Retrospective analysis of pathological types and imaging features in pancreatic cancer: A comprehensive study

BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.

Features of primary pancreatic lymphoma:A bi-institutional review with an emphasis on typical and atypical imaging features

BACKGROUND Primary pancreatic lymphoma(PPL)is a rare neoplasm.Being able to distinguish it from other pancreatic malignancies such as pancreatic ductal adenocarcinoma(PDAC)is important for appropriate management.Unlike PDAC,PPL is highly sensitive to chemotherapy and usually does not require surgery.Therefore,being able to identify PPL preoperatively will not only direct physicians towards the correct avenue of treatment,it will also avoid unnecessary surgical intervention.AIM To evaluate the typical and atypical multi-phasic computed tomography(CT)imaging features of PPL.METHODS A retrospective review was conducted of the clinical,radiological,and pathological records of all subjects with pathologically proven PPL who presented to our institutions between January 2000 and December 2020.Institutional review board approval was obtained for this investigation.The collected data were analyzed for subject demographics,clinical presentation,laboratory values,CT imaging features,and the treatment received.Presence of all CT imaging findings including size,site,morphology and imaging characteristics of PPL such as the presence or absence of nodal,vascular and ductal involvement in these subjects were recorded.Only those subjects who had a pre-treatment multiphasic CT of the abdomen were included in the study.RESULTS Twenty-nine cases of PPL were diagnosed between January 2000 and December 2020(mean age 66 years;13 males/16 females).All twenty-nine subjects were symptomatic but only 4 of the 29 subjects(14%)had B symptoms.Obstructive jaundice occurred in 24%of subjects.Elevated lactate dehydrogenase was seen in 81%of cases,whereas elevated cancer antigen 19-9 levels were present in only 10%of cases for which levels were recorded.The vast majority(90%)of tumors involved the pancreatic head and uncinate process.Mean tumor size was 7.8 cm(range,4.0-13.8 cm).PPL presented homogenous hypoenhancement on CT in 72%of cases.Small volume peripancreatic lymphadenopathy was seen in 28%of subjects.Tumors demonstrated encasement of superior mesenteric vessels in 69%of cases but vascular stenosis or occlusion only manifested in 5 out of the twentynine individuals(17%).Mild pancreatic duct dilatation was also infrequent and seen in only 17%of cases,whereas common bile duct(CBD)dilation was seen in 41%of subjects.Necrosis occurred in 10%of cases.Size did not impact the prevalence of pancreatic and CBD dilation,necrosis,or mesenteric root infiltration(P=0.525,P=0.294,P=0.543,and P=0.097,respectively).Pancreatic atrophy was not present in any of the subjects.CONCLUSION PPL is an uncommon diagnosis best made preoperatively to avoid unnecessary surgery and ensure adequate treatment.In addition to the typical CT findings of PPL,such as homogeneous hypoenhancement,absence of vascular stenosis and occlusion despite encasement,and peripancreatic lymphadenopathy,this study highlighted many less typical findings,including small volume necrosis and pancreatic and bile duct dilation.

Clinical and multimodal imaging features of acute macular neuroretinopathy lesions following recent SARS-CoV-2 infection

