Gastrointestinal Leiomyomas Research Articles

Efficacy of EUS-guided keyhole biopsies in diagnosing subepithelial lesions of the upper gastrointestinal tract.

Background and study aims Tissue acquisition is required for diagnosis of subepithelial lesions (SELs). However, obtaining adequate tissue remains challenging. This study investigated an EUS-guided technique using a forceps to create a channel and take multiple biopsies from the center of the lesion, therefore called endoscopic ultrasound-guided keyhole biopsy (EUS-KB). Patients and methods A retrospective cohort study was conducted in 56 patients with SELs in the upper gastrointestinal tract who were scheduled to undergo EUS-KB. The primary aim was to assess diagnostic yield, defined as the percentage of procedures where EUS-KB resulted in a definitive histopathological diagnosis. Furthermore, factors influencing diagnostic yield were investigated. Additional outcomes included technical success and adverse events. Results Technical success was achieved in 55 of 60 biopsies (91.7%). EUS-KB provided a diagnosis in 44 of 55 biopsies (80.0%), histology mostly showing gastrointestinal stromal tumor or leiomyoma. The diagnostic yield was not significantly influenced by the size or location of the SEL. Adverse events occurred in one patient (1.7%). Conclusions EUS-KB is a feasible and safe technique for obtaining a classifying diagnosis for SELs in the upper gastrointestinal tract. It could offer an alternative diagnostic modality, especially in lesions smaller than 20 mm.

Radiomics in the differential diagnosis of gastrointestinal stromal tumors and leiomyomas. A literature review

Radiomics in the differential diagnosis of gastrointestinal stromal tumors and leiomyomas. A literature review

Differentiating Gastrointestinal Stromal Tumors From Leiomyomas of Upper Digestive Tract Using Convolutional Neural Network Model by Endoscopic Ultrasonography.

Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tumors of the upper digestive tract, and the diagnosis of the tumors is essential for their treatment and prognosis. However, the ability of endoscopic ultrasonography (EUS) which could correctly identify the tumor types is limited and closely related to the knowledge, operational level, and experience of the endoscopists. Therefore, the convolutional neural network (CNN) is used to assist endoscopists in determining GISTs or leiomyomas with EUS. A model based on CNN was constructed according to GoogLeNet architecture to distinguish GISTs or leiomyomas. All EUS images collected from this study were randomly sampled and divided into training set (n=411) and testing set (n=103) in a ratio of 4:1. The CNN model was trained by EUS images from the training set, and the testing set was utilized to evaluate the performance of the CNN model. In addition, there were some comparisons between endoscopists and CNN models. It was shown that the sensitivity and specificity in identifying leiomyoma were 95.92%, 94.44%, sensitivity and specificity in identifying GIST were 94.44%, 95.92%, and accuracy in total was 95.15% of the CNN model. It indicates that the diagnostic accuracy of the CNN model is equivalent to skilled endoscopists, or even higher than them. While identifying GIST or leiomyoma, the performance of CNN model was robust, which is highlighting its promising role in supporting less-experienced endoscopists and reducing interobserver agreement.

Use of Endoscopic Ultrasound Elastography to Differentiate between Gastrointestinal Stromal Tumor and Leiomyoma Localized in the Upper Gastrointestinal Tract.

