Risultati per: Indicazioni per gli screening oncologici

Circulation, Volume 150, Issue Suppl_1, Page A4137945-A4137945, November 12, 2024. Background:Juvenile sudden cardiac death (SCD) has high impact on the family and society of the victim. While SCD screening programmes are effective in athletes, most (70-80%) young non-athletes individuals are not routinely screened.Research question:We hypothesized that a low-cost screening program may early identify subjects at risk of juvenile SCD, even in non-athletes.Goals:To evaluate the prevalence of SCD-related abnormal findings and, ultimately, to test the effectiveness of a screening programme in high schools.Methods:Between April 2023 and June 2024, high school individuals were enrolled in a screening programme in Tuscany (Pisa, Lucca and Livorno), based on a questionnaire investigating family history of juvenile SCD or diseases predisposing to SCD and symptoms (syncope, palpitations, chest pain), and digitally recorded electrocardiograms (ECGs). In case of abnormal findings, second-line investigations locally (echocardiography, Holter ECG monitoring and/or exercise testing) or third-line investigations at Fondazione Monasterio, Pisa, Italy (cardiac MRI, genetics or electrophysiological testing) were planned. Only preliminary results of the first-line screening are hereby reported.Results:We have currently enrolled 872 individuals (age 17.1±1.8 years, 481 [55%] males, 288 [33%] smokers, 102 [11.7%] recreational drugs users, and 645 [74%] non-competitive athletes). At questionnaires, 56 individuals (6.4%) had a family history of SCD, 32 (3.7%) a first-degree relative with cardiomyopathy, and 13 (1.5%) with channelopathy. As for symptoms, 21 participants (2.4%) reported chest pain or 26 (3%) syncope during exertion, while 90 (10.3%) paroxysmal palpitations. At ECG, we found 2 cases (0.2%) with a type-2 Brugada pattern, 1 female case (0.1%) with prolonged QTc interval (QTc 480 ms), 20 cases (2.3%) with V1-V3 T wave inversion (age > 16 years), 18 cases (2%) of left ventricular hypertrophy (non-athletes), and 4 cases (0.5%) with atypical ventricular ectopy. After the first-line screening, 61 (7%) and 10 (1.2%) individuals were referred to second and third-line investigations, which are currently ongoing.Conclusions:We hereby propose a screening model in high schools that includes specific health questionnaires and digitally recorded ECGs. From preliminary analyses, this approach seems sensitive enough to be tested as a model to favour the early diagnosis of diseased conditions associated with juvenile SCD in the general population.

Circulation, Volume 150, Issue Suppl_1, Page A4137986-A4137986, November 12, 2024. Background:Clinical trial screening is labor-intensive, time-consuming, and error prone. We have developed RECTIFIER, an AI-based clinical trial screening tool, to enhance the efficiency and accuracy of patient recruitment. This study aims to evaluate RECTIFIER’s effectiveness compared to manual screening in a randomized implementation study.Methods:This study was designed as an implementation study as part of an active heart failure trial named COPILOT-HF (NCT05734690). Potential eligible patients were identified via a structured electronic medical record query and randomized to be screened for clinical trial eligibility either by RECTIFIER or manually by clinical staff. The outcome measures included the number of patients contacted, and the number of patients reached for clinical trial enrollment. Data was collected over a period of 3 months.Results:A total of 3834 patients were included in the study, with 1919 patients randomized to the RECTIFIER group and 1915 patients to the manual screening group (Figure). Study staff could manually screen only 1367 patients at the end of the 3-month period. RECTIFIER identified more eligible patients compared to manual screening (833[43.4%] vs. 284[14.8%], p