AIM:To describe the clinical characteristics of eyes using multimodal imaging features with acute macular neuroretinopathy(AMN)lesions following severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.METHODS:Retrospective case series study.From December 18,2022 to February 14,2023,previously healthy cases within 1-week infection with SARS-CoV-2 and examined at Tianjin Eye Hospital to confirm the diagnosis of AMN were included in the study.Totally 5 males and 9 females[mean age:29.93±10.32(16-49)y]were presented for reduced vision,with or without blurred vision.All patients underwent best corrected visual acuity(BCVA),intraocular pressure,slit lamp microscopy,indirect fundoscopy.Simultaneously,multimodal imagings fundus photography(45°or 200°field of view)was performed in 7 cases(14 eyes).Near infrared(NIR)fundus photography was performed in 9 cases(18 eyes),optical coherence tomography(OCT)in 5 cases(10 eyes),optical coherence tomography angiography(OCTA)in 9 cases(18 eyes),and fundus fluorescence angiography(FFA)in 3 cases(6 eyes).Visual field was performed in 1 case(2 eyes).RESULTS:Multimodal imaging findings data from 14 patients with AMN were reviewed.All eyes demonstrated different extent hyperreflective lesions at the level of the inner nuclear layer and/or outer plexus layer on OCT or OCTA.Fundus photography(45°or 200°field of view)showed irregular hypo-reflective lesion around the fovea in 7 cases(14 eyes).OCTA demonstrated that the superficial retinal capillary plexus(SCP)vascular density,deep capillary plexus(DCP)vascular density and choriocapillaris(CC)vascular density was reduced in 9 case(18 eyes).Among the follow-up cases(2 cases),vascular density increased in 1 case with elevated BCVA;another case has vascular density decrease in one eye and basically unchanged in other eye.En face images of the ellipsoidal zone and interdigitation zone injury showed a low wedge-shaped reflection contour appearance.NIR image mainly show the absence of the outer retinal interdigitation zone in AMN.No abnormal fluorescence was observed in FFA.Corresponding partial defect of the visual field were visualized via perimeter in one case.CONCLUSION:The morbidity of SARS-CoV-2 infection with AMN is increased.Ophthalmologists should be aware of the possible,albeit rare,AMN after SARS-CoV-2 infection and focus on multimodal imaging features.OCT,OCTA,and infrared fundus phase are proved to be valuable tools for detection of AMN in patients with SARS-CoV-2.

Imaging features of alveolar soft part sarcoma

Objective The aim of this study was to analyze the imaging features of alveolar soft part sarcoma （ASPS）. Methods The imaging features of 11 cases with ASPS were retrospectively analyzed. Results ASPS mainly exhibited an isointense or slightly high signal intensity on Tl-weighted imaging （TlWl）, and a mixed high signal on T2-weighted imaging （T2Wl）. ASPS was partial, with rich tortuous flow voids, or ＂line-like＂ low signal septa. The essence of the mass was heterogeneous enhancement. The 1 H- MRS showed a slight choline peak at 3.2 ppm. Conclusion The well-circumscribed mass and blood voids, combined with ＂line-like＂ low signals play a significant role in diagnosis. The choline peak and the other signs may be auxiliary diagnoses.

Atypical imaging features of the primary spinal cord glioblastoma:A case report

BACKGROUND Primary spinal cord(PSC)glioblastoma(GB)is an extremely rare but fatal primary tumor of the central nervous system and associated with a poor prognosis.While typical tumor imaging features are generally easy to recognize,glioblastoma multiforme can have a wide range of imaging findings.Atypical GB is often misdiagnosed,which usually delays the optimal time for treatment.In this article,we discuss a clinical case of pathologically confirmed PSC GB under the guise of benign tumor imaging findings,as well as the most recent literature pertaining to PSC GB.CASE SUMMARY A 70-year-old female complained of limb weakness lasting more than 20 d.Irregular masses were observed inside and outside the left foramina of the spinal canal at C7-T1 on medical imaging.Based on the imaging features,radiologists diagnosed the patient with schwannoma.Tumor resection was performed under general anesthesia.The final histopathological findings revealed a final diagnosis of PSC GB,world health organization Grade IV.The patient subsequently underwent a 4-wk course of radiotherapy(60 Gy in 20 fractions)combined with temozolomide chemotherapy.The patient was alive at the time of submission of this manuscript.CONCLUSION Atypical GB presented unusual imaging findings,which led to misdiagnosis.Therefore,a complete recognition of imaging signs may facilitate early accurate diagnosis.

Imaging features of intrathoracic complications of lung transplantation:What the radiologists need to know

Lung transplantation has been a method for treating end stage lung disease for decades. Despite improvements in the preoperative assessment of recipients and donors as well as improved surgical techniques, lung transplant recipients are still at a high risk of developing postoperative complications which tend to impact negatively the patients' outcome if not recognised early. The recognised complications post lung transplantation can be broadly categorised into acute and chronic complications. Recognising the radiological features of these complications has a significant positive impact on patients' survival post transplantation. This manuscript provides a comprehensive review of the radiological features of post lung transplantations complications over a time continuum.

