Circular RNAs in breast cancer diagnosis,treatment and prognosis

Breast cancer has surpassed lung cancer to become the most common malignancy worldwide.The incidence rate and mortality rate of breast cancer continue to rise,which leads to a great burden on public health.Circular RNAs(circRNAs),a new class of noncoding RNAs(ncRNAs),have been recognized as important oncogenes or suppressors in regulating cancer initiation and progression.In breast cancer,circRNAs have significant roles in tumorigenesis,recurrence and multidrug resistance that are mediated by various mechanisms.Therefore,circRNAs may serve as promising targets of therapeutic strategies for breast cancer management.This study reviews the most recent studies about the biosynthesis and characteristics of circRNAs in diagnosis,treatment and prognosis evaluation,as well as the value of circRNAs in clinical applications as biomarkers or therapeutic targets in breast cancer.Understanding the mechanisms by which circRNAs function could help transform basic research into clinical applications and facilitate the development of novel circRNA-based therapeutic strategies for breast cancer treatment.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

A Hybrid Learning Algorithm for Breast Cancer Diagnosis

In many fields, particularly that of health, the diagnosis of diseases is a very difficult task to carry out. Therefore, early detection of diseases using artificial intelligence tools can be of paramount importance in the medical field. In this study, we proposed an intelligent system capable of performing diagnoses for radiologists. The support system is designed to evaluate mammographic images, thereby classifying normal and abnormal patients. The proposed method (DiagBC for Breast Cancer Diagnosis) combines two (2) intelligent unsupervised learning algorithms (the C-Means clustering algorithm and the Gaussian Mixture Model) for the segmentation of medical images and an algorithm for supervised learning (a modified DenseNet) for the diagnosis of breast images. Ultimately, a prototype of the proposed system was implemented for the Magori Polyclinic in Niamey (Niger) making it possible to diagnose (or classify) breast cancer into two (2) classes: the normal class and the abnormal class.

Analysis of the Clinical Value of Immunohistochemical Testing in the Pathological Diagnosis of Breast Cancer

Objective:To investigate the clinical value of immunohistochemistry(IHC)detection in the pathological diagnosis of breast cancer.Methods:Eighty breast cancer patients admitted to Baoding No.1 Central Hospital from June 2022 to June 2023 were selected as study subjects.The samples were divided into a positive group(40 cases)and a negative group(40 cases)according to ER and PR test results.Immunohistochemistry was performed on all patients to compare the differences between the two groups in C-erbB-2 positive expression and axillary lymph node metastasis.Results:The positive expression rate of C-erbB-2 in the positive group(35.00%)was significantly lower than that in the negative group(80.00%),with a highly significant difference(P<0.001).The axillary lymph node metastasis rate in the positive group(40.00%)was significantly lower than that in the negative group(75.00%),with a significant difference(P<0.05).Conclusion:Immunohistochemical detection in breast cancer pathology enhances diagnostic accuracy,predicts prognosis,and supports personalized treatment by identifying ER,PR,and C-erbB-2.It is worth being widely adopted in clinical practice.

Research Progress of Ultrasound Radiomics in The Diagnosis and Treatment of Breast Cancer

With the advancement of medical research in recent years and the frequent occurrence of different types of cancer, breast cancer has gradually attracted the public’s attention. The incidence of breast cancer is rising, mainly affecting women with a high mortality rate. According to the clinical treatment effect, early diagnosis and early treatment can effectively control the mortality of breast cancer and improve patient’s quality of life. Ultrasound radiomics is an emerging field that can extract quantitative high-dimensional data from ultrasound images. Recently, ultrasound radiomics has been widely used in the clinical treatment of breast cancer. This paper analyzed the research progress of ultrasound radiomics in the diagnosis and treatment of breast cancer.

