The combination of maximum standardized uptake value and clinical parameters for improving the accuracy in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.

Background: Anterior mediastinal masses are relatively uncommon, and mediastinal lymphomas are the malignancies most likely to be confused with thymic epithelial tumors (TETs). The aim of this study was to investigate whether the combination of 18fluorine-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) findings and clinical parameters is useful in differentiating lymphoma from TETs in anterior mediastinal masses. Methods: This retrospective study consecutively included 304 patients with anterior mediastinal masses (244 TETs and 60 lymphomas) who underwent 18F-FDG PET-CT 1 to 2 weeks before tumor resection or biopsy between August 2016 and March 2022. The correlations between the maximum standardized uptake value (SUVmax) of tumors and clinical parameters of patients with histology subtypes were analyzed. Receiver operating characteristic curve analysis was used to obtain the optimal cutoff values of age, lactate dehydrogenase (LDH), tumor size, and SUVmax to predict lymphoma. Logistic regression analysis was used to identify potential predictive factors for lymphoma. Results: Lymphoma was significantly associated with younger patient age, higher LDH level, larger tumor size, and higher SUVmax compared to TETs (P<0.001). In the modeling cohort, age ≤40.5 years, LDH level ≥197 U/L, tumor size ≥10.72 cm, and SUVmax ≥11.95 were identified as independent predictors for lymphoma with odds ratios of 20.14 [95% confidence interval (CI): 6.02-67.40; P<0.001], 4.89 (95% CI: 1.27-18.89; P=0.021), 8.82 (95% CI: 2.31-33.69; P=0.001), and 30.01 (95% CI: 6.59-136.72; P<0.001), respectively. The accuracy of age, LDH, tumor size, and SUVmax in predicting lymphoma was 84.8%, 67.8%, 85.2%, and 78.3% respectively. The combination of the four above parameters could improve the predictive accuracy to 89.1%, and in the validation cohort, this combination increased the predictive accuracy to 87.8%. Conclusions: SUVmax on 18F-FDG PET-CT has the potential ability to discriminate lymphomas from TETs in the diagnosis of anterior mediastinal masses, and the combination of SUVmax with clinical parameters can improve the diagnostic accuracy. This combination may therefore may be helpful in avoiding unnecessary operation in patients with anterior mediastinal lymphomas.

Value of multi-center 18F-FDG PET/CT radiomics in predicting EGFR mutation status in lung adenocarcinoma.

BACKGROUND: Accurate, noninvasive, and reliable assessment of epidermal growth factor receptor (EGFR) mutation status and EGFR molecular subtypes is essential for treatment plan selection and individualized therapy in lung adenocarcinoma (LUAD). Radiomics models based on 18F-FDG PET/CT have great potential in identifying EGFR mutation status and EGFR subtypes in patients with LUAD. The validation of multi-center data, model visualization, and interpretation are significantly important for the management, application and trust of machine learning predictive models. However, few EGFR-related research involved model visualization and interpretation, and multi-center trial. PURPOSE: To develop explainable optimal predictive models based on handcrafted radiomics features (HRFs) extracted from multi-center 18F-FDG PET/CT to predict EGFR mutation status and molecular subtypes in LUAD. METHODS: Baseline 18F-FDG PET/CT images of 383 LUAD patients from three hospitals and one public data set were collected. Further, 1808 HRFs were extracted from the primary tumor regions using Pyradiomics. Predictive models were built based on cross-combination of seven feature selection methods and seven machine learning algorithms. Yellowbrick and explainable artificial intelligence technology were used for model visualization and interpretation. Receiver operating characteristic curve, classification report and confusion matrix were used for model performance evaluation. Clinical applicability of the optimal models was assessed by decision curve analysis. RESULTS: STACK feature selection method combined with light gradient boosting machine (LGBM) reached optimal performance in identifying EGFR mutation status ([area under the curve] AUC = 0.81 in the internal test cohort; AUC = 0.62 in the external test cohort). Random forest feature selection method combined with LGBM reached optimal performance in predicting EGFR mutation molecular subtypes (AUC = 0.89 in the internal test cohort; AUC = 0.61 in the external test cohort). CONCLUSIONS: Explainable machine learning models combined with radiomics features extracted from multi-center/scanner 18F-FDG PET/CT have certain potential to identify EGFR mutation status and subtypes in LUAD, which might be helpful to the treatment of LUAD.

Exploring the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer patients.

