ISTER (Immune System - Tumor Efficiency Rate): An Important Key for Planning in Radiotherapic Facilities
The use of the oncologic index ISTER allows for a more effective planning of the radiotherapic facilities in the hospitals. Any change in the radiotherapy treatment, due to unexpected stops, may be adapted by recalculating the doses to the new treatment duration while keeping the optimal prognosis. The results obtained in a simulation model on millions of patients allow the definition of optimal success probability algorithms.
[1] VA Kuznetsov, I Makalkin, MA Taylor, and AS Perelson. Nonlinear
dynamics of immunogenic tumors: parameter estimation and global
bifurcation analysis. Bull Math Biology, 56:295-321, 1994.
[2] RK Sachs and LR Hlatky. Simple ode models of tumor growth and antiangiogenic
or radiation treatment. Math. Comp. Modelling, 33:1297-
1305, 2001.
[3] Galach M. Dynamics of the tumor-immune system competition - the
effect of time delay. Int J Appl Math Comput Sci, 13:395-406, 2003.
[4] H Enderling, RA Alexander, and AJ Mark. Mathematical modelling of
radiotherapy strategies for early breast cancer. Journal of Theoretical
Biology, 241:158-171, 2006.
[5] O Sotolongo-Costa and et al. Behavior of tumors under nonstationary
therapy. Physica D, 178:242-253, 2003.
[6] D Dingli, MD Cascino, K Josic, SJ Russell, and Z Bajzer. Mathematical
modeling of cancer radiovirotherapy. Mathematical Biosciences,
199:55-78, 2006.
[7] O Sotolongo-Grau, D Rodriguez Perez, JA Santos Miranda,
O Sotolongo-Costa, and JC Antoranz. Immune system-tumour
efficiency ratio as a new oncological index for radiotherapy treatment
optimization. Math Med Biol, 26(4):297-307, 2009.
[8] A d-Onofrio. A general framework for modeling tumor-inmune system
competition and immunotherapy: Mathematical analysis and biomedical
inferences. Physica D, 208:220-235, 2005.
[9] A Matzavinos, M Chaplain, and V Kuznetsov. Mathematical modelling
of the spatio-temporal response of cytotoxic t-lymphocytes to a solid
tumour. Math Med Biol, 21:1-34, 2004.
[10] A Matzavinos and M Chaplain. Travelling wave analysis of a model of
the immune response to cancer. C. R. Biologies, 327:995-1008, 2004.
[11] D Kirschner and J Panetta. Modelling immunotherapy of the tumorimmune
system interaction. J. Math. Biol., 38:235-252, 1998.
[12] L de Pillis, AE Radunskaya, and CL Wiseman. A validated mathematical
model of cell-mediated immune response to tumor growth. Cancer
Research, 65:7950-7958, 2005.
[13] VS Khoo. Radiotherapeutic techniques for prostate cancer, dose escalation
and brachytherapy. Clinical Oncology, 17:560-571, 2005.
[14] O. Sotolongo-Grau, D. Rodriguez-Perez, J. A. Santos-Miranda, M. M.
Desco, O. Sotolongo-Costa, and J. C. Antoranz. A mathematical aid
decision tool for rt planning. In O. D ossel and W.C. Schlegel, editors,
WC 2009, IFMBE Proceedings 25 I, pages 101-104, 2009.
[15] WJ Mackillop. Killing time: The consequences of delays in radiotherapy.
Radiotherapy and Oncology, 84:1 - 4, 2007.
[16] AR Jensen, HM Nellemann, and J Overgaard. Tumor progression in
waiting time for radiotherapy in head and neck cancer. Radiotherapy
and Oncology, 84:5-10, 2007.
[17] TL Whiteside. Apoptosis of immune cells in the tumor microenvironment
and peripheral circulation of patients with cancer: implications for
immunotherapy. Vaccine, 20:A46-A51, 2002.
[18] TL Whiteside. Immune suppression in cancer: Effects on immune cells,
mechanisms and future therapeutic intervention. Seminars in Cancer
Biology, 16:3-15, 2006.
[19] D Rodriguez-Perez, O Sotolongo-Grau, R Espinosa Riquelme,
O Sotolongo-Costa, JA Santos Miranda, and JC Antoranz. Assesment
of cancer immunotherapy aoutcome in terms of the immune response
time features. Math Med Biol, 24:287-300, 2007.
[20] S Sundstrom, R Bremnes, U Aasebo, S Aamdal, R Htlevoll, P Brunsvig,
DC Johannessen, O Klepp, PM Fayers, and Kaasa S. Hypofractioned
palliative radiotherapy (17 Gy per two fractions) in advanced non-smallcell
lung carcinoma is comparable to standard fractionation for symptom
control and survival: A national phase III trial. Journal of Clinical
Oncology, 22:801-810, 2004.
[21] GG Steel. Basic Clinical Radiobiology for Radiation Oncologists.
Edward Arnold Publishers, London, 1993.
[22] D Rades and S Lang. Prognostic value of haemoglobin levels during
concurrent radio-chemotherapy in the treatment of oesophageal cancer.
Clinical Oncology, 18:139-144, 2006.
[23] A Martin and SA Harbison. An introduction to radiation protection.
London, Chapman and Hall, 1998.
[24] P Mayles, A Nahum, and JC Rosenwald. Handbook of radiotherapy
physics. Taylor & Francis, London, 2007.
[1] VA Kuznetsov, I Makalkin, MA Taylor, and AS Perelson. Nonlinear
dynamics of immunogenic tumors: parameter estimation and global
bifurcation analysis. Bull Math Biology, 56:295-321, 1994.
