Early-stage Lesions Research Articles

OGC SO11 - Impact Evaluation of Endoscopic Mucosal Resection in the Foregut in a Tertiary Centre in the United Kingdom (UK)

Abstract Background Endoscopic mucosal resection (EMR) has emerged as a crucial technique for managing early-stage lesions in the oesophagus and stomach, encompassing precancerous and cancerous conditions.1 With fewer complications and excellent 5-year survival rates, EMR has shown potential as a less-invasive alternative to surgical resections.1 EMR achieves higher accuracy with its ability to obtain more profound and better quality tissue samples compared to conventional biopsies, which facilitates multidisciplinary team (MDT) discussions regarding treatment decisions.1 This study aims to evaluate the impact of EMR performed in an Oesophago-Gastric Cancer tertiary centre in the UK. Method This is a retrospective service evaluation of patients who underwent EMR from March 2021 to March 2024. A sample size of 73 EM (n=73) is identified. Data were collected from medical and endoscopic records, which includes patient’s demographics, American Society of Anaesthesiologists (ASA) grade, EMR indication, histology report and MDT outcome. EMRs performed were categorised into oesophageal, gastric and duodenal. Three main referral indications were identified; ‘polyp’, ‘dysplastic nodule in Barrett’s oesophagus’ and ‘possible early malignancy’. MDT outcomes were analysed thematically. Results Of the seventy-three patients identified, 78% is male and mean age at 71 years. Most patients (81%) are classified as ASA Grade 2. Polyp is identified in 37 patients (51%), making up the most common referral indication. 49% of the EMR were gastric, with remaining being oesophageal (41%) and duodenal (11%). 26% of histology results showed benign disease, 40% dysplastic disease, and 34% malignant. From histology reports, 47% of the EMRs achieved complete clearance margins. 28 patients (38%) were discharged with no further interventions and 12 patients (16%) received repeat EMR. 4 main themes were identified from MDT outcomes, with 43.8% patients needing surveillance endoscopy, 16.7% patients recommended for surgical intervention and repeated EMR each. Conclusion EMR has shown to be effective as a reference for further treatment decisions, especially for MDT discussions. It has been proven that EMR can be therapeutic in providing complete resection, particularly for benign and early dysplastic diseases.

Clinical and laboratory evaluation of the effectiveness of children's toothpastes containing 1000 ppm fluoride

Relevance. This article presents the findings from studies evaluating the effectiveness of toothpastes containing 1000 ppm fluoride in clinical settings. The data demonstrates the cumulative benefits of these toothpastes on oral hygiene, the reduction of inflammatory oral manifestations, and their anticaries effects.Purpose. To assess the effectiveness of fluoride-containing toothpastes through laboratory tests and clinical trials.Materials and methods. The study evaluated the effectiveness of toothpastes containing 1000 ppm fluoride using the following parameters: Greene-Vermillion hygiene index, periodontal indices (PMA and SBI), enamel mineralization and resistance, presence and number of carious lesions at the white spot stage, enamel hypersensitivity, and antimicrobial activity against Streptococcus spp.Results. The analysis of hygiene indices demonstrated that the tested toothpastes were highly effective in cleaning, with a positive cumulative effect on participants' oral hygiene. The use of these toothpastes significantly reduced inflammatory manifestations, decreased gum bleeding, and improved periodontal tissue health. A reduction in the number of participants with early-stage carious lesions, as well as a decrease in the overall number of lesions, was observed. The toothpastes also enhanced enamel resistance to acid exposure, contributing to their anticaries benefits. Enamel hypersensitivity was reduced, and a dose-dependent antibacterial effect against Streptococcus mutans, Streptococcus gordonii, and Streptococcus sobrinus was observed.Conclusion. Toothpastes containing 1000 ppm fluoride demonstrated strong cleaning and refreshing effects, along with a positive cumulative impact on oral hygiene and a significant reduction in inflammation. Their anticaries benefits were confirmed, and they also reduced enamel hypersensitivity. The tested toothpastes were well-tolerated, with no reports of allergic reactions or irritation.

