Features Of Polyps Research Articles

Development and External Validation of a Prediction Model for Colorectal Cancer Among Patients Awaiting Surveillance Colonoscopy Following Polypectomy

Demand for surveillance colonoscopy can sometimes exceed capacity, such as during and following the coronavirus disease 2019 pandemic, yet no tools exist to prioritize the patients most likely to be diagnosed with colorectal cancer (CRC) among those awaiting surveillance colonoscopy. We developed a multivariable prediction model for CRC at surveillance comparing performance to a model that assigned patients as low or high risk based solely on polyp characteristics (guideline-based model). Logistic regression was used for model development among patients receiving surveillance colonoscopy in 2014-2019. Candidate predictors included index colonoscopy indication, findings, and endoscopist adenoma detection rate, and patient and clinical characteristics at surveillance. Patients were randomly divided into model development (n= 36,994) and internal validation cohorts (n= 15,854). External validation was performed on 30,015 patients receiving surveillance colonoscopy in 2020-2022, and the multivariable model was then updated and retested. One hundred fourteen, 43, and 71 CRCs were detected at surveillance in the 3 cohorts, respectively. Polyp size ≥10 mm, adenoma detection rate <32.5% or missing, patient age, and ever smoked tobacco were significant CRC predictors; this multivariable model outperformed the guideline-based model (internal validation cohort area under the receiver-operating characteristic curve: 0.73, 95% confidence interval (CI): 0.66-0.81 vs 0.52, 95% CI: 0.45-0.60). Performance declined at external validation but recovered with model updating (operating characteristic curve: 0.72 95% CI: 0.66-0.77). When surveillance colonoscopy demand exceeds capacity, a prediction model featuring common clinical predictors may help prioritize patients at highest risk for CRC among those awaiting surveillance. Also, regular model updates can address model performance drift.

A Clinical-morphological Study of Colorectal Polyps with Emphasis on Serrated Lesions

Abstract Background: The World Health Organization introduced the entities of sessile serrated adenoma and traditional serrated adenoma, and hyperplastic polyps (HPs) under the serrated lesions category in 2010. Indian studies on demographic, clinical, and histopathological characteristics of colorectal polyps, especially on serrated lesions, are limited. Our study aimed to study the morphology of the colorectal polyps and estimate the percentage of serrated lesions in the polyps studied. Methodology: A cross-sectional hospital-based study was conducted on colorectal polyps received for routine histopathological examination from July 2013 to August 2015. The polyps were classified according to the WHO 2010 colon and rectum tumors classification. Data were compiled and analyzed using IBM SPSS statistics version 20.0. The interpretation was done in frequencies and percentages. Results: We studied a total of 200 colorectal polyps. The polyps were mostly seen in the descending colon (41%). Histologically, the majority of the colorectal polyps were adenomatous in nature (59%). The serrated lesions accounted for 29% of all colorectal polyps. The polyps were mostly seen in patients who were more than 40 years old. Conclusion: Adenomas were the most prevalent type of colorectal polyps, seen more in males, at a higher age, and distally located. Serrated lesions predominantly included HPs, mostly &lt;1 cm in size.

Single-cell landscape of the cellular microenvironment in three different colonic polyp subtypes in children.

The understanding of the heterogeneous cellular microenvironment of colonic polyps in paediatric patients with solitary juvenile polyps (SJPs), polyposis syndrome (PJS) and Peutz-Jeghers syndrome (PJS) remains limited. We conducted single-cell RNA sequencing and multiplexed immunohistochemistry (mIHC) analyses on both normal colonic tissue and different types of colonic polyps obtained from paediatric patients. We identified both shared and disease-specific cell subsets and expression patterns that played important roles in shaping the unique cellular microenvironments observed in each polyp subtype. As such, increased myeloid, endothelial and epithelial cells were the most prominent features of SJP, JPS and PJS polyps, respectively. Noticeably, memory B cells were increased, and a cluster of epithelial-mesenchymal transition (EMT)-like colonocytes existed across all polyp subtypes. Abundant neutrophil infiltration was observed in SJP polyps, while CX3CR1hi CD8+ T cells and regulatory T cells (Tregs) were predominant in SJP and JPS polyps, while GZMAhi natural killer T cells were predominant in PJS polyps. Compared with normal colonic tissues, myeloid cells exhibited specific induction of genes involved in chemotaxis and interferon-related pathways in SJP polyps, whereas fibroblasts in JPS polyps had upregulation of myofiber-associated genes and epithelial cells in PJS polyps exhibited induction of a series of nutrient absorption-related genes. In addition, the TNF-α response was uniformly upregulated in most cell subsets across all polyp subtypes, while endothelial cells and fibroblasts separately showed upregulated cell adhesion and EMT signalling in SJP and JPS polyps. Cell-cell interaction network analysis showed markedly enhanced intercellular communication, such as TNF, VEGF, CXCL and collagen signalling networks, among most cell subsets in polyps, especially SJP and JPS polyps. These findings strengthen our understanding of the heterogeneous cellular microenvironment of polyp subtypes and identify potential therapeutic approaches to reduce the recurrence of polyps in children.

