This paper presents a method for horizontally extending the field-of-view in cone-beam tomography to overcome the limitations of traditional detector sizes. The acquisition algorithms are implemented on an Exciscope Polaris phase-contrast micro-CT instrument, which ensures sufficient motion accuracy for horizontal extension solely reliant on stage positions, even at submicron voxel sizes. This innovation enables the construction of an automated data pipeline that bypasses the need for user input or image registration to recombine frames. Utilizing cloud computing for reconstruction, we efficiently handle large data sizes and computational demands. We demonstrate the method both with a reconstruction diameter of 12,500 voxels and with submicron voxel sizes, showcasing significant improvements in imaging capabilities.
Classical histology is the gold standard for soft-tissue analysis, and it is performed by imaging thin slices of a sample with a microscope. While the resolution is high in two dimensions, the sample preparation to be able to record images is time consuming, destructive and effectively limiting the recorded data to two dimensions. We propose virtual histology by x-ray phase-contrast computed tomography (CT) as a non-destructive imaging method to be used as a complement to classical histology. With our laboratory system, we focus on detailed imaging of soft-tissue tumours with the aim of distinguishing the tumour from healthy tissue.
Purpose: Surgery is an essential part of the curative plan for most patients affected with solid tumors. The outcome of such surgery, e.g., recurrence rates and ultimately patient survival, depends on several factors where the resection margin is of key importance. Presently, the resection margin is assessed by classical histology, which is time-consuming (several days), destructive, and basically only gives two-dimensional information. Clearly, it would be advantageous if immediate feedback on tumor extension in all three dimensions were available to the surgeon intraoperatively.
Approach: We investigate a laboratory propagation-based phase-contrast x-ray computed tomography system that provides the resolution, the contrast, and, potentially, the speed for this purpose. The system relies on a liquid-metal jet microfocus source and a scintillator-coated CMOS detector. Our study is performed on paraffin-embedded non-stained samples of human pancreatic neuroendocrine tumors, liver intrahepatic cholangiocarcinoma, and pancreatic serous cystic neoplasm (benign).
Results: We observe tumors with distinct and sharp edges having cellular resolution (∼10 μm) as well as many assisting histological landmarks, allowing for resection margin assessment. All x-ray data are compared with classical histology. The agreement is excellent.
Conclusion: We conclude that the method has potential for intraoperative three-dimensional virtual histology.
Surgery is an essential part of the curative plan for most patients affected with solid tumors. The outcome of such surgery, e.g., recurrence rates and ultimately patient survival, depends on several factors where the resection margin is of key importance. Presently the resection margin is assessed by classical histology, which is time-consuming (several days), destructive, and basically only gives two-dimensional information. Clearly it would be advantageous if immediate feedback on tumor extension in all three dimensions were available to the surgeon intra-operatively. In the present paper we investigate a laboratory propagation-based phase-contrast xray computed tomography (CT) system that provides the resolution, contrast, and, potentially, the speed for this purpose. The system relies on a liquid-metal jet micro-focus source and a scintillator-coated CMOS detector. The study is performed on paraffin-embedded non-stained samples of human pancreatic neuroendocrine tumors, liver intrahepatic cholangiocarcinoma, and pancreatic serous cystic neoplasm (benign). We observe tumors with distinct and sharp edges having cellular resolution (∼10 μm) as well as many assisting histological landmarks, allowing for resection margin assessment. All x-ray data is compared with classical histology. The agreement is excellent, and we conclude that the method has potential for intra-operative three-dimensional virtual histology.
Laboratory x-ray fluorescence (XRF) computed tomography (XFCT) with nanoparticles (NPs) as contrast agents now allows for in vivo preclinical imaging and longitudinal studies at low radiation dose. We present on developments of our XFCT arrangement capable of low-dose (<25 mGy) imaging with high signal-to-background resulting in high-spatial-resolution (200-400 μm) in vivo imaging of Ru, Rh and Mo NPs injected and accumulated locally in mice. We further demonstrate multiplexing capabilities by cross-talk-free separation of Ru, Rh and Mo XRF signal as well as envisioning the future of preclinical XFCT for active targeting and imaging of molecular markers (e.g., cancer cells).
X-ray fluorescence computed tomography (XFCT) with nanoparticles (NPs) as contrast agents has reached technical maturity allowing for in vivo preclinical imaging in the laboratory setting. We present the first in vivo longitudinal study with XFCT where mice were 5 times each during an 8-week period. Imaging is performed with low radiation dose (<25 mGy) and high signal-to-background for high-spatial-resolution imaging (200-400 µm) of molybdenum NP accumulations (down to ~50 µg/ml Mo). We further discuss our ongoing development of protein-coated NPs for actively targeting molecular markers (e.g., cancer), as well as potential clinical applications.
