• Volume/Page
  • Keyword
  • DOI
  • Citation
  • Advanced
   
 
 
 

Med. Phys. 38, 6362 (2011); http://dx.doi.org/10.1118/1.3658567 (9 pages)

Evaluations of an adaptive planning technique incorporating dose feedback in image-guided radiotherapy of prostate cancer

Han Liu and Qiuwen Wu

Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710

View MapView Map

(Received 28 July 2011; accepted 12 October 2011; revised 23 September 2011; published online 9 November 2011)

Full Text: Read Online (HTML) | Download PDF FREE | View Cart
Purpose: Online image guidance (IG) has been used to effectively correct the setup error and inter-fraction rigid organ motion for prostate cancer. However, planning margins are still necessary to account for uncertainties such as deformation and intra-fraction motion. The purpose of this study is to investigate the effectiveness of an adaptive planning technique incorporating offline dose feedback to manage inter-fraction motion and residuals from online correction.
Methods: Repeated helical CT scans from 28 patients were included in the study. The contours of prostate and organs-at-risk (OARs) were delineated on each CT, and online IG was simulated by matching center-of-mass of prostate between treatment CTs and planning CT. A seven beam intensity modulated radiation therapy (IMRT) plan was designed for each patient on planning CT for a total of 15 fractions. Dose distribution at each fraction was evaluated based on actual contours of the target and OARs from that fraction. Cumulative dose up to each fraction was calculated by tracking each voxel based on a deformable registration algorithm. The cumulative dose was compared with the dose from initial plan. If the deviation exceeded the pre-defined threshold, such as 2% of the D99 to the prostate, an adaptive planning technique called dose compensation was invoked, in which the cumulative dose distribution was fed back to the treatment planning system and the dose deficit was made up through boost radiation in future treatment fractions. The dose compensation was achieved by IMRT inverse planning. Two weekly compensation delivery strategies were simulated: one intended to deliver the boost dose in all future fractions (schedule A) and the other in the following week only (schedule B). The D99 to prostate and generalized equivalent uniform dose (gEUD) to rectal wall and bladder were computed and compared with those without the dose compensation.
Results: If only 2% underdose is allowed at the end of the treatment course, then 11 patients fail. If the same criteria is assessed at the end of each week (every five fractions), then 14 patients fail, with three patients failing the 1st or 2nd week but passing at the end. The average dose deficit from these 14 patients was 4.4%. They improved to 2% after the weekly compensation. Out of these 14 patients who needed dose compensation, ten passed the dose criterion after weekly dose compensation, three patients failed marginally, and one patient still failed the criterion significantly (10% deficit), representing 3.6% of the patient population. A more aggressive compensation frequency (every three fractions) could successfully reduce the dose deficit to the acceptable level for this patient. The average number of required dose compensation re-planning per patient was 0.82 (0.79) per patient for schedule A (B) delivery strategy. The doses to OARs were not significantly different from the online IG only plans without dose compensation.
Conclusions: We have demonstrated the effectiveness of offline dose compensation technique in image-guided radiotherapy for prostate cancer. It can effectively account for residual uncertainties which cannot be corrected through online IG. Dose compensation allows further margin reduction and critical organs sparing.

© 2011 American Association of Physicists in Medicine

ACKNOWLEDGMENTS

This study is supported by grant CA118037 from the National Institute of Health. The contents are solely the responsibility of the authors and do not necessarily represent the official view of the NIH.

Article Outline

  1. INTRODUCTION
  2. METHODS AND MATERIALS
    1. Patient data and initial treatment planning
    2. Online image guidance
    3. Offline analysis
      1. Organ deformation and cumulative dose analysis
      2. Dose compensation
  3. RESULTS
  4. DISCUSSIONS
  5. CONCLUSIONS

