Background: Age-related macular degeneration (AMD) represents a significant clinical concern, particularly in aging populations, and recent advancements in artificial intelligence (AI) have catalyzed substantial research interest in this domain. Despite the growing body of literature, there remains a need for a comprehensive, quantitative analysis to delineate key trends and emerging areas in the field of AI applications in AMD. This bibliometric analysis sought to systematically evaluate the landscape of AI-focused research on AMD to illuminate publication patterns, influential contributors, and focal research trends.
Methods: Using the Web of Science Core Collection (WoSCC), a search was conducted to retrieve relevant publications from 1992 to 2023. This analysis involved an array of bibliometric indicators to map the evolution of AI research in AMD, assessing parameters such as publication volume, national/regional and institutional contributions, journal impact, author influence, and emerging research hotspots. Visualization tools, including Bibliometrix, CiteSpace and VOSviewer, were employed to generate comprehensive assessments of the data.
Results: A total of 1,721 publications were identified, with the USA leading in publication output and the University of Melbourne as the most prolific institution. The journal Investigative Ophthalmology & Visual Science published the highest number of articles, and Schmidt-Eerfurth emerged as the most active author. Keyword and clustering analyses, along with citation burst detection, revealed three distinct research stages within the field from 1992 to 2023. Presently, research efforts are concentrated on developing deep learning (DL) models for AMD diagnosis and progression prediction. Prominent emerging themes include early detection, risk stratification, and treatment efficacy prediction. The integration of large language models (LLMs) and vision-language models (VLMs) for enhanced image processing also represents a novel research frontier.
Conclusions: This bibliometric analysis provides a structured overview of prevailing research trends and emerging directions in AI applications for AMD. These findings furnish valuable insights to guide future research and foster collaborative advancements in this evolving field.
{"title":"Evolutionary patterns and research frontiers of artificial intelligence in age-related macular degeneration: a bibliometric analysis.","authors":"Zuyi Yang, Dianzhe Tian, Xinyu Zhao, Lei Zhang, Yiyao Xu, Xin Lu, Youxin Chen","doi":"10.21037/qims-24-1406","DOIUrl":"10.21037/qims-24-1406","url":null,"abstract":"<p><strong>Background: </strong>Age-related macular degeneration (AMD) represents a significant clinical concern, particularly in aging populations, and recent advancements in artificial intelligence (AI) have catalyzed substantial research interest in this domain. Despite the growing body of literature, there remains a need for a comprehensive, quantitative analysis to delineate key trends and emerging areas in the field of AI applications in AMD. This bibliometric analysis sought to systematically evaluate the landscape of AI-focused research on AMD to illuminate publication patterns, influential contributors, and focal research trends.</p><p><strong>Methods: </strong>Using the Web of Science Core Collection (WoSCC), a search was conducted to retrieve relevant publications from 1992 to 2023. This analysis involved an array of bibliometric indicators to map the evolution of AI research in AMD, assessing parameters such as publication volume, national/regional and institutional contributions, journal impact, author influence, and emerging research hotspots. Visualization tools, including Bibliometrix, CiteSpace and VOSviewer, were employed to generate comprehensive assessments of the data.</p><p><strong>Results: </strong>A total of 1,721 publications were identified, with the USA leading in publication output and the University of Melbourne as the most prolific institution. The journal <i>Investigative Ophthalmology & Visual Science</i> published the highest number of articles, and Schmidt-Eerfurth emerged as the most active author. Keyword and clustering analyses, along with citation burst detection, revealed three distinct research stages within the field from 1992 to 2023. Presently, research efforts are concentrated on developing deep learning (DL) models for AMD diagnosis and progression prediction. Prominent emerging themes include early detection, risk stratification, and treatment efficacy prediction. The integration of large language models (LLMs) and vision-language models (VLMs) for enhanced image processing also represents a novel research frontier.</p><p><strong>Conclusions: </strong>This bibliometric analysis provides a structured overview of prevailing research trends and emerging directions in AI applications for AMD. These findings furnish valuable insights to guide future research and foster collaborative advancements in this evolving field.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"813-830"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015952","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}
Background and objective: Computed tomography (CT) imaging plays a crucial role in the early detection and diagnosis of life-threatening diseases, particularly in respiratory illnesses and oncology. The rapid advancement of deep learning (DL) has revolutionized CT image analysis, enhancing diagnostic accuracy and efficiency. This review explores the impact of advanced DL methodologies in CT imaging, with a particular focus on their applications in coronavirus disease 2019 (COVID-19) detection and lung nodule classification.
Methods: A comprehensive literature search was conducted, examining the evolution of DL architectures in medical imaging from conventional convolutional neural networks (CNNs) to sophisticated foundational models (FMs). We reviewed publications from major databases, focusing on developments in CT image analysis using DL from 2013 to 2023. Our search criteria included all types of articles, with a focus on peer-reviewed research papers and review articles in English.
Key content and findings: The review reveals that DL, particularly advanced architectures like FMs, has transformed CT image analysis by streamlining interpretation processes and enhancing diagnostic capabilities. We found significant advancements in addressing global health challenges, especially during the COVID-19 pandemic, and in ongoing efforts for lung cancer screening. The review also addresses technical challenges in CT image analysis, including data variability, the need for large high-quality datasets, and computational demands. Innovative strategies such as transfer learning, data augmentation, and distributed computing are explored as solutions to these challenges.
Conclusions: This review underscores the pivotal role of DL in advancing CT image analysis, particularly for COVID-19 and lung nodule detection. The integration of DL models into clinical workflows shows promising potential to enhance diagnostic accuracy and efficiency. However, challenges remain in areas of interpretability, validation, and regulatory compliance. The review advocates for continued research, interdisciplinary collaboration, and ethical considerations as DL technologies become integral to clinical practice. While traditional imaging techniques remain vital, the integration of DL represents a significant advancement in medical diagnostics, with far-reaching implications for future research, clinical practice, and healthcare policy.
