The stability of diffusion measurements with simultaneous multi-slice imaging: A multi-scanner, multi-site, test-retest study using the NIST/QIBA CaliberMRI diffusion phantom

Authors

Matthew Marzetti, Hamied A Haroon, William Lloyd, Todor Karaulanov, Yingfan Wang, Laura Parkes, Caroline Lea-Carnall, Irvin Teh, Gráinne Bourke and Ryckie G Wade

Published Date: 2026-06

Excerpts here:

“Abstract This study evaluated how simultaneous multi-slice (SMS) acceleration affects the accuracy and repeatability of apparent diffusion coefficient (ADC) measurements across multiple magnetic resonance imaging (MRI) platforms using a traceable diffusion phantom. A multi-centre, multi-scanner test-retest study was conducted across seven MRI systems from three major vendors using a CaliberMRI diffusion phantom”….. [Click link for full article]

“Conclusions Higher SMS factors can bias ADC measurements and reduce SNR. We advocate caution with high SMS factors in both clinical and research imaging where absolute ADC quantification is required. However, ADC measurements appear temporally consistent (even at high SMS factors) suggesting potential utility in longitudinal monitoring of relative ADC changes. Low SMS factors do not significantly degrade image quality or bias ADC values across scanner manufacturers and therefore may be clinically acceptable to reduce scan times. Future work could explore combining SMS acceleration with other clinically relevant parameter modifications, such as reduced TR, to further optimise scan efficiency and conducting in-vivo investigations.” [Click link for full article]

Please reach out to the authors directly!

Phantom used: CaliberMRI’s Model 128 Diffusion Phantom.

https://iopscience.iop.org/article/10.1088/2057-1976/ae7116

File Type: www
Categories: Diffusion-Weighted Imaging (DWI), mapping, Apparent Diffusion Coefficient (ADC), Diffusion, Diffusion Phantom Model 128, quantitative mri, NIST/RSNA/NCI Diffusion Phantom, NIST/QIBA Phantom, ADC, Reduced Scan Time, SMS, NIST, Reproducibility, Quality Control, QA, QC
Author: Laura Parkes, Caroline Lea-Carnall, Irvin Teh, Gráinne Bourke and Ryckie G Wade, Todor Karaulanov, Matthew Marzetti, Hamied A Haroon, William Lloyd, Yingfan Wang