Detection Of Lesions Research Articles

As how artificial intelligence is revolutionizing endoscopy.

With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.

Current progress and future perspectives in total‐body positron emission tomography/computed tomography. Part II: Clinical applications

AbstractTotal‐body positron emission tomography (TB‐PET) has significantly advanced from initial conception to global commercial availability. The high sensitivity of TB‐PET has led to superior lesion detection, thereby expanding the range of clinical applications. TB‐PET technology offers several advantages: (a) It enables the detection of small lesions, facilitating precise cancer staging and targeted cancer formulation. (b) The technology shortens the acquisition time while maintaining the quality of diagnostic images. (c) TB‐PET allows for a reduction in the amount of administered radiotracer, which minimizes image noise, reduces the effective radiation dose to patients, and enhances staff safety. (d) The scanner supports the development of new tracers and the dynamic imaging of these tracers throughout the entire body. (e) TB‐PET accommodates delayed scanning, which has been shown to improve the detection of small and previously undetected malignant lesions by enhancing the clearance in areas of significant background activity. (f) Owing to its high‐quality images, TB‐PET is suitable for parametric imaging, which offers several advantages over conventional standardized uptake value imaging. However, TB‐PET still faces several challenges. There is a lack of consensus on the optimal dose and scan duration for clinical diagnosis using TB‐PET. Additionally, unified standards for parametric imaging via TB‐PET are yet to be established, and the full clinical significance of this technology remains under‐explored. The accompanying review (Part 1) covers TB‐PET data manipulation and analysis.

Improving detection of oral lesions: Eye tracking insights from a randomized controlled trial comparing standardized to conventional approach.

Early detection of oral cancer (OC) or its precursors is the most effective measure to improve outcome. The reasons for missing them on conventional oral examination (COE) or possible countermeasures are still unclear. In this randomized controlled trial, we investigated the effects of standardized oral examination (SOE) compared to COE. 49 dentists, specialists, and dental students wearing an eye tracker had to detect 10 simulated oral lesions drawn into a volunteer's oral cavity. SOE had a higher detection rate at 85.4% sensitivity compared to 78.8% in the control (p = 0.017) due to higher completeness (p < 0.001). Detection rate correlated with examination duration (p = 0.002). A standardized approach can improve systematics and thereby detection rates in oral examinations. It should take at least 5 min. Perceptual and cognitive errors and improper technique cause oral lesions to be missed. Its wide implementation could be an additional strategy to enhance early detection of OC.

Detection of Ulcerative Colitis Lesions from Weakly Annotated Colonoscopy Videos Using Bounding Boxes

Ulcerative colitis is a chronic disease characterized by bleeding and ulcers in the colon. Disease severity assessment via colonoscopy videos is time-consuming and only focuses on the most severe lesions. Automated detection methods enable fine-grained assessment but depend on the training set quality. To suit the local clinical setup, an internal training dataset containing only rough bounding box annotations around lesions was utilized. Following previous works, we propose to use linear models in suitable color spaces to detect lesions. We introduce an efficient sampling scheme for exploring the set of linear classifiers and removing trivial models i.e., those showing zero false negative or positive ratios. Bounding boxes lead to exaggerated false detection ratios due to mislabeled pixels, especially in the corners, resulting in decreased model accuracy. Therefore, we propose to evaluate the model sensitivity on the annotation level instead of the pixel level. Our sampling strategy can eliminate up to 25% of trivial models. Despite the limited quality of annotations, the detectors achieved better performance in comparison with the state-of-the-art methods. When tested on a small subset of endoscopic images, the best models exhibit low variability. However, the inter-patient model performance was variable suggesting that appearance normalization is critical in this context.