PURPOSE: Our study intended to explore the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer (NSCLC) patients detected by next-generation sequencing (NGS). METHODS: NGS assay was performed in 1737 NSCLC patients, a total of 88 HER2 alterations and 176 negative HER2 with EGFR-negative patients were randomly selected for this study. RESULTS: When the HER2 status with EGFR-negative group was analyzed, multivariate analysis showed that smoking status, primary tumor SUVmax (pSUVmax) < 13.03 and stage were the independent deterministic factors of HER2 alterations. Multivariate cox regression analysis revealed that HER2 status, age, smoking status and stage were independent risk factors for overall survival (OS) in EGFR-negative NSCLC patients with different HER2 status. When the HER2 alterations group was separately analyzed, multivariate analysis demonstrated that low pSUVmax < 15.32 and histology were the independent deterministic factors of HER2 mutation. Multivariate cox regression analysis revealed that pSUVmax, smoking status, nodal involvement and treatment methods were independent risk factors for OS in EGFR-negative NSCLC patients with HER2 alterations. CONCLUSION: The study revealed that low pSUVmax was associated with HER2 alterations in EGFR-negative NSCLC patients, moreover HER2 mutation and HER2 amplification exhibited distinct 18F-FDG metabolic and clinical characteristics. Furthermore, it explored the prognostic value of HER2 alterations and 18F-FDG PET/CT metabolic parameters of pSUVmax in EGFR-negative NSCLC patients.

Relationships between SUVmax of lung adenocarcinoma and different T stages, histological grades and pathological subtypes: a retrospective cohort study in China.

OBJECTIVES: Cancer cell has aberrant metabolism. The purpose of this study aimed to investigate relationships between maximum standard uptake value (SUVmax）of 18fluoro-2-deoxy-d-glucose and T stages, histological grades and pathological subtypes of lung adenocarcinoma. DESIGN: Retrospective cohort study, employing the Kruskal-Wallis, Bonferroni-Dunn and Mann-Whitney tests to compare SUVmax of different T stages, histological grades and pathological subtypes of lung adenocarcinoma. SETTING: The outpatients who had aberrant positron emission tomography/CT (PET/CT) images in chest were enrolled this study from August 2016 to November 2018 in Shanghai, China. PARTICIPANT: Initial 11 270 patients with suspected lung cancer who underwent PET/CT examinations were surveyed. A total of 1454 patients who were diagnosed as lung adenocarcinoma by pathologist were included in this project. PRIMARY OUTCOME MEASURES: SUVmax value at different tumour-node-metastasis stages of lung adenocarcinoma before surgery. RESULTS: The mean SUVmax of patients with lung adenocarcinoma was significantly elevated with the increase in T stages. There were significant evident differences in SUVmax among T1a-T1c (p<0.05). However, after the staging of patients was more than T1 stage, SUVmax of T2a, T2b, T2 visceral pleural invasion, T3 and T4 had not dramatic changes. SUVmax value of lung adenocarcinoma in the same T stage group was the highest in patients with the high grade of malignancy and solid-predominant invasive adenocarcinoma. CONCLUSIONS: SUVmax value was significantly associated with T stages, grades of malignancy and pathological subtypes of lung adenocarcinoma.

Development of a PET/CT molecular radiomics-clinical model to predict thoracic lymph node metastasis of invasive lung adenocarcinoma ≤ 3 cm in diameter.

BACKGROUND: To investigate the value of 18F-FDG PET/CT molecular radiomics combined with a clinical model in predicting thoracic lymph node metastasis (LNM) in invasive lung adenocarcinoma (≤ 3 cm). METHODS: A total of 528 lung adenocarcinoma patients were enrolled in this retrospective study. Five models were developed for the prediction of thoracic LNM, including PET radiomics, CT radiomics, PET/CT radiomics, clinical and integrated PET/CT radiomics-clinical models. Ten PET/CT radiomics features and two clinical characteristics were selected for the construction of the integrated PET/CT radiomics-clinical model. The predictive performance of all models was examined by receiver operating characteristic (ROC) curve analysis, and clinical utility was validated by nomogram analysis and decision curve analysis (DCA). RESULTS: According to ROC curve analysis, the integrated PET/CT molecular radiomics-clinical model outperformed the clinical model and the three other radiomics models, and the area under the curve (AUC) values of the integrated model were 0.95 (95% CI: 0.93-0.97) in the training group and 0.94 (95% CI: 0.89-0.97) in the test group. The nomogram analysis and DCA confirmed the clinical application value of this integrated model in predicting thoracic LNM. CONCLUSIONS: The integrated PET/CT molecular radiomics-clinical model proposed in this study can ensure a higher level of accuracy in predicting the thoracic LNM of clinical invasive lung adenocarcinoma (≤ 3 cm) compared with the radiomics model or clinical model alone.