Effectiveness and safety of thin vs. thick cold snare polypectomy of small colorectal polyps: Systematic review and meta-analysis.

Background and study aims Cold-snare polypectomy (CSP) is considered the standard of care for resection of colorectal polyps ≤10 mm. Data on the efficacy of CSP performed with thin-wire snares compared0 with thick-wire snares are conflicting. We performed a meta-analysis comparing complete resection (CR) and adverse event rates of CSP using thin-wire and thick-wire snares. Patients and methods Comparative studies of adult patients with ≧1 colorectal polyp(s) ≦10 mm who underwent CSP with thin-wire or thick-wire snares were included. We collected data on study, patient, polyp, and snare characteristics. The primary outcome was CR rate. Secondary outcomes were polyp retrieval rate, intraprocedural bleeding, delayed post-polypectomy bleeding, deep mural injury or perforation, patient discomfort, total sedation, and procedure time. We used random-effects models to calculate risk ratios for outcomes. We performed risk of bias assessments, rated the certainty of evidence, and assessed publication bias for all studies. Results We included four randomized controlled trials (RCTs) and two observational studies including 1316 patients with 1679 polyps (826 thin-wire CSPs and 853 thick-wire CSPs). There was no significant difference between thin-wire CSP (92.1%) and thick-wire CSP (87.7%) for RCTs (risk ratio [RR] 1.05, 95% confidence interval [CI] 0.94-1.16) or observational studies (78.1% versus 79.6%, RR 1.03, 95% CI 0.99-1.08). There were no significant differences in polyp retrieval rate or intraprocedural bleeding. There were no cases of delayed bleeding or perforation. Conclusions We found no differences in CR rates for CSP between thin-wire and thick-wire snares. CSP, regardless of snare type, is safe and effective for resection of small colorectal polyps.

PSTNet: Enhanced Polyp Segmentation With Multi-Scale Alignment and Frequency Domain Integration.

Accurate segmentation of colorectal polyps in colonoscopy images is crucial for effective diagnosis and management of colorectal cancer (CRC). However, current deep learning-based methods primarily rely on fusing RGB information across multiple scales, leading to limitations in accurately identifying polyps due to restricted RGB domain information and challenges in feature misalignment during multi-scale aggregation. To address these limitations, we propose the Polyp Segmentation Network with Shunted Transformer (PSTNet), a novel approach that integrates both RGB and frequency domain cues present in the images. PSTNet comprises three key modules: the Frequency Characterization Attention Module (FCAM) for extracting frequency cues and capturing polyp characteristics, the Feature Supplementary Alignment Module (FSAM) for aligning semantic information and reducing misalignment noise, and the Cross Perception localization Module (CPM) for synergizing frequency cues with high-level semantics to achieve efficient polyp segmentation. Extensive experiments on challenging datasets demonstrate PSTNet's significant improvement in polyp segmentation accuracy across various metrics, consistently outperforming state-of-the-art methods. The integration of frequency domain cues and the novel architectural design of PSTNet contribute to advancing computer-assisted polyp segmentation, facilitating more accurate diagnosis and management of CRC.

Systematic Evaluation of Clinical, Nutritional, and Fecal Microbial Factors for Their Association With Colorectal Polyps.