Lightweight skin cancer detection IP hardware implementation using cycle expansion and optimal computation arrays methods

Skin cancer is recognized as one of the most perilous diseases globally. In the field of medical image classification, precise identification of early-stage skin lesions is imperative for accurate diagnosis. However, deploying these algorithms on low-cost devices and attaining high-efficiency operation with minimal energy consumption poses a formidable challenge due to their intricate computational demands. This study proposes a lightweight hardware design based on a convolutional neural network (CNN) for real-time processing of skin disease classifiers on portable devices. Our skin cancer recognition processor utilizes an optimally parallel designed processing engine (PE) for global computation, which greatly reduces hardware resource utilization by multiplexing of computational unit circuits. In addition, a design approach that provides loop unrolling effectively reduces the number of data accesses, thereby reducing computational complexity and logic resource requirements. The hardware circuits in this design perform data inference in convolutional, pooling, and fully connected layers based on 16-bit floating-point numbers. Evaluation of the HAM10000 database dataset shows that the architecture achieves an average classification accuracy of 97.8 %. We are the first to implement an all-hardware FPGA-based skin cancer detection platform that offers a 3.5x speedup in recognition compared to existing skin cancer accelerators at 50 MHz while consuming only 0.48 W of power. The implementation of this hardware architecture meets the major constraints of portable devices, featuring low resource utilization, low power consumption, and cost-effectiveness, while still providing efficient classification and high accuracy results.

A multi-slice attention fusion and multi-view personalized fusion lightweight network for Alzheimer’s disease diagnosis

ObjectiveAlzheimer’s disease (AD) is a type of neurological illness that significantly impacts individuals’ daily lives. In the intelligent diagnosis of AD, 3D networks require larger computational resources and storage space for training the models, leading to increased model complexity and training time. On the other hand, 2D slices analysis may overlook the 3D structural information of MRI and can result in information loss.ApproachWe propose a multi-slice attention fusion and multi-view personalized fusion lightweight network for automated AD diagnosis. It incorporates a multi-branch lightweight backbone to extract features from sagittal, axial, and coronal view of MRI, respectively. In addition, we introduce a novel multi-slice attention fusion module, which utilizes a combination of global and local channel attention mechanism to ensure consistent classification across multiple slices. Additionally, a multi-view personalized fusion module is tailored to assign appropriate weights to the three views, taking into account the varying significance of each view in achieving accurate classification results. To enhance the performance of the multi-view personalized fusion module, we utilize a label consistency loss to guide the model’s learning process. This encourages the acquisition of more consistent and stable representations across all three views.Main resultsThe suggested strategy is efficient in lowering the number of parameters and FLOPs, with only 3.75M and 4.45G respectively, and accuracy improved by 10.5% to 14% in three tasks. Moreover, in the classification tasks of AD vs. CN, AD vs. MCI and MCI vs. CN, the accuracy of the proposed method is 95.63%, 86.88% and 85.00%, respectively, which is superior to the existing methods.ConclusionsThe results show that the proposed approach not only excels in resource utilization, but also significantly outperforms the four comparison methods in terms of accuracy and sensitivity, particularly in detecting early-stage AD lesions. It can precisely capture and accurately identify subtle brain lesions, providing crucial technical support for early intervention and treatment.

Performance of post-mortem diagnostic tests for tuberculosis in wild ungulates at low and high prevalence assessed using Bayesian latent class models.

