Ventral anterior temporal lobe and signal loss


What is the optimal way to minimize the signal loss due to air-tissue interfaces in the Ventral anterior temporal lobe? We are interested in studying this and surrounding areas. However, what I understand is regular sequences such as the one we are using (TR=2,3x3x3mm voxels, 32 slices, TE=30ms, FA=78, FOV=192x192) is not very good in eliminating these artifacts?

Are there sequence parameters (printouts) or imaging methods (parallel, multiband) people would recommend using for this purpose?

I have heard that MB sequences may improve this signal loss, but I can not see how and why that would be the case. I am assuming using a MB sequence by on itself won’t change much unless the protocol parameters are modified accordingly as well. In other words, just putting a MB sequence with the same parameters as I mentioned above wouldn’t improve these artifacts, would they?



The air tissue interface is creating two type of artefacts in that area for 2D GRE-EPI sequences used in BOLD imaging

  • susceptibility induced distorsions
  • signal dropout due to intravoxel dephasing

One strategy that can be advantageous for you would be to acquire BOLD images with a multi-echo GRE-EPI sequences with two echoes or more and combine those echoes according to method derived from the paper below and implemented in tools such as FMRIPREP and TEDANA

Kundu, P.; Voon, V.; Balchandani, P.; Lombardo, M. V.; Poser, B. A.; Bandettini, P. A. Multi-Echo FMRI: A Review of Applications in FMRI Denoising and Analysis of BOLD Signals. NeuroImage 2017, 154, 59–80.

Other general approaches to improve the signal loss in this area could also use these strategies:

  • decrease the slice thickness to limit the intravoxel dephasing (but this will decrease your SNR)
  • change the slice orientation
  • reduce TE (knowing the best TE for BOLD sensitivity is for TE=T2*, one idea idea would be to measure the T2* in this area and optimize the TE with this knowledge).
1 Like

Thank you so much for your answer. I will look into these.