Volumetric MRI with sparse sampling for MR-guided 3D motion tracking via sparse prior-augmented implicit neural representation learning.

Background: Volumetric reconstruction of magnetic resonance imaging (MRI) from sparse samples is desirable for 3D motion tracking and promises to improve magnetic resonance (MR)-guided radiation treatment precision. Data-driven sparse MRI reconstruction, however, requires large-scale training datasets for prior learning, which is time-consuming and challenging to acquire in clinical settings.

Purpose: To investigate volumetric reconstruction of MRI from sparse samples of two orthogonal slices aided by sparse priors of two static 3D MRI through implicit neural representation (NeRP) learning, in support of 3D motion tracking during MR-guided radiotherapy.

Real time volumetric MRI for 3D motion tracking via geometry-informed deep learning.

Purpose: To develop a geometry-informed deep learning framework for volumetric MRI with sub-second acquisition time in support of 3D motion tracking, which is highly desirable for improved radiotherapy precision but hindered by the long image acquisition time.

Methods: A 2D-3D deep learning network with an explicitly defined geometry module that embeds geometric priors of the k-space encoding pattern was investigated, where a 2D generation network first augmented the sparsely sampled image dataset by generating new 2D representations of the underlying 3D subject. A geometry module then unfolded the 2D representations to the volumetric space.

Volumetric prediction of breathing and slow drifting motion in the abdomen using radial MRI and multi-temporal resolution modeling.

Abdominal organ motions introduce geometric uncertainties to radiotherapy. This study investigates a multi-temporal resolution 3D motion prediction scheme that accounts for both breathing and slow drifting motion in the abdomen in support of MRI-guided radiotherapy. Ten-minute MRI scans were acquired for 8 patients using a volumetric golden-angle stack-of-stars sequence.

Modeling intra-fractional abdominal configuration changes using breathing motion-corrected radial MRI.

Abdominal organ motions introduce geometric uncertainties to gastrointestinal radiotherapy. This study investigated slow drifting motion induced by changes of internal anatomic organ arrangements using a 3D radial MRI sequence with a scan length of 20 min. Breathing motion and cyclic GI motion were first removed through multi-temporal resolution image reconstruction.

Gastrointestinal 4D MRI with respiratory motion correction.

Purpose: Gastrointestinal motion patterns such as peristalsis and segmental contractions can alter the shape and position of the stomach and intestines with respect to other irradiated organs during radiation therapy. Unfortunately, these deformations are concealed by conventional four-dimensional (4D)-MRI techniques, which were developed to visualize respiratory motion by binning acquired data into respiratory motion states without considering the phases of GI motion. We present a method to reconstruct breathing-compensated images showing the phases of periodic gastric motion and study the effect of this motion on regional anatomical structures.

A hierarchical model of abdominal configuration changes extracted from golden angle radial magnetic resonance imaging.

Abdominal organs are subject to a variety of physiological forces that superimpose their effects to influence local motion and configuration. These forces not only include breathing, but can also arise from cyclic antral contractions and a range of slow configuration changes. To elucidate each individual motion pattern as well as their combined effects, a hierarchical motion model was built for characterization of these 3 motion modes (characterized as deformation maps between states) using golden angle radial MR signals.

Abdominal synthetic CT generation from MR Dixon images using a U-net trained with 'semi-synthetic' CT data.

Magnetic resonance imaging (MRI) is gaining popularity in guiding radiation treatment for intrahepatic cancers due to its superior soft tissue contrast and potential of monitoring individual motion and liver function. This study investigates a deep learning-based method that generates synthetic CT volumes from T1-weighted MR Dixon images in support of MRI-based intrahepatic radiotherapy treatment planning. Training deep neutral networks for this purpose has been challenged by mismatches between CT and MR images due to motion and different organ filling status.

The local electron attachment energy and the electrostatic potential as descriptors of surface-adsorbate interactions.

Two local reactivity descriptors computed by Kohn-Sham density functional theory (DFT) are used to predict and rationalize interactions of nucleophilic molecules (exemplified by CO and HO) with transition metal (TM) and oxide surfaces. The descriptors are the electrostatic potential, V(r), and the local electron attachment energy, E(r), evaluated on surfaces defined by the 0.001 e Bohr isodensity contour.

