Promise and pitfalls of quantitative imaging in oncology clinical trials. - Wikidata - awgldk - TriplyDB

Promise and pitfalls of quantitative imaging in oncology clinical trials.

Promise and pitfalls of quantitative imaging in oncology clinical trials.

http://www.wikidata.org/entity/Q36303765

about

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach Quantitative imaging in cancer evolution and ecology MR Imaging Biomarkers in Oncology Clinical Trials Strategies for modern biomarker and drug development in oncology.Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling.Demonstration of nonlinearity bias in the measurement of the apparent diffusion coefficient in multicenter trials.Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data.Metadata-driven Clinical Data Loading into i2b2 for Clinical and Translational Science Institutes.Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.Methods and challenges in quantitative imaging biomarker development Clinical utility of quantitative imaging.Do 18F-FDG PET/CT parameters in oropharyngeal and oral cavity squamous cell carcinomas indicate HPV status?Molecular Magnetic Resonance Imaging of Tumor Response to Therapy.Correction of Gradient Nonlinearity Bias in Quantitative Diffusion Parameters of Renal Tissue with Intra Voxel Incoherent Motion Prognostic value of FDG PET/CT-based metabolic tumor volumes in metastatic triple negative breast cancer patients 18F-FDG-PET/CT parameters as imaging biomarkers in oral cavity squamous cell carcinoma, is visual analysis of PET and contrast enhanced CT better than the numbers?Applications and limitations of radiomics QIN DAWG Validation of Gradient Nonlinearity Bias Correction Workflow for Quantitative Diffusion-Weighted Imaging in Multicenter Trials Dynamic contrast-enhanced magnetic resonance imaging in prostate cancer clinical trials: potential roles and possible pitfalls.Radiology and Enterprise Medical Imaging Extensions (REMIX).Managers of Molecular Imaging Laboratories (MOMIL) Interest Group.Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study.Translation in solid cancer: are size-based response criteria an anachronism?Targeting Hypoxia to Improve Non-Small Cell Lung Cancer Outcome.Radiomic features analysis in computed tomography images of lung nodule classification.Compartment modeling of dynamic brain PET--the impact of scatter corrections on parameter errors.Special Section Guest Editorial: Quantitative Imaging and the Pioneering Efforts of Laurence P. Clarke.Feasibility of state of the art PET/CT systems performance harmonisation.Validating the Imaging Biomarker: The Proof of Efficacy and Effectiveness

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Promise and pitfalls of quantitative imaging in oncology clinical trials.

http://www.wikidata.org/entity/Q36303765

description

2012 nî lūn-bûn

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2012年の論文

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2012年学术文章

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2012年学术文章

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2012年学术文章

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2012年学术文章

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2012年學術文章

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2012年學術文章

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2012年學術文章

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Promise and pitfalls of quantitative imaging in oncology clinical trials.

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Promise and pitfalls of quantitative imaging in oncology clinical trials.

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Promise and pitfalls of quantitative imaging in oncology clinical trials.

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J.MRI.2012.06.009

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Magnetic Resonance Imaging

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Promise and pitfalls of quantitative imaging in oncology clinical trials

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Christopher W Ryan

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Edward A Eikman

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Elizabeth R Gerstner

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Fiona M Fennessy

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Frank S Lieberman

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James M Mountz

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Kenneth M Forster

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Lawrence H Schwartz

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Richard L Wahl

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P2860

Need for standardization of 18F-FDG PET/CT for treatment response assessments

New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)

Reduced lung-cancer mortality with low-dose computed tomographic screening

Efficacy and safety of imatinib mesylate in advanced gastrointestinal stromal tumors

AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients.

Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results.

Validation of novel imaging methodologies for use as cancer clinical trial end-points

Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment.

Phase II study of risk-adapted therapy of newly diagnosed, aggressive non-Hodgkin lymphoma based on midtreatment FDG-PET scanning.

Advanced MRI and PET imaging for assessment of treatment response in patients with gliomas.

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1301-1312

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