A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer

• Published in: Radiotherapy and oncology 2010-02, Vol.94 (2), p.206-212
• Main Authors: Broggi, Sara, Fiorino, Claudio, Dell’Oca, Italo, Dinapoli, Nicola, Paiusco, Marta, Muraglia, Alessandro, Maggiulli, Eleonora, Ricchetti, Francesco, Valentini, Vincenzo, Sanguineti, Giuseppe, Cattaneo, Giovanni Mauro, Di Muzio, Nadia, Calandrino, Riccardo
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Dose Fractionation; Female; Head and neck cancer; Head and Neck Neoplasms - radiotherapy; Hematology, Oncology and Palliative Medicine; Humans; Linear Models; Logistic Models; Male; Middle Aged; Parotid anatomic change; Parotid Gland - radiation effects; Parotid shrinkage predictivity; Radiometry - methods; Radiotherapy Dosage; Radiotherapy, Intensity-Modulated - methods
• ISSN: 0167-8140; 1879-0887
• DOI: 10.1016/j.radonc.2009.12.014

Abstract Purpose To assess anatomical, clinical and dosimetric pre-treatment parameters, possibly predictors of parotid shrinkage during radiotherapy of head and neck cancer (HNC). Materials Data of 174 parotids from four institutions were analysed; patients were treated with IMRT, with radical and adjuvant intent. Parotid shrinkage was evaluated by the volumetric difference (Δ V ) between parotid volumes at the end and those at the start of the therapy, as assessed by CT images (MVCT for 40 patients, KVCT for 47 patients). Correlation between Δ V cc/% and a number of dosimetric, clinical and geometrical parameters was assessed. Univariate as well as stepwise logistic multivariate (MVA) analyses were performed by considering as an end-point a Δ V cc/% larger than the median value. Linear models of Δ V (continuous variable) based on the most predictive variables found at the MVA were developed. Results Median Δ V cc/% were 6.95 cc and 26%, respectively. The most predictive independent variables of Δ V cc at MVA were the initial parotid volume (IPV, OR: 1.100; p = 0.0002) and D mean (OR: 1.059; p = 0.038). The main independent predictors of Δ V % at MVA were age (OR: 0.968; p = 0.041) and V 40 (OR: 1.0338; p = 0.013). Δ V cc and Δ V % may be well described by the equations: Δ V cc = −2.44 + 0.076 D mean (Gy) + 0.279 IPV (cc) and Δ V % = 34.23 + 0.192 V 40 (%) − 0.2203 age (year). The predictive power of the Δ V cc model is higher than that of the Δ V % model. Conclusions IPV/age and D mean/ V 40 are the major dosimetric and clinical/anatomic predictors of Δ V cc and Δ V %. Δ V cc and Δ V % may be well described by bi-linear models including the above-mentioned variables.