Animal tuberculosis (TB) is often maintained by multi-host communities, including livestock and wildlife. Quantitative studies of such communities require estimating the true prevalence of TB, correcting the apparent prevalence by the diagnostic sensitivity (Se) and specificity (Sp) of the test. The goal of this study was to lay the foundations for estimating the true prevalence of TB in wild ungulate populations (wild boar and two cervids: red deer and fallow deer). We used Bayesian latent class models to assess the Se and Sp of gross pathology, IS6110 real-time PCR in tissues, bacteriological culture, and P22 indirect ELISA. We analyzed 308 harvested wild ungulates (211 wild boar and 97 cervids: 92 red deer and 5 fallow deer). The Se of bacteriological culture (80.4%, CI95 61.0-96.3%) and gross pathology (87.9%, CI95 69.5-99.9%) was reasonably good in wild boar. These tests showed lower Se in cervids: 60.2% (CI95 38.3-82.3%) for bacteriological culture and 81.5% (CI95 63.6-96.2%) for gross pathology. The Se of the real-time PCR was low (50.7% in wild boar and 53.0% in cervids). These tests showed Sp between 95.2 and 99.1% in both taxa. The P22 ELISA performed reasonably well in wild boar (Se = 71.9%, CI95 59.2-83.4%; Sp = 98.8%, CI95 96.9-99.9%) but lacked Sp in cervids (Se = 77.1%, CI95 62.9-89.7%; Sp = 74.5%, CI95 65.7-83.3%). The real-time PCR in wild boar and cervids and bacteriological culture in cervids tended to show higher Se in low-prevalence populations, possibly due to a higher proportion of early-stage TB lesions. In cervids, the parallel interpretation of gross pathology and bacteriological culture significantly improved the diagnostic performance (Se = 93.1%, CI95 84.7-98.9%; Sp = 92.9%, CI95 86.0-98.3%). Our results allow the estimation of true prevalence from the results of a single diagnostic test applied to harvested wild boar, red deer, and fallow deer, paving the way for more precise quantitative ecological studies of the multi-host TB maintenance community.

Synthesis and Application of Silver Nanoparticles for Caries Management: A Review.

Silver nanoparticles have unique physical, chemical, and biological properties that make them attractive for medical applications. They have gained attention in dentistry for their potential use in caries management. This study reviews the different synthesis methods of silver nanoparticles and the application of them for caries management. Silver nanoparticles are tiny silver and are typically less than 100 nanometres in size. They have a high surface area-to-volume ratio, making them highly reactive and allowing them to interact with bacteria and other materials at the molecular level. Silver nanoparticles have low toxicity and biocompatibility. Researchers have employed various methods to synthesise silver nanoparticles, including chemical, physical, and biological methods. By controlling the process, silver nanoparticles have defined sizes, shapes, and surface properties for wide use. Silver nanoparticles exhibit strong antibacterial properties, capable of inhibiting a broad range of bacteria, including antibiotic-resistant strains. They inhibit the growth of cariogenic bacteria, such as Streptococcus mutans. They can disrupt bacterial cell membranes, interfere with enzyme activity, and inhibit bacterial replication. Silver nanoparticles can inhibit biofilm formation, reducing the risk of caries development. Additionally, nano silver fluoride prevents dental caries by promoting tooth remineralisation. They can interact with the tooth structure and enhance the deposition of hydroxyapatite, aiding in repairing early-stage carious lesions. Silver nanoparticles can also be incorporated into dental restorative materials such as composite resins and glass ionomer cements. The incorporation can enhance the material's antibacterial properties, reducing the risk of secondary caries and improving the longevity of the restoration.

Skin-directed radiotherapy for primary cutaneous T-cell lymphomas.

To evaluate the efficacy and toxicities of skin-directed radiotherapy (RT) in primary cutaneous T-cell lymphoma (CTCL). We retrospectively analyzed 57 CTCL lesions treated with skin-directed RT between January 2000 and December 2022. Lesions were categorized into three distinct groups: early-stage disease treated with local RT, advanced-stage disease treated with local RT, and advanced-stage disease treated with total skin electron beam therapy (TSEBT). Treatment outcomes, including response rates, recurrence patterns, and local progression probability, were assessed for each group. Mycosis fungoides (MF) constituted 90.9% of the advanced-stage pathologies, while CD4+ primary cutaneous small/medium T-cell lymphoproliferative disorder was common in the early stage lesions (55%). Median RT doses were 30.6 Gy, 27 Gy, and 32 Gy for the local RT with early stage, the local RT with advanced stage, and TSEBT with advanced stage, respectively. The complete response rates were high across the groups: 95.5%, 70.8%, and 90.9%, respectively. Seven local recurrences (29.2%) occurred in the local RT group with advanced stage, while seven patients (63.6%) in the TSEBT group experienced local failure. All recurrences were observed in lesions and patients with MF. Acute toxicities were mainly grade 1 or 2, with no grade 3 or higher events. No significant association between RT dose and local progression rates in MF lesions was found. Skin-directed RT in CTCL is effective for local control and well-tolerated with less toxicity.