Circulation, Volume 150, Issue Suppl_1, Page A4137770-A4137770, November 12, 2024. Background:Metabolic syndrome is a cluster of conditions that increase the risk of heart disease and diabetes. Early identification and management are crucial, particularly in economically challenged regions where access to healthcare may be limited.Research Questions/Hypothesis:User-friendly self-report data accurately predict metabolic outcomes.Aims:To develop and validate nomograms for individualized estimation of metabolic syndrome risk.Methods:Data from 521 college students (60.1% aged 17-20 years; 68.7% female; 28.0% white) were collected in 2022/2023 from two Brazilian cities. These cities are located in the country’s poorest states, with Gini indices of 0.56 and 0.43. The potential predictors include demographic and economic variables, school-related factors, behaviors, and body weight. Based on predictors for abdominal obesity identified through multilevel logistic regression, we created a nomogram model. We performed the Hosmer-Lemeshow test to assess model calibration and used a bootstrapping approach (B = 150) for internal validation. To evaluate external validity, we assessed metabolic syndrome in a subset of 375 students. The area under the receiver operating characteristic curve (AUROC), with a threshold of 0.70, was used to evaluate the model’s discrimination accuracy.Results:We identified 114 (23.0%) college students who were abdominally obese. We found ten variables associated with the primary outcome: age, biological sex, physical education facilities, enrollment in sports competition (during elementary school); grade retention, preferred subject, physical education classes per week; enrollment in sports training (during secondary school); adherence of 24-hour movement behaviors and body weight. The proposed nomogram showed acceptable performance in the AUROC (0.94 [95% CI: 0.92-0.96). The calibration assessment indicated reasonable consistency of our model (p > 0.05). In the internal validation, we observed a decreased predictive capability (AUROC = 0.86).Conclusion:The 24h-MESYN risk score offers an effective self-screening tool for college students from diverse racial and ethnic backgrounds in economically challenged regions to assess their risk of developing metabolic syndrome.

Circulation, Volume 150, Issue Suppl_1, Page A4145524-A4145524, November 12, 2024. Introduction:White-coat hypertension (WCH) and masked hypertension (MH) complicate accurate blood pressure (BP) monitoring. While ambulatory BP monitoring (ABPM) is effective, its high cost and limited availability are significant barriers.Hypothesis:We hypothesized that a machine learning (ML) model using clinical data from a single outpatient visit could accurately predict WCH and MH.Aims:This study aimed to develop and validate ML-based prediction models for WCH and MH using accessible clinical data to improve diagnostic efficiency and accessibility.Methods:We enrolled patients from two hypertension cohorts, after excluding those with incomplete data. Patients were classified by office BP and ABPM readings per American Heart Association guidelines. ML models, including Multi-layer Perceptron （MLP）, Support Vector Machine (SVM), and Tabular Prior-Data Fitted Network (Tab-PFN), were developed. Input parameters included demographic data (age, gender, height, weight, smoker), and office BP (OBP) and heart rate measurements. Principal Component Analysis (PCA), kernel PCA (kPCA), or t-distributed stochastic neighbor embedding (t-SNE) were used to improve class separability.Results:The study population comprised 1481 participants with a mean age of 47.6 years (SD 13.6), 65% of whom were male and 20.1% were smokers. OBP measurements showed a mean systolic BP (SBP) of 128.7 mmHg (SD 15.4) and a mean diastolic BP (DBP) of 84.2 mmHg (SD 11.6). ABPM showed a mean 24-hour systolic BP of 122.5 mmHg (SD 11.8) and diastolic BP of 79.3 mmHg (SD 10.1). The inclusion of demographic and OBP data, along with advanced resampling and dimensionality reduction techniques, significantly improved the model’s predictive ability. The final TabPFN model achieved the best performance with recall, precision, F1 score, and accuracy of 0.747, 0.931, 0.829, and 0.807 for WCH, and 0.713, 0.954, 0.816, and 0.907 for MH.Conclusion:Our ML-based model effectively predicts WCH and MH using accessible clinical data, offering a cost-effective alternative before applying ABPM.