{"title":"Deep learning models for CT image classification: a comprehensive literature review.","authors":"Isah Salim Ahmad, Jingjing Dai, Yaoqin Xie, Xiaokun Liang","doi":"10.21037/qims-24-1400","DOIUrl":"10.21037/qims-24-1400","url":null,"abstract":"<p><strong>Background and objective: </strong>Computed tomography (CT) imaging plays a crucial role in the early detection and diagnosis of life-threatening diseases, particularly in respiratory illnesses and oncology. The rapid advancement of deep learning (DL) has revolutionized CT image analysis, enhancing diagnostic accuracy and efficiency. This review explores the impact of advanced DL methodologies in CT imaging, with a particular focus on their applications in coronavirus disease 2019 (COVID-19) detection and lung nodule classification.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted, examining the evolution of DL architectures in medical imaging from conventional convolutional neural networks (CNNs) to sophisticated foundational models (FMs). We reviewed publications from major databases, focusing on developments in CT image analysis using DL from 2013 to 2023. Our search criteria included all types of articles, with a focus on peer-reviewed research papers and review articles in English.</p><p><strong>Key content and findings: </strong>The review reveals that DL, particularly advanced architectures like FMs, has transformed CT image analysis by streamlining interpretation processes and enhancing diagnostic capabilities. We found significant advancements in addressing global health challenges, especially during the COVID-19 pandemic, and in ongoing efforts for lung cancer screening. The review also addresses technical challenges in CT image analysis, including data variability, the need for large high-quality datasets, and computational demands. Innovative strategies such as transfer learning, data augmentation, and distributed computing are explored as solutions to these challenges.</p><p><strong>Conclusions: </strong>This review underscores the pivotal role of DL in advancing CT image analysis, particularly for COVID-19 and lung nodule detection. The integration of DL models into clinical workflows shows promising potential to enhance diagnostic accuracy and efficiency. However, challenges remain in areas of interpretability, validation, and regulatory compliance. The review advocates for continued research, interdisciplinary collaboration, and ethical considerations as DL technologies become integral to clinical practice. While traditional imaging techniques remain vital, the integration of DL represents a significant advancement in medical diagnostics, with far-reaching implications for future research, clinical practice, and healthcare policy.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"962-1011"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016396","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}
Pub Date : 2025-01-02Epub Date: 2024-11-13DOI: 10.21037/qims-24-896
Qiu Bi, Yuchen Deng, Na Xu, Shan Wu, Hongjiang Zhang, Yichen Huang, Shuni Zhang, Shaoyu Wang, Yunzhu Wu, Kunhua Wu, Jie Zhang
Background: Accurate differentiation between benign and malignant endometrial lesions holds substantial clinical importance. This study aimed to evaluate the efficacy of various diffusion models in the preoperative diagnosis of early-stage endometrial carcinoma (EC).
Methods: A total of 72 consecutive patients with benign or malignant endometrial lesions from the First People's Hospital of Yunnan Province were prospectively enrolled between April 2021 and July 2023. Fourteen diffusion parameters derived from monoexponential diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), stretched exponential model (SEM), continuous-time random walk (CTRW), and fractional order calculus (FROC) models were calculated and compared. Independent predictors of early-stage EC were identified using logistic regression analysis. The performance of the diffusion parameters, both individually and in combination with effective clinical indicators, for differentiating benign and malignant endometrial lesions was evaluated.
Results: This study consisted of 17 patients with benign endometrial lesions and 55 patients with EC. Significant differences in age and menopausal status were observed between the benign and malignant endometrial groups (P=0.015 and P=0.011, respectively). With the exception of the pseudodiffusion coefficient (D*) and perfusion fraction (f), all other parameters exhibited significant differences between the benign and malignant groups (P<0.05). Mean kurtosis (MK), true diffusion coefficient (D), and temporal diffusion heterogeneity index (αCTRW) were identified as independent predictors of early-stage EC, achieving an area under the curve (AUC) of 0.903 [95% confidence interval (CI): 0.824-0.982], surpassing that of any individual diffusion parameter. The combination of these independent predictors with menopausal status yielded the highest AUC (0.922, 95% CI: 0.845-0.999), accuracy (93.1%), and sensitivity (100.0%).
Conclusions: MK, D, and αCTRW have the potential to serve as independent predictors in predicting early-stage EC, and the performance can be enhanced when combined with menopausal status.
