Snyder James M, Huang Raymond Y, Bai Harrison, Rao Vikram R, Cornes Susannah, Barnholtz-Sloan Jill S, Gutman David, Fasano Rebecca, Van Meir Erwin G, Brat Daniel, Eschbacher Jennifer, Quackenbush John, Wen Patrick Y, Lee Jong Woo
Departments of Neurosurgery and Neurology, Henry Ford Health System, Detroit, Michigan, USA.
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Neurooncol Adv. 2021 Jun 24;3(1):vdab088. doi: 10.1093/noajnl/vdab088. eCollection 2021 Jan-Dec.
Although IDH-mutant tumors aggregate to the frontotemporal regions, the clustering pattern of IDH-wildtype tumors is less clear. As voxel-based lesion-symptom mapping (VLSM) has several limitations for solid lesion mapping, a new technique, whole-lesion phenotype analysis (WLPA), is developed. We utilize WLPA to assess spatial clustering of tumors with IDH mutation from The Cancer Genome Atlas and The Cancer Imaging Archive.
The degree of tumor clustering segmented from T1 weighted images is measured to every other tumor by a function of lesion similarity to each other via the Hausdorff distance. Each tumor is ranked according to the degree to which its neighboring tumors show identical phenotypes, and through a permutation technique, significant tumors are determined. VLSM was applied through a previously described method.
A total of 244 patients of mixed-grade gliomas (WHO II-IV) are analyzed, of which 150 were IDH-wildtype and 139 were glioblastomas. VLSM identifies frontal lobe regions that are more likely associated with the presence of IDH mutation but no regions where IDH-wildtype was more likely to be present. WLPA identifies both IDH-mutant and -wildtype tumors exhibit statistically significant spatial clustering.
WLPA may provide additional statistical power when compared with VLSM without making several potentially erroneous assumptions. WLPA identifies tumors most likely to exhibit particular phenotypes, rather than producing anatomical maps, and may be used in conjunction with VLSM to understand the relationship between tumor morphology and biologically relevant tumor phenotypes.
尽管异柠檬酸脱氢酶（IDH）突变型肿瘤聚集在额颞叶区域，但IDH野生型肿瘤的聚集模式尚不清楚。由于基于体素的病变-症状映射（VLSM）在实体病变映射方面存在一些局限性，因此开发了一种新技术，即全病变表型分析（WLPA）。我们利用WLPA来评估来自癌症基因组图谱和癌症影像存档中IDH突变肿瘤的空间聚集情况。
通过基于豪斯多夫距离的病变相似性函数，测量从T1加权图像分割出的肿瘤聚集程度，两两肿瘤进行比较。根据其相邻肿瘤表现出相同表型的程度对每个肿瘤进行排名，并通过排列技术确定显著的肿瘤。通过先前描述的方法应用VLSM。
共分析了244例混合级别胶质瘤（世界卫生组织II-IV级）患者，其中150例为IDH野生型，139例为胶质母细胞瘤。VLSM识别出更可能与IDH突变存在相关的额叶区域，但未识别出IDH野生型更可能存在的区域。WLPA识别出IDH突变型和野生型肿瘤均表现出具有统计学意义的空间聚集。
与VLSM相比，WLPA可能提供额外的统计效力，且无需做出一些潜在的错误假设。WLPA识别出最可能表现出特定表型的肿瘤，而非生成解剖图谱，可与VLSM结合使用以了解肿瘤形态与生物学相关肿瘤表型之间的关系。