Circulation, Volume 150, Issue Suppl_1, Page A4141112-A4141112, November 12, 2024. Background:It is estimated that Peripheral Artery Disease (PAD) affects between 8.5 and 12 million Americans and its prevalence among adults over 40 years of age is increasing. PAD disproportionately affects Black Americans who, at any age, are twice as likely to experience PAD as their white counterparts but are less likely to be screened and benefit from early diagnosis and treatment.Research Questions/Hypothesis:Despite the high prevalence of PAD and the importance of early intervention, screening for PAD remains limited and/or underutilized particularly in primary care settings where most cases of PAD can be identified. This study sought to understand provider knowledge of PAD, associated risk factors, treatment, understanding of disparities in PAD and barriers and facilitators of PAD screening. It was hypothesized that limited resources, lack of awareness on the part of providers and patients, limitations of training in vascular medicine, and other issues are contributing to PAD morbidity and mortality, particularly among Black and Hispanic populations.Methods:Because no current PAD survey was found in the literature, a survey for providers to determine their knowledge, attitude, and beliefs about PAD and the importance and process of PAD screening for patients at risk was developed. The survey was administered to CommonSpirit Health providers in Sacramento, CA between December 2023- January 2024. Specialties engaged in the survey (N=145) included primary care, endocrine, nephrology, cardiology and podiatry providers.Results:Response rate was 21%. Of those responding, primary care was the specialty most represented(69%). A total of 65% of respondents identified medical treatment of risk factors as the primary way to treat PAD, 32% rated their knowledge of risk reduction therapies in PAD as below average, and 88% of respondents were either somewhat or not familiar with racial disparities in PAD. 24% of respondents identified the ‘lack of knowledge of PAD management guidelines’ as the most important barrier to their patients with PAD not receiving risk reduction therapies.Conclusions:Initial survey of providers identifies lack of knowledge as a key indicator of PAD screening practices, including knowledge on racial disparities in PAD. These identified gaps can inform targeted interventions to improve screening, early detection and treatment of PAD.

Circulation, Volume 150, Issue Suppl_1, Page A4140494-A4140494, November 12, 2024. Background:Primary care after pregnancy is recommended, especially for individuals with recent adverse pregnancy outcomes (APOs, such as preeclampsia or gestational diabetes), who are at increased risk for future heart disease. Health-related social needs (HRSNs) are recognized barriers to care, yet their pregnancy-related prevalence and associations with care are unknown. We sought to (1) describe the pregnancy-related prevalence of HRSNs, and (2) assess associations between pregnancy-related HRSNs and subsequent linkage to primary care.Methods:We analyzed electronic health record data for individuals with prenatal care and delivery (2018-2021) at our urban safety-net hospital. HRSNs were assessed via a routine screener, and we summarized individual responses during pregnancy through 6 weeks post partum as: any positive, all negative, or never screened. Postpartum linkage to primary care was defined as a completed primary care visit after 6 weeks through 1 year post partum. We analyzed the prevalence of HRSNs and their associations with linkage to primary care, using adjusted log-linked binomial regression models. In stratified models we assessed for effect modification by APO history and other variables.Results:Of 4941 individuals in our sample, 53% identified as Black non-Hispanic and 21% as Hispanic, 68% were publicly insured, and 93% completed ≥1 HRSN screening. Nearly 1 in 4 screened positive for any HRSN, most often food insecurity (14%) or housing instability (12%), and 53% linked to primary care. Compared with those who screened negative for all HRSNs (n=3491), linkage to primary care was similar among those who screened positive for any HRSNs (n=1079; adjusted risk ratio, aRR 1.04, 95% confidence interval, CI: 0.98-1.10) and lower among those never screened (n=371; aRR 0.77, 95% CI: 0.68-0.86). We found no evidence of effect modification by APO history, race/ethnicity, insurance, language, or Covid-19 pandemic exposure.Conclusions:In this diverse postpartum sample, we identified a 24% prevalence of pregnancy-related HRSNs and 53% subsequent linkage to primary care. Linkage to primary care was not associated with HRSN screening result (positive versus negative) but was significantly negatively associated with being missed by HRSN screening. Further research is needed to better understand HRSN screening practices and who is missed by screening, and to identify modifiable barriers to postpartum primary care especially after APOs.