Baseline Characteristics and Use of Pretherapeutic 18 F-Fluorodeoxyglucose-PET for Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal malignancy. Surgical resection is the only curative modality combined with neoadjuvant chemotherapy to improve survival. Given the limitations of traditional responses such as cross-sectional imaging (CT/MRI) or tumor markers, carbohydrate antigen 19-9 (CA19-9), the 2023 National Comprehensive Cancer Network guidelines included 18 F-fluorodeoxyglucose (FDG)-PET as an adjunct to assess response to neoadjuvant chemotherapy. There are common misconceptions on the metabolic activity (tumor avidity) in PDAC so we aimed to describe the baseline characteristics and use of FDG-PET in a cohort of treatment-naive patients with PDAC. A single-center retrospective study was conducted capturing all biopsy-proven, treatment-naive patients with PDAC who underwent either baseline FDG-PET/CT or FDG-PET/MRI imaging between 2008 and 2023. Baseline FDG-PET characteristics were collected, including primary tumors' maximum standardized uptake value defined as metabolic activity (FDG uptake) of tumor compared with surrounding pancreatic parenchymal background, and the identification of extrapancreatic metastatic disease. We identified 1,095 treatment-naive patients with PDAC who underwent baseline FDG-PET imaging at diagnosis. CA19-9 was elevated in 76% of patients. Overall, 96.3% (1,054) of patients had FDG-avid tumors with a median maximum standardized uptake value of 6.4. FDG-PET also identified suspicious extrapancreatic metastatic lesions in 50% of patients, with a higher proportion (p < 0.001) in PET/MRI (59.9%) vs PET/CT (44.3%). After controlling for CA19-9 elevation, PET/MRI was superior in detection of extrapancreatic lesions compared with PET/CT. FDG-PET has significant use in PDAC as a baseline imaging modality earlier neoadjuvant therapy given the majority of tumors are FDG-avid. FDG-PET can identify additional extrapancreatic suspicious lesions allowing for optimal initial staging, with PET/MRI having increased sensitivity over PET/CT.

Multimodal Imaging of Vitreo-Retinal Lymphoma: A Comprehensive Review

ABSTRACT Purpose Vitreoretinal lymphoma (VRL) is a rare lymphoma affecting the vitreous and the retina. Clinical diagnosis is challenging and often delayed and may lead to aggravated prognosis. This study aims to review multimodal imaging findings in VRL. Methods We performed a comprehensive narrative review of the multimodal imaging findings that might be useful in the detection of VRL lesions. Results The most frequent ocular manifestations of VRL are vitritis, and retinal and sub-retinal Pigmented Epithelium (RPE) infiltrations. Color Fundus Photography (CFP) detects vitreous haze, optic nerve, retinal and sub-RPE infiltration. Ultra-wide field imaging allows visualization of different patterns of vitreous haze and monitoring of VRL evolution through the detection of chorio-retinal atrophy (CRA). Fundus Autofluorescence shows granular hypo- and hyper-autofluorescent pattern. Optical Coherence Tomography (OCT) reveals vitreous cells, vertical hyper-reflective lesions and sub-RPE infiltrates. Fluorescein Angiography (FA) shows hypo or hyperfluorescent round lesions at the late stages of the examination, while Indocyanine Green Angiography (ICGA) detects round areas of focal hypo-fluorescence in the early phases that gradually enlarge in the late phases. B-scan ultrasonography detects vitreous opacities and homogeneous hyperreflective corpuscular material in the vitreous, and is a strongly recommended tool in suspecting VRL and is particularly useful when vitreous haze is impeding retinal examination. Conclusion Diagnostic vitrectomy with cytopathological analysis remains the gold standard for VRL diagnosis, however multimodal imaging allows the identification of suggestive retinal and vitreal lesions for early suspicion, diagnosis, and treatment and monitoring disease progression and response to treatment.

Evaluating Opt-In Vaginal Human Papillomavirus Self-Sampling: Participation Rates and Detection of High-Grade Lesions (CIN2+) among Unscreened Japanese Women Aged 30-39.

Cervical cancer incidence is increasing among Japanese women, which is partly attributed to low screening rates. This study examined the implementation of opt-in human papillomavirus (HPV) self-sampling among Japanese women aged 30-39 years who had not undergone cervical cancer screening, focusing on those requiring preconception care. The responses to the opt-in approach and effectiveness in detecting cervical squamous intraepithelial neoplasia 2 or worse (CIN2+) were evaluated. Participants used the Evalyn® Brush for self-sampling, with HPV testing conducted using the Cobas 4800 system (version 2.2.0). Out of 3489 eligible, unscreened women from four municipalities in Fukui Prefecture, only 10.6% (370/3489) requested the self-sampling kit. Of these, 77.3% (286/370) returned the kit (HPV testing rate: 8.2% (286/3489)). The HPV positivity rate was 13.7% (39/285), yet only 61.5% (24/39) of those with positive HPV results proceeded to cytology testing. Subsequently, three cases of CIN2+ were detected (10.5/1000). While this study demonstrated a reasonable kit return rate and indicated the capability of opt-in HPV self-sampling to detect CIN2+ cases in unscreened women, the low ordering rate of kits and suboptimal compliance for follow-up cytology testing highlight significant challenges. The findings suggest the need for more effective strategies to enhance participation in cervical cancer screening programs.

