Hajime Ichikawa1,2, Kazunori Kawakami3, Masahisa Onoguchi4, Takayuki Shibutani2, Kazuki Nagatake5, Tetsuo Hosoya5, Toshimune Ito6, Toyohiro Kato1, Hirotatsu Tsuchikame7, Hideki Shimada1. 1. Department of Radiology, Toyohashi Municipal Hospital, 50 Aza Hachiken Nishi, Aotake-Cho, Toyohashi, Aichi, 4418570, Japan. 2. Department of Quantum Medical Technology, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 9200942, Japan. 3. Diagnostic Products Marketing Dept, FUJIFILM Toyama Chemical Co, Ltd. 14-1, Kyobashi 2-Chome, Chuo-Ku, Tokyo, 1040031, Japan. 4. Department of Quantum Medical Technology, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 9200942, Japan. onoguchi@staff.kanazawa-u.ac.jp. 5. Quality Assurance Department, FUJIFILM Toyama Chemical Co., Ltd, 14-1, Kyobashi 2-Chome, Chuo-Ku, Tokyo, 1040031, Japan. 6. Department of Radiological Technology, Faculty of Medical Technology, Teikyo University, 2-11-1 Kaga, Itabashi-ku, Tokyo, 173-8605, Japan. 7. Department of Radiology, Saiseikai Yokohamashi Tobu Hospital, Tsurumi Ward, 3-6-1 Shimosueyoshi, Yokohama, Kanagawa, 2300012, Japan.
Abstract
OBJECTIVE: We previously developed a custom-design thoracic bone scintigraphy-specific phantom ("SIM2 bone phantom") to assess image quality in bone single-photon emission computed tomography (SPECT). We aimed to develop an automatic assessment system for imaging technology in bone SPECT and demonstrate the validity of this system. METHODS: Four spherical lesions of 13-, 17-, 22-, and 28-mm diameters in the vertebrae of SIM2 bone phantom simulating the thorax were filled with radioactivity (target-to-background ratio: 4). Dynamic SPECT acquisitions were performed for 15 min; reconstructions were performed using ordered subset expectation maximization at 3-15-min timepoints. Consequently, 216 lesions (54 SPECT images) were obtained: 120 and 96 lesions were used for software development and validation, respectively. The developed software used statistical parametric mapping to rigidly register and automatically calculate quantitative indexes (contrast-to-noise ratio, % coefficient of variance, % detectability equivalence volume, recovery coefficient, target-to-normal bone ratio, and full width at half maximum). A detectability score (DS) was used to define the four observation types (4, excellent; 3, adequate; 2, average; 1, poor) to score hot spherical lesions. The gold standard for DSs was independently classified by three experienced board-certified nuclear medicine technologists using the four observation types; thereafter, a consensus regarding the gold standard for DSs was reached. Using 120 lesions for development, decision tree analysis was performed to determine DS based on the quantitative indexes. We verified the validation of the quantitative indexes and their threshold values for automatic classification using 96 lesions for validation. RESULTS: The trends in the automatically calculated quantitative indices were consistent. Decision tree analysis produced four terminal groups; two quantitative indexes (% detectability equivalence volume and contrast-to-noise ratio) were used to classify DS. The automatically classified DSs exhibited an almost perfect agreement with the gold standard. The percentage agreement and kappa coefficient were 91.7% and 0.93, respectively, in 96 lesions for validation. CONCLUSIONS: The developed software automatically classified the detectability of hot lesions in the SIM2 bone phantom using the automatically calculated quantitative indexes, suggesting that this software could provide a means to automatically perform detectability analysis after data input that is excellent in reproducibility and accuracy.
OBJECTIVE: We previously developed a custom-design thoracic bone scintigraphy-specific phantom ("SIM2 bone phantom") to assess image quality in bone single-photon emission computed tomography (SPECT). We aimed to develop an automatic assessment system for imaging technology in bone SPECT and demonstrate the validity of this system. METHODS: Four spherical lesions of 13-, 17-, 22-, and 28-mm diameters in the vertebrae of SIM2 bone phantom simulating the thorax were filled with radioactivity (target-to-background ratio: 4). Dynamic SPECT acquisitions were performed for 15 min; reconstructions were performed using ordered subset expectation maximization at 3-15-min timepoints. Consequently, 216 lesions (54 SPECT images) were obtained: 120 and 96 lesions were used for software development and validation, respectively. The developed software used statistical parametric mapping to rigidly register and automatically calculate quantitative indexes (contrast-to-noise ratio, % coefficient of variance, % detectability equivalence volume, recovery coefficient, target-to-normal bone ratio, and full width at half maximum). A detectability score (DS) was used to define the four observation types (4, excellent; 3, adequate; 2, average; 1, poor) to score hot spherical lesions. The gold standard for DSs was independently classified by three experienced board-certified nuclear medicine technologists using the four observation types; thereafter, a consensus regarding the gold standard for DSs was reached. Using 120 lesions for development, decision tree analysis was performed to determine DS based on the quantitative indexes. We verified the validation of the quantitative indexes and their threshold values for automatic classification using 96 lesions for validation. RESULTS: The trends in the automatically calculated quantitative indices were consistent. Decision tree analysis produced four terminal groups; two quantitative indexes (% detectability equivalence volume and contrast-to-noise ratio) were used to classify DS. The automatically classified DSs exhibited an almost perfect agreement with the gold standard. The percentage agreement and kappa coefficient were 91.7% and 0.93, respectively, in 96 lesions for validation. CONCLUSIONS: The developed software automatically classified the detectability of hot lesions in the SIM2 bone phantom using the automatically calculated quantitative indexes, suggesting that this software could provide a means to automatically perform detectability analysis after data input that is excellent in reproducibility and accuracy.
Authors: H Schirrmeister; G Glatting; J Hetzel; K Nüssle; C Arslandemir; A K Buck; K Dziuk; A Gabelmann; S N Reske; M Hetzel Journal: J Nucl Med Date: 2001-12 Impact factor: 10.057