Detection Of Colorectal Adenomas Research Articles

Texture and color enhancement imaging versus white light imaging for the detection of colorectal adenomas: a systematic review and meta-analysis

Background Texture and color enhancement imaging (TXI) is a novel optical technology designed to improve visibility during endoscopy by highlighting subtle differences in morphology and color. This systematic review and meta-analysis aimed to determine whether TXI, compared to conventional white light imaging (WLI), can improve important colonoscopy quality indicators, specifically the adenoma detection rate (ADR) and adenomas per colonoscopy (APC). Methods We searched PubMed, EMBASE, and the Cochrane Central for studies comparing TXI to WLI in patients undergoing colonoscopy for any indication. Risk ratios (RR) and mean differences (MD) were computed using a random-effects model. Results We included 1541 patients from 3 studies, of which 2 were randomized controlled trials (RCTs). TXI was used in 775 (50.3%) patients. The indications for colonoscopy varied, including positive fecal immunochemical test (FIT), surveillance, and diagnostic workup for abdominal symptoms. In the pooled data, TXI significantly increased both ADR (57,8% versus 43.6%; RR 1.32 [95% CI, 1.20–1.46]; p < 0.001; I2 = 0%) and APC (MD 0.50 [95% CI, 0.37–0.64]; p < 0.001; I2 = 0%), compared to WLI. Furthermore, TXI was more effective at detecting nonpolypoid/flat adenomas, proximal/right-sided adenomas, and adenomas ≥ 10 mm in size. Colonoscopies with TXI had shorter withdrawal times. Conclusions Our meta-analysis demonstrates that TXI significantly improves the detection of colorectal adenomas in patients undergoing colonoscopy for various indications. TXI has the potential to improve the overall quality of colonoscopy and contribute to colorectal cancer prevention.

Optimal visual gaze pattern of endoscopists for improving adenoma detection during colonoscopy (with video)

Background and aimsVisual gaze pattern (VGP) analysis quantifies endoscopists’ specific eye movements. VGP during colonoscopy may be associated with polyp detection. However, the optimal VGP to maximize detection performance remains unclear. This study evaluated the optimal endoscopic VGP that enabled the highest colorectal adenoma detection. MethodsThis randomized controlled trial was conducted between July and December 2023. We developed an eye-tracking and feedback (ETF) system that instructed endoscopists to correct their gaze toward the periphery of an endoscope screen with an audible alert. Patients who underwent colonoscopy were randomly assigned to four groups: three intervention groups in which the endoscopist’s gaze was instructed to a different level of the peripheral screen area using the ETF system (the periphery of 4×4, 5×5, and 6×6 divisions of the screen) and a control group in which the endoscopist did not receive instructions. The primary outcome was the number of adenomas detected per colonoscopy (APC). ResultsIn total, 189 patients were enrolled. APC and adenoma detection rate were significantly higher in the 6×6 group than in the control group (1.82±2.41 vs. 0.59±1.17, P=0.002; 68.9% vs. 30.8%, P=0.002). The APC and the number of screen divisions were positively correlated (R=0.985, P=0.0152). The rate at which the endoscopist gazed at the periphery of the screen was positively correlated with the number of divisions (R=0.964, P=0.0363). ConclusionsColorectal adenoma detection was improved by correcting the endoscopist’s gaze to the periphery of the screen, especially by dividing the screen into 6×6 segments.

A novel index combining fecal immunochemical test, DNA test, and age improves detection of advanced colorectal adenoma.

Although the fecal immunochemical test for hemoglobin (FIT) is a widely used screening test for colorectal cancer, it is not sensitive enough to detect advanced colorectal adenoma. To address this issue, we performed this study to investigate whether combining the FIT and fecal DNA testing of methylated somatostatin (SST) could improve diagnostic performance for advanced colorectal adenoma. We collected feces from 79 healthy subjects with negative results on colonoscopy, 43 patients with non-advanced colorectal adenoma, 117 patients with advanced colorectal adenoma, and 126 patients with colorectal cancer. After fecal DNA was incubated with methylation-sensitive restriction enzymes, SST methylation levels were measured by droplet digital PCR. Using logistic multivariate analysis, we established a prediction formula for detecting colorectal neoplasia and named it the FAMS (FIT, age, methylated SST) index. The diagnostic performance of a single use of FIT for advanced colorectal adenoma showed a sensitivity of 29.1% (34/117) and specificity of 89.3% (109/122). In contrast, the FAMS index showed a sensitivity of 56.4% (66/117) at a similar specificity point of 91.0% (111/122). Furthermore, even at the higher specificity point of 94.3% (115/122), the sensitivity was still higher than that of FIT, reaching 42.7% (50/117). As the FAMS index showed better diagnostic performance for advanced colorectal adenoma than a single use of FIT, the FAMS index could be a promising tool for detecting advanced colorectal adenoma.

