Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Reassessing the role of cervical magnetic resonance imaging in diagnosing demyelinating disorders: a case misclassified as medullary infarction.","authors":"Bing Liu, Chao Nie, Shi-Ming Zhao, Guang-Cheng Ji","doi":"10.21037/qims-2024-2896","DOIUrl":"10.21037/qims-2024-2896","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5910-5915"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sparse-view spectral CT reconstruction via a coupled subspace representation and score-based generative model.","authors":"Jie Guo, Yizhong Wang, Shaoyu Wang, Zhizhong Zheng, Lei Li, Ailong Cai, Bin Yan","doi":"10.21037/qims-24-2226","DOIUrl":"10.21037/qims-24-2226","url":null,"abstract":"<p><strong>Background: </strong>Spectral computed tomography (CT) demonstrates significant potential for clinical application by providing rich structural and compositional information about scanned objects. However, sparse-view scanning introduces streak artifacts during image reconstruction, severely degrading image quality. Conventional regularization-based methods exhibit inherent limitations in preserving fine details and edge structures. To address this challenge, this study aimed to enhance reconstruction quality by developing a novel framework that synergistically integrates subspace decomposition with deep generative priors, effectively leveraging both low-rank properties and data-driven representations inherent to spectral CT images.</p><p><strong>Methods: </strong>To address these challenges, we proposed an unsupervised reconstruction framework for sparse-view imaging that synergistically integrates subspace representation with a score-based generative model (SGM), which exploits intrinsic information in the measurement signals. This framework leverages the low-rank prior of the subspace representation to guide the SGM in generating images that highly coincide with the ground truth. Specifically, high-dimensional spectral CT images are first decomposed into orthogonal subspace basis components and corresponding eigen-images, effectively reducing dimensionality while preserving spectral correlations. Subsequently, we employed a data-driven SGM to learn the statistical distribution of the image. This deep prior knowledge effectively supplements the limitations of low-rank regularization in capturing complex probability distribution of image. Afterward, we integrated an efficient alternating optimization algorithm that alternately updates subspace coefficients, enforcing consistency between physical measurements and learned priors. This integration results in a synergetic effect between model-driven low-rank priors and the data-driven distribution learning, significantly enhancing the accuracy of image and the model's generalization across diverse datasets.</p><p><strong>Results: </strong>In the simulation experiment, compared with the optimal comparison algorithm (Wavelet-SGM), the proposed algorithm has increased the peak signal-to-noise ratio (PSNR) by at least 3dB, and the structural similarity index measure (SSIM) by 2.54%. In the real data experiment, the results of this paper were the closest to the ground truth, with minimum error. Both qualitative and quantitative analysis demonstrated the promising and competitive performance of the proposed method in preserving details and reducing streaking artifacts.</p><p><strong>Conclusions: </strong>Our framework established a new paradigm for spectral CT reconstruction through the synthesis of the model-driven low-rank prior with a data-driven deep prior, which yielded mutual enhancement and complementarity, collectively improving the overall quality of the reconstructed images. This dual","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5474-5495"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209656/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tumor-induced osteomalacia secondary to phosphaturic mesenchymal tumor: a case description and literature analysis.","authors":"Weicheng Wang, Weina Hou, Xianghua Cong, Mingyuan Pang, Yujing Chu, Qi Wang, Huimin Sun, Li Zhang","doi":"10.21037/qims-24-2278","DOIUrl":"10.21037/qims-24-2278","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5900-5909"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Endovascular coiling versus microsurgical clipping for extremely small intracranial aneurysms: a comparative analysis of treatment strategies, complications, and clinical outcomes.","authors":"Qingqing Xu, Qi Tian, Wenrui Han, Chengli Liu, Jianming Liao, Mingchang