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Title: SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors

Abstract

Purpose: The dose–volume histogram (DVH) has been normally accepted as a tool for treatment plan evaluation. However, spatial information is lacking in DVH. As a supplement to the DVH in three-dimensional treatment planning, the differential DVH (DDVH) provides the spatial variation, the size and magnitude of the different dose regions within a region of interest, which can be incorporated into tumor control probability model. This study was to provide a method in evaluating and improving Gamma Knife treatment planning. Methods: 10 patients with brain metastases from different primary tumors including melanoma (#1,#4,#5, #10), breast cancer (#2), prostate cancer (#3) and lung cancer (#6–9) were analyzed. By using Leksell GammaPlan software, two plans were prepared for each patient. Special attention was given to the DDVHs that were different for different plans and were used for a comparison between two plans. Dose distribution inside target and tumor control probability (TCP) based on DDVH were calculated, where cell density and radiobiological parameters were adopted from literature. The plans were compared based on DVH, DDVH and TCP. Results: Using DVH, the coverage and selectivity were the same between plans for 10 patients. DDVH were different between two plans for each patient. The paired t-testmore » showed no significant difference in TCP between the two plans. For brain metastases from melanoma (#1, #4–5), breast cancer (#2) and lung cancer (#6–8), the difference in TCP was less than 5%. But the difference in TCP was about 6.5% for patient #3 with the metastasis from prostate cancer, 10.1% and 178.7% for two patients (#9–10) with metastasis from lung cancer. Conclusion: Although DVH provides average dose–volume information, DDVH provides differential dose– volume information with respect to different regions inside the tumor. TCP provides radiobiological information and adds additional information on improving treatment planning as well as adaptive radiotherapy. Further clinical validation is necessary.« less

Authors:
 [1];  [2];  [3];  [4]; ;  [5]
  1. East Carolina University, Greenville, NC (United States)
  2. East Carolina Univ, Rockville, MD (United States)
  3. Case Western Reserve University, Cleveland, OH (United States)
  4. Ohio State University, Columbus, OH (United States)
  5. University of Washington, Seattle, WA (United States)
Publication Date:
OSTI Identifier:
22548513
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; BRAIN; COMPUTER CODES; LUNGS; MAMMARY GLANDS; MELANOMAS; METASTASES; PATIENTS; PROSTATE; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; RADIOTHERAPY; VALIDATION

Citation Formats

Huang, Z, Feng, Y, Lo, S, Grecula, J, Mayr, N, and Yuh, W. SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors. United States: N. p., 2015. Web. doi:10.1118/1.4924833.
Huang, Z, Feng, Y, Lo, S, Grecula, J, Mayr, N, & Yuh, W. SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors. United States. doi:10.1118/1.4924833.
Huang, Z, Feng, Y, Lo, S, Grecula, J, Mayr, N, and Yuh, W. Mon . "SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors". United States. doi:10.1118/1.4924833.
@article{osti_22548513,
title = {SU-E-T-471: Improvement of Gamma Knife Treatment Planning Through Tumor Control Probability for Metastatic Brain Tumors},
author = {Huang, Z and Feng, Y and Lo, S and Grecula, J and Mayr, N and Yuh, W},
abstractNote = {Purpose: The dose–volume histogram (DVH) has been normally accepted as a tool for treatment plan evaluation. However, spatial information is lacking in DVH. As a supplement to the DVH in three-dimensional treatment planning, the differential DVH (DDVH) provides the spatial variation, the size and magnitude of the different dose regions within a region of interest, which can be incorporated into tumor control probability model. This study was to provide a method in evaluating and improving Gamma Knife treatment planning. Methods: 10 patients with brain metastases from different primary tumors including melanoma (#1,#4,#5, #10), breast cancer (#2), prostate cancer (#3) and lung cancer (#6–9) were analyzed. By using Leksell GammaPlan software, two plans were prepared for each patient. Special attention was given to the DDVHs that were different for different plans and were used for a comparison between two plans. Dose distribution inside target and tumor control probability (TCP) based on DDVH were calculated, where cell density and radiobiological parameters were adopted from literature. The plans were compared based on DVH, DDVH and TCP. Results: Using DVH, the coverage and selectivity were the same between plans for 10 patients. DDVH were different between two plans for each patient. The paired t-test showed no significant difference in TCP between the two plans. For brain metastases from melanoma (#1, #4–5), breast cancer (#2) and lung cancer (#6–8), the difference in TCP was less than 5%. But the difference in TCP was about 6.5% for patient #3 with the metastasis from prostate cancer, 10.1% and 178.7% for two patients (#9–10) with metastasis from lung cancer. Conclusion: Although DVH provides average dose–volume information, DDVH provides differential dose– volume information with respect to different regions inside the tumor. TCP provides radiobiological information and adds additional information on improving treatment planning as well as adaptive radiotherapy. Further clinical validation is necessary.},
doi = {10.1118/1.4924833},
journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 42,
place = {United States},
year = {2015},
month = {6}
}