Estimation of the spatial distribution of target cells for radiation pneumonitis in mouse lung

Tucker, Susan L.; Liao, Z.; Travis, Elizabeth L.

doi:10.1016/s0360-3016(97)00131-4

Cited by 60 publications

(31 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Inactivation probability (p ) for FSUs at different doses for different regions of the lung assuming homogeneous FSU density distribution (left axis), compared to the FSU density distribution assuming uniform FSU radiosensitivity (right axis), both based on elevated breathing rate data. general agreement with the conclusions of Tucker et al [13]. However, this distribution does not show a pronounced increase in the number of FSUs in the lung base compared to the lung apex, and cannot explain the larger amount of damage caused by base irradiation compared to apex irradiation.…”

Section: Discussionsupporting

confidence: 91%

“…Tucker et al [13] have argued that target cells located in certain anatomical regions of the lung may possess different radiation sensitivity, and spatial variation in FSU radiation sensitivity can thus not be ruled out as a contributing factor to our observations. In our first calculations, the parameters K and D 0 were fitted to the 100% subvolume data, which include both apical and basal cells/FSUs, and p (K ,D 0 ) then represents an effective value of the FSU inactivation probability.…”

Section: Discussionmentioning

confidence: 66%

“…Tucker et al [13] used the lethality data [11,12] to estimate the spatial distribution of target cells. In their analysis, all target cells were assumed to have the same radiosensitivity.…”

Section: Fsu Inactivation Modelmentioning

confidence: 99%

“…For the basal subvolumes the number of FSUs is displayed as a function of the respective subvolumes (v base ), while for the apical subvolumes the plotted values are N (/n apex as a function of v 0/100% (/v apex , where N 0/100. The results of the four data sets, as described in Table I, are shown together with the target-cell distribution obtained by Tucker et al [13] and a uniform (linear) distribution for comparison. Tucker's distribution seemed to agree better with our obtained distributions for the elevated breathing rate data than with the lethality distributions (Figure 3), although Tucker's distribution was derived from the lethality data.…”

Section: Fsu Distributionmentioning

confidence: 99%

“…Cumulative number of target cells or FSUs as a function of v% subvolume measured from the lung base, FSU inactivation probability assumed independent of localization. Data (elBR0/elevated breathing rate data, dead0/lethality data) are derived from Tucker's estimates [13] and from Table I (our optimizations assuming N0/100), with basal data plotted as n base (v base ) and apical data plotted as 100-n apex as a function of v0/100%-v apex . Subvolumes with no observed complications are excluded from this figure.…”

Section: Spatial Distribution Of Pmentioning

confidence: 99%

See 4 more Smart Citations

Analysis of normal tissue complication probability of the lung using a reliability model

Vågane

Olsen

2006

Acta Oncologica

View full text Add to dashboard Cite

Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 66%

“…Tucker et al [13] used the lethality data [11,12] to estimate the spatial distribution of target cells. In their analysis, all target cells were assumed to have the same radiosensitivity.…”

Section: Fsu Inactivation Modelmentioning

confidence: 99%

Section: Fsu Distributionmentioning

confidence: 99%

Section: Spatial Distribution Of Pmentioning

confidence: 99%

See 3 more Smart Citations

Analysis of normal tissue complication probability of the lung using a reliability model

Vågane

Olsen

2006

Acta Oncologica

View full text Add to dashboard Cite

Computed tomographic evaluation of radiation pneumonitis in a canine model

Forrest

Mahler

Vail

et al. 1998

Radiat. Oncol. Investig.

View full text Add to dashboard Cite

The objective of this study was to document the utility of computed tomography (CT) and a three‐dimensional (3‐D) radiotherapy treatment planning system for assessing the development of acute radiation pneumonitis in a canine model. Fourteen dogs were randomly assigned to a nonirradiated control group or one of three radiation dose groups receiving a single fraction of either 12, 15, or 18 Gy delivered to two‐thirds of the right hemithorax. CT and survey radiographs were performed in all dogs prior to and at defined intervals for up to 13 weeks following irradiation. All images were subjectively evaluated for development of radiation pneumonitis and CT images were quantitatively analyzed. Radiation pneumonitis was detected earlier with CT images than with radiographs. Quantitatively, functional lung volume and radiation pneumonitis lesion volume on CT images changed over time in all irradiated dogs. However, there was no statistically significant difference between the three radiation dose groups, but a marked difference between irradiated dogs and nonirradiated controls. These data suggest that CT is superior to survey radiography for the evaluation and quantification of acute radiation pneumonitis in this canine model. Quantification of acute radiation pneumonitis suggests future promise for evaluating the efficacy of modifiers to lessen the effects of irradiating normal lung tissue in this canine model. Radiat. Oncol. Invest. 6:128–134, 1998. © 1998 Wiley‐Liss, Inc.

show abstract

Prevention and treatment of radiotherapy‐induced side effects

2020

View full text Add to dashboard Cite

Radiotherapy remains a mainstay of cancer treatment, being used in roughly 50% of patients. The precision with which the radiation dose can be delivered is rapidly improving. This precision allows the more accurate targeting of radiation dose to the tumor and reduces the amount of surrounding normal tissue exposed. Although this often reduces the unwanted side effects of radiotherapy, we still need to further improve patients' quality of life and to escalate radiation doses to tumors when necessary. Highprecision radiotherapy forces one to choose which organ or functional organ substructures should be spared. To be able to make such choices, we urgently need to better understand the molecular and physiological mechanisms of normal tissue responses to radiotherapy. Currently, oversimplified approaches using constraints on mean doses, and irradiated volumes of normal tissues are used to plan treatments with minimized risk of radiation side effects. In this review, we discuss the responses of three different normal tissues to radiotherapy: the salivary glands, cardiopulmonary system, and brain. We show that although they may share very similar local cellular processes, they respond very differently through organ-specific, nonlocal mechanisms. We also discuss how a better knowledge of these mechanisms can be used to treat or to prevent the effects of radiotherapy on normal tissue and to optimize radiotherapy delivery.

show abstract

Estimation of the spatial distribution of target cells for radiation pneumonitis in mouse lung

Cited by 60 publications

References 43 publications

Analysis of normal tissue complication probability of the lung using a reliability model

Analysis of normal tissue complication probability of the lung using a reliability model

Computed tomographic evaluation of radiation pneumonitis in a canine model

Prevention and treatment of radiotherapy‐induced side effects

Contact Info

Product

Resources

About