Differentiation of large (≥ 5 cm) gastrointestinal stromal tumors from benign subepithelial tumors in the stomach: radiologists' performance using CT

Preoperative differentiation of gastric schwannomas and gastrointestinal stromal tumors based on computed tomography: a retrospective multicenter observational study

Introduction

Gastric schwannoma is a rare benign tumor accounting for only 1-2% of alimentary tract mesenchymal tumors. Owing to their low incidence rate, most cases are misdiagnosed as gastrointestinal stromal tumors (GISTs), especially tumors with a diameter of less than 5 cm. Therefore, this study aimed to develop and validate a diagnostic nomogram based on computed tomography (CT) imaging features for the preoperative prediction of gastric schwannomas and GISTs (diameters = 2-5 cm).

Methods

Gastric schwannomas in 47 patients and GISTs in 230 patients were confirmed by surgical pathology. Thirty-four patients with gastric schwannomas and 167 with GISTs admitted between June 2009 and August 2022 at Hospital 1 were retrospectively analyzed as the test and training sets, respectively. Seventy-six patients (13 with gastric schwannomas and 63 with GISTs) were included in the external validation set (June 2017 to September 2022 at Hospital 2). The independent factors for differentiating gastric schwannomas from GISTs were obtained by multivariate logistic regression analysis, and a corresponding nomogram model was established. The accuracy of the nomogram was evaluated using receiver operating characteristic and calibration curves.

Results

Logistic regression analysis showed that the growth pattern (odds ratio [OR] 3.626; 95% confidence interval [CI] 1.105-11.900), absence of necrosis (OR 4.752; 95% CI 1.464-15.424), presence of tumor-associated lymph nodes (OR 23.978; 95% CI 6.499-88.466), the difference between CT values during the portal and arterial phases (OR 1.117; 95% CI 1.042-1.198), and the difference between CT values during the delayed and portal phases (OR 1.159; 95% CI 1.080-1.245) were independent factors in differentiating gastric schwannoma from GIST. The resulting individualized prediction nomogram showed good discrimination in the training (area under the curve [AUC], 0.937; 95% CI, 0.900-0.973) and validation (AUC, 0.921; 95% CI, 0.830-1.000) datasets. The calibration curve showed that the probability of gastric schwannomas predicted using the nomogram agreed well with the actual value.

Conclusion

The proposed nomogram model based on CT imaging features can be used to differentiate gastric schwannoma from GIST before surgery.

Radiomics analysis of contrast-enhanced computerized tomography for differentiation of gastric schwannomas from gastric gastrointestinal stromal tumors

PURPOSE

To assess the performance of radiomics-based analysis of contrast-enhanced computerized tomography (CE-CT) images for distinguishing GS from gastric GIST.

METHODS

Forty-nine patients with GS and two hundred fifty-three with GIST were enrolled in this retrospective study. CT features were evaluated by two associate chief radiologists. Radiomics features were extracted from portal venous phase images using Pyradiomics software. A non-radiomics dataset (combination of clinical characteristics and radiologist-determined CT features) and a radiomics dataset were used to build stepwise logistic regression and least absolute shrinkage and selection operator (LASSO) logistic regression models, respectively. Model performance was evaluated according to sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve, and Delong's test was applied to compare the area under the curve (AUC) between different models.

RESULTS

A total of 1223 radiomics features were extracted from portal venous phase images. After reducing dimensions by calculating Pearson correlation coefficients (PCCs), 20 radiomics features, 20 clinical characteristics + CT features were used to build the models, respectively. The AUC values for the models using radiomics features and those using clinical features were more than 0.900 for both the training and validation groups. There were no significant differences in predictive performance between the radiomic and clinical data models according to Delong's test.

CONCLUSION

A radiomics-based model applied to CE-CT images showed comparable predictive performance to senior physicians in the differentiation of GS from GIST.

Factors associated with gastrointestinal stromal tumor rupture and pathological risk: A single-center retrospective study

BACKGROUND

Gastrointestinal stromal tumor (GIST) is a rare gastrointestinal mesenchymal tumor with potential malignancy. Once the tumor ruptures, regardless of tumor size and mitotic number, it can be identified into a high-risk group. It is of great significance for the diagnosis, treatment, and prognosis of GIST if non-invasive examination can be performed before surgery to accurately assess the risk of tumor.

AIM

To identify the factors associated with GIST rupture and pathological risk.

METHODS

A cohort of 50 patients with GISTs, as confirmed by postoperative pathology, was selected from our hospital. Clinicopathological and computed tomography data of the patients were collected. Logistic regression analysis was used to evaluate factors associated with GIST rupture and pathological risk grade.

RESULTS

Pathological risk grade, tumor diameter, tumor morphology, internal necrosis, gas-liquid interface, and Ki-67 index exhibited significant associations with GIST rupture (P < 0.05). Gender, tumor diameter, tumor rupture, and Ki-67 index were found to be correlated with pathological risk grade of GIST (P < 0.05). Multifactorial logistic regression analysis revealed that male gender and tumor diameter ≥ 10 cm were independent predictors of a high pathological risk grade of GIST [odds ratio (OR) = 11.12, 95% confidence interval (95%CI): 1.81-68.52, P = 0.01; OR = 22.96, 95%CI: 2.19-240.93, P = 0.01]. Tumor diameter ≥ 10 cm, irregular shape, internal necrosis, gas-liquid interface, and Ki-67 index ≥ 10 were identified as independent predictors of a high risk of GIST rupture (OR = 9.67, 95%CI: 2.15-43.56, P = 0.01; OR = 35.44, 95%CI: 4.01-313.38, P < 0.01; OR = 18.75, 95%CI: 3.40-103.34, P < 0.01; OR = 27.00, 95%CI: 3.10-235.02, P < 0.01; OR = 4.43, 95%CI: 1.10-17.92, P = 0.04).

CONCLUSION

Tumor diameter, tumor morphology, internal necrosis, gas-liquid, and Ki-67 index are associated with GIST rupture, while gender and tumor diameter are linked to the pathological risk of GIST. These findings contribute to our understanding of GIST and may inform non-invasive examination strategies and risk assessment for this condition.

Clinical significance of dual-energy dual-layer CT parameters in differentiating small-sized gastrointestinal stromal tumors from leiomyomas

PURPOSE

Small gastrointestinal stromal tumors (GISTs) can generally have nonspecific CT findings similar to those with benign submucosal tumors of the stomach. The purpose of this study was to explore the potential dual-layer dual-energy CT (dlDECT) parameters to differentiate small-sized (≤ 4 cm) GISTs from leiomyomas of the stomach.

MATERIALS AND METHODS

This retrospective study included 26 SMTs ≤ 4 cm in diameter with pathological confirmation of either GIST (n = 17) or leiomyoma (n = 9) from May 2018 to January 2022. All patients received contrast-enhanced CT. The normalized iodine concentration (NIC) and spectral slope (λHU) were compared between GIST and leiomyoma. Receiver-operating characteristic (ROC) curves were plotted and the areas under the curve (AUCs) were calculated to estimate the diagnostic performance of these markers for differentiating GISTs from leiomyomas.

RESULTS

NIC was significantly higher in GIST than in leiomyoma in the portal (P = 0.0019) and delayed phases (P = 0.0011). λHU was significantly higher in GIST than in leiomyoma in the portal (P = 0.0006) and delayed phases (P = 0.0009). AUC of the ROC curves using NIC to differentiate between GIST and leiomyoma were 0.875 and 0.895 in the portal and delayed phase; using λHU, they were 0.918 and 0.902 in the portal and delayed phase.

CONCLUSION

dlDECT parameters including NIC and λHU show promise as indicators for differentiating small-sized GISTs from leiomyomas.

Differentiating gastric schwannoma from gastric stromal tumor (≤5 cm) by histogram analysis based on iodine-based material decomposition images: a preliminary study

Objective

This study aims to investigate the value of histogram analysis based on iodine-based material decomposition (IMD) images obtained through dual-energy computed tomography (DECT) to differentiate gastric schwannoma (GS) from gastric stromal tumor (GST) (≤5 cm) preoperatively.

Methods

From January 2015 to January 2023, 15 patients with GS and 30 patients with GST (≤5 cm) who underwent biphasic contrast-enhanced scans using DECT were enrolled in this study. For each tumor, we reconstructed IMD images at the arterial phase (AP) and venous phase (VP). Nine histogram parameters were automatically extracted and selected using MaZda software based on the IMD of AP and VP, respectively, including mean, 1st, 10th, 50th, 90th, and 99th percentile of the iodine concentration value (Perc.01, Perc.10, Perc.50, Perc.90, and Perc.99), variance, skewness, and kurtosis. The extracted IMD histogram parameters were compared using the Mann-Whitney U-test. The optimal IMD histogram parameters were selected using receiver operating characteristic (ROC) curves.

