Bucher Andreas Michael, Egger Jan, Dietz Julia, Strecker Ralph, Hilbert Tom, Frodl Eric, Wenzel Mike, Penzkofer Tobias, Hamm Bernd, Chun Felix Kh, Vogl Thomas, Kleesiek Jens, Beeres Martin
Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.
Institute for AI in Medicine, University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany.
J Imaging Inform Med. 2024 Dec;37(6):3304-3315. doi: 10.1007/s10278-024-01150-6. Epub 2024 Jun 26.
Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.
多参数前列腺MRI（mpMRI）的标准化报告已广泛应用并遵循国际标准（PI-RADS）。然而，mpMRI的定量测量结果之间缺乏广泛的可比性。尽管T2映射序列可以提供可重复的定量图像测量，并从mpMRI中提取可靠的成像生物标志物，但这些序列通常耗时较长。因此，我们研究了在高度加速的T2映射序列上进行定量测量的价值，以确定区分良性和恶性病变的阈值。为此，我们评估了一种新型的、高度加速的T2映射研究序列，该序列能够在日常临床实践中以短采集时间进行高分辨率图像采集。在这项回顾性单中心研究中，我们纳入了54例因临床需要进行前列腺MRI检查且经活检确诊为癌（n = 37）或排除癌（n = 17）的患者。所有患者均接受了前列腺标准护理活检，活检结果用于确认或排除恶性病变的存在。我们使用通过限制最大似然法（REML）拟合的线性混合效应模型来确定癌组织和健康组织平均值之间的差异。我们发现，基于平均T2值，外周区的恶性病变与正常组织之间有良好的区分度。具体而言，无恶性病变组织的平均T2值为（151.7毫秒[95%置信区间：146.9 - 156.5毫秒]），而恶性病变组织的平均T2值为80.9毫秒[95%置信区间：67.9 - 79.1毫秒]；p < 0.001）。基于此评估，建议设定109.2毫秒的界限。此外，观察到外周区的T2值与PI-RADS评分之间存在显著相关性（p = 0.0194）。然而，未发现Gleason评分与T2弛豫时间之间存在相关性。使用REML，我们发现癌组织和健康组织的平均值差异为 -82.7毫秒。我们设定了109.2毫秒的临界值，以准确区分前列腺的恶性和非恶性区域。在常规成像中添加T2映射序列可能有助于自动病变检测，并促进前列腺的无对比剂多参数MRI检查。
