Speculum-Free Biomaterials, Multi-omics Liquid Biopsy, and AI-Driven Theranostic Imaging for Ovarian Cancer Detection

Ovarian cancer (OC) contributes to higher rates of fatalities among women affected by cancer. One of the main factors contributing to these deaths is that there are not many reliable ways to screen for OC at an earlier point in time. Existing forms of testing (such as CA125 blood tests and transvaginal ultrasound) are not sensitive or specific enough to detect OC in its earliest stages. Thus, there is a great need for alternative ways to find OC before it spreads to the point where it is more difficult to treat. This review describes some of the biomaterial-based imaging that is made from nanostructured and functional materials and diagnostic methods that can be used to detect OC earlier. The reason for investigating these potential imaging contrast agents is that they all have unique optical, magnetic, and electronic properties that allow for a wide range of imaging applications when properly coupled with tumor-targeting ligands, antibodies, or aptamers. Depending on which of these substances are used to target tumors, the use of these materials will have a large effect on the ability of various imaging modalities aided by nanoparticles, allowing for the controlled delivery of molecular contrast agents and imaging probes for real-time imaging of microenvironmental changes and tumor-associated biomarkers. Advances in microfluidic systems and lab-on-chip technologies that integrate biomaterials enable the detection of exosomal biomarkers, circulating tumor DNA, and epigenetic signatures from minimally invasive liquid biopsies. The use of artificial intelligence in the analysis of imaging data, specifically deep learning methods applied to the interpretation of radiomic imaging patterns and transvaginal ultrasonography, significantly increases the accuracy of diagnosing adnexal masses and risk stratification. These interdisciplinary approaches hold great promise for the identification of OC at its earliest stages and improving patient prognosis and clinical outcomes.