MRI-based tumour control probability in skull-base chordomas treated with carbon-ion therapy

Radiother Oncol. 2019 Aug:137:32-37. doi: 10.1016/j.radonc.2019.04.018. Epub 2019 Apr 30.

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 (D5034.16 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.

Keywords: Chordoma; Diffusion Magnetic Resonance Imaging; Heavy ion radiotherapy; Skull base.

MeSH terms

  • Chordoma / diagnostic imaging
  • Chordoma / radiotherapy*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Heavy Ion Radiotherapy* / methods
  • Humans
  • Probability
  • Skull Base Neoplasms / diagnostic imaging
  • Skull Base Neoplasms / radiotherapy*