The quantity and quality of preoperative material in colorectal cancer is often limiting factor in determination of risk factors and therapy planning. The most important negative prognostic factors are intravascular and perineural invasion, as well as tumor budding. Usually, the only parameter available in preoperative biopsy is tumor budding. However, the growing body of evidence suggests that cancer differentiation based on the poorly differentiated clusters has better prognostic value. The limiting factor in applying of these new parameters is reproducible, simple, cheap and fast method of their determination. In this paper we investigated the prognostic value of lacunarity, determined in preoperative biopsy. Lacunarity is a measure of spatial heterogeneity (inhomogeneity) in an image. It quantifies how objects fill the space, and enables analysis of gaps distribution, homogeneity of gaps, and presence of structures. It was shown that lacunarity and the total number of buds could be combined in a model which clearly divides colorectal cancer patients in low, medium and high risk subgroups. The paper also points out that the quantitative numerical methods are superior to semiquantitative methods, and that individual methods should be combined using algorithms to obtain a more accurate prediction. Because the study described is designed as a pilot study, verification is needed on a larger sample of patients from independent researchers.

结直肠癌术前材料的数量和质量通常是确定危险因素和治疗计划的限制因素。最重要的负面预后因素是血管内和神经周围浸润以及肿瘤出芽。通常，术前活检中唯一可用的参数是肿瘤出芽。然而，越来越多的证据表明，基于低分化簇的癌症分化具有更好的预后价值。应用这些新参数的限制因素是其测定方法可重复、简单、廉价且快速。在本文中，我们研究了术前活检确定的腔隙的预后价值。空隙度是图像中空间异质性（不均匀性）的度量。它量化了物体如何填充空间，并能够分析间隙分布、间隙均匀性和结构的存在。结果表明，腔隙和芽总数可以结合在一个模型中，该模型可以清楚地将结直肠癌患者分为低、中和高风险亚组。论文还指出，定量数值方法优于半定量方法，并且应使用算法将各个方法结合起来以获得更准确的预测。由于所描述的研究是一项试点研究，因此需要对来自独立研究人员的更大样本患者进行验证。