Laparoscopy-assisted trans gastric wedge resection: A safe treatment for gastric pyloric liposarcoma: A case report and literature review.

Background: Gastric liposarcoma (GL) is extremely rare and radical surgery has been the conventional treatment, even in small tumors. Laparoscopic wedge resection has been reported worldwide for subepithelial tumors of the stomach. Case presentation: The patient was an asymptomatic 63-year-old man presenting with a subepithelial gastric tumor. The esophagogastroduodenoscopy showed a 3 cm ulcerated soft tumor located in the posterior wall of the antrum just above the pylorus. Two preoperative biopsies were performed with a negative result for malignant neoplasm. Dynamic computerized tomography revealed 35 × 35 mm well-defined pyloric mass with fat density. Despite the difficult location of the tumor, function-preserving surgery was performed. Surgery was initiated by a laparoscopic approach with four trocars. After the dissection of the greater omentum, the greater curvature and the posterior wall of the stomach were exposed. A gastrostomy was performed in the anterior wall of the antrum. Due to the difficulty in identifying the tumor location, a mini-laparotomy was conducted. After assessing the pylorus and section parameters, the tumor was extracted by gastrostomy and resected with a linear stapler. The patient was discharged after five days with no complications. The histological diagnosis was a well-differentiated liposarcoma. Resection margins were clear. The tumor cells tested negative for MDM2. No adjuvant therapy was indicated. The patient is alive without recurrence. Conclusions: Despite its rarity, gastric liposarcoma should be respected for differential diagnosis in submucosal tumors. The main diagnostic method is histological, and surgery is the conventional treatment without yet having a consensus. Minimally invasive wedge resection might be a suitable treatment even if the location is close to the pylorus. Multicenter studies are required to obtain better results in the management of this pathology.

Exploring Gastric Perforation as an Uncommon yet Critical Complication of Gastrointestinal Stromal Tumors.

Hollow viscus perforation poses a significant diagnostic and therapeutic dilemma for the majority of clinicians. It is vitally important that in cases of gastrointestinal perforation, the tissue that was perforated is always evaluated, since a malignant tumor can cause this complication as a presentation form. Here, we present the case of a patient whose first manifestation of a malignant gastric tumor was its perforation and the presence of septic shock secondary to this. This case exemplifies the importance of innovative thinking in facilitating a comprehensive diagnostic and therapeutic strategy, leading to the timely identification and management of a malignant tumor by the oncology team; such interventions not only enhance patient outcomes but also mitigate morbidity and mortality rates.

Goblet Cell Adenocarcinoma in the Stomach: A Case Report.

Goblet cell adenocarcinoma (GCA) is known as an amphicrine tumor often seen in the appendix. Here, we report a rare case of GCA in the stomach. An 80-year-old man underwent gastroscopy due to epigastric pain and was diagnosed with gastric cancer. He received total gastrectomy and histology showed a mixture of a moderately-differentiated tubular adenocarcinoma, a mucinous adenocarcinoma, and a tumor composed of goblet-like mucinous cells with neuroendocrine differentiation. The tumor volume ratio was about 4:1:5, respectively, and a final diagnosis of GCA was made. The metastasis of the regional lymph node was occupied by only the component of goblet-like cells. GCA should be recognized as a rare histologic subtype of gastric cancer.

Risk factors for postgastric endoscopic submucosal dissection bleeding in direct oral anticoagulant users.

