Development-driven Diffusion Model for Longitudinal Prediction of Fetal Brain MRI with Unpaired Data

Longitudinal magnetic resonance imaging (MRI) is essential for studying the early development of the brain, as it allows to observe and analyze how the brain changes over time. Unfortunately, existing cohort research suffers from lacking sufficient MRI data for studying the development of fetal brains. Apart from research data, a viable alternative is the use of large-scale clinical fetal brain MRI data, which is currently the primary source for longitudinal studies. Although clinical data has several benefits, it is impeded by the inherent drawback of incomplete data. In the context of clinical practice, nearly all subjects undergo only one MRI scan throughout their entire pregnancy, resulting in a lack of longitudinal data for any fetus. To address this issue and obtain longitudinal clinical fetal brain MRI data, we propose to generate MR images for two adjacent gestational weeks (GWs) within one subject, thereby bridging the information gap between three consecutive GWs. This fetal MRI prediction task suffers from two significant challenges, including 1) heterogeneous generation and 2) the lack of paired training data at adjacent GWs. To tackle these two challenges, we propose a new approach, called the Development-driven Diffusion Model (DDM). Specifically, our approach first involves training a conditional diffusion model using population development information spanning all GWs. This allows the model to generate images at various GWs. Next, during the inference stage, we incorporate individual development information of a specific subject using a specially designed perception feature guidance module. The DDM enables the generated 3D MR images to encompass both the general characteristics representative of the targeted GWs, as well as the distinct feature specific to each individual. To assess the efficacy of our approach, extensive experiments were carried out on a large-scale clinical dataset obtained from three different medical centers. The experimental results unequivocally establish the effectiveness of DDM for generating longitudinal MR images of fetal brains.