Renal cell cancer rarely metastasizes to the thyroid gland, and it has been reported to present as a solitary mass. We present a case of diffuse thyroid cancer metastases from renal cell cancer. Bilateral internal jugular vein tumor thrombi were also present. To the best of our knowledge, this is the first description of diffuse thyroid metastases from renal cell cancer in the English literature. Renal cell cancer metastases should be considered in the differential of thyroid imaging abnormalities arising in the setting of known renal cell carcinoma, particularly late in the course of disease. This is frequently associated with internal jugular vein thrombi, which should be evaluated with an abnormal thyroid. Thyroglobulin levels are usually normal in such patients.

Objective

The objective of this study was to determine if clinical dynamic PET/CT imaging with ¹¹C-L-methyl-methionine (¹¹C-MET) in healthy older women can provide an estimate of tissue-level post-absorptive and post-prandial skeletal muscle protein synthesis that is consistent with the more traditional method of calculating fractional synthesis rate (FSR) of muscle protein synthesis from skeletal muscle biopsies obtained during an infusion of L-[ring ¹³C₆] phenylalanine (¹³C₆-Phe).

Methods

Healthy older women (73 ± 5 years) completed both dynamic PET/CT imaging with ¹¹C-MET and a stable isotope infusion of ¹³C₆-Phe with biopsies to measure the skeletal muscle protein synthetic response to 25 g of a whey protein supplement. Graphical estimation of the Patlak coefficient K_i from analysis of the dynamic PET/CT images was employed as a measure of incorporation of 11 C-MET in the mid-thigh muscle bundle.

Results

Post-prandial values [mean ± standard error of the mean (SEM)] were higher than post-absorptive values for both K_i (0.0095 ± 0.001 vs. 0.00785 ± 0.001 min^-1, p < 0.05) and FSR (0.083 ± 0.008 vs. 0.049 ± 0.006%/h, p < 0.001) in response to the whey protein supplement. The percent increase in K_i and FSR in response to the whey protein supplement was significantly correlated (r = 0.79, p = 0.015).

Conclusions

Dynamic PET/CT imaging with ¹¹C-MET provides an estimate of the post-prandial anabolic response that is consistent with a traditional, invasive stable isotope, and muscle biopsy approach. These results support the potential future use of ¹¹C-MET imaging as a non-invasive method for assessing conditions affecting skeletal muscle protein synthesis.

Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (¹⁸F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to that of radiologic readers. Materials and Methods Prospective ¹⁸F-FDG PET brain images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (2109 imaging studies from 2005 to 2017, 1002 patients) and retrospective independent test set (40 imaging studies from 2006 to 2016, 40 patients) were collected. Final clinical diagnosis at follow-up was recorded. Convolutional neural network of InceptionV3 architecture was trained on 90% of ADNI data set and tested on the remaining 10%, as well as the independent test set, with performance compared to radiologic readers. Model was analyzed with sensitivity, specificity, receiver operating characteristic (ROC), saliency map, and t-distributed stochastic neighbor embedding. Results The algorithm achieved area under the ROC curve of 0.98 (95% confidence interval: 0.94, 1.00) when evaluated on predicting the final clinical diagnosis of AD in the independent test set (82% specificity at 100% sensitivity), an average of 75.8 months prior to the final diagnosis, which in ROC space outperformed reader performance (57% [four of seven] sensitivity, 91% [30 of 33] specificity; P < .05). Saliency map demonstrated attention to known areas of interest but with focus on the entire brain. Conclusion By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Larvie in this issue.