Poorly differentiated thyroid carcinoma: a clinician's perspective.

Poorly differentiated thyroid carcinoma (PDTC) is a rare thyroid carcinoma originating from follicular epithelial cells. No explicit consensus can be achieved to date due to sparse clinical data, potentially compromising the outcomes of patients. In this comprehensive review from a clinician's perspective, the epidemiology and prognosis are described, diagnosis based on manifestations, pathology, and medical imaging are discussed, and both traditional and emerging therapeutics are addressed as well. Turin consensus remains the mainstay diagnostic criteria for PDTC, and individualized assessments are decisive for treatment option. The prognosis is optimal if complete resection is performed at early stage but dismal in nearly half of patients with locally advanced and/or distant metastatic diseases, in which adjuvant therapies such as 131I therapy, external beam radiation therapy, and chemotherapy should be incorporated. Emerging therapeutics including molecular targeted therapy, differentiation therapy, and immunotherapy deserve further investigations to improve the prognosis of PDTC patients with advanced disease.

An AKT/PRMT5/SREBP1 axis in lung adenocarcinoma regulates de novo lipogenesis and tumor growth.

Protein kinase B (AKT) hyperactivation and de novo lipogenesis are both common in tumor progression. Sterol regulatory element-binding protein 1 (SREBP1) is the master regulator for tumor lipid metabolism, and protein arginine methyltransferase 5 (PRMT5) is an enzyme that can catalyze symmetric dimethyl arginine (SDMA) modification of the mature form of SREBP1 (mSREBP1) to induce its hyperactivation. Here, we report that SDMA-modified mSREBP1 (mSREBP1-SDMA) was overexpressed and correlated with Ser473-phosphorylated AKT (AKT-473P) expression and poor patient outcomes in human lung adenocarcinomas. Furthermore, patients with AKT-473P and mSREBP1-SDMA coexpression showed the worst prognosis. Mechanistic investigation revealed that AKT activation upregulated SREBP1 at both the transcriptional and post-translational levels, whereas PRMT5 knockdown reversed AKT signaling-mediated mSREBP1 ubiquitin-proteasome pathway stabilization at the post-translational level. Meanwhile, AKT activation promoted nuclear PRMT5 to the cytoplasm without changing total PRMT5 expression, and the transported cytoplasmic PRMT5 (cPRMT5) induced by AKT activation showed a strong mSREBP1-binding ability. Immunohistochemical assay indicated that AKT-473P and mSREBP1-SDMA were positively correlated with cPRMT5 in lung adenocarcinomas, and high cPRMT5 levels in tumors were associated with poor patient outcomes. Additionally, PRMT5 knockdown reversed AKT activation-induced lipid synthesis and growth advantage of lung adenocarcinoma cells both in vitro and in vivo. Finally, we defined an AKT/PRMT5/SREBP1 axis involved in de novo lipogenesis and the growth of lung cancer. Our data also support that cPRMT5 is a potential therapeutic target for hyperactive AKT-driven lung adenocarcinoma.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.

OBJECTIVES: Anaplastic lymphoma kinase (ALK) rearrangement status examination has been widely used in clinic for non-small cell lung cancer (NSCLC) patients in order to find patients that can be treated with targeted ALK inhibitors. This study intended to non-invasively predict the ALK rearrangement status in lung adenocarcinomas by developing a machine learning model that combines PET/CT radiomic features and clinical characteristics. METHODS: Five hundred twenty-six patients of lung adenocarcinoma with PET/CT scan examination were enrolled, including 109 positive and 417 negative patients for ALK rearrangements from February 2016 to March 2019. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images. The maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) logistic regression were further employed to select the most distinguishable radiomic features to construct predictive models. The mRMR is a feature selection method, which selects the features with high correlation to the pathological results (maximum correlation), meanwhile retain the features with minimum correlation between them (minimum redundancy). LASSO is a statistical formula whose main purpose is the feature selection and regularization of data model. LASSO method regularizes model parameters by shrinking the regression coefficients, reducing some of them to zero. The feature selection phase occurs after the shrinkage, where every non-zero value is selected to be used in the model. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the models, and the performance of different models was compared by the DeLong test. RESULTS: A total of 22 radiomic features were extracted from PET/CT images for constructing the PET/CT radiomic model, and majority of these features used were based on CT features (20 out of 22), only 2 PET features were included (PET percentile 10 and PET difference entropy). Moreover, three clinical features associated with ALK mutation (age, burr and pleural effusion) were also employed to construct a combined model of PET/CT and clinical model. We found that this combined model PET/CT-clinical model has a significant advantage to predict the ALK mutation status in the training group (AUC = 0.87) and the testing group (AUC = 0.88) compared with the clinical model alone in the training group (AUC = 0.76) and the testing group (AUC = 0.74) respectively. However, there is no significant difference between the combined model and PET/CT radiomic model. CONCLUSIONS: This study demonstrated that PET/CT radiomics-based machine learning model has potential to be used as a non-invasive diagnostic method to help diagnose ALK mutation status for lung adenocarcinoma patients in the clinic.

