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Entropy-Based CT Radiomics as an Imaging Marker of Hepatic Injury in COVID-19.

Background: Hepatic involvement in COVID-19 is frequently observed, yet conventional CT imaging may fail to detect subtle parenchymal altera … ation, and vascular congestion, aligning with radiomic abnormalities. Conclusions: Entropy-based CT radiomics reflect microstructural liver alterations in COVID-19, supported by both biochemical and histopathological data. This approach may enhance the detection of hepatic injury beyond conventional imaging and could be explored in systemic infections.

Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI.

Rectal cancer (RC) is one of the most common malignant tumors of the digestive system and has an alarmingly high incidence and mortality rate globally. Compared to conventional imaging examinations, radiomics can extract quantitative features that reflect tumor heterogeneity and mine data from medical images. In this review, we discuss the potential value of multimodal MRI-based radiomics in the diagnosis and treatment of RC, with a special emphasis on the role of peritumoral tissue characteristics in clinical decision-making. Existing studies have shown that a radiomics model integrating intr…

The added value of radiomic analysis for predicting spontaneous preterm birth in the first trimester.

BACKGROUND AND OBJECTIVE: Preterm birth (PTB) is a public health problem. Researchers have worked to identify ways to detect women at risk for PTB early in pregnancy. Although existing biomarkers allow some women to be detected in the second trimester, detection in the first trimester is warranted to initiate earlier interventions. This study aims to explore the added value of radiomic analysis of transvaginal ultrasound (TVUS) images in the construction of first-trimester risk assessment models for predicting spontaneous preterm birth (sPTB). METHODS: A retrospective cohort study was conduct

A comparison between radiomic biological age and chronological age in estimating kidney function.

Accurate kidney function estimation hinges on essential markers of age and body size. The relative benefit of both markers has been debated with the emerging biological age and novel body size descriptors. We used radiomic biomarkers of age-related changes in body composition to construct new biological age indices as covariates of kidney function. A retrospective cohort of hospitalized patients with plasma concentrations of aminoglycosides and computed tomography images were evaluated. Aminoglycoside clearance served as a kidney function surrogate. A population pharmacokinetic model was const

Ultrasound radiomics for identifying microstructural changes in the femoral head with developmental dysplasia of the hip.

BACKGROUND: Non-invasive imaging methods for evaluating microstructural changes in patients with developmental dysplasia of the hip (DDH) are lacking. OBJECTIVE: To explore the feasibility of hip ultrasound radiomics to evaluate microstructural changes of the femoral head in patients with DDH. MATERIALS AND METHODS: A retrospective analysis was conducted on 59 patients with DDH and 66 healthy controls who underwent hip ultrasound examination. We used three-dimensional (3D) Slicer software to obtain femoral head ultrasound radiomics features and compared them between the DDH and healthy contr…

Radiomic identification of anemia features in monochromatic conjunctiva photographs in school-age children.

SIGNIFICANCE: Anemia remains a substantial global health challenge. Delayed detection often leads to various health complications. In school … l and textural characteristics of the conjunctiva microvasculature for anemia detection. APPROACH: Radiomics, an emerging machine learning approach for conventional medical imaging, is applied to conjunctiva photos to analyze morphological alterations in the microvasculature beyond direct visualization. Radiomic analyses are conducted on 12,441 palpebral a …

Integrating PET and MRI Radiomics for Staging and Prognostic Stratification in Anal Canal Cancer.

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Radiomics analysis for the early diagnosis of common sexually transmitted infections and skin lesions.

Early identification of sexually transmitted infection (STI) symptoms can prevent subsequent complications and improve STI control. We analysed 597 images from STIAtlas and categorised the images into four typical STIs and two skin lesions by the anatomical sites of infections. We first applied nine image filters and 11 machine-learning image classifiers to the images. We then extracted radiomics features from the filtered images and trained them with 99 models that combined image filters and classifiers. Model performance was evaluated by area under curve (AUC) and permutation importance. Whe…

Радиомикальный подход к клиническому МРТ проясняет связь между Таламом и Когницией в множестве склерозов.

СПРАВОЧНАЯ ИНФОРМАЦИЯ И ЦЕЛЬ: Радиомика излучает изображения, которые, возможно, не поддаются обнаружению в ходе обычного объемного анализа. Учитывая их роль в множестве склероза (MS), мы применили радиомедики к таламическим ядрам и изучили их связи с когнитивными характеристиками. МЕТОДЫ: В общей сложности 601 человек были включены (342 человека с MS [PwMS] из двух когорт и 259 лиц, осуществляющих контроль за состоянием здоровья. Радиомикальные функции (RF) и тома были получены из всего таламуса, пяти таламических ядер, и мутамен был разделен на трехмерные изображения Т1. Когнитивные характер

Совпадение в аннотации оригинала
BACKGROUND AND PURPOSE: Radiomics extracts imaging features that may not be detectable through conventional volumetric analyses. Given their role in multiple sclerosis (MS), we applied radiomics to thalamic nuclei and examined their associations with cognitive performance. METHODS: A total of 601 individuals were included (342 people with MS [PwMS] from two…

Radiomics to Detect Inflammation and Fibrosis on Magnetic Resonance Enterography in Stricturing Crohn's Disease.