Long-term impact of artificial intelligence on colorectal adenoma detection in high-risk colonoscopy.

Improved adenoma detection rate (ADR) has been demonstrated with artificial intelligence (AI)-assisted colonoscopy. However, data on the real-world application of AI and its effect on colorectal cancer (CRC) screening outcomes is limited. To analyze the long-term impact of AI on a diverse at-risk patient population undergoing diagnostic colonoscopy for positive CRC screening tests or symptoms. AI software (GI Genius, Medtronic) was implemented into the standard procedure protocol in November 2022. Data was collected on patient demographics, procedure indication, polyp size, location, and pathology. CRC screening outcomes were evaluated before and at different intervals after AI introduction with one year of follow-up. We evaluated 1008 colonoscopies (278 pre-AI, 255 early post-AI, 285 established post-AI, and 190 late post-AI). The ADR was 38.1% pre-AI, 42.0% early post-AI (P = 0.77), 40.0% established post-AI (P = 0.44), and 39.5% late post-AI (P = 0.77). There were no significant differences in polyp detection rate (PDR, baseline 59.7%), advanced ADR (baseline 16.2%), and non-neoplastic PDR (baseline 30.0%) before and after AI introduction. In patients with an increased pre-test probability of having an abnormal colonoscopy, the current generation of AI did not yield enhanced CRC screening metrics over high-quality colonoscopy. Although the potential of AI in colonoscopy is undisputed, current AI technology may not universally elevate screening metrics across all situations and patient populations. Future studies that analyze different AI systems across various patient populations are needed to determine the most effective role of AI in optimizing CRC screening in clinical practice.

Colorectal adenoma detection rate using texture and color enhancement imaging versus white light imaging with chromoendoscopy: a propensity score matching study.

Few studies have evaluated the adenoma detection rate (ADR) of colonoscopy with texture and color enhancement imaging (TXI), a novel image-enhancing technology. This study compares the detection of colorectal polyps using TXI to that using white light imaging (WLI). This single-center retrospective study used propensity-matched scoring based on the patients' baseline characteristics (age, sex, indication, bowel preparation, endoscopist, colonoscope type, and withdrawal time) to compare the results of patients who underwent chromoendoscopy using WLI or TXI at the Toyoshima Endoscopy Clinic. The differences in polyp detection rates and the mean number of detected polyps per colonoscopy were determined between the TXI and WLI groups. After propensity score matching, 1970 patients were enrolled into each imaging modality group. The mean patient age was 57.2±12.5years, and 44.5% of the cohort were men. The ADR was higher in the TXI group than in the WLI group (55.0% vs 49.4%, odds ratio: 1.25). High-risk ADR were more common in the TXI group than in the WLI group (17.6% vs 12.8%; OR: 1.45). The mean number of adenomas per colonoscopy (APC) was higher in the TXI group than in the WLI group (1.187 vs 0.943, OR: 1.12). APC with a flat morphology (1.093 vs 0.848, OR: 1.14) and APC of <6mm (0.992 vs 0.757, OR: 1.16) were higher in the TXI group than in the WLI group. Compared to WLI, TXI improved the ADR in patients who underwent chromoendoscopy based on actual clinical data.

Histopathological comparison of colorectal neoplasia or polyps development between young adults and older adults: Our experience of 735 consecutive cases and 1269 polyps.