A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma.

OBJECTIVES: This study aims to develop a clinically practical model to predict EGFR mutation in lung adenocarcinoma patients according to radiomics signatures based on PET/CT and clinical risk factors. METHODS: This retrospective study included 583 lung adenocarcinoma patients, including 295 (50.60%) patients with EGFR mutation and 288 (49.40%) patients without EGFR mutation. The clinical risk factors associated with lung adenocarcinoma were collected at the same time. We developed PET/CT, CT, and PET radiomics models for the prediction of EGFR mutation using multivariate logistic regression analysis, respectively. We also constructed a combined PET/CT radiomics-clinical model by nomogram analysis. The diagnostic performance and clinical net benefit of this risk-scoring model were examined via receiver operating characteristic (ROC) curve analysis while the clinical usefulness of this model was evaluated by decision curve analysis (DCA). RESULTS: The ROC analysis showed predictive performance for the PET/CT radiomics model (AUC = 0.76), better than the PET model (AUC = 0.71, Delong test: Z = 3.03, p value = 0.002) and the CT model (AUC = 0.74, Delong test: Z = 1.66, p value = 0.098). Also, the PET/CT radiomics-clinical combined model has a better performance (AUC = 0.84) to predict EGFR mutation than the PET/CT radiomics model (AUC = 0.76, Delong test: D = 2.70, df = 790.81, p value < 0.001) or the clinical model (AUC = 0.81, Delong test: Z = 3.46, p value < 0.001). CONCLUSIONS: We demonstrated that the combined PET/CT radiomics-clinical model has an advantage to predict EGFR mutation in lung adenocarcinoma. KEY POINTS: • Radiomics from lung tumor increase the efficiency of the prediction for EGFR mutation in clinical lung adenocarcinoma on PET/CT. • A radiomic nomogram was developed to predict EGFR mutation. • Combining PET/CT radiomics-clinical model has an advantage to predict EGFR mutation.

SUVmax of 18FDG PET/CT Predicts Histological Grade of Lung Adenocarcinoma.

OBJECTIVES: The relationship between the 18FDG PET-CT maximum standard uptake value (SUVmax) and the type of lung adenocarcinoma is still not established. The aim of this study was to investigate the relationship between SUVmax value and histological grade and pathological subtype of lung adenocarcinoma, and to determine the optimum SUVmax cutoffs for distinguishing different histological grades. MATERIALS AND METHODS: The data of 618 lung adenocarcinoma patients were retrospectively analyzed. The relationship between SUVmax measured on preoperative 18FDG-PET-CT and the histological grade and pathological subtype was examined. The Kruskal-Wallis test was used to compare differences among groups, and the Bonferroni-Dunn test for pairwise comparison among groups. ROC analysis was applied to determine the optimal cut-off values for distinguishing different groups. In addition, the cut-off value was verified in an independent cohort of 85 consecutive lung adenocarcinoma cases. RESULTS: The SUVmax was significantly different between the low, intermediate, and high-grade groups(p < .001). SUVmax value increased with increase in the degree of malignancy. The optimal cut-off value for identifying low-grade tumors was 2.01 (sensitivity 90.4%, specificity 86.9%, area under the curve [AUC] = 0.928, 95% confidence interval: 0.91-0.95; p < .001). The optimal cutoff SUVmax value for identifying high-grade tumors was 7.41 (sensitivity 79.8%, specificity 73.5%, AUC = 0.830, 95% confidence interval: 0.79-0.87; p < .001). The validation experiment showed that the coincidence rate was 88.89% in the low-level group, 64.15% in the middle-level group, and 78.57% in the high-level group. CONCLUSION: SUVmax can be used to predict pathological subtype and histological grade of lung adenocarcinoma. Thus, 18FDG PET-CT can serve as a noninvasive tool for precise diagnosis and help in the preoperative formulation of patient-specific treatment strategies.

The potential of 18F-FDG PET/CT in predicting PDL1 expression status in pulmonary lesions of untreated stage IIIB-IV non-small-cell lung cancer.

