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Cureus Mar 2021Breast cancer is the most common malignancy affecting women worldwide, and early diagnosis of breast cancer is the key to its successful and effective treatment.... (Review)
Review
Breast cancer is the most common malignancy affecting women worldwide, and early diagnosis of breast cancer is the key to its successful and effective treatment. Traditional imaging techniques such as mammography and ultrasound are used to detect and configure breast abnormalities; unfortunately, these modalities have low sensitivity and specificity, particularly in young patients with dense breast tissue, breast implants, or post-surgical scar/architecture distortions. Therefore, breast magnetic resonance imaging (MRI) has been superior in the characterization and detection of breast cancer, especially that with invasive features. This review article explores the importance of breast MRI in the early detection of invasive breast cancer versus traditional tools, including mammography and ultrasound, while also analyzing the use of MRI as a screening tool for high-risk women. We will also discuss the different MRI features for invasive ductal carcinoma and lobular carcinoma and the role of breast MRI in the detection of ductal carcinoma in situ with a focus on the utilization of new techniques, including MR spectroscopy and diffusion-weighted imaging.
PubMed: 33859904
DOI: 10.7759/cureus.13854 -
European Radiology Aug 2020To summarise and compare the performance of magnification mammography and digital zoom utilising a full-field digital mammography (FFDM) system in the detection and...
OBJECTIVES
To summarise and compare the performance of magnification mammography and digital zoom utilising a full-field digital mammography (FFDM) system in the detection and diagnosis of microcalcifications.
METHODS
We ran an extended search in MEDLINE, EMBASE, CINAHL, Engineering Village and Web of Science. Diagnostic test studies, experimental breast phantom studies and a Monte Carlo phantom study were included. A narrative approach was selected to summarise and compare findings regarding the detection of microcalcifications, while a hierarchical model with bivariate analysis was used for the meta-analysis of sensitivity and specificity for diagnosing microcalcifications.
RESULTS
Nine studies were included. Phantom studies suggested that the size of microcalcifications, magnification or zoom factor, exposure factors and detector technology determine whether digital zoom is equivalent to magnification mammography in the detection of microcalcifications. Pooled sensitivity for magnification and zoom calculated from the diagnostic test studies was 0.93 (95% CI 0.84-0.97) and 0.85 (95% CI 0.70-0.94), respectively. Pooled specificity was 0.55 (95% CI 0.51-0.58) and 0.56 (95% CI 0.50-0.62), respectively. The differences between the sensitivities and specificities were not statistically significant.
CONCLUSIONS
Digital zoom may be equivalent to magnification mammography. Diagnostic test studies and phantom studies using newer detector technology would contribute additional knowledge on this topic.
KEY POINTS
• The performance of digital zoom is comparable to magnification for detecting microcalcifications when newer detector technology and optimised imaging procedures are utilised. • The accuracy of digital zoom appears equivalent to geometric magnification in diagnosing microcalcifications.
Topics: Breast Diseases; Calcinosis; Female; Humans; Mammography; Phantoms, Imaging; Sensitivity and Specificity
PubMed: 32222798
DOI: 10.1007/s00330-020-06798-6 -
Frontiers in Oncology 2023Various natural language processing (NLP) algorithms have been applied in the literature to analyze radiology reports pertaining to the diagnosis and subsequent care of...
Various natural language processing (NLP) algorithms have been applied in the literature to analyze radiology reports pertaining to the diagnosis and subsequent care of cancer patients. Applications of this technology include cohort selection for clinical trials, population of large-scale data registries, and quality improvement in radiology workflows including mammography screening. This scoping review is the first to examine such applications in the specific context of breast cancer. Out of 210 identified articles initially, 44 met our inclusion criteria for this review. Extracted data elements included both clinical and technical details of studies that developed or evaluated NLP algorithms applied to free-text radiology reports of breast cancer. Our review illustrates an emphasis on applications in diagnostic and screening processes over treatment or therapeutic applications and describes growth in deep learning and transfer learning approaches in recent years, although rule-based approaches continue to be useful. Furthermore, we observe increased efforts in code and software sharing but not with data sharing.
PubMed: 37124523
DOI: 10.3389/fonc.2023.1160167 -
Cancer Causes & Control : CCC Nov 2023It may be important for women to have mammograms at different points in time to track changes in breast density, as fluctuations in breast density can affect breast... (Review)
Review
PURPOSE
It may be important for women to have mammograms at different points in time to track changes in breast density, as fluctuations in breast density can affect breast cancer risk. This systematic review aimed to assess methods used to relate repeated mammographic images to breast cancer risk.
METHODS
The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021. Eligibility criteria included published articles in English describing the relationship of change in mammographic features with risk of breast cancer. Risk of bias was assessed using the Quality in Prognostic Studies tool.