Imaging Features of Symptomatic Radiation-induced Cervical Artery Stenosis

Recently,the survival rate of head and neck cancer patients has increased with the improvement of radiotherapy （RT） technology and comprehensive treatment.Cancer survivors after RT are at increased risk for cerebrovascular events. Radiation-induced cervical artery stenosis （RICAS） has its own characteristics compared with those lesions without a history of RT.

Lung imaging characteristics in a patient infected with Elizabethkingia miricola following cerebral hemorrhage surgery: A case report

BACKGROUND Elizabethkingia miricola is a non-fermenting gram-negative bacterium,which was first isolated from the condensate of the Russian peace space station in 2003.Most studies on this bacterium have been carried out in the laboratory,and clinical case studies are rare.To date,a total of 6 clinical cases have been reported worldwide.CASE SUMMARY We present the first case of postoperative pulmonary infection in a patient with intracerebral hemorrhage due to Elizabethkingia miricola.The imaging character-istics of pulmonary infection were identified and the formulation and selection of the clinical treatment plan for this patient are discussed.CONCLUSION Elizabethkingia miricola infection is rare.When pulmonary infection occurs,computed tomography imaging may show diffuse distribution of a ground glass density shadow in both lungs,the air containing bronchial sign in local areas,thickening of bronchial vascular bundle,and pleural effusion.

The clinical and imaging features of 118 patients with spontaneous cerebral arterial dissections presenting with ischemic stroke

Objective To investigate the clinical and radiologic features of patients with spontaneous cerebral arterial dissections(CADs)presenting with ischemic stroke and to explore the effect of gender and age on those features.Methods Patients admitted to our stroke center diagnosed as ischemic stroke secondary to CADs from August 2008to April 2015 were prospectively registered.

NEW CORNER DETECTION ALGORITHM BASED ON MULTI-FEATURE SYNTHESIS

Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.

Imaging characteristics of orbital peripheral nerve sheath tumors:Analysis of 34 cases

BACKGROUND Peripheral nerve sheath tumors(PNSTs),a rare group of neoplasms in the orbit,comprise only 4%of all orbital tumors.At present,there are very few studies detailing the features of these tumors identified using imaging technology.AIM To compare the differences in location,morphology,magnetic resonance imaging(MRI)signal intensity/computed tomography(CT)value,and enhancement degree of tumors of different pathological PNSTs types.METHODS Clinical,pathological,CT,and MRI data were analyzed retrospectively in 34 patients with periorbital sheath tumors diagnosed using histopathology from January 2013 to August 2021.RESULTS Among 34 cases of orbital peripheral nerve sheath tumors,21 were schwannomas,12 were neurofibromas,and 1 was a plexiform neurofibroma.Common clinical symptoms presented by patients with these types of tumors include eyelid swelling,exophthalmos,and limited eye movement.Schwannomas mostly occur in the intramuscular space with small tumor volume and rare bone involvement.Neurofibromas develop in the extrapyramidal space with larger tumor volume and more bone involvement.Radiologically,schwannomas and neurofibromas are characterized by regular morphology and uneven density and signal.One case of plexiform neurofibroma showed tortuous and diffuse growth along the nerve,with a worm-like appearance on imaging.CONCLUSION Different pathological types of orbital peripheral nerve sheath tumors have unique imaging characteristics.Comprehensive consideration of the patient's clinical and imaging manifestations is of great value in the diagnosis of orbital peripheral nerve sheath tumors.

