Department of Industrial Engineering (DIN), Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Laboratorio di Tecnologia Medica, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
J Digit Imaging. 2023 Feb;36(1):143-152. doi: 10.1007/s10278-022-00700-0. Epub 2022 Oct 11.
The manual segmentation of muscles on magnetic resonance images is the gold standard procedure to reconstruct muscle volumes from medical imaging data and extract critical information for clinical and research purposes. (Semi)automatic methods have been proposed to expedite the otherwise lengthy process. These, however, rely on manual segmentations. Nonetheless, the repeatability of manual muscle volume segmentations performed on clinical MRI data has not been thoroughly assessed. When conducted, volumetric assessments often disregard the hip muscles. Therefore, one trained operator performed repeated manual segmentations (n = 3) of the iliopsoas (n = 34) and gluteus medius (n = 40) muscles on coronal T1-weighted MRI scans, acquired on 1.5 T scanners on a clinical population of patients elected for hip replacement surgery. Reconstructed muscle volumes were divided in sub-volumes and compared in terms of volume variance (normalized variance of volumes - nVV), shape (Jaccard Index-JI) and surface similarity (maximal Hausdorff distance-HD), to quantify intra-operator repeatability. One-way repeated measures ANOVA (or equivalent) tests with Bonferroni corrections for multiple comparisons were conducted to assess statistical significance. For both muscles, repeated manual segmentations were highly similar to one another (nVV: 2-6%, JI > 0.78, HD < 15 mm). However, shape and surface similarity were significantly lower when muscle extremities were included in the segmentations (e.g., iliopsoas: HD -12.06 to 14.42 mm, P < 0.05). Our findings show that the manual segmentation of hip muscle volumes on clinical MRI scans provides repeatable results over time. Nonetheless, extreme care should be taken in the segmentation of muscle extremities.
磁共振图像上的肌肉手动分割是重建医学成像数据中肌肉体积并提取临床和研究目的关键信息的金标准程序。(半)自动方法已经被提出以加快这一冗长的过程。然而,这些方法都依赖于手动分割。尽管如此,对临床 MRI 数据上执行的手动肌肉体积分割的重复性尚未进行彻底评估。当进行时,体积评估往往忽略了臀部肌肉。因此,一名经过培训的操作人员对接受髋关节置换手术的临床患者人群的冠状 T1 加权 MRI 扫描上的髂腰肌(n=34)和臀中肌(n=40)进行了 3 次重复手动分割。重建的肌肉体积被分为子体积,并根据体积方差(体积归一化方差-nVV)、形状(Jaccard 指数-JI)和表面相似性(最大 Hausdorff 距离-HD)进行比较,以量化操作员内重复性。采用单向重复测量方差分析(或等效方法)并进行 Bonferroni 校正多重比较来评估统计学意义。对于这两块肌肉,重复的手动分割彼此非常相似(nVV:2-6%,JI>0.78,HD<15mm)。然而,当将肌肉末端包括在分割中时,形状和表面相似性明显降低(例如,髂腰肌:HD-12.06 至 14.42mm,P<0.05)。我们的研究结果表明,在临床 MRI 扫描上对髋关节肌肉体积进行手动分割可以提供随时间推移的可重复结果。然而,在分割肌肉末端时应格外小心。