Abdominal DCE-MRI reconstruction with deformable motion correction for liver perfusion quantification.

Purpose: Abdominal dynamic contrast-enhanced (DCE) MRI suffers from motion-induced artifacts that can blur images and distort contrast-agent uptake curves. For liver perfusion analysis, image reconstruction with rigid-body motion correction (RMC) can restore distorted portal-venous input functions (PVIF) to higher peak amplitudes. However, RMC cannot correct for liver deformation during breathing.

Adsorption of Hydrogen Sulfide, Hydrosulfide and Sulfide at Cu(110) - Polarizability and Cooperativity Effects. First Stages of Formation of a Sulfide Layer.

Understanding the surface site preference for single adsorbates, the interactions between adsorbates, how these interactions affect surface site specificity in adsorption and perturb the electronic states of surfaces is important for rationalizing the structure of interfaces and the growth of surface products. Herein, using density functional theory (DFT) calculations, we investigated the adsorption of H S, HS and, S onto Cu(110). The surface site specificity observed for single adsorbates can be largely affected by the presence of other adsorbates, especially S that can affect the adsorption of other species even at distances of 13 Å.

Quantification of liver function by linearization of a two-compartment model of gadoxetic acid uptake using dynamic contrast-enhanced magnetic resonance imaging.

Dynamic gadoxetic acid-enhanced magnetic resonance imaging (MRI) allows the investigation of liver function through the observation of the perfusion and uptake of contrast agent in the parenchyma. Voxel-by-voxel quantification of the contrast uptake rate (k ) from dynamic gadoxetic acid-enhanced MRI through the standard dual-input, two-compartment model could be susceptible to overfitting of variance in the data. The aim of this study was to develop a linearized, but more robust, model.

Modeling of Normal Tissue Complications Using Imaging and Biomarkers After Radiation Therapy for Hepatocellular Carcinoma.

Purpose: To develop normal tissue complications (NTCP) models for hepatocellular cancer (HCC) patients who undergo liver radiation therapy (RT) and to evaluate the potential role of functional imaging and measurement of blood-based circulating biological markers before and during RT to improve the performance of these models.

Methods And Materials: The data from 192 HCC patients who had undergone RT from 2005 to 2014 were evaluated. Of the 192 patients, 146 had received stereotactic body RT (SBRT) and 46 had received conventional RT to a median physical tumor dose of 49.

σ-Holes and σ-lumps direct the Lewis basic and acidic interactions of noble metal nanoparticles: introducing regium bonds.

Using local DFT-based probes for electrostatic as well as charge transfer/polarization interactions, we are able to characterize Lewis basic and acidic sites on copper, silver and gold nanoparticles. The predictions obtained using the DFT-probes are compared to the interaction energies of the electron donating (CO, HO, NH and HS) and the electron accepting (BH, BF, HCl [H-down] and Na) compounds. The probes include the local electron attachment energy [E(r)], the average local ionization energy [Ī(r)], and the electrostatic potential [V(r)] and are evaluated on isodensity surfaces located at distances corresponding to typical interaction distances.

Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI.

Purpose: Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast-enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra-image motion blur remains after alignment and can alter the shape of contrast-agent uptake curves.

An Overdetermined System of Transform Equations in Support of Robust DCE-MRI Registration With Outlier Rejection.

Quantitative hepatic perfusion parameters derived by fitting dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of liver to a pharmacokinetic model are prone to errors if the dynamic images are not corrected for respiratory motion by image registration. The contrast-induced intensity variations in pre- and postcontrast phases pose challenges for the accuracy of image registration. We propose an overdetermined system of transformation equations between the image volumes in the DCE-MRI series to achieve robust alignment.

Effect of gradient field nonlinearity distortions in MRI-based attenuation maps for PET reconstruction.

