Sensitive and non-invasive assessment of hepatocellular iron using a novel room-temperature susceptometer.

BACKGROUND & AIMS: Liver iron accumulates in various chronic liver diseases where it is an independent factor for survival and carcinogenesis. We tested a novel room-temperature susceptometer (RTS) to non-invasively assess liver iron concentration (LIC). METHODS: Two hundred and sixty-four patients with or without signs of iron overload or liver disease were prospectively enrolled. Thirty-five patients underwent liver biopsy with semiquantitative iron determination (Prussian Blue staining), atomic absorption spectroscopy (AAS, n=33), or magnetic resonance imaging (MRI, n=15). RESULTS: In vitro studies demonstrated a highly linear (r2=0.998) association between RTS-signal and iron concentration, with a detection limit of 0.3mM. Using an optimized algorithm, accounting for the skin-to-liver capsule distance, valid measurements could be obtained in 84% of cases. LIC-RTS showed a significant correlation with LIC-AAS (r=0.74, p<0.001), LIC-MRI (r=0.64, p<0.001) and hepatocellular iron (r=0.58, p<0.01), but not with macrophage iron (r=0.32, p=0.30). Normal LIC-RTS was 1.4mg/g dry weight. Besides hereditary and transfusional iron overload, LIC-RTS was also significantly elevated in patients with alcoholic liver disease. The areas under the receiver operating characteristic curve (AUROC) for grade 1, 2 and 3 hepatocellular iron overload were 0.72, 0.89 and 0.97, respectively, with cut-off values of 2.0, 4.0 and 5.0mg/g dry weight. Notably, the positive and negative predictive values, sensitivity, specificity and accuracy of severe hepatic iron overload (HIO) (grade ≥2) detection, were equal to AAS and superior to all serum iron markers. Depletion of hepatic iron could be efficiently monitored upon phlebotomy. CONCLUSIONS: RTS allows for the rapid and non-invasive measurement of LIC. In comparison to MRI, it could be a cost-effective bedside method for LIC screening. Lay summary: Novel room-temperature susceptometer (RTS) allows for the rapid, sensitive, and non-invasive measurement of liver iron concentration. In comparison to MRI, it could be a cost-effective bedside method for liver iron concentration screening.

Ultrahigh resolution whole body photon counting computed tomography as a novel versatile tool for translational research from mouse to man.

X-ray computed tomography (CT) is a cardinal tool in clinical practice. It provides cross-sectional images within seconds. The recent introduction of clinical photon-counting CT allowed for an increase in spatial resolution by more than a factor of two resulting in a pixel size in the center of rotation of about 150 µm. This level of spatial resolution is in the order of dedicated preclinical micro-CT systems. However so far, the need for different dedicated clinical and preclinical systems often hinders the rapid translation of early research results to applications in men. This drawback might be overcome by ultra-high resolution (UHR) clinical photon-counting CT unifying preclinical and clinical research capabilities in a single machine. Herein, the prototype of a clinical UHR PCD CT (SOMATOM CounT, Siemens Healthineers, Forchheim, Germany) was used. The system comprises a conventional energy-integrating detector (EID) and a novel photon-counting detector (PCD). While the EID provides a pixel size of 0.6 mm in the centre of rotation, the PCD provides a pixel size of 0.25 mm. Additionally, it provides a quantification of photon energies by sorting them into up to four distinct energy bins. This acquisition of multi-energy data allows for a multitude of applications, e.g. pseudo-monochromatic imaging. In particular, we examine the relation between spatial resolution, image noise and administered radiation dose for a multitude of use-cases. These cases include ultra-high resolution and multi-energy acquisitions of mice administered with a prototype bismuth-based contrast agent (nanoPET Pharma, Berlin, Germany) as well as larger animals and actual patients. The clinical EID provides a spatial resolution of about 9 lp/cm (modulation transfer function at 10%, MTF10%) while UHR allows for the acquisition of images with up to 16 lp/cm allowing for the visualization of all relevant anatomical structures in preclinical and clinical specimen. The spectral capabilities of the system enable a variety of applications previously not available in preclinical research such as pseudo-monochromatic images. Clinical ultra-high resolution photon-counting CT has the potential to unify preclinical and clinical research on a single system enabling versatile imaging of specimens and individuals ranging from mice to man.

