Modified Hargreaves-Samani Equation for the Assessment of Reference Evapotranspiration in Alpine River Basins

n/

X-ray CT adaptation based on a 2D–3D deformable image registration framework using simulated in-room proton radiographies

The aim of this work is to investigate in-room proton radiographies to compensate realistic rigid and non-rigid transformations in clinical-like scenarios based on 2D–3D deformable image registration (DIR) framework towards future clinical implementation of adaptive radiation therapy (ART). Monte Carlo simulations of proton radiographies (pRads) based on clinical x-ray CT of a head and neck, and a brain tumor patients are simulated for two different detector configurations (i.e. integration-mode and list-mode detectors) including high and low proton statistics. A realistic deformation, derived from cone beam CT of the patient, is applied to the treatment planning CT. Rigid inaccuracies in patient positioning are also applied and the effect of small, medium and large fields of view (FOVs) is investigated. A stopping criterion, as desirable in realistic scenarios devoid of ground truth proton CT (pCT), is proposed and investigated. Results show that rigid and non-rigid transformations can be compensated based on a limited number of low dose pRads. The root mean square error with respect to the pCT shows that the 2D–3D DIR of the treatment planning CT based on 10 pRads from integration-mode data and 2 pRads from list-mode data is capable of achieving comparable accuracy (∼90% and >90%, respectively) to conventional 3D–3D DIR. The dice similarity coefficient over the segmented regions of interest also verifies the improvement in accuracy prior to and after 2D–3D DIR. No relevant changes in accuracy are found between high and low proton statistics except for 2 pRads from integration-mode data. The impact of FOV size is negligible. The convergence of the metric adopted for the stopping criterion indicates the optimal convergence of the 2D–3D DIR. This work represents a further step towards the potential implementation of ART in proton therapy. Further computational optimization is however required to enable extensive clinical validation

Different FDG-PET metabolic patterns at single-subject level in the behavioral variant of fronto-temporal dementia.

BACKGROUND: The diagnosis of probable behavioral variant of fronto-temporal dementia (bvFTD) according to current criteria requires the imaging evidence of frontal and/or anterior temporal atrophy or hypoperfusion/hypometabolism. Different variants of this pattern of brain involvement may, however, be found in individual cases, supporting the presence of heterogeneous phenotypes. OBJECTIVE: We examined in a case-by-case approach the FDG-PET metabolic patterns of patients fulfilling clinical criteria for probable bvFTD, assessing the presence and frequency of specific FDG-PET features. MATERIALS AND METHODS: Fifty two FDG-PET scans of probable bvFTD patients were retrospectively analyzed together with clinical and neuropsychological data. Neuroimaging experts rated the FDG-PET hypometabolism maps obtained at the single-subject level with optimized voxel-based Statistical Parametric Mapping (SPM). The functional metabolic heterogeneity was further tested by hierarchical cluster analysis and principal component analysis (PCA). RESULTS: Both the SPM maps and cluster analysis identified two major variants of cerebral hypometabolism, namely the "frontal" and the "temporo-limbic", which were correlated with different cognitive profiles. Executive and language deficits were the cognitive hallmark in the "frontal" subgroup, while poor encoding and recall on long-term memory tasks was typical of the "temporo-limbic" subgroup. DISCUSSION: SPM single-subject analysis indicates distinct patterns of brain dysfunction in bvFTD, coupled with specific clinical features, suggesting different profiles of neurodegenerative vulnerability. These findings have important implications for the early diagnosis of bvFTD and for the application of the recent international consensus criteria

Dosimetric accuracy and radiobiological implications of ion computed tomography for proton therapy treatment planning

Ion computed tomography (iCT) represents a potential replacement for x-ray CT (xCT) in ion therapy treatment planning to reduce range uncertainties, inherent in the semi-empirical conversion of xCT information into relative stopping power (RSP). In this work, we aim to quantify the increase in dosimetric accuracy associated with using proton-, helium- and carbon-CT compared to conventional xCT for clinical scenarios in proton therapy. Three cases imaged with active beam-delivery using an ideal single-particle-tracking detector were investigated using FLUKA Monte-Carlo (MC) simulations. The RSP accuracy of the iCTs was evaluated against the ground truth at similar physical dose. Next, the resulting dosimetric accuracy was investigated by using the RSP images as a patient model in proton therapy treatment planning, in comparison to common uncertainties associated with xCT. Finally, changes in relative biological effectiveness (RBE) with iCT particle type/spectrum were investigated by incorporating the repair-misrepair-fixation (RMF) model into FLUKA, to enable first insights on the associated biological imaging dose. Helium-CT provided the lowest overall RSP error, whereas carbon-CT offered the highest accuracy for bone and proton-CT for soft tissue. For a single field, the average relative proton beam-range variation was  −1.00%, +0.09%, −0.08% and  −0.35% for xCT, proton-, helium- and carbon-CT, respectively. Using a 0.5%/0.5mm gamma-evaluation, all iCTs offered comparable accuracy with a better than 99% passing rate, compared to 83% for xCT. The RMF model predictions for RBE for cell death relative to a diagnostic xCT spectrum were 0.82–0.85, 0.85–0.89 and 0.97–1.03 for proton-, helium-, and carbon-CT, respectively. The corresponding RBE for DNA double-strand break induction was generally below one. iCT offers great clinical potential for proton therapy treatment planning by providing superior dose calculation accuracy as well as lower physical and potentially biological dose exposure compared to xCT. For the investigated dose level and ideal detector, proton-CT and helium-CT yielded the best performance

Development of integration mode proton imaging with a single CMOS detector for a small animal irradiation platform

A novel irradiation platform for preclinical proton therapy studies foresees proton imaging for accurate setup and treatment planning. Imaging at modern synchrocyclotron-based proton therapy centers with high instantaneous particle flux is possible with an integration mode setup. The aim of this work is to determine an object’s water-equivalent thickness (WET) with a commercially available large-area CMOS sensor. Image contrast is achieved by recording the proton energy deposition in detector pixels for several incoming beam energies (here, called probing energies) and applying a signal decomposition method that retrieves the water-equivalent thickness. A single planar 114 mm × 65 mm CMOS sensor (49.5 µm pixel pitch) was used for this study, aimed at small-animal imaging. In experimental campaigns, at two isochronous cyclotron-based facilities, probing energies suitable for small-animal-sized objects were produced once with built-in energy layer switching and the other time, using a custom degrader wheel. To assess water-equivalent thickness accuracy, a micro-CT calibration phantom with 10 inserts of tissue-mimicking materials was imaged at three phantom-to-detector distances: 3 mm, 13 mm, and 33 mm. For 3 mm and 13 mm phantom-to-detector distance, the average water-equivalent thickness error compared to the ground truth was about 1 and the spatial resolution was 0.16(3) mm and 0.47(2) mm, respectively. For the largest separation distance of 33 mm air gap, proton scattering had considerable impact and the water-equivalent thickness relative error increased to 30, and the spatial resolution was larger than 1.75 mm. We conclude that a pixelated CMOS detector with dedicated post-processing methods can enable fast proton radiographic imaging in a simple and compact setup for small-animal-sized objects with high water-equivalent thickness accuracy and spatial resolution for reasonable phantom-to-detector distances