OBJECTIVES: Bleeding after endoscopic submucosal dissection (ESD) for gastric tumors in patients taking antithrombotic drugs, in particular direct oral anticoagulants (DOACs), remains unresolved; therefore, we evaluated the risk factors for post-ESD bleeding and drug differences in patients taking DOACs. METHODS: We included 278 patients taking antithrombotic drugs who underwent gastric ESD between January 2017 and March 2022. Antithrombotic drugs were withdrawn following the 2017 guidelines (Appendix on anticoagulants including DOACs). To further clarify differences in antithrombotic agents' effects, the peri-cancerous mucosa in the resected specimen was pathologically evaluated according to the Updated Sydney System. Multivariate analysis was performed to assess the risk of post-ESD bleeding. RESULTS: The incidence of post-ESD bleeding in patients taking DOACs was 19.6% (10/51). Among patients taking antithrombotic drugs, DOACs were identified as a possible factor involved in post-ESD bleeding (odds ratio [OR] 4.92). Among patients taking DOACs, possible factors included resection length diameter ≥30 mm (OR 3.72), presence of neutrophil infiltration (OR 2.71), lesions occurring in the lower third of stomach (OR 2.34), and preoperative antiplatelet use (OR 2.22). Post-ESD bleeding by DOAC type was 25.0% of patients (4/16) receiving apixaban, in 20.0% (3/15) receiving edoxaban, in 21.4% (3/14) receiving rivaroxaban, and in none of those receiving dabigatran. CONCLUSIONS: The administration of DOACs was shown to be a possible factor involved in post-ESD bleeding, and risk factors for patients taking DOACs included neutrophil infiltration. The pharmacological differences in the effects of DOACs contributing to bleeding in gastric ulcers suggest comparatively less bleeding with dabigatran after ESD.

Assessing clinical pathological characteristics and gene expression patterns associated with hepatoid adenocarcinoma of the stomach.

OBJECTIVE: The objective of this study is to assess the clinical pathological attributes of Hepatoid Adenocarcinoma of the Stomach (HAS) and to delineate the differential diagnostic considerations about it. METHOD: The investigation involved analyzing 31 HAS cases using histomorphological assessment, immunohistochemical profiling, and relevant gene detection methodologies. RESULTS: Among the 31 HAS cases, 9 (29.0%) were of trabecular hepatoid adenocarcinoma of the stomach, 7 (22.6%) were of glandular hepatoid adenocarcinoma of the stomach, 4 (12.9%) were of nesting hepatoid adenocarcinoma of the stomach, 3 (9.7%) were of clear cell hepatoid adenocarcinoma of the stomach, and 8 (25.8%) were of diverse hepatoid adenocarcinoma of the stomach. Of these 31 cases, 24 were male, accounting for 77.4% of the cases. Serum alpha-fetoprotein (AFP) levels were notably elevated, with radioimmunoassay results reaching 1240 ng/ml; 28 out of 31 cases had AFP levels below 25 µg/l, accounting for 90.3%. Related genes: HER2 protein indicated positive expression on the cell membrane in 35.5% (11/31) of the cases; HER2 gene amplification detected by the FISH technique was 12.9% (4/31). Tumoral stromal lymphocytes exhibited a PD-1 positive expression rate of 58.1% (18/31). In gastric cancer tissues, the PD-L1 positive rate was 45.1% (14/31). CONCLUSION: HAS represents a distinctive subtype of gastric cancer with a propensity for mimicking other forms of tumors, underscoring the significance of discerning its unique histopathological attributes for accurate differential diagnosis and tailored therapeutic interventions.

HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images.

BACKGROUND: Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity. METHODS: In this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios. RESULTS: Our baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks. CONCLUSIONS: Comprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

CALD1 facilitates epithelial-mesenchymal transition progression in gastric cancer cells by modulating the PI3K-Akt pathway.

