TY - JOUR
T1 - Statistical analysis and correlation discovery of tumor respiratory motion
AU - Wu, Huanmei
AU - Sharp, Gregory C.
AU - Zhao, Qingya
AU - Shirato, Hiroki
AU - Jiang, Steve B.
PY - 2007/8/21
Y1 - 2007/8/21
N2 - Tumors, especially in the thorax and abdomen, are subject to respiratory motion, and understanding the structure of respiratory motion is a key component to the management and control of disease in these sites. We have applied statistical analysis and correlation discovery methods to analyze and mine tumor respiratory motion based on a finite state model of tumor motion. Aggregates (such as minimum, maximum, average and mean), histograms, percentages, linear regression and multi-round statistical analysis have been explored. The results have been represented in various formats, including tables, graphs and text description. Different graphs, for example scatter plots, clustered column figures, 100% stacked column figures and box-whisker plots, have been applied to highlight different aspects of the results. The internal tumor motion from 42 lung tumors, 30 of which have motion larger than 5 mm, has been analyzed. Results for both inter-patient and intra-patient motion characteristics, such as duration and travel distance patterns, are reported. New knowledge of patient-specific tumor motion characteristics have been discovered, such as expected correlations between properties. The discovered tumor motion characteristics will be utilized in different aspects of image-guided radiation treatment, including treatment planning, online tumor motion prediction and real-time radiation dose delivery.
AB - Tumors, especially in the thorax and abdomen, are subject to respiratory motion, and understanding the structure of respiratory motion is a key component to the management and control of disease in these sites. We have applied statistical analysis and correlation discovery methods to analyze and mine tumor respiratory motion based on a finite state model of tumor motion. Aggregates (such as minimum, maximum, average and mean), histograms, percentages, linear regression and multi-round statistical analysis have been explored. The results have been represented in various formats, including tables, graphs and text description. Different graphs, for example scatter plots, clustered column figures, 100% stacked column figures and box-whisker plots, have been applied to highlight different aspects of the results. The internal tumor motion from 42 lung tumors, 30 of which have motion larger than 5 mm, has been analyzed. Results for both inter-patient and intra-patient motion characteristics, such as duration and travel distance patterns, are reported. New knowledge of patient-specific tumor motion characteristics have been discovered, such as expected correlations between properties. The discovered tumor motion characteristics will be utilized in different aspects of image-guided radiation treatment, including treatment planning, online tumor motion prediction and real-time radiation dose delivery.
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U2 - 10.1088/0031-9155/52/16/004
DO - 10.1088/0031-9155/52/16/004
M3 - Article
C2 - 17671334
AN - SCOPUS:34547773226
SN - 0031-9155
VL - 52
SP - 4761
EP - 4774
JO - Physics in medicine and biology
JF - Physics in medicine and biology
IS - 16
M1 - 004
ER -