Bulk evaluation and comparison of radiotherapy treatment plans for breast cancer


This study provides a bulk, retrospective analysis of 151 breast and chest wall radiotherapy treatment plans, as a small-scale demonstration of the potential breadth and value of the information that may be obtained from clinical data mining. The treatments were planned at three centres belonging to one organisation over a period of 3 months. All 151 plans were used to evaluate inter-centre consistency and compliance with a local planning protocol. A subset of 79 plans, from one centre, were used in a more detailed evaluation of the effects of anatomical asymmetry on heart and lung dose, the effects of a metallic temporary tissue expander port on dose homogeneity and the overall conformity and homogeneity achieved in routine breast treatment planning. Differences in anatomical structure contouring and nomenclature were identified between the three centres, with all centres showing some non-compliance with the local planning protocol. When evaluated against standard conformity indices, these breast plans performed relatively poorly. However, when evaluated against recommended organ-at-risk tolerances, all evaluated plans performed sufficiently well that tighter planning tolerances could be recommended for future planning. Heart doses calculated in left breast and chest wall treatments were significantly higher than heart doses calculated in right sided breast and chest wall treatments (p < 0.001). In the treatment involving a temporary tissue expander, the inflated implant effectively pushed the targeted breast tissue away from the healthy tissues, leading to a dose distribution that was relatively conformal, although attenuation through the tissue expander’s metallic port may have been underestimated by the treatment planning system. The results of this study exemplify the use of bulk treatment planning data to evaluate clinical workloads and inform ongoing treatment planning.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7


  1. 1.



  1. 1.

    Smith FM, Gallagher WM, Fox E, Stephens RB, Rexhepaj E, Petricoin EF 3rd, Liotta L, Kennedy MJ, Reynolds JV (2007) Combination of SELDI-TOF-MS and data mining provides early stage response prediction for rectal tumors undergoing multimodal neoadjuvant therapy. Ann Surg 245(2):259–266

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Chen MS, Han J, Yu PS (1996) Data mining: an overview from a database perspective. IEEE Trans Knowl Data Eng 8(6):866–883

    Article  Google Scholar 

  3. 3.

    Bellazzi R, Zupan B (2008) Predictive data mining in clinical medicine: current issues and guidelines. Int J Med Inf 77(2):81–97

    Article  Google Scholar 

  4. 4.

    Allozi R, Li XA, White J, Apte A, Tai A, Michalski JM, Bosch WR, Naqa IE (2010) Tools for consensus analysis of experts contours for radiotherapy structure definitions. Radiother Oncol 97(3):572–578

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Ebert MA, Haworth A, Kearvell R, Hooton B, Coleman R, Spry N, Bydder S, Joseph D (2008) Detailed review and analysis of complex radiotherapy clinical trial planning data: evaluation and initial experience with the SWAN software system. Radiother Oncol 86(2):200–210

    Article  PubMed  Google Scholar 

  6. 6.

    Beetz I, Schilstra C, Burlage FR, Koken PW, Doornaert P, Bijl HP, Chouvalova O, Leemans CR, de Bock GH, Christianen ME, van der Laan BF (2012) Development of NTCP models for head and neck cancer patients treated with three-dimensional conformal radiotherapy for xerostomia and sticky saliva: the role of dosimetric and clinical factors. Radiother Oncol 105(1):86–93

    Article  PubMed  Google Scholar 

  7. 7.

    Tsang Y, Ciurlionis L, Clark C, Venables K (2013) Development of a novel treatment planning test for credentialing rotational intensity-modulated radiotherapy techniques in the UK. Br J Radiol 86(1022):20120315

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Maggio A, Carillo V, Cozzarini C, Perna L, Rancati T, Valdagni R, Gabriele P, Fiorino C (2013) Impact of the radiotherapy technique on the correlation between dose-volume histograms of the bladder wall defined on MRI imaging and dose-volume/surface histograms in prostate cancer patients. Phys Med Biol 58(7):N115–N123

    Article  PubMed  Google Scholar 

  9. 9.

    Williams M, Bailey M, Forstner D, Metcalfe PE (2007) Multicentre quality assurance of intensity modulated radiation therapy plans: a precursor to clinical trials. Australas Radiol 51(5):472–479

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Sanchez-Nieto B, Nahum A (2000) BIOPLAN: software for the biological evaluation of radiotherapy treatment plans. Med Dosim 25(2):71–76

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Zhao B, Joiner MC, Orton CG, Burmeister J (2010) “SABER”: a new software tool for radiotherapy treatment plan evaluation. Med Phys 37(11):5586–5592

    Article  PubMed  Google Scholar 

  12. 12.

