[BIRADS 0 patient reclassification in a first-level of care unit]. / Reclasificación de pacientes BIRADS 0 en una unidad de primer nivel de atención.

Background: In Mexico and the world, breast cancer is the cancer type with the highest incidence and mortality for women. Its incidence has increased due to a higher life expectancy and a higher exposure to risk factors. Screening is done by mammography using the BIRADS (Breast Imaging Reporting and Data System) system, the standard for mammography screening report which classifies lesions assigning recommendations for patient follow-up. The system goes from 0 (not conclusive) to 6 (demonstrated malignancy), being of interest for this study the BIRADS 0 category. Objective: To describe patients classified as BIRADS 0 by mammography and their reclassification in a first-level hospital during 2021. Material and methods: Retrospective, descriptive, cross-sectional, observational study. Women over 40 years with a BIRADS 0 result were studied. The following databases were used: Institutional Cancer Registry, Family Medicine Information System, Electronic Clinical File, and the mammography and patient list from preventive medicine. Results: Reclassification by ultrasound (US) was achieved in 100% of patients, in all of the BIRADS US categories. In 3.8% of BIRADS 0 patients, ductal adenocarcinoma was found and confirmed by histological testing. Conclusion: All of the reassessed lesions with US were adequately reclassified.

Introducción: en México y el mundo, el cáncer de mama causa la mayor mortalidad por cáncer en mujeres. Su incidencia ha incrementado por una mayor esperanza de vida y exposición a factores de riesgo. El tamizaje de esta enfermedad se hace mediante mastografía, y para la estratificación de las lesiones se utiliza el sistema BIRADS (Breast Imaging Reporting and Data System), que estandariza el informe, categoriza las lesiones según el grado de sospecha y asigna recomendaciones a seguir. Dicho sistema va desde 0 (no concluyente) hasta 6 (lesión con malignidad demostrada) y es de interés para este estudio la categoría 0. Objetivo: describir la reclasificación de pacientes con reporte BIRADS 0 por mastografía durante 2021 en una unidad de primer nivel de atención. Material y métodos: estudio retrospectivo, descriptivo, transversal, observacional. Se estudiaron mujeres mayores de 40 años con resultado BIRADS 0. Se utilizaron las siguientes bases de datos: Registro Institucional de Cáncer, Sistema de Información de Medicina Familiar, Expediente Clínico Electrónico y lista nominal de mastografías y censo de pacientes sospechosos de medicina preventiva. Resultados: la reclasificación con ultrasonido (US) se logró en el 100% de pacientes, en todas las categorías de BIRADS US. En el 3.8% se confirmó carcinoma ductal por histología en las pacientes inicialmente categorizadas como BIRADS 0. Conclusiones: la totalidad de lesiones reevaluadas con US fueron reclasificadas satisfactoriamente.

USPSTF Recommendations and Overdiagnosis.

Overdiagnosis is the concept that some cancers detected at screening would never have become clinically apparent during a woman's lifetime in the absence of screening. This could occur if a woman dies of a cause other than breast cancer in the interval between mammographic detection and clinical detection (obligate overdiagnosis) or if a mammographically detected breast cancer fails to progress to clinical presentation. Overdiagnosis cannot be measured directly. Indirect methods of estimating overdiagnosis include use of data from randomized controlled trials (RCTs) designed to evaluate breast cancer mortality, population-based screening studies, or modeling. In each case, estimates of overdiagnosis must consider lead time, breast cancer incidence trends in the absence of screening, and accurate and predictable rates of tumor progression. Failure to do so has led to widely varying estimates of overdiagnosis. The U.S. Preventive Services Task Force (USPSTF) considers overdiagnosis a major harm of mammography screening. Their 2024 report estimated overdiagnosis using summary evaluations of 3 RCTs that did not provide screening to their control groups at the end of the screening period, along with Cancer Intervention and Surveillance Network modeling. However, there are major flaws in their evidence sources and modeling estimates, limiting the USPSTF assessment. The most plausible estimates remain those based on observational studies that suggest overdiagnosis in breast cancer screening is 10% or less and can be attributed primarily to obligate overdiagnosis and nonprogressive ductal carcinoma in situ.

Frequency and characteristics of errors by artificial intelligence (AI) in reading screening mammography: a systematic review.