The identification of risk factors for precursor lesions of colorectal cancer (CRC) holds great promise in the context of prevention. With this study, we aimed to identify patient characteristics associated with colorectal polyps (CPs) and polyp features of potential malignant progression. Furthermore, a potential association with gut microbiota in this context was investigated. In this single-center study, a total of 162 patients with CPs and 91 control patients were included. Multiple variables including information on lifestyle, diet, serum parameters, and gut microbiota, analyzed by 16S-rRNA gene amplicon sequencing and functional imputations (Picrust2), were related to different aspects of CPs. We observed that elevated serum alkaline phosphatase (AP) levels were significantly associated with the presence of high-grade dysplastic polyps. This association was further seen for patients with CRC. Thereby, AP correlated with other parameters of liver function. We did not observe significant changes in the gut microbiota between patients with CP and their respective controls. However, a trend toward a lower alpha-diversity was seen in patients with CRC. Interestingly, AP was identified as a possible clinical effect modifier of stool sample beta diversity. We show for the first time an increased AP in premalignant CP. Furthermore, AP showed a significant influence on the microbial composition of the intestine. Relatively elevated liver enzymes, especially AP, may contribute to the detection of precancerous dysplastic or neoplastic changes in colorectal lesions. The association between elevated AP, premalignant CP, and the microbiome merits further study.

Endoscopic and histopathological characteristics of polyp and colorectal cancer in people with a family history of colorectal cancer

Background: According to Globocan statistics in 2018, there were estimated 1.8 million cases of colorectal cancer and 881,000 deaths. The rate of colorectal cancer is tending to increase in people under 50 years old. According to the 2017 American Society for Gastrointestinal Endoscopy guidelines, Colonoscopy every 5 years beginning 10 years before the age at diagnosis of the youngest affect interval or age 40, whichever is earlier; for those with a single first-degree relative with colorectal cancer in whom no significant neoplasia appears by age 60 years, physicians can offer expanding the interval between colonoscopies. Objectives: (1) T o describe clinical features, endoscopic images, histopathology of polyps and colorectal cancer of first-degree relatives with colorectal cancer. (2) To determine the relationship between risk polyps and colorectal cancer with some factors. Materials and method: Cross-sectional study analyzing all first-degree relatives aged ≥ 40 years or approximately 10 years younger than the age of the patient diagnosed with colorectal cancer undergoing colonoscopy at the Functional Examination Department, Gia Dinh People’s Hospital during the period from June 2019 to December 2019. Results: In 85 cases: The main features of endoscopy were: rectal polyps 47.3%, sizes &lt; 5 mm 63.9%, multiple polyps 52.7%, sessile 91.7% and smooth surface 88.9%. Regarding histopathological characteristics: the proportion of adenomatous polyps and serrated polyps is nearly equal. Mild dysplasia accounts for the highest rate of 84.2%, high dysplasia accounting for 15.8%. There was 1 case of colorectal cancer, in the sigmoid colon, an ulcerative cancer. Factor related to colorectal polyps and colorectal cancer is age, other factors (gender, smoking, alcohol and abesity) didn’t relate. Conclusion: Our result shows that the majority of polyps are located in the rectum, adenomatous polyps and serrated polyps account for nearly equal proportions, there is a relationship between colon polyps and age, there is no relationship between colon polyps. with gender, smoking, alcohol and obesity. Key words: Colonoscopy, colorectal cancer, first-degree relative, polyp.

Attention combined pyramid vision transformer for polyp segmentation

Colorectal cancer (CRC) has become one of the most frequent cancers in the world. To prevent CRC, proper polyp localization in endoscopy images plays a vital role for detecting and removing colorectal polyps. Most polyp segmentation methods use convolutional neural networks (CNN) as their backbone, and have achieved promising results to effectively assist clinicians in their diagnosis. However, those CNN-based approaches have limitations in modeling accurate location and shape of polyps, due to the intrinsic locality property of convolutional operations. To address these limitations, this study proposes a novel network, namely Att-PVT, that combines CNN and Pyramid Vision Transformer (PVT) together for poly segmentation. The main challenge lies in maintaining long-range semantic information without sacrificing low-level features. Att-PVT applies multidimensional information extraction (MIE) to generate refined feature maps extracted from PVT for better feature representation. Cascaded context integration (CCI) is designed to adaptively aggregating the three highest layers of refined polyp features for learning semantic and location information. To accurately segment colorectal polyps, Att-PVT introduces multilevel feature fusion (MFF) module that explores the boundary information in the shallower layer based on the global map. The proposed workflow has undergone comparative experiments on three public datasets, namely Kvasir, ColonDB, and ETIS. The results show that the proposed approach achieves impressive mDice scores of 0.926, 0.817, and 0.794 for polyp segmentation tasks on these datasets, surpassing other state-of-the-art methods. This indicates the superior generalization and scalability of the proposed approach.

