Introduction

Abnormalities of placental development and function underlies many pathologies of pregnancy including preeclampsia and fetal growth restriction^1-3. MR imaging, such as Diffusion-Weighted and Diffusion-Tensor Imaging (DWI/DTI) provide useful information on placental miscrostructure and function^4,5. T2-relaxometry is a newly quantitated non-invasive method to estimate fetal blood oxygenation levels^4,6,7. Although these techniques may provide new insights into placental function, they remain investigational and currently do not have a role in the clinical diagnosis of placental dysfunction. Validating measurements in human placenta in vivo is not possible due to the invasiveness of such tests. The pregnant sheep is a resilient preclinical model of human pregnancy that has provided important understanding about fetal physiology. The multiple sheep placentomes differ from single human placenta, but data from chronic fetal and maternal instrumentation is relevant to study fetoplacental circulation^8,9.

The purpose of this study was to: 1) characterise apparent diffusion coefficient (ADC) and T2 at mid and late gestational age; and 2) use a placentome-specific multi-compartment model to estimate fetal blood oxygen saturation using MRI (FO₂).

Methods

Study Population & MR Imaging
All experimental protocols were reviewed and approved by the Animal Ethics Committee of the South Australian Health and Medical Research Institute and abide by the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes (National Health and Research Council).

At 109-111 (n=10) and 139-141 (n=5) days gestation, singleton pregnant ewes were anesthetised (induction: diazepam (0.3mg/kg), ketamine (7mg/kg); maintenance: 2.5% isoflurane), intubated and ventilated with 1:5L oxygen to air gas mixture (Lyppards, South Australia, Australia) for MRI session on a 3T Siemens Skyra Scanner (Erlangen, Germany)^10,11. Vascular catheters were implanted into the fetal femoral artery. DWI was performed at 7 b‐values $$$\bf b$$$ = (0,10,20,30,50,70,100,200,300,500,600 s.mm^-2) and T2-relaxometry at 10 echo times $$$\bf T_E$$$ = (81, 90, 96, 120, 150, 180, 210, 240, 270, 300 ms). Data was also acquired at b‐value 50 s.mm^-2 and 200 s.mm^-2 for $$$\bf T_E$$$ = (81, 90, 120, 150, 180, 210, 240 ms). DTI was acquired in 30 non-colinear directions at b-values of 50 s.mm^-2 and 100 s.mm^-2 and T_E=69 ms. Voxel resolution was $$$0.9 \times 0.9 \times 0.5$$$ mm.

Placentome Signal-Model
Sheep placentomes comprise a 6-layer epitheliochorial structure with two inter-digitating villous capillary trees; fetal and maternal blood both remain separately intravascular. Based on a previously used model to study human placental perfusion⁴, we defined a sheep-specific placentome model:
$$S({\bf b, T_E}) = S_0 \left[ e^{{\bf -b}d^*}\Big(fe^{-{\bf T_E}R_2^{f_b}} + ve^{-{\bf T_E}R_2^{mb}} \Big) +(1-f-v)e^{-{\bf b}d -{\bf T_E}R_2^{ts}}\right], \hspace{3cm} (1)$$


where $$$S$$$ is the measured MR signal and $$$S_0$$$ is the signal with b=0. The five model parameters are the feto-placenta blood volume fraction $$$f$$$, trophoblast diffusivity $$$d$$$, pseudo-diffusivity $$$d^*$$$, feto-placental blood relaxation $$$R_2^{f_b}=1/T_2^{f_b}$$$ and maternal blood volume fraction $$$v$$$. We used literature-based values for maternal blood relaxation $$$R_2^{ts}$$$ of (150 ms)^-1 and (46 ms)^-1.

Image-Processing
To minimise the effect of motion we used a nonrigid registration¹² and then manually delineated regions of interest (ROIs) containing the placentomes on the first b=0 image with the lowest T_E (ITK-SNAP Version 3.6.0, 2017). We applied log-linear voxel-wise fitting to obtain measurements of T2 and fractional anisotropy (FA). Voxel-wise fitting was performed with a Levenberg-Marquardt algorithm applied to Eq.(1) using in house software developed in MATLAB (MathWorks, Natick). To stabilise the fitting the following constraints were chosen: $$$0 < f< 1$$$ (no units), $$$0 < d < 1$$$(mm²s^-1), $$$0 < d^*<1$$$ (mm²s^-1), $$$0 < T_2^{f_b} < 150$$$ and $$$0 < v < 1$$$ (no units).

Statistical Analysis
Normality was assessed with Shapiro-Wilk test. Two-sample t-test was performed to compare the MRI-derived parameters between mid and late gestation. Significance level was set at 5%.

Results

Fig.2 and Tab.1 summarise the results of the MRI estimated parameters from all sheep. We found no difference in mean ADC between the two gestations. T2 and $$$T_2^{f_b}$$$ are consistent with a highly perfused and saturated tissue and found to significantly decrease at late gestation (P=0.035 and P=0.02). This suggests that it is related to the radial blood flow component of sheep placentome. There was a significant difference in mean FO₂ between mid and late gestation (P=0.02). Significantly higher $$$f$$$ was measured in late gestation placentomes that also had a significantly higher fractional anisotropy when compared to the earlier gestational age (P=0.038 and P=0.029). Values of $$$f$$$ from the sheep-placentome model were high in comparison to human placenta. We found no difference in mean $$$v$$$ but values were comparable to human placenta⁴.

Discussion

We performed DWI, DTI and T2-relaxometry in sheep placental tissue. We have also shown the first application of multi-compartment MRI model to the sheep placenta and show it can extract information about the oxygen status of the fetus. Although sheep placentomes are different in appearance to the human single placenta, they play a similar role maintaining two separated blood supplies in close proximity in order to facilitate exchange of oxygen and nutrients.

Conclusion

We presented how multi-compartment modelling of placental MRI can be used to estimate the FO₂ and characterised the diffusion properties of placentomes in uncomplicated pregnancy at mid and late gestation. Future work will investigate how these properties change in pregnancies with placental dysfunction.

Acknowledgements

This research was supported by the Wellcome Trust (210182/Z/18/Z, 101957/Z/13/Z, 203148/Z/16/Z) and the EPSRC (NS/A000027/1) and an ARC Future Fellowship (Level 3; FT170100431) to JLM.