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Parallel Imaging and Diffusion Tensor Imaging for Diffusion-Weighted MRI of the Liver: Preliminary Experience in Healthy Volunteers

¹ Department of Radiology, University of California, San Francisco, 505 Parnassus Ave., San Francisco, CA 94143.
² Department of Radiology, New York University Medical Center, 560 First Ave., TCH–HW 202, New York, NY 10016.
³ Department of Medicine, Division of Gastroenterology, University of California, San Francisco, San Francisco, CA 94143.

Received September 22, 2003; accepted after revision April 26, 2004.

Presented at the 2004 annual meeting of the American Roentgen Ray Society, Miami Beach, FL.

Partially supported by a grant from the Margulis Society, Department of Radiology, University of California, San Francisco.

Address correspondence to B. Taouli (bachir.taouli{at}med.nyu.edu).

Abstract

OBJECTIVE. Our aim was to determine whether parallel imaging and diffusion tensor imaging affect the measurement of apparent diffusion coefficient (ADC) during diffusion-weighted MRI of the liver in healthy volunteers.

SUBJECTS AND METHODS. We performed breath-hold single-shot echo-planar diffusion-weighted MRI of the liver in 10 healthy volunteers using conventional diffusion, conventional diffusion with parallel imaging, and diffusion tensor with parallel imaging sequences. TE values for the three sequences were 83, 74, and 63, respectively. Liver signal intensity was measured on all sequences and normalized to the SD of the measurement. Hepatic ADC was calculated by acquiring all sequences with b values of 0 and 500 sec/mm².

RESULTS. The normalized liver signal intensity was higher on diffusion tensor with parallel imaging and conventional diffusion with parallel imaging than on conventional diffusion without parallel imaging for a b value of 500 sec/mm² (13.0 and 10.1 vs 9.1, respectively; p < 0.03) and for a b value of 0 sec/mm² (9.0 and 7.6 vs 6.9, respectively; without reaching a significant difference, p = 0.12). Hepatic ADC was not significantly different between sequences (p = 0.16).

CONCLUSION. Higher signal intensity can be obtained when using parallel imaging and diffusion tensor imaging during diffusion-weighted MRI of the liver without compromising hepatic ADC measurement.

Results of several studies have suggested that measurement of hepatic apparent diffusion coefficient (ADC) by echo-planar diffusion-weighted MRI may be useful in the characterization of focal hepatic lesions (benign lesions have a higher ADC) and in the evaluation of diffuse liver disease (ADC is reduced in cirrhosis) [1–6]. However, single-shot echo-planar diffusion-weighted sequences of the liver are limited by poor signal-to-noise ratio, low spatial and contrast resolution, and relatively long TE values. The ideal TE value would approximate the T2 relaxation time of the liver parenchyma, (i.e., [mean ± SD] 46 ± 6 msec [7]), but most prior studies have used TE values of 70–123. [2, 4–6].

Parallel imaging and diffusion tensor imaging are MRI sequences that allow the use of shorter TEs and might facilitate diffusion-weighted MRI of the liver. Parallel imaging is a technique that relies on the fact that the signal from a multielement surface coil contains limited spatial information because of the differing sensitivities of the component coils [8, 9]. Parallel imaging reduces the train of gradient echoes in combination with a faster k-space traversal per unit of time. The resultant increased bandwidth per pixel in the phase-encoding direction and the shortened echo-planar imaging train thus improve image quality. Diffusion tensor imaging uses additional gradients to plot the relative degree of diffusion in multiple dimensions and has been used predominantly in areas in which diffusion is preferentially restricted in one direction. The use of multiple diffusion gradient directions during diffusion tensor imaging allows gradient summation, resulting in stronger applied gradients and shorter TE values. To our knowledge, the measurement of hepatic ADC in either normal or abnormal livers using parallel imaging or diffusion tensor techniques has not been described. Therefore, we undertook this study to determine whether parallel imaging and diffusion tensor imaging affect the measurement of hepatic ADC during diffusion-weighted MRI of the liver in healthy volunteers.

Subjects and Methods

Subjects
This prospective single-institution study was approved by our institutional committee on human research. Written informed consent was obtained from all participants. We recruited 10 healthy adult volunteers between September 2002 and May 2003. To avoid the potentially confounding effects of alcoholic liver disease and subsequent fatty infiltration, we did not recruit subjects with an alcohol consumption of greater than 30 g per day for men or 15 g per day for women [10]. The 10 healthy volunteers consisted of seven men and three women with a mean age of 33 years (range, 27–44). None of the volunteers had a known history of acute or chronic liver disease.