Results

Among the IMD histogram parameters of AP, the mean, Perc.50, Perc.90, Perc.99, variance, and skewness of the GS group were lower than that of the GST group (all P < 0.05). Among the IMD histogram parameters of VP, Perc.90, Perc.99, and the variance of the GS group was lower than those of the GST group (all P < 0.05). The ROC analysis showed that Perc.99 (AP) generated the best diagnostic performance with the area under the curve, sensitivity, and specificity being 0.960, 86.67%, and 93.33%, respectively, when using 71.00 as the optimal threshold.

Conclusion

Histogram analysis based on IMD images obtained through DECT holds promise as a valuable tool for the preoperative distinction between GS and GST (≤5 cm).

Machine learning-based predictive model for the differential diagnosis of ≤ 5 cm gastric stromal tumor and gastric schwannoma based on CT images

The clinical symptoms of ≤ 5 cm gastric stromal tumor (GST) and gastric schwannoma (GS) are similar, but the treatment regimens are different. This study explored the value of computed tomography (CT) combined with machine learning (ML) algorithms to find the best model to discriminate them. A total of 126 patients with GST ≤ 5 cm and 35 patients with GS ≤ 5 during 2013-2022 were included. CT imaging features included qualitative data (tumor location, growth pattern, lobulation, surface ulcer status, necrosis, calcification, and surrounding lymph nodes) and quantitative data [long diameter (LD); short diameter (SD); LD/SD ratio; degree of enhancement (DE); heterogeneous degree (HD)]. Patients were randomly divided into a training set (n = 112) and test set (n = 49) using 7:3 stratified sampling. The univariate and multivariate logistic regression analysis were used to identify independent risk factors. Five ML algorithms were used to build prediction models: Support Vector Machine, k-Nearest Neighbor, Random Forest, Extra Trees, and Extreme Gradient Boosting Machine. The analysis identified that HDv, lobulation, and tumor growth site were independent risk factors (P < 0.05). We should focus on these three imaging features of tumors, which are relatively easy to obtain. The area under the curve for the SVM, KNN, RF, ET, and XGBoost prediction models were, respectively, 0.790, 0.895, 0.978, 0.988, and 0.946 for the training set, and were, respectively, 0.848, 0.892, 0.887, 0.912, and 0.867 for the test set. The CT combined with ML algorithms generated predictive models to improve the differential diagnosis of ≤ 5 cm GST and GS which has important clinical practical value. The Extra Trees algorithm resulted in the optimal model.

Laparoscopic resection for gastric schwannoma larger than 30 mm with long-term outcomes

BACKGROUND AND AIMS

Laparoscopic resection has been reported as effective and safe for gastric schwannoma (GS) in the form of case reports. However, study on laparoscopic surgery in patients with GS larger than 30 mm has been rarely reported. To this end, the present study aimed to evaluate the safety and efficacy of laparoscopic resection for the treatment of GS larger than 30 mm and its long-term outcomes.

METHODS

This is a retrospective case series study of patients with GS larger than 30 mm who underwent laparoscopic resection at our hospital between January 2014 and December 2020. Clinical pathology, surgical and follow-up data were collected and analyzed.

RESULTS

A total of 10 patients with a mean age of 51.6 years were included. Seven tumors were located in gastric body, 2 in antrum and 1 in fundus. Laparoscopic gastric wedge resection was performed in 7 patients, while laparoscopic gastric local resection was performed in 3 patients. All patients achieved complete resection. The mean operation time was 112.6 ± 34.3 min, and the mean postoperative hospital stay was 13.8 ± 5.1 days. Postoperative gastroplegia occurred in 2 patients and was treated with conservative therapy. No recurrence, metastasis or residue was found during the follow-up of mean 45.1 months.

CONCLUSIONS

Laparoscopic resection is a safe and effective method for treating GS larger than 30 mm with favorable long-term follow-up outcomes. Laparoscopic resection may be considered as the first-line treatment for GS larger than 30 mm.

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors

Purpose

To develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs).

Methods

This retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS.

Results

The CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874-0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850.

Conclusions

The PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery.

Laparoscopic transgastric enucleation of a giant leiomyoma near the esophagogastric junction: A case report

INTRODUCTION AND IMPORTANCE

Gastric subepithelial tumors are surgically treated by tumorectomy without lymphadectomy, and many operations are currently performed via the minimally invasive technique. However, when they occur near the esophagogastric junction and the pyloric ring, there is a possibility that subtotal or total gastrectomy is required for tumor resection.

CASE PRESENTATION

An 18-year-old man presented with anemia. A giant subepithelial tumor near the esophagogastric junction was seen on a gastroscopy performed to find the cause of anemia. A computed tomography scan revealed a 7.5-cm homogeneous soft tissue mass near the esophagogastric junction, suggesting leiomyoma or gastrointestinal stromal tumors as gastric subepithelial tumors. Endoscopic ultrasound revealed an inhomogeneous and hypoechoic mass, consistent with a gastrointestinal stromal tumor. An endoscopic ultrasound-guided fine needle biopsy was performed, resulting in a diagnosis of leiomyoma. We performed the laparoscopic transgastric enucleation, and the final pathology report showed complete resection of a benign leiomyoma.

CLINICAL DISCUSSION

Laparoscopic surgery may be challenging for subepithelial tumors of the esophagogastric junction, but laparoscopic transgastric enucleation may be considered if the lesion is benign after a fine needle biopsy.

CONCLUSION

We report a case of a very young patient for whom laparoscopic transgastric enucleation of a giant gastric leiomyoma near the esophagogastric junction was a feasible organ-sparing procedure.

Differentiation of Small Gastrointestinal Stromal Tumor and Gastric Leiomyoma with Contrast-Enhanced CT

Objective

The value of multiphase contrast-enhanced CT in differentiating gastrointestinal stromal tumors (GISTs) and gastric leiomyomas (GLMs) which were ≤3 cm was evaluated using machine learning.

Methods

A retrospective analysis was conducted on 45 cases of small gastric wall submucosal tumors (including 22 GISTs and 23 GLMs) with pathologically confirmed diameter ≤3 cm and completed multiphase CT-enhanced scan images. The CT features including tumor location, maximum diameter, shape, margins, growth pattern, plain/enhanced CT value, cystic degeneration, calcification, ulcer, progressive reinforcement, perilesional lymph nodes, and the CT value ratio of the tumor to the aorta at the same level in the enhanced phase III scan of the two groups were evaluated. Tumor location and maximum diameter were automatically evaluated by machine learning.

Results

The GISTs and GLMs with a diameter ≤3 cm showed clear margins, uniform density on plain scan CT, and progressive homogeneous enhancement. The age of the GISTs is greater than that of the GLMs group. The plain scan CT value of the GISTs group was lower than that in the GLMs group. In the GISTs group, the lesions were mostly located in the fundus (68.18%), showing a mixed growth pattern (54.55%), and in the GLMs group, most lesions were located in the cardia (47.82%), showing an intraluminal growth pattern (95.65%). The abovementioned differences were statistically significant.

Conclusions

Contrast-enhanced CT has limited value in differentiating small GISTs from GLMs, which are ≤3 cm. Older age (>49.0 years), a low plain CT value (<42.5 Hu), mixed growth inside and outside the cavity, and noncardiac location tended to be the criteria for the diagnosis of small GISTs of the gastric wall.

Surgery for mesenchymal neoplasms of the esophagus: experience over 2 decades from a tertiary healthcare center in India

Mesenchymal tumors are the most common benign neoplasms of the esophagus. Owing to the rarity of these neoplasms, there is a dearth of literature regarding their diagnosis and management. Our 2-decade-long experience in managing these neoplasms surgically is presented. Relevant clinical data of all patients with esophageal mesenchymal neoplasms (EMNs) managed between January 2000 and May 2020 were retrospectively collected from a prospectively maintained esophageal diseases database in the Department of GI Surgery, AIIMS, New Delhi (India). Special emphasis was given to data pertaining to diagnostic evaluation of patients, type of surgery done (enucleation vs. resection), postoperative outcomes, histopathology and long-term follow-up. Nineteen patients (12 females; age 15-66 years) underwent surgery for EMN (mean tumor size 7.6 cm; enucleation 10; resection 9). On histopathological examination, 17 cases were noted to be benign esophageal leiomyomas and 2 were identified as gastrointestinal stromal tumors. There was no perioperative mortality. All cases were followed up for a median duration of 6 years (range 1-19 years) with no evidence of recurrence in any case. Though EMNs are uncommon, they are mostly benign, and the long-term outcomes after surgical excision are gratifying.