[2] RK Sachs and LR Hlatky. Simple ode models of tumor growth and antiangiogenic
or radiation treatment. Math. Comp. Modelling, 33:1297-
1305, 2001.
[3] Galach M. Dynamics of the tumor-immune system competition - the
effect of time delay. Int J Appl Math Comput Sci, 13:395-406, 2003.
[4] H Enderling, RA Alexander, and AJ Mark. Mathematical modelling of
radiotherapy strategies for early breast cancer. Journal of Theoretical
Biology, 241:158-171, 2006.
[5] O Sotolongo-Costa and et al. Behavior of tumors under nonstationary
therapy. Physica D, 178:242-253, 2003.
[6] D Dingli, MD Cascino, K Josic, SJ Russell, and Z Bajzer. Mathematical
modeling of cancer radiovirotherapy. Mathematical Biosciences,
199:55-78, 2006.
[7] O Sotolongo-Grau, D Rodriguez Perez, JA Santos Miranda,
O Sotolongo-Costa, and JC Antoranz. Immune system-tumour
efficiency ratio as a new oncological index for radiotherapy treatment
optimization. Math Med Biol, 26(4):297-307, 2009.
[8] A d-Onofrio. A general framework for modeling tumor-inmune system
competition and immunotherapy: Mathematical analysis and biomedical
inferences. Physica D, 208:220-235, 2005.
[9] A Matzavinos, M Chaplain, and V Kuznetsov. Mathematical modelling
of the spatio-temporal response of cytotoxic t-lymphocytes to a solid
tumour. Math Med Biol, 21:1-34, 2004.
[10] A Matzavinos and M Chaplain. Travelling wave analysis of a model of
the immune response to cancer. C. R. Biologies, 327:995-1008, 2004.
[11] D Kirschner and J Panetta. Modelling immunotherapy of the tumorimmune
system interaction. J. Math. Biol., 38:235-252, 1998.
[12] L de Pillis, AE Radunskaya, and CL Wiseman. A validated mathematical
model of cell-mediated immune response to tumor growth. Cancer
Research, 65:7950-7958, 2005.
[13] VS Khoo. Radiotherapeutic techniques for prostate cancer, dose escalation
and brachytherapy. Clinical Oncology, 17:560-571, 2005.
[14] O. Sotolongo-Grau, D. Rodriguez-Perez, J. A. Santos-Miranda, M. M.
Desco, O. Sotolongo-Costa, and J. C. Antoranz. A mathematical aid
decision tool for rt planning. In O. D ossel and W.C. Schlegel, editors,
WC 2009, IFMBE Proceedings 25 I, pages 101-104, 2009.
[15] WJ Mackillop. Killing time: The consequences of delays in radiotherapy.
Radiotherapy and Oncology, 84:1 - 4, 2007.
[16] AR Jensen, HM Nellemann, and J Overgaard. Tumor progression in
waiting time for radiotherapy in head and neck cancer. Radiotherapy
and Oncology, 84:5-10, 2007.
[17] TL Whiteside. Apoptosis of immune cells in the tumor microenvironment
and peripheral circulation of patients with cancer: implications for
immunotherapy. Vaccine, 20:A46-A51, 2002.
[18] TL Whiteside. Immune suppression in cancer: Effects on immune cells,
mechanisms and future therapeutic intervention. Seminars in Cancer
Biology, 16:3-15, 2006.
[19] D Rodriguez-Perez, O Sotolongo-Grau, R Espinosa Riquelme,
O Sotolongo-Costa, JA Santos Miranda, and JC Antoranz. Assesment
of cancer immunotherapy aoutcome in terms of the immune response
time features. Math Med Biol, 24:287-300, 2007.
[20] S Sundstrom, R Bremnes, U Aasebo, S Aamdal, R Htlevoll, P Brunsvig,
DC Johannessen, O Klepp, PM Fayers, and Kaasa S. Hypofractioned
palliative radiotherapy (17 Gy per two fractions) in advanced non-smallcell
lung carcinoma is comparable to standard fractionation for symptom
control and survival: A national phase III trial. Journal of Clinical
Oncology, 22:801-810, 2004.
[21] GG Steel. Basic Clinical Radiobiology for Radiation Oncologists.
Edward Arnold Publishers, London, 1993.
[22] D Rades and S Lang. Prognostic value of haemoglobin levels during
concurrent radio-chemotherapy in the treatment of oesophageal cancer.
Clinical Oncology, 18:139-144, 2006.
[23] A Martin and SA Harbison. An introduction to radiation protection.
London, Chapman and Hall, 1998.
[24] P Mayles, A Nahum, and JC Rosenwald. Handbook of radiotherapy
physics. Taylor & Francis, London, 2007.
@article{"International Journal of Medical, Medicine and Health Sciences:54092", author = "O. Sotolongo-Grau and D. Rodriguez-Perez and J. A. Santos-Miranda and M. M. Desco and O. Sotolongo-Costa and J. C. Antoranz", title = "ISTER (Immune System - Tumor Efficiency Rate): An Important Key for Planning in Radiotherapic Facilities", abstract = "The use of the oncologic index ISTER allows for a more effective planning of the radiotherapic facilities in the hospitals. Any change in the radiotherapy treatment, due to unexpected stops, may be adapted by recalculating the doses to the new treatment duration while keeping the optimal prognosis. The results obtained in a simulation model on millions of patients allow the definition of optimal success probability algorithms.
", keywords = "Mathematical model, radiation oncology, dynamical systems applications.", volume = "4", number = "5", pages = "197-4", }