In recent decades, there has been an increase in early-onset colorectal cancer, the need to screen individuals younger than 50 years of age, and the presence of histopathological differences remains unclear. The objective of this study was to explore the occurrence of polyps in both young adults and older individuals and to examine their potential correlation with colorectal cancer. In this retrospective study conducted between July 1, 2018, and October 5, 2022, in the Pathology Laboratory, we designed a study based on the histopathological features of colorectal polyps evaluated by an experienced gastrointestinal pathologist based on the WHO 2019 classification. We evaluated 735 consecutive patients who underwent colonoscopic polypectomy between July 2018 and October 2022. The prevalence of cases under the age of 50 was 13.9%, and adults over the age of 50 was 86.1%. A total of 1269 polyps were detected, 1215 (95.7%) were epithelial polyps and 145 (11.9%) were epithelial polyps under the age of 50. One hundred four conventional adenomas and four intramucosal carcinomas were detected in cases younger than 50 years. The patients in the low-risk adenoma group was 57%, and the rate of patients in the high-risk adenoma group was 14.9%. Overall, polyps were most common in the sigmoid colon and there was a statistically significant difference between detecting tubular adenomas in the sigmoid colon (P=0.04). Our current results confirm the detection of sporadic colorectal adenomas and advanced neoplasia in young adults.It is important to establish professional community guidelines for surveillance colonoscopy in these age groups.

Establishment and validation of an artificial intelligence-based model for real-time detection and classification of colorectal adenoma

Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time detection, we propose an improved adaptive lightweight ensemble model for real-time detection and classification of adenomas and other polyps. Firstly, we devised an adaptive lightweight network modification and effective training strategy to diminish the computational requirements for real-time detection. Secondly, by integrating the adaptive lightweight YOLOv4 with the single shot multibox detector network, we established the adaptive small object detection ensemble (ASODE) model, which enhances the precision of detecting target polyps without significantly increasing the model's memory footprint. We conducted simulated training using clinical colonoscopy images and videos to validate the method's performance, extracting features from 1148 polyps and employing a confidence threshold of 0.5 to filter out low-confidence sample predictions. Finally, compared to state-of-the-art models, our ASODE model demonstrated superior performance. In the test set, the sensitivity of images and videos reached 87.96% and 92.31%, respectively. Additionally, the ASODE model achieved an accuracy of 92.70% for adenoma detection with a false positive rate of 8.18%. Training results indicate the effectiveness of our method in classifying small polyps. Our model exhibits remarkable performance in real-time detection of colorectal adenomas, serving as a reliable tool for assisting endoscopists.

Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma.

Although colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality, current diagnostic tests for early-stage CRC and colorectal adenoma (CRA) are suboptimal. Therefore, there is an urgent need to explore less invasive screening procedures for CRC and CRA diagnosis. Untargeted gas chromatography-mass spectrometry (GC-MS) metabolic profiling approach was applied to identify candidate metabolites. We performed metabolomics profiling on plasma samples from 412 subjects including 200 CRC patients, 160 CRA patients and 52 normal controls (NC). Among these patients, 45 CRC patients, 152 CRA patients and 50 normal controls had their fecal samples tested simultaneously. Differential metabolites were screened in the adenoma-carcinoma sequence. Three diagnostic models were further developed to identify cancer group, cancer stage, and cancer microsatellite status using those significant metabolites. The three-metabolite-only classifiers used to distinguish the cancer group always keeps the area under the receiver operating characteristic curve (AUC) greater than 0.7. The AUC performance of the classifiers applied to discriminate CRC stage is generally greater than 0.8, and the classifiers used to distinguish microsatellite status of CRC is greater than 0.9. This finding highlights potential early-driver metabolites in CRA and early-stage CRC. We also find potential metabolic markers for discriminating the microsatellite state of CRC. Our study and diagnostic model have potential applications for non-invasive CRC and CRA detection.

Abstract 1061: Diagnostic application of a novel blood CDH17 immunoassay in the detection of colorectal adenoma

