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Comparison between postcontrast thin-slice T1-weighted 2D spin echo and 3D T1-weighted SPACE sequences in the detection of brain metastases at 1.5 and 3 T Insights Imaging (IF 4.7) Pub Date : 2024-03-14 Josef Vymazal, Zuzana Ryznarova, Aaron M. Rulseh
Accurate detection of metastatic brain lesions (MBL) is critical due to advances in radiosurgery. We compared the results of three readers in detecting MBL using T1-weighted 2D spin echo (SE) and sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) sequences with whole-brain coverage at both 1.5 T and 3 T. Fifty-six patients evaluated for MBL were included
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Ultrasonic shear wave elastography predicts the quality of the residual tendon before the rotator cuff repair Insights Imaging (IF 4.7) Pub Date : 2024-03-14 Xianghui Chen, Siming Chen, Fei Zhang, Yaqiong Zhu, Dan Yi, Hong Xu, Jie Tang, Qiang Zhang, Yuexiang Wang
Effective evaluation of rotator cuff tear residual tendon quality is the key to surgical repair. However, until now, the evaluation of rotator cuff tissue by ultrasonic shear wave elasticity (SWE) has been controversial. This prospective study analyzed the association between preoperative SWE and arthroscopic residual tendon quality scores. The shear wave velocity (SWV) of the deltoid muscle, the supraspinatus
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Deep learning-based automated lesion segmentation on pediatric focal cortical dysplasia II preoperative MRI: a reliable approach Insights Imaging (IF 4.7) Pub Date : 2024-03-13 Siqi Zhang, Yijiang Zhuang, Yi Luo, Fengjun Zhu, Wen Zhao, Hongwu Zeng
Focal cortical dysplasia (FCD) represents one of the most common causes of refractory epilepsy in children. Deep learning demonstrates great power in tissue discrimination by analyzing MRI data. A prediction model was built and verified using 3D full-resolution nnU-Net for automatic lesion detection and segmentation of children with FCD II. High-resolution brain MRI structure data from 65 patients
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Radiological biomarkers reflecting visceral fat distribution help distinguish inflammatory bowel disease subtypes: a multicenter cross-sectional study Insights Imaging (IF 4.7) Pub Date : 2024-03-13 Ziman Xiong, Peili Wu, Yan Zhang, Jun Chen, Yaqi Shen, Ihab Kamel, Bing Wu, Xianying Zheng, Zhen Li
To achieve automated quantification of visceral adipose tissue (VAT) distribution in CT images and screen out parameters with discriminative value for inflammatory bowel disease (IBD) subtypes. This retrospective multicenter study included Crohn’s disease (CD) and ulcerative colitis (UC) patients from three institutions between 2012 and 2021, with patients with acute appendicitis as controls. An automatic
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CT-based pancreatic radiomics predicts secondary loss of response to infliximab in biologically naïve patients with Crohn’s disease Insights Imaging (IF 4.7) Pub Date : 2024-03-13 Tian Yang, Jing Feng, Ruchen Yao, Qi Feng, Jun Shen
Predicting secondary loss of response (SLR) to infliximab (IFX) is paramount for tailoring personalized management regimens. Concurrent pancreatic manifestations in patients with Crohn’s disease (CD) may correlate with SLR to anti-tumor necrosis factor treatment. This work aimed to evaluate the potential of pancreatic radiomics to predict SLR to IFX in biologic-naive individuals with CD. Three models
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Prediction of clinically significant prostate cancer using radiomics models in real-world clinical practice: a retrospective multicenter study Insights Imaging (IF 4.7) Pub Date : 2024-02-29 Jie Bao, Xiaomeng Qiao, Yang Song, Yueting Su, Libiao Ji, Junkang Shen, Guang Yang, Hailin Shen, Ximing Wang, Chunhong Hu
To develop and evaluate machine learning models based on MRI to predict clinically significant prostate cancer (csPCa) and International Society of Urological Pathology (ISUP) grade group as well as explore the potential value of radiomics models for improving the performance of radiologists for Prostate Imaging Reporting and Data System (PI-RADS) assessment. A total of 1616 patients from 4 tertiary
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MRI T2 mapping and shear wave elastography for identifying main pain generator in delayed-onset muscle soreness: muscle or fascia? Insights Imaging (IF 4.7) Pub Date : 2024-02-29 Congcong Fu, Yu Xia, Bingshan Wang, Qiang Zeng, Shinong Pan
The main generator of delayed onset muscle soreness (DOMS) is still unknown. This study aimed to clarify the main generator of DOMS. Twelve participants performed eccentric exercise (EE) on lower legs. MRI and ultrasound were used to assess changes of calf muscle and deep fascia before and after EE. These results were then compared to the muscle pain level. Compared to baseline, muscle pain peaked
