Search Results (144)

Central nervous system (CNS) tumor with BCL6 corepressor gene BCOR/BCORL1 fusion is an extremely rare tumor entity, with fewer than 40 cases reported. These tumors are distinct from the WHO 2021-defined CNS tumor with BCOR internal tandem duplication. Even rarer are CNS tumors that match to the methylation class of CNS tumors with BCOR/BCORL1 fusion, but lack fusions and instead harbor truncating small nucleotide variants in BCOR. To our knowledge, only two other cases of this scenario have been previously reported. Due to their scarcity and morphological features that mimic oligodendrogliomas and ependymomas, the diagnosis of CNS tumor with BCOR/BCORL1 fusion can be challenging, and misdiagnoses are not uncommon. Histologic findings of Olig2 positivity with focal to absent GFAP warrant further evaluation for this tumor entity. Moreover, no standard of care therapy exists for these tumors, making treatment selection difficult. We present a case of a 37-year-old woman with a midline CNS tumor with BCOR/BCORL1 fusion, harboring a pathogenic BCOR c.626del (p.S209Cfs*7) (Exon 4) variant, who was successfully treated with definitive radiation therapy and adjuvant temozolomide. Notably, EMA showed focal strong dot-like perinuclear immunoreactivity, which has not been previously reported in these tumors. This case adds to the limited but growing body of evidence supporting the use of radiation and temozolomide in treating tumors matching the methylation class of CNS tumors with BCOR/BCORL1 fusion without a detectable fusion. Full article

Cancer metabolism is a hallmark of cancer. However, the impact of systemic metabolism and diet on tumour evolution is less understood. This study delves into the role of glucagon, as a component of the pancreatic microenvironment, in regulating features of pancreatic neuroendocrine tumour (pNET) cells and the metabolic remodelling occurring in the presence and absence of glucose. pNET cell lines (BON-1 and QGP-1) and the non-malignant pancreatic α-TC1 cell line were used as models. Results showed that pNET cells responded differently to glucose deprivation than α-TC1 cells. Specifically, pNET cells upregulated the GCGR in the absence of glucose, while α-TC1 cells did so in high-glucose conditions, allowing the glucagon-related pERK1/2 activation under these conditions in pNET cells. Glucagon enhanced cancerous features in pNET BON-1 cells under glucose-deprived and hyperglucagonemia-compatible concentrations. In the α-TC1 cell line, glucagon modulated cell features under high-glucose and physiological glucagon levels. NMR exometabolome analysis revealed differences in metabolic processes based on glucose availability and glucagon stimulation across cell lines, highlighting amino acid metabolism, glycolysis, and gluconeogenesis. The expression of metabolic genes was consistent with these findings. Interestingly, QGP-1 and α-TC1 cells produced glucose in no-glucose conditions, and glucagon upregulated glucose production in α-TC1 cells. This suggests that gluconeogenesis may be beneficial for some pNET subsets, pointing out novel metabolism-based strategies to manage pNETs, as well as a step forward in endocrinology and systemic metabolism. The association between GCGR expression and malignancy and a negative correlation between glucagon receptor (GCGR) and glucagon-like peptide-1 receptor (GLP-1R) expression was observed, indicating a biological role of glucagon in pNETs that deserves to be explored. Full article

Background: Poorly differentiated neuroendocrine tumors of the pancreas (pd-PNETs) are very rare tumors. Differentiating primary pd-PNET from neuroendocrine carcinomas, which metastasize to the pancreas, can be difficult. We will refer to any neuroendocrine carcinoma with pancreatic metastasis as secondary pd-PNETs. This study evaluates the differences in incidence, clinical picture, outcomes, and treatment between primary and secondary pd-PNETs. Methods: A comprehensive search of the pd-PNET database was performed to gather data on incidence, race, age, gender, clinical picture, and outcomes for primary and secondary pd-PNETs. The emphasis was on small-cell lung cancer (SCLC) and Merkel cell carcinoma (MCC) due to their associations with secondary pd-PNET. Additional data from the PubMed database were analyzed, and 12 case reports of primary pd-PNETs were added for clinical characteristic analysis. Results: Primary and secondary pd-PNETs exhibit highly similar profiles in terms of age, gender, race, and clinical features. However, treatment strategies are significantly different. Primary pd-PNETs are managed with tumor resection and platinum-based chemotherapy. Primary tumors usually have poor prognosis, with a median survival of 12 months. Treatment for secondary pd-PNETs varies based on the primary tumor. The treatment strategy for metastatic MCC was changed to immune checkpoint inhibitors (ICIs), and survival improved. Tarlatamab also recently showed a good response in the management of SCLC. These findings highlight the need for accurate and timely diagnosis to provide correct treatment. Conclusions: Patients with primary and secondary pd-PNETs exhibit similar clinical presentations and epidemiological characteristics. However, when a poorly differentiated neuroendocrine pancreatic mass is identified, it is critical to exclude MCC or small-cell lung carcinoma metastasis, as treatments may be different and prognosis may also be different. Full article

