18F-FDG Brain PET/CT 검사를 위한 데이터 비교 방법의 평가

Evaluation of Database Comparison Methods for 18F-FDG Brain PET/CT

Purpose Various database comparison methods(DCM) are used for analyzing functional neuro-imaging. It is possible to statistically evaluate decreased or increased metabolism of abnormal patient's brain by comparing with asymptomatic controls in DCM. And results of DCM are additionally used for easily explaining defect region. The aim of this study was to evaluate usefulness of statistical parametric mapping(SPM) and scenium. Materials and Methods Data of 15 patients(62.02±15.03 year) underwent ¹⁸F-FDG brain PET/CT were collected and analyzed. Biograph TruePoint 40 with TrueV, (Siemens) was used as a PET/CT scanner. Scenium(version 4.0) in Syngo.via(version VA30A) and SPM99 were applied for statistical evaluation. Consistency between PET reading and result of DCM were evaluated by 5 nuclear medicine physicians through a questionnaire survey. SUV and SD changes were evaluated by changing iteration, gaussian filter and matrix size in scenium. And average required time for generating result of SPM99 and scenium was compared by 3 medical technologists. Results Consistency from the result of SPM99 and scenium showed 84% and 92.4% compare to PET reading. When iteration 4, FWHM 8 and matrix size 168, SUV and SD were decreased by 0.59%, 8.73%, 4.69%, 20.38% and 0.88%, 8.25% respectively compare to routine parameter(iteration 8, FWHM 2 and matrix size 336) of scenium. Average required time of SPM99 and Scenium took 282 seconds and 116 seconds to generate result. Conclusion Results of SPM99 and Scenium showed high consistency compare to PET reading. Various parameters can be controled by user when using SPM. However, normal database needs to be acquired. And it takes significant amount of time and effort for the first set up. On the other hand, Scenium provides normal database even though modifiable parameters are limited. Therefore, more informations could be provided for brain PET/CT if properly understanding and selecting each DCM.