Current Medical Imaging Reviews最新文献

{"title":"Assessing Pulmonary Embolisms on Unenhanced CT Images Using Electron Density Images Derived from Dual-Layer Spectral Detector CT: A Single-centre Prospective Study Conducted at the Emergency Department.","authors":"Huayang Du, Xin Sui, Ruijie Zhao, Jiaru Wang, Ying Ming, Sirong Piao, Jinhua Wang, Xiaomei Lu, Lan Song, Wei Song","doi":"10.2174/0115734056316803241021102932","DOIUrl":"https://doi.org/10.2174/0115734056316803241021102932","url":null,"abstract":"<p><p>Aims To evaluate the utility of unenhanced spectral imaging, electron density (ED) and overlay electron density (OED) images for assessing pulmonary embolisms in patients with suspected or confirmed acute pulmonary embolism (APE). Background Multiple spectral images can be extrapolated from spectral detector CT (SDCT), ED and OED images. ED and OED images are highly sensitive to moisture-rich tissues. Potential use for detecting pulmonary artery thrombi in non-enhanced chest CT images. Objective To assess the sensitivity, specificity and accuracy of ED and OED images obtained using SDCT for the detection of pulmonary embolism on non-enhanced images. Method Seventy-nine patients who underwent unenhanced and CT pulmonary angiography using dual-layer spectral detector CT to evaluate APE between November 2021 and April 2022 were enrolled in this retrospective study. Based on unenhanced spectral and CTPA images, two radiologists identified areas of high density in the main, lobar, and segmental pulmonary arteries on ED and OED images and detected pulmonary embolism (PE) on enhanced images using a consultative approach. CTPA results were considered the gold standard. The diagnostic performance of ED and OED in detecting PE was analyzed. Results PE was detected in 40 patients (40/79), and 17, 69, and 20 PEs were detected in the main, lobar, and segmental arteries, respectively. The PE detection sensitivity on ED images was 69.7-94.7%, and the specificity was 58.5-98.2% for the individual, main, lobe, and segmental pulmonary arteries. The sensitivity and specificity for OED images were 94.1-95.2% and 80.0-98.1%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) were 53.6-87.7% and 69.7-95.9% for ED images, and 48.5-88.9% and 94.1-98.9% for OED images, respectively. The accuracy was 76.0-98.9% and 87.3-96.2% when using ED and OED images, respectively. The research identified that whether main, lobar or segmental pulmonary arteries with blood clots, EDW values ranged from 108.1-108.8 %EDW, 3.9-4.2 %EDW higher than those of arteries without emboli. Pulmonary arteries with emboli standardised ED values were 103.6-104.3 %EDW. Conclusion ED and OED images using spectral CT without contrast media demonstrated high diagnostic performance and could improve the visualization of PE.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence in Transcranial Doppler Ultrasonography.","authors":"Antonio Siniscalchi, Vincenzo Inghingolo, Piergiorgio Lochner, Giovanni Malferrari","doi":"10.2174/0115734056331493241217075436","DOIUrl":"https://doi.org/10.2174/0115734056331493241217075436","url":null,"abstract":"<p><p>Transcranial Doppler is an instrumental ultrasound method capable of providing data on various brain pathologies, in particular, the study of cerebral hemodynamics in stroke, quickly, economically, and with repeatability of the data themselves. However, literature reviews from clinical studies and clinical trials reported that it is an operator-dependent method, and the data can be influenced by external factors, such as noise, which may require greater standardization of the parameters. Artificial intelligence can be utilized on transcranial Doppler to increase the accuracy and precision of the data collected while decreasing operator dependencies. In a time-dependent pathology, such as stroke, characterized by hemodynamic evolution, the use of artificial intelligence in transcranial Doppler ultrasound could represent beneficial support for better diagnosis and treatment in time-dependent pathologies, such as stroke.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study Hotspot and Trend in the Field of Shear Wave Elastography: A Bibliometric Analysis from 2004 to 2024.","authors":"Jingjing Zhao, Linping Pian, Jie Chen, Quanjiang Wang, Feiyan Han, Yameng Liu","doi":"10.2174/0115734056353590250109081225","DOIUrl":"https://doi.org/10.2174/0115734056353590250109081225","url":null,"abstract":"<p><strong>Background: </strong>The objective of this study was to comprehensively review the literature on Shear Wave Elastography (SWE), a non-invasive imaging technique prevalent in medical ultrasound. SWE is instrumental in assessing superficial glandular tissues, abdominal organs, tendons, joints, carotid vessels, and peripheral nerve tissues, among others. By employing bibliometric analysis, we aimed to encapsulate the scholarly contributions over the past two decades, identifying key research areas and tracing the evolutionary trajectory of SWE.