{"title":"一种生成超快动态对比增强乳房磁共振成像中最大斜率图的简化方法。","authors":"Ayumu Funaki, Masaki Ohkubo, Kazunori Ohashi, Toshiro Shukuya, Yuka Yashima, Kazunori Kubota","doi":"10.1007/s12194-025-00931-0","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":46252,"journal":{"name":"Radiological Physics and Technology","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A simplified method for generating maximum slope maps in ultrafast dynamic contrast-enhanced breast magnetic resonance imaging.\",\"authors\":\"Ayumu Funaki, Masaki Ohkubo, Kazunori Ohashi, Toshiro Shukuya, Yuka Yashima, Kazunori Kubota\",\"doi\":\"10.1007/s12194-025-00931-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":46252,\"journal\":{\"name\":\"Radiological Physics and Technology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiological Physics and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12194-025-00931-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiological Physics and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12194-025-00931-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
A simplified method for generating maximum slope maps in ultrafast dynamic contrast-enhanced breast magnetic resonance imaging.
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.
期刊介绍:
The purpose of the journal Radiological Physics and Technology is to provide a forum for sharing new knowledge related to research and development in radiological science and technology, including medical physics and radiological technology in diagnostic radiology, nuclear medicine, and radiation therapy among many other radiological disciplines, as well as to contribute to progress and improvement in medical practice and patient health care.