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  • 1
    Online Resource
    Online Resource
    British Institute of Radiology ; 2020
    In:  The British Journal of Radiology Vol. 93, No. 1109 ( 2020-05-01), p. 20190625-
    In: The British Journal of Radiology, British Institute of Radiology, Vol. 93, No. 1109 ( 2020-05-01), p. 20190625-
    Abstract: Although various single genetic factors have been shown to affect radiosensitivity, high-throughput DNA sequencing analyses have revealed complex genomic landscapes in many cancer types. The aim of this study is to elucidate the association between accumulated alterations in driver and passenger genes and radiation therapy response. Methods: We used 59 human solid cancer cell lines derived from 11 organ sites. Radiation-induced cell death was measured using a standard colony-forming assay delivered as a single dose ranging from 0 to 12 Gy. Comprehensive genomic data for the cell lines were acquired from the Catalogue Of Somatic Mutations In Cancer v. 80. Random forest classifiers were constructed to predict radioresistant phenotypes using genomic features. The Cancer Genome Atlas data sets were used to evaluate the clinical impact of the genomic feature following radiotherapy. Results: The 59 cancer cell lines harbored either nucleotide variations or copy number variations in a median of 157 genes per cell. Radiosensitivity of the cancer cells was correlated with neither the number of driver gene mutations nor the number of passenger gene mutations. However, the proportion of driver gene alterations to total gene alterations in gene sets selected from the Kyoto Encyclopedia Genes and Genomes predicted radioresistant cells with sensitivity of 85% and specificity of 73%. High probability of radioresistance predicted by the model was associated with worse overall survival following definitive radiotherapy in patients of The Cancer Genome Atlas data sets. Conclusion: Cellular radiosensitivity was associated with the proportion of driver to total gene alterations in the selected oncogenic pathways, which may be a biomarker candidate for response to radiation therapy. Advances in knowledge: These findings suggest that accumulated alterations in not only driver genes but also passenger genes affect radiosensitivity.
    Type of Medium: Online Resource
    ISSN: 0007-1285 , 1748-880X
    RVK:
    Language: English
    Publisher: British Institute of Radiology
    Publication Date: 2020
    detail.hit.zdb_id: 1468548-6
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  • 2
    In: SpringerPlus, Springer Science and Business Media LLC, Vol. 4, No. 1 ( 2015-12)
    Type of Medium: Online Resource
    ISSN: 2193-1801
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2015
    detail.hit.zdb_id: 2661116-8
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  • 3
    In: Medical Physics, Wiley, Vol. 43, No. 6Part1 ( 2016-06), p. 3168-3177
    Abstract: During radiotherapy, maintaining the patient in a relaxed and comfortable state helps ensure respiratory regularity and reproducibility, thereby supports accurate respiratory tracking/gating treatment. Criteria to evaluate respiratory naturalness, regularity, and phase robustness are therefore needed to aid for the treatment system numerically and medical observers visually. This study introduces a new concept of respiratory tumor kinematics that describes the trajectory of tumor motion with respiration, leading to the minimum jerk theory. Using this theory, this study proposes novel respiratory criteria for respiratory naturalness, regularity, and phase robustness. Methods: According to respiratory tumor kinematics, tumor motion follows the minimum curvature/jerk trajectory in 4D spacetime. Using this theory, the following three respiratory criteria are proposed: (1) respiratory naturalness , the residual sum of the squared difference between the normalized average free respiratory wave (single inhalation/exhalation averaged over each 10 phases) and the normalized minimum jerk theoretical respiratory wave; (2) respiratory regularity , the cumulative jerk squared cost function sampling every 0.2 s with a peak adjustment coefficient, 16; and (3) respiratory phase robustness ( L Δ ), a second‐order partial differential in the respiratory position for regarded C j 16 as the respiratory position function. To verify these respiratory criteria, values obtained from CyberKnife tracking marker log data for 15 patients were compared with regard to the correlation error between the correlation model and the imaged tumor position, as well as with the number of remodels. The C j 16 growth curve was also compared between 15 patients and 15 healthy volunteers. Results: In the 15 patients, data with U s 〈 1 and C j 16 (60 s) 〈 10 000 satisfied average/maximum correlation errors of less than 1/3 mm. Data with higher U s values (less respiratory naturalness) and higher C j 16 (60 s) values (less respiratory regularity) demonstrated more than 3 mm average/5 mm maximum correlation errors and an increased number of remodels. The data for the 15 patients and 15 volunteers demonstrated that the C j 16 growth curve over 120 s from the start of sampling indicated patient‐specific respiratory trends and that the distribution of L Δ clearly showed the respiratory phase shift. In 22 of 30 subjects, the degree of change in the C j growth curve trends from 60 to 120 s was 22% ± 13% (average ± SD). In contrast, the residual data observed when C j 16 〉 1000 showed minimum and mean changes of 91% and 180%, respectively. Conclusions: The authors developed and verified novel respiratory criteria for respiratory naturalness, regularity, and phase robustness obtained using respiratory tumor kinematics and minimum jerk analysis. These criteria should be useful in monitoring respiratory trends on a real‐time basis during treatment, as well as in selecting optimal breathing for tracking/gating radiation treatment and defining numerical goals for respiratory training/gating.
    Type of Medium: Online Resource
    ISSN: 0094-2405 , 2473-4209
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 1466421-5
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  • 4
    In: International Journal of Radiation Oncology*Biology*Physics, Elsevier BV, Vol. 77, No. 3 ( 2010-07), p. 758-764
    Type of Medium: Online Resource
    ISSN: 0360-3016
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2010
    detail.hit.zdb_id: 1500486-7
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