Nerve injuries due to fractures in childhood : Primarily and secondarily on the upper extremity

The approach for nerve injuries in children in the context of fractures of the upper extremities is inconsistent in the literature. The underlying mostly retrospective studies do not usually consider the potential diagnostics. The frequency of nerve injuries with aclear need for reconstructive surgery is sometimes estimated so differently that precedent-setting errors in these studies must be assumed; however, as 10-20% of pediatric fractures near the elbow show primary or secondary nerve lesions, timely and appropriate further treatment is necessary. An overview concerning diagnostic tools with an explanation of potential results and an algorithm with atimeline for diagnostic and therapeutic management are presented. Good results after nerve lesions can only be achieved when timely diagnostics without delay and correct detection of axonal lesions which benefit from surgical treatment are carried out.

The insufficiency of CT examination in early detection of central lung squamous cell carcinoma and squamous epithelial precancerous lesions

BackgroundCT examination for lung cancer has been carried out for more than 20 years and great achievements have been made in the early detection of lung cancer. However, in the clinical work, a large number of advanced central lung squamous cell carcinoma are still detected through bronchoscopy. Meanwhile, a part of CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions are also accidentally detected through bronchoscopy.MethodsThis study retrospectively collects the medical records of patients in the bronchoscopy room of the Endoscopy Department of Zhejiang Cancer Hospital from January 2014 to December 2018. The inclusion criteria for patients includes: 1.Patient medical records completed, 2.Without history of lung cancer before the diagnosis and first pathological diagnosis of primary lung cancer, 3.Have the lung CT data of the same period, 4.Have the bronchoscopy records and related pathological diagnosis, 5.The patients undergoing radical surgical treatment must have a complete postoperative pathological diagnosis. Finally, a total of 10,851 patients with primary lung cancer are included in the study, including 7175 males and 3676 females, aged 22–98 years. Firstly, 130 patients with CT-occult lesions are extracted and their clinical features are analyzed. Then, 604 cases of single central squamous cell carcinoma and 3569 cases of peripheral adenocarcinoma are extracted and compares in postoperative tumor diameter and lymph node metastasis.Results115 cases of CT-occult central lung squamous cell carcinoma and 15 cases of squamous epithelial precancerous lesions are found. In the total lung cancer, the proportion of CT-occult lesions is 130/10,851 (1.20%). Meanwhile, all these patients are middle-aged and elderly men with a history of heavy smoking. There are statistically significant differences in postoperative median tumor diameter (3.65 cm vs.1.70 cm, P < 0.0001) and lymph node metastasis rate (50.99% vs.13.06%, P < 0.0001) between 604 patients with operable single central lung squamous cell carcinoma and 3569 patients with operable peripheral lung adenocarcinoma. Of the 604 patients with squamous cell carcinoma, 96.52% (583/604) are male with a history of heavy smoking and aged 40–82 years with a median age of 64 years.ConclusionsThis study indicates that the current lung CT examination of lung cancer is indeed insufficiency for the early diagnosis of central squamous cell carcinoma and squamous epithelial precancerous lesions. Further bronchoscopy in middle-aged and elderly men with a history of heavy smoking can make up for the lack of routine lung CT examination.

Evaluation of multiplexed sensitivity encoding diffusion-weighted imaging in detecting uterine lesions: Image quality optimization

