文章：

基于表面温度逆建模与稳态热成像的乳腺癌筛查

Breast Cancer Screening Using Inverse Modeling of Surface Temperatures and Steady-State Thermal Imaging

原文发布日期：19 June 2024

DOI: 10.3390/cancers16122264

类型: Article

开放获取: 是

英文摘要：

Cancer is characterized by increased metabolic activity and vascularity, leading to temperature changes in cancerous tissues compared to normal cells. This study focused on patients with abnormal mammogram findings or a clinical suspicion of breast cancer, exclusively those confirmed by biopsy. Utilizing an ultra-high sensitivity thermal camera and prone patient positioning, we measured surface temperatures integrated with an inverse modeling technique based on heat transfer principles to predict malignant breast lesions. Involving 25 breast tumors, our technique accurately predicted all tumors, with maximum errors below 5 mm in size and less than 1 cm in tumor location. Predictive efficacy was unaffected by tumor size, location, or breast density, with no aberrant predictions in the contralateral normal breast. Infrared temperature profiles and inverse modeling using both techniques successfully predicted breast cancer, highlighting its potential in breast cancer screening.

摘要翻译： 

癌症的特征在于代谢活动增强和血管增多，导致癌变组织相较于正常细胞出现温度变化。本研究聚焦于乳腺X光检查结果异常或临床疑似乳腺癌的患者，且仅限于经活检确诊的病例。通过使用超高灵敏度热成像相机及俯卧位患者定位，我们测量了体表温度，并结合基于传热原理的逆向建模技术来预测恶性乳腺病变。在涉及25个乳腺肿瘤的研究中，我们的技术准确预测了所有肿瘤，其尺寸最大误差小于5毫米，肿瘤定位误差小于1厘米。预测效果不受肿瘤大小、位置或乳腺密度的影响，且在对侧正常乳腺中未出现异常预测。红外温度分布图及两种技术相结合的逆向建模成功预测了乳腺癌，凸显了其在乳腺癌筛查中的应用潜力。

原文链接：

Breast Cancer Screening Using Inverse Modeling of Surface Temperatures and Steady-State Thermal Imaging