OBJECTIVECarpal Tunnel Syndrome (CTS) is a prevalent neuropathy where accurate diagnosis is crucial for effective treatment planning. This study introduces a novel approach for CTS grading using ultrasound, specifically through the analysis of the cross-sectional area (CSA) and shear wave elastography (SWE) of the median nerve in various wrist positions.METHODSOur research involved subjects from outpatient clinics, diagnosed with CTS through Nerve Conduction Studies (NCS), and a control group of healthy individuals. High-frequency ultrasound and SWE measurements were conducted in three wrist positions: straight, 45° extension, and 45° flexion.RESULTSThe key findings revealed significant differences in median nerve CSA and SWE values between the CTS and control groups across all wrist positions, with notable variances in SWE values correlating with wrist positioning. SWE demonstrated enhanced sensitivity and specificity in distinguishing between mild, moderate, and severe CTS, especially at 45° wrist flexion. In contrast, CSA measurements were limited in differentiating between the varying severity stages of CTS.CONCLUSIONSThe study concludes that SWE, particularly at 45° wrist flexion, provides a more precise diagnostic benchmark for CTS severity grading than CSA. This advancement in non-invasive diagnostic methodology not only aids in accurate CTS grading but also has significant implications in formulating tailored treatment strategies, potentially reducing the reliance on more invasive diagnostic methods like NCS.ADVANCEMENT IN KNOWLEDGEThis study marks a significant advancement in the ultrasound diagnosis of CTS. It particularly highlights the importance of applying SWE technology across various wrist joint angles, offering a new diagnostic benchmark. This discovery provides data support and additional insights for achieving an early consensus on ultrasound-based grading diagnosis of CTS.
{"title":"Ultrasound-Based Grading of Carpal Tunnel Syndrome: A Comparative Study of Cross-Sectional Area and Shear Wave Elastography at Different Wrist Joint Angles.","authors":"Qijiu Zou,Xiaoli Guo,Xuejun Ni,Xiaoyang Chen,Cheng Xu,Yifei Yin,Chen Huang","doi":"10.1093/bjr/tqae189","DOIUrl":"https://doi.org/10.1093/bjr/tqae189","url":null,"abstract":"OBJECTIVECarpal Tunnel Syndrome (CTS) is a prevalent neuropathy where accurate diagnosis is crucial for effective treatment planning. This study introduces a novel approach for CTS grading using ultrasound, specifically through the analysis of the cross-sectional area (CSA) and shear wave elastography (SWE) of the median nerve in various wrist positions.METHODSOur research involved subjects from outpatient clinics, diagnosed with CTS through Nerve Conduction Studies (NCS), and a control group of healthy individuals. High-frequency ultrasound and SWE measurements were conducted in three wrist positions: straight, 45° extension, and 45° flexion.RESULTSThe key findings revealed significant differences in median nerve CSA and SWE values between the CTS and control groups across all wrist positions, with notable variances in SWE values correlating with wrist positioning. SWE demonstrated enhanced sensitivity and specificity in distinguishing between mild, moderate, and severe CTS, especially at 45° wrist flexion. In contrast, CSA measurements were limited in differentiating between the varying severity stages of CTS.CONCLUSIONSThe study concludes that SWE, particularly at 45° wrist flexion, provides a more precise diagnostic benchmark for CTS severity grading than CSA. This advancement in non-invasive diagnostic methodology not only aids in accurate CTS grading but also has significant implications in formulating tailored treatment strategies, potentially reducing the reliance on more invasive diagnostic methods like NCS.ADVANCEMENT IN KNOWLEDGEThis study marks a significant advancement in the ultrasound diagnosis of CTS. It particularly highlights the importance of applying SWE technology across various wrist joint angles, offering a new diagnostic benchmark. This discovery provides data support and additional insights for achieving an early consensus on ultrasound-based grading diagnosis of CTS.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OBJECTIVESTo evaluate the performance of ultrasound-based deep learning (DL) models in distinguishing breast phyllodes tumors (PTs) from fibroadenomas (FAs) and their clinical utility in assisting radiologists with varying diagnostic experiences.METHODSWe retrospectively collected 1180 ultrasound images from 539 patients (247 PTs and 292 FAs). Five DL network models with different structures were trained and validated using nodule regions annotated by radiologists on breast ultrasound images. DL models were trained using the methods of transfer learning and 3-fold cross-validation. The model demonstrated the best evaluation index in the 3-fold cross-validation was selected for comparison with radiologists' diagnostic decisions. Two-round reader studies were conducted to investigate the value of DL model in assisting six radiologists with different levels of experience.RESULTSUpon testing, Xception model demonstrated the best diagnostic performance (AUC: 0.87, 95%CI: 0.81-0.92), outperforming all radiologists (all p < 0.05). Additionally, the DL model enhanced the diagnostic performance of radiologists. Accuracy demonstrated improvements of 4%, 4%, and 3% for senior, intermediate, and junior radiologists, respectively.CONCLUSIONSThe DL models showed superior predictive abilities compared to experienced radiologists in distinguishing breast PTs from FAs. Utilizing the model led to improved efficiency and diagnostic performance for radiologists with different levels of experience (6-25 years of work).ADVANCES IN KNOWLEDGEWe developed and validated a DL model based on the largest available dataset to assist in diagnosing PTs. This model has the potential to allow radiologists to discriminate two types of breast tumors which are challenging to identify with precision and accuracy, and subsequently to make more informed decisions about surgical plans.
