There are various examination methods for cardiovascular diseases. Non-invasive diagnosis and prognostic information acquisition are the current research hotspots of related imaging examinations. Positron emission tomography (PET)/magnetic resonance imaging (MRI) is a new advanced fusion imaging technology that combines the molecular imaging of PET with the soft tissue contrast function of MRI to achieve their complementary advantages. This article briefly introduces several major aspects of cardiac PET/MRI in the diagnosis of cardiovascular disease, including atherosclerosis, ischemic cardiomyopathy, nodular heart disease, and myocardial amyloidosis, in order to promote cardiac PET/MRI to be more widely used in precision medicine in this field.
Because of the unobvious early symptoms and low 5-year survival rate, the early diagnosis and treatment is of great significance for patients with non-small cell lung cancer. Glucose transporter-1 is the most widely distributed glucose transporters in various tissue cells in the human body, whose expression in non-small cell lung cancer is closely related to the histological types, lymph node metastasis, degree of differentiation, progression and prognosis.18F-FDG PET/CT imaging, a molecular imaging diagnostic method, is based on the characteristics of glucose metabolism in malignant tumors, which has been widely applied in the cancer diagnosis, stage division, evaluation of therapeutic effects and prognosis evaluation. Glucose transporter-1 is regulated and influenced by many factors, and it is closely related to 18F-FDG PET/CT imaging. This article briefly reviews the progress in the clinical application and correlation between glucose transporter-1 and 18F-FDG PET/CT imaging for non-small cell lung cancer, in order to improve the diagnosis and treatment of lung cancer.
Objective To investigate the accuracy of 18F-FDG positron emission tomography/computed tomography (PET/CT) combined with CT three-dimensional reconstruction (CT-3D) in the differential diagnosis of benign and malignant pulmonary nodules. Methods The clinical data of patients who underwent pulmonary nodule surgery in the Department of Thoracic Surgery, Northern Jiangsu People's Hospital from July 2020 to August 2021 were retrospectively analyzed. The preoperative 18F-FDG PET/CT and chest enhanced CT-3D and other imaging data were extracted. The parameters with diagnostic significance were screened by the area under the receiver operating characteristic (ROC) curve (AUC). Three prediction models, including PET/CT prediction model (MOD PET), CT-3D prediction model (MOD CT-3D), and PET/CT combined CT-3D prediction model (MOD combination), were established through binary logistic regression, and the diagnostic performance of the models were validated by ROC curve. Results A total of 125 patients were enrolled, including 57 males and 68 females, with an average age of 61.16±8.57 years. There were 46 patients with benign nodules, and 79 patients with malignant nodules. A total of 2 PET/CT parameters and 5 CT-3D parameters were extracted. Two PET/CT parameters, SUVmax≥1.5 (AUC=0.688) and abnormal uptake of hilar/mediastinal lymph node metabolism (AUC=0.671), were included in the regression model. Among the CT-3D parameters, CT value histogram peaks (AUC=0.694) and CT-3D morphology (AUC=0.652) were included in the regression model. Finally, the AUC of the MOD PET was verified to be 0.738 [95%CI (0.651, 0.824)], the sensitivity was 74.7%, and the specificity was 60.9%; the AUC of the MOD CT-3D was 0.762 [95%CI (0.677, 0.848)], the sensitivity was 51.9%, and the specificity was 87.0%; the AUC of the MOD combination was 0.857 [95%CI (0.789, 0.925)], the sensitivity was 77.2%, the specificity was 82.6%, and the differences were statistically significant (P<0.001). Conclusion 18F-FDG PET/CT combined with CT-3D can improve the diagnostic performance of pulmonary nodules, and its specificity and sensitivity are better than those of single imaging diagnosis method. The combined prediction model is of great significance for the selection of surgical timing and surgical methods for pulmonary nodules, and provides a theoretical basis for the application of artificial intelligence in the pulmonary nodule diagnosis.
ObjectiveTo investigate the imaging characteristics of gallium-68 labeled fibroblast activation protein inhibitor (68Ga-FAPI)-positron emission tomography/magnetic resonance (PET/MR) imaging in patients with liver fibrosis or liver tumor. MethodsThirteen patients with suspected liver tumor who underwent 68Ga-FAPI-PET/MR examination from May 2020 to April 2021 were retrospectively analyzed. Maximum standard uptake value (SUVmax) was investigated. All patients underwent liver surgery or biopsy. Scheuer scoring system was used to evaluate the liver fibrosis. The imaging characteristics of liver fibrosis or liver tumor were analyzed. ResultsThe liver fibrosis was confirmed in 6 patients, including 1 case of S2, 2 cases of S3, and 3 cases of S4. Among them, 4 patients had increased uptake of 68Ga-FAPI, with patchy or diffuse abnormal concentration of liver, and the SUVmax was 7.9±3.1. The liver imaging of the other 2 patients with liver fibrosis showed no obvious radioactive concentration. In addition, 2 patients were diagnosed with hepatocellular carcinoma, its SUVmax was 7.2 and 6.1; 1 patient was diagnosed with hepatobiliary duct carcinoma and its SUVmax was 13.8. Moreover, increased uptake of 68Ga-FAPI was observed in 4 patients with metastatic liver cancer, with SUVmax of 6.7±2.7. ConclusionBoth liver fibrosis and liver tumor are suitable for 68Ga-FAPI-PET/MR examination, which have different imaging characteristics.
