Asia Oceania Journal of Nuclear Medicine and Biology

Asia Oceania Journal of Nuclear Medicine and Biology

Impact of PET - CT motion correction in minimising the gross tumour volume in non-small cell lung cancer

Document Type : Original Article

Authors
Michael A Masoomi 1
Anne H McLean 2
Yassine Bouchareb 3
Will Ryder 4
Andy Robinson 5
1 1-Department of Nuclear Medicine, Farwaniya Hospital, Kuwait
2 2-Nuclear Medicine Physics, Queen Alexandra Hospital, Portsmouth, UK
3 3-Clinical Physics, Barts Health, NHS Trust, UK.
4 4-Faculty of Health Science, University of Sydney, Sydney, Australia
5 5-The Harley Street Clinic, London, UK
10.7508/aojnmb.2013.02.006
Abstract
Objective(s): To investigate the impact of respiratory motion on localization, and quantification of lung lesions for the Gross Tumor Volume utilizing a fully automated Auto3Dreg program and dynamic NURBS-based cardiac-torso digitized phantom (NCAT).
Methods: Respiratory motion may result in more than 30% underestimation of the SUV values of lung, liver and kidney tumor lesions. The motion correction technique adopted in this study was an image-based motion correction approach using, a voxel-intensity-based and a multi-resolution multi-optimization (MRMO) algorithm. The NCAT phantom was used to generate CT attenuation maps and activity distribution volumes for the lung regions. All the generated frames were co-registered to a reference frame using a time efficient scheme. Quantitative assessment including Region of Interest (ROI), image fidelity and image correlation techniques, as well as semi-quantitative line profile analysis and qualitatively overlaying non-motion and motion corrected image frames were performed.
Results: The largest motion was observed in the Z-direction. The greatest translation was for the frame 3, end inspiration, and the smallest for the frame 5 which was closet frame to the reference frame at 67% expiration. Visual assessment of the lesion sizes, 20-60mm at 3 different locations, apex, mid and base of lung showed noticeable improvement for all the foci and their locations.   The maximum improvements for the image fidelity were from 0.395 to 0.930 within the lesion volume of interest. The greatest improvement in activity concentration underestimation was 7.7% below the true activity for the 20 mm lesion in comparison to 34.4% below, prior to correction. The discrepancies in activity underestimation were reduced with increasing the lesion sizes. Overlaying activity distribution on the attenuation map showed improved localization of the PET metabolic information to the anatomical CT images.
Conclusion:The respiratory motion correction for the lung lesions has led to an improvement in the lesion size, localization and activity quantification with a potential application in reducing the size of the PET GTV for radiotherapy treatment planning applications and hence improving the accuracy of the regime in treatment of lung cancer.
Keywords
Motion correction
PET-CT
Lung cancer
NCAT
Subjects
  1. Jemal A, Thomas A, Murray T, Thun M. Cancer statistics 2002. CA Cancer J Clin. 2002; 52:23-47.
  2. Yusuf E, Sadek E, Nehmeh A, Pan T, Pevsner A, Rosenzweig KE, et al. The CT motion quantitation of lung lesions and its impact on PET-measured SUVs. J Nucl Med. 2004; 45:1287–92.
  3. Boucher L, Pordrigue S, Lecomte R. Respiratory Gating for 3-Dimensional PET of the Thorax: Feasibility and Initial Results. J Nucl Med. 2007; 45:214-9.
  4. Kitamura K, Shirato H, Seppenwoolde H Y, Onimaru R , Oda M, Fujita K, et al. Three-dimensional intrafractional movement of prostate measured during real-time tumor-tracking radiotherapy in supine and prone treatment positions. Int J RadiatOncolBiol Phys. 2002; 53(5):1117–23.
  5. Malone S, Crook JM, Kendal W S, Szanto J. Respiratory-induced prostate motion: quantification and characterization. Int J RadiatOncolBiol Phys. 2000;48(1):105–9.
  6. Weiss E, Vorwerk H, Richter S, Hess C F. Interfractional and intrafractional accuracy during radiotherapy of gynecologic carcinomas: A comprehensive evaluation using the ExacTrac system. Int J RadiatOncol Biol. Phys.2003; 56(1):69–79.
  7. Van de Steene J, Linthout N, de Mey J, Vinh-Hung V, Claassens C, Noppen M, et al.  Definition of gross tumor volume in lung cancer: inter-observer variability. 2002;62(1):37–49.
  8. Bowden P, Fisher R, Mac Manus M, Wirth A, Duchesne G, Millward M, et al. Measurement of lung tumor volumes using three-dimensional computer planning software. Int J RadiatOncolBiol Phys. 2002; 53(3):566–73.
  9. Senan S, van Sornsen de Koste J, Samson M, Tankink H, Jansen P, Nowak P J, et al. Evaluation of a target contouring protocol for 3D conformal radiotherapy in non-small cell lung cancer. 1999; 53(3):247–55.
  10. Hanley J, Debois M M , Mah M, Mageras G S, Raben A, Rosenzweig K, et al. Deep inspiration breath-hold technique for lung tumors: The potential value of target immobilization and reduced lung density in dose escalation.  Int J RadiatOncolBiol Phys. 1999; 45(3):603–11.
