RRIMS: Radiation Risk In Mammography Screening - model evaluation.

OBJECTIVE: The Radiation Risk In Mammography Screening (RRIMS) model was introduced as a novel tool to help females accurately calculate their lifetime mean glandular dose (MGD) and estimate their population-level risk of radiation-induced breast cancer incidence and mortality. METHODS: The model's accuracy was evaluated by comparing the received MGD of 317 women who had undergone a total of 733 visits across one to four rounds of screening. This was achieved by comparing the RRIMS predicted dose values with the same examination dose calculated manually by hand. Qualitative and quantitative statistical analyses were performed to assess the percentage difference (% diff) or agreement between the two values. RESULTS: Qualitative statistical analysis using the Bland-Altman plots demonstrated a statistically significant bias for the % diff between the manually calculated and RRIMS predicted dose values, where the mean (bias) was -2.02% with an upper and lower limit of agreement of 40.24% and -44.27%, respectively. Quantitative statistical analysis revealed an intraclass correlation coefficient (ICC, 3,1) of 0.64 (p-value < 0.001) and a Kendall's W of 0.83 (p-value < 0.001). CONCLUSION: The results indicate a statistically significant and reasonably good level of agreement between the manually calculated vs RRIMS predicted dose values. This work was focused on one of the major mammography equipment manufacturers that is Hologic, however there is potential for a multivendor applicability study of this model with future iterations. This will further improve upon this innovative dose and risk prediction tool that can empower healthcare professionals when making informed decisions and enhance patient care. ADVANCES IN KNOWLEDGE: This paper assesses the precision of the dose and risk model that our team has previously established. The results bring us one step closer to providing females and clinicians with a useful tool that can help explain and contextualise the benefits and risks associated with screening mammography.

A review of screening mammography: The benefits and radiation risks put into perspective.

INTRODUCTION/BACKGROUND: In medical imaging a benefit to risk analysis is required when justifying or implementing diagnostic procedures. Screening mammography is no exception and in particular concerns around the use of radiation to help diagnose cancer must be addressed. METHODS: The Medline database and various established reports on breast screening and radiological protection were utilised to explore this review. RESULTS/DISCUSSION: The benefit of screening is well argued; the ability to detect and treat breast cancer has led to a 91% 5-year survival rate and 497 deaths prevented from breast cancer amongst 100,000 screened women. Subsequently, screening guidelines by various countries recommend annual, biennial or triennial screening from ages somewhere between 40-74 years. Whilst the literature presents different perspectives on screening younger and older women, the current evidence of benefit for screening women <40 and ≥75 years is currently not strong. The radiation dose and associated risk delivered to each woman for a single examination is dependent upon age, breast density and breast thickness, however the average mean glandular dose is around 2.5-3 mGy, and this would result in 65 induced cancers and 8 deaths per 100,000 women over a screening lifetime from 40-74 years. This results in a ratio of lives saved to deaths from induced cancer of 62:1. CONCLUSION: Therefore, compared to the potential mortality reduction achievable with screening mammography, the risk is small.

RRIMS: Radiation Risk In Mammography Screening - a novel model for predicting the lifetime dose and risk of radiation-induced breast cancer from the first screening visit.

Objectives: Radiation Risk In Mammography Screening (RRIMS) builds on the prototype, formerly known as Breast-iRRISC, to develop a model that aims to establish a dose and risk profile for females by calculating their lifetime mean glandular dose (MGD) for each age of screening between 40 and 75 years, using only the information from her first screening visit. This is then used to allocate her to a dose category and estimate the lifetime risk of radiation-induced breast cancer incidence and mortality for a population of females in that category. Methods: This model training was developed using a large dataset of Hologic images containing a total of 20,232 images from 5,076 visits from 4,154 females. The female's breast characteristics and exposure parameters were extracted from the images to calculate the female's MGD throughout a lifetime of screening from just her first screening visit, using modelling of various parameters and their change through time. Results: This development has ultimately provided a model that uses the female's first screening visit to calculate the received MGD for all ages of potential screening. This has enabled the allocation of females to either a low-, medium-, or high-dose category, ultimately followed by the lifetime effective risk (LER) estimation for any screening attendance pattern. A female in the low-dose category undergoing biennial screening from 50 to 74 years would expect a risk of radiation-induced breast cancer incidence and mortality of 8.64 and 2.61 cases per 100,000 females, respectively. Similarly, a female in the medium- or high-dose category undergoing the same regimen would expect an incidence and mortality risk of 11.76 and 3.55, and 15.08 and 4.55 cases per 100,000 females, respectively. Conclusions: This novel approach of establishing a female's dose profile and lifetime risk from a single visit will further assist females in their informed consent on breast screening attendance and help inform policy-makers when exploring the benefits and drawbacks of various screening patterns and frequencies. Advances in knowledge: RRIMS is a novel tool that enables the assessment of a female's lifetime dose and risk profile using only the information from her first screening visit.

SCREENING MAMMOGRAPHY: DIAGNOSTIC EFFICACY-ISSUES AND CONSIDERATIONS FOR THE 2020S.

Diagnostic efficacy in medical imaging is ultimately a reflection of radiologist performance. This can be influenced by numerous factors, some of which are patient related, such as the physical size and density of the breast, and machine related, where some lesions are difficult to visualise on traditional imaging techniques. Other factors are human reader errors that occur during the diagnostic process, which relate to reader experience and their perceptual and cognitive oversights. Given the large-scale nature of breast cancer screening, even small increases in diagnostic performance equate to large numbers of women saved. It is important to identify the causes of diagnostic errors and how detection efficacy can be improved. This narrative review will therefore explore the various factors that influence mammographic performance and the potential solutions used in an attempt to ameliorate the errors made.

Breast-iRRISC: a novel model for predicting the individualised lifetime risk of radiation-induced breast cancer from a single screening event.

OBJECTIVES: This work establishes the prototype of a new innovative risk model that aims to evaluate the total risk involved with screening mammography for each individual female. This has been specifically designed to accommodate any combination of lifetime screening regimes, using only the information gathered from a single mammographic examination. METHODS: This model prototype was developed with the aid of a large dataset of images from the Cancer Institute New South Wales (CINSW) with over 30,000 images from over 7000 examinations. Each examination is derived from a separate female. RESULTS: This prototype which we have called Breast Individualised Risk of Radiation-Induced Screening Cancer (Breast-iRRISC) is a novel tool for the assessment of the lifetime risk involved with screening mammography. The results demonstrate the applicability of this approach to the various screening regimes utilised around the globe, in addition to the personalised screening frequency patterns females have undergone and are likely to receive in the future. CONCLUSIONS: This unique tailored approach to risk assessment will further empower females and clinicians towards a more informed clinical decision process regarding future imaging pathways. It will also inform health policy decisions regarding alternate screening durations and intervals. ADVANCES IN KNOWLEDGE: Breast-iRRISC is a novel tool that provides females, clinicians and health policymakers around the globe with the ability to quantify the lifetime risk of radiation-induced breast cancer from screening mammography on an individual level from a single exposure.