PET/CT-based radiomics analysis may help to predict neoadjuvant chemotherapy outcomes in breast cancer.

Background: The aim of this study was to evaluate the clinical usefulness of radiomics signature-derived 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) for the early prediction of neoadjuvant chemotherapy (NAC) outcomes in patients with (BC). Methods: A total of 124 patients with BC who underwent pretreatment PET-CT scanning and received NAC between December 2016 and August 2019 were studied. The dataset was randomly assigned in a 7:3 ratio to either the training or validation cohort. Primary tumor segmentation was performed, and radiomics signatures were extracted from each PET-derived volume of interest (VOI) and CT-derived VOI. Radiomics signatures associated with pathological treatment response were selected from within a training cohort (n = 85), which were then applied to generate different classifiers to predict the probability of pathological complete response (pCR). Different models were then independently tested in the validation cohort (n = 39) regarding their accuracy, sensitivity, specificity, and area under the curve (AUC). Results: Thirty-five patients (28.2%) had pCR to NAC. Twelve features consisting of five PET-derived signatures, four CT-derived signatures, and three clinicopathological variables were candidates for the model's development. The random forest (RF), k-nearest neighbors (KNN), and decision tree (DT) classifiers were established, which could be utilized to predict pCR to NAC with AUC ranging from 0.819 to 0.849 in the validation cohort. Conclusions: The PET/CT-based radiomics analysis might provide efficient predictors of pCR in patients with BC, which could potentially be applied in clinical practice for individualized treatment strategy formulation.

PET/CT Radiomic Features: A Potential Biomarker for EGFR Mutation Status and Survival Outcome Prediction in NSCLC Patients Treated With TKIs.

Backgrounds: Epidermal growth factor receptor (EGFR) mutation profiles play a vital role in treatment strategy decisions for non-small cell lung cancer (NSCLC). The purpose of this study was to evaluate the predictive efficacy of baseline 18F-FDG PET/CT-based radiomics analysis for EGFR mutation status, mutation site, and the survival benefit of targeted therapy. Methods: A sum of 313 NSCLC patients with pre-treatment 18F-FDG PET/CT scans and genetic mutations detection were retrospectively studied. Clinical and PET metabolic parameters were incorporated into independent predictors of determining mutation status and mutation site. The dataset was randomly allocated into the training and the validation sets in a 7:3 ratio. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with EGFR mutation profiles is built by feature selection. Three different prediction models based on support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were established. Furthermore, nomograms for estimation of overall survival (OS) and progression-free survival (PFS) were established by integrating PET/CT radiomics score (Rad-score), metabolic parameters, and clinical factors. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis and the calibration curve analysis. The decision curve analysis (DCA) was applied to estimate and compare the clinical usefulness of nomograms. Results: Three hundred thirteen NSCLC patients were classified into a training set (n=218) and a validation set (n=95). Multivariate analysis demonstrated that SUVmax and sex were independent indicators of EGFR mutation status and mutation site. Eight CT-derived RS, six PET-derived RS, and two clinical factors were retained to develop integrated models, which exhibited excellent ability to distinguish between EGFR wild type (EGFR-WT), EGFR 19 mutation type (EGFR-19-MT), and EGFR 21 mutation type (EGFR-21-MT). The SVM model outperformed the RF model and the DT model, yielding training area under the curves (AUC) of EGFR-WT, EGFR-19-WT, and EGFR-21-WT, with 0.881, 0.851, and 0.849, respectively, and validation AUCs of 0.926, 0.805 and 0.859, respectively. For prediction of OS, the integrated nomogram is superior to the clinical nomogram and the radiomics nomogram, with C-indexes of 0.80 in the training set and 0.83 in the validation set, respectively. Conclusions: The PET/CT-based radiomics analysis might provide a novel approach to predict EGFR mutation status and mutation site in NSCLC patients and could serve as useful predictors for the patients' survival outcome of targeted therapy in clinical practice.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images.

Background: Lymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes. Methods: This retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established. Results: Tumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively. Conclusions: The PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

Reproducibility and validity of dietary patterns identified using factor analysis among Chinese populations.

