Novel Strategy for Quantitative Analysis of IVIM Diffusion MRI in Ewingâ€™s Sarcoma Family of Tumours

Esha Baidya Kayal^{1}, Devasenathipathy K^{2}, Kedar Khare^{3}, Jayendra Tiru Alampally^{2}, Sameer Bakhshi^{4}, Raju Sharma^{2}, and Amit Mehndiratta^{1,5}

IVIM dataset from four patients (M:F=3:1, Age=25.3± 8.8 years), with Ewing sarcoma were acquired under the Institutional Review Board approved protocol. The acquisition were performed using 1.5T Philips Achieva MRI scanner with Spin Echo Planar imaging (SP-EPI) sequence with TE=66msec,TR= 1782msec, 5mm slice thickness and 144x144 matrix size. The DW images were acquired at 11 b-values (0, 10, 20, 30, 40, 50, 80, 100, 200, 400, 800 s/mm2). For one patient DWI images were acquired again after 2 cycles of chemotherapy. Thus in total five IVIM datasets were processed. Apparent diffusion coefficient (ADC) was estimated using mono-exponential fit for b≥ 200s/mm2. The IVIM datasets were analysed using four methods: i) Bi-Exponential (BE) model, ii) BE model with Total Variation (TV) penalty [3] (BE+TV), iii) BE model with Huber Penalty function [4] (BE+HPF) and iv) freeware Osirix. Three analysis methods, BE, BE+TV and BE+HPF, were implemented in an in-house built analysis toolbox implemented in MATLAB. An iterative optimization was performed using a nonlinear least square fitting algorithm along with the penalty functions.

Due to the nature of the data, the BE solution using simple optimization as well as that using Osirix package, might be highly noisy. In order to obtain physiologically meaningful solution we include gradient based penalties such as Total Variations [3] and Huber function [4] in our optimization model. Coefficient of determination (R2) was calculated to measure the goodness of fit for the four methods, using the in-vivo IVIM data and the best fitted signal with the model. R2 varies between 0 to1; values close to 0 being a poor and close to 1 a good model fit.

R2 values for four analysis
methods used for IVIM analysis in-vivo.

a. DWI
(b=800s/mm2), red circle shows the tumour ROI; b. Mean signal fit to tumour
using four methods showing both BE+TV and BE+HPF having a better fit.

Showing parametric Map of Diffusion coefficient (D), Perfusion
coefficient (D*), Perfusion fraction (f) for one representative patient
with Ewing sarcoma evaluated with four IVIM analysis methods. Parametric maps
with BE+TV and BE+HPF showing less image noise.

a,f) DWI image (b=800s/mm2);
b,g) ADC map; c,h) Diffusion coefficient (D); d,i) Perfusion coeffieicnt (D*);
e,j) Perfusion fraction (f) for one representative patient. a-e) baseline; f-j)
follow-up after 2 cycles of chemotherapy. Shows increase in perfusion fraction in
tumour post chemotherapy.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)

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