Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects

Table 1 Minimum requirement of data acquisition in diffusion tensor imaging pipeline processing[84]

Data acquisition parameter	Minimum requirement	Comments
Field signal	1.5 T or 3T	Give a higher visual score, larger number of fibres. 7T and above – enables identification of smaller anatomical structures
Number of diffusion direction	Approximate 21	Lowest should be 6 diffusion direction, however it is advice to use more than 6 direction and can go up to 100 directions
Image resolution	depend on the FOV (usually 24 cm × 24 cm)	Large enough to prevent aliasing
B-value	0-1000 s/mm2	500-5000+ for HARDI acquisition 2500 for q-space even higher, e.g., 5-8000
Number of b-values (b = 0) images	2	About 1 per 6 diffusion images
Number of averages	NSA = 2	Can improve the SNR

T: Tesla; FOV: field of view; HARDI: High angular resolution diffusion imaging; NSA: Number of signal average; SNR: Signal to noise ratio.

Table 2 Relevant previous studies applications in four pipeline processing

Pipeline processing	Relevant applications
Pipeline 1	Multiple sclerosis[52], Alzheimer's disease[53], cerebellar ataxia and cortical cerebellar atrophy[78], Krabbe disease[82], epilepsy[85], cubital tunnel syndrome[86], the white matter integrity of Alzheimer's disease[87], dementia[88]
Pipeline 2	Cubital tunnel syndrome[86], the white matter integrity of Alzheimer’s disease[87], epilepsy[89], neurosurgery and brain tumour[90]
Pipeline 3	Parkinson’s disease[91], Renal Failure[81,92], Epilepsy[93]
Pipeline 4	Dementia[87], neurosurgery and brain tumour[94]