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Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology. Radiology (IF 19.7) Pub Date : 2023-10-01 Jenna M Schabdach,J Eric Schmitt,Susan Sotardi,Arastoo Vossough,Savvas Andronikou,Timothy P Roberts,Hao Huang,Viveknarayanan Padmanabhan,Alfredo Ortiz-Rosa,Margaret Gardner,Sydney Covitz,Saashi A Bedford,Ayan S Mandal,Barbara H Chaiyachati,Simon R White,Edward Bullmore,Richard A I Bethlehem,Russell T Shinohara,Benjamin Billot,J Eugenio Iglesias,Satrajit Ghosh,Raquel E Gur,Theodore D Satterthwaite,David
Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic
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International Expert Consensus on US Lexicon for Thyroid Nodules. Radiology (IF 19.7) Pub Date : 2023-10-01 Cosimo Durante,Laszlo Hegedüs,Dong Gyu Na,Enrico Papini,Jennifer A Sipos,Jung Hwan Baek,Andrea Frasoldati,Giorgio Grani,Edward Grant,Eleonora Horvath,Jenny K Hoang,Susan J Mandel,William D Middleton,Rose Ngu,Lisa Ann Orloff,Jung Hee Shin,Pierpaolo Trimboli,Jung Hyun Yoon,Franklin N Tessler
Multiple US-based systems for risk stratification of thyroid nodules are in use worldwide. Unfortunately, the malignancy probability assigned to a nodule varies, and terms and definitions are not consistent, leading to confusion and making it challenging to compare study results and craft revisions. Consistent application of these systems is further hampered by interobserver variability in identifying
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US Predictors of Papillary Thyroid Microcarcinoma Progression at Active Surveillance. Radiology (IF 19.7) Pub Date : 2023-10-01 Ji Ye Lee,Ji-Hoon Kim,Yeo Koon Kim,Chang Yoon Lee,Eun Kyung Lee,Jae Hoon Moon,Hoon Sung Choi,Hwangbo Yul,Sun Wook Cho,Su-Jin Kim,Kyu Eun Lee,Do Joon Park,Young Joo Park
Background Active surveillance (AS) is an accepted strategy for patients with low-risk papillary thyroid microcarcinoma (PTMC). While previous studies have evaluated the prognostic value of US features, results have been inconsistent. Purpose To determine if US features can help predict tumor progression in patients with low-risk PTMC undergoing AS. Materials and Methods This prospective study enrolled
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Case 318: Adult Polyglucosan Body Disease. Radiology (IF 19.7) Pub Date : 2023-10-01 Eline Van den Borre,Gert Cypers,Piet Vanhoenacker,Sven Dekeyzer
A 72-year-old man sought care for a cognitive deterioration over the past 5 years. There was a documented decline in his performance on the Mini-Mental State Examination (30 of 30 in 2016, 23 of 30 in 2021), with mainly episodic memory impairment. A more detailed history revealed a gait problem, paresthesia in both feet, and nocturnal urinary frequency. Clinical examination findings were suggestive
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CT-based Diagnosis of Clinically Significant Portal Hypertension: An Opportunity to Prevent Complications. Radiology (IF 19.7) Pub Date : 2023-10-01 Tyler J Fraum
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Substitution with Low-Osmolar Iodinated Contrast Agent to Minimize Recurrent Immediate Hypersensitivity Reaction. Radiology (IF 19.7) Pub Date : 2023-10-01 Sujeong Kim,Kyung Nyeo Jeon,Jae-Woo Jung,Han-Ki Park,Whal Lee,Jongmin Lee,Hye-Ryun Kang
Background The recurrence of hypersensitivity reaction (HSR) to low-osmolar iodinated contrast media (LOCM) remains challenging despite premedication and substitution of the LOCM. Purpose To determine the optimal practical preventive strategy for LOCM substitution in patients with a history of prior immediate HSR to LOCM. Materials and Methods In a retrospective study, patients with an immediate HSR
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Left Anterior Descending Branch to Middle Cardiac Vein Fistula. Radiology (IF 19.7) Pub Date : 2023-10-01 Leizhi Ku,Xiaojing Ma
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US Follow-up of Papillary Microcarcinoma of the Thyroid Gland. Radiology (IF 19.7) Pub Date : 2023-10-01 Karen L Reuter
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CT Rule-in and Rule-out Criteria for Clinically Significant Portal Hypertension in Chronic Liver Disease. Radiology (IF 19.7) Pub Date : 2023-10-01 Subin Heo,Seung Soo Lee,Sang Hyun Choi,Dong Wook Kim,Hyo Jung Park,So Yeon Kim,So Jung Lee,Kang Mo Kim,Yong Moon Shin