Gastrointestinal stromal tumors (GISTs) have malignant potential. Distinction of GISTs from leiomyoma is important to the decision of follow-up or treatment for upper gastrointestinal tract subepithelial lesions (SELs). There are few studies on the evaluation of gastrointestinal SELs with endoscopic ultrasound (EUS) elastography. To evaluate the efficiency of strain ratio (SR) measurement and Giovannini's classification (Gc) by EUS elastography in differentiating GISTs from leiomyomas. Twenty-three lesions with histopathological diagnoses of 13 GISTs and 10 leiomyomas were evaluated. The lesions' SR values were obtained from EUS reports retrospectively. Giovannini's classification was performed according to the elastography images recorded in the system. The effectiveness of SR and Gc in the distinction between GIST and leiomyomas was evaluated. Twelve of the GISTs and 3 of the leiomyomas were with scores 4 and 5 according to Gc (p = 0.006). Gastrointestinal stromal tumors had a higher SR than leiomyomas (p = 0.001). For the diagnosis of GISTs, sensitivity/specificity/diagnostic accuracy were 92.3%/80%/87% for SR alone, 92.3%/70%/82.6% for Gc alone, and 84.6%/80%/82.6% for the use of both SR and Gc. This is the first study in which semi-quantitative (SR) and qualitative (Gc) methods were evaluated together for the distinction of GISTs and leiomyomas. The sensitivity of SR alone for diagnosing GIST is higher than that of Gc alone or the combination of both methods. Although SR alone does not diagnose GIST, it can be used as an auxiliary method in biopsy and follow-up decisions. Erdem RE, Bektaş M, Ellik ZM, et al. Use of Endoscopic Ultrasound Elastography to Differentiate between Gastrointestinal Stromal Tumor and Leiomyoma Localized in the Upper Gastrointestinal Tract. Euroasian J Hepato-Gastroenterol 2024;14(1):20-23.

Efficacy of real-time artificial intelligence-aid endoscopic ultrasonography diagnostic system in discriminating gastrointestinal stromal tumors and leiomyomas: a multicenter diagnostic study

Gastrointestinal stromal tumors (GISTs) represent the most prevalent type of subepithelial lesions (SELs) with malignant potential. Current imaging tools struggle to differentiate GISTs from leiomyomas. This study aimed to create and assess a real-time artificial intelligence (AI) system using endoscopic ultrasonography (EUS) images to differentiate between GISTs and leiomyomas. The AI system underwent development and evaluation using EUS images from 5 endoscopic centers in China between January 2020 and August 2023. EUS images of 1101 participants with SELs were retrospectively collected for AI system development. A cohort of 241 participants with SELs was recruited for external AI system evaluation. Another cohort of 59 participants with SELs was prospectively enrolled to assess the real-time clinical application of the AI system. The AI system's performance was compared to that of endoscopists. This study is registered with Chictr.org.cn, Number ChiCT2000035787. The AI system displayed an area under the curve (AUC) of 0.948 (95% CI: 0.921-0.969) for discriminating GISTs and leiomyomas. The AI system's accuracy (ACC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) reached 91.7% (95% CI 87.5%-94.6%), 90.3% (95% CI 83.4%-94.5%), 93.0% (95% CI 87.2%-96.3%), 91.9% (95% CI 85.3%-95.7%), and 91.5% (95% CI 85.5%-95.2%), respectively. Moreover, the AI system exhibited excellent performance in diagnosing ≤20mm SELs (ACC 93.5%, 95% CI 0.900-0.969). In a prospective real-time clinical application trial, the AI system achieved an AUC of 0.865 (95% CI 0.764-0.966) and 0.864 (95% CI 0.762-0.966) for GISTs and leiomyomas diagnosis, respectively, markedly surpassing endoscopists [AUC 0.698 (95% CI 0.562-0.834) for GISTs and AUC 0.695 (95% CI 0.546-0.825) for leiomyomas]. We successfully developed a real-time AI-assisted EUS diagnostic system. The incorporation of the real-time AI system during EUS examinations can assist endoscopists in rapidly and accurately differentiating various types of SELs in clinical practice, facilitating improved diagnostic and therapeutic decision-making. Science and Technology Commission Foundation of Shanghai Municipality, Science and Technology Commission Foundation of the Xuhui District, the Interdisciplinary Program of Shanghai Jiao Tong University and the Research Funds of Shanghai Sixth people's Hospital.

Application of Computer-Assisted Endoscopic Ultrasonography Based on Texture Features in Differentiating Gastrointestinal Stromal Tumors from Benign Gastric Mesenchymal Tumors.