Scoring systems for differentiating gastrointestinal stromal tumors and schwannomas from leiomyomas in the stomach

There is no practical predictive model for the diagnosis of gastrointestinal stromal tumors (GISTs). To establish a practical predictive model for the diagnosis of subepithelial lesions in the stomach, we reviewed patients with GISTs (n = 89), schwannomas (n = 7), and leiomyomas (n = 28).The tumor was more frequently found along the gastric cardia in the leiomyoma group (57.1%) than in the GIST/schwannoma group (2.1%, P < .01). Contrast enhancement (57.3% vs 0%, P < .01) and intra-tumoral necrosis (34.4% vs 0.0%, P < .01) were more frequently observed in the GIST/schwannoma group than in the leiomyoma group. On endoscopic ultrasonography, 58.3% of GISTs/schwannomas showed uneven echogenicity, whereas the echogenicity was uneven in 21.4% of leiomyomas (P < .01). There were no differences between the tumor color and the presence or absence of ulcer formation, tumor bleeding, irregularity of the tumor margin, cystic spaces, and hyperechoic spots between the 2 groups. Based on these results, we developed a 2-step diagnostic algorithm for GISTs/schwannomas. The first step comprises 1 endoscopic feature: a cardiac or non-cardiac location. Tumors with a cardiac location were judged as leiomyomas and those with a non-cardiac location were judged as GISTs/schwannomas, with 96.9% sensitivity and 57.1% specificity for GIST/schwannoma diagnosis. The second step comprises a combination of endoscopic (non-cardiac location), radiologic (positive contrast enhancement and intra-tumoral necrosis), and endosonographic (uneven echogenicity) features for a total of 4 points. We assigned 1 point to each feature. Tumors with scores of 2 to 4 were judged as GISTs/schwannomas, with 81.3% sensitivity and 92.9% specificity for GIST/schwannoma diagnosis.Our predictive model will be a practical guide for the management of gastric subepithelial lesions.

Perilesional Lymph Node Swelling Might Be a Radiologic Clue for Appendiceal Schwannoma: A Case Report

BACKGROUND

Gastrointestinal schwannoma is not a common type of tumor, and lesions originating from the appendix are extremely rare. Herein, we report a patient with appendiceal schwannoma characterized by lymph node swelling.

CASE REPORT

A 67-year-old male patient who had diabetes complained of weight loss. A computed tomography scan revealed a mass in the right side of the pelvic cavity. Moreover, a contrast-enhanced computed tomography scan showed perilesional lymph node swelling measuring up to 28 mm. A low-intensity mass was observed on T1-weighted imaging, heterogeneous high-intensity mass on T2-weighted imaging, and restricted diffusion on diffusion-weighted imaging. There were no abnormal findings on colonoscopy. Based on a preoperative examination, a differential diagnosis of either appendiceal schwannoma, carcinoid, or gastrointestinal stromal tumor was considered. During surgery, a large appendiceal mass and multiple swollen perilesional lymph nodes were observed. Therefore, ileocecal resection and D3 lymph node dissection were performed. Pathological and immunohistochemical analyses confirmed the diagnosis of appendiceal schwannoma. There were numerous swollen lymph nodes in the mesenteric region. The lymph nodes revealed reactive lymphoid hyperplasia, with enlarged follicles of various sizes and shapes with an irregular distribution. Almost all lymphocytes, except those at the germinal centers, were small.

CONCLUSION

Gastrointestinal schwannoma is characterized by lymph node swelling. Appendiceal schwannoma may have characteristics, including peritumoral lymph node swelling, similar to other types of gastrointestinal schwannoma such as that in the stomach. Thus, this characteristic can be a diagnostic clue for appendiceal schwannoma.

Differentiation of gastric schwannomas from gastrointestinal stromal tumors by CT using machine learning

OBJECTIVE

To identify schwannomas from gastrointestinal stromal tumors (GISTs) by CT features using Logistic Regression (LR), Decision Trees (DT), Random Forest (RF), and Gradient Boosting Decision Tree (GBDT).

METHODS

This study enrolled 49 patients with schwannomas and 139 with GISTs proven by pathology. CT features with P < 0.1 derived from univariate analysis were inputted to four models. Five machine learning (ML) versions, multivariate analysis, and radiologists' subjective diagnostic performance were compared to evaluate diagnosis performance of all the traditional and advanced methods.

RESULTS

The CT features with P < 0.1 were as follows: (1) CT attenuation value of unenhancement phase (CTU), (2) portal venous enhancement (CTV), (3) degree of enhancement in the portal venous phase (DEPP), (4) CT attenuation value of portal venous phase minus arterial phase (CTV-CTA), (5) enhanced potentiality (EP), (6) location, (7) contour, (8) growth pattern, (9) necrosis, (10) surface ulceration, (11) enlarged lymph node (LN). LR (M1), RF, DT, and GBDT models contained all of the above 11 variables, while LR (M2) was developed using six most predictive variables derived from (M1). LR (M2) model with AUC of 0.967 in test dataset was thought to be optimal model in differentiating the two tumors. Location in gastric body, exophytic and mixed growth pattern, lack of necrosis and surface ulceration, enlarged lymph nodes, and larger EP were the most important CT features suggestive of schwannomas.

CONCLUSION

LR (M2) provided the optimal diagnostic potency among other ML versions, multivariate analysis, and radiologists' performance on differentiation of schwannomas from GISTs.

Unusual Case of an Exophytic Leiomyoma of Rectum Mimicking Malignancy on 18F-FDG PET/CT

Rectal leiomyoma is an exceedingly rare benign lesion. We here report a case with extraluminal leiomyoma of the middle and lower parts of the rectum showing aberrant hypermetabolism on F-FDG PET/CT in a 54-year-old man.

A scoring model for radiologic diagnosis of gastric leiomyomas (GLMs) with contrast-enhanced computed tomography (CE-CT): Differential diagnosis from gastrointestinal stromal tumors (GISTs)

OBJECTIVES

To investigate CT findings and develop a diagnostic score model to differentiate GLMs from GISTs.

METHODS

This retrospective study included 109 patients with pathologically confirmed GLMs (n = 46) and GISTs (n = 63) from January 2013 to August 2018 who received CE-CT before surgery. Demographic and radiological features was collected, including lesion location, contour, presence or absence of intralesional necrosis and ulceration, growth pattern, whether the tumor involved EGJ, the long diameter (LD) /the short diameter (SD) ratio, pattern and degree of lesion enhancement. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors and establish a predictive model. Independent predictors for GLMs were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the model. Overall score distribution was divided into four groups to show differentiating probability of GLMs from GISTs.

RESULTS

Five CT features were the independent predictors for GLMs diagnosis in multivariate logistic regression analysis, including esophagogastric junction (EGJ) involvement (OR, 367.9; 95 % CI, 5.8-23302.8; P =  0.005), absence of necrosis (OR, 11.9; 95 % CI, 1.0-138. 1; P =  0.048) and ulceration (OR, 151.9; 95 % CI, 1.4-16899.6; P =  0.037), degree of enhancement (OR, 9.3; 95 % CI, 3.2-27.4; P <  0.001), and long diameter/ short diameter (LD/SD) ratio (OR,170.9; 95 % CI, 8.4-3493.4; P =  0.001). At a cutoff of 9 points, AUC for this score model was 0.95, with 95.65 % sensitivity, 79.37 % specificity, 77.19 % PPV, 96.15 % NPV and 86.24 % diagnostic accuracy. An increasing trend was showed in diagnostic probability of GLMs among four groups based on the score (P <  0.001).

CONCLUSIONS

The newly designed scoring system is reliable and easy-to-use for GLMs diagnosis by distinguishing from GISTs, including EGJ involvement, absence of ulceration and necrosis, mild enhancement and high LD/SD ratio. The overall score of model ranged from 1 to 17 points, which was divided into 4 groups: 1-7 points, 7-10 points, 10-13 points and 13-17 points, with a diagnostic probability of GLMs 0%, 45 %, 83 % and 100 %, respectively.

Occult follicular lymphoma in a swollen regional lymph node of gastric schwannoma

Background

Regional lymphadenopathy is more commonly noted in gastric schwannomas than in other gastric submucosal tumors. Most of the swollen lymph nodes associated with gastric schwannomas are non-metastatic lymphadenopathy.

