ArticlePhysics and imaging in radiation oncology2021
Intensity standardization methods in magnetic resonance imaging of head and neck cancer.
Article in Physics and imaging in radiation oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Population-Level Age Effects on the White Matter Structure Subserving Cognitive Flexibility in the Human Brain.eNeuro · 2026Pooled it
- Quantification of intervertebral disc degeneration using dual-energy computed tomography collagen maps: a comparative study with MRI Pfirrmann grading.Scientific reports · 2026Article
- Validation of MRI-based nnU-Net model for automated segmentation of neck lymph nodes in head and neck squamous cell carcinoma: a multicenter study.Neuroradiology · 2026Article
- Evaluating synthetic CT from deformable registration in directed adaptive radiotherapy for head and neck cancer.Journal of applied clinical medical physics · 2026Article
- Black bone MRI morphometry for mandibular cortical bone measurement in head and neck cancer patients: prospective method comparison with CT.Oral surgery, oral medicine, oral pathology and oral radiology · 2026Article
- Unpaired volumetric harmonization of brain MRI with conditional latent diffusion.Medical image analysis · 2026Article
- An MRI-derived head-neck finite element model.Biomechanics and modeling in mechanobiology · 2025Article
- Quantitative cardiac magnetic resonance standardized signal intensity comparison in dilated cardiomyopathy vs. cardiac sarcoidosis.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2025Article
- Evaluation of normalized T1 signal intensity obtained using an automated segmentation model in lower leg MRI as a potential imaging biomarker in Charcot-Marie-Tooth disease type 1 A.Scientific reports · 2025Article
- Towards quantitative intensity analysis of conventional T1-weighted images in multiple sclerosis.NeuroImage · 2025Article
- Exploring Quantitative MRI Biomarkers of Head and Neck Post-Radiation Lymphedema and Fibrosis: Post Hoc Analysis of a Prospective Trial.Head & neck · 2025Article
- Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRI.Head and Neck Tumor Segmentation for MR-Guided Applications : First MICCAI Challenge, HNTS-MRG 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, proceedings · 2025Article
- Baseline [European journal of nuclear medicine and molecular imaging · 2024Article
- Review
- Imaging of human papilloma virus (HPV) related oropharynx tumour: what we know to date.Infectious agents and cancer · 2023Review
- Multimodality radiomics analysis based on [European radiology · 2023Article
- A transformer-based hierarchical registration framework for multimodality deformable image registration.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2023Article
- Magnetic resonance imaging in naso-oropharyngeal carcinoma: role of texture analysis in the assessment of response to radiochemotherapy, a preliminary study.La Radiologia medica · 2023Observational
- Harmonization Strategies in Multicenter MRI-Based Radiomics.Journal of imaging · 2022Review
- Deep-learning-based generation of synthetic 6-minute MRI from 2-minute MRI for use in head and neck cancer radiotherapy.Frontiers in oncology · 2022Article
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Authors and funding
19 authors.
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Abstract
background and purposeConventional magnetic resonance imaging (MRI) poses challenges in quantitative analysis because voxel intensity values lack physical meaning. While intensity standardization methods exist, their effects on head and neck MRI have not been investigated. We developed a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluated intensity standardization methods for MRI of head and neck cancer (HNC) patients. MATERIALS AND
methodsTwo HNC cohorts (30 patients total) were retrospectively analyzed. One cohort was imaged with heterogenous acquisition parameters (HET cohort), whereas the other was imaged with homogenous acquisition parameters (HOM cohort). The standard deviation of cohort-level normalized mean intensity (SD NMI
resultsConsistency (SD NMI
conclusionsOur findings stress the importance of intensity standardization, either through the utilization of uniform acquisition parameters or specific intensity standardization methods, and the need for testing intensity consistency before performing quantitative analysis of HNC MRI.
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