Kaining Shi1, Ying Liu2, Yu Shi2, and Qiyong Guo2
1Imaging Systems Clinical Science, Philips Healthcare, Beijing, China, People's Republic of, 2Radiology department, Shengjing Hospital of China Medical University, Shenyang, China, People's Republic of
Synopsis
Fussy
clustering technique (FCM) has been combined with IVIM to increase the stability
and reduce the post-processing time of the nonlinear curve fitting in IVIM. Another
problem of the widely used bi-exponential IVIM model is its poor repeatability.
This work is to assess the repeatability of IVIM with FCM between two scans in
healthy liver by calculating the coefficient of variation and the 95%
Bland–Altman limits of agreements. Results proved that FCM could improve the
repeatability of IVIM, especially for the parameter D*, which was the most
unstable among total 3 parameters.Introduction
Fussy
clustering technique (FCM) can increase the stability and reduce the
post-processing time of DCE-MRI,
1,2 by sorting all voxels’ time-signal curves
into several types. To address the same problems in the Intravoxel Incoherent Motion
(IVIM) imaging, which is also
sensitive to noise and time-consuming, the FCM has been combined with the
nonlinear curve fitting of IVIM.
3 However, another problem of the
widely used bi-exponential IVIM model is its poor repeatability.
4-5 The purpose
of this work is to measure the repeatability of IVIM with FCM between two scans
in healthy liver, compared with regular pixel by pixel post processing method.
Method
3
female and 2 male young healthy volunteers (24-27 years old) were scanned by a
3T whole body scanner ( Ingenia, Philips Medical System, Best, The
Netherlands). The single-shot spin echo DWI was scanned twice in one exam with
following parameters: TE/TR 73/6000ms, FOV 360x360mm, acquisition matrix
128x189, 24 slices with the thickness of 7mm and 1mm gap, SENSE 3, NSA 2. 8 b
values ( 0, 20, 50, 100, 200, 350, 500, 800) were used.
The
post-process was performed on home-made software. The bi-exponential model6
was employed for the curve fitting: $$S(b)/S(0)=(1-f)\times\exp(-bD)+f\times\exp(-bD*)$$
Mask
was drawn manually to restrict the curve fitting to be performed only in liver
( Fig.1a ). To investigate the effect of cluster numbers, FCM with 20 clusters
and 40 clusters per slice were run respectively. 7 ROIs in total were drawn on
the Couinaud Segments7 2, 3, 4, 5, 6, 7, 8 respectively for each
liver (Fig.1). The repeatability of two scans was assessed by calculating the
coefficient of variation (CV), and the 95% Bland–Altman limits of agreements
(BA-LA) of IVIM derived parameters( D, D* and f) for each post-process method.
The CV was also calculated for all segments.
Result
Three
methods’ results of one volunteer’s two scans are demonstrated in Fig.1. D and
D* is more homogenous with FCM. The mean value, standard deviation and CV of
two scans are listed in Table.1. Both
two FCM methods have lower CV value for the D, compared to the normal method. D*
has the highest CV value in all three methods, while FCM with 20 clusters has
the lowest CV of D*. However, normal pixel-by- pixel method has the lowest CV
of f. The result of BA-LA assessment is shown in Fig.2. The CV of each segment
is listed in Table 2.
Discussion
In
this work, each ROI was saved and used in three methods of both two scans.
Without obvious motion between two scans, this strategy could maintain the area
and location of every ROI and got much better repeatability
than previous work.
4,5 D* had the worst repeatability, which is consistent with
previous reports, while FCM with 20 clusters can improve it with the price of increased
CV of f. However, since the CV of f is much smaller than that of D*and the
increase of f’s CV is much smaller than the decrease of D*’ CV, especially for
those regions with high CV of D*(such as segment 2 and 5), FCM with 20 clusters
improved the total repeatability of IVIM.
Acknowledgements
No acknowledgement found.References
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