</p><p><strong>Methods: </strong>For this study, we selected research articles related to SWE published between 2004 and March 2024 from the Web of Science Core Collection (WOSCC). We utilized sophisticated bibliometric tools, such as CiteSpace, VOSviewer, and SCImago Graphica, to analyze the trends in annual publications, contributing countries and institutions, journals, authors, co-cited authors, co-cited references, and keywords.</p><p><strong>Results: </strong>Our analysis yielded a total of 3606 papers. China emerged as the leading country in terms of publication output, with a strong collaborative relationship with the United States. Sun Yat-Sen University was identified as the institution with the highest number of publications. The keyword \"transient elastography\" was the most prevalent, with \"acoustic radiation force\" being a focal point in the initial stages of SWE research. Recently, Contrast-enhanced Ultrasound (CEUS) has emerged as a new research focus, signaling a potential direction for future research and development.</p><p><strong>Conclusion: </strong>The global research landscape for SWE is projected to expand continuously. Future research is likely to concentrate on the integrated application of SWE and CEUS for diagnostic purposes, along with exploring the clinical utility of multimodal ultrasound that synergistically combines SWE with other ultrasound technologies. This bibliometric research offers a comprehensive overview of the SWE literature, guiding researchers in their pursuit of further exploration and discovery.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"White Matter Fiber Bundle Alterations Correlate with Gait and Cognitive Impairments in Parkinson's Disease based on HARDI Data.","authors":"Lining Dong, Mingkai Zhang, Zheng Wang, Ying Yan, Ran An, Zhenchang Wang, Xuan Wei","doi":"10.2174/0115734056330364250109072154","DOIUrl":"https://doi.org/10.2174/0115734056330364250109072154","url":null,"abstract":"<p><strong>Background: </strong>The neuroanatomical basis of white matter fiber tracts in gait impairments in individuals suffering from Parkinson's Disease (PD) is unclear.</p><p><strong>Methods: </strong>Twenty-four individuals living with PD and 29 Healthy Controls (HCs) were included. For each participant, two-shell High Angular Resolution Diffusion Imaging (HARDI) and high-resolution 3D structural images were acquired using the 3T MRI. Diffusion-weighted data preprocessing was performed using the orientation distribution function to trace the main fiber tracts in PD individuals. Clinical characteristics between the two groups were compared, and the correlation between the FA value and behavioral data was analyzed. Quantitative gait and clinical parameters were recorded in PD at ON and OFF states, respectively.</p><p><strong>Results: </strong>The mean tract-specific FA values of the right Cingulum Cingulate (rCC) were statistically different between the PD group and the HC group (p =0.047). The FA value of 34-58 equidistant nodes in rCC was positively correlated with Mini-Mental State Examination (MMSE) (r=0.527, p=0.024), Berg Balance Scale (BBS)-OFF (r=0.480, p =0.040), and BBS-ON (r=0.528, p =0.024) scores, while it was negatively correlated with the MDS-UPDRS-III-ON score (r=-0.502, p =0.030). Regarding the gait analysis, the FA value was significantly correlated with velocity, cadence, and stride time of the pace and rhythm domains in both 'ON' and 'OFF' states, respectively (p<0.05).</p><p><strong>Conclusion: </strong>This study served as an initial exploration to establish that HARDI sequences could be employed as a robust tool for analyzing microstructural alterations in white matter fiber bundles among PD patients, although the sample size was small. We confirmed microstructural integrity impairment of rCC to be significantly associated with both gait and cognitive deficits in patients with PD. Early detection of microstructural changes in rCC and targeted treatment can help improve behavioral disorders. In the future, we intend to further integrate multimodal data with assessments of patient behavior both prior to and following intervention. We will validate our findings within an independent cohort to monitor disease progression and evaluate the efficacy of therapeutic interventions.