Clinical Efficacy of Reduced Dose Gadobutrol Versus Standard Dose Gadoterate for Contrast-Enhanced MRI of the CNS: An International Multicenter Prospective Crossover Trial (LEADER-75)

The impact of 3D real-IR delayed post gadolinium MRI parameterisation on the diagnostic performance and optimal descriptor selection in Ménière's disease

OBJECTIVES

To compare the performance and optimal combination of MRI descriptors used for the diagnosis of Ménière's disease (MD) between a real-IR sequence with "zero-point" endolymph (ZPE), and an optimised real-IR sequence with negative signal endolymph (NSE).

MATERIALS AND METHODS

This retrospective single-centre cross-sectional study evaluated delayed post-gadolinium ZPE and NSE real-IR MRI in consecutive patients with Ménièriform symptoms (8/2020-10/2023). Two observers assessed 14 MRI descriptors. "Definite MD" (2015 criteria) and "all MD" ears (wider clinical criteria) were compared to controls. Cohen's kappa and risk ratios (RR) were evaluated for each descriptor. Forward stepwise logistic regression established which combination of descriptors best predicted MD.

RESULTS

The study included 132 patients (57 men; mean age 57.7 ± 13.6), with 87 "all MD" (56 "definite") and 39 control ears. The NSE sequence demonstrated increased perilymph SNR, and improved both diagnostic performance and reliability for 9/14 descriptors. However, ZPE demonstrated superior diagnostic performance for the best descriptor of "saccule absent, large as or confluent with the utricle" (RR 6.571, ZPE; 6.300, NSE) and that of "asymmetric perilymphatic enhancement" (RR 3.628, ZPE; 2.903, NSE). Both sequences combined these two descriptors in the optimal predictive model for "definite MD", with "grade 2 cochlear hydrops" also significant for NSE. ZPE and NSE descriptor combinations both correctly classified 95.8% of ears. The ZPE descriptor combination performed better for "all MD" (ZPE, AUC-ROC 0.914; NSE, AUC-ROC 0.893).

CONCLUSION

Parameter optimisation with NSE Real-IR influenced the optimal selection of MRI descriptors but did not improve their diagnostic performance in definite MD.

KEY POINTS

Question Delayed post-gadolinium ZPE (FLAIR) and NSE (REAL-IR) sequences are widely applied for diagnosing MD, but their relative benefits remain unclear. Findings Optimised NSE sequences improve perilymphatic depiction and influence the selection of the optimal MRI descriptors, but do not improve diagnostic performance. Clinical relevance Radiologists may continue to apply either ZPE or NSE sequences since they offer similar diagnostic abilities, but the choice of the sequence will influence which MRI features should be evaluated to support the diagnosis of MD.

Evolving Characteristics of Gadolinium-Based Contrast Agents for MR Imaging: A Systematic Review of the Importance of Relaxivity

Gadolinium-based contrast agents (GBCAs) are widely and routinely used to enhance the diagnostic performance of magnetic resonance imaging and magnetic resonance angiography examinations. T1 relaxivity (r1) is the measure of their ability to increase signal intensity in tissues and blood on T1-weighted images at a given dose. Pharmaceutical companies have invested in the design and development of GBCAs with higher and higher T1 relaxivity values, and "high relaxivity" is a claim frequently used to promote GBCAs, with no clear definition of what "high relaxivity" means, or general concurrence about its clinical benefit. To understand whether higher relaxivity values translate into a material clinical benefit, well-designed, and properly powered clinical studies are necessary, while mere in vitro measurements may be misleading. This systematic review of relevant peer-reviewed literature provides high-quality clinical evidence showing that a difference in relaxivity of at least 40% between two GBCAs results in superior diagnostic efficacy for the higher-relaxivity agent when this is used at the same equimolar gadolinium dose as the lower-relaxivity agent, or similar imaging performance when used at a lower dose. Either outcome clearly implies a relevant clinical benefit. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Clinical Safety of Gadobutrol: Review of Over 25 Years of Use Exceeding 100 Million Administrations

BACKGROUND

The macrocyclic gadolinium-based contrast agent gadobutrol was introduced to the market in February 1998. Over the last 25 years, gadobutrol has been administered more than 100 million times worldwide providing a wealth of data related to safety.

OBJECTIVE

The aim of this study was to perform a thorough review and status update on gadobutrol's safety.

MATERIALS AND METHODS

Safety data from the clinical phase II-IV program and postmarketing surveillance were descriptively analyzed from February 1998 until December 31, 2022. Literature on special at-risk populations and specific safety aspects was critically summarized.