OBJECTIVES: To investigate the potential of 2-deoxy-2(18F)fluoro-d-glucose (18F-FDG) combined positron emission tomography and computed tomography (PET/CT) in predicting programmed cell death ligand-1 (PDL1) expression status in pulmonary lesions of advanced non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: This retrospective study includes 133 untreated stage IIIB-IV NSCLC patients who underwent pulmonary lesion biopsy for PDL1 immunochemistry 1-4 weeks after 18F-FDG PET/CT scanning, randomly assigned to cohorts for modelling and validation of PDL1 expression predictors. Mean and maximum standard uptake values (pSUVmean and pSUVmax), metabolic tumour volume (pMTV), and total lesion glycolysis (pTLG) of primary lesions were determined. PDL1 expression in pulmonary lesions (pPDL1) was determined using tumour proportion score (TPS), and pPDL1 TPS < 1%, 1-49 %, and ≥ 50 % were considered as pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively. RESULTS: pSUVmean and pSUVmax values were increased with the increase of pPDL1 levels, whereas pMTV and pTLG values were not associated with pPDL1 levels. In the modelling cohort, we found that pSUVmax rather than pSUVmean was an independent predictor for pPDL1-negative, pPDL1-moderate, and pPDL1-strong, whereas pSUVmax < 14.4, 14.4-17.5, and > 17.5 were suggested as predictors for pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively (odds ratio: 4.82, 3.92, and 4.45, respectively; P = 0.002, 0.021, and 0.020, respectively). In the validation cohort, pSUVmax < 14.4, 14.4-17.5, and > 17.5 showed significantly high probabilities of being pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively (P = 0.006). The accuracies of pSUVmax < 14.4, 14.4-17.5, and > 17.5 predicting pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively, in validation cohort, were 66.7 %, 75.8 %, and 84.8 %, respectively. CONCLUSION: pSUVmax on 18F-FDG PET/CT is a potential biomarker for pPDL1 TPS < 1%, 1-49 %, and ≥ 50 % in untreated stage IIIB-IV NSCLC, and therefore may be helpful for determining immunotherapeutic strategy for advanced NSCLC.

Pretreatment serum neutrophil-to-lymphocyte and monocyte-to-lymphocyte ratios: Two tumor-related systemic inflammatory markers in patients with thymic epithelial tumors.

OBJECTIVES: To understand underlying changes in pretreatment serum inflammatory markers associated with thymic epithelial tumors (TETs) development. METHODS: A retrospective analysis of 113 TETs patients who underwent 18-fluorine fluorodeoxyglucose (18F-FDG) positron emission tomography combined computed tomography (PET/CT) one to two weeks before tumor resection or biopsy was performed. Pretreatment serum neutrophil, monocyte, platelet, and lymphocyte counts, and fibrinogen and C-reaction protein (CRP) concentrations were measured one day before surgery or biopsy. Neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) were calculated by dividing corresponding cells counts by lymphocyte counts, respectively. The maximum standard uptake value (SUVmax) of 18F-FDG of primary TETs was applied to reflect tumor glycolytic activity. The student's t-test, one-way ANOVA analysis, Chi-square test, receiver operating characteristic curve analysis, and Logistic regression analysis were used for statistical analysis. RESULTS: The serum NLR and MLR were significantly higher in TETs patients than in healthy volunteers (P both ≤ 0.001). High serum NLR and MLR were related to the thymic carcinomas (TCs) subtype, elevated Masaoka-Koga (M-K) tumor stage, and metastasis of TETs (P all < 0.005). High serum NLR and MLR were also associated with high SUVmax values of TETs (P all < 0.005), with increasingly differences between groups as the cut-off values defining low-SUVmax and high-SUVmax groups increased. With the medium cutoff of NLR, MLR, and SUVmax of 3.07, 0.25, and 8.00 respectively, the high NLR and MLR levels were significantly associated with high SUVmax level of TETs (P both < 0.005). Moreover, the incidences of co-high SUVmax/NLR and co-high SUVmax/MLR were higher in TETs patients older than 55 years, with TCs, in M-K stage IV, and with metastasis (P all < 0.05). Both the co-high SUVmax/NLR and co-high SUVmax/MLR increased the risk of TETs metastasis (P both < 0.001), while the co-high SUVmax/MLR was also an independent risk factor for TETs metastasis (odds ratio: 3.92, 95% confidence interval: 1.02-15.12, P = 0.047). CONCLUSION: Pretreatment serum NLR and MLR of TETs patients are two tumor-progression- and tumor-glycolysis-related inflammatory markers. Enhanced tumor glycolytic activity and associated systemic inflammatory reaction may play a synergistic role in TETs metastasis.