The Application Value of Ultrasound Imaging in the Differential Diagnosis of Benign and Malignant Breast Nodules of BI-RADS 3 and Above

Objective:To explore the diagnostic value of ultrasound imaging for breast nodules of breast imaging-reporting and data system(BI-RADS)category 3 and above.Methods:From June 2021 to July 2022,163 patients with breast nodules of BI-RADS 3 or above were selected as the research subjects.After pathological diagnosis,24 cases were malignant breast nodules of BI-RADS 3 or above,while 139 cases were benign breast nodules of BI-RADS 3 or above.The diagnosis rate of malignant and benign breast nodules of BI-RADS 3 or above,including 95%CI,was observed and analyzed.Results:The malignant and benign detection rates of conventional ultrasound were 88.63%and 75.00%,respectively,and the malignant and benign detection rates of ultrasound imaging were 93.18%and 87.50%,respectively,with 95%CIs greater than 0.7.Conclusion:Ultrasound imaging can help improve the diagnostic accuracy of benign and malignant breast nodules of BI-RADS 3 and above and reduce the misdiagnosis rate.

Stage at diagnosis of colorectal cancer through diagnostic route:Who should be screened?

BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.

Endoscopic ultrasonography-related diagnostic accuracy and clinical significance on small rectal neuroendocrine neoplasms

This research aimed to examine the diagnostic accuracy and clinical significance of endoscopic ultrasonography(EUS)in the context of small rectal neuroendocrine neoplasms(NENs).A total of 108 patients with rectal subepithelial lesions(SELs)with a diameter of<20 mm were included in the analysis.The diagnosis and depth assessment of EUS was compared to the histology findings.The prevalence of NENs in rectal SELs was 78.7%(85/108).The sensitivity of EUS in detecting rectal NENs was 98.9%(84/85),while the specificity was 52.2%(12/23).Overall,the diagnostic accuracy of EUS in identifying rectal NENs was 88.9%(96/108).The overall accuracy rate for EUS in assessing the depth of invasion in rectal NENs was 92.9%(78/84).Therefore,EUS demonstrates reasonable diagnostic accuracy in detecting small rectal NENs,with good sensitivity but inferior specificity.EUS may also assist physicians in assessing the depth of invasion in small rectal NENs before endoscopic excision.

Non-participation of asymptomatic candidates in screening protocols reduces early diagnosis and worsens prognosis of colorectal cancer

The Agatsuma et al’s study shows that despite the evidence of the benefits of an early colorectal cancer(CRC)diagnosis,through screening in asymptomatic subjects,up to 50%of candidates reject this option and many of those affected are diagnosed later,in advanced stages.The efficacy of screening programs has been well-established for several years,which reduces the risk of CRC morbidity and mortality,without taking into account the test used for screening,or other tools.Nevertheless,a significant proportion of patients remain unscreened,so understanding the factors involved,as well as the barriers of the population to adherence is the first step to possibly modify the participation rate.These barriers could include a full range of social and political aspects,especially the type of financial provision of each health service.In Japan,health services are universal,and this advantageous situation makes it easier for citizens to access to these services,contributing to the detection of various diseases,including CRC.Interestingly,the symptomatic CRC group had a lower early-stage diagnosis rate than the patients detected during follow-up for other comorbidities,and symptomatic and cancer screening groups showed similar early-stage diagnosis.

Early diagnosis of pancreatic cancer: Shedding light on an unresolved challenge

Diagnosing early-stage pancreatic cancer(PC)remains a clinical challenge.Hence,studying novel imaging aspects that could enhance the diagnostic accuracy of malignant pancreatic precursor lesions is imperative.This article aims to un-derscore the promising role of emerging imaging aspects that may facilitate the earlier diagnosis of PC,thereby improving its management and prognosis.

