Objective To investigate the characteristic of the expression of facilitative glucose transporter 1 （Glut1） in bronchial aveolar carcinoma （BAC） and the relationship between expression of Glutl and fluorine-18 fluorodeoxyglucose （18F-FDG） uptake. Methods Twenty patients with BAC were imaged with 18F-FDG positron emission tomography （PET） before surgery. Maximum standard uptake value （SUVmax） and mean standard uptake value （SUVmean ） of tumor and standard uptake value of normal lung （SUVIung） were measured. The expression of Glutl was studied in paraffin sections by streptavidin peroxidase （SP） immunohistochemistry. Results All tumors of the patients could be detected by ^18F-FDG-PET. 18F-FDG uptake of tumor was higher than that of normal lung （SUV SUV and SUVlong were 3.09± 1.35, 2.37±1.03 and 0.39±0.09 respectively）. The expression of Glutl were positive in all tumors （73. 8%± 14. 8% of positive cell rate, 2. 8 ± 0. 9 grade of staining intensity）. Predominantly cytoplasm positive with weak staining intensity were observed in many tumors. Glutl negtive were observed in normal bronchial and lung parenchyma. Positive correlations were found among 18F-FDG uptake, Glut1 expression and tumor size （P〈0. 01）. Conclusion Glutl expression with peculiarity in BAC is correlate with 18F-FDG uptake.
Objective To introduce the current study on 18F-fluorodexyglucose positron emission tomography (18F-FDG PET) scanning in diagnosis and treatment of carcinoma of large intestine. Methods The literatures about 18F-FDG PET scanning in diagnosis and treatment of carcinoma of large intestine in recent years were reviewed. Results 18F-FDG PET scanning is superior to CT and MRI in identificating carcinoma of large intestine recurrence, metastasis in the early stage after operation and staging carcinoma of large intestine. Conclusion 18F-FDG PET scanning may be one of the accessory examinations in carcinoma of large intestine and may be helpful for the choice of treatment.
Solitary pulmonary nodule (SPN) is defined as a rounded opacity≤3 cm in diameter surrounded by lung parenchyma. The majority of smokers who undergo thin-section CT have SPNs, most of which are smaller than 7 mm. In the past, multiple follow-up examinations over a two-year period, including CT follow-up at 3, 6, 12, 18, and 24 months, were recommended when such nodules are detected incidentally. This policy increases radiation burden for the affected population. Nodule features such as shape, edge characteristics, cavitation, and location have not yet been found to be accurate for distinguishing benign from malignant nodules. When SPN is considered to be indeterminate in the initial exam, the risk factor of the patients should be evaluated, which includes patients' age and smoking history. The 2005 Fleischner Society guideline stated that at least 99% of all nodules 4 mm or smaller are benign; when nodule is 5-9 mm in diameter, the best strategy is surveillance. The timing of these control examinations varies according to the nodule size (4-6, or 6-8 mm) and the type of patients, specifically at low or high risk of malignancy concerned. Noncalcified nodules larger than 8 mm diameter bear a substantial risk of malignancy, additional options such as contrast material-enhanced CT, positron emission tomography (PET), percutaneous needle biopsy, and thoracoscopic resection or videoassisted thoracoscopic resection should be considered.
There are some problems in positron emission tomography/ computed tomography (PET/CT) lung images, such as little information of feature pixels in lesion regions, complex and diverse shapes, and blurred boundaries between lesions and surrounding tissues, which lead to inadequate extraction of tumor lesion features by the model. To solve the above problems, this paper proposes a dense interactive feature fusion Mask RCNN (DIF-Mask RCNN) model. Firstly, a feature extraction network with cross-scale backbone and auxiliary structures was designed to extract the features of lesions at different scales. Then, a dense interactive feature enhancement network was designed to enhance the lesion detail information in the deep feature map by interactively fusing the shallowest lesion features with neighboring features and current features in the form of dense connections. Finally, a dense interactive feature fusion feature pyramid network (FPN) network was constructed, and the shallow information was added to the deep features one by one in the bottom-up path with dense connections to further enhance the model’s perception of weak features in the lesion region. The ablation and comparison experiments were conducted on the clinical PET/CT lung image dataset. The results showed that the APdet, APseg, APdet_s and APseg_s indexes of the proposed model were 67.16%, 68.12%, 34.97% and 37.68%, respectively. Compared with Mask RCNN (ResNet50), APdet and APseg indexes increased by 7.11% and 5.14%, respectively. DIF-Mask RCNN model can effectively detect and segment tumor lesions. It provides important reference value and evaluation basis for computer-aided diagnosis of lung cancer.