目的评估基于超声的深度学习（DL）模型在区分乳腺植物瘤（PT）和纤维腺瘤（FA）方面的性能，以及它们在协助具有不同诊断经验的放射科医生方面的临床实用性。我们利用放射科医生在乳腺超声图像上标注的结节区域，训练并验证了五个具有不同结构的 DL 网络模型。DL 模型采用迁移学习和 3 倍交叉验证的方法进行训练。在 3 倍交叉验证中显示出最佳评价指标的模型被选中与放射科医生的诊断决定进行比较。结果经测试，Xception 模型表现出最佳诊断性能（AUC：0.87，95%CI：0.81-0.92），优于所有放射科医生（所有 p < 0.05）。此外，DL 模型还提高了放射科医生的诊断性能。结论与经验丰富的放射科医生相比，DL 模型在区分乳腺 PT 和 FA 方面显示出更出色的预测能力。利用该模型提高了具有不同经验水平（工作 6-25 年）的放射科医生的效率和诊断效果。该模型有可能让放射科医生分辨出两种类型的乳腺肿瘤，而这两种类型的肿瘤在精确度和准确性上都很难鉴别，因此放射科医生有可能做出更明智的手术方案决策。
{"title":"Deep learning-assisted distinguishing breast phyllodes tumors from fibroadenomas based on ultrasound images: a diagnostic study.","authors":"Yuqi Yan,Yuanzhen Liu,Jincao Yao,Lin Sui,Chen Chen,Tian Jiang,Xiaofang Liu,Yifan Wang,Di Ou,Jing Chen,Hui Wang,Lina Feng,Qianmeng Pan,Ying Su,Yukai Wang,Liping Wang,Lingyan Zhou,Dong Xu","doi":"10.1093/bjr/tqae147","DOIUrl":"https://doi.org/10.1093/bjr/tqae147","url":null,"abstract":"OBJECTIVESTo evaluate the performance of ultrasound-based deep learning (DL) models in distinguishing breast phyllodes tumors (PTs) from fibroadenomas (FAs) and their clinical utility in assisting radiologists with varying diagnostic experiences.METHODSWe retrospectively collected 1180 ultrasound images from 539 patients (247 PTs and 292 FAs). Five DL network models with different structures were trained and validated using nodule regions annotated by radiologists on breast ultrasound images. DL models were trained using the methods of transfer learning and 3-fold cross-validation. The model demonstrated the best evaluation index in the 3-fold cross-validation was selected for comparison with radiologists' diagnostic decisions. Two-round reader studies were conducted to investigate the value of DL model in assisting six radiologists with different levels of experience.RESULTSUpon testing, Xception model demonstrated the best diagnostic performance (AUC: 0.87, 95%CI: 0.81-0.92), outperforming all radiologists (all p < 0.05). Additionally, the DL model enhanced the diagnostic performance of radiologists. Accuracy demonstrated improvements of 4%, 4%, and 3% for senior, intermediate, and junior radiologists, respectively.CONCLUSIONSThe DL models showed superior predictive abilities compared to experienced radiologists in distinguishing breast PTs from FAs. Utilizing the model led to improved efficiency and diagnostic performance for radiologists with different levels of experience (6-25 years of work).ADVANCES IN KNOWLEDGEWe developed and validated a DL model based on the largest available dataset to assist in diagnosing PTs. This model has the potential to allow radiologists to discriminate two types of breast tumors which are challenging to identify with precision and accuracy, and subsequently to make more informed decisions about surgical plans.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David P J van Dijk,Leroy F Volmer,Ralph Brecheisen,Bibi Martens,Ross D Dolan,Adam S Bryce,David K Chang,Donald C McMillan,Jan H M B Stoot,Malcolm A West,Sander S Rensen,Andre Dekker,Leonard Wee,Steven W M Olde Damink,
BACKGROUNDBody composition assessment using computed tomography (CT) images at the L3-level is increasingly applied in cancer research. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.METHODSExpert-drawn segmentations of visceral and subcutaneous adipose tissue (VAT/SAT) and skeletal muscle (SM) of L3-CT-images of 3,187 patients undergoing abdominal surgery were used to train a DLNN. The external validation cohort was comprised of 2,535 patients with abdominal cancer. DLNN performance was evaluated with (geometric) Dice Similarity (DS) and Lin's Concordance Correlation Coefficient.RESULTSThere was a strong concordance between automatic and manual segmentations with median DS for SM, VAT, and SAT of 0.97 (interquartile range, IQR: 0.95-0.98), 0.98 (IQR: 0.95-0.98), and 0.95 (IQR: 0.92-0.97), respectively. Concordance correlations were excellent: SM 0.964 (0.959-0.968), VAT 0.998 (0.998-0.998), and SAT 0.992 (0.991-0.993). Bland-Altman metrics indicated only small and clinically insignificant systematic offsets; SM radiodensity: 0.23 hounsfield units (0.5%), SM: 1.26 cm2.m-2 (2.8%), VAT: -1.02 cm2.m-2 (1.7%), and SAT: 3.24 cm2.m-2 (4.6%).CONCLUSIONA robustly-performing and independently externally validated DLNN for automated body composition analysis was developed.ADVANCES IN KNOWLEDGECT-based body composition analysis is highly prognostic for long-term overall survival in oncology. This DLNN was succesfully trained and externally validated on several large patient cohorts and will therefore enable large scale population studies and implementation of body composition analysis into clinical practice.
