The roles of CT and EUS in the preoperative evaluation of gastric gastrointestinal stromal tumors larger than 2 cm

Chen, Tao; Xu, Lili; Dong, Xiaoyu; Li, Yue; Yu, Jiang; Xiong, Wei; Li, Guoxin

doi:10.1007/s00330-018-5945-6

Cited by 55 publications

(47 citation statements)

References 28 publications

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“…This finding was different from that in a previous study [25], in which size was the only significant predictor of high mitotic counts. However, there was no significant difference between the mitotic value and different sizes (p = 0.075) in our research, and our research was very similar to that of Chen et al [26], in which there was no difference between mitotic counts and size, while the difference between mitotic counts and shape or growth patterns was statistically significant. In addition, some studies evaluated tumor response to treatment with CT attenuation coefficient on enhanced CT [27,28], but they did not study the relationship between triphasic CT attenuation coefficients and mitotic value.…”

Section: Discussionsupporting

confidence: 89%

Risk stratification in GIST: shape quantification with CT is a predictive factor

Wei

Liang

et al. 2020

Eur Radiol

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Background Tumor shape is strongly associated with some tumor's genomic subtypes and patient outcomes. Our purpose is to find the relationship between risk stratification and the shape of GISTs. Methods A total of 101 patients with primary GISTs were confirmed by pathology and immunohistochemistry and underwent enhanced CT examination. All lesions' pathologic sizes were 1 to 10 cm. Points A and B were the extremities of the longest diameter (LD) of the tumor and points C and D the extremities of the small axis, which was the longest diameter perpendicular to AB. The four angles of the quadrangle ABCD were measured and each angle named by its summit (A, B, C, D). For regular lesions, we took angles A and B as big angle (BiA) and small angle (SmA). For irregular lesions, we compared A/B ratio and D/C ratio and selected the larger ratio for analysis. The chi-square test, t test, ROC analysis, and hierarchical or binary logistic regression analysis were used to analyze the data. Results The BiA/SmA ratio was an independent predictor for risk level of GISTs (p = 0.019). With threshold of BiA at 90.5°, BiA/SmA ratio at 1.35 and LD at 6.15 cm, the sensitivities for high-risk GISTs were 82.4%, 85.3%, and 83.8%, respectively; the specificities were 87.1%, 71%, and 77.4%, respectively; and the AUCs were 0.852, 0.818, and 0.844, respectively. LD could not effectively distinguish between intermediate-risk and high-risk GISTs, but BiA could (p < 0.05). Shape and Ki-67 were independent predictors of the mitotic value (p = 0.036 and p < 0.001, respectively), and the accuracy was 87.8%. Conclusions Quantifying tumor shape has better predictive efficacy than LD in predicting the risk level and mitotic value of GISTs, especially for high-risk grading and mitotic value > 5/50HPF. Key Points • The BiA/SmA ratio was an independent predictor affecting the risk level of GISTs. LD could not effectively distinguish between intermediate-risk and high-risk GISTs, but BiA could. • Shape and Ki-67 were independent predictors of the mitotic value.• The method for quantifying the tumor shape has better predictive efficacy than LD in predicting the risk level and mitotic value of GISTs.

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Section: Discussionsupporting

confidence: 89%

Risk stratification in GIST: shape quantification with CT is a predictive factor

Wei

Liang

et al. 2020

Eur Radiol

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“…The maximal diameter on the largest cross section of tumor in highmalignant potential GISTs was larger than that in lowmalignant GISTs in both the training and validation sets (p values < 0.001, respectively) (Table 3), the results of this study are consistent with the conclusion of the above reports. Similarly, some scholars believe that the presence of cystic degeneration and necrosis within the mass can be used as a reliable index to evaluate GISTs malignancy [32,33]. This hypothesis may be related to the fact that with the increase of malignancy of tumors, cystic degeneration and necrosis are more likely to occur inside the mass when the rate of differentiation and proliferation of tumor cells far exceeds the rate of proliferation of blood vessels.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors

2020

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Background: Gastrointestinal stromal tumors (GISTs), which are the most common mesenchymal tumors of the digestive system, are treated varyingly according to the malignancy. The purpose of this study is to develop and validate a nomogram for preoperative prediction of the malignant potential in patients with GIST. Methods: A total of 440 patients with pathologically confirmed GIST after surgery in our hospital from January 2011 to July 2019 were retrospectively analyzed. They were randomly divided into the training set (n = 308) and validation set (n = 132). CT signs and texture features of each patient were analyzed and predictive model were developed using the least absolute shrinkage and selection operator (lasso) regression. Then a nomogram based on selected parameters was developed. The predictive effectiveness of nomogram was evaluated by the area under receiver operating characteristic (ROC) curve (AUC). Concordance index (C-index) and calibration plots were formulated to evaluate the reliability and accuracy of the nomogram by bootstrapping based on internal (training set) and external (validation set) validity. The clinical application value of the nomogram was determined through the decision curve analysis (DCA).Results: Totally 156 GIST patients with low-malignant (very low and low risk) and 284 ones with high-malignant potential (intermediate and high risk) are enrolled in this study. The prediction nomogram consisting of size, cystoid variation and meanValue had an excellent discrimination both in training and validation sets (AUCs (95% confidence interval(CI)): 0.935 (0.908, 0.961), 0.933 (0.892, 0.974); C-indices (95% CI): 0.941 (0.912, 0.956), 0.935 (0.901, 0.982); sensitivity: 81.4, 90.6%; specificity: 75.0, 75.7%; accuracy: 88.0, 88.6%, respectively). The calibration curves indicated a good consistency between the actual observation and nomogram prediction for differentiating GIST malignancy. Decision curve analysis demonstrated that the nomogram was clinically useful. Conclusion: This study presents a prediction nomogram that incorporates the CT signs and texture parameter, which can be conveniently used to facilitate the preoperative individualized prediction of malignancy in GIST patients.

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“…Common presentations include vague abdominal pain, palpable mass, gastrointestinal bleeding, fever, anorexia, weight loss, and anemia. Clinical symptoms mostly depend on the size and site of the lesion, with the most common symptom being bleeding into the bowel or abdominal cavity secondary to ulceration of the tumor mucosa [5,7]. Our patient also presented with non-specific symptoms.…”

Section: Discussionmentioning

confidence: 74%

Early Diagnosis and Treatment of a Small Gastric Stromal Tumor – A Case Report and Literature Review

et al. 2020

Asp Biomed Clin Case Rep

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Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract and the stomach is the most affected site. Clinical manifestation is erratic depending on the tumor’s location, size, histological type, and stage. Ultrasound is useful in detecting gastric intramural tumor whereas computed tomography is the imaging modality of choice in further evaluating tumor characteristics and expansion, treatment planning, and monitoring recurrence. Definite diagnosis of GISTs is based on the immunohistochemical study. Early diagnosis and complete surgical resection of the tumor yield good long-term outcomes. We present a case of a small gastric GIST which was early detected and treated and the patient has tumor-free during 8 years of follow-up.

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The roles of CT and EUS in the preoperative evaluation of gastric gastrointestinal stromal tumors larger than 2 cm

Cited by 55 publications

References 28 publications

Risk stratification in GIST: shape quantification with CT is a predictive factor

Risk stratification in GIST: shape quantification with CT is a predictive factor

Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors

Early Diagnosis and Treatment of a Small Gastric Stromal Tumor – A Case Report and Literature Review

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