Superiority of mucosal incision-assisted biopsy over ultrasound-guided fine needle aspiration biopsy in diagnosing small gastric subepithelial lesions: a propensity score matching analysis

Endoscopic ultrasound-guided bite-on-bite biopsy and endoscopic ultrasound-guided fine-needle aspiration in the diagnosis of gastric tumors with negative malignant endoscopy biopsies: a retrospective cohort study

BACKGROUND

Specific types of gastric tumors, including gastric linitis plastica and lymphoma, may cause extensive deep-layer infiltration, impeding an accurate diagnosis with endoscopic biopsy. This study aims to evaluate the efficacy of endoscopic ultrasound (EUS)-guided bite-on-bite biopsy and EUS-guided fine-needle aspiration (EUS-FNA) in diagnosing gastric malignancies with negative endoscopic biopsies.

METHODS

We retrospectively analyzed suspicious malignant gastric lesion cases in our hospital from October 2017 to August 2023. Clinical manifestations, radiographical examinations, endoscopic examinations, histopathological results, and therapeutic strategies were recorded and analyzed.

RESULTS

Forty malignant gastric tumor cases with negative endoscopic biopsies were incorporated into our study. EUS-guided bite-on-bite biopsy was performed in 16 cases exclusively, whereas 17 patients received EUS-FNA exclusively, and seven patients underwent both simultaneously. Among the 23 patients who received the EUS-guided bite-on-bite biopsy, 22 (95.7%) were diagnosed with malignancies. Among the 24 patients who received EUS-FNA, a total of 19 cases with malignancies (79.2%) were confirmed by EUS-FNA (p = 0.11): 13 gastric adenocarcinomas, five metastatic malignancies, and one malignant stromal tumor. No adverse events were observed in any of the cases.

CONCLUSIONS

EUS-guided bite-on-bite biopsy and EUS-FNA possess their advantages and disadvantages. EUS-guided bite-on-bite biopsy could serve as a reliable diagnostic method for shallow lesions with negative malignant endoscopic biopsies.

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

Background

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.

Methods

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.

Findings

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 ≤20 mm 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].

Interpretation

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.

Funding

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.

Endoscopic resection in subepithelial lesions of the upper gastrointestinal tract: Experience at a tertiary referral hospital in The Netherlands

Background and study aims Histological confirmation of subepithelial lesions (SELs) in the upper gastrointestinal tract remains challenging. Endoscopic resection of SELs is increasingly used for its excellent diagnostic yield and opportunity to do away with continued surveillance. In this study, we aimed to evaluate the indications, success rates and complications of different endoscopic resection techniques for SELs at a large, tertiary referral hospital in Rotterdam, The Netherlands. Patients and methods Data between October 2013 and December 2021 were retrospectively collected and analyzed. Main outcomes were R0-resection rate, en bloc resection rate, recurrence rate, and procedure-related adverse events (AEs) (Clavien-Dindo). Secondary outcomes were procedure time, need for surgical intervention, and clinical impact on patient management. Results A total of 58 patients were referred for endoscopic resection of upper gastrointestinal SELs. The median diameter of lesions was 20 mm (range 7-100 mm). Median follow-up time was 5 months (range 0.4-75.7). Forty-eight procedures (83%) were completed successfully leading to en bloc resection in 85% and R0-resection in 63%. Procedure-related AEs occurred in six patients (13%). Severe complications (CD grade 3a) were seen in three patients. The local recurrence rate for (pre)malignant diagnosis was 2%. Additional surgical intervention was needed in seven patients (15%). A total of 32 patients (67%) could be discharged from further surveillance after endoscopic resection. Conclusions Endoscopic resection is a safe and effective treatment for SELs and offers valuable information about undetermined SELs for which repeated sampling attempts have failed to provide adequate tissue for diagnosis.

Diagnostic yield of endoscopic and EUS-guided biopsy techniques in subepithelial lesions of the upper GI tract: a systematic review

BACKGROUND AND AIMS

Obtaining adequate tissue samples in subepithelial lesions (SELs) remains challenging. Several biopsy techniques are available, but a systematic review including all available techniques to obtain a histologic diagnosis of SEL is lacking. The aim of this study was to evaluate the diagnostic yield and adverse event rates of endoscopic biopsies, EUS-guided FNA (EUS-FNA), EUS-guided fine-needle biopsy (FNB) (EUS-FNB), and mucosal incision-assisted biopsy (MIAB) for SELs in the upper GI tract.