Mixed neuroendocrine non-neuroendocrine neoplasms in gastroenteropancreatic tract

Mixed neuroendocrine non-neuroendocrine neoplasms(MiNENs)are a hetero-geneous group of malignant neoplasms that can settle in the gastroenteropan-creatic tract.They are composed of a neuroendocrine(NE)and a non-NE compo-nent in at least 30%of each tumour.The non-NE component can include different histological combinations of glandular,squamous,mucinous and sarcomatoid phenotypes,and one or both of the components can be low-or high grade malignant.Recent changes in the nomenclature of these neoplasms might lead to great deal of confusion,and the lack of specific clinical trials is the main reason why their management is difficult.The review aims to clarify the definition of MiNEN and analyze available evidence about their diagnosis and treatment options according to their location and extension through careful analysis of the available data.It would be important to reach a general consensus on their diagnosis in order to construct a classification that remains stable over time and facilitates the design of clinical trials that,due to their low incidence,will require long recruitment periods.

Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography

BACKGROUND Solid pseudopapillary neoplasms of the pancreas(SPN)share similar imaging findings with pancreatic ductal adenocarcinoma with cystic changes(PDAC with cystic changes),which may result in unnecessary surgery.AIM To investigate the value of computed tomography(CT)in differentiation of SPN from PDAC with cystic changes.METHODS This study retrospectively analyzed the clinical and imaging findings of 32 patients diagnosed with SPN and 14 patients diagnosed with PDAC exhibiting cystic changes,confirmed through pathological diagnosis.Quantitative and qualitative analysis was performed,including assessment of age,sex,tumor size,shape,margin,density,enhancement pattern,CT values of tumors,CT contrast enhancement ratios,“floating cloud sign,”calcification,main pancreatic duct dilatation,pancreatic atrophy,and peripancreatic invasion or distal metastasis.Multivariate logistic regression analysis was used to identify relevant features to differentiate between SPN and PDAC with cystic changes,and receiver operating characteristic curves were obtained to evaluate the diagnostic performance of each variable and their combination.RESULTS When compared to PDAC with cystic changes,SPN had a lower age(32 years vs 64 years,P<0.05)and a slightly larger size(5.41 cm vs 3.90 cm,P<0.05).SPN had a higher frequency of“floating cloud sign”and peripancreatic invasion or distal metastasis than PDAC with cystic changes(both P<0.05).No significant difference was found with respect to sex,tumor location,shape,margin,density,main pancreatic duct dilatation,calcification,pancreatic atrophy,enhancement pattern,CT values of tumors,or CT contrast enhancement ratios between the two groups(all P>0.05).The area under the receiver operating characteristic curve of the combination was 0.833(95%confidence interval:0.708-0.957)with 78.6%sensitivity,81.3%specificity,and 80.4%accuracy in differentiation of SPN from PDAC with cystic changes.CONCLUSION A larger tumor size,“floating cloud sign,”and peripancreatic invasion or distal metastasis are useful CT imaging features that are more common in SPN and may help discriminate SPN from PDAC with cystic changes.

Synchronous multiple primary malignant neoplasms in breast,kidney,and bilateral thyroid:A case report

BACKGROUND Multiple primary malignant neoplasms(MPMNs)are rare,while synchronous MPMNs(SMPMNs)are even less common.Owing to the progression of medical technology and the extension of life expectancy,its incidence is gradually increasing.CASE SUMMARY Although reports of breast and thyroid dual cancers are common,cases of an additional diagnosis of kidney primary cancer within the same individual are rare.CONCLUSION We present a case of simultaneous MPMN of three endocrine organs,reviewing the relevant literature to enhance our understanding of SMPMNs while emphasizing the increasingly important need for accurate diagnosis and multidisciplinary management whenever this challenging situation arises.