Gastrointestinal stromal tumors are common gastric mesenchymal tumors that are potentially malignant. However, endoscopic ultrasonography is poor in diagnosing gastrointestinal stromal tumors. The study investigated the efficacy of texture features extracted from endoscopic ultrasonography images to differentiate gastrointestinal stromal tumors from gastric mesenchymal tumors. The endoscopic ultrasonography examinations of 120 patients with confirmed gastric gastrointestinal stromal tumors, leiomyoma, or schwannoma were evaluated. Histology was considered the gold standard. Three feature combinations were extracted from endoscopic ultrasonography images of each lesion: 48 gray-level co-occurrence matrix-based features, 48 gray-level co-occurrence matrix-based features plus 3 global gray features, and 15 gray-gradient co-occurrence matrix-based features. Support vector machine classifiers were constructed by using feature combinations to diagnose gastric gastrointestinal stromal tumors. The area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were used to evaluate the diagnostic performance. The support vector machine model's diagnostic performance was compared with the endoscopists. The 3 feature combinations had better performance in differentiating gastrointestinal stromal tumors: gray-gradient cooccurrence matrix-based features yielded an area under the receiver operating characteristic curve of 0.90, which was significantly greater than an area under the receiver operating characteristic curve of 0.83 in gray-level co-occurrence matrix-based features and an area under the receiver operating characteristic curve of 0.84 in the texture features plus 3 global features. The support vector machine model (81.67% accuracy, 81.36% sensitivity, and 81.97% specificity) was also better than endoscopists (an average of 69.31% accuracy, 65.54% sensitivity, and 72.95% specificity) Conclusion:Texture features in computer-assisted endoscopic ultrasonography diagnosis are useful to differentiate gastrointestinal stromal tumors from benign gastric mesenchymal tumors and compare favorably with endoscopists. Support vector machine model using gray-gradient co-occurrence matrix-based texture features revealed the best diagnostic performance in diagnosing gastric gastrointestinal stromal tumors.

Prone Jack-Knife Transanal Minimally Invasive Surgery: A Safe and Effective Approach for Anterior Low Rectal GI Stromal Tumors.

Subepithelial rectal lesions, including gastrointestinal stromal tumours (GIST), leiomyomas, neuroendocrine tumours, lipomas, and schwannomas, are rare surgical conditions. 1 Surgical management in this region often entails radical surgical excisions with stoma creation. Radical surgical excisions with stoma creation are often required for surgical management in this region. In this video, we demonstrate a transanal minimally invasive surgery (TAMIS) approach to anterior low rectal GIST. Patient underwent neoadjuvant Imatinib Mesylate after multidisciplinary team discussion, and were evaluated preoperatively with colonoscopy, pelvis MRI, and endoscopic ultrasound-guided tissue biopsy. 2,3 The procedure was performed with the patient in the prone jack-knife position and using the GelPOINT® Path transanal access, providing an excellent surgical platform. 4 The access channel was chosen based on the lesion's location from the anal verge, and ports were placed in a triangular fashion onto the GelSeal Cap, including an apex 10 mm sleeve for the telescope connected to the insufflation stabilization bag, two lower 10 mm working ports, and an additional port if traction was necessary. The RapidVac TM smoke evacuator was used for smooth surgery without fluctuating the surgical field and to achieve optimal vision. Dissection was initiated over the lower margin of the mass into the subepithelial plane and then performed along and around the mass in the desired plane. This approach and positioning in prone jack-knife, allowed dissection under direct vision with excellent surgical ergonomics and avoided radical resection. Our video demonstrates the feasibility and safety of TAMIS for the management of anterior low rectal subepithelial lesion, providing an alternative to more radical surgical approaches. See Video Vignette.

