Case Report - Journal of Neuroinformatics and Neuroimaging (2025) Volume 10, Issue 2

Quantitative Susceptibility Mapping in Neurodegenerative Disease Diagnosis and Monitoring

Department of Neurology, University of Chile, Chile.

Corresponding Author:

Santiago Pérez
Department of Neurology
University of Chile, Chile
E-mail: s.perez@neurolatam.cl

Received: 03-Jan-2025, Manuscript No. AANN-25-169295; Editor assigned: 04-Jan-2025, PreQC No. AANN-25-1692955(PQ); Reviewed: 18-Jan-2025, QC No AANN-25-1692955; Revised: 21-Jan-2025, Manuscript No. AANN-25-1692955(R); Published: 28-Jan-2025, DOI:10.35841/aann -10.2.189

Citation: Pérez S. Quantitative susceptibility mapping in neurodegenerative disease diagnosis and monitoring. J NeuroInform Neuroimaging. 2025;10(2):189.

Introduction

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that measures and maps the magnetic susceptibility of tissues, providing unique insights into brain microstructure and composition. Unlike conventional MRI, which primarily reflects proton density and relaxation times, QSM quantifies tissue magnetic properties, allowing the detection of subtle changes related to iron accumulation, myelin content, and calcium deposition. In neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis, abnormal iron deposition and demyelination are common pathological features. QSM offers a sensitive, non-invasive method to visualize and quantify these abnormalities, making it a valuable tool for both early diagnosis and disease monitoring. Its ability to produce quantitative, reproducible measurements holds particular promise for tracking disease progression and assessing the effects of therapeutic interventions [1].

A key advantage of QSM in neurodegenerative disease research lies in its specificity for tissue magnetic properties compared to other MRI contrast mechanisms. Traditional susceptibility-weighted imaging (SWI) can visualize magnetic susceptibility differences but cannot provide absolute quantitative values, which limits cross-subject and longitudinal comparisons. QSM, by solving the ill-posed inverse problem of field-to-source mapping, enables precise quantification of susceptibility values across brain regions. This makes it possible to compare measurements between patients and healthy controls or to track individual changes over time. For example, in Parkinson’s disease, QSM has been used to detect elevated iron levels in the substantia nigra, correlating with disease severity. Similarly, in multiple sclerosis, QSM can quantify iron accumulation in deep gray matter as well as demyelination in white matter lesions, offering biomarkers that complement conventional lesion load measurements [2].

In Alzheimer’s disease and related dementias, QSM provides valuable information about the role of iron in disease pathology. Studies have shown that excessive iron accumulation in the hippocampus, basal ganglia, and cortical regions is associated with amyloid-beta and tau pathology. These iron-related changes may contribute to oxidative stress and neurodegeneration, making them important targets for early detection and therapeutic monitoring. QSM has also been used in mild cognitive impairment (MCI) populations to differentiate individuals who are more likely to progress to Alzheimer’s disease. Beyond iron quantification, QSM can detect microbleeds and calcifications that may further inform diagnosis and prognosis. Its non-invasive nature and ability to detect changes before substantial structural atrophy occurs make QSM a compelling candidate for inclusion in multimodal diagnostic protocols alongside positron emission tomography (PET) and cerebrospinal fluid biomarkers [3].

Technological and methodological advances have enhanced the utility of QSM for clinical and research applications. Improvements in MRI acquisition sequences, such as multi-echo gradient echo imaging, have reduced scan times while maintaining high spatial resolution. Advanced reconstruction algorithms, including morphology-enabled dipole inversion (MEDI) and total variation regularization, have improved the accuracy and robustness of susceptibility maps. These developments allow for more reliable quantification across different scanners and clinical settings. Moreover, integration of QSM with other imaging modalities—such as diffusion tensor imaging (DTI) for white matter integrity and functional MRI for network connectivity—can provide a more comprehensive picture of neurodegenerative disease processes. Automated region-of-interest analysis tools and whole-brain voxel-based approaches have further streamlined QSM analysis, making it more accessible to clinical researchers [4].

Despite its promise, several challenges must be addressed before QSM can be fully integrated into routine clinical workflows for neurodegenerative disease diagnosis and monitoring. The accuracy of susceptibility quantification can be influenced by factors such as background field removal, choice of reconstruction algorithm, and differences in MRI hardware and acquisition protocols. Standardization of acquisition and processing pipelines is essential for ensuring reproducibility across studies and institutions. Furthermore, while QSM provides a sensitive measure of iron and myelin changes, the interpretation of susceptibility alterations can be complex, as multiple tissue components can influence the signal. Longitudinal studies with large cohorts are needed to validate QSM-derived biomarkers and establish their prognostic value. Additionally, translating QSM findings into actionable clinical decisions will require further integration with other biomarkers and clinical assessments to fully capture the multifactorial nature of neurodegenerative diseases [5].

Conclusion

Quantitative Susceptibility Mapping has emerged as a powerful neuroimaging tool for detecting and quantifying pathological changes in neurodegenerative diseases. By providing precise measurements of iron deposition, myelin content, and other susceptibility-related tissue properties, QSM offers valuable biomarkers for early diagnosis, disease staging, and treatment monitoring. Its application spans a range of disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis, where it can reveal pathological processes that are invisible to conventional MRI. While technical and methodological challenges remain, ongoing advances in acquisition, reconstruction, and standardization are bringing QSM closer to clinical translation. As part of a multimodal neuroimaging strategy, QSM has the potential to significantly improve our understanding, diagnosis, and management of neurodegenerative diseases.

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