Background The value of CT in assessment of clinically significant portal hypertension (CSPH) has not been well determined. Purpose To evaluate the performance of CT features that have been associated with portal hypertension for diagnosing CSPH in patients with chronic liver disease (CLD). Materials and Methods This retrospective study included patients with CLD who underwent contrast-enhanced CT
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Broadening the Scope of Normal Control Images in Pediatric Neuroimaging-and Possibly Beyond. Radiology (IF 19.7) Pub Date : 2023-10-01 Birgit Betina Ertl-Wagner,Vivek Pai
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Selecting an Alternative Contrast Agent to Prevent Repeat Allergic-like Reactions. Radiology (IF 19.7) Pub Date : 2023-10-01 Jennifer S McDonald
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Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting. Radiology (IF 19.7) Pub Date : 2023-10-01 Jihye Yun,Yura Ahn,Kyungjin Cho,Sang Young Oh,Sang Min Lee,Namkug Kim,Joon Beom Seo
Background Most artificial intelligence algorithms that interpret chest radiographs are restricted to an image from a single time point. However, in clinical practice, multiple radiographs are used for longitudinal follow-up, especially in intensive care units (ICUs). Purpose To develop and validate a deep learning algorithm using thoracic cage registration and subtraction to triage pairs of chest
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Statistical Methods for Exploring Causal Relationships between Risk Factors and Liver Disease. Radiology (IF 19.7) Pub Date : 2023-10-01 Sarah E Monsell
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New Insights into the Pharmacology and Biodistribution of Gadolinium-based Contrast Agents. Radiology (IF 19.7) Pub Date : 2023-10-01 Michael F Tweedle
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Imaging Informatics: Maturing Beyond Adolescence to Enable the Return of the Doctor's Doctor. Radiology (IF 19.7) Pub Date : 2023-10-01 Paul J Chang
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Optimizing the Pairs of Radiologists That Double Read Screening Mammograms. Radiology (IF 19.7) Pub Date : 2023-10-01 Jessie J J Gommers,Craig K Abbey,Fredrik Strand,Sian Taylor-Phillips,David J Jenkinson,Marthe Larsen,Solveig Hofvind,Ioannis Sechopoulos,Mireille J M Broeders
Background Despite variation in performance characteristics among radiologists, the pairing of radiologists for the double reading of screening mammograms is performed randomly. It is unknown how to optimize pairing to improve screening performance. Purpose To investigate whether radiologist performance characteristics can be used to determine the optimal set of pairs of radiologists to double read
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MRI Proton Density Fat Fraction for Liver Disease Risk Assessment: A Call for Clinical Implementation. Radiology (IF 19.7) Pub Date : 2023-10-01 Scott B Reeder,Jitka Starekova
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The Future of AI and Informatics in Radiology: 10 Predictions. Radiology (IF 19.7) Pub Date : 2023-10-01 Curtis P Langlotz
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Gadolinium-based Contrast Agent Biodistribution and Speciation in Rats. Radiology (IF 19.7) Pub Date : 2023-10-01 Mariane Le Fur,Brianna F Moon,Iris Y Zhou,Samantha Zygmont,Avery Boice,Nicholas J Rotile,Ilknur Ay,Pamela Pantazopoulos,Adam S Feldman,Ivy A Rosales,Ira Doressa Anne L How,David Izquierdo-Garcia,Lida P Hariri,Andrei V Astashkin,Brian P Jackson,Peter Caravan
Background Gadolinium retention has been observed in organs of patients with normal renal function; however, the biodistribution and speciation of residual gadolinium is not well understood. Purpose To compare the pharmacokinetics, distribution, and speciation of four gadolinium-based contrast agents (GBCAs) in healthy rats using MRI, mass spectrometry, elemental imaging, and electron paramagnetic
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Change or No Change: Using AI to Compare Follow-up Chest Radiographs. Radiology (IF 19.7) Pub Date : 2023-10-01 Julianna Czum
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Association between Liver MRI Proton Density Fat Fraction and Liver Disease Risk. Radiology (IF 19.7) Pub Date : 2023-10-01 Tianyi Xia,Mulong Du,Huiqin Li,Yuancheng Wang,Junhao Zha,Tong Wu,Shenghong Ju