METHODS

A search strategy in multiple databases was performed. The primary outcome was diagnostic yield, defined as the percentage of procedures in which histology was obtained and resulted in a definitive histopathologic diagnosis. Secondary outcome measures included reported procedure-related adverse events, which were graded according to the AGREE (Adverse Events in Gastrointestinal Endoscopy) classification.

RESULTS

A total of 94 original articles were included. Studies were classified per endoscopic technique to obtain histopathology. This resulted in 8 included studies for endoscopic biopsy methods, 55 studies for EUS-FNA, 33 studies for EUS-FNB, and 26 studies for MIAB. Pooled rates for diagnostic yield were 40.6% (95% confidence interval [CI], 30.8-51.2) for endoscopic biopsy, 74.6% (95% CI, 69.9-78.7) for EUS-FNA, 84.2% (95% CI, 80.7-87.2) for EUS-FNB, and 88.2% (95% CI, 84.7-91.1) for MIAB. Reported procedure-related adverse events graded AGREE II or higher were 2.8% to 3.9% for endoscopic biopsies, 1.0% to 4.5% for EUS-FNA, .9% to 7.7% for EUS-FNB, and 1.9% to 7.9% for MIAB.

CONCLUSIONS

Based on the available evidence, MIAB and EUS-FNB seem to be most effective in terms of achieving a high diagnostic yield, with similar rates of adverse events.

Diagnostic Endoscopic Ultrasound (EUS) of the Luminal Gastrointestinal Tract

The purpose of this review is to focus on the diagnostic endoscopic ultrasound of the gastrointestinal tract. In the last decades, EUS has gained a central role in the staging of epithelial and sub-epithelial lesions of the gastrointestinal tract. With the evolution of imaging, the position of EUS in the diagnostic work-up and the staging flow-chart has continuously changed with two extreme positions: some gastroenterologists think that EUS is absolutely indispensable, and some think it is utterly useless. The truth is, as always, somewhere in between the two extremes. Analyzing the most up-to-date and strong evidence, we will try to give EUS the correct position in our daily practice.

Efficacy and histologic frequencies of endoscopic ultrasonography-guided tissue acquisition using conventional fine-needle aspiration needles for gastric subepithelial hypoechoic mass

Introduction/Purpose

For gastric subepithelial lesions (GSELs) showing a hypoechoic mass (HM) on endoscopic ultrasonography (EUS) imaging, the utility of EUS-guided tissue acquisition using conventional fine-needle aspiration needles (EUS-TA-CFNAN) and the frequency of histological types remain unclear. This study aimed to examine this issue.

Methods

This prospective observational study enrolled 291 consecutive patients who underwent EUS-TA-CFNAN for GSELs showing an HM (GSELHM) on EUS imaging. Immunohistochemical analysis was performed for all EUS-TA-CFNAN and surgically resected specimens. The main outcome measures were the technical results of EUS-TA-CFNAN and the frequency of histological types in GSELHM.

Results

The endoscopic ultrasound-guided tissue acquisition using conventional fine-needle aspiration needle diagnosis rate for GSELHM was 80.1% (95% confidence interval [CI]: 75.0-84.5, 233/291). It was significantly lower for antrum (P = 0.004) and lesions smaller than 2 cm (P = 0.003). There were no adverse events. The immunohistochemical diagnoses of EUS-TA-CFNAN included 149 cases of gastrointestinal stromal tumour (GIST) (51.2%), 48 cases of leiomyoma (16.5%), 11 cases of schwannoma (3.8%), 8 cases of the ectopic pancreas (2.7%), 5 cases of subepithelial lesion like cancer (1.7%), 12 cases of other lesions (4.1%), and 58 cases of undiagnosable lesions (19.9%). The frequency of malignant or potentially malignant tumour in GSELHM was 55.0% (95% CI: 49.1-60.8, 160/291). Surgery was performed in 149 patients according to the conclusive EUS-TA-CFNAN results, in which the diagnostic accuracy of EUS-TA-CFNAN was 97.3% (95% CI: 94.7-99.9, 145/149).

Conclusion

The use of EUS-TA-CFNAN for GSELHMs is safe and accurate. Gastric subepithelial lesions showing a hypoechoic mass have a reasonably high possibility of containing malignant or potentially malignant tumours, including GISTs.