Case presentation

A 69-year-old Japanese woman was referred to our hospital with a chief complaint of abdominal discomfort. Contrast-enhanced computed tomography (CT) of the abdomen revealed an extraluminal tumor with heterogeneous enhancement at the middle stomach on the lesser curve, accompanied with one swollen lymph node approximately 10 mm in size and several small lymph nodes in the perigastric region. These lymph nodes were flat; therefore, we considered them to be non-metastatic. The main tumor was removed via wedge resection. Soft and slightly swollen lymph nodes, which were compatible with the lymph nodes noted in the preoperative CT, were found near the main tumor in the fatty tissue at the lesser curvature of the stomach. An excisional biopsy of the largest lymph node was performed for the diagnosis. Based on pathological findings, a diagnosis of gastric schwannoma and follicular lymphoma (FL) was confirmed. The patient is doing well without recurrence of either the gastric schwannoma or FL 28 months postsurgery.

Conclusions

The present report detailed an extremely rare case of FL coincidentally discovered in the swollen regional lymph node of gastric schwannoma.

Differential diagnosis of liver metastases of gastrointestinal stromal tumors from colorectal cancer based on combined tumor biomarker with features of conventional ultrasound and contrast-enhanced ultrasound

PURPOSE

To explore the value of tumor marker CA125 and CEA linked with conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) features in differentiating gastrointestinal stromal tumors liver metastases (GISTLM) from colorectal cancer liver metastases (CRCLM).

MATERIALS AND METHODS

From December 2005 to February 2019, eighty patients with pathologically proven GISTLM together with 80 CRCLM patients were retrospectively evaluated with contrast-enhanced ultrasound (CEUS). Clinical characteristics such as CA125 and CEA were documented to compare the difference between GISTLM and CRCLM. Univariate analysis was performed to determine significant features in ultrasound and then these features were entered into multivariate logistic regression model to determine diagnostic criteria. By analyzing the tumor marker and imaging features, diagnostic performance was evaluated via receiver-operating characteristic (ROC) analysis. The sensitivity, specificity and accuracy were calculated for the diagnosis of GISTLM.

RESULTS

Multiple logistic regression analysis showed that increased CA125 and normal CEA were the independent variables of GISTLM. On conventional US, the features of hypo- or mix-echogenicity and anechoic area were associated with GISTLM. On CEUS, capsule enhancement, starting time of washout > 40 s and proportion of non-enhancement area > 20% were the features indicating GISTLM. All of the p values were < 0.05. When linking tumor marker with imaging features, the diagnostic sensitivity improved from 36.3-57.5% to 70.0%, and the area under the ROC (AUROC) curve improved from 0.681-0.750 to 0.838, with a specificity of 97.5%.

CONCLUSIONS

Combining the imaging features of conventional US and CEUS with serum tumor markers provides a potentially effective diagnostic method in differentiation of GISTLM and CRCLM.

New advances in radiomics of gastrointestinal stromal tumors

Gastrointestinal stromal tumors (GISTs) are uncommon neoplasms of the gastrointestinal tract with peculiar clinical, genetic, and imaging characteristics. Preoperative knowledge of risk stratification and mutational status is crucial to guide the appropriate patients’ treatment. Predicting the clinical behavior and biological aggressiveness of GISTs based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) evaluation is challenging, unless the lesions have already metastasized at the time of diagnosis. Radiomics is emerging as a promising tool for the quantification of lesion heterogeneity on radiological images, extracting additional data that cannot be assessed by visual analysis. Radiomics applications have been explored for the differential diagnosis of GISTs from other gastrointestinal neoplasms, risk stratification and prediction of prognosis after surgical resection, and evaluation of mutational status in GISTs. The published researches on GISTs radiomics have obtained excellent performance of derived radiomics models on CT and MRI. However, lack of standardization and differences in study methodology challenge the application of radiomics in clinical practice. The purpose of this review is to describe the new advances of radiomics applied to CT and MRI for the evaluation of gastrointestinal stromal tumors, discuss the potential clinical applications that may impact patients’ management, report limitations of current radiomics studies, and future directions.

Differentiation of gastric glomus tumor from small gastric stromal tumor by computed tomography

OBJECTIVE

This study was performed to investigate the value of computed tomography (CT) in the differentiation of gastric glomus tumors (GGTs) and small gastric stromal tumors (GSTs).

METHODS

Fifty-nine patients with pathologically confirmed GGTs (n = 11) and GSTs (n = 48) from 2006 to 2019 were retrospectively evaluated. All patients' preoperative CT imaging features were analyzed.

RESULTS

The following features were significantly different between GGTs and small GSTs: location in the antrum, endophytic growth, heterogeneous enhancement in the arterial phase, CT value in the arterial phase of ≥60.7 Hounsfield units (HU), CT value in the portal phase of ≥87.6 HU, degree of enhancement in the arterial phase of ≥29.9 HU, and degree of enhancement in the portal phase of ≥49.0 HU. A model including four randomly selected features among these seven criteria was built to differentiate GGTs from small GSTs with a sensitivity and specificity of 90.9% (10/11) and 100% (48/48), respectively.

CONCLUSION

We identified seven features that are useful for differentiating GGTs from small GSTs. A combination of four of these seven criteria may increase the diagnostic accuracy.

Case reports on a gastric mass presenting with regional lymphadenopathy: A differential diagnosis is gastric schwannoma

BACKGROUND

Gastric schwannomas are uncommon among a broad range of possible diagnoses in the work up of a gastric mass. Regional lymphadenopathy associated with gastric schwannoma is an even less common occurrence and one would otherwise suspect a malignant neoplasm.

CASE PRESENTATION

We present two non-consecutive cases from a signle academic center depicting Caucasian females in their 5th and 6th decades of life with gastric schwannoma and adjacent lymphadenopathy. Multiple lymph node excisions were performed without evidence of neoplasia.

DISCUSSION

Lymphadanopathy in the presence of a gastric mass typically represents malignant neoplasm. A less than likely presentation of gastric schwannoma with reactive regional lymph nodes poses a challenge to adequate preoperative diagnosis and increases risk for a more aggressive than necessary surgical approach with lymphadenectomy.

CONCLUSION

While the correlation between gastric schwannoma and lymphadenopathy is uncertain, this ought to be considered. If diagnosis can be confirmed preoperatively, omission of lymphadenectomy is appropriate.

Difference of computed tomographic characteristic findings between gastric and intestinal gastrointestinal stromal tumors

PURPOSE

We aimed to compare the computed tomography (CT) imaging differences between gastric and intestinal gastrointestinal stromal tumors (GISTs).

MATERIALS AND METHODS

Thirty-eight patients with 38 gastric GISTs and 27 with 31 intestinal GISTs were enrolled. Tumors were classified as small (< 5 cm) or large (≥ 5 cm). Qualitative and quantitative CT imaging characteristics on non-contrast and contrast-enhanced CT were evaluated by two radiologists independently and statistically compared.

RESULTS

Early venous return and higher CT number of the draining vein in the arterial phase were more frequent in small-sized intestinal GISTs than in small-sized gastric GISTs (p < 0.001). Small-sized intestinal GISTs demonstrated a wash-out pattern, whereas small-sized gastric GISTs showed a plateau pattern. Contrast enhancement was higher in small-sized intestinal GISTs than in small-sized gastric GISTs (p < 0.001). CT number was inversely proportional to the diameter of intestinal GISTs in both arterial and venous phases but not to that of gastric GISTs.

CONCLUSION

Strong enhancement with wash-out pattern and early venous return are characteristic findings of small-sized intestinal GISTs. Radiologists should be aware that CT findings of GISTs have a wide spectrum and may differ according to size and site of origin.

Identification of gastrointestinal stromal tumors from leiomyomas in the esophagogastric junction: A single-center review of 136 cases

To identify significant clinical and CT features for the differentiation of gastrointestinal stromal tumors (GISTs) from leiomyomas in the esophagogastric junction (EGJ).One hundred thirty six patients with pathologically proven GISTs (n = 87) and leiomyomas (n = 49) in the EGJ were enrolled. And preoperative CT images were available in 73 GISTs cases and 34 leiomyoma cases. Two radiologists reviewed the CT images by consensus with regard to tumor size, shape, growth pattern, surface, enhancement pattern, enhancement degree, attention at each phasic image and the presence of surface ulcer, calcification, and intralesional low attention.Eight significant clinical and CT features were identified for differentiating GISTs from leiomyomas: older age (>46.5 years), tumor long diameter >4.5 cm, heterogeneous enhancement, high degree enhancement, mean CT attenuation >69.2 HU, presences of intralesional low attenuation and surface ulcer, absences of calcification (P < .05). On the receiver operating characteristic curve analysis, an optimal cutoff score of 3.5 was achieved for differentiating GISTs from leiomyomas with an AUC of 0.844 (sensitivity: 76.7%, specificity: 76.5%).older age (>46.5 years), tumor long diameter >4.5 cm, heterogeneous enhancement, high degree enhancement, mean CT attenuation >69.2 HU, presences of intralesional low attenuation and surface ulcer, absence of calcification are significant features highly suggestive of GISTs in differentiation from leiomyomas in the EGJ.

