Advertisement

Advanced Imaging and Guidance System for Use in Intensity Modulated RT

  • D. A. Jaffray
  • K. K. Brock
  • M. B. Sharpe

6.4 Summary

The creation of a comprehensive system for simulation is being driven by both the advancements in imaging tools for characterization of the patient’s diseased and normal anatomy and by the introduction of volumetric imaging systems for daily guidance and verification of delivery. Such a comprehensive system will (i) accelerate the introduction of further developments in imaging to the simulation process, (ii) provide an appropriate infrastructure to support the vast quantity of imaging information that will be streaming from image-guidance approaches such as cone-beam CT systems. Genuine opportunity to bring accurate disease and normal structure characterization together with daily accounting of the dose delivered for better understanding of disease control and complication induction, as well as, permit re-optimization of the treatment’s parameters as therapy progresses.

Keywords

Radiat Oncol Biol Phys Magn Reson Image Deformable Image Registration Planning Compute Tomography Compute Tomography Dataset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ling CC, Humm J, Larson S, Amols H, Fuks Z, Leibel S, Koutcher JA (2000) Towards multidimensional radiotherapy (MD-CRT): biological imaging and biological conformality. Int J Radiat Oncol Biol Phys 47:551–560PubMedCrossRefGoogle Scholar
  2. 2.
    Mah D, Steckner M, Palacio E, Mitra R, Richardson T, Hanks GE (2002) Characteristics and quality assurance of a dedicated open 0.23 T MRI for radiation therapy simulation. Med Phys 29:2541–2547PubMedCrossRefGoogle Scholar
  3. 3.
    Mah D, Freedman G, Milestone B, Hanlon A, Palacio E, Richardson T, Movsas B, Mitra R, Horwitz E, Hanks GE (2002) Measurement of intrafractional prostate motion using magnetic resonance imaging. Int J Radiat Oncol Biol Phys 54:568–575PubMedCrossRefGoogle Scholar
  4. 4.
    Mah D, Steckner M, Hanlon A, Freedman G, Milestone B, Mitra R, Shukla H, Movsas B, Horwitz E, Vaisanen PP, Hanks GE (2002) MRI simulation: effect of gradient distortions on three-dimensional prostate cancer plans. Int J Radiat Oncol Biol Phys 53:757–765PubMedCrossRefGoogle Scholar
  5. 5.
    Jaffray DA, Chawla K, Yu C, Wong JW (1995) Dual-beam imaging for online verification of radiotherapy field placement. Int J Rad Oncol Biol Phys 33:1273–1280CrossRefGoogle Scholar
  6. 6.
    Jaffray DA, Drake DG, Moreau M, Martinez AA, Wong JW (1999) A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. Int J Radiat Oncol Biol Phys 45:773–789PubMedCrossRefGoogle Scholar
  7. 7.
    Jaffray DA, Siewerdsen JH, Wong JW, Martinez AA (2002) Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys 53:1337–1349PubMedCrossRefGoogle Scholar
  8. 8.
    Jaffray DA, Siewerdsen JH (2000) Cone-beam computed tomography with a flat-panel imager: initial performance characterization. Med Phys 27:1311–1323PubMedCrossRefGoogle Scholar
  9. 9.
    Siewerdsen JH, Jaffray DA (1999) A ghost story: spatiotemporal response characteristics of an indirect-detection flat-panel imager. Med Phys 26:1624–1641PubMedCrossRefGoogle Scholar
  10. 10.
    Siewerdsen JH, Jaffray DA (1999) Cone-beam computed tomography with a flat-panel imager: effects of image lag. Med Phys 26:2635–2647PubMedCrossRefGoogle Scholar
  11. 11.
    Siewerdsen JH, Jaffray DA (2000) Optimization of X-ray imaging geometry (with specific application to flat-panel cone-beam computed tomography). Med Phys 27:1903–1914PubMedCrossRefGoogle Scholar
  12. 12.
    Siewerdsen JH, Jaffray DA (2001) Cone-beam computed tomography with a flat-panel imager: magnitude and effects of X-ray scatter. Med Phys 28:220–231PubMedCrossRefGoogle Scholar
  13. 13.
