Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Carrington, Rhys; Spezi, Emiliano; Gwynne, Sarah; Dutton, Peter; Hurt, Chris; Staffurth, John; Crosby, Thomas (2016)
Publisher: BioMed Central
Journal: Radiation Oncology (London, England)
Languages: English
Types: Article
Subjects: RC0254, Radiology Nuclear Medicine and imaging, Oncology, Research
Purpose\ud \ud The first aim of this study was to assess plan quality using a conformity index (CI) and analyse its influence on patient outcome. The second aim was to identify whether clinical and technological factors including planning treatment volume (PTV) volume and treatment delivery method could be related to the CI value.\ud \ud \ud Methods and materials\ud \ud By extending the original concept of the mean distance to conformity (MDC) index, the OverMDC and UnderMDC of the 95 % isodose line (50Gy prescribed dose) to the PTV was calculated for 97 patients from the UK SCOPE 1 trial (ISCRT47718479). Data preparation was carried out in CERR, with Kaplan-Meier and multivariate analysis undertaken in EUCLID and further tests in Microsoft Excel and IBM’s SPSS.\ud \ud \ud Results\ud \ud A statistically significant breakpoint in the overall survival data, independent of cetuximab, was found with OverMDC (4.4 mm, p < 0.05). This was not the case with UnderMDC. There was a statistically significant difference in PTV volume either side of the OverMDC breakpoint (Mann Whitney p < 0.001) and in OverMDC value dependent on the treatment delivery method (mean IMRT = 2.1 mm, mean 3D-CRT = 4.1 mm Mann Whitney p < 0.001). Re-planning the worst performing patients according to OverMDC from 3D-CRT to VMAT resulted in a mean reduction in OverMDC of 2.8 mm (1.6–4.0 mm). OverMDC was not significant in multivariate analysis that included age, sex, staging, tumour type, and position.\ud \ud \ud Conclusion\ud \ud Although not significant when included in multivariate analysis, we have shown in univariate analysis that a patient’s OverMDC is correlated with overall survival. OverMDC is strongly related to IMRT and to a lesser extent with PTV volume. We recommend that VMAT planning should be used for oesophageal planning when available and that attention should be paid to the conformity of the 95 % to the PTV.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Bohsung J, Gillis S, Arrans R, Bakai A, De Wagter C, Knöös T, et al. IMRT treatment planning-A comparative inter-system and inter-centre planning exercise of the ESTRO QUASIMODO group. Radiother Oncol. 2005;76(3):354-61.
    • 2. Teoh AYB, Chiu PWY, Yeung WK, Liu SYW, Wong SKH, Ng EKW. Long-term survival outcomes after definitive chemoradiation versus surgery in patients with resectable squamous carcinoma of the esophagus: results from a randomized controlled trial. Ann Oncol. 2013;24(1):165-71.
    • 3. Wolf MC, Stahl M, Krause BJ, Bonavina L, Bruns C, Belka C, et al. Curative treatment of oesophageal carcinoma: current options and future developments. Radiat Oncol. 2011;6:55.
    • 4. Cunningham D, Starling N, Rao S, Iveson T, Nicolson M, Coxon F, et al. Capecitabine and oxaliplatin for advanced esophagogastric cancer. N Engl J Med. 2008;358(1):36-46.
    • 5. Pöttgen C, Stuschke M. Radiotherapy versus surgery within multimodality protocols for esophageal cancer - A meta-analysis of the randomized trials. Cancer Treat Rev. 2012;38(6):599-604.
    • 6. International Commission on Radiation Units and Measurements (ICRU). Prescribing, Recording and Reporting Photon Beam Therapy. ICRU Report 50. Bethesda: ICRU; 1993.
    • 7. International Commission on Radiation Units and Measurements (ICRU). Prescribing, Recording and Reporting Photon Beam Therapy [supplement to ICRU Report 50]. ICRU Report 62. Bethesda: ICRU; 1999.
    • 8. Warren S, Partridge M, Carrington R, Hurt C, Crosby T, Hawkins M. Radiobiological determination of dose escalation and normal tissue toxicity in definitive chemoradiation therapy for esophageal cancer. Int J Radiat Oncol Biol Phys. 2014;90:423-9.
    • 9. Vidal M, Vieillevigne L, Izar F, Ferrand R. Dosimetric comparison of RapidArc and 3D-Conformal RT for esophageal cancer. Physica Medica. 2012;28(Supplement 1):S2-3.
    • 10. Weber DC, Tomsej M, Melidis C, Hurkmans CW. QA makes a clinical trial stronger: Evidence-based medicine in radiation therapy. Radiother Oncol. 2012;105:4-8.
    • 11. Hurt G, Nixon L, Griffiths G, Al-Mokhtar R, Gollins S, Staffurth J, et al. SCOPE1: a randomised phase II/III multicentre clinical trial of definitive chemoradiation, with or without cetuximab, in carcinoma of the oesphagus. BMC Cancer. 2011;11:466-78.
