Purpose: To estimate, from experimental data, the retreatment radiation 'tolerances' of the spinal cord at different times after initial treatment.
Materials And Methods: A model was developed to show the relationship between the biological effective doses (BEDs) for two separate courses of treatment with the BED of each course being expressed as a percentage of the designated 'retreatment tolerance' BED value, denoted [Formula: see text] and [Formula: see text]. The primate data of Ang et al. ( 2001 ) were used to determine the fitted parameters. However, based on rodent data, recovery was assumed to commence 70 days after the first course was complete, and with a non-linear relationship to the magnitude of the initial BED (BED).
Results: The model, taking into account the above processes, provides estimates of the retreatment tolerance dose after different times. Extrapolations from the experimental data can provide conservative estimates for the clinic, with a lower acceptable myelopathy incidence. Care must be taken to convert the predicted [Formula: see text] value into a formal BED value and then a practical dose fractionation schedule.
Conclusions: Used with caution, the proposed model allows estimations of retreatment doses with elapsed times ranging from 70 days up to three years after the initial course of treatment.
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http://dx.doi.org/10.1080/09553002.2018.1430911 | DOI Listing |
Sci Rep
December 2024
Radiating Systems Group, Department of Applied Physics, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain.
The following paper presents the findings of a study conducted on the distances at which the field generated by a ϕ-symmetric circular Taylor aperture distribution can be classified as far-field, and also the efficiency across various study parameters. The [Formula: see text] transition integers that produce a monotonic distribution, which have been traditionally used and analyzed, are compared with those that yield a peaked distribution, and offer greater efficiency. Additionally, modified circular Taylor [Formula: see text] distributions featuring synthesized patterns with one or two depressed inner sidelobes, which have not been previously explored, are also examined.
View Article and Find Full Text PDFAnn Surg Oncol
December 2024
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
Background: We sought to define whether and how hepatic ischemia/reperfusion (I/R) as manifested by perioperative aspartate aminotransferase (AST) and alanine aminotransaminase (ALT) levels impact long-term outcomes after curative-intent resection of hepatocellular carcinoma (HCC).
Patients And Methods: Intrasplenic injection of HCC cells was used to establish a murine model of HCC recurrence with versus without I/R injury. Patients who underwent curative resection for HCC were identified from a multi-institutional derivative cohort (DC) and separate external validation (VC) cohort.
Sci Rep
December 2024
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
This study explores the problem of train scheduling (or) train timetabling and its impact on the administration of railway management. This is a highly dependable and effective public transportation system. The problem considers both single and multiple tracks along with multiple platforms with varying train capacities (like speed, passengers, and so on).
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December 2024
Department of Mathematics, Faculty of Science, The Hashemite University, P.O.Box 330127, Zarqa, 13133, Jordan.
In this study, we developed a Caputo-Fractional Chlamydia pandemic model to describe the disease's spread. We demonstrated the model's positivity and boundedness, ensuring biological relevance. The existence and uniqueness of the model's solution were established, and we investigated the stability of the α-fractional order model.
View Article and Find Full Text PDFSci Rep
December 2024
ETH Zurich, Zurich, Switzerland.
Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remains opaque. This makes it difficult for humans to validate a prediction made by AI against their own domain knowledge.
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