A Novel Approach to Detecting Contrast Extravasation in Computed Tomography: Evaluating the Injection Pressure-to-Injection Rate Ratio.


Journal

Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942

Informations de publication

Date de publication:
09 May 2024
Historique:
medline: 8 5 2024
pubmed: 8 5 2024
entrez: 8 5 2024
Statut: aheadofprint

Résumé

The purpose of this study was to evaluate the usefulness of the injection pressure-to-injection rate (IPIR) ratio for the early detection of contrast extravasation at the venipuncture site during contrast-enhanced computed tomography. We retrospectively enrolled 57,528 patients who underwent contrast-enhanced computed tomography examinations in a single hospital. The power injector recorded the contrast injection pressure at 0.25-second intervals. We constructed logistic regression models using the IPIR ratio as the independent variable and extravasation occurrence as the dependent variable (IPIR ratio models) at 1, 2, 3, 4, 5, and 6 seconds after the start of contrast administration. Univariate logistic regression models in which injection pressure is used as an independent variable (injection pressure models) were also constructed as a reference baseline. The performance of the models was evaluated with the area under the receiver operating characteristic curves. Of the 57,528 cases, 46,022 were assigned to the training group and 11,506 were assigned to the test group, which included 112 extravasation cases (0.24%) in the training group and 28 (0.24%) in the test group. The area under the receiver operating characteristic curves for the IPIR ratio models and injection pressure models were 0.555 versus 0.563 at t = 1 (P = 0.270), 0.712 versus 0.678 at t = 2 (P = 0.305), 0.758 versus 0.693 at t = 3 (P = 0.032), 0.776 versus 0.688 at t = 4 (P = 0.005), 0.810 versus 0.699 at t = 5 (P = 0.002), and 0.811 versus 0.706 at t = 6 (P = 0.002). The IPIR ratio models perform better in detecting contrast extravasation at 3 to 6 seconds after the start of contrast administration than injection pressure models.

Identifiants

pubmed: 38718419
doi: 10.1097/RCT.0000000000001614
pii: 00004728-990000000-00325
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

Toshinori Hirai has received research support from Canon Medical Systems and is a guarantor of this study. Takeshi Nakaura has received research support from Nemoto Kyorindo Co, Ltd. Nemoto Kyorindo Co, Ltd had no control over the interpretation, writing, or publication of this work. There are no conflicts of interest to report for the other authors.

Références

Heshmatzadeh Behzadi A, Farooq Z, Newhouse JH, et al. MRI and CT contrast media extravasation: a systematic review. Medicine (Baltimore). 2018;97:e0055.
Hwang EJ, Shin CI, Choi YH, et al. Frequency, outcome, and risk factors of contrast media extravasation in 142,651 intravenous contrast-enhanced CT scans. Eur Radiol. 2018;28:5368–5375.
Dykes TM, Bhargavan-Chatfield M, Dyer RB. Intravenous contrast extravasation during CT: a National Data Registry and practice quality improvement initiative. J Am Coll Radiol. 2015;12:183–191.
Wilson BG. Contrast media-induced compartment syndrome. Radiol Technol. 2011;83:63–77.
Bae KT. Intravenous contrast medium administration and scan timing at CT: considerations and approaches. Radiology. 2010;256:32–61.
Pfitzner J. Poiseuille and his law. Anaesthesia. 1976;31:273–275.
Pisano A. From tubes and catheters to the basis of hemodynamics: viscosity and Hagen–Poiseuille equation. In: Pisano A, ed. Physics for Anesthesiologists and Intensivists: From Daily Life to Clinical Practice. Cham, Switzerland: Springer International Publishing:89–98.
DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–845.
Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3:32–35.
Perkins NJ, Schisterman EF. The Youden index and the optimal cut-point corrected for measurement error. Biom J. 2005;47:428–441.
Ding S, Meystre NR, Campeanu C, et al. Contrast media extravasations in patients undergoing computerized tomography scanning: a systematic review and meta-analysis of risk factors and interventions. JBI Database System Rev Implement Rep. 2018;16:87–116.
Wienbeck S, Fischbach R, Kloska SP, et al. Prospective study of access site complications of automated contrast injection with peripheral venous access in MDCT. Am J Roentgenol. 2010;195:825–829.
Sinan T, Al-Khawari H, Chishti FA, et al. Contrast media extravasation: manual versus power injector. Med Princ Pract. 2005;14:107–110.
Schwab SA, Uder M, Anders K, et al. Peripheral intravenous power injection of iodinated contrast media through 22G and 20G cannulas: can high flow rates be achieved safely? A clinical feasibility study. Rofo. 2009;181:355–361.
Shaqdan K, Aran S, Thrall J, et al. Incidence of contrast medium extravasation for CT and MRI in a large academic medical centre: a report on 502,391 injections. Clin Radiol. 2014;69:1264–1272.
Kok M, Mihl C, Hendriks BMF, et al. Patient comfort during contrast media injection in coronary computed tomographic angiography using varying contrast media concentrations and flow rates: results from the EICAR trial. Invest Radiol. 2016;51:810–815.
Birnbaum BA, Nelson RC, Chezmar JL, et al. Extravasation detection accessory: clinical evaluation in 500 patients. Radiology. 1999;212:431–438.
Saade C, Brennan P. Clinical implementation of the new MEDRAD XDS contrast extravasation detector for multidetector computed tomography. J Med Imaging Radiat Sci. 2011;42:179–182.
Hoff L, Brabrand K, Andersen NB, et al. Monitoring x-ray contrast agent injections with Doppler ultrasound. In: 2008 IEEE Ultrasonics Symposium; November 2008; pp. 13–16. Available at: https://ieeexplore.ieee.org/document/4803268. Accessed April 22, 2024.

Auteurs

Naoki Kobayashi (N)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Takeshi Nakaura (T)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Kaori Shiraishi (K)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Hiroyuki Uetani (H)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Yasunori Nagayama (Y)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Masafumi Kidoh (M)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Seitaro Oda (S)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Daisuke Sakabe (D)

Department of Central Radiology, Kumamoto University Hospital.

Ryuji Ikeda (R)

Department of Central Radiology, Kumamoto University Hospital.

Masahiro Hatemura (M)

Department of Central Radiology, Kumamoto University Hospital.

Michiyo Murakami (M)

Department of Central Radiology, Kumamoto University Hospital.

Yoshinori Funama (Y)

Medical Physics, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.

Toshinori Hirai (T)

From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.

Classifications MeSH