Fractional Enhancement metric improves SNR and visualisation of quantitative two-point contrast-enhanced MRI in retroperitoneal sarcoma

Matthew David Blackledge^{1}, Christina Messiou^{1,2}, Jessica M Winfield^{1,2}, Dow Mu Koh^{1,2}, David J Collins^{1,2}, and Martin O Leach^{1,2}

Volumetric, large field-of-view contrast enhanced MRI typically involves only two MR measurements: One before contrast administration, S1, and another, S2, at some time $$$t$$$ when equilibrium of contrast is expected. To provide quantification of tissue enhancement in these cases, it is common to calculate the relative enhancement, $$$\epsilon_{R}$$$, at each voxel location: $$ \epsilon_{R} = \frac{S_{2} - S_{1}}{S_{1}}$$ Another possibility is to compute the fractional enhancement, $$$\epsilon_{F}$$$: $$ \epsilon_{R} = \frac{S_{2} - S_{1}}{S_{1} + S_{2}}$$

It can be shown that both quantitative parameters are monotonically increasing with increasing contrast agent concentration. Furthermore, both parameters are independent of T2*-weighting, proton density and coil sensitivity, improving their performance as quantitative metrics. However, little work has been done to investigate the statistical properties of these parameters and how this may affect clinical interpretation of contrast enhancement studies.

**Patients:** Twenty-five patients with
retroperitoneal sarcoma were imaged as part of a prospective single-centre
study including: 21 well-differentiated/dedifferentiated
liposarcomas, 3 leiomyosarcomas and 1 lipoma. All patients provided written consent prior to
their involvement in this study.

**Imaging:**
T1-weighted
imaging was acquired before and 4 minutes after the administration of gadolinium-based
contrast (Dotarem, 0.2 ml/kg boy weight administered at 2 ml/s using a power
injector) ensuring that the field of view covered the entire tumour in each
patient. We used a 3D FLASH sequence
with 17° flip angle ($$$\alpha$$$), repetition time (TR) = 3.8ms and echo time
(TE) = 1.06ms on a 1.5T machine (Aera, Siemens Healthcare, Germany).

**Simulations:** We investigated the response of
enhancement parameters, $$$\epsilon_{R}$$$
and $$$\epsilon_{F}$$$, by calculating the expected values as a function of contrast
agent, [CA], over the range 0-5 mM in the absence of noise. We use the standard formulae for T1w signal
intensity:

$$ \text{S}_{1}(\text{TR}, \alpha) = \text{S}_{0}\sin (\alpha)\frac{1 - \text{E}_{1}}{1-\cos (\alpha)\text{E}_{1}}, \quad \text{E}_{1} = \exp \left\{-\text{TR}\cdot\text{R}_{1}\right\}$$

$$ \text{S}_{2}(\text{TR}, \alpha) = \text{S}_{0}\sin (\alpha)\frac{1 - \text{E}_{1}\text{E}^{\Delta}_{1}}{1-\cos (\alpha)\text{E}_{1}\text{E}^{\Delta}_{1}}, \quad \text{E}^{\Delta}_{1} = \exp \left\{-\text{TR}\cdot\Delta\text{R}_{1}\right\}, \quad\Delta\text{R}_{1} = r_{1}\text{[CA]}$$

We matched all parameters in these simulations with those used for clinical imaging, matching the relaxivity of the contrast agent used ($$$r_{1} = 3.6 \text{ L mmol}^{-1}\text{ s}^{-1}$$$ [1]), over a range of plausible tissue T1-values (0.1-1.5 ms). We repeated these calculations but with the inclusion of Rician noise [2] at different SNRs ($$$\sigma_{0}$$$ = 20, 50, 80, 110, 140 and 170) for the base signal intensity, $$$\text{S}_{0}$$$. This simulation was repeated 105 times so that estimates of SNR for each of the enhancement parameters, $$$\epsilon_{R}$$$ and $$$\epsilon_{F}$$$, could be calculated over a range of T1 and [CA] values.

**
Image analysis:** A clinical radiologist with 15 years
experience in MR-imaging compared volumetric datasets of calculated enhancement parameters, $$$\epsilon_{R}$$$ and $$$\epsilon_{F}$$$, in
all 25 patients. Images were
viewed side-by-side on a multi-planar-reformat workstation (OsiriX,
Switzerland); the radiologist was blinded to the method used ($$$\epsilon_{R}$$$ or $$$\epsilon_{F}$$$). For each of the following subjective criteria:
(i) Overall contrast-to-noise, (ii) signal-to-noise, (iii) detection
of disease, (iv) image artefacts and (v) within-lesion contrast, the
radiologist decided whether one method was preferred over the other, or whether
they tied.

[1] Rohrer, M., Bauer, H., Mintrovitch, J. et al. “Comparison of Magnetic Properties of MRI Contrast Media Solutions at Different Magnetic Field Strengths”, Investigative Radiology, 40(11), 2005

[2] Gudbjartsson, H. and Patz, S. “The Rician Distribution of Noisy MR data”, Mag. Reson. Med., 34(6), 1995.

Simulation plots for relative enhancement (left)
and fractional enhancement (right) in the absence of noise over a range of
contrast agent concentrations and intrinsic tissue T1 values. Note that both indices are monotonically
increasing as a function of concentrations and T1. It may be noted that relative enhancement
appears to change more uniformly as a function of T1 and concentration.

Simulation plots for relative enhancement (left)
and fractional enhancement (right) for six different SNR values of $$$\text{S}_{0}$$$. Note that as $$$\sigma_{0}$$$ becomes low ($$$\sigma_{0}$$$
< 80), the relative enhancement is confounded by the presence of multiple
noise outliers, making it difficult to visualise the differences due to
intrinsic tissue T1 value and/or contrast agent concentration.

Plots of SNR for relative enhancement (red) and fractional enhancement (green) for six different SNR values for $$$\text{S}_{0}$$$. Note that the SNR of the fractional enhancement outperforms its counterpart in all cases and over all contrast agent concentrations and underlying tissue T1 values.

Results from radiological assessment of relative
enhancement fraction $$$\epsilon_{R}$$$ against fractional enhancement $$$\epsilon_{R}$$$
in 25 patients with retroperitoneal sarcoma.
Results that are statistically significant (p<0.005, exact
multinomial test) are indicated with a double asterisk (**).

Examples of relative enhancement (left) and
fractional enhancement maps (right) for two patient examples from the sarcoma
study. Note that windowing of the
fractional enhancement is much easier due to the absence of possible noise
outliers and allows the clinician to visualise the underlying tumour
heterogeneity without the presence of signal saturation (red arrow).

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

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