[Mristudio-users] 2 questions

Fri Apr 12 14:19:08 EDT 2013

Yes, the gradient table should be updated in real time, but it's not that
way for the current version.

For the 30-orientations, this is the paper many people refer;

The effect of gradient sampling schemes on measures derived from diffusion
tensor MRI: a Monte Carlo study.<http://www.ncbi.nlm.nih.gov/pubmed/15065255>

*Jones DK*.

Magn Reson Med. 2004 Apr;51(4):807-15.

and this is our more practical interpretation of this issue

Effects of diffusion weighting schemes on the reproducibility of
DTI-derived fractional anisotropy, mean diffusivity, and principal
eigenvector measurements at 1.5T.<http://www.ncbi.nlm.nih.gov/pubmed/17532649>

*Landman* BA, Farrell JA, Jones CK, Smith SA, Prince JL, *Mori* S.

Neuroimage. 2007 Jul 15;36(4):1123-38. Epub 2007 Apr 4.

On Fri, Apr 12, 2013 at 1:42 PM, Dorian P. <alb.net at gmail.com> wrote:

> Thank you Dr. Mori,
>
> You were right. Setting up "Rotate gradients if applicable" and
> closing-opening again the window showed the same gradients calculated from
> par/rec. It was a bit tricky because I thought "rotate gradients" would
> show the correct table in the textbox. Instead, the gradients in the box
> are wrong, they are corrected on the fly when the software loads the
> images. The only way to see them is to close and open the window again.
>
> About my second question, I agree to your advice, 16x2 should be more
> useful. Can you tell me which study said 32x1 is better than 16x2?
>
> Again thank you.
> Dorian
>
>
> 2013/4/12 susumu mori <susumu at mri.jhu.edu>
>
>> Answering your second question, simulation study says 32-orientation x 1
>> gives better SNR.
>> I always use 2 repetition. In your case, 16x2 because the subtraction of
>> the two sets gives good idea about existence of motion and quality of image
>> registration. You can find corrupted images easier too.
>>
>>
>> On Fri, Apr 12, 2013 at 10:41 AM, Dorian P. <alb.net at gmail.com> wrote:
>>
>>> Hi everybody, and thank you for previous answers.
>>>
>>> I have two questions today. First, I am comparing the gradient table
>>> obtained by PAR/REC and DICOM files. They are very different, I can't find
>>> similar lines. However, the final statistics on fiber tracking look
>>> similar. Below you can find the two gradient tables and the fiber
>>> statistics. Can you please tell me whether the difference in gradient
>>> tables is normal, and if one is more precise than the other (the PAR/REC
>>> table was calculated by a Matlab script developed at the John Hopkins).
>>>
>>> Second question: Given a fixed time is available on a 1.5T, is it better
>>> to obtain 2 scans of 16 directions or one scan of 32 directions? I can
>>> imagine the SNR is much better with two, but not sure whether more
>>> directions compensate for SNR too.
>>>
>>> Thank you.
>>> Dorian
>>>
>>>
>>> Gradient table calculated from Philips PAR file:
>>>
>>> 0: -0.44136, -0.57117, -0.69207
>>> 1: -0.56394, -0.42335, 0.70905
>>> 2: 0.69797, -0.70323, 0.13526