Proventricular and ventricular gastrointestinal stromal tumor (GIST) in a scarlet macaw (Ara chloropterus)

GISTs can be benign or malignant, and they have been reported in a wide variety of species, including humans, non-human primates, dogs, and cats; however, reports of this tumor in birds are rare. These neoplasms are seen in the gastrointestinal tract and are derived from the Cajal Cells responsible for regulating gastrointestinal motility. We report a case of a gastrointestinal stromal tumor in a scarlet macaw (Ara chloropterus) that was referred to necropsy at the Veterinary Hospital of the Federal University of Paraíba (UFPB), Northeastern Brazil. Macroscopically, the proventriculus and ventriculus were dilated, and the walls of both organs were thickened by a firm, ulcerated mass covered by fibrin strands. In the histopathology, the proventriculus presented an expansive, non-encapsulated neoplasm formed by homogeneous spindle cells, with eosinophilic cytoplasm, indistinct borders, mild to moderate pleomorphism, and rare mitotic figures, being suggestive of a leiomyoma. In immunohistochemistry, a positive multifocal immunolabeling for the C-KIT proto-oncogene was observed in the cytoplasm of neoplastic spindle cells, thus compatible with a gastrointestinal stromal tumor (GIST). The occurrence of GISTs in avian species might have been overlooked, and the authors recommend that previously reported gastrointestinal leiomyomas or leiomyosarcomas be tested for this immunomarker to rule out the possibility of GISTs.

Enhancing gastrointestinal submucosal tumor recognition in endoscopic ultrasonography: A novel multi-attribute guided contextual attention network

Endoscopic ultrasonography (EUS) is a valuable imaging modality for diagnosing gastrointestinal submucosal tumors (SMTs). However, inherent content variations in EUS images due to gastrointestinal tract mobility and handheld ultrasound instability challenge the saliency of SMTs’ visual features. The presence of fine-grained inter-class and large intra-class differences further complicates EUS-based diagnosis. To address these issues, this paper presents a novel Multi-Attribute Guided Contextual Attention Network (MAG-CA-Net) for interpretable SMT recognition in EUS. Inspired by endoscopists’ clinical diagnosis expertise, our framework initially localizes abnormal areas based on echo attributes and subsequently determines tumor categories using contextual semantics. Experimental results demonstrate the effectiveness of MAG-CA-Net, exhibiting improved recognition recall and precision rates for gastrointestinal stromal tumor, leiomyoma, and pancreatic rest. Specifically, the MAG network facilitates abnormal area localization, while the CA mechanism guides the model to focus on the most discriminative tumor-context-associated regions. The proposed method achieved an average classification accuracy of 93.16%, an average precision of 93.17%, a weighted recall of 93.16%, and an average F1-score of 93.15 % for the three disease categories. The proposed approach provides crucial guidelines for data collection standards and model development in the clinical diagnosis process of SMTs under EUS. Its interpretability analysis enhances the credibility of clinical physicians towards assisted diagnostic methods based on deep learning. The source code will be publicly available at https://gitee.com/HangbinZheng/mag-ca-net.

Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis.

