Project Details
Description
The collagen fiber orientation of human meniscus plays an important role on knee function and its molecular change is related to early detection of knee osteoarthritis (OA). Previous report demonstrated that using ultra-short echo time (UTE) imaging contributes to improving signal intensity of in-vitro meniscus and revealing the meniscal infrastructure. However, so far the clinical imaging method could not provide a high resolution and contrast image of human meniscus. In this project, we will develop an optimized pulse sequence and the corresponding reconstruction method for improving the image resolution and contrast. In addition, radial GRAPPA method will be subsequently established to be combined with the proposed protocol to effectively reduce the scan time for clinical human meniscus imaging. Several specific aims of this project are listed: (1) to improve image quality by reducing echo time using minimal phase RF excitation pulse and radial k-space sampling scheme. (2) to improve image contrast by alleviating the interference from fat tissue using adiabatic inversion pulse. (3) to establish the related reconstruction method for radial data. (4) to implement the proposed sequence to in vivo human meniscus imaging. (5) to establish a radial GRAPPA method for acceleration of image reconstruction. (6) to implement this method in quantitative T2* measurements of menisci for investigation of osteoarthritis. An execution of the entire project shall lead to a successful integration of the six specific aims listed above to establish an optimized protocol for human meniscus imaging, which contributes to the investigation of meniscal infrastructure and provide a possibility of the quantitative T2* measurements of menisci. As a result, we anticipate the results from human study can help us evaluate the possibility to use the proposed methods for clinical applications in the future.
Status | Finished |
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Effective start/end date | 8/1/14 → 10/31/15 |
Keywords
- pulse sequence design
- MR physics
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