Contrast medium protocols in routine chest CT: a survey study

Henning, Mette Karen; Aaløkken, Trond Mogens; Johansen, Safora

doi:10.1177/0284185121997111

Cited by 4 publications

(1 citation statement)

References 53 publications

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“…These infrequent resistance mutations will be evaluated in the continuous research. Thirdly, the optimal strategy for contrast enhancement in chest CT protocols is being debated [ 26 ]. Some guidelines and authors specifically recommend scanning after a delay of 20 − 35 s [ 27 , 28 ].…”

Section: Discussionmentioning

confidence: 99%

CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

Li,

Lv,

Wang

et al. 2023

Eur Radiol Exp

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Background To evaluate the value of computed tomography (CT) radiomics in predicting the risk of developing epidermal growth factor receptor (EGFR) T790M resistance mutation for metastatic non-small lung cancer (NSCLC) patients before first-line EGFR-tyrosine kinase inhibitors (EGFR-TKIs) therapy. Methods A total of 162 metastatic NSCLC patients were recruited and split into training and testing cohort. Radiomics features were extracted from tumor lesions on nonenhanced CT (NECT) and contrast-enhanced CT (CECT). Radiomics score (rad-score) of two CT scans was calculated respectively. A nomogram combining two CT scans was developed to evaluate T790M resistance within up to 14 months. Patients were followed up to calculate the time of T790M occurrence. Models were evaluated by area under the curve at receiver operating characteristic analysis (ROC-AUC), calibration curve, and decision curve analysis (DCA). The association of the nomogram with the time of T790M occurrence was evaluated by Kaplan–Meier survival analysis. Results The nomogram constructed with the rad-score of NECT and CECT for predicting T790M resistance within 14 months achieved the highest ROC-AUCs of 0.828 and 0.853 in training and testing cohorts, respectively. The DCA showed that the nomogram was clinically useful. The Kaplan–Meier analysis showed that the occurrence time of T790M difference between the high- and low-risk groups distinguished by the rad-score was significant (p < 0.001). Conclusions The CT-based radiomics signature may provide prognostic information and improve pretreatment risk stratification in EGFR NSCLC patients before EGFR-TKIs therapy. The multimodal radiomics nomogram further improved the capability. Relevance statement Radiomics based on NECT and CECT images can effectively identify and stratify the risk of T790M resistance before the first-line TKIs treatment in metastatic non-small cell lung cancer patients. Key points • Early identification of the risk of T790M resistance before TKIs treatment is clinically relevant. • Multimodel radiomics nomogram holds potential to be a diagnostic tool. • It provided an imaging surrogate for identifying the pretreatment risk of T790M. Graphical Abstract

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Section: Discussionmentioning

confidence: 99%

CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

Li,

Lv,

Wang

et al. 2023

Eur Radiol Exp

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Clinical audit of the image quality and customised contrast volume using P3T contrast injection software versus standard injection protocol in CT coronary angiography

Jayamani,

Pothiawala,

Ong

et al. 2024

Radiography

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Strategies for calculating contrast media dose for chest CT

Henning¹,

Gunn²,

Arenas³

et al. 2023

Eur Radiol Exp

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Background Total body weight (TBW) is a frequently used contrast media (CM) strategy for dose calculation in enhanced CT, yet it is suboptimal as it lacks consideration of patient characteristics, such as body fat percentage (BFP) and muscle mass. Alternative CM dosage strategies are suggested by the literature. Our objectives were to analyze the CM dose impact when adjusting to body composition using methods of obtaining lean body mass (LBM) and body surface area (BSA) along with its correlation with demographic factors in contrast enhanced chest CT examinations. Methods Eighty-nine adult patients referred for CM thoracic CT were retrospectively included, categorized as either normal, muscular, or overweight. Patient body composition data was used to calculate the CM dose according to LBM or BSA. LBM was calculated with the James method, Boer method, and bioelectric impedance (BIA). BSA was calculated using the Mostellar formula. We then correlated the corresponding CM doses with demographic factors. Results BIA demonstrated the highest and lowest calculated CM dose in muscular and overweight groups respectively, compared to other strategies. For the normal group, the lowest calculated CM dose was achieved using TBW. The calculated CM dose was more closely correlated with BFP using the BIA method. Conclusions The BIA method is more adaptive to variations in patient body habitus especially in muscular and overweight patients and is most closely correlated to patient demographics. This study could support utilizing the BIA method for calculating LBM for a body-tailored CM dose protocol for enhanced chest CT examinations. Relevance statement The BIA-based method is adaptive to variations in body habitus especially in muscular and overweight patients and is closely correlated to patient demographics for contrast-enhanced chest CT. Key points • Calculations based on BIA showed the largest variation in CM dose. • Lean body weight using BIA demonstrated the strongest correlation to patient demographics. • Lean body weight BIA protocol may be considered for CM dosing in chest CT. Graphical Abstract

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Contrast medium protocols in routine chest CT: a survey study

Cited by 4 publications

References 53 publications

CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

Clinical audit of the image quality and customised contrast volume using P3T contrast injection software versus standard injection protocol in CT coronary angiography

Strategies for calculating contrast media dose for chest CT

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