ObjectiveTo summarize the research progress of CT related to esophageal varices of cirrhotic patients complicated with portal hypertension.MethodsRelevant CT literatures of esophageal varices of cirrhotic patients complicated with portal hypertension were collected to make an review,then summarized the research status and progress of CT in the diagnosis and evaluation of lower esophageal varices.ResultCT had a good correlation with endoscopic diagnosis of esophageal varices, and CT was of great value in evaluating the presence, degree, and risk of esophageal varicose veins, especially in predicting the risk of esophageal varicose veins, which could be used as an effective modality to assist endoscopic examination to a certain extent.ConclusionsCT is an important examination method for esophageal varices, which has important value in diagnosis and evaluation. In the future, more further researches can be carried out to provide more strong and accurate support for the diagnosis and treatment of esophageal varices.
Objective To summarize the CT, MRI, and positron emission computed tomography (PET) imaging findings of hematologic malignancies of the pancreas, so as to improve the capacity of its diagnosis. Methods After searching articles concerning radiological research about hematologic malignancies of the pancreas, summarizing its imaging characteristics. Results Hematologic malignancies of the pancreas include pancreatic lymphoma, pancreatic multiple myeloma, myeloid sarcoma, posttransplantation lymphoproliferative disorder, and giant lymph node hyperplasia. ① Pancreatic lymphoma: imaging features of pancreatic lymphoma are segmental or diffuse homogeneous enlargement of the pancreas, diameter of mass >5 cm, adenopathy below the level of renal veins, and lack of pancreatic duct dilation. Blurred margins of pancreas by lymphadenopathy is highly suggestive of lymphoma. ② Pancreatic multiple myeloma: pancreatic multiple myeloma are hyperintense on both T1- and T2-weighted images. ③ Pancreatic granulocytic sarcoma: pancreatic granulocytic sarcoma present as homogeneous hypoenhancing mass on CT, usually without pancreatic duct dilation. On MRI, the lesions are isointense and mildly hyperintense on T1- and T2-weighted images respectively. ④ Posttransplantation lymphoproliferative disorder: diameter of leison of posttransplantation lymphoproliferative disorder usually is >5 cm with poor enhancement. Lesions are mildly hyperintense on T2-weighted images and extremely hypermetabolic on PET images. ⑤ Giant lymph node hyperplasia: it mainly appear as solitary noninvasive masses. Punctate calcification and surrounding supply vessels are observed in hyaline vascular type. Plasma cell type demonstrate unapparent enhancement and less calcification. Conclusions Hematologic malignancies of the pancreas manifest different imaging features on CT, MRI, and PET. Familiarity with such characteristics helps to early recognize diseases and determine next-step measures.
Objective To summarize the imaging manifestation and identification of ectopic pancreas (EP), so as to improve clinicians and radiologists’ knowledge of EP and aid in accurate preoperative diagnosis, thereby reducing the misdiagnosis rate and avoiding unnecessary surgery. Methods Combined with clinical experience and relevant literatures in recent years, the histopathology, common imaging manifestations and main differential diagnosis of ectopic pancreas were summarized. Results EP is a rare congenital developmental anomaly of pancreas, the most common location is the upper digestive system. At present, the commonly used imaging technology is computed tomography. The imaging findings of ectopic pancreas were similar to those of normal pancreas, and its density and enhancement characteristics were related to its histopathological composition. The specific signs of ectopic pancreas include “central umbilical sign” “ductal structure” and “flat/adherent sign”. Heterotopic pancreas should be differentiated from submucosal tumor of gastrointestinal tract. Conclusions The imaging findings of EP have certain characteristics. For some cases with atypical imaging findings, imaging diagnosis is difficult.
Image registration is of great clinical importance in computer aided diagnosis and surgical planning of liver diseases. Deep learning-based registration methods endow liver computed tomography (CT) image registration with characteristics of real-time and high accuracy. However, existing methods in registering images with large displacement and deformation are faced with the challenge of the texture information variation of the registered image, resulting in subsequent erroneous image processing and clinical diagnosis. To this end, a novel unsupervised registration method based on the texture filtering is proposed in this paper to realize liver CT image registration. Firstly, the texture filtering algorithm based on L0 gradient minimization eliminates the texture information of liver surface in CT images, so that the registration process can only refer to the spatial structure information of two images for registration, thus solving the problem of texture variation. Then, we adopt the cascaded network to register images with large displacement and large deformation, and progressively align the fixed image with the moving one in the spatial structure. In addition, a new registration metric, the histogram correlation coefficient, is proposed to measure the degree of texture variation after registration. Experimental results show that our proposed method achieves high registration accuracy, effectively solves the problem of texture variation in the cascaded network, and improves the registration performance in terms of spatial structure correspondence and anti-folding capability. Therefore, our method helps to improve the performance of medical image registration, and make the registration safely and reliably applied in the computer-aided diagnosis and surgical planning of liver diseases.