Value of CT Imaging in the Differentiation of Gastric Leiomyoma From Gastric Stromal Tumor

Purpose:

To discuss significant computed tomography (CT) findings that differentiate gastric leiomyomas (GLs) from small gastric stromal tumors (GSTs).

Methods:

One hundred sixty cases with pathologically proven GLs (n = 50) and GSTs (n = 110) with comprehensive CT images were enrolled in this retrospective study. Computed tomography findings (ie, size, location, contour, growth pattern, enhancement degree, necrosis, ulceration, calcification, and lymph nodes) were analyzed through the χ2 or Fisher exact test, independent T test, and multivariate (logistic regression) analysis. Sensitivity and specificity were also calculated.

Results:

Features of cardia location, endophytic growth, homogeneous gradual enhancement, absent of necrosis, long diameter less than 24 mm, short diameter less than 20 mm, unenhanced CT value larger than 35.2 Hounsfield units (HU), portal venous phase CT value larger than 67.4 HU, and enhancement degree of arterial and venous phase less than 16.2 HU and 32.4 HU were found to be statistically significant between GLs and small GSTs ( P < .05). On multivariate analysis, cardia location, endophytic growth, and homogeneous gradual enhancement were independent predictive factors for GLs and small GSTs.

Conclusion:

These 10 CT criteria are very helpful to differentiate GLs from small GSTs. Especially cardia location, endophytic growth, and homogeneous gradual enhancement are of high value in differential diagnosis.

Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.

Gastric gastrointestinal stromal tumours (2-5 cm): Correlation of CT features with malignancy and differential diagnosis

PURPOSE

The purpose of this study was to investigate the computed tomography (CT) features of 2-5 cm gastric gastrointestinal stromal tumors (GISTs), schwannomas and leimyomas which have close relationship with malignancy evaluation and differential diagnosis.

METHOD

Seventy-six patients with pathologically confirmed gastric submucosal tumors (SMTs) between 2-5 cm were included in this study, including 60 GISTs, 10 schwannomas and 6 leiomyomas. CT imaging features were reviewed and quantitative parameters including CT values during nonenhanced phase (CTV-N), portal phase (CTV-P) and delayed phase (CTV-D) were recorded. The association of CT features with mitotic counts of GISTs and the significantly different CT features between GISTs and benign SMTs were analyzed.

RESULTS

The lobulated contour was significantly more common in GISTs with high mitoses (P < 0.05). The value of CTV-D/CTV-P was significantly lower in GISTs with high mitoses (P < 0.05) and it was an independent predictor for high-mitosis GISTs (P = 0.049, odds ratio [OR] = 186.445) with an area under the curve (AUC) of 0.722. CT features including heterogeneous enhancement and presence of necrosis or cystic degeneration were significantly suggestive of GISTs instead of benign SMTs (P < 0.05). The value of CTV-D/CTV-P was significantly higher in schwannomas than that in GISTs (P < 0.05) with an AUC of 0.853. The value of CTV-P/CTV-N was significantly lower in leiomyomas than that in GISTs (P < 0.05) with an AUC of 0.883.

CONCLUSIONS

Some qualitative and quantitative parameters on contrast-enhanced CT can be helpful in preoperative diagnosis and risk stratification of 2-5 cm gastric GISTs.

Multiparametric MRI and 18F-FDG PET features for differentiating gastrointestinal stromal tumors from benign gastric subepithelial lesions

OBJECTIVES

To investigate whether multiparametric magnetic resonance imaging (MRI) and ¹⁸F-fluorodeoxyglucose positron emission tomography (PET) can be helpful in differentiating gastrointestinal stromal tumors (GISTs) from non-GISTs and high-risk GISTs from low-risk GISTs.

METHODS

This retrospective study included 56 patients with pathologically confirmed GISTs (n = 39), leiomyoma (n = 8), schwannoma (n = 5), heterotopic pancreas (n = 3), and glomus tumor (n = 1) who underwent MRI and/or PET examinations. Two radiologists reviewed MRI regarding location, shape, contour, growth pattern, margin, signal intensity (SI) on T1- (T1WI) and T2-weighted images (T2WI), degree and pattern of enhancement, hemorrhage, and necrosis. Mean apparent diffusion coefficient (ADC) and maximum standardized uptake value (SUV_max) were measured. Imaging features were compared among non-GISTs, low-risk GISTs, and high-risk GISTs using uni- and multivariate statistical analyses.

RESULTS

Size, longitudinal location, shape, contour, growth pattern, SI on T1- and T2WI, enhancement pattern, hemorrhage, necrosis, ADC, and SUV_max were significantly different among non-GISTs, low-risk GISTs, and high-risk GISTs (p < 0.05). On multivariate analysis, SI on T2WI (hazard ratio [HR], 66.0; p = 0.002) was the only independent variable for differentiating GISTs from non-GISTs whereas enhancement pattern (HR, 56.0; p = 0.041), ADC (HR, 0.997; p = 0.01), and SUV_max (HR, 2.08; p = 0.027) were significant features for differentiating between high-risk and low-risk GISTs.

CONCLUSIONS

Several qualitative and quantitative MRI and PET features including ADC and SUV_max values are significantly different among non-GISTs, low-risk GISTs, and high-risk GISTs. Multiparametric information obtained from MRI with or without PET can be useful for differentiation of gastric subepithelial tumors as well as for determining patients' management and prognosis.

KEY POINTS

• Several qualitative MRI features are helpful in distinguishing gastrointestinal stromal tumors (GISTs) from non-GISTs as well as high-risk GISTs from low-risk GISTs. • Apparent diffusion coefficient value on diffusion-weighted imaging can be useful in distinguishing GISTs from non-GISTs as well as high-risk GISTs from low-risk GISTs. • PET has the potential to distinguish between high-risk and low-risk GISTs.

Gastric sub-epithelial tumors: identification of gastrointestinal stromal tumors using CT with a practical scoring method

OBJECTIVES

To determine CT features that can identify gastrointestinal stromal tumors (GISTs) among gastric sub-epithelial tumors (SETs) and to explore a practical scoring method.

METHODS

Sixty-four patients with gastric SETs (51 GISTs and 13 non-GISTs) from hospital I were included for primary analyses, and 92 (67 GISTs and 25 non-GISTs) from hospital II constituted a validation cohort. Pre-operative CT images were reviewed for imaging features: lesion location, growth pattern, lesion margin, enhancement pattern, dynamic pattern, attenuation at each phasic images and presence of necrosis, superficial ulcer, calcification, and peri-lesion enlarged lymph node (LN). Clinical and CT features were compared between the two groups (GISTs versus non-GISTs) and a GIST-risk scoring method was developed; then, its performance for identifying GISTs was tested in the validation cohort.

RESULTS

Seven clinical and CT features were significantly suggestive of GISTs rather than non-GISTs: older age (> 49 years), non-cardial location, irregular margin, lower attenuation on unenhanced images (≤ 43 HU), heterogeneous enhancement, necrosis, and absence of enlarged LN (p < 0.05). At validation step, the established scoring method with cut-off score dichotomized into ≥ 4 versus < 4 for identifying GISTs revealed an AUC of 0.97 with an accuracy of 92%, a sensitivity of 100% and a negative predictive value (NPV) of 100%.

CONCLUSIONS

Gastric GISTs have special CT and clinical features that differ from non-GISTs. With a simple and practical scoring method based on the significant features, GISTs can be accurately differentiated from non-GISTs.

