic findings after dissection served as a reference for the
pathologic evaluation.
RESULTS. SNR and CNR in the GRAPPA images were comparable to the
standard acquisition at 3 T. The image quality was rated significantly higher
at 3 T with both normal and parallel acquisition compared with 1.5 T. There
was no significant difference in ligament and cartilage visualization or in
image quality between standard and GRAPPA reconstruction at 3 T. Ankle
abnormalities were better seen at 3 T than at 1.5 T for both normal and
parallel acquisitions.
CONCLUSION. Using higher field strength combined with parallel
technique, MR images of the ankle were obtained with excellent diagnostic
quality and a scan time reduction of about 44%. In addition, parallel imaging
can provide more flexibility in protocol design.
Keywords: ankle pathology • cartilage pathology • GRAPPA • high-field 3-T MRI • ligament pathology • parallel imaging • scan time reduction • tendon pathology
Introduction
High-field imaging—in particular, imaging at 3 T—has been shown
to improve musculoskeletal imaging compared with imaging at 1.5 T
[1,
2]. Improvements in the
signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are useful for
high-spatial-resolution imaging of cartilage at the knee
[1,
2]. Although
high-spatial-resolution imaging is important for research studies, overall
imaging time is a major consideration for routine clinical examinations. The
additional SNR at 3 T can also be used to reduce acquisition time. Other
traditional techniques for scanning time reduction are the acquisition of a
rectangular field of view (FOV) and the use of a long echo-train length in
fast spin-echo sequences.
In contrast, parallel imaging reduces scanning time not by changing either
the k-space bandwidth or the trajectory but by increasing the sampling
interval along the phase-encoding axis. When the MR signal is received by an
array of coils, the scan can be accelerated by acquiring fewer phase-encoding
data points, and the missing data can be synthesized after the acquisition
using the spatial-encoding information of all the coil elements, which is the
underlying principle of parallel imaging. Because scanning time is directly
proportional to the number of phase encodes, R-folds undersampling in the
phase-encoding direction reduces scanning time by the same factor, although a
penalty is paid in terms of the SNR
[3].
Especially in standard clinical musculoskeletal protocols, scanning time
reduction using parallel imaging can prevent motion artifacts and allows more
flexibility in protocol design. Several different reconstruction algorithms
have been proposed for parallel imaging, such as SENSE (sensitivity encoding)
[3]; SMASH (simultaneous
acquisition of spatial harmonics)
[4]; and, more recently, mSENSE
(modified SENSE) and GRAPPA (generalized autocalibrating partially parallel
acquisition) [5].
Studies that focus on the application of parallel imaging in clinical
musculoskeletal MRI at 1.5 T have been reported in the literature
[6–9].
Among those, GRAPPA proved to be a reliable technique with the highest
effective SNR while being robust to artifacts. However, a paucity of data
exists regarding parallel imaging at 3 T
[10,
11] and parallel imaging for
small-FOV, high-spatial-resolution MRI
[12]. Thus, for this study, we
focused on small-FOV imaging of the ankle at 3 T with an autocalibrating
parallel technique, and we compared the quality of the resulting images with
that of standard acquisitions at 3 and 1.5 T. The comparison was performed in
terms of SNR; CNR; image quality; ligament, tendon, and cartilage
visualization; and assessment of ankle abnormalities.
Materials and Methods
Specimens and Volunteers
MRI was performed in three fresh human cadaver ankle specimens (age of the
cadavers at patients' death, 60–96 years) with abnormalities of the
ligaments, tendons, and cartilage. Specimen examination was performed in
accordance with legal requirements and institutional guidelines. In addition,
three healthy human volunteers (age range, 23–31 years) without clinical
findings suggesting ankle abnormalities were examined. These examinations were
performed after institutional review board approval was granted, and informed
consent was obtained from each of the volunteers.
Imaging
All imaging procedures were performed on a 1.5-T scanner and a 3-T scanner
(Signa, GE Healthcare). Both MR systems were equipped with gradients, having a
maximum gradient strength of 4 x 10–4 T/cm. For imaging
of the specimens, a four-channel receiver coil (NMSC-001, Nova Medical) was
used; for imaging of the volunteers, an eight-channel receiver coil (SHc-Head,
Medical Devices) was used. A standard ankle protocol that had been previously
optimized at our institution for an acquisition time of approximately 6
minutes for each sequence at 1.5 and 3 T was applied.