BACKGROUND: CALD1 has been discovered to be abnormally expressed in a variety of malignant tumors, including gastric cancer (GC), and is associated with tumor progression and immune infiltration; however, the roles and mechanisms of CALD1 in epithelial-mesenchymal transition (EMT) in GC are unknown. AIM: To investigate the role and mechanism of CALD1 in GC progression, invasion, and migration. METHODS: In this study, the relationship between CALD1 and GC, as well as the possible network regulatory mechanisms of CALD1, was investigated by bioinformatics and validated by experiments. CALD1-siRNA was synthesized and used to transfect GC cells. Cell activity was measured using the CCK-8 method, cell migration and invasive ability were measured using wound healing assay and Transwell assay, and the expression levels of relevant genes and proteins in each group of cells were measured using qRT-PCR and Western blot. A GC cell xenograft model was established to verify the results of in vitro experiments. RESULTS: Bioinformatics results showed that CALD1 was highly expressed in GC tissues, and CALD1 was significantly higher in EMT-type GC tissues than in tissues of other types of GC. The prognosis of patients with high expression of CALD1 was worse than that of patients with low expression, and a prognostic model was constructed and evaluated. The experimental results were consistent with the results of the bioinformatics analysis. The expression level of CALD1 in GC cell lines was all higher than that in gastric epithelial cell line GES-1, with the strongest expression found in AGS and MKN45 cells. Cell activity was significantly reduced after CALD1-siRNA transfection of AGS and MKN45 cells. The ability of AGS and MKN45 cells to migrate and invade was reduced after CALD1-siRNA transfection, and the related mRNA and protein expression was altered. According to bioinformatics findings in GC samples, the CALD1 gene was significantly associated with the expression of members of the PI3K-AKT-mTOR signaling pathway as well as the EMT signaling pathway, and was closely related to the PI3K-Akt signaling pathway. Experimental validation revealed that upregulation of CALD1 increased the expression of PI3K, p-AKT, and p-mTOR, members of the PI3K-Akt pathway,while decreasing the expression of PTEN; PI3K-Akt inhibitor treatment decreased the expression of PI3K, p-AKT, and p-mTOR in cells overexpressing CALD1 (still higher than that in the normal group), but increased the expression of PTEN (still lower than that in the normal group). CCK-8 results revealed that the effect of CALD1 on tumor cell activity was decreased by the addition of the inhibitor. Scratch and Transwell experiments showed that the effect of CALD1 on tumor cell migration and invasion was weakened by the addition of the PI3K-Akt inhibitor. The mRNA and protein levels of EMT-related genes in AGS and MKN45 cells were greatly altered by the overexpression of CALD1, whereas the effect of overexpression of CALD1 was significantly weakened by the addition of the PI3K-Akt inhibitor. Animal experiments showed that tumour growth was slow after inhibition of CALD1, and the expression of some PI3K-Akt and EMT pathway proteins was altered. CONCLUSION: Increased expression of CALD1 is a key factor in the progression, invasion, and metastasis of GC, which may be associated with regulating the PI3K-Akt pathway to promote EMT.

A Prospective Observational Study on Gastric Endoscopic Submucosal Dissection under Continuous Administration of Antithrombotic Agents.

Background: This study aimed to assess the completion rate and postoperative bleeding incidence of endoscopic submucosal dissection (ESD) for gastric tumors under continuous antithrombotic therapy. Methods: A prospective observational study was conducted including 88 patients with 100 gastric lesions who underwent gastric endoscopic submucosal dissection (ESD) and received continuous antithrombotic therapy. Additionally, retrospective data on gastric ESD in 479 patients with 534 lesions who did not receive antithrombotic therapy were collected for comparison. Results: The en bloc resection rates (100% in the continuous antithrombotic therapy group vs. 100% in the non-antithrombotic therapy group) and complete resection rates (97.0% vs. 96.3%, respectively) were high and comparable between the groups. No significant differences were found in the specimen size or procedure time. Perforation rates were low (0% vs. 2.3%, respectively) and were not significantly different between the groups. However, postoperative bleeding occurred significantly more frequently in the continuous antithrombotic therapy group (10.2% vs. 4.2%, respectively) than in the non-antithrombotic therapy group. The subgroup analysis revealed a higher incidence of postoperative bleeding in patients receiving thienopyridine derivatives. Conclusions: Continuous administration of antithrombotic agents, especially thienopyridines, increased the risk of postprocedural hemorrhage following gastric ESD. These findings support the need for careful consideration of pharamcological management before ESD, aligning with the current guidelines.

Development of an Artificial Intelligence Model for the Classification of Gastric Carcinoma Stages Using Pathology Slides.