Quantitative Analysis of DCE and DSC-MRI: From Kinetic Modeling to Deep Learning.

BACKGROUND: Perfusion MRI is a well-established imaging modality with a multitude of applications in oncological and cardiovascular imaging. Clinically used processing methods, while stable and robust, have remained largely unchanged in recent years. Despite promising results from novel methods, their relatively minimal improvement compared to established methods did not generally warrant significant changes to clinical perfusion processing. RESULTS AND CONCLUSION: Machine learning in general and deep learning in particular, which are currently revolutionizing computer-aided diagnosis, may carry the potential to change this situation and truly capture the potential of perfusion imaging. Recent advances in the training of recurrent neural networks make it possible to predict and classify time series data with high accuracy. Combining physics-based tissue models and deep learning, using either physics-informed neural networks or universal differential equations, simplifies the training process and increases the interpretability of the resulting models. Due to their versatility, these methods will potentially be useful in bridging the gap between microvascular architecture and perfusion parameters, akin to MR fingerprinting in structural MR imaging. Still, further research is urgently needed before these methods may be used in clinical practice. KEY POINTS: · Machine learning offers promising methods for processing of perfusion data.. · Recurrent neural networks can classify time series with high accuracy.. · Data augmentation is essentially especially when using small datasets.. CITATION FORMAT: · Rotkopf LT, Zhang KS, Tavakoli AA et al. Quantitative Analysis of DCE and DSC-MRI: From Kinetic Modeling to Deep Learning. Fortschr Röntgenstr 2022; 194: 975 - 982.

Diffusion-mediated dephasing in the dipole field around a single spherical magnetic object.

In this work, the time evolution of the free induction decay caused by the local dipole field of a spherical magnetic perturber is analyzed. The complicated treatment of the diffusion process is replaced by the strong-collision-approximation that allows a determination of the free induction decay in dependence of the underlying microscopic tissue parameters such as diffusion coefficient, sphere radius and susceptibility difference. The interplay between susceptibility- and diffusion-mediated effects yields several dephasing regimes of which, so far, only the classical regimes of motional narrowing and static dephasing for dominant and negligible diffusion, respectively, were extensively examined. Due to the asymmetric form of the dipole field for spherical objects, the free induction decay exhibits a complex component in contradiction to the cylindrical case, where the symmetric local dipole field only causes a purely real induction decay. Knowledge of the shape of the corresponding frequency distribution is necessary for the evaluation of more sophisticated pulse sequences and a detailed understanding of the off-resonance distribution allows improved quantification of transverse relaxation.

Comparison of susceptibility weighted imaging and TOF-angiography for the detection of Thrombi in acute stroke.

BACKGROUND AND PURPOSE: Time-of-flight (TOF) angiography detects embolic occlusion of arteries in patients with acute ischemic stroke due to the absence of blood flow in the occluded vessel. In contrast, susceptibility weighted imaging (SWI) directly enables intravascular clot visualization due to hypointense susceptibility vessel signs (SVS) in the occluded vessel. The aim of this study was to compare the diagnostic accuracy of both methods to determine vessel occlusion in patients with acute stroke. METHODS: 94 patients were included who presented with clinical symptoms for acute stroke and displayed a delay on the time-to-peak perfusion map in the territory of the anterior (ACA), middle (M1, M1/M2, M2/M3) or posterior (PCA) cerebral artery. The frequency of SVS on SWI and vessel occlusion or stenosis on TOF-angiography was compared using the McNemar-Test. RESULTS: 87 of 94 patients displayed a clearly definable SVS on SWI. In 72 patients the SVS was associated with occlusion or stenosis on TOF-angiography. Fifteen patients exclusively displayed SVS on SWI (14 M2/M3, 1 M1), whereas no patient revealed exclusively occlusion or stenosis on TOF-angiography. Sensitivity for detection of embolic occlusion within major vessel segments (M1, M1/M2, ACA, and PCA) did not show any significant difference between both techniques (97% for SWI versus 96% for TOF-angiography) while the sensitivity for detection of embolic occlusion within M2/M3 was significantly different (84% for SWI versus 39% for TOF-angiography, p<0.00012). CONCLUSIONS: SWI and TOF-angiography provide similar sensitivity for central thrombi while SWI is superior for the detection of peripheral thrombi in small arterial vessel segments.