Background/Objectives: Pancreatic neoplasms, including adenocarcinoma, pancreatic neuroendocrine tumors (pNETs), intraductal papillary mucinous neoplasms (IPMNs), and high-grade cystic lesions, often require surgical resection as a form of curative treatment. However, comorbidities and high-risk features may preclude surgery. Endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) has emerged as a minimally invasive alternative with proven cytoreductive efficacy in solid tumors. This case series evaluates the safety and efficacy of EUS-RFA in patients with various unresectable, non-metastatic pancreatic neoplasms. Methods: A retrospective review was conducted on eight patients who underwent EUS-RFA at our institutions between July 2021 and February 2025. All patients were deemed unsuitable surgical candidates due to comorbidities such as advanced age, cardiovascular disease, renal insufficiency, and COPD or due to patient resistance to surgical intervention. EUS-RFA was performed using a 19-gauge RFA needle (Taewoong Corporation). Follow-up imaging was conducted 3 to 6 months after the completion of RFA treatment. Results: All eight patients demonstrated a good to excellent response in terms of tumor size reduction. The most notable response was observed in a patient with pNET, resulting in complete resolution from 15.6 × 12.0 mm to 0.0 × 0.0 mm after two RFA treatments. Other neoplasms, including pancreatic adenocarcinoma and intraductal papillary mucinous neoplasms (IPMNs), also demonstrated significant reductions. Mild post-procedure complications, including pancreatitis and abdominal pain, were noted in three cases. Conclusions: EUS-RFA is a promising alternative for managing unresectable pancreatic neoplasms in high-risk patients. Our findings support its use across various tumor types with favorable outcomes and minimal complications, reinforcing its role in expanding therapeutic options beyond surgery. Full article

Pancreatic neuroendocrine tumors (PNETs) are a rare subset of pancreatic neoplasms with diverse biological behavior and clinical presentations. Traditional treatment approaches, such as surgery and targeted therapies, have significantly improved outcomes. However, advancements in molecular biology, immunotherapy, and minimally invasive techniques have ushered in a new era of treatment possibilities. This manuscript explores the emerging modalities in PNET management, emphasizing the need for a multidisciplinary approach tailored to individual patient profiles. Full article

Background: Neuroendocrine neoplasms (NENs) represent a heterogeneous group of malignancies that consist of two major subtypes: neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs). Glucagon-like peptide-1 receptor agonists (GLP-1Ra) have demonstrated favorable results in preclinical studies, but their impact on NEN outcomes remains unexplored. Methods: Using the TriNetX US Research Network, we identified adult patients with NEN and either diabetes or obesity. After 1:1 propensity score matching based on demographics, comorbidities, procedures, and medication use, we compared survival outcomes between patients who received GLP-1Ra after NEN diagnosis and those who did not. Results: Among 32,464 eligible patients, 3139 received GLP-1Ra and 29,325 did not. After propensity matching, each cohort included 3043 patients with well-balanced baseline characteristics. During follow-up periods extending up to 15 years, all-cause mortality occurred in 356 (11.7%) GLP-1Ra users versus 753 (24.7%) non-users, representing a 13.0% absolute risk reduction (p < 0.001). GLP-1Ra use was associated with significantly improved survival (HR = 0.56, 95%CI = 0.49–0.63, p < 0.001). Both well-differentiated (HR = 0.52) and poorly differentiated tumors (HR = 0.56) showed significant improvement. Among primary sites, lung NENs demonstrated the most pronounced benefit (HR = 0.42). Tirzepatide showed the strongest association with reduced mortality (HR = 0.16), followed by semaglutide (HR = 0.27) and dulaglutide (HR = 0.52). Results: In this large propensity-matched study, GLP-1Ra use was associated with a 44.3% reduction in mortality risk among NEN patients with diabetes or obesity. The magnitude of the observed benefit suggests a potential role for GLP-1Ra as adjunctive therapy in this patient population. Prospective clinical trials are warranted to confirm these findings and explore underlying mechanisms. Full article

