Validation of a comprehensive analytical model for photothermal therapy planning in a layered medium with gold nanoparticles

Erkol, Hakan; Yelken, S.Z.; Algarawi, Maha; Gülşen, Gültekin; Nouizi, Farouk

doi:10.1016/j.ijheatmasstransfer.2020.120438

Cited by 9 publications

(3 citation statements)

References 51 publications

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“…Four hot spots are observed under the irradiation sites by the lasers. Heat penetrates the phantom from these sites and propagates towards its center and decays in an exponential scheme [20]. Figure 1.b shows the temperature map obtained using a phantom bearing two inclusion positioned at (5 , 5) , (0 , -5) with radii of 2.25 mm and 1.75 mm.…”

Section: Ai-based a Priori Information Generation 231 Data Generationmentioning

confidence: 99%

Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks

Nouizi,

Shah,

Saraswatula

et al. 2024

Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences

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Photo-magnetic imaging (PMI) is a novel diffuse optical imaging technique used to recover high resolution images of the optical absorption coefficient of bio-tissue. It uses near-infrared laser light to slightly warm up the tissue and measures the induced temperature using magnetic resonance thermometry (MRT). The measured temperature maps are then converted into absorption maps using a dedicated PMI image reconstruction algorithm. We present a convolutional neural network -based image reconstruction algorithm that improves the accuracy of the recovered absorption maps while reducing the recovery time. This approach directly delineates the boundaries of tumors on the MRT maps. These boundaries are then used to generate soft a priori information that will be employed to constrain the standard PMI image reconstruction algorithm. We evaluate the performance of the algorithm using a tissue-like phantom with an inclusion representing the presence of a potential tumor. The obtained results show that our new method can delineate the tumor region with an accuracy of ~96%.

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Section: Ai-based a Priori Information Generation 231 Data Generationmentioning

confidence: 99%

Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks

Nouizi,

Shah,

Saraswatula

et al. 2024

Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences

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“…PTT is a treatment technique in which a laser, or light energy, is irradiated onto the affected area to kill tumor tissue by increasing the temperature. PTT has the advantage of not requiring an incision to perform the treatment, resulting in no bleeding and quick recovery [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of temperature behavior in biological tissue in photothermal therapy according to laser irradiation angle

Kim,

Kim

2023

Bioengineered

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The type of death of biological tissue varies with temperature and is broadly classified as apoptosis and necrosis. A new treatment called photothermal therapy is being studied on this basis. Photothermal therapy is a treatment technique based on photothermal effects and has the advantage of not requiring incisions and, therefore, no bleeding. In this study, a numerical analysis of photothermal therapy for squamous cell carcinoma was performed. Photothermal agents used were gold nanoparticles, and the photothermal therapy effect was confirmed by changing the angle of the laser irradiating the tumor tissue. The effectiveness of photothermal therapy was quantitatively assessed on the basis of three apoptotic variables. Further, the volume fraction of gold nanoparticles in the tumor tissue and laser intensity with optimal therapeutic effect for different laser irradiation angles were studied. Thus, the findings of this study can aid the practical implementation of photothermal therapy in the future.

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“…Hence, a customized thermal protocol should be developed to attain these parameters prior to the treatment throughout simulation studies [6]. These simulation studies are generally performed through the modeling of the spatiotemporal distribution of temperature-induced by tissue light absorption using the bio-heat equation [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Multi‐Wavelength Photo‐Magnetic Imaging System for Photothermal Therapy Guidance

et al. 2020

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Background and Objectives: In photothermal therapy, cancerous tissue is treated by the heat generated from absorbed light energy. For effective photothermal therapy, the parameters affecting the induced temperature should be determined before the treatment by modeling the increase in temperature via numerical simulations. However, accurate simulations can only be achieved when utilizing the accurate optical, thermal, and physiological properties of the treated tissue. Here, we propose a multiwavelength photo-magnetic imaging (PMI) technique that provides quantitative and spatially resolved tissue optical absorption maps at any wavelength within the nearinfrared (NIR) window to assist accurate photothermal therapy planning. Study Design/Materials and Methods: The study was conducted using our recently developed multi-wavelength PMI system, which operates at four laser wavelengths (760, 808, 860, and 980 nm). An agar tissue-simulating phantom containing water, lipid, and ink was illuminated using these wavelengths, and the slight internal laserinduced temperature rise was measured using magnetic resonance thermometry (MRT). The phantom optical absorption was recovered at the used wavelengths using our dedicated PMI image reconstruction algorithm. These absorption maps were then used to resolve the concentration of the tissue chromophores, and thus deduce its optical absorption spectrum in the NIR region based on the Beer-Lambert law. Results: The optical absorption of the phantom was successfully recovered at the used four wavelengths with an average error of~1.9%. The recovered absorption coefficient was then used to simulate temperature variations inside the phantom. A comparison between the modeled temperature maps and the MRT measured ones showed that these maps are in a good agreement with an average pseudo R 2 statistic of 0.992. These absorption values were used to successfully recover the concentration of the used chromophores. Finally, these concentrations are used to accurately calculate the total absorption spectrum of the phantom in the NIR spectral window with an average error as low as~2.3%. Conclusions:Multi-wavelength PMI demonstrated a great ability to assess the distribution of tissue chromophores, thus providing its total absorption at any wavelength within the NIR spectral range. Therefore, applications of photothermal therapy applied at NIR wavelengths can benefit from the absorption spectrum recovered by PMI to determine important parameters such as laser power as well as the laser exposure time needed to attain a specific increase in temperature prior to treatment. Lasers Surg. Med.

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Validation of a comprehensive analytical model for photothermal therapy planning in a layered medium with gold nanoparticles

Cited by 9 publications

References 51 publications

Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks

Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks

Analysis of temperature behavior in biological tissue in photothermal therapy according to laser irradiation angle

Multi‐Wavelength Photo‐Magnetic Imaging System for Photothermal Therapy Guidance

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