Mammographic image quality in relation to positioning of the breast: A multicentre international evaluation of the assessment systems currently used, to provide an evidence base for establishing a standardised method of assessment

Using automated software evaluation to improve the performance of breast radiographers in tomosynthesis screening

OBJECTIVE

To improve breast radiographers' individual performance by using automated software to assess the correctness of breast positioning and compression in tomosynthesis screening.

MATERIALS AND METHODS

In this retrospective longitudinal analysis of prospective cohorts, six breast radiographers with varying experience in the field were asked to use automated software to improve their performance in breast compression and positioning. The software tool automatically analyzes craniocaudal (CC) and mediolateral oblique (MLO) views for their positioning quality by scoring them according to PGMI classifications (perfect, good, moderate, inadequate) and checking whether the compression pressure is within the target range. The positioning and compression data from the studies acquired before the start of the project were used as individual baselines, while the data obtained after the training were used to test whether conscious use of the software could help the radiographers improve their performance. The percentage of views rated perfect or good and the percentage of views in target compression were used as overall metrics to assess changes in performance.

RESULTS

Following the use of the software, all radiographers significantly increased the percentage of images rated as perfect or good in both CCs and MLOs. Individual improvements ranged from 7 to 14% for CC and 10 to 16% for MLO views. Moreover, most radiographers exhibited improved compression performance in CCs, with improvements up to 16%.

CONCLUSION

Active use of a software tool to automatically assess the correctness of breast compression and positioning in breast cancer screening can improve the performance of radiographers.

CLINICAL RELEVANCE STATEMENT

This study suggests that the use of a software tool for automatically evaluating correctness of breast compression and positioning in breast cancer screening can improve the performance of radiographers on these metrics, which may ultimately lead to improved screening outcomes.

KEY POINTS

• Proper breast positioning and compression are critical in breast cancer screening to ensure accurate diagnosis. • Active use of the software increased the quality of craniocaudal and mediolateral oblique views acquired by all radiographers. • Improved performance of radiographers is expected to improve screening outcomes.

Artificial intelligence to support person-centred care in breast imaging - A scoping review

AIM

To overview Artificial Intelligence (AI) developments and applications in breast imaging (BI) focused on providing person-centred care in diagnosis and treatment for breast pathologies.

METHODS

The scoping review was conducted in accordance with the Joanna Briggs Institute methodology. The search was conducted on MEDLINE, Embase, CINAHL, Web of science, IEEE explore and arxiv during July 2022 and included only studies published after 2016, in French and English. Combination of keywords and Medical Subject Headings terms (MeSH) related to breast imaging and AI were used. No keywords or MeSH terms related to patients, or the person-centred care (PCC) concept were included. Three independent reviewers screened all abstracts and titles, and all eligible full-text publications during a second stage.

RESULTS

3417 results were identified by the search and 106 studies were included for meeting all criteria. Six themes relating to the AI-enabled PCC in BI were identified: individualised risk prediction/growth and prediction/false negative reduction (44.3%), treatment assessment (32.1%), tumour type prediction (11.3%), unnecessary biopsies reduction (5.7%), patients' preferences (2.8%) and other issues (3.8%). The main BI modalities explored in the included studies were magnetic resonance imaging (MRI) (31.1%), mammography (27.4%) and ultrasound (23.6%). The studies were predominantly retrospective, and some variations (age range, data source, race, medical imaging) were present in the datasets used.

CONCLUSIONS

The AI tools for person-centred care are mainly designed for risk and cancer prediction and disease management to identify the most suitable treatment. However, further studies are needed for image acquisition optimisation for different patient groups, improvement and customisation of patient experience and for communicating to patients the options and pathways of disease management.

Comparison between two packages for pectoral muscle removal on mammographic images

Background

Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment.

Purpose

To compare performance of the two packages on a single database of FFDM images.

Methods

Only mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA’s and OpenBreast’s removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal–Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality.

Results

FFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA’s Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P < 0.05). No dependence on breast density or laterality has been found (Kruskal–Wallis test P > 0.05). Conclusion: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.

Canadian Association of Radiologists Mammography Accreditation Program-Clinical Image Assessment

The Canadian Association of Radiologists Mammography Accreditation Program (CAR-MAP) has advocated for quality mammography since its inception in 1991. Evidence based standards have been employed to address image quality, education of personnel, radiologists experience and reading volume. This article reviews the objectives and components of the accreditation program. Education requirements for the technologist, physicist and radiologist are described. A guide to the evaluation criteria for the clinical images is provided. Positioning requirements and technical considerations are detailed to assist facilities and their personnel in improving and maintaining image quality and choosing appropriate images for submission for accreditation.

Visualization of the Nipple in Profile: Does It Really Affect Selected Outcomes in Organized Mammographic Screening?

OBJECTIVE

To investigate whether having the nipple imaged in profile was associated with breast characteristics or compression parameters, and whether it affected selected outcomes in screening with standard digital mammography or digital breast tomosynthesis.

