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Comparative evaluation of zoomed and parallel diffusion-weighted imaging: A phantom study
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Received: ,
Accepted: ,
How to cite this article: Iwase A, Takatsu Y, Ohno N, Kitao A, Miyati T. Comparative evaluation of zoomed and parallel diffusion-weighted imaging: A phantom study. J Clin Imaging Sci. 2026;16:30. doi: 10.25259/JCIS_92_2025
Abstract
Objectives:
Single-shot echo-planar imaging sequences with parallel imaging are widely used for diffusion-weighted imaging (DWI). However, when small fields of view and higher phase-encoding reduction ratios (PRs) are applied, image quality may deteriorate because of imperfections in the unfolding process of parallel imaging. Previous studies have suggested that Zoomed DWI (Zoom-DWI) may address this limitation. Therefore, we compared Zoom-DWI with parallel DWI (Parallel-DWI) across different PRs to evaluate image quality.
Material and Methods:
Zoom-DWI and Parallel-DWI were performed using identical acquisition times and imaging parameters at different PRs. Signal-to-noise ratio (SNR), image uniformity, slice thickness, spatial resolution, and image distortion were evaluated.
Results:
At a PR of 66.6%, the SNR of Zoom-DWI was approximately 1.4–3.3-fold higher than that of Parallel-DWI at the image center, where reconstruction errors in parallel imaging become more pronounced as PR increases. Image uniformity was also higher in Zoom-DWI than in Parallel-DWI, and the difference increased by approximately 41.0% at a PR of 66.6%. Slice thickness, spatial resolution, and image distortion were comparable between the two methods.
Conclusion:
In this phantom study, Zoom-DWI demonstrated higher SNR and greater image uniformity than Parallel-DWI, particularly at higher PRs and in the central image region.
Keywords
Image uniformity
Parallel imaging
Phantom study
Signal-to-noise ratio
Zoomed diffusion-weighted imaging
INTRODUCTION
Diffusion-weighted imaging (DWI) plays an important role in diagnostic magnetic resonance imaging (MRI). It is particularly essential for diagnosing acute cerebral infarction and imaging spinal nerve fibers based on anisotropic diffusion.[1-3] Furthermore, DWI has been widely used clinically to evaluate the trunk region, including the mammary glands, pancreas, kidneys, uterus, prostate, bladder, and rectum.[4-14]
Single-shot echo-planar imaging (EPI) is commonly used to acquire diffusion-weighted images. Although this technique enables rapid image acquisition, substantial magnetic susceptibility artifacts and geometric distortion often degrade image quality.[8,14] Reducing the number of phase-encoding steps can help mitigate these distortions; however, this approach introduces aliasing artifacts. Parallel imaging addresses aliasing using coil sensitivity profiles; however, image quality may still deteriorate because of reconstruction (unfolding) errors [Figure 1]. These errors become more pronounced as the reduction factor (Rf) in parallel imaging increases.[15,16]
Another method for reducing the number of phase-encoding steps is local excitation (Zoom). Zoom restricts the field of view (FOV) and suppresses unfolding artifacts.[5-10,12-14,17,18]
Zoomed DWI (Zoom-DWI) uses oblique irradiation of excitation pulses (90° pulses) in the slice direction while applying refocusing pulses (180° pulses). The oblique irradiation of excitation pulses affects adjacent slice cross-sections and can produce aliasing errors, which can be reduced by applying spatial saturation pulses. As a result, the excitation range is confined to the phase-encoding direction, preventing imperfections in the unfolding process [Figure 2].[3,17,18]
Accordingly, Zoom-DWI offers potential advantages over conventional single-shot EPI-based DWI with parallel imaging (Parallel-DWI). However, the clinical application of Zoom-DWI requires prior understanding of its imaging characteristics. To the best of our knowledge, no previous quantitative studies have compared Zoom-DWI with Parallel-DWI under identical imaging conditions.
Accurate diagnosis depends on high-quality imaging. In this study, we investigated the potential utility of Zoom-DWI for improving image quality. Specifically, we compared Zoom-DWI with conventional Parallel-DWI to clarify the sequence characteristics of Zoom-DWI and to evaluate the effects of varying phase-encoding reduction ratios (PRs) on image quality.
MATERIAL AND METHODS
A phantom was used to objectively evaluate Zoom-DWI and Parallel-DWI in terms of signal-to-noise ratio (SNR), image uniformity, slice thickness, and spatial resolution. The present study was primarily a phantom study and did not involve human participants. A single anonymized clinical MR image was included solely to illustrate imaging artifacts. The use of the image was approved by the Institutional Review Board at Fujita Health University, number HM22-551, dated March 20, 2023.
