Background and Aim: Phenotypic heterogeneity within bacterial populations, including heteroresistance, antibiotic tolerance, and persistence, can conceal rare antibiotic-nonsusceptible subpopulations from conventional antimicrobial susceptibility testing (AST). This review aimed to examine emerging approaches for detecting and quantifying these hidden subpopulations and to evaluate their potential clinical relevance. Materials and Methods: Recent studies indexed in the international databases PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, SpringerLink, Embase, and Google Scholar, as well as the Iranian databases SID, Magiran, and MedLib, with a focus on recent years were reviewed using combinations of the keywords heteroresistance, rare antibiotic-resistant subpopulations, antimicrobial susceptibility testing, single-cell analysis, and microfluidics. Evidence was synthesized from population-based, single-cell, microfluidic, imaging, and emerging phenotypic approaches.
Results: Population Analysis Profiling remains an important reference method for characterizing heteroresistance but is labor-intensive and poorly suited to routine diagnostics. Recent evidence supports higher-resolution approaches. The Dilution-and-Delay assay has demonstrated detection of antibiotic-insensitive cells at frequencies as low as 1 in 100 million while simultaneously providing conventional MIC measurements. Single-cell and droplet-microfluidic platforms can further resolve cell-to-cell susceptibility distributions and dynamic antibiotic responses, enabling characterization of rare phenotypes that may be masked at the population level. However, differences in analytical definitions, workflows, and clinical validation currently limit direct implementation. Conclusion: Next-generation AST integrating population-level measurements with single-cell and high-resolution phenotyping may improve detection of clinically relevant hidden subpopulations. Standardization, reproducibility, cost-effectiveness, and prospective clinical validation are essential before widespread adoption.