1. Neuroscience

In vivo mapping of striatal neurodegeneration in Huntington’s disease with Soma and Neurite Density Imaging

  1. Vasileios Ioakeimidis
  2. Marco Palombo
  3. Chiara Casella
  4. Lucy Layland
  5. Carolyn McNabb
  6. Robin Schubert
  7. Philip Pallmann
  8. Monica Busse
  9. Cheney Drew
  10. Sundus Alusi
  11. Timothy Harrower
  12. Jane Davies
  13. Anne Rosser
  14. Claudia Metzler-Baddeley  Is a corresponding author
  1. Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, United Kingdom
  2. Danish Research Centre for Magnetic Resonance, Department for Radiology and Nuclear Medicine, Copenhagen University Hospital Amager and Hvidovre, Denmark
  3. Early Life Imaging Research Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom
  4. London Collaborative Ultra high field System (LoCUS), Kings College London, United Kingdom
  5. Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
  6. George Huntington Institut (GHI), Germany
  7. Centre for Trials Research, School of Medicine, Cardiff University, United Kingdom
  8. The Walton Centre for Neurology and Neurosurgery, Fazakerley, United Kingdom
  9. Royal Devon and Exeter NHS Trust, United Kingdom
  10. Neurology, Exeter NIHR Biomedical Research Centre, United Kingdom
  11. Cardiff and Vale University Health Board, Main University Hospital Wales Building, Cardiff University, Health Park Campus, United Kingdom
  12. Cardiff University Brain Repair Group, School of Biosciences, Cardiff University, United Kingdom
  13. Advanced Neurotherapeutics Centre (ANTC), Department of Neurology and Psychological Medicine, School of Medicine, Cardiff University, United Kingdom
https://doi.org/10.7554/eLife.107661.3
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Cite this article
  1. Vasileios Ioakeimidis
  2. Marco Palombo
  3. Chiara Casella
  4. Lucy Layland
  5. Carolyn McNabb
  6. Robin Schubert
  7. Philip Pallmann
  8. Monica Busse
  9. Cheney Drew
  10. Sundus Alusi
  11. Timothy Harrower
  12. Jane Davies
  13. Anne Rosser
  14. Claudia Metzler-Baddeley
(2026)
In vivo mapping of striatal neurodegeneration in Huntington’s disease with Soma and Neurite Density Imaging
eLife 14:RP107661.
https://doi.org/10.7554/eLife.107661.3
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9 figures, 6 tables and 2 additional files

Figures

Figure 1
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Volumetric differences in the basal ganglia and thalamus between Huntington’s disease (HD) (n = 56) and healthy control (HC) (n = 57) groups.

Regions of interest (ROIs) were segmented using FreeSurfer v6. All ROIs, except the left thalamus, showed significantly smaller volumes in the HD cohort after false discovery rate (5% FDR) correction for multiple comparisons. Colours indicate the strength of rank-biserial correlations (rrb) from Mann–Whitney U tests: red = strong effect (rrb ≥ 0.5), yellow = medium effect (0.3 ≤ rrb < 0.5), white = small effect (rrb < 0.3). Raincloud plots show the distribution of the volumetric measures in each ROI per group with orange for HD and green for HC participants. *p < 0.05; ***p < 0.001.

Figure 2 with 1 supplement
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Microstructural differences in regions of interest (ROIs) between Huntington’s disease (HD) (n = 56) and healthy control (HC) (n = 57) groups.

Median values of each microstructural measure were extracted per ROI. (A) HD individuals show reduced apparent soma density (fis) in the basal ganglia (BG). (B) Apparent soma radius (rs) is elevated in the caudate and putamen but reduced in the pallidum. (C) Extracellular signal fraction (fec) is increased in BG regions in the HD group. (D) Extracellular diffusivity (De) is higher in the putamen and pallidum. (E) Fractional anisotropy (FA) is elevated in the BG, and (F) mean diffusivity (MD; expressed in ×10–4 mm2/s) is increased in the striatum. Colours indicate the strength of rank-biserial correlations (rrb) from Mann–Whitney U tests: red = strong effect (rrb ≥ 0.5), yellow = medium effect (0.3 ≤ rrb < 0.5), white = small effect (rrb < 0.3). Raincloud plots show the distribution of the microstructural measures in each ROI per group with orange for HD and green for HC participants. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 2—figure supplement 1
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Bar plot showing the effect sizes and 95% confidence intervals for exploratory pairwise comparisons between HD-ISS 0–1 (n = 13), HD-ISS 2–3 (n = 17), and healthy controls (HC).

