Document Detail


Optimizing MR signal contrast of the temporomandibular joint disk.
MedLine Citation:
PMID:  21972123     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
PURPOSE: To use a tissue specific algorithm to numerically optimize UTE sequence parameters to maximize contrast within temporomandibular joint (TMJ) donor tissue. MATERIALS AND METHODS: A TMJ specimen tissue block was sectioned in a true sagittal plane and imaged at 3 Tesla (T) using UTE pulse sequences with dual echo subtraction. The MR tissue properties (PD, T(2) , T(2) *, and T(1) ) were measured and subsequently used to calculate the optimum sequences parameters (repetition time [TR], echo time [TE], and θ). RESULTS: It was found that the main contrast available in the TMJ could be obtained from T(2) (or T(2) *) contrast. With the first echo time fixed at 8 μs and using TR = 200 ms, the optimum parameters were found to be: θ ≈ 60°, and TE2 ≈ 15 ms, when the second echo is acquired using a gradient echo and θ ≈ 120°, and TE2 ≈ 15 ms, when the second echo is acquired using a spin echo. CONCLUSION: Our results show that MR signal contrast can be optimized between tissues in a systematic manner. The MR contrast within the TMJ was successfully optimized with facile delineation between disc and soft tissues. J. Magn. Reson. Imaging 2011;. © 2011 Wiley-Liss, Inc.
Authors:
Michael Carl; Hatice T Sanal; Eric Diaz; Jiang Du; Olivier Girard; Sheronda Statum; Richard Znamirowski; Christine B Chung
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-10-3
Journal Detail:
Title:  Journal of magnetic resonance imaging : JMRI     Volume:  -     ISSN:  1522-2586     ISO Abbreviation:  -     Publication Date:  2011 Oct 
Date Detail:
Created Date:  2011-10-5     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9105850     Medline TA:  J Magn Reson Imaging     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 Wiley-Liss, Inc.
Affiliation:
GE Healthcare, San Diego, California, USA. michael.carl@ge.com.
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