Endoscopic ultrasound-guided fine-needle aspiration for gastrointestinal subepithelial lesions

Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the first-choice procedure for obtaining pathological tissue samples from gastrointestinal (GI) subepithelial lesions (SELs). However, its diagnostic accuracy is lower than that for pancreatic masses owing to puncture difficulty and the need for immunostaining for definitive diagnosis. The advent of fine-needle biopsy needles, which have become well known in recent years, improves the diagnostic accuracy of EUS-FNA for GI SELs. The forward-viewing echoendoscope and rapid on-site evaluation (ROSE) have also helped to improve diagnostic accuracy. Furthermore, in facilities where ROSE is not available, endosonographers perform a macroscopic on-site evaluation. With these procedural innovations, EUS-FNA is now performed aggressively even for SELs smaller than 20 mm. The incidence of procedure-related adverse events such as bleeding and infection is low, and thus, EUS-FNA can be safely performed to diagnose SELs.

Utility and advantage of the unroofing technique for gastrointestinal subepithelial tumors: A multicenter retrospective cohort study

Background and aim

Various techniques for direct biopsy from gastrointestinal subepithelial tumors (SETs) have been reported, although no standard method has been established. A common feature of these techniques is the removal of overlaying mucosa to enable direct biopsies from the SETs. These methods have been synthesized under the collective term "unroofing technique". We conducted a multicenter retrospective study to assess its efficacy and identify potential complications.

Methods

This study was conducted in 10 hospitals and involved all eligible patients who underwent unroofing techniques to obtain biopsies for gastrointestinal SETs between April 2015 and March 2021. The primary endpoint was the diagnostic accuracy of the unroofing technique, and the secondary endpoints were the incidence of adverse events and the factors contributing to the accurate diagnosis.

Results

The study included 61 patients with 61 gastrointestinal SETs. The median tumor size was 20 mm, and the median procedure time was 38 min, with 82% successful tumor exposure. The rate of pathological diagnosis was 72.1%. In 44 patients with a pathological diagnosis, two showed discrepancies with the postresection pathological diagnosis. No factors, including facility experience, organ, tumor size, or tumor exposure, significantly affected the diagnostic accuracy. There was one case of delayed bleeding and two cases of perforation.

Conclusion

The diagnostic yield of the unroofing technique was acceptable. The unroofing technique was beneficial regardless of institutional experience, organ, tumor size, or actual tumor exposure.

Technical outcomes and postprocedural courses of mucosal incision-assisted biopsy for possible gastric gastrointestinal stromal tumors: A series of 48 cases (with video)

Objective

Mucosal incision-assisted biopsy (MIAB) has been introduced as an alternative to endoscopic ultrasound-guided fine needle aspiration for tissue sampling of subepithelial lesions. However, there have been few reports on MIAB, and the evidence is lacking, particularly in small lesions. In this case series, we investigated the technical outcomes and postprocedural influences of MIAB for gastric subepithelial lesions 10 mm or greater in size.

Methods

We retrospectively reviewed cases with the intraluminal growth type of possible gastrointestinal stromal tumors, in which MIAB was performed at a single institution between October 2020 and August 2022. Technical success, adverse events, and clinical courses following the procedure were evaluated.

Results

In 48 MIAB cases with a median tumor diameter of 16 mm, the success rate of tissue sampling and the diagnostic rate were 96% and 92%, respectively. Two biopsies were considered sufficient for making the definitive diagnosis. Postoperative bleeding occurred in one case (2%). In 24 cases, surgery has performed a median of two months after MIAB, and no unfavorable findings caused by MIAB were seen intraoperatively. Finally, 23 cases were histologically diagnosed as gastrointestinal stromal tumors, and no patients who underwent MIAB experienced recurrence or metastasis during a median observation period of 13 months.

Conclusions

The data indicated that MIAB appears feasible, safe, and useful for histological diagnosis of gastric intraluminal growth types of possible gastrointestinal stromal tumors, even those of a small size. Postprocedural clinical effects were considered negligible.

Comparative diagnostic yield of different endoscopic techniques for tissue sampling of upper gastrointestinal subepithelial lesions: a network meta-analysis

BACKGROUND

There is limited evidence on the comparative diagnostic performance of endoscopic tissue sampling techniques for subepithelial lesions. We performed a systematic review with network meta-analysis to compare these techniques.

METHODS

A systematic literature review was conducted for randomized controlled trials (RCTs) comparing the sample adequacy and diagnostic accuracy of bite-on-bite biopsy, mucosal incision-assisted biopsy (MIAB), endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA), and EUS-guided fine-needle biopsy (FNB). Results were expressed as relative risk (RR) and 95%CI.

