1995
DOI: 10.3109/02841869509127196
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Volume and Heterogeneity Dependence of the Dose-Response Relationship for Head And Neck Tumours

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Cited by 43 publications
(38 citation statements)
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References 27 publications
(15 reference statements)
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“…A relationship that is formally similar to the one derived in Equation 4 above has previously been suggested to hold up as an approximate relationship at the steepest part of the dose-response curve in the special case of a Poisson dose-response model [15]. As shown here, this formula is valid irrespective of the details of the dose-response curve, at all response levels and without any approximation.…”
Section: Discussionsupporting
confidence: 53%
“…A relationship that is formally similar to the one derived in Equation 4 above has previously been suggested to hold up as an approximate relationship at the steepest part of the dose-response curve in the special case of a Poisson dose-response model [15]. As shown here, this formula is valid irrespective of the details of the dose-response curve, at all response levels and without any approximation.…”
Section: Discussionsupporting
confidence: 53%
“…Due to its dependence on the effective clonogen number, γ should theoretically increase with tumor volume. This increase with tumor size was seen in clinical larynx cancer data by Ågren-Cronqvist et al (1995). Using an experimental mouse model, Khalil et al (1997) showed a slow increase in γ with tumor volume under ambient conditions.…”
Section: The Generalized Dose-response Gradientmentioning
confidence: 89%
“…The mechanistically-motivated model most often used to describe radiotherapeutic tumor control is the linear quadratic model [2][3][4][5][6][7], which has more recently been used to include heterogeneity, within and/or between tumors [23][24][25][26][27][28]. Consequently, as an example of a model which assumes that the same tumoricidal mechanisms operate at all radiation doses, we used the LQ model with heterogeneous tumor cell radiosensitivity (within a given tumor).…”
Section: Radiobiological Modelsmentioning
confidence: 99%