SNSVM:SqueezeNet-Guided SVM for Breast Cancer Diagnosis

Breast cancer is a major public health concern that affects women worldwide.It is a leading cause of cancer-related deaths among women,and early detection is crucial for successful treatment.Unfortunately,breast cancer can often go undetected until it has reached advanced stages,making it more difficult to treat.Therefore,there is a pressing need for accurate and efficient diagnostic tools to detect breast cancer at an early stage.The proposed approach utilizes SqueezeNet with fire modules and complex bypass to extract informative features from mammography images.The extracted features are then utilized to train a support vector machine(SVM)for mammography image classification.The SqueezeNet-guided SVMmodel,known as SNSVM,achieved promising results,with an accuracy of 94.10% and a sensitivity of 94.30%.A 10-fold cross-validation was performed to ensure the robustness of the results,and the mean and standard deviation of various performance indicators were calculated across multiple runs.This model also outperforms state-of-the-art models in all performance indicators,indicating its superior performance.This demonstrates the effectiveness of the proposed approach for breast cancer diagnosis using mammography images.The superior performance of the proposed model across all indicators makes it a promising tool for early breast cancer diagnosis.This may have significant implications for reducing breast cancer mortality rates.

Breast Cancer Diagnosis Using Artificial Intelligence Approaches: A Systematic Literature Review

One of the most prevalent cancers in women is breast cancer.Early and accurate detection can decrease the mortality rate associated with breast cancer.Governments and health organizations emphasize the significance of early breast cancer screening since it is associated to a greater variety of available treatments and a higher chance of survival.Patients have the best chance of obtaining effective treatment when they are diagnosed early.The detection and diagnosis of breast cancer have involved using various image types and imaging modalities.Breast“infrared thermal”imaging is one of the imaging modalities.,a screening instrument used to measure the temperature distribution of breast tissue,and even though it has not been used as extensively as mammography it demonstrated encouraging outcomes when utilized for early detection.It also has several advantages,as it is safe,painless,non-invasive,and inexpensive.The literature showed that the use of thermal images with deep neural networks improved the accuracy of early diagnosis of breast malformations.Therefore,in this paper,we aim to provide a systematic review of research efforts and state-of-the-art studies in the domain of breast cancer detection using AI techniques.The review highlighted different issues,such as using different imaging modalities and deep attention mechanisms with deep learning(DL),which proved to enhance detection accuracy.

A Novel Method for Diagnosis of Breast Cancer Tumors Based on Random Forest

GLOBOCAN 2020 cancer data shows that female breast cancer has become the most common cancer over lung cancer for the first time. As a disease threatening the life safety of women all over the world, how to improve the accuracy of breast cancer diagnosis and help patients get treatment as early as possible is of great importance. This paper introduces a new random forest-based breast cancer diagnosis method (NRFM), using the average radius, average texture, average circumference and other 30 indicators in the nucleus of breast mass as characteristics, to diagnose the benign and malignant breast cancer. NRFM proposed to randomly miss a certain percentage of breast cancer data, using random forest regression to fill in the experiment proved that using the method proposed in this paper, when the proportion of missing data reached 50%, the accuracy of breast cancer diagnosis will be as high as 96.85%. Experiments show that NRFM is easy to understand, convenient to operate, and has practical application value, which can assist doctors to improve the accuracy of breast cancer diagnosis.

Pre-Trained Deep Neural Network-Based Computer-Aided Breast Tumor Diagnosis Using ROI Structures

Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives training feature samples that make closer isolation toward the infection part.Hence,it is expensive due to a metaheuristic search of features occupying the global region of interest(ROI)structures of input images.Thus,it may lead to the high computational complexity of the pre-trained DNN-based CABTD method.This paper proposes a novel ensemble pretrained DNN-based CABTD method using global-and local-ROI-structures of B-mode ultrasound images.It conveys the additional consideration of a local-ROI-structures for further enhan-cing the pretrained DNN-based CABTD method’s breast tumor diagnostic performance without degrading its visual quality.The features are extracted at various depths(18,50,and 101)from the global and local ROI structures and feed to support vector machine for better classification.From the experimental results,it has been observed that the combined local and global ROI structure of small depth residual network ResNet18(0.8 in%)has produced significant improve-ment in pixel ratio as compared to ResNet50(0.5 in%)and ResNet101(0.3 in%),respectively.Subsequently,the pretrained DNN-based CABTD methods have been tested by influencing local and global ROI structures to diagnose two specific breast tumors(Benign and Malignant)and improve the diagnostic accuracy(86%)compared to Dense Net,Alex Net,VGG Net,and Google Net.Moreover,it reduces the computational complexity due to the small depth residual network ResNet18,respectively.