The protocol consisted of axial and sagittal T1-weighted, axial
fat-saturated T2-weighted, and coronal fat-saturated intermediate-weighted
fast spin-echo sequences and a fat-saturated spoiled gradient-recalled
acquisition in the steady state (SPGR) for dedicated cartilage imaging
(Table 1). In addition, at 3 T,
parallel imaging acquisitions were obtained for 3D SPGR sequences and
simulated for fast spin-echo sequences by decimating fully acquired data sets.
The parallel acquisitions had to be simulated for the fast spin-echo sequences
because the they were implemented only for gradient-echo sequences in the
scanner at the time that this study was performed.
Partial parallel imaging was used with a reduction factor (R) of 2
and 16 calibration lines. Thus, the parallel imaging data sets consisted of
144 phase encodes compared with 256 in a conventional acquisition. This
difference resulted in an acquisition time reduction of approximately 44% for
the parallel scans compared with the acquisition time for the conventional
scans at 1.5 T and at 3 T. The scanning times of the conventional acquisitions
at 1.5 and 3 T were in the same range, as shown in
Table 1.
All images were reconstructed offline on a workstation (Sun Workstation,
Solaris) using reconstruction software programmed in Matlab (MathWorks). For
the partially parallel imaging data sets, images were reconstructed using a
GRAPPA-based algorithm [12,
13], whereas full imaging data
sets were reconstructed using a standard Fourier reconstruction.
Image Analysis
SNR was measured in every sequence, and CNR was calculated for the SPGR
sequences. Images obtained from parallel imaging acquisition have a spatially
varying distribution of noise. In those images, SNR calculations, which are
based on mean signal intensity in a region of interest (ROI) and the
background noise, are not valid. Therefore, SNR and CNR were calculated from
twice-repeated acquisitions. An ROI was placed in the identical location on
each of the two images, and the average SNR in the ROI was determined as the
ratio of the average signal in the ROI in the mean image and the SD of the
signal in the difference image
[14]:
where Ix,y (A) is the signal intensity of the
pixel x,y in image A, and Ix,y (B) is the signal
intensity of the pixel x,y in the image B. The CNR was calculated for the SPGR
sequences and was defined as the SNR of the cartilage minus the SNR of the
bone marrow.
All the images were assessed by two radiologists independently concerning
image quality and visualization of anatomic structures and abnormalities. The
radiologists were blinded to all information about the specimens and
volunteers and to the field strength and type of reconstruction.
For all sequences, image quality was graded by each of the radiologists
using a 4-level confidence scale. Items subjectively assessed with this scale
included sharpness of edges; amount of blurring and noise; delineation of
small ligamentous structures; and contrast between different tissues, such as
joint fluid, cartilage, cortical bone, ligaments, and fat. Images were given a
score of 4 if subjective image quality was optimal so that ligaments and
cartilage were clearly demarcated and noise and artifacts were minimal to the
eye. A score of 3 was given when one or two of the previously mentioned
criteria were visually less than optimal. A score of 2 corresponded to
pronounced limitations in the images that affected diagnostic quality. Images
scored as 1 had substantial diagnostic limitations because of extensive
artifacts and noise.
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Fig. 1A —Spoiled gradient-recalled acquisition in the steady state
(SPGR) images show grade 3 cartilage defect (arrowhead) in ankle of
cadaver specimen. No significant difference in visualization of abnormality
was found between normal (A) and parallel (B) acquisitions at 3
T.
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Fig. 1B —Spoiled gradient-recalled acquisition in the steady state
(SPGR) images show grade 3 cartilage defect (arrowhead) in ankle of
cadaver specimen. No significant difference in visualization of abnormality
was found between normal (A) and parallel (B) acquisitions at 3
T.
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Fig. 1C —Spoiled gradient-recalled acquisition in the steady state
(SPGR) images show grade 3 cartilage defect (arrowhead) in ankle of
cadaver specimen. Cartilage defect was not seen at 1.5 T by one of two
radiologists.
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For the fast spin-echo sequences, visualization of four ankle
ligaments—that is, the anterior tibiofibular ligament, anterior
talofibular ligament, anterior tibiotalar ligament, and spring
ligament—was graded (4 = excellent, 1 = poor) by both radiologists
subjectively.
