Leighton Barnden1, Sonya Marshall-Gradisnik1, Donald Staines1, Ben Crouch2, and Zack Shan3
1Griffith University, Southport, QLD, Australia, 2Nuclear Medicine, Royal Adelaide Hospital, Adelaide, SA, Australia, 3University of Sunshine Coast, Sunshine Coast, QLD, Australia
Synopsis
The sensitivity of different structural MRI sequences for the detection of clinical abnormalities in cross-sectional studies was evaluated using actual population studies. We studied 3 patient cohorts on two MRI scanners (1.5T and 3T), using T1wSE, T2wSE, T1GRE, T2SPACE and MTC sequences for clinical group comparisons. Novel insights into their clinical potential of different
structural MRI scans indicated T1wSE and T2wSE offer advanced sensitivity and should be standard
in clinical cross-sectional studies. . Although our sensitivity
metric was computed for separate voxels, we expect inter-subject variance will have
a similar effect on the sensitivity for cluster detection.
introduction
Given that
in white matter 90% of R1(1/T1) contrast is determined by myelin, and in grey
matter 81% of R2*(1/T2*) contrast by
iron1, so-called ‘structural
MRI’ offers quite specific evaluation of functionally relevant brain molecules.
However, they are rarely used. Although scans with strong grey – white matter
contrast are visually appealing, their inter-subject variance determines
whether they are sensitive in cross-sectional comparisons. The sensitivity of
different structural MRI sequences for the detection of clinical abnormalities in
cross-sectional studies can best be evaluated by performing actual population
studies. Over 15 years we have studied 3 patient cohorts on two MRI scanners
(1.5T and 3T), using T1wSE, T2wSE, T1GRE, T2SPACE and MTC sequences for clinical
group comparisons and correlations with severity metrics2-5 (SE = spin echo, GRE = gradient
echo, SPACE = Siemens ‘optimized 3D fast spin-echo’ that yields T2 contrast,
and MTC = magnetization transfer contrast). methods
Using
standard voxel-based statistical analysis we here derive sensitivity in terms
of the effect size that would yield a nominal statistical inference for specific
sequences and cohorts. We report, for the above MRI sequences, the mean
sensitivity in two white matter regions: the sensorimotor cortex and the
brainstem.
Although
not relevant to our sensitivity results, each of the three cohorts consisted of
healthy controls (HC) and chronic fatigue syndrome (ME/CFS) subjects. Cohorts A
and B were acquired 6 years apart on the same Philips Integra 1.5 Tesla scanner
with a birdcage receive coil. Cohort C was acquired on a Siemens 3T Skyra
scanner with a 64 channel head-neck coil. Table 1 lists cohort and sequence details.
For each
cohort, standard voxel-wise image processing was performed using the SPM
(Statistical Parametric Mapping) package: (a) Spatial
normalization to a standard anatomical (MNI) space3,5, (b) Statistical
analysis via a ‘2 sample’ group comparison, using ‘proportional scaling’ to
adjust for variation in inter-subject global levels.
SPM output files permit
the cohort mean and standard deviation to be computed at each voxel6. A locally written Matlab script computed
voxel-wise sensitivity after Abbott et al6, expressed as the effect size (%
voxel mean) required to yield a nominal T statistic. Here we evaluate effect sizes in sensorimotor
and brainstem regions of interest (Fig 1).results
Sensitivity
images for 3 cohort C sequences are shown in Fig 2.
Table 2
lists the effect sizes required to yield significant statistical inference (T =
5.0) in the two regions assessed. These values scale linearly with the
reference T statistic chosen.
T1wSE was
the sequence with the highest sensitivity (smallest effect size) on the 3T
scanner (cohort 3). This was followed by T1GRE, T1wSE and T2wSE for cohort A. After
6 years there was an appreciable loss of sensitivity on the same 1.5T scanner (cohort
B). discussion
Gradient
echo (MPRAGE) structural scans are commonly acquired in fMRI and DTI studies to
facilitate spatial normalization, but MPRAGE signal amplitudes are not used
quantitatively. However, quantitative T1wSE and T2wSE have been successfully
implemented by our group (after further refining inter-subject intensity
adjustment)2-5.
Consistent with the 3-fold improvement in T1wSE sensitivity at 3T, strong differences between their
constituent HC and ME/CFS groups were seen at 3T but not 1.5T. Correlations with clinical
metrics were strong for both T1wSE and T2wSE at 1.5T2,4, and T1wSE at 3T. A T1wSE analysis
for cohort A that yielded a strong correlation, when repeated with T1 GRE was
insignificant, despite similar sensitivities. Although T2 SPACE yielded attractive
high spatial resolution images with ‘T2 contrast’, they were ineffective in our
cross-sectional studies.conclusion
This
analysis provides novel insights into the clinical potential of different
structural MRI scans. Quantitative T1wSE and T2wSE offer advanced sensitivity and should be standard
in clinical cross-sectional studies. This must be tempered, of course by the unknown
clinical effect sizes detected by each sequence. Although our sensitivity
metric was computed for separate voxels, we expect inter-subject variance will have
a similar effect on the sensitivity for cluster detection.Acknowledgements
We thank the patients and healthy controls who donated their time and effort to participate in this study. This study was supported by the Alison Hunter Memorial Foundation, Stafford Fox Medical Research Foundation, the Judith Jane Mason Foundation (MAS2015F024), Mr. Douglas Stutt, and the Blake-Beckett Foundation, Ian and Talei Stewart, Buxton Foundation and McCusker Charitable Foundation. Their financial support did not affect any aspect of the study.
We thank Richard Burnet, Peter DelFante and Richard Kwiatek in Adelaide for recruiting subjects and Kevin Finegan, Sandeep Bhuta and Tim Ireland at Gold Coast University Hospital for assistance in acquiring MRI scans.
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