Year: 2026
Type: preprint
Abstract: Purpose: Low-rank reconstruction methods such as SPICE substantially improve Magnetic Resonance Spectroscopic Imaging (MRSI) reconstruction quality. However, SPICE does not provide an estimate of reconstruction uncertainty. A framework for posterior uncertainty estimation in SPICE reconstruction is proposed, hereafter referred to as the framework. Theory and Methods: A Laplace approximation is used to estimate the covariance of the reconstructed spatial coefficients. This covariance is propagated through the spectral basis and spectral fitting to obtain metabolite concentration uncertainty. Matrix-free Hessian--vector products and voxel-wise conjugate-gradient estimation are used to avoid explicit construction or inversion of the full Hessian, making the method tractable. Results: Validation using repeated in vivo 7 T MRSI acquisitions showed that the estimated posterior uncertainty exhibited spatial and spectral patterns similar to those of empirical repeated-scan uncertainty. Experiments further demonstrated how spatial regularization and k-space undersampling affect the estimated uncertainty. Conclusion: The framework provides a practical framework for uncertainty quantification when using SPICE reconstruction of MRSI. It could be adapted to other regularised low-rank reconstruction methods.
Institution: University of Oxford
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G1009099251, Wellcome Centre for Integrative Neuroimaging, G2792775314, Developing spatially resolved imaging of functional neurochemistry and cell-type specific microstructure in the living human brain, State-of-the-Art Ultra-High-Field MRI for Crossing Scales in Basic Neuroscience, Developing spatially resolved imaging of functional neurochemistry and cell- type specific microstructure in the living human brain, G5219700674, G6016412662, G6989385907, G7107648810, Wellcome Centre for Integrative Neuroimaging, Wellcome Centre for Integrative Neuroimaging - extension, G9000353647
OpenAlex ID: W7225391100