Myocardial blood flow quantification by Rb-82 cardiac PET/CT: A detailed reproducibility study between two semi-automatic analysis programs.

BACKGROUND: Several analysis software packages for myocardial blood flow (MBF) quantification from cardiac PET studies exist, but they have not been compared using concordance analysis, which can characterize precision and bias separately. Reproducible measurements are needed for quantification to fully develop its clinical potential. METHODS: Fifty-one patients underwent dynamic Rb-82 PET at rest and during adenosine stress. Data were processed with PMOD and FlowQuant (Lortie model). MBF and myocardial flow reserve (MFR) polar maps were quantified and analyzed using a 17-segment model. Comparisons used Pearson's correlation ρ (measuring precision), Bland and Altman limit-of-agreement and Lin's concordance correlation ρc = ρ·C b (C b measuring systematic bias). RESULTS: Lin's concordance and Pearson's correlation values were very similar, suggesting no systematic bias between software packages with an excellent precision ρ for MBF (ρ = 0.97, ρc = 0.96, C b = 0.99) and good precision for MFR (ρ = 0.83, ρc = 0.76, C b = 0.92). On a per-segment basis, no mean bias was observed on Bland-Altman plots, although PMOD provided slightly higher values than FlowQuant at higher MBF and MFR values (P < .0001). CONCLUSIONS: Concordance between software packages was excellent for MBF and MFR, despite higher values by PMOD at higher MBF values. Both software packages can be used interchangeably for quantification in daily practice of Rb-82 cardiac PET.

Alveolar echinococcosis of the liver: Diffusion-weighted MRI findings and potential role in lesion characterisation

PURPOSE: To report the diffusion-weighted MRI findings in alveolar echinococcosis (AE) of the liver and evaluate the potential role of apparent diffusion coefficients (ADCs) in the characterisation of lesions. MATERIALS AND METHODS: We retrospectively included 22 patients with 63 AE liver lesions (≥1cm), examined with 3-T liver MRI, including a free-breathing diffusion-weighted single-shot echo-planar imaging sequence (b-values=50, 300 and 600s/mm(2)). Two radiologists jointly assessed the following lesion features: size, location, presence of cystic and/or solid components (according to Kodama's classification system), relative contrast enhancement, and calcifications (on CT). The ADCtotal, ADCmin and ADCmax were measured in each lesion and the surrounding liver parenchyma. RESULTS: Three type 1, 19 type 2, 17 type 3, three type 4 and 21 type 5 lesions were identified. The mean (±SD) ADCtotal, ADCmin and ADCmax for all lesions were 1.73±0.50, 0.76±0.38 and 2.63±0.76×10(-3)mm(2)/s, respectively. The mean ADCtotal for type 1, type 2, type 3, type 4 and type 5 lesions were 1.97±1.01, 1.76±0.53, 1.73±0.41, 1.15±0.42 and 1.76±0.44×10(-3)mm(2)/s, respectively. No significant differences were found between the five lesion types, except for type 4 (p=0.0363). There was a significant correlation between the presence of a solid component and low ADCmin (r=0.39, p=0.0016), whereas an inverse correlation was found between the relative contrast enhancement and ADCtotal (r=-0.34, p=0.0072). CONCLUSION: The ADCs of AE lesions are relatively low compared to other cystic liver lesions, which may help in the differential diagnosis. Although ADCs are of little use to distinguish between the five lesion types, their low value reflects the underlying solid component.

Intravoxel Incoherent Motion Metrics as Potential Biomarkers for Survival in Glioblastoma.

OBJECTIVE: Intravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma. METHODS: Fifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm2. Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses. RESULTS: We found that fCER and D*CER correlated with rCBFCER. The best cutoffs for 6-month survival were fCER>9.86% and D*CER>21.712 x10-3mm2/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162-25.88; AUC: 0.723; P = 0.031); fCER combined with treatment predicted survival with 100% accuracy. CONCLUSIONS: The IVIM-metrics fCER and D*CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma.