TY - JOUR
T1 - High-Frequency Ultrasound
T2 - Obtaining Optimal Images and the Effect of Image Artifacts on Image Quality
AU - Burk, Ruth S.
AU - Grap, Mary Jo
AU - Lucas, Valentina
AU - Munro, Cindy L.
AU - Wetzel, Paul A.
AU - Schubert, Christine M.
N1 - Funding Information:
This study was supported by funding from NIH, NR010381 (Grap PI). The authors acknowledge Mr. Harold M. Mess-ler for technical assistance.
Publisher Copyright:
© Copyright 2017, Copyright 2017 by Mary Ann Liebert, Inc. 2017.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/11
Y1 - 2017/11
N2 - Objective: High-frequency ultrasound (HFUS) images are being researched for use in the prevention, detection, and monitoring of pressure injuries in patients at risk. This seminal longitudinal study in mechanically ventilated adults describes image quality, the incidence of image artifacts, and their effect on image quality in critically ill subjects. Approach: Mechanically ventilated subjects from three adult intensive care units were enrolled, and multiple sacral images from each subject were obtained daily. Using a subset of best image per patient per day, artifacts were grouped, and their effect on image quality was statistically evaluated. Results: Of a total of 1761 images collected from 137 subjects, 8% were rated as poor. In the subset, 70% had good quality ratings. Four groups of artifacts were identified as follows: "bubbles," "texture problems," "layer nondifferentiation," and "reduced area for evaluation." Artifacts from at least one group were found in 83% of images. Bubbles were most frequently seen, but artifacts with adverse effect on image quality were "layer nondifferentiation," "texture problems," and "reduced area for evaluation." Innovation: HFUS image evaluation is still in the development phase with respect to tissue injury use. Artifacts are generally omnipresent. Quickly recognizing artifacts that most significantly affect image quality during scanning will result in higher quality images for research and clinical applications. Conclusion: Good quality images were achievable in study units; although frequent artifacts were present in images, in general, they did not interfere with evaluation. Artifacts related to "layer nondifferentiation" was the greatest predictor of poor image quality, prompting operators to immediately rescan the area.
AB - Objective: High-frequency ultrasound (HFUS) images are being researched for use in the prevention, detection, and monitoring of pressure injuries in patients at risk. This seminal longitudinal study in mechanically ventilated adults describes image quality, the incidence of image artifacts, and their effect on image quality in critically ill subjects. Approach: Mechanically ventilated subjects from three adult intensive care units were enrolled, and multiple sacral images from each subject were obtained daily. Using a subset of best image per patient per day, artifacts were grouped, and their effect on image quality was statistically evaluated. Results: Of a total of 1761 images collected from 137 subjects, 8% were rated as poor. In the subset, 70% had good quality ratings. Four groups of artifacts were identified as follows: "bubbles," "texture problems," "layer nondifferentiation," and "reduced area for evaluation." Artifacts from at least one group were found in 83% of images. Bubbles were most frequently seen, but artifacts with adverse effect on image quality were "layer nondifferentiation," "texture problems," and "reduced area for evaluation." Innovation: HFUS image evaluation is still in the development phase with respect to tissue injury use. Artifacts are generally omnipresent. Quickly recognizing artifacts that most significantly affect image quality during scanning will result in higher quality images for research and clinical applications. Conclusion: Good quality images were achievable in study units; although frequent artifacts were present in images, in general, they did not interfere with evaluation. Artifacts related to "layer nondifferentiation" was the greatest predictor of poor image quality, prompting operators to immediately rescan the area.
KW - high-frequency ultrasound
KW - intensive care unit
KW - ultrasound analysis
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U2 - 10.1089/wound.2017.0727
DO - 10.1089/wound.2017.0727
M3 - Article
AN - SCOPUS:85032837678
VL - 6
SP - 383
EP - 391
JO - Advances in Wound Care
JF - Advances in Wound Care
SN - 2162-1918
IS - 11
ER -