This study showcases a novel AI-driven approach to accurately differentiate between stage one and stage two gastric carcinoma based on pathology slide analysis. Gastric carcinoma, a significant contributor to cancer-related mortality globally, necessitates precise staging for optimal treatment planning and patient management. Leveraging a comprehensive dataset of 3540 high-resolution pathology images sourced from Kaggle.com, comprising an equal distribution of stage one and stage two tumors, the developed AI model demonstrates remarkable performance in tumor staging. Through the application of state-of-the-art deep learning techniques on Google's Collaboration platform, the model achieves outstanding accuracy and precision rates of 100%, accompanied by notable sensitivity (97.09%), specificity (100%), and F1-score (98.31%). Additionally, the model exhibits an impressive area under the receiver operating characteristic curve (AUC) of 0.999, indicating superior discriminatory power and robustness. By providing clinicians with an efficient and reliable tool for gastric carcinoma staging, this AI-driven approach has the potential to significantly enhance diagnostic accuracy, inform treatment decisions, and ultimately improve patient outcomes in the management of gastric carcinoma. This research contributes to the ongoing advancement of cancer diagnosis and underscores the transformative potential of artificial intelligence in clinical practice.

Gastric inflammatory myofibroblastic tumor: a case report.

BACKGROUND: Inflammatory myofibroblastic tumor (IMT) of the stomach is an uncommon mesenchymal neoplasm. We present a case of gastric submucosal tumor (SMT) where the final diagnosis was IMT. CASE PRESENTATION: A 69-year-old man presented with a 24-mm SMT on the posterior wall of the middle third of the stomach that was detected by screening upper gastrointestinal endoscopy. Abdominal contrast-enhanced computed tomography showed that the tumor was well-enhanced. Although endoscopic ultrasonography-guided biopsy was performed, the histological diagnosis was not confirmed preoperatively. Since the tumor was clinically suspected to be a gastrointestinal stromal tumor, we performed gastric wedge resection by laparoscopic-endoscopic cooperative surgery. Pathologically, proliferative spindle cells with a positive reaction for smooth muscle actin, negativity for c-kit, desmin, s-100, CD34, STAT-6, ß-catenin and anaplastic lymphoma kinase 1 were identified. Hence, the tumor was finally diagnosed as an IMT originating from the stomach. CONCLUSIONS: When an SMT of the stomach is identified, the possibility of gastric IMT should be considered.

Primary Squamous Cell Carcinoma of the Stomach: A Case Report.

Gastric squamous cell carcinoma (SCC) is a rare and puzzling entity that challenges conventional paradigms of gastric malignancies, especially in young adults. This case report presents a 22-year-old male with invasive SCC of the stomach, emphasizing the rarity of such occurrences and their diagnostic challenges. The literature review underscores the scarcity of information on gastric SCC, necessitating a critical examination of its clinical implications, etiological factors, and optimal management. The patient's complex medical history, diagnostic journey, and treatment course are detailed, highlighting the importance of multidisciplinary collaboration and advanced diagnostic techniques. Immunohistochemistry is a crucial tool for precise tumor characterization, and the absence of established risk factors emphasizes the enigmatic nature of gastric SCC. This case report contributes to the understanding of gastric SCC, prompting further research into its unique features, etiology, and therapeutic strategies in the context of gastric cancer.

A Case Report and Literature Review of Gastric Stump Carcinoma: An Uncommon Entity Following the Billroth II Procedure.

Gastric stump carcinoma is a rare phenomenon and could occur in individuals after a distal gastric resection. Regardless of the surgical approach, it can lead to certain complications. However, the Billroth II gastrojejunostomy procedure has been noted to have some specifically interesting complications due to the anatomical changes it triggers. These changes, such as bacterial overgrowth and enterogastric reflux, can cause metaplasia. We discuss a case of an 81-year-old male with a history of peptic ulcer disease (PUD) status post-Billroth II gastrojejunostomy 30 years prior who presented with a four-day history of bright red blood per rectum. On esophagogastroduodenoscopy (EGD), he was found to have friable, ulcerated mucosa at the anastomosis site. Biopsy results revealed CDX2-positive cells, indicating gastric adenocarcinoma. Although it is well-known that the anatomical changes of gastrojejunostomy will undoubtedly change the microbiome of the stomach, physicians should also be mindful of the more feared complications such as gastric stump carcinoma.

A Rare Variant of Gastric Adenocarcinoma Presenting as a Symptomatic Early-Stage Submucosal Tumor in the Gastric Antral Primary.