Dual-branch multi-information aggregation network with transformer and convolution for polyp segmentation

Computer-Aided Diagnosis (CAD) for polyp detection offers one of the most notable showcases. By using deep learning technologies, the accuracy of polyp segmentation is surpassing human experts. In such CAD process, a critical step is concerned with segmenting colorectal polyps from colonoscopy images. Despite remarkable successes attained by recent deep learning related works, much improvement is still anticipated to tackle challenging cases. For instance, the effects of motion blur and light reflection can introduce significant noise into the image. The same type of polyps has a diversity of size, color and texture. To address such challenges, this paper proposes a novel dual-branch multi-information aggregation network (DBMIA-Net) for polyp segmentation, which is able to accurately and reliably segment a variety of colorectal polyps with efficiency. Specifically, a dual-branch encoder with transformer and convolutional neural networks (CNN) is employed to extract polyp features, and two multi-information aggregation modules are applied in the decoder to fuse multi-scale features adaptively. Two multi-information aggregation modules include global information aggregation (GIA) module and edge information aggregation (EIA) module. In addition, to enhance the representation learning capability of the potential channel feature association, this paper also proposes a novel adaptive channel graph convolution (ACGC). To validate the effectiveness and advantages of the proposed network, we compare it with several state-of-the-art (SOTA) methods on five public datasets. Experimental results consistently demonstrate that the proposed DBMIA-Net obtains significantly superior segmentation performance across six popularly used evaluation matrices. Especially, we achieve 94.12% mean Dice on CVC-ClinicDB dataset which is 4.22% improvement compared to the previous state-of-the-art method PraNet. Compared with SOTA algorithms, DBMIA-Net has a better fitting ability and stronger generalization ability.

CSwinDoubleU-Net: A double U-shaped network combined with convolution and Swin Transformer for colorectal polyp segmentation

The early detection of polyps from colonoscopy can reduce the risk of colorectal cancer development and give timely treatment. Accurate polyp segmentation during colonoscopy examinations can help clinicians locate the polyps which is of great significance in the clinical prevention of colorectal cancer. However, due to large variations in terms of size, color, texture, and morphology of polyps, the similarity between the polyp lesions and their background, the variations of illumination, motion blur, low-contrast areas, intestinal contents during image acquisitions, precisely polyp segmentation is still an open issue. To overcome the challenges above, a new double U-shaped image segmentation network combining convolution structure and Shifted Windows (Swin) Transformer, namely CSwinDoubleU-Net, is proposed in this paper. The developed CSwinDoubleU-Net consists of two U-shaped encode-decode structures associated with a pure CNN-based structure and a pure Transformer-based one, and a feature fusion module that interacts with the two U-shaped parts. The first U-shaped codecs network utilizes the multi-convolution layers to extract the local feature information and the coordinate attention module in each skip connection to effectively reduce the loss of spatial information and obtain the accurate position information of the encoded features. Next, the second U-shaped codecs network uses the Swin Transformer layers with the sliding window to extract global feature information further. At last, a convolutional feature and self-attention feature fusion module (CSFFM) is designed to deeply fuse the local convolutional features extracted from the first U-shape structure and the global self-Attention features extracted from the second U-shape structure. The obtained multi-category and multi-dimensional fused feature information can help to recover the boundary features of polyps. Extensive experiments are conducted to validate the proposed CSwinDoubleU-Net on five publicly available datasets, including CVC-ClinicDB, Kvasir, CVC-ColonDB, CVC-T, and ETIS-Larib. The results show that the proposed model can outperform some state-of-the-art methods and achieve high segmentation performance for polyp images.