Abstract Background: Colorectal cancer (CRC) is the most prevalent gastrointestinal (GI) cancer and contribute significantly to global cancer deaths. The mechanism of CRC development is a complex multistage process from hyperplastic lesions to the formation of adenomas, followed by the progression into malignancy. Hence, early detection during hyperplastic and adenomatous stages warrants new screening tests for effective interception of malignancy progression. Cadherin-17 (CDH17) is a biomarker characterized by its overexpression in several GI cancers, but restricted expression in intestinal mucosal epithelium of normal tissues. We have developed a blood immunoassay using a panel of RUO grade antibodies that unveiled CDH17 as a potential marker with high detection sensitivity and specificity for detecting adenomas. Our immunoassay is useful in identifying high-risk individuals with adenomas that may develop into CRC, which can significantly improve the diagnostic efficiency of colonoscopy that is currently lacking. Methods: The study recruited 66 patients (54 adenoma and 12 hyperplasia) and 39 normal samples (no abnormality by colonoscopy). CDH17 level in plasma samples were measured using the CDH17 immunoassay. Results: The novel CDH17 diagnostic assay showed an operating dynamic range from 90ng to 123pg. We observed a progressive and significant increase in the circulating CDH17 level from normal samples to the hyperplasia group, followed by the adenoma group (mean: 1.66ng/mL, 3.20ng/mL, 4.93ng/mL, respectively P&amp;lt;0.0001). The assay performance by ROC curve demonstrated an AUC of &amp;gt;0.9, with a sensitivity of 85% and specificity of 86%. NPV and PPV were 84% and 87%, respectively. The assay outperforms two market available FIT-DNA tests at predicting adenomas (Table. 1). Conclusion: The novel CDH17 immunoassay is potentially a powerful tool for the detection of aberrant plasma CDH17 expression, improving the surveillance and the detection of high-risk individuals for CRC. CDH17 immunoassay outperforms market availalble FIT-DNA tests at detecting hyperplasia and adenoma FIT-DNA test 1 FIT-DNA test 2 CDH17 blood immunoassay Age 40-74 Age 50-84 Age 45-93 Sensitivity (%) Advanced adenoma 63.5 42.4 85.0 Non-advanced adenoma (i.e Hyperplasia) Unavailable 17.2 58.3 Specificity (%) Normal control (no abnormality by colonoscopy) 87.1 89.8 86.1 NPV (%) Advanced adenoma Unavailable Unavailable 83.8 Non-advanced adenoma (i.e Hyperplasia) Unavailable Unavailable 86.1 PPV (%) Advanced adenoma Unavailable Unavailable 87.2 Non-advanced adenoma (i.e Hyperplasia) Unavailable Unavailable 58.3 Citation Format: Ng Lui, Felix Hon, Stella Sun, Pauline Leung, David Ho, John Moon Luk, Dominic Chi-Chung Foo. Diagnostic application of a novel blood CDH17 immunoassay in the detection of colorectal adenoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1061.

Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions. This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups. A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01). Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.

Endoscopic Resection Techniques for Precancerous and Early Cancerous Lesions in the Rectum

Today, endoscopy plays a decisive role not only in the detection of colorectal adenomas and carcinomas, but also in the treatment of precancerous lesions, in particular flat adenomas and early carcinomas. In recent years, endoscopic submucosal dissection (ESD) has become increasingly important alongside classic polypectomy and mucosal resection after saline injection using a snare (EMR). Using ESD the lesion is marked, injected submucosally using viscous substances and the mucosa incised and tunneled with a transparent cap and a fine diathermy knife. Particularly in the case of widespread and high-risk lesions ESD enables a quasi-surgical "en bloc" resection almost regardless of size, with a histological R0 resection rate of far over 90% in specialized centers. ESD enables an excellent histopathological evaluation and has a low recurrence risk of 1-3%. Endoscopic full-thickness resection using a dedicated device (FTRD system) represents another addition to the armamentarium. It can be used for circumscribed submucosal, suspicious or scarred changes up to 2cm in the middle and upper rectum. Endoscopic intermuscular dissection (EID) enables histopathological analysis of the complete submucosa beyond the mucosa and upper submucosal layer by including the circular inner muscle layer within the resection specimen. It reduces basal R1 situations and offers a new perspective for T1 carcinomas through curative, organ-preserving endoscopic therapy, especially in the case of deep submucosal infiltration alone, without other risk factors for metastases. Indications, the procedure itself and significance of the various techniques for premalignant and early malignant lesions in the rectum are presented.

Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial.