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine-Learning Based Computed Tomography Radiomics Nomgram For Predicting Perineural Invasion In Gastric Cancer.","authors":"Pei Huang, Sheng Li, Zhikang Deng, Fangfang Hu, Di Jin, Situ Xiong, Bing Fan","doi":"10.2174/0115734056323323250102073559","DOIUrl":"https://doi.org/10.2174/0115734056323323250102073559","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to develop and validate predictive models for perineural invasion (PNI) in gastric cancer (GC) using clinical factors and radiomics features derived from contrast-enhanced computed tomography (CE-CT) scans and to compare the performance of these models.</p><p><strong>Methods: </strong>This study included 205 GC patients, who were randomly divided into a training set (n=143) and a validation set (n=62) in a 7:3 ratio. Optimal radiomics features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. A radiomics model was constructed utilizing the optimal among five machine learning filters, and a radiomics score (rad-score) was computed for each participant. A clinical model was built based on clinical factors identified through multivariate logistic regression. Independent clinical factors were combined with the radscore to create a combined radiomics nomogram. The discrimination ability of the models was evaluated by receiver operating characteristic (ROC) curves and the DeLong test.</p><p><strong>Results: </strong>Independent predictive factors of the clinical model included tumor T stage, N stage, and tumor differentiation, with AUC values of 0.777 and 0.809 in the training and validation sets. The radiomics model was constructed using the support vector machine (SVM) classifier with the best AUC (0.875 in the training set and 0.826 in the validation set). The combined radiomics nomogram, which combines independent clinical predictors and the rad-score, demonstrated better predictive performance (AUC=0.889 in the training set; AUC=0.885 in the validation set).</p><p><strong>Conclusion: </strong>The nomogram integrating independent clinical predictors and CE-CT radiomics was constructed to predict PNI in GC. This model demonstrated favorable performance and could potentially assist in prognosis evaluation and clinical decision-making for GC patients.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pneumocephalus and Pneumorrhachis Following Titanium Rib Implant: A Case Report and Literature Review.","authors":"Yusuf Koksal, Sefer Burak Aydin","doi":"10.2174/0115734056375842250109093802","DOIUrl":"https://doi.org/10.2174/0115734056375842250109093802","url":null,"abstract":"<p><strong>Introduction: </strong>Pneumocephalus and pneumorrhachis are rare postoperative complications, commonly occurring within a few days to months after spinal surgery. They are very rarely reported after thoracic surgeries. This case highlights a unique presentation in the emergency department involving headache and vomiting caused by late complications following thoracic surgery with a titanium rib implant.</p><p><strong>Case presentation: </strong>A 64-year-old male presented to the emergency department with headache and vomiting without fever since prior 1 week. He had a history of left lower lobectomy and thoracic wall reconstruction with a titanium rib implant 40 days earlier due to epidermoid lung cancer. Computed tomography imaging of head and thorax revealed bilateral pneumocephalus and extensive pneumorrhachis. After removal of the rib implant and dural repair, the patient fully recovered.</p><p><strong>Conclusion: </strong>This case underscores the importance of early imaging and diagnosis in patients presenting with neurological symptoms following thoracic surgery and emphasizes the need for enhanced monitoring protocols for patients with titanium implants.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Pneumonia Detection in Chest X-Rays Using Hybrid Convolutional and Vision Transformer Networks.","authors":"Benzorgat Mustapha, Yatong Zhou, Chunyan Shan, Zhitao Xiao","doi":"10.2174/0115734056326685250101113959","DOIUrl":"https://doi.org/10.2174/0115734056326685250101113959","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The objective of this research is to enhance pneumonia detection in chest X-rays by leveraging a novel hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with modified Swin Transformer blocks. This study aims to significantly improve diagnostic accuracy, reduce misclassifications, and provide a robust, deployable solution for underdeveloped regions where access to conventional diagnostics and treatment is limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The study developed a hybrid model architecture integrating CNNs with modified Swin Transformer blocks to work seamlessly within the same model. The CNN layers perform initial feature extraction, capturing