MRI technique and phantom design
MRI was performed using a 3-T scanner (Ingenia Omega-HP, Philips Medical Systems, Best, The Netherlands) with a 32-channel Torso coil and a 15-channel Head coil.
Figure 3 shows the phantoms used for each measurement. A 300-mm-diameter spherical phantom filled with mineral oil was used to assess SNR and image uniformity. Furthermore, a 200-mm-diameter cylindrical phantom containing CuSO4•5H2O was used to evaluate slice thickness, image distortion, and spatial resolution.
Zoom-DWI and Parallel-DWI were performed using identical imaging parameters. Images were acquired orthogonal to the gantry bore (i.e., in the axial plane), with the phase-encoding direction set from anterior to posterior. Parallel imaging was implemented using sensitivity encoding, an image-based reconstruction technique.
To compare Parallel-DWI and Zoom-DWI based on the reduced number of phase-encoding steps, the FOV of Zoom-DWI in the phase-encoding direction was adjusted and standardized. PR was defined as the percentage reduction in FOV in the phase-encoding direction for each Rf, calculated as (100−(100/Rf)). Specifically, PR was 0% for Rf = 1.0, 33.3% for Rf = 1.5, 50% for Rf = 2.0, and 66.6% for Rf = 3.0 [Table 1].
| Corresponding values for phase-encoding reduction | ||||
|---|---|---|---|---|
| Rf | 1 | 1.5 | 2 | 3 |
| PR (%) | 0 | 33.3 | 50 | 66.6 |
PR: Phase-encoding step reduction rate, Rf: Reduction factor
Physical evaluation items
All images were acquired in a single acquisition. SNR, image uniformity, slice thickness, geometric distortion, and spatial resolution were evaluated. Imaging parameters are summarized in Table 2.
| Parameter | SNR | Image nonuniformity | Slice thickness | Image distortion | Spatial resolution |
|---|---|---|---|---|---|
| FOV (mm) | 320 | 320 | 256 | 320 | 320 |
| Acquisition voxel size (mm) | 2×2 × 5 | 2×2 × 5 | 2×2 × 5 | 1.25×1.25×3 | 1.25×1.25×1 |
| Repetition time (ms) | 5000 | 5000 | 5000 | 5000 | 5000 |
| Echo time (ms) | 100 | 100 | 100 | 110 | 320 |
| bfactor (s/mm2) | 0 | 0 | 0 | 0 | 0 |
| Number of average | 1 | 1 | 1 | 1 | 1 |
FOV: Field of view, SNR: Signal-to-noise ratio
SNR measurement
Figure 4a and 4b shows five regions of interest (ROIs) of identical size (7.5 × 7.5 pixels) positioned on the images. For each ROI, SNR was calculated as the mean signal intensity divided by the standard deviation within the same ROI. The resulting SNR values were then compared.[19-21]
Image uniformity measurement
Image uniformity was assessed for Zoom-DWI and Parallel-DWI under the same imaging conditions used for the SNR measurements. Figures 4c and 4d shows the ROIs positioned at the centers of the Zoom-DWI and Parallel-DWI images, respectively. The ROI was set at 68 × 277.5 mm2 based on the Zoom-DWI PR3 images and applied to all images. After applying a low-pass filter to remove noise, the maximum and minimum signal intensities were measured, and image non-uniformity was calculated using Equation (1).[22,23]
Image non-uniformity (%) = (Smax − Smin)/(Smax + Smin) × 100 (1)
Where Smax and Smin are the maximum and minimum signal values within each ROI, respectively. Lower image nonuniformity (%) indicates greater image uniformity.
Slice thickness measurement
Slice thickness was measured for Zoom-DWI and Parallel-DWI. Figure 5a and 5b show the slice profiles obtained using the slab method, from which the full width at half-maximum (FWHM) was determined to represent slice thickness.[24]
Spatial resolution measurement
Spatial resolution was measured for Zoom-DWI and Parallel-DWI. Figure 5c, 5d, and 5e illustrate the scanned phantom containing pins with diameters ranging from 0.500 to 2.000 mm. Spatial resolution was defined as the smallest pin diameter that could be visually distinguished.
For resolution assessment, the images were binarized. By setting the window width of the phantom image to 1, the smallest prism diameter that could be separately identified was defined as the spatial resolution. Figure 5c, 5d, and 5e show spatial resolution in the phase-encoding and readout directions for images acquired with Zoom-DWI and Parallel-DWI at a PR of 66.6%, where image distortion was minimal.
