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The goal of the SunPy project is to facilitate and promote the use and development of community-led, free, and open source data analysis software for solar physics based on the scientific Python environment. The project achieves this goal by developing and maintaining the sunpy core package and supporting an ecosystem of affiliated packages. This paper describes the first official stable release (version 1.0) of the core package, as well as the project organization and infrastructure. This paper concludes with a discussion of the future of the SunPy project. [ABSTRACT FROM AUTHOR]

Mammography is one of the most commonly applied tools for early breast cancer screening. Automatic segmentation of breast masses in mammograms is essential but challenging due to the low signal-to-noise ratio and the wide variety of mass shapes and sizes. Existing methods deal with these challenges mainly by extracting mass-centered image patches manually or automatically. However, manual patch extraction is time-consuming and automatic patch extraction brings errors that could not be compensated in the following segmentation step. In this study, we propose a novel attention-guided dense-upsampling network (AUNet) for accurate breast mass segmentation in whole mammograms directly. In AUNet, we employ an asymmetrical encoder-decoder structure and propose an effective upsampling block, attention-guided dense-upsampling block (AU block). Especially, the AU block is designed to have three merits. Firstly, it compensates the information loss of bilinear upsampling by dense upsampling. Secondly, it designs a more effective method to fuse high- and low-level features. Thirdly, it includes a channel-attention function to highlight rich-information channels. We evaluated the proposed method on two publicly available datasets, CBIS-DDSM and INbreast. Compared to three state-of-the-art fully convolutional networks, AUNet achieved the best performances with an average Dice similarity coefficient of 81.8% for CBIS-DDSM and 79.1% for INbreast.

Peptide receptor radionuclide therapy (PRRT) with 177 Lu- radiolabeled octreotate is an effective treatment method for inoperable neuroendocrine tumours (NETs). There is growing evidence that estimates of the organ-at-risks (OARs) doses are necessary for the optimization of personalized PRRT (P-PRRT). Dosimetry, however, requires a complicated and time-consuming procedure, which hinders its implementation in the clinic. The aim of this study is to develop a practical and automatic technique to simplify personalized dosimetry of kidney, the major OAR in 177 Lu P-PRRT. The data from 30 NETs patients undergoing 44 personalized 177 Lu-DOTA-TATE therapy cycles were analyzed. To determine the biokinetics of the radiopharmaceutical in the kidneys, for each patient three SPECT/CT scans were acquired, at about 4 h, 24 h and 70 h after injection. The kidneys doses were evaluated using three different approaches: (1) a traditional approach based on whole kidney (WK) segmentation; (2) a small volume (SV) manual approach (M-SV) with observer-defined SV location; and (3) a software based SV-approach that automatically defines SV location (A-SV). Four different methods of automatic SV location selections were investigated. The SV kidney doses estimated using M-SV and A-SV approaches was evaluated and the accuracy of these two approaches were compared to the WK dosimetry. The kidney bio-kinetics, in terms of effective half-lives, obtained from both of the A-SV and M-SV approaches agreed to within 10% with those obtained from the WK segmentation. The average ratios of SV doses to WK doses were mostly about 1.8  ±  0.2 for both A-SV and M-SV approaches. The linear correlation coefficients between SV doses (both A-SV and M-SV) and WK doses were up to 0.9 with p   <  0.001. The differences between A-SV and M-SV were minor. By comparing different methods of SV location selections, independently selecting SV in images from each of the acquisitions was proved the most appropriate and accurate approach. An automatic, observer-independent method for selecting the location of the small volume in kidneys was developed. The accuracy of this dose estimation approach has been demonstrated by comparing it with the manual SV dosimetry, as well as the WK dosimetry. The proposed automatic approach can potentially be considered as a practical and simple method for dose estimation in the future clinical studies.

Low-energy x-ray imaging of the secondary electron bremsstrahlung (SEB) x-ray emitted during carbon-ion irradiation is a promising method for range estimation. However, it remains unclear whether the method can be used for imaging with the clinical dose levels of carbon-ion and whether the bremsstrahlung x-ray can be detected from the deeper part of the body. To clarify these points, we developed a new high resolution low-energy x-ray camera and conducted imaging of the SEB x-ray during the irradiation of carbon-ions of different energies and intensities. Imaging was also tried with an x-ray camera using a human-head-sized, 17 cm diameter cylindrical phantom. To develop a high resolution imaging detector for a low-energy x-ray, we used a 20  ×  20  ×  0.5 mm thick cerium-doped yttrium aluminum perovskite, YA1O 3 (YAP(Ce)) scintillator plate, which was optically coupled to a 25 mm square high quantum efficiency (HQE) type position sensitive photomultiplier tube (PSPMT). The imaging detector was encased in a 2 cm thick tungsten container and a pinhole collimator was attached to its camera head. After evaluating the camera's performance, SEB x-ray imaging was tried during irradiation of the carbon-ion and compared the results with a Monte Carlo simulation. We imaged the beam tracks by the SEB x-ray in real-time during irradiation of the carbon-ion and imaging and range estimation were possible even with near clinical dose level of 7.5  ×  10 8 particles of carbon-ion. Clear images of a SEB x-ray were also obtained for a 17 cm diameter cylindrical phantom. The measured images were good agreement with the Monte Carlo simulation. We confirmed that our developed YAP(Ce) camera is promising for imaging SEB x-rays during irradiation of carbon-ions even near clinical conditions.