Objective To investigate the advances and clinical efficacy evaluation method on neoadjuvant chemotherapy in patients with gastric cancer. Methods Literatures on the advances and clinical efficacy evaluation method on neoadjuvant chemotherapy in patients with gastric cancer were reviewed and analyzed. The agreement between computed tomography (CT), endoscopic ultrasound (EUS), magnetic resonance imaging (MRI) and positron emission tomography (PET) and the results of histopathology and survival was analyzed.Results CT and EUS were the method of efficacy evaluation commonly used at present, but the evaluation indexes and criteria were controversial, and the criteria for solid tumors seemed to be not feasible for gastric cancer. Diffusionweighted imaging (DWI) method needed more investigation, while PET held advantage in early selection of patients without response accurately.Conclusion There is no uniform standard for clinical efficacy evaluation yet, so an integration of diverse imaging methods may be the best choice to improve the accuracy of neoadjuvant chemotherapy in patients with gastric cancer.
ObjectiveTo systematically review the diagnostic value of FDG-PET, Aβ-PET and tau-PET for Alzheimer ’s disease (AD).MethodsPubMed, EMbase, The Cochrane Library, CNKI, WanFang Data, VIP and CBM databases were electronically searched to collect diagnostic tests of FDG-PET, Aβ-PET and tau-PET for AD from January 2000 to February 2020. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies; then, meta-analysis was performed by Meta-Disc 1.4 and Stata 14.0 software.ResultsA total of 31 studies involving 3 718 subjects were included. The results of meta-analysis showed that, using normal population as control, the sensitivity/specificity of FDG-PET and Aβ-PET in diagnosing AD were 0.853/0.734 and 0.824/0.771, respectively. Only 2 studies were included for tau-PET and meta-analysis was not performed.ConclusionsFDG-PET and Aβ-PET can provide good diagnostic accuracy for AD, and their diagnostic efficacy is similar. Due to limited quality and quantity of the included studies, more high quality studies are required to verify the above conclusions.
ObjectiveTo analyze the relationship between maximum standardized uptake value (SUVmax) of primary tumor detected by 18F-FDG positron emission tomography/computed tomography (PET/CT) and clinicopathologic factors in stageⅠnon-small cell lung cancer (NSCLC), and investigate the prognostic value of PET/CT on pathological feature. MethodsWe retrospectively analyzed clinical data of 182 patients with stageⅠNSCLC who underwent 18F-FDG PET/CT scan before lobectomy or segmentectomy in China-Japan Friendship Hospital from April 2013 to June 2014. There were 121 male and 61 female patients with their ages of 34-85 (68.1±9.8) years. Clinicopathologic factors including sex, age, smoking history, histology, TNM stage, T stage, tumor size, lymphatic vessel invasion, blood vessel invasion (BVI) and visceral pleural invasion were evaluated to identify the independent factors affecting SUVmax by univariate and multivariate regression analysis. The diagnostic efficiency and best cut-off point of SUVmax were calculated by the receiver operating characteristic curve. ResultsThe univariate analysis identified that sex (P=0.015), smoking history (P=0.001), histology (P < 0.001), TNM stage (P=0.004), T stage (P=0.001), tumor size (P < 0.001), BVI (P=0.001) were factors affecting SUVmax. Only histology (P=0.001), tumor size (P=0.006), BVI (P=0.009) were found to be significant independent factors according to multivariate regression analysis. The SUVmax of primary tumor was a predictor for BVI with the highest diagnostic accuracy at a cut-off value of 4.85, the sensitivity and specificity were 65.5% and 71.7%. ConclusionThe SUVmax is correlated with histology, tumor size and BVI in stageⅠNSCLC, higher in patients with non-adenocarcinoma, lager tumor and positive BVI. Furthermore, the probability of BVI could be predicted by SUVmax of the primary tumor.
