Predicting solitary pulmonary lesions in breast cancer patients using (18)fluorodeoxyglucose-positron emission tomography/computed tomography combined with clinicopathological characteristics.

Solitary pulmonary nodules (SPNs) remain difficult to diagnose for clinical therapeutic purposes in patients with a history of breast cancer. This study try to investigate the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) combined with clinicopathological predictors for the differential diagnosis of SPNs in breast cancer patients. One hundred and twenty breast cancer patients with newly detected SPNs were enrolled in the study and divided into a primary lung cancer (PLC) group and a breast cancer metastasis (BCM) group. The clinicopathological characteristics as well as metabolic and morphological characteristics on 18F-FDG-PET/CT images of 120 patients were retrospectively reviewed. The differences of clinicopathological and 18F-FDG-PET/CT characteristics between the two groups were analyzed, and multivariate analyses for the diagnosis of SPNs were performed. Clinicopathological terms of carcinoembryonic antigen (CEA) and CA15-3 levels exhibited significant differences between PLC and BCM groups (P = 0.005 and P = 0.001, respectively). Metabolic characteristics of 18F-FDG-PET/CT images included FDG uptake, SUVmax of SPNs, hilar and/or mediastinal lymph node metastasis, SUVmax of hilar and/or mediastinal lymph node, and extrapulmonary metastasis showed significant differences between PLC and BCM groups (P = 0.004, P < 0.001, P = 0.01, P = 0.032 and P = 0.023, respectively). The lobulation sign, spicule sign, and pleural indentation sign were identified as statistically different morphological features of PLC in CT images (all P < 0.001). Among these, the SUVmax of SPNs, lobulation sign, and pleural indentation sign were valuable predictive factors for accurate diagnosis of SPNs in breast cancer patients. 18F-FDG-PET/CT combined with serum tumor markers are valuable for the diagnosis of SPNs in breast cancer patients.

Xue Y ，Hou W ，He Y ，Xu A ，Li X ... -  《BMC Pulmonary Medicine》

Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules.

Chen S ，Harmon S ，Perk T ，Li X ，Chen M ，Li Y ，Jeraj R ... -  《-》

The value of 18F-FDG PET/CT in the diagnosis of different size of solitary pulmonary nodules.

Tang K ，Wang L ，Lin J ，Zheng X ，Wu Y ... -  《-》

An 18F-FDG-PET/CT-based radiomics signature for estimating malignance probability of solitary pulmonary nodule.

Some solitary pulmonary nodules (SPNs) as early manifestations of lung cancer, it is difficult to determine its nature, which brings great trouble to clinical diagnosis and treatment. Radiomics can deeply explore the essence of images and provide clinical decision support for clinicians. The purpose of our study was to explore the effect of positron emission tomography (PET) with 2-deoxy-2-[fluorine-18] fluoro-d-glucose integrated with computed tomography (CT; 18F-FDG-PET/CT) combined with radiomics for predicting probability of malignancy of SPNs. We retrospectively enrolled 190 patients with SPNs confirmed by pathology from January 2013 to December 2019 in our hospital. SPNs were benign in 69 patients and malignant in 121 patients. Patients were randomly divided into a training or testing group at a ratio of 7:3. Three-dimensional regions of interest (ROIs) were manually outlined on PET and CT images, and radiomics features were extracted. Synthetic minority oversampling technique (SMOTE) method was used to balance benign and malignant samples to a ratio of 1:1. In the training group, least absolute shrinkage and selection operator (LASSO) regression analyses and Spearman correlation analyses were used to select the strongest radiomics features. Three models including PET model, CT model, and joint model were constructed using multivariate logistic regression analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were plotted to evaluate diagnostic efficiency, calibration degree, and clinical usefulness of all models in training and testing groups. The estimative effectiveness of the joint model was superior to the CT or PET model alone in the training and testing groups. For the joint model, CT model, and PET model, area under the ROC curve was 0.929, 0.819, 0.833 in the training group, and 0.844, 0.759, 0.748 in the testing group, respectively. Calibration and decision curves showed good fit and clinical usefulness for the joint model in both training and testing groups. Radiomics models constructed by combining PET and CT radiomics features are valuable for distinguishing benign and malignant SPNs. The combined effect is superior to qualitative diagnoses with CT or PET radiomics models alone.

Zheng J ，Hao Y ，Guo Y ，Du M ，Wang P ，Xin J ... -  《-》

Is (18)F-FDG PET/CT useful for the differential diagnosis of solitary pulmonary nodules in patients with idiopathic pulmonary fibrosis?

Lee SH ，Sung C ，Lee HS ，Yoon HY ，Kim SJ ，Oh JS ，Song JW ，Kim MY ，Ryu JS ... -  《-》