Automatic differentiation of placental perfusion compartments by time-to-peak analysis in mice.

INTRODUCTION: The aim of this study was to develop an automatic differentiation of two perfusion compartments within the mouse placenta based on times of maximal contrast enhancement for a detailed and reproducible perfusion assessment. METHODS: Placentas (n = 17) from pregnant BALB/c mice (n = 10) were examined in vivo at 7T on gestation day 16.5. Coronal dual-echo 3D T1-weighted gradient-echo sequences were acquired after application of contrast agent for dynamic MRI. An adapted gamma variate function was fitted to the discrete concentration time curves to evaluate the effect of noise on perfusion and segmentation results. Time-to-peak maps based on fitted and discrete curves of each placenta were used to classify each voxel into the high- or low-blood flow compartment using k-means clustering. Perfusion analysis was performed using the steepest slope model and also applied to fitted and discrete curves. Results were compared to manually defined compartments from two independent observers using the Dice coefficient D. RESULTS: Manually defined placental areas of high-flow and low-flow were similar to the automatic segmentation for discrete (D = 0.76/0.75; D = 0.76/0.79) and fitted (D = 0.80/0.80; D = 0.81/0.82) concentration time curves. Mean perfusion values of discrete and fitted curves ranged in the high-flow compartment from 134 to 142 ml/min/100 ml (discrete) vs. 138-143 ml/min/100 ml (fitted) and in the low-flow compartment from 91 to 94 ml/min/100 ml (discrete) vs. 74-82 ml/min/100 ml (fitted). DISCUSSION: Our novel approach allows the automatic differentiation of perfusion compartments of the mouse placenta. The approach may overcome limitations of placental perfusion analyses caused by tissue heterogeneity and a potentially biased selection of regions of interest.

Application of the steepest slope model reveals different perfusion territories within the mouse placenta.

OBJECTIVES: The steepest slope model is a numerically robust and fast method for perfusion quantification. The purpose of this study was to evaluate if the steepest slope model can be used for quantifying placental perfusion in mice based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) datasets. MATERIAL AND METHODS: T1-weighted DCE MRI was performed in 5 pregnant BALB/c mice on gestation day (gd) 14.5 and in 5 mice on gd 16.5 using a 7T small animal MRI scanner. The placentas were manually delineated in the DCE datasets and the arterial input function (AIF) was selected from the kidney hilus. Placental perfusion was determined on a voxel-by-voxel basis using the steepest slope model. Perfusion was averaged over the entire placenta as well as separately calculated for the high-flow compartment within the central labyrinth zone and for the remaining low-flow placenta tissue. The AIF selection was independently performed by two observers for assessment of inter-observer differences. RESULTS: Mean perfusion on gd 14.5 was 135 ml/min/100 ml (standard deviation SD: 29 ml/min/100 ml placenta) and 112 ml/min/100 ml on gd 16.5 for the whole placenta (SD: 32 ml/min/100 ml). Perfusion in the high flow compartment in the central labyrinth was significantly higher (p ≤ 0.002) than in the low-flow compartment including the remaining placenta tissue: 184 ml/min/100 ml (SD: 39 ml/min/100 ml) vs. 119 ml/min/100 ml (SD 28 ml/min/100 ml) on gd 14.5 and 158 ml/min/100 ml (SD: 58 ml/min/100 ml) vs. 114 ml/min/100 ml (SD: 52 ml/min/100 ml of placenta) on gd 16.5. The mean relative inter-rater observer difference was 6%. CONCLUSION: The steepest slope model is a computationally simple method, which allows perfusion quantification in the mouse placenta. Furthermore, the results of this work indicate that the different placental compartments should be analyzed separately to prevent biased results due to averaging.