一个基于ConvLSTM的模型,用于预测激光间歇性热疗法期间的热损伤
Tingting Gao1, Libin Liang2, Hui Ding1
1Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, People's Republic of China.
Physics in medicine and biology
|February 7, 2025
概括
这项研究引入了一种新的AI模型,使用手术内温度数据准确预测大脑激光间歇性热疗法 (LITT) 期间的热损伤. 该模型对治疗诱导的组织变化的实时评估非常有希望.
科学领域:
- 医学物理和生物医学工程
- 医学中的人工智能
- 神经外科和瘤学
背景情况:
- 准确预测热损伤对于有效的激光间歇热疗法 (LITT) 至关重要,特别是在大脑治疗中.
- 目前使用对比度增强T1加权成像 (CE-T1WI) 的方法提供了术后评估,但依赖于传统模型,在预测体内损伤方面存在局限性.
- 现有的热损伤模型经常使用体外研究中的经验参数,并且无法捕捉临床上观察到的细微的三态组织损伤.
研究的目的:
- 开发和评估一种基于卷积长期短期记忆 (LSTM) 的新型模型,用于预测LITT期间的热损伤程度.
- 利用手术内磁共振温度成像 (MRTI) 数据来预测术后CE-T1WI上看到的增强边缘.
- 通过捕捉更详细的组织状态并使实时损伤评估成为可能,解决传统模型的局限性.
主要方法:
- 一个卷积式LSTM深度学习模型被设计用于处理LITT期间MRTI的手术内温度分布历史数据.
- 该模型在56名接受大脑LITT的患者的回顾性数据上进行了训练和验证.
- 通过将模型预测的增强边缘与实际的手术后CE-T1WI发现进行比较来评估性能.
主要成果:
- 拟议的模型在预测术后图像上的增强边形方面表现强,在测试数据集中达到0.82 (±0.063) 的Dice平均相似度系数.
- 该模型生成了实时预测的热损伤面积变化趋势,这些趋势与传统的热损伤模型非常相似.
- 这表明了准确,实时可视化和评估手术内热损伤的潜力.
结论:
- 新型卷积LSTM模型有效地预测LITT中的热损伤程度,使用手术内MRTI数据.
- 这种方法在传统模型上提供了显著的改进,因为它提供了更准确和潜在的热伤害实时评估.
- 开发的方法可以作为一个有价值的工具来提高图像引导LITT程序的精度和安全性.
相关概念视频
01:09Thermal Stress
If the temperature of an object is changed while it is prevented from expanding or contracting, the object is subjected to stress. The stress is compressive if the object expands in the absence of constraint and tensile if it contracts. This stress resulting from temperature change is known as thermal stress. It can be quite large and can cause damage. To avoid this stress, engineers may design components so they can expand and contract freely. For instance, on highways, gaps are deliberately...
01:27Thermal expansion and Thermal stress: Problem Solving
San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55 °C.
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55 °C.
01:19Thermal Strain
Thermal strain is a concept that arises when we consider how temperature changes affect structures. Unlike the conventional assumption that structures remain constant under load, real-world scenarios often involve temperature fluctuations that can significantly impact these structures. Consider a homogeneous rod with a uniform cross-section resting freely on a flat horizontal surface. If the rod's temperature increases, the rod elongates. This elongation is proportional to the temperature...