Quantitative characterization of rodent feto-placental vasculature morphology in micro-computed tomography images

An analysis of the influence of transfer learning when measuring the tortuosity of blood vessels

BACKGROUND AND OBJECTIVE

Convolutional Neural Networks (CNNs) can provide excellent results regarding the segmentation of blood vessels. One important aspect of CNNs is that they can be trained on large amounts of data and then be made available, for instance, in image processing software. The pre-trained CNNs can then be easily applied in downstream blood vessel characterization tasks, such as the calculation of the length, tortuosity, or caliber of the blood vessels. Yet, it is still unclear if pre-trained CNNs can provide robust, unbiased, results in downstream tasks involving the morphological analysis of blood vessels. Here, we focus on measuring the tortuosity of blood vessels and investigate to which extent CNNs may provide biased tortuosity values even after fine-tuning the network to a new dataset under study.

METHODS

We develop a procedure for quantifying the influence of CNN pre-training in downstream analyses involving the measurement of morphological properties of blood vessels. Using the methodology, we compare the performance of CNNs that were trained on images containing blood vessels having high tortuosity with CNNs that were trained on blood vessels with low tortuosity and fine-tuned on blood vessels with high tortuosity. The opposite situation is also investigated.

RESULTS

We show that the tortuosity values obtained by a CNN trained from scratch on a dataset may not agree with those obtained by a fine-tuned network that was pre-trained on a dataset having different tortuosity statistics. In addition, we show that improving the segmentation accuracy does not necessarily lead to better tortuosity estimation. To mitigate the aforementioned issues, we propose the application of data augmentation techniques even in situations where they do not improve segmentation performance. For instance, we found that the application of elastic transformations was enough to prevent an underestimation of 8% of blood vessel tortuosity when applying CNNs to different datasets.

CONCLUSIONS

The results highlight the importance of developing new methodologies for training CNNs with the specific goal of reducing the error of morphological measurements, as opposed to the traditional approach of using segmentation accuracy as a proxy metric for performance evaluation.

Micro-angiogenic patterns around orthodontic implants migrating in bone: A micro-CT study in the rat tail model

AIM

Recent studies revealed that implants can migrate in bone when subjected to continuous loading. Since this process is suspected to be accompanied by bone remodelling, which requires blood vessel formation, the present work aimed at assessing the micro-angiogenic patterns around migrating implants.

MATERIALS AND METHODS

In 16 rats, two customized implants were placed in a single tail vertebra and connected with contraction springs (forces: 0 N, 0.5 N, 1.0 N, 1.5 N). After 2 or 8 weeks of loading, the animals were scanned by micro-CT before and after vasculature perfusion with a silicone rubber. Vessels were segmented by subtraction of the two micro-CT scans. Vessel thickness (V.Th), vessel volume per total volume (VV/TV), and vascular spacing (V.Sp) were assessed in a peri-implant volume of interest (VOI) around each implant.

RESULTS

At 2 weeks of loading, force magnitude was significantly associated with VV/TV and V.Th values (χ²  = 10.942, p < .001 and χ²  = 6.028, p = .010, respectively). No significant differences were observed after 8 weeks of loading.

CONCLUSIONS

Within the limitations of an animal study, peri-implant vessel thickness and density were associated with force magnitude in the early loading phase, whereas effects diminished after 8 weeks of loading.

Investigating the Upstream and Downstream Hemodynamic Boundary Conditions of Healthy and Growth-Restricted Rat Feto-Placental Arterial Networks

The placenta uniquely develops to orchestrate maternal adaptations and support fetal growth and development. The expansion of the feto-placental vascular network, in part, underpins function. However it is unclear how vascular development is synergistically influenced by hemodynamics and how impairment may lead to fetal growth restriction (FGR). Here, we present a robust framework consisting of ex vivo placental casting, imaging and computational fluid dynamics of rat feto-placental networks where we investigate inlet (steady and transient) and outlet (zero-pressure, Murray's Law, asymmetric fractal trees and porous blocks) boundary conditions in a model of growth-restriction. We show that the Murray's Law flow-split boundary condition is not always appropriate and that mean steady-state inlet conditions produce comparable results to transient flow. However, we conclude that transient simulations should be adopted as they provide a larger amount of valuable data, a necessity to bridge the current knowledge gap in placental biomechanics. We also show preliminary data on changes in flow, shear stress, and flow deceleration between control and growth-restricted feto-placental networks. Our proposed framework provides a standardized approach for structural and hemodynamic analysis of feto-placental vasculature and has the potential to enhance our understanding of placental function.

Three-dimensional visualisation of the feto-placental vasculature in humans and rodents

Adequate development of the feto-placental circulation is critical for placental exchange function and healthy fetal growth. Understanding the structure of this circulation and how it informs fetal outcomes is important both in the human placenta, and the rodent, a purported comparative experimental model. Vascular casting and micro-CT imaging approaches enable detailed quantification of the complex vascular relationships in the feto-circulation, and provide detailed data to parameterise in silico models. Here, to assist researchers to apply these technically challenging methods we provide detailed approaches to cast and image; 1) human placentas at the cotyledon-level, and 2) whole rodent placentas.

Multiscale and multimodal imaging of utero-placental anatomy and function in pregnancy

Placental structures at the nano-, micro-, and macro scale each play important roles in contributing to its function. As such, quantifying the dynamic way in which placental structure evolves during pregnancy is critical to both clinical diagnosis of pregnancy disorders, and mechanistic understanding of their pathophysiology. Imaging the placenta, both exvivo and invivo, can provide a wealth of structural and/or functional information. This review outlines how imaging across modalities and spatial scales can ultimately come together to improve our understanding of normal and pathological pregnancies. We discuss how imaging technologies are evolving to provide new insights into placental physiology across disciplines, and how advanced computational algorithms can be used alongside state-of-the-art imaging to obtain a holistic view of placental structure and its associated functions to improve our understanding of placental function in health and disease.

Advances in imaging feto-placental vasculature: new tools to elucidate the early life origins of health and disease

Optimal placental function is critical for fetal development, and therefore a crucial consideration for understanding the developmental origins of health and disease (DOHaD). The structure of the fetal side of the placental vasculature is an important determinant of fetal growth and cardiovascular development. There are several imaging modalities for assessing feto-placental structure including stereology, electron microscopy, confocal microscopy, micro-computed tomography, light-sheet microscopy, ultrasonography and magnetic resonance imaging. In this review, we present current methodologies for imaging feto-placental vasculature morphology ex vivo and in vivo in human and experimental models, their advantages and limitations and how these provide insight into placental function and fetal outcomes. These imaging approaches add important perspective to our understanding of placental biology and have potential to be new tools to elucidate a deeper understanding of DOHaD.