MRI Technique
MRI was performed on a 1.5-T superconducting body scanner (Intera, Philips Medical Systems) equipped with high-performance gradients (maximum strength of 30 mT/m and maximum slew rate of 150 mT/m per millisecond). A four-element quadrature phased-array surface coil was used to optimize signal- to-noise ratio. Finger pulse triggering was used to decrease motion artifacts from heart beating, as shown in a previous study [11]. Conventional diffusion without parallel imaging, conventional diffusion with parallel imaging, and diffusion tensor with parallel imaging single-shot echo-planar diffusion-weighted MRI sequences were performed in all subjects, using b values of 0 and 500 sec/mm². The selection of a b value of 500 sec/mm² was based on a compromise between image quality and adequate diffusion strength. Higher b values were found to produce unacceptably low image signal. We used the following parameters: TR range of 1,800–2,400; TEs of 83 (conventional diffusion), 74 (conventional diffusion with parallel imaging), and 63 (diffusion tensor with parallel imaging); echo-planar imaging factors of 69 (conventional diffusion), 33 (conventional diffusion with parallel imaging), and 39 (diffusion tensor with parallel imaging); matrix of 128 x 83 (interpolated to 256 x 256); 1 signal acquired; field of view of 36–40 cm; acquisition times (one or more breath-holds as required) of 36–40 sec (conventional diffusion), 36–43 sec (conventional diffusion with parallel imaging), and 43–60 sec (diffusion tensor with parallel imaging); and slice thickness of 7 mm (15 slices acquired) with interslice gap of 2 mm. Parallel imaging was performed using sensitivity encoding (SENSE, Philips Medical Systems). An acceleration factor of 2 was used. The diffusion gradients were applied in three orthogonal directions for conventional diffusion and conventional diffusion with parallel imaging sequences (frequency-encoding [x], phase-encoding [y], and section-select directions [z]) and in six directions for diffusion tensor imaging with parallel imaging sequence (x, y, z, xy, yz, xz).

In addition, for diffusion tensor imaging, we used a rotated frame of reference known as "Gradient overplus" (Philips Medical Systems) that resulted in greater gradient strength and shorter TE values. Frequency-selective fat saturation was used in all sequences to reduce chemical shift artifacts. No contrast medium was administered.

MRI Evaluation
A radiologist who was undertaking a fellowship in abdominal imaging reviewed all images on a postprocessing workstation (Easy Vision Intera workstation, release 8.1.3, Philips Medical Systems). Liver signal intensity was recorded as the mean of values generated by placing three separate circular regions of interest (ROIs) of 3-cm diameters over the right hepatic lobe. Care was taken to exclude vessels from the ROIs. Because our version of parallel imaging incorporated a filter that reduced background noise, we could not directly measure the noise in each image. We calculated instead the normalized signal intensity represented by the ratio of mean signal in a homogeneous portion of the liver to the SD of signal over the ROI (the SD representing both noise and tissue signal heterogeneity). For the same b value and identical ROI, the signal heterogeneity should be constant, but the noise component varies.

Hepatic ADC was calculated by solving the diffusion equation:

signal intensity for b = 500 sec/mm² = (signal intensity for b = 0 sec/mm²) exp (–b x ADC).

Statistical Analysis
Normalized signal intensity of the liver and hepatic ADCs as measured by the three sequences for b values of 0 and 500 sec/mm² were compared using the nonparametric Kruskall-Wallis test for overall comparison and the nonparametric Wilcoxon's signed rank test for paired comparisons when the overall comparison was significant. A p value of less than 0.05 was considered significant.

Results

Liver signal intensity, SD of signal intensity, and normalized signal intensity obtained with the three different diffusion-weighted sequences for b values of 0 and 500 sec/mm² are shown in Table 1. When compared with a b value of 0 sec/mm², there was an attenuation of liver signal with a b value of 500 sec/mm². However, the normalized signal intensity (ratio of signal intensity to SD of signal intensity) is higher for a b value of 500 than for a b value of 0 and sec/mm², in relationship to smaller SDs with b value of 500.

For a b value of 0 sec/mm², higher normalized signal values were obtained with diffusion tensor with parallel imaging, followed by conventional diffusion with parallel imaging and conventional diffusion without parallel imaging; however, the difference was not significant (p = 0.12).

For b = 500 sec/mm², there was a significant difference among the three sequences (p < 0.03): diffusion tensor with parallel imaging showed the highest signal intensity, followed by conventional diffusion with parallel imaging and by conventional diffusion without parallel imaging. In paired comparisons for a b value of 500 sec/mm², the Wilcoxon's signed rank test showed no significant difference between conventional diffusion and conventional diffusion with parallel imaging (p = 0.57); however, there was a significant difference between conventional diffusion and diffusion tensor with parallel imaging and between conventional diffusion with parallel imaging and diffusion tensor with parallel imaging (p < 0.02 and p < 0.05, respectively). Hepatic ADCs were not significantly different among the three sequences (p = 0.16); values are shown in Table 2.