PURPOSE: Artificial intelligence (AI) for reading breast screening mammograms could potentially replace (some) human-reading and improve screening effectiveness. This systematic review aims to identify and quantify the types of AI errors to better understand the consequences of implementing this technology. METHODS: Electronic databases were searched for external validation studies of the accuracy of AI algorithms in real-world screening mammograms. Descriptive synthesis was performed on error types and frequency. False negative proportions (FNP) and false positive proportions (FPP) were pooled within AI positivity thresholds using random-effects meta-analysis. RESULTS: Seven retrospective studies (447,676 examinations; published 2019-2022) met inclusion criteria. Five studies reported AI error as false negatives or false positives. Pooled FPP decreased incrementally with increasing positivity threshold (71.83% [95% CI 69.67, 73.90] at Transpara 3 to 10.77% [95% CI 8.34, 13.79] at Transpara 9). Pooled FNP increased incrementally from 0.02% [95% CI 0.01, 0.03] (Transpara 3) to 0.12% [95% CI 0.06, 0.26] (Transpara 9), consistent with a trade-off with FPP. Heterogeneity within thresholds reflected algorithm version and completeness of the reference standard. Other forms of AI error were reported rarely (location error and technical error in one study each). CONCLUSION: AI errors are largely interpreted in the framework of test accuracy. FP and FN errors show expected variability not only by positivity threshold, but also by algorithm version and study quality. Reporting of other forms of AI errors is sparse, despite their potential implications for adoption of the technology. Considering broader types of AI error would add nuance to reporting that can inform inferences about AI's utility.

ACR Appropriateness Criteria® Imaging of Invasive Breast Cancer.

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

ACR Appropriateness Criteria® Female Breast Cancer Screening: 2023 Update.

Early detection of breast cancer from regular screening substantially reduces breast cancer mortality and morbidity. Multiple different imaging modalities may be used to screen for breast cancer. Screening recommendations differ based on an individual's risk of developing breast cancer. Numerous factors contribute to breast cancer risk, which is frequently divided into three major categories: average, intermediate, and high risk. For patients assigned female at birth with native breast tissue, mammography and digital breast tomosynthesis are the recommended method for breast cancer screening in all risk categories. In addition to the recommendation of mammography and digital breast tomosynthesis in high-risk patients, screening with breast MRI is recommended. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

The FDA Enhancing Quality Using the Inspection Program (EQUIP) Breast Imaging Quality Initiative. 5-Year Clinical Experience.

OBJECTIVES: To evaluate the effects of the Enhancing Quality Using the Inspection Program (EQUIP) on quality control (QC) and quality assurance (QA) at an academic medical center. METHODS: EQUIP audit logs for technologist image quality review as well as mammography unit QA and QC formed the basis for study data. One randomly selected screening mammogram was evaluated by the lead interpreting physician (LIP) using EQUIP criteria for each technologist for each imaging site worked, initially semiannually and then monthly. One randomly selected screening mammogram interpreted by each interpreting physician (IP) for each imaging site was evaluated on a semiannual basis. Quarterly, the LIP reviewed QA and QC logs for each mammography unit with deficiencies further investigated. RESULTS: Of 214 965 eligible screening mammograms performed, 5955 (2.8%) underwent EQUIP image quality review. Five were found to be technically inadequate (0.08%, 5955/214 965). The LIP identified 20 significant interpretive differences compared with the clinical interpretation resulting in 10 biopsies and 7 previously undetected malignancies, with supplemental cancer detection rate of 1.2/1000 cases reviewed. Two hundred ninety mammography unit QA/QC reviews identified 31 potential deficiencies, 29 of which were due to human documentation error (93.4%). CONCLUSION: EQUIP review of both IP and technologists' quality and mammography unit QA/QC logs as performed identified few deficiencies. EQUIP policies should be evaluated at each institution and modified to best utilize resources and provide opportunities for meaningful quality improvement. Although not an EQUIP focus, supplemental cancer detection was observed as might be expected with double reading.

[A Study on the Uncertainty of the Average Glandular Dose in Quality Control of Mammographic X-ray Units].

【Purpose】 Accurate control of X-ray units and dosimeters and analysis of the uncertainties associated with the accurate measurement of radiation doses are essential for the effective establishment and application of diagnostic reference levels. In this study, the uncertainty of the average glandular dose (AGD) in the quality control of mammography equipment was evaluated in detail, and recommendations were provided to improve the accuracy and safety of radiological practice. 【Methods】 In the uncertainty analysis of the AGD, the relative standard uncertainties in the measurements of the half-value layer, the incident air kerma, and the conversion factor were considered and finally expressed as expanded uncertainties, the intervals of which were clearly defined. 【Results】 From the AGD measurements using two types of dosimeters, it was found that the primary sources of uncertainty are the uncertainty of the calibration factors of the dosimeters and the uncertainty of the conversion factors.【Conclusion】 To reduce uncertainty, the use of regularly calibrated dosimeters is effective and reliable. Two types of dosimeters are commonly used; the results of this study may serve as a reference value for the uncertainty of AGD in quality control in medical facilities.