Background A better understanding of the association between liver MRI proton density fat fraction (PDFF) and liver diseases might support the clinical implementation of MRI PDFF. Purpose To quantify the genetically predicted causal effect of liver MRI PDFF on liver disease risk. Materials and Methods This population-based prospective observational study used summary-level data mainly from the UK Biobank
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Milestones in CT: Past, Present, and Future. Radiology (IF 19.7) Pub Date : 2023-10-01 Cynthia H McCollough,Prabhakar Shantha Rajiah
In 1971, the first patient CT examination by Ambrose and Hounsfield paved the way for not only volumetric imaging of the brain but of the entire body. From the initial 5-minute scan for a 180° rotation to today's 0.24-second scan for a 360° rotation, CT technology continues to reinvent itself. This article describes key historical milestones in CT technology from the earliest days of CT to the present
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Reliability and Feasibility of Low-Field-Strength Fetal MRI at 0.55 T during Pregnancy. Radiology (IF 19.7) Pub Date : 2023-10-01 Jordina Aviles Verdera,Lisa Story,Megan Hall,Tom Finck,Alexia Egloff,Paul T Seed,Shaihan J Malik,Mary A Rutherford,Joseph V Hajnal,Raphaël Tomi-Tricot,Jana Hutter
Background The benefits of using low-field-strength fetal MRI to evaluate antenatal development include reduced image artifacts, increased comfort, larger bore size, and potentially reduced costs, but studies about fetal low-field-strength MRI are lacking. Purpose To evaluate the reliability and feasibility of low-field-strength fetal MRI to assess anatomic and functional measures in pregnant participants
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Intravenous Thrombolytic Therapy for Large Core Infarctions Undergoing Mechanical Thrombectomy: A "Bridge" Worth Crossing? Radiology (IF 19.7) Pub Date : 2023-10-01 David F Kallmes,Alejandro Rabinstein
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Noncontrast MR Lymphography: Precise and Useful. Radiology (IF 19.7) Pub Date : 2023-10-01 Lionel Arrivé,Laurence Monnier-Cholley,Sanaâ El Mouhadi
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Endovascular Thrombectomy Outcomes with and without Intravenous Thrombolysis for Large Ischemic Cores Identified with CT or MRI. Radiology (IF 19.7) Pub Date : 2023-10-01 Imad Derraz,Solène Moulin,Benjamin Gory,Maéva Kyheng,Caroline Arquizan,Vincent Costalat,Bertrand Lapergue,
Background Whether intravenous thrombolysis (IVT) prior to endovascular thrombectomy (EVT) provides additional benefits in patients with acute ischemic stroke (AIS) and a large infarct core (LIC) remains unclear. Purpose To examine whether treatment with IVT before EVT is beneficial in patients with LIC identified with CT or MRI (Alberta Stroke Program Early CT score 0-5). Materials and Methods This
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Contrast-enhanced US Evaluation of Hepatocellular Carcinoma Response to Chemoembolization: A Prospective Multicenter Trial. Radiology (IF 19.7) Pub Date : 2023-10-01 Esika Savsani,Colette M Shaw,Flemming Forsberg,Corinne E Wessner,Andrej Lyshchik,Patrick O'Kane,Ji-Bin Liu,Rashmi Balasubramanya,Christopher G Roth,Haresh Naringrekar,Scott W Keith,Allison Tan,Kevin Anton,Kristen Bradigan,Jesse Civan,Susan Schultz,Susan Shamimi-Noori,Stephen Hunt,Michael C Soulen,Robert F Mattrey,Yuko Kono,John R Eisenbrey
Background Contrast-enhanced (CE) US has been studied for use in the detection of residual viable hepatocellular carcinoma (HCC) after locoregional therapy, but multicenter data are lacking. Purpose To compare two-dimensional (2D) and three-dimensional (3D) CE US diagnostic performance with that of CE MRI or CT, the current clinical standard, in the detection of residual viable HCC after transarterial
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AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis. Radiology (IF 19.7) Pub Date : 2023-10-01 Marthe Larsen,Camilla F Olstad,Henrik W Koch,Marit A Martiniussen,Solveig R Hoff,Håkon Lund-Hanssen,Helene S Solli,Karl Øyvind Mikalsen,Steinar Auensen,Jan Nygård,Kristina Lång,Yan Chen,Solveig Hofvind
Background Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography. Purpose To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer. Materials and Methods Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this
