期刊论文详细信息
Radiation Oncology
Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription
Johannes HAM Kaanders1  Henk Huizenga1  Aswin L Hoffmann2 
[1] Department of Radiation Oncology, Radboud University Nijmegen Medical Center, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands;Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, P.O. Box 1588, Maastricht, 6201 BN, The Netherlands
关键词: Decision-making;    Dose-response relations;    Individualisation;    Treatment planning;    Radiotherapy;   
Others  :  1154421
DOI  :  10.1186/1748-717X-8-55
 received in 2012-12-10, accepted in 2013-02-28,  发布年份 2013
PDF
【 摘 要 】

Background

In current practice, patients scheduled for radiotherapy are treated according to ‘rigid’ protocols with predefined dose prescriptions that do not consider risk-taking preferences of individuals. The therapeutic operating characteristic (TOC) graph is applied as a decision-aid to assess the trade-off between treatment benefit and morbidity to facilitate dose prescription customisation.

Methods

Historical dose-response data from prostate cancer patient cohorts treated with 3D-conformal radiotherapy is used to construct TOC graphs. Next, intensity-modulated (IMRT) plans are generated by optimisation based on dosimetric criteria and dose-response relationships. TOC graphs are constructed for dose-scaling of the optimised IMRT plan and individualised dose prescription. The area under the TOC curve (AUC) is estimated to measure the therapeutic power of these plans.

Results

On a continuous scale, the TOC graph directly visualises treatment benefit and morbidity risk of physicians’ or patients’ choices for dose (de-)escalation. The trade-off between these probabilities facilitates the selection of an individualised dose prescription. TOC graphs show broader therapeutic window and higher AUCs with increasing target dose heterogeneity.

Conclusions

The TOC graph gives patients and physicians access to a decision-aid and read-out of the trade-off between treatment benefit and morbidity risks for individualised dose prescription customisation over a continuous range of dose levels.

【 授权许可】

   
2013 Hoffmann et al; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20150407104321376.pdf 523KB PDF download
Figure 5. 24KB Image download
Figure 4. 40KB Image download
Figure 3. 43KB Image download
Figure 2. 52KB Image download
Figure 1. 50KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

