Quality Improvement Initiatives to Assess and Improve PET/CT Injection Infiltration Rates at Multiple Centers

被引:19
作者
Wong, Terence Z. [1 ,2 ]
Benefield, Thad [2 ]
Masters, Shane [3 ]
Kiser, Jackson W. [4 ]
Crowley, James [4 ]
Osborne, Dustin [5 ]
Mawlawi, Osama [6 ]
Barnwell, James [7 ]
Gupta, Pawan [8 ]
Mintz, Akiva [9 ]
Ryan, Kelley A. [10 ]
Perrin, Steven R. [10 ]
Lattanze, Ronald K. [10 ]
Townsend, David W. [11 ]
机构
[1] Duke Univ, Durham, NC USA
[2] Univ N Carolina, Chapel Hill, NC 27515 USA
[3] Wake Forest Baptist Med Ctr, Winston Salem, NC USA
[4] Carilion Clin, Roanoke, VA USA
[5] Univ Tennessee, Grad Sch Med, Radiol Mol Imaging & Translat Res, Knoxville, TN USA
[6] Univ Texas MD Anderson Canc Ctr, Dept Imaging Phys, Houston, TX 77030 USA
[7] Wake Radiol, Raleigh, NC USA
[8] UCLA Hlth, David Geffen Sch Med, Dept Mol & Med Pharmacol, Div Nucl Med, Los Angeles, CA USA
[9] Columbia Univ, Med Ctr, New York, NY USA
[10] Lucerno Dynam LLC, Cary, NC USA
[11] A STAR NUS Clin Imaging Res Ctr, 14 Med Dr, Singapore 117599, Singapore
关键词
quality improvement; PET/CT; infiltration; extravasation; FDG; POSITRON-EMISSION-TOMOGRAPHY; FDG-PET/CT; CT; EXTRAVASATION; F-18-FDG; THERAPY; SCAN; SITE;
D O I
10.2967/jnmt.119.228098
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
PET/CT radiotracer infiltration is not uncommon and is often outside the imaging field of view. Infiltration can negatively affect image quality, image quantification, and patient management. Until recently, there has not been a simple way to routinely practice PET radiopharmaceutical administration quality control and quality assurance. Our objectives were to quantify infiltration rates, determine associative factors for infiltration, and assess whether rates could be reduced at multiple centers and then sustained. Methods: A "design, measure, analyze, improve, and control" quality improvement methodology requiring novel technology was used to try to improve PET/CT injection quality. Teams were educated on the importance of quality injections. Baseline infiltration rates were measured, center-specific associative factors were analyzed, team meetings were held, improvement plans were established and executed, and rates remeasured. To ensure that injection-quality gains were retained, real-time feedback and ongoing monitoring were used. Sustainability was assessed. Results: Seven centers and 56 technologists provided data on 5,541 injections. The centers' aggregated baseline infiltration rate was 6.2% (range, 2%-16%). On the basis of their specific associative factors, 4 centers developed improvement plans and reduced their aggregated infiltration rate from 8.9% to 4.6% (P < 0.0001). Ongoing injection monitoring showed sustainability. Significant variation was found in centerand technologist-level infiltration rates (P < 0.0001 and P = 0.0020, respectively). Conclusion: A quality improvement approach with new technology can help centers measure infiltration rates, determine associative factors, implement interventions, and improve and sustain injection quality. Because PET/CT im ages help guide patient management, the monitoring and improvement of radiotracer injection quality are important.
引用
收藏
页码:326 / 331
页数:6
相关论文
共 43 条
  • [21] Leveraging Quality Improvement and Shared Learning to Improve Infant Well-Child Visit Rates in Texas
    Rocha, Emily Stauffer
    Penate, Susana Beatriz
    Van Ramshorst, Ryan D.
