Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Quantitative magnetic resonance imaging parameters of lumbar paraspinal muscles and their relationship to function and ageing in healthy subjects.","authors":"Viktoria Kokosova, Peter Krkoska, Daniela Vlazna, Marek Dostal, Petra Ovesna, Katerina Matulova, Blanka Adamova","doi":"10.21037/qims-2024-2633","DOIUrl":"https://doi.org/10.21037/qims-2024-2633","url":null,"abstract":"<p><p>Muscle ageing involves structural and functional changes of muscles, mainly their replacement by fatty and fibrous tissue accompanied by the loss of muscle function. Quantitative magnetic resonance imaging (qMRI) methods have potential to provide biomarkers of degenerative changes in muscles with ageing. To assess the relationship between qMRI parameters of lumbar paraspinal muscles (LPMs) and their function and evolution with ageing in healthy subjects, 90 volunteers underwent MRI of lumbar spine and LPM utilising a 6-point Dixon gradient echo sequence. Using manual muscle segmentation, fat fraction (FF) and functional muscle volume (FMV) were calculated for LPM, with the psoas muscle (PS) as a control muscle. Functional parameters of LPM (strength and endurance) were assessed. Based on our data analysis, both FF and FMV of LPM correlate significantly with maximal isometric lumbar extensor muscle strength, but not with endurance. With ageing, FF of LPM increases by 34% per decade, while FF of PS increases by 17% per decade. This difference between LPM and the PS in the rate of FF increase is significant. FMV evinces a decreasing trend in both LPM and PS. However, only FMV of PS decreases significantly by 7% per decade. Our cross-sectional study shows a significant correlation between qMRI parameters of LPM and their strength. FF appears to be a biomarker of muscle ageing with different ageing patterns of distinct muscle groups: LPM and PS.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6517-6525"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735398","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":"Successful rescue from acute myocardial infarction in an anemic woman with anomalous origin of the left main coronary artery from the right coronary artery: a case description and literature analysis.","authors":"Erqiu Du, Jin Pan, Liang Dong, Baofu Chen","doi":"10.21037/qims-24-1380","DOIUrl":"https://doi.org/10.21037/qims-24-1380","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6559-6566"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735400","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":"Accuracy and consistency of subtraction dual-layer spectral computed tomography in diagnosing coronary stenosis: invasive coronary angiography validation study.","authors":"Xinglu Li, Yilin Xu, Zhixin Sun, Wen Chen, Xingbiao Chen, Chun-Hong Hu","doi":"10.21037/qims-24-1810","DOIUrl":"https://doi.org/10.21037/qims-24-1810","url":null,"abstract":"<p><strong>Background: </strong>Noninvasive assessment of coronary artery stenosis is critical for the diagnosis and management of coronary artery disease (CAD), particularly in patients with intermediate pretest probability for CAD or contraindications to invasive procedures. However, conventional coronary computed tomography angiography (CCTA_con) is limited by the presence of artifacts from calcified plaques, leading to overestimation of stenosis severity. Subtraction CCTA (CCTA_sub) has the potential to overcome these limitations by eliminating these artifacts and improving the visualization of the vessel wall, thereby enhancing diagnostic accuracy in terms of percent diameter stenosis (DS). The objective of our study was to evaluate the feasibility of using CCTA_sub with dual-layer spectral CT to improve coronary vessel wall visualization and the diagnostic accuracy across different plaque types.</p><p><strong>Methods: </strong>Seventy-one consecutive patients with suspected or known CAD who underwent both CCTA and invasive coronary angiography (ICA) within 30 days participated in this study. Subtraction images were generated via the subtraction of virtual noncontrast datasets from 70-keV datasets of dual-layer spectral computed tomography (CT). Two independent radiologists evaluated the image quality and the conspicuity of the inner and outer vessel walls in subtraction images. ICA served as the gold standard for DS assessment. Interobserver agreement for subjective image quality was assessed using weighted kappa statistics. The diagnostic accuracy of CCTA_sub in measuring DS was evaluated via receiver operating characteristic curve analyses.</p><p><strong>Results: </strong>The study population comprised 45 males (mean age: 64.5±11.5 years) and 26 females (mean age: 67.8±9.6 years), with 62.1% having severe DS (≥50%) as confirmed by ICA. The subjective evaluation of subtraction images yielded high scores for image quality (2.8±1.8), inner vessel wall conspicuity (1.8±0.8), and outer vessel wall conspicuity (1.9±0.9). Radiologists' subjective scores showed good consistency (all kappa values ≥0.7). Compared to CCTA_con, CCTA_sub demonstrated higher agreement in measuring the DS of coronary arteries (intraclass correlation coefficient: 0.96 <i>vs.