Enhanced visualization of mobile chest X-ray images in the intensive care setting using software scatter correction

被引:2
|
作者
Targett, Harry [1 ]
Hutchinson, Dominic [2 ]
Hartley, Richard [1 ]
McWilliam, Richard [3 ]
Lopez, Ben [3 ]
Crone, Ben [3 ]
Bonner, Stephen [2 ]
机构
[1] South Tees Hosp NHS Fdn Trust, James Cook Univ Hosp, Dept Clin Radiol, Middlesbrough, Cleveland, England
[2] South Tees Hosp NHS Fdn Trust, James Cook Univ Hosp, Dept Crit Care, Middlesbrough, Cleveland, England
[3] IBEX Innovat Ltd, Explorer 2,NET Pk, Sedgefield TS21 3FF, England
基金
“创新英国”项目;
关键词
Digital radiography; mobile chest X-ray; scatter correction; technology assessments; DOSE REDUCTION; RADIOGRAPHY; PERFORMANCE; QUALITY; ALIGNMENT; CONTRAST;
D O I
10.1177/02841851221087631
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background Mobile chest X-ray (CXR) scans are performed within intensive treatment units (ITU) without anti-scatter grids for confirming tube and line hardware placement. Assessment is therefore challenging due to degraded subject contrast resulting from scatter. Purpose To evaluate the efficacy of a software scatter correction method (commercially named Trueview) for enhanced hardware visualization and diagnostic quality in the ITU setting. Material and Methods A total of 30 CXR scans were processed using Trueview and compared with standard original equipment manufacturer (OEM) images via observer scoring study involving two radiology and four ITU doctors to compare visualization of tubes and lines. Results were analyzed to determine observer preference and likelihood of diagnostic quality. Results Reviewers were more likely to score Trueview higher than OEM for mediastinal structures, bones, retrocardiac region, tube visibility, and tube safety (P < 0.01). Visual grading characteristic analysis suggested a clinical preference for Trueview compared with OEM for mediastinal structures (area under the visual grading characteristic curve [AUC(VGC)] = 0.60, 95% confidence interval [CI] = 0.55-0.65), bones (AUC(VGC) = 0.61, 95% CI = 0.55-0.66), retrocardiac region (AUC(VGC) = 0.64, 95% CI = 0.59-0.69), tube visibility (AUC(VGC) = 0.65, 95% CI = 0.60-0.70), and tube safety (AUC(VGC) = 0.68, 95% CI = 0.64-0.73). Reviewers were indifferent to visualization of the lung fields (AUC(VGC) = 0.49, 95% CI = 0.44-0.55). Registrars (3/6 reviewers) were indifferent to the mediastinal structure regions (AUC(VGC) = 0.54, 95% CI = 0.47-0.62). Conclusion Reviewers were more confident in identifying the placement and safety of tubes and lines when reviewing Trueview images than they were when reviewing OEM.
引用
收藏
页码:563 / 571
页数:9
相关论文
共 50 条
  • [1] Development of an image quality evaluation system for bedside chest X-ray images using scatter correction processing
    Mori, Kazuya
    Negishi, Toru
    RADIOLOGICAL PHYSICS AND TECHNOLOGY, 2025, 18 (01) : 249 - 257
  • [2] Chest x-ray in the intensive care unit
    Galimany Masclans, Jordi
    Berlanga Olalla, Raquel
    Pernas Canadell, Juan Carlos
    IMAGEN DIAGNOSTICA, 2013, 4 (01): : 13 - 19
  • [3] EVALUATION OF DOSE REDUCTION POTENTIALS OF A NOVEL SCATTER CORRECTION SOFTWARE FOR BEDSIDE CHEST X-RAY IMAGING
    Renger, Bernhard
    Brieskorn, Carina
    Toth, Vivien
    Mentrup, Detlef
    Jockel, Sascha
    Lohoefer, Fabian
    Schwarz, Martin
    Rummeny, Ernst J.
    Noel, Peter B.
    RADIATION PROTECTION DOSIMETRY, 2016, 169 (1-4) : 60 - 67
  • [4] The principles and effectiveness of X-ray scatter correction software for diagnostic X-ray imaging: A scoping review
    Sayed, Mohammad
    Knapp, Karen M.
    Fulford, Jon
    Heales, Christine
    Alqahtani, Saeed J.
    EUROPEAN JOURNAL OF RADIOLOGY, 2023, 158
  • [5] A software-based x-ray scatter correction method for breast tomosynthesis
    Feng, Steve Si Jia
    Sechopoulos, Ioannis
    MEDICAL PHYSICS, 2011, 38 (12) : 6643 - 6653
  • [6] Automatic correction of x-ray scatter and veiling glare in simulated fluoroscopic images
    Close, RA
    Shah, KC
    Whiting, JS
    PHYSICS OF MEDICAL IMAGING, 1998, 3336 : 668 - 674
  • [7] Pneumonia Detection in Chest X-Ray Images Using Enhanced Restricted Boltzmann Machine
    Wahid, Fazli
    Azhar, Sania
    Ali, Sikandar
    Zia, Muhammad Sultan
    Abdulaziz Almisned, Faisal
    Gumaei, Abdu
    JOURNAL OF HEALTHCARE ENGINEERING, 2022, 2022
  • [8] A Deep Learning-Based Scatter Correction of Simulated X-ray Images
    Lee, Heesin
    Lee, Joonwhoan
    ELECTRONICS, 2019, 8 (09)
  • [9] Introduction of a manual mobile cassette positioning device for chest X-ray examinations on intensive care patients
    Schaefer, Stefan B.
    Roswag, Ilse
    Krombach, Gabriele A.
    INTENSIVE CARE MEDICINE, 2016, 42 (03) : 475 - 476
  • [10] Introduction of a manual mobile cassette positioning device for chest X-ray examinations on intensive care patients
    Stefan B. Schäfer
    Ilse Roswag
    Gabriele A. Krombach
    Intensive Care Medicine, 2016, 42 : 475 - 476