    Sonke J, Remeijer P, van Herk M (2003) Respiration-correlated cone-beam CT: obtaining a four-dimensional data set. Med Phys 30:1415CrossRefGoogle Scholar
  14. 14.
    Brock KK, McShan DL, Ten Haken RK, Hollister SJ, Dawson LA, Balter JM (2003) Inclusion of organ deformation in dose calculations. Med Phys 30:290–295PubMedCrossRefGoogle Scholar
  15. 15.
    Joshi S, Pizer S, Fletcher PT, Yushkevich P, Thall A, Marron JS (2002) Multiscale deformable model segmentation and statistical shape analysis using medial descriptions. IEEE Trans Med Imaging 21:538–550PubMedCrossRefGoogle Scholar
  16. 16.
    Yan D, Jaffray DA, Wong JW (1999) A model to accumulate fractionated dose in a deforming organ. Int J Radiat Oncol Biol Phys 44:665–675PubMedCrossRefGoogle Scholar
  17. 17.
    Lauterbur PC (1973) Image formation by induced local interactions: examples of employing nuclear magnetic resonance. Nature 242:190–191CrossRefGoogle Scholar
  18. 18.
    Curran WJ, Hackney DB, Blitzer PH, Bilaniuk L (1986) The value of magnetic resonance imaging in treatment planning of nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 12:2189–2196PubMedGoogle Scholar
  19. 19.
    Fraass BA, McShan DL, Diaz RF, Ten Haken RK, Aisen A, Gebarski S, Glazer G, Lichter AS (1987) Integration of magnetic resonance imaging into radiation therapy treatment planning: I. Technical considerations. Int J Radiat Oncol Biol Phys 13:1897–1908PubMedGoogle Scholar
  20. 20.
    Glatstein E, Lichter AS, Fraass BA, Kelly BA, van de Geijn J (1985) The imaging revolution and radiation oncology: use of CT, ultrasound, and NMR for localization, treatment planning and treatment delivery. Int J Radiat Oncol Biol Phys 11:299–314PubMedGoogle Scholar
  21. 21.
    Schad LR, Boesecke R, Schlegel W, Hartmann GH, Sturm V, Strauss LG, Lorenz WJ (1987) Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors. J Comput Assist Tomogr 11:948–954PubMedGoogle Scholar
  22. 22.
    Carlson JW, Minemura T (1993) Imaging time reduction through multiple receiver coil data acquisition and image reconstruction. Magn Reson Med 29:681–687PubMedGoogle Scholar
  23. 23.
    McKenzie CA, Lim D, Ransil BJ, Morrin M, Pedrosa I, Yeh EN, Sodickson DK, Rofsky NM (2004) Shortening MR image acquisition time for volumetric interpolated breath-hold examination with a recently developed parallel imaging reconstruction technique: clinical feasibility. Radiology 230:589–594PubMedGoogle Scholar
  24. 24.
    Hawighorst H, Schreiber W, Knopp MV, Essig M, Engenhart-Cabilic R, Brix G, van Kaick G (1996) Macroscopic tumor volume of malignant glioma determined by contrast-enhanced magnetic resonance imaging with and without magnetization transfer contrast. Magn Reson Imaging 14:1119–1126PubMedCrossRefGoogle Scholar
  25. 25.
    Khoo VS, Dearnaley DP, Finnigan DJ, Padhani A, Tanner SF, Leach MO (1997) Magnetic resonance imaging (MRI): considerations and applications in radiotherapy treatment planning. Radiother Oncol 42:1–15PubMedCrossRefGoogle Scholar
  26. 26.
    Schad LR, Boesecke R, Schlegel W, Hartmann GH, Sturm V, Strauss LG, Lorenz WJ (1987) Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors. J Comput Assist Tomogr 11:948–954PubMedGoogle Scholar
  27. 27.
    Nelson SJ, Graves E, Pirzkall A, Li X, Chan AA, Vigneron DB, McKnight TR (2002) In vivo molecular imaging for planning radiation therapy of gliomas: an application of 1H MRSI. J Magn Reson Imaging 16:464–476PubMedCrossRefGoogle Scholar
  28. 28.
    Pirzkall A, McKnight TR, Graves EE, Carol MP, Sneed PK, Wara WW, Nelson SJ, Verhey LJ, Larson DA (2001) MR-spectroscopy guided target delineation for high-grade gliomas. Int J Radiat Oncol Biol Phys 50:915–928PubMedCrossRefGoogle Scholar
  29. 29.