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What Happens When AI Is Wrong? Radiology (IF 19.7) Pub Date : 2023-10-01 Grayson L Baird,Michael H Bernstein,Michael K Atalay
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The Potential of Low-Field-Strength MRI for Simpler Fetal Scanning. Radiology (IF 19.7) Pub Date : 2023-10-01 Penny A Gowland
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Leveraging Differences in AI and Human "Vision" to Improve Breast Cancer Detection. Radiology (IF 19.7) Pub Date : 2023-10-01 Tejas S Mehta
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Cinematic Rendering of Retrograde Jejunogastric Intussusception. Radiology (IF 19.7) Pub Date : 2023-10-01 Hui-Hui Zhang,Xian-Zheng Tan
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Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium. Radiology (IF 19.7) Pub Date : 2023-10-01 Kathryn J Fowler,Sudhakar K Venkatesh,Nancy Obuchowski,Michael S Middleton,Jun Chen,Kay Pepin,Jessica Magnuson,Kathy J Brown,Danielle Batakis,Walter C Henderson,Sudha S Shankar,Tania N Kamphaus,Alex Pasek,Roberto A Calle,Arun J Sanyal,Rohit Loomba,Richard Ehman,Anthony E Samir,Claude B Sirlin,Sarah P Sherlock
Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient
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Global Variation in Magnetic Resonance Imaging Quality of the Prostate. Radiology (IF 19.7) Pub Date : 2023-10-01 Francesco Giganti,Alexander Ng,Aqua Asif,Vinson Wai-Shun Chan,Marimo Rossiter,Arjun Nathan,Pramit Khetrapal,Louise Dickinson,Shonit Punwani,Chris Brew-Graves,Alex Freeman,Mark Emberton,Caroline M Moore,Clare Allen,Veeru Kasivisvanathan,
Background High variability in prostate MRI quality might reduce accuracy in prostate cancer detection. Purpose To prospectively evaluate the quality of MRI scanners taking part in the quality control phase of the global PRIME (Prostate Imaging Using MRI ± Contrast Enhancement) trial using the Prostate Imaging Quality (PI-QUAL) standardized scoring system, give recommendations on how to improve the
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Expanding Role of Advanced Image Analysis in CT-detected Indeterminate Pulmonary Nodules and Early Lung Cancer Characterization. Radiology (IF 19.7) Pub Date : 2023-10-01 Ashley Elizabeth Prosper,Michael N Kammer,Fabien Maldonado,Denise R Aberle,William Hsu
The implementation of low-dose chest CT for lung screening presents a crucial opportunity to advance lung cancer care through early detection and interception. In addition, millions of pulmonary nodules are incidentally detected annually in the United States, increasing the opportunity for early lung cancer diagnosis. Yet, realization of the full potential of these opportunities is dependent on the
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MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum. Radiology (IF 19.7) Pub Date : 2023-10-01 Christopher O Lew,Longfei Zhou,Maciej A Mazurowski,P Murali Doraiswamy,Jeffrey R Petrella,
Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict
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Guidelines for Use of Large Language Models by Authors, Reviewers, and Editors: Considerations for Imaging Journals. Radiology (IF 19.7) Pub Date : 2023-10-01 Linda Moy
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Revamping Prostate MRI Protocols: From Simple Modifications to Quality Improvement. Radiology (IF 19.7) Pub Date : 2023-10-01 Haidara Almansour,Victoria Chernyak
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MRI Biomarkers and Their Future Impact on Nonalcoholic Fatty Liver Disease. Radiology (IF 19.7) Pub Date : 2023-10-01 Kazuto Kozaka,Osamu Matsui
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Feasibility and Prospect of Privacy-preserving Large Language Models in Radiology. Radiology (IF 19.7) Pub Date : 2023-10-01 Wenli Cai
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Feasibility of Using the Privacy-preserving Large Language Model Vicuna for Labeling Radiology Reports. Radiology (IF 19.7) Pub Date : 2023-10-01 Pritam Mukherjee,Benjamin Hou,Ricardo B Lanfredi,Ronald M Summers
Background Large language models (LLMs) such as ChatGPT, though proficient in many text-based tasks, are not suitable for use with radiology reports due to patient privacy constraints. Purpose To test the feasibility of using an alternative LLM (Vicuna-13B) that can be run locally for labeling radiography reports. Materials and Methods Chest radiography reports from the MIMIC-CXR and National Institutes