METHODS

In this IRB-approved retrospective study, results from 87 450 examinations (174 900 breasts) performed as part of BreastScreen Norway, 2016-2019, were compared by nipple in profile status and screening technique using descriptive statistics and generalized estimating equations. Unadjusted and adjusted odds ratios with 95% confidence intervals (95% CIs) were estimated for outcomes of interest, including age, breast volume, volumetric breast density, and compression force as covariates.

RESULTS

Achieving the nipple in profile versus not in profile was associated with lower breast volume (845.1 cm3 versus 1059.9 cm3, P < 0.01) and higher mammographic density (5.6% versus 4.4%, P < 0.01). Lower compression force and higher compression pressure were applied to breasts with the nipple in profile (106.6 N and 11.5 kPa) compared to the nipple not in profile (110.8 N and 10.5 kPa, P < 0.01 for both). The adjusted odds ratio was 0.95 (95% CI: 0.88-1.02; P = 0.15) for recall and 0.92 (95% CI: 0.77-1.10; P = 0.36) for screen-detected cancer for nipple in profile versus not in profile.

CONCLUSION

Breast characteristics and compression parameters might hamper imaging of the nipple in profile. However, whether the nipple was in profile or not on the screening mammograms did not influence the odds of recall or screen-detected cancer, regardless of screening technique.

Effect of image quality and motivation of radiographer teams in mammography after dedicated training and the use of an evaluation tool like PGMI

INTRODUCTION

High quality and motivated staff are key factors for successful breast imaging teams. The aim of this study is to find out what effects intensive training of already experienced radiographers - including the embedment of evaluation tools and building a new routine workflow - has on image quality and how the motivation and satisfaction of employees change by that.

METHODS

A mixed methods study was planned to show changes in image quality simultaneously to motivation of the team after a dedicated training with an expert. Two readers evaluated the quality of 1496 mammograms (775 before, 721 after training) with PGMI (perfect/good/moderate/inadequate) in consensus. To record subjective long-term experiences of the alterations due to the training the radiographers were asked to fill in a written questionnaire.

RESULTS

After training the PGMI values considerably shift to a preferred level (p < 0.05) - higher values for P (8,9% to 25,5%) and G (38,2% to 57,1%) and lower values for M (34,1% to 15,4%) and I (18,8% to 1,9%). All radiographers have experienced noticeable improvement and benefit through the initiation of the training.

CONCLUSION

After training there is significant improvement in the image quality of mammograms and an increase in motivation and professional well-being of the radiographers.

IMPLICATIONS FOR PRACTICE

Due to the urgent need for high quality in breast diagnostics and the worldwide frequency of mammographic examinations, investments should be made to establish thoughtful training programs for radiographers and further develop possibilities for assessment like PGMI.

Development and validation of a novel measure of adverse patient positioning in mammography

PURPOSE

The primary aim was to develop and validate a novel mammography positioning measure, specifically incorporating parameters which might relate to mammography pain. We then explored relationships between the new adverse positioning score and (1) pain; (2) patient and technique factors.

METHODS

A 15-item instrument incorporating positioning features with potential to relate to mammography pain was developed. Participants' mammograms (n = 310) were reviewed for presence of these features. Validity was investigated using the Rasch model. Scores produced by the resultant measure were investigated for associations with patients' pain scores and relevant patient and technique factors, using Pearson correlation, analysis of variance, and multiple linear regression.

RESULTS

Statistical indices within the Rasch measurement framework provided good evidence that the measure reflected a coherent construct of adverse positioning. Thus, the scores produced with the measurement instrument were valid for use in further statistical analysis. There is, however, scope for improvement of the measure's discriminatory properties. Adverse positioning scores were higher for greater breast volumes (r = 0.12, p=.0391) and body mass index (BMI) (r = 0.13, p=.0349), and varied by mammographer (F(11,298) 2.38, p = .0078). The relationships with BMI and mammographer persisted in regression modelling. No relationship was found between adverse positioning and pain.

CONCLUSIONS

Evidence from Rasch analysis suggests that this novel measure is valid for quantifying a coherent "adverse positioning" construct in mammography. Adverse positioning scores varied by mammographer and were related to higher patient BMI but not to mammography pain. The measure warrants expansion, further refinement, and testing in larger studies.

Assessment of breast positioning criteria in mammographic screening: Agreement between artificial intelligence software and radiographers

OBJECTIVES

To determine the agreement between artificial intelligence software (AI) and radiographers in assessing breast positioning criteria for mammograms from standard digital mammography and digital breast tomosynthesis.

METHODS

Assessment of breast positioning was performed by AI and by four radiographers in pairs of two on 156 examinations of women screened in Bergen, April to September 2019, as part of BreastScreen Norway. Ten criteria were used; three for craniocaudal and seven for mediolateral-oblique view. The criteria evaluated the appearance of the nipple, breast rotation, pectoral muscle, inframammary fold and pectoral nipple line. Intraclass correlation and Cohen's kappa coefficient (κ) were used to investigate the correlation and agreement between the radiographer's assessments and AI.

