OBJECTIVES: The determination of lesion boundaries on FDG PET is difficult due to the point-spread blurring and unknown uptake of activity within a lesion. Standard threshold-based methods for volumetric quantification on PET usually neglect any size dependence and are biased by dependence on the signal-to-background ratio (SBR). A novel, model-based method is hypothesized to provide threshold levels independent f the SBR and to allow accurate measurement of volumes down to the resolution of the PET scanner. METHODS: A background-subtracted relative-threshold level (RTL) method was derived, based on a convolution of the point-spread function and a sphere with diameter D. Validation of the RTL method was performed using PET imaging of a Jaszczak phantom with seven hollow spheres (D=10-60 mm). Activity concentrations for the background and spheres (signal) were varied to obtain SBRs of 1.5-10. An iterative procedure was introduced for volumetric quantification, as the optimal RTL depends on a priori knowledge of the volume. The feasibility of the RTL method was tested in two patients with liver metastases and compared to a standard method using a fixed percentage of the signal. RESULTS: Phantom data validated that the theoretically optimal RTL depends on the sphere size, but not on the SBR. Typically, RTL=40% (D=15-60 mm), and RTL>50% for small spheres (D<12 mm). The RTL method is better applicable to patient data than the standard method. CONCLUSIONS: Based on an iterative procedure, the RTL method has been shown to provide optimal threshold levels independent of the SBR and to be applicable in phantom and in patient studies. It is a promising tool for lesion delineation and volumetric quantification of PET lesions.
OBJECTIVES: The determination of lesion boundaries on FDG PET is difficult due to the point-spread blurring and unknown uptake of activity within a lesion. Standard threshold-based methods for volumetric quantification on PET usually neglect any size dependence and are biased by dependence on the signal-to-background ratio (SBR). A novel, model-based method is hypothesized to provide threshold levels independent f the SBR and to allow accurate measurement of volumes down to the resolution of the PET scanner. METHODS: A background-subtracted relative-threshold level (RTL) method was derived, based on a convolution of the point-spread function and a sphere with diameter D. Validation of the RTL method was performed using PET imaging of a Jaszczak phantom with seven hollow spheres (D=10-60 mm). Activity concentrations for the background and spheres (signal) were varied to obtain SBRs of 1.5-10. An iterative procedure was introduced for volumetric quantification, as the optimal RTL depends on a priori knowledge of the volume. The feasibility of the RTL method was tested in two patients with liver metastases and compared to a standard method using a fixed percentage of the signal. RESULTS: Phantom data validated that the theoretically optimal RTL depends on the sphere size, but not on the SBR. Typically, RTL=40% (D=15-60 mm), and RTL>50% for small spheres (D<12 mm). The RTL method is better applicable to patient data than the standard method. CONCLUSIONS: Based on an iterative procedure, the RTL method has been shown to provide optimal threshold levels independent of the SBR and to be applicable in phantom and in patient studies. It is a promising tool for lesion delineation and volumetric quantification of PET lesions.
Authors: Tony Shepherd; Mika Teras; Reinhard R Beichel; Ronald Boellaard; Michel Bruynooghe; Volker Dicken; Mark J Gooding; Peter J Julyan; John A Lee; Sébastien Lefèvre; Michael Mix; Valery Naranjo; Xiaodong Wu; Habib Zaidi; Ziming Zeng; Heikki Minn Journal: IEEE Trans Med Imaging Date: 2012-06-04 Impact factor: 10.048
Authors: Ronald Boellaard; Wim J G Oyen; Corneline J Hoekstra; Otto S Hoekstra; Eric P Visser; Antoon T Willemsen; Bertjan Arends; Fred J Verzijlbergen; Josee Zijlstra; Anne M Paans; Emile F I Comans; Jan Pruim Journal: Eur J Nucl Med Mol Imaging Date: 2008-08-15 Impact factor: 9.236
Authors: Mathieu Hatt; John A Lee; Charles R Schmidtlein; Issam El Naqa; Curtis Caldwell; Elisabetta De Bernardi; Wei Lu; Shiva Das; Xavier Geets; Vincent Gregoire; Robert Jeraj; Michael P MacManus; Osama R Mawlawi; Ursula Nestle; Andrei B Pugachev; Heiko Schöder; Tony Shepherd; Emiliano Spezi; Dimitris Visvikis; Habib Zaidi; Assen S Kirov Journal: Med Phys Date: 2017-05-18 Impact factor: 4.071