Treatment planning evaluation and optimization should be biologically and not dose/volume based

Medical Physics

Volumn 42, Issue 6, 2015, Pages 2753-2756

  Deasy, Joseph O ^a   Mayo, Charles S ^b   Orton, Colin G ^c  

^a MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

^b MAYO CLINIC   (United States)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

DOSE-VOLUME; OPTIMISATIONS; TREATMENT PLANNING;

MEDICINE;

ALGORITHM; CANCER CONTROL; CANCER RADIOTHERAPY; DOSIMETRY; EXTERNAL BEAM RADIOTHERAPY; HUMAN; IMAGE GUIDED RADIOTHERAPY; INTENSITY MODULATED RADIATION THERAPY; MAXIMUM PERMISSIBLE DOSE; NORMAL TISSUE COMPLICATION PROBABILITY; RADIATION DOSE; RADIATION DOSE DISTRIBUTION; RADIATION INJURY; SHORT SURVEY; STATISTICAL ANALYSIS; TISSUE DISTRIBUTION; TREATMENT PLANNING; TUMOR CONTROL PROBABILITY; TUMOR VOLUME; NEOPLASMS; PROBABILITY; RADIATION INJURIES; RADIOTHERAPY DOSAGE; RADIOTHERAPY PLANNING SYSTEM; TREATMENT OUTCOME;

HUMANS; NEOPLASMS; PROBABILITY; RADIATION DOSAGE; RADIATION INJURIES; RADIOTHERAPY DOSAGE; RADIOTHERAPY PLANNING, COMPUTER-ASSISTED; TREATMENT OUTCOME;

EID: 84929603670     PISSN: 00942405     EISSN: 24734209     Source Type: Journal    
DOI: 10.1118/1.4916670     Document Type: Short Survey

References (16)

1. J. O. Deasy et al., "Improving normal tissue complication probability models: The need to adopt a "data-pooling" culture," Int. J. Radiat. Oncol., Biol., Phys. 76, S151-S154 (2010). 10.1016/j.ijrobp.2009.06.094
2. S. M. Bentzen et al., "Quantitative analyses of normal tissue effects in the clinic (QUANTEC): An introduction to the scientific issues," Int. J. Radiat. Oncol., Biol., Phys. 76 (3), S3-S9 (2010). 10.1016/j.ijrobp.2009.09.040
3. X. A. Li et al., "The use and QA of biologically related models for treatment planning: Short report of the TG-166 of the therapy physics committee of the AAPM," Med. Phys. 39, 1386-1409 (2012). 10.1118/1.3685447
4. L. Cella et al., "Complication probability models for radiation-induced heart valvular dysfunction: Do heart-lung interactions play a role?," PLoS One 9 (10), e111753 (2014). 10.1371/journal.pone.0111753
5. S. L. Tucker et al., "Incorporating single-nucleotide polymorphisms into the Lyman model to improve prediction of radiation pneumonitis," Int. J. Radiat. Oncol., Biol., Phys. 85 (1), 251-257 (2013). 10.1016/j.ijrobp.2012.02.021
6. M. R. Nazem-Zadeh et al., "Response-driven imaging biomarkers for predicting radiation necrosis of the brain," Phys. Med. Biol. 59 (10), 2535-2547 (2014). 10.1088/0031-9155/59/10/2535
7. I. El Naqa, P. Pater, and J. Seuntjens, "Monte Carlo role in radiobiological modelling of radiotherapy outcomes," Phys. Med. Biol. 57 (11), R75-R97 (2012). 10.1088/0031-9155/57/11/r75
8. F. M. Kong, C. Pan, A. Eisbruch, and R. K. Ten Haken, "Physical models and simpler dosimetric descriptors of radiation late toxicity," Semin. Radiat. Oncol. 17 (2), 108-120 (2007). 10.1016/j.semradonc.2006.11.007
9. J. Jeong, K. I. Shoghi, and J. O. Deasy, "Modelling the interplay between hypoxia and proliferation in radiotherapy tumour response," Phys. Med. Biol. 58, 4897-4919 (2013). 10.1088/0031-9155/58/14/4897
10. A. Chi, W. A. Tomé, J. Fowler, R. Komaki, N. P. Nguyen, M. P. Mehta, and J. S. Welsh, "Stereotactic body radiation therapy in non-small-cell lung cancer: Linking radiobiological modeling and clinical outcome," Am. J. Clin. Oncol. 34, 432-441 (2011). 10.1097/COC.0b013e3181df4b3f
11. M. Partridge, M. Ramos, A. Sardaro, and M. Brada, "Dose escalation for non-small cell lung cancer: Analysis and modelling of published literature," Radiother. Oncol. 99, 6-11 (2011). 10.1016/j.radonc.2011.02.014
12. J. D. Fenwick, A. E. Nahum, Z. I. Malik, C. V. Eswar, M. Q. Hatton, V. M. Laurence, J. F. Lester, and D. B. Landau, "Escalation and intensification of radiotherapy for stage III non-small cell lung cancer: Opportunities for treatment improvement," Clin. Oncol. 21, 343-360 (2009). 10.1016/j.clon.2008.12.011
13. S. L. Tucker et al., "Late rectal toxicity on RTOG 94-06: Analysis using a mixture Lyman model," Int. J. Radiat. Oncol., Biol., Phys. 78, 1253-1260 (2010). 10.1016/j.ijrobp.2010.01.069
14. M. E. M. C. Christianen et al., "Predictive modelling for swallowing dysfunction after primary (chemo) radiation: Results of a prospective observational study," Radiother. Oncol. 105, 107-114 (2012). 10.1016/j.radonc.2011.08.009
15. J. Uzan and A. E. Nahum, "Radiobiologically guided optimisation of the prescription dose and fractionation scheme in radiotherapy using BioSuite," Br. J. Radiol. 85, 1279-1286 (2012). 10.1259/bjr/20476567
16. J. O. Deasy, A. Niemierko, D. Herbert, D. Yan, A. Jackson, R. K. Ten Haken, M. Langer, and S. Sapareto, "Methodological issues in radiation dose-volume outcome analyses: Summary of a joint AAPM/NIH workshop," Med. Phys. 29, 2109-2127 (2002). 10.1118/1.1501473