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.
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.
The aim of this study is to analyze the concordance between EDV, ESV and LVEF values derived from 18F-FDG PET, GSPECT and ECHO in patients with myocardial infarction. Sixty-four patients with coronary artery disease (CAD) and myocardial infarction were enrolled in the study.. Each patient underwent at least two of the above mentioned studies within 2 weeks. LVEF、 EDV and ESV values were analyzed with dedicated software. Statistical evaluation of correlation and agreement was carried out EDV was overestimated by 18F-FDG PET compared with GSPECT [(137.98±61.71) mL and (125.35±59.34) mL]; ESV was overestimated by 18F-FDG PET (85.89±55.21) mL and GSPECT (82.39±55.56) mL compared with ECHO (68.22±41.37) mL; EF was overestimated by 18F-FDG PET (41.96%±15.08%) and ECHO (52.18%±13.87%) compared with GSPECT (39.75%±15.64%), and EF was also overestimated by 18F-FDG PET compared with GSPECT. The results of linear regression analysis showed good correlation between EDV, ESV and LVEF values derived from 18F-FDG PET, GSPECT and ECHO (r=0.643-0.873, P=0.000). Bland-Altman analysis indicated that 18F-FDG PET correlated well with ECHO in the Left ventricular function parameters. While GSPECT correlated well with 18F-FDG PET in ESV, GSPECT had good correlation with Echo in respect of EDV and EF; whereas GSPECT had poor correlation with PET/ECHO in the remaining left ventricular function parameters. Therefore, the clinical physicians should decide whether they would use the method according to the patients' situation and diagnostic requirements.
Galectin-3 and human bone marrow endothelial cell marker (HBME-1), which play an important role in tumor growth and metastasis, are good markers for thyroid cancer. The diagnosis specificity and accuracy for thyroid cancers have been increased with the application of 18F-fluordeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT). The value of Galectin-3, HBME-1 expression and 18F-FDG imaging in differentiated thyroid carcinoma is reviewed in the present paper.
Objective To summary the recent progression of imaging methods which mainly applied on the early detection and qualitative diagnosis of pancreatic cancer. Method The newest related literatures between home and abroad were collected and reviewed. Results Ultrasonic, computed tomography, magnetic resonance imaging and positron emission tomography mostly be used on pancreatic cancer detection and diagnosis. Conclusion Each method gets its own advantage even computed tomography seems like dominated on the detection and diagnosis pancreatic cancer, moreover, magnetic resonance imaging has been improved rapidly in recent years which shows its enormous potential.
Primary hepatocellular carcinoma is a common cancer. Many patients are found with intermediate-advanced stage, rapid development, poor treatment and high mortality. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) can discover the early lesions and therefore plays an important role in diagnosis, treatment and prognosis of patients with hepatocellular carcinoma. It especially has obvious advantages in detecting metastasis and monitoring recurrence. However, 18F-FDG PET/CT imaging has poor quality and low diagnosis rate. Understanding the advantages and limitations of 18F-FDG PET/CT can provide better basis for clinical diagnosis and treatment for hepatocellular carcinoma patients. This article briefly introduces the research and application of 18F-FDG PET/CT in the diagnosis and treatment of hepatocellular carcinoma.
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.
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.
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.