Improvement of early detection of breast cancer through collaborative multi-country efforts: Observational clinical study

Long-term outcomes of Türkiye's first population-based mammography screening program: a decade of breast cancer detection and survival analysis in Bahçeşehir

BACKGROUND

The Bahçeşehir population-based mammography screening program (BMSP) is an example of Türkiye's first population-based screening program. This study aims to reveal the successful implementation of population-based secreening program in one of the low- and middle-income countries, Türkiye and long-term results of patients diagnosed with breast cancer during BMSP.

METHODS

This study was conducted between 2009 and 2019, in the Bahçeşehir county of Istanbul. Women between the ages of 40 and 69 living in this region were invited every two years to undergo clinical breast examination (CBE) and mammography screening. All data was recorded in a dedicated software program. Women diagnosed with breast cancer were followed as a separate cohort.

RESULTS

During the 10-year screening period, 8,825 women were screened and 146 (1.7%) breast cancers were detected. The median age at diagnosis for these patients was 52.9 years (40-69). The risk of breast cancer was 1.39 times higher (95% CI: 1.01-1.93) in women aged ≥ 50 compared to those less than 50 years (p = 0.045). The Cox regression analysis revealed that age at first birth, and number of births were significant predictors of breast cancer risk (p < 0.001, and p = 0.011). The breast cancer rate tends to increase as the breast density category progresses from A to D (p < 0.001). The median follow-up time for 146 breast cancer patients was 95.3 months. The 10-year breast cancer specific survival rate was 85%.

CONCLUSIONS

This study demonstrates that with a committed team and sufficient infrastructure, screening mammography can be effectively carried out in Türkiye, leading to early detection and lower mortality rates. The recommended age to commence screening is 40 years old.

Value of automated breast ultrasound in screening: Standalone and as a supplemental to digital breast tomosynthesis

We aimed to determine the value of standalone and supplemental automated breast ultrasound (ABUS) in detecting cancers in an opportunistic screening setting with digital breast tomosynthesis (DBT) and compare this combined screening method to DBT and ABUS alone in women older than 39 years with BI-RADS B-D density categories. In this prospective opportunistic screening study, 3466 women aged 39 or older with BI-RADS B-D density categories and with a mean age of 50 were included. The screening protocol consisted of DBT mediolateral-oblique views, 2D craniocaudal views, and ABUS with three projections for both breasts. ABUS was evaluated blinded to mammography findings. Statistical analysis evaluated diagnostic performance for DBT, ABUS, and combined workflows. Twenty-nine cancers were screen-detected. ABUS and DBT exhibited the same cancer detection rates (CDR) at 7.5/1000 whereas DBT + ABUS showed 8.4/1000, with ABUS contributing an additional CDR of 0.9/1000. Standalone ABUS outperformed DBT in detecting 12.5% more invasive cancers. DBT displayed better accuracy (95%) compared to ABUS (88%) and combined approach (86%). Sensitivities for DBT and ABUS were the same (84%), with DBT + ABUS showing a higher rate (94%). DBT outperformed ABUS in specificity (95% vs. 88%). DBT + ABUS exhibited a higher recall rate (14.89%) compared to ABUS (12.38%) and DBT (6.03%) (p < .001). Standalone ABUS detected more invasive cancers compared to DBT, with a higher recall rate. The combined approach showed a higher CDR by detecting one additional cancer per thousand.