{"title":"Differentiation of early-stage endometrial carcinoma from benign endometrial lesions: a comparative study of six diffusion models.","authors":"Qiu Bi, Yuchen Deng, Na Xu, Shan Wu, Hongjiang Zhang, Yichen Huang, Shuni Zhang, Shaoyu Wang, Yunzhu Wu, Kunhua Wu, Jie Zhang","doi":"10.21037/qims-24-896","DOIUrl":"10.21037/qims-24-896","url":null,"abstract":"<p><strong>Background: </strong>Accurate differentiation between benign and malignant endometrial lesions holds substantial clinical importance. This study aimed to evaluate the efficacy of various diffusion models in the preoperative diagnosis of early-stage endometrial carcinoma (EC).</p><p><strong>Methods: </strong>A total of 72 consecutive patients with benign or malignant endometrial lesions from the First People's Hospital of Yunnan Province were prospectively enrolled between April 2021 and July 2023. Fourteen diffusion parameters derived from monoexponential diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), stretched exponential model (SEM), continuous-time random walk (CTRW), and fractional order calculus (FROC) models were calculated and compared. Independent predictors of early-stage EC were identified using logistic regression analysis. The performance of the diffusion parameters, both individually and in combination with effective clinical indicators, for differentiating benign and malignant endometrial lesions was evaluated.</p><p><strong>Results: </strong>This study consisted of 17 patients with benign endometrial lesions and 55 patients with EC. Significant differences in age and menopausal status were observed between the benign and malignant endometrial groups (P=0.015 and P=0.011, respectively). With the exception of the pseudodiffusion coefficient (D*) and perfusion fraction (f), all other parameters exhibited significant differences between the benign and malignant groups (P<0.05). Mean kurtosis (MK), true diffusion coefficient (D), and temporal diffusion heterogeneity index (α<sub>CTRW</sub>) were identified as independent predictors of early-stage EC, achieving an area under the curve (AUC) of 0.903 [95% confidence interval (CI): 0.824-0.982], surpassing that of any individual diffusion parameter. The combination of these independent predictors with menopausal status yielded the highest AUC (0.922, 95% CI: 0.845-0.999), accuracy (93.1%), and sensitivity (100.0%).</p><p><strong>Conclusions: </strong>MK, D, and α<sub>CTRW</sub> have the potential to serve as independent predictors in predicting early-stage EC, and the performance can be enhanced when combined with menopausal status.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"121-134"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016409","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}
Pub Date : 2025-01-02Epub Date: 2024-12-30DOI: 10.21037/qims-24-1113
Tao Gao, Yongwei Guo, Alexander C Rokohl, Wanlin Fan, Ming Lin, Sitong Ju, Xueting Li, Xiaojun Ju, Xincen Hou, Till A Rosenkranz, Guosheng Zhang, Haixia Bai, Kaiwen Ni, Ke Yao, Ludwig M Heindl
<p><strong>Background: </strong>With globalization, oculoplastic surgeons must understand the intricate morphological nuances of the periocular region across ethnicities to ensure precise treatment and avoid facial disharmony or dysfunction. Direct comparisons in two-dimensional (2D)-based periocular morphology between studies can be challenging due to the limited number of parameters and complicated variations in equipment, environments, measurement personnel, and methods. Therefore, it is imperative to explore the detailed three-dimensional (3D) periocular morphological disparities between young Caucasian and Chinese populations. This study aimed to establish gender- and ethnicity-specific 3D anthropometric data in periocular soft tissue for young Caucasian and Chinese adults and to determine the inter-racial and inter-gender differences.</p><p><strong>Methods: </strong>This descriptive, cross-sectional study enrolled 46 Asians and 101 Caucasians aged 18 to 30 years. 3D models were analyzed with 32 landmarks, yielding 21 linear distances, three curvatures, six angles, and three proportions. Comparisons were made across left and right eyes, ethnic groups, and sexes to assess ethnic disparities and sexual dimorphism.</p><p><strong>Results: </strong>Twenty-nine measurements were compared between the left and right sides revealing significant differences (P<0.002) in two measurements for Caucasian and Chinese females, respectively. However, these differences were submillimeter levels and potentially inconsequential in practical settings with left-right differences of -0.58 and -0.57 mm (P<0.001) for double-eyelid fold-palpebral margin distance (medial) (FPDm) and double-eyelid fold-palpebral margin distance (medial limbus) (FLmD) in Chinese females and -0.38 and -0.52 mm (P<0.001) for palpebral fissure width (PFW) and lower palpebral margin length (LPML) in Caucasian females. Caucasian males displayed significantly larger palpebral fissure height (PFH), iris diameter (ID), LPML, lateral canthal angle (LCA), canthal tilt (CT), palpebral fissure index (PFI), and canthal angular index (CAI), as well as smaller inner intercanthal distance (EnD), outer intercanthal distance (ExD), and canthal index (CI) than Chinese males (P<0.05). In contrast, Caucasian females showed significantly larger PFW, ID, LPML, LCA, CT, and CAI, as well as smaller EnD, ExD, CI, and medial canthal angle (MCA) than Chinese females (P<0.05). Furthermore, Caucasians showed more prominent double-eyelid folds, except at the pupil center in females. In eyebrow measurements, Caucasian males exhibited non-significant differences with Chinese males, while Caucasian females had significantly larger measurements at lateral positions but smaller ones at the endocanthion than Chinese females (P<0.05).</p><p><strong>Conclusions: </strong>This study established sex- and ethnicity-specific 3D anthropometric data for the periocular region of young Caucasian and Chinese adults. These findings mu
{"title":"Racial and sexual differences of eyebrow and eyelid morphology: three-dimensional analysis in young Caucasian and Chinese populations.","authors":"Tao Gao, Yongwei Guo, Alexander C Rokohl, Wanlin Fan, Ming Lin, Sitong Ju, Xueting Li, Xiaojun Ju, Xincen Hou, Till A Rosenkranz, Guosheng Zhang, Haixia Bai, Kaiwen Ni, Ke Yao, Ludwig M Heindl","doi":"10.21037/qims-24-1113","DOIUrl":"10.21037/qims-24-1113","url":null,"abstract":"<p><strong>Background: </strong>With globalization, oculoplastic surgeons must understand the intricate morphological nuances of the periocular region across ethnicities to ensure precise treatment and avoid facial disharmony or dysfunction. Direct comparisons in two-dimensional (2D)-based periocular morphology between studies can be challenging due to the limited number of parameters and complicated variations in equipment, environments, measurement personnel, and methods. Therefore, it is imperative to explore the detailed three-dimensional (3D) periocular morphological disparities between young Caucasian and Chinese populations. This study aimed to establish gender- and ethnicity-specific 3D anthropometric data in periocular soft tissue for young Caucasian and Chinese adults and to determine the inter-racial and inter-gender differences.</p><p><strong>Methods: </strong>This descriptive, cross-sectional study enrolled 46 Asians and 101 Caucasians aged 18 to 30 years. 3D models were analyzed with 32 landmarks, yielding 21 linear distances, three curvatures, six angles, and three proportions. Comparisons were made across left and right eyes, ethnic groups, and sexes to assess ethnic disparities and sexual dimorphism.