Since the effects of respiration, nutrition, and exercise on blood flow in the hepatic vein are not well understood, the objective of this study was to determine the hemodynamic influence of these factors on hepatic venous circulation using Doppler ultrasonographic tracings. The venous blood flow of the middle hepatic vein was determined during arrested full inspiration, midinspiration, and expiration in 25 healthy subjects. The maximum velocity and the systolic-to-diastolic ratio of the blood flow were measured. The portal vein blood flow velocity was measured in 20 volunteers before and after food intake. The portal vein blood flow and the hepatic vein flow velocity were examined in eight volunteers after exercise. During inspiration, maximum blood flow velocity of the hepatic veins decreased compared to midinspiration (P < 0.001). With expiration the maximum velocity increased (P < 0.001). After food consumption, there was no change in the velocity of the hepatic veins, but the portal vein blood flow increased (P = 0.041). After physical exercises, the maximum velocity of the hepatic venous flow increased, on average, about 148% (P = 0.01), and the portal vein blood flow decreased about 44% (P = 0.027). To achieve standard measurements of hepatic venous blood flow, the state of respiration and physical exertion should be established. The nutritional status had only a minor influence on hepatic vein measurements.

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Objectives The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and conventional polychromatic 120-kVp images with modern reconstruction algorithms adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning image reconstruction (DLIR) were compared. Methods A temperature-regulating water circuit system was developed for the systematic evaluation of the correlation between temperature and Hounsfield units (HU). The measurements were performed on a Revolution CT with gemstone spectral imaging technology (GSI). Complementary measurements were performed without GSI (voltage 120 kVp, current 130–545 mA). The measured object was a tissue equivalent phantom in a temperature range of 18 to 50°C. The evaluation was carried out for VMI at 40 to 140 keV and polychromatic 120-kVp images. Results The regression analysis showed a significant inverse linear dependency between temperature and average HU regardless of ASIR-V and DLIR. VMI show a higher temperature sensitivity compared to polychromatic images. The temperature sensitivities were 1.25 HU/°C (120 kVp) and 1.35 HU/°C (VMI at 140 keV) for fat, 0.38 HU/°C (120 kVp) and 0.47 HU/°C (VMI at 40 keV) for muscle and 1.15 HU/°C (120 kVp) and 3.58 HU/°C (VMI at 50 keV) for bone. Conclusions Dual-energy with VMI enables a higher temperature sensitivity for fat, muscle and bone. The reconstruction with ASIR-V and DLIR has no significant influence on CT-based thermometry, which opens up the potential of drastic dose reductions. Key Points • Virtual monoenergetic images (VMI) enable a higher temperature sensitivity for fat (8%), muscle (24%) and bone (211%) compared to conventional polychromatic 120-kVp images. • With VMI, there are parameters, e.g. monoenergy and reconstruction kernel, to modulate the temperature sensitivity. In contrast, there are no parameters to influence the temperature sensitivity for conventional polychromatic 120-kVp images. • The application of adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning–based image reconstruction (DLIR) has no effect on CT-based thermometry, opening up the potential of drastic dose reductions in clinical applications.

The perfusion patterns of lymph nodes provide useful additional information in the differential diagnosis of cervical lymphadenopathy.