Artifacts in contrast-enhanced mammography: are there differences between vendors?

Neppalli, Saish; Kessell, Meredith; Madeley, Carolyn; Hill, Melissa L.; Vlaskovsky, Philip; Taylor, Donna

doi:10.1016/j.clinimag.2021.06.031

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…Image processing applied to the images should therefore be functioning as designed, and this should enable the evaluation of artefacts such as the halo artefact. Although there was some evidence of a halo for the systems, the degree was much lower than that reported in some studies (Yagil et al 2016, Neppalli et al 2021, Gennaro et al 2022. This is rather a simple test object and lacks the anatomical detail or realistic function to assess artefacts such as transient retention of contrast, negative contrast enhancement or air trapping (Bhimani et al 2017, Nori et al 2020.…”

Section: Discussionmentioning

confidence: 86%

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry

Marshall,

Cockmartin,

Bosmans

2023

Phys. Med. Biol.

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Part II of this study describes constancy tests for artefacts and image uniformity, exposure time, and phantom-based dosimetry; these are applied to four mammography systems equipped with CEM capability. Artefacts were tested using a breast phantom that simulated breast shape and thickness change at the breast edge. Image uniformity was assessed using rectangular poly(methyl)methacrylate PMMA plates at phantom thicknesses of 20, 40 and 60mm, for the low energy (LE), high energy (HE) images and the recombined CEM image. Uniformity of signal and of the signal to noise ratio (SNR) was quantified. To estimate CEM exposure times, breast simulating blocks were imaged in automatic exposure mode (AEC). The resulting x-ray technique factors were then set manually and exposure time for LE and HE images and total CEM acquisition time was measured with a multimeter. Mean glandular dose (MGD) was assessed as a function of simulated breast thickness using three different phantom compositions: i) glandular and adipose breast tissue simulating blocks combined to give glandularity values that were typical of those in a screening population, as thickness was changed ii) PMMA sheets combined with polyethylene blocks iii) PMMA sheets with spacers. Image uniformity was superior for LE compared to HE images. Two systems did not generate recombined images for the uniformity test when the detector was fully covered. Acquisition time for a CEM image pair for a 60mm thick breast equivalent phantom ranged from 3.4s to 10.3s. Phantom composition did not have a strong influence on MGD, with differences generally smaller than 10%. MGD for the HE images was lower than for the LE images, by a factor of between 1.3 and 4.0, depending on system and simulated breast thickness. When combined with the iodine signal assessment in part I, these tests provide a comprehensive assessment of CEM system imaging performance.

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Section: Discussionmentioning

confidence: 86%

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry

Marshall,

Cockmartin,

Bosmans

2023

Phys. Med. Biol.

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“…Therefore, it is still necessary to stress the importance of high-quality images. Neppalli et al reported [45] that the type, incidence, and severity of CEM-specific artifacts differ between image device vendors. To date, several image-processing algorithms have been developed to reduce artifacts and improve the image quality [46][47][48].…”

Section: Table 4 Summary Of Additional Exploratory Analysis For Corre...mentioning

confidence: 99%

Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images

et al. 2022

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Background Radiomics plays an important role in the field of oncology. Few studies have focused on the identification of factors that may influence the classification performance of radiomics models. The goal of this study was to use contrast-enhanced mammography (CEM) images to identify factors that may potentially influence the performance of radiomics models in diagnosing breast lesions. Methods A total of 157 women with 161 breast lesions were included. Least absolute shrinkage and selection operator (LASSO) regression and the random forest (RF) algorithm were employed to construct radiomics models. The classification result for each lesion was obtained by using 100 rounds of five-fold cross-validation. The image features interpreted by the radiologists were used in the exploratory factor analyses. Univariate and multivariate analyses were performed to determine the association between the image features and misclassification. Additional exploratory analyses were performed to examine the findings. Results Among the lesions misclassified by both LASSO and RF ≥ 20% of the iterations in the cross-validation and those misclassified by both algorithms ≤5% of the iterations, univariate analysis showed that larger lesion size and the presence of rim artifacts and/or ripple artifacts were associated with more misclassifications among benign lesions, and smaller lesion size was associated with more misclassifications among malignant lesions (all p < 0.050). Multivariate analysis showed that smaller lesion size (odds ratio [OR] = 0.699, p = 0.002) and the presence of air trapping artifacts (OR = 35.568, p = 0.025) were factors that may lead to misclassification among malignant lesions. Additional exploratory analyses showed that benign lesions with rim artifacts and small malignant lesions (< 20 mm) with air trapping artifacts were misclassified by approximately 50% more in rate compared with benign and malignant lesions without these factors. Conclusions Lesion size and artifacts in CEM images may affect the diagnostic performance of radiomics models. The classification results for lesions presenting with certain factors may be less reliable.

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“…[1][2][3] In the dual-shot (DS) imaging procedure, HE and LE images are acquired sequentially with a time interval between exposures, often leading to motion artifacts. [4][5][6] One solution to this problem is using a dual-layer (DL) detector for simultaneous acquisition of HE and LE images with a single exposure. 7 This concept has attracted a lot of attention in spectral imaging applications.…”

Section: Introductionmentioning

confidence: 99%

Cascaded system analysis of a direct-indirect dual-layer flat-panel-detector for contrast-enhanced breast imaging

Wu,

Duan,

Huang

et al. 2024

17th International Workshop on Breast Imaging (IWBI 2024)

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Artifacts in contrast-enhanced mammography: are there differences between vendors?

Cited by 7 publications

References 13 publications

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: II. Artefacts/uniformity, exposure time and phantom-based dosimetry

Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images

Cascaded system analysis of a direct-indirect dual-layer flat-panel-detector for contrast-enhanced breast imaging

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