You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Metabolic response demonstrated by 18F-FDG-PET/CT in metastatic medullary thyroid carcinoma under sorafenib therapy. A 51-year-old woman with a medullary thyroid carcinoma (MTC) presented with a palpable nodule in the right breast. Serum calcitonin was 1,453 pg/ml and carcinoembryonic antigen was 201 ng/ml. Cervical ultrasound and bone scintigraphy were normal. Computed tomography (CT) showed nodules in the right breast and anterior thoracic wall and a hypodense lesion in the right hepatic lobe. Histology of the breast nodule confirmed metastasis from MTC. To evaluate the metabolic activity of these lesions, 18F-fluorodeoxiglucose positron emission tomography-CT (FDG-PET/CT) scan was requested. Axial fused images revealed high FDG uptake by the breast and thoracic wall nodules and the right hepatic lobe. FDG-PET/CT also showed uptake in sacrum and right iliac bone, undetected by CT and bone scintigraphy. After seven cycles of sorafenib PET/CT became negative. Calcitonin decreased to 82.5. A PET/CT performed 6 months later remained negative. This is the first published image of the complete metabolic response of MTC to sorafenib therapy using FDG-PET/CT.
{"Chemical": ["sorafenib", "18F-fluorodeoxiglucose", "FDG", "18F-FDG"]}