A review of mammographic positioning image quality criteria for the craniocaudal projection

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.

Evaluation of the quality of mammographic breast positioning: a quality improvement study

BACKGROUND

Although there are concerns that inadequate breast positioning in mammographic examinations may lead to cancers being missed, few studies have examined the quality of breast positioning, especially in the Canadian context. Our objective was to assess the quality of breast positioning in mammographic examinations in a Quebec-wide representative sample of technologists.

METHODS

This quality improvement study was part of a professional inspection launched by the Ordre des technologues en imagerie médicale, en radio-oncologie et en électrophysiologie médicale du Québec among its members. The inspection was conducted between May and July 2017 on a proportionate stratified random sample of all active technologists certified in mammography in Quebec. Each technologist provided images from 15 consecutive mammographic examinations they performed in the previous 6 months. The quality of positioning was then evaluated by senior technologists using a quality assessment tool specifically developed for this inspection. A technologist was deemed to have failed the professional inspection when at least 7 of the 15 mammographic examinations were scored as critical failures. Proportions were calculated accounting for sampling weights and correction for finite population.

RESULTS

Among the 520 technologists certified in mammography in Quebec, 76 technologists (14.6%) were randomly selected for the professional inspection and contributed images from 1127 mammographic examinations. Thirty-eight technologists (weighted percentage 50.3%, 95% confidence interval [CI] 37.6% to 63.0%) failed the professional inspection. Overall, 492 mammographic examinations (43.7%, 95% CI 38.6% to 48.8%) had at least 1 image scored as a critical failure.

INTERPRETATION

Half of the technologists performing mammographic examinations in Quebec who participated in this study failed the inspection, and a substantial proportion of their mammographic examinations demonstrated critical failures in breast positioning. Overall, our findings are concordant with those of previous studies and highlight the need for additional investigations assessing the quality of breast positioning in mammographic examinations in other jurisdictions.

Interobserver variability in quality assessment of magnetic resonance images

Background

The perceptual quality of magnetic resonance (MR) images influences diagnosis and may compromise the treatment. The purpose of this study was to evaluate how the image quality changes influence the interobserver variability of their assessment.

Methods

For the variability evaluation, a dataset containing distorted MRI images was prepared and then assessed by 31 experienced medical professionals (radiologists). Differences between observers were analyzed using the Fleiss’ kappa. However, since the kappa evaluates the agreement among radiologists taking into account aggregated decisions, a typically employed criterion of the image quality assessment (IQA) performance was used to provide a more thorough analysis. The IQA performance of radiologists was evaluated by comparing the Spearman correlation coefficients, ρ, between individual scores with the mean opinion scores (MOS) composed of the subjective opinions of the remaining professionals.

Results

The experiments show that there is a significant agreement among radiologists (κ=0.12; 95% confidence interval [CI]: 0.118, 0.121; P<0.001) on the quality of the assessed images. The resulted κ is strongly affected by the subjectivity of the assigned scores, separately presenting close scores. Therefore, the ρ was used to identify poor performance cases and to confirm the consistency of the majority of collected scores (ρ_mean = 0.5706). The results for interns (ρ_mean = 0.6868) supports the finding that the quality assessment of MR images can be successfully taught.

Conclusions

The agreement observed among radiologists from different imaging centers confirms the subjectivity of the perception of MR images. It was shown that the image content and severity of distortions affect the IQA. Furthermore, the study highlights the importance of the psychosomatic condition of the observers and their attitude.

Full-field digital mammography: the '30% rule' and influences on visualisation of the pectoralis major muscle on the craniocaudal view of the breast

INTRODUCTION

To investigate compliance to the '30% rule' and key factors which may influence visualisation of the pectoralis major muscle (PMM) on the craniocaudal (CC) view of the breast.

METHODS

A retrospective review of 2688 paired full-field digital mammography (FFDM) CC view mammograms of women attending BreastScreen NSW between August and October 2015 was undertaken. PMM visualisation and measurements of PMM width and length, compressed breast thickness, the posterior nipple line (PNL) and age were recorded. Statistical analysis was performed using descriptive and inferential statistics to investigate associations between key breast measurements, age and PMM visualisation.

RESULTS

PMM visualisation was reported in 10.4% of images unilaterally (one breast, left or right only), 14.1% bilaterally (both left and right breasts) and 24.5% overall (unilateral and bilateral combined). There was little or no correlations between PMM length or width and age, breast compressed thickness or PNL. Multiple logistic regression analysis found that up to 15% of the variance in visualisation of the PMM was accounted for by the predictors overall. While some predictors provided a statistically significant contribution to the model, the contribution was small and the odds ratio for all predictors approximated 1.

CONCLUSION

This research could not replicate the '30% rule', and visualisation of the PMM was determined not to be influenced by the variables investigated. The significance of the 'rule' itself must be challenged where the vast majority of images (70-85%) do not comply, and there is no requirement for repeat imaging if the 'rule' is not met. Further research should be undertaken to validate this study including analysis of diagnostic images for comparison.

Automatic segmentation of the pectoral muscle based on boundary identification and shape prediction

The purpose of this work is to identify the pectoral muscle region in mediolateral oblique (MLO) view mammograms even when the boundary is blurred or obscured. The problem is decoupled into two subproblems in our study: identifying parts of boundaries with high confidence and predicting the overall shape of the pectoral muscle. Due to the similarity in intensity and texture between pectoral muscle and gland tissue, we trained a deep neural network to distinguish them in the first subproblem. The boundary with high confidence can be obtained according to the consistency of predictions from multiple converged models. For the shape prediction problem, a generative adversarial network (GAN) is used to learn mapping from a given identified region and the breast shape to the overall pectoral muscle shape. Our method is evaluated on a mammogram dataset including 633 MLO view mammograms collected from three different datacenters. We take U-Net as our baseline model and the dataset is divided into three groups according to the performance of U-Net for evaluation. In all three groups, U-Net achieves 80.1%, 92.9%, and 98.3% in the Dice similarity coefficient, respectively, and our method achieves 85.2%, 94.8%, and 98.1% in the Dice similarity coefficient, respectively. The experiment shows that our method effectively estimates the pectoral muscle boundary, even parts of boundaries that are difficult to detect, and greatly improves the performance of segmentation in this case.