Extraction du signal respiratoire à partir de projections cone-beam pour l'imagerie TDM 4D
Extraction of the respiratory signal from cone-beam projections for 4D CT imaging
OPEN ACCESS
To be efficient, the treatement of the lung cancers with radiation therapy must take into account the respiratory motion. The knowledge of this motion requires the acquisition of 4D computed tomography (CT) images. The free-breathing thorax 4D CT images currently acquired use gated or respiratory-correlated methods. These methods involve the collection of a respiratory signal during the acquisition of data in order to sort them into different groups. The quality of the 4D CT image thus depends on an accurate description by the signal of the position of the thorax in the respiratory cycle. The signal is generally acquired by independent measurements of densitometric data (spirometer, thermometer,...). We propose to extract it directly from the sequence of 2D cone-beam (CB) projections acquired around the free-breathing thorax. Our method derives the motion between two consecutive 2D CB projections using a block matching algorithm. Blocks are positioned around points of interest constituting a regular sampling of the 2D CB projections. A unidimensional signal is derived from the trajectory of each block in the sequence after projection. Aggregation of a subset of selected makes it possible to derive the respiratory signal during the acquisition time. Our method is validated quantitatively on simulated data and qualitatively on real data. On simulated data, we obtain a respiratory signal with 97.5 % linear correlation with the reference. On real data, the extracted signal allow to reconstruct 4D CT images for comparison with the blurred 3D CT image obtained without taking into account the respiratory motion.
Résumé
Le traitement des cancers des poumons par radiothérapie doit prendre en compte les mouvements respiratoires pour être efficace. La connaissance de ce mouvement passe par l'obtention d'images tomodensitométriques (TDM) 4D. Les images TDM 4D du thorax en respiration libre acquises actuellement utilisent les méthodes de type gated ou respiration-correlated. Ces méthodes nécessitent un signal respiratoire, recueilli pendant l'acquisition des données, pour trier celles-ci en différents groupes. La qualité de l'image TDM 4D dépend alors d'une description correcte, par le signal respiratoire, de la position du thorax dans le cycle respiratoire au cours de l'acquisition. Ce signal est généralement acquis par une mesure indépendante des données densitométriques (spiromètre, thermomètre,...). Nous proposons de l'extraire directement de la séquence de projections cone-beam (CB) 2D acquises autour du thorax en respiration libre. Notre méthode extrait le mouvement entre deux projections CB 2D consécutives par un algorithme de mise en correspondance de blocs. Ces blocs sont positionnés autour de points d'intérêt constituant un sous-échantillonnage régulier des projections CB 2D. Nous déduisons de la trajectoire de chaque bloc dans la séquence un signal unidimensionnel après projection. Une sélection d'un sous-ensemble de ces signaux nous permet d'obtenir, après agrégation, le signal respiratoire pendant le temps de l'acquisition. Notre méthode est validée quantitativement sur données simulées et qualitativement sur données réelles. Sur données simulées, nous obtenons un signal respiratoire corrélé linéairement à 97,5 % avec la référence. Sur données réelles, le signal extrait nous permet de reconstruire l'image TDM 4D d'un patient que l'on compare à l'image TDM 3D floue, obtenue sans prise en compte du mouvement respiratoire.
Respiratory signal, 4D reconstruction, computed tomograpy, cone-beam, thorax, radiation therapy
Mots clés
Signal respiratoire, reconstruction 4D, tomodensitométrie, cone-beam, thorax, radiothérapie
[1] V. BOLDEA, D. SARRUT, S. CLIPPE, Lung deformation estimation with non-rigid registration for radiotherapy treatment. IN Lecture Notes in Computer Science Springer Verlag, editor, Medical Image Computing and Computer-Assisted Intervention, volume 2878, pages 770-7, 2003.
[2] S. BONNET, A. KOENIG, S. ROUX, P. HUGONNARD, R. GUILLEMAUD, P. GRANGEAT, Dynamic X-Ray Computed Tomography, Proceedings of the IEEE, 91(10): 1574-1587, 2003.
[3] E.M.F. DAMEN, J.W.H. WOLTHAUS, M. VAN HERK, J.-J. SONKE, P. REMEIJER, L. ZIJP, Image-Guided radiotherapy for lung cancer: Respiration correlated cone-beam CT to verify tumor position and motion characteristics during treatment delivery (abstract), International Journal of Radiation Oncology Biology Physics, 60(1): S198, 2004.
[4] J.D. ESCOLAR, A. ESCOLAR, Lung histeresis: a morphological view, Histology and Histopathology, 19(1): p. 159-166, 2004.
[5] L.A. FELDKAMP, L.C. DAVIS, J.W. KRESS, Practical cone-beam algorithm, Journal of Optical Society of America A, 1(6): 612-619, 1984.
[6] E.C. FORD, G.S. MAGERAS, E. YORKE, C.C. LING, Respirationcorrelated spiral CT: A method of measuring respiratory-induced anatomic motion for radiation treatment planning, Medical Physics, 30(1): 88-97, 2003.
[7] D.P. GIERGA, J. BREWER, G.C. SHARP, M. BETKE, C.G. WILLETT, G.T.Y. CHEN, The correlation between internal and external markers for abdominal tumors: implications for respiratory gating, International Journal of Radiation Oncology Biology Physics, 61(5): p.1551-1558, 2005.
[8] P. GRANGEAT, La Tomographie, Hermes Science, 2002.
[9] P. GRANGEAT, A. KOENIG, T. RODET, S. BONNET, Theoretical framework for a dynamic cone-beam reconstruction algorithm based on a dynamic particle model, Physics in Medicine and Biology, 47(15): 2611-2625, 2002.
