Scholarlink

<p>Intraprocedural visualization of the iceball boundary is often limited at the fat–ice interface, where frozen fat—despite increased computed tomography (CT) values—remains within the negative range, thus yielding limited contrast with non-frozen fat. This limitation is relevant in CT-guided renal cryoablation involving perirenal fat. We evaluated a stepwise CT post-processing method of subtraction and scaled addition with probabilistically adjusted thresholding, using an in situ fat–muscle phantom. This two-step process involved fixed zero-threshold subtraction (Step 1: post-freezing image minus pre-freezing image) and kernel density estimation-based threshold subtraction (Step 2: Step 1 output minus post-freezing image), based on pixel-wise fat-attenuation distributions. Contrast-to-noise ratio improved in both fat and non-fat tissues. In fat tissue, boundary contrast selectively increased by reducing CT values in non-frozen regions, whereas in non-fat tissue, by reducing them in frozen regions. Iceball boundaries aligned with magnetic resonance imaging. This approach may improve iceball demarcation and warrants validation in clinical practice.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Subtraction-based Stepwise computed tomography post-processing with probabilistically adjusted thresholding for fat–ice demarcation: an in situ study

  • 期刊论文

  • 发表日期：

    2025年12月15日

查看全文
  • Chihiro Itou,
  • Yoshiki Ishihara,
  • Atsushi Urikura,
  • Miyuki Sone

摘要

Intraprocedural visualization of the iceball boundary is often limited at the fat–ice interface, where frozen fat—despite increased computed tomography (CT) values—remains within the negative range, thus yielding limited contrast with non-frozen fat. This limitation is relevant in CT-guided renal cryoablation involving perirenal fat. We evaluated a stepwise CT post-processing method of subtraction and scaled addition with probabilistically adjusted thresholding, using an in situ fat–muscle phantom. This two-step process involved fixed zero-threshold subtraction (Step 1: post-freezing image minus pre-freezing image) and kernel density estimation-based threshold subtraction (Step 2: Step 1 output minus post-freezing image), based on pixel-wise fat-attenuation distributions. Contrast-to-noise ratio improved in both fat and non-fat tissues. In fat tissue, boundary contrast selectively increased by reducing CT values in non-frozen regions, whereas in non-fat tissue, by reducing them in frozen regions. Iceball boundaries aligned with magnetic resonance imaging. This approach may improve iceball demarcation and warrants validation in clinical practice.