Adenoma detection rate (ADR) is an important indicator of colonoscopy quality and colorectal cancer incidence. Both linked-color imaging (LCI) with artificial intelligence (LCA) and LCI alone increase adenoma detection during colonoscopy, although it remains unclear whether one modality is superior. This study compared ADR between LCA and LCI alone, including according to endoscopists' experience (experts and trainees) and polyp size. Patients undergoing colonoscopy for positive fecal immunochemical tests, follow-up of colon polyps, and abdominal symptoms at a single institution were randomly assigned to the LCA or LCI group. ADR, adenoma per colonoscopy (APC), cecal intubation time, withdrawal time, number of adenomas per location, and adenoma size were compared. The LCA (n=400) and LCI (n=400) groups showed comparable cecal intubation and withdrawal times. The LCA group showed a significantly higher ADR (58.8% vs. 43.5%; P<0.001) and mean (95%CI) APC (1.31 [1.15 to 1.47] vs. 0.94 [0.80 to 1.07]; P<0.001), particularly in the ascending colon (0.30 [0.24 to 0.36] vs. 0.20 [0.15 to 0.25]; P=0.02). Total number of nonpolypoid-type adenomas was also significantly higher in the LCA group (0.15 [0.09 to 0.20] vs. 0.08 [0.05 to 0.10]; P=0.02). Small polyps (≤5, 6-9mm) were detected significantly more frequently in the LCA group (0.75 [0.64 to 0.86] vs. 0.48 [0.40 to 0.57], P<0.001 and 0.34 [0.26 to 0.41] vs. 0.24 [0.18 to 0.29], P=0.04, respectively). In both groups, ADR was not significantly different between experts and trainees. LCA was significantly superior to LCI alone in terms of ADR.

Accuracy of GPT-4 in histopathological image detection and classification of colorectal adenomas

AimsTo evaluate the accuracy of Chat Generative Pre-trained Transformer (ChatGPT) powered by GPT-4 in histopathological image detection and classification of colorectal adenomas using the diagnostic consensus provided by pathologists as...

The Diagnostic Accuracy (DA) of ColonView Fecal Immunochemical Test (FIT) in Detecting Colorectal Adenoma (CRA) Can Be Improved by the Diagnostic Models (DM) that Include Triage and Risk Features of CRA.

This study assessed whether the diagnostic accuracy (DA) of ColonView (CV) fecal immunochemical test (FIT) in detecting colorectal adenoma (CRA) can be improved by the diagnostic models (DM) that include triage and risk features of CRA. A total of 5,090 participants of colorectal neoplasia (CRN) screening were recruited prospectively between January 2014 and December 2016. The CRN cohort of 486 patients included 222 CRA patients and 264 non-CRA patients of whom three consecutive fecal samples were analyzed by two fecal occult blood (FOB) assays (CV FIT test, HemoccultSENSA test). Hierarchical multilevel logistic models were used to test the DA of CV test and DMs, visualised as hierarchical summary receiving operating characteristic (HSROC) curves. In conventional receiving operating characteristic (ROC) analysis, the area under the curve (AUC) values of the age, height, weight, and body mass index (BMI) were 0.60, 0.57, 0.54, and 0.51, respectively. The AUC values for different DMs ranged from 0.69 (for DM without triage I/II and SENSA), and the highest AUC value of 0.70 was reached for DM with all variables included. In HSROC analysis, the AUC values for i) lowR variables, ii) highR variables, and ii) DMs were as follows: i) AUC=0.506, ii) AUC=0.566 and iii) AUC=0.732. The differences in AUC values were: between i) and ii) p=0.008; between i) and iii) p<0.0001; between ii) and iii) p<0.0001. The results demonstrated that DMs, particularly those including risk factors, significantly improved the DA of the CV FIT test in detecting CRA compared to traditional low-risk (lowR) and high-risk (highR) features alone. This study provides novel evidence supporting the enhanced diagnostic performance of DMs in combination with CV FIT testing for the detection of CRA.

Impact of a Time-Related Benchmark on the Adenoma Detection Rate in Surveillance Colonoscopy: A STROBE Statement-Oriented Cross-Sectional Cohort Study.

Colorectal adenomas are precursor lesions of globally increasing colorectal cancer. Hence, a high adenoma detection rate in colonoscopy is pivotal. We investigated the clinical impact of stratified colonoscopy observation time combined with observation time/intubation time ratio on the detection of colorectal adenomas. We conducted a single-center retrospective study including 369 consecutive patients who underwent colonoscopy following fecal immunochemical tests between May 2021 and April 2022. The primary outcome measure was the impact of the stratified observation time and observation time/ intubation time ratio (category 1: <6.0 minutes and <1.0, category 2: <6.0 minutes and ≥1.0, category 3: ≥6.0 minutes and <1.0, and category 4: ≥6.0 minutes and ≥1.0) on adenoma detection rate. Cecum intubation was obtained in 367 patients (99.5%). Adenomas were detected in 226 patients (61.2%). From the univariate analysis, age ≥53 years, habitual alcohol intake, colonoscopy attachment (+), and observation time with observation time/intubation time ratio categories 3 and 4 were determined as significant factors for adenoma detection rate. From the logistic regression analysis, age ≥ 53 years (odds ratio: 4.86, 95% CI: 2.25-10.52), habitual alcohol intake (odds ratio: 2.26, 95% CI: 1.33-3.82), category 3 (odds ratio: 3.66, 95% CI: 1.81-7.45), and category 4 (odds ratio: 5.60, 95% CI: 2.92-10.73) were significant factors for adenoma detection rate. We propose the observation time with observation time/intubation time ratio combined benchmark (with categories' thresholds based on observation time >6 minutes and scope withdrawal time exceeding intubation time [observation time/intubation time ratio > 1]) as a novel colonoscopy quality indicator. These findings represent an important educational message for endoscopists.

