Academic Journal
Tensor Decomposition-Based Multi-Signal Matrix Pencil Method for Myelin Water Fraction Estimation.
| Title: | Tensor Decomposition-Based Multi-Signal Matrix Pencil Method for Myelin Water Fraction Estimation. |
|---|---|
| Authors: | Kurian D; School of Electronic Systems and Automation, Digital University Kerala, Thiruvananthapuram, Kerala, India.; Indian Institute of Information Technology and Management, Thiruvananthapuram, Kerala, India., Alonso-Ortiz E; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, Quebec, Canada.; Centre de Recherche du CHU Sainte-Justine, Montreal, Quebec, Canada., Arshad F; Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India., Paul JS; School of Electronic Systems and Automation, Digital University Kerala, Thiruvananthapuram, Kerala, India.; Indian Institute of Information Technology and Management, Thiruvananthapuram, Kerala, India. |
| Source: | Magnetic resonance in medicine [Magn Reson Med] 2026 Jun; Vol. 95 (6), pp. 3503-3518. Date of Electronic Publication: 2026 Feb 04. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Wiley Country of Publication: United States NLM ID: 8505245 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2594 (Electronic) Linking ISSN: 07403194 NLM ISO Abbreviation: Magn Reson Med Subsets: MEDLINE |
| Imprint Name(s): | Publication: 1999- : New York, NY : Wiley Original Publication: San Diego : Academic Press |
| MeSH Terms: | Myelin Sheath*/chemistry , Brain*/diagnostic imaging , Water*/chemistry , Magnetic Resonance Imaging*/methods , Image Processing, Computer-Assisted*/methods, Algorithms ; Humans ; Computer Simulation ; Signal-To-Noise Ratio ; Body Water ; Reproducibility of Results |
| Abstract: | Purpose: To develop a robust method for estimating myelin water fraction (MWF) from multi-echo gradient-recalled echo (mGRE) data under acquisition regimes that limit echo-train length and support higher spatial sampling. Methods: A tensor decomposition-based multi-signal matrix pencil (T-MP) framework is proposed to incorporate data-driven spatial information from neighboring voxels into MWF estimation. By leveraging the reduced temporal sampling requirements of matrix pencil-based approaches, the method enables stable parameter estimation with fewer echoes compared to conventional iterative fitting techniques. The performance of the proposed method was evaluated using numerical simulations across a range of signal-to-noise ratios and echo spacings, as well as in vivo mGRE datasets acquired at different spatial resolutions with shortened echo trains. Results: Numerical simulations demonstrate that accurate MWF estimation can be achieved with substantially fewer temporal samples, facilitating acquisition protocols that prioritize spatial encoding. In vivo experiments show that the proposed method provides consistent MWF maps across different spatial resolutions without qualitative degradation. Kernel density analysis reveals improved estimation consistency in both white and gray matter compared with conventional voxel-wise fitting approaches. In addition, the proposed framework substantially reduces per-slice computation time. Conclusion: A tensor decomposition-based multi-signal matrix pencil method for MWF estimation is presented that integrates spatially informed signal structure while reducing temporal sampling requirements. The proposed framework supports spatially efficient mGRE acquisitions and provides improved robustness and computational efficiency compared to existing voxel-wise approaches. (© 2026 International Society for Magnetic Resonance in Medicine.) |
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| Grant Information: | BT/PR41560/AI/133/38/2020 Department of Biotechnology, Ministry of Science and Technology, India; R.11012/05/2020-HR Indian Council of Medical Research |
| Contributed Indexing: | Keywords: matrix pencil method; multi‐compartment relaxometry; myelin water fraction (MWF); tensor decomposition |
| Substance Nomenclature: | 059QF0KO0R (Water) |
| Entry Date(s): | Date Created: 20260204 Date Completed: 20260707 Latest Revision: 20260707 |
| Update Code: | 20260707 |
| DOI: | 10.1002/mrm.70283 |
| PMID: | 41639720 |
| Database: | MEDLINE |
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