Background/Objective: Identifying patterns of diagnostic imaging workflow parallel to the influence of certain variables, such as pathology guidelines over time, provides valuable insight for clinical decision making. This study presents a recurring trend of initial imaging orders and follow-ups, up to the diagnosis of pancreatic neuroendocrine tumors (pNETs), across two decades, with scans which led to pathological investigation. Methods: Three readers evaluated common conventional imaging among initial and follow-up studies for lesion detection and localization. Inter-reader and intra-reader analyses were controlled as contributing factors to the imaging diagnostic trend. Results: Our results show that CT was the prominent initial scan in pNET workup, likely due to their wide availability, high spatial resolution, and rapid acquisition, with a sufficient detection rate throughout both decades, regardless of technical advances. However, MRI scans also gained soaring popularity, especially among syndromic patients, likely due to follow-up and anatomical surgery precision. Conclusions: Newer modalities may be eventually useful and only requested for pNETs staging and further treatment. Full article

Background/Objectives: Pancreatic cancer remains one of the most aggressive and lethal malignancies, with limited effective treatment options for advanced stages. Microwave Ablation (MWA) has emerged as a minimally invasive therapeutic modality, offering potential benefits in tumor control. This review aims to critically assess the safety and efficacy of MWA in the treatment of pancreatic cancer, focusing on its application in various pancreatic lesions. Methods: We systematically reviewed studies published between 2010 and 2023 that evaluated the use of MWA in pancreatic tumors, including locally advanced pancreatic cancer (LAPC), pancreatic neuroendocrine tumors (PNETs), and pancreatic metastases from renal cell carcinoma (RCC). Due to limited data on survival rates and long-term outcomes, our analysis concentrated primarily on the technical aspects and immediate procedural outcomes of MWA. Results: MWA was technically feasible in all cases. The overall complication rate was approximately 16.7% (nine patients), with higher incidences in tumors located in the pancreatic head. Reported complications included pancreatitis and pseudocyst formation. Procedural parameters varied, with applied energy ranging from 20 to 80 watts and ablation times between 2 to 15 min, depending on the microwave generator type and approach (percutaneous, intraoperative or endoscopic). All cases demonstrated effective necrosis of the target tissue, and several studies reported notable tumor size reductions, averaging up to 70%. Conclusions: MWA shows promise as a therapeutic option for pancreatic cancer, achieving high technical success rates and significant tumor reductions. However, the procedure is associated with a moderate complication rate, particularly in tumors located in the pancreatic head. Full article

Background: Pancreatic neuroendocrine neoplasms (PNENs) are rare but clinically significant tumors with variable radiological presentations that complicate diagnosis. While typical PNENs are well characterized, atypical features, such as cystic or hypoenhancing patterns, are less understood and can lead to diagnostic delays or misdiagnosis. This study aimed to evaluate atypical radiological presentations of PNENs, focusing on their impact on diagnostic pathways and differentiation from other pancreatic pathologies. Methods: A retrospective review was conducted of all PNEN cases diagnosed at a single tertiary center between 2010 and 2020. Cases with histopathological confirmation and available cross-sectional imaging were included. Radiological features were categorized as typical (solid and hyperenhancing) or atypical (cystic and hypoenhancing). Demographic, radiological, and pathological data were analyzed. Comparisons between typical and atypical PNENs were performed using descriptive and inferential statistics. Results: Among 77 PNEN cases, 39 met the inclusion criteria. Atypical radiological presentations were identified in 46% of cases, including cystic (18%) and hypoenhancing (28%) lesions. Hypoenhancing PNENs were significantly more likely to present with advanced disease (54% vs. 14% in typical PNENs, p = 0.016). In contrast, none of the cystic PNENs exhibited advanced disease. Atypical PNENs posed greater diagnostic challenges, with alternative diagnoses initially considered in 64% of hypoenhancing and 43% of cystic cases compared to 10% of typical PNENs (p = 0.0042). Conclusions: Atypical PNENs, particularly hypoenhancing lesions, present significant diagnostic challenges and are more likely to be associated with advanced disease. These findings highlight the need for improved recognition of atypical imaging patterns and more precise diagnostic strategies. However, the retrospective design and small cohort size limit the generalizability of our findings. Further multicenter studies are warranted to refine the imaging criteria and optimize the differentiation from other pancreatic neoplasms. Full article