Autoimmune pancreatitis (AIP) is a unique subtype of chronic pancreatitis, which shares many clinical presentations with pancreatic ductal adenocarcinoma (PDA). The misdiagnosis of AIP often leads to unnecessary pancreatic resection. 18F-FDG positron emission tomography/ computed tomography (PET/CT) could provide comprehensive information on the morphology, density, and functional metabolism of the pancreas at the same time. It has been proved to be a promising modality for noninvasive differentiation between AIP and PDA. However, there is a lack of clinical analysis of PET/CT image texture features. Difficulty still remains in differentiating AIP and PDA based on commonly used diagnostic methods. Therefore, this paper studied the differentiation of AIP and PDA based on multi-modality texture features. We utilized multiple feature extraction algorithms to extract the texture features from CT and PET images at first. Then, the Fisher criterion and sequence forward floating selection algorithm (SFFS) combined with support vector machine (SVM) was employed to select the optimal multi-modality feature subset. Finally, the SVM classifier was used to differentiate AIP from PDA. The results prove that texture analysis of lesions helps to achieve accurate differentiation of AIP and PDA.
Medical whole-body positron emission tomography (PET), one of the most successful molecular imaging technologies, has been widely used in the fields of cancer diagnosis, cardiovascular disease diagnosis and cranial nerve study. But, on the other hand, the sensitivity, spatial resolution and signal-noise-ratio of the commercial medical whole-body PET systems still have some shortcomings and a great room for improvement. The sensitivity, spatial resolution and signal-noise-ratio of PET system are largely affected by the performances of the scintillators and the photo detectors. The design of a PET system is usually a trade-off in cost and performance. A better image quality can be achieved by optimizing and balancing the key components which affect the system performance the most without dramatically increases in cost. With the development of the scintillator, photo-detector and high speed electronic system, the performance of medical whole-body PET system would be dramatically improved. In this paper, we report current progresses and discuss future directions of the developments of technologies in medical whole-body PET system.
Prostate cancer is the most common tumor of the urinary system, and its mortality rate is second only to lung cancer. With the specific and high expression on the surface of prostate cancer cells, prostate-specific membrane antigen (PSMA) has been an ideal theranostic target of prostate cancer with great clinical significance and research value. Positron emission tomography/computed tomography (PET/CT), a new modality of molecular imaging combining functional metabolic information and anatomical structure, provides high diagnostic performance for cancer detection. This paper mainly reviewed recent progress of PSMA inhibitors labeled by positron-emitting radionuclides for early diagnosis, preoperative staging, response assessment, restaging and metastasis detection of prostate cancer.
The convolutional neural network (CNN) could be used on computer-aided diagnosis of lung tumor with positron emission tomography (PET)/computed tomography (CT), which can provide accurate quantitative analysis to compensate for visual inertia and defects in gray-scale sensitivity, and help doctors diagnose accurately. Firstly, parameter migration method is used to build three CNNs (CT-CNN, PET-CNN, and PET/CT-CNN) for lung tumor recognition in CT, PET, and PET/CT image, respectively. Then, we aimed at CT-CNN to obtain the appropriate model parameters for CNN training through analysis the influence of model parameters such as epochs, batchsize and image scale on recognition rate and training time. Finally, three single CNNs are used to construct ensemble CNN, and then lung tumor PET/CT recognition was completed through relative majority vote method and the performance between ensemble CNN and single CNN was compared. The experiment results show that the ensemble CNN is better than single CNN on computer-aided diagnosis of lung tumor.
In the process of positron emission tomography (PET) data acquiring, respiratory motion reduces the quality of PET imaging. In this paper, we present a correction method using three level grids B-spline elastic method to correct denoised and reorganized sinograms for respiratory motion correction. Using GATE simulates NCAT respiratory motion model to generate raw data which are used in experiment, the experiment results showed a significantly improved respiratory image with higher quality of PET, and the motion blur and structural information were fixed. The results proved the method of this paper would be effective for the elastic registration.