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How does image quality affect radiologists’ perceived ability for image interpretation and lesion detection in digital mammography?

Boita, Joana ; van Engen, Ruben E. ; Mackenzie, Alistair ; Tingberg, Anders LU ; Bosmans, Hilde ; Bolejko, Anetta LU ; Zackrisson, Sophia LU ; Wallis, Matthew G. ; Ikeda, Debra M. and Van Ongeval, Chantal , et al. (2021) In European Radiology
Abstract

Objectives: To study how radiologists’ perceived ability to interpret digital mammography (DM) images is affected by decreases in image quality. Methods: One view from 45 DM cases (including 30 cancers) was degraded to six levels each of two acquisition-related issues (lower spatial resolution and increased quantum noise) and three post-processing-related issues (lower and higher contrast and increased correlated noise) seen during clinical evaluation of DM systems. The images were shown to fifteen breast screening radiologists from five countries. Aware of lesion location, the radiologists selected the most-degraded mammogram (indexed from 1 (reference) to 7 (most degraded)) they still felt was acceptable for interpretation. The median... (More)

Objectives: To study how radiologists’ perceived ability to interpret digital mammography (DM) images is affected by decreases in image quality. Methods: One view from 45 DM cases (including 30 cancers) was degraded to six levels each of two acquisition-related issues (lower spatial resolution and increased quantum noise) and three post-processing-related issues (lower and higher contrast and increased correlated noise) seen during clinical evaluation of DM systems. The images were shown to fifteen breast screening radiologists from five countries. Aware of lesion location, the radiologists selected the most-degraded mammogram (indexed from 1 (reference) to 7 (most degraded)) they still felt was acceptable for interpretation. The median selected index, per degradation type, was calculated separately for calcification and soft tissue (including normal) cases. Using the two-sided, non-parametric Mann-Whitney test, the median indices for each case and degradation type were compared. Results: Radiologists were not tolerant to increases (medians: 1.5 (calcifications) and 2 (soft tissue)) or decreases (median: 2, for both types) in contrast, but were more tolerant to correlated noise (median: 3, for both types). Increases in quantum noise were tolerated more for calcifications than for soft tissue cases (medians: 3 vs. 4, p = 0.02). Spatial resolution losses were considered less acceptable for calcification detection than for soft tissue cases (medians: 3.5 vs. 5, p = 0.001). Conclusions: Perceived ability of radiologists for image interpretation in DM was affected not only by image acquisition-related issues but also by image post-processing issues, and some of those issues affected calcification cases more than soft tissue cases. Key Points: • Lower spatial resolution and increased quantum noise affected the radiologists’ perceived ability to interpret calcification cases more than soft tissue lesion or normal cases. • Post-acquisition image processing-related effects, not only image acquisition-related effects, also impact the perceived ability of radiologists to interpret images and detect lesions. • In addition to current practices, post-acquisition image processing-related effects need to also be considered during the testing and evaluation of digital mammography systems.

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publication status
epub
subject
keywords
Breast cancer, Digital mammography, Perception, Quality control
in
European Radiology
publisher
Springer
external identifiers
  • scopus:85099750643
  • pmid:33475774
ISSN
0938-7994
DOI
10.1007/s00330-020-07679-8
language
English
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yes
id
65b005a5-52fa-4143-93a5-694350a8f3df
date added to LUP
2021-02-02 11:07:12
date last changed
2021-03-24 03:33:21
@article{65b005a5-52fa-4143-93a5-694350a8f3df,
  abstract     = {<p>Objectives: To study how radiologists’ perceived ability to interpret digital mammography (DM) images is affected by decreases in image quality. Methods: One view from 45 DM cases (including 30 cancers) was degraded to six levels each of two acquisition-related issues (lower spatial resolution and increased quantum noise) and three post-processing-related issues (lower and higher contrast and increased correlated noise) seen during clinical evaluation of DM systems. The images were shown to fifteen breast screening radiologists from five countries. Aware of lesion location, the radiologists selected the most-degraded mammogram (indexed from 1 (reference) to 7 (most degraded)) they still felt was acceptable for interpretation. The median selected index, per degradation type, was calculated separately for calcification and soft tissue (including normal) cases. Using the two-sided, non-parametric Mann-Whitney test, the median indices for each case and degradation type were compared. Results: Radiologists were not tolerant to increases (medians: 1.5 (calcifications) and 2 (soft tissue)) or decreases (median: 2, for both types) in contrast, but were more tolerant to correlated noise (median: 3, for both types). Increases in quantum noise were tolerated more for calcifications than for soft tissue cases (medians: 3 vs. 4, p = 0.02). Spatial resolution losses were considered less acceptable for calcification detection than for soft tissue cases (medians: 3.5 vs. 5, p = 0.001). Conclusions: Perceived ability of radiologists for image interpretation in DM was affected not only by image acquisition-related issues but also by image post-processing issues, and some of those issues affected calcification cases more than soft tissue cases. Key Points: • Lower spatial resolution and increased quantum noise affected the radiologists’ perceived ability to interpret calcification cases more than soft tissue lesion or normal cases. • Post-acquisition image processing-related effects, not only image acquisition-related effects, also impact the perceived ability of radiologists to interpret images and detect lesions. • In addition to current practices, post-acquisition image processing-related effects need to also be considered during the testing and evaluation of digital mammography systems.</p>},
  author       = {Boita, Joana and van Engen, Ruben E. and Mackenzie, Alistair and Tingberg, Anders and Bosmans, Hilde and Bolejko, Anetta and Zackrisson, Sophia and Wallis, Matthew G. and Ikeda, Debra M. and Van Ongeval, Chantal and Pijnappel, Ruud and Broeders, Mireille and Sechopoulos, Ioannis},
  issn         = {0938-7994},
  language     = {eng},
  month        = {01},
  publisher    = {Springer},
  series       = {European Radiology},
  title        = {How does image quality affect radiologists’ perceived ability for image interpretation and lesion detection in digital mammography?},
  url          = {http://dx.doi.org/10.1007/s00330-020-07679-8},
  doi          = {10.1007/s00330-020-07679-8},
  year         = {2021},
}