{"title":"External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal computed tomography images.","authors":"David P J van Dijk,Leroy F Volmer,Ralph Brecheisen,Bibi Martens,Ross D Dolan,Adam S Bryce,David K Chang,Donald C McMillan,Jan H M B Stoot,Malcolm A West,Sander S Rensen,Andre Dekker,Leonard Wee,Steven W M Olde Damink,","doi":"10.1093/bjr/tqae191","DOIUrl":"https://doi.org/10.1093/bjr/tqae191","url":null,"abstract":"BACKGROUNDBody composition assessment using computed tomography (CT) images at the L3-level is increasingly applied in cancer research. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.METHODSExpert-drawn segmentations of visceral and subcutaneous adipose tissue (VAT/SAT) and skeletal muscle (SM) of L3-CT-images of 3,187 patients undergoing abdominal surgery were used to train a DLNN. The external validation cohort was comprised of 2,535 patients with abdominal cancer. DLNN performance was evaluated with (geometric) Dice Similarity (DS) and Lin's Concordance Correlation Coefficient.RESULTSThere was a strong concordance between automatic and manual segmentations with median DS for SM, VAT, and SAT of 0.97 (interquartile range, IQR: 0.95-0.98), 0.98 (IQR: 0.95-0.98), and 0.95 (IQR: 0.92-0.97), respectively. Concordance correlations were excellent: SM 0.964 (0.959-0.968), VAT 0.998 (0.998-0.998), and SAT 0.992 (0.991-0.993). Bland-Altman metrics indicated only small and clinically insignificant systematic offsets; SM radiodensity: 0.23 hounsfield units (0.5%), SM: 1.26 cm2.m-2 (2.8%), VAT: -1.02 cm2.m-2 (1.7%), and SAT: 3.24 cm2.m-2 (4.6%).CONCLUSIONA robustly-performing and independently externally validated DLNN for automated body composition analysis was developed.ADVANCES IN KNOWLEDGECT-based body composition analysis is highly prognostic for long-term overall survival in oncology. This DLNN was succesfully trained and externally validated on several large patient cohorts and will therefore enable large scale population studies and implementation of body composition analysis into clinical practice.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Colien Hazelaar,Richard Canters,Kirsten Kremer,Indra Lubken,Femke Vaassen,Jeroen Buijsen,Maaike Berbée,Wouter van Elmpt
OBJECTIVETo evaluate two years of clinical experience with markerless breath-hold liver stereotactic radiotherapy (SBRT) using non-invasive nasal high flow therapy (NHFT) for breath-hold prolonging and surface guidance (SGRT) for monitoring.METHODSHeated and humidified air was administered via a nasal cannula (40 L/min, 80% oxygen, 34 °C). Patients performed voluntary inspiration breath-holds with visual feedback. After a training session, 4-5 breath-hold CT scans were acquired to delineate an internal target volume (ITV) accounting for inter- and intra-breath-hold variations. Patients were treated in 3-8 fractions (7.5-20 Gy/fraction) using SGRT-controlled beam-hold. Patient setup was performed using SGRT and CBCT imaging. A post-treatment CBCT was acquired for evaluation purposes.RESULTSFifteen patients started the training session and received treatment, of whom 10 completed treatment in breath-hold. Half of all 60-second CBCT scans were acquired during a single breath-hold. The average maximum breath-hold duration during treatment ranged from 47-108 s. Breath-hold ITV was on average 6.5 cm³/30% larger (range: 1.1-23.9 cm³/5-95%) than the largest GTV. Free-breathing ITV based on 4DCT scans was on average 16.9 cm³/47% larger (range: -2.3-58.7 cm3/-16-157%) than the breath-hold ITV. The average 3D displacement vector of the area around PTV for the post-treatment CBCT scans was 5.0 mm (range: 0.7-12.9 mm).CONCLUSIONSLiver SBRT in breath-hold using NHFT and SGRT is feasible for the majority of patients. An ITV reduction was observed compared to free-breathing treatments. To further decrease the PTV, internal anatomy-based breath-hold monitoring is desired.ADVANCES IN KNOWLEDGENon-invasive NHFT allows for prolonged breath-holding during surface-guided liver SBRT.
