Current Medical Imaging Reviews最新文献

{"title":"Magnetic Resonance Imaging Study on Older Patients with Cognitive Impairment and Depression.","authors":"Shuang Zhang, Yuping Qin, Meng Ding, Jining Yang, Tao Zhang","doi":"10.2174/0115734056281104241220113235","DOIUrl":"https://doi.org/10.2174/0115734056281104241220113235","url":null,"abstract":"<p><strong>Background: </strong>Understanding brain changes in older patients with depression and their relationship with cognitive abilities may aid in the diagnosis of depression in this population. This study aimed to explore the association between brain lesions and cognitive performance in older patients with depression.</p><p><strong>Methods: </strong>We utilized magnetic resonance imaging data from a previous study, which included older adults with and without depression. Smoothed Regional Homogeneity (ReHo) and local brain Amplitude of Low-frequency Fluctuation (ALFF) values were assessed to examine brain activity.</p><p><strong>Results: </strong>The analysis revealed decreased ReHo in the left middle temporal gyrus, left middle frontal gyrus, and left precuneus, as well as increased local ALFF in the right middle occipital gyrus, left postcentral gyrus, and right precentral gyrus in older patients with depression. These alterations may contribute to behavioral and cognitive changes. However, no significant relationship was found between ReHo values and Montreal Cognitive Assessment (MoCA) scores. In contrast, increased local ALFF in the left postcentral gyrus and right precentral gyrus was negatively correlated with MoCA scores.</p><p><strong>Conclusion: </strong>This study demonstrated a significant association between regional brain alterations in patients with depression and cognitive behavior. Thus, this work identified functional brain regions and cognitive performance in older adults with depression, highlighting specific brain regions that play a crucial role in cognitive abilities in this population.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933654","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":"Perforated Meckel's Diverticulum in an Adult that Resembles Acute Appendicitis: A Case Report and Review of the Literature.","authors":"Noha Bakhsh, Mai Banjar","doi":"10.2174/0115734056320557241211115403","DOIUrl":"https://doi.org/10.2174/0115734056320557241211115403","url":null,"abstract":"<p><strong>Background: </strong>Perforation is one of the rarest effects of Meckel's diverticulum and may clinically resemble acute appendicitis.</p><p><strong>Case report: </strong>A 34-year-old woman with pain in the right iliac fossa, nausea, and vomiting for three days was brought to the emergency department. An abdominal examination indicated rebound tenderness in the area of the right iliac fossa. Abdominal ultrasound showed a heterogeneous lesion in the left iliac fossa measuring 5 cm × 3.5 cm × 4 cm with no internal vascularity. Abdominal Computed Tomography (CT) demonstrated a hypodense lesion located left of the midline of the abdomen, which was inseparable from the small bowel at the antimesenteric border. Laparoscopic exploration was performed, and an intraoperative diagnosis of perforated Meckel's diverticulum with phlegmon formation was made. The patient had an uneventful recovery.</p><p><strong>Conclusion: </strong>Radiologists should be aware of the possibility of complicated Merkel's diverticulum when encountering cases of acute abdominal pain. If there is a lower abdominal inflammatory process and a normal appendix is identified, there should be a high degree of suspicion when examining the CT scan.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933655","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":"Challenges in Diagnosing Primary Intracranial Ewing Sarcoma/Peripheral Primitive Neuroectodermal Tumor: A Case Report.","authors":"Shigang Luo, Feifei Wang, Huan Haung, GuangCai Tang","doi":"10.2174/0115734056334823241216180031","DOIUrl":"https://doi.org/10.2174/0115734056334823241216180031","url":null,"abstract":"<p><strong>Background: </strong>Primary intracranial Ewing Sarcoma/peripheral Primitive Neuroectodermal Tumor (EWS/pPNET) is exceedingly rare and easy to misdiagnose.</p><p><strong>Case presentation: </strong>We present a case involving a 23-year-old male who presented with headaches and vomiting. The preoperative brain imaging revealed an irregular mass in the left parietal lobe, initially misdiagnosed as meningioma. However, the surgical specimen was ultimately diagnosed as primary intracranial EWS/pPNET. The patient underwent a total tumor resection, followed by adjuvant chemotherapy and radiotherapy. No recurrence or distant metastasis was observed 18 months after the surgery.