</p><p><strong>Results: </strong>Twenty-nine measurements were compared between the left and right sides revealing significant differences (P<0.002) in two measurements for Caucasian and Chinese females, respectively. However, these differences were submillimeter levels and potentially inconsequential in practical settings with left-right differences of -0.58 and -0.57 mm (P<0.001) for double-eyelid fold-palpebral margin distance (medial) (FPDm) and double-eyelid fold-palpebral margin distance (medial limbus) (FLmD) in Chinese females and -0.38 and -0.52 mm (P<0.001) for palpebral fissure width (PFW) and lower palpebral margin length (LPML) in Caucasian females. Caucasian males displayed significantly larger palpebral fissure height (PFH), iris diameter (ID), LPML, lateral canthal angle (LCA), canthal tilt (CT), palpebral fissure index (PFI), and canthal angular index (CAI), as well as smaller inner intercanthal distance (EnD), outer intercanthal distance (ExD), and canthal index (CI) than Chinese males (P<0.05). In contrast, Caucasian females showed significantly larger PFW, ID, LPML, LCA, CT, and CAI, as well as smaller EnD, ExD, CI, and medial canthal angle (MCA) than Chinese females (P<0.05). Furthermore, Caucasians showed more prominent double-eyelid folds, except at the pupil center in females. In eyebrow measurements, Caucasian males exhibited non-significant differences with Chinese males, while Caucasian females had significantly larger measurements at lateral positions but smaller ones at the endocanthion than Chinese females (P<0.05).</p><p><strong>Conclusions: </strong>This study established sex- and ethnicity-specific 3D anthropometric data for the periocular region of young Caucasian and Chinese adults. These findings mu","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"882-897"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744102/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016473","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}
Pub Date : 2025-01-02Epub Date: 2024-12-20DOI: 10.21037/qims-24-1429
Ching-Hsue Cheng, Jun-He Yang, Yu-Chen Hsu
Background: Image segmentation is crucial in medical diagnosis, helping to identify diseased areas in images for more accurate diagnoses. The U-Net model, a convolutional neural network (CNN) widely used for medical image segmentation, has limitations in extracting global features and handling multi-scale pathological information. This study aims to address these challenges by proposing a novel model that enhances segmentation performance while reducing computational demands.
Methods: We introduce the LUNeXt model, which integrates Vision Transformers (ViT) with a redesigned convolution block structure. This model employs depthwise separable convolutions to capture global features with fewer parameters. Comprehensive experiments were conducted on four diverse medical image datasets to evaluate the model's performance.
Results: The LUNeXt model demonstrated competitive segmentation performance with a significant reduction in parameters and floating-point operations (FLOPs) compared to traditional U-Net models. The application of explainable AI techniques provided clear visualization of segmentation results, highlighting the model's efficacy in efficient medical image segmentation.
Conclusions: LUNeXt facilitates efficient medical image segmentation on standard hardware, reducing the learning curve and making advanced techniques more accessible to practitioners. This model balances the complexity and parameter count, offering a promising solution for enhancing the accuracy of pathological feature extraction in medical images.
{"title":"A streamlined U-Net convolution network for medical image processing.","authors":"Ching-Hsue Cheng, Jun-He Yang, Yu-Chen Hsu","doi":"10.21037/qims-24-1429","DOIUrl":"10.21037/qims-24-1429","url":null,"abstract":"<p><strong>Background: </strong>Image segmentation is crucial in medical diagnosis, helping to identify diseased areas in images for more accurate diagnoses. The U-Net model, a convolutional neural network (CNN) widely used for medical image segmentation, has limitations in extracting global features and handling multi-scale pathological information. This study aims to address these challenges by proposing a novel model that enhances segmentation performance while reducing computational demands.</p><p><strong>Methods: </strong>We introduce the LUNeXt model, which integrates Vision Transformers (ViT) with a redesigned convolution block structure. This model employs depthwise separable convolutions to capture global features with fewer parameters. Comprehensive experiments were conducted on four diverse medical image datasets to evaluate the model's performance.</p><p><strong>Results: </strong>The LUNeXt model demonstrated competitive segmentation performance with a significant reduction in parameters and floating-point operations (FLOPs) compared to traditional U-Net models. The application of explainable AI techniques provided clear visualization of segmentation results, highlighting the model's efficacy in efficient medical image segmentation.</p><p><strong>Conclusions: </strong>LUNeXt facilitates efficient medical image segmentation on standard hardware, reducing the learning curve and making advanced techniques more accessible to practitioners. This model balances the complexity and parameter count, offering a promising solution for enhancing the accuracy of pathological feature extraction in medical images.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"455-472"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016019","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}
Background: Traditional freehand puncture relies on non-real-time computed tomography (CT) images, which significantly affects the accuracy of puncturing targets in the lower lung lobes with respiratory motion. This study aims to assess the safety and feasibility of a teleoperated robotic system and low-dose CT for the accurate real-time puncture of targets in the lungs of live pigs during breathing under fluoroscopic guidance.
Methods: Two puncture methods were analyzed: freehand and robot-assisted. For each method, one puncture was performed on a target implanted in the lower lung lobe of live pigs (five animals per group, two targets per animal), totaling 20 punctures. Using a tube current of 30 mA, group A received freehand punctures with conventional CT, while group B received robot-assisted punctures with real-time CT fluoroscopy. Data on operation time (OT), number of needle adjustments (NA), puncture time (PT), radiation dose (RD), and puncture accuracy were collected and analyzed. Statistical analysis was performed using SPSS version 26.0, and data were compared using a Mann-Whitney U test.
Results: The puncture accuracy rate was 100% in both groups. The RD was similar between the groups (P=0.25414). Nonetheless, the surgical robotic system was associated with a significantly shorter OT and PT and a smaller NA (P=0.00016, 0.00015, 0.00005).
Conclusions: Teleoperated robotic systems combined with low-dose CT can accurately puncture millimeter-level targets in the lower lung lobes in real time during breathing under fluoroscopic guidance. Compared with freehand puncture with intermittent scans, the new technique reduces the NA and shortens the OT and PT. Moreover, this technique can improve the targeting and interventional treatment of tumors.