Current perspectives on pancreatic serous cystic neoplasms:Diagnosis, management and beyond

Pancreatic cystic neoplasms have been increasingly recognized recently. Comprising about 16% of all resected pancreatic cystic neoplasms, serous cystic neoplasms are uncommon benign lesions that are usually asymptomatic and found incidentally. Despite overall low risk of malignancy, these pancreatic cysts still generate anxiety, leading to intensive medical investigations with considerable financial cost to health care systems. This review discusses the general background of serous cystic neoplasms, including epidemiology and clinical characteristics, and provides an updated overview of diagnostic approaches based on clinical features, relevant imaging studies and new findings that are being discovered pertaining to diagnostic evaluation. We also concisely discuss and propose management strategies for better quality of life.

New insights in diagnosis and treatment of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms(GEP-NENs)are rare epithelial neoplasms derived from pluripotent endocrine cells along the gastrointestinal tract and pancreas.GEP-NENs are classified into well-differentiated neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas.Despite overlapping morphological features,GEP-NENs vary in molecular biology,epigenetic,clinical behavior,treatment response,and prognosis features and remain an unmet clinical challenge.In this review,we introduce recent updates on the histopathologic classification,including the tumor grading and staging system,molecular genetics,and systemic evaluation of the diagnosis and treatment of GEP-NENs at different anatomic sites,together with some insights into the diagnosis of challenging and unusual cases.We also discuss the application of novel therapeutic approaches for GEP-NENs,including peptide receptor radionuclide therapy,targeted therapy,and immunotherapy with immune checkpoint inhibitors.These findings will help improve patient care with precise diagnosis and individualized treatment of patients with GEP-NENs.

Endoscopic techniques for diagnosis and treatment of gastroentero-pancreatic neuroendocrine neoplasms:Where we are

BACKGROUND The correct localization of the primary tumor site and a complete histological diagnosis represent the milestones for the proper management of gastro-enteropancreatic neuroendocrine neoplasms(GEP-NENs).AIM To analyze current evidence on the role of endoscopy in the diagnosis/treatment of GEP-NENs.METHODS An extensive bibliographical search was performed in PubMed to identify guidelines and primary literature(retrospective and prospective studies,systematic reviews,case series)published in the last 15 years,using both medical subject heading(MeSH)terms and free-language keywords:gastro-enteropancreatic neuroendocrine neoplasms;endoscopy;ultrasound endoscopy;capsule endoscopy;double-balloon enteroscopy;diagnosis;therapy;staging.RESULTS In the diagnostic setting,endoscopic ultrasonography(EUS)represents the diagnostic gold standard for pancreatic NENs and the technique of choice for the locoregional staging of gastric,duodenal and rectal NENs.The diagnosis of small bowel NENs(sbNENs)has been improved with the advent of video capsule endoscopy and double-balloon enteroscopy,which allow for direct visualization of the entire small bowel;however,data regarding the efficacy/safety of these techniques in the detection of sbNENs are scanty and often inconclusive.From a therapeutic point of view,endoscopic removal is the treatment of choice for the majority of gastric NENs(type 1/2),for well-differentiated localized nonmetastatic duodenal NENs<1 cm,confined to the submucosa layer and for<10 mm,stage T1–T2,rectal NENs.EUS-guided pancreatic locoregional ablative treatments have been proposed in recent studies with promising results in order to control symptoms or reduce tumor burden in selected patients.CONCLUSION Standard axial endoscopy and EUS still play a pivotal role in several GEP-NENs.Advanced techniques for increasing the rate of R0 resection should be reserved for high-volume referral centers.