BACKGROUND: Protein-losing enteropathy (PLE) is a severe complication of Fontan circulation with increased risk of end-organ dysfunction. We evaluated tissue oxygenation via near-infrared spectroscopy (NIRS) at different exercise levels in Fontan patients. METHODS: Assessment of multisite NIRS during cycle ergometer exercise and daily activities in three groups: Fontan patients with PLE; without PLE; patients with dextro-transposition of the great arteries (d-TGA); comparing univentricular with biventricular circulation and Fontan with/without PLE. Renal threshold analysis (<65%;<55%;<45%) of regional oxygen saturation (rSO2) was performed. RESULTS: Fontan patients showed reduced rSO2 (p < 0.05) in their quadriceps femoris muscle compared with biventricular d-TGA patients at all time points. rSO2 in renal tissue was reduced at baseline (p = 0.002), exercise (p = 0.0062), and daily activities (p = 0.03) in Fontan patients with PLE. Renal threshold analysis identified critically low renal rSO2 (rSO2 < 65%) in Fontan patients with PLE during exercise (95% of monitoring time below threshold) and daily activities (83.7% time below threshold). CONCLUSION: Fontan circulation is associated with decreased rSO2 values in skeletal muscle and hypoxemia of renal tissue solely in patients with PLE. Reduced rSO2 already during activities of daily life, might contribute to comorbidities in patients with Fontan circulation, including PLE and renal failure.
BackgroundMonitoring minimally invasive thermo ablation procedures using magnetic resonance (MR) thermometry allows therapy of tumors even close to critical anatomical structures. Unfortunately, intraoperative monitoring remains challenging due to the necessary accuracy and real‐time capability. One reason for this is the statistical error introduced by MR measurement, which causes the prediction of ablation zones to become inaccurate.PurposeIn this work, we derive a probabilistic model for the prediction of ablation zones during thermal ablation procedures based on the thermal damage model CEM43. By integrating the statistical error caused by MR measurement into the conventional prediction, we hope to reduce the amount of falsely classified voxels.MethodsThe probabilistic CEM43 model is empirically evaluated using a polyacrilamide gel phantom and three in‐vivo pig livers.ResultsThe results show a higher accuracy in three out of four data sets, with a relative difference in Sørensen–Dice coefficient from to 3.97% compared to the conventional model. Furthermore, the ablation zones predicted by the probabilistic model show a false positive rate with a relative decrease of 11.89%–30.04% compared to the conventional model.ConclusionThe presented probabilistic thermal dose model might help to prevent false classification of voxels within ablation zones. This could potentially result in an increased success rate for MR‐guided thermal ablation procedures. Future work may address additional error sources and a follow‐up study in a more realistic clinical context.
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