{"title":"Accurate puncture of targets in the lower lung lobes with respiratory motion using a teleoperated robotic system and low-dose computed tomography fluoroscopy: an experimental animal study.","authors":"Xiaofeng He, Yueyong Xiao, Xiao Zhang, Xiaobo Zhang, Xin Zhang, Yingtian Wei, Zhongliang Zhang, Xiaodong Xue","doi":"10.21037/qims-24-843","DOIUrl":"10.21037/qims-24-843","url":null,"abstract":"<p><strong>Background: </strong>Traditional freehand puncture relies on non-real-time computed tomography (CT) images, which significantly affects the accuracy of puncturing targets in the lower lung lobes with respiratory motion. This study aims to assess the safety and feasibility of a teleoperated robotic system and low-dose CT for the accurate real-time puncture of targets in the lungs of live pigs during breathing under fluoroscopic guidance.</p><p><strong>Methods: </strong>Two puncture methods were analyzed: freehand and robot-assisted. For each method, one puncture was performed on a target implanted in the lower lung lobe of live pigs (five animals per group, two targets per animal), totaling 20 punctures. Using a tube current of 30 mA, group A received freehand punctures with conventional CT, while group B received robot-assisted punctures with real-time CT fluoroscopy. Data on operation time (OT), number of needle adjustments (NA), puncture time (PT), radiation dose (RD), and puncture accuracy were collected and analyzed. Statistical analysis was performed using SPSS version 26.0, and data were compared using a Mann-Whitney <i>U</i> test.</p><p><strong>Results: </strong>The puncture accuracy rate was 100% in both groups. The RD was similar between the groups (P=0.25414). Nonetheless, the surgical robotic system was associated with a significantly shorter OT and PT and a smaller NA (P=0.00016, 0.00015, 0.00005).</p><p><strong>Conclusions: </strong>Teleoperated robotic systems combined with low-dose CT can accurately puncture millimeter-level targets in the lower lung lobes in real time during breathing under fluoroscopic guidance. Compared with freehand puncture with intermittent scans, the new technique reduces the NA and shortens the OT and PT. Moreover, this technique can improve the targeting and interventional treatment of tumors.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"417-426"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016025","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}
Pub Date : 2025-01-02Epub Date: 2024-12-30DOI: 10.21037/qims-24-1309
Nicolas Haelewijn, Jean-Louis Peters-Dickie, Roel de Ridder, Kevin Deschamps, Christine Detrembleur, Sébastien Lobet, Valentien Spanhove
<p><strong>Background: </strong>Quantitative ultrasound imaging is a popular technique to assess the structural properties of the intrinsic and extrinsic foot muscles. Although several studies examined test-retest reliability, specific gaps remain in assessing inter-rater reliability, particularly distinguishing between image acquisition and muscle measurement. Additionally, these studies utilized equipment that may not be generalizable across both clinical and research settings and often involved small sample sizes without prior sample size calculations. This study aimed to investigate test-retest reliability as well as global and measurement-based inter-rater reliability (MIRR) using a low-end ultrasound device to measure intrinsic and extrinsic foot muscle sizes.</p><p><strong>Methods: </strong>This prospective reliability study included 21 active individuals. Five intrinsic muscles [abductor hallucis (AbH), flexor digitorum brevis (FDB), flexor hallucis brevis (FHB), quadratus plantae (QP), abductor digiti minimi (AbDM)], and three extrinsic muscles [peroneal (PER), flexor digitorum longus, tibialis anterior (TA)] were scanned. Three investigators independently acquired images on two occasions and measured cross-sectional area (CSA) and thickness in September and October 2023. Participants were assessed either at the Musculoskeletal Research Group laboratory (University of Leuven, Bruges) or in the Rehabilitation Sciences laboratory (Ghent University hospital). Test-retest (same investigator, one week in between), global inter-rater (each investigator measures own image set) and MIRR (three investigators measure one image set) was performed following intra-class correlation, standard error of the measurement (SEM) and coefficient of variation.</p><p><strong>Results: </strong>Test-retest reliability showed intraclass-correlation coefficients of 0.60-0.88 for the FDB and 0.38-0.73 for the TA. SEM ranged from 0.16 to 0.41 cm<sup>2</sup> (CSA) and from 0.05 to 0.31 cm (thickness) for the intrinsic, while they ranged from 0.19 to 1.13 cm<sup>2</sup> and from 0.12 to 0.44 cm for the extrinsic muscles. Global inter-rater correlation coefficients varied between 0.4 and 0.8 for the AbH and FDB. Measurement based inter-rater correlation coefficient varied between 0.50 and 0.96 for AbH, FDB, TA and PER muscles. SEM ranged from 0.14 to 0.89 cm<sup>2</sup> (CSA) and from 0.07 to 0.24 cm (thickness) for the intrinsic, while they ranged from 0.29 to 0.85 cm<sup>2</sup> (CSA) and from 0.12 to 0.51 cm (thickness) for the extrinsic muscles. Coefficients of variations were between 4% and 34%. For test-retest, they were consistently ≤10% for AbH thickness, FDB CSA, FHB and TA. FDB coefficients of variation were ≤10% across all inter-rater reliabilities.</p><p><strong>Conclusions: </strong>Most muscles demonstrated moderate to excellent test-retest reliability using a portable ultrasound device, supporting its generalizability. However, the greater variability in
