Skip to content
#diffusion models Open access

Developing an SNR-efficient tensor-valued diffusion encoding protocol for studying brain microstructural changes in neurodegeneration

Sep 2026 · medRxiv · 0 citations · 8 references
Medicine

Abstract

Tensor-valued diffusion encoding (TDE) is an emerging diffusion MRI technique that uses advanced diffusion-encoding waveforms and modeling to provide enhanced specificity to brain microstructure compared with conventional Stejskal-Tanner pulsed-gradient encoding. However, the diffusion encoding duration to achieve the same b-value is substantially increased in TDE, resulting in relatively low SNR and spatial resolution (>2 mm isotropic). In this study, we developed an SNR-efficient, high-resolution TDE protocol with 1.8-mm isotropic resolution and clinically feasible scan time and evaluated its reproducibility and sensitivity to age-related microstructural differences. Eleven cognitively normal older adults (5F/6M, 62-71 years) and seven younger adults (3F/4M, 22-31 years) were scanned at 3T using an in-house TDE sequence incorporating an SNR-efficient multi-band multi-shot EPI readout and reconstruction. Quantitative diffusion metrics, including mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (FA), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), and total mean kurtosis (MKT), were evaluated in the bilateral temporal parts of the cingulum bundles (CBT), bilateral fornix (FX), and global white matter (WM). Older participants underwent two scans to assess reproducibility using intraclass correlation coefficients (ICCs) and Bland-Altman analysis, and diffusion metrics were compared between younger and older groups using Wilcoxon signed-rank tests with false discovery rate (FDR) correction. All metrics except MKI demonstrate moderate-to-excellent reproducibility across all WM regions (ICCs[≥]0.64). Exploratory comparisons show age-related differences in FA, FA, and MKA with p<0.05 before FDR correction, particularly in the fornix, although none remains significant after correction. These findings demonstrate the feasibility of SNR-efficient TDE at 1.8-mm isotropic resolution with approximately 70-mm brain coverage in approximately 12 minutes and establish its reproducibility for high-resolution brain microstructural imaging.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9

Related blog posts

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.