Circulation, Volume 150, Issue Suppl_1, Page A4131622-A4131622, November 12, 2024. Introduction:Chronic liver disease affects more than 1.5 billion adults worldwide, but the majority of cases are asymptomatic and undiagnosed. Echocardiography is broadly performed and visualizes the liver; however, this information is not diagnostically leveraged.Hypothesis and Aims:We hypothesized that a deep-learning algorithm can detect chronic liver diseases using subcostal echocardiography images that contains hepatic tissue. To develop and evaluate a deep learning algorithm on subcostal echocardiography videos to enable opportunistic screening for chronic liver disease.Methods:We identified adult patients who received echocardiography and abdominal imaging (either abdominal ultrasound or abdominal magnetic resonance imaging) with ≤30 days between tests. A convolutional neural network pipeline was developed to predict the presence of cirrhosis or steatotic liver disease (SLD) using echocardiogram images. The model performance was evaluated in a held-out test dataset, dataset in which diagnosis was made by magnetic resonance imaging, and external dataset.Results:A total of 2,083,932 echocardiography videos (51,608 studies) from Cedars-Sinai Medical Center (CSMC) were used to develop EchoNet-Liver, an automated pipeline that identifies high quality subcostal images from echocardiogram studies and detects presence of cirrhosis or SLD. In a total of 11,419 quality-controlled subcostal videos from 4,849 patients, a chronic liver disease detection model was able to detect the presence of cirrhosis with an AUC of 0.837 (0.789 – 0.880) and SLD with an AUC of 0.799 (0.758 – 0.837). In a separate test cohort with paired abdominal MRIs, cirrhosis was detected with an AUC of 0.726 (0.659-0.790) compared to MR elastography and SLD was detected with an AUC of 0.704 (0.689-0.718). In the external test cohort of 66 patients (n = 130 videos), the model detected cirrhosis with an AUC of 0.830 (0.738 – 0.909) and SLD with an AUC of 0.768 (0.652 – 0.875).Conclusions:Deep learning assessment of clinically indicated echocardiography enables opportunistic screening of SLD and cirrhosis. Application of this algorithm may identify patients who may benefit from further diagnostic testing and treatment for hepatic disease.

Introduction
The prevalence of mental health problems is increasing worldwide, particularly in the vulnerable group of older people. The limited availability of therapists, long wait periods and increasing shortage of healthcare resources limit adequate care. As a result, digital applications are becoming more commonplace as an alternative to human therapists. However, these tend to be used by younger people with higher education, digital health literacy and experience. In Germany, applications that are approved by the health authorities, so-called digital health applications (DiGAs), can be prescribed by physicians and psychotherapists. It remains unclear to the extent older people are experienced with, are willing and can use a DiGA. Therefore, this research aims to identify specific challenges of older people’s accessibility, user experience and engagement with DiGA for depressive disorders. The DiGA4Aged project consists of: (1) a pilot study on usability, (2) a screening study on potential participants for a randomised controlled trial (RCT) evaluating the digital experience of the target population and (3) an RCT to test the effectiveness of a digital nurse as individualised user support in the intervention group. This paper focuses on the pilot study and the screening study.

Methods and analysis
The instrumental components in preparing for the RCT are a mixed-method pilot and observational quantitative screening study, which are described in this manuscript. The pilot study includes questionnaires (covering sociodemographic data, user experience, health literacy, electronic health literacy, media affinity, severity of depression and perceived usability of DiGA), a concurrent think aloud method and a semistructured interview to evaluate two applications with regard to their usability for, acceptance by and needs of older people. The observational screening study collects data of older patients consecutively admitted to an acute care geriatric hospital ward using various questionnaires to identify which clinical and medical factors are associated with the access to, experience with and (non-)use of digital media. Data from the comprehensive geriatric assessment is collected as well as data on their digital media experience and digital health literacy.

