Computed tomographic characteristics of gastric schwannoma

Gastric schwannoma: Computed tomography and perigastric lymph node characteristics

BACKGROUND

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.

AIM

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

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Identifying subtle differences : a radiomics model assessment for gastric schwannomas and gastrointestinal stromal tumors across risk grades

Objective

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.

Methods

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.

Results

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).

Conclusion

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.

A Machine Learning-Driven Surface-Enhanced Raman Scattering Analysis Platform for the Label-Free Detection and Identification of Gastric Lesions

Background

Gastric lesions pose significant clinical challenges due to their varying degrees of malignancy and difficulty in early diagnosis. Early and accurate detection of these lesions is crucial for effective treatment and improved patient outcomes.

Methods

This paper proposed a label-free and highly sensitive classification method for serum of patients with different degrees of gastric lesions by combining surface-enhanced Raman scattering (SERS) and machine learning analysis. Specifically, we prepared Au lotus-shaped (AuLS) nanoarrays substrates using seed-mediated and liquid-liquid interface self-assembly method for measuring SERS spectra of serum, and then the collected spectra were processed by principal component analysis (PCA) - multi-local means based nearest neighbor (MLMNN) model to achieve differentiation.

Results

By employing this pattern analysis, AuLS nanoarray substrates can achieve fast, sensitive, and label-free serum spectral detection. The classification accuracy can reach 97.5%, the sensitivity is higher than 96.7%, and the specificity is higher than 95.0%. Moreover, by analyzing the PCs loading plots, the most critical spectral features distinguishing different degrees of gastric lesions were successfully captured.

Conclusion

This discovery lays the foundation for combining SERS with machine learning for real-time diagnosis and recognition of gastric lesions.

Gastric Schwannoma in an Octogenarian: A Case Report and Review of the Literature

Gastric schwannomas are an exceedingly rare tumor arising from the myenteric plexus of the gastrointestinal enteric nervous system. These schwannomas are most commonly benign and reported to occur in female patients with a mean age of 58 at presentation. They are most often discovered incidentally, but can occasionally present with abdominal discomfort, obstructive symptoms, or GI bleeding. Frequently, the initial clinical consideration is for a gastrointestinal stromal tumor, which is much more common. A definitive diagnosis is made with microscopic imaging and immunohistochemical staining. Complete surgical resection, typically performed laparoscopically, is the most definitive and usually curative treatment, requiring no further follow-up. Herein, we present the first and only case of gastric schwannoma in an octogenarian and discuss an update on current diagnostic and therapeutic options.

Gastric schwannoma: The gastrointestinal tumor simulator - case report and review of the literature

INTRODUCTION AND IMPORTANCE

Gastric schwannoma is a rare and benign tumor originating from the peripheral nerves of the stomach. Despite its benign nature, this tumor typically remains asymptomatic for an extended period, and its radiological and endoscopic presentation poses challenges in distinguishing it from other gastric mesenchymal tumors.

CASE PRESENTATION

Here, we present a rare case of a patient experiencing gastric pain and melena secondary to a gastric mass. The initial preoperative diagnosis indicated a gastrointestinal stromal tumor, but subsequent pathological and immunohistochemical staining of the surgical specimen confirmed the presence of gastric schwannoma.

DISCUSSION

To gain insights into this uncommon condition, we conducted an electronic search on PubMed using the keywords "gastric schwannoma" and "gastric neurinoma." Our focus centered on case series containing more than five cases of gastric localization, resulting in the analysis of 14 case series involving a total of 321 patients. Our review aims to comprehensively discuss the clinical, radiological, and therapeutic aspects associated with this rare disease.

CONCLUSION

In the absence of a definitive preoperative diagnosis, the surgical approach is considered the primary treatment for resectable gastric schwannoma, given its excellent long-term outcomes. However, further studies are imperative to better define the role of endoscopic resection in managing this condition.

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.

Computed tomographic imaging features to differentiate gastric schwannomas from gastrointestinal stromal tumours: a matched case-control study