    Breen SL, Zhang B (2010) Audit of an automated checklist for quality control of radiotherapy treatment plans. Radiother Oncol 97(3):579–584

    Article  PubMed  Google Scholar 

  13. 13.

    Crowe SB, Kairn T, Middlebrook N, Hill B, Christie DR, Knight RT, Kenny J, Langton CM, Trapp JV (2013) Retrospective evaluation of dosimetric quality for prostate carcinomas treated with 3D conformal, intensity modulated and volumetric modulated arc radiotherapy. J Med Radiat Sci 60(4):131–138

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Gintz D, Latifi K, Caudell J, Nelms B, Zhang G, Moros E, Feygelman V (2016) Initial evaluation of automated treatment planning software. J Appl Clin Med Phys 17(3):331–346

    Google Scholar 

  15. 15.

    Kairn T, Crowe S, Kenny J, Knight R, Trapp J (2014) Predicting the likelihood of QA failure using treatment plan accuracy metrics. J Phys Conf Ser 489(1):012051

    Article  Google Scholar 

  16. 16.

    Crowe S, Kairn T, Kenny J, Knight R, Hill B, Langton CM, Trapp J (2014) Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results. Australas Phys Eng Sci Med 37(3):475–482

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Crowe SB, Kairn T, Middlebrook N, Sutherland B, Hill B, Trapp J (2015) Evaluation of IMRT and VMAT pre-treatment quality assurance using portal dosimetry. Phys Med Biol 60(6):2587–2601

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Australian Institute of Health and Welfare (2014) Australian cancer incidence and mortality (ACIM) books: breast cancer. AIHW, Canberra

    Google Scholar 

  19. 19.

    Landberg T, Chavaudra J, Dobbs H et al (1999) ICRU report 62 prescribing, recording and reporting photon beam therapy (supplement to ICRU report 50). International Commission on Radiotherapy Units and Measurements, Bethesda

    Google Scholar 

  20. 20.

    Stewart F, Hoving S, Russell N (2010) Vascular damage as an underlying mechanism of cardiac and cerebral toxicity in irradiated cancer patients. Radiat Res 174(6b):865–869

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Nilsson G, Holmberg L, Garmo H, Duvernoy O, Sjogren I, Lagerqvist B, Blomqvist C (2012) Distribution of coronary artery stenosis after radiation for breast cancer. J Clin Oncol 30(4):380–386

    Article  PubMed  Google Scholar 

  22. 22.

    Darby SC, Ewertz M, McGale P, Bennet AM, Blom-Goldman U, Brnnum D, Correa C, Cutter D, Gagliardi G, Gigante B, Jensen MB (2013) Risk of ischemic heart disease in women after radiotherapy for breast cancer. N Engl J Med 368(11):987–998

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Bouillon K, Haddy N, Delaloge S, Garbay JR, Garsi JP, Brindel P, Mousannif A, Le MG, Labbe M, Arriagada R, Jougla E (2011) Long-term cardiovascular mortality after radiotherapy for breast cancer. J Am Coll Cardiol 57(4):445–452

    Article  PubMed  Google Scholar 

  24. 24.

    Spear SL, Majidian A (1998) Immediate breast reconstruction in two stages using textured, integrated valve tissue expanders and breast implants: a retrospective review of 171 consecutive breast reconstructions from 1989 to 1996. Plast Reconstr Surg 101(1):53–63

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Kairn T, Crowe S, Fogg P, Trapp J (2013) The appearance and effects of metallic implants in CT images. Australas Phys Eng Sci Med 36(2):209–217

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Donovan E, Bleakley N, Denholm E, Evans P, Gothard L, Hanson J, Peckitt C, Reise S, Ross G, Sharp G, Symonds-Tayler R (2007) Randomised trial of standard 2D radiotherapy (RT) versus intensity modulated radiotherapy (IMRT) in patients prescribed breast radiotherapy. Radiother Oncol 82(3):254–264

    Article  PubMed  Google Scholar 

  27. 27.

    Donovan E, Yarnold J, Adams E, Morgan A, Warrington A, Evans P (2014) An investigation into methods of IMRT planning applied to breast radiotherapy. Br J Radiol 81(964):311–322

    Article  Google Scholar 

  28. 28.

    Crowe S, Kairn T, Fielding AL (2009) The development of a Monte Carlo system to verify radiotherapy treatment dose calculations. Radiother Oncol 92:S71

    Article  Google Scholar 

  29. 29.

