scholarly journals Erratum: “Effective use of x rays in diagnostic radiology: Guidance for the optimization of image quality and absorbed dose in the patient by use of a Monte Carlo computational model of the imaging chain” [Med. Phys. 23, 177 (1996)]

1996 ◽  
Vol 23 (6) ◽  
pp. 985-985
Author(s):  
Michael Sandborg
1994 ◽  
Vol 42 (3) ◽  
pp. 167-180 ◽  
Author(s):  
Michael Sandborg ◽  
David R. Dance ◽  
Jan Persliden ◽  
Gudrun Alm Carlsson

2007 ◽  
Vol 555 ◽  
pp. 141-146 ◽  
Author(s):  
Srboljub J. Stanković ◽  
M. Petrović ◽  
M. Kovačević ◽  
A. Vasić ◽  
P. Osmokrović ◽  
...  

CdZnTe detectors have been employed in diagnostic X-ray spectroscopy. This paper presents the Monte Carlo calculation of X-ray deposited energy in a CdZnTe detector for different energies of photon beam. In incident photon direction, the distribution of absorbed dose as deposited energy in detector is determined. Based on the dependence of the detector response on the thickness and different Zn fractions, some conclusions about changes of the material characteristics could be drawn. Results of numerical simulation suggest that the CdZnTe detector could be suitable for X-ray low energy.


1999 ◽  
Vol 76 (4) ◽  
pp. 388-392 ◽  
Author(s):  
M. Alonso ◽  
T. Barriuso ◽  
M. J. Castañeda ◽  
N. Díaz-Caneja ◽  
I. Gutiérrez ◽  
...  

2021 ◽  
Author(s):  
Devin Miles ◽  
Ning Cao ◽  
George Sandison ◽  
Robert D Stewart ◽  
Greg Moffitt ◽  
...  

Purpose: Cancer cells produce innate immune signals following radiation damage, with STING pathway signaling as a critical mediator. High linear energy transfer (LET) radiations create larger numbers of DNA double-strand breaks (DSBs) per unit dose than low-LET radiations and may therefore be more immunogenic. We studied the dose response characteristics of pro-immunogenic type-I interferon, interferon-beta (IFNβ), and its reported suppressor signal, three-prime repair exonuclease 1 (TREX1), in vitro with low-LET x-rays and high-LET fast neutrons. Methods: Merkel cell carcinoma cells (MCC) were irradiated by graded doses of x-rays (1-24 Gy) or fast neutrons (1-8 Gy). IFNβ was measured as a function of dose via ELISA assay, and exonuclease TREX1 expression via immunofluorescence microscopy. The Monte Carlo damage simulation (MCDS) was used to model fast neutron relative biological effectiveness for DSB induction (RBEDSB) and compared to laboratory measurements of the RBE for IFNβ production (RBEIFNβ) and TREX1 upregulation (RBETREX1). RBEIFNβ models were also applied to radiation transport simulations to quantify the potential secretion of IFNβ in representative clinical beams. Results: Peak IFNβ secretion occurred at 5.7 Gy for fast neutrons and at 14.0 Gy for x-rays, i.e., an effective RBEIFNβ of 2.5 ± 0.2. The amplitude (peak value) of secreted IFNβ signal did not significantly differ between x-rays and fast neutrons (P > 0.05). TREX1 signal increased linearly with absorbed dose, with a four-fold higher upregulation per unit dose for fast neutrons relative to x-rays (RBETREX1 of 4.0 ± 0.1). Monte Carlo modeling of IFNβ suggests Bragg peak-to-entrance ratios of IFNβ production of 40, 100, and 120 for proton, alpha, and carbon ion beams, respectively, a factor of 10-20-fold higher compared to their corresponding physical dose peak-to-entrance ratios. The spatial width of the Bragg peak for IFNβ production is also a factor of two smaller. Conclusion: High-LET fast neutrons initiate a larger IFNβ response per unit absorbed dose than low-LET x-rays (i.e., RBEIFNβ value of 2.5). The RBE value for IFNβ is quite similar to data reported in the literature for DSB induction and cellular, post-irradiation micronucleation formation for neutrons and x-rays. The increased IFNβ release after high-LET radiation may be a contributing factor in stimulating a systemic anti-tumor, adaptive immune response (abscopal effect). However, our results indicate that TREX1 anti-inflammatory signaling in vitro for MCC cells is larger per unit dose for fast neutrons than for x-rays (RBETREX1 of 4.0). Given these competing effects, additional studies are needed to clarify whether or not high-LET radiations are therapeutically advantageous over low-LET radiation for pro-inflammatory immune signaling in other cell lines in vitro and for in vivo cancer models.