Chemopreventive Potential of Phyllanthus emblica Fruit Extract against Colon and Liver Cancer Using a Dual-Organ Rat Carcinogenesis Model.

Humans are frequently exposed to various carcinogens capable of inducing cancer in multiple organs. Phyllanthus emblica (P. emblica) is known for its strong antioxidant properties and potential in cancer prevention. However, its effectiveness against combined carcinogens remains relatively unexplored. This study aimed to assess the chemopreventive potential of the ethanolic extract of P. emblica fruits against preneoplastic lesions in the liver and colon using a rat model. Rats were administered with diethylnitrosamine (DEN) and 1,2-dimethylhydrazine (DMH) to induce hepato- and colon carcinogenesis, respectively. The ethanolic extract of P. emblica fruit at 100 and 500 mg/kg bw significantly reduced the number of preneoplastic lesions in the liver by 74.7% and 55.6%, respectively, and in the colon by 39.2% and 40.8%, respectively. Similarly, the extract decreased the size of preneoplastic lesions in the liver by 75.2% (100 mg/kg bw) and 70.6% (500 mg/kg bw). Furthermore, the extract significantly reduced the cell proliferation marker in the liver by 70.3% (100 mg/kg bw) and 61.54% (500 mg/kg bw), and in the colon by 62.7% (100 mg/kg bw) and 60.5% (500 mg/kg bw). The ethanolic extract also enhanced liver antioxidant enzyme activities and demonstrated free radical scavenging in DPPH, ABTS, and FRAP assays. Additionally, the dichloromethane fraction of P. emblica showed significant cancer prevention potential by reducing intracellular ROS and NO production by 61.7% and 35.4%, respectively, in RAW 264.7 macrophages. It also exhibited antimutagenic effects with a reduction of 54.0% against aflatoxin B1 and 52.3% against 2-amino-3,4-dimethylimidazo[4,5-f]quinoline-induced mutagenesis in Salmonella typhimurium. Finally, this study highlights the chemopreventive activity of P. emblica fruit extract against the initiation of early-stage carcinogenic lesions in the liver and colon in rats treated with dual carcinogens.

Effectiveness and safety of biosilicate-enhanced bleaching gels on enamel with early erosion lesion.

This study evaluated the efficacy and cytotoxicity of 35% hydrogen peroxide (HP) gel incorporated with 10% (w/w) biosilicate (BioS) on sound enamel and early-stage enamel erosion lesions. Discs of enamel/dentin were selected, subjected to erosive cycles (0.3% citric acid, pH 2.6), and treated with (n = 8): HP (35% HP, positive control); HP_BioS [carboxymethyl cellulose (CMC) + HP + BioS]; BioS (CMC + BioS); CMC (negative control). The discs were adapted to artificial pulp chambers with the enamel exposed for bleaching, and the dentin facing toward the culture medium (Dulbecco's modified Eagle's medium [DMEM]). Bleaching was performed in three 30-min sessions at 7-day intervals. After bleaching, the diffusion product (DMEM extract + diffused HP) was pipetted onto MDPC-23 odontoblastic cell line and inoculated. Color parameters (ΔL, Δa, Δb), color change (ΔE00), and changes in whiteness index (ΔWID) were determined before (T0) and after the last bleaching session (T3). Cell viability (MTT, %), H2O2 diffusion (μg/mL), oxidative cell stress (OxS), and cell fluorescence (live/dead assay, in confocal microscopy) were assessed (ANOVA/Tukey; α = 0.05). No difference in ΔL, Δa, Δb, ΔE00, and ΔWID were found between HP and HP_BioS (p > 0.05). The incorporation of BioS decreased the HP diffusion into the substrates and mitigated oxidative stress in early-stage eroded enamel (p < 0.05). HP_BioS presented significantly higher cell viability compared with HP under erosion conditions. Live/dead assay indicated that BioS_HP maintained viability with larger clusters of viable cells. Incorporating BioS into HP maintained bleaching effectiveness, favored cell viability, reduced the oxidative stress, and the cytotoxicity in teeth with early-stage erosion. BioS formulation showed promising results for reducing cytotoxicity in patients seeking tooth bleaching and presenting undetectable early-stage erosion.