Image distortion measurement
Image distortion was evaluated for Zoom-DWI and Parallel-DWI using images acquired with a 1-mm slice thickness to minimize partial volume effects.
As shown in Figure 6, the distances between the central pin and the four peripheral pins located at the top, left, bottom, and right of the phantom image (D1–D4) were measured. Distortion (%) was then calculated using Equation (2).[25]
Where D is the measured distance (mm) between pins, and the true distance between pins was 25 mm.
Image analysis
Image analysis was conducted using ImageJ version 1.53k (National Institutes of Health, Bethesda, MD, USA), and numerical calculations were performed using Microsoft Excel (Microsoft Corp., Redmond, WA, USA). Statistical analysis was not performed because each imaging acquisition was conducted only once.
RESULTS
Zoom-DWI showed no unfolding errors at any PR. At a PR of 66.6%, Zoom-DWI exhibited substantially higher SNR and greater image uniformity than Parallel-DWI [Figure 7a-d and Table 3]. Conversely, no significant differences were observed between the two methods in slice thickness, spatial resolution, or image distortion across the range of PRs [Figure 7e and f, Table 3].
| Physical evaluation items | Scan type | Measurement position | PR (%) | |||
|---|---|---|---|---|---|---|
| 0 | 33.3 | 50 | 66.6 | |||
| SNR | ZoomDWI | Average of ROI 1–4 | 26.54 | 25.39 | 23.63 | 18.3 |
| ROI 5 | 34.03 | 27.76 | 31.62 | 24.96 | ||
| ParallelDWI | Average of ROI 1–4 | 21.15 | 20.16 | 17.91 | 14.47 | |
| ROI 5 | 22.58 | 20.03 | 17.35 | 7.6 | ||
| Image nonuniformity | ZoomDWI | 28.4 | 30.17 | 29.01 | 33.8 | |
| ParallelDWI | 32.24 | 31.52 | 34.5 | 69.13 | ||
| Slice thickness | ZoomDWI | 5.35 | 5.15 | 5.3 | 5.15 | |
| ParallelDWI | 5.05 | 4.95 | 4.8 | 4.7 | ||
| Spatial resolution | ZoomDWI | 1.25 | 1.25 | 1.25 | 1.25 | |
| ParallelDWI | 1.25 | 1.25 | 1.25 | 1.25 | ||
| Image distortion | ZoomDWI | D1 | 0.4 | 0.8 | 0.4 | 0.4 |
| D2 | 6.8 | 3.2 | 1.2 | 0.4 | ||
| D3 | 29.6 | 18 | 14 | 11.6 | ||
| D4 | 0.4 | 1.2 | 0.8 | 2 | ||
| ParallelDWI | D1 | 0.8 | 0 | 0.4 | 0 | |
| D2 | 8 | 4 | 0.8 | 0 | ||
| D3 | 30.8 | 21.6 | 12.8 | 10.8 | ||
| D4 | 0.4 | 0.8 | 2 | 2 | ||
DWI: Diffusion-weighted imaging, PR: Phase-encoding step reduction rate, ROI: Region of interest, SNR: Signal-to-noise ratio
SNR measurement
The SNR of Zoom-DWI was higher than that of Parallel-DWI in nearly all ROIs. Across ROIs 1–4, the average SNR of Zoom-DWI was approximately 1.3 times greater [Figure 7a and b, Table 3]. At a PR of 66.6%, the SNR of Zoom-DWI was 3.3 times higher than that of Parallel-DWI [Figure 7c and Table 3].
Image uniformity measurement
The lowest image non-uniformity was 28.4% for Zoom-DWI at a PR of 0%, whereas the highest image nonuniformity was 69.1% for Parallel-DWI at a PR of 66.6%. At this PR, the largest difference in image nonuniformity between Zoom-DWI and Parallel-DWI was 35.3% [Figure 7d and Table 3].
Slice thickness measurement
Zoom-DWI produced higher FWHM values than Parallel-DWI, with a maximum FWHM 1.10-fold higher at a PR of 50.0% and a minimum FWHM 1.04-fold higher at a PR of 33.3% [Figure 7e and Table 3].
Spatial resolution measurement
Zoom-DWI and Parallel-DWI showed the same spatial resolution of 1.25 mm in the frequency-encoding and phase-encoding directions [Figure 7f and Table 3].