{"title":"Clinical implementation and evaluation of stereotactic liver radiotherapy in inspiration breath-hold using nasal high flow therapy and surface guidance.","authors":"Colien Hazelaar,Richard Canters,Kirsten Kremer,Indra Lubken,Femke Vaassen,Jeroen Buijsen,Maaike Berbée,Wouter van Elmpt","doi":"10.1093/bjr/tqae177","DOIUrl":"https://doi.org/10.1093/bjr/tqae177","url":null,"abstract":"OBJECTIVETo evaluate two years of clinical experience with markerless breath-hold liver stereotactic radiotherapy (SBRT) using non-invasive nasal high flow therapy (NHFT) for breath-hold prolonging and surface guidance (SGRT) for monitoring.METHODSHeated and humidified air was administered via a nasal cannula (40 L/min, 80% oxygen, 34 °C). Patients performed voluntary inspiration breath-holds with visual feedback. After a training session, 4-5 breath-hold CT scans were acquired to delineate an internal target volume (ITV) accounting for inter- and intra-breath-hold variations. Patients were treated in 3-8 fractions (7.5-20 Gy/fraction) using SGRT-controlled beam-hold. Patient setup was performed using SGRT and CBCT imaging. A post-treatment CBCT was acquired for evaluation purposes.RESULTSFifteen patients started the training session and received treatment, of whom 10 completed treatment in breath-hold. Half of all 60-second CBCT scans were acquired during a single breath-hold. The average maximum breath-hold duration during treatment ranged from 47-108 s. Breath-hold ITV was on average 6.5 cm³/30% larger (range: 1.1-23.9 cm³/5-95%) than the largest GTV. Free-breathing ITV based on 4DCT scans was on average 16.9 cm³/47% larger (range: -2.3-58.7 cm3/-16-157%) than the breath-hold ITV. The average 3D displacement vector of the area around PTV for the post-treatment CBCT scans was 5.0 mm (range: 0.7-12.9 mm).CONCLUSIONSLiver SBRT in breath-hold using NHFT and SGRT is feasible for the majority of patients. An ITV reduction was observed compared to free-breathing treatments. To further decrease the PTV, internal anatomy-based breath-hold monitoring is desired.ADVANCES IN KNOWLEDGENon-invasive NHFT allows for prolonged breath-holding during surface-guided liver SBRT.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leyla Ebrahimpour,Yannick Lemaréchal,Sevinj Yolchuyeva,Michèle Orain,Fabien Lamaze,Arnaud Driussi,François Coulombe,Philippe Joubert,Philippe Després,Venkata S K Manem
OBJECTIVEThe influence of radiomics pipeline and the grey-level discretization on the discovery of immunotherapy biomarkers is still a poorly understood topic. This study is aimed at identifying robust features by comparing two radiomics libraries and their association with clinical outcomes in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs).METHODSA retrospective cohort of 164 NSCLC patients administered with ICIs was used in this study. Radiomic features were extracted from the pre-treatment CT scans. Univariate models were used to assess the association of radiomics features with progression free survival (PFS), PD-L1 and CD8 cell counts. We also examined the impact of gray-level discretization on feature robustness by evaluating the association of features with clinical endpoints.RESULTSWe extracted 1224, 441 radiomic features using Pyradiomics and RaCat, respectively, out of which 75 were common between them. We showed that the directionality of association between features and clinical endpoints is specific to the radiomic library used. Overall, more Pyradiomics and RaCat features were statistically associated with PFS, and PD-L1, respectively. We found intensity-based features to be more agnostic to the gray-level discretization parameters. Among features that showed significant correlation with PFS with varying gray-level discretization parameters, 45% were intensity-based, compared to PD-L1, and CD8.CONCLUSIONSThis study highlights the heterogeneity of radiomics libraries and the gray level discretization parameters that will impact the feature selection and predictive model development. Importantly, our work highlights the significance of selecting features that are agnostic to radiomics libraries for clinical translation.ADVANCES IN KNOWLEDGEOur study emphasizes the need to select stable CT-derived handcrafted features to build immunotherapy biomarkers, which is a necessary precursor for multi-institutional validation of imaging biomarkers.