Characterization of early-stage lesions and investigation on the role of mucosal trauma in hemorrhagic bowel syndrome in cattle

Hemorrhagic bowel syndrome (HBS) is characterized by a dissecting intramucosal hematoma at the small bowel, causing obstruction and severe hemorrhage in dairy cattle. Recent investigation revealed the presence of early-stage lesions in cows affected by HBS. These are presumed to be the initial stage of the hematoma, as both share unique dissection of the lamina muscularis mucosae (LMM) as histological hallmark. Early-stage lesions of HBS have not been characterized in greater detail, and neither has the hypothesis of mucosal abrasion as etiology been explored. Therefore, the first objective of the present study was to characterize the morphology of early-stage lesions, by gross examination, histochemistry, immunohistochemistry and transmission electron microscopy. The second objective was to determine the effect of mucosal abrasion to the small intestine in an ex vivo model. A total of 86 early-stage lesions from 10 cows with HBS were characterized. No underlying alterations at the LMM were evident which could explain their occurrence. However, degeneration at the ultrastructural level of the LMM smooth muscle cells was present in 3 of 4 lesions, it is however unclear whether this is primary or secondary. Bacteriological examination did not reveal any association with a specific bacterium. Experimental-induced and early-stage lesions were gross and histologically evaluated and scored in three cows with HBS and seven controls. Experimentally induced lesions in both affected cows and controls, were histologically very similar to the naturally occurring early-stage lesions. Altogether, the results are suggestive for mucosal trauma to play a role in the pathogenesis of HBS.

Analyzing Temperature Distributions and Gradient Behaviors for Early-Stage Tumor Lesions in 3D Computational Model of Breast

The computational modelling and analysis of internal and external temperature distributions and their gradients, associated with the first stage of mammary tumors, was performed to relate thermal parameters to relevant tumor characteristics. A realistic 3D geometric model of breast anatomy was used to simulate tumor cases that were characterized in real life at their primary clinical stage. The thermophysical parameters of three tumors were extracted to implement the models; a fourth case without a tumor was used as a reference to provide quantitative measurements of temperature increases and gradient changes. The analysis considered superficial and internal temperature distributions and gradients, computed throughout specific paths. Finally, an evaluation was made of the ability of the thermometric technologies available today to detect the changes estimated in simulations. Maximum temperature increments in the range of 2.30 to 3.20 °C and in the range of 0.15 to 0.30 °C were found on internal and superficial paths, respectively. Internal gradient peak magnitudes fluctuated within the range of 0.34 to 1.14 °C/mm. Thermal results indicated a direct correlation between tumor size and temperature rise. Nevertheless, gradient results showed that the heat generation rate, an indicator of tumor malignancy, was directly proportional to internal gradient maximum peaks, which were related to tumor boundaries regardless of tumor size.

P.085 Characterizing molecular alterations in glioma growth and progression

Background: High grade gliomas (HGG) are incurable, aggressive brain malignances that carry poor prognoses. Significant scientific advances have uncovered many of the features of these diseases; however, it remains unclear how mutations and transcriptional changes drive glioma growth and progression. Methods: We used a Nestin-Cre mouse model in combination with an extrinsic chemical mutagen (N-ethyl-N-nitrosurea, ENU), to model HGG. We combined our mouse model with live animal in vivo magnetic resonance imaging to track tumor growth over time, and sample discrete lesions during premalignant, early stage tumor, and end stage tumor phases. Results: We show that the somatic mutations, copy number changes, and transcriptional profiles of tumors vary depending on the stage of growth, and that the Raf/Ras pathway is key for tumor growth with a recurring Braf mutation occurring in early stage lesions. Gene set enrichment analysis (GSEA) shows that end stage tumors have increased immunogenic/inflammatory activity, and increased signaling through Raf/Ras. Conclusions: The combination of genetic and nongenetic insults results in activating mutations in early lesions, which continue to be biologically active and underlie key differences between early and end stage tumors. Overall, this work sheds light on important differences between early and late stage tumors.