RESULTS

Eight RCTs were identified. EUS-FNB was significantly superior to EUS-FNA in terms of sample adequacy (RR 1.20 [95%CI 1.05-1.45]), whereas none of the other techniques significantly outperformed EUS-FNA. Additionally, bite-on-bite biopsy was significantly inferior to EUS-FNB (RR 0.55 [95%CI 0.33-0.98]). Overall, EUS-FNB appeared to be the best technique (surface under cumulative ranking [SUCRA] score 0.90) followed by MIAB (SUCRA 0.83), whereas bite-on-bite biopsy showed the poorest performance. When considering lesions <20 mm, MIAB, but not EUS-FNB, showed significantly higher accuracy rates compared with EUS-FNA (RR 1.68 [95%CI 1.02-2.88]). Overall, MIAB ranked as the best intervention for lesions <20 mm (SUCRA score 0.86 for adequacy and 0.91 for accuracy), with EUS-FNB only slightly superior to EUS-FNA. When rapid on-site cytological evaluation (ROSE) was available, no difference between EUS-FNB, EUS-FNA, and MIAB was observed.

CONCLUSION

EUS-FNB and MIAB appeared to provide better performance, whereas bite-on-bite sampling was significantly inferior to the other techniques. MIAB seemed to be the best option for smaller lesions, whereas EUS-FNA remained competitive when ROSE was available.

Diagnosis by Endoscopic Ultrasonography-Guided Sampling through the Lower Gastrointestinal Tract

Endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNA/FNB) is very safe and has a high diagnostic rate for upper gastrointestinal lesions, especially pancreatic lesions, but its application in the lower gastrointestinal tract has rarely been reported. Due to the tortuous course of the colorectum, with the sigmoid colon particularly prone to perforation, most endoscopists are reluctant to perform lateral-sector endoscopic ultrasound scanning without a water-bag protection for the puncture. The ultrasonic endoscopy and flexible puncture needle techniques recently introduced into clinical practice have made ultrasound-guided puncture safer and more convenient. In addition, endoscopists have carefully tested various protective measures to improve the safety of the lower gastrointestinal puncture, substantially increasing its clinical feasibility. In this article, we review the iterations of endoscopic ultrasound equipment introduced in recent years and the many ingenious ideas proposed by endoscopists regarding lower gastrointestinal puncture.

EUS-Guided Diagnosis of Gastric Subepithelial Lesions, What Is New?

Gastric subepithelial lesions (SELs) are intramural lesions that arise underneath the gastric mucosa. SELs can be benign, but can also be malignant or have malignant potential. Therefore, correct diagnosis is crucial. Endosonography has been established as the diagnostic gold standard. Although the identification of some of these lesions can be carried out immediately, solely based on their echo characteristics, for certain lesions histological examination is necessary. Sometimes histology can be inconclusive, especially for smaller lesions. Therefore, new methods have been developed in recent years to assist decision making, such as contrast enhanced endosonography, EUS elastography, and artificial intelligence systems. In this narrative review we provide a complete overview of the gastric SELs and summarize the new data of the last ten years concerning the diagnostic advances of endosonography on this topic.

Updates in the diagnosis and management of small-bowel tumors

Small-bowel tumors represent a rare entity comprising 0.6% of all new cancer cases in the US, and only 3% of all gastrointestinal neoplasms. They are a heterogenous group of neoplasms comprising of about forty different histological subtypes with the most common being adenocarcinoma, neuroendocrine tumors, stromal tumors and lymphomas. Their incidence has been reportedly increasing over recent years, partly owing to the advances and developments in the diagnostic modalities. Small-bowel capsule endoscopy, device assisted enteroscopy and dedicated small-bowel cross-sectional imaging are complimentary tools, supplementing each other in the diagnostic process. Therapeutic management of small-bowel tumors largely depends on the histological type and staging at diagnosis. The aim of the present review article is to discuss relevant advances in the diagnosis and management of small-bowel tumors.