PurposeTo compare the image quality of multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) and single-shot echo-planar imaging (SS-EPI-DWI) techniques in uterine MRI. MethodsEighty-eight eligible patients underwent MUSE-DWI and SS-EPI-DWI examinations simultaneously using a 3.0 T MRI system. Two radiologists independently performed quantitative and qualitative analysis of the two groups of images using a double-blind method. The weighted Kappa test was used to evaluate the interobserver agreement. Wilcoxon's rank sum test was used for qualitative parameters, and paired t-test was used for quantitative parameters. Spearman rank correlation analysis was used to obtained correlation between pathological results and mean apparent diffusion coefficient (ADC) value. ResultsThe qualitative and quantitative analysis of the images by the two radiologists were in good or excellent agreement, with weighted kappa value ranging from 0.636 to 0.981. The scores of total subjective image quality (15.4 ± 0.99) and signal-to-noise ratio (158.99 ± 60.71) of MUSE-DWI were significantly higher than those of SS-EPI-DWI (12.93 ± 1.62 P < 0.001; 130.23 ± 48.29 P < 0.05). It effectively reduced image distortion and artifact, and had better lesion conspicuity. There was no significant difference in contrast-to-noise ratio score and average ADC values between the two DWI sequences. The average ADC values of the two DWI sequences were highest in the normal uterus group and lowest in the endometrial cancer group, with statistically significant differences among groups (P < 0.01). In addition, the average ADC values of the two DWI sequences were negatively correlated with the type of lesions, decreasing with the malignancy of the lesions (r = −0.805 P < 0.01, r = −0.815 P < 0.01). ConclusionCompared to SS-EPI-DWI, MUSE-DWI can significantly reduce distortion, artifacts, and fuzziness in MRI of uterine lesions, which is more conducive to lesion detection.

Deep Learning-Based Psoriasis Assessment: Harnessing Clinical Trial Imaging for Accurate Psoriasis Area Severity Index Prediction

Introduction: Image-based machine learning holds great promise for facilitating clinical care; however, the datasets often used for model training differ from the interventional clinical trial-based findings frequently used to inform treatment guidelines. Here, we draw on longitudinal imaging of psoriasis patients undergoing treatment in the Ultima 2 clinical trial (NCT02684357), including 2,700 body images with psoriasis area severity index (PASI) annotations by uniformly trained dermatologists. Methods: An image-processing workflow integrating clinical photos of multiple body regions into one model pipeline was developed, which we refer to as the “One-Step PASI” framework due to its simultaneous body detection, lesion detection, and lesion severity classification. Group-stratified cross-validation was performed with 145 deep convolutional neural network models combined in an ensemble learning architecture. Results: The highest-performing model demonstrated a mean absolute error of 3.3, Lin’s concordance correlation coefficient of 0.86, and Pearson correlation coefficient of 0.90 across a wide range of PASI scores comprising disease classifications of clear skin, mild, and moderate-to-severe disease. Within-person, time-series analysis of model performance demonstrated that PASI predictions closely tracked the trajectory of physician scores from severe to clear skin without systematically over- or underestimating PASI scores or percent changes from baseline. Conclusion: This study demonstrates the potential of image processing and deep learning to translate otherwise inaccessible clinical trial data into accurate, extensible machine learning models to assess therapeutic efficacy.

Advanced Diagnostic and Therapeutic Endoscopy for Early Gastric Cancer.

Endoscopy is mandatory to detect early gastric cancer (EGC). When considering the cost-effectiveness of the endoscopic screening of EGC, risk stratification by combining serum pepsinogen values and anti-H. pylori IgG antibody values is very promising. After the detection of suspicious lesions of EGC, a detailed observation using magnifying endoscopy with band-limited light is necessary, which reveals an irregular microsurface and/or an irregular microvascular pattern with demarcation lines in the case of cancerous lesions. Endocytoscopy enables us to make an in vivo histological diagnosis. In terms of the indications for endoscopic resection, the likelihood of lymph node metastasis and technical difficulties in en bloc resection is considered, and they are divided into absolute, expanded, and relative indications. Endoscopic mucosal resection and endoscopic submucosal dissection are the main treatment modalities nowadays. After endoscopic resection, curability is evaluated histologically as endoscopic curability (eCura) A, B, and C (C-1 and C-2). Recent evidence suggests that the outcomes of endoscopic resection for many EGCs are comparable to those of gastrectomy and that endoscopic resection is the gold standard for node-negative early gastric cancers. Personalized medicine is also being developed to overcome the unmet needs in treatments of EGC, for example the further expansion of indications and newer resection techniques, such as full-thickness resection.

