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Volume Delineation in Cervical Cancer With T2 and Diffusion-weighted MRI: Agreement on Volumes Between Observers

Consuelo Rosa, Andrea Delli Pizzi, Antonietta Augurio, L. Caravatta, M. Di Tommaso, Erica Mincuzzi, Sebastiano Cinalli, Raffaella Basilico, Annamaria Porreca, Marta Di Nicola, Domenico Genovesi

2020In Vivo13 citationsDOIOpen Access PDF

Abstract

Aim: To delineate cervical cancer gross tumor volume (GTV) on T2-magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps, assessing volumes and inter-observer agreement between two observers. Patients and Methods: A radiologist and a radiation oncologist delineated GTV on T2 (T2<sub>GTV</sub>) and ADC (ADC<sub>GTV</sub>) sequences. Dice similarity index (DICE) and Bland–Altman analysis were used to estimated concordance. Results: Mean T2<sub>GTV</sub> and ADC<sub>GTV</sub> volumes were 43.84±71.47 cc and 37.28±68.92 cc according to the radiologist, and 43.4±70.44 cc and 36.65±69.21 cc according to the radiation oncologist. ADC led to statistically significantly smaller volumes compared to T2. The mean DICE index was 0.86 for T2<sub>GTV</sub> and 0.84 for ADC<sub>GTV</sub>. The Bland–Altman plots globally showed concordance. Conclusion: GTV delineation was smaller in the ADC maps compared to T2-MRI, reaching an almost perfect agreement between observers. Thanks to this acceptable variability, adding functional imaging might provide more information for tumor delineation, improving reproducibility for image-guided adaptive radiotherapy.

Topics & Concepts

Nuclear medicineMedicineReproducibilityRadiation oncologistMagnetic resonance imagingEffective diffusion coefficientConcordanceDiffusion MRITomotherapyRadiation therapyLimits of agreementRadiologyMathematicsStatisticsInternal medicineEndometrial and Cervical Cancer TreatmentsMRI in cancer diagnosisRadiomics and Machine Learning in Medical Imaging
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