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Liver imaging and pregnancy: what to expect when your patient is expecting Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Giorgia Porrello, Roberto Cannella, Jacques Bernuau, Antoine Agman, Giuseppe Brancatelli, Marco Dioguardi Burgio, Valérie Vilgrain
Liver diseases in pregnancy can be specific to gestation or only coincidental. In the latter case, the diagnosis can be difficult. Rapid diagnosis of maternal-fetal emergencies and situations requiring specialized interventions are crucial to preserve the maternal liver and guarantee materno-fetal survival. While detailed questioning of the patient and a clinical examination are highly important, imaging
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A retrospective study on adverse events of intravenous administration of sulfur hexafluoride microbubbles in abdominal and superficial applications in 83,778 patients Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Di Li, Rui Zhang, Huixia Lan, Mianni Chen, Zhenli Huang, Huijuan Zhao, Shan Guo, Ming Xu, Yangyang Lei
To investigate the rate of adverse events (AEs) caused by intravenous administration of sulfur hexafluoride microbubbles in abdominal and superficial applications retrospectively and to explore practical measures for prevention and treatment of them. This study enrolled 83,778 contrast-enhanced ultrasound (CEUS) examinations using sulfur hexafluoride microbubbles intravenously performed during 11 years
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The value of periportal hyperintensity sign from gadobenate dimeglumine-enhanced hepatobiliary phase MRI for predicting clinical outcomes in patients with decompensated cirrhosis Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Lanqing Cong, Yan Deng, Shuo Cai, Gongzheng Wang, Xinya Zhao, Jingzhen He, Songbo Zhao, Li Wang
To determine the value of periportal hyperintensity sign from gadobenate dimeglumine (Gd-BOPTA)-enhanced hepatobiliary phase (HBP) magnetic resonance imaging (MRI) for predicting clinical outcomes in patients with decompensated cirrhosis. A total of 199 cirrhotic patients who underwent Gd-BOPTA-enhanced MRI were divided into control group (n = 56) and decompensated cirrhosis group (n = 143). The presence
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The use of PET/MRI in radiotherapy Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Qi Yan, Xia Yan, Xin Yang, Sijin Li, Jianbo Song
Positron emission tomography/magnetic resonance imaging (PET/MRI) is a hybrid imaging technique that quantitatively combines the metabolic and functional data from positron emission tomography (PET) with anatomical and physiological information from MRI. As PET/MRI technology has advanced, its applications in cancer care have expanded. Recent studies have demonstrated that PET/MRI provides unique advantages
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Review of strategies to reduce the contamination of the water environment by gadolinium-based contrast agents Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Helena M. Dekker, Gerard J. Stroomberg, Aart J. Van der Molen, Mathias Prokop
Gadolinium-based contrast agents (GBCA) are essential for diagnostic MRI examinations. GBCA are only used in small quantities on a per-patient basis; however, the acquisition of contrast-enhanced MRI examinations worldwide results in the use of many thousands of litres of GBCA per year. Data shows that these GBCA are present in sewage water, surface water, and drinking water in many regions of the
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Rotator cuff tear patterns: MRI appearance and its surgical relevance Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Alexeys Perez Yubran, Luis Cerezal Pesquera, Eva Llopis San Juan, Fernando Idoate Saralegui, Alvaro Cerezal Canga, Antonio Cruz Camara, Gustavo Matheus Valdivieso, Carolina Pisanti Lopez
A new perspective on rotator cuff anatomy has allowed a better understanding of the patterns of the different rotator cuff tears. It is essential for radiologists to be aware of these different patterns of tears and to understand how they might influence treatment and surgical approach. Our objective is to review the arthroscopy correlated magnetic resonance imaging appearance of the different types
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Computed tomography-based body composition parameters can predict short-term prognosis in ulcerative colitis patients Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Jun Lu, Hui Xu, Haiyun Shi, Jing Zheng, Tianxin Cheng, Minsi Zhou, Xinjun Han, Yuxin Wang, Xuxu Meng, Xiaoyang Li, Jiahui Jiang, Peng Li, Zhenghan Yang, Lixue Xu
Emerging evidence suggests a potential relationship between body composition and short-term prognosis of ulcerative colitis (UC). Early and accurate assessment of rapid remission based on conventional therapy via abdominal computed tomography (CT) images has rarely been investigated. This study aimed to build a prediction model using CT-based body composition parameters for UC risk stratification.