Significant comparisons are marked with *p < 0.05, **p < 0.01, and ***p < 0.001.

Figure 3 with 1 supplement
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Correlations between Q-Motor principal component and SANDI indices.

(A) Correlation matrix and (B–G) selected scatter plots illustrating Spearman’s rho correlations between SANDI measures and the Q-Motor principal component. (A) Each cell represents the Spearman’s rho correlation strength, with pink indicating negative and green positive correlations. (B–G) Each plot includes a best-fit least squares linear regression line with standard error indicated by the grey shaded area, along with the Spearman’s rho (ρ) and the corresponding FDR-p value. Regression lines are included for visualisation only and do not reflect variance explained (R2) or imply linear model fit. Scatter dot colours represent participants’ HD-ISS stage. Unclassified refers to those participants who could not be classified due to having CAG 36–40 or incomplete clinical data. Abbreviations: De: extracellular diffusivity; fec: extracellular signal fraction; fin: neurite density signal fraction; fis: soma density signal fraction; PC: principal component; rs: soma radius.

Figure 3—figure supplement 1
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Scatterplot showing positive relationship between the Q-Motor principal component and the disease burden measure (CAP100) with the Spearman’s rho (ρ) test.

Scatter dot colours represent participants’ HD-ISS stage and those who were not classified due to having CAG <40 or incomplete clinical data.

Figure 4 with 1 supplement
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Correlations between the Q-Motor principal component and DTI and volumetric measures.

(A) Correlation matrix and (B–D) selected scatter plots illustrating Spearman’s rho correlations between diffusion tensor imaging (DTI), volumetric measures and the Q-Motor principal component. (A) Each cell represents the Spearman’s rho correlation strength, with pink indicating negative and green positive correlations. (B–D) Each plot includes a best-fit least squares linear regression line with standard error indicated by the grey shaded area, along with the Spearman’s rho (ρ) and the corresponding FDR-p value. Regression lines are included for visualisation only and do not reflect variance explained (R2) or imply linear model fit. Scatter dot colours represent participants’ HD-ISS stage. Unclassified refers to those participants who could not be classified due to having CAG 36–40 or incomplete clinical data. Abbreviations: FA: fractional anisotropy; MD: mean diffusivity.

Figure 4—figure supplement 1
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Correlation heatmaps showing the cross-correlation of SANDI, diffusion tensor imaging (DTI), and volumetric (normalised for intracranial volume) measures, averaged across the caudate, putamen, pallidum, and thalamus.

Heatmaps are shown separately for the full sample, healthy controls (HC), and Huntington’s disease (HD) participants. Correlations are expressed as Spearman’s rho coefficients.

Figure 5
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Standardised beta coefficients of SANDI microstructural metrics predicting volume (normalised for intracranial volume) in regions of interest in the healthy control group.

Data were modelled by firstly accounting for age, followed by the step-wise inclusion of all SANDI indices. The figure displays the predictor variables included in the final regression models for each region of interest. Abbreviations: De: extracellular diffusivity; fis: soma density signal fraction; rs: soma radius; TFC: total functional capacity. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 6
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Standardised beta coefficients of SANDI microstructural metrics predicting volume (normalised for intracranial volume) in (A) left and (B) right hemisphere regions of interest in individuals with Huntington’s disease.

Data were modelled by firstly accounting for age and total functional capacity scores simultaneously, followed by the step-wise inclusion of all SANDI indices. The figure displays the predictor variables included in the final regression models for each region of interest. Abbreviations: De: extracellular diffusivity; fec: extracellular signal fraction; fis: soma density signal fraction; rs: soma radius. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 7
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Correlations between disease burden (CAP100) and brain microstructural and volumetric measures.