RESULTS
Twenty articles were included. The Breast Imaging Reporting and Data System and Cumulus were most commonly used for classifying mammographic density and automated assessment was used on more recent digital mammograms. Time between mammograms varied from 1 year to a median of 4.1, and only nine of the studies used more than two mammograms. Several studies showed that adding change of density or mammographic features improved model performance. Variation in risk of bias of studies was highest in prognostic factor measurement and study confounding.
CONCLUSION
This review provided an updated overview and revealed research gaps in assessment of the use of texture features, risk prediction, and AUC. We provide recommendations for future studies using repeated measure methods for mammogram images to improve risk classification and risk prediction for women to tailor screening and prevention strategies to level of risk.
Topics: Female; Humans; Breast Density; Breast Neoplasms; Mammography; Breast; Risk; Risk Factors
PubMed: 37340148
DOI: 10.1007/s10552-023-01739-2 -
BMJ Open Nov 2021Attendance at population-based breast cancer (mammographic) screening varies. This comprehensive systematic review and meta-analysis assesses all identified... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
Attendance at population-based breast cancer (mammographic) screening varies. This comprehensive systematic review and meta-analysis assesses all identified patient-level factors associated with routine population breast screening attendance.
DESIGN
CINAHL, Cochrane Library, Embase, Medline, OVID, PsycINFO and Web of Science were searched for studies of any design, published January 1987-June 2019, and reporting attendance in relation to at least one patient-level factor.
DATA SYNTHESIS
Independent reviewers performed screening, data extraction and quality appraisal. OR and 95% CIs were calculated for attendance for each factor and random-effects meta-analysis was undertaken where possible.
RESULTS
Of 19 776 studies, 335 were assessed at full text and 66 studies (n=22 150 922) were included. Risk of bias was generally low. In meta-analysis, increased attendance was associated with higher socioeconomic status (SES) (n=11 studies; OR 1.45, 95% CI: 1.20 to 1.75); higher income (n=5 studies; OR 1.96, 95% CI: 1.68 to 2.29); home ownership (n=3 studies; OR 2.16, 95% CI: 2.08 to 2.23); being non-immigrant (n=7 studies; OR 2.23, 95% CI: 2.00 to 2.48); being married/cohabiting (n=7 studies; OR 1.86, 95% CI: 1.58 to 2.19) and medium (vs low) level of education (n=6 studies; OR 1.24, 95% CI: 1.09 to 1.41). Women with previous false-positive results were less likely to reattend (n=6 studies; OR 0.77, 95% CI: 0.68 to 0.88). There were no differences by age group or by rural versus urban residence.
CONCLUSIONS
Attendance was lower in women with lower SES, those who were immigrants, non-homeowners and those with previous false-positive results. Variations in service delivery, screening programmes and study populations may influence findings. Our findings are of univariable associations. Underlying causes of lower uptake such as practical, physical, psychological or financial barriers should be investigated.
TRIAL REGISTRATION NUMBER
CRD42016051597.
Topics: Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening; Text Messaging
PubMed: 34848507
DOI: 10.1136/bmjopen-2020-046660 -
Cureus Apr 2024This systematic review aimed to critically assess the effectiveness of mammography, ultrasound, and magnetic resonance imaging (MRI) in the detection of breast... (Review)
Review
This systematic review aimed to critically assess the effectiveness of mammography, ultrasound, and magnetic resonance imaging (MRI) in the detection of breast carcinoma within dense breast tissue. An exhaustive search of contemporary literature was undertaken, focusing on the diagnostic accuracy, false positive and negative rates, and clinical implications of the aforementioned imaging modalities. Each modality was assessed in isolation and side by side against the others to draw comparative inferences. While mammography remains a foundational imaging modality, its effectiveness waned within the context of dense breast tissue. Ultrasound demonstrated a strong differentiation prowess, especially among specific demographic cohorts. MRI, despite its exceptional precision and differentiation capabilities, exhibited a tendency for slightly elevated false positive rates. No single modality emerged as singularly superior for all cases. Instead, an integrated approach, combining the strengths of each modality based on individual patient profiles and clinical scenarios, is recommended. This tailored approach ensures optimized detection rates and minimizes diagnostic ambiguities, underscoring the significance of individualized patient care in the field of diagnostic radiology.
PubMed: 38800325
DOI: 10.7759/cureus.59054 -
In Vivo (Athens, Greece) 2023COVID-19 has dramatically impacted non-pandemic-related care, including preventive medicine. Our objective was to quantify the alterations in the volume of screening... (Review)
Review
BACKGROUND/AIM
COVID-19 has dramatically impacted non-pandemic-related care, including preventive medicine. Our objective was to quantify the alterations in the volume of screening tests for breast and cervical cancer during the COVID-19 era compared to pre-pandemic levels. Secondarily, we discussed the causes responsible for this change, presented suggestions for screening optimization and conducted a targeted search of the relevant literature for worsening of future mortality due to screening setback.
