Increasing evidence indicates that sarcopenia and obesity can be risk factors for incident dementia. We investigated the association of body composition including muscle and visceral adipose tissue (VAT) with the probability of Alzheimer’s disease (AD) in healthy middle-aged and elderly subjects using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT). This study included 110 healthy subjects with available whole-body FDG PET/CT scans and medical records. Muscle and VAT tissues were measured on the abdominal CT slice, and the PMOD Alzheimer’s discrimination FDG PET analysis tool (PALZ) score was evaluated on the brain PET of the same subject using software PALZ. Skeletal muscle index (r: −0.306; P = 0.031) was significantly negatively associated with the PALZ score in the elderly patients. Muscle area (β: −0.640; P = 0.043) and skeletal muscle index (β: −0.557; P = 0.043) were independently associated with the PALZ score in elderly subjects after adjustments for sex, duration of education, hypertension, diabetes mellitus, and smoking and drinking status. Increased muscle tissue was associated with a lower probability of AD in elderly subjects, but VAT was not associated with a lower probability of AD in middle-or older-aged adults.

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).

Cho SG, et al. Korean J Radiol. 2023 Oct;24(10):1017-1027. https://doi.org/10.3348/kjr.2023.0149