Feasibility of the application of deep learning-reconstructed ultra-fast respiratory-triggered T2-weighted imaging at 3 T in liver imaging

ObjectiveThe evaluate the feasibility of a novel deep learning-reconstructed ultra-fast respiratory-triggered T2WI sequence (DL-RT-T2WI) In liver imaging, compared with respiratory-triggered Arms-T2WI (Arms-RT-T2WI) and respiratory-triggered FSE-T2WI (FSE-RT-T2WI) sequences. Methods71 patients with liver lesions underwent 3-T MRI and were prospectively enrolled. Two readers independently analyzed images acquired with DL-RT-T2WI, Arms-RT-T2WI, and FSE-RT-T2WI. The qualitative evaluation indicators, including overall image quality (OIQ), sharpness, noise, artifacts, lesion detectability (LC), lesion characterization (LD), cardiacmotion–related signal loss (CSL), and diagnostic confidence (DC), were evaluated in two readers, and further statistically compared using paired Wilcoxon rank-sum test among three sequences. Results176 lesions were detected in DL-RT-T2W and Arms-RT-T2WI, and 175 were detected in FSE-RT-T2WI. The acquisition time of DL-RT-T2WI was improved by 4.8–7.9 folds compared to the other two sequences. The OIQ was scored highest for DL-RT-T2WI (R1, 4.61 ± 0.52 and R2, 4.62 ± 0.49), was significantly superior to Arms-RT-T2WI (R1, 4.30 ± 0.66 and R2, 4.34 ± 0.69) and FSE-RT-T2WI (R1, 3.65 ± 1.08 and R2, 3.75 ± 1.01). Artifacts and sharpness scored highest for DL-RT-T2WI, followed by Arms-RT-T2WI, and were lowest for FSE-RT-T2WI in both two readers. Noise and CSL for DL-RT-T2WI scored similar to Arms-RT-T2WI (P > 0.05) and were significantly superior to FSE-RT-T2WI (P < 0.001). Both LD and LC for DL-RT-T2WI were significantly superior to Arms-RT-T2WI and FSE-RT-T2WI in two readers (P < 0.001). DC for DL-RT-T2WI scored best, significantly superior to Arms-RT-T2WI (P < 0.010) and FSE-RT-T2WI (P < 0.001). ConclusionsThe novel ultra-fast DL-RT-T2WI is feasible for liver imaging and lesion characterization and diagnosis, not only offers a significant improvement in acquisition time but also outperforms Arms-RT-T2WI and FSE-RT-T2WI concerning image quality and DC.

The use of thermovision in the detection of asymptomatic facial inflammation – Pilot study

Abstract Introduction: Asymptomatic inflammatory foci resulting from chronic dental infections or the presence of foreign bodies, e.g., in the sinuses, leading to serious local and systemic complications. These conditions, despite the absence of symptoms, are a source of bacterial, toxic, allergic, and neurogenic effects. Despite the developed radiological diagnostics in the form of pantomographic images and cone beam computed tomography (CBCT), thermal imaging is increasingly mentioned as an auxiliary tool in detecting and treating inflammatory foci of the craniofacial region. It is due that thermal imaging can bring indirectly metabolic information about studied tissues and thus allow the detection of early inflammatory lesions yet not invisible on X-ray diagnostics. The purpose of the study was to apply and validate a protocol for identifying asymptomatic inflammatory foci in the maxillofacial area using thermal imaging. Material and methods: Patients referred to the institute were examined for the presence of inflammatory foci. Analysis of radiographs revealed asymptomatic foci in the maxillary sinus, which were associated with the presence of a displaced foreign body. Thermographic examinations were performed using a FLIR T540 thermal imaging camera. Results: The obtained results showed a significant temperature difference between the suspected and opposite sinus. It was also confirmed that after the foreign body was removed from the sinus the temperature showed a dynamic decrease in time. Conclusions: According to the study, thermography has the potential to become an essential diagnostic tool for inflammation of odontogenic origin. It offers non-invasiveness, safety, real-time imaging, painless and completely safe.

Diagnostic performance of linked color imaging for gastric cancer by Helicobacter pylori infection status: A subanalysis of the large-scale, multicenter randomized controlled trial LCI-FIND.

Linked color imaging (LCI) is a new image enhancement technology that facilitates the recognition of subtle differences in mucosal color. In the large-scale, multicenter randomized controlled trial LCI-FIND, LCI demonstrated good diagnostic performance for the detection of tumor lesions in the upper gastrointestinal tract. The aim of the present study was to exploratively evaluate the diagnostic performance of LCI according to H. pylori infection status as a subanalysis of LCI-FIND trial. The patients were randomly allocated to receive white light imaging (WLI) first, followed by LCI (WLI group), or vice versa (LCI group), and the two groups were compared for the detection of tumors. Data from this trial were analyzed by the presence/absence of H. pylori infection and further analyzed by successful or unsuccessful eradication in the H. pylori infection group. The 752 patients in the WLI group and 750 patients in the LCI group who had participated in the LCI-FIND trial were included. In the successful eradication group, more gastric lesions were detected by primary mode in the LCI group than in the WLI group, indicating that more lesions were missed by WLI. Fisher's exact probability test for the comparison of the WLI and LCI groups yielded a p-value of 0.0068, with missed gastric lesions being detected 0.136 times (95% confidence interval: 0.020-0.923), significantly less with LCI than with WLI. The current study suggests that LCI should be used for gastric cancer screening, particularly in patients with successful H. pylori eradication.