Endoscopic Ultrasound Advanced Techniques for Diagnosis of Gastrointestinal Stromal Tumours

Gastrointestinal Stromal Tumors (GISTs) are subepithelial lesions (SELs) that commonly develop in the gastrointestinal tract. GISTs, unlike other SELs, can exhibit malignant behavior, so differential diagnosis is critical to the decision-making process. Endoscopic ultrasound (EUS) is considered the most accurate imaging method for diagnosing and differentiating SELs in the gastrointestinal tract by assessing the lesions precisely and evaluating their malignant risk. Due to their overlapping imaging characteristics, endosonographers may have difficulty distinguishing GISTs from other SELs using conventional EUS alone, and the collection of tissue samples from these lesions may be technically challenging. Even though it appears to be less effective in the case of smaller lesions, histology is now the gold standard for achieving a final diagnosis and avoiding unnecessary and invasive treatment for benign SELs. The use of enhanced EUS modalities and elastography has improved the diagnostic ability of EUS. Furthermore, recent advancements in artificial intelligence systems that use EUS images have allowed them to distinguish GISTs from other SELs, thereby improving their diagnostic accuracy.

Negligible procedure-related dissemination risk of mucosal incision-assisted biopsy for gastrointestinal stromal tumors versus endoscopic ultrasound-guided fine-needle aspiration/biopsy

BACKGROUND

Mucosal incision-assisted biopsy (MIAB) is a valuable alternative to endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNAB) for sampling gastric subepithelial lesions (SELs). This study aimed to evaluate the potential risk of dissemination and impact on postoperative prognosis associated with MIAB, which has not yet been investigated.

METHODS

Study 1: A prospective observational study was conducted to examine the presence or absence and growth rate of tumor cells in gastric juice before and after the procedure in patients with SELs who underwent MIAB (n = 25) or EUS-FNAB (n = 22) between September 2018 and August 2021. Study 2: A retrospective study was conducted to examine the impact of MIAB on postoperative prognosis in 107 patients with gastrointestinal stromal tumors diagnosed using MIAB (n = 39) or EUS-FNAB (n = 68) who underwent surgery between January 2001 and July 2020.

RESULTS

In study 1, although no tumor cells were observed in gastric juice in MIAB before the procedure, they were observed in 64% of patients after obtaining samples (P < 0.001). In contrast, no tumor cells were observed in the gastric juice in EUS-FNAB before and after the procedure. In study 2, there was no significant difference in 5-year disease-free survival between MIAB (100%) and EUS-FNAB (97.1%) (P = 0.27).

CONCLUSION

MIAB is safe, with little impact on postoperative prognosis, although the procedure releases some tumor cells after damaging the SEL's pseudocapsule.

Auxiliary diagnosis of subepithelial lesions by impedance measurement during endoscopic ultrasound-guided fine-needle biopsy

BACKGROUND AND AIMS

EUS-guided FNA/biopsy (EUS-FNA/B) is the citerion standard for diagnosing subepithelial lesions (SELs); however, its diagnostic ability for SELs <20 mm is low. We developed a new diagnostic method to differentiate between GI stromal tumor (GIST) and non-GIST by measuring high-frequency impedance (H-impedance) using an EUS-FNB needle.

METHODS

The H-impedance of gastric epithelial neoplasms from 16 cases were measured with a conventional impedance probe to confirm whether H-impedance is clinically useful for assessing cell density (study 1). The H-impedance values of exposed SELs from 25 cases with use of the conventional probe (study 2) and nonexposed SELs from 20 cases with use of the EUS-FNB needle probe (study 3) were measured to determine the diagnostic ability of H-impedance for differentiating GISTs from non-GISTs.

RESULTS

H-impedance significantly positively correlated with cell density (P = .030) (study 1). The H-impedance of GIST (99.5) measured with a conventional probe was significantly higher than with those of the muscular layer (82.4) and leiomyoma (89.2) (P < .01) (study 2). The H-impedance of GIST measured with the EUS-FNB needle was also significantly higher than that of leiomyoma (GIST: 80.2 vs leiomyoma, 71.8; P = .015). The diagnostic yield of the impedance method for differentiating GISTs from non-GISTs had 94.4% accuracy, 88.9% sensitivity, 100% specificity, and 0.95 area under the curve. Diagnostic ability was not affected by lesion size (P = .86) (study 3).

CONCLUSION

Auxiliary differential diagnosis between gastric GISTs and non-GISTs by the H-impedance measurement during EUS-FNB could be a good option, especially when the lesion is <20 mm.

