How does image quality affect radiologists’ perceived ability for image interpretation and lesion detection in digital mammography?
Autor: | Ioannis Sechopoulos, Anetta Bolejko, Mireille J. M. Broeders, Sophia Zackrisson, Debra M. Ikeda, Chantal Van Ongeval, Joana Boita, Alistair Mackenzie, Matthew G. Wallis, Ruben E. van Engen, Hilde Bosmans, Ruud M. Pijnappel, Anders Tingberg |
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Přispěvatelé: | Inorganic Materials Science, MESA+ Institute, Sechopoulos, Ioannis [0000-0001-9615-8205], Apollo - University of Cambridge Repository |
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
medicine.medical_specialty
Digital mammography Image quality media_common.quotation_subject Breast Neoplasms NOISE Breast cancer Radiologists medicine Contrast (vision) Humans Radiology Nuclear Medicine and imaging Breast Image resolution Neuroradiology media_common Science & Technology medicine.diagnostic_test business.industry Physics Radiology Nuclear Medicine & Medical Imaging Soft tissue Calcinosis Quality control Interventional radiology General Medicine medicine.disease Women's cancers Radboud Institute for Health Sciences [Radboudumc 17] PROCESSING ALGORITHMS Radiographic Image Enhancement Female Perception Radiology business Life Sciences & Biomedicine Calcification Mammography |
Zdroj: | European radiology, 31(7), 5335-5343. Springer European Radiology European Radiology, 31, 7, pp. 5335-5343 European Radiology, 31, 5335-5343 |
ISSN: | 0938-7994 |
Popis: | 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. |
Databáze: | OpenAIRE |
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