Due to the complex anatomy of the pelvis, various tumors may arise in this region. Some of these tumors are well known and have distinctive features that allow them to be identified by magnetic resonance imaging (MRI). These include sacrococcygeal teratoma (SCT), the most prevalent congenital tumor in children, often diagnosed prenatally and most frequently occurring in this anatomical location, and ovarian teratoma, which in its mature form is the most common ovarian neoplasm in children and adolescents. Additionally, rhabdomyosarcoma (RMS), commonly found in the bladder in both genders and in the prostate in males, and Ewing sarcoma (ES), affecting the flat bones of the pelvis, are relatively common tumors. In this study, selected atypical pelvic tumors in children are presented. Most of them are tumors of the reproductive system, such as cervical cancer, small cell neuroendocrine carcinoma of the ovary, ES/primitive neuroectodermal tumor (PNET) of the ovary, diffuse large B-cell lymphoma (DLBCL) of the ovaries and ovarian Sertoli–Leydig cell tumor (SLCT) with RMS due to DICER1 syndrome. Additionally, tumors originating from the nervous system, including neuroblastoma (NBL) and plexiform neurofibroma (pNF), associated and not associated with neurofibromatosis type 1 (NF1), are discussed. Furthermore, Rosai–Dorfman disease involving the pelvic and inguinal lymph nodes is presented. By reviewing the literature and presenting our cases, we tried to find radiological features of individual tumors that would bring the radiologist closer to the correct diagnosis, ensuring the implementation of appropriate treatment. However, the MR images cannot be considered in isolation. Additional patient data, such as the clinical picture, comorbidities/syndromes, and laboratory test results, are necessary. Full article

Pancreatic neuroendocrine tumors (pNETs) are rare but increasingly prevalent malignancies with varied prognoses and a diverse range of treatment options, including surgery, somatostatin analogues (SSAs), chemotherapy, targeted therapy, and peptide receptor radionuclide therapy (PRRT). This retrospective cohort study analyzed treatment patterns among 189 pNET patients treated between January 2010 and June 2021 at two Canadian cancer centres: the Verspeeten Family Cancer Centre (VFCC), which offers PRRT, and the Ottawa Hospital Cancer Centre (TOHCC), which does not at the time of the study. Data on demographics, tumor characteristics, and treatment modalities were collected, and statistical analyses were conducted using chi-square, Fisher’s exact test, and the Kruskal–Wallis test. Among eligible patients, 53% presented with stage IV disease. Surgical resection was the most common treatment, followed by SSAs, chemotherapy, PRRT, and targeted therapy. Stage IV patients at VFCC were significantly more likely to receive PRRT (60%) compared to TOHCC (6%) and underwent more PRRT cycles, with a higher prevalence of well-differentiated tumors observed at VFCC. With these differences it was clear that the non-PRRT centre was unable to provide patients with the same level of PRRT access during the study period compared to patients seen at the PRRT site. The findings underscore the critical role of PRRT availability in influencing treatment patterns and highlight the need for equitable access to specialized therapies across Canada to optimize outcomes for pNET patients. Full article

Endoscopic ultrasound (EUS)-guided radiofrequency ablation (RFA) is a promising minimally invasive technique for the treatment of pancreatic lesions. This review first focuses on the technical aspects in EUS-RFA: the procedure typically employs EUS probes with integrated radiofrequency electrodes, enabling accurate targeting and ablation of pancreatic lesions. Different types of RFA devices, monopolar and bipolar energy delivery systems, are discussed, along with considerations for optimal ablation, including energy settings, procedure time, and pre- and post-procedural management. This paper presents a comprehensive literature review of EUS-RFA applied to both solid and cystic pancreatic lesions, including functioning and non-functioning pancreatic neuroendocrine tumors (pNETs), pancreatic cystic lesions (PCLs), pancreatic ductal adenocarcinoma (PDAC), and pancreatic metastases (PMs), discussing current evidence on safety, efficacy, clinical outcomes, and adverse events (AEs). EUS-RFA is an emerging technique with expanding potential for the treatment of both benign and malignant conditions; however, further studies are needed to better define patient selection criteria, assess long-term benefits, and establish definitive indications for its use. Full article