    Dubois DF, Prestidge BR, Hotchkiss LA, Prete JJ, Bice WS Jr (1998) Intraobserver and interobserver variability of MR imaging-and CT-derived prostate volumes after transperineal interstitial permanent prostate brachytherapy. Radiology 207:785–789PubMedGoogle Scholar
  30. 30.
    Parker CC, Damyanovich A, Haycocks T, Haider M, Bayley A, Catton CN (2003) Magnetic resonance imaging in the radiation treatment planning of localized prostate cancer using intra-prostatic fiducial markers for computed tomography coregistration. Radiother Oncol 66:217–224PubMedCrossRefGoogle Scholar
  31. 31.
    Coakley FV, Qayyum A, Kurhanewicz J (2003) Magnetic resonance imaging and spectroscopic imaging of prostate cancer. J Urol 170:S69–S75PubMedCrossRefGoogle Scholar
  32. 32.
    Menard C, Smith IC, Somorjai RL, Leboldus L, Patel R, Littman C, Robertson SJ, Bezabeh T (2001) Magnetic resonance spectroscopy of the malignant prostate gland after radiotherapy: a histopathologic study of diagnostic validity. Int J Radiat Oncol Biol Phys 50:317–323PubMedCrossRefGoogle Scholar
  33. 33.
    Mizowaki T, Cohen GN, Fung AY, Zaider M (2002) Towards integrating functional imaging in the treatment of prostate cancer with radiation: the registration of the MR spectroscopy imaging to ultrasound/CT images and its implementation in treatment planning. Int J Radiat Oncol Biol Phys 54:1558–1564PubMedCrossRefGoogle Scholar
  34. 34.
    Pickett B, Kurhanewicz J, Fein B, Coakley F, Shinohara K, Roach M (2003) Use of magnetic resonance imaging and spectroscopy in the evaluation of external beam radiation therapy for prostate cancer. Int J Radiat Oncol Biol Phys 57:S163–S164CrossRefGoogle Scholar
  35. 35.
    Gibbs P, Liney GP, Lowry M, Kneeshaw PJ, Turnbull LW (2004) Differentiation of benign and malignant sub-1 cm breast lesions using dynamic contrast enhanced MRI. Breast 13:115–121PubMedCrossRefGoogle Scholar
  36. 36.
    Hathaway PB, Mankoff DA, Maravilla KR, Austin-Seymour MM, Ellis GK, Gralow JR, Cortese AA, Hayes CE, Moe RE (1999) Value of combined FDG PET and MR imaging in the evaluation of suspected recurrent local-regional breast cancer: preliminary experience. Radiology 210:807–814PubMedGoogle Scholar
  37. 37.
    Muuller RD, Barkhausen J, Sauerwein W, Langer R (1998) Assessment of local recurrence after breast-conserving therapy with MRI. J Comput Assist Tomogr 22:408–412PubMedCrossRefGoogle Scholar
  38. 38.
    Sardanelli F, Lozzelli A, Fausto A (2003) MR imaging of the breast: indications, established technique, and new directions. Eur Radiol 13(Suppl 3):N28–N36PubMedGoogle Scholar
  39. 39.
    Viehweg P, Heinig A, Lampe D, Buchmann J, Heywang-Kobrunner SH (1998) Retrospective analysis for evaluation of the value of contrast-enhanced MRI in patients treated with breast conservative therapy. MAGMA 7:141–152PubMedGoogle Scholar
  40. 40.
    Muryama S, Akamine T, Sakai S, Oshiro Y, Kakinohana Y, Soeda H, Toita T, Adachi G (2004) Risk factor of radiation pneumonitis: assessment with velocity-encoded cine magnetic resonance imaging of pulmonary artery. J Comput Assist Tomogr 28:204–208PubMedCrossRefGoogle Scholar
  41. 41.
    Takenaka D, Ohno Y, Hatabu H, Ohbayashi C, Yoshimura M, Ohkita Y, Sugimura K (2002) Differentiation of metastatic versus non-metastatic mediastinal lymph nodes in patients with non-small cell lung cancer using respiratory-triggered short inversion time inversion recovery (STIR) turbo spin-echo MR imaging. Eur J Radiol 44:216–224PubMedCrossRefGoogle Scholar
  42. 42.
    Yankelevitz DF, Henschke CI, Batata M, Kim YS, Chu F (1994) Lung cancer: evaluation with MR imaging during and after irradiation. J Thorac Imaging 9:41–46PubMedGoogle Scholar
  43. 43.
    Jeong YY, Kang HK, Chung TW, Seo JJ, Park JG (2003) Uterine cervical carcinoma after therapy: CT and MR imaging findings. Radiographics 23:969–981PubMedGoogle Scholar