X-ray fluorescence tomography (XFCT) using nanoparticles (NPs) as contrast agents shows promise for high-spatial- resolution 3D molecular imaging. The technique has been demonstrated experimentally on phantoms as well as in small animals, i.e., mice. Parallel to experimental development, simulations play a key role in investigating the performance of existing and proposed XFCT arrangements. Up until recently, however, realistic simulations of small-animal XFCT have been unavailable due to the lack of appropriate, accurate and accelerated Monte Carlo (MC) based tools.
We have developed the tools necessary to simulate highly realistic small-animal XFCT. Our MC tool, XRFGPU is based on the accelerated open-source MC-GPU and allows simulations with speeds >1000x faster than other existing MC codes capable of similar simulations. Using available high-resolution digital mouse phantoms, we can predict the performance of any XFCT imaging arrangement and produce the realistic data needed for future development of small-animal XFCT. Here we validate the simulations against our laboratory arrangement, capable of 200 μm spatial-resolution XFCT of mice. Comparisons using a phantom confirms that the simulations are accurate. Lastly, we compare simulated images with images acquired in vivo using our laboratory arrangement showing how simulations can be used to enhance the interpretation of experimental data.
P. Soffitta, R. Bellazzini, E. Bozzo, V. Burwitz, A. Castro-Tirado, E. Costa, T. Courvoisier, H. Feng, S. Gburek, R. Goosmann, V. Karas, G. Matt, F. Muleri, K. Nandra, M. Pearce, J. Poutanen, V. Reglero, D. Sabau Maria, A. Santangelo, G. Tagliaferri, C. Tenzer, J. Vink, M. Weisskopf, S. Zane, I. Agudo, A. Antonelli, P. Attina, L. Baldini, A. Bykov, R. Carpentiero, E. Cavazzuti, E. Churazov, E. Del Monte, D. De Martino, I. Donnarumma, V. Doroshenko, Y. Evangelista, I. Ferreira, E. Gallo, N. Grosso, P. Kaaret, E. Kuulkers, J. Laranaga, L. Latronico, D. Lumb, J. Macian, J. Malzac, F. Marin, E. Massaro, M. Minuti, C. Mundell, J. U. Ness, T. Oosterbroek, S. Paltani, G. Pareschi, R. Perna, P.-O. Petrucci, H. B. Pinazo, M. Pinchera, J. P. Rodriguez, M. Roncadelli, A. Santovincenzo, S. Sazonov, C. Sgro, D. Spiga, J. Svoboda, C. Theobald, T. Theodorou, R. Turolla, E. Wilhelmi de Ona, B. Winter, A. M. Akbar, H. Allan, R. Aloisio, D. Altamirano, L. Amati, E. Amato, E. Angelakis, J. Arezu, J.-L. Atteia, M. Axelsson, M. Bachetti, L. Ballo, S. Balman, R. Bandiera, X. Barcons, S. Basso, A. Baykal, W. Becker, E. Behar, B. Beheshtipour, R. Belmont, E. Berger, F. Bernardini, S. Bianchi, G. Bisnovatyi-Kogan, P. Blasi, P. Blay, A. Bodaghee, M. Boer, M. Boettcher, S. Bogdanov, I. Bombaci, R. Bonino, J. Braga, W. Brandt, A. Brez, N. Bucciantini, L. Burderi, I. Caiazzo, R. Campana, S. Campana, F. Capitanio, M. Cappi, M. Cardillo, P. Casella, O. Catmabacak, B. Cenko, P. Cerda-Duran, C. Cerruti, S. Chaty, M. Chauvin, Y. Chen, J. Chenevez, M. Chernyakova, C. C. Cheung, D. Christodoulou, P. Connell, R. Corbet, F. Coti Zelati, S. Covino, W. Cui, G. Cusumano, A. D’Ai, F. D’Ammando, M. Dadina, Z. Dai, A. De Rosa, L. de Ruvo, N. Degenaar, M. Del Santo, L. Del Zanna, G. Dewangan, S. Di Cosimo, N. Di Lalla, G. Di Persio, T. Di Salvo, T. Dias, C. Done, M. Dovciak, G. Doyle, L. Ducci, R. Elsner, T. Enoto, J. Escada, P. Esposito, C. Eyles, S. Fabiani, M. Falanga, S. Falocco, Y. Fan, R. Fender, M. Feroci, C. Ferrigno, W. Forman, L. Foschini, C. Fragile, F. Fuerst, Y. Fujita, J. L. Gasent-Blesa, J. Gelfand, B. Gendre, G. Ghirlanda, G. Ghisellini, M. Giroletti, D. Goetz, E. Gogus, J.