RESULTS

The intraclass correlation for the pectoral nipple line between the radiographers and AI was >0.92. A substantial to almost perfect agreement (κ > 0.69) was observed between the radiographers and AI on the nipple in profile criterion. We observed a slight to moderate agreement for the other criteria (κ = 0.06-0.52) and generally a higher agreement between the two pairs of radiographers (mean κ = 0.70) than between the radiographers and AI (mean κ = 0.41).

CONCLUSIONS

AI has great potential in evaluating breast position criteria in mammography by reducing subjectivity. However, varying agreement between radiographers and AI was observed. Standardized and evidence-based criteria for definitions, understandings and assessment methods are needed to reach optimal image quality in mammography.

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.

Current practice in mammographic imaging of the augmented breast in Australia

AIM

This study seeks to document the imaging series used in contemporary Australian practice for imaging the augmented breast, with a secondary focus on differences in practice and opinion between BreastScreen Australia and diagnostic imaging services.

METHODS

A SurveyMonkey link was distributed through the Australian Society of Medical Imaging and Radiation Therapy (ASMIRT) and was assessable during December 2017 and January 2018. The questionnaire investigated: years of experience, facility type and location, image acquisition systems, appointment times, patients imaged per week, technique and imaging series used, use of limited compression views, rationale for variation in imaging series and the use of ultrasound. Descriptive statistics were produced for all variables with chi-squared tests used for comparisons between categorical variables.

RESULTS

The most frequently used series was the eight-image Eklund ID technique 64% and 59% (submuscular) and 68% and 58% (subglandular) for BSA and diagnostic services, respectively. Eighteen different combinations of projections were reported with eight combinations common to both subglandular and submuscular imaging. The majority of participants attributed imaging series preferences to dose reduction and radiologist preference.

CONCLUSION

This research has demonstrated varied approaches to the routine imaging of women with breast implants and identified the need for the establishment of dedicated evidence-based imaging protocols to ensure that regardless of which setting a woman attends that they receive standardised imaging with minimal dose and maximum breast coverage. This is a reassurance that is not applicable to current practice.

Consensus about image quality assessment criteria of breast implants mammography using Delphi method with radiographers and radiologists

Aims

To identify image quality criteria that can be applied to assess breast implant (BI) mammograms according to radiologists and radiographers’ perspectives and to explore the level of agreement about criteria priority.

Methods

A two-round Delphi method using a questionnaire was applied to identify the level of agreement between experts, asking them to rank each image criteria available for mammography according to 4 possible answers (1 = need to have, 2 = nice to have, 3 = not pertinent/appropriate, 4 = do not know). Criteria for craniocaudal (CC), mediolateral-oblique (MLO) and lateral (ML), with and without Eklund manoeuvre, were included. This process was repeated after removing the less relevant criteria.

Results

Between first and second rounds, different results were obtained regarding the criteria to assess CC and MLO images. Details for anatomic areas were considered the most relevant by radiographers during the first round, while general criteria were prioritised during the second round. Radiologists focused more on analysis of the spread of the breast tissue, if the breast was aligned with detector’s centre and level of contrast. The analysis of implant flow, the BI anterior edge and the maximum retropulsion of BI when Eklund manoeuvre is performed were the specific aspects of BI imaging considered as relevant for assessment.

Conclusions

The importance of each criterion used to assess BI mammograms was not the same between radiographers and radiologists, suggesting the two groups of experts are looking for different requirements from the image. Further education and training is necessary to align strategies for assessing BI mammograms, and some criteria need to be adapted to reduce subjectivity.

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

Detection of breast cancer is reliant on optimal breast positioning and the production of quality images. Two projections, the mediolateral oblique and craniocaudal (CC), are routinely performed. Determination of successful positioning and inclusion of all breast tissue is achieved through meeting stated image quality criteria. For the CC view, current image quality criteria are inconsistent. Absence of reliable anatomical markers, other than the nipple, further contribute to difficulties in assessing the quality of CC views. The aim of this paper was to explore published international quality standards to identify and find the origin of any CC positioning criteria which might provide for quantitative assessment. The pectoralis major (pectoral) muscle was identified as a key posterior anatomical structure to establish optimum breast tissue inclusion on mammographic projections. It forms the first two of the three main CC metrics that are frequently reported (1) visualization of the pectoral muscle, (2) measurement of the posterior nipple line and (3) depiction of retroglandular fat. This literature review explores the origin of the three metrics, and discusses three key publications, spanning 1992 to 1994, on which subsequent image quality standards have been based. The evidence base to support published CC metrics is sometimes not specified and more often, the same set of publications are cited, most often without critical evaluation. To conclude, there remains uncertainty if the metrics explored for the CC view support objective evaluation and reproducibility to confirm optimal breast positioning and quality images.