Mct64

As a routine protocol of FDG-PET, after fasting more than 4 h, patients were intravenously injected with 5.18 MBq/kg of FDG. After 1 h, PET image was acquired from the skull base to the proximal thigh using dedicated PET/CT scanners (Biograph mCT 40 or mCT 64, Siemens, Erlangen, Germany) for 1 min per bed. A Gaussian filter (FWHM 5 mm) was applied to reduce noise, and images were reconstructed using an ordered-subset expectation maximization algorithm (2 iterations and 21 subsets).

5‐HT_1B receptor binding was measured with the radioligand [¹¹C]AZ10419369, which was synthesized as described previously (da Cunha‐Bang et al., 2017). An intravenous bolus injection of the radioligand was given over 20 s, followed by 81‐min dynamic data acquisition. Data were arranged into 43 frames (12 × 10, 6 × 20, 6 × 60, 8 × 120, and 11 × 300 s) and reconstructed using the ordered subset expectation maximization method with a coregistered computed tomography (CT)‐based attenuation correction map, 4 iterations, 21 subsets, and 4 mm FWHM filter. For CT‐based attenuation correction, a low‐dose CT image (120 kVp, 36–40 mAs, less than 0.5 mSv effective dose) of the head was performed on Siemens Biograph TruePoint 40/64 or mCT 64 PET/CT scanners based on availability, with bilinear scaling to 511 keV (Carney et al., 2006), with the minor adaptation of the method as implemented on Siemens Biograph PET/CT (Ladefoged et al., 2015).

FDG PET scans were performed using dedicated PET/CT scanners of our center: Biograph mCT40 and mCT64 (Siemens Medical Solutions, Erlangen, Germany). As a routine clinical protocol, after 8 hours of fasting, the patients were intravenously injected with 5.18 MBq/kg (0.14 mCi/kg) of F‐18 FDG. The images from the thighs to the cranial vertex were obtained 60 min after the injection. PET data were reconstructed by an iterative algorithm. All PET images were interpreted using the dedicated software syngo.via (Siemens Medical Solutions, Erlangen, Germany). Imaging parameters, including the maximal standardized uptake value (SUV_max), were evaluated by manually drawing a volume of interest over the thyroid lesion. To conduct the correlation analysis between transcriptome‐level features and imaging features, we utilized SUV_max as it is a widely accepted measure for tumor metabolism in clinical practice and represents the most metabolically active part of the tumor.

All patients fasted for at least 6 hours, and blood glucose levels were confirmed to be < 140 mg/dL. 5.18 MBq/kg (0.14 mCi/kg) of ¹⁸F-FDG was intravenously injected, and PET/CT was performed 60 minutes after injection using dedicated PET/CT scanners (Biograph mCT40 or mCT64, Siemens Healthcare). A low-dose CT scan (120 kVp, 50 mAs) was performed first for attenuation correction and anatomical localization, and PET images were obtained from the skull base to the proximal thigh for 1 minute per bed position (6–7 bed positions for a patient). PET images were reconstructed by an iterative algorithm (ordered subset expectation maximization, iteration 2, subset 21). Images were reviewed by two specialists (J.C.P. with 20-year experience and R.L. with 5-year experience), who were unaware of patient and clinical information. On PET/CT fusion images, a volume of interest was drawn carefully to encircle the primary breast tumor and SUV_max was measured using an analysis software package (Syngo.via, Siemens Healthcare) as the index for glucose metabolism.