Image distortion measurement
The maximum difference in image distortion between Zoom-DWI and Parallel-DWI was 3.6%, observed at a PR of 33.3% and measurement position D-3, with greater distortion in Parallel-DWI. The minimum difference was 0%, indicating no detectable distortion between the two methods at PRs of 0% and 66.6% at position D-4. Overall, image distortion decreased as PR increased [Table 3].
DISCUSSION
Principal finding
We evaluated the image quality characteristics of Zoom-DWI and found that it provided particularly high SNR in the central image region and greater image uniformity than Parallel-DWI. However, no differences were observed in slice thickness or spatial resolution between the two methods. These findings are likely attributable to errors in the image unfolding process. In parallel imaging, unfolding accuracy may decrease as the independence of multiple coils, represented by the g-factor, increases during reconstruction.[15,16,26,27] This reflects unfolding errors inherent to parallel imaging.[28]
In Parallel-DWI, higher PRs led to a marked reduction in central SNR, likely because of unfolding errors, whereas SNR differences in peripheral regions between Zoom-DWI and Parallel-DWI were minimal. This central loss of image quality is a limitation of parallel imaging. Increasing the parallel imaging factor can reduce image distortion,[29] which is particularly beneficial when combined with EPI, a distortion-prone technique; however, image degradation may also increase under these conditions. In this regard, Zoom-DWI offers an advantage, particularly at high parallel imaging factors and small FOV settings. The reduction in image uniformity observed in Parallel-DWI is likely attributable to the same underlying mechanisms.
The improvements observed with Zoom-DWI are primarily related to differences in image reconstruction and parallel imaging mechanisms. By restricting the FOV to the ROI through selective excitation, Zoom-DWI minimizes reconstruction errors caused by signal unfolding in the phase-encoding direction. Consequently, Zoom-DWI is less susceptible to unfolding-related artifacts than Parallel-DWI, particularly at higher PRs.
Furthermore, the reduced FOV suppresses increases in the g-factor inherent to parallel imaging, thereby mitigating noise amplification. This reduction in g-factor-related noise may have contributed to the improved SNR stability and image uniformity observed with Zoom-DWI in the present study. Collectively, these findings suggest that Zoom-DWI improves image quality by avoiding unfolding-related errors, because no unfolding process is required, and by reducing g-factor-related noise amplification compared with Parallel-DWI.
Clinical implications
This study provided a physical comparison of Parallel-DWI and Zoom-DWI with selective excitation and compared their respective imaging characteristics. Zoom-DWI demonstrated advantages in SNR and uniformity in local imaging, particularly by avoiding the effects of unfolding errors near the image center. Parallel-DWI may exhibit substantial unfolding errors at high undersampling rates, particularly in the central image region, because of limitations in reconstruction accuracy. These effects may vary depending on the patient’s body habitus, imaging FOV, and anatomical location.
These findings are particularly relevant to abdominal and pelvic imaging, such as the pancreas and prostate, where susceptibility-induced distortion and parallel imaging-related unfolding artifacts can impair detection and diagnostic accuracy. The improved central SNR and image uniformity observed with Zoom-DWI may therefore improve lesion conspicuity in these regions.
Clinical studies have reported that Zoom-DWI produces clearer prostate images and minimizes image distortion and artifacts.[30] Similar findings were observed in the present phantom study. Therefore, comparable improvements in image quality may also be expected in other pelvic organs and centrally located abdominal organs such as the pancreas.
Difficulty in identifying lesions
DWIs play an important role in tumor detection and in differentiating benign from malignant lesions. However, when false image components are superimposed on the target area because of unfolding errors, lesion boundaries may become obscured, making it difficult to determine lesion location and size accurately. Furthermore, inappropriate enhancement of low- and high-signal regions may reduce tumor-to-background contrast and impair lesion conspicuity.[31]
Occurrence of false lesions
Image distortion can generate signal abnormalities that do not truly exist and may be misinterpreted as false-positive tumor lesions.[32]
Misestimation of the apparent diffusion coefficient (ADC)
The ADC derived from DWIs is an important parameter for tumor characterization. Associations between the SNR and ADC have been reported previously.[33,34] Unfolding errors may result in abnormally low or high ADC values within lesions. Such errors may affect differentiation between malignant and benign lesions and reduce contrast between tumors and surrounding tissue, potentially obscuring tumor boundaries. For example, reduced ADC is considered an indicator of malignancy in prostate cancer. However, excessive ADC reduction caused by artifacts may make it difficult to distinguish benign from malignant lesions.