</p><p><strong>Conclusion: </strong>When the imaging features of young patients' lesions are solid, aggressive, and unevenly enhanced masses, physicians should be aware of the possibility of primary intracranial EWS/pPNET, and if possible, Gross Total Resection (GTR) and intensive chemotherapy and radiotherapy are recommended.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933566","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":"Exploring the Prevalence and Coexistence of Metabolic Dysfunction-associated Steatotic Liver Disease in Type 2 Diabetes Mellitus Patients Using Ultrasound: A Cross-sectional Study.","authors":"Ibrahim Hadadi, Mohamed Adam, Mustafa J Musa, Awadia Gareeballah, Mansour Alqahtani, Ibrahem Kanbayti, Ahmed Hazazi","doi":"10.2174/0115734056354807241217043210","DOIUrl":"https://doi.org/10.2174/0115734056354807241217043210","url":null,"abstract":"<p><strong>Background: </strong>Type 2 diabetes Mellitus (T2DM) increases vulnerability to metabolic dysfunction-associated steatotic liver disease (MASLD). Therefore, this study aims to determine the prevalence and coexistence of MASLD in patients with T2DM using ultrasound.</p><p><strong>Methods: </strong>This cross-sectional retrospective study included 168 patients with T2DM from multiple diabetes clinics in Abha City, Asir region, recruited between August 2023 and December 2023. Adult patients aged 18 and over with T2DM were included, and data was extracted from patient files. All patients were examined by ultrasound to determine the prevalence and coexistence of MASLD in patients with T2DM. Hepatic steatosis on Bmode ultrasound is qualitatively classified on a four-point scale: normal (0), mild (1), moderate (2), and severe (3).</p><p><strong>Results: </strong>Out of 168 patients, 68.4% were identified with MASLD, mostly with diffuse liver (97.4%) diagnosed through ultrasound. MASLD was significantly higher in individuals with uncontrolled diabetes (72.5%) than those with controlled diabetes (46.2%), with a significant difference (p=0.015) and an odds ratio (OR) of 3.081, indicating uncontrolled diabetics are over three times more likely to develop MASLD. The uncontrolled group had a statistically significant larger liver size than the control group (13.6cm ±1.43 vs. 13.0cm ±1.20, respectively: [p=0.032, 95%CI 0.053-1.12]). Furthermore, a notable association was observed between increased BMI and the prevalence of MASLD in individuals with T2DM. Furthermore, no significant association was found between the duration of diabetes and the severity of MASLD, nor between the grading of MASLD and gender.</p><p><strong>Conclusion: </strong>This study highlights a crucial association between uncontrolled diabetes and increased MASLD prevalence, emphasizing the importance of diabetes management in reducing MASLD risk.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933642","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":"Imaging Characteristics of Primary Mucinous Cystadenocarcinoma of the Breast: A Case Report and Literature Review.","authors":"Yizhong Bian, Lei Xu, Yibo Zhou, Jizhen Li","doi":"10.2174/0115734056345716241213075234","DOIUrl":"https://doi.org/10.2174/0115734056345716241213075234","url":null,"abstract":"<p><strong>Introduction: </strong>Mucinous Cystadenocarcinoma (MCA) of the breast remains a relatively rare condition, and to date, there is no systematic summary of its imaging manifestations. Therefore, this report presents a detailed account of the diagnosis and treatment of mucinous cystadenocarcinoma in a 40-year-old woman, with a particular focus on imaging findings. Additionally, we conducted a comprehensive literature review on this disease and summarized its key imaging features. This manuscript provides valuable insights and methodologies for the accurate diagnosis of mucinous cystadenocarcinoma.