Predictive role of Apparent Diffusion Coefficient (ADC) from Diffusion Weighted MRI in patients with sacral chordoma treated with carbon ion radiotherapy (CIRT) alone. Issue 126 (May 2020) - Preda, Lorenzo; Casale, Silvia; Fanizza, Marianna; Fiore, Maria Rosaria; Viselner, Gisela; Paganelli, Chiara; Buizza, Giulia; Fontana, Giulia; Vitolo, Viviana; Barcellini, Amelia; Baroni, Guido; Fossati, Piero; et al.
Highlights: Baseline ADC could predict response to treatment in sacral chordoma treated with CIRT. Chordoma lesions with different baseline ADC, differently respond to CIRT. DWI as an imaging biomarker of treatment response in sacral chordoma. Abstract: Purpose: To evaluate if baseline ADC from DWI sequences could predict response to treatment in patients with sacral chordoma not suitable for surgery treated with carbon ion radiotherapy (CIRT) alone compared with volume changes. Methods: Fifty-nine patients with sacral chordoma not suitable for surgery underwent one cycle of CIRT alone and a minimum of 12-months follow-up. All patients underwent MRI before treatment (baseline), every three months in the first two years after treatment, and every six months afterwards. For each MRI, lesion volume was obtained and median, kurtosis, and skewness ADC were analyzed within the whole lesion volume. Volume changes between baseline and the last available follow-up were used to divide patients with partial response, progression of disease and stable disease (PR, PD, and SD). Results: Ten patients were excluded since DWI sequences from baseline MRI were not available. ADC maps obtained from baseline DWI examinations of 50 lesions in the remaining 49 patients were considered. Seven lesions were categorized as PD, 30 PR, and 13 SD. PD showed significantly higher median ADC values at baseline (p = 0.003) compared with both PR and SD (1665vs1253vs1263 *10 −6 mm²/s), and more negative skewness values (-0.26vs0.26vs0.08), although not significantly different (p = 0.16). Conclusions: Preliminary results suggest that baseline ADC could predict response to treatment with CIRT, particularly to detect potential non-responder patients.