Gastric schwannoma (GS) is often misdiagnosed as gastrointestinal stromal tumors due to the high incidence of the latter. However, these two types differ significantly in pathology and biological behavior.

To evaluate the computed tomography characteristics of GS and provide insights into its accurate diagnosis.

Twenty-three cases of GS confirmed between January 2011 and December 2023 were assessed clinically and radiologically. Imaging characteristics, including tumor location, size, contour, ulceration, growth pattern, enhancement degree and pattern, cystic change, calcification, and perigastric lymph nodes (PLNs), were reviewed by two experienced radiologists.

Our sample included 18 females and 5 males, with a median age of 54.7 years. A total of 39.1% of cases were asymptomatic. GSs appeared as oval and well-defined submucosal tumors, with exophytic (43.5%) or mixed (endoluminal + exophytic; 43.5%) growth patterns. The tumors were primarily located in the gastric body (78.3%). Ulcerations were observed in 8 cases (34.5%), and PLNs were observed in 15 cases (65%). The average degree of enhancement was 48.3 Hounsfield units. Twenty cases (87%) showed peak enhancement in the delayed phase. Most GSs were homogeneous, while cystic change (13.0%) and calcification (17.4%) were rare.

GS predominantly showed gradual homogenous enhancement with peak enhancement in the delayed phase. PLNs around GS are helpful in differentiating GS from other gastric submucosal tumors.

This study aims to develop and validate an enhanced computed tomography (CT)-based radiomics model to differentiate gastric schwannomas (GS) from gastrointestinal stromal tumors (GIST) across various risk categories.

This retrospective analysis was conducted on 26 GS and 82 GIST cases, all confirmed by postoperative pathology. Data was divided into training and validation cohorts at a 7:3 ratio. We collected patient demographics, clinical presentations, and detailed CT imaging characteristics. Through univariable and multivariable logistic regression analyses, we identified independent predictors for discriminating between GS and GIST, facilitating the construction of a conventional model. Radiomic features were extracted and refined through manual 3D segmentation of venous phase thin-slice images to develop a radiomics model. Subsequently, we constructed a comprehensive combined model by integrating selected clinical and radiomics indicators. The diagnostic performances of all models in differentiating GS from GIST and stratifying GISTs according to malignancy risk were evaluated.

We identified several key independent variables distinguishing GS from GIST, including tumor location, cystic changes, degree of enhancement in arterial phase, and enhancement uniformity. The conventional model achieved AUCs of 0.939 and 0.869 in the training and validation cohort, respectively. Conversely, the radiomics model, predicated on eight pivotal radiomics features, demonstrated AUCs of 0.949 and 0.839. The combined model, incorporating tumor location, degree of enhancement in arterial phase, enhancement uniformity, and a radiomics model derived rad-score, significantly outperformed the traditional approach, achieving AUCs of 0.989 and 0.964 in the respective cohorts. The combined model showed superior diagnostic accuracy in distinguishing GS from GIST, as well as GS from high or low malignancy potential GISTs, as evidenced by IDI values of 0.2538, 0.2418, and 0.2749 (P<0.05 for all).

The combined model based on CT imaging features and radiomics features presents a promising non-invasive approach for accurate preoperative differentiation between gastric schwannomas and gastrointestinal stromal tumors.

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.

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.

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.

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

To retrospectively analyze the computed tomography (CT) findings and clinical manifestations of gastric calcifying fibrous tumor (CFTs).The features of 7 cases with pathologically proven gastric CFTs who had undergone CT were assessed, including tumor location, contour, growth, degree of enhancement, calcification and clinical data. In addition, the size and CT value of each lesion were measured. The mean values of these CT findings and clinical data were statistically analyzed only for continuous variables.Four patients were female and three were male (mean age: 33.3 years; range: 22 ∼ 47 years). Nonspecific clinical symptoms: abdominal pain and discomfort were observed in four cases and the CFTs were incidentally detected in the other three cases. Regarding tumor markers, lower ferritin levels were observed in three female patients. All of the gastric CFTs were solitary and mainly located inside the body; they were in round or oval shape and exhibited endophytic growth. Gastric CFTs are usually small sized and could contain confluent and coarse calcifications; cyst, necrosis, ulcer, bleeding and surrounding lymphadenopathy were not found in any of the cases. Unenhanced CT values of gastric CFTs were higher than those of same-transect soft tissue. Mild-to-moderate enhancement in the arterial phase and progressive enhancement in the portal venous phase were mainly noted.A gastric mass with a high unenhanced CT attenuation value, confluent and coarse calcifications and mild-to-moderate enhancement could prompt a diagnosis of gastric CFT. In addition, (1) being young- or middle-aged, (2) having relatively low ferritin levels, and (3) tumor located in the gastric body have critical reference value for diagnosis of gastric CFT.

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

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.

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).

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.

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).

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.

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.

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.

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.

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.

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).

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.