Archana Vadiraj Malagi1, Arjun Lokesh2, Esha Baidya Kayal1, Kedar Khare3, Virendra Kumar4, Chandan J. Das2, and Amit Mehndiratta1,5
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2Department of Radiodiagnosis, All India Institute of Medical Sciences Delhi, New Delhi, India, 3Department of Physics, Indian Institute of Technology Delhi, New Delhi, India, 4Department of Nuclear Magnetic Resonance (NMR), All India Institute of Medical Sciences Delhi, New Delhi, India, 5Department of Biomedical Engineering, All India Institute of Medical Sciences Delhi, New Delhi, India
Synopsis
Currently in countries with poor resources availability of higher magnetic strength 3T MRI is low. Objective is to analyze whether with lower magnetic strength 1.5T MRI with advanced parameter reconstruction method can perform better or equivalent to 3T MRI. IVIM-DKI signal was modelled using hybrid (HY) model which produces non-physiological inhomogeneity in parameter map. This inhomogeneity can be corrected by using total variation penalty function (TV) with HY model. IVIM-DKI maps obtained from HY with TV produced more clinically reliable than HY model. Even with low magnetic strength i.e. 1.5T, overall HY+TV model outperformed qualitatively & quantitatively against 3T MRI results.
Introduction
Intravoxel incoherent
motion and Diffusion kurtosis Imaging(IVIM-DKI) provides quantitative information
on microstructural, microvasculature and heterogeneity in Prostate cancer(PCa)1,2. IVIM-DKI signal can be modelled using hybrid
model(HY) which is combination of biexponential(BE) IVIM and DKI model3. Hybrid IVIM-DKI
model suffers from two main challenges: Firstly, parameter map obtained from HY
model are prone to local inhomogeneity which can be corrected using parameter
reconstruction method such as Total Variation(TV)4 penalty function
which provides adaptive spatial homogeneity by removing spurious values in the
image3,5.
Secondly, in countries
with low resource settings such as India there is big problem against availability and accessibility of MRI with higher magnetic strength6. Most commonly used magnetic strength in
prostate MRI are 1.5T and 3T, where latter provides high SNR and also suffers
from artifact due to susceptibility and signal heterogeneity7. Therefore, our
aim of this study is to evaluate differences in IVIM-DKI parameter maps obtained
from 1.5T and 3T with parameter reconstruction method using TV. And to investigate
whether 1.5T with parameter reconstruction(TV) and HY model can provide better or equivalent clinically interpretable parameter map.Methods
Clinical Data acquisition:
A total of 20 male patients with biopsy proven PCa were recruited, 10 patients(age: 63±4.83 years) were scanned in 1.5T MRI(Achieva; Philips Healthcare, Best, the Netherlands) and 10 patients(age:66.1±5.65 years) were scanned in 3T MRI(Ingenia; Philips Healthcare, Best, the Netherlands) at AIIMS, New Delhi, India, with a standard MRI protocol, including IVIM-DKI with 13b-values=0,25,50,75,100,150,200,500,800,1000,1250,1500,2000s/mm2 using phased-array surface coil(1.5T: TR=5.774s,TE=0.081s; 3T: TR=4.899s,TE=0.094s). T2-weighted imaging was also acquired on both the MRI system with TR=3.863s and TE=0.09s in 1.5T and TR=3.727s and TE=0.1s in 3T.
Analysis: Parameter estimation
in clinical data were performed using in-house toolbox in MATLAB. HY model is defined
below3:
$$\frac{S}{S_0}=f\exp(-bD^{*} )+(1-f)\exp(-bD+\frac{1}{6} b^{2} D^{2} k)$$
where S and S0
are diffusion signals with and without diffusion gradient b in s/mm2, respectively. D, D*, f and k are molecular diffusion and pseudo-diffusion coefficient, perfusion fraction and kurtosis parameter respectively. All data were processed using both HY and
hybrid-model+TV(HY+TV). Non-linear least square optimization was used for both HY
and HY+TV. In HY+TV model, image gradient was obtained and this was used to
update the parameter values with TV parameters(alpha and beta) set to 0.01 and
0.996.
ROI localization:
For tumor ROI, DWI at b=2000s/mm2 (hyperintense) and ADC map (hypointense)
was used to localize tumor. Healthy peripheral zone(PZ) was drawn on b=0 s/mm2
image as shown in Figure1. Both the ROIs
were validated by radiologist with three years’ experience on prostate.
