Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Neuroimage Clin. 2019;23:101938. doi: 10.1016/j.nicl.2019.101938. Epub 2019 Jul 15.
The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-conventional MR sequences.
The lesion segmentation approach was evaluated with (LeMan-PV) and without (LeMan) the partial volume framework using "conventional" and "non-conventional" MR imaging in a two-year follow-up prospective study of 32 early RRMS patients. Manual segmentations of new, enlarged, shrunken, and stable lesions were used to evaluate the performance of the method variants. The true positive rate was estimated for those lesion evolutions in both white matter and cortex. The number of false positives was compared with two strategies for longitudinal analyses. New lesion tissue volume estimation was evaluated using Bland-Altman plots. Wilcoxon signed-rank test was used to evaluate the different setups.
The best median of the true positive rate was obtained using LeMan-PV with non-conventional sequences (P < .05): 87%, 87%, 100%, 83%, for new, enlarged, shrunken, and stable WM lesions, and 50%, 60%, 50%, 80%, for new, enlarged, shrunken, and stable cortical lesions, respectively. Most of the missed lesions were below the mean lesion size in each category. Lesion progression maps presented a median of 0 false positives (range:0-9) and the partial volume framework improved the volume estimation of new lesion tissue.
LeMan-PV exhibited the best performance in the detection of new, enlarged, shrunken and stable WM lesions. The method showed lower performance in the detection of cortical lesions, likely due to their low occurrence, small size and low contrast with respect to surrounding tissues. The proposed lesion progression map might be useful in clinical trials or clinical routine.
本研究的目的是评估一种新的病变分割工具在纵向分析中的性能，并使用常规和非常规磁共振（MR）序列验证两个时间点之间生成的病变进展图。
在一项为期两年的前瞻性研究中，对 32 例早期 RRMS 患者使用（LeMan-PV）和不使用（LeMan）部分容积框架的病变分割方法，结合“常规”和“非常规”MR 成像对其进行评估。使用新的、扩大的、缩小的和稳定的病变的手动分割来评估方法变体的性能。在白质和皮质中，对所有病变演变都进行了真阳性率的估计。与两种纵向分析策略进行了假阳性率的比较。使用 Bland-Altman 图评估新病变组织体积估计。Wilcoxon 符号秩检验用于评估不同的设置。
在使用非常规序列时，LeMan-PV 获得了最佳的真阳性率中位数（P<.05）：新、扩大、缩小和稳定的 WM 病变的分别为 87%、87%、100%和 83%；新、扩大、缩小和稳定的皮质病变的分别为 50%、60%、50%和 80%。大多数漏诊的病变都低于每个类别的平均病变大小。病变进展图的中位数为 0 个假阳性（范围：0-9），部分容积框架提高了新病变组织的体积估计。
LeMan-PV 在检测新的、扩大的、缩小的和稳定的 WM 病变方面表现出最佳的性能。该方法在检测皮质病变方面的性能较低，可能是由于其发生率较低、病变较小以及与周围组织的对比度较低所致。所提出的病变进展图可能在临床试验或临床常规中有用。