Despite New Recommendations, the Debate Over Mammography Guidelines Continues.

This Medical News story discusses new USPSTF recommendations about the timing of screening mammograms.

Breast Imaging Reporting and Data System (BI-RADS®): a success history and particularities of its use in Brazil.

BI-RADS® is a standardization system for breast imaging reports and results created by the American College of Radiology to initially address the lack of uniformity in mammography reporting. The system consists of a lexicon of descriptors, a reporting structure with final categories and recommended management, and a structure for data collection and auditing. It is accepted worldwide by all specialties involved in the care of breast diseases. Its implementation is related to the Mammography Quality Standards Act initiative in the United States (1992) and breast cancer screening. After its initial creation in 1993, four additional editions were published in 1995, 1998, 2003 and 2013. It is adopted in several countries around the world and has been translated into 6 languages. Successful breast cancer screening programs in high-income countries can be attributed in part to the widespread use of BI-RADS®. This success led to the development of similar classification systems for other organs (e.g., lung, liver, thyroid, ovaries, colon). In 1998, the structured report model was adopted in Brazil. This article highlights the pioneering and successful role of BI-RADS®, created by ACR 30 years ago, on the eve of publishing its sixth edition, which has evolved into a comprehensive quality assurance tool for multiple imaging modalities. And, especially, it contextualizes the importance of recognizing how we are using BI-RADS® in Brazil, from its implementation to the present day, with a focus on breast cancer screening.

Radiologists' performance in reading digital breast tomosynthesis with and without synthesized views for cancer detection.

OBJECTIVE: The study aims to evaluate the diagnostic efficacy of radiologists and radiology trainees in digital breast tomosynthesis (DBT) alone vs DBT plus synthesized view (SV) for an understanding of the adequacy of DBT images to identify cancer lesions. METHODS: Fifty-five observers (30 radiologists and 25 radiology trainees) participated in reading a set of 35 cases (15 cancer) with 28 readers reading DBT and 27 readers reading DBT plus SV. Two groups of readers had similar experience in interpreting mammograms. The performances of participants in each reading mode were compared with the ground truth and calculated in term of specificity, sensitivity, and ROC AUC. The cancer detection rate in various levels of breast density, lesion types and lesion sizes between 'DBT' and 'DBT + SV' were also analyzed. The difference in diagnostic accuracy of readers between two reading modes was assessed using Man-Whitney U test. p < 0.05 indicated a significant result. RESULTS: There was no significant difference in specificity (0.67-vs-0.65; p = 0.69), sensitivity (0.77-vs-0.71; p = 0.09), ROC AUC (0.77-vs-0.73; p = 0.19) of radiologists reading DBT plus SV compared with radiologists reading DBT. Similar result was found in radiology trainees with no significant difference in specificity (0.70-vs-0.63; p = 0.29), sensitivity (0.44-vs-0.55; p = 0.19), ROC AUC (0.59-vs-0.62; p = 0.60) between two reading modes. Radiologists and trainees obtained similar results in two reading modes for cancer detection rate with different levels of breast density, cancer types and sizes of lesions (p > 0.05). CONCLUSION: Findings show that the diagnostic performances of radiologists and radiology trainees in DBT alone and DBT plus SV were equivalent in identifying cancer and normal cases. ADVANCES IN KNOWLEDGE: DBT alone had equivalent diagnostic accuracy as DBT plus SV which could imply the consideration of using DBT as a sole modality without SV.

Comparing image quality of five breast tomosynthesis systems based on radiologists' reviews of phantom data.

