Systematic optimization of ultrasound grayscale imaging presets and its application in abdominal scanning. Issue 10 (11th August 2020)

• Record Type: Journal Article
• Authors: Long, Zaiyang; Zhou, Wei; Tradup, Donald J.; Stekel, Scott F.; Callstrom, Matthew R.; Hangiandreou, Nicholas J.
• Is Part Of: Journal of applied clinical medical physics. Volume 21:Issue 10(2020)
• Page Start: 192
• Page End: 199
• Publication Date: 2020-08-11
• Subjects: grayscale -- image preset -- preset optimization -- ultrasound; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13000
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Purpose: Ultrasound grayscale imaging preset optimization has often been qualitative and dependent upon vendor application specialists. This study aimed to propose a systematic approach for grayscale imaging preset optimization and apply the approach in a clinical abdominal scan setting. Methods: A six‐step approach was detailed including identification of clinical task, adjustment of basic parameters, fine‐tuning of advanced parameters, image performance metrics confirmation, clinical evaluation and data analysis, and implementation of new presets and monitoring of clinical usage. Its application in an abdominal scanning task was described for each step with phantoms, volunteers, and software tools. Results: Clinical image data analytics facilitated the understanding of the imaging task, relevant transducers, and target characteristics, in addition to specific requests from radiologists. Quantitative measurements were made on global image contrast and gray map function. In addition, clinically relevant phantoms and volunteer scans without and with acoustic distortion layers were involved to determine the new presets. Furthermore, phantom signal to noise ratio study and clinical evaluation using volunteers with different body habitus were utilized to confirm the superiority of the new presets. Quantitative clinical usage monitoring demonstrated successful implementation of the new presets. Conclusions: A systematic approach for grayscale imaging preset optimization has been proposed and successfully applied for a specific clinical task. This approach was designed to be generalizable and relatively flexible, which would facilitate movement away from previous qualitative and subjective approaches.