Understanding colorectal polyps to prevent colorectal cancer

Background: Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide. Most CRCs arise through carcinogenesis pathways from precancerous lesions, such as adenoma and sessile serrated lesions (SSLs). Understanding the characteristics of such precancerous colorectal polyps and the carcinogenesis pathways helps to develop CRC preventive strategies via screening, colonoscopic polypectomy, and surveillance.Current Concepts: Benign colorectal tumors can be classified as conventional adenomatous and serrated polyps. Conventional adenoma is one of the most prevalent precancerous polyps detected on screening colonoscopy, but most are small. Small colorectal adenomas are less likely to contain advanced histology, such as villous features, high-grade dysplasia, or invasive cancer. A small adenoma may progress slowly over 10 years to become an invasive cancer via the chromosomal instability pathway. SSL is a recently established precancerous lesion and is estimated to account for approximately 15% of sporadic CRC. Most SSLs are not dysplastic and progress very slowly through the serrated carcinogenesis pathway. Conversely, SSL with dysplasia (SSLD) may progress more rapidly, as a mismatch repair gene product is defective. According to colonoscopy studies, SSLD comprises only 4% to 8% of SSLs, with a prevalence of 0.1% to 0.9%. Most precancerous lesions detected on colonoscopy progress slowly to CRC and are appropriate targets for colonoscopic polypectomy for the prevention of CRC.Discussion and Conclusion: Colorectal adenoma and SSL are representative precancerous lesions of CRC and most are slow progressing enough to be detected and removed via colonoscopy before CRC development.

Factors influencing age at onset of colorectal polyps and benefit-finding after polypectomy.

Screening, followed by colonoscopic polypectomy, has been widely performed in China. However, factors influencing age at onset of colorectal polyps and benefit-finding after polypectomy have been insufficiently studied or ignored. A total of 152 patients with colorectal polyps first detected in First Affiliated Hospital of Huzhou University from July to September 2022 were enrolled in this study. We selected 11 factors associated with the risk of colorectal polyps, including gender, body mass index, occupational stress, education level, income satisfaction, smoking, alcohol consumption, exercise frequency, diet, family history and polyp characteristics. Benefit-finding after polypectomy was obtained by follow-up for 142 of these patients. Multivariate linear regression analysis showed that being overweight (i.e., body mass index ≥25 kg/m2), higher education level, lower exercise frequency, and refrigerated food preference were associated with early-onset colorectal polyps. Patients with a preference for pickled food and age ≥50 years at first colorectal polyp detection had lower benefit findings after colonoscopic polypectomy. Colorectal polyps may develop earlier in people who are overweight, well-educated, exercise less, and prefer refrigerated food. In addition, patients who prefer pickled food and age at onset ≥50 years have lower benefit-finding requiring more attention in future colonoscopy follow-ups.

Epidemiological and Histological Characteristics of Polyps Detected with Positive Tests During Mass Screening in the Wilaya of Béjaia

Detection of polyps during screening colonoscopy has improved significantly in recent years. This results in an increase in the detection rate of adenomas thanks in particular to technological innovations ( chromoendoscopy with indigo carmine or electronic) and the training of gastroenterologists, which is inversely correlated with the occurrence of colorectal cancer. The main objective of our study is to describe the epidemiological profile and histological characteristics of polyps and adenomas detected during a mass screening operation for colorectal cancer in a healthy population in the wilaya of Bejaia. The total number of polyps found in our target population is 196 in 89 people. A person can have a minimum of 1 polyp and a maximum of 6 polyps, the average number of polyps per person is 2 polyps, 43% of the population participating in mass screening for colorectal cancer have at least one polyp and 28% have two polyps.

MCSF-Net: a multi-scale channel spatial fusion network for real-time polyp segmentation.

