Statistical modeling of CTV motion and deformation for IMRT of early-stage rectal cancer.

PURPOSE To derive and validate a statistical model of motion and deformation for the clinical target volume (CTV) of early-stage rectal cancer patients. METHODS AND MATERIALS For 16 patients, 4 to 5 magnetic resonance images (MRI) were acquired before each fraction was administered. The CTV was delineated on each MRI. Using a leave-one-out methodology, we constructed a population-based principal component analysis (PCA) model of the CTV motion and deformation of 15 patients, and we tested the model on the left-out patient. The modeling error was calculated as the amount of the CTV motion-deformation of the left-out-patient that could not be explained by the PCA model. Next, the PCA model was used to construct a PCA target volume (PCA-TV) by accumulating motion-deformations simulated by the model. A PCA planning target volume (PTV) was generated by expanding the PCA-TV by uniform margins. The PCA-PTV was compared with uniform and nonuniform CTV-to-PTV margins. To allow comparison, geometric margins were determined to ensure adequate coverage, and the volume difference between the PTV and the daily CTV (CTV-to-PTV volume) was calculated. RESULTS The modeling error ranged from 0.9 ± 0.5 to 2.9 ± 2.1 mm, corresponding to a reduction of the CTV motion-deformation between 6% and 60% (average, 23% ± 11%). The reduction correlated with the magnitude of the CTV motion-deformation (P<.001, R=0.66). The PCA-TV and the CTV required 2-mm and 7-mm uniform margins, respectively. The nonuniform CTV-to-PTV margins were 4 mm in the left, right, inferior, superior, and posterior directions and 8 mm in the anterior direction. Compared to uniform and nonuniform CTV-to-PTV margins, the PCA-based PTV significantly decreased (P<.001) the average CTV-to-PTV volume by 128 ± 20 mL (49% ± 4%) and by 35 ± 6 mL (20% ± 3.5%), respectively. CONCLUSIONS The CTV motion-deformation of a new patient can be explained by a population-based PCA model. A PCA model-generated PTV significantly improved sparing of organs at risk compared to uniform and nonuniform CTV-to-PTV margins.

[1]  M. Alber,et al.  Modelling individual geometric variation based on dominant eigenmodes of organ deformation: implementation and evaluation , 2005, Physics in medicine and biology.

[2]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  J. Sonke,et al.  Target volume shape variation during hypo-fractionated preoperative irradiation of rectal cancer patients. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[4]  I. Jolliffe Principal Component Analysis , 2002 .

[5]  Andrew Bayley,et al.  Rectal motion in patients receiving preoperative radiotherapy for carcinoma of the rectum. , 2011, International journal of radiation oncology, biology, physics.

[6]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[7]  Karin Haustermans,et al.  IGRT in rectal cancer , 2008, Acta oncologica.

[8]  J. Sonke,et al.  Target volume shape variation during irradiation of rectal cancer patients in supine position: comparison with prone position. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[9]  Jasper Nijkamp,et al.  Target volume delineation variation in radiotherapy for early stage rectal cancer in the Netherlands. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[10]  L Bondar,et al.  A population-based model to describe geometrical uncertainties in radiotherapy: applied to prostate cases , 2011, Physics in medicine and biology.

[11]  C. V. D. van de Velde,et al.  Late side effects of short-course preoperative radiotherapy combined with total mesorectal excision for rectal cancer: increased bowel dysfunction in irradiated patients--a Dutch colorectal cancer group study. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[12]  D. Dearnaley,et al.  Intensity-modulated radiotherapy in patients with locally advanced rectal cancer reduces volume of bowel treated to high dose levels. , 2006, International journal of radiation oncology, biology, physics.

[13]  Rainer Fietkau,et al.  Preoperative versus postoperative chemoradiotherapy for rectal cancer. , 2004, The New England journal of medicine.

[14]  S Breedveld,et al.  Computation of mean and variance of the radiotherapy dose for PCA-modeled random shape and position variations of the target , 2014, Physics in medicine and biology.

[15]  Hein Putter,et al.  Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer: 12-year follow-up of the multicentre, randomised controlled TME trial. , 2011, The Lancet. Oncology.

[16]  M. V. van Herk,et al.  Repeat CT assessed CTV variation and PTV margins for short- and long-course pre-operative RT of rectal cancer. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.