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Aminoborane, H2NBH2 and its isotopologues, H2N10BH2, D2NBD2, and D2N10BD2, have been studied by high‐level ab initio methods. All calculations rely on multidimensional potential energy surfaces and dipole moment surfaces including high‐order mode coupling terms, which have been obtained from electronic structure calculations at the level of explicitly correlated coupled‐cluster theory, CCSD(T)‐F12, or the distinguishable cluster approximation, DCSD. Subsequent vibrational structure calculations based on second‐order vibrational perturbation theory, VPT2, and vibrational configuration interaction theory, VCI, were used to determine rotational constants, centrifugal distortion constants, vibrationally averaged geometrical parameters and (an)harmonic vibrational frequencies. The impact of core‐correlation effects is discussed in detail. Rovibrational VCI calculations were used to simulate the gas phase spectra of these species and an in‐depth analysis of the ν7 band of aminoborane is provided. Color‐coding is used to reveal the identity of the individual progressions of the rovibrational transitions for this particular mode. [ABSTRACT FROM AUTHOR]

Purpose: The implementation of volumetric in‐room imaging for online adaptive radiotherapy makes extensive testing of this image data for treatment planning necessary. Especially for proton beams the higher sensitivity to stopping power properties of the tissue results in more stringent requirements. Current approaches mainly focus on recalculation of the plans on the new image data, lacking experimental verification, and ignoring the impact on the plan re‐optimization process. The aim of this study was to use gel and film dosimetry coupled with a three‐dimensional (3D) printed head phantom (based on the planning CT of the patient) for 3D range verification of intensity‐corrected cone beam computed tomography (CBCT) image data for adaptive proton therapy. Methods: Single field uniform dose pencil beam scanning proton plans were optimized for three different patients on the patients' planning CT (planCT) and the patients' intensity‐corrected CBCT (scCBCT) for the same target volume using the same optimization constraints. The CBCTs were corrected on projection level using the planCT as a prior. The dose optimized on planCT and recalculated on scCBCT was compared in terms of proton range differences (80% distal fall‐off, recalculation). Moreover, the dose distribution resulting from recalculation of the scCBCT‐optimized plan on the planCT and the original planCT dose distribution were compared (simulation). Finally, the two plans of each patient were irradiated on the corresponding patient‐specific 3D printed head phantom using gel dosimetry inserts for one patient and film dosimetry for all three patients. Range differences were extracted from the measured dose distributions. The measured and the simulated range differences were corrected for range differences originating from the initial plans and evaluated. Results: The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1 mm and the interquartile ranges (IQRs) within 0.3 mm for all three patients. The range differences of the film measurement were accurately matching with the simulation approach in the film plane. The median values of these range differences deviated less than 0.1 mm and the IQRs less than 0.4 mm. For the full 3D evaluation of the gel range differences, the median value and IQR matched those of the simulation approach within 0.7 and 0.5 mm, respectively. scCBCT‐ and planCT‐based dose distributions were found to have a range agreement better than 3 mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement). Conclusions: The results of this initial study indicate that an online adaptive proton workflow based on scatter‐corrected CBCT image data for head irradiations is feasible. The novel presented measurement‐ and simulation‐based method was shown to be equivalent to the standard literature recalculation approach. Additionally, it has the capability to catch effects of image differences on the treatment plan optimization. This makes the measurement‐based approach particularly interesting for quality assurance of CBCT‐based online adaptive proton therapy. The observed uncertainties could be kept within those of the registration and positioning. The proposed validation could also be applied for other alternative in‐room images, e.g. for MR‐based pseudoCTs. [ABSTRACT FROM AUTHOR]

Purpose: To systematically analyze intravoxel incoherent motion (IVIM) MRI in a perfusable capillary phantom closely matching the geometry of capillary beds in vivo and to compare the validity of the biexponential pseudo‐diffusion and the recently introduced phase‐distribution IVIM model. Methods: IVIM‐MRI was performed at 12 different flow rates (0.2⋯2.4mL/min) in a capillary phantom using 4 different DW‐MRI sequences (2 with monopolar and 2 with flow‐compensated diffusion‐gradient schemes, with up to 16b values between 0 and 800s/mm2). Resulting parameters from the assessed IVIM models were compared to results from optical microscopy. Results: The acquired data were best described by a static and a flowing compartment modeled by the phase‐distribution approach. The estimated signal fraction f of the flowing compartment stayed approximately constant over the applied flow rates, with an average of f=0.451±0.023 in excellent agreement with optical microscopy (f=0.454±0.002). The estimated average particle flow speeds v=0.25⋯2.7mm/s showed a highly significant linear correlation to the applied flow. The estimated capillary segment length of approximately 189um agreed well with optical microscopy measurements. Using the biexponential model, the signal fraction f was substantially underestimated and displayed a strong dependence on the applied flow rate. Conclusion: The constructed phantom facilitated the detailed investigation of IVIM‐MRI methods. The results demonstrate that the phase‐distribution method is capable of accurately characterizing fluid flow inside a capillary network. Parameters estimated using the biexponential model, specifically the perfusion fraction f, showed a substantial bias because the model assumptions were not met by the underlying flow pattern. [ABSTRACT FROM AUTHOR]