CT Versus Endoscopic Ultrasound for Differentiating Small (2-5 cm) Gastrointestinal Stromal Tumors From Leiomyomas

OBJECTIVE. Abdominal CT or endoscopic ultrasound is recommended for the evaluation of gastric subepithelial tumors. However, few studies have compared the diagnostic performance of these two methods. We compared the diagnostic performance of CT versus endoscopic ultrasound for gastric subepithelial tumors smaller than 5 cm. We also identified significant CT findings associated with the diagnosis of gastrointestinal stromal tumors. MATERIALS AND METHODS. Seventy-one patients with pathologically proven gastric subepithelial tumors were enrolled. We examined the diagnostic performance of CT compared with endoscopic ultrasound. We analyzed CT findings, including the location, long diameter (LD), short diameter (SD), LD-SD ratio, contour, margin, growth pattern, degree and pattern of enhancement, attenuation value, intralesional necrosis, calcification, hemorrhage, surface dimpling, and perilesional lymph node. RESULTS. Endoscopic ultrasound had a sensitivity of 77.6%, specificity of 61.5%, PPV of 90.0%, NPV of 38.1%, and accuracy of 74.6%. CT had a sensitivity of 84.5%, specificity of 53.8%, PPV of 89.1%, NPV of 43.8%, and accuracy of 78.9%. Multivariate analysis revealed that the presence of intralesional necrosis (odds ratio [OR], 10.88; p = 0.037) and an LD-SD ratio less than 1.5 (OR, 32.37; p = 0.002) were independent CT findings for the diagnosis of gastrointestinal stromal tumors. CONCLUSION. CT is as effective as endoscopic ultrasound for the diagnosis of gastric subepithelial tumors smaller than 5 cm. Tumors with intralesional necrosis and an LD-SD ratio less than 1.5 may require further pathologic diagnosis.

Computed tomographic characteristics of gastric schwannoma

Objective

This study aimed to characterize the computed tomographic (CT) features of gastric schwannoma (GS).

Methods

We retrospectively reviewed CT images of 19 cases of histologically proven GS between January 2010 and December 2015. Tumor location, size, contour, margin, growth pattern, and degree and pattern of enhancement, perigastric lymph nodes, ulceration, necrosis, and calcification were evaluated.

Results

GS was located in the gastric body (73.7%), gastric antrum (15.8%), and gastric fundus (10.5%), with a mean maximum diameter of 4.5 ± 1.8 cm. All tumors presented as oval, well-defined solid masses, with exophytic (36.8%), endoluminal (15.8%), or mixed (47.4%) growth patterns. Ulcers (57.9%) and perigastric lymph nodes (47.4%) were observed. Moderate enhancement (87.5%) was observed in the portal phase. Eighteen (94.7%) cases showed homogeneous enhancement.

Conclusions

GS typically presents as a mass in the stomach with an exophytic or mixed growth pattern, moderate homogeneous enhancement, and is prone to be accompanied by perigastric lymph node inflammatory reactive swelling. Larger GSs are more likely to be associated with ulcers.

Simple Analysis of the Computed Tomography Features of Gastric Schwannoma

OBJECTIVE

The objective of this study was to assess the computed tomography (CT) findings of gastric schwannoma (GS) and identify the difference between large (> 5 cm) and small (≤ 5 cm) GS.

MATERIALS AND METHODS

CT findings of 38 pathologically proven cases of GSs were retrospectively reviewed. The CT evaluation of GS included categorical variables (location, contour, growth pattern, enhancement pattern, necrosis, ulceration, calcification, and lymph nodes) and continuous variables (size, CT value of 3 phases, and enhancement degree). The lesion was divided into 2 groups (large [> 5 cm] and small [≤ 5 cm] GS) according to the tumor size. The Fisher exact test was used for categorical variables and the Student t or Mann-Whitney U test for continuous variables.

RESULTS

Of the 38 patients, there were 32 women and 6 men. The median age was 54.5 years (range 39-79). Most of patients (65.8%, [25 of 38]) had nonspecific gastrointestinal symptoms such as abdominal or gastric pain, fullness and discomfort, bleeding, and melena. The tumors were mainly located in the stomach body (71.1% [27 of 38]), and the mean diameter was 3.7 cm (range 1.5 cm-10.3 cm), of which included large (> 5 cm) (n = 8) and small (≤ 5 cm) (n = 30). All of the GSs were benign, 9 of whom had palpable perigastric lymph nodes, which confirmed by pathology for the reactive inflammatory hyperplasia. Growth pattern, pattern of enhancement, necrosis, calcification, surface ulceration, and lymph node in the CT images were found to be significant variables for differentiating large (> 5 cm) and small (≤ 5 cm) GS (P < .05).

CONCLUSION

GSs were predominantly located at the gastric body and occurred most frequently in women between the ages of 40-70 years, and showed gradual enhancement after contrast enhancement. Palpable perigastric lymph nodes could not be considered as malignant factor of GS. There 7 computed CT criteria are significant difference between large (> 5 cm) and small (≤ 5 cm) GS.

Clinicopathological and morphological spectrum of gastrointestinal stromal tumours on multi-detector computed tomography

PURPOSE

To describe the clinicopathological and morphological features of gastrointestinal stromal tumours (GISTs) on multi-detector computed tomography (MDCT).

MATERIAL AND METHODS

MDCT (plain and post contrast) images of 25 confirmed cases of GISTs were retrospectively evaluated from our hospital database. The images were analysed for the location, size, growth pattern, attenuation pattern, relation to adjacent structures, presence or absence of ulceration, calcification, metastases, lymphadenopathy, and for any complications such as haemorrhage, intestinal obstruction, etc. Institutional Ethics Committee clearance was obtained prior to the commencement of the study. Statistics used included percentage frequency.

RESULTS

Our study group comprised 14 males and 11 females. The mean age of our study population was 60 years (age range: 40 to 82 years). The mean tumour size was 11.7 cm. The stomach and small bowel accounted for 76% of the primary tumour site. The commonest imaging appearance of GIST observed in our study was that of an exophytic mass (76%) with a heterogenous pattern of enhancement (96%) with intratumoural necrosis (76%). MDCT demonstrated complications in three patients (12%). Six patients presented with metastatic foci (five to the liver and one to the lung), while lymphadenopathy was observed in five patients (20%). Associated complications included intestinal obstruction (8%) and retrogastric haematoma (4%). Incidental findings included uterine fibroid (n = 1), ovarian dermoid (n = 1), and chronic pancreatitis (n = 1).

CONCLUSIONS

GISTs are predominantly large tumours with a well circumscribed and exophytic pattern on MDCT, with or without cystic/necrotic areas, and they mostly show a heterogenous pattern of enhancement on post-contrast administration.

Peritumoral lymphoid cuff correlates well with lymph node enlargement in gastrointestinal schwannomas

Background/Aims

To determine the incidence of regional lymphadenopathy in gastrointestinal (GI) schwannoma and to evaluate the relationship between peritumoral lymphoid cuff and lymphadenopathy.

Methods

We queried 118 GI tract schwannomas and reviewed radiologic findings, intraoperative findings, and electronic medical records of all cases for enlarged regional lymph nodes.

Results

Location of tumors included 85 gastric (72%), 11 colonic (9.3%), 7 esophageal (5.9%), 3 pancreatic (2.5%), 1 hepatic (0.8%), and 11 mesenteric (9.3%). The size of the tumors ranged from 0.2 to 11 cm (mean 3.8 cm). Histologically, 70.3% showed a peritumoral lymphoid cuff ranging in thickness from 0.3 to 6 mm (mean 1.6 mm). The peritumoral lymphoid cuff was significantly more frequent in gastric schwannomas (78.8%) followed by colonic (72.7%), esophageal (57.1%) and rare in other locations (p = 0.001). Of the 106 cases for which clinical or radiologic data was available for, 76 cases (71.7%) showed regional lymphadenopathy. The presence of peritumoral lymphoid cuff showed significant correlation with regional lymphadenopathy (p < 0.001) and the size of enlarged lymph nodes (p = 0.002).

Conclusions

A peritumoral lymphoid cuff is frequently seen in GI tract schwannomas and correlates well with regional lymphadenopathy. However, in a significant subset (29.7%), a lymphoid cuff was not present warranting continued need for caution in the preoperative radiologic and postoperative pathologic diagnoses.

Randomized crossover trial comparing EUS-guided fine-needle aspiration with EUS-guided fine-needle biopsy for gastric subepithelial tumors

AIM

The purpose of this study is to compare the diagnostic yield of endoscopic ultrasound (EUS)-guided fine-needle aspiration (EUS-FNA) and EUS-guided fine-needle biopsy (EUS-FNB) for gastric subepithelial tumors (SET).

METHODS

Patients diagnosed SET derived from fourth layer of the stomach were prospectively enrolled and randomly assigned to undergo both EUS-FNA using standard needle and EUS-FNB using a core biopsy needle alternatively to the same lesion a total of four times per session. The specimen was carefully examined for the presence of a macroscopic visible core, appearing as threadlike yellowish or bloody pieces of tissue and blinded histocytologic analyses were conducted. For spindle cell lesions by hematoxylin and eosin staining (H&E) on histologic evaluation, immunohistochemical staining was performed in all cases to confirm the pathological diagnosis.

