کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2159562 1090862 2010 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی تحقیقات سرطان
پیش نمایش صفحه اول مقاله
A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer
چکیده انگلیسی

PurposeTo assess anatomical, clinical and dosimetric pre-treatment parameters, possibly predictors of parotid shrinkage during radiotherapy of head and neck cancer (HNC).MaterialsData 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 (ΔV) 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 ΔVcc/% 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 ΔVcc/% larger than the median value. Linear models of ΔV (continuous variable) based on the most predictive variables found at the MVA were developed.ResultsMedian ΔVcc/% were 6.95 cc and 26%, respectively. The most predictive independent variables of ΔVcc at MVA were the initial parotid volume (IPV, OR: 1.100; p = 0.0002) and Dmean (OR: 1.059; p = 0.038). The main independent predictors of ΔV% at MVA were age (OR: 0.968; p = 0.041) and V40 (OR: 1.0338; p = 0.013). ΔVcc and ΔV% may be well described by the equations: ΔVcc = −2.44 + 0.076 Dmean (Gy) + 0.279 IPV (cc) and ΔV% = 34.23 + 0.192 V40 (%) − 0.2203 age (year). The predictive power of the ΔVcc model is higher than that of the ΔV% model.ConclusionsIPV/age and Dmean/V40 are the major dosimetric and clinical/anatomic predictors of ΔVcc and ΔV%. ΔVcc and ΔV% may be well described by bi-linear models including the above-mentioned variables.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Radiotherapy and Oncology - Volume 94, Issue 2, February 2010, Pages 206–212
نویسندگان
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