Precision Optimization of Iodinated Contrast Media Delivery: Impact on Diagnostic Accuracy, Pathological Correlation, and the Emerging Paradigm of High-Attenuation Spectral Imaging

Introduction: The Imperative for Precision in Iodinated Contrast Delivery

The administration of iodinated contrast media (ICM) has become a cornerstone of modern diagnostic radiology, with an estimated 50 million computed tomography (CT) examinations performed annually in the United States alone, approximately half of which utilize intravenous contrast. Despite this ubiquity, the transition from standardized, fixed-volume protocols to precision-optimized, patient-centric delivery remains a critical frontier in medical imaging. The fundamental objective of contrast-enhanced CT (CECT) is to improve the depiction of disorders across various organ systems—including the liver, kidneys, pancreas, and vasculature—by leveraging the high X-ray attenuation properties of the iodine atom. However, the efficacy of this enhancement is governed by a complex interplay of patient-related factors, acquisition parameters, and the physicochemical properties of the contrast agent itself.

In the current era of precision medicine, individualized strategies for ICM administration are necessitated by the need to optimize image quality while minimizing the total iodine dose (TID) and associated radiation exposure. Standardized dosing based on total body weight (TBW) often results in inconsistent tissue enhancement, characterized by over-dosing in slim patients and sub-optimal opacification in the obese population. These inconsistencies exacerbate clinical diagnostic risks, particularly in the context of under-enhanced scans where subtle lesions may be missed, or over-enhanced scans where artifacts and toxicity risks are heightened. Consequently, the industry is witnessing a disruptive shift—led by innovators such as SATMED Health—toward advanced delivery systems and dosing models that challenge the status quo to drive positive patient outcomes.

Historical Evolution: From Inorganic Salts to Non-Ionic Monomers

The history of contrast media is inextricably linked with the evolution of radiological equipment. The journey began in 1921 with the use of Lipiodol, an iodinated oil, marking the centenary of ICM in clinical practice. Early experimentation with inorganic sodium iodide and bromide proved too toxic for routine use, leading to the development of organic iodinated compounds in the late 1920s. In 1929, the introduction of Uroselectan A represented the first water-soluble iodinated organic contrast agent, which laid the foundation for the tri-iodinated benzene ring structure that remains the basis of modern contrast media.

The mid-20th century saw the emergence of ionic, high-osmolality contrast media (HOCM), such as diatrizoate and iothalamate. These first-generation agents were hyperosmolar, with osmolalities approximately five to six times that of human plasma. The high osmolality was a primary driver of adverse physiological effects, including endothelial damage, fluid shifts from the interstitial to the vascular compartment, and significant patient discomfort. The 1970s and 1980s heralded the development of low-osmolality contrast media (LOCM) and later iso-osmolality contrast media (IOCM). These newer non-ionic agents, such as iohexol, iopromide, and iopamidol, significantly improved the safety profile by reducing the incidence of adverse reactions and improving patient tolerability.

Contrast Generation	Classification	Osmolality (mOsm/kg)	Iodine:Particle Ratio	Adverse Event Incidence (per million)
First (1950s)	HOCM (Ionic Monomer)	1300–2140	1.5:1	193.8
Second (1980s)	LOCM (Non-ionic Monomer)	600–850	3.0:1	44.4
Third (1990s)	IOCM (Non-ionic Dimer)	~290	6.0:1	Varies by population

The synergy between these advanced non-ionic agents and the rapid acquisition speeds of multi-detector CT (MDCT) scanners allowed for more precise timing of the contrast bolus, leading to the widespread clinical reality of CT angiography (CTA).

 

Physicochemical Properties and Physiological Interaction

The diagnostic utility of ICM is derived from the ability of the iodine atom (Z=53) to absorb X-ray photons through the photoelectric effect. The probability of this interaction is proportional to the cube of the atomic number, making iodine far more effective than the light elements found in biological tissues. The attenuation of the X-ray beam is described by the Beer-Lambert law, where the linear attenuation coefficient is fundamentally tied to the concentration of iodine within a given voxel.

 

Osmolality, Viscosity, and Fluid Dynamics

Iodinated contrast agents possess several key properties—iodine concentration, osmolality, and viscosity—that influence their diagnostic efficiency and safety profile. Osmolality refers to the number of particles in solution per kilogram of water. Hypertonic agents (HOCM and LOCM) cause water to move from the interstitial space into the vascular compartment, resulting in hypervolemia, vasodilation, and potential neurotoxicity. Viscosity, or the “thickness” of the fluid, is determined by the molecular structure and concentration of the agent. High-viscosity agents require longer infusion times and higher injection pressures, which can be a limiting factor when using small-gauge peripheral catheters.