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Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis. Radiology (IF 19.7) Pub Date : 2023-10-01 Pedro Vianna,Sara-Ivana Calce,Pamela Boustros,Cassandra Larocque-Rigney,Laurent Patry-Beaudoin,Yi Hui Luo,Emre Aslan,John Marinos,Talal M Alamri,Kim-Nhien Vu,Jessica Murphy-Lavallée,Jean-Sébastien Billiard,Emmanuel Montagnon,Hongliang Li,Samuel Kadoury,Bich N Nguyen,Shanel Gauthier,Benjamin Therien,Irina Rish,Eugene Belilovsky,Guy Wolf,Michaël Chassé,Guy Cloutier,An Tang
Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepatic steatosis in NAFLD at US, with biopsy as the reference standard. Materials and Methods This retrospective study included patients with NAFLD and control
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Multivariable Quantitative US Parameters for Assessing Hepatic Steatosis. Radiology (IF 19.7) Pub Date : 2023-10-01 Hidekatsu Kuroda,Takuma Oguri,Naohisa Kamiyama,Hidenori Toyoda,Satoshi Yasuda,Kento Imajo,Yasuaki Suzuki,Katsutoshi Sugimoto,Tomoyuki Akita,Junko Tanaka,Yutaka Yasui,Masayuki Kurosaki,Namiki Izumi,Atsushi Nakajima,Yudai Fujiwara,Tamami Abe,Keisuke Kakisaka,Takayuki Matsumoto,Takashi Kumada
Background Because of the global increase in the incidence of nonalcoholic fatty liver disease, the development of noninvasive, widely available, and highly accurate methods for assessing hepatic steatosis is necessary. Purpose To evaluate the performance of models with different combinations of quantitative US parameters for their ability to predict at least 5% steatosis in patients with chronic liver
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Cost-effectiveness of Endovascular Treatment for Acute Stroke with Large Infarct: A United States Perspective. Radiology (IF 19.7) Pub Date : 2023-10-01 Johanna Maria Ospel,Wolfgang Gerhard Kunz,Rosalie Victoria McDonough,Mayank Goyal,Kazutaka Uchida,Nobuyuki Sakai,Hiroshi Yamagami,Shinichi Yoshimura,
Background The health economic benefit of endovascular treatment (EVT) in addition to best medical management for acute ischemic stroke with large ischemic core is uncertain. Purpose To assess the cost-effectiveness of EVT plus best medical management versus best medical management alone in treating acute ischemic stroke with large vessel occlusion and a baseline Alberta Stroke Program Early CT Score
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Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers. Radiology (IF 19.7) Pub Date : 2023-10-01 Firas Khader,Gustav Müller-Franzes,Tianci Wang,Tianyu Han,Soroosh Tayebi Arasteh,Christoph Haarburger,Johannes Stegmaier,Keno Bressem,Christiane Kuhl,Sven Nebelung,Jakob Nikolas Kather,Daniel Truhn
Background Clinicians consider both imaging and nonimaging data when diagnosing diseases; however, current machine learning approaches primarily consider data from a single modality. Purpose To develop a neural network architecture capable of integrating multimodal patient data and compare its performance to models incorporating a single modality for diagnosing up to 25 pathologic conditions. Materials
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Beyond Clinical Efficacy to Cost-effectiveness of Endovascular Therapy for Large Acute Infarcts. Radiology (IF 19.7) Pub Date : 2023-10-01 Elysa Widjaja
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Prospective Evaluation of AI Triage of Pulmonary Emboli on CT Pulmonary Angiograms. Radiology (IF 19.7) Pub Date : 2023-10-01 Steven A Rothenberg,Cody H Savage,Asser Abou Elkassem,Satinder Singh,Mostafa Abozeed,Omar Hamki,Kevin Junck,Srini Tridandapani,Mei Li,Yufeng Li,Andrew D Smith
Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic studies. Purpose To determine whether use of an AI triage system to detect PE on CTPA studies improves radiologist performance or examination and report turnaround times in a clinical setting. Materials and Methods This prospective
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Clinical Applications of Photon-counting CT: A Review of Pioneer Studies and a Glimpse into the Future. Radiology (IF 19.7) Pub Date : 2023-10-01 Philippe C Douek,Sara Boccalini,Edwin H G Oei,David P Cormode,Amir Pourmorteza,Loic Boussel,Salim A Si-Mohamed,Ricardo P J Budde
