Microwave breast imaging: A review of clinical potential and technological advances

Table 6 Summary of clinical evaluation of microwave breast imaging systems

Application	Description	Advantages	Challenges/limitations	Ref.
Primary breast cancer detection	Detects malignant tumors based on dielectric contrast	Non-ionizing, safe, repeatable; good for dense breasts	Low spatial resolution; noise sensitivity	[54,55]
Differentiating benign vs malignant lesions	Uses dielectric differences for classification	Good contrast between tissues; non-invasive	Needs clinical validation	[56]
Post-treatment monitoring	Tracks tissue changes after surgery or radiation	Can detect permittivity changes over time	Limited scans at longer follow-ups	[57]
Lesion size and localization	Assesses size/location in real-time	Complements mammography where sensitivity is limited	Dense breasts can obscure signals	[58]
Lymph node metastasis detection	Detects axillary lymph nodes using radar MWI	Helps with TNM staging; reduces unnecessary surgeries	Difficult with overlapping tissues	[59]
Breast tissue classification with ML	Uses AI/ML to classify lesion-containing vs healthy scans	Improves sensitivity; useful for screening	Signal variability; system training needs	[60,61]
Early detection in dense breasts	MBI outperforms mammography in dense tissues	No compression, non-ionizing, suitable for frequent use	Still requires more data from large trials	[62]
Adjunct to conventional imaging	Used in combination with ultrasound/MRI	Improves diagnostic confidence	Requires data integration methods	[56,63]
ML-based diagnostic models	CNNs and U-Nets used for tumor classification & segmentation	Enhances accuracy and image reconstruction	Needs diverse, well-annotated datasets	[64,65]
Detection of treatment-related changes	Tracks dielectric changes post-radiotherapy	Shows significant permittivity differences	Limited follow-up data	[57]
Clinical feasibility of portable systems	Portable devices tested for in-clinic use	Cost-effective, accessible, repeatable	Small patient numbers so far	[66]
Synthetic breast phantoms and simulations	Used to validate algorithms and device configurations	Allows modeling of dielectric variability	Phantom data may not generalize to real breasts	[67,68]
Contrast-agent enhanced MWI	Use of nanoparticles (e.g., ZnO) for dielectric contrast	Enhances visibility of tumors	Needs further safety studies	[69]

MBI: Microwave breast imaging; MWI: Microwave imaging; TNM: Tumor-node-metastasis staging system; ML: Machine learning; AI: Artificial Intelligence; CNN: Convolutional neural network; UWB: Ultra-wideband; ZnO: Zinc oxide.