Addressing Global Gaps in Mammography Screening for Improved Breast Cancer Detection: A Review of the Literature

Breast cancer is the second most common cancer globally, with 2.3 million new cases annually, constituting 11.6% of all cancer cases. It is also the fourth leading cause of cancer deaths, claiming 670,000 lives a year. This high incidence of breast cancer morbidity worldwide has increased the urgent need for standardized and adequate screening methods, including clinical breast examination, self-breast examination, and mammography screening tests for non-symptomatic individuals. Mammography is considered the gold standard for breast cancer screening, with early randomized control trials showing significant reductions in mortality rates in women aged 50 and over (International Agency for Research on Cancer and American College of Radiology). Despite this, discrepancies in mammography practices across different healthcare settings regarding adherence to international standards raise concerns. A comprehensive review of the vast literature looking at the practices and norms of mammography screening worldwide highlighted several domains that present limitations to screening. These include epidemiological data deficits, lack of educational training offered to radiographers and varied image quality indices, exposure technique, method of breast compression, dose calculation, reference levels, screening frequency intervals, and diverse distribution of resources, particularly in developing countries. These factors shed light on the substantial discrepancies in the implementation and efficacy of screening programs, underscoring the necessity for future research endeavors to collaborate in creating coherent, standardized, evidence-based guidelines. Addressing these issues can enhance the feasibility, sensitivity, and accessibility of screening programs, resulting in favorable impacts on the early diagnosis and survival of breast cancer on a global scale.

The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country

AIM

We aimed to investigate the efficiency and accuracy of an artificial intelligence (AI) algorithm for detecting interval cancers in a middle-income country's national screening program.

MATERIAL AND METHODS

A total of 2,129,486 mammograms reported as BIRADS 1 and 2 were matched with the national cancer registry for interval cancers (IC). The IC group consisted of 442 cases, of which 36 were excluded due to having mammograms incompatible with the AI system. A control group of 446 women with two negative consequent mammograms was defined as time-proven normal and constituted the normal group. The cancer risk scores of both groups were determined from 1 to 10 with the AI system. The sensitivity and specificity values of the AI system were defined in terms of IC detection. The IC group was divided into subgroups with six-month intervals according to their time from screening to diagnosis: 0-6 months, 6-12 months, 12-18 months, and 18-24 months. The diagnostic performance of the AI system for all patients was evaluated using receiver operating characteristics (ROC) curve analysis. The diagnostic performance of the AI system for major and minor findings that expert readers determined was re-evaluated.

RESULTS

AI labeled 53% of ICs with the highest score of 10. The sensitivity of AI in detecting ICs was 53.7% and 38.5% at specificities of 90% and 95%, respectively. Area under the curve (AUC) of AI in detecting major signs was 0.93 (95% CI: 0.90-0.95) with a sensitivity of 81.6% and 72.4% at specificities of 90% and 95%, respectively (95% CI: 0.73-0.88 and 95% CI: 0.60-0.82 respectively) and minor signs was 0.87 (95% CI: 0.87-0.92) with a sensitivity of 70% and 53% at a specificity of 90% and 95%, respectively (95% CI: 0.65-0.82 and 95% CI: 0.52-0.71 respectively). In subgroup analysis for time to diagnosis, the AUC value of the AI system was higher in the 0-6 month period than in later periods.

CONCLUSION

This study showed the potential of AI in detecting ICs in initial mammograms and reducing human errors and undetected cancers.

Breast imaging in focus: A bibliometric overview of visual quality, modality innovations, and diagnostic performance

INTRODUCTION

Breast imaging plays a crucial role in the early detection and management of breast cancer, with visual quality, modality innovation and diagnostic performance being key factors in achieving accurate diagnoses and optimal patient outcomes. This paper presents a comprehensive bibliometric analysis of the literature on the three above elements focusing on breast imaging, aiming to uncover publication trends, identify influential works and authors, and highlight future research directions.

METHODS

We employed a methodical bibliometric approach, making use of Scopus and Web of Science (WoS) databases for gathering literatures. We planned our search strategy, concentrating on terms linked to "breast imaging," "image quality," and "diagnostic accuracy" to ensure a systematic examination of the subject. The enhanced search functions in these databases enabled us to narrow down and improve our findings, choosing only the articles, conference papers, and book sections that are most relevant. After conducting a thorough screening process to remove duplicates and evaluate significance, we utilized ScientoPy and VOSviewer software for an in-depth bibliometric analysis. This helped to explore trends in publications, patterns of citations, and thematic groups, giving us a better understanding of how the field has changed and where it currently stands. Our approach prioritized assessing methodological quality and bias in the studies we included, guaranteeing the reliability of our findings.

