This subproject is one of many research subprojects utilizing the resources provided by a Shared Instrumentation Grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the grant, which is not necessarily the institution for the investigator. DESCRIPTION (provided by applicant): A.
SPECIFIC AIMS We seek support for a high-resolution head camera for positron emission tomography (PET) of the brain, the CTI ECAT HRRT. Massachusetts General Hospital has a long record of leadership in the fields of neuroimaging, both in PET and MRI. The existing PET equipment, however, is not optimized for brain imaging: the modern cameras we have are whole-body systems, and are increasingly occupied with clinical needs. The existing PET cameras are also located in the clinical hospital area rather than in the research campus (some 15 minutes away). Locating the proposed dedicated brain instrument at the Charlestown campus will allow not only improve performance (greater sensitivity, higher resolution) for the problems MGH investigators are studying with PET, but will facilitate existing PET-oriented research and allow multi-modal integration of results in ways that could further benefit existing funded (and future) research. The proposed instrument has unique features that are particularly beneficial for neuroimaging: a smaller field of view, boosting resolution; the use of LSO crystal material, giving it higher sensitivity and/or speed; and the presence of depth-of-interaction electronics, which allow the resolution to be much more uniform over the field of view. This uniformity is a key issue for quantitation, and quantitation is increasingly a critical issue for many of our funded researchers especially for correlation with other modalities. Placement of the HRRT in the proposed environment will provide a unique facility to advance brain imaging research that in turn will provide insights for a variety of illnesses and biomedical questions.
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| Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi et al. (2016) Dopamine D1 signaling organizes network dynamics underlying working memory. Sci Adv 2:e1501672 |
| Putcha, Deepti; Ross, Robert S; Cronin-Golomb, Alice et al. (2016) Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease. J Int Neuropsychol Soc 22:205-15 |
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