A Real-time Breast Hyperthermia Monitoring Scheme Based on Processing of Microwave Scattering Parameters with Deep Learning

This study proposes a new method based on deep learning to determine whether the temperature values ​​are at an appropriate level during the use of microwave hyperthermia method in the treatment of breast cancer. To implement our method, we utilize the temperature dependent dielectric properties of biological tissues to generate the heating scenarios that simulates the thermal behavior of biological tissue during the breast cancer hyperthermia treatment. Using the temperature-dependent dielectric properties we designated corresponding temperature thresholds, next, we labeled the malignant tumor region and the healthy tissue region in accordance with the pre-determined thresholds. In addition, scattering problems are solved based on treatment (hot or heated) and pre-treatment (cool) scenarios. Using the difference between hot and cool states, we train, test, and validate the CNN. Our main purpose in the project is to determine whether the tissue is heated in the desired temperature region using only the single frequency differential scattered electric field data.

A Real-time Breast Hyperthermia Monitoring Scheme Based on Processing of Microwave Scattering Parameters with Deep Learning

This study proposes a new method based on deep learning to determine whether the temperature values ​​are at an appropriate level during the use of microwave hyperthermia method in the treatment of breast cancer. To implement our method, we utilize the temperature dependent dielectric properties of biological tissues to generate the heating scenarios that simulates the thermal behavior of biological tissue during the breast cancer hyperthermia treatment. Using the temperature-dependent dielectric properties we designated corresponding temperature thresholds, next, we labeled the malignant tumor region and the healthy tissue region in accordance with the pre-determined thresholds. In addition, scattering problems are solved based on treatment (hot or heated) and pre-treatment (cool) scenarios. Using the difference between hot and cool states, we train, test, and validate the CNN. Our main purpose in the project is to determine whether the tissue is heated in the desired temperature region using only the single frequency differential scattered electric field data.

Heat Transfer in Biological Spherical Tissues during Hyperthermia of Magnetoma

Hyperthermia therapy is now being used to treat cancer. However, understanding the pattern of temperature increase in biological tissues during hyperthermia treatment is essential. In recent years, many physicians and engineers have studied the use of computational and mathematical models of heat transfer in biological systems. The rapid progress in computing technology has intrigued many researchers. Many medical procedures also use engineering techniques and mathematical modeling to ensure their safety and assess the risks involved. One such model is the modified Pennes bioheat conduction equation. This paper provides an analytical solution to the modified Pennes bioheat conduction equation with a single relaxation time by incorporating in it the (MGT) equation. The suggested model examines heat transport in biological tissues as forming an infinite concentric spherical region during magnetic fluid hyperthermia. To investigate thermal reactions caused by temperature shock, specifically the influence of heat generation through heat treatment on a skin tumor [AEGP9], the Laplace transformation, and numerical inverse transformation methods are used. This model was able to explain the effects of different therapeutic approaches such as cryotherapy sessions, laser therapy, and physical occurrences, transfer, metabolism support, and blood perfusion. Comparison of the numerical results of the suggested model with those in the literature confirmed the validity of the model’s numerical results.

Carbon nano-dot for cancer studies as dual nano-sensor for imaging intracellular temperature or pH variation

Cellular temperature and pH govern many cellular physiologies, especially of cancer cells. Besides, attaining higher cellular temperature plays key role in therapeutic efficacy of hyperthermia treatment of cancer. This requires bio-compatible, non-toxic and sensitive probe with dual sensing ability to detect temperature and pH variations. In this regard, fluorescence based nano-sensors for cancer studies play an important role. Therefore, a facile green synthesis of orange carbon nano-dots (CND) with high quantum yield of 90% was achieved and its application as dual nano-sensor for imaging intracellular temperature and pH was explored. CND was synthesized from readily available, bio-compatible citric acid and rhodamine 6G hydrazide using solvent-free and simple heating technique requiring purification by dialysis. Although the particle size of 19 nm (which is quite large for CND) was observed yet CND exhibits no surface defects leading to decrease in photoluminescence (PL). On the contrary, very high fluorescence was observed along with good photo-stability. Temperature and pH dependent fluorescence studies show linearity in fluorescence intensity which was replicated in breast cancer cells. In addition, molecular nature of PL of CND was established using pH dependent fluorescence study. Together, the current investigation showed synthesis of highly fluorescent orange CND, which acts as a sensitive bio-imaging probe: an optical nano-thermal or nano-pH sensor for cancer-related studies.

Dual Targeting of Cancer Cells and MMPs with Self-Assembly Hybrid Nanoparticles for Combination Therapy in Combating Cancer

The co-delivery of chemotherapeutic agents and immune modulators to their targets remains to be a great challenge for nanocarriers. Here, we developed a hybrid thermosensitive nanoparticle (TMNP) which could co-deliver paclitaxel-loaded transferrin (PTX@TF) and marimastat-loaded thermosensitive liposomes (MMST/LTSLs) for the dual targeting of cancer cells and the microenvironment. TMNPs could rapidly release the two payloads triggered by the hyperthermia treatment at the site of tumor. The released PTX@TF entered cancer cells via transferrin-receptor-mediated endocytosis and inhibited the survival of tumor cells. MMST was intelligently employed as an immunomodulator to improve immunotherapy by inhibiting matrix metalloproteinases to reduce chemokine degradation and recruit T cells. The TMNPs promoted the tumor infiltration of CD3+ T cells by 2-fold, including memory/effector CD8+ T cells (4.2-fold) and CD4+ (1.7-fold), but not regulatory T cells. Our in vivo anti-tumor experiment suggested that TMNPs possessed the highest tumor growth inhibitory rate (80.86%) compared with the control group. We demonstrated that the nanoplatform could effectively inhibit the growth of tumors and enhance T cell recruitment through the co-delivery of paclitaxel and marimastat, which could be a promising strategy for the combination of chemotherapy and immunotherapy for cancer treatment.