Department of Radiology, Toyohashi Municipal Hospital, 50 Aza Hachiken Nishi, Aotake-Cho, Toyohashi, Aichi, 4418570, Japan.
Department of Quantum Medical Technology, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 9200942, Japan.
Ann Nucl Med. 2021 Aug;35(8):937-946. doi: 10.1007/s12149-021-01631-6. Epub 2021 May 24.
We previously developed a custom-design thoracic bone scintigraphy-specific phantom ("SIM 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.
Four spherical lesions of 13-, 17-, 22-, and 28-mm diameters in the vertebrae of SIM 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.
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.
The developed software automatically classified the detectability of hot lesions in the SIM 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.
我们之前开发了一种定制设计的胸部骨骼闪烁照相专用体模（“SIM 骨骼体模”），用于评估骨单光子发射计算机断层扫描（SPECT）中的图像质量。本研究旨在开发一种用于骨 SPECT 成像技术的自动评估系统，并验证该系统的有效性。
SIM 骨骼体模的椎骨中模拟胸部填充有 13、17、22 和 28mm 直径的四个球形病变，放射性活度（靶与背景比：4）。进行 15min 动态 SPECT 采集；使用有序子集期望最大化在 3-15min 时间点进行重建。因此，获得了 216 个病变（54 个 SPECT 图像）：120 个和 96 个病变分别用于软件开发和验证。开发的软件使用统计参数映射来刚性注册并自动计算定量指标（对比噪声比、%方差系数、%可探测等效体积、恢复系数、靶与正常骨比和半最大值全宽）。使用探测得分（DS）来定义四个观察类型（4，优秀；3，足够；2，平均；1，差）来对热球形病变进行评分。三位经验丰富的核医学技师独立使用这四种观察类型对 DS 进行分类，以确定金标准；之后，对 DS 的金标准达成共识。使用 120 个病变进行开发，基于定量指标进行决策树分析以确定 DS。我们使用 96 个病变进行验证，验证了定量指标及其自动分类的阈值的有效性。
自动计算的定量指标的趋势一致。决策树分析产生了四个终端组；两个定量指标（%可探测等效体积和对比噪声比）用于分类 DS。使用 96 个病变进行验证，自动分类的 DS 与金标准几乎完全一致。在 96 个病变中，百分比一致性和kappa 系数分别为 91.7%和 0.93。
使用自动计算的定量指标，开发的软件可以自动对 SIM 骨骼体模中热病变的可探测性进行分类，这表明该软件可以在数据输入后提供一种自动进行可探测性分析的方法，其具有出色的可重复性和准确性。