RESULTS

We reviewed 2984 relevant publications, revealing a consistent annual growth rate of 2.8% in breast imaging research, with the United States and Europe leading in contributions. The study found that advancements in radiological technologies and international collaboration are driving forces behind the field's expansion. Key subject areas such as 'Radiology, Nuclear Medicine, and Medical Imaging' dominated, underscoring their impact on diagnostic quality. Notable authors and institutions have been identified for their influential research, characterized by high citation metrics and significant scholarly impact.

CONCLUSION

The study shows a continuous increase in research on breast imaging, considered by new technologies and teamwork defining the present time. The assessment highlights a key move towards utilizing digital imaging methods and computational analysis, affecting the improvement of future diagnostic procedures and patients' results. The study highlights the importance of continued international collaborations to tackle the new barriers in breast imaging and make the most of technological progress.

IMPLICATIONS FOR PRACTICE

This study shows a focus on using interdisciplinary methods and cutting-edge technology in breast imaging to help healthcare professionals improve their performance and accuracy in diagnosis. Recognizing vital research and emerging trends should guide clinical guidelines, radiology training, and patient care plans to encourage the use of effective techniques and stimulate innovation in diagnostic approaches.

Effectiveness of interventions for improving timely diagnosis of breast and cervical cancers in low-income and middle-income countries: a systematic review

OBJECTIVES

To systematically synthesise available evidence on the nature and effectiveness of interventions for improving timely diagnosis of breast and cervical cancers in low and middle-income countries (LMICs).

DESIGN

A systematic review of published evidence. The review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses.

DATA SOURCES

A comprehensive search of published literature was conducted. In addition, relevant grey literature sources and bibliographical references of included studies were searched for potentially eligible evidence.

STUDY SELECTION

Studies published between January 2010 and November 2020 were eligible for inclusion. To be eligible, studies had to report on interventions/strategies targeted at women, the general public or healthcare workers, aimed at improving the timely diagnosis of breast and/or cervical cancers in LMIC settings.

DATA EXTRACTION AND SYNTHESIS

Literature search, screening, study selection, data extraction and quality appraisal were conducted by two independent reviewers. Evidence was synthesised and reported using a global taxonomy framework for early cancer diagnosis.

RESULTS

From the total of 10 593 records identified, 21 studies conducted across 20 LMICs were included in this review. Most of the included studies (16/21) focused primarily on interventions addressing breast cancers; two focused on cervical cancer while the rest examined multiple cancer types. Reported interventions targeted healthcare workers (12); women and adolescent girls (7) and both women and healthcare workers (3). Eight studies reported on interventions addressing access delays; seven focused on interventions addressing diagnostic delays; two reported on interventions targeted at addressing both access and diagnostic delays, and four studies assessed interventions addressing access, diagnostic and treatment delays. While most interventions were demonstrated to be feasible and effective, many of the reported outcome measures are of limited clinical relevance to diagnostic timeliness.

CONCLUSIONS

Though limited, evidence suggests that interventions aimed at addressing barriers to timely diagnosis of breast and cervical cancer are feasible in resource-limited contexts. Future interventions need to address clinically relevant measures to better assess efficacy of interventions.

PROSPERO REGISTRATION NUMBER

CRD42020177232.