Accurately obtaining both the number and the location of rice plants plays a critical role in agricultural applications, such as precision fertilization and yield prediction. With the rapid development of deep learning, numerous models for plant counting have been proposed. However, many of these models contain a large number of parameters, making them unsuitable for deployment in agricultural settings with limited computational resources. To address this challenge, we propose a novel pruning method, Cosine Norm Fusion (CNF), and a lightweight feature fusion technique, the Depth Attention Fusion Module (DAFM). Based on these innovations, we modify the existing P2PNet network to create P2P-CNF, a lightweight model for rice plant counting. The process begins with pruning the trained network using CNF, followed by the integration of our lightweight feature fusion module, DAFM. To validate the effectiveness of our method, we conducted experiments using rice datasets, including the RSC-UAV dataset, captured by UAV. The results demonstrate that our method achieves a MAE of 3.12 and an RMSE of 4.12 while utilizing only 33% of the original network parameters. We also evaluated our method on other plant counting datasets, and the results show that our method achieves a high counting accuracy while maintaining a lightweight architecture. Full article

In computer vision, recognizing plant pictures has emerged as a multidisciplinary area of interest. In the last several years, much research has been conducted to determine the type of plant in each image automatically. The challenges in identifying the medicinal plants are due to the changes in the effects of image light, stance, and orientation. Further, it is difficult to identify the medicinal plants due to factors like variations in leaf shape with age and changing leaf color in response to varying weather conditions. The proposed work uses machine learning techniques and deep neural networks to choose appropriate leaf features to determine if the leaf is a medicinal or non-medicinal plant. This study presents a neural network design based on PSR-LeafNet (PSR-LN). PSR-LeafNet is a single network that combines the P-Net, S-Net, and R-Net, all intended for leaf feature extraction using the minimum redundancy maximum relevance (MRMR) approach. The PSR-LN helps obtain the shape features, color features, venation of the leaf, and textural features. A support vector machine (SVM) is applied to the output achieved from the PSR network, which helps classify the name of the plant. The model design is named PSR-LN-SVM. The advantage of the designed model is that it suits more considerable dataset processing and provides better results than traditional neural network models. The methodology utilized in the work achieves an accuracy of 97.12% for the MalayaKew dataset, 98.10% for the IMP dataset, and 95.88% for the Flavia dataset. The proposed models surpass all the existing models, having an improvement in accuracy. These outcomes demonstrate that the suggested method is successful in accurately recognizing the leaves of medicinal plants, paving the way for more advanced uses in plant taxonomy and medicine. Full article

The number of rice seedlings and their spatial distribution are the main agronomic components for determining rice yield. However, the above agronomic information is manually obtained through visual inspection, which is not only labor-intensive and time-consuming but also low in accuracy. To address these issues, this paper proposes RS-P2PNet, which automatically counts and locates rice seedlings through point supervision. Specifically, RS-P2PNet first adopts Resnet as its backbone and introduces mixed local channel attention (MLCA) in each stage. This allows the model to pay attention to the task-related feature in the spatial and channel dimensions and avoid interference from the background. In addition, a multi-scale feature fusion module (MSFF) is proposed by adding different levels of features from the backbone. It combines the shallow details and high-order semantic information of rice seedlings, which can improve the positioning accuracy of the model. Finally, two rice seedling datasets, UERD15 and UERD25, with different resolutions, are constructed to verify the performance of RS-P2PNet. The experimental results show that the MAE values of RS-P2PNet reach 1.60 and 2.43 in the counting task, and compared to P2PNet, they are reduced by 30.43% and 9.32%, respectively. In the localization task, the Recall rates of RS-P2PNet reach 97.50% and 96.67%, exceeding those of P2PNet by 1.55% and 1.17%, respectively. Therefore, RS-P2PNet has effectively accomplished the counting and localization of rice seedlings. In addition, the MAE and RMSE of RS-P2PNet on the public dataset DRPD reach 1.7 and 2.2, respectively, demonstrating good generalization. Full article