{"title":"The impact of radiomics libraries and gray level discretization on the discovery of immunotherapy biomarkers in NSCLC patients.","authors":"Leyla Ebrahimpour,Yannick Lemaréchal,Sevinj Yolchuyeva,Michèle Orain,Fabien Lamaze,Arnaud Driussi,François Coulombe,Philippe Joubert,Philippe Després,Venkata S K Manem","doi":"10.1093/bjr/tqae187","DOIUrl":"https://doi.org/10.1093/bjr/tqae187","url":null,"abstract":"OBJECTIVEThe influence of radiomics pipeline and the grey-level discretization on the discovery of immunotherapy biomarkers is still a poorly understood topic. This study is aimed at identifying robust features by comparing two radiomics libraries and their association with clinical outcomes in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs).METHODSA retrospective cohort of 164 NSCLC patients administered with ICIs was used in this study. Radiomic features were extracted from the pre-treatment CT scans. Univariate models were used to assess the association of radiomics features with progression free survival (PFS), PD-L1 and CD8 cell counts. We also examined the impact of gray-level discretization on feature robustness by evaluating the association of features with clinical endpoints.RESULTSWe extracted 1224, 441 radiomic features using Pyradiomics and RaCat, respectively, out of which 75 were common between them. We showed that the directionality of association between features and clinical endpoints is specific to the radiomic library used. Overall, more Pyradiomics and RaCat features were statistically associated with PFS, and PD-L1, respectively. We found intensity-based features to be more agnostic to the gray-level discretization parameters. Among features that showed significant correlation with PFS with varying gray-level discretization parameters, 45% were intensity-based, compared to PD-L1, and CD8.CONCLUSIONSThis study highlights the heterogeneity of radiomics libraries and the gray level discretization parameters that will impact the feature selection and predictive model development. Importantly, our work highlights the significance of selecting features that are agnostic to radiomics libraries for clinical translation.ADVANCES IN KNOWLEDGEOur study emphasizes the need to select stable CT-derived handcrafted features to build immunotherapy biomarkers, which is a necessary precursor for multi-institutional validation of imaging biomarkers.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"190 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OBJECTIVEThe study aimed to investigate the correlation between fat fraction (FF), R2* value of vertebrae based on IDEAL-IQ sequence and bone mineral density (BMD) based on QCT, and their diagnostic value for low BMD and osteoporosis.MATERIALS AND METHODSSubgroups were divided according to different gender, age, BMI and bone mass to compare the differences in parametric variables. One-way ANOVA, independent samples t-test, correlation coefficient analysis, linear regression analysis and ROC curve analysis were performed.RESULTSSignificant differences were found in FF among different bone mass groups, and between different gender and age groups. While R2* only had significant difference between different gender groups and males with different age. BMD was significantly negatively correlated with FF, especially in women, and FF significantly negatively affected BMD after controlling for gender, age and BMI. There was mildly positive correlation between BMD and R2* in men, and R2* significantly positively influenced BMD controlling for the confounders. In addition, FF was positively correlated with age, whereas R2* was negatively correlated with age in men. FF had high diagnostic efficacy for low bone mass and osteoporosis, while R2* alone was weakly diagnostic.CONCLUSIONVertebral FF can be served as a potential important imaging biomarker for assessing low BMD and osteoporosis, and R2* of males can be utilized as an complementary parameter for evaluating osteoporosis.ADVANCES IN KNOWLEDGEThe IDEAL-IQ sequence has the potential to be used as an accessory examination in the diagnosis of osteoporosis, assessment of treatment efficacy and prediction of fracture risk.
{"title":"Assessing fat fraction and R2* value of lumbar spine based on MRI as a marker of bone mineral density.","authors":"Feng Zhou,Bo Sheng,Furong Lv","doi":"10.1093/bjr/tqae192","DOIUrl":"https://doi.org/10.1093/bjr/tqae192","url":null,"abstract":"OBJECTIVEThe study aimed to investigate the correlation between fat fraction (FF), R2* value of vertebrae based on IDEAL-IQ sequence and bone mineral density (BMD) based on QCT, and their diagnostic value for low BMD and osteoporosis.MATERIALS AND METHODSSubgroups were divided according to different gender, age, BMI and bone mass to compare the differences in parametric variables. One-way ANOVA, independent samples t-test, correlation coefficient analysis, linear regression analysis and ROC curve analysis were performed.RESULTSSignificant differences were found in FF among different bone mass groups, and between different gender and age groups. While R2* only had significant difference between different gender groups and males with different age. BMD was significantly negatively correlated with FF, especially in women, and FF significantly negatively affected BMD after controlling for gender, age and BMI. There was mildly positive correlation between BMD and R2* in men, and R2* significantly positively influenced BMD controlling for the confounders. In addition, FF was positively correlated with age, whereas R2* was negatively correlated with age in men. FF had high diagnostic efficacy for low bone mass and osteoporosis, while R2* alone was weakly diagnostic.CONCLUSIONVertebral FF can be served as a potential important imaging biomarker for assessing low BMD and osteoporosis, and R2* of males can be utilized as an complementary parameter for evaluating osteoporosis.ADVANCES IN KNOWLEDGEThe IDEAL-IQ sequence has the potential to be used as an accessory examination in the diagnosis of osteoporosis, assessment of treatment efficacy and prediction of fracture risk.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mihir M Rao,Jim Zhong,Usman Mahay,Philip Haslam,Jai Patel
OBJECTIVESThe development of technical skills in peripheral and aortic endovascular intervention is an essential part of interventional radiology (IR) training. Access to endovascular training remains contentious, with IR and vascular surgery (VS) trainees competing for opportunities. The Collaborative Peripheral and Aortic Endovascular Training Survey (CPAETS) aimed to evaluate IR trainees' experiences, expectations, and barriers to endovascular training.METHODSCPAETS was a joint survey between the British Society of Interventional Radiology and the Rouleaux Club (UK Vascular Trainees' Association), open for 12 weeks and distributed to UK-based IR and VS trainees. This article focuses on IR trainee responses.RESULTSThirty-two responses were received from IR trainees across England, Scotland and Wales. Overall, 59% of respondents were satisfied with their endovascular training. IR trainees reported less regular hands-on experience of aortic endovascular procedures (50%) compared to peripheral endovascular procedures (93%). Consequently fewer trainees (65%) felt confident in achieving the necessary aortic endovascular competencies by the end of their training, compared to peripheral procedures (89%).CONCLUSIONLimited exposure to aortic endovascular procedures resulted in reduced confidence levels in performing aortic intervention as compared to peripheral procedures. Potential solutions to bridge some of these IR training gaps include greater pre-operative and post-operative presence, the use of simulators and IR fellowships to ensure adequate training opportunities.ADVANCES IN KNOWLEDGEThis article provides a snapshot of the current gaps in IR endovascular training in the UK, with insight into solutions that can enable trainees to develop clinical and technical competencies required for IR consultant practice.