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Deep learning model based on multi-lesion and time series CT images for predicting the benefits from anti-HER2 targeted therapy in stage IV gastric cancer Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Meng He, Zi-fan Chen, Song Liu, Yang Chen, Huan Zhang, Li Zhang, Jie Zhao, Jie Yang, Xiao-tian Zhang, Lin Shen, Jian-bo Gao, Bin Dong, Lei Tang
To develop and validate a deep learning model based on multi-lesion and time series CT images in predicting overall survival (OS) in patients with stage IV gastric cancer (GC) receiving anti-HER2 targeted therapy. A total of 207 patients were enrolled in this multicenter study, with 137 patients for retrospective training and internal validation, 33 patients for prospective validation, and 37 patients
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Prognostic value of right atrial strains in arrhythmogenic right ventricular cardiomyopathy Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Jin-Yu Zheng, Bing-Hua Chen, Rui Wu, Dong-Aolei An, Ruo-Yang Shi, Chong-Wen Wu, Lang-Lang Tang, Lei Zhao, Lian-Ming Wu
Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive fibrofatty infiltration of atrial and ventricular myocardium resulting in adverse cardiac events. Atrial function has been increasingly recognized as prognostically important for cardiovascular disease. As the right atrial (RA) strain is a sensitive parameter to describe RA function, we
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T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Hang Li, Li Chai, Hong Pu, Long-lin Yin, Mou Li, Xin Zhang, Yi-sha Liu, Ming-hui Pang, Tao Lu
To investigate whether T2-weighted imaging (T2WI)-based intratumoral and peritumoral radiomics can predict extranodal extension (ENE) and prognosis in patients with resectable rectal cancer. One hundred sixty-seven patients with resectable rectal cancer including T3T4N + cases were prospectively included. Radiomics features were extracted from intratumoral, peritumoral 3 mm, and peritumoral-mesorectal
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Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Fengying Qin, Xinyan Sun, Mingke Tian, Shan Jin, Jian Yu, Jing Song, Feng Wen, Hongming Xu, Tao Yu, Yue Dong
To develop and validate a magnetic resonance imaging-based (MRI) deep multiple instance learning (D-MIL) model and combine it with clinical parameters for preoperative prediction of lymph node metastasis (LNM) in operable cervical cancer. A total of 392 patients with cervical cancer were retrospectively enrolled. Clinical parameters were analysed by logistical regression to construct a clinical model
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Coronary chronic total occlusion on coronary CT angiography: what radiologists should know? Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Wei Xu, Junfeng Ma, Yiwen Chen, Fan Zhou, Changsheng Zhou, Long Jiang Zhang
Coronary chronic total occlusion (CTO) often occurs in patients with obstructive coronary artery disease, which remains one of the greatest challenges for interventional cardiologists. Coronary computed tomography angiography (CCTA) with its emerging post-processing techniques can provide a detailed assessment of CTO lesions before percutaneous coronary intervention (PCI), playing an important role
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CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies Insights Imaging (IF 4.7) Pub Date : 2024-02-27 Salvatore Gitto, Renato Cuocolo, Merel Huisman, Carmelo Messina, Domenico Albano, Patrick Omoumi, Elmar Kotter, Mario Maas, Peter Van Ooijen, Luca Maria Sconfienza
To systematically review radiomic feature reproducibility and model validation strategies in recent studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas, thus updating a previous version of this review which included studies published up to 2020. A literature search was conducted on EMBASE and PubMed databases for papers published between January 2021 and March 2023. Data regarding
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MRI-based synthetic CT for assessment of the bony elements of the sacroiliac joints in children Insights Imaging (IF 4.7) Pub Date : 2024-02-18 Eva Schiettecatte, Elke Vereecke, Jacob L. Jaremko, Lieve Morbée, Caroline Vande Walle, Lennart Jans, Nele Herregods
The purpose of this study is to assess the equivalency of MRI-based synthetic CT (sCT) to conventional CT for sacroiliac joint bony morphology assessment in children. A prospective study was performed. Children who had (PET-)CT-scan underwent additional MRI. sCT-CT image quality was analyzed by two readers subjectively overall, semi-quantitatively in terms of cortical delineation, joint facet defects
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Superolateral Hoffa fat pad edema in adolescent competitive alpine skiers: temporal evolution over 4 years and risk factors Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Georg C. Feuerriegel, Adrian A. Marth, Stefan Fröhlich, Johannes Scherr, Jörg Spörri, Reto Sutter
To longitudinally assess and correlate the prevalence of superolateral Hoffa fat pad (SHFP) edema with changes in features of the knee extensor mechanism in adolescent competitive alpine skiers over 48 months. Competitive alpine skiers were prospectively enrolled in 2018 and underwent bilateral knee MRI at baseline and after 48 months. MRI was assessed for the prevalence of SHFP edema. Features of
