Image-to-Graph Convolutional Network for 2D/3D Deformable Model Registration of Low-Contrast Organs

Organ shape reconstruction based on a single-projection image during treatment has wide clinical scope, e.g., in image-guided radiotherapy and surgical guidance. We propose an image-to-graph convolutional network that achieves deformable registration of a three-dimensional (3D) organ mesh for a low-contrast two-dimensional (2D) projection image. This framework enables simultaneous training of two types of transformation: from the 2D projection image to a displacement map, and from the sampled per-vertex feature to a 3D displacement that satisfies the geometrical constraint of the mesh structure. Assuming application to radiation therapy, the 2D/3D deformable registration performance is verified for multiple abdominal organs that have not been targeted to date, i.e., the liver, stomach, duodenum, and kidney, and for pancreatic cancer. The experimental results show shape prediction considering relationships among multiple organs can be used to predict respiratory motion and deformation from digitally reconstructed radiographs with clinically acceptable accuracy

2D/3D Deep Image Registration by Learning 3D Displacement Fields for Abdominal Organs

Deformable registration of two-dimensional/three-dimensional (2D/3D) images of abdominal organs is a complicated task because the abdominal organs deform significantly and their contours are not detected in two-dimensional X-ray images. We propose a supervised deep learning framework that achieves 2D/3D deformable image registration between 3D volumes and single-viewpoint 2D projected images. The proposed method learns the translation from the target 2D projection images and the initial 3D volume to 3D displacement fields. In experiments, we registered 3D-computed tomography (CT) volumes to digitally reconstructed radiographs generated from abdominal 4D-CT volumes. For validation, we used 4D-CT volumes of 35 cases and confirmed that the 3D-CT volumes reflecting the nonlinear and local respiratory organ displacement were reconstructed. The proposed method demonstrate the compatible performance to the conventional methods with a dice similarity coefficient of 91.6 \% for the liver region and 85.9 \% for the stomach region, while estimating a significantly more accurate CT values

Statistical deformation reconstruction using multi-organ shape features for pancreatic cancer localization

Respiratory motion and the associated deformations of abdominal organs and tumors are essential information in clinical applications. However, inter- and intra-patient multi-organ deformations are complex and have not been statistically formulated, whereas single organ deformations have been widely studied. In this paper, we introduce a multi-organ deformation library and its application to deformation reconstruction based on the shape features of multiple abdominal organs. Statistical multi-organ motion/deformation models of the stomach, liver, left and right kidneys, and duodenum were generated by shape matching their region labels defined on four-dimensional computed tomography images. A total of 250 volumes were measured from 25 pancreatic cancer patients. This paper also proposes a per-region-based deformation learning using the non-linear kernel model to predict the displacement of pancreatic cancer for adaptive radiotherapy. The experimental results show that the proposed concept estimates deformations better than general per-patient-based learning models and achieves a clinically acceptable estimation error with a mean distance of 1.2 ± 0.7 mm and a Hausdorff distance of 4.2 ± 2.3 mm throughout the respiratory motion

X-ray2Shape: Reconstruction of 3D Liver Shape from a Single 2D Projection Image

[2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020, Montreal, QC, Canada]Computed tomography (CT) and magnetic resonance imaging (MRI) scanners measure three-dimensional (3D) images of patients. However, only low-dimensional local two-dimensional (2D) images may be obtained during surgery or radiotherapy. Although computer vision techniques have shown that 3D shapes can be estimated from multiple 2D images, shape reconstruction from a single 2D image such as an endoscopic image or an X-ray image remains a challenge. In this study, we propose X-ray2Shape, which permits a deep learning-based 3D organ mesh to be reconstructed from a single 2D projection image. The method learns the mesh deformation from a mean template and deep features computed from the individual projection images. Experiments with organ meshes and digitally reconstructed radiograph (DRR) images of abdominal regions were performed to confirm the estimation performance of the methods

Psychological Stress Induced by Prone Positioning among Adults with Severe Cerebral Palsy

The purpose of this study was to investigate the psychological impact of various positionings in subjects with cerebral palsy (CP). The participants were 17 individuals with severe motor and intellectual disability due to CP. They began in a sitting position in their wheelchair, and were placed consecutively in prone or supine positions, with no intervals between placements. Physiological observations were made in each position, and included salivary α-amylase activity, pulse, percutaneous oxygen saturation, respiratory rate, learance or not of airway secretions, and occurrence or not of adverse events. Salivary α-amylase activity values were higher in the prone position than in the baseline and supine positions (p<0.05). Clearance of airway secretions was significantly more prevalent in the prone position than in the baseline and supine positions (p <0.05). The participants’ pulse was significantly lower in the supine and prone positions than in the baseline position (p<0.05). Greater prevalence of airway secretion clearance and significantly higher stress levels as indicated by saliva amylase were observed in the prone position than in the other two positions. Therefore, when such patients are placed in a prone position, close attention to airway management and the potential for psychological stress may be necessary