Colorectal cancer is a globally prevalent cancer type that necessitates prompt screening. Colonoscopy is the established diagnostic technique for identifying colorectal polyps. However, missed polyp rates remain a concern. Early detection of polyps, while still precancerous, is vital for minimizing cancer-related mortality and economic impact. In the clinical setting, precise segmentation of polyps from colonoscopy images can provide valuable diagnostic and surgical information. Recent advances in computer-aided diagnostic systems, specifically those based on deep learning techniques, have shown promise in improving the detection rates of missed polyps, and thereby assisting gastroenterologists in improving polyp identification. In the present investigation, we introduce MCSF-Net, a real-time automatic segmentation framework that utilizes a multi-scale channel space fusion network. The proposed architecture leverages a multi-scale fusion module in conjunction with spatial and channel attention mechanisms to effectively amalgamate high-dimensional multi-scale features. Additionally, a feature complementation module is employed to extract boundary cues from low-dimensional features, facilitating enhanced representation of low-level features while keeping computational complexity to a minimum. Furthermore, we incorporate shape blocks to facilitate better model supervision for precise identification of boundary features of polyps. Our extensive evaluation of the proposed MCSF-Net on five publicly available benchmark datasets reveals that it outperforms several existing state-of-the-art approaches with respect to different evaluation metrics. The proposed approach runs at an impressive ∼45 FPS, demonstrating notable advantages in terms of scalability and real-time segmentation.

Surgical management of broad-based sessile vocal cord polyps: Transnasal vocal fold polypectomy versus microlaryngoscopic surgery: Our experience in 159 cases.

In this study, we retrospectively reviewed and compared the treatment outcomes and complications of office transnasal vocal fold polypectomy (TVFP) with those of microplarygoscopic surgery (MLS) for different clinical and histopathological features of broad-based sessile vocal fold polyps. We retrospectively reviewed the records of 159 consecutive patients with broad-based sessile vocal fold polyps treated by TVFP or MLS. The differences in efficacy and complication between these two surgical techniques were compared according to the different types of vocal fold polyps. Satisfactory outcomes of both TVFP and MLS treatments were reported in patients with oedematous, gelatinous and vascular types of vocal fold polyps (p > .05). The efficacy of TVFP was slightly worse than MLS in fibrous polyps group (p < .05). The TVFP-treated patients did not exhibit obvious complications, whereas several MLS-treated patients had suffered different complications. The therapeutic effects of both TVFP and MLS on the treatment of broad-based sessile vocal cord polyps are related to their clinical characteristics and histological types. Satisfactory outcomes are achieved in oedematous, gelatinous, and vascular types of polyps after either surgical procedure. TVFP has fewer surgical complications than MLS which can be a preferred option for the treatment of broad-based sessile vocal cord polyps at outpatient setting. TVFP also can be an alternative surgery option for patients who could not tolerate general anaesthesia or laryngeal suspension. In contrast, MLS has proven to be a particularly advantageous treatment in patients who have fibrous type of polyps.

Development and validation of a risk prediction model for post-polypectomy colorectal cancer in the USA: a prospective cohort study

Effective risk stratification tools for post-polypectomy colorectal cancer (PPCRC) are lacking. We aimed to develop an effective risk stratification tool for the prediction of PPCRC in three large population-based cohorts and to validate the tool in a clinical cohort. Leveraging the integrated endoscopic, histopathologic and epidemiologic data in three U.S population-based cohorts of health professional (the Nurses' Health Study (NHS) I, II and Health Professionals Follow-up Study (HPFS)), we developed a risk score to predict incident PPCRC among 26,741 patients with a polypectomy between 1986 and 2017. We validated the PPCRC score in the Mass General Brigham (MGB) Colonoscopy Cohort (Boston, Massachusetts, U.S) of 76,603 patients with a polypectomy between 2007 and 2018. In all four cohorts, we collected detailed data on patients' demographics, endoscopic history, polyp features, and lifestyle factors at polypectomy. The outcome, incidence of PPCRC, was assessed by biennial follow-up questionnaires in the NHS/HPFS cohorts, and through linkage to the Massachusetts Cancer Registry in the MGB cohort. In all four cohorts, individuals who were diagnosed with CRC or died before baseline or within six months after baseline were excluded. We used Cox regression to calculate the hazard ratio (HR), 95% confidence interval (CI) and assessed the discrimination using C-statistics and reclassification using the Net Reclassification Improvement (NRI). During a median follow-up of 12.8 years (interquartile range (IQR): 9.3, 16.7) and 5.1 years (IQR: 2.7, 7.8) in the NHS/HPFS and MGB cohorts, we documented 220 and 241 PPCRC cases, respectively. We identified a PPCRC risk score based on 11 predictors. In the validation cohort, the PPCRC risk score showed a strong association with PPCRC risk (HR for high vs. low, 3.55, 95% CI, 2.59-4.88) and demonstrated a C-statistic (95% CI) of 0.75 (0.70-0.79), and was discriminatory even within the low- and high-risk polyp groups (C-statistic, 0.73 and 0.71, respectively) defined by the current colonoscopy surveillance recommendations, leading to a NRI of 45% (95% CI, 36-54%) for patients with PPCRC. We developed and validated a risk stratification model for PPCRC that may be useful to guide tailored colonoscopy surveillance. Further work is needed to determine the optimal surveillance interval and test the added value of other predictors of PPCRC beyond those included in the current study, along with implementation studies. USNational Institutes of Health, the American Cancer Society, the South-Eastern Norway Regional Health Authority, the Deutsche Forschungsgemeinschaft.