Subepithelial lesions (SELs) are gastrointestinal tumors with heterogeneous malignant potential. Endoscopic ultrasonography (EUS) is the leading method for evaluation, but without histopathological analysis, precise differentiation of SEL risk is limited. Artificial intelligence (AI) is a promising aid for the diagnosis of gastrointestinal lesions in the absence of histopathology. To determine the diagnostic accuracy of AI-assisted EUS in diagnosing SELs, especially lesions originating from the muscularis propria layer. Electronic databases including PubMed, EMBASE, and Cochrane Library were searched. Patients of any sex and > 18 years, with SELs assessed by EUS AI-assisted, with previous histopathological diagnosis, and presented sufficient data values which were extracted to construct a 2 × 2 table. The reference standard was histopathology. The primary outcome was the accuracy of AI for gastrointestinal stromal tumor (GIST). Secondary outcomes were AI-assisted EUS diagnosis for GIST vs gastrointestinal leiomyoma (GIL), the diagnostic performance of experienced endoscopists for GIST, and GIST vs GIL. Pooled sensitivity, specificity, positive, and negative predictive values were calculated. The corresponding summary receiver operating characteristic curve and post-test probability were also analyzed. Eight retrospective studies with a total of 2355 patients and 44154 images were included in this meta-analysis. The AI-assisted EUS for GIST diagnosis showed a sensitivity of 92% [95% confidence interval (CI): 0.89-0.95; P < 0.01), specificity of 80% (95%CI: 0.75-0.85; P < 0.01), and area under the curve (AUC) of 0.949. For diagnosis of GIST vs GIL by AI-assisted EUS, specificity was 90% (95%CI: 0.88-0.95; P = 0.02) and AUC of 0.966. The experienced endoscopists' values were sensitivity of 72% (95%CI: 0.67-0.76; P < 0.01), specificity of 70% (95%CI: 0.64-0.76; P < 0.01), and AUC of 0.777 for GIST. Evaluating GIST vs GIL, the experts achieved a sensitivity of 73% (95%CI: 0.65-0.80; P < 0.01) and an AUC of 0.819. AI-assisted EUS has high diagnostic accuracy for fourth-layer SELs, especially for GIST, demonstrating superiority compared to experienced endoscopists' and improving their diagnostic performance in the absence of invasive procedures.

Gastrointestinal Subepithelial Lesions: A Review

AbstractSubmucosal lesions, also known as subepithelial lesions, are often encountered during endoscopy of the gastrointestinal tract. Most of the lesions are asymptomatic and can be diagnosed by routine endoscopic ultrasonography. Few lesions like gastrointestinal submucosal tumors (GIST) and leiomyoma require biopsy/fine-needle aspiration cytology (FNAC) for differentiation. Lesions like neuroendocrine tumors can be diagnosed by deep endoscopic biopsy as they originate from the inner mucosal layer. Management depends on the size and layer of origin of the lesion. Smaller lesions can be removed by endoscopic procedures and bigger lesions by surgery. Smaller lesions can be safely surveilled.

Stereomicroscopic on-site evaluation in endoscopic ultrasound-guided tissue acquisition of upper gastrointestinal subepithelial lesions.

In stereomicroscopic sample isolation processing, the cutoff value (≥4 mm) of stereomicroscopically visible white cores indicates high diagnostic sensitivity. We aimed to evaluate endoscopic ultrasound-guided tissue acquisition (EUS-TA) using a simplified stereomicroscopic on-site evaluation of upper gastrointestinal subepithelial lesions (SELs). In this multicenter prospective trial, we performed EUS-TA using a 22-gauge Franseen needle in 34 participants with SELs derived from the upper gastrointestinal muscularis propria, requiring pathological diagnosis. The presence of stereomicroscopically visible white core (SVWC) in each specimen was assessed using stereomicroscopic on-site evaluation. The primary outcome was EUS-TA's diagnostic sensitivity with stereomicroscopic on-site evaluation based on the SVWC cutoff value (≥4 mm) for malignant upper gastrointestinal SELs. The total number of punctures was 68; 61 specimens (89.7%) contained stereomicroscopically visible white cores ≥4 mm in size. The final diagnoses were gastrointestinal stromal tumor, leiomyoma, and schwannoma in 76.5%, 14.7%, and 8.8% of the cases, respectively. The sensitivity of EUS-TA with stereomicroscopic on-site evaluation based on the SVWC cutoff value for malignant SELs was 100%. The per-lesion accuracy of histological diagnosis reached the highest level (100%) at the second puncture. Stereomicroscopic on-site evaluation showed high diagnostic sensitivity and could be a new method for diagnosing upper gastrointestinal SELs using EUS-TA.

Histopathologic findings in laparoscopic sleeve gastrectomy: is routine full pathologic evaluation indicated?

