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Title: SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation

Abstract

Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generated target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacentmore » lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.« less

Authors:
; ; ; ;  [1]; ;  [2]
  1. University of North Carolina, Chapel Hill, NC (United States)
  2. MIM Software Inc., Cleveland, OH (United States)
Publication Date:
OSTI Identifier:
22634704
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; CORRELATIONS; FLUORINE 18; FLUORODEOXYGLUCOSE; IMAGES; LUNGS; LYMPH; LYMPH NODES; MONTE CARLO METHOD; NEOPLASMS; PHANTOMS; POSITRON COMPUTED TOMOGRAPHY; SIMULATION

Citation Formats

Dance, M, Wu, G, Gao, Y, Das, S, Lian, J, Pirozzi, S, and Nelson, A. SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation. United States: N. p., 2016. Web. doi:10.1118/1.4956003.
Dance, M, Wu, G, Gao, Y, Das, S, Lian, J, Pirozzi, S, & Nelson, A. SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation. United States. doi:10.1118/1.4956003.
Dance, M, Wu, G, Gao, Y, Das, S, Lian, J, Pirozzi, S, and Nelson, A. Wed . "SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation". United States. doi:10.1118/1.4956003.
@article{osti_22634704,
title = {SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation},
author = {Dance, M and Wu, G and Gao, Y and Das, S and Lian, J and Pirozzi, S and Nelson, A},
abstractNote = {Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generated target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacent lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.},
doi = {10.1118/1.4956003},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}