Partial-volume effect (PVE) is a significant issue in PET tumor imaging that can introduce large biases in tracer uptake measurements. PVE occurs due to two main factors: the finite spatial resolution of the imaging system, which causes blurring and spillover between regions, and image sampling, which leads to inaccuracies in signal intensity due to the discrete nature of voxel grids. These effects can lead to underestimation of tumor uptake, especially in small tumors, and can affect the interpretation of PET images in clinical settings. PVE has important implications for the monitoring of tumor response to therapy. Accurate measurement of tumor metabolism is crucial for determining the effectiveness of treatment, as changes in metabolic activity may occur before visible changes in tumor size. However, PVE can distort these measurements, leading to incorrect conclusions about the tumor's response to therapy. Several methods have been proposed to correct for PVE, including recovery coefficients (RC), geometric transfer matrices (GTM), and deconvolution techniques. These methods aim to improve the accuracy of PET measurements by accounting for the effects of PVE. However, the choice of correction method depends on various factors, including tumor size, shape, and surrounding tissues, as well as the spatial resolution and reconstruction parameters of the PET system. The practical impact of PVE correction is significant, as it can improve the accuracy of PET measurements and provide more reliable information for clinical decision-making. However, the implementation of PVE correction methods requires careful consideration of the imaging parameters and the specific characteristics of the tumor being studied. Despite the challenges associated with PVE correction, ongoing research is aimed at developing more effective and widely applicable methods to improve the accuracy of PET tumor imaging.Partial-volume effect (PVE) is a significant issue in PET tumor imaging that can introduce large biases in tracer uptake measurements. PVE occurs due to two main factors: the finite spatial resolution of the imaging system, which causes blurring and spillover between regions, and image sampling, which leads to inaccuracies in signal intensity due to the discrete nature of voxel grids. These effects can lead to underestimation of tumor uptake, especially in small tumors, and can affect the interpretation of PET images in clinical settings. PVE has important implications for the monitoring of tumor response to therapy. Accurate measurement of tumor metabolism is crucial for determining the effectiveness of treatment, as changes in metabolic activity may occur before visible changes in tumor size. However, PVE can distort these measurements, leading to incorrect conclusions about the tumor's response to therapy. Several methods have been proposed to correct for PVE, including recovery coefficients (RC), geometric transfer matrices (GTM), and deconvolution techniques. These methods aim to improve the accuracy of PET measurements by accounting for the effects of PVE. However, the choice of correction method depends on various factors, including tumor size, shape, and surrounding tissues, as well as the spatial resolution and reconstruction parameters of the PET system. The practical impact of PVE correction is significant, as it can improve the accuracy of PET measurements and provide more reliable information for clinical decision-making. However, the implementation of PVE correction methods requires careful consideration of the imaging parameters and the specific characteristics of the tumor being studied. Despite the challenges associated with PVE correction, ongoing research is aimed at developing more effective and widely applicable methods to improve the accuracy of PET tumor imaging.