Easy detection of tumor in oncologic whole-body PET by projection reconstruction images with maximum intensity projection algorithm

Whole-body PET scanning for an oncology study produces a large number of tr ansaxial images by data acquisition over multiple bed positions. The sagitt al and coronal reformatted images are often used for better understanding o f radioisotope distribution. We reduced the number of PET images by calcula ting projection images and evaluated the merit of additional data processin g for the visualization and detection of tumors. After reconstructing whole -body F-18-FDG PET images (6-8 bed positions) of eight cancer patients, ant ero-posterior and lateral projection images were calculated by the maximum intensity projection (MIP) algorithm, the standard deviation projection (SD ) algorithm and the summed voxel projection (SUM) algorithm. The projection images were compared with 2D whole-body images for visualizing foci. The f ocal uptakes of various positions in original whole-body PET data (294-392 transaxial images) were visualized on only two MIP reformatted images when superimposition of hot spots did not occur. Even if one hot spot was superi mposed over the other hot spot, we could recognize the existence of at leas t one focus and determine the true positions of the hot spots from correspo nding transaxial images. The SD image was found inferior for showing a cont rast of small foci to the corresponding MIP images in the neck, mediastinum and abdomen. The SUM image failed to visualize many metastatic lesions. MI P is a promising technique for the easy preliminary assessment of tumor dis tribution in oncologic whole-body PET study.