    • 12. Button MR, Morgan CA, Croydon ES, Roberts SA, Crosby TDL. Study to Determine Adequate Margins in Radiotherapy Planning for Esophageal Carcinoma by Detailing Patterns of Recurrence after Definitive Chemoradiotherapy. Int J Rad Oncol Biol Phys. 2009;73(3):818-23.
    • 13. Crosby T, Hurt C, Falk S, Gollins S, Mukherjee S, Staffurth J, et al. Chemoradiotherapy with or without cetuximab in patients with oesophageal cancer (SCOPE 1): a mluticentre, phase 2/3 randomised trial. Lancet. 2013. Online Publication.
    • 14. Wills L, Millin A, Paterson J, Crosby T, Staffurth J. The effect of planning algorithms in oesophageal radiotherapy in the context of the SCOPE 1 trial. Radiother Oncol. 2009;93:462-7.
    • 15. Gwynne S, Spezi E, Wills L, Nixon L, Hurt C, Joseph G, et al. Toward semiautomated assessment of target volume delineation in radiotherpay trials: the SCOPE 1 pretrial test case. Int J Radiat Oncol Biol Phys. 2012;84(4):1037-42.
    • 16. Moore KL, Schmidt R, Moiseenko V, Olsen LA, Tan J, Xiao Y, et al. Quantifying unnecessary normal tissue complication risks due to suboptimal planning: A secondary study of RTOG 0126. Int J Rad Oncol Biol Phys. 2015;92(2):228-35.
    • 17. Knoos T, Kristensen I, Nilsson P. Volumetric and dosimetric evaluation of radiation treatment plans: Radiation conformity index. Int J Radiat Oncol Biol Phys. 1998;42(5):1169-76.
    • 18. Kataria T, Sharma K, Subramani V, Karrthick KP, Bisht SS. Homogeneity Index: An objective tool for assessment of conformal radiation treatments. J Med Phys. 2012;37(4):207-13.
    • 19. O'Deasy J, Blanco AI, Clark VH. CERR: A computational environment for radiotherapy research. Med Phys. 2003;30(5):979-85.
    • 20. Santanam L, Hurkmans C, Mutic S, Van Vliet-Vroegindeweij C, Brame S, Straube W, et al. Standardizing naming conventions in radiation oncology. Int J Rad Oncol Biol Phys. 2012;83(4):1344-9.
    • 21. Feuvret L, Noel G, Mazeron JJ, Bey P. Conformity index: A review. Int J Radiat Oncol Biol Phys. 2006;64(2):333-42.
    • 22. Jena R, Kirkby NF, Burton KE, Hoole ACF, Tan LT, Burnet NG. A novel algorithm for the morphometric assessment of radiotherapy treatment planning volumes. Brit J Radiol. 2010;83:44-51.
    • 23. Gayou O, Parda DS, Miften M. EUCLID: an outcome analysis tool for highdimensional clinical studies. Phys Med Biol. 2007;52:1705-19.
    • 24. Chen Y, Wu X, Bu S, He C, Wang W, Liu J, et al. Promising outcomes of definitive chemoradiation and cetuximab for patient with esophageal squamous cell carcinoma. Japan J Cancer Res. 2012;1:1.
    • 25. Li XA, Alber M, O'Deasy J, Jackson A, Jee KK, Marks LR, 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. 2012;39(3):1386-409.
    • 26. Williams BA, Mandrekar JN, Mandrekar SJ, Cha SS, Furth AF. Finding Optimal Cutpoint for Continuous Covariates with Binary and Time-To-Event Outcomes. Rochester: Mayo Foundation; 2006.
    • 27. Nicolini G, Ghosh-Laskar S, Shrivastava SK, Banerjee S, Chaudhary S, Agarwal JP, et al. Volumetric Modulation Arc Radiotherapy With Flattening Filter-Free Beams Compared With Static Gantry IMRT and 3D Conformal Radiotherapy for Advanced Esophageal Cancer: A Feasibility Study. Int J Rad Oncol Biol Phys. 2012;84(2):553-60.
    • 28. Murthy KK, Shukeili KA, Kumar SS, Davis CA, Chandran RR, Namrata S. Evaluation of dose coverage to target volume and normal tissue sparing in the adjuvant radiotherapy of gastric cancers: 3D-CRT compared with dynamic IMRT. Biomed Imaging Interv. 2010;6:e29-36.
    • 29. Freilich J, Hoffe SE, Almhanna K, Dinwoodie W, Yue B, Fulpo W, et al. Comparative outcomes for 3D conformal versus intensity modulated radiation therapy for esophageal cancer. Dis Esophagus. In Press.
    • 30. Chun SG, Hu C, Choy H, Komaki RU, Timmerman RD, Schild SE, et al. Comparison of 3-D Conformal and Intensity Modulated Radiation Therapy Outcomes for Locally Advanced Non-Small Cell Lung Cancer in NRG Oncology/RTOG 0617. Int J Rad Oncol Biol Phys. 2015;93(3, Supplement):S1-2.
  • No related research data.
  • No similar publications.