(A) Correlation matrix and (B–J) selected scatter plots illustrating Spearman’s rho correlations between SANDI, diffusion tensor imaging (DTI), and volumetric measures with CAP100. Each scatter plot includes a best-fit least squares linear regression line with standard error indicated by the grey shaded area, along with the Spearman’s rho (ρ) and the corresponding FDR-p value. Regression lines are included for visualisation only and do not reflect variance explained (R2) or imply linear model fit. Scatter dot colours represent participants’ HD-ISS stage and those who were not classified due to having CAG <40 or incomplete clinical data. Abbreviations: De: extracellular diffusivity; FA: fractional anisotropy; fec: extracellular signal fraction; fin: neurite density signal fraction; fis: soma density signal fraction; MD: mean diffusivity; rs: soma radius; vol: normalised volume.

Author response image 1
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Analysis of the accuracy and precision of SANDI model parameters estimation.

We simulated 104 synthetic diffusion signals using the SANDI model with random combinations of five parameters: fneurite(fin), fsoma(fis), Din, Rsoma(rs), and De. Parameters were sampled uniformly from: fneurite, fsoma ∈ [0,1]; Din, De ∈[0.5,3.0] µm2/ms; 𝑅soma 𝛜[1,12] µm. Rician noise with experimentally estimated variance was added, and the SANDI model was then fit to the noisy signals. For each parameter, we report the relative percentage error between estimated and ground-truth values as a function of the parameter value (normalized to [0,1]), together with goodness-of-fit (R2).

Author response image 2
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Sensitivity to 5% parameter modulations.

The matrices show how a controlled perturbation in one parameter propagates into the estimated values of all model parameters. Each row corresponds to a 5% increase in the parameter on the y-axis; the resulting percentage change observed in each estimated parameter is reported along the x-axis. An ideal estimator would yield a purely diagonal matrix, with 5% on the diagonal and 0% elsewhere (no cross-talk). In (A), we used the same synthetic SANDI signals as in Figure 1. In (B), we additionally generated 104 synthetic signals incorporating neurite–extra-cellular exchange using the NEXI model [https://doi.org/10.1016/j.neuroimage.2022.119277] and an exchange time representative of human cortex (𝜏ex ≈ 30 ms) [https://doi.org/10.1162/imag_a_00104].

Tables

Table 1
Demographic and clinical information of participants.
HD groupHC groupStatistic (p-value)
NMean (SD)NMean (SD)
Age5646.12 (13.79)5744.96 (13.75)t(111) = 0.446 (0.657)
Female, N (%)25 (44.7%)31 (54.4%)χ2 = 1.073 (0.300)
Education (years)3814.16 (2.58)1415.86 (2.54)t(50) = 2.06 (0.448)
HD-ISS Stage 0/1/2/3, Ntotal4/9/5/12, 30
MOCA5526.47 (3.55)-
TOPF5649.70 (13.16)-
UHDRS-TFC5612.11 (1.25)-
UHDRS-TMS5111.03 (15.82)-
CAG5041.82 (2.67)-
CAP5080.55 (22.60)-
SDMT3845.47 (14.91)

  1. Abbreviations: CAG: Cytosine Adenine Guanine; CAP: CAG-Age-Product; HC: healthy controls; HD: Huntington’s disease; HD-ISS: Huntington’s Disease Integrated Staging System; MOCA: Montreal Cognitive Assessment; SD: standard deviation; SDMT: Symbol Digit Modalities Test; TFC: total functional capacity; TMS: Total Motor Score; TOPF: Test of Premorbid Functioning; UHDRS: United Huntington’s Disease Rating Scale.

Table 2
Descriptive and Mann–Whitney statistics for intracranial volume-normalised regions of interest.
HD groupHC groupStatistic (FDR-p, effect size)
Region of interestL/RMean (SD)Mean (SD)U (p, rank-biserial correlation)
CaudateL1.95a (0.45a)2.35a (0.24a)2464 (<0.001, 0.544)
R2.06a (0.43a)2.41a (0.25a)2376 (<0.001, 0.489)
PutamenL2.67a (0.62a)3.22a (0.46a)2397 (<0.001, 0.502)
R2.67a (0.66a)3.25a (0.40a)2479 (<0.001, 0.553)
PallidumL1.15a (0.20a)1.32a (0.13a)2382 (<0.001, 0.492)
R1.13a (0.17a)1.26a (0.12a)2323 (<0.001, 0.456)
ThalamusL4.83a (0.49a)4.99a (0.41a)1955 (0.063, 0.224)
R4.72a (0.39a)4.91a (0.40a)1981 (0.048, 0.241)

  1. Abbreviations: FDR: false discovery rate; HC: healthy controls; HD: Huntington’s disease; L: left hehmisphere; R: right hemisphere; SD: standard deviation. Significant results are highlighted in bold.

