Estimation of the optimum number and location of nanoparticle injections and the specific loss power for ideal hyperthermia

Boroon, Mostafa Pasandi; Ayani, Mohammad Bagher; Bazaz, Sajad Razavi

doi:10.1016/j.jtherbio.2018.01.010

Cited by 14 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It should be noted from this figure that the temperature profile is more uniform with two injections (figure 5(b) in comparison to a single injection (figure 5(a))). The temperature profile aligns with the expected temperature profile using single and multi-injection strategies [21,[23][24][25]. The temperature is higher near the injection location and lowers as one approaches the tumor boundary [11,13,19,21,36,58].…”

Section: Spatial Temperature Profile In Tumor Modelssupporting

confidence: 68%

“…Previous works [21,[23][24][25][26][27] have shown that multi-injection increases the MNP distribution region in the tumor as well as thermally affected tumor volume. Salloum et al [24] utilized the Nelder-Mead (NM) optimization algorithm to identify the optimal heat source and its distribution around the injection sites (peak strength of SAR (specific absorption rate) and its Gaussian spread).…”

Section: Introductionmentioning

confidence: 98%

“…Therefore, the geometrical irregularities associated with the tumor increase the complexity of devising a suitable intratumoral injection protocol for MNPH. To address these challenges, researchers have explored multiple methods to enhance the effectiveness of MNPH, including employing a multi-injection strategy for MNP delivery and utilizing power modulation techniques [13,[20][21][22][23]. In the present work, we have focused on developing the multi-injection strategy because of its effectiveness in MNPH, as demonstrated by previously proposed multi-injection strategies [21,[23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

“…Jiang et al [27] have used the PSO (particle swarm optimization) algorithm to explore the homogenous temperature distribution in circular and elliptical tumor models with different injections. Boroon et al [23] used a conjugate gradient approach to evaluate the best injection locations and the optimized heat source in a 2D square brain tumor model. The results showed that increasing the injection sites could lead to an increase in tumor damage; however, injecting MNP fluid to multiple locations with precision is a challenging task.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimation of the injection criteria for magnetic hyperthermia therapy based on tumor morphology

Singh,

Kumar

2024

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

Intratumoral multi-injection strategy enhances the efficacy of magnetic nanoparticle hyperthermia therapy (MNPH). In this study, criteria for the selection of injections and their location depending on the tumor shape/geometry are developed. The developed strategy is based on the thermal dosimetry results of different invasive 3D tumor models during MNPH simulation. MNPH simulations are conducted on physical tumor tissue models encased within healthy tissue. The tumor shapes are geometrically divided into a central tumor region containing maximum tumor volume and a peripheral tumor portion protruding in any random direction. The concepts of core and invasive radius are used to geometrically divide the tumor volume. Primary & secondary injections are used to inject MNP fluid into these respective tumor regions based on the invasiveness of the tumor. The optimization strategy is devised based on the zone of influence of primary & secondary injection. Results indicate that the zone of influence of secondary injection lies between 0.7 and 0.8 times the radial distance between the center of the tumor core and branch node point (extreme far endpoint on the invasive tumor surface). Additionally, the multi-injection strategy is more effective when the protrusion volume exceeds 10% of the total volume. The proposed algorithm is used to devise multi-injection strategies for arbitrarily shaped tumors and will assist in pre-planning magnetic nanoparticle hyperthermia therapy.

show abstract

Section: Spatial Temperature Profile In Tumor Modelssupporting

confidence: 68%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of the injection criteria for magnetic hyperthermia therapy based on tumor morphology

Singh,

Kumar

2024

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

show abstract

“…[4] The malignant cells can be ablated without damaging the healthy cells if the treatment temperature of bio-tissue is in a range between 42 • C and 46 • C. [5] The treatment temperature for the bio-tissue is a key factor to determine the treatment effect, which strongly depends on many factors, such as the shape of tumor, the dose of nanofluid, the injection location, the properties of nanofluid and bio-tissue, and other injection behaviors during nanofluid injection. [6,7] However, most of the factors are unable to be changed due to their intrinsic characteristics except for the dose and injection location of nanofluid. Therefore, it is necessary to optimize these two items prior to the therapy in order to obtain better treatment temperature distribution for therapeutic target.…”

Section: Introductionmentioning

confidence: 99%

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Tang¹,

Zou²,

Flesch³

et al. 2022

Chinese Phys. B

View full text Add to dashboard Cite

Thermally induced apoptosis for tumors depends mainly on the intrinsic characteristics of biological tissues as well as treatment temperature profile during magnetic hyperthermia. Further, treatment temperature distribution inside tumor depends on the injection behavior of irregular tumors, such as the injection dose and the injection location of nanofluids. In order to improve the treatment effect, the simulated annealing algorithm is adopted in this work to optimize the nanofluid injection behavior, and the improved Arrhenius model is used to evaluate the malignant ablations for three typical malignant tumor cell models. In addition, both the injection behavior optimization and the mass diffusion of nanofluid are both taken into consideration in order to improve the treatment effect. The simulation results demonstrate that the injection behavior can be optimized effectively by the proposed optimization method before therapy, the result of which can also conduce to improving the thermal apoptosis possibility for proposed typical malignant cells. Furthermore, an effective approach is also employed by considering longer diffusion duration and correct power dissipation at the same time. The results show that a better result can then be obtained than those in other cases when the power dissipation of MNPs is set to be Q MNP = 5.4 × 107 W·m3 and the diffusion time is 16 h.

show abstract

Optimization of focused multi-site injection therapy to provide the desired temperature pattern for arbitrary tumor configuration based on MNP hyperthermia: Implementation of dual phase lag bioheat equation

Roohi

Baromand

Emdad

et al. 2021

Ain Shams Engineering Journal

View full text Add to dashboard Cite

Estimation of the optimum number and location of nanoparticle injections and the specific loss power for ideal hyperthermia

Cited by 14 publications

References 26 publications

Estimation of the injection criteria for magnetic hyperthermia therapy based on tumor morphology

Estimation of the injection criteria for magnetic hyperthermia therapy based on tumor morphology

Thermal apoptosis analysis considering injection behavior optimization and mass diffusion during magnetic hyperthermia

Optimization of focused multi-site injection therapy to provide the desired temperature pattern for arbitrary tumor configuration based on MNP hyperthermia: Implementation of dual phase lag bioheat equation

Contact Info

Product

Resources

About