To investigate clinical data and computed tomographic (CT) imaging features in differentiating gastric schwannomas (GSs) from gastric stromal tumours (GISTs) in matched patients, 31 patients with GSs were matched with 62 patients with GISTs (1:2) in sex, age, and tumour site. The clinical and imaging data were analysed. A significant (P < 0.05) difference was found in the tumour margin, enhancement pattern, growth pattern, and LD values between the 31 patients with GSs and 62 matched patients with GISTs. The GS lesions were mostly (93.5%) well defined while only 61.3% GIST lesions were well defined.The GS lesions were significantly (P = 0.036) smaller than the GIST lesions, with the LD ranging 1.5-7.4 (mean 3.67 cm) cm for the GSs and 1.0-15.30 (mean 5.09) cm for GIST lesions. The GS lesions were more significantly (P = 0.001) homogeneously enhanced (83.9% vs. 41.9%) than the GIST lesions. The GS lesions were mainly of the mixed growth pattern both within and outside the gastric wall (74.2% vs. 22.6%, P < 0.05) compared with that of GISTs. No metastasis or invasion of adjacent organs was present in any of the GS lesions, however, 1.6% of GISTs experienced metastasis and 3.2% of GISTs presented with invasion of adjacent organs. Heterogeneous enhancement and mixed growth pattern were two significant (P < 0.05) independent factors for distinguishing GS from GIST lesions. In conclusion: GS and GIST lesions may have significantly different features for differentiation in lesion margin, heterogeneous enhancement, mixed growth pattern, and longest lesion diameter, especially heterogeneous enhancement and mixed growth pattern.

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.

Gastric Schwannoma: A Rare Subepithelial Lesion of the Stomach

Gastric schwannomas (GS) are rare, slow-growing, benign subepithelial (SE) lesions of the stomach. These are difficult to differentiate preoperatively from other types of SE lesions, as the gross appearance and clinical presentation are very similar especially the gastrointestinal stromal tumors (GISTs), which are the most common SE lesions of the stomach. We present the case of a 35-year-old Asian man with a one-month history of intermittent, right, upper quadrant pain and hematemesis. Preoperatively, intravenous contrast-enhanced computer tomography scan (CECT) showed a well-circumscribed lesion in the upper abdomen closer to the stomach's lesser curvature. Endoscopic ultrasound revealed an ulcerated subepithelial lesion and subsequent biopsy with a 22-gauge fine-needle biopsy (22G FNB) needle confirmed the diagnosis of GS. The patient underwent distal gastrectomy and a Bilroth 1 procedure. The postoperative biopsy was consistent with the initial one, therefore supporting the diagnosis of gastric schwannoma. Postoperatively, the recovery remained uneventful.

PET Scanning May Not Distinguish Benign Schwannoma from Metastasis in a Patient with Lung Adenocarcinoma

A 69-year-old man was diagnosed with lung adenocarcinoma with metastasis because two masses in the right intercostal space and right back muscle showed high accumulation on positron emission tomography (PET). The 6-month treatment with osimertinib significantly reduced his lung lesion, but no changes were observed in the metastatic lesions. Needle biopsy revealed that the lesion in the right back muscle was a schwannoma. Surgical resection revealed that the right intercostal lesion was also a schwannoma; subsequently, a right upper lobectomy was performed. The patient was finally diagnosed with lung adenocarcinoma without metastasis. High accumulations of lesions observed on PET may indicate schwannomas.

LEARNING POINTS

Benign schwannomas could show high accumulations on positron emission tomography.Accurate diagnosis of schwannoma using only images is quite challenging.Histological examinations should be considered when asymptomatic lesions are suspected to be metastases.

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.

A radiologic diagnostic scoring model based on CT features for differentiating gastric schwannoma from gastric gastrointestinal stromal tumors

We aimed to further explore the CT features of gastric schwannoma (GS), propose and validate a convenient diagnostic scoring system to distinguish GS from gastric gastrointestinal stromal tumors (GISTs) preoperatively. 170 patients with submucosal tumors pathologically confirmed (GS n=35; gastric GISTs n=135) from Hospital 1 were analyzed retrospectively as the training cohort, and 72 patients (GS=11; gastric GISTs=61) from Hospital 2 were enrolled as the validation cohort. We searched for significant CT imaging characteristics and constructed the scoring system via binary logistic regression and converted regression coefficients to weighted scores. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. For convenient assessment, the system was further divided into four score ranges and their diagnostic probability of GS was calculated respectively. Four CT imaging characteristics were ultimately enrolled in this scoring system, including transverse position (2 points), location (5 points), perilesional lymph nodes (6 points) and pattern of enhancement (2 points). The AUC of the scoring model in the training cohort were 0.873 (95% CI, 0.816-0.929) and the cutoff point was 6 points. In the validation cohort, the AUC was 0.898 (95% CI, 0.804-0.957) and the cutoff value was 5 points. Four score ranges were as follows: 0-3 points for very low probability of GS, 4-7 points for low probability; 8-9 points for middle probability; 10-15 points for very high probability. A convenient scoring model to preoperatively discriminate GS from gastric GISTs was finally proposed.

