Optimizing plasmonic photothermal therapy a numerical study on tissue specific thermal and optical properties for cancer treatment

Abstract

Effective cancer treatment demands precision to target malignant tissues while sparing healthy ones. This study investigates numerically the role of plasmonic photothermal therapy (PPTT) as a minimally invasive approach to achieve this goal, focusing on the interplay between nanoparticle (NP) size, resonance wavelength, and the thermal properties of biological tissues. Tailoring NP characteristics to align with tissue-specific optical and thermal properties enables precise thermal delivery, enhancing therapeutic efficacy while minimizing collateral damage. Resonance wavelength shifts with NP size, while tissue parameters like thermal conductivity and refractive index further influence temperature profiles. These findings highlight the importance of optimizing PPTT protocols through computational modeling and experimental validation. This approach advances personalized cancer therapies, offering safer and more effective treatment outcomes.

Fig. 1

Schematic distribution of nanoparticles.

Fig. 2

Heat maps of a 50-by-50 AuNP distribution. (a) 20 nm NPs, (b) 30 nm NPs, (c) 40 nm NPs, (d) 50 nm NPs.

Fig. 3

Temperature profile across a 50-by-50 AuNP distribution.

Fig. 4

Maximum temperature as a function of the height of the plane of measurement with respect to the plane of the AuNP distribution.

Fig. 5

Resonance wavelength with respect to the refractive indices of different tissue types for 4 different AuNP sizes. The vertical dashed lines represent the tissues’ indices of refraction.

Fig. 6

Maximum temperature as a function of thermal conductivity and refractive index for 6 cell types. 1-Bone Marrow (red and yellow), 2-Epidermis (skin), 3-Brain Gray Matter, 4-Subcutaneous Fat, 5-Blood Cancer (jurkat cells), 6-Cervical Cancer (HeLa cells).