ObjectiveTo conduct a meta-analysis comparing the accuracy of artificial intelligence (AI)-assisted diagnostic systems based on 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) and structural MRI (sMRI) in the diagnosis of Alzheimer's disease (AD). MethodsOriginal studies dedicated to the development or validation of AI-assisted diagnostic systems based on 18F-FDG PET/CT or sMRI for AD diagnosis were retrieved from the Web of Science, PubMed, and Embase databases. Studies meeting the inclusion criteria were collected, and the risk of bias and clinical applicability of the included studies were assessed using the PROBAST checklist. The pooled sensitivity, specificity, and area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated using a bivariate random-effects model. ResultsTwenty-six studies met the inclusion criteria, yielding a total of 38 2×2 contingency tables related to diagnostic performance. Specifically, 24 contingency tables were based on 18F-FDG PET/CT to distinguish AD patients from normal cognitive (NC) controls, and 14 contingency tables were based on sMRI for the same purpose. The meta-analysis results showed that for 18F-FDG PET/CT, the AI-assisted diagnostic systems had a pooled sensitivity, specificity, and SROC-AUC of 89% (95%CI 88% to 91%), 93% (95%CI 91% to 94%), and 0.96 (95%CI 0.93 to 0.97), respectively. For sMRI, the AI-assisted diagnostic systems had a pooled sensitivity, specificity, and SROC-AUC of 88% (95%CI 85% to 90%), 90% (95%CI 87% to 92%), and 0.94 (95%CI 0.92 to 0.96), respectively. ConclusionAI-assisted diagnostic systems based on either 18F-FDG PET/CT or sMRI demonstrated similar performance in the diagnosis of AD, with both showing high accuracy.
ObjectiveTo analyze the influencing factors for image quality of 18F-deoxyglucose (FDG) positron emission tomography (PET)/CT systemic tumor imaging and explore the method of control in order to improve the PET/CT image quality. MethodsRetrospective analysis of image data from March to June 2011 collected from 1 000 18F-FDG whole body tumor imaging patients was carried out. We separated standard films from non-standard films according to PET/CT image quality criteria. Related factors for non-standard films were analyzed to explore the entire process quality control. ResultsThere were 158 cases of standard films (15.80%), and 842 of non-standard films (84.20%). Artifact was a major factor for non-standard films (93.00%, 783/842) followed by patients’ injection information recording error (2.49%, 21/842), the instrument factor (1.90%, 16/842), incomplete scanning (0.95%, 8/842), muscle and soft tissue uptake (0.83%, 7/842), radionuclide contamination (0.59%, 5/842), and drug injection (0.24%, 2/842). The waste film rate was 5.80% (58/1 000), and the redoing rate was 2.20% (22/1 000). ConclusionComplex and diverse factors affect PET/CT image quality throughout the entire process, but most of them can be controlled if doctors, nurses and technicians coordinate and cooperate with each other. The rigorous routine quality control of equipment and maintenance, patients’ full preparation, appropriate position and scan field, proper parameter settings, and post-processing technology are important factors affecting the image quality.
Prostate cancer is the most common malignant tumor in male urinary system, and the morbidity and mortality rate are increasing year by year. Traditional imaging examinations have some limitations in the diagnosis of prostate cancer, and the advent of molecular imaging probes and imaging technology have provided new ideas for the integration of diagnosis and treatment of prostate cancer. In recent years, prostate-specific membrane antigen (PSMA) has attracted much attention as a target for imaging and treatment of prostate cancer. PSMA ligand positron emission tomography (PET) has important reference value in the diagnosis, initial staging, detection of biochemical recurrence and metastasis, clinical decision-making guidance and efficacy evaluation of prostate cancer. This article briefly reviews the clinical research and application progress on PSMA ligand PET imaging in prostate cancer in recent years, so as to raise the efficiency of clinical applications.