>>> 3: -0.59198, -0.34304, -0.72931
>>> 4: -0.15274, -0.74584, -0.64838
>>> 5: 0.074435, -0.77687, -0.62525
>>> 6: 0.47574, -0.63875, -0.60471
>>> 7: 0.74718, -0.22799, -0.62429
>>> 8: -0.5922, -0.34308, -0.7291
>>> 9: -0.24242, -0.7705, -0.58954
>>> 10: 0.34275, -0.76982, -0.53843
>>> 11: 0.56981, -0.55721, -0.60402
>>> 12: 0.75753, -0.35855, -0.54552
>>> 13: -0.66312, -0.52489, -0.53364
>>> 14: -0.43153, -0.75822, -0.48876
>>> 15: 0.59311, -0.69541, -0.40574
>>> 16: 0.74571, -0.52489, -0.41038
>>> 17: -0.71084, -0.70326, 0.011793
>>> 18: -0.75432, -0.41491, 0.50878
>>> 19: 0.65451, -0.41491, 0.63204
>>> 20: 0.41865, -0.64824, 0.63602
>>> 21: -0.71152, -0.70239, 0.019779
>>> 22: -0.69363, -0.35558, 0.62645
>>> 23: -0.71454, -0.69646, 0.066208
>>> 24: -0.354, -0.63595, 0.68575
>>> 25: 0.22954, -0.63595, 0.7368
>>> 26: 0.69727, -0.70239, 0.14303
>>> 27: 0.64596, -0.224, 0.72977
>>> 28: -0.71425, -0.69728, 0.060467
>>> 29: -0.033138, -0.62847, 0.77712
>>> 30: 0.69693, -0.70198, 0.14667
>>> 31: 0.64313, 0.073913, 0.76219
>>> 32: 0, 0, 0
>>> 33: 100, 100, 100
>>>
>>>
>>>
>>>
>>>
>>> Gradient table obtined by DICOM file:
>>>
>>> 0: 0.000000, 0.000000, 0.000000, 0.000000
>>> 1: -0.499998, -0.499998, -0.707110, 850.000000
>>> 2: -0.499998, -0.499998, 0.707110, 850.000000
>>> 3: 0.707107, -0.707107, 0.000000, 850.000000
>>> 4: -0.653288, -0.270606, -0.707098, 850.000000
>>> 5: -0.208664, -0.675630, -0.707095, 850.000000
>>> 6: 0.019658, -0.706829, -0.707112, 850.000000
>>> 7: 0.421225, -0.567950, -0.707109, 850.000000
>>> 8: 0.689925, -0.154927, -0.707108, 850.000000
>>> 9: -0.653495, -0.270675, -0.706880, 850.000000
>>> 10: -0.292882, -0.707102, -0.643604, 850.000000
>>> 11: 0.294515, -0.706411, -0.643619, 850.000000
>>> 12: 0.514993, -0.486072, -0.706056, 850.000000
>>> 13: 0.707102, -0.292882, -0.643604, 850.000000
>>> 14: -0.707102, -0.472486, -0.526084, 850.000000
>>> 15: -0.472486, -0.707102, -0.526084, 850.000000
>>> 16: 0.555492, -0.643950, -0.526077, 850.000000
>>> 17: 0.707102, -0.472486, -0.526084, 850.000000
>>> 18: -0.707107, -0.707107, -0.000212, 850.000000
>>> 19: -0.707102, -0.472486, 0.526084, 850.000000
>>> 20: 0.707102, -0.472486, 0.526084, 850.000000
>>> 21: 0.472486, -0.707102, 0.526084, 850.000000
>>> 22: -0.707085, -0.707085, 0.007849, 850.000000
>>> 23: -0.636392, -0.425181, 0.643604, 850.000000
>>> 24: -0.706047, -0.706047, 0.054730, 850.000000
>>> 25: -0.292882, -0.707102, 0.643604, 850.000000
>>> 26: 0.292882, -0.707102, 0.643604, 850.000000
>>> 27: 0.707085, -0.707085, 0.007849, 850.000000
>>> 28: 0.707102, -0.292882, 0.643604, 850.000000
>>> 29: -0.706260, -0.706260, 0.048932, 850.000000
>>> 30: 0.034719, -0.706256, 0.707105, 850.000000
>>> 31: 0.707060, -0.707060, 0.011526, 850.000000
>>> 32: 0.707107, -0.000000, 0.707107, 850.000000
>>> 33: 100.000000, 100.000000, 100.000000, 850.000000
>>>
>>> Fiber statistics for each:
>>> http://img580.imageshack.us/img580/2887/capturenbh.jpg
>>>
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>>
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