Computer Aided Diagnosis of Colorectal Neoplasms During Colonoscopic Examination
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Neoplasms,Colon Polyp,Neoplasms
PROVIDER: 2237983 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:The purpose of this study is to assess whether computer aided technology (CAD) can help in the diagnosis of polyps found the bowel compared with visual inspection alone and therefore whether it is beneficial in helping clinicians to decide whether to remove a polyp or not. Presently, most endoscopists remove all polyps found and send them to the laboratory for testing. The number of colonoscopies is increasing, meaning that more polyps are detected and removed. This comes at a significant cost to the health service and increases the time taken to complete a colonoscopy.
| 2348616 | ecrin-mdr-crc
Project description:Multimaterials deposition, a distinct advantage in bioprinting, overcomes material's limitation in hydrogel-based bioprinting. Multimaterials are deposited in a build/support configuration to improve the structural integrity of three-dimensional bioprinted construct. A combination of rapid cross-linking hydrogel has been chosen for the build/support setup. The bioprinted construct was further chemically cross-linked to ensure a stable construct after print. This paper also proposes a file segmentation and preparation technique to be used in bioprinting for printing freeform structures.
| S-EPMC7294690 | biostudies-literature
Project description:ObjectiveOur aim was to propose a preoperative computer-aided diagnosis scheme to differentiate pancreatic serous cystic neoplasms from other pancreatic cystic neoplasms, providing supportive opinions for clinicians and avoiding overtreatment.Materials and methodsIn this retrospective study, 260 patients with pancreatic cystic neoplasm were included. Each patient underwent a multidetector row computed tomography scan and pancreatic resection. In all, 200 patients constituted a cross-validation cohort, and 60 patients formed an independent validation cohort. Demographic information, clinical information, and multidetector row computed tomography images were obtained from Picture Archiving and Communication Systems. The peripheral margin of each neoplasm was manually outlined by experienced radiologists. A radiomics system containing 24 guideline-based features and 385 radiomics high-throughput features was designed. After the feature extraction, least absolute shrinkage selection operator regression was used to select the most important features. A support vector machine classifier with 5-fold cross-validation was applied to build the diagnostic model. The independent validation cohort was used to validate the performance.ResultsOnly 31 of 102 serous cystic neoplasm cases in this study were recognized correctly by clinicians before the surgery. Twenty-two features were selected from the radiomics system after 100 bootstrapping repetitions of the least absolute shrinkage selection operator regression. The diagnostic scheme performed accurately and robustly, showing the area under the receiver operating characteristic curve = 0.767, sensitivity = 0.686, and specificity = 0.709. In the independent validation cohort, we acquired similar results with receiver operating characteristic curve = 0.837, sensitivity = 0.667, and specificity = 0.818.ConclusionThe proposed radiomics-based computer-aided diagnosis scheme could increase preoperative diagnostic accuracy and assist clinicians in making accurate management decisions.
| S-EPMC6374001 | biostudies-literature
Project description:Recent clinical trials using antibodies with low toxicity and high efficiency have raised expectations for the development of next-generation protein therapeutics. However, the process of obtaining therapeutic antibodies remains time consuming and empirical. This review summarizes recent progresses in the field of computer-aided antibody development mainly focusing on antibody modeling, which is divided essentially into two parts: (i) modeling the antigen-binding site, also called the complementarity determining regions (CDRs), and (ii) predicting the relative orientations of the variable heavy (V(H)) and light (V(L)) chains. Among the six CDR loops, the greatest challenge is predicting the conformation of CDR-H3, which is the most important in antigen recognition. Further computational methods could be used in drug development based on crystal structures or homology models, including antibody-antigen dockings and energy calculations with approximate potential functions. These methods should guide experimental studies to improve the affinities and physicochemical properties of antibodies. Finally, several successful examples of in silico structure-based antibody designs are reviewed. We also briefly review structure-based antigen or immunogen design, with application to rational vaccine development.
| S-EPMC3449398 | biostudies-literature
Project description:Rodent models of retinal angiogenesis play a pivotal role in angiogenesis research. These models are a window to developmental angiogenesis, to pathological retinopathy, and are also in vivo tools for anti-angiogenic drug screening in cancer and ophthalmic research. The mouse model of oxygen-induced retinopathy (OIR) has emerged as one of the leading in vivo models for these purposes. Many of the animal studies that laid the foundation for the recent breakthrough of anti-angiogenic treatments into clinical practice were performed in the OIR model. However, readouts from the OIR model have been time-consuming and can vary depending on user experience. Here, we present a computer-aided quantification method that is characterized by (i) significantly improved efficiency, (ii) high correlation with the established hand-measurement protocols, and (iii) high intra- and inter-individual reproducibility of results. This method greatly facilitates quantification of retinal angiogenesis while at the same time increasing lab-to-lab reproducibility of one of the most widely used in vivo models in angiogenesis research.