Correlation between combining 18F-FDG PET/CT metabolic parameters and other clinical features and ALK or ROS1 fusion in patients with non-small-cell lung cancer.

PURPOSE: Our study intended to explore the association between combining 18F-FDG PET/CT metabolic parameters and other clinical features and anaplastic lymphoma kinase (ALK) or c-ros oncogene 1 (ROS1) fusion in non-small-cell lung cancer (NSCLC). METHODS: Eight hundred and six patients with wild-type epidermal growth factor receptor (EGFR) mutation were screened for ALK or ROS1 fusion and subjected to 18F-FDG PET/CT prior to treatment at our hospital. The associations between ALK or ROS1 fusion and clinical characteristics and the PET/CT parameters were analyzed. Multivariate logistic regression analysis was performed to explore independent deterministic factors associated with ALK and ROS1 fusion. RESULTS: Eighty-two patients (11.7%) with ALK fusion were found. Multivariate analysis demonstrated that high pSUVmax ≥ 10.6, low primary tumor lesion glycolysis (pTLG) < 101.8, young age, nonsmoker status, and high carcinoembryonic antigen (CEA) level correlated with ALK fusion in NSCLC. The receiver operating characteristic (ROC) curve yielded the area under curve (AUC) values of 0.603 and 0.873 for high pSUVmax alone and the combination of the five factors, respectively. Twenty-six patients (5.6%) with ROS1 fusion were found. Multivariate analysis revealed that high pSUVmax ≥ 8.8, young age, and nonsmoker status correlated with ROS1 fusion in NSCLC. The ROC curve yielded AUC values of 0.662 and 0.813 for high pSUVmax alone and the combination of the three factors, respectively. CONCLUSION: The study indicated that combining 18F-FDG PET/CT metabolic parameters and other clinical parameters were correlated with ALK and ROS1 mutation in NSCLC patients and may help to refine the process of optimal patient selection to gene test for targeted therapy.

Minor components of micropapillary and solid subtypes in lung invasive adenocarcinoma (≤ 3 cm): PET/CT findings and correlations with lymph node metastasis.

OBJECTIVE: To investigate the PET/CT findings in lung invasive adenocarcinoma with minor components of micropapillary or solid contents and its association with lymph node metastasis. MATERIALS AND METHODS: A total of 506 lung invasive adenocarcinoma (≤ 3 cm) patients who underwent a PET/CT examination and resection surgery were included. According to the proportion of solid/micropapillary components, the patients were classified into three groups: solid/micropapillary-negative (SMPN) (n = 258), solid/micropapillary-minor (SMPM; > 5% not predominant) (n = 158) and solid/micropapillary-predominant (SMPP; > 5% most dominant) (n = 90). The patients' PET/CT findings, including SUVmax, MTV, TLG and CT characteristics, and other clinical factors were compared by one-way ANOVA test. Logistic regression analysis was done to identify the most predictive findings for lymph node metastasis. RESULTS: The value of SUVmax, MTV, TLG and tumor size was highest in SMPP group, followed by SMPM and SMPN group (P < 0.001).The areas under the curve for SUVmax, MTV and TLG for node metastasis were 0.822, 0.843 and 0.835, respectively. Univariate analysis found that the SMPP and SMPM group had more lymph node metastasis than the SMPN group (P < 0.001). Furthermore, the lymph node metastasis group had higher CEA, SUVmax, MTV, TLG, tumor size and more pleural invasion (P < 0.001). Logistic regression analysis found that SMPP pathological type, SMPM pathological type, higher CEA and male patients were risk factors for lymph node metastasis (P < 0.01). CONCLUSIONS: Lung invasive adenocarcinoma with micropapillary or solid contents had higher SUVmax, MTV, TLG and tumor size and was associated with lymph node metastasis, even if they were not predominant.

Radioiodine Uptake and Thyroglobulin-Guided Radioiodine Remnant Ablation in Patients with Differentiated Thyroid Cancer: A Prospective, Randomized, Open-Label, Controlled Trial.

