Internal dosimetry using data derived from autoradiographs. Academic Article uri icon

Overview

abstract

  • Cancer therapies based on administered radionuclides require accurate information on tumor dose. One of the major factors influencing the distribution of absorbed-dose characteristics is the uniformity of the radiolabel distribution in tissue. To study the effect of nonuniformities, we used image analysis techniques to measure automatically the coordinates of autoradiographic grains (sources) and cell nuclei in cut sections from three different tumors, following treatment with radiolabeled antibodies. The spatial distribution data of sources and cell nuclei from these tumor sections were assessed and the pattern of energy deposition in the cell nuclei calculated, assuming that each autoradiograph grain corresponded to a source of the alpha emitter astatine-211 (211At) or the beta emitter yttrium-90 (90Y). The distribution of deposited energy obtained for the real grain distributions was compared to the distribution assuming a locally uniform source distribution, i.e., simulating grain count averaging as produced by a microdensitometric method within a 100 x 100 microns 2 frame size (frame averaging), and a uniform distribution across the entire section (section averaging). The results show first that when the grain distribution is uniform, the average dose within the section is an adequate estimate of the dose to the cell nuclei. Second, when the grain distribution is nonuniform, the distribution of doses to the cell nuclei is significantly less when calculations use the measured grain coordinates, or frame averaging, than when section averaging is used. Third, when the sources are located on or in the cells, both frame and section averaging produce underestimates of the dose to the cell nuclei.

publication date

  • October 1, 1993

Research

keywords

  • Autoradiography
  • Radioimmunotherapy
  • Radiometry

Identity

Scopus Document Identifier

  • 0027437696

PubMed ID

  • 8410302

Additional Document Info

volume

  • 34

issue

  • 10