Literature DB >> 10705021

Normal tissue complication probabilities: dependence on choice of biological model and dose-volume histogram reduction scheme.

V Moiseenko1, J Battista, J Van Dyk.   

Abstract

PURPOSE: To evaluate the impact of dose-volume histogram (DVH) reduction schemes and models of normal tissue complication probability (NTCP) on ranking of radiation treatment plans. METHODS AND MATERIALS: Data for liver complications in humans and for spinal cord in rats were used to derive input parameters of four different NTCP models. DVH reduction was performed using two schemes: "effective volume" and "preferred Lyman". DVHs for competing treatment plans were derived from a sample DVH by varying dose uniformity in a high dose region so that the obtained cumulative DVHs intersected. Treatment plans were ranked according to the calculated NTCP values.
RESULTS: Whenever the preferred Lyman scheme was used to reduce the DVH, competing plans were indistinguishable as long as the mean dose was constant. The effective volume DVH reduction scheme did allow us to distinguish between these competing treatment plans. However, plan ranking depended on the radiobiological model used and its input parameters.
CONCLUSIONS: Dose escalation will be a significant part of radiation treatment planning using new technologies, such as 3-D conformal radiotherapy and tomotherapy. Such dose escalation will depend on how the dose distributions in organs at risk are interpreted in terms of expected complication probabilities. The present study indicates considerable variability in predicted NTCP values because of the methods used for DVH reduction and radiobiological models and their input parameters. Animal studies and collection of standardized clinical data are needed to ascertain the effects of non-uniform dose distributions and to test the validity of the models currently in use.

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Year:  2000        PMID: 10705021     DOI: 10.1016/s0360-3016(99)00473-3

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  6 in total

1.  Damage assessment in gastric cancer treatment with adjuvant radiochemotherapy: calculation of the NTCP's from the differential HDV of the organs at risk.

Authors:  Amadeo Wals; Jorge Contreras; José Macías; Inmaculada Fortes; Daniel Rivas; Pedro González; Ismael Herruzo
Journal:  Clin Transl Oncol       Date:  2006-04       Impact factor: 3.405

2.  A comparison of dose-response characteristics of four NTCP models using outcomes of radiation-induced optic neuropathy and retinopathy.

Authors:  Vitali Moiseenko; William Y Song; Loren K Mell; Niranjan Bhandare
Journal:  Radiat Oncol       Date:  2011-06-06       Impact factor: 3.481

Review 3.  Modeling Radiotherapy Induced Normal Tissue Complications: An Overview beyond Phenomenological Models.

Authors:  Marco D'Andrea; Marcello Benassi; Lidia Strigari
Journal:  Comput Math Methods Med       Date:  2016-12-01       Impact factor: 2.238

4.  Transformation of physical DVHs to radiobiologically equivalent ones in hypofractionated radiotherapy analyzing dosimetric and clinical parameters: a practical approach for routine clinical practice in radiation oncology.

Authors:  Zoi Thrapsanioti; Irene Karanasiou; Kalliopi Platoni; Efstathios P Efstathopoulos; George Matsopoulos; Maria Dilvoi; George Patatoukas; Demetrios Chaldeopoulos; Nikolaos Kelekis; Vassilis Kouloulias
Journal:  Comput Math Methods Med       Date:  2013-11-19       Impact factor: 2.238

5.  A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets.

Authors:  Brad Warkentin; Pavel Stavrev; Nadia Stavreva; Colin Field; B Gino Fallone
Journal:  J Appl Clin Med Phys       Date:  2004-01-01       Impact factor: 2.102

6.  Assessment of radiobiological metrics applied to patient-specific QA process of VMAT prostate treatments.

Authors:  Francisco Clemente-Gutiérrez; Consuelo Pérez-Vara; María H Clavo-Herranz; Concepción López-Carrizosa; José Pérez-Regadera; Carmen Ibáñez-Villoslada
Journal:  J Appl Clin Med Phys       Date:  2016-03-08       Impact factor: 2.102

  6 in total

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