BACKGROUND: Radioiodine (131I) remnant ablation (RRA) has become a key step in the postoperative treatment of differentiated thyroid cancer (DTC). However, inadequate or excessive 131I is common using fixed activities. This study was designed to explore the feasibility of radioiodine uptake and thyroglobulin (RAIU-Tg)-guided RRA. METHODS: A total of 277 patients were randomized to the RAIU-Tg-based activity group or a fixed activity of 3.7 GBq group at a ratio of 4:1. The RAIU-Tg-based activity was established based on four levels of RAIU (≤2%, 2-5%, 5-15%, and >15%) and Tg levels (≤2, 2-5, 5-10, and >10 ng/mL). Based on this, 131I activities of 1.1, 1.85, 3.7, and 5.55 GBq were administered. If the levels for RAIU and Tg were not in the same category, the higher activity determined by either RAIU or Tg was administered. Successful RRA was defined as negative diagnostic whole-body scan and Tg <1 ng/mL (anti-Tg antibody negative) or negative diagnostic whole-body scan (anti-Tg antibody positive) under thyrotropin stimulation six months or more post RRA. RESULTS: There was no statistically significant difference in baseline characteristics between the RAIU-Tg-based activity group (n = 207) and the fixed activity group (n = 58). The activity of 131I used in the RAIU-Tg-based activity group (3.26 ± 1.54 GBq) was significantly lower than that used in the fixed activity group (p < 0.0001), whereas the rate of successful RRA in the RAIU-Tg-based activity group was significantly higher than the rate in the fixed activity group (94.2% vs. 70.7%; p < 0.0001). The rates of successful RRA in the four subgroups of the RAIU-Tg-based activity group were comparable (p = 0.543). Although there was no statistically significant difference in the incidence of total/short-term adverse effects between the RAIU-Tg-based activity group and the fixed activity group, a significantly lower incidence of intermediate adverse effects, which predominantly consisted of xerostomia, was reported in the RAIU-Tg-based activity group. CONCLUSIONS: Compared to a fixed activity of 3.7 GBq, RAIU-Tg-guided dosimetry can improve the success rate and decrease the incidence of intermediate side effects of RRA in postoperative patients with DTC.

Predicting 131I-avidity of metastases from differentiated thyroid cancer using 18F-FDG PET/CT in postoperative patients with elevated thyroglobulin.

The quantitative relationship between iodine and glucose metabolism in metastases from differentiated thyroid cancer (DTC) remains unknown. Aim of the prospective study was to establish the value of 18F-FDG PET/CT in predicting 131I-avidity of metastases from DTC before the first radioiodine therapy. A total of 121 postoperative DTC patients with elevated stimulated serum thyroglobulin (ssTg) who underwent 131I adjuvant therapy or therapy after 18F-FDG PET/CT scan were enrolled. The Receiver operating characteristic curve was established to create an optimal cut-off point and evaluate the value of SUVmax for predicting 131I-avidity. In our study, the median SUVmax in 131I-nonavid metastatic target lesions was also significantly higher than that in 131I-avid metastatic target lesions (5.37 vs. 3.30; P = 0.000). At a cut-off value of 4.0 in SUVmax, the area under curve was 0.62 with the sensitivity, specificity, positive predictive value and negative predictive value of 75.3%, 56.7%, 76.1%, and 54.8%, respectively. These results suggest that 18F-FDG PET/CT may be of great value in identifying metastases in postoperative DTC patients with elevated ssTg before 131I administration, leading to an improved management of disease. 18F-FDG positive metastatic DTC with SUVmax of greater than 4.0 possesses higher probability of non-avidity to radioiodine.

99mTc-pertechnetate-avid metastases from differentiated thyroid cancer are prone to benefit from 131I therapy: A prospective observational study.

The aim of this study is to determine the contribution of neck and chest Tc-pertechnetate scan to the management of postoperative patients with suspicious metastatic differentiated thyroid cancer (DTC), particularly to the prediction of response to radioiodine (I) therapy. Just before I administration, a total of 184 postoperative DTC patients with stimulated serum thyroglobulin (ssTg) >10 ng/mL were enrolled to undergo neck and chest Tc-pertechnetate scan, which were directly compared with post-therapeutic I scan to determine the concordance of site and number of metastatic lesions. The percentage changes in ssTg between Tc-pertechnetate-avid group and Tc-pertechnetate-nonavid group were compared, and the response to I in both groups was analyzed according to the nature of Tc-pertechnetate avidity as well. The percentages of concordance between Tc-pertechnetate and I scan in detecting metastases were 65.7% and 26.0% in per-patient and per-site analyses with low unweighted kappa, respectively. Tc-pertechnetate scan led to a change in therapeutic decision making in 19/184 (10.3%) patients. In 72 patients with I-avid metastases, the ssTg in Tc-pertechnetate-avid group (n = 13) decreased significantly compared with that in Tc-pertechnetate-nonavid group (n = 59) (median: -81.56% vs -48.14%; Z = -4.276, P = .000). The difference of therapeutic response between Tc-pertechnetate-avid group and Tc-pertechnetate-nonavid group was statistically significant (χ = 8.4; P = .03). Although the consistency between Tc-pertechnetate scan before I administration and post-therapy I scan in detecting metastases is low, identifying metastases in postoperative DTC patients with elevated ssTg via Tc-pertechnetate scan prior to I therapy provides incremental value for therapeutic decision making. Notably, patients with Tc-pertechnetate-avid metastases may be more prone to benefit from I therapy than those with Tc-pertechnetate-nonavid metastases.