</p><p><strong>Case presentation: </strong>We report a 40-year-old premenopausal woman who discovered multiple cysts in her left breast five years ago. Over the past two years, the size of these tumors has increased. Ultrasound examination indicated that the cysts had grown to 27 x 17mm. Following a puncture, the cysts were confirmed to be benign and were not monitored regularly. A year later, the patient's mass in the left breast increased, and an ultrasound exam indicated a suspicious mixed echo area in the upper outer quadrant, suggestive of a malignant lesion. Mammography showed amorphous suspicious calcifications in the lesion area, distributed in segments. Contrast-enhanced magnetic resonance imaging displayed non-mass-type enhancement of the lesion, with a dynamic enhanced imaging time-signal intensity curve (TIC) showing a rapidly rising plateau pattern. Postoperative pathology confirmed invasive carcinoma of the left breast along with mucinous cystadenocarcinoma. Four months after surgery, the patient developed multiple abnormal lymph nodes in the left axilla, which were confirmed to be metastasis upon pathology examination. Following radiotherapy, the patient's condition remained stable during the follow-up period.</p><p><strong>Conclusion: </strong>Most MCA lesions typically exhibit clear borders and irregular edges, with some displaying expansive growth and compression of surrounding tissues. Mammography can reveal calcified components in lesions. Ultrasound often reveals an isoechoic or hypoechoic mass with well-defined borders but irregular edges. Magnetic resonance imaging (MRI) can show clear boundaries and uneven enhancement of the lesions, and the timeintensity curve (TIC) of the mass area often shows an inflow enhancement pattern.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933648","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":"Advanced CNN Architecture for Brain Tumor Segmentation and Classification using BraTS-GOAT 2024 Dataset.","authors":"Vaidehi Satushe, Vibha Vyas, Shilpa Metkar, Davinder Paul Singh","doi":"10.2174/0115734056344235241217155930","DOIUrl":"https://doi.org/10.2174/0115734056344235241217155930","url":null,"abstract":"<p><strong>Background: </strong>The BraTS Generalizability Across Tumors (BraTS-GoAT) initiative addresses the critical need for robust and generalizable models in brain tumor segmentation. Despite advancements in automated segmentation techniques, the variability in tumor characteristics and imaging modalities across clinical settings presents a significant challenge.</p><p><strong>Objective: </strong>This study aims to develop an advanced CNN-based model for brain tumor segmentation that enhances consistency and utility across diverse clinical environments. The objective is to improve the generalizability of CNN models by applying them to large-scale datasets and integrating robust preprocessing techniques.</p><p><strong>Methods: </strong>The proposed approach involves the application of advanced CNN models to the BraTS 2024 challenge dataset, incorporating preprocessing techniques such as standardization, feature extraction, and segmentation. The model's performance was evaluated based on accuracy, mean Intersection over Union (IOU), average Dice coefficient, Hausdorff 95 score, precision, sensitivity, and specificity.</p><p><strong>Results: </strong>The model achieved an accuracy of 98.47%, a mean IOU of 0.8185, an average Dice coefficient of 0.7, an average Hausdorff 95 score of 1.66, a precision of 98.55%, a sensitivity of 98.40%, and a specificity of 99.52%. These results demonstrate a significant improvement over the current gold standard in brain tumor segmentation.</p><p><strong>Conclusion: </strong>The findings of this study contribute to establishing benchmarks for generalizability in medical imaging, promoting the adoption of CNN-based brain tumor segmentation models in diverse clinical environments. This work has the potential to improve outcomes for patients with brain tumors by enhancing the reliability and effectiveness of automated segmentation techniques.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933559","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 Detection of Colon Diseases via a Fused Deep Learning Model with an Auxiliary Fusion Layer and Residual Blocks on Endoscopic Images.","authors":"Rakesh Kumar, Vatsala Anand, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman","doi":"10.2174/0115734056353246241209060804","DOIUrl":"https://doi.org/10.2174/0115734056353246241209060804","url":null,"abstract":"<p><strong>Background: </strong>Colon diseases are major global health issues that often require early detection and correct diagnosis to be effectively treated. Deep learning approaches and recent developments in medical imaging have demonstrated promise in increasing diagnostic accuracy.