Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding

作者：Yusuf Emre Erdi, Osama R. Mawlawi, Steven M. Larson, Massimo Imbriaco, HENRY W. D. YEUNG, R.D. Finn, John Laurence Humm · 发表于：Cancer · 年份：1997 · DOI：10.1002/(sici)1097-0142(19971215)80:12+<2505::aid-cncr24>3.0.co;2-f · 被引用次数：476 · 研究领域：Medical Imaging Techniques and Applications、Radiomics and Machine Learning in Medical Imaging、Lung Cancer Diagnosis and Treatment

BACKGROUND It is common protocol in radionuclide therapies to administer a tracer dose of a radiopharmaceutical, determine its lesion uptake and biodistribution by gamma imaging, and then use this information to determine the most effective therapeutic dose. This treatment planning approach can be used to quantitate accurately the activity and volume of lesions and organs with positron emission tomography (PET). In this article, the authors focus on the specification of appropriate volumes of interest (VoI) using PET in association with computed tomography (CT). METHODS The authors have developed an automatic image segmentation schema to determine the VoI of metastases to the lung from PET images, under conditions of variable background activity. An elliptical Jaszczak phantom containing a set of spheres with volumes ranging from 0.4 to 5.5 mL was filled with F-18 activity (2-3 μCi/mL) corresponding to activities clinically observed in lung lesions. Images were acquired with a cold background and then with variable source-to-background (S/B) ratios of: 7.4, 5.5, 3.1, and 2.8. Lesion VoI analysis was performed on 10 patients with 17 primary or metastatic lung lesions, applying the optimum threshold values derived from the phantom experiments. Initial volume estimates for lung lesions were determined from CT images. Approximate S/B ratios were obtained for the corresponding lesions on F-18-fluoro-2-deoxy-D-glucose (18FDG)-PET images. From the CT estimate of the lesion size and ...