Ethics and dissemination
The overall project DiGA4Aged received ethical approval on 17 November 2023 from the ethics committee of the Medical Faculty of Ruhr-University Bochum (registration number 23-7901). Results will be disseminated within the scientific community via publication in peer-reviewed journals as well as presentation at national conferences. The findings from the pilot study and the observational screening study will determine the selection of the DiGA and the recruitment strategy for the subsequent RCT.

Trial registration numbers
The pilot study has been prospectively registered in the German Clinical Trials Register (DRKS00033640, registered on 18 March 2024, available from https://drks.de/search/de/trial/DRKS00033640). Likewise, the observational screening study has been prospectively registered in the German Clinical Trials Register (DRKS00032931, registered on 29 November 2023, available from https://drks.de/search/de/trial/DRKS00032931).

Objectives
To identify and map the available evidence for whether a test of handgrip strength (HGS) and/or the chair stand test (CST) have been used as screening tools for the detection of sarcopenia in elderly individuals within primary care settings.

Design
This study was designed as a scoping review, in accordance with the methodological framework for scoping reviews, developed by Arksey and O’Malley, and using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews.

Data sources
A literature search was conducted to identify relevant articles listed in PubMed and Scopus databases up to 16 October 2023.

Eligibility criteria
Studies including individuals aged ≥60 years who had undergone assessments of HGS and/or the CST in primary care settings were included.

Data extraction and synthesis
Following the article selection process, based on predetermined criteria for inclusion and exclusion, the selected articles were analysed regarding population demographics, the setting in which the research was conducted, the study design, used diagnostic tools and reported results.

Results
The search yielded 282 unique articles, of which 7 were included in the final analysis. All seven included articles had a cross-sectional study design, whereof one also had a longitudinal 3-year follow-up. The number of participants ranged from 75 to 719. Three of the articles used the diagnostic criteria presented by European Working Group on Sarcopenia in Older People (EWGSOP), two used the criteria by Asian Working Group for Sarcopenia 2019, one used the EWGSOP2 criteria and one applied both the EWGSOP and EWGSOP2 criteria to their data. All the articles used HGS to assess muscle strength. CST was not used for this purpose in any of the articles, although it was used to estimate physical performance or as part of the short physical performance battery. The prevalence of sarcopenia in the included articles was 12.0%–20.7%, while the prevalence of possible sarcopenia was 69.9%–73.3% and that of probable sarcopenia was 25.5%–94%.

Conclusion
None of the included articles aimed to study a test of HGS and/or the CST as screening tools for the detection of sarcopenia. However, four of the articles diagnosed possible or probable sarcopenia by using a test of HGS and/or the CST among elderly patients in a primary care setting. There is a need for more research to elucidate whether a test of HGS and/or the CST might be used for screening of sarcopenia in primary care.

Background
Child maltreatment (CM) encompasses physical, emotional or sexual abuse, physical or emotional/psychological neglect or intimate partner (or domestic) violence and is associated with adverse cognitive, behavioural, physical and social outcomes that often continue shaping adulthood. The early and valid detection of CM is essential to initiate treatment and intervention as well as to avoid continued violence against the child. Various occupational groups, such as healthcare providers, teachers, social workers, psychotherapists and others, encounter maltreated children in their professional settings. Systematic reviews on instruments to assess suspected CM often report on retrospective measurement via caregiver’s or child’s self-report and are frequently limited to the health system as a setting. The purpose of this Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant systematic review is to synthesise the evidence on psychometric properties of instruments to assess suspected CM at the presentation to a broad range of different occupational groups who work with children inside and outside the healthcare system.