Purpose: To improve the robustness of pulmonary ventilation‐ and perfusion‐weighted imaging with Fourier decomposition (FD) MRI in the presence of respiratory and cardiac frequency variations by replacing the standard fast Fourier transform with the more general nonuniform Fourier transform. Theory and Methods: Dynamic coronal single‐slice MRI of the thorax was performed in 11 patients and 5 healthy volunteers on a 1.5T whole‐body scanner using a 2D ultra‐fast balanced steady‐state free‐precession sequence with temporal resolutions of 4‐9 images/s. For the proposed nonuniform Fourier‐decomposition (NUFD) approach, the original signal with variable physiological frequencies that was acquired with constant sampling rate was retrospectively transformed into a signal with (ventilation or perfusion) frequency‐adapted sampling rate. For that purpose, frequency tracking was performed with the synchro‐squeezed wavelet transform. Ventilation‐ and perfusion‐weighted NUFD amplitude and signal delay maps were generated and quantitatively compared with regularly sampled FD maps based on their signal‐to‐noise ratio (SNR). Results: Volunteers and patients showed statistically significant increases of SNR in frequency‐adapted NUFD results compared to regularly sampled FD results. For ventilation data, the mean SNR increased by 43.4%±25.3% and 24.4%±31.9% in volunteers and patients, respectively; for perfusion data, SNR increased by 93.0%±36.1% and 75.6%±62.8%. Two patients showed perfusion signal in pulmonary areas with NUFD that could not be imaged with FD. Conclusion: This study demonstrates that using nonuniform Fourier transform in combination with frequency tracking can significantly increase SNR and reduce frequency overlaps by collecting the signal intensity onto single frequency bins. [ABSTRACT FROM AUTHOR]

Purpose Variability across devices, patients, and time still hinders widespread recognition of dynamic contrast-enhanced magnetic resonance imaging ( DCE- MRI) as quantitative biomarker. The purpose of this work was to introduce and characterize a dedicated microchannel phantom as a model for quantitative DCE- MRI measurements. Methods A perfusable, MR-compatible microchannel network was constructed on the basis of sacrificial melt-spun sugar fibers embedded in a block of epoxy resin. Structural analysis was performed on the basis of light microscopy images before DCE- MRI experiments. During dynamic acquisition the capillary network was perfused with a standard contrast agent injection system. Flow-dependency, as well as inter- and intrascanner reproducibility of the computed DCE parameters were evaluated using a 3.0 T whole-body MRI. Results Semi-quantitative and quantitative flow-related parameters exhibited the expected proportionality to the set flow rate (mean Pearson correlation coefficient: 0.991, P < 2.5e-5). The volume fraction was approximately independent from changes of the applied flow rate through the phantom. Repeatability and reproducibility experiments yielded maximum intrascanner coefficients of variation ( CV) of 4.6% for quantitative parameters. All evaluated parameters were well in the range of known in vivo results for the applied flow rates. Conclusion The constructed phantom enables reproducible, flow-dependent, contrast-enhanced MR measurements with the potential to facilitate standardization and comparability of DCE- MRI examinations. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to propose and evaluate a new wavelet-based technique for classification of arterial and venous vessels using time-resolved cerebral CT perfusion data sets. Methods: Fourteen consecutive patients (mean age 73 yr, range 17-97) with suspected stroke but no pathology in follow-up MRI were included. A CT perfusion scan with 32 dynamic phases was performed during intravenous bolus contrast-agent application. After rigid-body motion correction, a Paul wavelet (order 1) was used to calculate voxelwise the wavelet power spectrum (WPS) of each attenuation-time course. The angiographic intensity A was defined as the maximum of the WPS, located at the coordinates T (time axis) and W (scale/width axis) within the WPS. Using these three parameters (A, T, W) separately as well as combined by (1) Fisher's linear discriminant analysis (FLDA), (2) logistic regression (LogR) analysis, or (3) support vector machine (SVM) analysis, their potential to classify 18 different arterial and venous vessel segments per subject was evaluated. Results: The best vessel classification was obtained using all three parameters A and T and W [area under the curve (AUC): 0.953 with FLDA and 0.957 with LogR or SVM]. In direct comparison, the wavelet-derived parameters provided performance at least equal to conventional attenuation-timecourse parameters. The maximum AUC obtained from the proposed wavelet parameters was slightly (although not statistically significantly) higher than the maximum AUC (0.945) obtained from the conventional parameters. Conclusions: A new method to classify arterial and venous cerebral vessels with high statistical accuracy was introduced based on the time-domain wavelet transform of dynamic CT perfusion data in combination with linear or nonlinear multidimensional classification techniques. [ABSTRACT FROM AUTHOR]