Impact on therapy planning
DWI is also used for surgical decision-making and radiation therapy planning.[35,36] Misidentification of lesion size and extent may complicate treatment selection. For example, unclear lesion localization in prostate cancer may adversely affect planning for targeted therapy, such as brachytherapy.[37] Because image distortion introduces positional uncertainty, higher PRs may be beneficial in reducing distortion.[38]
As described above, unfolding errors may cause difficulty identifying lesions in the central trunk, generate false lesions, and lead to inaccurate ADC evaluation, potentially reducing diagnostic accuracy and contributing to treatment planning errors. Therefore, when Parallel-DWI is used, appropriate undersampling rates, coil selection, and phase-encoding direction should be considered. Furthermore, selecting techniques such as Zoom-DWI for local imaging may support reliable diagnosis, particularly in organs susceptible to unfolding errors.
In contrast, Zoom-DWI can suppress unwanted signals through selective excitation and image only the target region, suggesting the potential for more stable image quality in these organs. However, because the imaging range of Zoom-DWI is restricted by the selected excitation region, its use may be limited when lesion localization is uncertain or broad anatomical coverage is required.
Potential clinical translation and cost/time trade-offs
From a clinical perspective, Zoom-DWI involves a tradeoff between acquisition time and image quality. By design, Zoom-DWI reduces excitation interference between adjacent slices through selective slice excitation and the introduction of interslice gaps, which may prolong acquisition time. However, at a high PR (66.6%), Zoom-DWI exhibited an approximately threefold higher SNR than Parallel-DWI, equivalent to approximately 10 signal averages.
This finding suggests that the number of signal averages required for Zoom-DWI is reduced while maintaining comparable image quality, thereby partially or fully offsetting the increased acquisition time associated with its sequence design. In contrast, increasing signal averages beyond this level in Parallel-DWI is unlikely to substantially improve SNR because DWI relies on image averaging rather than repeated acquisition of raw diffusion data, providing limited noise reduction without additional diffusion information.
Thus, the high SNR achieved with Zoom-DWI is not solely attributable to signal averaging but reflects intrinsic advantages in its acquisition and reconstruction strategy. This finding highlights its potential for efficient clinical implementation despite longer nominal acquisition times.
Limitations
This study has several limitations. First, all experiments were performed using phantoms without patient data; therefore, the clinical diagnostic performance of Zoom-DWI could not be directly examined. However, the phantom design enabled objective physical assessment independent of biological variability and provides foundational reference data for future clinical studies.
Second, each imaging condition was acquired only once, and formal statistical comparisons based on repeated measurements were not performed. This study was designed as a controlled phantom experiment to enable direct comparison between Zoom-DWI and Parallel-DWI under identical acquisition parameters; therefore, each condition was intentionally acquired once to ensure strict consistency. Nevertheless, measurement variability in this setup is typically within a few percent, substantially smaller than the observed differences in SNR and image uniformity between methods. Therefore, it is unlikely that the main findings can be explained by measurement variability alone. In addition, variability within ROIs used for SNR calculations provides a basic estimate of signal dispersion, supporting measurement stability.
Third, this study was limited to images acquired at a b-value of 0 s/mm2, and higher b-values were not evaluated. Motion-probing gradients were intentionally excluded to simplify the analysis and enable clearer comparison of the physical characteristics between the two sequences.
Future work
Only images acquired at a b-value of 0 s/mm2 were analyzed in this study to eliminate the influence of diffusion weighting and allow direct comparison of the physical characteristics of Zoom-DWI and conventional Parallel-DWI. As a result, diffusion-related properties such as ADC could not be assessed. Future studies incorporating multiple b-values are warranted to examine these diffusion-related characteristics. Furthermore, this study was limited to phantom experiments and did not include clinical imaging or patient validation; therefore, biological factors such as motion and physiological artifacts were not considered. To comprehensively evaluate the clinical applicability of Zoom-DWI and Parallel-DWI, future studies should include patient data, repeated acquisitions, and appropriate statistical analyses.
CONCLUSION
At high PRs, Zoom-DWI demonstrated higher SNR and greater uniformity than Parallel-DWI in the central image region, where the limitations of parallel imaging reconstruction are most pronounced. This phantom study is consistent with previous reports and supports the potential clinical utility of Zoom-DWI.
Ethical approval
The research/study was approved by the Institutional Review Board at Fujita Health University, number HM22-551, dated March 20, 2023.
Declaration of patient consent
Patient’s consent is not required as patients identity is not disclosed or compromised.
Conflicts of interest
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript, and no images were manipulated using AI.
Financial support and sponsorship: Nil.
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