BACKGROUND AND AIMS: Non-invasive cross-sectional imaging via magnetic resonance enterography [MRE] offers excellent accuracy for the diagnosis of stricturing complications in Crohn's disease [CD] but is limited in determining the degrees of fibrosis and inflammation within a stricture. We developed and validated a radiomics-based machine-learning model for separately characterizing the degree of histopathological inflammation and fibrosis in CD strictures and compared it to centrally read visual radiologist scoring of MRE. METHODS: This single-centre, cross-sectional study included 51 CD pat…

Radiomic- and dosiomic-based clustering development for radio-induced neurotoxicity in pediatric medulloblastoma.

BACKGROUND: Texture analysis extracts many quantitative image features, offering a valuable, cost-effective, and non-invasive approach for individual medicine. Furthermore, multimodal machine learning could have a large impact for precision medicine, as texture biomarkers can underlie tissue microstructure. This study aims to investigate imaging-based biomarkers of radio-induced neurotoxicity in pediatric patients with metastatic medulloblastoma, using radiomic and dosiomic analysis. METHODS: This single-center study retrospectively enrolled children diagnosed with metastatic medulloblastoma

CT and MRI radiomic features of lung cancer (NSCLC): comparison and software consistency.

BACKGROUND: Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques. METHODS: Contrast-enhanced CT and MRI images of 35 patients affected wi…

Predictive value of radiomics for intracranial aneurysm rupture: a systematic review and meta-analysis.

OBJECTIVE: To systematically review the literature on radiomics for predicting intracranial aneurysm rupture and conduct a meta-analysis to obtain evidence confirming the value of radiomics in this prediction. METHODS: A systematic literature search was conducted in PubMed, Web of Science, Embase, and The Cochrane Library databases up to March 2024. The QUADAS-2 tool was used to assess study quality. Stata 15.0 and Review Manager 5.4.1 were used for statistical analysis. Outcomes included combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (+LR), negative likelihood ratio…

Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

BACKGROUND: Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. METHODS: We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol includ…

Robustness and classification capabilities of MRI radiomic features in identifying carotid plaque vulnerability.

OBJECTIVES: To assess how radiomic features may be combined with plaque morphological and compositional features identified by multi-contras … ty of the results were investigated by assessing the robustness of the radiomic features. RESULTS: Radiomics combined with a relatively conventional plaque morphological and compositional metric-based model provided incremental value over a conventional model alone (area under curve [AUC], 0.819 ± 0.002 vs 0.689 ± 0.019, respectively, P = .014). The radiom …

Combining Radiomics and Autoencoders to Distinguish Benign and Malignant Breast Tumors on US Images.

Background US is clinically established for breast imaging, but its diagnostic performance depends on operator experience. Computer-assisted (real-time) image analysis may help in overcoming this limitation. Purpose To develop precise real-time-capable US-based breast tumor categorization by combining classic radiomics and autoencoder-based features from automatically localized lesions. Materials and Methods A total of 1619 B-mode US images of breast tumors were retrospectively analyzed between April 2018 and January 2024. nnU-Net was trained for lesion segmentation. Features were extracted fr…

Radiomics as a measure superior to common similarity metrics for tumor segmentation performance evaluation.

PURPOSE: To propose radiomics features as a superior measure for evaluating the segmentation ability of physicians and auto-segmentation tools and to compare its performance with the most commonly used metrics: Dice similarity coefficient (DSC), surface Dice similarity coefficient (sDSC), and Hausdorff distance (HD). MATERIALS/METHODS: The data of 10 lung cancer patients' CT images with nine tumor segmentations per tumor were downloaded from the RIDER (Reference Database to Evaluate Response) database. Radiomics features of 90 segmented tumors were extracted using the PyRadiomics program. The…

An automatic radiomic-based approach for disease localization: A pilot study on COVID-19.

Radiomics is an innovative field in Personalized Medicine to help medical specialists in diagnosis and prognosis. Mainly, the application of Radiomics to medical images requires the definition and delimitation of the Region Of Interest (ROI) on the medical image to extract radiomic features. The aim of this preliminary study is to define an approach that automatically detects the specific areas indicative of a particular disease and examines them to minimize diagnostic errors associated with false positives and false negatives. This approach aims to create a nxn grid on the DICOM image sequenc…

Interobserver delineation variability of computed tomography-based radiomic features of the parotid gland.

PURPOSE: To assess the interobserver delineation variability of radiomic features of the parotid gland from computed tomography (CT) images and evaluate the correlation of these features for head and neck cancer (HNC) radiotherapy patients. MATERIALS AND METHODS: Contrast-enhanced CT images of 20 HNC patients were utilized. The parotid glands were delineated by treating radiation oncologists (ROs), a selected RO and AccuContour auto-segmentation software. Dice similarity coefficients (DSCs) between each pair of observers were calculated. A total of 107 radiomic features were extracted, whose

The prognostic role of MRI-based radiomics in tongue carcinoma: a multicentric validation study.

PURPOSE: Radiomics is an emerging field that utilizes quantitative features extracted from medical images to predict clinically meaningful outcomes. Validating findings is crucial to assess radiomics applicability. We aimed to validate previously published magnetic resonance imaging (MRI) radiomics models to predict oncological outcomes in oral tongue squamous cell carcinoma (OTSCC). MATERIALS AND METHODS: Retrospective multicentric study on OTSCC surgically treated from 2010 to 2019. All patients performed preoperative MRI, including contrast-enhanced T1-weighted (CE-T1), diffusion-weighted …