Li","doi":"10.21037/qims-2024-2848","DOIUrl":"10.21037/qims-2024-2848","url":null,"abstract":"<p><strong>Background: </strong>Generally, extremely small intracranial aneurysms (ESIAs) are defined as having a maximum diameter of less than 2 mm. Despite technological improvement, treating ESIAs remains challenging for neurosurgery specialists. ESIA treatment has long been controversial owing to the high risk of complications associated with both endovascular coiling (EC) and microsurgical clipping (MC). This retrospective cohort study assessed postoperative complications, angiographic outcomes, and long-term clinical efficacy in ESIAs patients receiving EC or MC interventions. The objective was to evaluate the effectiveness of different surgical interventions for patients diagnosed with ESIAs.</p><p><strong>Methods: </strong>Patients who underwent EC or MC between February 2013 and December 2023 were retrospectively analyzed. A total of 153 patients were included in this study, encompassing both ruptured and unruptured cases of ESIAs. Notably, unruptured cases were associated with larger ipsilateral aneurysms, which were either ruptured or at a significant risk of rupture. Imaging follow-up evaluations were conducted using computed tomography angiography (CTA) or digital subtraction angiography (DSA), whereas patient recovery outcomes were assessed using the Glasgow Outcome Scale (GOS). The primary outcome measure was the GOS score recorded 6 months post-treatment. Secondary outcomes included the GOS score at discharge, the embolization rate 6 months after treatment, and postoperative complications such as cerebral infarction, hydrocephalus, and postoperative rebleeding.</p><p><strong>Results: </strong>This study included 153 patients, 84 of whom were treated with EC and 69 with MC. In the EC group, 28 cases of unruptured aneurysms were identified, whereas the MC group had 20 cases of unruptured aneurysms. EC treatment demonstrated slight benefits in clinical outcomes at discharge, with statistically significant differences 6 months after treatment. The EC group had a shorter hospital stay compared with the MC group (14.40±6.57 <i>vs.</i> 20.17±7.38 days, P<0.0001), but there was no significant difference in special complications (16.67% <i>vs.</i> 27.54%, P=0.1038). Postoperative angiography revealed a lower occlusion rate in the EC group at discharge (84.52% <i>vs.</i> 100%) and 6 months after treatment (88.10% <i>vs.</i> 89.86%). Subgroup analysis for a favorable outcome revealed a sex-related difference between the EC and MC groups at follow-up. Specifically, female patients treated with EC demonstrated a better long-term prognosis compared with those treated with MC.</p><p><strong>Conclusions: </strong>Both EC and MC treatments are suitable for patients with ESIAs. However, the EC group exhibited fewer hospitalization days than the MC group, whereas the latter demonstrated a higher occlusion rate. Female patients may have better long-term outcomes with EC treatment. Further confirmation through large-sample, multi-center trials is need","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5604-5620"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Huge trichobezoar resulting in gastrointestinal obstruction: a case description of Rapunzel syndrome.","authors":"Na Duan, Tao Zhou, Zhongqiu Wang","doi":"10.21037/qims-2024-2702","DOIUrl":"10.21037/qims-2024-2702","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5916-5920"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic abnormalities in the insula of patients with interictal migraine without aura: a prospective cross-sectional study.","authors":"Liping Wang, Huaxia Pu, Jingyuan Zhou, Xintong Wu, Wenyu Liu, Shujiang Zhang, Dong Zhou, Qiang Yue, Qiyong Gong","doi":"10.21037/qims-2024-2553","DOIUrl":"10.21037/qims-2024-2553","url":null,"abstract":"<p><strong>Background: </strong>The insula plays a crucial role in the pathophysiology of patients with migraine without aura (MWoA), but the exact neurometabolic mechanisms are still unclear. This study aimed to explore possible neurometabolic mechanisms in the insula during the interictal period in MWoA patients, and neurometabolic differences between high frequency (HF) and law frequency (LF) headache patients via proton magnetic resonance spectroscopy (¹H-MRS).