Eun Cho1 and Jin Hwa Lee1
1Radiology, Dong-A University Hospital, Busan, Korea, Republic of
Synopsis
We evaluated the clinical
feasibility of the reduced field-of-view diffusion weighted imaging (rFOV DWI)
with computed DWI technique in patients with breast cancer by performing a
comparison and analysis of the inter-method agreement among the acquired rFOV
DWI (rFOVA), rFOV DWI with computed DWI technique (synthetic rFOV DWI; rFOVS),
and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in
patients with breast cancer. We found that the rFOV DWI and rFOV DWI with
computed DWI technique showed nearly equivalent level of image quality required
for analysis of the tumors and lesion conspicuity compared with DCE MRI.
Synopsis
We evaluated
the clinical feasibility of the reduced field-of-view diffusion weighted
imaging (rFOV DWI) with computed DWI technique in patients with breast cancer
by performing a comparison and analysis of the inter-method agreement among the
acquired rFOV DWI (rFOVA), rFOV DWI with computed DWI technique (synthetic rFOV
DWI; rFOVS), and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in patients with breast
cancer. We found that the rFOV DWI and rFOV DWI with computed DWI technique showed nearly
equivalent level of image quality required for analysis of the tumors and
lesion conspicuity compared with DCE MRI.Introduction
Diffusion-weighted imaging
(DWI) is one of the most frequently used magnetic resonance imaging (MRI)
sequences in breast cancer patients. However, bilateral DWI is limited by
magnetic susceptibility and chemical shift artifacts, low signal-to-noise ratio
(SNR), and low resolution.1-3 Therefore, various techniques
have been suggested for minimizing these drawbacks. Reduced field-of-view
(rFOV) DWI can improve the image quality with decreased artifacts and
relatively high SNR and resolution compared to conventional DWI.4-8 And computed DWI technique has recently emerged, which can
improve the SNR and reduce artifacts.9 We focused on the merits of combining the advantages of the
two DWI MRI techniques in the breast cancer patient. We
hypothesized that a high resolution of various b-value images
could be obtained by applying the above two techniques while reducing imaging
acquisition time. Therefore, the purpose of this study was to evaluate the
clinical feasibility of rFOV DWI with computed DWI technique in patients with
breast cancer by performing a comparison and analysis of the inter-method
agreement among the acquired rFOV DWI (rFOVA), rFOV DWI with computed DWI
technique (synthetic rFOV DWI; rFOVS), and DCE MRI.Methods
Totally, 130 biopsy-proven breast cancers from 130
women (age, 34-87 years; mean, 52.7 years) who underwent breast MRI from April
2017 to December 2017 were included. The image-sets of conventional rFOVA and
rFOVS were reviewed and analyzed by comparing with DCE MRI. The rFOVS were
reformatted by calculation of the apparent diffusion coefficient curve obtained
from conventional rFOVA b=0 s/mm2
and b=500 s/mm2. Visual
assessment of the image quality of rFOVA b=1000
s/mm2, rFOVS, and DCE MRI was done using a 4-point grading system. Morphologic
analyses of the shape, margin, and size of the index cancer was performed on rFOVA,
rFOVS and DCE MRI. For quantitative analysis, the signal-to-noise ratio (SNR),
contrast-to-noise ratio (CNR), and contrast of tumor-to-parenchyma (TPC) were
calculated.Results
Image quality scores with rFOVA, rFOVS, and DCE MRI
were not significantly different (P=0.357).
Lesion analysis of shape, margin, and size of the index cancer also did not
show significant differences among the three sequences (P=0.858, P=0.242, and P=0.858, respectively). SNR, CNR, and
TPC of DCE MRI were significantly higher than those of rFOVA and rFOVS (P<0.001, P=0.001, and P=0.016,
respectively). Statistically significant differences were not found between the
SNR, CNR, and TPC of rFOVA and those of rFOVS (P>0.999, P>0.999,
and P>0.999, respectively).Discussion
In this study, we found that morphologic analysis
and size measurement of the tumor could be performed well with rFOV DWI. In
addition, with rFOVS, images equivalent to rFOVA could be obtained even with a
relatively short image acquisition time. These results suggest that using rFOV
DWI with computed DWI technique can provide efficient and accurate analysis of
the breast tumor even with the short image acquisition time.Conclusion
In conclusion, both the rFOV DWI
and rFOV DWI with computed DWI technique showed nearly equivalent levels of
image quality required for analysis of the tumors and for lesion conspicuity
compared with DCE MRI. The rFOV DWI with computed DWI technique especially, has
the potential to have a useful clinical role in morphological evaluation of the
breast tumor due to the relatively short image acquisition time and avoidance
of contrast agent.Acknowledgements
No acknowledgement found.References
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