BACKGROUND: Developments in image reconstruction techniques for planar imaging, also known as enhanced planar processing (EPP), enabled the possibility to reconstruct planar scintigraphic images with low count statistics, providing the opportunity to reduce image acquisition times. In this study, the performance of EPP for oncologic half-time bone scintigraphy images was evaluated. METHODS: The EPP software was evaluated for different imaging conditions using standardized phantom experiments. Additionally, 51 patients with prostate and breast cancer were prospectively included and underwent bone scintigraphy using a standard and half-time protocol. Independent reading was performed on three image types (standard, half-time non-processed, and half-time EPP) by three observers, scoring the number and anatomical location of lesions, image quality, and diagnostic confidence by which the definitive diagnosis was made. RESULTS: EPP images had improved contrast and lower noise levels compared to the non-processed half-time images. It was determined that EPP images acquired at double scan speed had similar image quality to the standard non-processed images. There was substantial agreement with respect to diagnosis and diagnostic confidence based on all three image types between the observers. Image quality in the EPP images was higher with respect to the non-processed half-time images, and was comparable to the standard images. CONCLUSION: Diagnostic confidence was not affected by reduction in image acquisition time. There was substantial agreement between all three observers with respect to the diagnosis provided in all three image types. Subjective and objective image quality improved when half-time images were processed with EPP software.
|Journal||Quarterly journal of nuclear medicine and molecular imaging|
|Publication status||Published - Sep 2018|
Grootjans, W., Serem, S. J., Gomes, M. I., Heijmen, L., Bulten, B., Mijnheere, E. P., ... van den Broek, W. J. (2018). Half-time bone scintigraphy in prostate and breast cancer patients. Quarterly journal of nuclear medicine and molecular imaging, 62(3), 303-312. https://doi.org/10.23736/S1824-4785.16.02830-2