</i> 0.60). CCTA_sub also demonstrated robust performance in accurately detecting DS [area under the curve: 0.986; 95% confidence interval (CI): 0.955-0.998], with a sensitivity of 98.2% and a specificity of 87.9%.</p><p><strong>Conclusions: </strong>Subtraction images derived from dual-layer spectral CT improved the visualization of the coronary artery vessel wall and showed good agreement with ICA in assessing the DS of coronary arteries. The findings support the clinical utility of CCTA_sub for accurate stenosis quantification, potentially reducing the need for invasive diagnostics in select patients.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6137-6146"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735428","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":"Analyzing explainability of YOLO-based breast cancer detection using heat map visualizations.","authors":"Awika Ariyametkul, May Phu Paing","doi":"10.21037/qims-2024-2911","DOIUrl":"https://doi.org/10.21037/qims-2024-2911","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Breast cancer is the most frequently diagnosed and leading cause of cancer-related mortality among women worldwide. The danger of this disease is due to its asymptomatic nature in the early stages, thereby underscoring the importance of early detection. Mammography, a specialized X-ray imaging technique for breast examination, has been pivotal in facilitating early detection and reducing mortality rates. In recent years, artificial intelligence (AI) has gained substantial popularity across various fields, including medicine. Numerous studies have leveraged AI techniques, particularly convolutional neural networks (CNNs) and You Only Look Once (YOLO)-based models, for medical image detection and classification. However, the predictions of such AI models often lack transparency and explainability, resulting in low trustworthiness. This study aims to address this gap by investigating three state-of-the-art versions of the YOLO algorithm-YOLO version 9 (YOLOv9), YOLO version 10 (YOLOv10), and YOLO version 11 (YOLO11)-trained on breast cancer imaging datasets, specifically the INbreast and Mammographic Image Analysis Society (MIAS) databases. Additionally, to address the challenges posed by the lack of explainability and transparency, we integrate seven explainable artificial intelligence (XAI) methods: Grad-CAM, Grad-CAM++, Eigen-CAM, EigenGrad-CAM, XGrad-CAM, LayerCAM, and HiResCAM.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study utilized two publicly available breast cancer image databases: INbreast: toward a Full-field Digital Mammographic Database and the MIAS dataset. Preprocessing steps were applied to standardize all images in accordance with the input requirements of the YOLO architecture, as these datasets were used to train the three most recent versions of YOLO. The YOLO model demonstrating the highest performance-measured by mean average precision (mAP), precision, and recall-was selected for integration with seven different XAI methods. The performance of each XAI technique was evaluated both qualitatively through visual inspection and quantitatively using several metrics, including matching ground truth (mGT), Pearson correlation coefficient (PCC), precision, recall, and root mean square error (RMSE). These methodologies were employed to interpret and visualize the \"black box\" decision-making processes of the top-performing YOLO model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Based on our experimental findings, YOLO11 outperformed YOLOv9 (mAP 0.868) and YOLOv10 (mAP 0.926), achieving the highest mAP of 0.935, with classification accuracies of 95% for benign and 80% for malignant cases. Among the evaluated XAI techniques, HiResCAM provided the most effective visual explanations, attaining the highest mGT score of 0.49, surpassing EigenGrad-CAM (0.45) and LayerCAM (0.42) in both visual and quantitative evaluations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The integration of YOLO11 with HiResCAM offers a robust solution that c","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6252-6271"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735430","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":"Application of non-invasive imaging in myocardial infarction: a bibliometric analysis from January 2003 to December 2022.","authors":"Pei Yang, Xinwen Wu, Yaya Zhao, Qingyou Ye, Mengyao Hu, Yinping Leng, Xuan Xiao, Jiahui Zhang, Haibo Ren, Lianggeng Gong","doi":"10.21037/qims-24-878","DOIUrl":"https://doi.org/10.21037/qims-24-878","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Myocardial infarction (MI) is a leading cause of death and disability worldwide. Non-invasive cardiac imaging has garnered significant attention in both MI diagnostic and prognostic research. Despite the growing body of published articles, no comprehensive, quantitative analysis has been conducted to delineate key trends and emerging areas in the field of non-invasive imaging for MI. This bibliometric analysis aimed to systematically evaluate the landscape of non-invasive cardiac imaging-focused research on MI in terms of the research status, publication patterns, influential contributors, hotspots, and focal development trends.