Diagnostic Performance of AI for Cancers Registered in A Mammography Screening Program: A Retrospective Analysis

Purpose: To evaluate the performance of an artificial intelligence (AI) algorithm in a simulated screening setting and its effectiveness in detecting missed and interval cancers. Methods: Digital mammograms were collected from Bahcesehir Mammographic Screening Program which is the first organized, population-based, 10-year (2009-2019) screening program in Turkey. In total, 211 mammograms were extracted from the archive of the screening program in this retrospective study. One hundred ten of them were diagnosed as breast cancer (74 screen-detected, 27 interval, 9 missed), 101 of them were negative mammograms with a follow-up for at least 24 months. Cancer detection rates of radiologists in the screening program were compared with an AI system. Three different mammography assessment methods were used: (1) 2 radiologists’ assessment at screening center, (2) AI assessment based on the established risk score threshold, (3) a hypothetical radiologist and AI team-up in which AI was considered to be the third reader. Results: Area under curve was 0.853 (95% CI = 0.801-0.905) and the cut-off value for risk score was 34.5% with a sensitivity of 72.8% and a specificity of 88.3% for AI cancer detection in ROC analysis. Cancer detection rates were 67.3% for radiologists, 72.7% for AI, and 83.6% for radiologist and AI team-up. AI detected 72.7% of all cancers on its own, of which 77.5% were screen-detected, 15% were interval cancers, and 7.5% were missed cancers. Conclusion: AI may potentially enhance the capacity of breast cancer screening programs by increasing cancer detection rates and decreasing false-negative evaluations.

Bahcesehir long-term population-based screening compared to National Breast Cancer Registry Data: effectiveness of screening in an emerging country

PURPOSE

We aimed to show the effects of long-term screening on clinical, pathologic, and survival outcomes in patients with screen-detected breast cancer and compare these findings with breast cancer patients registered in the National Breast Cancer Registry Data (NBCRD).

METHODS

Women aged 40-69 years, living in Bahcesehir county, Istanbul, Turkey, were screened every 2 years using bilateral mammography. The Bahcesehir National Breast Cancer Registry Data (BMSP) data were collected during a 10-year screening period (five rounds of screening). BMSP data were compared with the NBCRD regarding age, cancer stage, types of surgery, tumor size, lymph node status, molecular subtypes, and survival rates.

RESULTS

During the 10-year screening period, 8758 women were screened with 22621 mammograms. Breast cancer was detected in 130 patients; 51 (39.2%) were aged 40-49 years. The comparison of breast cancer patients in the two programs revealed that BMSP patients had earlier stages, higher breast-conserving surgery rates, smaller tumor size, more frequent negative axillary nodal status, lower histologic grade, and higher ductal carcinoma in situ rates than NBCRD patients (p = 0.001, for all).

CONCLUSION

These results indicate the feasibility of successful population-based screening in middle-income countries.

Spanish translation and psychometric evaluation of the Healthcare Professional Knowledge of Radiation Protection scale

The objective of this work was to make an intercultural adaptation and provide a Spanish translation and psychometric evaluation of the original English version of the Healthcare Professional Knowledge of Radiation Protection (HPKRP) scale. The Spanish translation was carried out following international guidelines for the process of cross-cultural adaptation of self-report measures. A cross-sectional design study was carried out. One hundred and thirty-eight nurses from four different hospitals in Barcelona (Spain) completed the Spanish version of the scale. The total score of the scale was calculated. The Pearson correlation coefficient (PCC) was used to evaluate a possible correlation between score and years of experience. A t-test for independent samples was used to evaluate significant differences between different groups. Cronbach's alpha, the corrected item-total correlation coefficient and the test-retest coefficient were used to determine internal consistency. The exploratory factor and parallel analysis were also calculated. All statistical tests were carried out with a level of significance α = 0.05. The mean scale score was poor among Spanish nurses. The PCC between total score and years of experience showed a non-significant correlation (p > 0.05). No differences were found between nurses who worked in radiation-exposed units and those who worked in units without radiation exposure (p > 0.05). A Cronbach α of 0.98 was obtained for the items of the scale. The corrected item-total correlation range was 0.5-0.8. The test-retest correlation coefficient was 0.9. The exploratory analysis factor showed a single factorial structure which explained 60.86% of the variance. The new scale translated into Spanish (Sp-HPKRP) could be used to evaluate the degree of knowledge about radiological protection.

