Subject-specific regional measures of water diffusion are associated with impairment in chronic spinal cord injuryJournal Name: Neuroradiology

Ann S. Choe1,2*, Cristina L. Sadowsky3,4, Seth A. Smith5, 6, Peter C.M. van Zijl1,2, James J. Pekar1,2, Visar Belegu3,7

1Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA;2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205 USA;3International Center for Spinal Cord Injury, Kennedy Krieger Institute, Baltimore, MD 21205 USA;4Physical Medicine and Rehabilitation, Kennedy Krieger Institute, Baltimore, MD 21205 USA;5Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37235 USA;6Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37235 USA;7Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA

*Corresponding author:Ann S. Choe, Ph.D.F. M. Kirby Research Center for Functional Brain Imaging Kennedy Krieger Institute707 North BroadwayBaltimore, Maryland 21205 USAPhone: +1(443) 923-9500Email: annschoe@gmail.com

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Supplemental Text

Effects of injury level on fractional anisotropy

Studies have shown that FA values decrease 10-15% along the length of the cervical cord (in C2 to

C6 direction) [1]. To investigate the effect of such underlying decrease of baseline FA values, we first

modeled the changes of baseline FA values along the length of the healthy cervical spinal cords, by

performing a polynomial regression fit on the FAIRRI values obtained from the healthy individual dataset.

We then used the modeled data to weigh the FAIRRI values of each SCI patient, according to their level of

injuries. Results of the linear regression analysis of the weighted FAIRRI values and ISNCSCI-tot (Figure

S2) show that the observed strength of the correlation between ISNCSCI-tot with weighted FA IRRI in fact

becomes stronger (R2=0.643) compared to that with the regular FAIRRI values (R2=0.605). This result

shows that, despite the possible confounding effects, the proposed subject-specific injury demarcation

approach can provide robust outcome measures that are more specific to impairments compared to the

conventional approach.

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Supplemental Figures

Figure S1. Spatial dependence of the association between FA and total ISNCSCI score.

Linear regression analyses were performed to observe the effect of spinal cord RRI on the relationship

between the ISNCSCI-tot score and FA. Scatter plot and estimated linear trend line are shown for each

ROI. The association between FAIRRI and ISNCSCI-tot is stronger then that between FAAL and ISNCSCI-

tot, as well as those between FA measurements from other ROIs. Detailed result of the linear regression

analyses can be found in Table 4.

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Figure S2. Association between weighted FAIRRI and total ISNCSCI score.

FAIRRI values were weighted according to the injury level of SCI patients, to reflect the possible underlying

decrease in FA values along the length of cervical spinal cord. Results show that the strength of the

correlation between the weighted FAIRRI and ISNCSCI-tot is stronger (indicated by the larger adjusted R2

value) than that between the non-weighted FAIRRI and ISNCSCI-tot.

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Supplemental Tables

Table S1. (Cohort without TM individuals) Effect of spinal cord column and spinal cord region-relative-to-injury (RRI) on diffusion tensor imaging (DTI) indices.

The effect of spinal cord column (right and left lateral, dorsal, and ventral columns) and RRI region

(regions superior to, at, and inferior to injury epicenter) on fractional anisotropy (FA), axial diffusivity (AD),

and radial diffusivity (RD) was tested using a two-way analysis of variance (ANOVA). Spinal cord RRI was

identified as the main source of variation for all three DTI indices. In other words, DTI index values

measured from each RRI region were significantly different from each other. Conversely, different spinal

cord columns did not have significantly different DTI index values.

DTI indices

Source of variationSpinal Cord Columns

(p-value)Spinal Cord RRI

(p-value)FA 0.338 0.005*

AD 1.000 0.006*RD 1.000 0.005*

*Statistically significant (p< 0.05)

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Table S2. (Cohort without TM individuals) Mean and standard deviation measurement of each DTI index.

In healthy individuals, only the DTI indices from the all levels (AL) region were obtained, and the

measurements were then compared with the corresponding AL-region DTI index values from the

individuals with SCI. Significant decrease in FAAL and increase in RDAL indicate severe damage in injured

cords.

Mean ± SDHealthy individuals Individuals with SCI

AL AL SRRI ERRI IRRIFA 0.72±0.04 0.48 ± 0.08* 0.52 ± 0.10 0.483 ± 0.10 0.440 ± 0.13

AD (µm2/ms) 2.04±0.14 2.21±0.29 2.15±0.41 2.11±0.33 2.43±0.47

RD (µm2/ms) 0.53±0.09 1.10±0.29* 1.00±0.39 1.04±0.28 1.32±0.52* Statistically significant (p < 0.05)

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Table S3. (Cohort without TM individuals) Spatial dependence of the correlation between DTI indices and total ISNCSCI scores.

Stronger correlation (i.e., larger R2 value) is observed between total ISNCSCI scores (ISNCSCI-tot) and

DTI indices obtained from the IRRI-region, compared to that between the ISNCSCI-tot and DTI indices

obtained from SRRI-, ERRI-, and AL-regions – indicating spatial dependence of the correlation between

DTI indices and total ISNCSCI scores.

RRI Adjusted R2 Slope [p-val] InterceptFASRRI 0.003 0.000397 [1.000] 0.477FAERRI 0.182 0.000660 [0.254] 0.408FAIRRI 0.590 0.00149 [0.003*] 0.262FAAL 0.344 0.000748 [0.050*] 0.399

ADSRRI -0.039 -0.00113 [1.000] 2.281ADERRI -0.002 -0.00126 [1.000] 2.253ADIRRI 0.314 -0.00424 [0.087] 2.936ADAL 0.314 -0.00171 [0.543] 2.406

RDSRRI -0.007 -0.00146 [1.000] 1.163RDERRI 0.208 -0.00213 [0.199] 1.278RDIRRI 0.468 -0.00554 [0.017*] 1.981RDAL 0.310 -0.00256 [0.073] 1.394

*Statistically significant: p < 0.05, corrected

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1. Wheeler-Kingshott CA, Hickman SJ, Parker GJ, Ciccarelli O, Symms MR, Miller DH, Barker GJ (2002)

Investigating cervical spinal cord structure using axial diffusion tensor imaging. Neuroimage 16:93-102

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