Measuring breathing induced oesophageal motion and its dosimetric impact

Stereotactic body radiation therapy allows for a precise and accurate dose delivery. Organ motion during treatment bares the risk of undetected high dose healthy tissue exposure. An organ very susceptible to high dose is the oesophagus. Its low contrast on CT and the oblong shape renders motion estimation difficult. We tackle this issue by modern algorithms to measure the oesophageal motion voxel-wise and to estimate motion related dosimetric impact. Oesophageal motion was measured using deformable image registration and 4DCT of 11 internal and 5 public datasets. Current clinical practice of contouring the organ on 3DCT was compared to timely resolved 4DCT contours. The dosimetric impact of the motion was estimated by analysing the trajectory of each voxel in the 4D dose distribution. Finally an organ motion model was built, allowing for easier patient-wise comparisons. Motion analysis showed mean absolute maximal motion amplitudes of 4.24 +/- 2.71 mm left-right, 4.81 +/- 2.58 mm anterior-posterior and 10.21 +/- 5.13 mm superior-inferior. Motion between the cohorts differed significantly. In around 50 % of the cases the dosimetric passing criteria was violated. Contours created on 3DCT did not cover 14 % of the organ for 50 % of the respiratory cycle and the 3D contour is around 38 % smaller than the union of all 4D contours. The motion model revealed that the maximal motion is not limited to the lower part of the organ. Our results showed motion amplitudes higher than most reported values in the literature and that motion is very heterogeneous across patients. Therefore, individual motion information should be considered in contouring and planning.

[1]  M Hussein,et al.  Challenges in calculation of the gamma index in radiotherapy - Towards good practice. , 2017, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[2]  Gorjan Alagic,et al.  #p , 2019, Quantum information & computation.

[3]  G. Starkschall,et al.  Assessment of consistency in contouring of normal‐tissue anatomic structures , 2003, Journal of applied clinical medical physics.

[4]  R. Castillo,et al.  A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets , 2009, Physics in medicine and biology.

[5]  Kana Takahashi,et al.  Intrafraction esophageal motion in patients with clinical T1N0 esophageal cancer. , 2018, Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology.

[6]  R. Castillo,et al.  Four-dimensional deformable image registration using trajectory modeling , 2010, Physics in medicine and biology.

[7]  Z. Lambert,et al.  SegTHOR: Segmentation of Thoracic Organs at Risk in CT images , 2019, 2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA).

[8]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[9]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[10]  Dimos Baltas,et al.  Esophagus segmentation in CT via 3D fully convolutional neural network and random walk , 2017, Medical physics.

[11]  Andrzej Niemierko,et al.  Implications of respiratory motion as measured by four-dimensional computed tomography for radiation treatment planning of esophageal cancer. , 2009, International journal of radiation oncology, biology, physics.

[12]  P. Keall,et al.  Esophagus and spinal cord motion relative to GTV motion in four-dimensional CTs of lung cancer patients. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[13]  Composite QA for intensity-modulated radiation therapy using individual volume–based 3D gamma indices , 2018, Journal of radiation research.

[14]  Stephen M. Moore,et al.  The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository , 2013, Journal of Digital Imaging.

[15]  T. Kimura,et al.  Quantifying esophageal motion during free-breathing and breath-hold using fiducial markers in patients with early-stage esophageal cancer , 2018, PloS one.

[16]  Dimos Baltas,et al.  One-Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking , 2019, IEEE Transactions on Medical Imaging.

[17]  Max A. Viergever,et al.  elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.

[18]  Rudy Guerra,et al.  Determination of respiratory motion for distal esophagus cancer using four-dimensional computed tomography. , 2008, International journal of radiation oncology, biology, physics.

[19]  Benjamin Movsas,et al.  Consideration of dose limits for organs at risk of thoracic radiotherapy: atlas for lung, proximal bronchial tree, esophagus, spinal cord, ribs, and brachial plexus. , 2011, International journal of radiation oncology, biology, physics.

[20]  U Nestle,et al.  LungTech, an EORTC Phase II trial of stereotactic body radiotherapy for centrally located lung tumours: a clinical perspective. , 2015, The British journal of radiology.

[21]  K Paskalev,et al.  Esophageal motion during radiotherapy: quantification and margin implications. , 2010, Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus.

[22]  Ping Xia,et al.  Tolerance limits and methodologies for IMRT measurement‐based verification QA , 2018, Medical physics.

[23]  J. Bayouth,et al.  Impact of temporal probability in 4D dose calculation for lung tumors. , 2015, Journal of applied clinical medical physics.

[24]  G. Fitzgerald,et al.  'I. , 2019, Australian journal of primary health.

[25]  T. Sørensen,et al.  A method of establishing group of equal amplitude in plant sociobiology based on similarity of species content and its application to analyses of the vegetation on Danish commons , 1948 .

[26]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[27]  Hao Gao,et al.  Impact of Esophageal Motion on Dosimetry and Toxicity With Thoracic Radiation Therapy , 2019, Technology in cancer research & treatment.

[28]  Paul Aljabar,et al.  Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017 , 2018, Medical physics.

[29]  Radhe Mohan,et al.  Four-dimensional computed tomography-based treatment planning for intensity-modulated radiation therapy and proton therapy for distal esophageal cancer. , 2008, International journal of radiation oncology, biology, physics.

[30]  J. Bayouth,et al.  Impact of temporal probability in 4D dose calculation for lung tumors , 2015, Journal of applied clinical medical physics.

[31]  Stefanie Ehrbar,et al.  Three-dimensional versus four-dimensional dose calculation for volumetric modulated arc therapy of hypofractionated treatments. , 2016, Zeitschrift fur medizinische Physik.

[32]  Klaus H. Maier-Hein,et al.  nnU-Net: Breaking the Spell on Successful Medical Image Segmentation , 2019, ArXiv.

[33]  Tinsu Pan,et al.  Motion of the Esophagus Due to Cardiac Motion , 2014, PloS one.

[34]  John H. Lewis,et al.  3D delivered dose assessment using a 4DCT-based motion model. , 2015, Medical physics.

[35]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

[36]  P. Brown,et al.  Dosimetric impact of esophagus motion in single fraction spine stereotactic body radiotherapy , 2019, Physics in medicine and biology.

[37]  Lech Papiez,et al.  Excessive toxicity when treating central tumors in a phase II study of stereotactic body radiation therapy for medically inoperable early-stage lung cancer. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[38]  S. Shimizu,et al.  Esophageal motion characteristics in thoracic esophageal cancer: Impact of clinical stage T4 versus stages T1-T3 , 2016, Advances in radiation oncology.

[39]  Patrick Clarysse,et al.  Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs. , 2010, Medical physics.

[40]  C. Jeong,et al.  Evaluation of delivered dose to a moving target by 4D dose reconstruction in gated volumetric modulated arc therapy , 2018, PloS one.