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 (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. Results: Median 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. Conclusions: IPV/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.
| Original language | English |
|---|---|
| Pages (from-to) | 206-212 |
| Number of pages | 7 |
| Journal | Radiotherapy and Oncology |
| Volume | 94 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Feb 2010 |
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Keywords
- Head and neck cancer
- Parotid anatomic change
- Parotid shrinkage predictivity
ASJC Scopus subject areas
- Oncology
- Radiology Nuclear Medicine and imaging
- Hematology
Cite this
A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer. / 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.
In: Radiotherapy and Oncology, Vol. 94, No. 2, 02.2010, p. 206-212.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A two-variable linear model of parotid shrinkage during IMRT for head and neck cancer
AU - Broggi, Sara
AU - Fiorino, Claudio
AU - Dell'Oca, Italo
AU - Dinapoli, Nicola
AU - Paiusco, Marta
AU - Muraglia, Alessandro
AU - Maggiulli, Eleonora
AU - Ricchetti, Francesco
AU - Valentini, Vincenzo
AU - Sanguineti, Giuseppe
AU - Cattaneo, Giovanni Mauro
AU - Di Muzio, Nadia
AU - Calandrino, Riccardo
PY - 2010/2
Y1 - 2010/2
N2 - 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 (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. Results: Median 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. Conclusions: IPV/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.
AB - 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 (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. Results: Median 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. Conclusions: IPV/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.
KW - Head and neck cancer
KW - Parotid anatomic change
KW - Parotid shrinkage predictivity
UR - http://www.scopus.com/inward/record.url?scp=77249156010&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77249156010&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2009.12.014
DO - 10.1016/j.radonc.2009.12.014
M3 - Article
C2 - 20117852
AN - SCOPUS:77249156010
VL - 94
SP - 206
EP - 212
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
SN - 0167-8140
IS - 2
ER -