Automated contrast medium monitoring system for computed tomography – Intra-institutional audit

Lauretti, Dario Luca; Neri, Emanuele; Faggioni, Lorenzo; Paolicchi, Fabio; Caramella, Davide; Bartolozzi, Carlo

doi:10.1016/j.compmedimag.2015.08.004

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…The mean volume and the mean injection rate were low in this study, corresponding to 83.19 ± 7.29 mL and 2.90 ± 0.34 mL/s, respectively. Lauretti et al, in an intrainstitutional audit, reported a mean volume of 93.73 ± 17.58 mL and a flow rate of 3.53 ± 0.89 mL/s [ 24 ]. Paradoxically, we observed in this study that the higher the ICM concentration, the greater the volume injected.…”

Section: Discussionmentioning

confidence: 99%

“…In principle, the volume of the iodinated contrast medium to be injected should take into account the concentration by injecting the same dose of iodine for patients of the same weight [ 25 ]. The implementation of an automated iodinated contrast media management system, as demonstrated in the study by Lauretti et al, could assist in the effective management by improving and harmonising the quality of injection protocols [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo)

Gbande

N’timon

Tchakpedeou³

et al. 2023

Radiology Research and Practice

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Background. There is great variability between centers regarding contrast injection protocols. They should only be injected if they can provide useful information for diagnosis with the necessary and sufficient quantity of iodine. We wanted to know through this study if the use of iodinated contrast media is optimised in abdominal CT scans performed for cancer assessment in Lomé. Materials and Methods. It was a cross-sectional, descriptive, and analytical study with a prospective collection over a period of 6 months in three CT units in Lomé. It involved abdominal CT scans performed for oncological evaluation. Data were reported as the mean ± standard deviation. The Pearson correlation coefficient, ANOVA, chi-square, and the Fisher test were used. Results. A total of 218 examinations were recorded. The female sex represented 56.88% of the patients. The mean age was 50.92 ± 15.78 years. The mean weight was 70.46 ± 15.23 kg. The mean BMI was 24.91 ± 5.32 kg/m2. The examinations were performed with a voltage of 120 kV in 195 cases (89.45%). The mean dose of injected iodine was 0.42 ± 0.09 gI/kg with a dose of 0.40 gI/kg at 80 kV and 0.45 gI/kg at 130 kV. The mean injection rate was 2.90 ± 0.34 mL/s. The mean injected volume was 83.19 ± 7.29 mL. The mean duration of the injection was 30.60 ± 7.39 s. The mean iodine delivery rate was 0.98 ± 0.17 gI/s. There was no saline injection in 152 cases (69.72%). Liver contrast enhancement was satisfactory in 94.5% of cases. There was a strong negative linear correlation between the dose of injected iodine and weight. Conclusions. Optimization guidelines for the use of iodinated contrast media are not always applied. Therefore, monitoring and benchmarking programmes for iodinated contrast injection protocols that involve all radiology personnel should be implemented.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo)

Gbande

N’timon

Tchakpedeou³

et al. 2023

Radiology Research and Practice

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“…Johnson et al's findings did not find a correlation between liver parenchyma enhancement with weight because their focus was variation for the same patient between multiple visits. Other authors have reported automated solutions for obtaining contrast injection parameters 25 . Several reports have looked at the actual enhancement amount providing a measure equivalent to Q-ICE, but their methodology required noncontrast and enhanced phases 26–28 .…”

Section: Discussionmentioning

confidence: 99%

“…Other authors have reported automated solutions for obtaining contrast injection parameters. 25 Several reports have looked at the actual enhancement amount providing a measure equivalent to Q-ICE, but their methodology required noncontrast and enhanced phases. [26][27][28] Quantification of iodine contrast enhancement as we have implemented in this article mitigates the need for a dedicated noncontrast series.…”

Section: Discussionmentioning

confidence: 99%

A Metric for Quantification of Iodine Contrast Enhancement (Q-ICE) in Computed Tomography

Szczykutowicz

Viggiano

Rose³

et al. 2021

J Comput Assist Tomogr

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Background: Poor contrast enhancement is related to issues with examination execution, contrast prescription, computed tomography (CT) protocols, and patient conditions. Currently, our community has no metric to monitor true enhancement on routine single-phase examinations because this requires knowledge of both pre-and postcontrast CT number. Purpose:We propose an automatable solution to quantifying contrast enhancement without requiring a dedicated noncontrast series. Methods:The difference in CT number between a target region in an enhanced and unenhanced image defines the metric "quantification of iodine contrast enhancement" (Q-ICE). Quantification of iodine contrast enhancement uses the noncontrast bolus tracking baseline image from routine abdominal examinations, which mitigates the need for a dedicated noncontrast series. We applied this method retrospectively to 312 patient livers from 2 sites between 2017 and 2020. Each site used a weight-based contrast injection protocol for weights 60 to 113 kg and a constant volume less than 60 kg and greater than 113 kg. Hypothesis testing was performed to compare Q-ICE between sites and detect Q-ICE dependence on weight and kilovoltage (kV).Results: Mean Q-ICE differed between sites (P = 0.004) by 4.96 Hounsfield unit with 95% confidence interval (1.63-8.28), albeit this difference was roughly 2 times smaller than the SD in Q-ICE across patients at a single site. For patients between 60 and 113 kg, we did not observe evidence of Q-ICE varying with patient weight (P = 0.920 and 0.064 for 120 and 140 kV, respectively). The Q-ICE did vary with patient weight for patients less than 60 kg (P = 0.003) and greater than 113 kg (P = 0.04). We observed a roughly 10 Hounsfield unit reduction in Q-ICE liver for patients scanned with 140 versus 120 kV. We observed several underenhancing examinations with an arterial phase appearance motivating our CT protocol optimization team to consider increasing the delay for slowly enhancing patients.Conclusions: A quality metric for quantifying CT contrast enhancement was developed and suggested tangible opportunities for quality improvement and potential financial savings.

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Usage of structured reporting in radiological practice: results from an Italian online survey

Faggioni

Coppola

Ferrari³

et al. 2016

Eur Radiol

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Automated contrast medium monitoring system for computed tomography – Intra-institutional audit

Cited by 6 publications

References 31 publications

Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo)

Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo)

A Metric for Quantification of Iodine Contrast Enhancement (Q-ICE) in Computed Tomography

Usage of structured reporting in radiological practice: results from an Italian online survey

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