PURPOSE: To evaluate the effectiveness of the single-energy metal artifact reduction (SEMAR) technique for improving the accuracy of I-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy. METHODS AND MATERIALS: Postimplant CT images of 40 patients treated with I-125 prostate brachytherapy were acquired. For all patients, 2 data sets were reconstructed, 1 with SEMAR algorithms (SEMAR image), and the other without SEMAR algorithms (non-SEMAR image). Seed locations are automatically detected by the automatic seed finder tool, and their locations were compared between the SEMAR and non-SEMAR images. Dosimetric parameters using seed locations as detected were compared. RESULTS: The true-positive fraction of properly detected seeds on the SEMAR image as determined from a reference seed distribution defined by one investigator was significantly higher than the true-positive fraction on the non-SEMAR image (p = 0.011). The variabilities in D90 (p = 0.001), V100 (p = 0.007), and V150 (p = 0.007) were significantly reduced for seed location on the SEMAR image as compared with non-SEMAR image. CONCLUSIONS: Prostate postimplant CT with SEMAR improved the accuracy of seed localization and postimplant dosimetric parameters. Copyright Â
PURPOSE: To evaluate the effectiveness of the single-energy metal artifact reduction (SEMAR) technique for improving the accuracy of I-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy. METHODS AND MATERIALS: Postimplant CT images of 40 patients treated with I-125 prostate brachytherapy were acquired. For all patients, 2 data sets were reconstructed, 1 with SEMAR algorithms (SEMAR image), and the other without SEMAR algorithms (non-SEMAR image). Seed locations are automatically detected by the automatic seed finder tool, and their locations were compared between the SEMAR and non-SEMAR images. Dosimetric parameters using seed locations as detected were compared. RESULTS: The true-positive fraction of properly detected seeds on the SEMAR image as determined from a reference seed distribution defined by one investigator was significantly higher than the true-positive fraction on the non-SEMAR image (p = 0.011). The variabilities in D90 (p = 0.001), V100 (p = 0.007), and V150 (p = 0.007) were significantly reduced for seed location on the SEMAR image as compared with non-SEMAR image. CONCLUSIONS: Prostate postimplant CT with SEMAR improved the accuracy of seed localization and postimplant dosimetric parameters. Copyright Â