Images from a healthy volunteer are shown in Figures 1A, 1B, 1C, 1D, 1E, 1F, 1G, 1H, and 1I.

View larger version (113K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1A. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (111K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1B. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (135K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1C. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (99K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1D. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (101K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1E. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (124K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1F. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (152K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1G. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (132K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1H. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

View larger version (127K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1I. —27-year-old healthy male volunteer. Transverse diffusion-weighted MR images of abdomen obtained at same level with three single-shot echo-planar imaging sequences without contrast injection: conventional diffusion (b = 0 sec/mm2 [A]), conventional diffusion with parallel imaging (b = 0 sec/mm2 [B]), diffusion tensor with parallel imaging (b = 0 sec/mm2 [C]), conventional diffusion (b = 500 sec/mm2 [D]), conventional diffusion with parallel imaging (b = 500 sec/mm2 [E]), diffusion tensor with parallel imaging (b = 500 sec/mm2 [F]), and corresponding apparent diffusion coefficient (ADC) maps [G–I]. More signal is noted on diffusion tensor image for b value of 500 sec/mm2 (F) than on conventional diffusion images without (D) and with (E) parallel imaging. Background noise is suppressed with parallel imaging. Hepatic ADC (x 10–3 mm2/sec) was (mean ± SD) 1.8 ± 0.4 (conventional diffusion), 1.7 ± 0.4 (conventional diffusion with parallel imaging), and 1.9 ± 0.3 (diffusion tensor with parallel imaging).

Discussion

Our preliminary results suggest that parallel imaging and diffusion tensor imaging can be combined to improve signal intensity during diffusion-weighted MRI of the liver, without compromising measurement of hepatic ADC, particularly after application of the diffusion gradients. The diffusion tensor imaging technique in conjunction with parallel imaging benefits from the shorter TEs as well as from additional sample points for generating the isotropic diffusion and ADC maps, with subsequent improvement in signal intensity. By decreasing the echo-train length, we found that parallel imaging reduces off-resonance and blurring artifacts related to echo-planar imaging [8, 9, 12, 13], although image quality was not analyzed as an end point in our study. Parallel imaging with diffusion tensor imaging could be used to increase matrix acquisition size [14], with subsequent better image qual ity. Potential applications include the evaluation of liver fibrosis in chronic hepatitis and better detection and characterization of focal liver lesions.

Our results are also consistent with recent studies on brain diffusion-weighted MRI that showed that conventional diffusion imaging with parallel imaging and diffusion tensor imaging with parallel imaging were of the same or better quality than conventional echo-planar sequences [9, 12, 13, 15]. In our study, improved image quality with parallel imaging occurred despite the theoretic decrease in signal-to-noise ratio using this technique [8, 12, 16].

We did not measure the signal-to-noise ratio, but we measured instead the normalized signal (ratio of signal intensity and SD of signal intensity). We think that the SD of signal intensity reflects both heterogeneity of tissues and noise. For the same b value and identical ROI, the signal heterogeneity should be constant but the noise component varies.

Described applications of parallel imaging include 3D contrast-enhanced angiography [17], real-time cardiac imaging [18], brain functional imaging [19], and multiphasic dynamic-enhanced abdominal imaging [20].

Our study highlights the potential for the novel combination of parallel imaging and diffusion tensor imaging during diffusion-weighted MRI of the liver. To date, diffusion tensor imaging has been used predominantly for brain imaging, particularly fiber tractography [21–24]. Only one study has described the use of diffusion tensor imaging in the abdomen for evaluation of the kidneys in healthy volunteers [25]. We found that the combination of parallel imaging and diffusion tensor imaging maximized the advantageous reduction in TEs, despite the slightly longer acquisition time related to the multiple diffusion gradient directions. We found no difference in the measurement of hepatic ADC among the sequences investigated. Although we obtained higher ADC values for normal liver (1.51–1.60 x 10^–3 mm²/sec) than those reported in a recent study (0.92–1.14 x 10^–3 mm²/sec) [11], the difference may be related to the lower b value that we used (500 vs 1,300 sec/mm²).

Our study has some limitations. Only a small number of subjects were studied. We did not evaluate fractional anisotropy on diffusion tensor imaging, although this evaluation is unlikely to have been helpful because a previous study showed that normal liver has isotropic diffusion [6]. As with other studies, we found measurement of ADC to have a relatively large SD. More precise techniques for ADC measurement would be desirable. We did not investigate the role of different b values because a previous study showed satisfactory results with a b value of 500 sec/mm² [6] and because higher b values are associated with a greater reduction in signal and lower image quality.

In conclusion, diffusion tensor imaging and parallel imaging can be used to increase signal intensity during diffusion-weighted MRI of the liver without compromising the measurement of hepatic ADC.

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