Gastric schwannoma treated by endoscopic full-thickness resection and endoscopic purse-string suture: A case report

BACKGROUND

Schwannomas, also known as neurinomas, are tumors that derive from Schwann cells. Gastrointestinal schwannomas are extremely rare, but the stomach is the most common site. Gastric schwannomas are usually asymptomatic. Endoscopy and imaging modalities might offer useful preliminary diagnostic information. However, to diagnose schwannoma, the immunohistochemical positivity for S-100 protein is essential, whereas CD117, CD34, SMA, desmin, and DOG-1 are negative.

CASE SUMMARY

A 45-year-old female was found to have a gastric mass during a medical examination, which was diagnosed as a gastric schwannoma. We performed endoscopic full-thickness resection and endoscopic purse-string suture. Pathology and immunohistochemical staining confirmed the diagnosis of gastric schwannoma through the positivity of S-100 protein. Furthermore, to exclude the misdiagnosis of gastrointestinal stromal tumor, we performed a mutational detection of the c-Kit and PDGFRA genes. Postoperative follow-up revealed that the patient recovered well.

CONCLUSION

Immunohistochemical staining is essential for the diagnosis of schwannoma. Endoscopic full-thickness resection is an effective treatment method for gastric schwannoma.

What About Gastric Schwannoma? A Review Article

PURPOSE

Gastric schwannomas (GSs) are rare mesenchymal neoplasms of the gastrointestinal tract. Diagnosis is often achieved postoperatively, based on pathology reports of retrieved specimens. The aim of the present study is to follow up all patients with gastric schwannoma (Gs) undergoing endoscopic, partial, or more extended surgery and to evaluate the appearance of local or distant recurrence.

METHODS

A PubMed, Cochrane, and Embase systematic review of the literature has been performed. Original papers, review articles, and case reports published between 1988 and 2019 were considered eligible. All the studies who met the inclusion criteria were analyzed. Statistical analysis of data has been performed using GraphPad Prism 7 software.

RESULTS

Three hundred twenty-eight articles were found, and a total of 102 were included and analyzed in depth. Fifty-three papers reported the follow-up information, ranging from 1 to 417 months across different studies. Among them, 31 patients underwent endoscopic removal of the gastric lesions; 140 patients underwent local surgery, including wedge resection or partial gastrectomy; and 148 patients underwent subtotal or total gastrectomy. The median follow-up was of 27-38-33 months, respectively. No recurrence or distant metastasis was detected in the endoscopy group. Among local surgery group, liver metastasis was reported in one case; in extended surgery group, one patient died for multiple liver metastases.

CONCLUSIONS

Local or more extended surgery involved a larger cohort of patients and reported satisfactory long-term results compared with endoscopy group. Surgery in absence of a definite preoperative diagnosis is considered the gold standard treatment for resectable Gs.

A Rare Case of Gastric Schwannoma: A Case Report and Literature Review

In general, schwannoma is a benign and slow-glowing neoplasm that rarely occurs in the gastrointestinal tract as a submucosal tumor (SMT), with the most common site being the stomach. As gastric schwannoma (GS) is a rare tumor, there is limited data in the literature about its clinical features. The diagnosis of schwannoma can only be made by pathological examination with positive staining for S-100 protein. It is necessary to obtain an accurate diagnosis to introduce optimal treatment options preoperatively. However, a precise diagnosis of GS is difficult, even with modern imaging techniques. On the other hand, a complete resection with a negative surgical margin (R0) of GS is considered the best treatment, with an excellent prognosis. We present a case of a 66-year-old female patient who underwent laparoscopic-assisted wedge gastrectomy for gastric SMT, pathologically diagnosed as GS, with positive staining for S-100 protein and negative for c-kit and CD34. At 12-month follow-up after surgery, there was no recurrence or metastasis of GS. Our treatment is appropriate and effective in case of GS exceeding 50 mm.

Gastric schwannoma: a diagnosis that should be known in 2019

Gastric schwannoma (GS) is a rare neoplasm of the stomach deriving from Schwann cells of the peripheral nerves in 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. Preoperatively, GSs are difficult to differentiate from other mesenchymal tumors, such as gastrointestinal stromal tumor (GIST) or leiomyoma, which develop from mesenchymal stem cells. The optimal management of GS is based on the symptoms of the patient, tumor size and histologic grading. Here, we report the case of a GS in a 73-year-old female who underwent a wedge gastric resection following a clinical diagnosis of GIST. A histological and immunohistochemical study was performed excluding the misdiagnosis of GIST. The histomorphological features of the lesion and absence of c-Kit and strong positivity of S100 indicated the diagnosis of GS.