local patterns within the images. At the same time, the modified Swin Transformer blocks handle long-range dependencies and global context through window-based self-attention mechanisms. Preprocessing steps included resizing images to 224x224 pixels and applying Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance image features. Data augmentation techniques, such as horizontal flipping, rotation, and zooming, were utilized to prevent overfitting and ensure model robustness. Hyperparameter optimization was conducted using Optuna, employing Bayesian optimization (Tree-structured Parzen Estimator) to fine-tune key parameters of both the CNN and Swin Transformer components, ensuring optimal model performance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The proposed hybrid model was trained and validated on a dataset provided by the Guangzhou Women and Children's Medical Center. The model achieved an overall accuracy of 98.72% and a loss of 0.064 on an unseen dataset, significantly outperforming a baseline CNN model. Detailed performance metrics indicated a precision of 0.9738 for the normal class and 1.0000 for the pneumonia class, with an overall F1-score of 0.9872. The hybrid model consistently outperformed the CNN model across all performance metrics, demonstrating higher accuracy, precision, recall, and F1-score. Confusion matrices revealed high sensitivity and specificity with minimal misclassifications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The proposed hybrid CNN-ViT model, which integrates modified Swin Transformer blocks within the CNN architecture, provides a significant advancement in pneumonia detection by effectively capturing both local and global features within chest X-ray images. The modifications to the Swin Transformer blocks enable them to work seamlessly with the CNN layers, enhancing the model's ability to understand complex visual patterns and dependencies. This results in superior classification performance. The lightweight design of the model eliminates the need for extensive hardware, facilitating easy deployment in resource-constrained settings. This innovative approach not only improves pneumonia diagnosis but also has the potential to enhance patient outcomes and support healthcare providers in underdeveloped regions. Fu","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Cardiac Remodeling and/or Myocardial Fibrosis Based on Hemodynamic Parameters of Vena Cava in Athletes.","authors":"Bin-Yao Liu, Fan Zhang, Min-Song Tang, Xing-Yuan Kou, Qian Liu, Xin-Rong Fan, Rui Li, Jing Chen","doi":"10.2174/0115734056316396241227064057","DOIUrl":"https://doi.org/10.2174/0115734056316396241227064057","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to assess the hemodynamic changes in the vena cava and predict the likelihood of Cardiac Remodeling (CR) and Myocardial Fibrosis (MF) in athletes utilizing four-dimensional (4D) parameters.</p><p><strong>Materials and methods: </strong>A total of 108 athletes and 29 healthy sedentary controls were prospectively recruited and underwent Cardiac Magnetic Resonance (CMR) scanning. The 4D flow parameters, including both general and advanced parameters of four planes for the Superior Vena Cava (SVC) and Inferior Vena Cava (IVC) (sheets 1-4), were measured and compared between the different groups. Four machine learning models were employed to predict the occurrence of CR and/or MF.</p><p><strong>Results: </strong>Most general 4D flow parameters related to VC were increased in athletes and positive athletes compared to controls (p < 0.05). Gradient Boosting Machine (GBM) was the most effective model in sheet 2 of SVC, with the area under the curve values of 0.891, accuracy of 85.2%, sensitivity of 84.6%, and specificity of 85.4%. The top five predictors in descending order were as follows: net positive volume, forward volume, waist circumference, body weight, and body surface area.</p><p><strong>Conclusion: </strong>Physical activity can induce a high flow state in the vena cava. CR and/or MF may elevate the peak velocity and maximum pressure gradient of the IVC. This study successfully constructed a GBM model with high efficacy for predicting CR and/or MF. This model may provide guidance on the frequency of follow-up and the development of appropriate exercise plans for athletes.