TY - JOUR
T1 - Toward Precise Osteotomies
T2 - A Coarse-to-Fine 3D Cut Plane Planning Method for Image-Guided Pelvis Tumor Resection Surgery
AU - Zhang, Yu
AU - Li, Fengzan
AU - Qiu, Lei
AU - Xu, Lihui
AU - Niu, Xiaohui
AU - Sui, Yao
AU - Zhang, Shunli
AU - Zhang, Qing
AU - Zhang, Li
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Surgical resection is the main clinical method for the treatment of bone tumors. A critical procedure for bone tumor resection is to plan a set of cut planes that enable resecting the bone tumor with a safe margin while preserving the maximum amount of healthy bone. Currently, the surgeons rely on manual methods to plan the cut planes, which highly depend on the surgeons' experiences and have been demonstrated to be error-prone, and in turn, increase the recurrence rate or resect much healthy bone. This study targets on improving the precision of cut plane planning for the image guided pelvis tumor resection surgeries. A semi-automatic approach to cut plane planning was proposed via a coarse-to-fine strategy. It can efficiently identify a dangerous region in the 3D space, which contains the bone tumor and its surrounding normal tissue with a safe margin. By projecting the dangerous region into an appropriate 2D space, a segmented boundary-constrained linear regression method was leveraged to plan a set of 3D cut planes that ensure the minimum area of the resected specimen in the 2D space while having the dangerous region cleared. Further, a coarse-to-fine 3D cut plane planning method was developed by incorporating a 3D cut plane refinement scheme with our 2D planning method. Extensive experiments, on the surgical data from nine previous pelvis tumor resection surgeries, demonstrated that our proposed approach substantially improved the localization precision of cut planes (${p}< {0.001}$) and decreased the amount of resected specimen (${p}< {0.05}$), as compared to the manual method.
AB - Surgical resection is the main clinical method for the treatment of bone tumors. A critical procedure for bone tumor resection is to plan a set of cut planes that enable resecting the bone tumor with a safe margin while preserving the maximum amount of healthy bone. Currently, the surgeons rely on manual methods to plan the cut planes, which highly depend on the surgeons' experiences and have been demonstrated to be error-prone, and in turn, increase the recurrence rate or resect much healthy bone. This study targets on improving the precision of cut plane planning for the image guided pelvis tumor resection surgeries. A semi-automatic approach to cut plane planning was proposed via a coarse-to-fine strategy. It can efficiently identify a dangerous region in the 3D space, which contains the bone tumor and its surrounding normal tissue with a safe margin. By projecting the dangerous region into an appropriate 2D space, a segmented boundary-constrained linear regression method was leveraged to plan a set of 3D cut planes that ensure the minimum area of the resected specimen in the 2D space while having the dangerous region cleared. Further, a coarse-to-fine 3D cut plane planning method was developed by incorporating a 3D cut plane refinement scheme with our 2D planning method. Extensive experiments, on the surgical data from nine previous pelvis tumor resection surgeries, demonstrated that our proposed approach substantially improved the localization precision of cut planes (${p}< {0.001}$) and decreased the amount of resected specimen (${p}< {0.05}$), as compared to the manual method.
KW - 3D cut plane refinement
KW - Cut plane planning
KW - dangerous region generation
KW - pelvis tumor resection
KW - segmented boundary-constrained linear regression
UR - https://www.scopus.com/pages/publications/85084518402
U2 - 10.1109/TMI.2019.2951838
DO - 10.1109/TMI.2019.2951838
M3 - 文章
C2 - 31714218
AN - SCOPUS:85084518402
SN - 0278-0062
VL - 39
SP - 1511
EP - 1523
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 5
M1 - 8892498
ER -