Statistics:
For estimating accuracy and precision of parameter maps, coefficient of
variation(CV) for individual parameters and combined CV(CVcombined) for
a method was obtained by averaging all CV of IVIM-DKI parameters. Two sample
t-test(unpaired) for computation of any significant differences(p<0.05)
between HY and HY+TV performance and 1.5T and 3T.Results
Performance of HY and
HY+TV in 1.5T and 3TMRI:
In tumor and healthy PZ
region, HY+TV model showed low CVcombined by 106.23% and
111.54% decrease against HY model for 1.5T and 3T respectively as shown in
figure2. Figure3 shows IVIM-DKI
parameter maps of two representative patients with PIRADS 4 PCa. Qualitatively,
parameter maps obtained from HY+TV model appear more homogenous with low
spurious values in both 1.5T and 3T. Tumor in both 1.5T and 3T results
appears hypointense in D and f map whereas in D* and k it appears
hyperintense. Table1 shows in tumor, D*, and k parameters shows higher values, whereas D and f values are low in
tumor against healthy PZ in both MRI.
Comparison of performance
between HY+TV model in 1.5T with HY model in 3T MRI:
For 1.5T, HY+TV model
showed low CVcombined as compared to HY model for 3T by
111.49% decrease with p<0.001. Even in parameter-wise comparision
HY+TV model performed better using 1.5T IVIM-DKI images. For tumor region, D, D*,
f and k parameter with HY+TV model(1.5T) showed lower CV by 49.42%,
225.21%, 82.39%, and 83.54% decrease against HY model(3T)
respectively as shown in table2. Similar trend was observed for healthy PZ region with overall low
CV of HY+TV model.Discussion
IVIM-DKI images analyzed
using hybrid model producing parametric map; which were susceptible to noise
and had non-physiological inhomogeneity in 1.5T and 3T MRI. This was corrected
by HY+TV with significantly lower CV in all IVIM-DKI parameters, as it reduces
abrupt variations in parameter values for both MR strength systems. We
demonstrated that even with low magnetic strength i.e. 1.5T, overall HY+TV qualitatively
& quantitatively outperformed with clinical interpretable parameter maps
and showed low CV as compared to 3T results with HY model.
Quantitative values of parameter maps obtained from HY+TV model were comparable to literatures8–10. Hypointensity was
observed in ADC, D and f parameter maps due to high cellularity in tumor
causing obstruction in diffusion and perfusion. Whereas, k parameter showed
hyperintense region due to high tissue heterogeneity in tumor. D* parameter
showed very high CV obtained from both model and thus it becomes difficult to
interpret the clinical utility. Conclusion
Better clinical interpretability and accurate quantification of DWI-IVIM parameter maps, HY+TV might be used for diagnosis and planning surgery of prostate cancer patients. Accurate and comparable parametric maps can be obtained from 1.5T with HY+TV.Acknowledgements
This study was supported by IIT Delhi and AIIMS Delhi. AVM was supported by research fellowship fund from Ministry of Human Resource Development, Government of India.References
1. Le Bihan D. et al. Separation of diffusion and perfusion in intravoxel
incoherent motion MR imaging. Radiology.1988;168:497–505.
2. Jensen J H, Helpern J A, Ramani A. et al. Diffusional Kurtosis
Imaging : The Quantification of Non- Gaussian Water Diffusion by Means of
Magnetic Resonance Imaging. Magn Reson Med.2005;1440:1432–1440.
3. Wu W C, Yang S C, Chen Y F, Tseng H M. et al. Simultaneous assessment
of cerebral blood volume and diffusion heterogeneity using hybrid IVIM and DK
MR imaging: initial experience with brain tumors. Eur. Radiol.2017;27:306–314.
4. Rudin L I, Osher S & Fatemi E. Nonlinear total variation based
noise removal algorithms. Phys. D nonlinear Phenom.1992;60:259–268.
5. Kayal E B et al. Quantitative Analysis of Intravoxel Incoherent Motion
(IVIM) Diffusion MRI using Total Variation and Huber Penalty Function. Med.
Phys.2017;44:5849–5858.
6. Jankharia G R. Commentary-radiology in India: the next decade. Indian
J. Radiol. Imaging.2008;18:189.
7. Mazaheri Y, Vargas H A, Nyman G et al. Image artifacts on prostate
diffusion-weighted magnetic resonance imaging: trade-offs at 1.5 Tesla and 3.0
Tesla. Acad. Radiol.2013;20:1041–1047.
8. Zhang Y D. et al. The histogram analysis of diffusion-weighted
intravoxel incoherent motion (IVIM) imaging for differentiating the gleason
grade of prostate cancer. Eur. Radiol.2015;25:994–1004.
9. Shinmoto H. et al. An intravoxel incoherent motion diffusion-weighted
imaging study of prostate cancer. Am. J. Roentgenol.2012;199:496–500.
10. Tamura C. et al. Diffusion kurtosis imaging study of prostate cancer:
preliminary findings. J. Magn. Reson. Imaging.2014;40:723–729.