Radiotherapy cancer treatment modeling with fractional or ordinary derivative

This short communication presents two versions of the cancer treatment model, the ordinary derivative version and the fractional derivative version. The two models were used to simulate a cancer treatment process of a cancer patient with an initial tumor volume of 28.4 cm3 . The simulated final volumes produced by the fractional derivative version were 28.17 cm3 and 5.68 cm3 the normal cells and tumor respectively, while those of the ordinary derivative version were 16.97 cm3 and 0.0 cm3 . In addition, the fractional derivative version was used to simulate a no-treatment process with an initial tumor volume of 5 cm3 , and the final volumes were 4.91 cm3 and 17.41 cm3 for the normal cells and tumor respectively. It was concluded that the radiotherapy treatment process was better simulated with the fractional derivative model.

2018 ◽  
Vol 133 (3) ◽  
Author(s):  
Mustafa Ali Dokuyucu ◽  
Ercan Celik ◽  
Hasan Bulut ◽  
Haci Mehmet Baskonus

2020 ◽  
Vol 49 (11) ◽  
pp. 2833-2846
Author(s):  
Musiliu Folarin Farayola ◽  
Sharidan Shafie ◽  
Fuaada Mohd Siam

2019 ◽  
Vol 1 (2) ◽  
pp. 51-54
Author(s):  
Musiliu Folarin Farayola ◽  
Sharidan Shafie ◽  
Fuaada Mohd Siam

The use of the improved cancer treatment model predicted the population changes in the normal and cancer cells during radiotherapy. The simulated radiation doses are 15 Gy, 18 Gy, 20 Gy and 24 Gy administered 5 times for each dose. The population of the cancer cells reduced from 40 % of the carrying capacity to 10.72%, 23.25 %, 1.61 % and 3.72 % of the carrying capacity for the respective doses. The population of the normal cells reduced from 70% of the carrying capacity to 65.50%, 62.48%, 68.49% and 67.59% of the carrying capacity for the respective doses. During the no treatment stage (0 Gy), the model predicted an increase in the population of cancer cells and a decrease in the population of normal cells.


2021 ◽  
pp. 39-43
Author(s):  
Yadav Ambica ◽  
Tandon Anupama

Objective:To evaluate inuence of volumetric tumor doubling time on survival of patients with intracranial tumors. Study design: 20 patients with intracranial tumor of either sex and any age were included, if two imaging scans were available/could be done in which change in tomor volume was appreciable and the tumor margins were well demarcated. Based on change in tumor volume, tumor doubling time (DT) and predictive survival time (PST) were calculated. Patients were followed up for 6 months or longer for actual survival time (AST). Results: The histological grade was found to have a signicant correlation with DT (P value 0.046) and PST of the tumor (P value 0.038). DT and PSTwere found to be signicantly lower in high grade astrocytomas. Age, gender, tumor location and initial tumor volume were not found to have a signicant correlation with DTand PST. When DTwas compared to PST, excellent correlation was seen which was statistically signicant (Pvalue < 0.001) and suggested a linear relationship. Conclusion: Computed Tomography (CT) & Magnetic Resonance Imaging (MRI) can accurately dene the intracranial tumors and can reliably measure their volume. Calculation of tumor volume, change in tumor volume, DT and PST based on imaging studies is easy and reproducible. DT and PST have an excellent correlation & there is a linear relationship between the two. Histological grade and DT are the signicant prognostic factors while age, gender, tumor location and initial tumor volume are not signicant prognostic factors in patients with brain tumors.


2013 ◽  
Vol 4 (1) ◽  
pp. 5-8 ◽  
Author(s):  
Paul Zarogoulidis ◽  
Georgia Trakada ◽  
Konstantinos Zarogoulidis

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