Imaging of a focal liver lesion using ordered subset expectation maximization technique

Abstract

RBC blood pool SPECT has been used to diagnose focal liver lesions such as hemangioma because of its high specificity. However, its low spatial resolution is a major limitation. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. The authors compared this new modified iterative reconstruction method with conventional filtered back projection (FBP) in the imaging of liver hemangioma. Sixty four projection data were acquired using a dual head gamma camera in 25 patients with cavernous hemangioma of the liver, and this raw data was transferred to a LINUX based personal computer. After the replacement of the header file as an interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging, which in the authors' investigation was considered to be 4 iterations and 16 subsets. After this process, all the images processed by FBP and OSEM, in the same cases, were evaluated by 3 experts. According to a blind review of 28 lesions, OSEM images revealed at least same or better qualities than FBP in nearly all cases. Although there was no significant difference in the detection of large lesions (67.9%), 5 small lesions (17.9%) were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions (14.3%). In conclusion, OSEM revealed better contrast and definition in the depiction of liver hemangioma, and a higher sensitivity in the detection of small lesions. Furthermore, this reconstruction method didn't require a higher computer system or protracted reconstruction time, therefore, OSEM offers a good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma