Browsing by Author "Yunusa, Garba Haruna"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Open Access
    Assessment of the impact of the application single photon emission computerized tomography and SPECT-CT on lesion catergorization
    (2015) Yunusa, Garba Haruna; Brink, Anita; Mann, Michael D
    Objectives: To assess initial experience with the use of a new SPECT-CT in the evaluation of lesions. Methods: The folder number, radiopharmaceutical used and type of scan of patients examined with a new Siemens T6 SPECT-CT between 2 April and 31 December 2013 were retrieved. The number of 99m Tc -MDP bone scans was sufficient for a detailed analysis. The scans were re-processed and reported by the observer before he was given any clinical information. Whole body planar, whole body planar plus SPECT and whole body planar plus SPECT-CT images were assessed successively in three separate sessions at least two weeks apart. At each session, the certainties of detection, localisation, and categorisation of each lesion were recorded. Results: A total of 539 lesions were seen on the whole body, SPECT and CT images in 133 patients. The whole body images showed no lesions in three patients and 378 lesions in 130 patients, 117(31%) lesions in areas not covered by the SPECT. SPECT detected 122 additional lesions in 79 patients. Thirty-nine (12.2%) lesions were seen only on CT in 32 (24.1%) patients. F or the 261 lesions seen on the planar images in the SPECT FOV, lesion detection was definite in 233 (89.3%), localisation definite in 151(57.9%) and categorisation definite in 123 (47.1%) lesions. On the SPECT, definite lesion detection, localisation and categorisation were recorded respectively for 259 (99.2%), 228 (87.4%) and 176 (67.4%) of the 261 lesions. Lesion detection, localisation and categorisation certainties were definite for 100%, 99.1% and 94.7% of the SPECT-CT lesions respectively. Conclusion: Whole body planar scintigraphy is essential in lesion detection. SPECT markedly improves lesion detection and localisation and CT enhances lesion categorisation.