Gastric adenocarcinomas are a well-known malignancy, with the vast majority presenting as primary mucosal invasions. However, a rare form of this cancer presents from the submucosal layer and mimics submucosal tumors (SMTs). This variant of gastric adenocarcinoma is not only rare, but it is also frequently misdiagnosed as other conditions such as gastrointestinal stromal tumors, lymphoma, or sarcoma. This case report describes a unique case of early gastric adenocarcinoma that presented as a submucosal tumor without invasion into the muscularis propria or primary involvement from the gastric mucosa. Additionally, this raises an important clinical question of whether this variant of gastric adenocarcinoma behaves differently from mucosal-origin cancers in terms of invasion and metastasis. This case highlights the diagnostic challenges and the importance of early detection and accurate diagnosis of this rare presentation of gastric adenocarcinoma. This case also provides valuable insights into the clinical variability of submucosal gastric adenocarcinomas and the need for further research to optimize its management and improve patient outcomes.

Clinical value of oral contrast-enhanced ultrasonography in diagnosis of gastric tumors.

BACKGROUND: The incidence of gastric cancer remains high, and it is the sixth most common cancer and the fourth leading cause of cancer deaths worldwide. Oral contrast-enhanced ultrasonography is a simple, non-invasive, and painless method for the diagnosis of gastric tumors. AIM: To explore the diagnostic value of oral contrast-enhanced ultrasonography for the detection of gastric tumors. METHODS: The screening results based on oral contrast-enhanced ultrasonography and electronic gastroscopy were compared with those of the postoperative pathological examination. RESULTS: Among 42 patients with gastric tumors enrolled in the study, the diagnostic accordance rate was 95.2% for oral contrast-enhanced ultrasonography (n = 40) and 90.5% for electronic gastroscopy (n = 38) compared with postoperative pathological examination. The Kappa value of consistency test with pathological findings was 0.812 for oral contrast-enhanced ultrasonography and 0.718 for electronic gastroscopy, and there was no significant difference between them (P = 0.397). For the TNM staging of gastric tumors, the accuracy rate of oral contrast-enhanced ultrasonography was 81.9% for the overall T staging and 50%, 77.8%, 100%, and 100% for T1, T2, T3, and T4 staging, respectively. The sensitivity and specificity were both 100% for stages T3 and T4. The diagnostic accuracy rate of oral contrast-enhanced ultrasonography was 93.8%, 80%, 100%, and 100% for stages N0, N1-N3, M0, and M1, respectively. CONCLUSION: The accordance rate of qualitative diagnosis by oral contrast-enhanced ultrasonography is comparable to that of gastroscopy, and it could be used as the preferred method for the early screening of gastric tumors.

Prevalence of Gastric Epithelial Tumors in Helicobacter pylori-uninfected Individuals Undergoing a Medical Checkup.

Objective This study investigated the prevalence of gastric epithelial tumor in Helicobacter pylori-uninfected subjects who underwent esophagogastroduodenoscopy (EGD) as part of an annual checkup. Methods A total of 20,540 EGD examinations of H. pylori-uninfected individuals (12,917 men, 7,623 women; mean age 51.5±9.2 years old) were performed between April 2016 and March 2023. The prevalence of gastric epithelial tumor discovery and the size and location of each lesion type were analyzed. Results According to 20,540 examinations, 61 gastric epithelial tumors were endoscopically and histologically diagnosed in 58 of the subjects, with a prevalence rate of 0.28%. These tumors included signet-ring carcinoma (n=10, 0.05%), gastric adenocarcinoma of fundic-gland type (n=10, 0.05%), intestinal-type well-differentiated adenocarcinoma (n=2, 0.01%), and raspberry-type gastric foveolar tumors (n=36, 0.18%). One subject had two intestinal-type well-differentiated adenocarcinomas, and two each had two raspberry-type gastric foveolar tumors. The mean sizes of the signet-ring carcinomas, gastric adenocarcinoma of fundic-gland type, intestinal-type well-differentiated adenocarcinomas, and raspberry-type gastric foveolar tumors were 6.4, 4.7, 5.0, and 3.4 mm, respectively. Each lesion was located at a specific site in the stomach characteristic of its type. Conclusion In the present H. pylori-uninfected subjects, the prevalence of gastric epithelial tumors found on an EGD examination was 0.28%. Endoscopic examination should be performed in H. pylori-uninfected individuals to detect such tumors in characteristic locations.

SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images.

Gastric cancer is a significant contributor to cancer-related fatalities globally. The automated segmentation of gastric tumors has the potential to analyze the medical condition of patients and enhance the likelihood of surgical treatment success. However, the development of an automatic solution is challenged by the heterogeneous intensity distribution of gastric tumors in computed tomography (CT) images, the low-intensity contrast between organs, and the high variability in the stomach shapes and gastric tumors in different patients. To address these challenges, we propose a self-attention backward network (SaB-Net) for gastric tumor segmentation (GTS) in CT images by introducing a self-attention backward layer (SaB-Layer) to feed the self-attention information learned at the deep layer back to the shallow layers. The SaB-Layer efficiently extracts tumor information from CT images and integrates the information into the network, thereby enhancing the network's tumor segmentation ability. We employed datasets from two centers, one for model training and testing and the other for external validation. The model achieved dice scores of 0.8456 on the test set and 0.8068 on the external verification set. Moreover, we validated the model's transfer learning ability on a publicly available liver cancer dataset, achieving results comparable to state-of-the-art liver cancer segmentation models recently developed. SaB-Net has strong potential for assisting in the clinical diagnosis of and therapy for gastric cancer. Our implementation is available at https://github.com/TyrionJ/SaB-Net.

Oncological Adequacy of Laparoscopic Surgery for Bulky Gastric Cancer: Results of a Western Single-Center Series.

BACKGROUND: Gastric cancer is increasing worldwide and one million new cases were estimated globally in 2020. Use of the laparoscopic approach is increasing especially for subtotal gastrectomy. However, to date, solid data on locally advanced bulky tumors are lacking. The aim of this study is to assess the role of laparoscopic surgery in bulky gastric tumors. METHODS: We performed an observational retrospective single-center analysis. The following data were collected and analyzed for each patient: demographics, tumor-related data, intra-operative data, peri-operative data, and pathological data. Statistical analysis was conducted, including descriptive statistics and chi-squared test, to analyze the differences between categorical variables. RESULTS: O the 116 patients who underwent gastric surgery, 49 patients were included in the study protocol. All patients had bulky gastric tumors. Eighteen patients underwent laparoscopic gastrectomy and 31 open gastrectomy. The median number of lymph nodes removed was 28.5 (15-46) in the laparoscopic group and 23.05 (6-62) in the open group (p = 0.04). In total, 5.6% of patients of the laparoscopic group had <16 lymph nodes harvested and 35.5% in the open group (p = 0.035). No statistical differences were found between the open and laparoscopic groups in terms of surgical margins (p = 0.69). CONCLUSIONS: Laparoscopic surgery is still a subject of debate in locally advanced bulky gastric cancer. Limited data are available concerning Western patients. This study showed superiority in terms of the quality of lymphadenectomy and non-inferiority in terms of radical resection margins.

Using machine learning to identify patients at high risk of developing low bone density or osteoporosis after gastrectomy: a 10-year multicenter retrospective analysis.