Efficacy of ultrasound endoscopy with artificial intelligence for the differential diagnosis of non-gastric gastrointestinal stromal tumors

Gastrointestinal stromal tumors (GISTs) are common subepithelial lesions (SELs) and require treatment considering their malignant potential. We recently developed an endoscopic ultrasound-based artificial intelligence (EUS-AI) system to differentiate GISTs from non-GISTs in gastric SELs, which were used to train the system. We assessed whether the EUS-AI system designed for diagnosing gastric GISTs could be applied to non-gastric GISTs. Between January 2015 and January 2021, 52 patients with non-gastric SELs (esophagus, n = 15; duodenum, n = 26; colon, n = 11) were enrolled. The ability of EUS-AI to differentiate GISTs from non-GISTs in non-gastric SELs was examined. The accuracy, sensitivity, and specificity of EUS-AI for discriminating GISTs from non-GISTs in non-gastric SELs were 94.4%, 100%, and 86.1%, respectively, with an area under the curve of 0.98 based on the cutoff value set using the Youden index. In the subanalysis, the accuracy, sensitivity, and specificity of EUS-AI were highest in the esophagus (100%, 100%, 100%; duodenum, 96.2%, 100%, 0%; colon, 90.9%, 100%, 0%); the cutoff values were determined using the Youden index or the value determined using stomach cases. The diagnostic accuracy of EUS-AI increased as lesion size increased, regardless of lesion location. EUS-AI based on gastric SELs had good diagnostic ability for non-gastric GISTs.

Mucosal incision-assisted biopsy versus endoscopic ultrasound-assisted tissue acquisition for subepithelial lesions: a systematic review and meta-analysis

Background/Aims

Mucosal incision-assisted biopsy (MIAB) for tissue acquisition (TA) from subepithelial lesions (SELs) is emerging as an alternative to endoscopic ultrasound (EUS)-guided TA. Only a limited number of studies compared the diagnostic utility of MIAB and EUS for upper gastrointestinal (GI) SELs; therefore, we conducted this systematic review and meta-analysis.

Methods

A comprehensive literature search from January 2020 to January 2022 was performed to compare the diagnostic accuracy and safety of MIAB and EUS-guided TA for upper GI SELs.

Results

Seven studies were included in this meta-analysis. The pooled technical success rate (risk ratio [RR], 0.96; 95% confidence interval [CI], 0.89–1.04) and procedural time (mean difference=–4.53 seconds; 95% CI, –22.38 to 13.31] were comparable between both the groups. The overall chance of obtaining a positive diagnostic yield was lower with EUS than with MIAB for all lesions (RR, 0.83; 95% CI, 0.71–0.98) but comparable when using a fine-needle biopsy needle (RR, 0.93; 95% CI, 0.83–1.04). The positive diagnostic yield of MIAB was higher for lesions <20 mm (RR, 0.75; 95% CI, 0.63–0.89). Six studies reported no adverse events.

Conclusions

MIAB can be considered an effective alternative to EUS-guided TA for upper GI SELs without an increased risk of adverse events.

Differentiating Gastrointestinal Stromal Tumors from Leiomyomas Using a Neural Network Trained on Endoscopic Ultrasonography Images

BACKGROUND

Endoscopic ultrasonography (EUS) is crucial to diagnose and evaluate gastrointestinal mesenchymal tumors (GIMTs). However, EUS-guided biopsy does not always differentiate gastrointestinal stromal tumors (GISTs) from leiomyomas. We evaluated the ability of a convolutional neural network (CNN) to differentiate GISTs from leiomyomas using EUS images. The conventional EUS features of GISTs were also compared with leiomyomas.

PATIENTS AND METHODS

Patients who underwent EUS for evaluation of upper GIMTs between 2010 and 2020 were retrospectively reviewed, and 145 patients (73 women and 72 men; mean age 54.8 ± 13.5 years) with GISTs (n = 109) or leiomyomas (n = 36), confirmed by immunohistochemistry, were included. A total of 978 images collected from 100 patients were used to train and test the CNN system, and 384 images from 45 patients were used for validation. EUS images were also evaluated by an EUS expert for comparison with the CNN system.

RESULTS

The sensitivity, specificity, and accuracy of the CNN system for diagnosis of GIST were 92.0%, 64.3%, and 86.98% for the validation dataset, respectively. In contrast, the sensitivity, specificity, and accuracy of the EUS expert interpretations were 60.5%, 74.3%, and 63.0%, respectively. Concerning EUS features, only higher echogenicity was an independent and significant factor for differentiating GISTs from leiomyomas (p < 0.05).

CONCLUSIONS

The CNN system could diagnose GIMTs with higher accuracy than an EUS expert and could be helpful in differentiating GISTs from leiomyomas. A higher echogenicity may also aid in differentiation.