  1. M. G. Herman, T. M. Pisansky, J. J. Kruse, J. I. Prisciandaro, B. J. Davis, and B. F. King, “Technical aspects of daily online positioning of the prostate for three-dimensional conformal radiotherapy using an electronic portal imaging device,” Int. J. Radiat. Oncol. Biol. Phys. 57, 1131–1140 (2003). [ISI] [MEDLINE]
  2. F. Van den Heuvel, J. Fugazzi, E. Seppi, and J. D. Forman, “Clinical application of a repositioning scheme, using gold markers and electronic portal imaging,” Radiother. Oncol. 79, 94–100 (2006). [MEDLINE]
  3. D. A. Jaffray, “Emergent technologies for 3-dimensional image-guided radiation delivery,” Semin. Radiat. Oncol. 15, 208–216 (2005). [MEDLINE]
  4. L. Court, I. Rosen, R. Mohan, and L. Dong, “Evaluation of mechanical precision and alignment uncertainties for an integrated CT/LINAC system,” Med. Phys. 30, 1198–1210 (2003)MPHYA6000030000006001198000001. [MEDLINE]
  5. D. Yan, D. Lockman, D. Brabbins, L. Tyburski, and A. Martinez, “An off-line strategy for constructing a patient-specific planning target volume in adaptive treatment process for prostate cancer,” Int. J. Radiat. Oncol. Biol. Phys. 48, 289–302 (2000). [Inspec] [ISI] [MEDLINE]
  6. A. A. Martinez, D. Yan, D. Lockman, D. Brabbins, K. Kota, M. Sharpe, D. A. Jaffray, F. Vicini, and J. Wong, “Improvement in dose escalation using the process of adaptive radiotherapy combined with three-dimensional conformal or intensity-modulated beams for prostate cancer,” Int. J. Radiat. Oncol. Biol. Phys. 50, 1226–1234 (2001). [MEDLINE]
  7. M. S. Hoogeman, M. van Herk, J. de Bois, and J. V. Lebesque, “Strategies to reduce the systematic error due to tumor and rectum motion in radiotherapy of prostate cancer,” Radiother. Oncol. 74, 177–185 (2005). [MEDLINE]
  8. T. T. Nuver, M. S. Hoogeman, P. Remeijer, M. van Herk, and J. V. Lebesque, “An adaptive offline procedure for radiotherapy of prostate cancer,” Int. J. Radiat. Oncol. Biol. Phys. 67, 1559–1567 (2007). [Inspec] [MEDLINE]
  9. Y. Lei and Q. Wu, “A hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy,” Phys. Med. Biol. 55, 2221–2234 (2010).
  10. H. Liu and Q. Wu, “Dosimetric and geometric evaluation of a hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy,” Phys. Med. Biol. 56, 5045–5062 (2011).
  11. Q. Wu, J. Liang, and D. Yan, “Application of dose compensation in image-guided radiotherapy of prostate cancer,” Phys. Med. Biol. 51, 1405–1419 (2006). [MEDLINE]
  12. A. de la Zerda, B. Armbruster, and L. Xing, “Formulating adaptive radiation therapy (ART) treatment planning into a closed-loop control framework,” Phys. Med. Biol. 52, 4137–4153 (2007). [MEDLINE]
  13. J. Liang and D. Yan, “Reducing uncertainties in volumetric image based deformable organ registration,” Med. Phys. 30, 2116–2122 (2003)MPHYA6000030000008002116000001. [ISI] [MEDLINE]
  14. D. Yan, D. A. Jaffray, and J. W. Wong, “A model to accumulate fractionated dose in a deforming organ,” Int. J. Radiat. Oncol. Biol. Phys. 44, 665–675 (1999). [MEDLINE]
  15. Y. Chi, J. Liang, and D. Yan, “A material sensitivity study on the accuracy of deformable organ registration using linear biomechanical models,” Med. Phys. 33, 421–433 (2006)MPHYA6000033000002000421000001. [MEDLINE]
  16. K. K. Brock, M. B. Sharpe, L. A. Dawson, S. M. Kim, and D. A. Jaffray, “Accuracy of finite element model-based multi-organ deformable image registration,” Med. Phys. 32, 1647–1659 (2005)MPHYA6000032000006001647000001. [MEDLINE]
  17. K. K. Brock, A. M. Nichol, C. Menard, J. L. Moseley, P. R. Warde, C. N. Catton, and D. A. Jaffray, “Accuracy and sensitivity of finite element model-based deformable registration of the prostate,” Med. Phys. 35, 4019–4025 (2008)MPHYA6000035000009004019000001. [MEDLINE]
  18. Q. Wu, R. Mohan, A. Niemierko, and R. Schmidt-Ullrich, “Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose,” Int. J. Radiat. Oncol. Biol. Phys. 52, 224–235 (2002). [MEDLINE]
  19. S. V. Spirou and C. S. Chui, “A gradient inverse planning algorithm with dose-volume constraints,” Med. Phys. 25, 321–333 (1998)MPHYA6000025000003000321000001. [ISI] [MEDLINE]
  20. J. Adamson and Q. Wu, “Prostate intrafraction motion evaluation using kV fluoroscopy during treatment delivery: a feasibility and accuracy study,” Med. Phys. 35, 1793–1806 (2008)MPHYA6000035000005001793000001. [MEDLINE]
  21. J. Adamson and Q. Wu, “Inferences about prostate intrafraction motion from pre- and 2p2osttreatment volumetric imaging,” Int. J. Radiat. Oncol. Biol. Phys. 75, 260–267 (2009).
  22. J. Adamson and Q. Wu, “Prostate intrafraction motion assessed by simultaneous kilovoltage fluoroscopy at megavoltage delivery I: Clinical observations and pattern analysis,” Int. J. Radiat. Oncol. Biol. Phys. 78, 1563–1570 (2010).
  23. J. Adamson and Q. Wu, “Prostate intrafraction motion assessed by simultaneous kV fluoroscopy at MV delivery II: Adaptive strategies,” Int. J. Radiat. Oncol. Biol. Phys. 78, 1323–1330 (2010).
  24. J. Adamson, Q. Wu, and D. Yan, “Dosimetric effect of intrafraction motion and residual setup error for hypofractionated prostate intensity-modulated radiotherapy with online cone beam computed tomography image guidance,” Int. J. Radiat. Oncol. Biol. Phys. 80, 453–461 (2011).
  25. Q. Wu, G. Ivaldi, J. Liang, D. Lockman, D. Yan, and A. Martinez, “Geometric and dosimetric evaluations of an online image-guidance strategy for 3D-CRT of prostate cancer,” Int. J. Radiat. Oncol. Biol. Phys. 64, 1596–1609 (2006). [Inspec] [MEDLINE]
  26. F. A. Lerma, B. Liu, Z. Wang, B. Yi, P. Amin, S. Liu, Y. Feng, and C. X. Yu, “Role of image-guided patient repositioning and online planning in localized prostate cancer IMRT,” Radiother. Oncol. 93, 18–24 (2009).
  27. Q. J. Wu, D. Thongphiew, Z. Wang, B. Mathayomchan, V. Chankong, S. Yoo, W. R. Lee, and F. F. Yin, “On-line re-optimization of prostate IMRT plans for adaptive radiation therapy,” Phys. Med. Biol. 53, 673–691 (2008). [MEDLINE]
  28. T. Li, D. Thongphiew, X. Zhu, W. R. Lee, Z. Vujaskovic, F. F. Yin, and Q. J. Wu, “Adaptive prostate IGRT combining online re-optimization and re-positioning: A feasibility study,” Phys. Med. Biol. 56, 1243–1258 (2011).