1997 ◽  
Vol 38 (6) ◽  
pp. 1010-1014
Author(s):  
J. Persliden ◽  
P. Larsson ◽  
B. Noren ◽  
S. Wirell
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Wong ◽  
Z. Q. Lin ◽  
L. Wang ◽  
A. G. Chung ◽  
B. Shen ◽  
...  

AbstractA critical step in effective care and treatment planning for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause for the coronavirus disease 2019 (COVID-19) pandemic, is the assessment of the severity of disease progression. Chest x-rays (CXRs) are often used to assess SARS-CoV-2 severity, with two important assessment metrics being extent of lung involvement and degree of opacity. In this proof-of-concept study, we assess the feasibility of computer-aided scoring of CXRs of SARS-CoV-2 lung disease severity using a deep learning system. Data consisted of 396 CXRs from SARS-CoV-2 positive patient cases. Geographic extent and opacity extent were scored by two board-certified expert chest radiologists (with 20+ years of experience) and a 2nd-year radiology resident. The deep neural networks used in this study, which we name COVID-Net S, are based on a COVID-Net network architecture. 100 versions of the network were independently learned (50 to perform geographic extent scoring and 50 to perform opacity extent scoring) using random subsets of CXRs from the study, and we evaluated the networks using stratified Monte Carlo cross-validation experiments. The COVID-Net S deep neural networks yielded R$$^2$$ 2 of $$0.664 \pm 0.032$$ 0.664 ± 0.032 and $$0.635 \pm 0.044$$ 0.635 ± 0.044 between predicted scores and radiologist scores for geographic extent and opacity extent, respectively, in stratified Monte Carlo cross-validation experiments. The best performing COVID-Net S networks achieved R$$^2$$ 2 of 0.739 and 0.741 between predicted scores and radiologist scores for geographic extent and opacity extent, respectively. The results are promising and suggest that the use of deep neural networks on CXRs could be an effective tool for computer-aided assessment of SARS-CoV-2 lung disease severity, although additional studies are needed before adoption for routine clinical use.


Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1889
Author(s):  
Arthur Bongrand ◽  
Charbel Koumeir ◽  
Daphnée Villoing ◽  
Arnaud Guertin ◽  
Ferid Haddad ◽  
...  

Proton therapy (PRT) is an irradiation technique that aims at limiting normal tissue damage while maintaining the tumor response. To study its specificities, the ARRONAX cyclotron is currently developing a preclinical structure compatible with biological experiments. A prerequisite is to identify and control uncertainties on the ARRONAX beamline, which can lead to significant biases in the observed biological results and dose–response relationships, as for any facility. This paper summarizes and quantifies the impact of uncertainty on proton range, absorbed dose, and dose homogeneity in a preclinical context of cell or small animal irradiation on the Bragg curve, using Monte Carlo simulations. All possible sources of uncertainty were investigated and discussed independently. Those with a significant impact were identified, and protocols were established to reduce their consequences. Overall, the uncertainties evaluated were similar to those from clinical practice and are considered compatible with the performance of radiobiological experiments, as well as the study of dose–response relationships on this proton beam. Another conclusion of this study is that Monte Carlo simulations can be used to help build preclinical lines in other setups.


Sign in / Sign up

Export Citation Format

Share Document