RESULTS

A total of 23 patients were enrolled and underwent paired EUS-FNA and -FNB sampling. The diagnostic rate due to immunohistochemical staining was 73.9% and 91.3%, respectively (P = .120). The rate of obtaining specimens with a macroscopic yellowish core and only a bloody core among the tissue specimens were respectively 43.5% and 52.2% for EUS-FNA and 69.6% and 30.4% for EUS-FNB. The diagnostic rate for a yellowish core (84.6%) and a bloody core (84.2%, P = .971) did not differ significantly.

CONCLUSION

Both techniques were equivalently safe and successful in terms of a high diagnostic yield for gastric SET. And the tissue that can be immunohistochemically stained is present even in the specimens that appear to be a macroscopically bloody core.

Gastric Schwannoma: A Tumor Must Be Included in Differential Diagnoses of Gastric Submucosal Tumors

Gastric schwannoma (GS) is a rare neoplasm of the stomach. It accounts for 0.2% of all gastric tumors and is mostly benign, slow-growing, and asymptomatic. Due to its rarity, GS is not widely recognized by clinicians, and the precise differential diagnosis between GS and other gastric submucosal tumors remains difficult preoperatively. The present study reports a case of GS misdiagnosed as gastrointestinal stromal tumor and reviews the clinical, imaging, and pathological features, treatment, and follow-up of 221 patients with GS previously reported in the English literature. Although GS is rare, the case reported in the current study highlights the importance of including GS in differential diagnoses of gastric submucosal tumors. Furthermore, the findings of the review suggest that although many cases are asymptomatic, the most common symptoms are abdominal pain or discomfort, not gastrointestinal bleeding, and malignant GSs present with clinical symptoms more commonly. Although large-sample multicenter studies on the efficacy, safety, and oncological outcomes of minimally invasive techniques are required, the findings presented herein may be helpful for clinicians when diagnosing or treating GS.

Differentiation between gastrointestinal schwannomas and gastrointestinal stromal tumors by computed tomography

The aim of the present study was to identify computed tomography (CT) features to assist in differentiating gastrointestinal schwannomas from gastrointestinal stromal tumors (GISTs). CT images of gastrointestinal schwannomas (n=15) and GISTs (n=50) were analyzed. The absolute CT values of tumor/aorta during plain scan/arterial phase/venous phase were recorded as tumor plain scan (Tp)/aorta plain scan (Ap), tumor arterial phase (Ta)/aorta arterial phase (Aa) and tumor venous phase (Tv)/aorta venous phase (Av), respectively, and normalized CT values of the three phases were calculated as Sp=Tp/Ap, Sa=Ta/Aa and Sv=Tv/Av, respectively. The difference in tumor CT value between arterial and venous phases was calculated and recorded as Tv-a. CT data including tumor size, contour, margin, growth pattern, presence of calcification, cystic change, hemorrhage, ulceration, perilesional lymph nodes (PLNs), local invasion to surrounding structures, metastasis, ascites, vasculatures, enhancement pattern/degree, Tp/Ta/Tv and Sp/Sa/Sv were evaluated for each patient. Receiver operating characteristic (ROC) curve analysis was used to assess the ability of the CT data to differentiate gastrointestinal schwannomas from GISTs. Compared with GISTs, gastrointestinal schwannomas more frequently demonstrated round contouring, relatively smaller tumor size, a homogeneous enhancement pattern, with the presence of PLNs and a higher level of vasculature (P<0.05), whilst the presence of cystic changes were more common in GISTs compared with gastrointestinal schwannomas (P<0.05). The Sa, Ta and Tv-a of gastrointestinal schwannomas were less compared with those of GISTs (P<0.05). The difference in margin, growth pattern, intra-tumoral calcifications and hemorrhage were insignificant (P>0.05). ROC analysis indicated that tumor size, cystic change, the presence of PLNs, tumor enhancement pattern and Sa demonstrated improved diagnostic potential compared with others [area under the curve (AUC) >0.7], amongst which cystic change demonstrated the best diagnostic ability (AUC=0.82). Size exhibited the highest sensitivity, 90%, and cystic change, Sa exhibited the best specificity, 87%. Quantitative analysis indicated that certain features aided the differentiation between gastrointestinal schwannomas and GISTs using CT imaging.

Contrast-enhanced (endoscopic) ultrasound and endoscopic ultrasound elastography in gastrointestinal stromal tumors

Background and Objectives:

Gastrointestinal stromal tumors (GISTs) represent the largest group of subepithelial tumors (SET) of the upper gastrointestinal (GI) tract. They may show malignant behavior, in contrast to other SET. Endoscopic ultrasound (EUS) is frequently used to characterize SET. With the introduction of contrast-enhanced ultrasound (CEUS) into EUS (CE-EUS), distinct enhancement patterns can be detected. In the presented study, the characteristic features of CE-EUS in GIST are analyzed and compared with those of other SET.

Materials and Methods:

Consecutive patients from four centers with SET of the upper and middle GI tract were included and received endoscopic or transcutaneous CEUS. The results were compared with EUS-guided tissue acquisition, forceps biopsy, or surgical resection.

Results:

Forty-two out of 62 (68%) patients had SET of the stomach, 17/62 (27%) of the small intestine, 2/62 (3%) of the esophagus, and 1/62 (2%) extraintestinal. Eighty-one percent underwent surgery. Leiomyoma was found in 5/62 (8%) and GIST in 57/62 patients (92%). Thirty-nine out of 57 (68%) patients had GIST lesions in the stomach, 17/57 (30%) had GIST of the small intestine, and 1/57 (2%) patients had extraintestinal GISTs. GIST size was 62.6 ± 42.1 (16–200) mm. Hyperenhancement had a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 98%, 100%, 100%, 93%, and 98% for the diagnosis of GIST. Fifty out of 57 patients with GIST (88%) showed avascular areas in the center of the lesions.

Conclusion:

CE-EUS and CEUS show hyperenhancement and avascular areas in a high percentage of GIST but not in leiomyoma. Thus, GIST and leiomyoma can be discriminated accurately.

CT Features of Colorectal Schwannomas: Differentiation from Gastrointestinal Stromal Tumors

Purpose

To find differential CT features of colorectal schwannomas from gastrointestinal stromal tumors (GISTs).

Materials and Methods

CT features of 13 pathologically proven colorectal schwannomas and 21 GISTs were retrospectively reviewed. The following CT items were analyzed: size, longitudinal and transverse location, shape, margin, homogeneity, necrosis, surface ulceration, calcification, degree of attenuation, the presence of enlarged lymph node (LN), and metastasis. Among the features, significant variables were evaluated using univariate statistical tests. The optimal cut-off point of tumor size was obtained by ROC analysis. Binary logistic regression analysis was used to find the most independent CT variables.

Results

Small size, non-rectum location, smooth margin, homogeneous high attenuation without necrosis, and the presence of enlarged LNs were found to be significant variables to differentiate schwannomas from GISTs (P<0.05). The optimized cut-off point for tumor size in distinguishing GISTs from schwannomas was 3.9 cm (AUC = 0.808, sensitivity = 66.7%, specificity = 92.3%, P<0.0001). Binary regression analysis revealed that only non-rectum location remained independent predictor for schwannomas differentiated from GISTs (odds ratio = 31.667, P = 0.001).

Conclusion

Colorectal schwannomas usually located in non-rectum and appear as small subepithelial nodules showing homogeneous high attenuation and smooth margin. Schwannomas exclusively accompany with enlarged LNs.

Esophageal insufflation computed tomography for the diagnosis and management of esophageal submucosal tumors

BACKGROUND

The selection of therapy for benign esophageal lesions depends in part on whether the lesion extends to or through the esophageal muscle wall. The advent of endoscopic dissection of deep lesions has made this distinction important in the choice between different forms of advanced endoscopic therapy. The goal of this study was to evaluate esophageal insufflation computed tomography (EICT) for the diagnosis and management of esophageal submucosal tumors (SMTs).

METHODS

Between April 2011 and May 2013 at the Second Affiliated Hospital of Harbin Medical University, 27 patients with esophageal SMTs diagnosed by gastroscopy were studied observationally. Entry criteria included tumors larger than 0.5 cm. We compared endoscopic ultrasound (EUS) and EICT to assess lesion depth and the relationship between the submucosal lesion and the esophageal wall using the resected lesion as the gold standard.

RESULTS

Twenty-seven esophageal SMTs were evaluated. EUS and EICT accurately identified nine as superficial to the muscularis propria. EICT correctly identified the relation of the tumor extension and the outer esophageal wall in all 18 lesions that originated from the muscularis propria; only nine were correctly assessed by EUS (P < 0.001).