MATERIALS AND METHODS
We systematically searched Pubmed, Google Scholar and Epistemonikos for articles in English or Greek, published from March 11th, 2020, until September 14th, 2022, that illustrated quantitative variations of mammograms or Pap/HPV tests. Preprint articles, editorials and speeches were excluded. Quality of included studies was assessed via the JBI critical appraisal checklist for studies reporting prevalence data. The evidence was narratively synthesized.
RESULTS
A total of 56 articles were included, being either observational studies or reports from cancer registries. Large reductions were universally identified, peaked during the first wave but partially persisted after easing of the restrictions.
CONCLUSION
Our systematic review provides an updated record of the variations in screening volume and approaches screening neglect from a multidimensional perspective answering why it happened and how we could achieve recovery. A strong awareness campaign is proposed, in conjunction with triaging citizens more likely to benefit from screening. Cervical self-sampling is emphasized in the literature. Various studies displayed a potential increase in cancer mortality in the future based on predictive statistical models.
Topics: Female; Humans; Uterine Cervical Neoplasms; Early Detection of Cancer; Pandemics; COVID-19; Mammography
PubMed: 37369493
DOI: 10.21873/invivo.13230 -
Cancer Medicine Apr 2024Contrast-enhanced spectral imaging (CEM) is a new mammography technique, but its diagnostic value in dense breasts is still inconclusive. We did a systematic review and... (Meta-Analysis)
Meta-Analysis
PURPOSE
Contrast-enhanced spectral imaging (CEM) is a new mammography technique, but its diagnostic value in dense breasts is still inconclusive. We did a systematic review and meta-analysis of studies evaluating the diagnostic performance of CEM for suspicious findings in dense breasts.
MATERIALS AND METHODS
The PubMed, Embase, and Cochrane Library databases were searched systematically until August 6, 2023. Prospective and retrospective studies were included to evaluate the diagnostic performance of CEM for suspicious findings in dense breasts. The QUADAS-2 tool was used to evaluate the quality and risk of bias of the included studies. STATA V.16.0 and Review Manager V.5.3 were used to meta-analyze the included studies.
RESULTS
A total of 10 studies (827 patients, 958 lesions) were included. These 10 studies reported the diagnostic performance of CEM for the workup of suspicious lesions in patients with dense breasts. The summary sensitivity and summary specificity were 0.95 (95% CI, 0.92-0.97) and 0.81 (95% CI, 0.70-0.89), respectively. Enhanced lesions, circumscribed margins, and malignancy were statistically correlated. The relative malignancy OR value of the enhanced lesions was 28.11 (95% CI, 6.84-115.48). The relative malignancy OR value of circumscribed margins was 0.17 (95% CI, 0.07-0.45).
CONCLUSION
CEM has high diagnostic performance in the workup of suspicious findings in dense breasts, and when lesions are enhanced and have irregular margins, they are often malignant.
Topics: Female; Humans; Breast; Breast Density; Breast Neoplasms; Contrast Media; Mammography; Sensitivity and Specificity
PubMed: 38659408
DOI: 10.1002/cam4.7128 -
Oncology 2021The aim of this study is to systematically review the literature to summarize the evidence surrounding the clinical utility of artificial intelligence (AI) in the field...
BACKGROUND
The aim of this study is to systematically review the literature to summarize the evidence surrounding the clinical utility of artificial intelligence (AI) in the field of mammography. Databases from PubMed, IEEE Xplore, and Scopus were searched for relevant literature. Studies evaluating AI models in the context of prediction and diagnosis of breast malignancies that also reported conventional performance metrics were deemed suitable for inclusion. From 90 unique citations, 21 studies were considered suitable for our examination. Data was not pooled due to heterogeneity in study evaluation methods.
SUMMARY
Three studies showed the applicability of AI in reducing workload. Six studies demonstrated that AI can aid in diagnosis, with up to 69% reduction in false positives and an increase in sensitivity ranging from 84 to 91%. Five studies show how AI models can independently mark and classify suspicious findings on conventional scans, with abilities comparable with radiologists. Seven studies examined AI predictive potential for breast cancer and risk score calculation. Key Messages: Despite limitations in the current evidence base and technical obstacles, this review suggests AI has marked potential for extensive use in mammography. Additional works, including large-scale prospective studies, are warranted to elucidate the clinical utility of AI.
Topics: Breast Neoplasms; Female; Humans; Machine Learning; Mammography; Reproducibility of Results
PubMed: 34023831
DOI: 10.1159/000515698 -
Korean Journal of Radiology Aug 2021To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis.
MATERIALS AND METHODS
Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies.
RESULTS
Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone ( < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses.
CONCLUSION
Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.
Topics: Breast Density; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening; Sensitivity and Specificity
PubMed: 34047504
DOI: 10.3348/kjr.2020.1227