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We systematically searched the Web of Science Core Collection (WoSCC) to retrieve publications related to MI imaging between 2003 and 2022. Only \"articles\" and \"reviews\" written in English were included in the final analysis. Subsequently, a manual screening process was employed to eliminate articles not relevant to the topic. The search results were exported as a plain text file in \"Full Record and Cited References\" format, and stored as \"download_*.txt\". CiteSpace and VOSviewer software were used to conduct the bibliometric and visualization analyses. These tools allowed us to analyze countries/regions and institutions' contributions, the top journals, prolific authors, influential references, and keywords.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Our bibliometric analysis included 33,480 publications from 138 countries, involving contributions from 19,554 institutions and 146,043 authors. Annual publications in this field have shown a rapid increase since approximately 2004. The United States of America (USA) leads in MI imaging research, boasting the highest number of publications (n=11,431), prolific research institutions, and numerous core authors. Notably, Harvard University and the University of California System emerged as the primary research institutions. Among the authors, Budoff was the most prolific contributor (n=209). The co-citation analysis, which measures how frequently an author's work is cited together with other key studies in the field, showed that Kim (n=2,794) was the most influential author based on co-citations, highlighting his significant influence in the area. Most articles appeared in the journal of the &lt;i&gt;American College of Cardiology&lt;/i&gt;, while &lt;i&gt;Circulation&lt;/i&gt; was the most frequently co-cited journal. Key topics included MI, risk-factor, magnetic resonance imaging (MRI), and atherosclerosis. Recent popular keywords such as ST-elevation myocardial infarction (STEMI), coronary computed tomography angiography (CTA), guidelines, and recommendations indicated future research directions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our bibliometric analysis revealed that MI non-invasive imaging is a rapidly developing field, with emerging trends in multimodal imaging and artificial intelligence (AI). These findings suggest that the integration of","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6340-6359"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735432","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":"Assessing differences in growth and shape between symptomatic and asymptomatic abdominal aortic aneurysms.","authors":"Drew J Braet, Timothy J Baker, Jonathan L Eliason, C Alberto Figueroa, Nicholas S Burris","doi":"10.21037/qims-2024-2985","DOIUrl":"https://doi.org/10.21037/qims-2024-2985","url":null,"abstract":"<p><strong>Background: </strong>While the risk of abdominal aortic aneurysm (AAA) rupture typically rises with increasing maximum aortic diameter (Dmax), this metric alone does not reflect the full morphological complexity of AAAs and is inadequate for accurately predicting rupture risk. In this study, we aimed to explore differences in growth and shape between asymptomatic AAA (aAAA) and symptomatic AAA (sAAA).</p><p><strong>Methods: </strong>Patients with infra-renal AAA and ≥2 CTA from 2010-2023 were identified. PRAEVAorta (Nurea, Bordeaux, France) was used to obtain segmentations of the aorta and its branches. Each segmentation was manually reviewed for accuracy using 3D Slicer. Patient demographics, Dmax, AAA flow lumen (AFL), and intraluminal thrombus (ILT) volume were obtained and compared between aAAA and sAAA. A subgroup of aAAA were matched with sAAA on sex and baseline Dmax (12 matched pairs) for comparison of shape, curvature, and 3D-growth. Statistical shape modeling (SSM) derived mean shapes for aAAA and sAAA were compared. Shape [quantified using distance to centerline (DC) in cm], curvature, and 3D-growth (defined as the difference in shape over time) were compared over eight aortic segments.</p><p><strong>Results: </strong>Fifty-five patients with AAA (12 sAAA) were included (47.3% female). Patients with sAAA were younger than those with aAAA [66.0 (60.9, 70.1) <i>vs.</i> 71.0 (65.3, 74.9) years, P=0.026], less likely to be Caucasian (75.0% <i>vs.</i> 95.3%, P=0.030), and less likely to have hypertension (50.0% <i>vs.</i> 81.4%, P=0.027). There was no difference in AAA Dmax (4.6 <i>vs.</i> 4.8 cm), volume (103.5 <i>vs.</i> 98.7 mm³), AFL (65.4 <i>vs.</i> 52.8 mm³), or ILT volume (37.9 <i>vs.</i> 36.7 mm³) between aAAA and sAAA. Although there was no difference in change of Dmax over time, sAAA had larger increases in AAA volume [1.6 (1.1, 7.8) <i>vs.</i> 1.1 (0.4, 2.1) cm³/month, P=0.019] and AFL volume [1.1 (0.5, 5.7) <i>vs.</i> 0.4 (0.2, 1.2) cm³/month, P=0.017] than aAAA. Despite possible qualitative shape differences seen on SSM, quantifiable differences in shape or curvature between aAAA and sAAA were not identified across eight aortic segments. At the left lateral aneurysm neck, sAAA had higher 3D-growth than aAAA [0.17 (0.05, 0.55) <i>vs.