RT Journal Article
SR Electronic
T1 Automated temporal subtraction scheme for FDG-PET scans by using a statistical model for normal cases
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 1334
OP 1334
VO 51
IS supplement 2
A1 Takeshi Hara
A1 Tokifumi Suzuki
A1 Tomoya Asai
A1 Tetsuro Katafuchi
A1 Satoshi Itoh
A1 Tatsunori Kobayashi
A1 Hiroshi Fujita
YR 2010
UL http://jnm.snmjournals.org/content/51/supplement_2/1334.abstract
AB 1334 Objectives The purpose of this study was to develop a new method for quantitative analysis of SUV of FDG-PET scans to examine the normality and temporal changes by use of a score which is based on the range of SUV on normal cases. Methods Our scheme consisted of two approaches which included the construction of a normal model and the determination of the score as an index for the abnormality of a FDG-PET scan. To construct the normal model, all of the normal scans were registered into one model which indicated the normal range of SUV at all voxels. The body surface and organs were deformed into the model by using a thin-plate-spline (TPS) technique. In order to determine the abnormality of SUV based on the deviation estimated from many normal cases in this study, we obtained a score based on the 3D visualization of the deviations derived from a simple statistical approach. The deviation was calculated based on the mean (M) and the standard deviation (SD). Results We employed 243 (Male: 143, Female: 100) normal cases to determine the normal metabolism distribution of FDG and also 63 abnormal cases with 73 cancer lesions. The scores for normal cases in all voxels were in the range from zeros to plus/minus 2 SD. Most of the scores of abnormal regions associated with cancer and metastasis were larger than the upper limit of the model. The SUV of an abnormal spot in colon cancer was 2.07 but the score was determined as 5.55 based on the deviation from the M and SD. With the body registration method, the temporal subtraction images for SUV were also obtained by using the previous and current images. Conclusions Our computerized scheme would be useful for visualization and comparison of changing lesions on FDG-PET scans. Research Support This work is supported partly by a grant from Japan Government Grant-in-Aid for Scientific Research (C) 19500385