A novel computer-aided energy decision-making system improves patient treatment by microwave ablation of thyroid nodule

The current basis of microwave ablation (MWA) energy use for thyroid nodules (TN) is inadequate, leading to tissue carbonization, which is strongly associated with complications and poor prognosis. This study aims to devise a novel energy decision-making system to improve the subjective use of energy in current MWA procedures. Data from 916 subjects (1364 TN) across three medical centers were collected. In the first two sets, the single-stitch ablation needle energy (ANE) was calculated by analyzing MWA procedure videos. The causes of TN over-ablation (carbonization) were examined, and the relationship between well-ablated TN and ANE was explored based on TN attributes (volume and Young's modulus). Three-dimensional (3D) reconstruction of TN was performed, and a computer-aided model was constructed to optimize the distribution of the ANE field within the 3D-TN. Subsequently, a novel energy decision-making system was developed and tested. The third set was used for external validation. The cause of TN carbonization was found to be related to the overload of ANE with corrected Young's modulus and the selection of mismatched ablation needle power (ANP). A precise ANE model (Model 1) based on well-ablated TN and a needle-placement model (Model 2) based on the 3D-TN and ANP were subsequently constructed. The coupled new energy decision-making system (Model 1 + 2) demonstrated strong clinical generalization capabilities. In conclusion, this novel energy decision-making system can effectively improve the use of MWA energy, significantly promoting the precise treatment of TN.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2025-02-21
DOI
https://doi.org/10.1016/j.compbiomed.2025.109823
Citations
1
Primary Topic
Thyroid Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.29

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article

A novel computer-aided energy decision-making system improves patient treatment by microwave ablation of thyroid nodule

Xiaolan Zhu, Yuhao Xu, Hu Xu, Rui Wang et al.
1 citations
Computers in Biology and Medicine
Thyroid Cancer Diagnosis and Treatment
1.29
article

A novel computer-aided energy decision-making system improves patient treatment by microwave ablation of thyroid nodule

Xiaolan Zhu, Yuhao Xu, Hu Xu, Rui Wang, Yifeng Luo, Yuefeng Li, Zhengdong Fei, Rui Du
article en
1 citations

Abstract

The current basis of microwave ablation (MWA) energy use for thyroid nodules (TN) is inadequate, leading to tissue carbonization, which is strongly associated with complications and poor prognosis. This study aims to devise a novel energy decision-making system to improve the subjective use of energy in current MWA procedures. Data from 916 subjects (1364 TN) across three medical centers were collected. In the first two sets, the single-stitch ablation needle energy (ANE) was calculated by analyzing MWA procedure videos. The causes of TN over-ablation (carbonization) were examined, and the relationship between well-ablated TN and ANE was explored based on TN attributes (volume and Young's modulus). Three-dimensional (3D) reconstruction of TN was performed, and a computer-aided model was constructed to optimize the distribution of the ANE field within the 3D-TN. Subsequently, a novel energy decision-making system was developed and tested. The third set was used for external validation. The cause of TN carbonization was found to be related to the overload of ANE with corrected Young's modulus and the selection of mismatched ablation needle power (ANP). A precise ANE model (Model 1) based on well-ablated TN and a needle-placement model (Model 2) based on the 3D-TN and ANP were subsequently constructed. The coupled new energy decision-making system (Model 1 + 2) demonstrated strong clinical generalization capabilities. In conclusion, this novel energy decision-making system can effectively improve the use of MWA energy, significantly promoting the precise treatment of TN.

Computers in Biology and MedicineVol. 188
Jiangsu University (CN), Xuzhou Medical College (CN), Affiliated Hospital of Jiangsu University (CN), Yixing People's Hospital (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Affordable and clean energy
Openalex Percentile: Top 22%
Thyroid Cancer Diagnosis and Treatment
1.29
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