Recent research advances on simulation modeling of temperature distribution in microwave ablation of lung tumors

Figures & data

Figure 1. Schematic diagram of MWA treatment of lung tumor.

Table 1. Summary of characteristic parameters of the lung tissue.

Num.	Refs.	Thermal conductivity $k$ (W/m·K)	Density $\rho$ (kg/m^3)	Specific heat capacity $c$ (J/kg·K)	Blood perfusion $\omega$(S^−1)	Electrical conductivity $\sigma$ (S/m)	Permittivity $\epsilon$	Threshold temperature $T$ (°C)	Tissue type	Condition
1	Gao, 2019 [16]	0.2	480	–	–	0.423	33	60	Porcine lung	Ex vivo
2	Radmilović, 2021 (average) [23–25]	0.39	385	3886	0.0036	0.804	20.5	50	Lung	Simulation
3	Yang, 2020-inflated	0.16	240	2500	0.00361	0.80	20.47	–	Lung	Simulation
	Mediate	0.18	360	2500	0.00361	1.24	34.42	–	Lung	Simulation
	Deflated [26,27]	0.20	480	2500	0.00361	1.68	48.38	–	Lung	Simulation
4	Liu, 2019-flooded	0.52	1030	3886	0.00709	–	–	–	Lung	Simulation
	Higher inflated	0.39	400	3886	0.00708	–	–	–	Lung	Simulation
	Lower inflated [28–33]	0.39	700	3886	0.00709	–	–	–	Lung	Simulation
5	Avishek, 2021 [34]	0.33^a	–	–	0.0026^a	0.804^a	20.5^a	–	Lung	Simulation
		0.39^b	–	–	0.0155^b	1.69 ^b	43^b	–	Lung	Simulation
		0.53^c	–	–	0.0674^c	2.43 ^c	57.2^c	–	Lung	Simulation
6	Keangin, 2019 [35]	–	–	–	–	–	30.01	–	Porcine lung	Ex vivo
7	Brace, 2009(inflated) [13]	0.302	260	2500	0.00087	0.804	20.5	–	Porcine lung	Ex vivo
8	Hasgall, 2022-deflated	0.39	1050	3886	0.00702	1.68	48.4	–	Lung	–
	Inflated [36]	0.39	394	3886	0.00263	0.804	20.5	–	Lung	–
9	Singh, 2018 [37,38]	0.39	394	3886	0.00263	0.122	–	–	Lung	Simulation
10	Singh, 2019 [39]	0.39^b	394^a	3886^a	0.00263	0.804^a	20.5^a	–	Lung	Simulation
11	Hu, 2022-deflated	0.39	480	3886	–	0.804	33	60	Porcine lung	Ex vivo
	Inflated [12]	0.16	394	2500	–	0.306	20.47	60	Porcine lung	Ex vivo
12	Sebek, 2021 (average) [40,41]	0.39	–	–	–	1.47	40.5	–	Lung	Simulation

Note: a: low; b: medium; c: high; ‘–’ indicates that there is no reference to this term in the text.

Figure 2. Simulation process of lung tumor MWA.

Figure 3. Lung tissue model. (a) Cylindrical lung tissue model. (b) Real lung tissue model.

Figure 4. Lung tumor model. (a) Whole lung tissue-level model. (b) Traditional spherical tumor model. (c) Real tumor model based on CT slice.

Table 2. Comparison of advantages and disadvantages of heat transfer models.

Heat transfer model	Advantages	Disadvantages
Pennes equation	The calculation process is simple, easy to analyze and widely used, and the additional term used to show that the perfusion heat transfer is linear in temperature.	It is assumed that the blood flow is uniform. The arterial blood is kept at constant temperature. Different directions of blood flow are not considered. The arteriovenous convection is ignored.
Porous media model	The division of biological tissue into solid and liquid overcomes the defect of Pennes equation.	The process of solving solid tissue and liquid tissue is complex.

Table 3. Comparison of advantages and disadvantages of thermal damage assessment techniques.

Thermal damage assessment model	Advantages	Disadvantages
Isotherm threshold (IT)	Straightforward and intuitive	The correlation between target type and heating duration is not taken into account.
Arrhenius model	Simple, direct and widely used	Only two states of biological tissue are considered, and the transition between these states is single and irreversible.
Thermal equivalent dose (TID)	Widely used in thermal damage models at lower temperatures	Not suitable for thermal ablation processes with higher temperatures above 50 °C.

Table 4. Ablation results for different power and time combinations.

Num.	Refs	Power $P$ (W)	Time $t$ (s)	Transverse diameter $s$ (mm)	Longitudinal diameter $L$ (mm)	Volume $V$ (cm^3)	Sphericity $SI$	Maximum temperature $T$ (°C)	Threshold temperature $T^{\prime }$ (°C)	Tissue type	Condition
1	Gao 2019 [16]	30/40/50	120	13.4/19.1/22.0	16.3/22.9/28.5	–	–	67.2/73.6/78.7	60	Porcine lung	Ex vivo
		30/40/50	240			–	–	71.5/81.7/99.3	60		Ex vivo
		30/40/50	360	23.0/36.8/39.9	30.2/41.2/51.4	–	–	75.6/85.3/106.7	60	Porcine lung	Ex vivo
		30/40/50	360	29.5/44.0/48.9	41.1/55.7/66.3	–	–	183.2/231.9/280.7	60	Porcine lung	Simulation
				40.5/46.9/51.9	56.3/62.1/66.7					Lung
2	Pfannenstiel 2017 [18]	60/80	300	11.5/14	31.5/24.5	–	0.37/0.65	–	–	Porcine lung	Ex vivo
		60	300	16	37.75	–	–	–	–	Canine lung	In vivo
3	Habert 2021 [49]	50	600	–	36	17.1	0.65	–	–	Porcine lung	In vivo
		75	600	–	40	17.9	0.54	–	–	Porcine lung	In vivo
		100	600	–	43	20.7	0.53	–	–	Porcine lung	In vivo
		100	300	–	43	11.0	0.56	–	–	Porcine lung	In vivo
		100	600	–	43	20.7	0.53	–	–	Porcine lung	In vivo
		100	720	–	52	30.2	0.35	–	–	Porcine lung	In vivo
4	Gao 2017 [52]	60	600	33.62	51.91	–	–	123.6	–	Lung	Simulation
		60	600	34	55	–	–	–	–	Phantom	Ex vivo
5	Keangin 2019 [35]	60	360	20	–	4.19	–	–	50	Porcine lung	Ex vivo
		80	360	24	–	7.23	–	–	50	Porcine lung	Ex vivo
		100	360	26	–	9.20	–	–	50	Porcine lung	Ex vivo
6	Radmilović–Radjenović2022[68]	10	600	–	–	–	–	63.4	–	Lung	Simulation
7	Sebek 2020 [69]	32	300	17.67	25.3	–	–	–	–	Porcine lung	In vivo
		24	600	17.6	20	–	–	–	–	Porcine lung	In vivo
8	Sebek2021 [40]	30/60	600	15/30	–/35	–	–	–	–	Porcine lung	In vivo
		30/60	600	16.8/30.6	27.2/37	–	–	–	–	Lung	Simulation

Note: ‘–’ indicates that there is no reference to this term in the text.

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