Role of the texture features of images in the diagnosis of solitary pulmonary nodules in different sizes

Objective： To explore the role of the texture features of images in the diagnosis of solitary pulmonary nodules （SPNs） in different sizes. Materials and methods： A total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes： ≤10, 11-20, and 〉20 mm. Their texture features were segmented and extracted. The differences in the image features between benign and malignant SPNs were compared. The SPNs in these three groups were determined and analyzed with the texture features of images. Results： These 379 SPNs were successfully segmented using the 2D Otsu threshold method and the self-adaptive threshold segmentation method. The texture features of these SPNs were obtained using the method of grey level co-occurrence matrix （GLCM）. Of these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. The entropy, contrast, energy, homogeneity, and correlation were 3.5597±0.6470, 0.5384±0.2561, 0.1921±0.1256, 0.8281±0.0604, and 0.8748±0.0740 in the benign SPNs and 3.8007±0.6235, 0.6088±0.2961, 0.1673±0.1070, 0.7980±0.0555, and 0.8550±0.0869 in the malignant SPNs （all P〈0.05）. The sensitivity, specificity, and accuracy of the texture features of images were 83.3%, 90.0%, and 86.8%, respectively, for SPNs sized 〈10 mm, and were 86.6%, 88.2%, and 87.1%, respectively, for SPNs sized 11-20 mm and 94.7%, 91.8%, and 93.9%, respectively, for SPNs sized 〉20 mm. Conclusions： The entropy and contrast of malignant pulmonary nodules have been demonstrated to be higher in comparison to those of benign pulmonary nodules, while the energy, homogeneity correlation of malignant pulmonary nodules are lower than those of benign pulmonary nodules. The texture features of images can reflect the tissue features and have high sensitivity, specificity, and accuracy in differentiating SPNs. The sensitivity and accuracy increase for larger SPNs.

Image block feature vectors based on a singular-value information metric and color-texture description

In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.

An Object-based Approach for Two-level Gully Feature Mapping Using High-resolution DEM and Imagery： A Case Study on Hilly Loess Plateau Region, China

Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.

FEATURE EXTRACTION OF BONES AND SKIN BASED ON ULTRASONIC SCANNING

In the prosthetic socket design, aimed at the high cost and radiation deficiency caused by CT scanning which is a routine technique to obtain the cross-sectional image of the residual limb, a new ultrasonic scanning method is developed to acquire the bones and skin contours of the residual limb. Using a pig fore-leg as the scanning object, an overlapping algorithm is designed to reconstruct the 2D cross-sectional image, the contours of the bone and skin are extracted using edge detection algorithm and the 3D model of the pig fore-leg is reconstructed by using reverse engineering technology. The results of checking the accuracy of the image by scanning a cylinder work pieces show that the extracted contours of the cylinder are quite close to the standard circumference. So it is feasible to get the contours of bones and skin by ultrasonic scanning. The ultrasonic scanning system featuring no radiation and low cost is a kind of new means of cross section scanning for medical images.

Evolutionary Computation Based Optimization of Image Zernike Moments Shape Feature Vector

The image shape feature can be described by the image Zernike moments. In this paper, we points out the problem that the high dimension image Zernike moments shape feature vector can describe more detail of the original image but has too many elements making trouble for the next image analysis phases. Then the low dimension image Zernike moments shape feature vector should be improved and optimized to describe more detail of the original image. So the optimization algorithm based on evolutionary computation is designed and implemented in this paper to solve this problem. The experimental results demonstrate the feasibility of the optimization algorithm.

A Method of Using Information Entropy of an Image as an Effective Feature for Com-puter-Aided Diagnostic Applications

Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. In general, a CAD system employs a classifier to detect or distinguish between abnormal and normal tissues on images. In the phase of classification, a set of image features and/or texture features extracted from the images are commonly used. In this article, we investigated the characteristic of the output entropy of an image and demonstrated the usefulness of the output entropy acting as a texture feature in CAD systems. In order to validate the effectiveness and superiority of the output-entropy-based texture feature, two well-known texture features, i.e., mean and standard deviation were used for comparison. The database used in this study comprised 50 CT images obtained from 10 patients with pulmonary nodules, and 50 CT images obtained from 5 normal subjects. We used a support vector machine for classification. A leave-one-out method was employed for training and classification. Three combinations of texture features, i.e., mean and entropy, standard deviation and entropy, and standard deviation and mean were used as the inputs to the classifier. Three different regions of interest (ROI) sizes, i.e., 11 × 11, 9 × 9 and 7 × 7 pixels from the database were selected for computation of the feature values. Our experimental results show that the combination of entropy and standard deviation is significantly better than both the combination of mean and entropy and that of standard deviation and mean in the case of the ROI size of 11 × 11 pixels (p < 0.05). These results suggest that information entropy of an image can be used as an effective feature for CAD applications.

