Hyperthyroidism Clinical Trial
Official title:
Comparison of Standardized Update Value Using Single-photo Emission Computed Tomography and Computed Tomography Between Grave's Disease (Hyperthyroidism) Patients and Normal Humans
The purpose of this study is to find out the capacity of standardized uptake value (SUV) using single-photo emission computed tomography and computed tomography (SPECT/CT) in diagnosing Grave's Disease (hyperthyroidism).
Traditionally it is considered that only positron emission tomography(PET) has the ability
to obtain standardized uptake value（SUV）while single-photo emission computed
tomography(SPECT) does not have. Recently with the developing of technology, the ability of
SPECT has been extended.
On the other hand, thyroid imaging by SPECT can only play an auxiliary role in
hyperthyroidism diagnosis mainly since it is regarded as nonquantitative. So the
investigators design this study to search the capacity and accuracy of SUV provided by SPECT
and CT(CT is used for reconstruction algorithm) in diagnosing GD.
This is a multiple-center study containing nine groups in China that use GE Discovery NM/CT,
an advanced equipment. Thus, the data can be more accurate and more available.
And this is a perspective clinical trial, taking about eight months. The investigators plan
to evaluate at least 50 Grave's Disease(GD) patients and 50 normal humans as contrast in
all.
Every GD patient must have been diagnosed and the results of thyroid function tests(such as
TSH,FT3,FT4） must be available. If necessary, the patient's rate of iodine uptake should
also be known before he/she being included in this study. As for normal people, the results
of thyroid function tests should be within the range of normal value.
The data of each participant will be gathered and stored. And the data processing will be
done with the help of GE staff, using the software Q.Metrix to get the value of SUVmean,
SUVmax. Finally T test will be used in comparison of the differences.
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Observational Model: Case Control, Time Perspective: Cross-Sectional
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