Colonoscopy Combined with Me-Nbi to Observe the Canceration Characteristics of Colon Polyps and the Correlation of RHOC Protein Expression.

The current study was carried out to analyze the characteristics of colon polyps canceration observed by colonoscopy combined with ME-NBI (Magnifying Endoscopy combined with Narrow-Band Imaging) and its correlation with RhoC (Ras homolog gene family, member C) protein expression. For this purpose, A total of 300 patients with colorectal polyps and cancerous lesions (192 colorectal polyps and 200 cancerous lesions) who were treated in the digestive endoscopy room of the hospital and underwent colonoscopy were selected, and they were divided into polyp group and malignant lesion according to the diagnosis results. groups, 150 cases in each group. There were 75 patients with non-adenomatous polyps and 75 patients with adenomatous polyps in the polyp group; 75 patients with high-grade neoplasia and cancerous changes in the malignant group. The microvascular structure and surface structure of the lesions were observed by colonoscopy, and the correlation between microvascular morphological characteristics and RhoC protein expression was analyzed. Results showed that the probability of positive RhoC protein expression in the polyp group was significantly lower than that in the malignant transformation group, and the difference was statistically significant (P<0.05). In the malignant transformation group, the positive rate of RhoC expression in mucosal and submucosal superficial infiltration of 150 patients with colon polyp carcinoma was lower than that in submucosal deep infiltration, and the difference was statistically significant (P<0.05). NICE (National Institute for Clinical Excellence) type 2 was diagnosed as colorectal superficial submucosal The sensitivity, specificity, and accuracy of colorectal submucosal invasion were 73.1%, 84.6%, and 83.2%, respectively; the sensitivity, specificity, and accuracy of NICE type 3 in diagnosing colorectal submucosal invasion were 74.6%, 96.8%, and 92.7%, respectively. . Type 2 and type 3 lesions with cancerous features in NICE classification were correlated with the expression of RhoC protein (P<0.05). In conclusion, NICE classification under colonoscopy combined with magnifying colonoscopy has a good effect on colorectal lesions. Differential diagnostic value, RhoC protein is highly expressed in colon cancer and is closely related to the occurrence of colon cancer and the depth of lesion invasion. With the progression of colorectal adenomas, the expression of RhoC protein in the lesions gradually increased.

ECTransNet: An Automatic Polyp Segmentation Network Based on Multi-scale Edge Complementary.

Colonoscopy is acknowledged as the foremost technique for detecting polyps and facilitating early screening and prevention of colorectal cancer. In clinical settings, the segmentation of polyps from colonoscopy images holds paramount importance as it furnishes critical diagnostic and surgical information. Nevertheless, the precise segmentation of colon polyp images is still a challenging task owing to the varied sizes and morphological features of colon polyps and the indistinct boundary between polyps and mucosa. In this study, we present a novel network architecture named ECTransNet to address the challenges in polyp segmentation. Specifically, we propose an edge complementary module that effectively fuses the differences between features with multiple resolutions. This enables the network to exchange features across different levels and results in a substantial improvement in the edge fineness of the polyp segmentation. Additionally, we utilize a feature aggregation decoder that leverages residual blocks to adaptively fuse high-order to low-order features. This strategy restores local edges in low-order features while preserving the spatial information of targets in high-order features, ultimately enhancing the segmentation accuracy. According to extensive experiments conducted on ECTransNet, the results demonstrate that this method outperforms most state-of-the-art approaches on five publicly available datasets. Specifically, our method achieved mDice scores of 0.901 and 0.923 on the Kvasir-SEG and CVC-ClinicDB datasets, respectively. On the Endoscene, CVC-ColonDB, and ETIS datasets, we obtained mDice scores of 0.907, 0.766, and 0.728, respectively.

