Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
BMJ Open. 2024 Oct 14;14(10):e089552. doi: 10.1136/bmjopen-2024-089552.
Technetium thyroid uptake (TcTU) measured by single-photon emission CT/CT (SPECT/CT) is an important diagnostic tool for the differential diagnosis of Graves' disease and destructive thyroiditis. Artificial intelligence (AI) may reduce CT-induced radiation exposure by substituting the role of CT in attenuation correction (AC) and thyroid segmentation, thus realising CT-free SPECT. This study aims to compare the diagnostic accuracy for the differential diagnosis of thyrotoxicosis between CT-free SPECT and SPECT/CT.
The AI-based CT-free SPECT is a single-blind, multicentre, prospective, non-inferiority, clinical trial with a paired design conducted in the Republic of Korea. Eligible participants are adult (≥19 years old) thyrotoxicosis patients without a previous history of hyperthyroidism or hypothyroidism. Approximately 160 subjects will be screened for quantitative thyroid SPECT/CT using Tc-99m pertechnetate. CT-free thyroid SPECT will be realised using only SPECT data by the trained convolutional neural networks. TcTU will be calculated by SPECT/CT and CT-free SPECT in each subject. The primary endpoint is the accuracy of diagnosing Graves' disease using TcTU. The trial will continue until 152 completed datasets have been enrolled to assess whether the 95% (two-sided) lower confidence limit of the accuracy difference (CT-free SPECT accuracy-SPECT/CT accuracy) for Graves' disease is greater than -0.1. The secondary endpoints include the accuracy of diagnosing destructive thyroiditis and predicting the need for antithyroid drug prescription within 1 month of the SPECT/CT.
The study protocol has been approved by the institutional review board of Seoul National University Bundang Hospital (IRB No. B-2304-824-301), Konkuk University Medical Center (IRB No. 2023-05-022-006) and Chonnam National University Hospital (IRB No. CNUH-2023-108). Findings will be disseminated as reports, presentations and peer-reviewed journal articles.
KCT0008387, Clinical Research Information Service of the Republic of Korea (CRIS).
锝甲状腺摄取率（TcTU）的单光子发射 CT/CT（SPECT/CT）测量是格雷夫斯病和破坏性甲状腺炎鉴别诊断的重要诊断工具。人工智能（AI）可以通过替代 CT 在衰减校正（AC）和甲状腺分割中的作用来减少 CT 引起的辐射暴露，从而实现无 CT 的 SPECT。本研究旨在比较无 CT 的 SPECT 和 SPECT/CT 在鉴别诊断甲状腺毒症中的诊断准确性。
基于 AI 的无 CT 的 SPECT 是一项在韩国进行的单盲、多中心、前瞻性、非劣效性、临床研究，采用配对设计。合格的参与者是年龄在 19 岁及以上的、无甲亢或甲减既往病史的甲状腺毒症患者。大约 160 名患者将接受 Tc-99m 高锝酸盐的定量甲状腺 SPECT/CT 筛查。无 CT 的甲状腺 SPECT 将仅使用经过训练的卷积神经网络的 SPECT 数据来实现。在每个患者中，TcTU 将通过 SPECT/CT 和无 CT 的 SPECT 计算。主要终点是使用 TcTU 诊断格雷夫斯病的准确性。该试验将继续进行，直到有 152 个完整数据集入组，以评估诊断格雷夫斯病的准确性差异（无 CT 的 SPECT 准确性-SPECT/CT 准确性）的 95%（双侧）置信下限是否大于-0.1。次要终点包括诊断破坏性甲状腺炎的准确性和预测 SPECT/CT 后 1 个月内是否需要抗甲状腺药物处方的准确性。
该研究方案已获得首尔国立大学盆唐医院机构审查委员会（IRB 编号：B-2304-824-301）、孔敬大学医学中心（IRB 编号：2023-05-022-006）和全南国立大学医院（IRB 编号：CNUH-2023-108）的批准。研究结果将以报告、演讲和同行评议的期刊文章形式发表。
KCT0008387，韩国临床研究信息服务（CRIS）。