[10] A.C. KAK, M. SLANEY, Principles of Computerized Tomographic Imaging, IEEE Press, 1998.
[11] P.J. KEALL, 4-Dimensional computed tomography imaging and treatment planning, Radiation Oncology, 14(1): 80-90, 2004.
[12] P.J. KEALL, G. STARKSCHALL, H. SHUKLA, K.M. FORSTER, V. ORTIZ, C.W. STEVENS, S.S. VEDAM, R. GEORGE, T. GUERRERO, R. MOHAN, Acquiring 4D thoracic CT scans using a multislice helical method, Physics in Medicine and Biology, 49(10): 2053-2067, 2004.
[13] N. KOCH, H. HELEN LIU, G. STARKSCHALL, M. JACOBSON, K. FORSTER, Z. LIAO, R. KOMAKI, C.W. STEVENS, Evaluation of internal lung motion for respiratory-gated radiotherapy using MRI: Part I-correlating internal lung motion with skin fiducial motion, International Journal of Radiation Oncology Biology Physics, 60(5) : 1459, 2004.
[14] T. KONDO, I. KOBAYASHI, Y. TAGUCHI, Y. OHTA, N. YANAGIMACHI, A dynamic analysis of chest wall motions with MRI in healthy young subjects, Respirology, 5(1): 16, 2000.
[15] H.D. KUBO, B.C. HILL, Respiration gated radiotherapy treatment: a technical study. Physics in Medicine and Biology, 41(1): 83-91, 1996.
[16] P.G. LACROUTE, Fast volume rendering using a shear-warp factorization of the viewing transformation, PhD thesis, Stanford University, 1995.
[17] D.A. LOW, M. NYSTROM, E. KALININ, P.J. PARIKH, J.F. DEMPSEY, J.D. BRADLEY, S. MUTIC, S.H. WAHAB, T. ISLAM, G. CHRISTENSEN, D.G. POLITTE, B.R. WHITING, A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. Medical Physics, 30(6): 1254-1263, 2003.
[18] W. LU, P.J. PARIKH, I.M. EL NAQA, M.M. NYSTROM, J.P. HUBENSCHMIDT, S.H. WAHAB, S. MUTIC, A.K. SINGH, G.E. CHRISTENSEN, J.D. BRADLEY, D.A. LOW, Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients. Medical Physics, 32(4): 835-1228, 2005.
[19] S. MORI, M. ENDO, T. TSUNOO, S. KANDATSU, S. TANADA, H. ARADATE, Y. SAITO, H. MIYAZAKI, K. SATOH, S. MATSUSHITA, M. KUSAKABE, Physical performance evaluation of a 256-Slice CT-Scanner for four-dimensional imaging, Medical Physics, 31(6): 1348-1356, 2004.
[20] T. PAN, T.Y. LEE, E. RIETZEL, G.T.Y. CHEN, 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT, Medical Physics, 31(2): 333-341, 2004.
[21] C.J. RITCHIE, J.D. GODWIN, C.R. CRAWFORD, W. STANFORD, H. ANNO, Y. KIM, Minimum scan speeds for suppression of motion artifacts in CT, Radiology, 185(1): 37-42, 1992.
[22] D. SARRUT, V. BOLDEA, M. AYADI, J.-N. BADEL, C. GINESTET, S. CLIPPE, Non-rigid registration method to assess reproducibility of breath-holding with ABC in lung cancer, International Journal of Radiation Oncology Biology Physics, 61(2): 281-294, 2005.
[23] D. SARRUT, V. BOLDEA, S. MIGUET, C. GINESTET, Simulation of 4D CT images from deformable registration between inhale and exhale breath-hold CT scans. Medical Physics, 33(3):605-617, 2006.
[24] T. SIKORA, MPEG-1 and MPEG-2 digital video coding standards, IEEE Signal Processing Management, 14(5): 82-100, 1997.
[25] J.-J. SONKE, L. ZIJP, P. REMEIJER, M. VAN HERK, Respiratory correlated cone beam CT. Medical Physics, 32(4): 1176-1186, 2005.
[26] R.W.M. UNDERBERG, F.J. LAGERWAARD, J.P. CUIJPERS, B.J. SLOTMAN, J.T. VAN SÖRNSEN DE KOSTE, S. SENAN, Fourdimensional CT scans for treatment planning in stereotactic radiotherapy for stage I lung cancer, International Journal of Radiation Oncology Biology Physics, 60(4): 1283-1290, 2004.
[27] S.S. VEDAM, P.J. KEALL, V.R. KINI, H. MOSTAFAVI, H.P. SHUKLA, R. MOHAN, Acquiring a four-dimensional computed tomography dataset using an external respiratory signal, Physics in Medicine and Biology, 48(1): 45-62, 2003.
[28] J.W. WONG, M.B. SHARPE, D.A. JAFFRAY, V.R. KINI, J.M. ROBERTSON, J.S. STROMBERG, A.A. MARTINEZ, The use of active breathing control (ABC) to reduce margin for breathing motion, International Journal of Radiation Oncology Biology Physics, 44(4): 911-919, 1999.
[29] T. ZHANG, H. KELLER, M.J. O'BRIEN, T.R. MACKIE, B. PALIWAL, Application of the spirometer in respiratory gated radiotherapy, Medical Physics, 30(12):3165-3171, 2003.
[30] L. ZIJP, J.-J. SONKE, M. VAN HERK, Extraction of the respiratory signal from sequential thorax Cone-Beam X-ray images. In International Conference on the Use of Computers in Radiation Therapy, 2004.