Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.
Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.
复制标题
DOI：
10.1117/1.jmi.5.1.011003
复制
发表时间：
2018-01
期刊：
影响因子：
--
通讯作者：
Hylton N
中科院分区：
文献类型：
--
作者：
Newitt DC;Malyarenko D;Chenevert TL;Quarles CC;Bell L;Fedorov A;Fennessy F;Jacobs MA;Solaiyappan M;Hectors S;Taouli B;Muzi M;Kinahan PE;Schmainda KM;Prah MA;Taber EN;Kroenke C;Huang W;Arlinghaus LR;Yankeelov TE;Cao Y;Aryal M;Yen YF;Kalpathy-Cramer J;Shukla-Dave A;Fung M;Liang J;Boss M;Hylton N
弥散加权MRI在许多医学领域已经变得无处不在，包括癌症诊断和治疗反应监测。扩散指标的重现性对于它们作为这些领域的定量生物标志物被接受是至关重要的。我们研究了从NCI定量成像网络和在线扫描时间生成的ADC图使用的后处理软件实现中获得的表观扩散系数（ADC）的变异性。评价了体模和体内乳腺研究的二（）和四（）值扩散度量。对于体模ADC测量和体内测量，大多数实施的一致性都很好，具有相对偏差（）和（体模），但在最低体模ADC值时ADC偏差较高。体内一致性良好，典型偏差为3%，但在线地图的偏差更高。多个b值ADC实现被分成由拟合算法确定的两组。组间平均ADC差异范围从体模数据的可忽略不计到体内数据的2.8%。个别实现和在线参数映射发现了一些更高的偏差。尽管总体一致性良好，但ADC测量的实施偏倚有时很大，可能大到足以引起多中心研究的关注。
Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two () and four () -value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo , with relative biases () and (phantom ) but with higher deviations in ADC at the lowest phantom ADC values. In vivo concordance was good, with typical biases of to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.