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How AI should be used in radiology: assessing ambiguity and completeness of intended use statements of commercial AI products Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Kicky G. van Leeuwen, Dennis M. Hedderich, Hugh Harvey, Steven Schalekamp
Intended use statements (IUSs) are mandatory to obtain regulatory clearance for artificial intelligence (AI)-based medical devices in the European Union. In order to guide the safe use of AI-based medical devices, IUSs need to contain comprehensive and understandable information. This study analyzes the IUSs of CE-marked AI products listed on AIforRadiology.com for ambiguity and completeness. We retrieved
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Imaging-based deep learning in kidney diseases: recent progress and future prospects Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Meng Zhang, Zheng Ye, Enyu Yuan, Xinyang Lv, Yiteng Zhang, Yuqi Tan, Chunchao Xia, Jing Tang, Jin Huang, Zhenlin Li
Kidney diseases result from various causes, which can generally be divided into neoplastic and non-neoplastic diseases. Deep learning based on medical imaging is an established methodology for further data mining and an evolving field of expertise, which provides the possibility for precise management of kidney diseases. Recently, imaging-based deep learning has been widely applied to many clinical
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Intravoxel incoherent motion diffusion-weighted imaging for predicting kidney allograft function decline: comparison with clinical parameters Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Wei Wang, Yuanmeng Yu, Jinsong Chen, Longjiang Zhang, Xue Li
To evaluate the added benefit of diffusion-weighted imaging (DWI) over clinical parameters in predicting kidney allograft function decline. Data from 97 patients with DWI of the kidney allograft were retrospectively analyzed. The DWI signals were analyzed with both the mono-exponential and bi-exponential models, yielding total apparent diffusion coefficient (ADCT), true diffusion (D), pseudo-diffusion
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Assessment of intestinal luminal stenosis and prediction of endoscopy passage in Crohn’s disease patients using MRI Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Wenjuan Wu, Yan Jin, Dongyang Zhu, Junqing Wang, Yue Cheng, Lei Zhang
Crohn’s disease (CD) is an inflammatory disease of the gastrointestinal tract. The disease behavior changes over time, and endoscopy is crucial in evaluating and monitoring the course of CD. To reduce the economic burden of patients and alleviate the discomfort associated with ineffective examination, it is necessary to fully understand the location, extent, and severity of intestinal stenosis in patients
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Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world data Insights Imaging (IF 4.7) Pub Date : 2024-02-16 Simon J. Doran, Theo Barfoot, Linda Wedlake, Jessica M. Winfield, James Petts, Ben Glocker, Xingfeng Li, Martin Leach, Martin Kaiser, Tara D. Barwick, Aristeidis Chaidos, Laura Satchwell, Neil Soneji, Khalil Elgendy, Alexander Sheeka, Kathryn Wallitt, Dow-Mu Koh, Christina Messiou, Andrea Rockall
MAchine Learning In MyelomA Response (MALIMAR) is an observational clinical study combining “real-world” and clinical trial data, both retrospective and prospective. Images were acquired on three MRI scanners over a 10-year window at two institutions, leading to a need for extensive curation. Curation involved image aggregation, pseudonymisation, allocation between project phases, data cleaning, upload
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Inter-platform reproducibility of ultrasound-based fat fraction for evaluating hepatic steatosis in nonalcoholic fatty liver disease Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Sun Kyung Jeon, Jeong Min Lee
To evaluate the inter-platform reproducibility of ultrasound-based fat fraction examination in nonalcoholic fatty liver disease (NAFLD). Patients suspected of having NAFLD were prospectively enrolled from January 2023. Ultrasound-based fat fraction examinations were performed using two different platforms (ultrasound-derived fat fraction [UDFF] and quantitative ultrasound-derived estimated fat fraction
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O-RADS MRI risk stratification system: pearls and pitfalls Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Stephanie Nougaret, Leo Razakamanantsoa, Elizabeth A. Sadowski, Erica B. Stein, Yulia Lakhman, Nicole M. Hindman, Aurelie Jalaguier-Coudray, Andrea G. Rockall, Isabelle Thomassin-Naggara
In 2021, the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee developed a risk stratification system and lexicon for assessing adnexal lesions using MRI. Like the BI-RADS classification, O-RADS MRI provides a standardized language for communication between radiologists and clinicians. It is essential for radiologists to be familiar with the O-RADS
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Comparison contrast-enhanced CT with contrast-enhanced US in diagnosing combined hepatocellular-cholangiocarcinoma: a propensity score-matched study Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Jie Yang, Yun Zhang, Wu-yong-ga Bao, Yi-di Chen, Hanyu Jiang, Jia-yan Huang, Ke-yu Zeng, Bin Song, Zi-xing Huang, Qiang Lu