S440 Impact of Artificial Intelligence on Colorectal Adenoma Detection in High-Risk Colonoscopy: Initial Experience at a Safety-Net Hospital

S440 Impact of Artificial Intelligence on Colorectal Adenoma Detection in High-Risk Colonoscopy: Initial Experience at a Safety-Net Hospital

The incremental yield of adenoma detection with I-Scan versus high-definition white light colonoscopy-a systematic review and meta-analysis of randomized studies.

The incremental yield of I-Scan virtual chromoendoscopy compared to high-definition white light endoscopy (HD-WLE) in detection of colorectal adenomas has not been thoroughly elucidated. A systematic search from inception to April 2023 was conducted to identify randomized controlled trials (RCTs) comparing I-Scan to HD-WLE for detection of adenomas. A random effects model was used to compute risk difference (RD) with corresponding 95% confidence intervals in adenoma detection rate (ADR). Influence analysis was done to assess robustness of findings. The number needed to diagnose was computed. Heterogeneity was assessed using the I2 statistic and explored further by subgroup analyses defined a priori. Certainty in effect estimates was assessed using the GRADE approach. We identified four studies (I-Scan n = 730, HD-WLE n = 765). I-Scan increased adenoma detection by 9% (risk difference (RD), 0.09; 0.04, 0.14; I2 02%; certainty, low). Influence analysis revealed that the gain in yield remained statistically significant with exclusion of all but one study. The number needed to capture one additional adenomatous polyp with I-Scan use was 11.2. I-Scan 1 use was associated with a statistically significant gain in ADR, whereas no significant difference in ADR was noted with I-Scan use on subgroup analysis. In conclusion, I-Scan increases the yield of adenoma detection by 9% compared to HD-WLE, with low certainty in the estimate of this effect. Data on the gain in yield of detecting large polyps, sessile serrated lesions, and on the impact of formally training endoscopists and trainees in I-Scan use and similar technology on adenoma detection rate are needed.

Fibroblast Activation Protein-α (FAP) Identifies Stromal Invasion in Colorectal Neoplasia.

The increasing detection of colorectal adenomas and early adenocarcinomas (ADCs) in the context of nationwide screening programs has led to a significant increase in the incidence of inconclusive diagnoses in which histopathologic analysis of endoscopic biopsies does not allow pathologists to provide a reliable diagnosis of stromal invasion. The objective of this study was to analyze the discriminative capacity of the immunohistochemical expression of fibroblast activation protein-α (FAP) in distinguishing colorectal adenomas with low-grade dysplasia (LGD) and high-grade dysplasia (HGD) from invasive intestinal-type ADCs. The study analyzed the first endoscopic biopsies from a series of patients classified as inconclusive or conclusive for stromal invasion based on the pathologic report. In total, 30 ADCs, 52 HGDs, and 15 LGDs were included in the study. FAP expression was detected in 23/30 ADCs and was negative in all adenomas with either LGD or HGD features (100% specificity and 76.7% sensitivity, area under the curve=0.883, CI=0.79-0.98). Considering these findings, we conclude that FAP is a potentially useful tool for helping pathologists identify invasive lesions in colorectal endoscopic biopsies, avoiding unnecessary biopsy repetitions.

Influence of Sedated Endoscopy on Colorectal Adenoma Detection Rate: A Multicenter Study

Influence of Sedated Endoscopy on Colorectal Adenoma Detection Rate: A Multicenter Study

P-400 Validation study of a high-performance whole-blood assay for the detection of colorectal advanced adenomas in average risk population

P-400 Validation study of a high-performance whole-blood assay for the detection of colorectal advanced adenomas in average risk population