Method
A systematic search will be performed in Scopus, PsycInfo, Medline and Web of Science with no limit on the earliest publication until January 2022. Eligibility criteria include studies that investigate psychometric properties of instruments to assess suspected CM in children and adolescents under 18 years by a professional proxy. After the independent screening of studies by two reviewers, quality assessment and data extraction will be performed using an adaptation of the COnsensus-based Standards for the selection of health Measurement INstruments Risk of Bias checklist, Strengthening the Reporting of Observational Studies in Epidemiology: Explanation and Elaboration report and Downs and Black checklist for measuring study quality. Screening, quality assessment and data extraction will be done using Covidence. The results will be presented in narrative form and, if adequate, a meta-analysis will be performed.

Discussion
This review aims to give an overview of the psychometric properties of different instruments designed to screen suspected CM by professional proxies. The results will be of interest to different occupational groups who need information about methodological quality and characteristics of instruments to make decisions about the best-suited tool for a specific purpose. Furthermore, the results of this review will support the development of novel instruments and might improve the existing ones.

Ethics and dissemination
Ethics approval will not be required. The results of this systematic review will be submitted for publication in a peer-reviewed journal.

PROSPERO registration number
CRD42022297997.

Objective
To evaluate the cost-effectiveness of risk-stratified hepatocellular carcinoma (HCC) screening in diabetic patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

Design
A state-transition model from a healthcare payer perspective on a lifetime horizon.

Setting
Japan.

Population
A hypothetical cohort of 50-year-old diabetic patients with MASLD risk-stratified according to degree of obesity and progression to cirrhosis. Metabolic dysfunction-associated steatotic liver (MASL), metabolic dysfunction-associated steatohepatitis (MASH) and MASH cirrhosis are progressive manifestations of this specific type of liver disease.

Intervention
Abdominal ultrasound (US), US with alpha-fetoprotein (AFP), US with AFP and lectin-reactive alpha-fetoprotein (AFP-L3), CT, extracellular contrast-media-enhanced MRI (ECCM-MRI), gadoxetic acid-enhanced MRI (EOB-MRI) and no screening.

Main outcome measure
Costs, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), early-stage HCC cases, advanced-stage HCC cases and HCC-related deaths.

Results
EOB-MRI is the most cost-effective screening method for non-obese diabetic patients with MASH cirrhosis and for obese diabetic patients with MASH and MASH cirrhosis. Cost-effectiveness was sensitive to HCC incidence in non-obese diabetic patients with MASH cirrhosis and obese diabetic patients with MASH, and the adherence rate of HCC screening in obese diabetic patients with MASH. When the semiannual HCC incidence was between 0.008 and 0.0138 in non-obese diabetic patients with MASH cirrhosis, US with AFP was more cost-effective than EOB-MRI. Cost-effectiveness acceptability curves showed that EOB-MRI was 50.7%, 96.0% and 99.9% cost-effective in obese diabetic patients with MASH and non-obese diabetic patients with MASH cirrhosis, and obese diabetic patients with MASH cirrhosis at a willingness-to-pay level of $50 000 per QALY gained. Compared with no screening in 100 000 non-obese diabetic patients with MASH cirrhosis and obese diabetic patients with MASH cirrhosis, EOB-MRI reduced total costs by US$69 million and by US$142 million, increased lifetime effectiveness by 12 546 QALYs and by 15 815 QALYs, detected 17 873 and 21 014 early-stage HCC cases, and averted 2068 and 2471 HCC-related deaths, respectively.

Conclusions
Of all HCC screening methods for diabetic patients with MASH cirrhosis, EOB-MRI yields the greatest cost-saving with the highest QALYs, detects the greatest number of early-stage HCC cases and averts the greatest number of advanced-stage HCC cases and HCC-related deaths. The findings provide important insights for the precise implementation of risk-stratified HCC surveillance to reduce morbidity and mortality and improve the quality of life in diabetic patients with MASLD.

