Detection of bladder metabolic artifacts in 18F-FDG PET imaging. (1st April 2016)

• Record Type: Journal Article
• Authors: Roman-Jimenez, Geoffrey; Crevoisier, Renaud De; Leseur, Julie; Devillers, Anne; Ospina, Juan David; Simon, Antoine; Terve, Pierre; Acosta, Oscar
• Is Part Of: Computers in biology and medicine. Volume 71(2016)
• Page Start: 77
• Page End: 85
• Publication Date: 2016-04-01
• Subjects: Image processing -- PET/CT -- Bladder artifact -- Cervical cancer -- Radiotherapy -- Nuclear medicine; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2016.02.002
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Positron emission tomography using 18 F-fluorodeoxyglucose ( 18 F-FDG-PET) is a widely used imaging modality in oncology. It enables significant functional information to be included in analyses of anatomical data provided by other image modalities. Although PET offers high sensitivity in detecting suspected malignant metabolism, 18 F-FDG uptake is not tumor-specific and can also be fixed in surrounding healthy tissue, which may consequently be mistaken as cancerous. PET analyses may be particularly hampered in pelvic-located cancers by the bladder׳s physiological uptake potentially obliterating the tumor uptake. In this paper, we propose a novel method for detecting 18 F-FDG bladder artifacts based on a multi-feature double-step classification approach. Using two manually defined seeds (tumor and bladder), the method consists of a semi-automated double-step clustering strategy that simultaneously takes into consideration standard uptake values (SUV) on PET, Hounsfield values on computed tomography (CT), and the distance to the seeds. This method was performed on 52 PET/CT images from patients treated for locally advanced cervical cancer. Manual delineations of the bladder on CT images were used in order to evaluate bladder uptake detection capability. Tumor preservation was evaluated using a manual segmentation of the tumor, with a threshold of 42% of the maximal uptake within the tumor. Robustness was assessed by randomly selecting different initial seeds. The classification averages were 0.94 ± 0.09 for sensitivity, 0.98 ± 0.01 specificity, and 0.98 ± 0.01 accuracy. These results suggest that this method is able to detect most 18 F-FDG bladder metabolism artifacts while preserving tumor uptake, and could thus be used as a pre-processing step for further non-parasitized PET analyses. Abstract : Highlights: A novel method for detecting bladder metabolic artifacts in 18F-FDG PET images. A k -means clustering method combining both multimodal PET-CT data and spatial information. The method was tested on 52 PET/CT images of cervical cancer patients. The method suppresses most of the bladder artifacts while preserving tumor uptake.