Inverse heat transfer prediction of the thermal parameters of tumors during cryosurgery

• Published in: International journal of thermal sciences 2023-10, Vol.192, p.108453, Article 108453
• Main Authors: Hafid, Mohamed, Lacroix, Marcel, Hebbir, Nacer
• Format: Article
• Language: English
• Subjects: Blood perfusion rate; Cryosurgery; Enthalpy method; Inverse approach; Metabolic heat generation; Pennes model
• ISSN: 1290-0729; 1778-4166
• DOI: 10.1016/j.ijthermalsci.2023.108453

An inverse heat transfer approach for predicting the moving freezing front and the temperature distribution inside tumors during cryosurgery is presented. By recording the time-varying temperature at the surface of the diseased tissues, the inverse method is able to estimate simultaneously the blood perfusion rate and the metabolic heat generation of the tumor. Once these thermal properties are determined, the temperature field and the moving freezing front are predicted with a direct method. The direct problem is solved with the one-dimension Pennes bioheat equation and the enthalpy method. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM). The following effects on the predictions of the inverse method are investigated: (i) the initialization of the unknown thermal properties; (ii) the thermal properties of the diseased tissues; (iii) the duration of cryosurgery; (iv) the temperature of the cryoprobe; (v) the noise level on the recorded temperatures; and (vi) the total number of recorded data. It is shown that the proposed inverse method remains accurate and stable for all cases investigated. Recommendations are made for the initialization of the parameters of the inverse method and for the total number of measurements. [Display omitted] •A promising alternative to MRI and ultrasound for controlling the motion of the freezing front during cryosurgery is proposed.•A non-isothermal phase change process of freezing tissues is developed.•The inverse approach is able to predict the blood perfusion rate and the metabolic heat generation during cryosurgery.•The effect of the most influential parameters on the inverse predictions is examined.