title: Combining multiple FDG-PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods.
abstract: OBJECTIVE
  Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation.
  
  
  METHODS
  The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs).
  
  
  RESULTS
  MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p = 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p = 0.0027). DSC was not significantly different between 128 × 128 and 256 × 256 grid sizes for either method (MJV, p = 0.0519; STAPLE, p = 0.5672) but was for SMASD values (MJV, p < 0.0001; STAPLE, p = 0.0164). The best individual method varied depending on object characteristics. However, both MJV and STAPLE provided essentially equivalent accuracy to using the best independent method in every situation, with mean differences in DSC of 0.01-0.03, and 0.05-0.12 mm for SMASD.
  
  
  CONCLUSIONS
  Combining segmentations offers a robust approach to object segmentation in PET. Both MJV and STAPLE improved accuracy and were robust against the widely varying performance of individual segmentation methods. Differences between MJV and STAPLE are such that either offers good performance when combining volumes. Neither method requires a training dataset but MJV is simpler to interpret, easy to implement and fast.
authors.affiliation: Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705, USA. ross.mcgurk@duke.edu
authors.forename: Ross J
authors.initials: RJ
authors.lastname: McGurk
authors.forename: James
authors.initials: J
authors.lastname: Bowsher
authors.forename: John A
authors.initials: JA
authors.lastname: Lee
authors.forename: Shiva K
authors.initials: SK
authors.lastname: Das
mesh_terms: D000465:Algorithms; D019788:Fluorodeoxyglucose F18; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D010363:Pattern Recognition, Automated / Q000379:methods; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D061089:Radiotherapy, Image-Guided / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
references.citation: IEEE Trans Med Imaging. 2004 Jul;23(7):903-21
references.pmid: 15250643
references.citation: J Nucl Med. 2007 May;48(5):744-51
references.pmid: 17475962
references.citation: J Nucl Med. 2010 Feb;51(2):268-76
references.pmid: 20080896
references.citation: Med Phys. 2008 Aug;35(8):3711-21
references.pmid: 18777930
references.citation: J Nucl Med. 2009 May;50 Suppl 1:122S-50S
references.pmid: 19403881
references.citation: IEEE Trans Med Imaging. 2009 Aug;28(8):1266-77
references.pmid: 19228554
references.citation: Eur J Nucl Med Mol Imaging. 2007 Sep;34(9):1427-38
references.pmid: 17431616
references.citation: Cancer. 1997 Dec 15;80(12 Suppl):2505-9
references.pmid: 9406703
references.citation: Radiology. 2007 Jul;244(1):263-72
references.pmid: 17495174
references.citation: Med Phys. 2006 Nov;33(11):4280-8
references.pmid: 17153406
references.citation: Acad Radiol. 2004 Feb;11(2):178-89
references.pmid: 14974593
references.citation: Schizophr Bull. 1991;17(3):483-9
references.pmid: 1947873
references.citation: J Nucl Med. 2007 Jan;48(1):108-14
references.pmid: 17204706
references.citation: EJNMMI Res. 2011 Oct 05;1(1):23
references.pmid: 22214263
references.citation: IEEE Trans Med Imaging. 2009 Jun;28(6):881-93
references.pmid: 19150782
references.citation: Med Phys. 2009 Oct;36(10):4349-58
references.pmid: 19928065
references.citation: Eur J Nucl Med Mol Imaging. 2010 Nov;37(11):2165-87
references.pmid: 20336455
references.citation: Int J Radiat Oncol Biol Phys. 2007 Nov 15;69(4):1282-9
references.pmid: 17967318
references.citation: Phys Med Biol. 2010 Feb 21;55(4):1099-113
references.pmid: 20107246
references.citation: J Nucl Med. 2005 Aug;46(8):1342-8
references.pmid: 16085592
references.citation: Eur J Radiol. 2012 Nov;81(11):3535-41
references.pmid: 22277291
references.citation: Med Phys. 2010 Mar;37(3):1309-24
references.pmid: 20384268
references.citation: IEEE Trans Med Imaging. 1994;13(4):716-24
references.pmid: 18218550
references.citation: J Natl Cancer Inst. 2000 Feb 2;92(3):205-16
references.pmid: 10655437
references.citation: Med Phys. 2013 Jan;40(1):012401
references.pmid: 23298110
references.citation: J Nucl Med. 2009 Oct;50(10):1655-65
references.pmid: 19759099
references.citation: Comput Med Imaging Graph. 1996 Jan-Feb;20(1):31-41
references.pmid: 8891420
references.citation: Clin Positron Imaging. 1999 May;2(3):159-171
references.pmid: 14516540
references.citation: Eur J Nucl Med Mol Imaging. 2011 Apr;38(4):663-72
references.pmid: 21225425
references.citation: Phys Med Biol. 2007 Jun 21;52(12):3467-91
references.pmid: 17664555
references.citation: Int J Radiat Oncol Biol Phys. 2003 Nov 1;57(3):853-63
references.pmid: 14529793
references.citation: J Nucl Med. 2006 Feb;47(2):200-7
references.pmid: 16455624
references.citation: J Nucl Med. 1995 Oct;36(10):1836-9
references.pmid: 7562051