title: Multimodal Partial-Volume Correction: Application to 18F-Fluoride PET/CT Bone Metastases Studies.
abstract: (18)F-fluoride PET/CT offers the opportunity for accurate skeletal metastasis staging, compared with conventional imaging methods. (18)F-fluoride is a bone-specific tracer whose uptake depends on osteoblastic activity. Because of the resulting increase in bone mineralization and sclerosis, the osteoblastic process can also be detected morphologically in CT images. Although CT is characterized by high resolution, the potential of PET is limited by its lower spatial resolution and the resulting partial-volume effect. In this context, the synergy between PET and CT presents an opportunity to resolve this limitation using a novel multimodal approach called synergistic functional-structural resolution recovery (SFS-RR). Its performance is benchmarked against current resolution recovery technology using the point-spread function (PSF) of the scanner in the reconstruction procedure.
  
  
  METHODS
  The SFS-RR technique takes advantage of the multiresolution property of the wavelet transform applied to both functional and structural images to create a high-resolution PET image that exploits the structural information of CT. Although the method was originally conceived for PET/MR imaging of brain data, an ad hoc version for whole-body PET/CT is proposed here. Three phantom experiments and 2 datasets of metastatic bone (18)F-fluoride PET/CT images from primary prostate and breast cancer were used to test the algorithm performances. The SFS-RR images were compared with the manufacturer's PSF-based reconstruction using the standardized uptake value (SUV) and the metabolic volume as metrics for quantification.
  
  
  RESULTS
  When compared with standard PET images, the phantom experiments showed a bias reduction of 14% in activity and 1.3 cm(3) in volume estimates for PSF images and up to 20% and 2.5 cm(3) for the SFS-RR images. The SFS-RR images were characterized by a higher recovery coefficient (up to 60%) whereas noise levels remained comparable to those of standard PET. The clinical data showed an increase in the SUV estimates for SFS-RR images up to 34% for peak SUV and 50% for maximum SUV and mean SUV. Images were also characterized by sharper lesion contours and better lesion detectability.
  
  
  CONCLUSIONS
  The proposed methodology generates PET images with improved quantitative and qualitative properties. Compared with standard methods, SFS-RR provides superior lesion segmentation and quantification, which may result in more accurate tumor characterization.
authors.affiliation: Centre for Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, United Kingdom Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom.
authors.forename: Elisabetta
authors.initials: E
authors.lastname: Grecchi
authors.affiliation: PET Imaging Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas's Hospital, London, United Kingdom; and.
authors.forename: Jim
authors.initials: J
authors.lastname: O'Doherty
authors.affiliation: Centre for Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, United Kingdom.
authors.forename: Mattia
authors.initials: M
authors.lastname: Veronese
authors.affiliation: Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom Division of Biomedical Imaging, University of Leeds, Leeds, United Kingdom.
authors.forename: Charalampos
authors.initials: C
authors.lastname: Tsoumpas
authors.affiliation: Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom PET Imaging Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas's Hospital, London, United Kingdom; and.
authors.forename: Gary J
authors.initials: GJ
authors.lastname: Cook
authors.affiliation: Centre for Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, United Kingdom federico.turkheimer@kcl.ac.uk.
authors.forename: Federico E
authors.initials: FE
authors.lastname: Turkheimer
mesh_terms: D016477:Artifacts; D001859:Bone Neoplasms / Q000175:diagnosis* / Q000556:secondary*; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D064847:Multimodal Imaging / Q000295:instrumentation / Q000379:methods; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: 18F-fluoride; PET/CT; multimodal imaging; partial-volume correction; wavelet