William Harvey Greene

Constrained non-rigid registration for use in image-guided adaptive radiotherapy

A constrained non-rigid registration (CNRR) algorithm for use in prostate image-guided adaptive radiotherapy is presented in a coherent mathematical framework. The registration algorithm is based on a global rigid transformation combined with a series of local injective non-rigid multi-resolution cubic B-spline Free Form Deformation (FFD) transformations. The control points of the FFD are used to non-rigidly constrain the transformation to the prostate, rectum, and bladder. As well, the control points are used to rigidly constrain the transformation to the estimated position of the pelvis, left femur, and right femur. The algorithm was tested with both 3D conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT) dose plan data sets. The 3DCRT dose plan set consisted of 10 fan-beam CT (FBCT) treatment-day images acquired from four different patients. The IMRT dose plan set consisted of 32 cone-beam CT (CBCT) treatment-day images acquired from 4 different patients. The CNRR was tested with different combinations of anatomical constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR results were used to adapt the dose plans to account for patient positioning errors as well as inter-day bone motion and intrinsic organ deformation. Each adapted dose plan improved performance by lowering radiation distribution to the rectum and bladder while increasing or maintaining radiation distribution to the prostate.

A Constrained Non-rigid Registration Algorithm for Use in Prostate Image-Guided Radiotherapy

A constrained non-rigid registration (CNRR) algorithm for use in updating prostate external beam image-guided radiotherapy treatment plans is presented in this paper. The developed algorithm is based on a multi-resolution cubic B-spline FFD transformation and has been tested and verified using 3D CT images from 10 sets of real patient data acquired from 4 different patients on different treatment days. The registration can be constrained to any combination of the prostate, rectum, bladder, pelvis, left femur, and right femur. The CNRR was tested with 5 different combinations of constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR was then used to update the treatment plans to account for articulated, rigid bone motion and non-rigid organ deformation. Each updated treatment plan outperformed the original treatment plan by increasing radiation dosage to the prostate and lowering radiation dosage to the rectum and bladder.

A CONSTRAINED NON-RIGID REGISTRATION ALGORITHM FOR APPLICATION IN PROSTATE RADIOTHERAPY

This paper presents a novel free-form deformation registration algorithm with non-rigid constraints to capture the transformation between the planning day and treatment day CT images used for external beam radiotherapy for prostate cancer. The algorithm is constrained to the predetermined motion of a segmented organ, which is described by an injective free-form deformation (FFD) based on B-splines. The end goal is for the injective transformation to be used to update the radiotherapy plan to take into account bone and soft tissue deformation. The results of the algorithm have been compared to those achieved using rigid and fully non-rigid registration. The results clearly indicate that the constrained non-rigid registration algorithm presented in this paper performed much better at capturing the motion of the constrained organ, the bladder in this case, than the rigid or fully non-rigid registration algorithms.

Tracking organ overlap for a constrained non-rigid registration algorithm

This paper tracks organ (prostate, rectum, bladder) overlap in a constrained non-rigid registration (NRR) algorithm to register computed tomographic (CT) images used in external beam prostate radiotherapy. The local motion of the organs is described by a hierarchical multi-resolution FFD based on cubic B-splines. Registration is achieved by minimizing a cost function which is a combination of three functions representing the overlap of the critical organs, image similarity and smoothness of the transformation. The constrained NRR algorithm generated better registration results when compared to an unconstrained NRR algorithm.

Supportive Care in the Cancer Patient

“Supportive care,” as the term is currently used, embraces a large and diverse group of medical and paramedical specialties, of which the common bond is the minimization or prevention of the common complications of cancer and its therapy. Although not unique to those with malignancy, the art and science of caring for their social, psychological, and somatic distress have become more highly developed than for perhaps any other single patient group. There have been a number of recent reviews of all or parts of this field (Holland and Frei, 1973; Goepp and Hammond, 1975).

Corrigendum to “Constrained non-rigid registration for use in image-guided adaptive radiotherapy” [Medical Image Analysis 13 (2009) 809–817]

Corrigendum Corrigendum to ‘‘Constrained non-rigid registration for use in image-guided adaptive radiotherapy” [Medical Image Analysis 13 (2009) 809–817] W.H. Greene *, S. Chelikani , K. Purushothaman , J.P.S. Knisely , Z. Chen , X. Papademetris , L.H. Staib , J.S. Duncan a,b Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA Department of Therapeutic Radiology, Yale University, New Haven, CT 06520, USA