ObjectiveTo evaluate the clinical feasibility and safety of CT-guided percutaneous microwave ablation for peripheral solitary pulmonary nodules.MethodsThe imaging and clinical data of 33 patients with pulmonary nodule less than 3 cm in diameter treated by CT-guided microwave ablation treatment (PMAT) in our hospital from July 2018 to December 2019 were retrospectively analyzed. There were 21 males and 12 females aged 38-90 (67.6±13.4) years. Among them, 26 patients were confirmed with lung cancer by biopsy and 7 patients were clinically considered as partial malignant lesions. The average diameter of 33 nodules was 0.6-3.0 (1.8±0.6) cm. The 3- and 6-month follow-up CT was performed to evaluate the therapy method by comparing the diameter and enhancement degree of lesions with 1-month CT manifestation. Short-term treatment analysis including complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD) was calculated according to the WHO modified response evaluation criteria in solid tumor (mRECIST) for short-term efficacy evaluation. Eventually the result of response rate (RR) was calculated. Progression-free survival was obtained by Kaplan–Meier analysis.ResultsCT-guided percutaneous microwave ablation was successfully conducted in all patients. Three patients suffered slight pneumothorax. There were 18 (54.5%) patients who achieved CR, 9 (27.3%) patients PR, 4 (12.1%) patients SD and 2 (6.1%) patients PD. The short-term follow-up effective rate was 81.8%. Logistic analysis demonstrated that primary and metastatic pulmonary nodules had no difference in progression-free time (log-rank P=0.624).ConclusionPMAT is of high success rate for the treatment of solitary pulmonary nodules without severe complications, which can be used as an effective alternative treatment for nonsurgical candidates.
In order to suppress the geometrical artifacts caused by random jitter in ray source scanning, and to achieve flexible ray source scanning trajectory and meet the requirements of task-driven scanning imaging, a method of free trajectory cone-beam computed tomography (CBCT) reconstruction is proposed in this paper. This method proposed a geometric calibration method of two-dimensional plane. Based on this method, the geometric calibration phantom and the imaging object could be simultaneously imaged. Then, the geometric parameters could be obtained by online calibration method, and then combined with the geometric parameters, the alternating direction multiplier method (ADMM) was used for image iterative reconstruction. Experimental results showed that this method obtained high quality reconstruction image with high contrast and clear feature edge. The root mean square errors (RMSE) of the simulation results were rather small, and the structural similarity (SSIM) values were all above 0.99. The experimental results showed that it had lower image information entropy (IE) and higher contrast noise ratio (CNR). This method provides some practical value for CBCT to realize trajectory freedom and obtain high quality reconstructed image.
For patients with partial jaw defects, cysts and dental implants, doctors need to take panoramic X-ray films or manually draw dental arch lines to generate Panorama images in order to observe their complete dentition information during oral diagnosis. In order to solve the problems of additional burden for patients to take panoramic X-ray films and time-consuming issue for doctors to manually segment dental arch lines, this paper proposes an automatic panorama reconstruction method based on cone beam computerized tomography (CBCT). The V-network (VNet) is used to pre-segment the teeth and the background to generate the corresponding binary image, and then the Bezier curve is used to define the best dental arch curve to generate the oral panorama. In addition, this research also addressed the issues of mistakenly recognizing the teeth and jaws as dental arches, incomplete coverage of the dental arch area by the generated dental arch lines, and low robustness, providing intelligent methods for dental diagnosis and improve the work efficiency of doctors.
Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.
Trabecular microstructure is an important factor in determining bone strength and physiological function. Normal X-ray and computed tomography (CT) cannot accurately reflect the microstructure of trabecular bone. High-resolution peripheral quantitative computed tomography (HR-pQCT) is a new imaging technique in recent years. It can qualitatively and quantitatively measure the three-dimensional microstructure and volume bone mineral density of trabecular bone in vivo. It has high precision and relative low dose of radiation. This new imaging tool is helpful for us to understand the trabecular microstructure more deeply. The finite element analysis of HR-pQCT data can be used to predict the bone strength accurately. We can assess the risk of osteoporosis and fracture with three-dimensional reconstructed images and trabecular microstructure parameters. In this review, we summarize the technical flow, data parameters and clinical application of HR-pQCT in order to provide some reference for the popularization and extensive application of HR-pQCT.
ObjectiveTo investigate the radiomics features to distinguish invasive lung adenocarcinoma with micropapillary or solid structure. MethodsA retrospective analysis was conducted on patients who received surgeries and pathologically confirmed invasive lung adenocarcinoma in our hospital from April 2016 to August 2019. The dataset was randomly divided into a training set [including a micropapillary/solid structure positive group (positive group) and a micropapillary/solid structure negative group (negative group)] and a testing set (including a positive group and a negative group) with a ratio of 7∶3. Two radiologists drew regions of interest on preoperative high-resolution CT images to extract radiomics features. Before analysis, the intraclass correlation coefficient was used to determine the stable features, and the training set data were balanced using synthetic minority oversampling technique. After mean normalization processing, further radiomics features selection was conducted using the least absolute shrinkage and selection operator algorithm, and a 5-fold cross validation was performed. Receiver operating characteristic (ROC) curves were depicted on the training and testing sets to evaluate the diagnostic performance of the radiomics model. ResultsA total of 340 patients were enrolled, including 178 males and 162 females with an average age of 60.31±6.69 years. There were 238 patients in the training set, including 120 patients in the positive group and 118 patients in the negative group. There were 102 patients in the testing set, including 52 patients in the positive group and 50 patients in the negative group. The radiomics model contained 107 features, with the final 2 features selected for the radiomics model, that is, Original_ glszm_ SizeZoneNonUniformityNormalized and Original_ shape_ SurfaceVolumeRatio. The areas under the ROC curve of the training and the testing sets of the radiomics model were 0.863 (95%CI 0.815-0.912) and 0.857 (95%CI 0.783-0.932), respectively. The sensitivity was 91.7% and 73.7%, the specificity was 78.8% and 84.0%, and the accuracy was 85.3% and 78.4%, respectively. ConclusionThere are differences in radiomics features between invasive pulmonary adenocarcinoma with or without micropapillary and solid structures, and the radiomics model is demonstrated to be with good diagnostic value.