Presentato alla Camera il policy brief di Europa Donna Italia

Universal screening of syphilis in emergency departments (EDs) could increase case detection, a recent investigation in Open Forum Infectious Diseases suggests.

Colpito almeno il 7% italiani, solo il 10% dei pazienti lo sa

Introduction
ISMiHealth is a clinical decision support system, integrated as a software tool in the electronic health record system of primary care, that aims to improve the screening performance on infectious diseases and female genital mutilation (FGM) in migrants. The aim of this study is to assess the health impact of the tool and to perform a process evaluation of its feasibility and acceptability when implemented in primary care in Catalonia (Spain).

Methods and analysis
This study is a cluster randomised control trial where 35 primary care centres in Catalonia, Spain will be allocated into one of the two groups: intervention and control. The health professionals in the intervention centres will receive prompts, through the ISMiHealth software, with screening recommendations for infectious diseases and FGM targeting the migrant population based on an individualised risk assessment. Health professionals of the control centres will follow the current routine practice.
A difference in differences analysis of the diagnostic rates for all aggregated infections and each individual condition between the intervention and control centres will be performed. Mixed-effects logistic regression models will be carried out to identify associations between the screening coverage and predictor factors. In addition, a process evaluation will be carried out using mixed methodology.

Ethics and dissemination
The study protocol has been approved by the institutional review boards at Hospital Clínic (16 June 2022, HCB/2022/0363), Clinical Research Ethics Committee of the Primary Care Research Institute IDIAPJGol (22 June 2022, 22/113-P) and the Almería Research Ethics Committee (27 July 2022, EMC/apg). The study will follow the tenets of the Declaration of Helsinki and Good Clinical Practice. All researchers and associates signed a collaboration agreement in which they undertake to abide by good clinical practice standards.
Findings will be disseminated in peer-reviewed journals and communications to congresses.

Trial registration number
NCT05868005.

Introduction
Microwave imaging presents several potential advantages including its non-ionising and harmless nature. This open, multicentric, interventional, prospective, non-randomised trial aims to validate MammoWave’s artificial intelligence (AI)-based classification algorithm, leveraging microwave imaging, to achieve a sensitivity exceeding 75% and a specificity exceeding 90% in breast screening.

Methods and analysis
10 000 volunteers undergoing regular mammographic breast cancer screening will be recruited across 9 European centres and invited to participate in the clinical study, involving MammoWave testing on both breasts. MammoWave results will be checked against the reference standard, to be intended as the output of conventional breast examination path (with histological confirmation of cancer cases) with 2 years follow-up. Anonymised clinical and MammoWave’s results, including microwave images, associated features and a label provided by the AI-based classification algorithm, will be collected and stored in a dedicated electronic case report form. The prospective study will involve a comparative analysis between the output of the conventional breast examination path (control intervention) and the labels provided by MammoWave’s AI system (experimental intervention). These labels will categorise breasts into two groups: breast With Suspicious Finding, indicating the presence of a suspicious lesion or No Suspicious Finding, indicating the absence of a lesion or the presence of a low-suspicion lesion. This trial aims to provide evidence regarding the novel MammoWave’s AI system for detecting breast cancer in asymptomatic populations during screening.

Ethics and dissemination
This study was approved by the Research Ethics Committee of the Liguria Region (CET), Italy (CET-Liguria: 524/2023—DB id 13399), the Research Ethics Committee of Complejo Hospitalario de Toledo (CEIC), Spain (CEIC-1094), the National Ethics Committee for Clinical Research (CEIC), Portugal (CEIC-2311KC814), the Bioethical Committee of Pomeranian Medical University in Szczecin, Poland (KB-006/23/2024) and the Zurich Cantonal Ethics Commission, Switzerland (BASEC 2023-D0101). The findings of this study will be disseminated through academic and scientific conferences as well as peer-reviewed journals.

Trial registration number
NCT06291896.