Application of Photoshop-based Image Analysis to Quantification of Hormone Receptor Expression in Breast Cancer
Overview
Authors
Affiliations
The benefit of quantifying estrogen receptor (ER) and progesterone receptor (PR) expression in breast cancer is well established. However, in routine breast cancer diagnosis, receptor expression is often quantified in arbitrary scores with high inter- and intraobserver variability. In this study we tested the validity of an image analysis system employing inexpensive, commercially available computer software on a personal computer. In a series of 28 invasive ductal breast cancers, immunohistochemical determinations of ER and PR were performed, along with biochemical analyses on fresh tumor homogenates, by the dextran-coated charcoal technique (DCC) and by enzyme immunoassay (EIA). From each immunohistochemical slide, three representative tumor fields (x20 objective) were captured and digitized with a Macintosh personal computer. Using the tools of Photoshop software, optical density plots of tumor cell nuclei were generated and, after background subtraction, were used as an index of immunostaining intensity. This immunostaining index showed a strong semilogarithmic correlation with biochemical receptor assessments of ER (DCC, r = 0.70, p < 0.001; EIA, r = 0.76, p < 0.001) and even better of PR (DCC, r = 0.86; p < 0.01; EIA, r = 0.80, p < 0.001). A strong linear correlation of ER and PR quantification was also seen between DCC and EIA techniques (ER, r = 0.62, p < 0.001; PR, r = 0.92, p < 0.001). This study demonstrates that a simple, inexpensive, commercially available software program can be accurately applied to the quantification of immunohistochemical hormone receptor studies.
Characterization of an Estrogen Receptor α-Selective F-Estradiol PET Tracer.
Sluka P, Ackermann U, Rigopoulos A, Wardan H, Pezaro C, Burvenich I World J Nucl Med. 2024; 23(3):153-160.
PMID: 39170834 PMC: 11335392. DOI: 10.1055/s-0044-1786518.
Sireci F, Lorusso F, Dispenza F, Immordino A, Gallina S, Salvago P J Pers Med. 2023; 13(8).
PMID: 37623462 PMC: 10455511. DOI: 10.3390/jpm13081211.
An integrated framework for quantifying immune-tumour interactions in a 3D co-culture model.
Al-Hity G, Yang F, Campillo-Funollet E, Greenstein A, Hunt H, Mampay M Commun Biol. 2021; 4(1):781.
PMID: 34168276 PMC: 8225809. DOI: 10.1038/s42003-021-02296-7.
Chu A, Kok S, Tsui J, Lin M, Aguirre B, Wadehra M J Reprod Immunol. 2021; 145:103309.
PMID: 33774530 PMC: 8722772. DOI: 10.1016/j.jri.2021.103309.
Ilic I, Stojanovic N, Radulovic N, Zivkovic V, Randjelovic P, Petrovic A Medicina (Kaunas). 2019; 55(8).
PMID: 31405154 PMC: 6722798. DOI: 10.3390/medicina55080461.