Funaki Ayumu, Ohkubo Masaki, Ohashi Kazunori, Shukuya Toshiro, Yashima Yuka, Kubota Kazunori
Department of Radiological Technology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minamikoshigaya, Koshigaya, Saitama, 323-0845, Japan.
Graduate School of Health Sciences, Niigata University, Niigata, Japan.
Radiol Phys Technol. 2025 Jul 1. doi: 10.1007/s12194-025-00931-0.
Clinical measurement of the maximum slope (MS) using ultrafast dynamic contrast-enhanced (UF-DCE) breast magnetic resonance imaging (MRI) is typically performed by placing a region of interest (ROI) in the most enhanced area within a lesion. However, previous studies have not clarified whether visually identified enhanced areas consistently exhibit the highest MS values. These ROI-based MS measurements require MS maps to ensure appropriate ROI placement. However, generating MS maps requires specialized software capable of pixel-by-pixel MS calculations, which are available only at a few facilities. Therefore, this study proposed a simplified method for generating MS maps. This method involves subtracting consecutive UF-DCE images, applying temporal maximum intensity projection, normalizing the resulting image by dividing it by the pre-contrast image signal intensity, and converting it to a slope by dividing it by the temporal resolution. The MS maps generated using the proposed method were compared with those obtained using a robust pixel-by-pixel curve-fitting method, in addition to the final-phase UF-DCE images. In all cases with breast lesions (n = 13), the signal intensity distributions on the proposed MS maps closely resembled those on the curve-fitting maps, with a significantly higher similarity than those on the final-phase UF-DCE images (p < 0.001). The derived mean absolute error of MS values after regression-based modification was 0.78 ± 0.72 (%/s). The proposed method improves the reliability of ROI placement in conventional ROI-based MS measurements and supports the direct quantification of MS values from map pixel data.
使用超快动态对比增强（UF-DCE）乳腺磁共振成像（MRI）对最大斜率（MS）进行临床测量时，通常是在病变内增强最明显的区域放置感兴趣区（ROI）。然而，以往的研究尚未阐明通过视觉识别的增强区域是否始终呈现最高的MS值。这些基于ROI的MS测量需要MS图来确保ROI的正确放置。然而，生成MS图需要能够逐像素进行MS计算的专业软件，而只有少数机构具备这种软件。因此，本研究提出了一种生成MS图的简化方法。该方法包括减去连续的UF-DCE图像，应用时间最大强度投影，将所得图像除以前对比图像信号强度进行归一化，并除以时间分辨率将其转换为斜率。除了最终相位的UF-DCE图像外，还将使用所提出方法生成的MS图与使用稳健的逐像素曲线拟合方法获得的MS图进行了比较。在所有乳腺病变病例（n = 13）中，所提出的MS图上的信号强度分布与曲线拟合图上的信号强度分布非常相似，相似度显著高于最终相位的UF-DCE图像（p < 0.001）。基于回归修正后得出的MS值的平均绝对误差为0.78±0.72（%/s）。所提出的方法提高了传统基于ROI的MS测量中ROI放置的可靠性，并支持从图像素数据直接定量MS值。
