191 related articles for article (PubMed ID: 21937139)
1. Dealing with geometric uncertainties in dose painting by numbers: introducing the ΔVH.
Witte M; Shakirin G; Houweling A; Peulen H; van Herk M
Radiother Oncol; 2011 Sep; 100(3):402-6. PubMed ID: 21937139
[TBL] [Abstract][Full Text] [Related]
2. Generation of prescriptions robust against geometric uncertainties in dose painting by numbers.
Sterpin E; Differding S; Janssens G; Geets X; Grégoire V; Lee JA
Acta Oncol; 2015 Feb; 54(2):253-60. PubMed ID: 24991892
[TBL] [Abstract][Full Text] [Related]
3. Treatment plan comparison between helical tomotherapy and MLC-based IMRT using radiobiological measures.
Mavroidis P; Ferreira BC; Shi C; Lind BK; Papanikolaou N
Phys Med Biol; 2007 Jul; 52(13):3817-36. PubMed ID: 17664579
[TBL] [Abstract][Full Text] [Related]
4. An in silico comparison between margin-based and probabilistic target-planning approaches in head and neck cancer patients.
Fontanarosa D; van der Laan HP; Witte M; Shakirin G; Roelofs E; Langendijk JA; Lambin P; van Herk M
Radiother Oncol; 2013 Dec; 109(3):430-6. PubMed ID: 24044789
[TBL] [Abstract][Full Text] [Related]
5. Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning.
Chetty IJ; Rosu M; Kessler ML; Fraass BA; Ten Haken RK; Kong FM; McShan DL
Int J Radiat Oncol Biol Phys; 2006 Jul; 65(4):1249-59. PubMed ID: 16798417
[TBL] [Abstract][Full Text] [Related]
6. Probabilistic objective functions for margin-less IMRT planning.
Bohoslavsky R; Witte MG; Janssen TM; van Herk M
Phys Med Biol; 2013 Jun; 58(11):3563-80. PubMed ID: 23640114
[TBL] [Abstract][Full Text] [Related]
7. Adaptive dose painting by numbers for head-and-neck cancer.
Duprez F; De Neve W; De Gersem W; Coghe M; Madani I
Int J Radiat Oncol Biol Phys; 2011 Jul; 80(4):1045-55. PubMed ID: 20643512
[TBL] [Abstract][Full Text] [Related]
8. Radiation dose escalation based on FDG-PET driven dose painting by numbers in oropharyngeal squamous cell carcinoma: a dosimetric comparison between TomoTherapy-HA and RapidArc.
Differding S; Sterpin E; Hermand N; Vanstraelen B; Nuyts S; de Patoul N; Denis JM; Lee JA; Grégoire V
Radiat Oncol; 2017 Mar; 12(1):59. PubMed ID: 28335778
[TBL] [Abstract][Full Text] [Related]
9. Intensity-modulated radiotherapy optimization in a quasi-periodically deforming patient model.
Söhn M; Weinmann M; Alber M
Int J Radiat Oncol Biol Phys; 2009 Nov; 75(3):906-14. PubMed ID: 19747782
[TBL] [Abstract][Full Text] [Related]
10. Probabilistic evaluation of target dose deterioration in dose painting by numbers for stage II/III lung cancer.
Fontanarosa D; Witte M; Meijer G; Shakirin G; Steenhuijsen J; Schuring D; van Herk M; Lambin P
Pract Radiat Oncol; 2015; 5(4):e375-82. PubMed ID: 25680996
[TBL] [Abstract][Full Text] [Related]
11. Data-driven approach to generating achievable dose-volume histogram objectives in intensity-modulated radiotherapy planning.
Wu B; Ricchetti F; Sanguineti G; Kazhdan M; Simari P; Jacques R; Taylor R; McNutt T
Int J Radiat Oncol Biol Phys; 2011 Mar; 79(4):1241-7. PubMed ID: 20800382
[TBL] [Abstract][Full Text] [Related]
12. Intensity-modulated radiation therapy dose prescription, recording, and delivery: patterns of variability among institutions and treatment planning systems.
Das IJ; Cheng CW; Chopra KL; Mitra RK; Srivastava SP; Glatstein E
J Natl Cancer Inst; 2008 Mar; 100(5):300-7. PubMed ID: 18314476
[TBL] [Abstract][Full Text] [Related]
13. Combined PET/CT for IMRT treatment planning of NSCLC: contrast-enhanced CT images for Monte Carlo dose calculation.
Mönnich D; Lächelt S; Beyer T; Werner MK; Thorwarth D
Phys Med; 2013 Nov; 29(6):644-9. PubMed ID: 22975430
[TBL] [Abstract][Full Text] [Related]
14. Uncertainty reduction in intensity modulated proton therapy by inverse Monte Carlo treatment planning.
Morávek Z; Rickhey M; Hartmann M; Bogner L
Phys Med Biol; 2009 Aug; 54(15):4803-19. PubMed ID: 19622848
[TBL] [Abstract][Full Text] [Related]
15. Selective robust optimization: A new intensity-modulated proton therapy optimization strategy.
Li Y; Niemela P; Liao L; Jiang S; Li H; Poenisch F; Zhu XR; Siljamaki S; Vanderstraeten R; Sahoo N; Gillin M; Zhang X
Med Phys; 2015 Aug; 42(8):4840-7. PubMed ID: 26233211
[TBL] [Abstract][Full Text] [Related]
16. Multicriteria optimization enables less experienced planners to efficiently produce high quality treatment plans in head and neck cancer radiotherapy.
Kierkels RG; Visser R; Bijl HP; Langendijk JA; van 't Veld AA; Steenbakkers RJ; Korevaar EW
Radiat Oncol; 2015 Apr; 10():87. PubMed ID: 25885444
[TBL] [Abstract][Full Text] [Related]
17. Predictive gamma passing rate by dose uncertainty potential accumulation model.
Shiba E; Saito A; Furumi M; Murakami Y; Ohguri T; Tsuneda M; Yahara K; Nishio T; Korogi Y; Nagata Y
Med Phys; 2019 Feb; 46(2):999-1005. PubMed ID: 30536878
[TBL] [Abstract][Full Text] [Related]
18. The accuracy of the out-of-field dose calculations using a model based algorithm in a commercial treatment planning system.
Wang L; Ding GX
Phys Med Biol; 2014 Jul; 59(13):N113-28. PubMed ID: 24925858
[TBL] [Abstract][Full Text] [Related]
19. Limitations of a convolution method for modeling geometric uncertainties in radiation therapy: the radiobiological dose-per-fraction effect.
Song W; Battista J; Van Dyk J
Med Phys; 2004 Nov; 31(11):3034-45. PubMed ID: 15587657
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of DVH-based treatment plan verification in addition to gamma passing rates for head and neck IMRT.
Visser R; Wauben DJ; de Groot M; Steenbakkers RJ; Bijl HP; Godart J; van't Veld AA; Langendijk JA; Korevaar EW
Radiother Oncol; 2014 Sep; 112(3):389-95. PubMed ID: 25154319
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