  11. Yorke E D, Wang L, Rosenzweig K E, Mah D, Paoli J B, Chui C S. Evaluation of deep inspiration breath-hold lung treatment plans with Monte Carlo dose calculation. Int J RadiatOncolBiol Phys. 2002;53(4):1058–70.
  12. Erridge S C, Seppenwoolde Y, Muller S,  van Herk M,  De Jaeger K,  Belderbos J S, et al. Portal imaging to assess set-up errors, tumor motion and tumor shrinkage during conformal radiotherapy of non-small cell lung cancer. Radiother Oncol.2003;66(1):75–85.
  13. Nehmeh SA, Erdi Y E, Ling C C, Rosenzweig K E, Schoder H, Larson S M, et al. Effect of Respiratory Gating on Quantifying PET Image of Lung Cancer. J Nucl Med. 2002; 43:876-81.
  14. Rahmim A. Advanced motion correction methods in PET. Iran J Nucl Med. 2005; 13: 1-17.
  15. Vedam S S, Kini V R, Keall P J, Ramakrishnan V, Mostafavi H, Mohan R. Quantifying the predictability of diaphragm motion during respiration with a noninvasive external marker. Med Phys. 2003;30(4):505–13.
  16. Kini V R, Vedam S S, Keall P J, Patil S, Chen C, Mohan R.Patient training in respiratory-gated radiotherapy. Med Dosim. 2003;28(1):7–11.
  17. Ford E C, Mageras G S, Yorke E, Rosenzweig K E, Wagman R, Ling C C. Evaluation of respiratory movement during gated radiotherapy using film and electronic portal imaging. Int J RadiatOncolBiol Phys. 2002;52(2):522–31.
  18. Kubo H D, Len P M, Minohara S, Mostafavi H. Breathing-synchronized radiotherapy program at the University of California Davis Cancer Center. Med Phys. 2000; 27(2):346–53.
  19. Vedam S S, Keall P J, Kini V R, Mohan R. Determining parameters for respirationgated radiotherapy.  Med Phys. 2001;28(10):2139–46.
  20. Mageras G S, Yorke E, Rosenzweig K, Braban L, Keatley E, Ford E, Leibel S A, et al. Fluoroscopic evaluation of diaphragmatic motion reduction with a respiratory gated radiotherapy system. J ApplClin Med Phys. 2001;2:191–200.
  21. Wagman R, Yorke E, Giraud P, Ford E, Sidhu K, Mageras G, Minsky B, Rosenzweig K. Reproducibility of organ position with respiratory gating for liver tumors: use in doseescalation. Int J RadiatOncolBiol Phys. 2003; 55:659–68.
  22. Mageras G S, Yorke E. Deep inspiration breath hold and respiratory gating strategies for reducing organ motion in radiation treatment. SeminRadiatOncol. 2004;14(1):65–75.
  23. Segars WP. Development of a new dynamic NURBS-based cardiac torso (NCAT) phantom: PhD Thesis, University of North Carolina. 2001.
  24. Engel H,Steinert H, Buck A, Berthold T, HuchBöni R A, Schulthess GKV. Whole-body PET: Physiological and ArtifactualFluorodeoxyglucose Accumulations. J Nucl Med.1996; 37:441-6.
  25. Ramos CD,Erdi YE, Gonen M, Riedel E, Yeung HWD, Macapinlac H, et al.  FDG-PET standardized uptake values in normal anatomical structures using iterativereconstruction segmented attenuation correction and filtered back-projection.  Eur J Nucl Med. 2001; 28:155-64.
  26. Fletcher R, Powell MJD. A rapidly convergent descent method for minimization. The Computer Journal. 1963; 6:163-8.
  27. Nelder JA, Mead R. A simplex method for function minimization. The Computer Journal. 1965; 7 (4):308-13.
  28. Rorden C, Brett M. Stereotaxic display of brain lesions. Behavioural Neurology. 2000; 12, 191-200.
  29. Rasband WS. ImageJ. U.S. National Institutes of Health, Bethesda, Maryland, USA, http://rsb.info.nih.gov/ij/, 1997-2005 (accessed on 5/09/07).
  30. Loening AM, Gambhir SS.AMIDE: A Free Software Tool for Multimodality Medical Image Analysis. Molecular Imaging. 2003; 2(3):131-7.
  31. Krak NC, Boellaard R, Hoekstra OS, Twisk JW, Hoekstra CJ, Lammertsma AA. Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial. Eur J Nucl Med. 2005;32:294–301.
  32. Soret M, Bacharach SL, Buvat I. Partial –Volume Effect in PET Tumor Imaging. Journal of Nuclear Medicine. 2007; 48(6): 932-45.
  33. Masoomi MA, Robinson A, Bouchareb Y, Spyrou   PET/CT Motion Correction in Paediatric Gut Inflammation Drug Response Therapy. American Nuclear Society Transaction, Washington, USA, 2007, Vol. 97, 241.
  34. Boucek J, Francis R J, Green A J. Automated approach to identification and quantitation of tumour volumes in chemotherapy monitoring using FDG PET. J Nucl Med.2005;46:464 (Suppl.).
  35. Masoomi MA. Quantitative and Qualitative Imaging in Single Photon Emission Tomography for Nuclear Medicine Applications, PhD Thesis, University of Surrey Press, UK. 1990.
  36. Lamare M J, Carbayo L, Cresson T, Kontaxakis G, Santos A, Cheze Le Rest C, et al. List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations. Phys Med Biol. 2007; 52: 5187-204.
  37. Bouchareb Y, Janka R and Kalender WA. Generation of multi-phase (4D) CT data based on a non-rigid registration approach and MR breath hold scans. Medical Image Understanding and Analysis Proceeding, London. 2004; 236-239.
Asia Oceania Journal of Nuclear Medicine and Biology
Volume 1, Issue 2 - Serial Number 2
October 2013
Pages 35-46