Department of Ultrasound, Fujian Medical University Affiliated Union Hospital, Fuzhou, Fujian, China.
Scand J Gastroenterol. 2022 Mar;57(3):352-358. doi: 10.1080/00365521.2021.2002396. Epub 2021 Nov 15.
To explore and establish a reliable and noninvasive ultrasound model for predicting the biological risk of gastrointestinal stromal tumors (GISTs).
We retrospectively reviewed 266 patients with pathologically-confirmed GISTs and 191 patients were included. Data on patient sex, age, tumor location, biological risk classification, internal echo, echo homogeneity, boundary, shape, blood flow signals, presence of necrotic cystic degeneration, long diameter, and short/long (S/L) diameter ratio were collected. All patients were divided into low-, moderate-, and high-risk groups according to the modified NIH classification criteria. All indicators were analyzed by univariate analysis. The indicators with inter-group differences were used to establish regression and decision tree models to predict the biological risk of GISTs.
There were statistically significant differences in long diameter, S/L ratio, internal echo level, echo homogeneity, boundary, shape, necrotic cystic degeneration, and blood flow signals among the low-, moderate-, and high-risk groups (all .05). The logistic regression model based on the echo homogeneity, shape, necrotic cystic degeneration and blood flow signals had an accuracy rate of 76.96% for predicting the biological risk, which was higher than the 72.77% of the decision tree model (based on the long diameter, the location of tumor origin, echo homogeneity, shape, and internal echo) ( = .008). In the low-risk and high-risk groups, the predicting accuracy rates of the regression model reached 87.34 and 81.82%, respectively.
Transabdominal ultrasound is highly valuable in predicting the biological risk of GISTs. The logistic regression model has greater predictive value than the decision tree model.
探索并建立一种可靠的、非侵入性的超声模型，以预测胃肠道间质瘤（GIST）的生物学风险。
我们回顾性分析了 266 例经病理证实的 GIST 患者，其中 191 例纳入研究。收集患者的性别、年龄、肿瘤位置、生物学风险分级、内部回声、回声均匀性、边界、形状、血流信号、有无坏死囊变、长径、长短径比等数据。所有患者均按照 NIH 改良分级标准分为低危组、中危组和高危组。单因素分析所有指标，组间有差异的指标建立回归和决策树模型预测 GIST 的生物学风险。
低危组、中危组和高危组的长径、长短径比、内部回声水平、回声均匀性、边界、形状、坏死囊变和血流信号比较，差异均有统计学意义（均 P<0.05）。基于回声均匀性、形状、坏死囊变和血流信号的 Logistic 回归模型预测 GIST 生物学风险的准确率为 76.96%，高于基于长径、肿瘤起源部位、回声均匀性、形状和内部回声的决策树模型（准确率为 72.77%）（ P=0.008）。在低危组和高危组中，回归模型的预测准确率分别达到 87.34%和 81.82%。
经腹超声对预测 GIST 的生物学风险具有较高价值，Logistic 回归模型比决策树模型具有更高的预测价值。