{"title":"Quantitative ultrasonography of the foot muscles: a comprehensive perspective on reliability.","authors":"Nicolas Haelewijn, Jean-Louis Peters-Dickie, Roel de Ridder, Kevin Deschamps, Christine Detrembleur, Sébastien Lobet, Valentien Spanhove","doi":"10.21037/qims-24-1309","DOIUrl":"10.21037/qims-24-1309","url":null,"abstract":"<p><strong>Background: </strong>Quantitative ultrasound imaging is a popular technique to assess the structural properties of the intrinsic and extrinsic foot muscles. Although several studies examined test-retest reliability, specific gaps remain in assessing inter-rater reliability, particularly distinguishing between image acquisition and muscle measurement. Additionally, these studies utilized equipment that may not be generalizable across both clinical and research settings and often involved small sample sizes without prior sample size calculations. This study aimed to investigate test-retest reliability as well as global and measurement-based inter-rater reliability (MIRR) using a low-end ultrasound device to measure intrinsic and extrinsic foot muscle sizes.</p><p><strong>Methods: </strong>This prospective reliability study included 21 active individuals. Five intrinsic muscles [abductor hallucis (AbH), flexor digitorum brevis (FDB), flexor hallucis brevis (FHB), quadratus plantae (QP), abductor digiti minimi (AbDM)], and three extrinsic muscles [peroneal (PER), flexor digitorum longus, tibialis anterior (TA)] were scanned. Three investigators independently acquired images on two occasions and measured cross-sectional area (CSA) and thickness in September and October 2023. Participants were assessed either at the Musculoskeletal Research Group laboratory (University of Leuven, Bruges) or in the Rehabilitation Sciences laboratory (Ghent University hospital). Test-retest (same investigator, one week in between), global inter-rater (each investigator measures own image set) and MIRR (three investigators measure one image set) was performed following intra-class correlation, standard error of the measurement (SEM) and coefficient of variation.</p><p><strong>Results: </strong>Test-retest reliability showed intraclass-correlation coefficients of 0.60-0.88 for the FDB and 0.38-0.73 for the TA. SEM ranged from 0.16 to 0.41 cm<sup>2</sup> (CSA) and from 0.05 to 0.31 cm (thickness) for the intrinsic, while they ranged from 0.19 to 1.13 cm<sup>2</sup> and from 0.12 to 0.44 cm for the extrinsic muscles. Global inter-rater correlation coefficients varied between 0.4 and 0.8 for the AbH and FDB. Measurement based inter-rater correlation coefficient varied between 0.50 and 0.96 for AbH, FDB, TA and PER muscles. SEM ranged from 0.14 to 0.89 cm<sup>2</sup> (CSA) and from 0.07 to 0.24 cm (thickness) for the intrinsic, while they ranged from 0.29 to 0.85 cm<sup>2</sup> (CSA) and from 0.12 to 0.51 cm (thickness) for the extrinsic muscles. Coefficients of variations were between 4% and 34%. For test-retest, they were consistently ≤10% for AbH thickness, FDB CSA, FHB and TA. FDB coefficients of variation were ≤10% across all inter-rater reliabilities.</p><p><strong>Conclusions: </strong>Most muscles demonstrated moderate to excellent test-retest reliability using a portable ultrasound device, supporting its generalizability. However, the greater variability in","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"203-216"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016433","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}
<p><strong>Background: </strong>Although <sup>18</sup>F-prostate-specific membrane antigen-1007 (<sup>18</sup>F-PSMA-1007) positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance imaging (mpMRI) are good predictors of prostate cancer (PCa) prognosis, their combined ability to predict prostate-specific antigen (PSA) persistence has not been thoroughly evaluated. In this study, we assessed whether clinical, mpMRI, and <sup>18</sup>F-PSMA-1007 PET/CT characteristics could predict PSA persistence in patients with PCa treated with radical prostatectomy (RP).</p><p><strong>Methods: </strong>This retrospective study involved consecutive patients diagnosed with PCa who underwent both preoperative mpMRI and PSMA PET/CT scans between April 2019 and June 2022. Scatter plots and heat maps were employed to determine the correlation of mpMRI and PSMA PET/CT features with preoperative PSA. Univariate logistic regression analyses were used assess the correlation between age, maximum Prostate Imaging-Reporting and Data System (PI-RADS) score, prostate-specific antigen density (PSAD), extracapsular extension (EPE), seminal vesicle invasion (SVI), total lesion PSMA (PSMA-TL), and PSA persistence. Multivariate logistic regression analyses were used to develop a predictive model for PSA persistence, while decision tree analysis was used to classify patients into different risk groups for easy interpretation and visualization. We divided the patient cohort into training and validation sets in an 8:2 ratio. To ensure the reliability of the model, we performed five-fold cross-validation of the validation results.</p><p><strong>Results: </strong>Ultimately, this study included 190 patients with PCa. The median age of the patients was 69 years [interquartile range (IQR) 64-73 years]. Among the patients, 35 (18%) experienced PSA persistence following RP. Additionally, SVI was identified in 31 (16%) patients. The median values for SUVmax and PSMA-TL were 11.83 (IQR 7.44-20.89) and 41.92 (IQR 21.25-113.83), respectively. Spearman correlation analysis indicated that the preoperative PSA levels in patients with PCa were slightly correlated with the maximum standardized uptake value (SUVmax) (r=0.41; P<0.001), significantly correlated with PSMA-TL (r=0.58, P<0.001), and strongly correlated with PSAD (r=0.865, P<0.001). Multivariate logistic regression analysis showed that the independent predictors of PSA persistence were SVI on mpMRI [area under the curve (AUC)=0.63; 95% confidence interval (CI): 0.516-0.739] and PSMA-TL (AUC =0.80; 95% CI: 0.723-0.877) on PSMA PET/CT (all P values <0.05). Patients with SVI and PSMA-TL >63.38 cm<sup>3</sup> were more likely to have PSA persistence. Decision tree analysis stratified patients into low-risk (5%), intermediate-risk (36%), and high-risk (48%) categories for PSA persistence. The model exhibited good discriminatory capability in internal validation (AUC 0.93, 95% CI: 0.850-0.930).</p><p><stron