HER inhibitor promotes BRAF/MEK inhibitor-induced redifferentiation in papillary thyroid cancer harboring BRAFV600E.

Redifferentiation therapy with BRAF/MEK inhibitors to facilitate treatment with radioiodine represents a good choice for radioiodine-refractory differentiated thyroid carcinoma, but recent initial clinical outcomes were modest. MAPK rebound caused by BRAF/MEK inhibitors-induced activation of HER2/HER3 is a resistance mechanism, and combination with HER inhibitor to prevent MAPK rebound may sensitize BRAFV600E-mutant thyroid cancer cells to redifferentiation therapy. To evaluate if inhibiting both BRAF/MEK and HER can produce stronger redifferetiation effect, we tested the effects of BRAF/MEK inhibitor dabrafenib/selumetinib alone or in combination with HER inhibitor lapatinib on the expression and function of iodine- and glucose-handling genes in BRAFV600E-positive BCPAP and K1 cells, using BHP 2-7 cells harboring RET/PTC1 rearrangement as control. Herein, we showed that lapatinib prevented MAPK rebound and sensitized BRAFV600E-positive papillary thyroid cancer cells to BRAF/MEK inhibitors. Dabrafenib/selumetinib alone increased iodine-uptake and toxicity and suppressed glucose-metablism in BRAFV600E-positive papillary thyroid cancer cells. When lapatinib was added, more significant effects on iodine- and glucose-handling gene expression, cell membrane location of sodium/iodine symporter as well as radioiodine uptake and toxicity were observed. Thus, combined therapy using HER inhibitor and BRAF/MEK inhibitor presented more significant redifferentiation effect on papillary thyroid cancer cells harboring BRAFV600E than BRAF/MEK inhibitor alone. In vivo and clinical studies assessing such combined targeted redifferentiation strategy were warranted.

Increased 18F-FDG uptake of heterotopic pancreatitis in the small intestine: A CARE-compliant case report.

BACKGROUD: Heterotopic pancreas (HP), a relatively uncommon congenital anomaly, is rarely noted during F-FDG positron-emission tomography/computed tomography (PET/CT) scan. METHODS: A 60-year-old woman was referred to our hospital due to a 10-day history of abdominal pain with elevated levels of serum amylase and lipase. Abdominal CT and ultrasound examinations were negative. In order to search for the cause, an F-FDG PET/CT whole body scan was suggested to an old woman revealing the presence of F-FDG accumulating nodule in small intestine. RESULTS: Surgical findings and pathologic results confirmed the diagnosis of small intestinal heterotopic pancreas with active chronic inflammation. CONCLUSION: This uncommon case underscores the necessity of considering heterotopic pancreatitis in small intestine with focal F-FDG uptake as a possible differential diagnosis in intestinal tumor and tuberculosis.

Challenges and strategies on radioiodine treatment for differentiated thyroid carcinoma.

OBJECTIVE: Radioiodine ((131)I) is considered an effective and low-risk therapeutic radionuclide for differentiated thyroid carcinoma (DTC); however, dilemmas exist in the optimization of indications, pre-treatment thyroid stimulating hormone (TSH) stimulation, dose decision, as well as in the treatment of (131)I-refractory disease. Refined strategies on (131)I treatment for DTC based on late evidence and novel insights are greatly needed. CONCLUSION: The indications of (131)I ablation continue to be refined with a better understanding of the risks and benefits. For pre-treatment TSH stimulation, recombinant human thyrotropin presents a better choice as it improves the quality of life, but is indicated only for ablation of the thyroid remnant and follow-up. Decreased doses of (131)I seem to be more appropriate in patients without gross residual disease or metastases, but maximal doses are suggested in patients with advanced disease. Imaging procedures contributing to decision-making for patients with advanced DTC also continue to be modified. As for the (131)I-refractory disease, there is a trend to increase (131)I uptake and retention by using additional therapeutic agents like kinase inhibitors with encouraging results.