MRI-based tumour control probability in skull-base chordomas treated with carbon-ion therapy. (August 2019)

• Record Type: Journal Article
• Authors: Buizza, Giulia; Molinelli, Silvia; D'Ippolito, Emma; Fontana, Giulia; Pella, Andrea; Valvo, Francesca; Preda, Lorenzo; Orecchia, Roberto; Baroni, Guido; Paganelli, Chiara
• Is Part Of: Radiotherapy and oncology. Volume 137(2019)
• Page Start: 32
• Page End: 37
• Publication Date: 2019-08
• Subjects: Diffusion Magnetic Resonance Imaging -- Heavy ion radiotherapy -- Chordoma -- Skull base; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2019.04.018
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: Skull-base chordoma response to carbon-ion therapy is not fully characterized. Diffusion-weighted MRI provides ADC maps that can be related to cellular density. MRI can provide patient-specific information for tumour control probability models. Abstract: Purpose: To derive personalized tumour control probability (TCP) models, using diffusion-weighted (DW-) MRI for defining initial tumour cellular density in skull-base chordoma patients undergoing carbon-ion radiotherapy (CIRT). Materials and methods: 67 patients affected by skull-base chordoma were enrolled for a standardized CIRT treatment (70.4 Gy (RBE) prescription dose). Local control information was clinically assessed. For 20 of them, apparent diffusion coefficient (ADC) maps were computed from DW-MRI and then converted into cellular density. Radiosensitivity parameters ( α, β ) were estimated from the available data through an optimization procedure, taking advantage of a relationship observed between local control and the dose received by at least the 98% of the gross tumour volume. These parameters were fed into two poissonian TCP models, based on the LQ model, being the first (TCPLIT ) computed from literature parameters and the second (TCPADC ) enriched by a personalized initial cellular density derived from ADC maps. Results: The inclusion of the cellular density derived from ADC into TCPADC yielded slightly higher dose values at which TCP = 0.5 (D50 = 38.91 Gy (RBE)) with respect to TCPLIT (D50 34.16 Gy (RBE)). This suggested a more conservative approach, even if the prognostic power of TCPADC and TCPLIT, tested with respect to local control, was equivalent in terms of sensitivity (0.867) and specificity (0.600). Conclusions: Both TCPADC and TCPLIT exhibited good agreement with a clinically validated information of local control, the former providing more conservative predictions.