</p><p><strong>Methods: </strong>A total of 22 MWoA patients and 22 age-, gender-, and education-matched healthy controls (HCs) were included in this prospective cross-sectional study. The subjects underwent routine T1-weighted imaging (T1WI) and single-voxel ¹H-MRS scans, with the region of interest fixed in the left insula. Metabolites, including myo-inositol (Ins), N-acetyl aspartate (NAA), choline-containing compound (Cho), creatine and phosphocreatine (Cr), glutamate and glutamine (Glx), were quantified via the linear combination model (LCModel) software, and then corrected for the partial volume effect of cerebrospinal fluid (CSF). The MWoA patients were categorized into LF and HF headache groups according to their headache frequency. Metabolic differences between the groups were tested by an analysis of covariance (ANCOVA), and the clinical relevance of these metabolites was analyzed by Pearson or Spearman correlation analyses.</p><p><strong>Results: </strong>During the interictal period of headache, the Ins (MWoA <i>vs</i>. HCs: 5.16±1.14 <i>vs</i>. 6.21±1.14, P=0.017), NAA (MWoA <i>vs</i>. HCs: 5.70±1.23 <i>vs</i>. 6.59±1.12, P=0.015), and Glx (MWoA <i>vs</i>. HCs: 12.88±1.63 <i>vs</i>. 14.36±2.17, P=0.020) concentrations were significantly decreased in the insula of the MWoA patients compared to the HCs. Further, the HF headache patients had obviously higher Cr levels than the LF headache patients (HF <i>vs</i>. LF: 6.16±0.67 <i>vs</i>. 6.01±0.91, P=0.037). The headache frequency of the MWoA patients was positively correlated with the headache-attributed lost time-90 days (HALT-90) scale (r=0.560, P=0.010) and Hamilton Depression Rating Scale (HAMD) (r=0.529, P=0.017) scores. In addition, a higher HALT-90 score was associated with a higher Cho level in the MWoA patients (r=0.654, P=0.002).</p><p><strong>Conclusions: </strong>The dysfunction or loss of neurons and glial cells, and excitatory neurotransmitter conversion imbalance may be the key changes in the insula of interictal MWoA patients. HF headaches are characterized by hypometabolism, which may be caused by more serious mitochondrial dysfunction.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5436-5449"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic diagnosis of autism spectrum disorders in children through resting-state functional magnetic resonance imaging with machine vision.","authors":"Zahra Khandan Khadem-Reza, Reza Ahmadi Lashaki, Mohammad Amin Shahram, Hoda Zare","doi":"10.21037/qims-24-1402","DOIUrl":"10.21037/qims-24-1402","url":null,"abstract":"<p><strong>Background: </strong>Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by impairments in social interactions, communication, repetitive behaviors, and restricted interests. Magnetic resonance imaging (MRI) has been increasingly used to identify common patterns in individuals with autism for classification purposes. This study aims to develop an intelligent system for diagnosing ASD in children using resting-state functional magnetic resonance imaging (fMRI) and machine learning algorithms.</p><p><strong>Methods: </strong>This study proposes a method for classifying children with ASD versus healthy control (HC) using resting-state fMRI. This study used images from 26 autistic children and 26 controls, aged 5 to 10 years. Image features were extracted from both groups, and the children with ASD were classified from the HCs using support vector machine (SVM), random forest (RF), K-nearest neighbor (KNN), and artificial neural network (ANN) algorithms.</p><p><strong>Results: </strong>Our experimental results reveal that the proposed method accurately detects ASD using the ABIDE dataset and achieves accuracy of 88.46%, 73.07%, 82.69%, and 90.38% with SVM, RF, KNN and ANN algorithms, respectively.</p><p><strong>Conclusions: </strong>Diagnosing autism through clinical evaluations is time-consuming and relies on expert expertise, highlighting the importance of intelligent diagnosis for this disorder. In this study, we developed an intelligent system that demonstrated high accuracy in ASD diagnosis using resting-state fMRI and machine learning techniques.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"4935-4946"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209650/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain synthetic magnetic resonance imaging and quantitative susceptibility mapping in patients with hepatitis B virus-related decompensated cirrhosis.","authors":"Hong Jin, Dongcui Wang, Ziyun Wang, Xun Ning, Wu Xing","doi":"10.21037/qims-2024-2969","DOIUrl":"10.21037/qims-2024-2969","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The traditional diagnostic methods for early hepatic encephalopathy (HE) detection involve certain limitations, including subjectivity and low sensitivity. This study aimed to integrate synthetic magnetic resonance imaging (SyMRI) and quantitative susceptibility mapping (QSM) techniques to examine the changes