CONCLUSIONS

EICT enables improved judgment of the relation of esophageal lesions and the esophageal-mediastinal border. We propose EICT as a new, safe, effective, useful, simple and high-tolerance method for assessing the depth and relationships of esophageal submucosal lesions.

Gastrointestinal stromal tumours (GISTs) with a thousand faces: atypical manifestations and causes of misdiagnosis on imaging

Gastrointestinal stromal tumours (GISTs) can lead to emergency situations, such as gastrointestinal bleeding, intestinal obstruction, and tumoural rupture with haemoperitoneum or peritonitis. In addition, if a GIST grows exophytically to a large size, it is often misdiagnosed as a tumour arising from adjacent organs. Sometimes, the atypical appearance of GISTs on imaging causes diagnostic confusion. In this article, we illustrate a variety of GISTs with atypical presentations and also discuss the important diagnostic clues for differentiating GISTs from other lesions.

Feasibility and Diagnostic Yield of Endoscopic Ultrasonography-Guided Fine Needle Biopsy With a New Core Biopsy Needle Device in Patients With Gastric Subepithelial Tumors

As treatment decisions for patients with gastric subepithelial tumors (SETs) largely depend on the histopathologic diagnosis, noninvasive and effective tissue acquisition methods are definitely required for proper management of gastric SETs. Recently, a new endoscopic ultrasonography-guided fine needle biopsy (EUS-FNB) device with ProCore reverse bevel technology was developed. We aimed to elucidate the feasibility and diagnostic yield of EUS-FNB with this new core biopsy needle device in patients with gastric SETs. A prospectively maintained database was retrospectively reviewed to identify consecutive patients who underwent EUS-FNB with a 22-gauge ProCore needle for gastric SETs 2 cm or larger. The main outcome measurement was the diagnostic yield of EUS-FNB. Procedure results were categorized into diagnostic, suggestive, or nondiagnostic. Of the 43 patients, needle punctures were successful in all cases irrespective of tumor location. EUS-FNB procedure results were diagnostic in 86.0%, suggestive in 4.7%, and nondiagnostic in 9.3% of cases, respectively. The diagnostic yield was the highest in fundus (100.0%), followed by body (89.5%), cardia (83.3%), and antrum (50.0%). All 18 patients with cardiac SET were finally diagnosed to have leiomyoma, and 16 patients with diagnostic or suggestive results avoided surgery. A heterogeneous echo pattern on EUS was found in 33.3% of cases with nondiagnostic or suggestive results and in 5.4% with diagnostic results. In multivariate analysis, no independent predictor of unsuccessful EUS-FNB with nondiagnostic or suggestive results was identified. Agreement between EUS-FNB and surgical pathology was 100% with respect to the diagnosis of gastrointestinal stromal tumor. However, there was a significant discrepancy in mitotic counts observed between the EUS-FNB and surgical specimens in patients with gastrointestinal stromal tumor. There were no significant procedure-related adverse events during and after the procedures. EUS-FNB with a 22G ProCore needle is a technically feasible, safe, and effective procedure for pathologic diagnosis of gastric SETs. This procedure can help refine surgical indications and facilitate a proper treatment decisions for gastric SETs, especially in the cardia.

Leiomyomas in the gastric cardia: CT findings and differentiation from gastrointestinal stromal tumors

OBJECTIVE

To describe CT findings of leiomyomas and gastrointestinal stromal tumors (GISTs) in the gastric cardia and to identify their differentiating features.

MATERIALS AND METHODS

CT images of pathologically proven leiomyomas (n=26) and GISTs (n=19) in the gastric cardia were retrospectively reviewed for esophagogastric junction (EGJ) involvement, contour, surface, growth pattern, enhancement pattern and degree of the tumor, and the presences of intralesional low attenuation, calcification and surface dimples or ulcers. The long (LD) and short diameters (SD), LD/SD ratio, and attenuation value of each lesion were measured.

RESULTS

EGJ involvement, homogeneous enhancement, intermediate or low enhancement, absences of intralesional low attenuation and surface dimples or ulcers, LD/SD ratio >1.2, and attenuation value ≤71.2HU were significant findings for differentiating leiomyomas from GISTs (P<0.05 for each finding). An LD/SD ratio of >1.2 and attenuation value of ≤71.2HU yielded sensitivities of 84.6% and 61.5%, and specificities of 52.6% and 84.2%, respectively, on the receiver operating characteristic curve analysis. When at least five of these seven criteria were used in combination, the sensitivity and specificity for diagnosing leiomyomas were 100% (26 of 26) and 89.5% (17 of 19), respectively. When any six of these criteria were used, a specificity of 100% was achieved.

CONCLUSIONS

CT features including EGJ involvement, enhancement pattern and degree, presences of intralesional low attenuation and surface dimples or ulcers, LD/SD ratio, and attenuation value could help differentiating leiomyomas from GISTs in the gastric cardia, particularly in the manner of combination.

Status of the gastric mucosa with endoscopically diagnosed gastrointestinal stromal tumor

Background. Since gastrointestinal stromal tumor (GIST) is a mesenchymal submucosal tumor, the endosonographic, CT, and MRI features of gastric GISTs have been widely investigated. However, the GIST-bearing gastric mucosa status has not been reported. Objective. To characterize the GIST-bearing gastric mucosa status in terms of the degree of inflammation and atrophy, assessed endoscopically. Subjects and Methods. The subjects were 46 patients with submucosal tumors (histologically proven gastric GISTs) who had undergone upper gastrointestinal endoscopy in our hospital between April 2007 and September 2012. They were retrospectively evaluated regarding clinicopathological features, the endoscopically determined status of the entire gastric mucosa (presence or absence and degree of atrophy), presence or absence and severity of endoscopic gastritis/atrophy (A-B classification) at the GIST site, and presence or absence of H. pylori infection. Results. Twenty-three patients had no mucosal atrophy, but 17 and 6 had closed- and open-type atrophy, respectively. Twenty-six, 5, 12, 1, 1, and 1 patients had grades B0, B1, B2, B3, A0, and A1 gastritis/atrophy at the lesion site, respectively, with no grade A2 gastritis/atrophy. Conclusion. The results suggest that gastric GISTs tend to arise in the stomach wall with H. pylori-negative, nonatrophic mucosa or H. pylori-positive, mildly atrophic mucosa.

State of the Art in the Treatment of Gastrointestinal Stromal Tumors

BACKGROUND

Gastrointestinal stromal tumors (GISTs) are the most frequently diagnosed mesenchymal neoplasms of the gastrointestinal tract. Despite their biological and clinical heterogeneity, the majority of these tumors are positive for the receptor tyrosine kinase KIT and are driven by KIT- or platelet-derived growth factor receptor alpha (PDGFRA)-activating mutations. There are still uncertainties regarding their clinical and molecular characterization and the optimal treatment regimens, making it difficult to establish a universal treatment algorithm for these tumors.

SUMMARY

From a clinical perspective, the main difference between GISTs and other gastrointestinal neoplasms is that the benign or malignant behavior of GISTs cannot be predicted from histopathology, but instead relies on empirically established scoring systems. Clinical data suggest that malignant potential may be an inherent quality of some GISTs rather than a feature acquired by the tumor during disease progression. Thus, some patients may require prolonged anti-tumor treatment even after complete surgical removal of the tumor.

KEY MESSAGE

Although GISTs are the most frequently occurring mesenchymal neoplasms in the gastrointestinal tract, no universal treatment algorithms exist. This paper reviews the current evidence that guides the management of GISTs.

PRACTICAL IMPLICATIONS

The management of localized GISTs involves the use of surgical resection, with the inclusion of preoperative tyrosine kinase inhibitor treatment for locally advanced, primarily unresectable tumors and for resectable cases requiring extensive surgery. Imatinib is also indicated as adjuvant therapy after complete surgical removal of GISTs with a high estimated risk of recurrence unless specific mutations conferring imatinib resistance are present. The optimal duration of adjuvant treatment is still controversial. For patients with metastatic imatinib-sensitive GISTs, imatinib constitutes the first-line standard treatment. Molecular characterization of the tumor (with respect to the PDGFRA and KIT genes) is mandatory prior to imatinib therapy. Sunitinib and regorafenib are established as alternative treatments for patients demonstrating generalized disease progression on imatinib. New tyrosine kinase inhibitors such as ponatinib and crenolanib as well as drugs targeting alternative pathways are currently under investigation. Surgery and locally ablative treatments may be indicated in some metastatic patients.