Finite difference-embedded UNet for solving transcranial ultrasound frequency-domain wavefield.

Transcranial ultrasound imaging assumes a growing significance in the detection and monitoring of intracranial lesions and cerebral blood flow. Accurate solution of partial differential equation (PDE) is one of the prerequisites for obtaining transcranial ultrasound wavefields. Grid-based numerical solvers such as finite difference (FD) and finite element methods have limitations including high computational costs and discretization errors. Purely data-driven methods have relatively high demands on training datasets. The fact that physics-informed neural network can only target the same model limits its application. In addition, compared to time-domain approaches, frequency-domain solutions offer advantages of reducing computational complexity and enabling stable and accurate inversions. Therefore, we introduce a framework called FD-embedded UNet (FEUNet) for solving frequency-domain transcranial ultrasound wavefields. The PDE error is calculated using the optimal 9-point FD operator, and it is integrated with the data-driven error to jointly guide the network iterations. We showcase the effectiveness of this approach through experiments involving idealized skull and brain models. FEUNet demonstrates versatility in handling various input scenarios and excels in enhancing prediction accuracy, especially with limited datasets and noisy information. Finally, we provide an overview of the advantages, limitations, and potential avenues for future research in this study.

Relative Efficacies of Interventions to Improve the Quality of Screening-Related Colonoscopy: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials

Significant variability exists in colonoscopy quality indicators, including adenoma detection rate (ADR). We synthesized evidence from randomized trials in a network meta-analysis on interventions to improve colonoscopy quality. We included trials from database inceptions to September 25, 2023, of patients undergoing screening-related colonoscopy and presented efficacies of interventions within domains (periprocedural parameters, endoscopist-directed interventions, intraprocedural techniques, endoscopic technologies, distal attachment devices, and additive substances) compared to standard colonoscopy. The primary outcome was ADR. We used a Bayesian random-effects model using Markov-chain Monte Carlo simulation, with 10,000 burn-ins and 100,000 iterations. We calculated odds ratios with 95% credible intervals and present surface under the cumulative ranking (SUCRA) curves. We included 124 trials evaluating 37 interventions for the primary outcome. Nine interventions resulted in statistically significant improvements in ADR compared to standard colonoscopy (9-minute withdrawal time, dual observation, water exchange, i-SCAN [Pentax Ltd], linked color imaging, computer-aided detection, Endocuff [Olympus Corp], Endocuff Vision [Olympus Corp], and oral methylene blue). Dual observation (SUCRA, 0.84) and water exchange (SUCRA, 0.78) ranked highest among intraprocedural techniques; i-SCAN (SUCRA, 0.95), linked color imaging (SUCRA, 0.85), and computer-aided detection (SUCRA, 0.78) among endoscopic technologies; WingCap (A&A Medical Supply LLC) (SUCRA, 0.87) and Endocuff (SUCRA, 0.85) among distal attachment devices and oral methylene blue (SUCRA, 0.94) among additive substances. No interventions improved detection of advanced adenomas, and only narrow-band imaging improved detection of serrated lesions (odds ratio, 2.94; 95% credible interval, 1.46-6.25). Several interventions are effective in improving adenoma detection and overall colonoscopy quality, many of which are cost-free. These results can inform endoscopists, unit managers, and endoscopy societies on relative efficacies.