Lung cancer screening: new frontiers

Lung cancer is the leading cause of cancer-related deaths worldwide. In early, asymptomatic stages, curative treatment is possible, but the disease is often diagnosed too late. Lung cancer screening (LCS) using low-dose computed tomography (LDCT) helps to detect potentially malignant lesions in early stages and to reduce lung cancer mortality. The application of artificial intelligence (AI) algorithms enables amore precise analysis of LDCT scans. Ameta-analysis of eight LCS studies revealed astatistically significant 12% relative reduction in lung cancer mortality. Based on strong scientific evidence, arecommendation for astructured lung cancer screening program using LDCT for the high-risk population in Germany was issued. The holistic LCS program requires aclear definition of the high-risk population, individual risk assessment, qualified personnel for conducting and reading examinations, verification of all diagnostic and therapeutic steps, central documentation and quality assurance, as well as the integration of tobacco cessation programs.

4-nitroquinoline 1-oxide-induced oral epithelial lesions exhibit time- and stage-dependent changes in the tumor immune microenvironment.

Oral tongue squamous cell carcinoma (OTSCC) is the most common cancer of the oral cavity and is associated with high morbidity due to local invasion and lymph node metastasis. Tumor infiltrating lymphocytes (TILs) are associated with good prognosis in oral cancer patients and dictate response to treatment. Ectopic sites for immune activation in tumors, known as tertiary lymphoid structures (TLS), and tumor-associated high-endothelial venules (TA-HEVs), which are specialized lymphocyte recruiting vessels, are associated with a favorable prognosis in OSCC. Why only some tumors support the development of TLS and HEVs is poorly understood. In the current study we explored the infiltration of lymphocyte subsets and the development of TLS and HEVs in oral epithelial lesions using the 4-nitroquinoline 1-oxide (4NQO)-induced mouse model of oral carcinogenesis. We found that the immune response to 4NQO-induced oral epithelial lesions was dominated by T cell subsets. The number of T cells (CD4+, FoxP3+, and CD8+), B cells (B220+) and PNAd+ HEVs increased from the earliest to the latest endpoints. All the immune markers increased with the severity of the dysplasia, while the number of HEVs and B cells further increased in SCCs. HEVs were present already in early-stage lesions, while TLS did not develop at any timepoint. This suggests that the 4NQO model is applicable to study the dynamics of the tumor immune microenvironment at early phases of oral cancer development, including the regulation of TA-HEVs in OTSCC.

LRFE: A NOVEL LOCAL RESPONSE FEATURE ELIMINATION PROCESS FOR IDENTIFICATION OF LUNG CANCER CELLS

One of the main causes of cancer-related mortality across the globe is lung cancer. Early-stage lung cancer frequently exhibits no symptoms, which delays diagnosis until the illness has progressed. Before symptoms manifest, screening and early detection techniques can aid in the early diagnosis and treatment of lung cancer. Many olden research papers have implemented image processing and few latest papers have implemented computer vision techniques to detect lung cancer. Particularly when dealing with minor or subtle anomalies, image processing algorithms may not be able to detect lung cancer lesions with sufficient sensitivity and specificity. It is still difficult to increase the detection algorithms' accuracy and dependability, especially when dealing with early-stage lesions or situations where attributes overlap. It takes a lot of processing power, such as high-performance GPUs and enormous memory capacities, to train deep learning models, particularly large-scale convolutional neural networks (CNNs). In this proposed research, the model pre-processes the images using the ostu and sober filter mechanisms because Otsu's approach adjusts to the features of the input image, including noise, contrast, and lighting fluctuations. It is capable of handling images with varying dynamic ranges and intensity distributions without depending on pre-established threshold settings. When it comes to image noise, the Sobel filter is more resilient than other edge detection methods. It produces clearer edge maps and fewer false detections by determining the gradient magnitude, which amplifies edge information while suppressing noise. The features are extracted using the tuned AlexNet pre-trained model, in AlexNet there is a layer known as “Layer-wise Relevance Propagation”. By giving each pixel or feature in the input image a relevance score, the LRP layer offers fine-grained feature attribution. This makes it possible to analyze in great depth which particular elements or areas of the input image are most important for the network to forecast, which helps to clarify the underlying patterns that the network has learned. At last, the extracted features are further reduced using the enhanced feature elimination method. By iteratively selecting subsets of features based on their importance, RFE helps to identify the most relevant features for the classification task. Integrating RFE with SVM classifiers can lead to improved model performance by focusing on the subset of features that are most discriminative and informative for the classification problem.