Endoscopic management of subepithelial lesions including neuroendocrine neoplasms: European Society of Gastrointestinal Endoscopy (ESGE) Guideline

1: ESGE recommends endoscopic ultrasonography (EUS) as the best tool to characterize subepithelial lesion (SEL) features (size, location, originating layer, echogenicity, shape), but EUS alone is not able to distinguish among all types of SEL.Strong recommendation, moderate quality evidence. 2: ESGE suggests providing tissue diagnosis for all SELs with features suggestive of gastrointestinal stromal tumor (GIST) if they are of size > 20 mm, or have high risk stigmata, or require surgical resection or oncological treatment.Weak recommendation, very low quality evidence. 3: ESGE recommends EUS-guided fine-needle biopsy (EUS-FNB) or mucosal incision-assisted biopsy (MIAB) equally for tissue diagnosis of SELs ≥ 20 mm in size.Strong recommendation, moderate quality evidence. 4: ESGE recommends against surveillance of asymptomatic gastrointestinal (GI) tract leiomyomas, lipomas, heterotopic pancreas, granular cell tumors, schwannomas, and glomus tumors, if the diagnosis is clear.Strong recommendation, moderate quality evidence. 5: ESGE suggests surveillance of asymptomatic esophageal and gastric SELs without definite diagnosis, with esophagogastroduodenoscopy (EGD) at 3-6 months, and then at 2-3-year intervals for lesions < 10 mm in size, and at 1-2-year intervals for lesions 10-20 mm in size. For asymptomatic SELs > 20 mm in size that are not resected, ESGE suggests surveillance with EGD plus EUS at 6 months and then at 6-12-month intervals.Weak recommendation, very low quality evidence. 6: ESGE recommends endoscopic resection for type 1 gastric neuroendocrine neoplasms (g-NENs) if they grow larger than 10 mm. The choice of resection technique should depend on size, depth of invasion, and location in the stomach.Strong recommendation, low quality evidence. 7: ESGE suggests considering removal of histologically proven gastric GISTs smaller than 20 mm as an alternative to surveillance. The decision to resect should be discussed in a multidisciplinary meeting. The choice of technique should depend on size, location, and local expertise.Weak recommendation, very low quality evidence. 8: ESGE suggests that, to avoid unnecessary follow-up, endoscopic resection is an option for gastric SELs smaller than 20 mm and of unknown histology after failure of attempts to obtain diagnosis.Weak recommendation, very low quality evidence. 9: ESGE recommends basing the surveillance strategy on the type and completeness of resection. After curative resection of benign SELs no follow-up is advised, except for type 1 gastric NEN for which surveillance at 1-2 years is advised.Strong recommendation, low quality evidence. 10: For lower or upper GI NEN with a positive or indeterminate margin at resection, ESGE recommends repeating endoscopy at 3-6 months and another attempt at endoscopic resection in the case of residual disease.Strong recommendation, low quality evidence.

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.

Artificial intelligence-based diagnosis of upper gastrointestinal subepithelial lesions on endoscopic ultrasonography images

BACKGROUND

Endoscopic ultrasonography (EUS) is useful for the differential diagnosis of subepithelial lesions (SELs); however, not all of them are easy to distinguish. Gastrointestinal stromal tumors (GISTs) are the commonest SELs, are considered potentially malignant, and differentiating them from benign SELs is important. Artificial intelligence (AI) using deep learning has developed remarkably in the medical field. This study aimed to investigate the efficacy of an AI system for classifying SELs on EUS images.

METHODS

EUS images of pathologically confirmed upper gastrointestinal SELs (GIST, leiomyoma, schwannoma, neuroendocrine tumor [NET], and ectopic pancreas) were collected from 12 hospitals. These images were divided into development and test datasets in the ratio of 4:1 using random sampling; the development dataset was divided into training and validation datasets. The same test dataset was diagnosed by two experts and two non-experts.

RESULTS

A total of 16,110 images were collected from 631 cases for the development and test datasets. The accuracy of the AI system for the five-category classification (GIST, leiomyoma, schwannoma, NET, and ectopic pancreas) was 86.1%, which was significantly higher than that of all endoscopists. The sensitivity, specificity, and accuracy of the AI system for differentiating GISTs from non-GISTs were 98.8%, 67.6%, and 89.3%, respectively. Its sensitivity and accuracy were significantly higher than those of all the endoscopists.

CONCLUSION

The AI system, classifying SELs, showed higher diagnostic performance than that of the experts and may assist in improving the diagnosis of SELs in clinical practice.

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.