To develop and compare noninvasive models for differentiating between combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and HCC based on serum tumor markers, contrast-enhanced ultrasound (CEUS), and computed tomography (CECT). From January 2010 to December 2021, patients with pathologically confirmed cHCC-CCA or HCC who underwent both preoperative CEUS and CECT were retrospectively enrolled. Propensity
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Reply to a Letter to the Editor on Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Nikita Sushentsev, Tristan Barrett, Leonardo Rundo
Dear Editor-in-Chief, We have read the letter concerning our recent publication in Insights into Imaging titled Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review [1] on our previously published work [2]. First, we acknowledge that some of the concerns raised by the authors
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Radiation reduction for interventional radiology imaging: a video frame interpolation solution Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Zhijiang Tang, Qiang Xiong, Xuantai Wu, Tianyi Xu, Yuxuan Shi, Ximing Xu, Jun Xu, Ruijue Wang
The aim of this study was to diminish radiation exposure in interventional radiology (IR) imaging while maintaining image quality. This was achieved by decreasing the acquisition frame rate and employing a deep neural network to interpolate the reduced frames. This retrospective study involved the analysis of 1634 IR sequences from 167 pediatric patients (March 2014 to January 2022). The dataset underwent
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Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Youjia Wen, Zuhua Song, Qian Li, Dan Zhang, Xiaojiao Li, Jiayi Yu, Zongwen Li, Xiaofang Ren, Jiayan Zhang, Qian Liu, Jie Huang, Dan Zeng, Zhuoyue Tang
To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration
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Neuroimaging features of primary central nervous system post-transplantation lymphoproliferative disorder following hematopoietic stem cell transplant in patients with β-thalassemia: a case series and review of literature Insights Imaging (IF 4.7) Pub Date : 2024-02-14 Xueqing Yang, Xi Deng, Meiqing Wu, Sean W. Chen, Muliang Jiang, Liling Long, Bihong T. Chen
Primary central nervous system post-transplantation lymphoproliferative disorder (PCNS-PTLD) is a rare but serious complication of hematopoietic stem cell transplantation (HSCT) in patients with severe β-thalassemia. This study aimed to assess the clinical presentation, pathological characteristics, neuroimaging findings, and treatment strategies in patients with β-thalassemia who developed PCNS-PTLD
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Ultrasound imaging of the posterior lateral corner of the knee: a pictorial review of anatomy and pathologies Insights Imaging (IF 4.7) Pub Date : 2024-02-09 Wei-Ting Wu, Kentaro Onishi, Kamal Mezian, Ondřej Naňka, Bow Wang, Daniel Chiung-Jui Su, Vincenzo Ricci, Ke-Vin Chang, Levent Özçakar
Assessment of the posterior lateral knee pain poses diagnostic challenges, requiring accurate evaluation of various structures in light of the medical history and physical examination. Despite substantial progress in the ultrasonographic diagnosis of musculoskeletal disorders, the current protocol (EURO-MUSCULUS/USPRM. Basic scanning protocols for knee) fails to conduct a comprehensive investigation
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Digital breast tomosynthesis in mammographic screening: false negative cancer cases in the To-Be 1 trial Insights Imaging (IF 4.7) Pub Date : 2024-02-08 Nataliia Moshina, Axel Gräwingholt, Kristina Lång, Ritse Mann, Tone Hovda, Solveig Roth Hoff, Per Skaane, Christoph I. Lee, Hildegunn S. Aase, Aslak B. Aslaksen, Solveig Hofvind
The randomized controlled trial comparing digital breast tomosynthesis and synthetic 2D mammograms (DBT + SM) versus digital mammography (DM) (the To-Be 1 trial), 2016–2017, did not result in higher cancer detection for DBT + SM. We aimed to determine if negative cases prior to interval and consecutive screen-detected cancers from DBT + SM were due to interpretive error. Five external breast radiologists
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Contrast-enhanced mammography BI-RADS: a case-based approach to radiology reporting Insights Imaging (IF 4.7) Pub Date : 2024-02-08 Luca Nicosia, Ottavia Battaglia, Massimo Venturini, Federico Fontana, Manuela Minenna, Aurora Pesenti, Diana Budascu, Filippo Pesapane, Anna Carla Bozzini, Maria Pizzamiglio, Lorenza Meneghetti, Antuono Latronico, Giulia Signorelli, Luciano Mariano, Enrico Cassano
Contrast-enhanced mammography (CEM) is a relatively recent diagnostic technique increasingly being utilized in clinical practice. Until recently, there was a lack of standardized reporting for CEM findings. However, this has changed with the publication of a supplement in the Breast Imaging Reporting and Data System (BI-RADS). A comprehensive understanding of CEM is essential for further enhancing