The viscosity of ICM increases exponentially with iodine concentration and decreases with temperature. For instance, a contrast agent with 400 mgI/mL is significantly more viscous than one with 300 mgI/mL, requiring careful management of injection parameters to avoid excessive pressure on the venous wall. However, high-concentration agents offer the advantage of delivering a high iodine load using a lower volume of fluid, which can be beneficial in patients with limited fluid tolerance or poor venous access.

 

Pharmacokinetics and the Extracellular Fluid Space

Upon intravenous injection, ICM follows a multi-compartmental pharmacokinetic model. Initially, the contrast is confined to the intravascular space (the bolus phase), followed by rapid distribution into the extracellular fluid (ECF) space of various organs. Because iodine is highly water-soluble and does not cross cell membranes (except in the kidneys for excretion), its volume of distribution (Vd) is essentially equivalent to the ECF volume. The liver, pancreas, and kidneys exhibit a significant ECF component, making them ideal targets for parenchymal enhancement evaluation.

In the context of obesity, the distribution of ICM becomes complex. Adipose tissue is poorly perfused and has a much smaller ECF volume compared to solid viscera. Therefore, fat does not contribute significantly to the distribution of the contrast agent. When dosing is based strictly on TBW, obese patients receive an iodine load that is disproportionately high for their vascular and parenchymal volume, whereas lean patients may be under-dosed if they have a high muscle-to-fat ratio.

 

Patient-Specific Dosing Models: Beyond Total Body Weight

The limitations of TBW-based dosing have led researchers to investigate alternative metrics that better correlate with the Vd of iodine. Lean body weight (LBW), body mass index (BMI), and body surface area (BSA) have all been proposed as more accurate determinants of the required contrast dose.

1. Boer Formula:

   • LBW_{Men} = (1.10 \times weight) – 128 \times (weight^2 / (100 \times height)^2)

   • LBW_{Women} = (1.07 \times weight) – 148 \times (weight^2 / (100 \times height)^2) (Note: weight in kg, height in m)

2. James Formula:

   • LBW_{Men} = 1.1 \times weight – 128 \times (weight / height)^2

   • LBW_{Women} = 1.07 \times weight – 148 \times (weight / height)^2 (Note: weight in kg, height in cm)

The Transition to Lean Body Weight (LBW)

Current clinical evidence increasingly favors the use of LBW-based protocols, particularly for abdominal CT imaging. Studies have shown that calculating the contrast volume based on LBW allows for consistent hepatic enhancement with significantly less inter-patient variability compared to TBW-based dosing. In one experimental cohort, diagnostic-quality abdominal CT scans were achieved using a dose of 0.63 to 0.65 gI/kg of LBW. This strategy is particularly advantageous for patients with a high BMI, as it prevents the overestimation of the iodine dose by disregarding non-perfused adipose tissue.

The estimation of LBW in clinical practice relies on sex-specific mathematical models. Two of the most common are the Boer formula and the James formula:

1.  

Comparative research indicates that the Boer formula may be the preferred method for LBW estimation in obese patients, leading to more accurate iodine load calculations and optimal liver enhancement. By using a ratio such as 700 mgI/kg of LBW, radiologists can effectively standardize the contrast signal across diverse body habitus.

 

Physiological Dosing and Cardiac Output

While body habitus determines the final magnitude of enhancement, cardiac output is the primary determinant of the timing and peak of the contrast bolus. In patients with high cardiac output, the contrast bolus travels faster and undergoes greater dilution, leading to an earlier but potentially lower peak enhancement. Precision delivery must, therefore, account for these hemodynamic variations, often through the use of automated bolus tracking or test bolus techniques to synchronize the scan acquisition with the peak of the time-density curve (TDC).

Technological Catalysts for Optimization: Tube Voltage and IDR

The optimization of ICM delivery cannot be viewed in isolation from the CT acquisition parameters. Tube voltage (kVp) and the Iodine Delivery Rate (IDR) are the two most influential technical variables in modern CECT.

The K-Edge Effect and Low Tube Voltage Imaging

The attenuation of iodine increases significantly as the X-ray energy spectrum approaches its K-shell binding energy of 33.2 keV. Lowering the tube voltage from the standard 120 kVp to 100 kVp or 80 kVp shifts the mean photon energy closer to this K-edge, thereby increasing the attenuation of the contrast agent. This phenomenon allows for a dual reduction strategy: clinicians can maintain image quality while simultaneously reducing both the radiation dose and the TID.