Laparoscopic sleeve gastrectomy (SG) is the most commonly performed bariatric surgery. The resected gastric segment is routinely sent for pathology evaluation. No formal national recommendation exists that mandates pathology review. We proposed to study the largest histopathologic series in SG patients yet reported. The primary objective of our study was to determine whether a subgroup of patients who underwent bariatric surgery in the northeastern Unites States is more susceptible to having clinically significant pathologic findings that may benefit from routine histopathologic evaluation of the gastric sleeve specimen. University hospital. A retrospective electronic chart review of patients who underwent SG at a single large academic institution was performed. Patient demographics, body mass index, and histopathologic reports of the gastric specimens obtained during SG were analyzed. The records of 3543 patients were reviewed. A total of 1076 patients had abnormal pathologies, including gastritis (938), follicular gastritis (98), intestinal metaplasia (25), gastrointestinal stromal tumor (12), leiomyoma (1), lymphoma (1), and other malignancy (1). Black and Hispanic patients had a higher incidence of developing gastrointestinal stromal tumor and intestinal metaplasia. A higher incidence of Helicobacter pylori infection among specimens with abnormal pathologies was noted. The findings of this study call into question the routine use of pathology workup in gastric specimens after SG. Our data suggest that such analysis may be warranted in certain subtypes of patients such as older Black and Hispanic patients in the northeastern United States.

Can EUS-FNA cytology reliably classify gastric submucosal spindle cell tumors?

Cytological diagnosis using endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) for gastric submucosal spindle cell tumors, such as gastrointestinal stromal tumors (GISTs), leiomyomas, and schwannomas, is challenging because of their similar morphological characteristics. To clarify the cytological differential points, we reviewed the EUS-FNA cytology specimens of GISTs (37 cases), leiomyomas (11 cases), and schwannomas (4 cases). Twelve cytomorphological features were evaluated: lymphocytes, crushed nuclei, naked spindle nuclei, mast cell, length of the streaming arrangement, cellularity, nuclei at the cluster margin (nuclei located at the periphery of the cell cluster), peripheral feathering (loosely aggregated cells at the margin of a cell cluster tended to taper like feathers), metachromasia, wavy nuclei, fishhook-type nuclei, and anisonucleosis. Among these features, lymphocytes, naked spindle nuclei, length of the streaming arrangement, cellularity, nuclei at the cluster margins, peripheral feathering, and anisonucleosis were statistically significant for differentiation. Based on these findings, we developed an algorithm for cytodiagnosis. The algorithm was taught to four cytologists, and the interobserver agreement and correct diagnosis rates were compared before and after education, which showed a significant improvement. The histological types of gastric submucosal spindle cell tumors can be estimated using this algorithm for EUS-FNA cytology. Furthermore, this algorithm can be applied for cytological diagnosis at bedside during rapid on-site evaluation.

Distinguishing Gastrointestinal Leiomyomas From Muscularis Propria in Biopsy Specimens by Differential Expression of S100 Immunohistochemical Stain.

Interpreting small biopsy specimens or fine-needle aspirations of gastrointestinal tract (GI) smooth muscle lesions may be challenging when the differential diagnosis includes leiomyoma vs muscularis propria (MP). We evaluated the utility of S100 staining in distinguishing GI leiomyomas from MP. A search was conducted in our laboratory information system for cases of leiomyomas arising within the GI tract (2004-2021). Site-matched controls containing MP were selected (2018-2020). Five high-power fields (hpf) were counted on S100 immunohistochemical stains by two pathologists in the resections and by three different blinded pathologists in the biopsy specimens and analyzed. The median S100 count was 2.5/5 hpf in leiomyoma resection cases (n = 38), which was significantly lower than the median count of 548/5 hpf in MP (n = 19) with a P value of <.0001. The median S100 count in biopsy specimens (n = 16) was 1.2/5 hpf and within the expected range of 1 to 104/5 hpf (minimum-maximum value) established by the leiomyoma resections. S100 counts in the normal MP were significantly higher than those observed in leiomyomas (P < .001). S100 staining can aid in distinguishing a leiomyoma from MP in the GI tract, which is especially helpful when evaluating cases with limited sampling.

