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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. 2016. "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 = 2016,
month = 6
}
  • Purpose: To improve the accuracy of volume and apparent diffusion coefficient (ADC) measurements in diffusion-weighted magnetic resonance imaging (MRI), we proposed a method based on thresholding both the b0 images and the ADC maps. Methods and Materials: In 21 heterogeneous lesions from patients with metastatic gastrointestinal stromal tumors (GIST), gross lesion were manually contoured, and corresponding volumes and ADCs were denoted as gross tumor volume (GTV) and gross ADC (ADC{sub g}), respectively. Using a k-means clustering algorithm, the probable high-cellularity tumor tissues were selected based on b0 images and ADC maps. ADC and volume of the tissues selected using themore » proposed method were denoted as thresholded ADC (ADC{sub thr}) and high-cellularity tumor volume (HCTV), respectively. The metabolic tumor volume (MTV) in positron emission tomography (PET)/computed tomography (CT) was measured using 40% maximum standard uptake value (SUV{sub max}) as the lower threshold, and corresponding mean SUV (SUV{sub mean}) was also measured. Results: HCTV had excellent concordance with MTV according to Pearson's correlation (r=0.984, P<.001) and linear regression (slope = 1.085, intercept = −4.731). In contrast, GTV overestimated the volume and differed significantly from MTV (P=.005). ADC{sub thr} correlated significantly and strongly with SUV{sub mean} (r=−0.807, P<.001) and SUV{sub max} (r=−0.843, P<.001); both were stronger than those of ADC{sub g}. Conclusions: The proposed lesion-adaptive semiautomatic method can help segment high-cellularity tissues that match hypermetabolic tissues in PET/CT and enables more accurate volume and ADC delineation on diffusion-weighted MR images of GIST.« less
  • Purpose: Validate the consistency of a gradient-based segmentation tool to facilitate accurate delineation of PET/CT-based GTVs in head and neck cancers by comparing against hybrid PET/MR-derived GTV contours. Materials and Methods: A total of 18 head and neck target volumes (10 primary and 8 nodal) were retrospectively contoured using a gradient-based segmentation tool by two observers. Each observer independently contoured each target five times. Inter-observer variability was evaluated via absolute percent differences. Intra-observer variability was examined by percentage uncertainty. All target volumes were also contoured using the SUV percent threshold method. The thresholds were explored case by case so itsmore » derived volume matched with the gradient-based volume. Dice similarity coefficients (DSC) were calculated to determine overlap of PET/CT GTVs and PET/MR GTVs. Results: The Levene’s test showed there was no statistically significant difference of the variances between the observer’s gradient-derived contours. However, the absolute difference between the observer’s volumes was 10.83%, with a range from 0.39% up to 42.89%. PET-avid regions with qualitatively non-uniform shapes and intensity levels had a higher absolute percent difference near 25%, while regions with uniform shapes and intensity levels had an absolute percent difference of 2% between observers. The average percentage uncertainty between observers was 4.83% and 7%. As the volume of the gradient-derived contours increased, the SUV threshold percent needed to match the volume decreased. Dice coefficients showed good agreement of the PET/CT and PET/MR GTVs with an average DSC value across all volumes at 0.69. Conclusion: Gradient-based segmentation of PET volume showed good consistency in general but can vary considerably for non-uniform target shapes and intensity levels. PET/CT-derived GTV contours stemming from the gradient-based tool show good agreement with the anatomically and metabolically more accurate PET/MR-derived GTV contours, but tumor delineation accuracy can be further improved with the use PET/MR.« less