| S-EPMC4005267 | biostudies-literature
Project description:Virus-cell fusion is the primary means by which the human immunodeficiency virus-1 (HIV) delivers its genetic material into the human T-cell host. Fusion is mediated in large part by the viral glycoprotein 41 (gp41) which advances through four distinct conformational states: (i) native, (ii) pre-hairpin intermediate, (iii) fusion active (fusogenic), and (iv) post-fusion. The pre-hairpin intermediate is a particularly attractive step for therapeutic intervention given that gp41 N-terminal heptad repeat (NHR) and C-terminal heptad repeat (CHR) domains are transiently exposed prior to the formation of a six-helix bundle required for fusion. Most peptide-based inhibitors, including the FDA-approved drug T20, target the intermediate and there are significant efforts to develop small molecule alternatives. Here, we review current approaches to studying interactions of inhibitors with gp41 with an emphasis on atomic-level computer modeling methods including molecular dynamics, free energy analysis, and docking. Atomistic modeling yields a unique level of structural and energetic detail, complementary to experimental approaches, which will be important for the design of improved next generation anti-HIV drugs.
| S-EPMC3666032 | biostudies-literature
Project description:Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.
| S-EPMC5857607 | biostudies-literature
Project description:Computer-aided drug design (CADD) approaches are playing an increasingly important role in understanding the fundamentals of ligand-receptor interactions and helping medicinal chemists design therapeutics. About 5 years ago, we presented a chapter devoted to an overview of CADD methods and covered typical CADD protocols including structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches that were frequently used in the antibiotic drug design process. Advances in computational hardware and algorithms and emerging CADD methods are enhancing the accuracy and ability of CADD in drug design and development. In this chapter, an update to our previous chapter is provided with a focus on new CADD approaches from our laboratory and other peers that can be employed to facilitate the development of antibiotic therapeutics.
| S-EPMC9838881 | biostudies-literature
Project description:Recent data indicates limited awareness and compliance on infection prevention procedures by dental offices and by dental laboratories. Guidelines for infection prevention in dentistry have been published by Centres for Disease Control and Prevention since 2003; the section "IX-Special consideration" includes a subsection concerning the prevention in dental laboratories, but it has not been modernised in later versions to fit the needs of traditional and computer-aided technology. Traditional techniques required disinfecting items (impression, chewing waxes, and appliances) with well-suited products, which are also chosen for limiting impression changes or appliance deterioration. Effective procedures are available with difficulties. Some of these contain irritant or non-eco-friendly disinfectants. The transport of impression, to dental laboratories, is often delayed with limited precautions for limiting cross-infection. Gypsum casts are frequently contaminated mainly by bacteria and their antibiotic-resistant strains and even stored for long periods during dental implant supported restoration and orthodontic therapy, becoming a hidden source of infection. Nowadays, computer-aided design/computer-aided manufacturing technology seems to be an interesting way to promote both business and safety, being more comfortable for patients and more accurate than traditional technology. A further advantage is easier infection prevention since, for the most part, mainly digital impression and casts are not a source of cross-infection and the transport of contaminated items is reduced and limited to try-in stages. Nevertheless, a peculiar feature is that a digital electronic file is of course unalterable, but may be ruined by a computer virus. Additionally, the reconditioning of scanner tips is determinant for the optical characteristics and long term use of the scanner, but information for its reconditioning from producers is often limited. This study focuses on some critical points including (a) insufficient guidelines, (b) choice of proper procedure for scanner reconditioning, and (c) data protection in relation to patient privacy.
| S-EPMC6699473 | biostudies-other
Project description:Nowadays, colonoscopy is considered the gold standard for the detection of lesions in the colorectal mucosa. However, around 25% of polyps may be missed during the conventional colonoscopy. Based on this, new technological tools aimed to improve the quality of the procedures, diminishing the technical and operator-related factors associated with the missed lesions. These tools use artificial intelligence (AI), a computer system able to perform human tasks after a previous training process from a large dataset. The DiscoveryTM AI-assisted polyp detector (Pentax Medical, Hoya Group, Tokyo, Japan) is a newly developed detection system based on AI. It was designed to alert and direct the attention to potential mucosal lesions. According to its remarkable features, it may increase the polyp and adenoma detection rates (PDR and ADR, respectively) and decrease the adenoma miss rate (AMR).
Based on the above, the investigators aim to assess the real-world effectiveness of the DiscoveryTM AI-assisted polyp detector system in clinical practice and compare the results between expert (seniors) and non-expert (juniors) endoscopists.
| 8858 | ecrin-mdr-crc