In the cadaver specimens, abnormalities were evaluated on 1.5- and 3-T
scans on and parallel scans obtained at 3 T separately. Macroscopic findings
after dissection served as the standard of reference. Ligament and tendon
abnormalities were assessed using the fast spin-echo sequences. Although no
ligament abnormalities were present, abnormalities of eight tendons (tibialis
anterior and posterior, flexor and extensor hallucis longus, flexor and
extensor digitorum longus, and peroneus brevis and longus) were described on a
5-point scale. The absence of abnormalities was scored as 0; tenosynovitis,
which appear as pronounced fluid around the tendon, was scored as 1;
tendinosis, which showed elevated, abnormal signal, as 2; partial split or
full split tear as 3; and complete rupture as 4.
Cartilage abnormalities were evaluated on the SPGR sequences. The depth of
a lesion was categorized using a modified Noyes classification
[15]: 1, lesion < 50% of
the cartilage thickness; 2, lesion > 50% of the cartilage thickness, 3,
full-thickness lesion. Similar classification systems were used for
macroscopic assessments.
Statistically significant differences in image quality, SNR, and CNR were
tested using a paired two-sided Student's t test with a significance
level of p < 0.05. All statistical computations were processed
using SPSS software (version 11.5, SPSS).
Results
GRAPPA imaging using a reduction factor (R) of 2 resulted in a
scanning time reduction of 44% compared with conventional imaging. SNRs and
CNRs calculated from repeated acquisitions were comparable between the GRAPPA
images with an R of 2 and the conventional images obtained at 3 T
(Table 2) for both specimen and
volunteer studies. Comparing 3- and 1.5-T images, SNRs and CNRs had doubled on
the SPGR sequence at 3 T (Figs.
1A,
1B, and
1C) while remaining similar on
the fast spin-echo sequences (Figs.
2A,
2B,
2C,
2D,
2E,
2F,
3A,
3B, and
3C) because of the increased
spatial resolution of the 3-T sequences. Line profiles plotted from
conventionally acquired images and parallel images at 3 T matched closely, as
shown on the 3-T SPGR images in Figure
4. These images also show comparable edge sharpness between the
conventional and GRAPPA images.
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Fig. 2A —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 2B —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 2C —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 2D —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 2E —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 2F —T1-weighted (A–C) and fat-saturated T2-weighted
(D–F) images of ankle joint in cadaver specimen. Images show
superior image quality at 3 T (A, B, D, and E) as opposed to 1.5
T (C and F). No significant difference in image quality or
signal-to-noise ratio (SNR) was found between normal (A and D)
and parallel (B and E) acquisitions at 3 T (p >
0.05). Mean values of image quality for T1-weighted sequences were as follows:
2.8 (1.5 T), 3.5 (3 T), and 3.5 (3 T with generalized autocalibrating
partially parallel acquisition [GRAPPA] algorithm). Mean values of SNR for
T1-weighted sequences were as follows 43.0 (1.5 T), 49.7 (3 T), and 47.2 (3 T
with GRAPPA algorithm [3.0TGR]).
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Fig. 3A —31-year-old healthy male volunteer. Axial T1-weighted fast
spin-echo images of foot show superior delineation of spring ligament
(arrow) at 3 T (A and B) as opposed to 1.5 T
(C); 3.0TGR = 3.0T with GRAPPA algorithm. No significant
difference was found between (A) and parallel (B) acquisitions
at 3 T; visualization of this ligament was rated very good at 3 T and as
moderate at 1.5 T (C) by both radiologists.
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Fig. 3B —31-year-old healthy male volunteer. Axial T1-weighted fast
spin-echo images of foot show superior delineation of spring ligament
(arrow) at 3 T (A and B) as opposed to 1.5 T
(C); 3.0TGR = 3.0T with GRAPPA algorithm. No significant
difference was found between (A) and parallel (B) acquisitions
at 3 T; visualization of this ligament was rated very good at 3 T and as
moderate at 1.5 T (C) by both radiologists.
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Fig. 3C —31-year-old healthy male volunteer. Axial T1-weighted fast
spin-echo images of foot show superior delineation of spring ligament
(arrow) at 3 T (A and B) as opposed to 1.5 T
(C); 3.0TGR = 3.0T with GRAPPA algorithm. No significant
difference was found between (A) and parallel (B) acquisitions
at 3 T; visualization of this ligament was rated very good at 3 T and as
moderate at 1.5 T (C) by both radiologists.
