Groundbreaking research that could change the current imaging and mammogram paradigm has just been published in the imminent scientific publication, Nature.
The work focuses on improving breast cancer detection through a new method that analyzes surface temperature data, overcoming limitations seen in traditional mammography, especially in women with dense breast tissue where tumors are harder to detect.
Mammography, the standard screening method, struggles with sensitivity, particularly in dense breast tissue, leading to missed tumors and unnecessary biopsies.
The paper introduces the IRI-Numerical Engine, a tool that uses an inverse heat transfer approach based on bioheat transfer equations to analyze surface temperature variations caused by tumors, which are not affected by tissue density.
The study validates the IRI-Numerical Engine with twenty-three breast cancer patients, demonstrating its ability to accurately predict the presence, size, and location of tumors without being hindered by breast density. This method, which complements mammography, could significantly reduce the need for biopsies and the anxiety associated with false positives from screening.
Despite the relatively small sample size, the results are promising, showing accurate predictions for both the presence and absence of cancer, underscoring the potential of this technology as an adjunct to traditional screening methods.
The paper also reviews the limitations of current screening techniques, including mammography, ultrasound, and MRI, highlighting their struggles with sensitivity and specificity, particularly in dense breast tissue. It discusses the advancements in computer-aided diagnostics and the potential of various technologies to improve detection rates.
Furthermore, the work details the methodology behind the IRI-Numerical Engine, including patient-specific digital breast modeling, thermal simulations based on bioheat transfer equations, and an inverse heat transfer approach to detect tumors from surface temperature data.
The research suggests that this new method could play a crucial role in the future of breast cancer screening, offering a non-invasive, accurate alternative that could work alongside existing technologies to improve early detection rates, especially in patients with dense breast tissue.
However, it calls for larger scale clinical trials to further validate the effectiveness and reliability of this approach before it can be integrated into current screening protocols.