{"title":"A machine learning model incorporating <sup>18</sup>F-prostate-specific membrane antigen-1007 positron emission tomography/computed tomography and multiparametric magnetic resonance imaging for predicting prostate-specific antigen persistence in patients with prostate cancer after radical prostatectomy.","authors":"Fangansheng Chen, Jia Jiang, Yushi Peng, Ling Wang, Junping Lan, Shuying Bian, Hanzhe Wang, Zhe Xiao, Yimin Chen, Yinuo Fu, Xiangwu Zheng, Kun Tang","doi":"10.21037/qims-24-1149","DOIUrl":"10.21037/qims-24-1149","url":null,"abstract":"<p><strong>Background: </strong>Although <sup>18</sup>F-prostate-specific membrane antigen-1007 (<sup>18</sup>F-PSMA-1007) positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance imaging (mpMRI) are good predictors of prostate cancer (PCa) prognosis, their combined ability to predict prostate-specific antigen (PSA) persistence has not been thoroughly evaluated. In this study, we assessed whether clinical, mpMRI, and <sup>18</sup>F-PSMA-1007 PET/CT characteristics could predict PSA persistence in patients with PCa treated with radical prostatectomy (RP).</p><p><strong>Methods: </strong>This retrospective study involved consecutive patients diagnosed with PCa who underwent both preoperative mpMRI and PSMA PET/CT scans between April 2019 and June 2022. Scatter plots and heat maps were employed to determine the correlation of mpMRI and PSMA PET/CT features with preoperative PSA. Univariate logistic regression analyses were used assess the correlation between age, maximum Prostate Imaging-Reporting and Data System (PI-RADS) score, prostate-specific antigen density (PSAD), extracapsular extension (EPE), seminal vesicle invasion (SVI), total lesion PSMA (PSMA-TL), and PSA persistence. Multivariate logistic regression analyses were used to develop a predictive model for PSA persistence, while decision tree analysis was used to classify patients into different risk groups for easy interpretation and visualization. We divided the patient cohort into training and validation sets in an 8:2 ratio. To ensure the reliability of the model, we performed five-fold cross-validation of the validation results.</p><p><strong>Results: </strong>Ultimately, this study included 190 patients with PCa. The median age of the patients was 69 years [interquartile range (IQR) 64-73 years]. Among the patients, 35 (18%) experienced PSA persistence following RP. Additionally, SVI was identified in 31 (16%) patients. The median values for SUVmax and PSMA-TL were 11.83 (IQR 7.44-20.89) and 41.92 (IQR 21.25-113.83), respectively. Spearman correlation analysis indicated that the preoperative PSA levels in patients with PCa were slightly correlated with the maximum standardized uptake value (SUVmax) (r=0.41; P<0.001), significantly correlated with PSMA-TL (r=0.58, P<0.001), and strongly correlated with PSAD (r=0.865, P<0.001). Multivariate logistic regression analysis showed that the independent predictors of PSA persistence were SVI on mpMRI [area under the curve (AUC)=0.63; 95% confidence interval (CI): 0.516-0.739] and PSMA-TL (AUC =0.80; 95% CI: 0.723-0.877) on PSMA PET/CT (all P values <0.05). Patients with SVI and PSMA-TL >63.38 cm<sup>3</sup> were more likely to have PSA persistence. Decision tree analysis stratified patients into low-risk (5%), intermediate-risk (36%), and high-risk (48%) categories for PSA persistence. The model exhibited good discriminatory capability in internal validation (AUC 0.93, 95% CI: 0.850-0.930).</p><p><stron","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"30-41"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744181/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016015","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}
Background: Carotid ultrasound is a helpful approach for classifying cardiovascular risk. Quantitative flow ratio (QFR) is used to evaluate functionally significant coronary artery stenosis (CAS). The aim of this prospective study was to investigate the correlation between carotid artery features from carotid ultrasound and functionally significant CAS. Furthermore, this study aimed to evaluate the diagnostic performance of carotid ultrasound in diagnosing functional CAS.
Methods: Carotid ultrasound was performed in 82 patients with suspicious coronary artery disease, measuring carotid intima-media thickness (IMT), internal artery diameter (IAD), and carotid plaques. QFR values were measured in all patients, and functionally significant CAS was defined as QFR ≤0.8. Forty patients (48.8%) had non-functionally significant CAS with QFR >0.8, while 42 patients (51.2%) had functionally significant CAS with QFR ≤0.8. Logistic regression analyses were performed to evaluate the association among functionally significant CAS, carotid ultrasound features and clinical parameters. A receiver operating characteristic (ROC) curve was developed to assess the capability of carotid ultrasound to diagnose functionally significant CAS.
Results: Patients with functionally significant CAS (QFR ≤0.8) had greater IMT, carotid bifurcation IAD and internal carotid artery-IAD, compared to patients with non-functionally significant CAS, with P values of <0.001, 0.015, and 0.011, respectively. The presence of carotid plaque was significantly higher in the functionally significant CAS group (95.2%) compared to the non-functionally significant CAS group (60%), with a P value of <0.001. In multivariable logistic regression analysis, maximum plaque height (MPH) (OR: 1.777, P=0.018) was associated with functionally significant CAS in patients with coronary artery disease. ROC curves showed plaque area to be superior to IMT, MPH and plaque length in identifying functionally significant CAS. The cutoff value of the plaque area was 9.07, and the sensitivity and specificity were 85.7% and 70.0%.
Conclusions: Carotid artery properties measured by carotid ultrasound were associated with functionally significant CAS. Plaque area is the most clinically useful parameter for detecting functionally significant CAS compared to IMT, MPH, and plaque length.
