Improved quantification for local regions of interest in preclinical PET imaging

In Positron Emission Tomography, there are several causes of quantitative inaccuracy, such as partial volume or spillover effects. The impact of these effects is greater when using radionuclides that have a large positron range, e.g. (68)Ga and (124)I, which have been increasingly used in the clinic. We have implemented and evaluated a local projection algorithm (LPA), originally evaluated for SPECT, to compensate for both partial-volume and spillover effects in PET. This method is based on the use of a high-resolution CT or MR image, co-registered with a PET image, which permits a high-resolution segmentation of a few tissues within a volume of interest (VOI) centered on a region within which tissue-activity values need to be estimated. The additional boundary information is used to obtain improved activity estimates for each tissue within the VOI, by solving a simple inversion problem. We implemented this algorithm for the preclinical Argus PET/CT scanner and assessed its performance using the radionuclides (18)F, (68)Ga and (124)I. We also evaluated and compared the results obtained when it was applied during the iterative reconstruction, as well as after the reconstruction as a postprocessing procedure. In addition, we studied how LPA can help to reduce the 'spillover contamination', which causes inaccurate quantification of lesions in the immediate neighborhood of large, 'hot' sources. Quantification was significantly improved by using LPA, which provided more accurate ratios of lesion-to-background activity concentration for hot and cold regions. For (18)F, the contrast was improved from 3.0 to 4.0 in hot lesions (when the true ratio was 4.0) and from 0.16 to 0.06 in cold lesions (true ratio  =  0.0), when using the LPA postprocessing. Furthermore, activity values estimated within the VOI using LPA during reconstruction were slightly more accurate than those obtained by post-processing, while also visually improving the image contrast and uniformity within the VOI.

[1]  B F Hutton,et al.  Application of distance-dependent resolution compensation and post-reconstruction filtering for myocardial SPECT. , 1998, Physics in medicine and biology.

[2]  Richard Laforest,et al.  Quantitative small animal PET imaging with nonconventional nuclides. , 2009, Nuclear medicine and biology.

[3]  K Thielemans,et al.  The effect of regularization in motion compensated PET image reconstruction: a realistic numerical 4D simulation study , 2013, Physics in medicine and biology.

[4]  Mark Lubberink,et al.  Quantitative imaging of 124I and 86Y with PET , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[5]  Stefan P. Müller,et al.  Improved Regional Activity Quantitation in Nuclear Medicine Using a New Approach to Correct for Tissue Partial Volume and Spillover Effects , 2012, IEEE Transactions on Medical Imaging.

[6]  Manuel Desco,et al.  Tissue-Dependent and Spatially-Variant Positron Range Correction in 3D PET , 2015, IEEE Transactions on Medical Imaging.

[7]  A. Schmid,et al.  PET quantitation and imaging of the non-pure positron-emitting iodine isotope 124I. , 2002, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[8]  L. Strauss,et al.  Gallium-68-DOTA-albumin as a PET blood-pool marker: experimental evaluation in vivo. , 2005, Nuclear medicine and biology.

[9]  E. Hoffman,et al.  Calculation of positron range and its effect on the fundamental limit of positron emission tomography system spatial resolution. , 1999, Physics in medicine and biology.

[10]  Michael J. Welch,et al.  MicroPET imaging with non-conventional isotopes , 2001 .

[11]  I. Buvat,et al.  A review of partial volume correction techniques for emission tomography and their applications in neurology, cardiology and oncology , 2012, Physics in medicine and biology.

[12]  Paul Kinahan,et al.  Attenuation correction for a combined 3D PET/CT scanner. , 1998, Medical physics.

[13]  M. Modat,et al.  The importance of appropriate partial volume correction for PET quantification in Alzheimer’s disease , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[14]  W. Breeman,et al.  The 68Ge/68Ga generator has high potential, but when can we use 68Ga-labelled tracers in clinical routine? , 2007, European Journal of Nuclear Medicine and Molecular Imaging.

[15]  Study of CT-based positron range correction in high resolution 3D PET imaging , 2011 .

[16]  R Laforest,et al.  Image quality with non-standard nuclides in PET. , 2008, The quarterly journal of nuclear medicine and molecular imaging : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR), [and] Section of the Society of....

[17]  R. Carson.  A Maximum Likelihood Method for Region-of-Interest Evaluation in Emission Tomography , 1986, Journal of computer assisted tomography.

[18]  K S Pentlow,et al.  Quantitative imaging of I-124 using positron emission tomography with applications to radioimmunodiagnosis and radioimmunotherapy. , 1991, Medical physics.

[19]  Sudeepti Southekal,et al.  Evaluation of a method for projection-based tissue-activity estimation within small volumes of interest , 2012, Physics in medicine and biology.

[20]  J J Vaquero,et al.  Positron range estimations with PeneloPET , 2013, Physics in medicine and biology.

[21]  A. Blanco.  Positron Range Effects on the Spatial Resolution of RPC-PET , 2006, 2006 IEEE Nuclear Science Symposium Conference Record.

[22]  A. Evans,et al.  Correction for partial volume effects in PET: principle and validation. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[23]  M. Papisov,et al.  Iodine-124 as a label for pharmacological PET imaging. , 2009, Molecular pharmaceutics.

[24]  J J Vaquero,et al.  FIRST: Fast Iterative Reconstruction Software for (PET) tomography. , 2006, Physics in medicine and biology.

[25]  Jurgen Seidel,et al.  Performance evaluation of the GE healthcare eXplore VISTA dual-ring small-animal PET scanner. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[26]  J. M. Udias,et al.  Simulation of triple coincidences in PET , 2013, 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).

[27]  H. Malcolm Hudson,et al.  Accelerated image reconstruction using ordered subsets of projection data , 1994, IEEE Trans. Medical Imaging.

[28]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.

[29]  Yong Du,et al.  Partial volume effect compensation for quantitative brain SPECT imaging , 2005, IEEE Transactions on Medical Imaging.

[30]  S. Libutti,et al.  Partial-Volume Correction in PET: Validation of an Iterative Postreconstruction Method with Phantom and Patient Data , 2007, Journal of Nuclear Medicine.

[31]  S. Moore,et al.  Activity estimation in small volumes with non-uniform radiotracer uptake using a local projection-based fitting approach , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.

[32]  Jerry L Prince,et al.  Measurement of Radiotracer Concentration in Brain Gray Matter Using Positron Emission Tomography: MRI-Based Correction for Partial Volume Effects , 1992, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[33]  Invalidity of SUV Measurements of Lesions in Close Proximity to Hot Sources due to “Shine-Through” Effect on FDG PET-CT Interpretation , 2012, Radiology research and practice.

[34]  E. Hoffman,et al.  Quantitation in Positron Emission Computed Tomography: 1. Effect of Object Size , 1979, Journal of computer assisted tomography.

[35]  Patrick Dupont,et al.  Anatomical-based FDG-PET reconstruction for the detection of hypo-metabolic regions in epilepsy , 2004, IEEE Transactions on Medical Imaging.

[36]  I. Buvat,et al.  Partial-Volume Effect in PET Tumor Imaging* , 2007, Journal of Nuclear Medicine.

[37]  M. Desco,et al.  PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation , 2006, 2006 IEEE Nuclear Science Symposium Conference Record.