To promote accurate image-guided radiotherapy (IGRT) for a proton pencil beam scanning (PBS) system, a new quality assurance (QA) procedure employing a cone-shaped scintillator detector has been developed for multiple QA tasks in a semi-automatic manner. The cone-shaped scintillator detector (XRV-124, Logos Systems, CA) is sensitive to both x-ray and proton beams. It records scintillation on the cone surface as a 2D image, from which the geometry of the radiation field that enters and exits the cone can be extracted. Utilizing this feature, QA parameters that are essential to PBS IGRT treatment were measured and analyzed. The first applications provided coincidence checks of laser, imaging and radiation isocenters, and dependencies on gantry angle and beam energies. The analysis of the Winston-Lutz test was made available by combining the centricity measurements of the x-ray beam and the pencil beam. The accuracy of the gantry angle was validated against console readings provided by the digital encoder and an agreement of less than 0.2° was found. The accuracy of the position measurement was assessed with a robotic patient positioning system (PPS) and an agreement of less than 0.5 mm was obtained. The centricity of the two onboard x-ray imaging systems agreed well with that from the routinely used Digital Imaging Positioning System (DIPS), up to a consistent small shift of (-0.5 mm, 0.0 mm, -0.3 mm). The pencil beam spot size, in terms of σ of Gaussian fitting, agreed within 0.2 mm for most energies when compared to the conventional measurements by a 2D ion-chamber array (MatriXX-PT, IBA Dosimetry, Belgium). The cone-shaped scintillator system showed advantages in making multi-purpose measurements with a single setup. The in-house algorithms were successfully implemented to measure and analyze key QA parameters in a semi-automatic manner. This study presents an alternative and more efficient approach for IGRT QA for PBS and potentially for linear accelerators.

Deformable 3D radiation dosimetry is receiving growing interest for the validation of image-guided radiotherapy treatments (IGRT) of moving and deformable targets. Previously, a proof-of-concept of a flexible anthropomorphic 3D dosimeter called 'FlexyDos3D' has been demonstrated. One of the concerns with respect to the FlexyDos3D dosimeter is its dose-response instability. The effect of different formulations of the dosimeter on its stability were investigated. A stable formulation for the dosimeter was found by optimising the ratios of curing agent and base of the silicone matrix between 3% and 4.5% [w/w] curing agent. The effects of elevated curing temperatures and times upon the dosimetric properties were also investigated and the dose-response was found to be independent of curing times for curing times over an hour at 120 °C. 1 H NMR spectra of the dosimeter chemical constituents and the effect of radiation dose were determined. The evaporation and diffusion rates of chloroform in the dosimeter were determined and are the likely cause of the dosimeters depth-dose profile uncertainties. A composition for a stable silicone dosimeter which can be cured quickly at elevated temperatures was found, demonstrating the potential for 3D printing of patient-specific dosimeters. However, it is suggested that another radical initiator be used in future formulations of the dosimeter.

Although luminescence of water lower in energy than the Cerenkov-light threshold during proton and carbon-ion irradiation has been found, the phenomenon has not yet been implemented for Monte Carlo simulations. The results provided by the simulations lead to misunderstandings of the physical phenomenon in optical imaging of water during proton and carbon-ion irradiation. To solve the problems, as well as to clarify the light production of the luminescence of water, we modified a Monte Carlo simulation code to include the light production from the luminescence of water and compared them with the experimental results of luminescence imaging of water. We used GEANT4 for the simulation of emitted light from water during proton and carbon-ion irradiation. We used the light production from the luminescence of water using the scintillation process in GEANT4 while those of Cerenkov light from the secondary electrons and prompt gamma photons in water were also included in the simulation. The modified simulation results showed similar depth profiles to those of the measured data for both proton and carbon-ion. When the light production of 0.1 photons/MeV was used for the luminescence of water in the simulation, the simulated depth profiles showed the best match to those of the measured results for both the proton and carbon-ion compared with those used for smaller and larger numbers of photons/MeV. We could successively obtain the simulated depth profiles that were basically the same as the experimental data by using GEANT4 when we assumed the light production by the luminescence of water. Our results confirmed that the inclusion of the luminescence of water in Monte Carlo simulation is indispensable to calculate the precise light distribution in water during irradiation of proton and carbon-ion.

The nucleobase 5-hydroxymethylcytosine (5-hmC), a modified form of cytosine, is an important epigenetic mark related to regulation of gene expression. 5-hmC levels are highly dynamic during early development and are modulated during the progression of neurodegenerative disease and cancer. We describe a spectroscopic method for the global quantification of 5-hmC in genomic DNA. This method relies on the enzymatic glucosylation of 5-hmC, followed by a glucose oxidation step that results in the formation of aldehyde moieties that are covalently linked to a fluorescent reporter by oxime ligation. The fluorescence intensity of the labeled sample is directly proportional to its 5-hmC content. We show that this simple and cost-effective technique is suitable for quantification of 5-hmC content in different mouse tissues.