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Radiomics Analysis of Magnetic Resonance Proton Density Fat Fraction for the Diagnosis of Hepatic Steatosis in Patients With Suspected NonAlcoholic Fatty Liver Disease

Sim KC, Kim MJ, Cho Y, Kim HJ, Park BJ, Sung DJ, Han NY, Han YE, Kim TH, Lee YJ

Background: This study aimed to assess the diagnostic feasibility of radiomics analysis based on magnetic resonance (MR)-proton density fat fraction (PDFF) for grading hepatic steatosis in patients with suspected non-alcoholic...
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Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy

Kim KM, Hwang H, Sohn B, Park K, Han K, Ahn SS, Lee W, Chu MK, Heo K, Lee SK

Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and...
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Association of Fluorodeoxyglucose Positron Emission Tomography Radiomics Features with Clinicopathological Factors and Prognosis in Lung Squamous Cell Cancer

Erol M, Önner H, Küçükosmanoğlu

Aim To evaluate the role of fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics features (RFs) for predicting clinicopathological factors (CPFs) and prognosis in patients with resected lung squamous...
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Development and Validation of a Model Using Radiomics Features from an Apparent Diffusion Coefficient Map to Diagnose Local Tumor Recurrence in Patients Treated for Head and Neck Squamous Cell Carcinoma

Kim M, Lee JH, Joo L, Jeong B, Kim S, Ham S, Yun J, Kim N, Chung SR, Choi YJ, Baek JH, Lee JY, Kim Jh

Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and...
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Evolution of Radiological Treatment Response Assessments for Cancer Immunotherapy: From iRECIST to Radiomics and Artificial Intelligence

Kim N, Lee ES, Won SE, Yang M, Lee AJ, Shin Y, Ko Y, Pyo J, Park HJ, Kim KW

Immunotherapy has revolutionized and opened a new paradigm for cancer treatment. In the era of immunotherapy and molecular targeted therapy, precision medicine has gained emphasis, and an early response assessment...
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Combination of 18 F-Fluorodeoxyglucose PET/CT Radiomics and Clinical Features for Predicting Epidermal Growth Factor Receptor Mutations in Lung Adenocarcinoma

Li S, Li Y, Zhao M, Wang P, Xin J

Objective: To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on 18 F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19...
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Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke

Zhou Y, Wu D, Yan S, Xie Y, Zhang S, Lv W, Qin Y, Liu Y, Liu C, Lu J, Li J, Zhu H, Liu WV, Liu H, Zhang G, Zhu W

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean...
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Artificial Intelligence in Neuroimaging: Clinical Applications

Choi KS, Sunwoo L

Artificial intelligence (AI) powered by deep learning (DL) has shown remarkable progress in image recognition tasks. Over the past decade, AI has proven its feasibility for applications in medical imaging....
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Prediction of Cognitive Progression in Individuals with Mild Cognitive Impairment Using Radiomics as an Improvement of the ATN System: A Five-Year Follow-Up Study

Song R, Wu X, Liu H, Guo D, Tang L, Zhang W, Feng J, Li C

Objective: To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). Materials and Methods: A...
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Quality of Radiomics Research on Brain Metastasis: A Roadmap to Promote Clinical Translation

Park CJ, Park YW, Ahn SS, Kim D, Kim EH, Kang SG, Chang JH, Kim SH, Lee SK

Objective: Our study aimed to evaluate the quality of radiomics studies on brain metastases based on the radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual...
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Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

Park YW, Lee N, Ahn SS, Chang JH, Lee SK

Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid...
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Computed tomography-based radiomic model predicts radiological response following stereotactic body radiation therapy in early-stage non-small-cell lung cancer and pulmonary oligo-metastases

Cheung BMF, Lau KS, Lee VHF, Leung TW, Kong FMS, Luk MY, Yuen KK

Purpose: Radiomic models elaborate geometric and texture features of tumors extracted from imaging to develop predictors for clinical outcomes. Stereotactic body radiation therapy (SBRT) has been increasingly applied in the...
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Prediction of Prognosis in Glioblastoma Using Radiomics Features of Dynamic Contrast-Enhanced MRI

Pak E, Choi KS, Choi SH, Park CK, Kim TM, Park SH, Lee JH, Lee ST, Hwang I, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods: One hundred and fifty patients (92 male [61.3%];...
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Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

Purkayastha S, Xiao Y, Jiao Z, Thepumnoeysuk R, Halsey K, Wu J, Tran TML, Hsieh B, Choi JW, Wang D, Vallières M, Wang R, Collins S, Feng X, Feldman M, Zhang PJ, Atalay M, Sebro R, Yang L, Fan Y, Liao Wh, Bai HX

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials...
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Breast Ultrasound Microvascular Imaging and Radiogenomics

Park AY, Seo BK, Han MR

Microvascular ultrasound (US) techniques are advanced Doppler techniques that provide high sensitivity and spatial resolution for detailed visualization of low-flow vessels. Microvascular US imaging can be applied to breast lesion...
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Performance of Prediction Models for Diagnosing Severe Aortic Stenosis Based on Aortic Valve Calcium on Cardiac Computed Tomography: Incorporation of Radiomics and Machine Learning

Kang Ng, Suh YJ, Han K, Kim YJ, Choi BW

Objective: We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms. Materials...
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Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage

Song Z, Guo D, Tang Z, Liu H, Li X, Luo S, Yao X, Song W, Song J, Zhou Z

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in...
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Quality Reporting of Radiomics Analysis in Mild Cognitive Impairment and Alzheimer’s Disease: A Roadmap for Moving Forward

Won SY, Park YW, Park M, Ahn SS, Kim J, Lee SK

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement...
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Squamous Cell Carcinoma and Lymphoma of the Oropharynx: Differentiation Using a Radiomics Approach

Bae S, Choi YS, Sohn B, Ahn SS, Lee SK, Yang J, Kim J

The purpose of this study was to evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based machine learning algorithms in differentiating squamous cell carcinoma (SCC) from lymphoma in the oropharynx....
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Evaluating Focal 18F-FDG Uptake in Thyroid Gland with Radiomics

Aksu A, Şen NPK, Acar E, Kaya G

Purpose: The aim of this study was to evaluate the ability of 18F-FDG PET/CT texture analysis to predict the exact pathological outcome of thyroid incidentalomas. Methods: 18F-FDG PET/CT images between March...
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