Microbiome-based disease prediction with multimodal variational information bottlenecks.

Scientific research is shedding light on the interaction of the gut microbiome with the human host and on its role in human health. Existing machine learning methods have shown great potential in discriminating healthy from diseased microbiome states. Most of them leverage shotgun metagenomic sequencing to extract gut microbial species-relative abundances or strain-level markers.

Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

Purpose: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground truth. The second aim is to demonstrate the feasibility of magnetic resonance imaging (MRI)-based proton therapy planning for the brain by assessing the range shift error within the clinical acceptance threshold.

Methods And Materials: The image database included 15 pairs of MRI/CT scans of the head.

Advanced Multimodal Methods for Cranial Pseudo-CT Generation Validated by IMRT and VMAT Radiation Therapy Plans.

Purpose: To investigate advanced multimodal methods for pseudo-computed tomography (CT) generation from standard magnetic resonance imaging sequences and to validate the results by intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans. We present 2 novel methods that employ key techniques to enhance pseudo-CTs and investigate the effect on image quality and applicability for IMRT and VMAT planning.

Materials And Methods: The data set contains CT and magnetic resonance image scans from 15 patients who underwent cranial radiation therapy.

Proton range shift analysis on brain pseudo-CT generated from T1 and T2 MR.

Background: In radiotherapy, MR imaging is only used because it has significantly better soft tissue contrast than CT, but it lacks electron density information needed for dose calculation. This work assesses the feasibility of using pseudo-CT (pCT) generated from T1w/T2w MR for proton treatment planning, where proton range comparisons are performed between standard CT and pCT.

Material And Methods: MR and CT data from 14 glioblastoma patients were used in this study.

Longitudinal Motion Assessment of the Carotid Artery Using Speckle Tracking and Scale-Invariant Feature Transform.

The purpose of this work is to present and validate a novel approach for ultra-sound-based speckle tracking to measure the carotid artery longitudinal displacement, and to assess the apparent sliding between of Intima-Media Complex (IMC) and Adventitia (Ad) layers. This method utilizes feature detectors and descriptors to localize and track keypoints for local motion quantification. The procedure was tested and validated on an in silico dataset and on 18 heathy volunteers and 16 patients.