Enzymatic Conversion of Cypridina Luciferyl Sulfate to Cypridina Luciferin with Coenzyme A as a Sulfate Acceptor in Cypridina (Vargula) hilgendorfii

In the luminous ostracod Cypridina (presently Vargula) hilgendorfii, Cypridina luciferyl sulfate (3-enol sulfate of Cypridina luciferin) is converted to Cypridina luciferin by a sulfotransferase with 3′-phosphoadenosine-5′-phosphate (PAP) as a sulfate acceptor. The resultant Cypridina luciferin is used for the luciferase–luciferin reaction of Cypridina to emit blue light. The luminescence stimulation with major organic cofactors was examined using the crude extracts of Cypridina specimens, and we found that the addition of coenzyme A (CoA) to the crude extracts significantly stimulated luminescence intensity. Further, the light-emitting source in the crude extracts stimulated with CoA was identified as Cypridina luciferyl sulfate, and we demonstrated that CoA could act as a sulfate acceptor from Cypridina luciferyl sulfate. In addition, the sulfate group of Cypridina luciferyl sulfate was also transferred to adenosine 5′-monophosphate (5′-AMP) and adenosine 3′-monophosphate (3′-AMP) by a sulfotransferase. The sulfated products corresponding to CoA, 5′-AMP, and 3′-AMP were identified using mass spectrometry. This is the first report that CoA can act as a sulfate acceptor in a sulfotransferase reaction

Molecular analysis of afibrinogenemic mutations caused by a homozygous FGA1238 bp deletion, and a compound heterozygous FGA1238 bp deletion and novel FGA c.54+3A > C substitution

We identified two afibrinogenemic girls in two Japanese families and performed molecular analysis to clarify the mechanisms of fibrinogen defects. Genetic analyses were performed by PCR amplification of the fibrinogen gene and DNA sequence analysis. To analyze the mechanisms of mature fibrinogen defects in plasma, we cloned minigenes from the proposita's PCR-amplified DNA, transfected them into CHO cells, and sequenced the cDNA amplified with the RT reaction followed by PCR. Sequence analyses indicated that one was caused by a homozygous 1238 bp deletion of the fibrinogen A alpha-chain gene (FGA Delta 1238) and the other was a compound heterozygous FGA Delta 1238 and novel FGA c.54+3A > C substitution. The minigene corresponding to FGA Delta 1238 generates two aberrant mRNAs, both of which may induce a frameshift and terminate prematurely. In contrast, the minigene corresponding to FGA c.54+3A > C generates two aberrant mRNAs, one of which may induce a frameshift and terminate prematurely, and the other uses a cryptic 5' splice site in exon 1, resulting in the deletion of six amino acids in signal peptides. Molecular analyses of both genetic variants suggest that the lack of a mature A alpha-chain, impaired assembly, and/or secretion of the fibrinogen molecule may lead to afibrinogenemia.ArticleINTERNATIONAL JOURNAL OF HEMATOLOGY. 96(1):39-46 (2012)journal articl

Observation of biexcitonic emission at extremely low power density in tungsten disulfide atomic layers grown on hexagonal boron nitride

Monolayer transition metal dichalcogenides (TMDCs) including WS2, MoS2, WSe2 and WS2, are two-dimensional semiconductors with direct bandgap, providing an excellent field for exploration of many-body effects in 2-dimensions (2D) through optical measurements. To fully explore the physics of TMDCs, the prerequisite is preparation of high-quality samples to observe their intrinsic properties. For this purpose, we have focused on high-quality samples, WS2 grown by chemical vapor deposition method with hexagonal boron nitride as substrates. We observed sharp exciton emissions, whose linewidth is typically 22~23 meV, in photoluminescence spectra at room temperature, which result clearly demonstrates the high-quality of the current samples. We found that biexcitons formed with extremely low-excitation power (240 W/cm^2) at 80 K, and this should originate from the minimal amount of localization centers in the present high-quality samples. The results clearly demonstrate that the present samples can provide an excellent field, where one can observe various excitonic states, offering possibility of exploring optical physics in 2D and finding new condensates