# Microwave technologies for biomedical diagnosis and therapy: advances, challenges, and perspectives

## TL;DR

Microwave technologies are being explored for biomedical uses like diagnosis and therapy due to their safety and sensitivity, though challenges remain in making them widely applicable.

## Contribution

This review integrates biophysical foundations with recent advances in microwave biosensing, imaging, and therapy, highlighting novel trends like AI and wearable platforms.

## Key findings

- Microwave systems offer non-ionizing, sensitive methods for detecting biomarkers and assessing tissues.
- Emerging trends like AI-driven interpretation and microfluidics are enhancing microwave sensing and therapy capabilities.
- Current barriers include dielectric model variability and limited in vivo validation, which hinder clinical translation.

## Abstract

Microwave technologies have emerged as powerful tools for biomedical diagnosis and therapy due to their non-ionizing nature, sensitivity to dielectric changes, and compatibility with compact, low-cost systems. This review provides a unified perspective that integrates the biophysical foundations of dielectric characterization with advances in biosensing, imaging, and therapeutic microwave platforms. A systematic examination of the primary material characterization techniques—non-resonant, transmission-line resonant, and metamaterial-based methods—highlights how their frequency-dependent interactions with biological media underpin molecular, cellular, and tissue-level sensing. We synthesize recent progress in microstrip and resonant biosensors for detecting biochemical, metabolic, oncological, and pathogenic biomarkers, alongside developments in microwave imaging for functional tissue assessment and energy-based therapies such as hyperthermia and ablation. This integrated framework clarifies how the methodological diversity of microwave systems supports increasingly specialized biomedical applications. Despite their promise, current microwave technologies face several barriers to clinical translation, including variability in dielectric models, calibration and reproducibility challenges, spatial-resolution constraints, and limited in vivo validation. Addressing these limitations requires advancing beyond traditional architectures. Accordingly, this review also consolidates emerging trends in microfluidics, wearable and implantable platforms, artificial intelligence (AI)-driven signal interpretation, and multimodal integration, illustrating how these capabilities enhance sensing performance, enable adaptive therapy monitoring, and advance microwave systems toward personalized theranostic applications. By articulating the interplay between methods, capabilities, and unresolved challenges, a comprehensive and timely roadmap is offered that distinguishes microwave technologies from conventional diagnostic modalities and underscores their unique potential in next-generation biomedical engineering.