A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Abstract

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

Maturation-informed synthetic Magnetic Resonance Images of the Developing Human Fetal Brain

“…In this context, we demonstrated that synthetic, yet realistic data can efficiently complement scarce clinical datasets, providing valuable support fot data-demanding deep learning (DL) models for fetal brain MRI tissue segmentation [26][27][28] , as well as the optimization of advanced reconstruction techniques 26,[29][30][31] . These exploratory studies were based on the first Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN) that simulates as closely as possible the FSE sequences used in clinical routine for fetal brain examination to generate realistic T2w images of the fetal brain throughout maturation from a variety of segmented HR anatomical images of healthy and pathological subjects 26 . Despite a good tissue contrast, the synthetic T2w MR images used in this work were originally derived from a three-class model of the fetal brain (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF)) that does not allow to capture key maturation processes and metabolic changes occurring in WM tissues across gestation.…”

“…In the wake of this first prototype 32 , the proposed data descriptor showcases a full dataset of highly realistic in silico data composed of: i) 594 synthetic T2w MR images corresponding to 78 developing fetal brains, derived from HR annotations of SRreconstructed, real clinical data acquired on various MR scanners and following the different clinical protocols in place at Lausanne University Hospital (CHUV) and at University Children's Hospital Zurich (Kispi); ii) automatically-generated brain masks and fetal brain annotations of the LR series;…”

“…Due to the lack of characterizations or normative maps of T 1 and T 2 relaxometry measurements of fetal brain structures, all tissues from the segmented fetal brain images are merged into three main classes: GM, WM and CSF. According to previous 2/15 empirical relaxometry values provided in the literature [37][38][39][40][41] , an average T 1 , respectively T 2 value is assigned to each of these classes, without consideration of the GA or spatial a priori on the finer location within the brain 26 (see Figure 3-(A)).…”

“…As routinely performed in clinical practice, two partially overlapping LR series are generated in every orientation for subsequent SR reconstruction of the fetal brain volume. Since the realism of interslice, 3D random rigid movements of the fetus encoded during k-space sampling achieved with FaBiAN v1.2 32 has already been validated 26 , the dataset showcased in this work is generated without additional movement not to induce any bias in the qualitative evaluation of the realism of the generated LR series by the radiologists, but also to make it possible to align SR reconstructions from the simulated images to the corresponding ground truth label maps they originate from. Besides non-standardized MR sequence parameters, only a few studies have investigated T 1 and T 2 properties of the developing brain, either in utero 38,39,41 or in preterm newborns 37,40 .…”

“…Qualitative evaluation of the realism of the simulated low-resolution series 2) 32 and our new numerical WM model (FaBiAN v2.0) 34 . Young fetuses diagnosed with spina bifida prior surgery were excluded from this evaluation as the absence of extra-axial CSF substantially alters the quality of the clinical acquisitions and subsequent simulations.…”