Scholarlink

Objectives <p>This study aimed to compare the diagnostic performance of CT-derived fractional flow reserve (CT-FFR) using model-based iterative reconstruction (MBIR) and high-resolution deep learning reconstruction (HR-DLR) images to detect functionally significant stenosis with invasive FFR as the reference standard.</p> Materials and methods <p>This single-center retrospective study included 79 consecutive patients (mean age, 70 ± 11 [SD] years; 57 male) who underwent coronary CT angiography followed by invasive FFR between February 2022 and March 2024. CT-FFR was calculated using a mesh-free simulation. The cutoff for functionally significant stenosis was defined as FFR ≤ 0.80. CT-FFR was compared with MBIR and HR-DLR using receiver operating characteristic curve analysis.</p> Results <p>The mean invasive FFR value was 0.81 ± 0.09, and 46 of 98 vessels (47%) had FFR ≤ 0.80. The mean noise of HR-DLR was lower than that of MBIR (14.4 ± 1.7 vs 23.5 ± 3.1, <i>p</i> &lt; 0.001). The area under the receiver operating characteristic curve for the diagnosis of functionally significant stenosis of HR-DLR (0.88; 95% CI: 0.80, 0.95) was higher than that of MBIR (0.76; 95% CI: 0.67, 0.86; <i>p</i> = 0.003). The diagnostic accuracy of HR-DLR (88%; 86 of 98 vessels; 95% CI: 80, 94) was higher than that of MBIR (70%; 69 of 98 vessels; 95% CI: 60, 79; <i>p</i> &lt; 0.001).</p> Conclusions <p>HR-DLR improves image quality and the diagnostic performance of CT-FFR for the diagnosis of functionally significant stenosis.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>The effect of HR-DLR on the diagnostic performance of CT-FFR has not been investigated</i>.</p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>HR-DLR improved the diagnostic performance of CT-FFR over MBIR for the diagnosis of functionally significant stenosis as assessed by invasive FFR</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>HR-DLR would further enhance the clinical utility of CT-FFR in diagnosing the functional significance of coronary stenosis</i>.</p> Graphical Abstract <p></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

High-resolution deep learning reconstruction to improve the accuracy of CT fractional flow reserve

  • 期刊论文

  • 发表日期：

    2025年5月22日

查看全文
  • Nobuo Tomizawa,
  • Ruiheng Fan,
  • Shinichiro Fujimoto,
  • Yui O. Nozaki,
  • Yuko O. Kawaguchi,
  • Kazuhisa Takamura,
  • Makoto Hiki,
  • Tadao Aikawa,
  • Norihito Takahashi,
  • Iwao Okai,
  • Shinya Okazaki,
  • Kanako K. Kumamaru,
  • Tohru Minamino,
  • Shigeki Aoki

摘要

Objectives

This study aimed to compare the diagnostic performance of CT-derived fractional flow reserve (CT-FFR) using model-based iterative reconstruction (MBIR) and high-resolution deep learning reconstruction (HR-DLR) images to detect functionally significant stenosis with invasive FFR as the reference standard.

Materials and methods

This single-center retrospective study included 79 consecutive patients (mean age, 70 ± 11 [SD] years; 57 male) who underwent coronary CT angiography followed by invasive FFR between February 2022 and March 2024. CT-FFR was calculated using a mesh-free simulation. The cutoff for functionally significant stenosis was defined as FFR ≤ 0.80. CT-FFR was compared with MBIR and HR-DLR using receiver operating characteristic curve analysis.

Results

The mean invasive FFR value was 0.81 ± 0.09, and 46 of 98 vessels (47%) had FFR ≤ 0.80. The mean noise of HR-DLR was lower than that of MBIR (14.4 ± 1.7 vs 23.5 ± 3.1, p < 0.001). The area under the receiver operating characteristic curve for the diagnosis of functionally significant stenosis of HR-DLR (0.88; 95% CI: 0.80, 0.95) was higher than that of MBIR (0.76; 95% CI: 0.67, 0.86; p = 0.003). The diagnostic accuracy of HR-DLR (88%; 86 of 98 vessels; 95% CI: 80, 94) was higher than that of MBIR (70%; 69 of 98 vessels; 95% CI: 60, 79; p < 0.001).

Conclusions

HR-DLR improves image quality and the diagnostic performance of CT-FFR for the diagnosis of functionally significant stenosis.

Key Points

Question The effect of HR-DLR on the diagnostic performance of CT-FFR has not been investigated.

Findings HR-DLR improved the diagnostic performance of CT-FFR over MBIR for the diagnosis of functionally significant stenosis as assessed by invasive FFR.

Clinical relevance HR-DLR would further enhance the clinical utility of CT-FFR in diagnosing the functional significance of coronary stenosis.

Graphical Abstract