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Diagnostic accuracy of MRI, CT, and [18F]FDG-PET-CT in detecting lymph node metastases in clinically early-stage cervical cancer — a nationwide Dutch cohort study Insights Imaging (IF 4.7) Pub Date : 2024-02-08 Ester P. Olthof, Brenda J. Bergink-Voorthuis, Hans H. B. Wenzel, Jordy Mongula, Jacobus van der Velden, Anje M. Spijkerboer, Judit A. Adam, Ruud L. M. Bekkers, Jogchum J. Beltman, Brigitte F. M. Slangen, Hans W. Nijman, Ramon G. V. Smolders, Nienke E. van Trommel, Petra L. M. Zusterzeel, Ronald P. Zweemer, Lukas J. A. Stalpers, Constantijne H. Mom, Maaike A. van der Aa
Imaging is increasingly used to assess lymph node involvement in clinically early-stage cervical cancer. This retrospective study aimed to evaluate the diagnostic accuracy of MRI, CT, and [18F]FDG-PET-CT. Women with International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage IA2-IIA cervical cancer and pretreatment imaging between 2009 and 2017 were selected from the Netherlands Cancer
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Deep learning for differentiation of osteolytic osteosarcoma and giant cell tumor around the knee joint on radiographs: a multicenter study Insights Imaging (IF 4.7) Pub Date : 2024-02-07 Jingjing Shao, Hongxin Lin, Lei Ding, Bing Li, Danyang Xu, Yang Sun, Tianming Guan, Haiyang Dai, Ruihao Liu, Demao Deng, Bingsheng Huang, Shiting Feng, Xianfen Diao, Zhenhua Gao
To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs. Patients with osteolytic OS and GCT proven by postoperative pathology were retrospectively recruited from four centers (center A, training and internal testing; centers B, C, and D, external testing). Sixteen radiologists with different experiences in musculoskeletal
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Radiology AI Deployment and Assessment Rubric (RADAR) to bring value-based AI into radiological practice Insights Imaging (IF 4.7) Pub Date : 2024-02-05 Bart-Jan Boverhof, W. Ken Redekop, Daniel Bos, Martijn P. A. Starmans, Judy Birch, Andrea Rockall, Jacob J. Visser
To provide a comprehensive framework for value assessment of artificial intelligence (AI) in radiology. This paper presents the RADAR framework, which has been adapted from Fryback and Thornbury’s imaging efficacy framework to facilitate the valuation of radiology AI from conception to local implementation. Local efficacy has been newly introduced to underscore the importance of appraising an AI technology
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Broken-fat pad sign: a characteristic radiographic finding to distinguish between knee rheumatoid arthritis and osteoarthritis Insights Imaging (IF 4.7) Pub Date : 2024-02-05 Qizheng Wang, Weili Zhao, Xiaoxi Ji, Yongye Chen, Ke Liu, Yupeng Zhu, Ruixin Yan, Siyuan Qin, Peijin Xin, Ning Lang
Diagnostic imaging plays an important role in the pre-treatment workup of knee osteoarthritis (OA) and rheumatoid arthritis (RA). Herein, we identified a useful MRI sign of infrapatellar fat pad (IPFP) to improve diagnosis. Eighty-one age- and sex-matched RA and OA patients each, with pathological diagnosis and pre-treatment MRI were retrospectively evaluated. All randomized MR images were blinded
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Post-treatment surveillance imaging in head and neck cancer: a systematic review Insights Imaging (IF 4.7) Pub Date : 2024-02-05 Stefaan Van Hoe, Robert Hermans
In patients treated for head and neck cancer, imaging studies are usually obtained within 3–6 months after treatment for assessment of treatment response. After 6 months, most guidelines advocate clinical follow-up, with imaging reserved for patients with clinically suspect or equivocal findings. However, some guidelines do recommend systematic imaging surveillance, and many clinicians tend to include
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Prediction of late recurrence after curative-intent resection using MRI-measured spleen volume in patients with hepatocellular carcinoma and cirrhosis Insights Imaging (IF 4.7) Pub Date : 2024-02-02 Chongtu Yang, Jia Tan, Yidi Chen, Yanshu Wang, Yali Qu, Jie Chen, Hanyu Jiang, Bin Song
Late recurrence of hepatocellular carcinoma (HCC) after liver resection is regarded as a de novo tumor primarily related to the severity of underlying liver disease. We aimed to investigate risk factors, especially spleen volume, associated with late recurrence in patients with HCC and cirrhosis. We retrospectively analyzed 301 patients with HCC and cirrhosis who received curative resection and preoperative
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Advancements in diagnostic and interventional radiology for stroke treatment: the path from trial to bedside through the pre-MR CLEAN, MR CLEAN, and MR CLEAN II eras Insights Imaging (IF 4.7) Pub Date : 2024-01-30 Noor Samuels, Rob A. van de Graaf, Yvo B. W. M. Roos, Diederik Dippel, Aad van der Lugt
The stroke field is inevitably connected with imaging in which radiologists fulfill a central role. Our landmark MR CLEAN trial led to the implementation of baseline computed tomography angiography or magnetic resonance angiography in the acute stroke workup and subsequent endovascular treatment (EVT) for ischemic stroke patients with a large vessel occlusion in the anterior circulation, resulting
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O-RADS MRI to classify adnexal tumors: from clinical problem to daily use Insights Imaging (IF 4.7) Pub Date : 2024-01-30 Yohann Dabi, Andrea Rockall, Elisabeth Sadowski, Cyril Touboul, Leo Razakamanantsoa, Isabelle Thomassin-Naggara
