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A multifractal approach to space‐filling recovery for PET quantification
Author(s) -
Willaime Julien M. Y.,
Aboagye Eric O.,
Tsoumpas Charalampos,
Turkheimer Federico E.
Publication year - 2014
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4898122
Subject(s) - partial volume , multifractal system , robustness (evolution) , fractal dimension , ground truth , medical imaging , segmentation , mathematics , artificial intelligence , image registration , nuclear medicine , image segmentation , repeatability , fractal , computer science , pattern recognition (psychology) , statistics , medicine , image (mathematics) , mathematical analysis , biochemistry , chemistry , gene
Purpose: A new image‐based methodology is developed for estimating the apparent space‐filling properties of an object of interest in PET imaging without need for a robust segmentation step and used to recover accurate estimates of total lesion activity (TLA). Methods: A multifractal approach and the fractal dimension are proposed to recover the apparent space‐filling index of a lesion (tumor volume, TV) embedded in nonzero background. A practical implementation is proposed, and the index is subsequently used with mean standardized uptake value (SUV mean ) to correct TLA estimates obtained from approximate lesion contours. The methodology is illustrated on fractal and synthetic objects contaminated by partial volume effects (PVEs), validated on realistic 18 F‐fluorodeoxyglucose PET simulations and tested for its robustness using a clinical 18 F‐fluorothymidine PET test–retest dataset. Results: TLA estimates were stable for a range of resolutions typical in PET oncology (4–6 mm). By contrast, the space‐filling index and intensity estimates were resolution dependent. TLA was generally recovered within 15% of ground truth on postfiltered PET images affected by PVEs. Volumes were recovered within 15% variability in the repeatability study. Results indicated that TLA is a more robust index than other traditional metrics such as SUV mean or TV measurements across imaging protocols. Conclusions: The fractal procedure reported here is proposed as a simple and effective computational alternative to existing methodologies which require the incorporation of image preprocessing steps (i.e., partial volume correction and automatic segmentation) prior to quantification.