TY - JOUR
T1 - Modelling tumour volume variations in head and neck cancer: magnetic resonance imaging contribution for patients undergoing induction chemotherapy
AU - Dinapoli, Nicola
AU - Tartaglione, Tommaso
AU - Bussu, Francesco
AU - Autorino, Rosa
AU - Micciche', Francesco
AU - Sciandra, Mariacarmela
AU - Visconti, Emiliano
AU - Colosimo, Cesare
AU - Paludetti, Gaetano
AU - Valentini, Vincenzo
PY - 2017
Y1 - 2017
N2 - Primary tumour volume evaluation has predictive value for estimating survival
outcomes. Using volumetric data acquired by MRI in patients undergoing induction
chemotherapy (IC) these outcomes were estimated before the radiotherapy course in
head and neck cancer (HNC) patients. MRI performed before and after IC in 36
locally advanced HNC patients were analysed to measure primary tumour volume. The
two volumes were correlated using the linear-log ratio (LLR) between the volume
in the first MRI and the volume in the second. Cox's proportional hazards models
(CPHM) were defined for loco-regional control (LRC), disease-free survival (DFS)
and overall survival (OS). Strict evaluation of the influence of volume
delineation uncertainties on prediction of final outcomes has been defined. LLR
showed good predictive value for all survival outcomes in CPHM. Predictive models
for LRC and DFS at 24 months showed optimal discrimination and prediction
capability. Evaluation of primary tumour volume variations in HNC after IC
provides an example of modelling that can be easily used even for other adaptive
treatment approaches. A complete assessment of uncertainties in covariates
required for running models is a prerequisite to create reliable clinically
models.
AB - Primary tumour volume evaluation has predictive value for estimating survival
outcomes. Using volumetric data acquired by MRI in patients undergoing induction
chemotherapy (IC) these outcomes were estimated before the radiotherapy course in
head and neck cancer (HNC) patients. MRI performed before and after IC in 36
locally advanced HNC patients were analysed to measure primary tumour volume. The
two volumes were correlated using the linear-log ratio (LLR) between the volume
in the first MRI and the volume in the second. Cox's proportional hazards models
(CPHM) were defined for loco-regional control (LRC), disease-free survival (DFS)
and overall survival (OS). Strict evaluation of the influence of volume
delineation uncertainties on prediction of final outcomes has been defined. LLR
showed good predictive value for all survival outcomes in CPHM. Predictive models
for LRC and DFS at 24 months showed optimal discrimination and prediction
capability. Evaluation of primary tumour volume variations in HNC after IC
provides an example of modelling that can be easily used even for other adaptive
treatment approaches. A complete assessment of uncertainties in covariates
required for running models is a prerequisite to create reliable clinically
models.
KW - Head and neck cancer
KW - Induction chemotherapy
KW - MR
KW - Survival Modelling
KW - Volumetry
KW - Head and neck cancer
KW - Induction chemotherapy
KW - MR
KW - Survival Modelling
KW - Volumetry
UR - http://hdl.handle.net/10807/91448
U2 - 10.14639/0392-100X-906
DO - 10.14639/0392-100X-906
M3 - Article
SN - 1827-675X
VL - 2017
SP - 9
EP - 16
JO - Acta Otorhinolaryngologica Italica
JF - Acta Otorhinolaryngologica Italica
ER -
