Predicting 18F-FDG SUVs of metastatic pulmonary nodes from CT images in patients with differentiated thyroid cancer by using a convolutional neural network

PurposeThe aim of this study was to predict standard uptake values (SUVs) from computed tomography (CT) images of patients with lung metastases from differentiated thyroid cancer (DTC-LM).MethodsWe proposed a novel SUVs prediction model using 18-layer Residual Network for generating SUVmax, SUVmean, SUVmin of metastatic pulmonary nodes from CT images of patients with DTC-LM. Nuclear medicine specialists outlined the metastatic pulmonary as primary set. The best model parameters were obtained after five-fold cross-validation on the training and validation set, further evaluated in independent test set. Mean absolute error (MAE), mean squared error (MSE), and mean relative error (MRE) were used to assess the performance of regression task. Specificity, sensitivity, F1 score, positive predictive value, negative predictive value and accuracy were used for classification task. The correlation between predicted and actual SUVs was analyzed.ResultsA total of 3407 nodes from 74 patients with DTC-LM were collected in this study. On the independent test set, the average MAE, MSE and MRE was 0.3843, 1.0133, 0.3491 respectively, and the accuracy was 88.26%. Our proposed model achieved high metric scores (MAE=0.3843, MSE=1.0113, MRE=34.91%) compared with other backbones. The predicted SUVmax (R2 = 0.8987), SUVmean (R2 = 0.8346), SUVmin (R2 = 0.7373) were all significantly correlated with actual SUVs.ConclusionThe novel approach proposed in this study provides new ideas for the application of predicting SUVs for metastatic pulmonary nodes in DTC patients

Repurposing homoharringtonine for thyroid cancer treatment through TIMP1/FAK/PI3K/AKT signaling pathway

Summary: Homoharringtonine (HHT), an alkaloid isolated from Cephalotaxus, is an effective anti-leukemia agent and exhibits inhibitory effects in various solid tumors. However, the impacts of HHT treatment on thyroid cancer (TC) remain unclear. Our findings demonstrated that HHT exhibited remarkable anti-TC activity that involved inhibiting cell proliferation, invasion, and migration, as well as inducing apoptosis. Proteomics analysis revealed that the expression of the tissue inhibitor of metalloproteinase 1 (TIMP1) was downregulated in TC cells after HHT treatment. TIMP1 overexpression promoted TC progression and partially reversed the anti-TC effects of HHT, while TIMP1 downregulation inhibited TC progression and enhanced the anti-TC effects of HHT. Furthermore, TIMP1 re-expression attenuated the enhancement of anti-TC effects of HHT induced by TIMP1 knockdown. Mechanistically, HHT exerted anti-TC effects by downregulating TIMP1 expression and then inactivating the FAK/PI3K/AKT signaling pathway. Taken together, our study demonstrated that HHT could inhibit TC progression by inhibiting the TIMP1/FAK/PI3K/AKT signaling pathway