目的培养外周和主动脉血管内介入治疗的技术技能是介入放射学（IR）培训的重要组成部分。由于介入放射学和血管外科（VS）受训人员都在争夺培训机会，因此获得血管内介入培训的机会仍存在争议。外周和主动脉血管内培训合作调查（CPAETS）旨在评估介入放射学受训者在血管内培训方面的经历、期望和障碍。METHODSCPAETS是英国介入放射学会和Rouleaux俱乐部（英国血管受训者协会）联合开展的一项调查，为期12周，调查对象为英国的介入放射学和血管外科受训者。结果：共收到 32 份来自英格兰、苏格兰和威尔士的 IR 实习生的回复。总体而言，59%的受访者对血管内培训表示满意。与外周血管内手术（93%）相比，主动脉血管内手术（50%）的定期实践经验较少。因此，与外周血管手术（89%）相比，在培训结束时有信心达到必要的主动脉血管内手术能力的学员较少（65%）。弥补主动脉内介入培训差距的潜在解决方案包括加强术前和术后培训、使用模拟器和主动脉内介入研究员计划以确保充足的培训机会。
{"title":"A National Survey of Interventional Radiology Trainees on Peripheral and Aortic Endovascular Training.","authors":"Mihir M Rao,Jim Zhong,Usman Mahay,Philip Haslam,Jai Patel","doi":"10.1093/bjr/tqae186","DOIUrl":"https://doi.org/10.1093/bjr/tqae186","url":null,"abstract":"OBJECTIVESThe development of technical skills in peripheral and aortic endovascular intervention is an essential part of interventional radiology (IR) training. Access to endovascular training remains contentious, with IR and vascular surgery (VS) trainees competing for opportunities. The Collaborative Peripheral and Aortic Endovascular Training Survey (CPAETS) aimed to evaluate IR trainees' experiences, expectations, and barriers to endovascular training.METHODSCPAETS was a joint survey between the British Society of Interventional Radiology and the Rouleaux Club (UK Vascular Trainees' Association), open for 12 weeks and distributed to UK-based IR and VS trainees. This article focuses on IR trainee responses.RESULTSThirty-two responses were received from IR trainees across England, Scotland and Wales. Overall, 59% of respondents were satisfied with their endovascular training. IR trainees reported less regular hands-on experience of aortic endovascular procedures (50%) compared to peripheral endovascular procedures (93%). Consequently fewer trainees (65%) felt confident in achieving the necessary aortic endovascular competencies by the end of their training, compared to peripheral procedures (89%).CONCLUSIONLimited exposure to aortic endovascular procedures resulted in reduced confidence levels in performing aortic intervention as compared to peripheral procedures. Potential solutions to bridge some of these IR training gaps include greater pre-operative and post-operative presence, the use of simulators and IR fellowships to ensure adequate training opportunities.ADVANCES IN KNOWLEDGEThis article provides a snapshot of the current gaps in IR endovascular training in the UK, with insight into solutions that can enable trainees to develop clinical and technical competencies required for IR consultant practice.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OBJECTIVETo investigate the failure patterns based on precision radiation treatment and to determine the predictive factors of treatment failure for sinonasal squamous cell carcinoma (SNSCC) patients.MATERIALSThis was a retrospective study that included 214 cases of treatment failure from 441 consecutive patients. Two experienced radiation oncologists evaluated the tumor volume of cases with local recurrence. The 5-year overall survival (OS), progression-free survival rates (PFS), and distant-metastasis-free survival (DMFS) were estimated. Investigations were performed on the factors that predicted local failure or distant metastasis.RESULTS140 (31.7%) patients developed local recurrence, 24 (5.4%) experienced regional failure, and 65 (14.7%) underwent distant metastasis. In-field, marginal, and out-of-field failures occurred in 55.7% (78/140), 33.6% (47/140), and 10.7% (15/140) of patients with local recurrence, respectively. In logistic regression analysis, factors statistically significant for total local failure included treatment mode (p < 0.01), chemotherapy (p < 0.01), and surgical margins (p < 0.01). Primary tumors with poor differentiation (p = 0.018) and R2 resection margin (p = 0.009) were more prone to develop distant failure. The 5-year OS, PFS, and DMFS rates were 57.8%, 52.0%, and 56.7% for the whole cohort. In univariate and multivariate analysis, the skull base involvement was an independent predictor for poorer OS and PFS; orbital invasion was an independent predictor for poorer OS.CONCLUSIONSLocal recurrence and distant metastasis were the most common failure modes. Treatment mode, chemotherapy, and surgical margins were related to local recurrence. Poor differentiation and R2 resection margin were predictors for distant failure.ADVANCE IN KNOWLEDGELocal recurrence is the most common failure pattern in patients with sinonasal squamous cell carcinoma who accepted chemoradiotherapy, and marginal and out-of-field failures occurred in 44.3% of patients with local recurrence.
