Mammography image quality and evidence based practice: Analysis of the demonstration of the inframammary angle in the digital setting

Spuur, Kelly; Webb, Jodi; Poulos, Ann; Nielsen, Sharon; Robinson, Wayne

doi:10.1016/j.ejrad.2018.01.004

Cited by 10 publications

(9 citation statements)

References 15 publications

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“…Image quality assessment is one of the most critical aspects for diagnosis since it combines many factors (equipment, positioning, technique, and radiographer-patient interaction). For that reason, it was not a surprise to verify that 22 parameters for assessing clinical IQ were identified in literature research [4,[47][48][49][50], with positioning being the larger group of items followed by artefacts, sharpness, and exposure parameters. Nevertheless, the published criteria and the recommendations provided by agencies and professional bodies do not cover IQ items to evaluate breast implants mammograms.…”

Section: Discussionmentioning

confidence: 96%

“…Criteria to assess mammography images available in the literature are mainly for mammograms without implants [4,6,15,21,27,46,47] and are related to specific anatomical details that should be included in the images (pectoral muscle, inframammary angle, retroglandular adipose tissue). Sharpness, artefacts, information/labeling, and exposure parameters were also parameters identified in the review that should be assessed to decide if the image is diagnostic.…”

Section: Literature Reviewmentioning

confidence: 99%

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Study of breast implants mammography examinations for identification of suitable image quality criteria

2020

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Purpose: To characterise the mammography technique used in breast cancer screening programmes for breast implants (BI) and to identify if the image quality (IQ) criteria available in literature are applicable to BI imaging. Methods: The study was conducted in two phases: literature review to find IQ criteria used in mammography combining keywords in several sources; and assessment of 1207 BI mammograms using the criteria that was identified previously to see if they were achieved or not. An observation grid was used to collect information about positioning, beam energy, compression force, and exposure mode. Descriptive statistics and Student's t test and χ 2 test were performed according to the nature of the variables. Results: Forty-seven out of 2188 documents were included in the analysis, with 13 items identified to assess the quality of positioning, 4 for sharpness, 3 for artefacts, and 2 for exposure parameters. After applying the criteria to BI mammograms, retroglandular fat was not included in 37.3% of the images. The "Pectoral-Nipple-Line" criterion was achieved in 35% of MLO/ML images. The placement of the implant (subpectoral/subglandular) or performing the Eklund had significant influence on the visible anatomy (p = < 0.005), alongside whether the breast was aligned to the detector's centre. Conclusions: Some of the criteria used to assess standard mammograms were not applicable to BI due to implant overlap. The alignment of the image with the detector's centre seems to have an impact on the amount of visible tissue. Further studies are necessary to define the appropriate protocol, technique, and suitable quality criteria to assess BI mammograms.

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Section: Discussionmentioning

confidence: 96%

Section: Literature Reviewmentioning

confidence: 99%

Study of breast implants mammography examinations for identification of suitable image quality criteria

2020

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“…Furthermore, studies have raised questions regarding the achievability and relevance of some of the criteria used. 2,12,25 The most recent attempts to improve systems for image quality assessment have, as far as we are aware, not reduced the subjectivity or lack of evidence. 5,26 This highlights the importance of standardized and evidencebased criteria in systems for assessment of breast positioning in order to achieve uniform assessment and optimal image quality in mammography.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, performing image quality classification is subjective as the assessment differs between assessors, both for PGMI and for other classification systems, raising questions about the reliability and validity of these systems. [10][11][12][13] In 2017, UK guidelines for mammographic screening stated that PGMI and EAR are no longer acceptable methods to assess image quality. 5 However, high-quality images are still a prerequisite in order to achieve a high sensitivity in diagnostic as well as screening mammography.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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“…With the implementation of digital mammography and breast tomosynthesis in BCSP across Europe, it is important to establish what are the best approaches for imaging the breast, including those with implants, namely protocols and techniques, but also how to evaluate and interpret the images. Considering there is limited evidence in published literature about IQ criteria for BI mammography assessment [7,9,[14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33], this study aimed to identify image quality criteria that can be applied to assess breast implant mammograms according to both radiologists' and radiographers' perspectives. It also aimed to explore the level of agreement regarding the priority of each criterion to distinguish between those that must be verified and those that are not a priority to determine when an examination needs to be rejected and/or repeated.…”

Section: Introductionmentioning

confidence: 99%

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

2020

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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.

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Mammography image quality and evidence based practice: Analysis of the demonstration of the inframammary angle in the digital setting

Cited by 10 publications

References 15 publications

Study of breast implants mammography examinations for identification of suitable image quality criteria

Study of breast implants mammography examinations for identification of suitable image quality criteria

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

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

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