TY - JOUR
T1 - Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy
AU - Rigaud, Bastien
AU - Simon, Antoine
AU - Gobeli, Maxime
AU - Leseur, Julie
AU - Duvergé, Loig
AU - Williaume, Danièle
AU - Castelli, Joël
AU - Lafond, Caroline
AU - Acosta, Oscar
AU - Haigron, Pascal
AU - De Crevoisier, Renaud
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over five weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organ-at-risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient's modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library, showing an improvement in both target coverage and OAR sparing.
AB - External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over five weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organ-at-risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient's modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library, showing an improvement in both target coverage and OAR sparing.
KW - PCA model
KW - Radiotherapy
KW - cervical
KW - deformable mesh registration
KW - planning library
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U2 - 10.1109/TMI.2018.2865547
DO - 10.1109/TMI.2018.2865547
M3 - Article
C2 - 30130179
AN - SCOPUS:85051797419
SN - 0278-0062
VL - 38
SP - 406
EP - 416
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 2
M1 - 8438508
ER -