S3521 A Rare Case of Duodenal Leiomyoma

Introduction: Only 1–5% of gastrointestinal neoplasms are found in the small intestine. Adenocarcinomas, lymphomas, and neuroendocrine tumors are the most common malignant tumors seen in the small intestine, while gastrointestinal stromal tumors, leiomyosarcomas, and leiomyomas are uncommon. The jejunum, ileum, and duodenum are the three most common locations for leiomyomas. We are presenting a rare case of a female with duodenal leiomyoma. Case Description/Methods: A 70-year-old female presented to the hospital with complaints of fatigue and weakness. Laboratory evaluation showed iron deficiency anemia with hemoglobin 7.5g/dl and hematocrit 25.4%. The patient reported an episode of black tarry stool about a week before the presentation. The patient received one packed red blood cell transfusion, and upper gastrointestinal endoscopy (EGD) was performed to evaluate anemia. EGD revealed non-erosive gastritis and gastric erosions without any current or recent bleeding stigmata. A single large pedunculated polyp was found in the duodenum's first portion, extending into the second portion of the duodenum(a). Biopsy from the polyp revealed submucosal leiomyoma without any evidence of dysplasia or malignancy(b). The next day, a colonoscopy showed significant diverticulosis and non-bleeding internal hemorrhoids. The patient remained hemodynamically stable and was discharged home the next day. The patient presented about a month later with iron deficiency anemia again. Repeat EGD and colonoscopy performed this time showed no obvious source of bleeding. We also conducted a pill cam study, which also came back negative. (Figure) Discussion: It is unusual for leiomyomas, which are benign smooth muscle tumors, to develop in the gastrointestinal tract. Males are more likely than females to be diagnosed with duodenal leiomyomas in the 6th and 7th decades of life. The origin and pathology of these tumors in the gastrointestinal tract remain a mystery. Leiomyomas of the duodenum seldom cause symptoms. When a duodenal tumor is larger, it might cause more severe symptoms, such as bleeding, nausea, vomiting, and weakness. In our patient described above, we believe the leiomyoma caused bleeding, as no other definitive source of bleeding was found even after a complete evaluation. The case describes a rare duodenal tumor with an unusual presentation.Figure 1.: a. EGD showing a large pedunculated polyp extending from the first portion to the second portion of the duodenum. b. H&E stain showing submucosal benign spindle cell proliferation. No atypia, pleomorphism or mitotic activity.

Exploration of a new method for Photoshop-assisted endoscopic ultrasound to distinguish gastrointestinal stromal tumor and leiomyoma

Background Gastrointestinal stromal tumors (GISTs) and leiomyomas (GILs) are difficult to be distinguished by endoscopic ultrasound (EUS). Photoshop software combined with EUS has limitations in distinguishing GIST and GIL by detecting gray values. Therefore, the research aims to explore the new method by Photoshop in distinguishing the features of GISTs from GILs. Methods Patients who underwent EUS and were confirmed as GIST and GIL pathologically were included. The images of EUS were analyzed by Photoshop software. The mean gray value of tumor (Tmean), muscularis propria (Mmean), submucosa (Smean), water (Wmean) and TSD that originated from the same image, were calculated one by one. Then the ratio of the mean gray value of tumor to muscularis propria (TMratio), submucosa (TSratio), and water (TWratio) were calculated, respectively. Results Four hundred seventy-two patients (239 GILs and 233 GISTs) were enrolled in this study retrospectively. All the tumors were located in the stomach. Tmean and TSD were significantly higher in GISTs than in the GILs group (63.10 ± 23.29 vs. 57.70 ± 22.67, p = .011; 26.24 ± 8.99 vs. 24.30 ± 8.26, p = .015). TMratio, TSratio, and TWratio were also significantly higher in GISTs group (0.97 ± 0.37 vs. 0.81 ± 0.28, p < .001; 0.42 ± 0.14 vs. 0.38 ± 0.12, p < .001; 2.65 ± 1.36 vs. 2.16 ± 1.02, p < .001). The AUC of Tmean was 0.952 (95% CI 0.897–1.000), which can better distinguish GIST from GIL; the sensitivity was 0.900, the specificity was 0.975, and the Youden Index was 0.875, and the cutoff was 79.64. The AUCs of TMratio, TSratio, and TWratio were 0.917 (95% CI 0.844–0.991), 0.897 (95% CI 0.812–0.981), and 0.929 (95% CI 0.8870–0.987), respectively. The aforementioned data was verified in the clinical cases of known results, including 40 GISTs and 40 GILs. The sensitivity of Tmean, TMratio, TSratio, and TWratio for diagnosis of GIL was 97.5%, 82.5%, 95%, and 97.5%, respectively. And they were 62.5%, 95%, 80%, and 92.5% for GIST. Conclusion The application of Photoshop combined with EUS to detect the gray value and standard deviation has a specific value in distinguishing GIST from GIL, but with some deviation. Applying the gray value ratio also has great discrimination significance and can avoid the differences in operation from different instrument and equipment personnel. Therefore, it is worthy of clinical promotion in the future.

