Lei Qin^{1}, Daniel I Glazer^{2}, Pelin Aksit Ciris^{2}, Andriy Fedorov^{2}, Thiele Kobus^{3}, Fiona M Fennessy^{1,2}, Stephan E Maier^{2}, and Robert Mulkern^{4}

Intravoxel Incoherent Motion (IVIM) DWI was acquired with 13
b-values, ranging from 0 to 250 s/mm^{2}. With such low b-values, a
short TE results in a better signal-to-noise ratio. Monoexponential fitting was
performed to obtain ADC, and biexponential fitting was performed to obtain
diffusion D, perfusion fraction f, and perfusion related
pseudo-diffusion coefficient D*. In a prostate cancer (PCa)
patient cohort, we only found a significant difference between normal and tumor
tissue for D, which was absent in ADC,
f, and D*.
This suggests that IVIM biexponential analysis can help remove perfusion
component from diffusion, leading to a more accurate measurement in diffusion
coefficient.

INTRODUCTION

Diffusion weighted imaging (DWI) is used to help diagnose and stage prostate cancer. In the peripheral zone, where the majority of PCa occurs, conventional mono-exponential fitted apparent diffusion coefficient (ADC) values of cancer are generally lower than normal tissue. Intravoxel incoherent motion (IVIM) DWI was introduced to separate diffusion and perfusion componentsMETHODS

This was a prospective study approved by the local
institutional review board. Fifteen patients with PCa were
recruited in the study. All had tumors in the peripheral zone (PZ). DWI
acquisition was performed at 3T (General Electric) using an endorectal coil. A
single-shot spin-echo echo-planar imaging sequence, with TR 4000ms, TE 52ms, one
signal average, acquisition matrix 64*64, and thirteen b-values 0, 10, 20, 30,
40, 50, 60, 70, 80, 90, 100, 120, 250 s/mm^{2} along three orthogonal
directions was used for diffusion imaging. A
radiologist fellowship trained in abdominal imaging defined two regions of
interest (ROIs) on each patient’s b=250 s/mm^{2} image, one inside
the index lesion and the other within contralateral normal PZ tissue.
Conventional monoexponential fitting was performed to obtain ADC using all
b-values. Biexponential fitting was also performed to obtain perfusion and
diffusion parameters respectively. The biexponential IVIM function is defined
as:

S_{b}=S_{0}·[f·exp(-bD*)+(1-f)·exp(-bD)]

where D is the true diffusion, D* is perfusion-related pseudo-diffusion coefficient, and f is the perfusion fraction. The fitting was carried out in the following steps:

1. Monoexponential
fitting of the two largest b-values 120 and 250 s/mm^{2 }to obtain an
initial D, where the contribution
from pseudo-diffusion to the total signal is expected to be less than 0.1%. Extrapolate
the signal to all b-values to obtain S_{D}=S_{0}·(1-f)·exp(-bD) , where S_{D }denotes diffusion component of the signal.

2. Subtract
measured signal S_{b} from S_{D} to obtain perfusion component, S_{D*}=S_{b}-S_{D}=S_{0}·f·exp(-bD*). Because this is a
monoexponential decay, we can obtain D* from the subtracted signal S_{D*}, and the intercept is S_{0}''=S_{0}·f.

3. Subtract S_{D*} from S_{b} to obtain diffusion component, S_{D}=S_{b}-S_{D*}=S_{0}·(1-f)·exp(-bD) . Because this is a
monoexponential decay, we can refine the initial D from the subtracted signal S_{D} , and the intercept is S_{0}'=S_{0}·(1-f).

4. Go
back to step 2 until the change in fitted S_{D}+S_{D*} is negligible.

5. Calculate f= S_{0}''/(S_{0}''+S_{0}').

Paired t-tests were used to compare diffusion and perfusion parameters between normal and tumor tissues. Statistical significance was considered at p<0.05. Fitting with the iterative linear method and statistical analyses were all performed using in-house software developed with Matlab R2013b (Mathworks Inc, Natick, MA).

RESULTS

Figure 1 shows example ROI for normal and tumor tissue with corresponding measured mean signal inside the ROI respectively. The final fitted curve plotted on a logarithmic scale does not deviate from a straight line at low b-values, suggesting that the perfusion component in the measured signal is very small. Diffusion D is different between two tissues whereby tumor has a smaller D than normal tissue. In the patient data shown, the perfusion fraction is the same for both tissues, i.e., f=0.071. Figure 2 shows the boxplots of the diffusion and perfusion parameters in the 15 patients. D is smaller than ADC for both tissues. The difference between normal and tumor tissues is only significant in D (DISCUSSION

Different b-values have been used for IVIM acquisitions with large ranges of diffusion and perfusion parameters reportedCONCLUSION

IVIM biexponential analysis can help extract the perfusion component from the diffusion coefficient, leading to a more accurate measurement of the latter in the setting of PCa.1. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 1988;168: 497-505.

2. Riches SF, Hawtin K, Charles-Edwards EM, de Souza NM. Diffusion-weighted imaging of the prostate and rectal wall: comparison of biexponential and monoexponential modelled diffusion and associated perfusion coefficients. NMR in Biomedicine. 2009;22: 318-325.

3. Pang Y, Turkbey B, Bernardo M, et al. Intravoxel incoherent motion MR imaging for prostate cancer: an evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations. Magn Reson Med. 2013;69: 553-562.

4. Mulkern RV, Barnes AS, Haker SJ, et al. Biexponential Characterization of Prostate Tissue Water Diffusion Decay Curves Over an Extended b-factor Range. Magnetic Resonance Imaging. 2006;24: 563-568.

5. Ueda Y, Takahashi S, Ohno N, et al. Triexponential function analysis of diffusion-weighted MRI for diagnosing prostate cancer. J Magn Reson Imaging. 2016;43: 138-148.

Figure 1. Example ROI of normal and tumor tissue, and the
corresponding DWI signal on logarithmic scale. Normal tissue is in blue, tumor
tissue is in red.

Figure 2. Boxplots of ADC,
D, f , and D* of normal and tumor tissues
from all patients in the study cohort. The number on top of each box is mean ±
standard deviation.