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Fig. 4 —Line profiles of spoiled gradient-recalled acquisition in the
steady state (SPGR) images of cadaver specimen suggest edge sharpness of
conventional images and of generalized autocalibrating partially parallel
acquisition (GRAPPA) images is comparable at 3 T. Gray region corresponds to
cartilage. 3.0 TGR = 3.0T imaging with GRAPPA algorithm.
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The image quality of all sequences was rated highest at 3 T
(Table 3) for both specimen and
volunteer studies. The axial T1-weighted sequence obtained an average score of
3.5 of 4 points at 3 T for both parallel and normal acquisitions, compared
with a score of 2.8 at 1.5 T. There was no significant difference between
parallel and normal acquisitions at 3 T for all sequences (p >
0.05), whereas 3 T performed significantly better than 1.5 T in three of five
sequences (p < 0.05).
Similar trends were found for ligament visualization
(Table 4). For all ligaments,
visualization was rated highest for images obtained using a normal acquisition
at 3 T (average score, 3.6). The average scores were slightly lower for
parallel acquisition at 3 T (average score, 3.5), but this difference was not
significant (p < 0.05). Both average scores were significantly
higher than the average score at 1.5 T (p < 0.05); however,
ligament visualization was good even at 1.5 T (average score, 3.3 of 4
points).
The pathologic examination of the three ankle specimens revealed three
cartilage abnormalities that were classified as one grade 3 lesion in the
lateral talus, one grade 2 lesion in the medial talus, and one grade 1 lesion
in the tibia. Furthermore, in two specimens, three tendon abnormalities were
found: a partial split tear of the peroneus tendon was seen in two specimens
and a partial split tear associated with tenosynovitis of the peroneus longus
tendon was seen in one specimen. In the third specimen, an os tibiale externum
was present.
The tendon abnormalities were detected on all three sequence types. The
grade 3 cartilage lesion was seen on images obtained using both parallel and
standard acquisitions at 3 and 1.5 T. However, at 1.5 T, this cartilage lesion
was described by only one of the two radiologists. The grade 1 and 2 cartilage
lesions were missed in all three acquisitions by both radiologists.
Discussion
The results of our study have shown that higher-field-strength (i.e., 3-T)
imaging combined with parallel imaging produces MR images of the ankle that
are of excellent diagnostic quality while decreasing scanning time by 44%.
Images acquired using the GRAPPA algorithm with a reduction factor of 2 were
visually indistinguishable from images obtained using standard acquisitions.
Theoretically, for parallel imaging with low reduction factors, an SNR
decrease by the square root of the acceleration factor R—and
thus a similar effective SNR compared with conventional
acquisition—would be expected. The calibration lines incorporated in the
GRAPPA reconstruction slightly reduce the SNR loss to a lower factor than
R. For fast spin-echo sequences, the reduction in T2 decay that
results from performing parallel imaging also partly offsets the SNR loss.
Parallel imaging techniques such as GRAPPA are referred to as
"autocalibrating" techniques because the coil calibration
necessary for the parallel imaging reconstruction is built into the
accelerated scan. Hence, the reconstruction is not affected by patient motion
between scans or by gradient nonlinearity in the high-resolution scan. GRAPPA
has several advantages over other parallel imaging techniques for our specific
application. In small-FOV imaging, often, there is slight aliasing outside the
ROI but within the FOV. Griswold et al.
[5] showed that parallel
imaging techniques that belong to the class of GRAPPA are more robust to such
situations than SENSE-like parallel imaging techniques. Moreover, the quality
of image reconstruction by the former class of parallel imaging techniques is
not as sensitive to errors in estimation of coil sensitivities as the
latter.
Figures 2B and
2E show axial
GRAPPA-reconstructed images of the left ankle with slight aliasing from the
right ankle. The aliasing in the FOV and difficulty of estimating the coil
sensitivity in certain regions would compromise the image quality for a
SENSE-like parallel imaging technique, whereas as can be seen in Figures
2B and
2E, the GRAPPA technique
provided a good image quality.
The limitations for this preliminary study must be considered. First, coils
optimized for musculoskeletal and parallel imaging were not available for both
3- and 1.5-T scanners. The benefit of parallel imaging is expected to be
higher with optimized receiver arrays. Another potential limitation of this
study is the small sample size and limited range and number of abnormalities
that were analyzed. However, these factors do not affect the comparison of
image quality as presented.