Boundary-Sensitive Segmentation of Small Liver Lesions.

Early diagnosis plays a pivotal role in handling the global health challenge posed by liver diseases. However, early-stage lesions are typically quite small, presenting significant difficulties due to insufficient regions for developing effective features, indistinguishable boundaries of small lesions, and a lack of tiny liver lesion masks. To address these issues, we approach the solution in two-fold: an efficient model and a high-quality dataset. The model is built upon the advantages of path signature and camouflaged object detection. The path signature narrows down the ambiguous boundaries between lesions and other tissues while the camouflaged object detection achieves high accuracy in detecting inconspicuous lesions. The two are seamlessly integrated to ensure high accuracy and fidelity. For the dataset, we collect more than ten thousand liver images with over four thousand lesions, approximately half of which are small. Experiments on both an established dataset and our newly constructed one show that the proposed model outperforms state-of-the-art semantic segmentation and camouflaged object detection models, particularly in detecting small lesions. Moreover, the decisive and faithful salience maps generated by the model at the boundary regions demonstrate its strong robustness.

A nomogram to predict severe COVID-19 patients with increased pulmonary lesions in early days.

This study aimed to predict severe coronavirus disease 2019 (COVID-19) progression in patients with increased pneumonia lesions in the early days. A simplified nomogram was developed utilizing artificial intelligence (AI)-based quantified computed tomography (CT). From 17 December 2019 to 20 February 2020, a total of 246 patients were confirmed COVID-19 infected in Jingzhou Central Hospital, Hubei Province, China. Of these patients, 93 were mildly ill and had follow-up examinations in 7 days, and 61 of them had enlarged lesions on CT scans. We collected the neutrophil-to-lymphocyte ratio (NLR) and three quantitative CT features from two examinations within 7 days. The three quantitative CT features of pneumonia lesions, including ground-glass opacity volume (GV), semi-consolidation volume (SV), and consolidation volume (CV), were automatically calculated using AI. Additionally, the variation volumes of the lesions were also computed. Finally, a nomogram was developed using a multivariable logistic regression model. To simplify the model, we classified all the lesion volumes based on quartiles and curve fitting results. Among the 93 patients, 61 patients showed enlarged lesions on CT within 7 days, of whom 19 (31.1%) developed any severe illness. The multivariable logistic regression model included age, NLR on the second time, an increase in lesion volume, and changes in SV and CV in 7 days. The personalized prediction nomogram demonstrated strong discrimination in the sample, with an area under curve (AUC) and the receiver operating characteristic curve (ROC) of 0.961 and a 95% confidence interval (CI) of 0.917-1.000. Decision curve analysis illustrated that a nomogram based on quantitative AI was clinically useful. The integration of CT quantitative changes, NLR, and age in this model exhibits promising performance in predicting the progression to severe illness in COVID-19 patients with early-stage pneumonia lesions. This comprehensive approach holds the potential to assist clinical decision-making.

Head and neck cancer: epidemiological aspects of two large Brazilian medical centers

Objective: To compare clinical and epidemiological aspects of Head and neck cancers (HNC) patients treated in hospitals in northeast and southeast regions of Brazil. Methodology: The study cross-sectional retrospective analyzed 519 medical records of patients treated between 2016 and 2021. The factors evaluated for HNC prevalence included demographic data, predisposing factors, tumor location, treatment type, and related oral manifestations. Qualitative variables were expressed in absolute and relative frequencies. The chi-square test assessed potential associations between these variables (p&lt; 0.05). Results: 54.1% of patients were men and 45.9% were women. Hospitals significantly differed regarding sex, age, and tobacco use (p&lt; 0.05). The accumulated percentage indicated that adults under 60 years old were the most affected (62.6%). The larynx/hypopharynx was the most prevalent location (51.8%), followed by the oral cavity (25.8%). The tongue was the most affected anatomical region in the oral cavity (11.0%). Conclusion: Patient profile showed possible changes, with both sexes being similarly affected in increasingly younger patients. Demographic and lifestyle factors suggest an association with HNC, representing information for consideration when screening more susceptible patients and tracking early-stage lesions.