  • Purpose: To examine MRI and CT for glandular breast tissue (GBT) volume delineation and to assess interobserver variability. Methods and Materials: Fifteen breast cancer patients underwent a planning CT and MRI, consecutively, in the treatment position. Four observers (two radiation oncologists and two radiologists) delineated the GBT according to the CT and separately to the MR images. Volumes, centers of mass, maximum extensions with standard deviations (SD), and interobserver variability were quantified. Observers viewed delineation differences between MRI and CT and delineation differences among observers. Results: In cranio-lateral and cranio-medial directions, GBT volumes were delineated larger using MRI when comparedmore » with those delineated with CT. Center of mass on MRI shifted a mean (SD) 17% (4%) into the cranial direction and a mean 3% (4%) into the dorsal direction when compared with that on the planning CT. Only small variations between observers were noted. The GBT volumes were approximately 4% larger on MRI (mean [SD] ratio MRI to CT GBT volumes, 1.04 [0.06]). Findings were concordant with viewed MRI and CT images and contours. Conformity indices were only slightly different; mean conformity index was 77% (3%) for MRI and 79% (4%) for CT. Delineation differences arising from personal preferences remained recognizable irrespective of the imaging modality used. Conclusions: Contoured GBT extends substantially further into the cranio-lateral and cranio-medial directions on MRI when compared with CT. Interobserver variability is comparable for both imaging modalities. Observers should be aware of existing personal delineation preferences. Institutions are recommended to review and discuss target volume delineations and to design supplementary guidelines if necessary.« less
  • Purpose: To evaluate the clinical application of a robust semiautomatic image segmentation method to determine the brain target volumes in radiation therapy treatment planning. Methods and Materials: A local robust region-based algorithm was used on MRI brain images to study the clinical target volume (CTV) of several patients. First, 3 oncologists delineated CTVs of 10 patients manually, and the process time for each patient was calculated. The averages of the oncologists’ contours were evaluated and considered as reference contours. Then, to determine the CTV through the semiautomatic method, a fourth oncologist who was blind to all manual contours selected 4-8more » points around the edema and defined the initial contour. The time to obtain the final contour was calculated again for each patient. Manual and semiautomatic segmentation were compared using 3 different metric criteria: Dice coefficient, Hausdorff distance, and mean absolute distance. A comparison also was performed between volumes obtained from semiautomatic and manual methods. Results: Manual delineation processing time of tumors for each patient was dependent on its size and complexity and had a mean (±SD) of 12.33 ± 2.47 minutes, whereas it was 3.254 ± 1.7507 minutes for the semiautomatic method. Means of Dice coefficient, Hausdorff distance, and mean absolute distance between manual contours were 0.84 ± 0.02, 2.05 ± 0.66 cm, and 0.78 ± 0.15 cm, and they were 0.82 ± 0.03, 1.91 ± 0.65 cm, and 0.7 ± 0.22 cm between manual and semiautomatic contours, respectively. Moreover, the mean volume ratio (=semiautomatic/manual) calculated for all samples was 0.87. Conclusions: Given the deformability of this method, the results showed reasonable accuracy and similarity to the results of manual contouring by the oncologists. This study shows that the localized region-based algorithms can have great ability in determining the CTV and can be appropriate alternatives for manual approaches in brain cancer.« less
  • Purpose: To study anatomic biologic contouring (ABC), using a previously described distinct halo, to unify volume contouring methods in treatment planning for head and neck cancers. Methods and Materials: Twenty-five patients with head and neck cancer at various sites were planned for radiation therapy using positron emission tomography/computed tomography (PET/CT). The ABC halo was used in all PET/CT scans to contour the gross tumor volume (GTV) edge. The CT-based GTV (GTV-CT) and PET/CT-based GTV (GTV-ABC) were contoured by two independent radiation oncologists. Results: The ABC halo was observed in all patients studied. The halo had a standard unit value ofmore » 2.19 {+-} 0.28. The mean halo thickness was 2.02 {+-} 0.21 mm. Significant volume modification ({>=}25%) was seen in 17 of 25 patients (68%) after implementation of GTV-ABC. Concordance among observers was increased with the use of the halo as a guide for GTV determination: 6 patients (24%) had a {<=}10% volume discrepancy with CT alone, compared with 22 (88%) with PET/CT (p < 0.001). Interobserver variability decreased from a mean GTV difference of 20.3 cm{sup 3} in CT-based planning to 7.2 cm{sup 3} in PET/CT-based planning (p < 0.001). Conclusions: Using the 'anatomic biologic halo' to contour GTV in PET/CT improves consistency among observers. The distinctive appearance of the described halo and its presence in all of the studied tumors make it attractive for GTV contouring in head and neck tumors. Additional studies are needed to confirm the correlation of the halo with presence of malignant cells.« less