MGF-net: Multi-channel group fusion enhancing boundary attention for polyp segmentation.

Colonic polyps are the most prevalent neoplastic lesions detected during colorectal cancer screening, and timely detection and excision of these precursor lesions is crucial for preventing multiple malignancies and reducing mortality rates. The pressing need for intelligent polyp detection has led to the development of a high-precision intelligent polyp segmentation network designed to improve polyp screening rates during colonoscopies. In this study, we employed ResNet50 as the backbone network and embedded a multi-channel grouping fusion encoding module in the third to fifth stages to extract high-level semantic features of polyps. Receptive field modules were utilized to capture multi-scale features, and grouping fusion modules were employed to capture salient features in different group channels, guiding the decoder to generate an initial global mapping with improved accuracy. To refine the segmentation of the initial global mapping, we introduced an enhanced boundary weight attention module that adaptively thresholds the initial global mapping using learnable parameters. A self-attention mechanism was then utilized to calculate the long-distance dependency relationship of the polyp boundary area, resulting in an output feature map with enhanced boundaries that effectively refines the boundary of the target area. We carried out contrast experiments of MGF-Net with mainstream polyp segmentation networks on five public datasets of ColonDB, CVC-ColonDB, CVC-612, Kvasir, and ETIS. The results demonstrate that the segmentation accuracy of MGF-Net is significantly improved on the datasets. Furthermore, a hypothesis test was conducted to assess the statistical significance of the computed results. Our proposed MGF-Net outperforms existing mainstream baseline networks and presents a promising solution to the pressing need for intelligent polyp detection. The proposed model is available at https://github.com/xiefanghhh/MGF-NET.

Polyps and Colorectal Cancer in Serrated Polyposis Syndrome: Contribution of the Classical Adenoma-Carcinoma and Serrated Neoplasia Pathways.

Patients with serrated polyposis syndrome (SPS) have an increased risk to develop colorectal cancer (CRC). Due to an abundance of serrated polyps, these CRCs are assumed to arise mainly through the serrated neoplasia pathway rather than through the classical adenoma-carcinoma pathway. We aimed to evaluate the pathogenetic routes of CRCs in patients with SPS. We collected endoscopy and pathology data on CRCs and polyps of patients with SPS under treatment in our center. Our primary end point was the proportion of BRAFV600E mutated CRCs, indicating serrated pathway CRCs (sCRCs). CRCs lacking BRAFV600E most likely inferred a classical adenoma-carcinoma origin (aCRCs). We assessed patient, polyp, and CRC characteristics and stratified for BRAFV600E mutation status. Thirty-five patients with SPS harbored a total of 43 CRCs. Twenty-one CRCs (48.8%) carried a BRAFV600E mutation, 10 of which lacked MLH1 staining and 17 (81%) were located in the proximal colon. Twenty-two CRCs (51.1%) did not carry a BRAFV600E mutation and were MLH1 proficient. Of these 22 putatively aCRCs, 17 (77.3%) were located distally and one-third (36.4%) harbored a pathogenic KRAS or NRAS mutation. In patients with BRAFwt -CRCs, a higher ratio of the median number of conventional adenomas versus serrated polyps was found (4 vs 13) than patients with BRAFV600E -CRCs (1 vs 14). Our study indicates that in patients with SPS, the ratio of sCRCs:aCRCs on average is 50:50. This elevated sCRC:aCRC ratio in patients with SPS, when compared with non-SPS patients, correlates well with the differences in the ratios of the numbers of sessile serrated lesions and conventional adenomas in patients with SPS and non-SPS patients, respectively.