Abstract 737: Arrays of 3D ECM-embedded fibroblast clusters for characterization of ECM remodeling by primary cancer associated fibroblasts and for evaluation of drugs attenuating fibrotic ECM remodeling

Abstract Chronic fibrosis can lead to organ failure and is also associated with cancer, where the tumor is interpreted as a chronic wound, and the fibrotic tumor environment drives disease progression. Fibrosis occurs in an inflammatory environment where macrophages are activated, and fibroblasts transdifferentiate into myofibroblasts. Activated macrophages stimulate the myofibroblasts to produce excessive amounts of collagen-rich ECM. Changes in proteolytic activity and high contractile forces that myofibroblasts apply onto their tissue environment, further lead to extensive remodeling of the healthy tissue matrix into a scar matrix. Similar activity is displayed by cancer-associated fibroblasts (CAFs) in tumors. Intervening with the excessive ECM remodeling by activated fibroblasts represents a candidate therapeutic strategy to normalize the architecture of fibrotic and malignant tissues. We developed a screening platform using an assay based on automated image guided injection of clusters of fibroblasts in wells of multi-well plates preloaded with a collagen-rich ECM network. The identical x-y-z position, spacing, and size of the ECM-embedded fibroblast clusters in each well facilitates automated real time confocal microscopy and quantitative image analysis algorithms. We use this setup for automated quantitative analysis of ECM remodeling activity of CAFs obtained from early-stage colorectal cancer patients. We find that CAFs from these early-stage lesions display increased ECM remodeling capacity as compared to patient matched normal fibroblasts. We then use the same setup to screen a series of compounds for their ability to attenuate ECM remodeling triggered by TGFb-activated primary human fibroblasts. We detect known and novel pathways, and we identify small molecule inhibitors with a promising efficacy versus toxicity profile. Lastly, we detect a previously unknown concentration-dependent side effect of ALK5 inhibitors that leads to the identification of a novel profibrotic pathway and indicates that caution is warranted for the clinical application of ALK5 inhibitors. Citation Format: Erik H. J. Danen. Arrays of 3D ECM-embedded fibroblast clusters for characterization of ECM remodeling by primary cancer associated fibroblasts and for evaluation of drugs attenuating fibrotic ECM remodeling [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 737.

In-hospital metrics for the Treatment of Cervical Cancer in Minas Gerais in 2021 – Time Series from 2012 to 2021.

Cervical cancer (CC) is the third most common tumor in the female population. Due to the importance of its morbimortality, public health policies have been developed in Brazil since the mid-1980s. It is decisive to detect lesions in early stages for the prognosis and conduct to be adopted, so that lesions in a more advanced stage, usually require more invasive procedures and hospital admissions. In spite of prevention and control measures currently adopted, it is important to monitor prevalence rates of hospital procedures for cervical cancer and its lethality, with the purpose of contributing to the planning of prevention actions. OBJECTIVE: To describe the frequency of hospital procedures for CC in Minas Gerais, and to observe their trend from 2012 to 2021. METHODS: The present work consists of a descriptive, ecological, observational study of hospital procedures for CC in Minas Gerais in 2021; and an analytical study from 2012 to 2021. RESULTS AND DISCUSSION: In Minas Gerais in 2021, 2,122 hospital procedures were performed due to CC. The most common age group was from 35- to 44-year-olds, followed by 45- to 54-year-olds. Of the total number of procedures, hospital admissions to treat cancer patients was the most common one followed by two other clinical procedures. The analysis of this time series has shown a significant decrease when procedures were observed globally (all age groups) and for 35-to-44-year-olds and 45-to-54-year-olds. CONCLUSION: In spite of the improvement trend of some indicators, when observing this time series, these indicators need to be continually monitored so that the real impacts of the proposed actions to improve the general scenario are verified, and especially the age groups who have not shown reduced rates. Interventions should be considered not only in health, but those that also cover socioeconomic and humanitarian indicators.