INTRODUCTION: Osteoporosis that emerges subsequent to gastrectomy poses a significant threat to the long-term health of patients. The primary objective of this investigation was to formulate a machine learning algorithm capable of identifying substantial preoperative, intraoperative, and postoperative risk factors. This algorithm, in turn, would enable the anticipation of osteoporosis occurrence after gastrectomy. METHODS: This research encompassed a cohort of 1125 patients diagnosed with gastric cancer, including 108 individuals with low bone density or osteoporosis. A total of 40 distinct variables were collected, comprising patient demographics, pertinent medical history, medication records, preoperative examination attributes, surgical procedure specifics, and intraoperative details. Four distinct machine learning algorithms-extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and k-nearest neighbor algorithm (KNN)-were employed to establish the predictive model. Evaluation of the models involved receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Shapley additive explanation (SHAP) was employed for visualization and analysis. RESULTS: Among the four prediction models employed, the XGBoost algorithm demonstrated exceptional performance. The ROC analysis yielded excellent predictive accuracy, showcasing area under the curve (AUC) values of 0.957 and 0.896 for training and validation sets, respectively. The calibration curve further confirmed the robust predictive capacity of the XGBoost model. The DCA demonstrated a notably higher benefit rate for patients undergoing intervention based on the XGBoost model. Moreover, the AUC value of 0.73 for the external validation set indicated favorable extrapolation of the XGBoost prediction model. SHAP analysis outcomes unveiled numerous high-risk factors for osteoporosis development after gastrectomy, including a history of chronic obstructive pulmonary disease (COPD), inflammatory bowel disease (IBD), hypoproteinemia, postoperative neutrophil-to-lymphocyte ratio (NLR) exceeding 3, steroid usage history, advanced age, and absence of calcitonin use. CONCLUSION: The osteoporosis prediction model derived through the XGBoost machine learning algorithm in this study displays remarkable predictive precision and carries significant clinical applicability.

A Rare but Aggressive Malignancy: A Case Report of a Gastrointestinal Neuroectodermal Tumor (GNET).

Gastrointestinal neuroectodermal tumors (GNETs) are extremely rare and intriguing malignancies originating from neural crest cells in the digestive tract. The digestive tract's neural crest cells can give rise to incredibly unusual and interesting gastrointestinal neuroectodermal tumors (GNETs). GNETs present considerable hurdles in diagnosis and management because of their rarity and varied expression. In this case report, a 45-year-old male patient is described who had signs of GNET, such as exhaustion, weight loss, and abdominal pain. A 7-cm jejunum tumor and related thickening of the gut wall were discovered using imaging investigations. The diagnosis of malignant GNET was confirmed by surgical resection, and adjuvant treatment was given. A recurring tumor required a second surgical procedure despite an initial disease-free period. The report emphasizes the difficulties involved in the diagnosis, treatment, and long-term effects of GNETs. The rarity of GNETs necessitates the development of standardized treatment protocols as well as additional research to enhance diagnostic precision and explore novel therapeutic approaches for this aggressive malignancy.

Identification of high-risk factors associated with mortality at 1-, 3-, and 5-year intervals in gastric cancer patients undergoing radical surgery and immunotherapy: an 8-year multicenter retrospective analysis.

Background: Combining immunotherapy with surgical intervention is a prevailing and radical therapeutic strategy for individuals afflicted with gastric carcinoma; nonetheless, certain patients exhibit unfavorable prognoses even subsequent to this treatment regimen. This research endeavors to devise a machine learning algorithm to recognize risk factors with a high probability of inducing mortality among patients diagnosed with gastric cancer, both prior to and during their course of treatment. Methods: Within the purview of this investigation, a cohort of 1015 individuals with gastric cancer were incorporated, and 39 variables encompassing diverse features were recorded. To construct the models, we employed three distinct machine learning algorithms, specifically extreme gradient boosting (XGBoost), random forest (RF), and k-nearest neighbor algorithm (KNN). The models were subjected to internal validation through employment of the k-fold cross-validation technique, and subsequently, an external dataset was utilized to externally validate the models. Results: In comparison to other machine learning algorithms employed, the XGBoost algorithm demonstrated superior predictive capacity regarding the risk factors that affect mortality after combination therapy in gastric cancer patients for a duration of one year, three years, and five years posttreatment. The common risk factors that significantly impacted patient survival during the aforementioned time intervals were identified as advanced age, tumor invasion, tumor lymph node metastasis, tumor peripheral nerve invasion (PNI), multiple tumors, tumor size, carcinoembryonic antigen (CEA) level, carbohydrate antigen 125 (CA125) level, carbohydrate antigen 72-4 (CA72-4) level, and H. pylori infection. Conclusion: The XGBoost algorithm can assist clinicians in identifying pivotal prognostic factors that are of clinical significance and can contribute toward individualized patient monitoring and management.