Eighteen to 35% of adnexal masses remain non-classified following ultrasonography, leading to unnecessary surgeries and inappropriate management. This finding led to the conclusion that ultrasonography was insufficient to accurately assess adnexal masses and that a standardized MRI criteria could improve these patients’ management. The aim of this work is to present the different steps from the identification
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CT-based radiomics signature of visceral adipose tissue and bowel lesions for identifying patients with Crohn’s disease resistant to infliximab Insights Imaging (IF 4.7) Pub Date : 2024-01-30 Yangdi Wang, Zixin Luo, Zhengran Zhou, Yingkui Zhong, Ruonan Zhang, Xiaodi Shen, Lili Huang, Weitao He, Jinjiang Lin, Jiayu Fang, Qiapeng Huang, Haipeng Wang, Zhuya Zhang, Ren Mao, Shi-Ting Feng, Xuehua Li, Bingsheng Huang, Zhoulei Li, Jian Zhang, Zhihui Chen
To develop a CT-based radiomics model combining with VAT and bowel features to improve the predictive efficacy of IFX therapy on the basis of bowel model. This retrospective study included 231 CD patients (training cohort, n = 112; internal validation cohort, n = 48; external validation cohort, n = 71) from two tertiary centers. Machine-learning VAT model and bowel model were developed separately to
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Interactive training workshop to improve prostate mpMRI knowledge: results from the ESOR Nicholas Gourtsoyiannis teaching fellowship Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Tristan Barrett, Kang-Lung Lee, Fredrik Illerstam, Henrik S. Thomsen, Kartik S. Jhaveri, Vibeke Løgager
Prostate MRI is established for the investigation of patients presenting with suspected early prostate cancer. Outcomes are dependent on both image quality and interpretation. This study assessed the impact of an educational intervention on participants’ theoretical knowledge of the technique. Eighty-one clinicians from two centers with varying experience in prostate MRI participated. Baseline knowledge
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Convolutional neural networks for the differentiation between benign and malignant renal tumors with a multicenter international computed tomography dataset Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Michail E. Klontzas, Georgios Kalarakis, Emmanouil Koltsakis, Thomas Papathomas, Apostolos H. Karantanas, Antonios Tzortzakakis
To use convolutional neural networks (CNNs) for the differentiation between benign and malignant renal tumors using contrast-enhanced CT images of a multi-institutional, multi-vendor, and multicenter CT dataset. A total of 264 histologically confirmed renal tumors were included, from US and Swedish centers. Images were augmented and divided randomly 70%:30% for algorithm training and testing. Three
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A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Ming Ni, Shujing Li, Xiaoyi Wen, Ben Wang, Chenyu Jiang, Xianchang Zhang, Ning Lang, Liang Jiang, Huishu Yuan
Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM. Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing
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Myocardial involvement characteristics by cardiac MR imaging in neurological and non-neurological Wilson disease patients Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Wei Deng, Jie Zhang, Zhuoran Jia, Zixiang Pan, Zhen Wang, Huimin Xu, Liang Zhong, Yongqiang Yu, Ren Zhao, Xiaohu Li
To explore the characteristics of myocardial involvement in Wilson Disease (WD) patients by cardiac magnetic resonance (CMR). We prospectively included WD patients and age- and sex-matched healthy population. We applied CMR to analyze cardiac function, strain, T1 maps, T2 maps, extracellular volume fraction (ECV) maps, and LGE images. Subgroup analyzes were performed for patients with WD with predominantly
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Intratumoral and peritumoral radiomics predict pathological response after neoadjuvant chemotherapy against advanced gastric cancer Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Chenchen Liu, Liming Li, Xingzhi Chen, Chencui Huang, Rui Wang, Yiyang Liu, Jianbo Gao
To investigate whether intratumoral and peritumoral radiomics may predict pathological responses after neoadjuvant chemotherapy against advanced gastric cancer. Clinical, pathological, and CT data from 231 patients with advanced gastric cancer who underwent neoadjuvant chemotherapy at our hospital between July 2014 and February 2022 were retrospectively collected. Patients were randomly divided into
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A holistic approach to implementing artificial intelligence in radiology Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Bomi Kim, Stephan Romeijn, Mark van Buchem, Mohammad Hosein Rezazade Mehrizi, Willem Grootjans
Despite the widespread recognition of the importance of artificial intelligence (AI) in healthcare, its implementation is often limited. This article aims to address this implementation gap by presenting insights from an in-depth case study of an organisation that approached AI implementation with a holistic approach. We conducted a longitudinal, qualitative case study of the implementation of AI in
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Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Rui Sun, Meng Zhang, Lei Yang, Shifeng Yang, Na Li, Yonghua Huang, Hongzheng Song, Bo Wang, Chencui Huang, Feng Hou, Hexiang Wang
