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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月23日

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  • Omar Eladarousy,
  • Zahraa Zibara,
  • Khaled Hussari,
  • Nissrine Al Helou,
  • Rana Nicolas

摘要

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.