A new automated delineation method for SPECT lung scans using adaptive dual‐exponential thresholding

An accurate method for delineating lung contours in single photon emission computed tomography (SPECT) is critical to respiratory studies such as pulmonary embolism (PE) and respiratory aerosol deposition. Current delineation methods are not adaptive in nature and may require a priori information on lung volumes. We have developed a dual‐exponential thresholding method that solely requires SPECT scans, and is fast, accurate, and adaptive in nature. A dataset consisted of 90 patients was studied retrospectively. While most were suspected of PE, other pulmonary disorders were also present. SPECT ventilation scans were obtained after inhalation of ∼40 MBq of 99mTc‐Technegas. Examination of the corresponding natural logarithmically transformed histograms revealed dual exponential functions like pattern. Adaptive thresholds were found as the intercept between the two exponential functions. 350 Monte Carlo simulations representative of normally‐ventilated scans with varying counts were used to quantitatively measure and evaluate the method. Our method correctly delineated lung volumes to above 97% agreement for 310 of the 350 Monte Carlo simulations with maximum count values greater than or equal to 31. The 40 low‐count simulations were included purely as extreme cases. For real patient scenario, an experienced physician was called upon to visually delineate a sample of 50 actual patient scans, and these delineated lung volumes were used as gold standard and compared with those delineated using our method. Our results had an average of 96% agreement. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 22–27, 2007