Purpose: 2-[18F]FDG PET/CT plays an important role in the management of pulmonary nodules. Convolutional neural networks (CNNs) automatically learn features from images and have the potential to improve the discrimination between malignant and benign pulmonary nodules. The purpose of this study was to develop and validate a CNN model for classification of pulmonary nodules from 2-[18F]FDG PET images. Methods: One hundred thirteen participants were retrospectively selected. One nodule per participant. The 2-[18F]FDG PET images were preprocessed and annotated with the reference standard. The deep learning experiment entailed random data splitting in five sets. A test set was held out for evaluation of the final model. Four-fold cross-validation was performed from the remaining sets for training and evaluating a set of candidate models and for selecting the final model. Models of three types of 3D CNNs architectures were trained from random weight initialization (Stacked 3D CNN, VGG-like and Inceptionv2-like models) both in original and augmented datasets. Transfer learning, from ImageNet with ResNet-50, was also used. Results: The final model (Stacked 3D CNN model) obtained an area under the ROC curve of 0.8385 (95% CI: 0.6455–1.0000) in the test set. The model had a sensibility of 80.00%, a specificity of 69.23% and an accuracy of 73.91%, in the test set, for an optimised decision threshold that assigns a higher cost to false negatives. Conclusion A 3D CNN model was effective at distinguishing benign from malignant pulmonary nodules in 2-[18F]FDG PET images.

OBJECTIVE: To identify and synthesize the most recent available evidence of effectiveness of acupuncture on pain, physical function and health-related quality of life (HRQoL) in patients with rheumatoid arthritis (RA). METHODS: A comprehensive search of 12 Western and Chinese databases was undertaken from their inception up to end of 2016. Randomized controlled trials (RCTs), concerning patients with RA treated with needle acupuncture, written in English, Portuguese, German or Chinese were included. Primary outcomes included pain, physical function and HRQoL. Secondary outcomes included morning stiffness, functional impairment, number of tender and swollen joints and serum concentrations of inflamatory markers. Methodological quality was assessed by three independent reviewers using the standardized critical appraisal instrument from the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument. RESULTS: Twenty-two studies met the inclusion criteria. Of those, 9 studies were excluded after assessment of their methodological quality. The remaining 13 original RCTs included 974 patients. Ten of these studies published in China, showed favorable statistical significant effects of acupuncture in relieving symptoms of RA compared with controls. CONCLUSIONS Evidence suggests that acupuncture interventions may have a positive effect in pain relief, physical function and HRQoL in RA patients. However, due to the heterogeneity and methodologic limitations of the studies included in this systematic review, evidence is not strong enough to produce a best practice guideline.