A smart and operator independent system to delineate tumours in Positron Emission Tomography scans. (1st November 2018)

• Record Type: Journal Article
• Authors: Comelli, Albert; Stefano, Alessandro; Russo, Giorgio; Sabini, Maria Gabriella; Ippolito, Massimo; Bignardi, Samuel; Petrucci, Giovanni; Yezzi, Anthony
• Is Part Of: Computers in biology and medicine. Volume 102(2018)
• Page Start: 1
• Page End: 15
• Publication Date: 2018-11-01
• Subjects: Cancer segmentation -- Active contour algorithm -- 18F-fluoro-2-deoxy-d-glucose and 11C-labeled methionine PET imaging -- Biological target volume; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2018.09.002
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Positron Emission Tomography (PET) imaging has an enormous potential to improve radiation therapy treatment planning offering complementary functional information with respect to other anatomical imaging approaches. The aim of this study is to develop an operator independent, reliable, and clinically feasible system for biological tumour volume delineation from PET images. Under this design hypothesis, we combine several known approaches in an original way to deploy a system with a high level of automation. The proposed system automatically identifies the optimal region of interest around the tumour and performs a slice-by-slice marching local active contour segmentation. It automatically stops when a "cancer-free" slice is identified. User intervention is limited at drawing an initial rough contour around the cancer region. By design, the algorithm performs the segmentation minimizing any dependence from the initial input, so that the final result is extremely repeatable. To assess the performances under different conditions, our system is evaluated on a dataset comprising five synthetic experiments and fifty oncological lesions located in different anatomical regions (i.e. lung, head and neck, and brain) using PET studies with 18F-fluoro-2-deoxy- d -glucose and 11C-labeled Methionine radio-tracers. Results on synthetic lesions demonstrate enhanced performances when compared against the most common PET segmentation methods. In clinical cases, the proposed system produces accurate segmentations (average dice similarity coefficient: 85.36 ± 2.94%, 85.98 ± 3.40%, 88.02 ± 2.75% in the lung, head and neck, and brain district, respectively) with high agreement with the gold standard (determination coefficient R 2 = 0.98). We believe that the proposed system could be efficiently used in the everyday clinical routine as a medical decision tool, and to provide the clinicians with additional information, derived from PET, which can be of use in radiation therapy, treatment, and planning. Graphical abstract: Image 1 Highlights: An innovative system for the segmentation of biological tumour volumes in PET images. Automatic identification of an operator independent mask containing the tumour. A slice-by-slice local active contour based approach. Automatic termination condition to obtain a process nearly full automatic.