BACKGROUND: Previous studies have shown differences in technical image quality between digital breast tomosynthesis (DBT) systems. However, quantitative image quality measurements may not necessarily fully reflect the clinical performance of DBT. PURPOSE: To study the subjective image quality of five DBT systems manufactured by Fujifilm, GE, Hologic, Planmed, and Siemens using phantom images. MATERIAL AND METHODS: A TOR MAM test object with polymethyl methacrylate plates was imaged on five DBT systems from different vendors. Three DBT acquisitions were performed at mean glandular doses of 1.0 mGy, 2.0 mGy, and 3.5 mGy while maintaining a constant phantom set-up. Eight DBT acquisitions with different test plate positions and phantom set-up thicknesses were performed at clinically applied dose levels. Additionally, three conventional two-dimensional mammogram images were acquired with different phantom thicknesses. Six radiologists ranked the systems based on the visibilities of the targets seen in the phantom images. RESULTS: In the DBT acquisitions performed at comparable dose levels, one system differed significantly from all other systems in microcalcification scores. When using site-specific DBT protocols, significant differences were found between the devices for microcalcification, filament, and low-contrast targets. A strong correlation was observed between the reviewer scores and radiation doses in DBT acquisitions, whereas no such correlation was observed in the 2D acquisitions. CONCLUSION: In DBT acquisitions, dose level was found to be a major factor explaining image quality differences between the systems, regardless of other acquisition parameters. Most DBT systems performed equally well at similar dose levels.

Ensuring Clarity and Understandability of the FDA's Breast Density Notifications.

This Viewpoint discusses the use of breast density notifications to inform women with dense breast tissue of the potential need for supplemental cancer screening, as well as the need to ensure that such notifications are clear and understandable to women of all language backgrounds, literacy levels, educational levels, and socioeconomic backgrounds.

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.

Imaging and pathological discordance amongst the plethora of breast lesions in breast biopsies.

INTRODUCTION: Imaging-guided breast tissue biopsy has become an acceptable alternative to open surgical biopsy for nonpalpable breast lesions. Discussion of abnormal results of the correlation between imaging and pathological findings can be very challenging as it can assist in decision-making with regard to the further treatment options by arriving at a comprehensive diagnosis. MATERIALS AND METHODS: This was a retrospective study. Radiological data from imaging-guided breast biopsies of 500 patients during a 6-year period was collected and classified by a specialist radiologist as per the BI-RADS format. Histopathology reports were studied and discordance analyzed. RESULTS: A total of 500 cases were reviewed. Approximately 33% (168) cases fell into the BI-RADS 3 category, 24.4% (122) into the BI-RADS 4, and 37% (187) into BI-RADS 5 categories. Approximately 50% (n = 250) cases were benign, 2.6% (13) belonged to the high-risk category, and 47.4% (237) were malignant. The number of discordant cases was 12 (2.4%), mostly due to technical factors. Sensitivity of biopsies to detect malignancy was 85%, specificity was 96%, and accuracy of biopsy in diagnosing cancer was 90%. DISCUSSION: The "triple assessment" is the most sensitive method for detecting early breast cancer. An effective communication pathway must be established between a clinician, radiologist, and pathologist for surgical excision in discordance as it carries a high prevalence of carcinoma in these lesions. CONCLUSION: In discordant cases, either due to abnormal results of imaging or of abnormal pathological findings, the final decision is based on two concordant findings, out of the three parameters. This involves a multidisciplinary breast conference and an active participation by the pathologist.

The age-specific differences in histopathological tumor characteristics and TNM classification of breast carcinomas in Quality assured mamma diagnostic (QuaMaDi) program in the state of Schleswig-Holstein in Germany.

BACKGROUND: We explored the hypothesis that high-quality standards in diagnostic mammography can lead to an early diagnosis of breast cancers and identifies at risk populations outside screening programs. The histopathological features and distribution of the TNM classification were examined in relation to patient age in a large group of women with breast cancers participating in the Quality Assured Mamma Diagnostic (QuaMaDi) program of the state of Schleswig-Holstein. PATIENTS AND METHODS: Surgical pathological reports were studied for clinicopathological characteristics, receptor status, molecular subtype and tumor stage. The analysis was conducted by dividing the study population into three age groups: women under 50 years (pre-screening), 50-69 years (peri-screening) and over 70 years (post-screening). RESULTS: 7.111 biopsies and 2.887 resection specimens were included. Breast cancer was diagnosed in 4.241 (59.7%) cases, one fourth of them in women < 50 years. Elderly women (> 70 years) had more well-differentiated, estrogen receptor (ER)-positive and HER2-negative carcinomas, whereas younger women (< 50 years) tended to have more poorly differentiated, ER negative, and HER2-positive carcinomas. 47% of breast carcinoma were luminal B tumors and were most common regardless of age. 70.4% of resected specimen had pT1 stage. Nodal negative were 71.2%. CONCLUSION: In QuaMaDi breast cancer was diagnosed at an early and potentially curable stage of the disease due to high-quality standards in diagnostic mammography. In addition, regardless of age, an increased number of prognostically unfavorable molecular subtypes were detected. Thus, QuaMaDi helps to identify at risk populations. QuaMaDi significantly improves diagnostic mammography and complements mammography screening programs.