PT - JOURNAL ARTICLE AU - Hara, Takeshi AU - Katafuchi, Tetsuro AU - Ito, Satoshi AU - Suzuki, Tokifumi AU - Matsumoto, Takuya AU - Zhou, Xiangrong AU - Fujita, Hiroshi TI - Automated temporal subtraction scheme of torso FDG-PET scans by using a statistical shape model for normal cases DP - 2011 May 01 TA - Journal of Nuclear Medicine PG - 2097--2097 VI - 52 IP - supplement 1 4099 - http://jnm.snmjournals.org/content/52/supplement_1/2097.short 4100 - http://jnm.snmjournals.org/content/52/supplement_1/2097.full SO - J Nucl Med2011 May 01; 52 AB - 2097 Objectives To develop an automated scheme of temporal subtraction for torso FDG-PET scan as a quantitative image analysis method by using a statistical method to obtain Z-scores of the lesion SUV. Methods We configured a normal model that indicates the normal range of SUV voxel by voxel. All of the normal scans were automatically registered into one model by using automated recognition method of bladder, liver, and body surface technique and 3D image deformation approach by using Affine transformation and thin-plate-spline technique. Z-scores of SUV (Score) were defined as deviations using the mean (M) and the standard deviation (SD) : Z-score(x, y, z) = {DeformedSUV(x, y, z) - M(x, y, z)} / SD(x, y, z). The mean and the standard deviation at a voxel were extracted from the normal model at the corresponding position in the deformed patient volume. The differences of SUV (ΔSUV) and Z-score (ΔZ-score) were obtained after the body region was deformed to fit the model. Results Normal cases of 243 (Male: 143, Female: 100) were employed to determine the normal metabolism distribution of FDG, and 63 abnormal cases were analyzed. The Z-scores for normal cases were in the range from zeros to plus/minus 2 SD. Most of the Z-scores in suspicious spots that the SUVmax were less than 5.0 showed statistical abnormalities (Z-score >2.0). Conclusions We have developed a quantitative image analysis scheme to estimate the abnormalities by the score of SUV by using the normal model and an automated subtraction method between current and previous PET scans. The subtraction images may be useful in interpretation of FDG-PET scans to confirm interval changes during chemotherapy and cancer progress diagnosis. Research Support This work is supported partly by a grant from Japan Government Grant-in-Aid for Scientific Research (C) 19500385