Purpose: Attenuation correction is a requirement for quantification of the activity distribution in PET. The need to base attenuation correction on MRI instead of CT has arisen with the introduction of integrated PET/MRI systems. The aim was to describe the effect of residual gradient field nonlinearity distortions on PET attenuation correction.

Molecular and dissociative adsorption of water and hydrogen sulfide at perfect and defective Cu(110) surfaces.

We performed a density functional theory (DFT) investigation of the molecular and dissociative adsorption of HO and HS at perfect and defective Cu(110) surfaces described using supercells with c(6 × 6) periodicity. The defective surface consists of a terrace surrounded by pits. We found considerable differences in adsorption modes and energies for HO and HS.

Accuracy of inverse treatment planning on substitute CT images derived from MR data for brain lesions.

Background: In this pilot study we evaluated the performance of a substitute CT (s-CT) image derived from MR data of the brain, as a basis for optimization of intensity modulated rotational therapy, final dose calculation and derivation of reference images for patient positioning.

Methods: S-CT images were created using a Gaussian mixture regression model on five patients previously treated with radiotherapy. Optimizations were compared using D max, D min, D median and D mean measures for the target volume and relevant risk structures.

CT substitutes derived from MR images reconstructed with parallel imaging.

Purpose: Computed tomography (CT) substitute images can be generated from ultrashort echo time (UTE) MRI sequences with radial k-space sampling. These CT substitutes can be used as ordinary CT images for PET attenuation correction and radiotherapy dose calculations. Parallel imaging allows faster acquisition of magnetic resonance (MR) images by exploiting differences in receiver coil element sensitivities.

Searching for the thermodynamic limit--a DFT study of the step-wise water oxidation of the bipyramidal Cu7 cluster.

Oxidative degradation of copper in aqueous environments is a major concern in areas such as catalysis, electronics and construction engineering. A particular challenge is to systematically investigate the details of this process for non-ideal copper surfaces and particles under the conditions found in most real applications. To this end, we have used hybrid density functional theory to study the oxidation of a Cu7 cluster in water solution.

Improved quality of computed tomography substitute derived from magnetic resonance (MR) data by incorporation of spatial information--potential application for MR-only radiotherapy and attenuation correction in positron emission tomography.

Background: Estimation of computed tomography (CT) equivalent data, i.e. a substitute CT (s-CT), from magnetic resonance (MR) images is a prerequisite both for attenuation correction of positron emission tomography (PET) data acquired with a PET/MR scanner and for dose calculations in an MR-only radiotherapy workflow.

Treatment planning of intracranial targets on MRI derived substitute CT data.

Background: The use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To eliminate systematic uncertainties due to image registration, a workflow based entirely on MRI may be preferable. In the present pilot study, we investigate dose calculation accuracy for automatically generated substitute CT (s-CT) images of the head based on MRI.

Mechanistic insights into copper-catalyzed Sonogashira-Hagihara-type cross-coupling reactions: sub-mol% catalyst loadings and ligand effects.

An efficient catalytic system for Sonogashira-Hagihara-type reactions displaying ligand acceleration in the copper-catalyzed formation of C(sp²)-C(sp) bonds is described. The structure of the ligand plays a key role for the coupling efficiency. Various copper sources show excellent catalytic activity, even in sub-mol% quantities.

Reactivity of metal oxide clusters with hydrogen peroxide and water--a DFT study evaluating the performance of different exchange-correlation functionals.

We have performed a density functional theory (DFT) investigation of the interactions of H2O2, H2O and HO radicals with clusters of ZrO2, TiO2 and Y2O3. Different modes of H2O adsorption onto the clusters were studied. In almost all the cases the dissociative adsorption is more exothermic than molecular adsorption.

Computational design of a Diels-Alderase from a thermophilic esterase: the importance of dynamics.

A novel computational Diels-Alderase design, based on a relatively rare form of carboxylesterase from Geobacillus stearothermophilus, is presented and theoretically evaluated. The structure was found by mining the PDB for a suitable oxyanion hole-containing structure, followed by a combinatorial approach to find suitable substrates and rational mutations. Four lead designs were selected and thoroughly modeled to obtain realistic estimates of substrate binding and prearrangement.