Georgetown University School of Medicine, Washington, DC, USA.
Radiology. 2012 Jan;262(1):144-51. doi: 10.1148/radiol.11110266.
To compare prostate gland volume (PV) estimation of automated computer-generated multifeature active shape models (MFAs) performed with 3-T magnetic resonance (MR) imaging with that of other methods of PV assessment, with pathologic specimens as the reference standard.
All subjects provided written informed consent for this HIPAA-compliant and institutional review board-approved study. Freshly weighed prostatectomy specimens from 91 patients (mean age, 59 years; range, 42-84 years) served as the reference standard. PVs were manually calculated by two independent readers from MR images by using the standard ellipsoid formula. Planimetry PV was calculated from gland areas generated by two independent investigators by using manually drawn regions of interest. Computer-automated assessment of PV with an MFA was determined by the aggregate computer-calculated prostate area over the range of axial T2-weighted prostate MR images. Linear regression, linear mixed-effects models, concordance correlation coefficients, and Bland-Altman limits of agreement were used to compare volume estimation methods.
MFA-derived PVs had the best correlation with pathologic specimen PVs (slope, 0.888). Planimetry derived volumes produced slopes of 0.864 and 0.804 for two independent readers when compared with specimen PVs. Ellipsoid formula-derived PVs had slopes closest to one when compared with planimetry PVs. Manual MR imaging and MFA PV estimates had high concordance correlation coefficients with pathologic specimens.
MFAs with axial T2-weighted MR imaging provided an automated and efficient tool with which to assess PV. Both MFAs and MR imaging planimetry require adjustments for optimized PV accuracy when compared with prostatectomy specimens.
比较使用 3T 磁共振(MR)成像进行自动计算机生成多特征主动形状模型(MFA)的前列腺体积(PV)估计与其他 PV 评估方法,以病理标本为参考标准。
所有受试者均提供书面知情同意书,该研究符合 HIPAA 规定并经机构审查委员会批准。91 例患者的新鲜称重前列腺切除术标本(平均年龄 59 岁;范围,42-84 岁)作为参考标准。两名独立读者通过使用标准椭圆公式从 MR 图像手动计算 PV。两名独立研究人员通过使用手动绘制的感兴趣区域从腺体区域计算出的面积来计算平面 PV。通过在轴向 T2 加权前列腺 MR 图像范围内进行的聚合计算机计算的前列腺区域,使用 MFA 对 PV 进行计算机自动评估。使用线性回归、线性混合效应模型、一致性相关系数和 Bland-Altman 协议界限来比较体积估计方法。
MFA 衍生的 PV 与病理标本 PV 相关性最好(斜率,0.888)。与标本 PV 相比,两名独立读者生成的平面 PV 的斜率为 0.864 和 0.804。与平面 PV 相比,椭圆公式衍生的 PV 斜率最接近 1。手动 MR 成像和 MFA PV 估计与病理标本具有很高的一致性相关系数。
轴向 T2 加权 MR 成像的 MFA 提供了一种自动且高效的工具,可用于评估 PV。与前列腺切除术标本相比,MFA 和 MR 成像平面都需要进行调整,以实现最佳的 PV 准确性。