CT systems equipped with photon-counting detectors (PCDs), referred to as photon-counting CT (PCCT), are beginning to change imaging in several subspecialties, such as cardiac, vascular, thoracic, and musculoskeletal radiology. Evidence has been building in the literature underpinning the many advantages of PCCT for different clinical applications. These benefits derive from the distinct features of
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Expectation Meets Reality: AI-powered CT Pulmonary Angiogram Triage in the Real World. Radiology (IF 19.7) Pub Date : 2023-10-01 David J Murphy,Syer Ree Tee
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The Initial Steps of Multimodal AI in Radiology. Radiology (IF 19.7) Pub Date : 2023-10-01 Felipe C Kitamura,Eric J Topol
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Advancing AI-assisted US Screening for Fatty Liver. Radiology (IF 19.7) Pub Date : 2023-10-01 Theresa A Tuthill
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Hepatic Steatosis Assessment: Harnessing the Power of Integrating Multiple Quantitative US Parameters. Radiology (IF 19.7) Pub Date : 2023-10-01 Aiguo Han
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Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion. Radiology (IF 19.7) Pub Date : 2023-09-01 Louis Lind Plesner,Felix C Müller,Mathias W Brejnebøl,Lene C Laustrup,Finn Rasmussen,Olav W Nielsen,Mikael Boesen,Michael Brun Andersen
Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially available AI tools for detection of airspace disease, pneumothorax, and pleural effusion on chest radiographs. Materials and Methods This retrospective
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Clinical Performance of Current-Generation AI Tools for Chest Radiographs. Radiology (IF 19.7) Pub Date : 2023-09-01 Masahiro Yanagawa,Noriyuki Tomiyama
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Four-dimensional Flow MRI Assessment of Portal Hemodynamics and Hepatic Regeneration after Portal Vein Embolization. Radiology (IF 19.7) Pub Date : 2023-09-01 Ryota Hyodo,Yasuo Takehara,Takashi Mizuno,Kazushige Ichikawa,Ryota Horiguchi,Shoji Kawakatsu,Takashi Mizuno,Tomoki Ebata,Shinji Naganawa,Ning Jin,Yoshito Ichiba
Background Percutaneous transhepatic portal vein (PV) embolization (PVE) is a standard preoperative procedure for advanced biliary cancer when the future liver remnant (FLR) is insufficient, yet the effect of this procedure on portal hemodynamics is still unclear. Purpose To assess whether four-dimensional (4D) MRI flowmetry can be used to estimate FLR volume and to identify the optimal time for this
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Automated Background Parenchymal Enhancement Measurements at MRI to Predict Breast Cancer Risk. Radiology (IF 19.7) Pub Date : 2023-09-01 Louisa Bokacheva
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The Potential for Deep Learning Reconstruction to Improve the Quality of T2-weighted Prostate MRI. Radiology (IF 19.7) Pub Date : 2023-09-01 Baris Turkbey
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Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI. Radiology (IF 19.7) Pub Date : 2023-09-01 Leon M Bischoff,Johannes M Peeters,Leonie Weinhold,Philipp Krausewitz,Jörg Ellinger,Christoph Katemann,Alexander Isaak,Oliver M Weber,Daniel Kuetting,Ulrike Attenberger,Claus C Pieper,Alois M Sprinkart,Julian A Luetkens
Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisition time. However, DL reconstruction methods combined with compressed sensing for prostate MRI have not been well studied. Purpose To use an industry-developed DL algorithm to reconstruct low-resolution T2-weighted turbo spin-echo (TSE) prostate MRI scans and compare these with standard sequences. Materials
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Radiologist's Guide to Evaluating Publications of Clinical Research on AI: How We Do It. Radiology (IF 19.7) Pub Date : 2023-09-01 Seong Ho Park,Ah-Ram Sul,Yousun Ko,Hye Young Jang,June-Goo Lee
Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessment of the validity, reproducibility, and clinical applicability of AI studies. However, AI studies are generally perceived to be more difficult for clinician readers to evaluate than traditional clinical research studies. This special report-as an effective
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Four-dimensional Flow MRI Helps Predict Future Liver Remnant Hypertrophy after Transhepatic Portal Vein Embolization. Radiology (IF 19.7) Pub Date : 2023-09-01 Alejandro Roldán-Alzate,Thekla H Oechtering