Journal article
A region growing method for tumor volume segmentation on PET images for rectal and anal cancer patients
Medical physics (Lancaster), v 36(10), pp 4349-4358
04 Sep 2009
PMID: 19928065
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The application of automated segmentation methods for tumor delineation on
F
18
-fluorodeoxyglucose positron emission tomography (FDG-PET) images presents an opportunity to reduce the interobserver variability in radiotherapy (RT) treatment planning. In this work, three segmentation methods were evaluated and compared for rectal and anal cancer patients: (i) Percentage of the maximum standardized uptake value
(
SUV
%
max
)
, (ii) fixed SUV cutoff of 2.5
(
SUV
2.5
)
, and (iii) mathematical technique based on a confidence connected region growing (CCRG) method. A phantom study was performed to determine the
SUV
%
max
threshold value and found to be 43%,
SUV
43
%
max
. The CCRG method is an iterative scheme that relies on the use of statistics from a specified region in the tumor. The scheme is initialized by a subregion of pixels surrounding the maximum intensity pixel. The mean and standard deviation of this region are measured and the pixels connected to the region are included or not based on the criterion that they are greater than a value derived from the mean and standard deviation. The mean and standard deviation of this new region are then measured and the process repeats. FDG-PET-CT imaging studies for 18 patients who received RT were used to evaluate the segmentation methods. A PET avid
(
PET
avid
)
region was manually segmented for each patient and the volume was then used to compare the calculated volumes along with the absolute mean difference and range for all methods. For the
SUV
43
%
max
method, the volumes were always smaller than the
PET
avid
volume by a mean of 56% and a range of 21%-79%. The volumes from the
SUV
2.5
method were either smaller or larger than the
PET
avid
volume by a mean of 37% and a range of 2%-130%. The CCRG approach provided the best results with a mean difference of 9% and a range of 1%-27%. Results show that the CCRG technique can be used in the segmentation of tumor volumes on FDG-PET images, thus providing treatment planners with a clinically viable starting point for tumor delineation and minimizing the interobserver variability in radiotherapy planning.
Metrics
Details
- Title
- A region growing method for tumor volume segmentation on PET images for rectal and anal cancer patients
- Creators
- Ellen Day - Allegheny General HospitalJames Betler - Allegheny General HospitalDavid Parda - Allegheny General HospitalBodo Reitz - Allegheny General HospitalAlexander Kirichenko - Allegheny General HospitalSeyed Mohammadi - Allegheny General HospitalMoyed Miften - University of Colorado Denver
- Publication Details
- Medical physics (Lancaster), v 36(10), pp 4349-4358
- Publisher
- American Association of Physicists in Medicine
- Resource Type
- Journal article
- Academic Unit
- Radiation Oncology (and Nuclear Medicine)
- Web of Science ID
- WOS:000270246000004
- Scopus ID
- 2-s2.0-70349661886
- Other Identifier
- 991019168238004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Radiology, Nuclear Medicine & Medical Imaging