  2. aMultiplied by 10−3.

Table 3
Descriptive and Mann–Whitney statistics for microstructural measures in regions of interest.
HD groupHC groupStatistic (FDR-p, effect size)
Microstructural measureRegion of interestL/RMean (SD)Mean (SD)U (p, rank-biserial correlation)
Apparent soma densityCaudateL0.43 (0.05)0.46 (0.02)2227 (<0.001, 0.395)
R0.45 (0.05)0.48 (0.02)2318 (<0.001, 0.452)
PutamenL0.39 (0.05)0.42 (0.03)2140 (0.003, 0.341)
R0.42 (0.05)0.44 (0.03)2099 (0.007, 0.315)
PallidumL0.21 (0.05)0.24 (0.04)2187 (0.001, 0.370)
R0.21 (0.05)0.24 (0.04)2249 (<0.001, 0.409)
ThalamusL0.34 (0.03)0.34 (0.02)1692 (0.701, 0.060)
R0.35 (0.03)0.35 (0.02)1661 (0.776, 0.041)
Apparent soma sizeCaudateL9.80 (0.25)9.58 (0.15)746 (<0.001, –0.533)
R9.72 (0.25)9.52 (0.12)751 (<0.001, –0.529)
PutamenL9.61 (0.29)9.43 (0.15)885 (<0.001, –0.445)
R9.63 (0.27)9.40 (0.14)791 (<0.001, –0.504)
PallidumL8.41 (1.08)8.88 (0.58)2126 (0.004, 0.332)
R8.59 (0.94)9.05 (0.45)2300 (<0.001, 0.447)
ThalamusL9.51 (0.14)9.50 (1.32)1502 (0.701, –0.059)
R9.54 (0.13)9.52 (0.12)1515 (0.723, –0.051)
Extracellular signal fractionCaudateL0.38 (0.04)0.36 (0.01)757 (<0.001, –0.526)
R0.37 (0.02)0.36 (0.01)984 (<0.001, –0.383)
PutamenL0.36 (0.03)0.34 (0.02)1048 (0.003, –0.343)
R0.34 (0.03)0.32 (0.01)892 (<0.001, –0.441)
PallidumL0.36 (0.04)0.33 (0.02)910 (<0.001, –0.430)
R0.35 (0.04)0.32 (0.02)932 (<0.001, –0.416)
ThalamusL0.34 (0.02)0.33 (0.01)1294 (0.130, –0.189)
R0.33 (0.01)0.32 (0.01)1636 (0.853, 0.025)
Extracellular diffusivityCaudateL1.47 (0.28)1.40 (0.11)1420 (0.418, –0.110)
R1.51 (0.25)1.44 (0.13)1482 (0.633, –0.071)
PutamenL1.47 (0.17)1.36 (0.11)902 (<0.001, –0.435)
R1.62 (0.20)1.49 (0.11)1002 (0.001, –0.372)
PallidumL1.62 (0.20)1.48 (0.12)842 (<0.001, –0.472)
R1.76 (0.23)1.59 (0.14)809 (<0.001, –0.493)
ThalamusL1.47 (0.07)1.44 (0.07)1411 (0.394, –0.116)
R0.31 (0.03)0.31 (0.03)1377 (0.305, –0.137)
Apparent neurite densityCaudateL0.18 (0.04)0.17 (0.02)1514 (0.723, –0.051)
R0.18 (0.05)0.16 (0.02)1317 (0.167, –0.175)
PutamenL0.24 (0.04)0.23 (0.03)1374 (0.303, –0.139)
R0.23 (0.04)0.23 (0.03)1411 (0.394, –0.116)
PallidumL0.41 (0.05)0.42 (0.03)1553 (0.854, –0.027)
R0.43 (0.05)0.43 (0.03)1473 (0.605, –0.078)
ThalamusL0.31 (0.03)0.31 (0.03)1565 (0.868, –0.019)
R0.31 (0.03)0.31 (0.03)1459 (0.554, –0.086)
Fractional anisotropyCaudateL0.18 (0.04)0.16 (0.02)993 (0.001, –0.378)
R0.20 (0.07)0.16 (0.02)889 (<0.001, –0.443)
PutamenL0.19 (0.04)0.17 (0.02)873 (<0.001, –0.453)
R0.20 (0.04)0.17 (0.02)710 (<0.001, –0.555)
PallidumL0.28 (0.04)0.26 (0.03)1115 (0.010, –0.301)
R0.28 (0.05)0.26 (0.02)995.5 (<0.001, –0.401)
ThalamusL0.33 (0.02)0.33 (0.02)1808 (0.319, 0.133)
R0.33 (0.02)0.33 (0.02)1532 (0.776, –0.040)
Mean diffusivityCaudateL6.50a (0.41a)6.23a (0.13a)777.5 (<0.001, –0.513)
R6.44a (0.36a)6.20a (0.12a)760.5 (<0.001, –0.523)
PutamenL6.22a (0.34a)5.95a (0.15a)653.5 (<0.001, –0.591)
R6.20a (0.34a)5.91a (0.13a)624.5 (<0.001, –0.609)
PallidumL5.54a (0.36a)5.51a (0.23a)1557.5 (0.854, –0.024)
R5.52a (0.30a)5.49a (0.18a)1437 (0.474, –0.100)
ThalamusL5.98a (0.14a)5.96a (0.11a)1509 (0.721, –0.055)
R6.01a (0.13a)6.00a (0.11a)1566.5 (0.868, –0.018)

