Modelling of FDG metabolism in liver voxels.

Kinetic analysis is a tool used to glean additional information from positron emission tomography (PET) data by exploiting the dynamics of tissue metabolism. The standard irreversible and reversible two compartment models used in kinetic analysis were initially developed to analyse brain PET data. The application of kinetic analysis to PET of the liver presents the opportunity to move beyond the generic standard models and develop physiologically informed pharmacokinetic models that incorporate structural and functional features in particular to the liver. In this paper, we develop a new compartment model, called the tubes model, which is informed by the liver׳s sinusoidal architecture, high fractional blood volume, high perfusion rate, and large hepatocyte surface area facing the space of Disse. The tubes model distributes tracer between the blood and intracellular compartments in more physiologically faithful proportions than the standard model, producing parametric images with improved contrast between healthy and neoplastic tissue.

Development of an automated measure of iliac artery tortuosity that successfully predicts early graft-related complications associated with endovascular aneurysm repair.

OBJECTIVES: Iliac artery tortuosity has been linked to the likelihood of complications following endovascular aneurysm repair (EVAR). Measures of tortuosity can be established from CT images; however, the reproducibility of existing scoring techniques has not been clearly established. It remains unclear whether it is tortuosity at focal locations or for the vessel as a whole that is most relevant to adverse events. The two aims of this study were to develop an automated measure of iliac artery tortuosity to assist with surgical planning by providing an objective assessment of procedural difficulty, and to correlate this measure with early postoperative outcomes. DESIGN AND METHODS: Unlike existing approaches, the present measure of tortuosity considers spatial scale, which incorporates the effects of local anatomy. A computerized imaging algorithm was used to segment vasculature and establish a medial line and vascular boundary from contrast enhanced CT scans of 150 patients undergoing EVAR. Two tortuosity measures were examined: curvature and vessel to straight-line length (L1/L2-ratio). For a given spatial scale, the maximum tortuosity was computed on both iliac arteries and the artery with the lower maximum was selected for analysis. Correlation of tortuosity with early (<30 day) and longer-term graft-related complications was assessed. RESULTS: Maximal tortuosity at a 10 mm scale was a significant predictor of early (<30 day) complications (p = .016 for curvature and p = .006 for L1/L2-ratio), but not of long-term complications. Aneurysmal diameter was independent of tortuosity (Pearson's r value = -.006). CONCLUSION: The results demonstrate that, at a local scale, tortuosity measures are correlated with early outcomes. The spatial scale at which tortuosity is measured is important. The optimal scale of 10 mm implies that adverse events could be linked to a focal anatomical location.

Correlation of MRI-derived apparent diffusion coefficients in newly diagnosed gliomas with [18F]-fluoro-L-dopa PET: what are we really measuring with minimum ADC?

BACKGROUND AND PURPOSE: There is significant interest in whether diffusion-weighted MR imaging indices, such as the minimum apparent diffusion coefficient, may be useful clinically for preoperative tumor grading and treatment planning. To help establish the pathologic correlate of minimum ADC, we undertook a study investigating the relationship between minimum ADC and maximum FDOPA PET uptake in patients with newly diagnosed glioblastoma multiforme. MATERIALS AND METHODS: MR imaging and FDOPA PET data were acquired preoperatively from 15 patients who were subsequently diagnosed with high-grade brain tumor (WHO grade III or IV) by histopathologic analysis. ADC and SUVR normalized FDOPA PET maps were registered to the corresponding CE MR imaging. Regions of minimum ADC within the FDOPA-defined tumor volume were anatomically correlated with areas of maximum FDOPA SUVR uptake. RESULTS: Minimal anatomic overlap was found between regions exhibiting minimum ADC (a putative marker of tumor cellularity) and maximum FDOPA SUVR uptake (a marker of tumor infiltration and proliferation). FDOPA SUVR measures for tumoral regions exhibiting minimum ADC (1.36±0.22) were significantly reduced compared with those with maximum FDOPA uptake (2.45±0.88, P=.0001). CONCLUSIONS: There was a poor correlation between minimum ADC and the most viable/aggressive component of high-grade gliomas. This study suggests that other factors, such as tissue compression and ischemia, may be contributing to restricted diffusion in GBM. Caution should be exercised in the clinical use of minimum ADC as a marker of tumor grade and the use of this index for guiding tumor biopsies preoperatively.

Joint factor and kinetic analysis of dynamic FDOPA PET scans of brain cancer patients.

Kinetic analysis is an essential tool of Positron Emission Tomography image analysis. However it requires a pure tissue time activity curve (TAC) in order to calculate the system parameters. Pure tissue TACs are particularly difficult to obtain in the brain as the low resolution of PET means almost all voxels are a mixture of tissues. Factor analysis explicitly accounts for mixing but is an underdetermined problem that can give arbitrary results. A joint factor and kinetic analysis is proposed whereby factor analysis explicitly accounts for mixing of tissues. Hence, more meaningful parameters are obtained by the kinetic models, which also ensure a less ambiguous solution to the factor analysis. The method was tested using a cylindrical phantom and the 18F-DOPA data of a brain cancer patient.