{"title":"Patterns of treatment failure in patients with sinonasal squamous cell carcinoma after chemoradiotherapy.","authors":"Li Wang,Jie Wang,Tian Wang,Yi Li,Xinmao Song","doi":"10.1093/bjr/tqae175","DOIUrl":"https://doi.org/10.1093/bjr/tqae175","url":null,"abstract":"OBJECTIVETo investigate the failure patterns based on precision radiation treatment and to determine the predictive factors of treatment failure for sinonasal squamous cell carcinoma (SNSCC) patients.MATERIALSThis was a retrospective study that included 214 cases of treatment failure from 441 consecutive patients. Two experienced radiation oncologists evaluated the tumor volume of cases with local recurrence. The 5-year overall survival (OS), progression-free survival rates (PFS), and distant-metastasis-free survival (DMFS) were estimated. Investigations were performed on the factors that predicted local failure or distant metastasis.RESULTS140 (31.7%) patients developed local recurrence, 24 (5.4%) experienced regional failure, and 65 (14.7%) underwent distant metastasis. In-field, marginal, and out-of-field failures occurred in 55.7% (78/140), 33.6% (47/140), and 10.7% (15/140) of patients with local recurrence, respectively. In logistic regression analysis, factors statistically significant for total local failure included treatment mode (p < 0.01), chemotherapy (p < 0.01), and surgical margins (p < 0.01). Primary tumors with poor differentiation (p = 0.018) and R2 resection margin (p = 0.009) were more prone to develop distant failure. The 5-year OS, PFS, and DMFS rates were 57.8%, 52.0%, and 56.7% for the whole cohort. In univariate and multivariate analysis, the skull base involvement was an independent predictor for poorer OS and PFS; orbital invasion was an independent predictor for poorer OS.CONCLUSIONSLocal recurrence and distant metastasis were the most common failure modes. Treatment mode, chemotherapy, and surgical margins were related to local recurrence. Poor differentiation and R2 resection margin were predictors for distant failure.ADVANCE IN KNOWLEDGELocal recurrence is the most common failure pattern in patients with sinonasal squamous cell carcinoma who accepted chemoradiotherapy, and marginal and out-of-field failures occurred in 44.3% of patients with local recurrence.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L S Ch'ng,A S Mahfudz,H Azman,M M Zainal Alam,E Saib,N S A Rosaland,M I Ahmad Sabri
INTRODUCTIONFluoroscopic guided procedures are a mainstay for Interventional Radiology (IR) procedures. Practice is needed for the novice to interpret fluoroscopic images and simultaneously perform the procedure hands-on as well as control the foot pedal to screen. We describe the development of a training simulation model which simulates the human kidney, ureter and bladder.METHODStereolithography (SLA) 3D Print technology using SLA resin and Anycubic SLA printer were employed. A plastic tubing was used to connect the 3D printed kidney and bladder as the ureter. This simulation model permits fluoroscopic guided filling of "pelvicalyceal system" with contrast as well as ureteric stenting, guidewire and drainage catheter manipulation. Effectiveness of the model to attain skills for nephrostomy exchange and ureteric stenting was obtained via questionnaire from trainees prior to and after utilising the model.RESULTThe 3D printing simulation model of the kidney, ureter and bladder system enable trainees to perform nephrostomy exchange, nephrostogram and antegrade stenting. Participants felt more confident to perform the procedures as they were more familiar with the procedure. Besides that, participants felt their wire and catheter manipulation skills have improved after using the simulation model.CONCLUSIONNeph-ex simulation model is safe and effective for hands-on training in improving proficiency of fluoroscopy-guided nephrostomy exchange and antegrade ureteric stenting.
