Investigating rectal toxicity associated dosimetric features with deformable accumulated rectal surface dose maps for cervical cancer radiotherapy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-07-06

AUTHORS

Jiawei Chen, Haibin Chen, Zichun Zhong, Zhuoyu Wang, Brian Hrycushko, Linghong Zhou, Steve Jiang, Kevin Albuquerque, Xuejun Gu, Xin Zhen

ABSTRACT

BACKGROUND: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction. METHODS: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including 12 with Grade ≥ 2 rectum toxicity and 30 patients with Grade 0-1 toxicity (non-toxicity patients). The cumulative equivalent 2-Gy rectal surface dose was deformably summed using the deformation vector fields obtained through a recent developed local topology preserved non-rigid point matching algorithm. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectum surface dose map (RSDM). The dose volume parameters (DVPs) were calculated from the 3D rectum surface, while the texture features and the dose geometric parameters (DGPs) were extracted from the 2D RSDM. Representative features further computed from DVPs, textures and DGPs by principle component analysis (PCA) and statistical analysis were respectively fed into a support vector machine equipped with a sequential feature selection procedure. The predictive powers of the representative features were compared with the GEC-ESTRO dosimetric parameters D0.1/1/2cm3. RESULTS: Satisfactory predictive accuracy of sensitivity 74.75 and 84.75%, specificity 72.67 and 79.87%, and area under the receiver operating characteristic curve (AUC) 0.82 and 0.91 were respectively achieved by the PCA features and statistical significant features, which were superior to the D0.1/1/2cm3 (AUC 0.71). The relative area in dose levels of 64Gy, 67Gy, 68Gy, 87Gy, 88Gy and 89Gy, perimeters in dose levels of 89Gy, as well as two texture features were ranked as the important factors that were closely correlated with rectal toxicity. CONCLUSIONS: Our extensive experimental results have demonstrated the feasibility of the proposed scheme. A future large patient cohort study is still needed for model validation. More... »

PAGES

125

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13014-018-1068-0

DOI

http://dx.doi.org/10.1186/s13014-018-1068-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105336356

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29980214


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28 schema:description BACKGROUND: Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional dose-toxicity model is based on the dose volume histogram, which is the parameter lacking spatial dose information. To overcome this limit, we explore a comprehensive rectal dose-toxicity model based on both dose volume histogram and dose map features for accurate radiation toxicity prediction. METHODS: Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively studied, including 12 with Grade ≥ 2 rectum toxicity and 30 patients with Grade 0-1 toxicity (non-toxicity patients). The cumulative equivalent 2-Gy rectal surface dose was deformably summed using the deformation vector fields obtained through a recent developed local topology preserved non-rigid point matching algorithm. The cumulative three-dimensional (3D) dose was flattened and mapped to a two-dimensional (2D) plane to obtain the rectum surface dose map (RSDM). The dose volume parameters (DVPs) were calculated from the 3D rectum surface, while the texture features and the dose geometric parameters (DGPs) were extracted from the 2D RSDM. Representative features further computed from DVPs, textures and DGPs by principle component analysis (PCA) and statistical analysis were respectively fed into a support vector machine equipped with a sequential feature selection procedure. The predictive powers of the representative features were compared with the GEC-ESTRO dosimetric parameters D<sub>0.1/1/2cm</sub><sup>3</sup>. RESULTS: Satisfactory predictive accuracy of sensitivity 74.75 and 84.75%, specificity 72.67 and 79.87%, and area under the receiver operating characteristic curve (AUC) 0.82 and 0.91 were respectively achieved by the PCA features and statistical significant features, which were superior to the D<sub>0.1/1/2cm</sub><sup>3</sup> (AUC 0.71). The relative area in dose levels of 64Gy, 67Gy, 68Gy, 87Gy, 88Gy and 89Gy, perimeters in dose levels of 89Gy, as well as two texture features were ranked as the important factors that were closely correlated with rectal toxicity. CONCLUSIONS: Our extensive experimental results have demonstrated the feasibility of the proposed scheme. A future large patient cohort study is still needed for model validation.
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35 schema:keywords DGPs
36 Extensive experimental results
37 GEC-ESTRO dosimetric parameters D
38 PCA features
39 RSDM
40 accuracy
41 accurate radiation toxicity prediction
42 algorithm
43 analysis
44 area
45 beam radiotherapy
46 better knowledge
47 brachytherapy
48 cancer patients
49 cancer radiotherapy
50 cervical cancer patients
51 cervical cancer radiotherapy
52 cohort study
53 component analysis
54 comprehensive rectal dose-toxicity model
55 control
56 conventional dose-toxicity model
57 deformation vector fields
58 dose
59 dose escalation
60 dose information
61 dose levels
62 dose map features
63 dose maps
64 dose-toxicity model
65 dose-toxicity relationship
66 dose-volume histograms
67 dose-volume parameters
68 dosimetric features
69 dosimetric parameters D
70 escalation
71 experimental results
72 external beam radiotherapy
73 factors
74 feasibility
75 feature selection procedure
76 features
77 field
78 future large patient cohort study
79 geometric parameters
80 grade
81 grade 0
82 histogram
83 important factor
84 information
85 knowledge
86 large patient cohort study
87 levels
88 limit
89 local control
90 local topology
91 machine
92 map features
93 maps
94 matching algorithm
95 model
96 model validation
97 non-rigid point matching algorithm
98 parameter D
99 parameters
100 patient cohort study
101 patients
102 perimeter
103 plane
104 point matching algorithm
105 power
106 prediction
107 predictive accuracy
108 predictive power
109 principle component analysis
110 procedure
111 radiation toxicity prediction
112 radiotherapy
113 receiver
114 rectal dose-toxicity model
115 rectal surface dose
116 rectal surface dose maps
117 rectal toxicity
118 rectum surface
119 rectum toxicity
120 relationship
121 relative area
122 representative features
123 results
124 safe dose escalation
125 satisfactory predictive accuracy
126 scheme
127 selection procedure
128 sequential feature selection procedure
129 significant features
130 spatial dose information
131 statistical analysis
132 statistical significant features
133 study
134 support vector machine
135 surface
136 surface dose
137 surface dose map
138 texture
139 texture features
140 three-dimensional dose
141 topology
142 toxicity
143 toxicity prediction
144 two-dimensional plane
145 validation
146 vector fields
147 vector machine
148 volume histograms
149 volume parameters
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