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Value of Using Quantitative MRI based on Synthetic Acquisition and Apparent Diffusion Coefficient to Monitor Multiple Sclerosis Lesion Activity.","authors":"Abdullah H Abujamea, Fahad B Albadr, Arwa M Asiri","doi":"10.2174/0115734056343086250103020830","DOIUrl":"https://doi.org/10.2174/0115734056343086250103020830","url":null,"abstract":"<p><strong>Background: </strong>Multiple sclerosis (MS) is one of the most common disabling central nervous system diseases affecting young adults. Magnetic resonance imaging (MRI) is an essential tool for diagnosing and following up multiple sclerosis. Over the years, many MRI techniques have been developed to improve the sensitivity of MS disease detection. In recent years synthetic MRI (sMRI) and quantitative MRI (qMRI) have gained traction in neuroimaging applications, providing more detailed information than traditional acquisition methods. These techniques enable the detection of microstructural changes in the brain with high sensitivity and robustness to inter-scanner and inter-observer variability. This study aims to evaluate the feasibility of using these techniques to avoid administering intravenous gadolinium-based contrast agents (GBCAs) for assessing MS disease activity and monitoring.</p><p><strong>Materials and methods: </strong>Forty-two known MS patients, aged 20 to 45, were scanned as part of their routine follow-up. MAGnetic resonance image Compilation (MAGiC) sequence, an implementation of synthetic MRI, was added to our institute's routine MS protocol to automatically generate quantitative maps of T1, T2, and PD. T1, T2, PD, and apparent diffusion coefficient (ADC) data were collected from regions of interest (ROIs) representing normalappearing white matter (NAWM), enhancing, and non-enhancing MS lesions. The extracted information was compared, and statistically analyzed, and the sensitivity and specificity were calculated.</p><p><strong>Results: </strong>The mean R1 (the reciprocal of T1) value of the non-enhancing MS lesions was 0.694 s-1 (T1=1440 ms), for enhancing lesions 1.015 s-1 (T1=985ms), and for NAWM 1.514 s-1 (T1=660ms). For R2 (the reciprocal of T2) values, the mean value was 6.816 s-1 (T2=146ms) for nonenhancing lesions, 8.944 s-1 (T2=112 ms) for enhancing lesions, and 1.916 s-1 (T2=522 ms) for NAWM. PD values averaged 93.069% for nonenhancing lesions, 82.260% for enhancing lesions, and 67.191% for NAWM. For ADC, the mean value for non-enhancing lesions was 1216.60×10-6 mm2/s, for enhancing lesions 1016.66×10-6 mm2/s, and for NAWM 770.51×10-6 mm2/s.</p><p><strong>Discussion: </strong>Our results indicate that enhancing and non-enhancing MS lesions significantly decrease R1 and R2 values. Non-enhancing lesions have significantly lower R1 and R2 values compared to enhancing lesions.</p><p><strong>Conclusion: </strong>Conversely, PD values are significantly higher in non-enhancing lesions than in enhancing lesions. For ADC, while NAWM has lower values, there was minimal difference between the mean ADC values of enhancing and non-enhancing lesions.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HIV Infection Complicated with Cytomegalovirus Colitis: A Case Report of 18FFDG PET/CT Imaging.","authors":"Shengwei Fang, Peipei Zhang","doi":"10.2174/0115734056361753241226065721","DOIUrl":"https://doi.org/10.2174/0115734056361753241226065721","url":null,"abstract":"<p><strong>Background: </strong>Cytomegalovirus (CMV) infection is common in the digestive and central nervous systems and can infect the entire digestive tract from the mouth to the rectum. In immunocompromised patients, CMV infection is prone to develop into CMV disease, especially in Acquired Immune Deficiency Syndrome (AIDS) patients. Severe cases may accelerate the progression of AIDS patients and form systemic CMV infection. Timely diagnosis and treatment are very important for the prognosis of patients.</p><p><strong>Case presentation: </strong>In this paper, we report a 36-year-old man with a Human Immunodeficiency Virus (HIV) infection complicated with CMV colitis. Three weeks ago, he developed abdominal pain with fresh blood in the stool, accompanied by anal pain. He was found to be HIV positive 8 years ago. An enhanced CT scan showed edema and irregular thickening of the rectal wall, obvious enhancement of the mucosa, and multiple enlarged lymph nodes around. 18F-FDG PET/CT imaging displayed diffuse rectum wall thickening and increased glucose metabolism, and the SUV max was 12.7. There were multiple enlarged lymph nodes around the rectum, glucose metabolism was increased, and the SUVmax was 4.6.</p><p><strong>Conclusion: </strong>18F-FDG-PET imaging technology has potential value in the diagnosis of CMV colitis, especially in immunocompromised patients. Detection of FDG concentrations in the colon wall can help diagnose CMV infection and understand the extent of the lesion, which is essential for the timely initiation of antiviral therapy.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142958910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}