  1. Abbreviations: FDR: false discovery rate; HC: healthy controls; HD: Huntington’s disease; L: left hemisphere; R: right hemisphere; SD: standard deviation. Significant results are highlighted in bold.

  2. aMultiplied by 10–4.

Table 4
Hierarchical linear regression predicting normalised volumes from SANDI microstructural metrics, controlling for age in the healthy control participants.
ROIModelPredictor(s)Adjusted R2ΔR2F-value (p-value)ΔF-valueβt-valuep-value
Left caudate1Age0.0840.1006.115 (0.017) –0.316–2.4730.031
2Age0.1670.0966.599 (0.003)6.474–0.166–1.2260.297
 fis    0.3452.5440.026
Left putamen1Age0.2470.26019.328 (<0.001) –0.510−4.396<0.001
Left pallidum1Age0.0040.0221.247 (0.269) –0.149–1.1170.341
Left thalamus1Age0.1740.18812.761 (0.001) –0.434–3.5720.003
Right caudate1Age0.0460.0633.715 (0.059) –0.252–1.9270.087
2Age0.1110.0804.508 (0.015)5.029–0.348–2.6160.023
 De    0.2992.2430.048
Right putamen1Age0.2340.24818.109 (<0.001) –0.498–4.255<0.001
2Age0.2890.06712.389 (<0.001)5.265–0.602–4.954<0.001
 De    0.2792.2950.045
Right pallidum1Age–0.0170.0010.058 (0.811) 0.0320.2410.847
2Age0.1080.1394.392 (0.017)8.7180.0030.0250.980
 De    0.3742.9530.011
Right thalamus1Age0.1110.1277.966 (0.007) –0.356–2.8220.015
Table 5
Hierarchical linear regression models predicting normalised volumes in each region of interest from SANDI microstructural metrics, controlling for age and TFC in HD participants.
ROIModelPredictorsAdjusted R2ΔR2F-value (p-value)ΔF-valueβt-valuep-value
Left caudate1Age0.2770.30411.136 (<0.001)–0.398–3.2490.005
TFC0.2802.2810.046
2Age0.5470.26822.308 (<0.001)31.383–0.370–3.810<0.001
TFC–0.034–0.3030.822
rs–0.611–5.602<0.001
3Age0.6000.05820.853 (<0.001)7.623–0.273–2.7880.016
TFC–0.068–0.6380.594
rs–0.529–4.963<0.001
fis0.2882.7610.016
Left putamen1Age0.2960.32312.150 (<0.001)–0.415–3.4360.003
TFC0.2822.3310.043
2Age0.5290.23320.855 (<0.001)26.238–0.332–3.3110.005
TFC0.1731.7110.129
fec–0.507–5.122<0.001
3Age0.6010.07520.934 (<0.001)9.961–0.341–3.6900.003
TFC0.0710.7210.552
fec–0.427–4.515<0.001
rs–0.309–3.1560.007
4Age0.6300.03419.016 (<0.001)4.818–0.485–4.386<0.001
TFC0.1681.6050.157
fec–0.489–5.126<0.001
rs–0.349–3.6380.003
De0.3022.1950.052
Left pallidum1Age0.1070.1404.165 (0.021)–0.152–1.1190.341
TFC0.2992.1980.052
2Age0.3440.24110.278 (<0.001)19.4850.0350.2780.829
