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用概率学热剂量模型改善MR指导前列腺聚焦超声波除的缩估计

Simon Schröer¹, Julian Glandorf¹, Daniel Düx¹

¹Department of Diagnostic and Interventional Radiology, Hannover Medical School, Carl-Neuberg-Straße 1, 30655 Hannover, Germany; STIMULATE Research Campus, 39106 Magdeburg, Germany.

Computers in biology and medicine

|May 17, 2025

概括

一个新的概率CEM43热剂量模型 (pCEM43) 通过减少虚假阳性,而不需要先前的硬件知识,从而改善前列腺癌切除的实时评估. 这种更高的准确性可以提高治疗成功率,并最大限度地降低瘤复发风险.

科学领域:

医学物理医学物理
在瘤学瘤学.
生物医学工程生物医学工程

背景情况:

精确的实时评估磁共振 (MR) 导向的前列腺癌穿尿管超声波除是具有挑战性的,因为在除区域附近的虚假阳性缩分类.
传统方法依赖于先验的传感器知识来过温度图,这可能会限制实时适应性.

研究的目的:

引入和评估一个修改后的概率学CEM43热剂量模型 (pCEM43),以改进通过尿道超声波除的实时监测.
评估pCEM43模型在不需要硬件特定的先前知识的情况下减少虚假阳性的能力,仅使用基线图像噪声统计数据.

主要方法:

修改后的pCEM43模型应用于22个采用TULSA Pro系统与MR温度计 (PRFS-EPI序列) 获得的通过尿道超声波切除数据集.
模型的性能使用Sørensen-Dice系数 (DSC),相对假阳性率 (rFPR),灵敏度,平均轮高估 (MCO) 和平均轮低估 (MCU) 来评估.
结果与未过的CEM43 (CEM43) 和时空过的CEM43 (STF-CEM43) 模型进行了比较,并进行了计算时间分析.

主要成果:

与CEM43 (38.9%) 和STF-CEM43 (64.2%) (p≤0.001) 相比,pCEM43模型实现了显著更高的中位数DSC (70.7%).
与CEM43和STF-CEM43 (p≤0.001) 相比,pCEM43的rFPR (0.32 ±0.28) 和MCO (0.5) 的平均值明显较低.
在不同模型中,灵敏度和MCU是可比的,pCEM43显示最小的高估值和没有显著的低估值.

结论:

经过修改的pCEM43模型提高了监测准确度,并减少了实时的除体积过高估计,而不需要先验硬件信息.
这种方法有可能提高MR导向前列腺切除的治疗成功率,并减轻未切除和瘤复发的风险.
未来的研究将专注于验证pCEM43模型在不同热移除技术和组织类型的普遍性.

关键词:

用MR指导的横尿道超声波除术.前列腺瘤是一个前列腺瘤.热剂量模型的热剂量模型.测温仪测温仪是用来测温的.

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