Breast Cancer Detection in Qatar: Evaluation of Mammography Image Quality Using A Standardized Assessment Tool

Objective

Compared with other countries in the Middle East, Qatar has one of the highest breast cancer incidence and mortality rates. Poor quality mammography images may be associated with advanced stage breast cancer, however there is limited information about the quality of breast imaging in Qatar. Our purpose was to evaluate the clinical image quality of mammography examinations performed at a tertiary care center in Doha, Qatar using a standardized assessment tool.

Materials and Methods

Bilateral mammograms from consecutive patients from a tertiary care cancer center in Doha, Qatar were obtained. Proportions of examinations deemed adequate for interpretation were estimated. Standardized clinical image quality assessment form was utilized to evaluate image quality components. For each image, image quality components were given grades on a 1-5 scale (5-excellent, 4-good, 3-average, 2-fair, 1-poor). Mean scores with 95% confidence intervals were estimated for each component.

Results

Consecutive sample of 132 patients was obtained representing 528 mammographic images. Overall, 99.2% of patients underwent examinations rated as acceptable for interpretation. Mean scores for each image quality component ranged from 4.045 to 5.000 (lowest score for inframammary fold). Image quality component scores were 93.0% excellent, 5.2% good, 1.1% average, 0.6% fair, and 0.1% poor.

Conclusion

Overall image quality at a tertiary care center in Doha, Qatar was acceptable for interpretation with minimal areas identified for improvement.

Evaluation of the diagnostic value of circulating tumor cells with CytoSorter® CTC capture system in patients with breast cancer

PURPOSE

In this study, we aimed to investigate the viability of utilizing CytoSorter® system to detect circulating tumor cells (CTCs) and to evaluate the diagnostic value of CTCs in breast cancer (BC).

METHODS

A total of 366 females patients suspected of having BC and 30 healthy female volunteers were enrolled in this study. CTCs were enriched by CytoSorter® , a microfluidic-based CTCs capturing platform. CTC detection was performed before operation or biopsy. Based on the biopsy results, patients were divided into two groups, namely patients with BC and patients with benign breast diseases (BBD). Patients with BBD and healthy volunteers were serving as controls. The correlation between CTC enumeration and patients' clinicopathological characteristics was evaluated. The receiver operating characteristic (ROC) curve was plotted to assess the diagnostic potency of CytoSorter® system in BC.

RESULTS

Based on the biopsy results, 130 BC patients at different cancer stages and 236 patients with BBD were enrolled in the study. Seven subjects were dropped out from the study. CTCs were detected in 109 of 128 BC patients, in one of 29 healthy volunteers, and in 37 of 232 patients with BBD. Maximum CTC counts detected in BC patients, healthy volunteers, and patients with BBD were 8, 1, and 4, respectively. Statistical analysis showed CTCs could be used to distinguish BC patients from healthy volunteers and patients with BBD (P < .0001). Circulating tumor cells were statistically associated with patients' cancer stage (P = .0126), tumor size (tumor node metastasis [TNM] T stage, P = .0253), cancer type (invasive vs noninvasive, P = .0141), and lymph node metastasis (P = .0436). More CTCs were found in patients at advanced cancer stage or TNM T stage and in patients with invasive tumor or lymph node metastasis. Furthermore, CTC detection rates in BC patients at Tis and T1-4 stages were 50%, 81.67%, 91.07%, 100%, and 100%, respectively. When the CTC cut-off value was set to 2, the ROC curve gave an area under the curve (AUC) of 0.86 with a specificity and sensitivity of 95.4% and 76.56%, respectively. Taken together, CTCs could be used as a diagnostic aid in assistance of cancer screening and staging.

CONCLUSION

Circulating tumor cells were successfully isolated in BC patients using CytoSorter® system. CTCs can be used to differentiate BC patients from the patients with BBD or healthy volunteers, and as a diagnostic aid for early cancer diagnosis and cancer staging.