TFC0.1110.8890.455
fec–0.577–4.414<0.001
3Age0.4240.08610.741 (<0.001)7.8850.1150.9610.425
TFC0.0490.4170.753
fec–0.486–3.8370.001
rs0.3442.8080.015
Left thalamus1Age0.3020.32812.455 (<0.001)–0.456–3.7860.001
TFC0.2361.9560.085
Right caudate1Age0.2760.30411.117 (<0.001)–0.410–3.3410.005
TFC0.2652.1620.054
2Age0.4430.17115.036 (<0.001)16.233–0.426–3.9570.001
TFC0.0060.0480.976
rs–0.485–4.0290.001
3Age0.5100.07314.807 (<0.001)7.898–0.326–3.0430.009
TFC–0.018–0.1560.902
rs–0.456–4.0200.001
fis0.2962.8100.015
Right putamen1Age0.3330.35814.218 (<0.001)–0.499–4.243<0.001
TFC0.2111.7970.111
2Age0.5700.23624.432 (<0.001)29.159–0.425–4.450<0.001
TFC–0.070–0.6520.593
rs–0.578–5.400<0.001
Right pallidum1Age0.0430.0792.177 (0.124)–0.043–0.3080.822
TFC0.2641.8740.097
2Age0.2650.2287.367 (<0.001)16.4300.0940.7370.550
TFC0.1160.9020.454
fec–0.530–4.0530.001
Right thalamus1Age0.3470.37215.076 (<0.001)–0.550–4.723<0.001
TFC0.1451.2420.295
Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Software/algorithmSANDI Matlab ToolboxPalombo et al., 2020
10.1016/j.neuroimage.2020.116835		RRID:SCR_028525/
Github		Multi-shell diffusion imaging analyses toolbox for SANDI model fitting

Additional files

MDAR checklist
https://cdn.elifesciences.org/articles/107661/elife-107661-mdarchecklist1-v1.docx
Supplementary file 1

Exploratory HD-ISS analyses.

(a) Demographic and clinical information per HD-ISS stage. (b) Descriptive statistics for motor outcome measures. (c) Rotated component loadings on the Q-Motor outcome measures. (d) Descriptive statistics and non-parametric pairwise comparisons for SANDI indices (significant for total HD sample versus HC) between HD-ISS 0–1, HD-ISS 2–3, and healthy controls.

https://cdn.elifesciences.org/articles/107661/elife-107661-supp1-v1.docx

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  1. Vasileios Ioakeimidis
  2. Marco Palombo
  3. Chiara Casella
  4. Lucy Layland
  5. Carolyn McNabb
  6. Robin Schubert
  7. Philip Pallmann
  8. Monica Busse
  9. Cheney Drew
  10. Sundus Alusi
  11. Timothy Harrower
  12. Jane Davies
  13. Anne Rosser
  14. Claudia Metzler-Baddeley
(2026)
In vivo mapping of striatal neurodegeneration in Huntington’s disease with Soma and Neurite Density Imaging
eLife 14:RP107661.
https://doi.org/10.7554/eLife.107661.3