    Crowe SB, Kairn T, Trapp JV, Fielding AL (2012) Experimental evaluation of MCDTK, the Monte Carlo DICOM tool-kit. IFMBE Proc 39:1807–1810

    Article  Google Scholar 

  30. 30.

    Emami B, Lyman J, Brown A, Cola L, Goitein M, Munzenrider J, Shank B, Solin L, Wesson M (1991) Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 21(1):109–122

    CAS  Article  PubMed  Google Scholar 

  31. 31.

    Hansen EK, Roach M (2007) Handbook of evidence-based radiation oncology. Springer, New York

    Google Scholar 

  32. 32.

    Shaw E, Scott C, Souhami L, Dinapoli R, Kline R, Loeffler J, Farnan N (2000) Single dose radiosurgical treatment of recurrent previously irradiated primary brain tumors and brain metastases: final report of RTOG protocol 90-05. Int J Radiat Oncol Biol Phys 47(2):291–298

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Niemierko A (1997) Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 24(1):103–110

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Burman C, Kutcher G, Emami B, Goitein M (1991) Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 21(1):123–135

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Feuvret L, Noel G, Mazeron JJ, Bey P (2006) Conformity index: a review. Int J Radiat Oncol Biol Phys 64(2):333–342

    Article  PubMed  Google Scholar 

  36. 36.

    Shaw E, Kline R, Gillin M, Souhami L, Hirschfeld A, Dinapoli R, Martin L (1993) Radiation Therapy Oncology Group: radiosurgery quality assurance guidelines. Int J Radiat Oncol Biol Phys 27(5):1231–1239

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Lefkopoulos D, Dejean C, El-Balaa H, Platoni K, Grandjean P, Foulquier JN, Schlienger M (2000) The use of computers in radiation therapy. Springer, New York, pp 356–358

    Google Scholar 

  38. 38.

    Van’t Riet A, Mak AC, Moerland MA, Elders LH, van der Zee W (1997) A conformation number to quantify the degree of conformality in brachytherapy and external beam irradiation: application to the prostate. Int J Radiat Oncol Biol Phys 37(3):731–736

    Article  PubMed  Google Scholar 

  39. 39.

    Bridge P, Carmichael MA, Brady C, Dry A (2013) A snapshot of radiation therapy techniques and technology in Queensland: an aid to mapping undergraduate curriculum. J Med Radiat Sci 60(1):25–34

    Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Asena A, Kairn T, Crowe SB, Trapp JV (2015) Establishing the impact of temporary tissue expanders on electron and photon beam dose distributions. Phys Med 31(3):281–285

    CAS  Article  PubMed  Google Scholar 

  41. 41.

    Lomax NJ, Scheib SG (2003) Quantifying the degree of conformity in radiosurgery treatment planning. Int J Radiat Oncol Biol Phys 55(5):1409–1419

    Article  PubMed  Google Scholar 

  42. 42.

    Frazier RC, Vicini FA, Sharpe MB, Yan D, Fayad J, Baglan KL, Kestin LL, Remouchamps VM, Martinez AA, Wong JW (2004) Impact of breathing motion on whole breast radiotherapy: a dosimetric analysis using active breathing control. Int J Radiat Oncol Biol Phys 58(4):1041–1047

    Article  PubMed  Google Scholar 

  43. 43.

    Sixel KE, Aznar MC, Ung YC (2001) Deep inspiration breath hold to reduce irradiated heart volume in breast cancer patients. Int J Radiat Oncol Biol Phys 49(1):199–204

    CAS  Article  PubMed  Google Scholar 

  44. 44.

    Kairn T, Crowe S, Kenny J, Mitchell J, Burke M, Schlect D, Trapp J (2013) Dosimetric effects of a high-density spinal implant. J P Conf Ser 444(1):012108

    Article  Google Scholar 

Download references


This study was supported by the Australian Research Council, the Wesley Research Institute, Genesis Cancer Care Queensland (formerly Premion) and the Queensland University of Technology (QUT), through linkage Grant Number LP110100401.

Author information



Corresponding author

Correspondence to T. Kairn.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kairn, T., Crowe, S.B., Langton, C.M. et al. Bulk evaluation and comparison of radiotherapy treatment plans for breast cancer. Australas Phys Eng Sci Med 39, 633–644 (2016). https://doi.org/10.1007/s13246-016-0454-x

Download citation


  • Treatment planning
  • Data mining
  • Radiation therapy