Filip Szczepankiewicz

Restriction-weighted q-space trajectory imaging (ResQ): Toward mapping diffusion time effects with tensor-valued diffusion encoding in human prostate cancer xenografts

This paper introduces ResQ, a framework for mapping diffusion time effects in prostate cancer xenografts using tensor-valued diffusion encoding, showing improved parameter accuracy compared to traditional methods.

Characterising the diffusion functional signature of negative BOLD with interleaved TMS-fMRI in the human brain

The paper investigates negative BOLD responses using interleaved TMS-fMRI and dfMRI in the human brain, finding no ADC-fMRI response and suggesting sensitivity to subtle neural activity in ipsilateral regions.

ZOnally magnified Oblique Multi-slice (ZOOM) for cardiac diffusion weighted imaging in vivo

This paper evaluates ZOOM as an alternative to ZOOMit for cardiac diffusion weighted imaging, showing reduced TE and aliasing artifacts.

Robust constrained weighted least squares for in vivo human cardiac diffusion kurtosis imaging

This paper develops RCWLS for cardiac DKI to improve signal fitting by combining robust estimation with convexity constraints, showing it reliably captures expected kurtosis patterns and corrects corrupted regions.

Cardiac diffusion kurtosis imaging in the human heart in vivo using 300mT/m gradients

This paper demonstrates the feasibility of cardiac diffusion kurtosis imaging (DKI) in humans using high gradient strength MRI, showing non-Gaussian water diffusion behavior and significant radial kurtosis differences.

Mapping grey and white matter activity in the human brain with isotropic ADC-fMRI

This study introduces isotropic ADC-fMRI to detect grey and white matter activity, showing it is more temporally specific than BOLD-fMRI and provides balanced mapping of both brain regions.

Evaluating the dependence of ADC-fMRI on haemodynamics inbreath-hold and resting-state conditions

This study evaluates ADC-fMRI's dependence on haemodynamics during breath-hold and resting-state conditions, finding it less affected by vascular contributions compared to dfMRI and BOLD.

Meningioma microstructure assessed by diffusion MRI: an investigation of the source of mean diffusivity and fractional anisotropy by quantitative histology

This paper investigates how histological features like cell density and structure anisotropy explain variations in diffusion MRI metrics MD and FAIP in meningioma tumors, finding that cell density explains variability across but not within tumors.

Accuracy and precision in super-resolution MRI: Enabling spherical tensor diffusion encoding at ultra-high b-values and high resolution

This paper introduces a super-resolution reconstruction framework for diffusion MRI, showing it improves signal accuracy and precision in low-SNR conditions, especially with high-resolution and spherical b-tensor encoding.

Neural Networks for parameter estimation in microstructural MRI: a study with a high-dimensional diffusion-relaxation model of white matter microstructure

This study uses deep neural networks to accelerate parameter estimation in a high-dimensional diffusion-relaxation MRI model but finds that machine learning cannot replace careful acquisition protocol design.

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

This paper introduces a method to estimate orientation-specific relaxation-diffusion features using nonparametric Monte Carlo MRI signal inversion, enabling detailed analysis of white matter microstructure.

The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

The paper investigates the dot-compartment in diffusion MRI using ultra-strong gradients and spherical tensor encoding, finding residual signals in cerebellar grey matter and white matter.

Joint RElaxation-Diffusion Imaging Moments (REDIM) to probe neurite microstructure

This paper introduces REDIM, a method to compute joint moments of relaxation-diffusion to characterize neural microstructure, showing it can distinguish fiber bundles with similar orientations but different relaxation rates.