-L. Gomez, D. Gonzalez, R. Gonzalez-Riestra, E. Gotthelf, L. Gou, P. Grandi, V. Grinberg, F. Grise, C. Guidorzi, N. Gurlebeck, T. Guver, D. Haggard, M. Hardcastle, D. Hartmann, C. Haswell, A. Heger, M. Hernanz, J. Heyl, L. Ho, J. Hoormann, J. Horak, J. Huovelin, D. Huppenkothen, R. Iaria, C. Inam Sitki, A. Ingram, G. Israel, L. Izzo, M. Burgess, M. Jackson, L. Ji, J. Jiang, T. Johannsen, C. Jones, S. Jorstad, J. J. E. Kajava, M. Kalamkar, E. Kalemci, T. Kallman, A. Kamble, F. Kislat, M. Kiss, D. Klochkov, E. Koerding, M. Kolehmainen, K. Koljonen, S. Komossa, A. Kong, S. Korpela, M. Kowalinski, H. Krawczynski, I. Kreykenbohm, M. Kuss, D. Lai, M. Lan, J. Larsson, S. Laycock, D. Lazzati, D. Leahy, H. Li, J. Li, L.-X. Li, T. Li, Z. Li, M. Linares, M. Lister, H. Liu, G. Lodato, A. Lohfink, F. Longo, G. Luna, A. Lutovinov, S. Mahmoodifar, J. Maia, V. Mainieri, C. Maitra, D. Maitra, A. Majczyna, S. Maldera, D. Malyshev, A. Manfreda, A. Manousakis, R. Manuel, R. Margutti, A. Marinucci, S. Markoff, A. Marscher, H. Marshall, F. Massaro, M. McLaughlin, G. Medina-Tanco, M. Mehdipour, M. Middleton, R. Mignani, P. Mimica, T. Mineo, B. Mingo, G. Miniutti, S. M. Mirac, G. Morlino, A. Motlagh, S. Motta, A. Mushtukov, S. Nagataki, F. Nardini, J. Nattila, G. Navarro, B. Negri, Matteo Negro, S. Nenonen, V. Neustroev, F. Nicastro, A. Norton, A. Nucita, P. O’Brien, S. O’Dell, H. Odaka, B. Olmi, N. Omodei, M. Orienti, M. Orlandini, J. Osborne, L. Pacciani, V. Paliya, I. Papadakis, A. Papitto, Z. Paragi, P. Pascal, B. Paul, L. Pavan, A. Pellizzoni, E. Perinati, M. Pesce-Rollins, E. Piconcelli, A. Pili, M. Pilia, M. Pohl, G. Ponti, D. Porquet, A. Possenti, K. Postnov, I. Prandoni, N. Produit, G. Puehlhofer, B. Ramsey, M. Razzano, N. Rea, P. Reig, K. Reinsch, T. Reiprich, M. Reynolds, G. Risaliti, T. 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Zdziarski, A. Zech, H. Zhang, S. Zhang, W. Zhang, A. Zoghbi
XIPE, the X-ray Imaging Polarimetry Explorer, is a mission dedicated to X-ray Astronomy. At the time of
writing XIPE is in a competitive phase A as fourth medium size mission of ESA (M4). It promises to reopen the
polarimetry window in high energy Astrophysics after more than 4 decades thanks to a detector that efficiently
exploits the photoelectric effect and to X-ray optics with large effective area. XIPE uniqueness is time-spectrally-spatially-
resolved X-ray polarimetry as a breakthrough in high energy astrophysics and fundamental physics.
Indeed the payload consists of three Gas Pixel Detectors at the focus of three X-ray optics with a total effective
area larger than one XMM mirror but with a low weight. The payload is compatible with the fairing of the Vega
launcher. XIPE is designed as an observatory for X-ray astronomers with 75 % of the time dedicated to a Guest
Observer competitive program and it is organized as a consortium across Europe with main contributions from
Italy, Germany, Spain, United Kingdom, Poland, Sweden.
X-ray fluorescence tomography (XFCT) has potential for high-resolution 3D molecular x-ray bio-imaging. In this
technique the fluorescence signal from targeted nanoparticles (NPs) is measured, providing information about the spatial
distribution and concentration of the NPs inside the object. However, present laboratory XFCT systems typically have
limited spatial resolution (>1 mm) and suffer from long scan times and high radiation dose even at high NP
concentrations, mainly due to low efficiency and poor signal-to-noise ratio.
We have developed a laboratory XFCT system with high spatial resolution (sub-100 μm), low NP concentration and
vastly decreased scan times and dose, opening up the possibilities for in-vivo small-animal imaging research. The system
consists of a high-brightness liquid-metal-jet microfocus x-ray source, x-ray focusing optics and an energy-resolving
photon-counting detector. By using the source’s characteristic 24 keV line-emission together with carefully matched
molybdenum nanoparticles the Compton background is greatly reduced, increasing the SNR. Each measurement
provides information about the spatial distribution and concentration of the Mo nanoparticles. A filtered back-projection
method is used to produce the final XFCT image.
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