Artificial intelligence-based CT-free quantitative thyroid SPECT for thyrotoxicosis: study protocol of a multicentre, prospective, non-inferiority study - Jae Hoon Moon; Ji Hye Kim; Soyeon Ahn; Dongkyu Oh; Hyun Gee Ryoo; Hyun Woo Chung; Sang-Geon Cho; Kyounghyoun Kwon; Young So; Won Woo Lee (BMJ Open)
Introduction 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.Methods and analysis 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.Ethics and dissemination 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.Trial registration number KCT0008387, Clinical Research Information Service of the Republic of Korea (CRIS).