New Fragile Watermarking Technique to Identify Inserted Video Objects Using H.264 and Color Features

The transmission of video content over a network raises various issues relating to copyright authenticity,ethics,legality,and privacy.The protection of copyrighted video content is a significant issue in the video industry,and it is essential to find effective solutions to prevent tampering and modification of digital video content during its transmission through digital media.However,there are stillmany unresolved challenges.This paper aims to address those challenges by proposing a new technique for detectingmoving objects in digital videos,which can help prove the credibility of video content by detecting any fake objects inserted by hackers.The proposed technique involves using two methods,the H.264 and the extraction color features methods,to embed and extract watermarks in video frames.The study tested the performance of the system against various attacks and found it to be robust.The evaluation was done using different metrics such as Peak-Signal-to-Noise Ratio(PSNR),Mean Squared Error(MSE),Structural Similarity Index Measure(SSIM),Bit Correction Ratio(BCR),and Normalized Correlation.The accuracy of identifying moving objects was high,ranging from 96.3%to 98.7%.The system was also able to embed a fragile watermark with a success rate of over 93.65%and had an average capacity of hiding of 78.67.The reconstructed video frames had high quality with a PSNR of at least 65.45 dB and SSIMof over 0.97,making them imperceptible to the human eye.The system also had an acceptable average time difference(T=1.227/s)compared with other state-of-the-art methods.

Robustness Evaluation of Remote-Sensing Image Feature Detectors with TH Priori-Information Data Set

In this paper,we build a remote-sensing satellite imagery priori-information data set,and propose an approach to evaluate the robustness of remote-sensing image feature detectors.The building TH Priori-Information(TPI)data set with 2297 remote sensing images serves as a standardized high-resolution data set for studies related to remote-sensing image features.The TPI contains 1)raw and calibrated remote-sensing images with high spatial and temporal resolutions(up to 2 m and 7 days,respectively),and 2)a built-in 3-D target area model that supports view position,view angle,lighting,shadowing,and other transformations.Based on TPI,we further present a quantized approach,including the feature recurrence rate,the feature match score,and the weighted feature robustness score,to evaluate the robustness of remote-sensing image feature detectors.The quantized approach gives general and objective assessments of the robustness of feature detectors under complex remote-sensing circumstances.Three remote-sensing image feature detectors,including scale-invariant feature transform(SIFT),speeded up robust features(SURF),and priori information based robust features(PIRF),are evaluated using the proposed approach on the TPI data set.Experimental results show that the robustness of PIRF outperforms others by over 6.2%.

Jamming Recognition Based on Feature Fusion and Convolutional Neural Network

The complicated electromagnetic environment of the BeiDou satellites introduces vari-ous types of external jamming to communication links,in which recognition of jamming signals with uncertainties is essential.In this work,the jamming recognition framework proposed consists of fea-ture fusion and a convolutional neural network(CNN).Firstly,the recognition inputs are obtained by prepossessing procedure,in which the 1-D power spectrum and 2-D time-frequency image are ac-cessed through the Welch algorithm and short-time Fourier transform(STFT),respectively.Then,the 1D-CNN and residual neural network(ResNet)are introduced to extract the deep features of the two prepossessing inputs,respectively.Finally,the two deep features are concatenated for the following three fully connected layers and output the jamming signal classification results through the softmax layer.Results show the proposed method could reduce the impacts of potential feature loss,therefore improving the generalization ability on dealing with uncertainties.