RESULTS

Forty-five clinical phase II-IV studies recruited 7856 patients receiving gadobutrol. Drug-related adverse events (AEs) were reported in 3.4% and serious AEs in <0.1% of patients. Nausea (0.7%) and dysgeusia (0.4%) were the most reported AEs. All other drug-related AEs occurred ≤0.3%. After more than 100 million gadobutrol administrations, overall adverse drug reactions (ADRs) from postmarketing surveillance (including clinical trials) were rare with an overall reporting rate of 0.0356%, hypersensitivity reactions (0.0147%), nausea (0.0032%), vomiting (0.0025%), and dyspnea (0.0010%). All other ADRs were <0.001%. No trend for higher rates of AEs was found in patients with reduced renal or liver function. Seven clinical studies reported safety findings in 7292 children ≤18 years, thereof 112 newborns/toddlers younger than 2 years. Overall, 61 ADRs (0.84%) were reported, including 3 serious ones. Adverse events in patients ≥65 years of age ("elderly") were significantly less frequent than in younger patients. A total of 4 reports diagnostic of or consistent with nephrogenic systemic fibrosis have been received. No causal relationship has been established between clinical signs and symptoms and the presence of small amounts of gadolinium in the body in patients with normal renal function after use of gadobutrol.

CONCLUSIONS

More than 100 million administrations worldwide have shown gadobutrol's well-established benefit-risk profile in any approved indication and populations.

Clinical Efficacy of Gadobutrol: Review of Over 25 Years of Use Exceeding 100 Million Administrations

BACKGROUND

Gadobutrol has been administered more than 100 million times worldwide, since February 1998, that is, over the last 25 years. Numerous clinical studies in a broad range of indications document the long-term experience with gadobutrol.

OBJECTIVE

The aim of this study was to provide a literature-based overview on gadobutrol's efficacy in 9 approved indications and use in children.

MATERIALS AND METHODS

Efficacy results in patients of all age groups including sensitivity, specificity, accuracy, and positive/negative predictive values were identified by a systematic literature search on Embase until December 31, 2022. Nine approved indications were considered: central nervous system (CNS), magnetic resonance angiography (MRA), breast, heart, prostate, kidney, liver, musculoskeletal, whole body, and various indications in children.

RESULTS

Sixty-five publications (10 phase III, 2 phase IV, 53 investigator-initiated studies) reported diagnostic efficacy results obtained from 7806 patients including 271 children, at 369 centers worldwide. Indication-specific sensitivity ranges were 59%-98% (CNS), 53%-100% (MRA), 80%-100% (breast), 64%-90% (heart), 64%-96% (prostate), 71-85 (kidney), 79%-100% (liver), 53%-98% (musculoskeletal), and 78%-100% (children). Indication-specific specificity ranges were 75%-100% (CNS), 64%-99% (MRA), 58%-98% (breast), and 47%-100% (heart).

CONCLUSIONS

The evaluated body of evidence, consisting of 65 studies with 7806 patients, including 271 children and 7535 adults, showed that gadobutrol is an efficacious magnetic resonance imaging contrast agent for all age groups in various approved indications throughout the whole body.

Review of strategies to reduce the contamination of the water environment by gadolinium-based contrast agents

Gadolinium-based contrast agents (GBCA) are essential for diagnostic MRI examinations. GBCA are only used in small quantities on a per-patient basis; however, the acquisition of contrast-enhanced MRI examinations worldwide results in the use of many thousands of litres of GBCA per year. Data shows that these GBCA are present in sewage water, surface water, and drinking water in many regions of the world. Therefore, there is growing concern regarding the environmental impact of GBCA because of their ubiquitous presence in the aquatic environment. To address the problem of GBCA in the water system as a whole, collaboration is necessary between all stakeholders, including the producers of GBCA, medical professionals and importantly, the consumers of drinking water, i.e. the patients. This paper aims to make healthcare professionals aware of the opportunity to take the lead in making informed decisions about the use of GBCA and provides an overview of the different options for action.In this paper, we first provide a summary on the metabolism and clinical use of GBCA, then the environmental fate and observations of GBCA, followed by measures to reduce the use of GBCA. The environmental impact of GBCA can be reduced by (1) measures focusing on the application of GBCA by means of weight-based contrast volume reduction, GBCA with higher relaxivity per mmol of Gd, contrast-enhancing sequences, and post-processing; and (2) measures that reduce the waste of GBCA, including the use of bulk packaging and collecting residues of GBCA at the point of application.Critical relevance statement This review aims to make healthcare professionals aware of the environmental impact of GBCA and the opportunity for them to take the lead in making informed decisions about GBCA use and the different options to reduce its environmental burden.Key points• Gadolinium-based contrast agents are found in sources of drinking water and constitute an environmental risk.• Radiologists have a wide spectrum of options to reduce GBCA use without compromising diagnostic quality.• Radiology can become more sustainable by adopting such measures in clinical practice.

Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy?

Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.

Artificial Contrast: Deep Learning for Reducing Gadolinium-Based Contrast Agents in Neuroradiology

ABSTRACT

Deep learning approaches are playing an ever-increasing role throughout diagnostic medicine, especially in neuroradiology, to solve a wide range of problems such as segmentation, synthesis of missing sequences, and image quality improvement. Of particular interest is their application in the reduction of gadolinium-based contrast agents, the administration of which has been under cautious reevaluation in recent years because of concerns about gadolinium deposition and its unclear long-term consequences. A growing number of studies are investigating the reduction (low-dose approach) or even complete substitution (zero-dose approach) of gadolinium-based contrast agents in diverse patient populations using a variety of deep learning methods. This work aims to highlight selected research and discusses the advantages and limitations of recent deep learning approaches, the challenges of assessing its output, and the progress toward clinical applicability distinguishing between the low-dose and zero-dose approach.

Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance

OBJECTIVES

The purpose of this study was to implement a state-of-the-art convolutional neural network used to synthesize artificial T1-weighted (T1w) full-dose images from corresponding noncontrast and low-dose images (using various settings of input sequences) and test its performance on a patient population acquired prospectively.

MATERIALS AND METHODS

In this monocentric, institutional review board-approved study, a total of 138 participants were included who received an adapted imaging protocol with acquisition of a T1w low dose after administration of 10% of the standard dose and acquisition of a T1w full dose after administration of the remaining 90% of the standard dose of a gadolinium-containing contrast agent. A total of 83 participants formed the training sample (51.7 ± 16.5 years, 36 women), 25 the validation sample (55.3 ± 16.4 years, 11 women), and 30 the test sample (55.0 ± 15.0 years, 9 women). Four input settings were differentiated: only the T1w noncontrast and T1w low-dose images (standard setting), only the T1w noncontrast and T1w low-dose images with a prolonged postinjection time of 5 minutes (5-minute setting), multiple noncontrast sequences (T1w, T2w, diffusion) and the T1w low-dose images (extended setting), and only noncontrast sequences (T1w, T2w, diffusion) were used (zero-dose setting). For each setting, a deep neural network was trained to synthesize artificial T1w full-dose images, which were assessed on the test sample using an objective evaluation based on quantitative metrics and a subjective evaluation through a reader-based study. Three readers scored the overall image quality, the interchangeability in regard to the clinical conclusion compared with the true T1w full-dose sequence, the contrast enhancement of lesions, and their conformity to the respective references in the true T1w full dose.

RESULTS

Quantitative analysis of the artificial T1w full-dose images of the standard setting provided a peak signal-to-noise ratio of 33.39 ± 0.62 (corresponding to an average improvement of the low-dose sequences of 5.2 dB) and a structural similarity index measure of 0.938 ± 0.005. In the 4-fold cross-validation, the extended setting yielded similar performance to the standard setting in terms of peak signal-to-noise ratio ( P = 0.20), but a slight improvement in structural similarity index measure ( P < 0.0001). For all settings, the reader study found comparable overall image quality between the original and artificial T1w full-dose images. The proportion of scans scored as fully or mostly interchangeable was 55%, 58%, 43%, and 3% and the average counts of false positives per case were 0.42 ± 0.83, 0.34 ± 0.71, 0.82 ± 1.15, and 2.00 ± 1.07 for the standard, 5-minute, extended, and zero-dose setting, respectively. Using a 5-point Likert scale (0 to 4, 0 being the worst), all settings of synthesized full-dose images showed significantly poorer contrast enhancement of lesions compared with the original full-dose sequence (difference of average degree of contrast enhancement-standard: -0.97 ± 0.83, P = <0.001; 5-minute: -0.93 ± 0.91, P = <0.001; extended: -0.96 ± 0.97, P = <0.001; zero-dose: -2.39 ± 1.14, P = <0.001). The average scores of conformity of the lesions compared with the original full-dose sequence were 2.25 ± 1.21, 2.22 ± 1.27, 2.24 ± 1.25, and 0.73 ± 0.93 for the standard, 5-minute, extended, and zero-dose setting, respectively.

CONCLUSIONS

The tested deep learning algorithm for synthesis of artificial T1w full-dose sequences based on images after administration of only 10% of the standard dose of a gadolinium-based contrast agent showed very good quantitative performance. Despite good image quality in all settings, both false-negative and false-positive signals resulted in significantly limited interchangeability of the synthesized sequences with the original full-dose sequences.