Ectopic Pancreatic tissue of Stomach: Pathology, Endoscopy, Endoscopic Ultrasonogram and Abdominal CT Findings

&lt;p&gt;We present an intresting case of heterotopic pancreas(HP) of the stomach in the posterior wall of antrum in a 60-years old female. The endoscopy, endoscopic ultrasonogram (EUS) and abdominal CT showed typical characteristics and with some vaiable appearances of this gastric lesion. The preoperation differential diagnosis includes gastrointestinal stromal tumor, leiomyoma, schwannoma and ectopic pancreatic tissue. The patient underwent laparoscopic wedge rsection. The frozen section and final pathologic diagnosis all confirmed ectopic pancreatic tissue. We also discuss the characteristics in correlation of the pathology with endoscopy, EUS and abdominal CT findings.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

The Diagnosis of Small Gastrointestinal Subepithelial Lesions by Endoscopic Ultrasound-Guided Fine Needle Aspiration and Biopsy.

Endoscopic ultrasonography (EUS) has been widely accepted in the diagnosis of all types of tumors, especially pancreatic tumors, lymph nodes, and subepithelial lesions (SELs). One reason is that the examination can provide a detailed observation, with tissue samples being immediately obtained by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA). Many SELs are detected incidentally during endoscopic examinations without symptoms. Most SELs are mesenchymal tumors originating from the fourth layer, such as gastrointestinal stromal tumors (GISTs), leiomyomas, and schwannomas. GISTs are potentially malignant. Surgical treatment is recommended for localized GISTs of ≥20 mm. However, the indications for the diagnosis and follow-up of GISTs of <20 mm in size are controversial. There are several reports on the rapid progression or metastasis of small GISTs. Therefore, it is important to determine whether a SEL is a GIST or not. The main diagnostic method is EUS-FNA. Recently, endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) using a new biopsy needle has been reported to obtain larger tissue samples. Additionally, various biopsy methods have been reported to have a high diagnostic rate for small GISTs. In local gastric SELs, regardless of the tumor size, EUS can be performed first; then, EUS-FNA/B or various biopsy methods can be used to obtain tissue samples for decision-making in relation to therapy and the follow-up period.

Transanal excision of anorectal leiomyoma, a rare location pathology: case report and review

Gastrointestinal leiomyomas (GILM) are benign tumors truly originated in the smooth muscle of the digestive tract, therefore, they are mesenchymal tumors and can come from the muscularis propria, muscularis mucosae or from the smooth muscle of the blood vessels. These tumors occur more frequently in women and despite being the second most common mesenchymal mural tumor of the digestive tract, anorectal location is very rare, representing less than 0.1% of all anorectal neoplasms. In the present case, we reported a patient with a rectal submucosal leiomyoma that was excised using a transanal approach.