</p><p><strong>Objective: </strong>This work suggests that a Convolutional Neural Network (CNN) model paired with other models can detect different gastrointestinal (GI) abnormalities or diseases from endoscopic images via the fusion of residual blocks, including alpha dropouts (αDO) and auxiliary fusing layers.</p><p><strong>Methods: </strong>To automatically diagnose colon disorders from medical images, this work explores the use of a fused deeplearning model that incorporates the EfficientNetB0, MobileNetV2, and ResNet50V2 architectures. By integrating these features, the fused model aims to improve the classification accuracy and robustness for various colon diseases. The proposed model incorporates an auxiliary fusion layer and a fusion residual block. By combining diverse features through an auxiliary fusion layer, the network can create more comprehensive and richer representations, capturing intricate patterns that might be missed by single-source processing. The fusion residual block incorporates residual connections, which help mitigate the vanishing gradient problem. By adding the input of the block directly to its output, these connections facilitate better gradient flow during backpropagation, allowing for deeper and more stable training. A wide range of endoscopic images are used to assess the proposed model, offering an accurate depiction of various disease scenarios. Results The proposed model, with an auxiliary fusion layer and residual blocks, exhibited an enormous reduction in overfitting and performance saturation. The proposed model achieved an impressive 98.03% training accuracy and 97.90% validation accuracy after evaluation, outperforming the majority of typically trained DCNNs in terms of efficiency and accuracy.</p><p><strong>Conclusion: </strong>The proposed method developed a lightweight model that correctly identifies disorders of the gastrointestinal (GI) tract by combining advanced techniques, including feature fusion, residual learning, and self-normalization.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933635","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":"FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.","authors":"Shagun Sharma, Kalpna Guleria, Ayush Dogra","doi":"10.2174/0115734056333970241212132150","DOIUrl":"https://doi.org/10.2174/0115734056333970241212132150","url":null,"abstract":"<p><strong>Background: </strong>Pneumonia is an acute respiratory infection that has emerged as the predominant catalyst for escalating mortality rates worldwide. In the pursuit of the prevention and prediction of pneumonia, this work employs the development of an advanced deep-learning model by using a federated learning framework. The deep learning models rely on the utilization of a centralized system for disease prediction on the medical imaging data and pose risks of data breaches and exploitation; however, federated learning is a decentralized architecture which significantly reduces data privacy concerns.</p><p><strong>Methods: </strong>The federated learning works in a distributed architecture by sending a global model to clients rather than sending the data to the model. The proposed federated deep learning-based FedPneu computer-aided diagnosis model has been implemented in 2, 3, 4, and 5 clients architecture for early pneumonia detection using X-ray images. The key parameters configuration include batch size, learning rate, optimizer, decay, momentum, epochs, rounds, and random-split as 32, 0.0001, SGD, 0.000001, 0.9, 10, 100, and 42, respectively.</p><p><strong>Results: </strong>The results of the proposed federated deep learning-based FedPneu model have been provided in terms of round-wise accuracy, loss, and computational time. The highest accuracy of 85.632% has been achieved with 2-clients federated deep learning architecture, whereas, 3, 4, and 5 clients architecture achieved 85.536%, 76.112%, and 74.123% accuracies, respectively.</p><p><strong>Conclusion: </strong>In the proposed privacy-protected federated deep learning-based FedPneu model, the two-client architecture has been resulted as the most optimal framework for pneumonia detection among 3-clients, 4-clients, and 5-clients architecture. The model works in a collaborative and privacyprotected framework with a multi-silo dataset which could be highly beneficial for healthcare departments to maintain patient's data privacy with improved prediction outcomes.