Ruth S Burk1, Mary Jo Grap1, Valentina Lucas2, Cindy L Munro3, Paul A Wetzel4, Christine M Schubert5. 1. Department of Adult Health and Nursing Systems School of Nursing, Virginia Commonwealth University, Richmond, Virginia. 2. Department of Surgery, Virginia Commonwealth University Health System, Richmond, Virginia. 3. College of Nursing, University of South Florida, Tampa, Florida. 4. Biomedical Engineering Department, School of Engineering, Virginia Commonwealth University, Richmond, Virginia. 5. Department of Mathematics and Statistics, Air Force Institute of Technology, Wright-Patterson Air Force Base, Dayton, Ohio.
Abstract
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.
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.
Entities:
Keywords:
high-frequency ultrasound; intensive care unit; ultrasound analysis
Authors: Ruth S Burk; Angela Parker; Lisa Sievers; Melissa B Rooney; Anathea Pepperl; Christine M Schubert; Mary Jo Grap Journal: Intensive Crit Care Nurs Date: 2015-01-27 Impact factor: 3.072
Authors: Mary Jo Grap; Ruth Srednicki Burk; Valentina Lucas; Cindy L Munro; Paul A Wetzel; Christine M Schubert Journal: Intensive Crit Care Nurs Date: 2014-10-16 Impact factor: 3.072
Authors: Mary Jo Grap; Cindy L Munro; Paul A Wetzel; Christine M Schubert; Anathea Pepperl; Ruth S Burk; Valentina Lucas Journal: Am J Crit Care Date: 2016-05 Impact factor: 2.228
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