Figures (8) Tables (2)

Figures (click on thumbnails to view enlargements)

FIG.1
Prostate D99 differences [Eq. ( 1 )] between the normalized cumulative dose and the initial plan dose as a function of treatment fraction for each patient. The pre-defined criterion (solid horizontal lines) chosen was −2%. Black star dashed curve: patients passed the criterion at the end of treatment course. Open circle solid curve: patients failed. The “#” in each figure indicates the patient ID.

FIG.1 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.2
Prostate D99 differences as a function of treatment fraction after application of weekly dose compensation. The pre-defined criterion (solid horizontal lines) chosen was −2%. Black star dashed curve: patients passed the criterion at the end of treatment. Open circle curve: patients failed. Blank space: patients do not need dose compensation. Only results from schedule A strategy are shown.

FIG.2 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.3
Comparison of two weekly compensation delivery strategies for two typical patients. (a) Schedule A had better dose improvement than schedule B; (b) schedule B had better dose improvement than schedule A.

FIG.3 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.4
Pass rate at the end of each treatment week with and without dose compensation.

FIG.4 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.5
Dose-volume histograms (DVHs) comparison of prostate, bladder, and rectal wall for one patient at the end of treatment. Notice that the dose axis for prostate does not start from 0 in order to show the differences among different curves. “Planned” was the initial plan; “Cumulative” was the cumulative dose distribution delivered to the patient based on the initial plan with online IG only; “Compensation” was the cumulative dose after performing weekly compensation.

FIG.5 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.6
Dose indices (gEUD) of critical organs. The gEUD values are expressed as a ratio of plan doses at zero margins.

FIG.6 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.7
Comparison of different dose compensation schedules for patient 24.

FIG.7 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

FIG.8
Daily and cumulative D99 differences as a function of treatment fraction for patient 5.

FIG.8 Download High Resolution Image (.zip file) | Export Figure to PowerPoint

Tables

Table I. Comparison of treatment schedules for online image guidance and weekly compensation. “×” indicates delivery of the initial treatment plan 0; “o” indicates compensation is delivered with modified plan 1; “Δ” indicates compensation is delivered with modified plan 2.

View Table
Table II. Comparison of CTV dose deficits with and without dose compensation. The dose deficits are expressed as (average ± stdev) % as defined in Eq. (1). The numbers in parenthesis are the number of patients for the calculation.

View Table


Close

close