Advancements in the Diagnosis of Gastric Subepithelial Tumors

A diagnosis of subepithelial tumors (SETs) is sometimes difficult due to the existence of overlying mucosa on the lesions, which hampers optical diagnosis by conventional endoscopy and tissue sampling with standard biopsy forceps. Imaging modalities, by using computed tomography and endoscopic ultrasonography (EUS) are mandatory to noninvasively collect the target's information and to opt candidates for further evaluation. Particularly, EUS is an indispensable diagnostic modality for assessing the lesions precisely and evaluating the possibility of malignancy. The diagnostic ability of EUS appears increased by the combined use of contrast-enhancement or elastography. Histology is the gold standard for obtaining the final diagnosis. Tissue sampling requires special techniques to break the mucosal barrier. Although EUS-guided fine-needle aspiration (EUS-FNA) is commonly applied, mucosal cutting biopsy and mucosal incision-assisted biopsy are comparable methods to definitively obtain tissues from the exposed surface of lesions and seem more useful than EUS-FNA for small SETs. Recent advancements in artificial intelligence (AI) have a potential to drastically change the diagnostic strategy for SETs. Development and establishment of noninvasive methods including AI-assisted diagnosis are expected to provide an alternative to invasive, histological diagnosis.

A Case of Myoepithelial Hamartoma: Morphological Variation Supported by OCT4 Expression

In this report, we describe a patient with myoepithelial hamartoma, which is regarded as synonymous with adenomyosis and heterotopic pancreas. Endoscopy revealed a submucosal tumor in the antrum of the stomach. Subsequently, distal gastrectomy with Roux-en-Y reconstruction was performed. Histological findings of adenomyomatous lesion and heterotopic pancreatic tissue were observed in this lesion. The distribution of OCT4, which is a pluripotency marker, varied in each part.

Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors

BACKGROUND

Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS images. If artificial intelligence (AI) can be used for the diagnosis of SELs, it should provide several benefits, including objectivity, simplicity, and quickness. In this pilot study, we propose an AI diagnostic system for SELs and evaluate its efficacy.

METHODS

Thirty sets each of EUS images with SELs ≥ 20 mm or < 20 mm were prepared for diagnosis by an EUS diagnostic system with AI (EUS-AI) and three EUS experts. The EUS-AI and EUS experts diagnosed the SELs using solely the EUS images. The concordance rates of the EUS-AI and EUS experts' diagnoses were compared with the pathological findings of the SELs.

RESULTS

The accuracy, sensitivity, and specificity for SELs < 20 mm were 86.3, 86.3, and 62.5%, respectively for the EUS-AI, and 73.3, 68.2, and 87.5%, respectively, for the EUS experts. In contrast, accuracy, sensitivity, and specificity for SELs ≥ 20 mm were 90.0, 91.7, and 83.3%, respectively, for the EUS-AI, and 53.3, 50.0, and 83.3%, respectively, for the EUS experts. The area under the curve for the diagnostic yield of the EUS-AI for SELs ≥ 20 mm (0.965) was significantly higher than that (0.684) of the EUS experts (P = 0.007).

CONCLUSION

EUS-AI had a good diagnostic yield for SELs ≥ 20 mm. EUS-AI has potential as a good option for the diagnosis of SELs.

Endoscopic diagnosis and management of gastric subepithelial lesions

PURPOSE OF REVIEW

The purpose of this manuscript is to provide an in-depth review of gastric subepithelial lesions (SELs) and describe the current approach to endoscopic diagnosis and management of these lesions.

RECENT FINDINGS

Gastric SELs are a relatively frequent finding on routine endoscopy (incidence 0.2-3%). A systematic approach to diagnosis and management is key because many SELs are of little consequence, while others carry a high risk of malignant transformation. Because esophagogastroduodenoscopy (EGD) cannot delineate depth of invasion or subepithelial appearance, endoscopic ultrasound (EUS) should be considered a first-line modality. Recent data suggest EUS-guided fine needle biopsy (FNB) may be superior to traditional fine needle aspiration (FNA) for the diagnosis of gastric SELs due to its ability to obtain histologic specimens for immunohistochemical staining. Alternative techniques for tissue sampling (combined with simultaneous resection) include submucosal resection, endoscopic submucosal dissection (ESD), submucosal tunnelling with endoscopic resection (STER) or endoscopic full-thickness resection (EFTR).

SUMMARY

This review details the endoscopic diagnosis and management of gastric SELs. Although EUS-guided sampling remains a first-line strategy (preferably with FNB), recent techniques including ESD, STER and EFTR have the potential to provide additional diagnostic and therapeutic options.