Embedded artificial intelligence system using deep learning and raspberrypi for the detection and classification of melanoma

&lt;div lang="EN-US"&gt;&lt;span&gt;Melanoma is a kind of skin cancer that originates in melanocytes responsible for producing melanin, it can be a severe and potentially deadly form of cancer because it can metastasize to other regions of the body if not detected and treated early. To facilitate this process, Recently, various computer-assisted low-cost, reliable, and accurate diagnostic systems have been proposed based on artificial intelligence (AI) algorithms, particularly deep learning techniques. This work proposed an innovative and intelligent system that combines the internet of things (IoT) with a Raspberry Pi connected to a camera and a deep learning model based on the deep convolutional neural network (CNN) algorithm for real-time detection and classification of melanoma cancer lesions. The key stages of our model before serializing to the Raspberry Pi: Firstly, the preprocessing part contains data cleaning, data transformation (normalization), and data augmentation to reduce overfitting when training. Then, the deep CNN algorithm is used to extract the features part. Finally, the classification part with applied Sigmoid Activation Function. The experimental results indicate the efficiency of our proposed classification system as we achieved an accuracy rate of 92%, a precision of 91%, a sensitivity of 91%, and an area under the curve- receiver operating characteristics (AUC-ROC) of 0.9133.&lt;/span&gt;&lt;/div&gt;

The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial

BackgroundThe use of computer-aided detection (CADe) has increased the adenoma detection rates (ADR) during colorectal cancer (CRC) screening/surveillance in randomized controlled trials (RCT) but has not shown benefit in real-world implementation studies. We performed a single-center pragmatic RCT to evaluate the impact of real-time CADe on ADR in colonoscopy performed by community gastroenterologists. MethodsWe enrolled 1100 patients undergoing colonoscopy for CRC screening, surveillance, positive fecal-immunohistochemical tests, and diagnostic indications at one community-based center from 09/2022 to 03/2023. Patients were randomly assigned (1:1) to traditional-colonoscopy or real-time CADe Blinded pathologists analyzed histopathologic findings. The primary outcome was adenoma detection rate (ADR, the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy (APC), sessile-serrated lesion detection rate (SSLDR), and non-neoplastic resection rate. ResultsThe median age was 55.5 (IQR 50-62), 61% were female, 72.7% were Hispanic ethnicity, and 9.1% had inadequate bowel preparation. The ADR for the CADe group was significantly higher than the traditional-colonoscopy group (42.5% vs. 34.4%, p=0.005). The mean APC was significantly higher in the CADe group compared to the traditional-colonoscopy group (0.89±1.46 vs. 0.60±1.12, p<0.001). The improvement in adenoma detection was driven by increased detection of <5 mm adenomas. CADe had a higher SSLDR than traditional-colonoscopy (4.7% vs. 2.0%, p=0.01) The improvement in ADR with CADe was significantly higher in the first half of the study (47.2% vs. 33.7%, p=0.002) compared to the second half (38.7% vs. 34.9%, p=0.33). ConclusionsIn a single-center pragmatic randomized controlled trial, real-time CADe modestly improved ADR and APC in average-detector community endoscopists. (ClinicalTrials.gov number, NCT05963724).

Multispectral Imaging Method in Laparoscopy

Introduction. At present, video data acquired in narrow spectral bands are widely used to improve the efficiency of diagnostics in various medical fields, laparoscopy in particular. Conventional laparoscopy uses images obtained in the white light. Images obtained in the visible range suitably depict the color and textural features of tissues. However, it is difficult for a physician to use visible images for distinguishing between lesion areas and normal tissues, largely due to their proximity in color and texture. The efficiency of lesion detection can be improved using fluorescence images, which clearly differentiate lesion areas from normal tissues. However, the use multispectral data implies the need to present the images obtained both in the white and fluorescence light to the physician. In this paper, we propose an image composition method based on visible and fluorescence images, which facilitates their analysis by physicians. A distinctive feature of the method is the use of CIEDE 2000 metric for image fusion, which takes the properties of human vision into account.Aim. Development of a method for multispectral data visualization, which provides a physician with an image that combines white light data and a color-highlighted area of lesions.Materials and methods. The proposed method consists of the following steps: preprocessing of images obtained in visible and fluorescence light; segmentation of the lesion area in the fluorescence images; generation of a pseudo-color image of the segmented lesion area; and fusion of the pseudo-color image with the image obtained in the white light.Results. The proposed method forms an image that includes an image of the operation area obtained in the white light and a separated lesion area based on fluorescence information in the near infrared range. The image composite takes the properties of human vision into account. An experimental study of the method was carried out on actual laparoscopic images, involving endoscopists who were experts in subjective evaluation of video images. The method of paired comparisons was used to evaluated the presented images. The majority of experts preferred the fused image formed by the proposed method to those visualized simultaneously in the white and fluorescence light.Conclusion. The developed method ensures generation of images with an increased diagnostic value.