PURPOSE: Previous studies have shown that the mean absorbed dose to a tissue element may not be a suitable quantity for correlating with the biological response of cells in that tissue element. Cell survival can depend strongly on the distribution of radioactivity at the cellular and multicellular levels. Furthermore, when cellular absorbed doses are examined, the cross-dose from neighbor cells can be less radiotoxic than the self-dose component. To better understand how the nonuniformity of activity among cells can affect the dose response, a computer model of a 3D tissue culture was previously constructed and showed that activity distribution among cells is significantly more relevant than the mean absorbed dose for low-energy-electron emitters. The present work greatly expands upon those findings. METHODS: In the present study, we used this same computer model but restricted the number of labeled cells to a fraction of the whole cell population (50%, 10%, and 1%, respectively). The labeled cells were randomly distributed among the whole cell population. RESULTS: While the activity distribution is an important factor in determining the tissue response for low-energy-electron emitters, the fraction of labeled cells has an even more pronounced effect on survival response. For all electron energies studied, reducing the percentage of cells labeled significantly increases the surviving fraction of the whole population. CONCLUSIONS: This study provides abundant information on killing tumor and normal cells under some conditions relevant to targeted radionuclide therapy of isolated tumor cells and micrometastases. The percentage of cells labeled, activity distribution among the labeled cells, and electron energy play key roles in determining their response. Most importantly, and not previously demonstrated, lognormal activity distributions can have a profound impact on the response of the tumor cells even when the radionuclide emits high-energy electrons.
PURPOSE: Previous studies have shown that the mean absorbed dose to a tissue element may not be a suitable quantity for correlating with the biological response of cells in that tissue element. Cell survival can depend strongly on the distribution of radioactivity at the cellular and multicellular levels. Furthermore, when cellular absorbed doses are examined, the cross-dose from neighbor cells can be less radiotoxic than the self-dose component. To better understand how the nonuniformity of activity among cells can affect the dose response, a computer model of a 3D tissue culture was previously constructed and showed that activity distribution among cells is significantly more relevant than the mean absorbed dose for low-energy-electron emitters. The present work greatly expands upon those findings. METHODS: In the present study, we used this same computer model but restricted the number of labeled cells to a fraction of the whole cell population (50%, 10%, and 1%, respectively). The labeled cells were randomly distributed among the whole cell population. RESULTS: While the activity distribution is an important factor in determining the tissue response for low-energy-electron emitters, the fraction of labeled cells has an even more pronounced effect on survival response. For all electron energies studied, reducing the percentage of cells labeled significantly increases the surviving fraction of the whole population. CONCLUSIONS: This study provides abundant information on killing tumor and normal cells under some conditions relevant to targeted radionuclide therapy of isolated tumor cells and micrometastases. The percentage of cells labeled, activity distribution among the labeled cells, and electron energy play key roles in determining their response. Most importantly, and not previously demonstrated, lognormal activity distributions can have a profound impact on the response of the tumor cells even when the radionuclide emits high-energy electrons.
Authors: Jay H Solanki; Thomas Tritt; Jordan B Pasternack; Julia J Kim; Calvin N Leung; Jason D Domogauer; Nicholas W Colangelo; Venkat R Narra; Roger W Howell Journal: Radiat Res Date: 2017-05-25 Impact factor: 2.841
Authors: Didier A Rajon; Brian S Canter; Calvin N Leung; Tom A Bäck; J Christopher Fritton; Edouard I Azzam; Roger W Howell Journal: Int J Radiat Biol Date: 2021-07-26 Impact factor: 3.352