title: Thoracic cavity definition for 3D PET/CT analysis and visualization.
abstract: X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical details on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage=99.2% and leakage=0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment.
authors.affiliation: School of Electrical Engineering and Computer Science, Penn State University, University Park, PA, United States.
authors.forename: Ronnarit
authors.initials: R
authors.lastname: Cheirsilp
authors.affiliation: Department of Medicine, Division of Pulmonary, Allergy, and Critical Care, Penn State University, Milton S. Hershey Medical Center, Hershey, PA, United States.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Bascom
authors.affiliation: Department of Radiology, Penn State University, Milton S. Hershey Medical Center, Hershey, PA, United States.
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Allen
authors.affiliation: School of Electrical Engineering and Computer Science, Penn State University, University Park, PA, United States. Electronic address: weh2@psu.edu.
authors.forename: William E
authors.initials: WE
authors.lastname: Higgins
mesh_terms: D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D049268:Positron-Emission Tomography / Q000379:methods*; D035423:Thoracic Cavity; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: CT imaging; Chest; Image segmentation; Lung cancer; Multimodal imaging; PET/CT; Pulmonary imaging; Thoracic region segmentation; Visualization