    HEALTHCARE, 2024, 12 (19)
  • [22] Evaluation of PET quantitation accuracy among multiple discovery IQ PET/CT systems via NEMA image quality test
    Vallot, Delphine
    De Ponti, Elena
    Morzenti, Sabrina
    Gramek, Anna
    Pieczonka, Anna
    Llompart, Gabriel Reynes
    Siennicki, Jakub
    Deak, Paul
    Dutta, Chiranjib
    Uribe, Jorge
    Caselles, Olivier
    EJNMMI PHYSICS, 2020, 7 (01)
  • [23] Evaluation of PET quantitation accuracy among multiple discovery IQ PET/CT systems via NEMA image quality test
    Delphine Vallot
    Elena De Ponti
    Sabrina Morzenti
    Anna Gramek
    Anna Pieczonka
    Gabriel Reynés Llompart
    Jakub Siennicki
    Paul Deak
    Chiranjib Dutta
    Jorge Uribe
    Olivier Caselles
    EJNMMI Physics, 7
  • [24] Quality improvement initiative to improve safe injection practices by nurses in labour room of a tertiary care centre, India
    Pradeep, Jeena
    Kumari, Prabha
    Puri, Manju
    Pradeep, Charuta
    Gauba, Anu
    BMJ OPEN QUALITY, 2025, 13 (SUPPL_1)
  • [25] Diffuse Infiltration of Multiple Myeloma With Initial Manifestation of Cavernous Sinus Syndrome Unveiled by 18F-FDG PET/CT
    Li, Chunyan
    Shao, Fuqiang
    Yang, Yuhui
    Lan, Xiaoli
    CLINICAL NUCLEAR MEDICINE, 2019, 44 (09) : 746 - 747
  • [26] Do Quality Improvement Initiatives Improve Outcomes for Patients in Antiretroviral Programs in Low- and Middle-Income Countries? A Systematic Review
    Hargreaves, Sally
    Rustage, Keiran
    Nellums, Laura B.
    Bardfield, Joshua E.
    Agins, Bruce
    Barker, Pierre
    Massoud, M. Rashad
    Ford, Nathan P.
    Doherty, Meg
    Dougherty, Gillian
    Singh, Satvinder
    JAIDS-JOURNAL OF ACQUIRED IMMUNE DEFICIENCY SYNDROMES, 2019, 81 (05) : 487 - 496
  • [27] Rescue Protocol to Improve the Image Quality of 18F-FDG PET/CT Myocardial Metabolic Imaging
    Sun, Xiao-Xin
    Li, Shuheng
    Wang, Yawen
    Li, Wei
    Wei, Hongxing
    He, Zuo-Xiang
    CLINICAL NUCLEAR MEDICINE, 2021, 46 (05) : 369 - 374
  • [28] Pilot of a team-based quality improvement strategy to improve cardiovascular risk factors care in community mental health centers
    Murphy, Karly A.
    Gennusa, Joseph
    Dalcin, Arlene T.
    Cook, Courtney
    Goldsholl, Stacy
    Fink, Tyler
    Daumit, Gail L.
    Wang, Nae-Yuh
    Thompson, David
    Mcginty, Emma E.
    FRONTIERS IN PSYCHIATRY, 2025, 16
  • [29] Multiple training interventions significantly improve reproducibility of PET/CT-based lung cancer radiotherapy target volume delineation using an IAEA study protocol
    Konert, Tom
    Vogel, Wouter V.
    Everitt, Sarah
    MacManus, Michael P.
    Thorwarth, Daniela
    Fidarova, Elena
    Paez, Diana
    Sonke, Jan-Jakob
    Hanna, Gerard G.
    RADIOTHERAPY AND ONCOLOGY, 2016, 121 (01) : 39 - 45
  • [30] Clinical Pilot of a Deep Learning Elastic Registration Algorithm to Improve Misregistration Artifact and Image Quality on Routine Oncologic PET/CT
    Chamberlin, Jordan H.
    Schaefferkoetter, Joshua
    Hamill, James
    Kabakus, Ismail M.
    Horn, Kevin P.
    O'Doherty, Jim
    Elojeimy, Saeed
    ACADEMIC RADIOLOGY, 2025, 32 (02) : 1015 - 1025