Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jun 16;3(1):84.
doi: 10.1038/s43856-023-00318-5.

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis

Pramod Kumar Pisharady  1 , Lynn E Eberly  2   3 , Isaac M Adanyeguh  2 , Georgios Manousakis  4 , Gaurav Guliani  4 , David Walk #  4 , Christophe Lenglet #  2
Affiliations

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis

Pramod Kumar Pisharady et al. Commun Med (Lond). .

Abstract

Background: Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord.

Methods: We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section.

Results: We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics.

Conclusions: Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.

Plain language summary

ALS is a disease affecting the brain and spinal cord which leads to weakness and muscle wasting. It is important to be able to measure disease-related changes whilst clinical trials are ongoing to assess whether the treatments being tested are working. We imaged the brain and spinal cord of people with and without ALS at 3 time points over a year. We found changes in the brain and spine over time. This study demonstrates that brain imaging could be potentially used to assess changes in disease progression during clinical trials, giving an indication of whether the treatments being tested are having an effect.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Whole brain cross-sectional group difference (ALS vs. control) - Tract based spatial statistics.
Cross-sectional TBSS results at initial visit with comparison of group differences (n = 20 in each group) in Fsum (panels in row 1 and 2) and FA (panels in row 3 and 4). Color-coded regions show the areas where statistically significant group differences exist (p < 0.05, corrected for multiple comparisons across space). Green arrows indicate regions where group differences are detected by Fsum but not by FA (Fsum - Sum of fiber volume fractions, FA Fractional anisotropy).
Fig. 2
Fig. 2. Summary of cross-sectional group difference (ALS vs. control) in different brain and spinal cord measures.
a–e Scatter dot plots of multiple measures from the brain and the spinal cord showing the group difference between ALS participants (n = 20) and controls (n = 20). For each group, the plot shows the mean (blackline) with 95% confidence interval (green lines) (ALS Amyotrophic lateral sclerosis, FA Fractional anisotropy, Fsum Sum of fiber volume fractions, CST Corticospinal tract, C2 Spinal cord C2 level, CSA Cross-sectional area).
Fig. 3
Fig. 3. Correlation between ALSFRS-R and brain fixel-based measures.
Correlation between ALSFRS-R and (a) mean FDC of brain CST left and (b) mean FDC of brain CST right. Sample size n = 20 (ALSFRS-R ALS functional rating scale - revised, FDC Fiber density and cross-section, CST Corticospinal tract).
Fig. 4
Fig. 4. Whole brain longitudinal change in ALS participants - Tract based spatial statistics.
Longitudinal TBSS results showing regions where longitudinal changes are noted in the 12-month follow-up ALS data compared to the baseline ALS data (n = 11), in Fsum (panels in row 1 and 2) and FA (panels in row 3 and 4). Color-coded regions show the areas where statistically significant group differences exist (p < 0.05, corrected for multiple comparisons across space). (Fsum Sum of fiber volume fractions, FA Fractional anisotropy).
Fig. 5
Fig. 5. Whole brain longitudinal change in ALS participants - Fixel Based Analysis.
Figure 2 Longitudinal FBA results showing coronal and sagittal views of fiber alterations. Decrease in FDC (row 1), FD (row 2), and log FC (row 3) are detected in the one-year follow-up in ALS data compared to the baseline ALS data (n = 11). Color represents fiber orientations (red-left to right, blue-inferior to superior) (ALS Amyotrophic lateral sclerosis, FDC Fiber density and cross-section, FD Fiber density, FCFiber cross-section, FBA Fixel-based analysis).
Fig. 6
Fig. 6. Summary of longitudinal change in different brain and spinal cord measures.
Longitudinal changes in ALS participants (n = 11, panels in column 1) and controls (n = 13, panels in column 2) in (a) brain FA, (b) brain Fsum, (c) superior temporal cortical thickness, (d) spinal cord CST RD at C2, (e) spinal cord CSA at C2, and (f) brain FDC. The corresponding effect sizes and p-values of the longitudinal change in ALS participants are provided in Table 4 (ALS Amyotrophic lateral sclerosis, FA Fractional anisotropy, Fsum Sum of fiber volume fractions, RD Radial diffusivity, CST Corticospinal tract, C2 Spinal cord C2 level, CSA Cross-sectional area, FDC Fiber density and cross-section).
See this image and copyright information in PMC

References

    1. Stejskal EO, Tanner JE. Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 1965;42:288. doi: 10.1063/1.1695690. - DOI
    1. Concha L. A macroscopic view of microstructure: using diffusion-weighted images to infer damage, repair, and plasticity of white matter. Neuroscience. 2014;276(Sep):14–28. doi: 10.1016/j.neuroscience.2013.09.004. - DOI - PubMed
    1. Robberecht W, Philips T. The changing scene of amyotrophic lateral sclerosis. Nat. Rev. Neurosci. 2013;14:248–264. doi: 10.1038/nrn3430. - DOI - PubMed
    1. Rose S, et al. Direct evidence of intra- and interhemispheric corticomotor network degeneration in amyotrophic lateral sclerosis: An automated MRI structural connectivity study. Neuroimage. 2012;59:2661–2669. doi: 10.1016/j.neuroimage.2011.08.054. - DOI - PubMed
    1. Li J, et al. A meta-analysis of diffusion tensor imaging studies in amyotrophic lateral sclerosis. Neurobiol. Aging. 2012;33:1833–1838. doi: 10.1016/j.neurobiolaging.2011.04.007. - DOI - PubMed