Synopsis

DTI templates of the adult human brain are commonly used in neuroimaging, and their characteristics influence the accuracy of the application. The purpose of this work was to compare eight available standardized DTI templates to each other, as well as to study-specific templates, in terms of template characteristics and performance in spatial normalization and detection of small inter-group FA differences. The IIT v.3.0 template was shown to combine a number of desirable characteristics, and allows higher inter-subject spatial normalization accuracy and detection of smaller inter-group FA differences, compared to other templates, including study-specific templates, for both younger and older adults.

Introduction

Methods

Two 3T datasets from the Enhanced Nathan Kline Institute Rockland Sample (http://fcon_1000.projects.nitrc.org/indi/enhanced/sharing.html) were used in this work. Dataset 1 included DTI and T₁-weighted data from 72 healthy young and middle-aged adults (18-59 years of age), and Dataset 2 included DTI and T₁-weighted data from 72 healthy older adults (65-85 years of age), collected using SE-EPI-DTI (2x2x2 mm³, b=1,500 s/mm², 128 diffusion directions, nine b=0 s/mm² volumes) and 3D MPRAGE (1x1x1 mm³). DTI processing was conducted using TORTOISE¹.

Eight standardized DTI templates of the adult human brain and two study-specific templates were compared. The standardized templates included five providing full tensor information: IIT v.3.0², IIT2³, ICBM81⁴, Eve⁵, and NTU-DSI-122-DTI⁶; and three providing only tensor-derived scalar quantities: ENIGMA⁷, FMRIB58 (FMRIB), and SRI24⁸. The two study-specific diffusion tensor templates were constructed based on Datasets 1 (SS-y) and 2 (SS-o), separately, using a state-of-the-art approach (DTI-TK⁹).

A) FA maps of all templates were compared in terms of image sharpness, ability to identify small brain structures, and artifacts content.

B) The accuracy of inter-subject DTI spatial normalization achieved when using each of the templates as reference was compared across templates, for normalization of younger (Dataset 1) and older (Dataset 2) adults, separately. For templates providing full tensor information, tensor-based registration was conducted using DTI-TK^9-14. For templates providing only tensor-derived scalar quantities, FA-based registration was conducted using ART^15,16, followed by finite strain tensor reorientation¹⁷. A number of metrics were used to assess the accuracy of inter-subject spatial normalization voxel-wise. Histograms of these quantities in white matter were generated for Datasets 1 and 2, separately, and were compared across templates using the one-sided two-sample Kolmogorov-Smirnov (KS) test.

C) Power analysis was used to assess the impact of spatial normalization accuracy on the ability to detect small inter-group FA differences (assuming two groups, 100 participants per group, significance at p<0.05, power>0.95). Maps of the minimum detectable inter-group FA differences were generated for all templates, and corresponding cumulative distributions were compared across templates using the one-sided two-sample KS test.

Results

A) Image sharpness was higher in the FA maps of Eve and IIT v.3.0 compared to other templates (Fig.1). Fine white matter details were observed throughout the brain in IIT v.3.0 and Eve templates, while the same information was often lost in other templates (Fig.2A). Image artifacts were present in ICBM81, Eve, NTU-DSI-122-DTI, and SRI24 (Fig.2B).

B) The accuracy of inter-subject spatial normalization was higher when using the IIT v.3.0 template compared to all other templates, including the corresponding study-specific templates, for both younger (Fig.3A) and older adults (Fig.3B)(p<10^-8 in all cases).

C) Power analysis showed that, on average over all white matter, the IIT v.3.0 template allowed detection of smaller inter-group FA differences compared to other templates, including the study-specific templates, for both younger (Figs.4A,5A) and older adults (Figs.4B,5B)(p<10^-8 in all cases).

Discussion

The IIT v.3.0 template combines a number of desirable characteristics over other templates: full-tensor information, population-based, high image sharpness, no visible artifacts, features representative of individual adult brains. It was demonstrated that the IIT v.3.0 template allows higher inter-subject DTI spatial normalization accuracy, and detection of smaller inter-group FA differences, compared to other templates, including study-specific templates, for both younger and older adults.

At first glance, the results showing higher spatial normalization accuracy when using a standardized instead of a study-specific template appear to be in conflict with the work by van Hecke et al.¹⁸, which established the use of study-specific templates as the modus operandi in DTI investigations. However, van Hecke et al. only compared a study-specific template and a single standardized template, namely ICBM81. The present work is actually in agreement with the findings by van Hecke et al. Moreover, the present work substantially extends that of van Hecke et al.¹⁸ by considering standardized templates that were not available in 2011, and shows that IIT v.3.0, a standardized template, can lead to higher spatial normalization accuracy than study-specific templates constructed with state-of-the-art approaches. This result is of high significance as it pertains to the template selection strategy used in many DTI studies.

Acknowledgements

References

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