</i> 0.01 (-0.03, 0.14) mm/month, P=0.027].</p><p><strong>Conclusions: </strong>sAAA had larger increase in AAA volume and AFL volume over time when compared to aAAA (despite no difference in diameter, volume, or change in diameter). Despite no quantifiable differences in shape or curvature between aAAA and sAAA, sAAA had larger 3D-growth in the left lateral aneurysm neck compared to aAAA. Volumetric changes, shape, and 3D-growth may be better predictors of AAA rupture risk. However, larger scale studies are warranted to confirm these preliminary findings and explore the mechanisms underlying these differences.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"5955-5968"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735433","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":"Beyond direct visualization: a comparative analysis of computed tomography dacryocystographic features in dacryolithiasis, lacrimal sac cysts, and primary acquired nasolacrimal duct obstruction.","authors":"Xinhan Cui, Binghui Liu, Xing Huang, Jing Zhang, Yan Wang","doi":"10.21037/qims-2024-2971","DOIUrl":"https://doi.org/10.21037/qims-2024-2971","url":null,"abstract":"<p><strong>Background: </strong>Dacryoliths occur in approximately 5.8-18% of patients undergoing dacryocystorhinostomy (DCR), but conventional diagnostic methods often fail to distinguish them from other causes of nasolacrimal duct obstruction (NLDO). This study aimed to analyze the characteristic features of dacryoliths on computed tomography dacryocystography (CT-DCG) and to establish imaging criteria for their differential diagnosis from lacrimal sac cysts and primary acquired nasolacrimal duct obstruction (PANDO).</p><p><strong>Methods: </strong>In this retrospective case-control study, CT-DCG images from 54 patients (18 with surgically confirmed dacryoliths, 18 with lacrimal sac cysts, and 18 with PANDO) were analyzed. The assessment included lacrimal sac dimensions, contrast distribution patterns, and characteristic imaging features. For each case, the extent of contrast filling, surface irregularities, and presence of calcification were evaluated. Intraoperative findings and histopathological results were documented for dacryolith cases.</p><p><strong>Results: </strong>Analysis of contrast distribution patterns on CT-DCG revealed significant differences between groups (P<0.01), with dacryolith cases showing characteristic moderate contrast filling (63.30%±20.43%), significantly different from the minimal filling in lacrimal sac cysts (29.44%±11.77%) and near-complete filling in PANDO cases (80.14%±15.46%). Dacryoliths demonstrated characteristic imaging features including surface filling defects (82.4%), peripheral calcification (64.7%), and density interface lines (23.5%). Lacrimal sac dimensions showed significant differences in both transverse and anteroposterior (AP) diameters (P<0.01), primarily due to enlargement in the lacrimal sac cyst group, while dacryolith and PANDO groups showed comparable measurements. Intraoperatively, combined sac-duct involvement was most common (44.4%), and histopathological examination revealed periodic acid Schiff-positive staining in 38.89% of dacryolith cases.</p><p><strong>Conclusions: </strong>CT-DCG revealed characteristic contrast distribution patterns in dacryolithiasis, with moderate contrast filling that differed significantly from the filling of both lacrimal sac cysts and PANDO. When combined with surface filling defects, peripheral calcification, or density interface lines, these imaging features may serve as valuable diagnostic indicators for preoperative detection of dacryoliths.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6175-6184"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735438","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":"Effect of respiration-induced motion on a three-dimensional magnetic resonance imaging-based adaptive radiotherapy workflow in a 1.5T magnetic resonance linear accelerator.","authors":"Yongchang Wu, Hang Yu, Qing Xiao, Jing Li, Weige Wei, Lian Duan, Sen Bai, Guangjun Li","doi":"10.21037/qims-2024-2866","DOIUrl":"https://doi.org/10.21037/qims-2024-2866","url":null,"abstract":"<p><strong>Background: </strong>The long acquisition time of three-dimensional (3D) magnetic resonance imaging (MRI) makes it vulnerable to motion-induced artifacts such as blurring and ghosting, which may compromise target delineation and dose accuracy. Although motion management strategies such as four-dimensional MRI and cine MRI have been proposed, the specific influence of respiratory parameters-particularly amplitude and frequency-on the geometric and dosimetric precision of magnetic resonance-guided adaptive radiotherapy (RT) remains inadequately quantified. This study thus aimed to systematically evaluate how respiratory-induced linear translational motion affects delineation accuracy and dose distribution in MRI-based adaptive RT.