  44. 44.
    Lyng H, Vorren AO, Sundfor K, Taksdal I, Lien HH, Kaalhus O, Rofstad EK (2001) Assessment of tumor oxygenation in human cervical carcinoma by use of dynamic Gd-DTPA-enhanced MR imaging. J Magn Reson Imaging 14:750–756PubMedCrossRefGoogle Scholar
  45. 45.
    Schoeppel SL, Ellis JH, LaVigne ML, Schea RA, Roberts JA (1992) Magnetic resonance imaging during intracavitary gynecologic brachytherapy. Int J Radiat Oncol Biol Phys 23:169–174PubMedGoogle Scholar
  46. 46.
    Wachter-Gerstner N, Wachter S, Reinstadler E, Fellner C, Knocke TH, Potter R (2003) The impact of sectional imaging on dose escalation in endocavitary HDR-brachytherapy of cervical cancer: results of a prospective comparative trial. Radiother Oncol 68:51–59PubMedCrossRefGoogle Scholar
  47. 47.
    Ghilezan M, Siewerdsen JH, van Herk M, Martinez A, Jaffray DA (2002) Assessment of prostate and seminal vesicles motion/deformation using sagittal cinneMRI for margin determination in on-line Image-Guided Radiation Therapy (IGRT) for prostate cancer. Int J Radiat Oncol Biol Phys 54:182–182CrossRefGoogle Scholar
  48. 48.
    Koch N, Liu HH, Olsson LE, Jackson EF (2003) Assessment of geometrical accuracy of magnetic resonance images for radiation therapy of lung cancers. J Appl Clin Med Phys 4:352–364PubMedCrossRefGoogle Scholar
  49. 49.
    Mizowaki T, Nagata Y, Okajima K, Kokubo M, Negoro Y, Araki N, Hiraoka M (2000) Reproducibility of geometric distortion in magnetic resonance imaging based on phantom studies. Radiother Oncol 57:237–242PubMedCrossRefGoogle Scholar
  50. 50.
    Wang D, Doddrell DM, Cowin G (2004) A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging. Magn Reson Imaging 22:529–542PubMedCrossRefGoogle Scholar
  51. 51.
    Bharatha A, Hirose M, Hata N, Warfield SK, Ferrant M, Zou KH, Suarez-Santana E, Ruiz-Alzola J, D’Amico A, Cormack RA, Kikinis R, Jolesz FA, Tempany CM (2001) Evaluation of three-dimensional finite element-based deformable registration of pre-and intraoperative prostate imaging. Med Phys 28:2551–2560PubMedCrossRefGoogle Scholar
  52. 52.
    Brock KK, Hollister SJ, Dawson LA, Balter JM (2002) Technical note: creating a four-dimensional model of the liver using finite element analysis. Med Phys 29:1403–1405PubMedCrossRefGoogle Scholar
  53. 53.
    Brock KM, Balter JM, Dawson LA, Kessler ML, Meyer CR (2003) Automated generation of a four-dimensional model of the liver using warping and mutual information. Med Phys 30:1128–1133PubMedCrossRefGoogle Scholar
  54. 54.
    Joshi S, Pizer S, Fletcher PT, Yushkevich P, Thall A, Marron JS (2002) Multiscale deformable model segmentation and statistical shape analysis using medial descriptions. IEEE Trans Med Imaging 21:538–550PubMedCrossRefGoogle Scholar
  55. 55.
    Liang J, Yana D (2003) Reducing uncertainties in volumetric image based deformable organ registration. Med Phys 30:2116–2122PubMedCrossRefGoogle Scholar
  56. 56.
    Meyer CR, Boes JL, Kim B, Bland PH, Zasadny KR, Kison PV, Koral K, Frey KA, Wahl RL (1997) Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations. Med Image Anal 1:195–206PubMedCrossRefGoogle Scholar
  57. 57.
    Rohlfing T, Maurer CR Jr, O’Dell WG, Zhong J (2004) Modeling liver motion and deformation during the respiratory cycle using intensity-based nonrigid registration of gated MR images. Med Phys 31:427–432PubMedCrossRefGoogle Scholar
  58. 58.
    Yan D, Jaffray DA, Wong JW (1999) A model to accumulate fractionated dose in a deforming organ. Int J Radiat Oncol Biol Phys 44:665–675PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • D. A. Jaffray
    • 1
  • K. K. Brock
    • 1
  • M. B. Sharpe
    • 1
  1. 1.Radiation PhysicsPrincess Margaret HospitalTorontoCanada

Personalised recommendations