in quantitative parameter values of patients with hepatitis B virus-related (HBV-related) decompensated cirrhosis, with the goal of providing imaging-based evidence for early neurological symptoms and disease monitoring in patients with cirrhosis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Data from 41 patients with HBV-related decompensated cirrhosis and 40 healthy controls were prospectively collected. T1 values, T2 values, proton density (PD) values, and magnetic susceptibility values of the bilateral frontal white matter, parietal white matter, occipital white matter, caudate nuclei, putamen, globus pallidus, thalamus, substantia nigra, red nuclei, and dentate nuclei were measured. Analysis of covariance (ANCOVA) was used to compare these values between the two groups. P values obtained were then corrected via the false-discovery rate (FDR) method. Correlation analysis was used to determine the correlation between the brain quantitative parameter values of patients and their clinical indicators.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In the SyMRI study, patients with cirrhosis had significantly lower T1 values in the right frontal white matter (RFWM) (P=0.030), left frontal white matter (LFWM) (P=0.043), right parietal white matter (RPWM) (P=0.038), left parietal white matter (LPWM) (P=0.043), right occipital white matter (ROWM) (P=0.016), right caudate nuclei (P&lt;0.001), left caudate nuclei (P=0.003), right putamen (RPUT) (P&lt;0.001), left putamen (P&lt;0.001), right globus pallidus (RGP) (P=0.007), right thalamus (RTHA) (P=0.044), right substantia nigra (RSN) (P=0.019), right dentate nuclei (P=0.033), and left dentate nuclei (P=0.016). Additionally, these patients had significantly lower T2 values in the RPUT (P=0.026), left putamen (P=0.043), RTHA (P=0.026), and left thalamus (LTHA) (P=0.016), along with significantly lower PD values in the RPWM (P=0.045), right caudate nuclei (P&lt;0.001), left caudate nuclei (P&lt;0.001), RPUT (P&lt;0.001), left putamen (P&lt;0.001), RTHA (P=0.016), right red nucleus (RRN) (P=0.016), and left red nucleus (LRN) (P=0.016). Moreover, the platelet count of patients was positively correlated with the T1 and PD values in the caudate nuclei (T1 right: r=0.451, P=0.030; T1 left: r=0.397, P=0.042; PD right: r=0.443, P=0.030; PD left: r=0.476 P=0.030) and putamen (T1 right: r=0.453, P=0.030; T1 left: r=0.400, P=0.042; PD right: r=0.463, P=0.030; PD left: r=0.510, P=0.026). In the QSM study, patients tended to exhibit an increase in magnetic susceptibility value in the ROWM and LTHA.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The measurement of T1 values, T2 values, PD values, and magnetic susceptibility values in deep g","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5312-5322"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209631/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI radiomics for diagnosing small BI-RADS 4 breast lesions: an interpretable model.","authors":"Chaokang Han, Jiayue Chen, Minping Hong, Shuqi Chen, Yujie Ying, Jiahuan Liu, Fan Yang, Hua Qian, Xuewei Ding, Ruixin Zhang, Jinghan Wu, Louting Hu, Chengchen Xu, Xuejing Liu, Wangwei Lin, Changyu Zhou, Maosheng Xu, Zhen Fang","doi":"10.21037/qims-24-1893","DOIUrl":"10.21037/qims-24-1893","url":null,"abstract":"<p><strong>Background: </strong>The early detection of breast cancer is crucial. Magnetic resonance imaging (MRI) offers significant advantages in the diagnosis of lesions. We aimed to develop and validate an interpretable MRI-based radiomics model to identify small Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions to help radiologists with decision making.</p><p><strong>Methods: </strong>In total, 561 patients (with 580 small BI-RADS category 4 lesions) from two centers (The First Affiliated Hospital of Zhejiang Chinese Medical University and The Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine) were consecutively enrolled in this study, and the radiomics features of the intratumoral and peritumoral (3 mm) regions were extracted. After a series of feature selections, extreme gradient boosting (XGBoost) was used to construct the radiomics model, and the radiomics score (radscore) was calculated. Univariate and multivariate logistic regression analyses were performed to determine the pathological malignant-related clinico-radiological factors. Finally, a model was constructed that combined the radscore and clinico-radiological factors using logistic algorithms. Subsequently, our artificial intelligence (AI)-assisted strategy was validated in an external group (n=163), and its clinical utility was evaluated by measuring improvements in BI-RADS classification accuracy with AI support.