Multimodal partial volume correction: Application to [C]PIB PET/MRI myelin imaging in multiple sclerosis.

The [C]PIB PET tracer, originally developed for amyloid imaging, has been recently repurposed to quantify demyelination and remyelination in multiple sclerosis (MS). Myelin PET imaging, however, is limited by its low resolution that deteriorates the quantification accuracy of white matter (WM) lesions. Here, we introduce a novel partial volume correction (PVC) method called Multiresolution-Multimodal Resolution-Recovery (MM-RR), which uses the wavelet transform and a synergistic statistical model to exploit MRI structural images to improve the resolution of [C]PIB PET myelin imaging.

Multimodal Partial-Volume Correction: Application to 18F-Fluoride PET/CT Bone Metastases Studies.

Unlabelled: (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.

Quantification of Dynamic [18F]FDG Pet Studies in Acute Lung Injury.

Purpose: This work aims to investigate lung glucose metabolism using 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) positron emission tomography (PET) imaging in acute lung injury (ALI) patients.

Procedures: Eleven ALI patients and five healthy controls underwent a dynamic [(18)F]FDG PET/X-ray computed tomography (CT) scan. The standardized uptake values (SUV) and three different methods for the quantification of glucose metabolism (i.

Brain shaving: adaptive detection for brain PET data.

The intricacy of brain biology is such that the variation of imaging end-points in health and disease exhibits an unpredictable range of spatial distributions from the extremely localized to the very diffuse. This represents a challenge for the two standard approaches to analysis, the mass univariate and the multivariate that exhibit either strong specificity but not as good sensitivity (the former) or poor specificity and comparatively better sensitivity (the latter). In this work, we develop an analytical methodology for positron emission tomography that operates an extraction ('shaving') of coherent patterns of signal variation while maintaining control of the type I error.