To establish a model for predicting lymph node metastasis in bladder cancer (BCa) patients. We retroactively enrolled 239 patients who underwent three-phase CT and resection for BCa in two centers (training set, n = 185; external test set, n = 54). We reviewed the clinical characteristics and CT features to identify significant predictors to construct a clinical model. We extracted the hand-crafted
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Endometriosis MR mimickers: T2-hypointense lesions Insights Imaging (IF 4.7) Pub Date : 2024-01-25 Edouard Ruaux, Wendaline M. VanBuren, Stéphanie Nougaret, Marie Gavrel, Mathilde Charlot, Flavia Grangeon, Pierre-Adrien Bolze, Isabelle Thomassin-Naggara, Pascal Rousset
Endometriosis is a common crippling disease in women of reproductive age. Magnetic resonance imaging (MRI) is considered the cornerstone radiological technique for both the diagnosis and management of endometriosis. While its sensitivity, especially in deep infiltrating endometriosis, is superior to that of ultrasonography, many sources of false-positive results exist, leading to a lack of specificity
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Endometriosis MR mimickers: T1-hyperintense lesions Insights Imaging (IF 4.7) Pub Date : 2024-01-24 Edouard Ruaux, Stéphanie Nougaret, Marie Gavrel, Mathilde Charlot, Mojgan Devouassoux-Shisheboran, François Golfier, Isabelle Thomassin-Naggara, Pascal Rousset
Endometriosis is a chronic and disabling gynecological disease that affects women of reproductive age. Magnetic resonance imaging (MRI) is considered the cornerstone radiological technique for both the diagnosis and management of endometriosis. While MRI offers higher sensitivity compared to ultrasonography, it is prone to false-positive results, leading to decreased specificity. False-positive findings
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ESR Journals editors’ joint statement on Guidelines for the Use of Large Language Models by Authors, Reviewers, and Editors Insights Imaging (IF 4.7) Pub Date : 2024-01-24 Bernd Hamm, Luis Marti-Bonmati, Francesco Sardanelli
The impact of artificial intelligence (AI)-assisted technologies, such as Large Language Models (LLMs), chatbots, or image creators, on biomedical publishing was discussed by the editors of radiology journals at the annual Radiology Editors’ Forum, held on August 11–12, 2023, in Chicago, Illinois. The forum was attended by over 40 individuals, representing 30 biomedical imaging journals from 9 countries
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Assessment of lung deformation in patients with idiopathic pulmonary fibrosis with elastic registration technique on pulmonary three-dimensional ultrashort echo time MRI Insights Imaging (IF 4.7) Pub Date : 2024-01-23 Xiaoyan Yang, Pengxin Yu, Haishuang Sun, Mei Deng, Anqi Liu, Chen Li, Wenyan Meng, Wenxiu Xu, Bingbing Xie, Jing Geng, Yanhong Ren, Rongguo Zhang, Min Liu, Huaping Dai
To assess lung deformation in patients with idiopathic pulmonary fibrosis (IPF) using with elastic registration algorithm applied to three-dimensional ultrashort echo time (3D-UTE) MRI and analyze relationship of lung deformation with the severity of IPF. Seventy-six patients with IPF (mean age: 62 ± 6 years) and 62 age- and gender-matched healthy controls (mean age: 58 ± 4 years) were prospectively
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Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA Insights Imaging (IF 4.7) Pub Date : 2024-01-22 Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina Kottler, John Mongan, Lauren Oakden-Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald, John Slavotinek
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights
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A framework to integrate artificial intelligence training into radiology residency programs: preparing the future radiologist Insights Imaging (IF 4.7) Pub Date : 2024-01-17 Maria Jorina van Kooten, Can Ozan Tan, Elfi Inez Saïda Hofmeijer, Peter Martinus Adrianus van Ooijen, Walter Noordzij, Maria Jolanda Lamers, Thomas Christian Kwee, Rozemarijn Vliegenthart, Derya Yakar
To present a framework to develop and implement a fast-track artificial intelligence (AI) curriculum into an existing radiology residency program, with the potential to prepare a new generation of AI conscious radiologists. The AI-curriculum framework comprises five sequential steps: (1) forming a team of AI experts, (2) assessing the residents’ knowledge level and needs, (3) defining learning objectives
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Emergency department CT examinations demonstrate no evidence of early viral circulation at the start of the COVID-19 pandemic—a multicentre epidemiological study Insights Imaging (IF 4.7) Pub Date : 2024-01-17 Amandine Crombé, Claire Dupont, François Casalonga, Mylène Seux, Nicolas Favard, Agnès Coulon, Thomas Jurkovic, Hubert Nivet, Guillaume Gorincour
Biological studies suggested that the COVID-19 outbreak in France occurred before the first official diagnosis on January 24, 2020. We investigated this controversial topic using a large collection of chest CTs performed throughout French emergency departments within 6 months before the 1st lockdown. Overall, 49,311 consecutive patients (median age: 60 years, 23,636/49,311 [47.9%] women) with available