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933646","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":"Displaced Femoral Neck Fractures Treated with Percutaneous Compression Plates in Elderly Individuals: An Effect Analysis Based on Imaging.","authors":"Huli Liu, Kai Zhao, Ying Yang, Liansheng Dai, Sanjun Gu, Haifeng Li, Yu Liu","doi":"10.2174/0115734056349481241218062504","DOIUrl":"https://doi.org/10.2174/0115734056349481241218062504","url":null,"abstract":"<p><strong>Background: </strong>The effects of percutaneous compression plate (PCP) internal fixation for femoral neck fractures (FNFs) in elderly individuals have rarely been reported. Therefore, this study aimed to investigate the efficacy of PCCP internal fixation for displaced FNFs in elderly individuals based on imaging.</p><p><strong>Methods: </strong>The clinical data of 32 elderly patients with FNFs treated with PCCP from January 2015 to December 2022 were retrospectively analyzed. The average age of the participants was 68.7 ± 4.8 years (range, 65-80 years). Nineteen patients had Garden type III, and 13 patients had Garden type IV. Six patients had Pauwels type I, 15 patients had type II, and 11 patients had type III. Twelve patients had Singh index level IV, 14 patients had level V, and 6 patients had level VI. The time from injury to operation ranged from 3-14 days, with an average of 5.8 days. A radiological assessment was conducted. The relationships between efficacy and age, Pauwels classification, the Singh index, and the Garden alignment index were analyzed.</p><p><strong>Results: </strong>At postoperative week 1, fracture reduction was acceptable in 31 patients. The time to start walking was 5.7 ± 3.7 days. The follow-up time ranged from 2.1 to 4 years, with an average of 2.7 years. There were 2 cases of delayed healing and no cases of nonunion or internal fixation failure. The healing time ranged from 4-8 months, with an average of 4.9 months. Fifteen patients (46.9%) showed healing with shortening of the femoral neck, and 3 patients (9.4%) had avascular necrosis (AVN). Correlation analysis revealed that healing with shortening of the femoral neck was positively correlated with age and the Singh index and that AVN was positively correlated with the Pauwels classification (p < 0.05).</p><p><strong>Conclusion: </strong>The efficacy of PCCPs for internal fixation of displaced FNFs in elderly individuals without severe osteoporosis is satisfactory, especially for patients who can ambulate early postoperatively. The main complications are healing with shortening of the femoral neck and AVN, which are prone to occur in patients with severe osteoporosis and Pauwels type III FNFs, respectively.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933634","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":"Sound Touch Viscosity (STVi) for Thyroid Gland Evaluation in Healthy Individuals: A Pilot Study : STVi for Thyroid Gland Evaluation.","authors":"Feng Mao, Yuemingming Jiang, Yunzhong Wang, Zhenbin Xu, Zhuo Wei, Xueli Zhu, Libin Chen, Shengmin Zhang","doi":"10.2174/0115734056335791241202115022","DOIUrl":"10.2174/0115734056335791241202115022","url":null,"abstract":"<p><strong>Objective: </strong>This prospective study aimed to establish the typical viscosity range of the thyroid gland in healthy individuals using a new method called the Sound Touch Viscosity (STVi) technique with a linear array transducer.</p><p><strong>Methods: </strong>Seventy-eight healthy volunteers were enrolled between March, 2023 and April, 2023. Thyroid viscosity was measured using the Resona R9 ultrasound system equipped with a linear array transducer (L15-3WU). Each patient had three valid viscosity measurements taken for each thyroid lobe, and the average values were analyzed. Thyroid gland stiffness was measured and analyzed simultaneously.</p><p><strong>Results: </strong>The study included 51 women and 27 men with an average age of 48 years. The mean viscosity measurement for a normal thyroid gland was 1.10 ± 0.41 Pa.s (ranging from 0.38 to 2.25 Pa.s). There were no significant differences in viscosity between the left and right lobes of the thyroid gland. We found no significant variations in viscosity based on gender, age, or body mass index (BMI). There was a notable positive correlation between thyroid viscosity and stiffness measurements (r = 0.717, p < 0.001).</p><p><strong>Conclusion: </strong>Our findings suggest that STVi is a highly reliable method for assessing the thyroid. This technique holds promise as a new, non-invasive approach to evaluating thyroid parenchyma viscosity.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142933596","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}