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. 2006;70(6):403-10.
doi: 10.1159/000098812. Epub 2007 Jan 18.

Determination and prediction of P-glycoprotein and multidrug-resistance-related protein expression in breast cancer with double-phase technetium-99m sestamibi scintimammography. Visual and quantitative analyses

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Determination and prediction of P-glycoprotein and multidrug-resistance-related protein expression in breast cancer with double-phase technetium-99m sestamibi scintimammography. Visual and quantitative analyses

In-Ju Kim et al. Oncology. 2006.

Abstract

Purpose: To determine and predict P-glycoprotein (Pgp) and multidrug-resistance-related protein (MRP) expression in untreated breast cancer patients by visual and quantitative indices of double-phase (99m)Tc MIBI scintimammography (DSMM).

Patients and methods: Eighty-two patients with untreated breast cancer received DSMM. Pgp and MRP expression was assessed by immunohistochemical (IHC) staining of surgical specimens. Visual and quantitative analyses were compared with the results of IHC to determine and predict Pgp and MRP.

Results: The early and delayed tumor to normal tissue ratio (T/N) of the Pgp-negative and MRP-negative group had significantly higher values than those of the Pgp-positive and MRP-positive group. However, there were no statistically significant differences in washout rate (WR, in %) according to the expression of Pgp and MRP. The optimal T/N ratios were <or =2.23 for early and < or =1.75 for delayed image for Pgp expression and < or =2.45 for early and < or =1.96 for delayed image for MRP expression. The optimal visual grades of DSMM for the determination of Pgp and MRP expression were < or =3. With logistic regression analysis, potent predictors of DSMM were visual assessment for Pgp expression and early T/N for MRP expression.

Conclusion: In conclusion, despite a moderate sensitivity and specificity, visual and quantitative indices of DSMM could be used to determine and predict Pgp and MRP expression in untreated breast cancer. However, these findings need confirmation in a larger patient cohort to enable a better validation of Pgp and MRP expression to determine optimal early and delayed T/Ns and to investigate predictors of Pgp and MRP expression in breast cancer.

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