{"title":"Association between carotid ultrasound features and the detection of functionally significant coronary artery stenosis: a prospective study based on quantitative flow ratio.","authors":"Jili Long, Jingru Lin, Jia Tao, Qinglong Meng, Bing Zhang, Yanjin Tian, Mengyi Liu, Hao Wang","doi":"10.21037/qims-24-1528","DOIUrl":"10.21037/qims-24-1528","url":null,"abstract":"<p><strong>Background: </strong>Carotid ultrasound is a helpful approach for classifying cardiovascular risk. Quantitative flow ratio (QFR) is used to evaluate functionally significant coronary artery stenosis (CAS). The aim of this prospective study was to investigate the correlation between carotid artery features from carotid ultrasound and functionally significant CAS. Furthermore, this study aimed to evaluate the diagnostic performance of carotid ultrasound in diagnosing functional CAS.</p><p><strong>Methods: </strong>Carotid ultrasound was performed in 82 patients with suspicious coronary artery disease, measuring carotid intima-media thickness (IMT), internal artery diameter (IAD), and carotid plaques. QFR values were measured in all patients, and functionally significant CAS was defined as QFR ≤0.8. Forty patients (48.8%) had non-functionally significant CAS with QFR >0.8, while 42 patients (51.2%) had functionally significant CAS with QFR ≤0.8. Logistic regression analyses were performed to evaluate the association among functionally significant CAS, carotid ultrasound features and clinical parameters. A receiver operating characteristic (ROC) curve was developed to assess the capability of carotid ultrasound to diagnose functionally significant CAS.</p><p><strong>Results: </strong>Patients with functionally significant CAS (QFR ≤0.8) had greater IMT, carotid bifurcation IAD and internal carotid artery-IAD, compared to patients with non-functionally significant CAS, with P values of <0.001, 0.015, and 0.011, respectively. The presence of carotid plaque was significantly higher in the functionally significant CAS group (95.2%) compared to the non-functionally significant CAS group (60%), with a P value of <0.001. In multivariable logistic regression analysis, maximum plaque height (MPH) (OR: 1.777, P=0.018) was associated with functionally significant CAS in patients with coronary artery disease. ROC curves showed plaque area to be superior to IMT, MPH and plaque length in identifying functionally significant CAS. The cutoff value of the plaque area was 9.07, and the sensitivity and specificity were 85.7% and 70.0%.</p><p><strong>Conclusions: </strong>Carotid artery properties measured by carotid ultrasound were associated with functionally significant CAS. Plaque area is the most clinically useful parameter for detecting functionally significant CAS compared to IMT, MPH, and plaque length.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"553-562"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744129/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016266","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}
Pub Date : 2025-01-02Epub Date: 2024-12-17DOI: 10.21037/qims-2024-2568
Yì Xiáng J Wáng, James F Griffith, Jason C S Leung, Timothy C Y Kwok
Background: How different gender-specific bone mineral density cutpoint T-scores are associated with different hip fragility fracture (FFx) prediction sensitivity has not been well studied. This article presents an updated analysis of hip FFx prediction among older people by a dual-energy X-ray absorptiometry (DXA) measure, using literature results and our own Chinese data.
Methods: We systematically searched literature reports on DXA T-score results measured at the timepoint of a hip FFx. With osteoporotic fractures in women (MsOS) and in men (MrOS) Hong Kong studies, at baseline 2,000 Chinese women (mean: 72.5 years) and 2,000 Chinese men (mean: 72.3 years) were recruited. Female participants were followed up for 8.8±1.5 years, and 69 FFx were recorded. Male participants were followed up for 9.9±2.8 years, and 63 hip FFx were recorded.
Results: Ten articles published femoral neck (FN) and/or total hip (TH) T-score at the timepoint of a hip FFx with separated females' or males' T-score data. We estimated that, if a DXA exam were taken shortly before the FFx accident, females' FN, females' TH, males' FN, or males' TH T-scores on average predicted 66.9%, 70.4%, 66.5%, and 67.8% of the hip FFx. For the MsOS and MrOS Hong Kong studies, a combination of baseline FN and TH T-score predicted >50% of the cases with a follow-up hip FFx. A combination of baseline FN T-score, TH T-score, lumbar spine T-score, and spine fracture-like deformity assessment predicted 68.1% of the female cases with a follow-up hip FFx, and 63.4% of the male cases with a follow-up hip FFx.
Conclusions: If a DXA scan is regularly performed, approximately 70% of the hip FFx incidents can be predicted for older women and men.
{"title":"Majority of hip fragility fractures among older people can be predicted by a DXA examination: an updated analysis of literature results and empirical Chinese data with a focus on the validation of the newly proposed osteofrailia criterion for men.","authors":"Yì Xiáng J Wáng, James F Griffith, Jason C S Leung, Timothy C Y Kwok","doi":"10.21037/qims-2024-2568","DOIUrl":"10.21037/qims-2024-2568","url":null,"abstract":"<p><strong>Background: </strong>How different gender-specific bone mineral density cutpoint T-scores are associated with different hip fragility fracture (FFx) prediction sensitivity has not been well studied. This article presents an updated analysis of hip FFx prediction among older people by a dual-energy X-ray absorptiometry (DXA) measure, using literature results and our own Chinese data.</p><p><strong>Methods: </strong>We systematically searched literature reports on DXA T-score results measured at the timepoint of a hip FFx. With osteoporotic fractures in women (MsOS) and in men (MrOS) Hong Kong studies, at baseline 2,000 Chinese women (mean: 72.5 years) and 2,000 Chinese men (mean: 72.3 years) were recruited. Female participants were followed up for 8.8±1.5 years, and 69 FFx were recorded. Male participants were followed up for 9.9±2.8 years, and 63 hip FFx were recorded.</p><p><strong>Results: </strong>Ten articles published femoral neck (FN) and/or total hip (TH) T-score at the timepoint of a hip FFx with separated females' or males' T-score data. We estimated that, if a DXA exam were taken shortly before the FFx accident, females' FN, females' TH, males' FN, or males' TH T-scores on average predicted 66.9%, 70.4%, 66.5%, and 67.8% of the hip FFx. For the MsOS and MrOS Hong Kong studies, a combination of baseline FN and TH T-score predicted >50% of the cases with a follow-up hip FFx. A combination of baseline FN T-score, TH T-score, lumbar spine T-score, and spine fracture-like deformity assessment predicted 68.1% of the female cases with a follow-up hip FFx, and 63.4% of the male cases with a follow-up hip FFx.</p><p><strong>Conclusions: </strong>If a DXA scan is regularly performed, approximately 70% of the hip FFx incidents can be predicted for older women and men.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 1","pages":"473-485"},"PeriodicalIF":2.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016324","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}
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