</p><p><strong>Results: </strong>The combined model demonstrated a robust predictive capability, and had area under the curve (AUC) values of 0.897 [95% confidence interval (CI): 0.862-0.931], 0.871 (95% CI: 0.803-0.934), and 0.869 (95% CI: 0.807-0.920) in the training, internal validation, and external validation groups, respectively. Additionally, the contribution of each feature to the radiomics and combined models was illustrated using the SHapley Additive exPlanations (SHAP) algorithm, a method for interpreting machine-learning models. Further, the AI-assisted strategy improved the two radiologists' AUC values in the two modes (the 4b+ and 4c) significantly.</p><p><strong>Conclusions: </strong>An interpretable combined model based on MRI was developed to distinguish between benign and malignant small BI-RADS4 lesions to assist radiologists to make more accurate diagnostic decisions.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5060-5072"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification of normal skin thickness using very high-frequency ultrasound: a clinical study in Chinese adults.","authors":"Yongrui Wang, Mei Tian, Ruiqian Guo, Fangxue Du, Li Qiu, Yuanjiao Tang","doi":"10.21037/qims-2024-2637","DOIUrl":"10.21037/qims-2024-2637","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Measurement of skin thickness provides an objective basis for diagnosing skin diseases and evaluating treatment efficacy. High-frequency ultrasound (HFUS) offers the advantages of high frequency and resolution, enabling clear visualization of the epidermis, dermis. Very high-frequency ultrasound (VHFUS) boasts an even higher frequency and resolution, allowing for more precise imaging of each skin layer. Both ultrasonic probes with different frequencies can accurately measure skin thickness. The purpose of this study was to compare the differences in skin thickness measured by the above ultrasonic probes in healthy Chinese adults and to analyze the factors influencing skin thickness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 74 healthy volunteers were included in this cross-sectional study. VHFUS (50 MHz) and HFUS (20 MHz) were used to obtain normal sonographic images of the skin, and the epidermal, dermal, and full-thickness skin thicknesses were measured. We compared the differences in skin thickness measurements between probes of different frequencies, and the differences in VHFUS skin thickness measurements in different sections, left and right sides, sexes, and different parts, and analyzed the relationship between skin thickness measurements and age and body mass index (BMI).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The differences between the epidermal layers of the abdomen (0.1100±0.0178, 0.1097±0.0156 mm; 0.1176±0.0159, 0.1159±0.0158 mm) and chest (0.1039±0.0189, 0.1038±0.0171 mm; 0.1102±0.0169, 0.1134±0.0159 mm) in the longitudinal and transverse sections observed using VHFUS and HFUS were statistically significant (P=0.007, 0.018, 0.034, 0.001). Right and left comparisons of the dermal and full-thickness skin thickness measurements of the forearm (dermal: 1.6138±0.4217, 1.5696±0.3900 mm; full-thickness skin: 1.7324±0.4311, 1.6772±0.3898 mm), and leg (dermal: 1.7977±0.4987, 1.7164±0.4342 mm; full-thickness skin: 1.8964±0.4827, 1.8336±0.4330 mm) show statistically significant differences. Sex comparisons indicated differences in the dermal and full-thickness skin measurements in certain areas (P&lt;0.05). Furthermore, the epidermal layer of the right foot dorsum, dermal layer, and overall skin thickness of the right calf were negatively correlated with age (r=-0.245, -0.229, -0.257). Some dermal and full-thickness skin measurements exhibited weak positive correlations with BMI (r=0.302, 0.306, 0.313, 0.314, 0.300, 0.291, 0.299, 0.302, 0.263, 0.262, 0.255, 0.257). Significant differences in the thicknesses of the skin were observed across various anatomical regions (P&lt;0.05).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;VHFUS can obtain clear skin sonograms and accurately measure skin thickness, particularly epidermal thickness. For sites where there is no significant difference in skin thickness between the two sides, the contralateral side can be selected as a reference for unilateral lesions, and age, BMI, and sex impact skin","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 6","pages":"5218-5231"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209672/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}