【 参考文献 】
  • [1]Amols HI, Zaider M, Heyes MK, Schiff PB: Physician/patient-driven risk assignment in radiation oncology: reality or fancy? Int J Radiat Oncol Biol Phys 1997, 38:455-461.
  • [2]Van Tol-Geerdink JJ, Stalmeier PF, Van Lin EN, Schimmel EC, Huizenga H, Van Daal WA, Leer JW: Do prostate cancer patients want to choose their own radiation treatment. Int J Radiat Oncol Biol Phys 2006, 66:1105-1111.
  • [3]Van Tol-Geerdink JJ, Stalmeier PFM, Pasker-de Jong PCM, Huizenga H, Van Lin EN, Schimmel EC, Leer JW, Van Daal WA: Systematic review of the effect of radiation dose on tumour control and morbidity in the treatment of prostate cancer by 3D-CRT. Int J Radiat Oncol Biol Phys 2006, 64:534-543.
  • [4]Van Tol-Geerdink JJ, Stalmeier PF, Van Lin EN, Schimmel EC, Huizenga H, Van Daal WA, Leer JW: Do patients with localised prostate cancer treatment really want more aggressive treatment. J Clin Oncol 2006, 24:4581-4586.
  • [5]Warkentin B, Stavrev P, Stvreva N, Field C, Fallone BG: A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets. J Appl Clin Med Phys 2004, 5:50-63.
  • [6]Van Baardwijk A, Bosmans G, Bentzen S, Boersma L, Dekker A, Wanders R, Wouters BG, Lambin P, De Ruysscher D: Radiation dose prescription for non-small-cell lung cancer according to normal tissue dose constraints: an in silico clinical trial. Int J Radiat Oncol Biol Phys 2008, 71:1103-1110.
  • [7]Hoffmann AL, Troost EG, Huizenga H, Kaanders JH, Bussink J: Individualized dose prescription for hypofractionation in advanced non-smal-cell lung cancer radiotherapy: an in silico trial. Int J Radiat Oncol Biol Phys 2012, 83:1596-1602.
  • [8]Van Baardwijk A, Wanders S, Boersma L, Borger J, Öllers M, Dingemans AM, Bootsma G, Geraedts W, Pitz C, Lunde R, Lambin P, De Ruysscher D: Mature results of an individualized radiation dose prescription study based on normal tissue constraints in stage I to III non-small-cell lung cancer. J Clin Oncol 2010, 28:1380-1386.
  • [9]Brahme A: Treatment optimization using physical and radiobiological objective functions. In Radiation Therapy Physics. Edited by Smith AR. Berlin: Springer; 1995:209-246.
  • [10]Lind BK, Mavroidis P, Hyödynmaa S, Kappas C: Optimisation of the dose level for a given treatment plan to maximise the complication-free tumour cure. Acta Oncol 1999, 38:787-798.
  • [11]Moore DH, Mendelsohn ML: Optimal treatment levels in cancer therapy. Cancer 1972, 30:97-106.
  • [12]Tokars RP, Griem ML: Carcinoma of the nasopharynx and optimisation of radiotherapeutic management for tumour control and spinal cord injury. Int J Radiat Oncol Biol Phys 1979, 5:1741-1748.
  • [13]Metz CE, Tokars RP, Kronman HB, Griem ML: Maximum likelihood estimation of dose-response parameters for therapeutic operating characteristic (TOC) analysis of carcinoma of the nasopharynx. Int J Radiat Oncol Biol Phys 1982, 8:1185-1192.
  • [14]Ågren A, Brahme A, Turesson I: Optimisation of uncomplicated control for head and neck tumours. Int J Radiat Oncol Biol Phys 1990, 19:1077-1085.
  • [15]Andrews JR: Benefit, risk and optimisation by ROC analysis in cancer therapy. Int J Radiat Oncol Biol Phys 1985, 11:1557-1562.
  • [16]Hanley JA, McNeil BJ: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143:29-36.
  • [17]Eriksson K, Rehbinder H: Advanced tools for radiobiological evaluation and optimisation of treatment plans. In Proceedings of XVth International Conference on the Use of Computers in Radiation Therapy (ICCR). Volume II: 4–7 June 2007. Toronto: University of Toronto; 2007:60-64.
  • [18]Miralbell R, Roberts SA, Zubizarreta E, Hendry JH: Dose-fractionation sensitivity of prostate cancer deduced from radiotherapy outcomes of 5,969 patients in seven international institutional datasets: α/β = 1.4 (0.9 2.2) Gy. Int J Radiat Oncol Biol Phys 2012, 82:e17-e24.
  • [19]Michalski JM, Gay H, Jackson A, Tucker SL, Deasy JO: Radiation dose-volume effects in radiation-induced rectal injury. Int J Radiat Oncol Biol Phys 2010, 76(Suppl 3):S123-S129.
  • [20]Dale E, Hellebust TP, Skjønsberg A, Høgberg T, Olsen DR: Modeling normal tissue complication probability from repetitive computed tomography scans during fractionated high-dose-rate brachytherapy and external beam radiotherapy of the uterine cervix. Int J Radiat Oncol Biol Phys 2000, 47:963-971.
  • [21]Uzan J, Nahum AE: Radiobiologically guided optimisation of the prescription dose and fractionation scheme in radiotherapy using BioSuite. Br J Radiol 2012, 85:1279-1286.
  • [22]Vinogradskiy Y, Tucker SL, Bluett JB, Wages CA, Liao Z, Martel MK: Prescribing radiation dose to lung cancer patients based on personalized toxicity estimates. J Thorac Oncol 2012, 7:1676-1682.
  • [23]Ottosson RO, Engstrom PE, Sjöstrom D, Behrens CF, Karlsson A, Knöös T, Ceberg C: The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques. Acta Oncol 2009, 48:233-237.
  文献评价指标  
  下载次数:66次 浏览次数:8次