I think it's possible that two different b-values would increase precision of the DTI measurements.<div><br></div><div>If you have time to acquire 60 DWIs (usually about 7-8 min), you have choices of;</div><div><br></div>
<div>1) 60 orientations</div><div>2) 30 orientations x 2 repeat</div><div>3) 30 orientations x 2 b-values (e.g. 500 and 1,000).</div><div><br></div><div>There are papers recommending #1, although I don't think those previous papers compared #1 and #3.</div>
<div>Personally, I prefer #2 because the two identical scans provide visual clues about quality of the data. If you subtract two repetitions, which are supposed to be identical, you can see patient movement and corrupted images right away. </div>
<div>In reality, DTI measurement precision is dominated by physiological noise. Although we apply some correction methods such as post-processing co-registration and outlier rejections, my impression is that we still have to see the data to make sure the data don't contain very bad images. For that purpose, I value the usefulness of the subtracted images more than small increase in precision detected by simulation studies, although one can argue that the inspection of the subtracted images is too qualitative. It's just my 2 cents.<br>
<br><div class="gmail_quote">On Mon, Nov 29, 2010 at 12:46 PM, Meredith Reid <span dir="ltr"><<a href="mailto:mer.reid@gmail.com">mer.reid@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
DTI experts,<br><br>I have been considering the options of multiple repetitions versus multiple b-values. In light of Correia et al.'s simulations (<a href="http://www.ncbi.nlm.nih.gov/pubmed/18687552" target="_blank">http://www.ncbi.nlm.nih.gov/pubmed/18687552</a>), it seems to me that 30 directions at 2 different b-values may be advantageous (versus 2 repetitions of one b-value at 30 directions) since I am interested in both scalar measures and tractography. Any thoughts on this? Has anyone compared these scenarios in acquired data?<br>
<br>Thanks,<br><font color="#888888">Meredith Reid<br>
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