Comparative analysis of quantitative susceptibility mapping in preclinical dementia detection.

Chandrasekharan Kesavadas, Joseph Suresh Paul, Arun Raj T, Sheelakumari Raghavan

Journal: European journal of radiology 2024;178():111598

PMID: 38996737

Abstract

PURPOSE

This review aims to explore the role of Quantitative Susceptibility Mapping (QSM) in the early detection of neurodegenerative diseases, particularly Alzheimer's disease (AD) and Lewy body dementia (LBD). By examining QSM's ability to map brain iron deposition, we seek to highlight its potential as a diagnostic tool for preclinical dementia.

METHODOLOGY

QSM techniques involve the advanced processing of MRI phase images to reconstruct tissue susceptibility, employing methods such as spherical mean value filtering and Tikhonov regularization for accurate background field removal. This review discusses how these methodologies enable the precise quantification of iron and other elements within the brain.

RESULTS

QSM has demonstrated effectiveness in identifying early pathological changes in key brain regions, including the hippocampus, basal ganglia, and substantia nigra. These regions are significantly impacted in the early stages of AD and LBD. Studies reviewed indicate that QSM can detect subtle neurodegenerative changes, providing valuable insights into disease progression. However, challenges remain in standardizing QSM processing algorithms to ensure consistent results across different studies.

CONCLUSION

QSM emerges as a promising tool for early dementia detection, offering precise measurements of brain iron deposition and other critical biomarkers. The review underscores the importance of refining QSM methodologies and integrating them with other imaging modalities to improve early diagnosis and management of neurodegenerative diseases. Future research should focus on standardizing QSM techniques and exploring their synergistic use with other neuroimaging methods to enhance its clinical utility.

Copyright © 2024 Elsevier B.V. All rights reserved.

Address: Medical Image Computing and Signal Processing Laboratory, Digital University-Kerala (DUK), Trivandrum, India. Electronic address: [email protected].; Medical Image Computing and Signal Processing Laboratory, Digital University-Kerala (DUK), Trivandrum, India. Electronic address: [email protected].; Mayo Clinic - Rochester Department of Radiology, Doctor of Philosophy, USA. Electronic address: [email protected].; Imaging Science and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Science and Technology, Trivandrum, India. Electronic address: [email protected].
Bant logo

© Copyright 2026, Nutrition Evidence

NED wishes to thank the following organisations for their support:

We use cookies to improve your experience and analyze site traffic with Google Analytics. By continuing to use our site, you agree to our use of cookies. Learn more.