</p><p><strong>Methods: </strong>An MR-compatible motion phantom was employed to replicate patient-specific respiratory-induced translational motion, with amplitude and frequency variations extracted from real patient waveforms being incorporated. Eight distinct respiratory patterns were generated, and MR images were acquired with standard spin-spin relaxation time-weighted (T2W) three-dimensional (3D) Cartesian sequences for each pattern. The internal target volume (ITV) delineated by clinicians based on 3D MR images was compared with the reference ITV (ITV_ref) generated with the digital phantom. Key delineation metrics [e.g., Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD)] and dosimetric parameters (e.g., dose received by 95% of the volume) were evaluated, and statistical analyses were performed to assess the correlations between respiratory motion characteristics and the observed variations.</p><p><strong>Results: </strong>Respiratory amplitude significantly affected delineation accuracy and dosimetric consistency. The DSC decreased linearly with increasing amplitude, from 0.96 at 2.50 mm to 0.83 at 12.50 mm, while the HD and MSD increased proportionally (2.62 to 6.32 mm and 0.08 to 0.64 mm, respectively). Dosimetric analysis showed a notable reduction in ITV_ref dose coverage at higher amplitudes, with the dose received by 95% of the volume decreasing by 481.55 cGy at 12.50 mm relative to the prescribed total dose of 4,500 cGy. In contrast, respiratory frequency had minimal impact, with changes remaining within clinically acceptable ranges.</p><p><strong>Conclusions: </strong>This study investigated the impact of respiratory-induced linear translational motion on ITV delineation and dosimetric accuracy in MR-guided RT. It was found that large respiratory amplitudes significantly compromised geometric and dosimetric precision, whereas frequency had minimal influence. The results emphasize the limitations of 3D Cartesian MRI due to motion-averaged artifacts and support the development of advanced imaging techniques for improving ITV delineation accuracy.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6486-6500"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735449","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":"Hereditary transthyretin cardiac amyloidosis with Glu109Lys mutation presenting with low sensitivity to ^99mTc pyrophosphate in scintigraphy: a case description.","authors":"Yun-Peng Wei, Da-Chun Zhao, Xiao Li, Chao Ren, Kai-Ni Shen, Zhuang Tian","doi":"10.21037/qims-2024-2928","DOIUrl":"https://doi.org/10.21037/qims-2024-2928","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6571-6577"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290679/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735454","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":"High-frequency quantitative ultrasound in characterizing human skin aging: an exploration of the non-modeling and modeling approaches.","authors":"Yuzhen Li, Bingbing He, Xun Lang, Guang Shi, Ningtao Zhang, Zhenyu Guo, Yufeng Zhang","doi":"10.21037/qims-24-1753","DOIUrl":"https://doi.org/10.21037/qims-24-1753","url":null,"abstract":"<p><strong>Background: </strong>High-frequency quantitative ultrasound (HQUS) technology, with its non-invasiveness, high-resolution, objectivity, and reproducibility, holds significant potential for characterizing skin aging through the analysis of the internal structure of tissues. This study aims to explore a framework for characterizing skin aging assessment through HQUS technology to facilitate the subsequent analysis of skin aging-related studies.</p><p><strong>Methods: </strong>In this study, an exploration of non-modeling and modeling HQUS techniques in characterizing skin aging was conducted. In particular, we tested the conventional approach using the envelope amplitude, the non-modeling approach based on the small-window entropy and the modeling approach with the Nakagami parameters (<i>m</i> and <i>Ω</i>) at scanning depths of 1 and 1.5 mm, respectively, and discovered that such a characterization framework is well-suitable for quantifying skin aging. These parameters were calculated based on ultrasound backscattered signals at a high frequency of 42 MHz from the facial skin (from the epidermis to the dermis) of 70 female participants aged 24-57 years and then analyzed using the linear fitting and receiver operating characteristic (ROC) curves.</p><p><strong>Results: </strong>The results show that there exists a linear correlation between all parameters and participant ages at scanning depths of 1 and 1.5 mm, respectively. Among them, the correlation coefficients for parameter <i>m</i> are r²=0.84 (P<0.0001) and r²=0.65 (P<0.0001), which are higher than those for the relative envelope amplitude, small-window entropy, and parameter <i>Ω</i>. Moreover, the parameter <i>m</i> also has the highest area under the curve among the ROC curves, regardless of the scanning depth.</p><p><strong>Conclusions: </strong>This characterization framework, especially the modeling of the Nakagami parameter <i>m</i>, has great feasibility for the characterization of human skin aging. The proposed framework holds significant potential for assessing the efficacy of facial rejuvenation products, photofacials, and similar treatments.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 7","pages":"6372-6385"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735455","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}