Clinical and radiomic features for predicting the treatment response of repetitive transcranial magnetic stimulation in major neurocognitive disorder: Results from a randomized controlled trial
Sign Up to like & getrecommendations! Published in 2022 at "Human Brain Mapping"
DOI: 10.1002/hbm.26032
Abstract: Image‐guided repetitive transcranial magnetic stimulation (rTMS) has shown clinical effectiveness in senior adults with co‐occurring depression and cognitive impairment, yet the imaging markers for predicting the treatment response are less investigated. In this clinical trial,… read more here.
Keywords: transcranial magnetic; rtms; repetitive transcranial; treatment ... See more keywords
Assessment of severity in neuropsychiatric disorders based on radiomic features with prior shape level set and metaheuristic algorithms
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22306
Abstract: The diagnostic and clinical overlap between schizophrenia (SZ) and schizoaffective (SA) is vital oncological issue in psychiatry disorder. This study is designed to examine tissue variation in cerebellum region. Shape prior levelset method is used… read more here.
Keywords: radiomic features; shape; features extracted; cerebellum ... See more keywords
Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi‐institutional study
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Magnetic Resonance Imaging"
DOI: 10.1002/jmri.25562
Abstract: To evaluate in a multi‐institutional study whether radiomic features useful for prostate cancer (PCa) detection from 3 Tesla (T) multi‐parametric MRI (mpMRI) in the transition zone (TZ) differ from those in the peripheral zone (PZ). read more here.
Keywords: multi institutional; institutional study; radiomic features; prostate cancer ... See more keywords
Reliability of tumor segmentation in glioblastoma: impact on the robustness of MRI-radiomic features.
Sign Up to like & getrecommendations! Published in 2019 at "Medical physics"
DOI: 10.1002/mp.13624
Abstract: PURPOSE The use of radiomic features as biomarkers of treatment response and outcome or as correlates to genomic variations requires that the computed features are robust and reproducible. Segmentation, a crucial step in radiomic analysis,… read more here.
Keywords: radiomic features; mri radiomic; segmentation; method ... See more keywords
Machine learning prediction of axillary lymph node metastasis in breast cancer: 2D versus 3D radiomic features.
Sign Up to like & getrecommendations! Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14538
Abstract: PURPOSE The purpose of this study was to distinguish axillary lymph node (ALN) status using preoperative breast DCE-MRI radiomics and compare the effects of 2D and 3D analysis. METHODS A retrospective study including 154 breast… read more here.
Keywords: radiomic features; machine learning; breast; analysis ... See more keywords
Identification of reproducible radiomic features from on-board volumetric images: A multi-institutional phantom study.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16376
Abstract: BACKGROUND Radiomics analysis using on-board volumetric images has attracted research attention as a method for predicting prognosis during treatment; however, the lack of standardization is still one of the main concerns. PURPOSE This study investigated… read more here.
Keywords: filter based; volumetric images; radiomic features; treatment ... See more keywords
A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images
Sign Up to like & getrecommendations! Published in 2017 at "European Radiology"
DOI: 10.1007/s00330-017-5154-8
Abstract: ObjectivesTo develop a model using radiomic features extracted from MR images to distinguish radiation necrosis from tumour progression in brain metastases after Gamma Knife radiosurgery.MethodsWe retrospectively identified 87 patients with pathologically confirmed necrosis (24 lesions)… read more here.
Keywords: radiomic features; tumour progression; radiation necrosis; necrosis tumour ... See more keywords
Differentiation between pilocytic astrocytoma and glioblastoma: a decision tree model using contrast-enhanced magnetic resonance imaging-derived quantitative radiomic features
Sign Up to like & getrecommendations! Published in 2018 at "European Radiology"
DOI: 10.1007/s00330-018-5706-6
Abstract: ObjectiveTo differentiate brain pilocytic astrocytoma (PA) from glioblastoma (GBM) using contrast-enhanced magnetic resonance imaging (MRI) quantitative radiomic features by a decision tree model.MethodsSixty-six patients from two centres (PA, n = 31; GBM, n = 35)… read more here.
Keywords: tree model; radiomic features; model; contrast enhanced ... See more keywords
Classification of early stage non-small cell lung cancers on computed tomographic images into histological types using radiomic features: interobserver delineation variability analysis
Sign Up to like & getrecommendations! Published in 2017 at "Radiological Physics and Technology"
DOI: 10.1007/s12194-017-0433-2
Abstract: Radiomics, which involves the extraction of large numbers of quantitative features from medical images, has attracted attention in cancer research. In radiomics analysis, tumor segmentation is a crucial step. In this study, we evaluated the… read more here.
Keywords: radiomic features; delineation; analysis; variability ... See more keywords
Radioproteomics in Breast Cancer: Prediction of Ki-67 Expression With MRI-based Radiomic Models.
Sign Up to like & getrecommendations! Published in 2021 at "Academic radiology"
DOI: 10.1016/j.acra.2021.02.001
Abstract: RATIONALE AND OBJECTIVES We aimed to investigate the value of magnetic resonance image (MRI)-based radiomics in predicting Ki-67 expression of breast cancer. METHODS In this retrospective study, 159 lesions from 154 patients were included. Radiomic… read more here.
Keywords: radiomic features; mri based; breast cancer; expression ... See more keywords
Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients
Sign Up to like & getrecommendations! Published in 2021 at "Computers in Biology and Medicine"
DOI: 10.1016/j.compbiomed.2021.104304
Abstract: Objective To develop prognostic models for survival (alive or deceased status) prediction of COVID-19 patients using clinical data (demographics and history, laboratory tests, visual scoring by radiologists) and lung/lesion radiomic features extracted from chest CT… read more here.
Keywords: using clinical; covid patients; radiomic features; value ... See more keywords