Multi-Specialty Expert Physician Identification of Extranodal Extension in Computed Tomography Scans of Oropharyngeal Cancer Patients: Prospective Blinded Human Inter-Observer Performance Evaluation.
null nullOnur SahinKareem A WahidNicolette TakuRenjie HeMohamed A NaserAbdallah S R MohamedAntti MäkitieBenjamin H KannKimmo KaskiJaakko SahlstenJoel JaskariMoran AmitMelissa M ChenGregory M ChronowskiEduardo M DiazAdam S GardenRyan P GoepfertJeffrey P GuenetteG Brandon GunnJussi HirvonenFrank HoebersNandita Guha-ThakurtaJason JohnsonDiana KayaShekhar D KhanparaKristofer NymanStephen Y LaiMiriam LangoKim O LearnedAnna LeeCarol M LewisAnastasios ManiakasAmy C MorenoJeffery N MyersJack PhanKristen B PytyniaDavid I RosenthalVlad SandulacheDawid SchellingerhoutShalin J ShahAndrew G SikoraMax WintermarkClifton David FullerPublished in: medRxiv : the preprint server for health sciences (2023)
Detection of ENE in HPV+OPC patients on CT imaging remains a difficult task with high variability, regardless of clinician specialty. Although some differences do exist between the specialists, they are often minimal. Further research in automated analysis of ENE from radiographic images is likely needed.
Keyphrases
- computed tomography
- dual energy
- end stage renal disease
- deep learning
- positron emission tomography
- contrast enhanced
- endothelial cells
- newly diagnosed
- emergency department
- ejection fraction
- magnetic resonance imaging
- chronic kidney disease
- image quality
- primary care
- high resolution
- prognostic factors
- machine learning
- clinical trial
- randomized controlled trial
- high throughput
- high grade
- optical coherence tomography
- study protocol
- mass spectrometry
- magnetic resonance
- real time pcr
- quantum dots
- clinical evaluation
- bioinformatics analysis