简介透视引导手术是介入放射学（IR）手术的主流。新手需要练习如何解读透视图像，同时动手进行手术，以及控制脚踏板到屏幕。我们介绍了模拟人体肾脏、输尿管和膀胱的训练模拟模型的开发过程。方法采用立体光刻（SLA）3D 打印技术，使用 SLA 树脂和 Anycubic SLA 打印机。使用塑料管连接 3D 打印的肾脏和膀胱作为输尿管。该模拟模型允许在透视引导下用造影剂填充 "肾盂-膀胱系统"，以及操作输尿管支架、导丝和引流导管。结果肾脏、输尿管和膀胱系统的 3D 打印模拟模型使学员能够进行肾造口术、肾造影术和前路支架植入术。由于学员们对手术过程更加熟悉，因此他们在进行手术时更有信心。结论肾造口术模拟模型在提高透视引导下肾造口术交换和输尿管逆行支架置入术的熟练程度方面，是一种安全有效的实训方法。
{"title":"Neph-ex: A 3D Printed Interventional Radiology (IR) Training Tool for Nephrostomy Exchange.","authors":"L S Ch'ng,A S Mahfudz,H Azman,M M Zainal Alam,E Saib,N S A Rosaland,M I Ahmad Sabri","doi":"10.1093/bjr/tqae184","DOIUrl":"https://doi.org/10.1093/bjr/tqae184","url":null,"abstract":"INTRODUCTIONFluoroscopic guided procedures are a mainstay for Interventional Radiology (IR) procedures. Practice is needed for the novice to interpret fluoroscopic images and simultaneously perform the procedure hands-on as well as control the foot pedal to screen. We describe the development of a training simulation model which simulates the human kidney, ureter and bladder.METHODStereolithography (SLA) 3D Print technology using SLA resin and Anycubic SLA printer were employed. A plastic tubing was used to connect the 3D printed kidney and bladder as the ureter. This simulation model permits fluoroscopic guided filling of \"pelvicalyceal system\" with contrast as well as ureteric stenting, guidewire and drainage catheter manipulation. Effectiveness of the model to attain skills for nephrostomy exchange and ureteric stenting was obtained via questionnaire from trainees prior to and after utilising the model.RESULTThe 3D printing simulation model of the kidney, ureter and bladder system enable trainees to perform nephrostomy exchange, nephrostogram and antegrade stenting. Participants felt more confident to perform the procedures as they were more familiar with the procedure. Besides that, participants felt their wire and catheter manipulation skills have improved after using the simulation model.CONCLUSIONNeph-ex simulation model is safe and effective for hands-on training in improving proficiency of fluoroscopy-guided nephrostomy exchange and antegrade ureteric stenting.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mario Juliano, Naziya Samreen, Celin Chacko, Samantha L Heller
Current breast cancer screening relies on mammography, digital breast tomosynthesis and breast ultrasound. In select populations, breast MRI is also of great utility. However, multiple factors limit widespread use of breast MRI for screening. Efforts have been made to increase the availability of breast MRI for screening, in large part due to the increased cancer detection rate of breast MRI compared to mammography. Techniques include shortening standard breast MRI protocols with the potential for accommodating MRI screening in a higher number of patients. This review will explain the role of abbreviated breast MRI and ultrafast breast MRI in breast imaging, and detail how these approaches differ from standard dynamic contrast-enhanced breast MRI. In addition, limitations and advantages of these techniques will also be discussed.
目前的乳腺癌筛查主要依靠乳房 X 线照相术、数字乳腺断层扫描和乳腺超声波。在特定人群中，乳腺核磁共振成像也非常有用。然而，多种因素限制了乳腺磁共振成像在筛查中的广泛应用。人们一直在努力提高乳腺核磁共振成像筛查的可用性，这在很大程度上是由于乳腺核磁共振成像的癌症检出率比乳腺 X 线照相术更高。相关技术包括缩短标准的乳腺磁共振成像方案，以便为更多患者提供磁共振成像筛查。本综述将解释缩略乳腺 MRI 和超快乳腺 MRI 在乳腺成像中的作用，并详细说明这些方法与标准动态对比增强乳腺 MRI 的区别。此外，还将讨论这些技术的局限性和优势。
{"title":"Clinical role of abbreviated and ultrafast mri in breast imaging.","authors":"Mario Juliano, Naziya Samreen, Celin Chacko, Samantha L Heller","doi":"10.1093/bjr/tqae079","DOIUrl":"https://doi.org/10.1093/bjr/tqae079","url":null,"abstract":"Current breast cancer screening relies on mammography, digital breast tomosynthesis and breast ultrasound. In select populations, breast MRI is also of great utility. However, multiple factors limit widespread use of breast MRI for screening. Efforts have been made to increase the availability of breast MRI for screening, in large part due to the increased cancer detection rate of breast MRI compared to mammography. Techniques include shortening standard breast MRI protocols with the potential for accommodating MRI screening in a higher number of patients. This review will explain the role of abbreviated breast MRI and ultrafast breast MRI in breast imaging, and detail how these approaches differ from standard dynamic contrast-enhanced breast MRI. In addition, limitations and advantages of these techniques will also be discussed.","PeriodicalId":516851,"journal":{"name":"The British Journal of Radiology","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140812659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：