In the present study, we evaluated the reproducibility and validity of dietary patterns among Chinese adult populations. A random subsample of 203 participants (aged 31-80 years) from a community-based nutrition and health survey was enrolled. An eighty-seven-item FFQ was administered twice (FFQ1 and FFQ2) 1 year apart; four 3 consecutive day, 24-h dietary recalls (24-HDR, as a reference method) were performed between the administrations of the two FFQ every 3 months. Dietary patterns from three separate dietary sources were derived using factor analysis based on twenty-eight predefined food groups. Comparisons between dietary pattern scores were made by using Pearson's or intraclass correlation coefficients (ICC), cross-classification analysis, weighted κ statistic and Bland-Altman plots; the four major dietary patterns identified from FFQ1, FFQ2 and 24-HDR were similar. Regarding reproducibility, ICC for z-scores between FFQ1 and FFQ2 were all >0·6 for dietary patterns. The 'animal and plant protein' pattern had the highest ICC of 0·870. For validity, the adjusted Pearson's correlation coefficients for dietary pattern z-scores between two FFQ and the mean of four 3 consecutive day 24-HDR ranged from 0·387 for the 'Chinese traditional' pattern to 0·838 for the 'animal and plant protein' pattern. More than 75 % of the participants were classified into the same or adjacent quartile, and <5 % were misclassified into opposite quartiles. The weighted κ ranged from 0·259 to 0·680. Bland-Altman plots indicated that no significant deviation was found between two dietary assessment methods. Our findings indicate a good reasonable reproducibility and a reasonable validity of dietary patterns derived by factor analysis in China.

[A survey on the agricultural profession-related injuries among 11 902 rural residents in Shandong province].

OBJECTIVE: To understand the prevalence and risk factors of agricultural activities related injuries among rural residents in Shandong province. METHODS: A retrospective investigation was conducted among agricultural profession-related workers in 20 villages with multistage cluster sampling method in Shandong province. Four times face-to-face interview were conducted by trained interviewers, including 32 students and local medical personnel under constructed questionnaires. Accidental injuries occurred in the activities or in the agricultural profession-related jobs were recorded, from May 1(st)2009 to April 30(st) 2010. Data was input and analyzed by SPSS 13.0 statistical software. RESULTS: A total of 837 cases reported at least 1 job-related injury out of the 11 902 people who had been surveyed in one year. The crude incidence rate was 7.03% and the standardized incidence rate was 7.36%, higher in males (9.01%) than in females (4.10%), χ² = 105.53, P = 0.000. Children and adolescents (≤ 14 aged) had the higher incidence rate (9.50%), χ² = 9.70, P = 0.008. People working in the area of commercial service related to agricultural products had the highest incidence rate (12.94%). In particular, those occupations that related to agricultural construction or materials appeared to have had higher incidence rates as 16.80% and 15.59% respectively, than other kinds of jobs (χ² = 167.30, P = 0.000). There were higher proportion of injuries occurred in the roads (28.79%), in the fields (28.08%)during labor work (38.00%) transportation (27.97%), respectively. The seasonality of agricultural injures mostly occurred between June and August, accounted for 47.43%. Major external causes related to injuries were instruments or tools (31.42%) being used, transportation (24.13%) and falls (20.19%). Wounds on limbs took the majority (56.39%). The accidental self-inflicted injury occupied 76.82%, while accidents to passive injuries occupied 11.47%, other kinds accounted for 11.71%. Most of the accidents caused mild or moderate damage, accounted for 60.22% and 30.34% respectively. 7 cases died of injuries, with the fatality rate as 0.84% and the mortality rate was 58.81 per one hundred thousand. 72 cases ended up in disability caused by injuries, with the morbidity rate as 6.05 per thousand. Answers to the major internal causes of injuries appeared to be: "did not know how to protect oneself" (29.87%) with females (45.41%) in particular, followed by"over fatigue" and "inappropriate treatment" which took the 2(nd) place in males. Major natural environmental factors of injuries would relate to "high air temperature and humidity but lower wind velocity" (14.93%), "unclear signs on the country road" (12.19%), "the sky was cloudy or dark" (10.87%), "slippery road caused by rain or snow" (10.51%), "kids were unintended" (10.27%) etc. Most of the wounded received treatment clinically (50.18%), with the percentile (P50) of medical cost as 182.76 RMB (Yuan). The proportion of inpatient was 27.72% and with percentile of time as P(50) = 7.57 day and cost as P(50) = 2840.00 RMB Yuan. The wounded had a rest of P50 = 5.9 days, with an indirect cost as P(50) = 233.16 RMB Yuan. CONCLUSION: The results of this study indicated that the incidence of agricultural profession-related injuries was high, with serious harm. Behavioral intervention and awareness of injuries should be enhanced, together with the improvement of environmental condition.