In conclusion, the combination of parallel and high-field MRI can provide
high-spatial-resolution images with good diagnostic quality in a short
scanning time. In addition to reducing scanning time, parallel imaging can
provide more flexibility in protocol design—for example, with 3D
sequences the technique can be used to improve volume coverage without
increasing scanning time. Alternatively, if SNR permits, spatial resolution
can be improved without increasing acquisition time compared with the standard
acquisition. For 2D fast spin-echo sequences, a reduction of echo-train length
will reduce T2 blurring and can improve the SNR compared with standard
acquisitions. The reduction in the number of 180° pulses during the
sequence will also decrease the radiofrequency power deposition in the
subject, which can be a significant benefit at higher magnetic fields.
Although we used only a reduction factor of 2 for this study, higher
reduction factors can be used with a receiver array optimized for
musculoskeletal applications if the baseline SNR is sufficiently high. The
results of this study showed that parallel imaging using the GRAPPA algorithm
provides a robust way to further improve musculoskeletal imaging at high field
strength. A large-scale clinical study evaluating different abnormalities in
the ankle to determine the optimal combination of reduction factor, image
quality, and time necessary for imaging each abnormality now is clearly
warranted.
References
- Gold GE, Han E, Stainsby J, Wright G, Brittain J, Beaulieu C.
Musculoskeletal MRI at 3.0 T: relaxation times and image contrast.
AJR 2004; 183:343
-351[Abstract/Free Full Text]
- Masi JN, Sell CA, Phan C, et al. Cartilage MR imaging at 3.0 versus
that at 1.5 T: preliminary results in a porcine model.
Radiology 2005;236
: 140-150[Abstract/Free Full Text]
- Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE:
sensitivity encoding for fast MRI. Magn Reson Med1999; 42:952
-962[CrossRef][Medline]
- Sodickson DK, Manning WJ. Simultaneous acquisition of spatial
harmonics (SMASH): fast imaging with radiofrequency coil arrays.
Magn Reson Med 1997;38
: 591-603[Medline]
- Griswold MA, Jakob PM, Heidemann RM, et al. Generalized
autocalibrating partially parallel acquisitions (GRAPPA). Magn
Reson Med 2002; 47:1202
-1210[CrossRef][Medline]
- Kreitner KF, Romaneehsen B, Krummenauer F, Oberholzer K, Muller LP,
Duber C. Fast magnetic resonance imaging of the knee using a parallel
acquisition technique (mSENSE): a prospective performance evaluation.
Eur Radiol 2006;16
: 1659-1666[CrossRef][Medline]
- Magee T, Shapiro M, Williams D. Usefulness of simultaneous
acquisition of spatial harmonics technique for MRI of the knee.
AJR 2004; 182:1411
-1415[Abstract/Free Full Text]
- Romaneehsen B, Oberholzer K, Muller LP, Kreitner KF. Rapid
musculoskeletal magnetic resonance imaging using integrated parallel
acquisition techniques (IPAT): initial experiences.
Rofo 2003; 175:1193
-1197[Medline]
- Niitsu M, Ikeda K. Routine MR examination of the knee using
parallel imaging. Clin Radiol 2003;58
: 801-807[CrossRef][Medline]
- Frydrychowicz A, Bley TA, Winterer JT, et al. Accelerated
time-resolved 3D contrast-enhanced MR angiography at 3T: clinical experience
in 31 patients. MAGMA 2006;19
: 187-195[CrossRef][Medline]
- Markl M, Uhl M, Wieben O, et al. High resolution 3T MRI for the
assessment of cervical and superficial cranial arteries in giant cell
arteritis. J Magn Reson Imaging 2006;24
: 423-427[CrossRef][Medline]
- Banerjee S, Choudhury S, Han ET, et al. Autocalibrating parallel
imaging of in vivo trabecular bone microarchitecture at 3 Tesla.
Magn Reson Med 2006;56
: 1075-1084[CrossRef][Medline]
- Banerjee S, Han E, Brau A, Majumdar S. Parallel imaging of
trabecular bone micro-architecture using autocalibrating technique at 3 T.
(abstr) Magn Reson Med 2006;56
(P): 2452
- Dietrich SBR, Reiser OM, Schoenberg SO. Influence of parallel
imaging and other reconstruction techniques on the measurement of
signal-to-noise ratios. (abstr) Magn Reson Med2005; 54(P)
- Noyes FR, Stabler CL. A system for grading articular cartilage
lesions at arthroscopy. Am J Sports Med1989; 17:505
-513[Abstract/Free Full Text]
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Introduction