In coronary CT angiography (CCTA), the use of a 100 kVp protocol has been shown to achieve optimal vessel enhancement while reducing the TID by 32.1% and the radiation dose by 38.5% compared to 120 kVp protocols. To implement this successfully, a personalized contrast volume calculation algorithm must be used to ensure that the reduction in iodine load is precisely balanced against the increase in attenuation provided by the lower kVp.

The Strategic Importance of Iodine Delivery Rate (IDR)

The IDR represents the flow of iodine mass per unit of time, calculated as the product of the contrast concentration and the injection flow rate:

IDR is the primary determinant of peak vascular attenuation in CTA. While a standard IDR of 1.5 to 2.0 gI/s is often recommended for CCTA, higher rates exceeding 2.0 gI/s are feasible and may be necessary for low-kVp imaging. A practical approach for optimizing delivery is the “10-to-10 rule,” which suggests decreasing the IDR by 10% for every 10 kVp reduction in tube voltage.

Tube Voltage (kVp)	Recommended IDR (gI/s)	Context
120 kVp	2.0–2.2	Standard CCTA/Vascular
100 kVp	1.6–1.8	Optimized TID Reduction
80 kVp	1.3–1.4	Extreme Dose/TID Reduction

Impact on Diagnostic Accuracy: Clinical Specializations

The ultimate goal of precision contrast delivery is the enhancement of diagnostic accuracy, defined by the sensitivity, specificity, and predictive values of the imaging study.

Cardiovascular Imaging and Coronary CTA

In the assessment of coronary artery pathology, uniform and adequate enhancement of the vascular lumen is critical for the detection of stenosis. Research in candidates for transcatheter aortic valve replacement (TAVI) has demonstrated that optimized CCTA can achieve a negative predictive value (NPV) of up to 97% for ruling out obstructive coronary artery disease (CAD), potentially sparing patients from more invasive coronary angiography (ICA).

Precision is particularly vital in CCTA to avoid streak artifacts from the right heart, which can be mitigated through multiphasic injection protocols. A common triphasic approach includes:

1. Initial Bolus: 100% contrast to achieve target arterial opacification.

2. Transition Phase: A 50/50 mix of contrast and saline to maintain the plateau while reducing right-sided attenuation.

3. Saline Flush: 100% saline bolus chase to push the remaining contrast into the central circulation.

Abdominal Oncology and Parenchymal Visualization

In abdominal imaging, the timing of the contrast phases must be precisely managed to maximize the contrast between lesions and the surrounding parenchyma. For the visualization of tumors in the liver or pancreas, TBW-based dosing subgroups receiving 500 mgI/kg at 120 kVp have shown superior performance for parenchymal visualization, whereas 450 mgI/kg at 100 kVp is often recommended for assessing the vasculature.

Pathological Correlation and Tissue Characterization

The degree and pattern of contrast enhancement provide vital insights into the underlying pathophysiology of tissues, serving as an in vivo biomarker for vascularity and cellularity.

Microvascular Invasion (MVI) and Liver Parenchyma

In patients with hepatocellular carcinoma (HCC), dynamic contrast-enhanced CT is a primary method for evaluating pathological information. Research has identified that the CT value in the portal venous phase (PVP) is an independent risk factor for the presence of microvascular invasion (MVI). MVI-positive tumors often exhibit lower CT values in both the arterial and portal venous phases. When combined with clinical markers like the ALBI score and AFP levels, the diagnostic AUC for MVI prediction reaches 0.82.

Microvessel Density (MVD) and Pancreatic Cancer

The enhancement characteristics of pancreatic adenocarcinoma are closely correlated with the tumor’s histopathological grade and intratumoral angiogenesis. Studies have demonstrated a strong negative correlation ($r_s = -0.790$) between the degree of CT enhancement in the pancreatic parenchymal phase and the microvessel density (MVD) count. Poorly differentiated tumors typically show less enhancement compared to well-differentiated ones, likely due to a higher degree of fibrosis and reduced functional vascularity.

Perfusion Metrics in Acute Ischemic Stroke

In the management of acute ischemic stroke (AIS), CT perfusion (CTP) provides hemodynamic parameters such as cerebral blood volume (CBV) and mean transit time (MTT) that are crucial for predicting clinical outcomes. These parameters, derived from the SVD deconvolution of the time-density curve, allow for the identification of the ischemic core and the salvageable penumbra.

The High-Concentration Paradigm: 400 mgI/mL Agents

The emergence of high-concentration ICM, specifically agents with 400 mgI/mL (e.g., Iomeprol), offers a new set of advantages and challenges for clinical optimization.

Comparative Efficacy and Patient Comfort

High-concentration ICM allows for a lower total volume of injection and a slower injection flow rate to achieve the same IDR as standard-concentration agents. This can significantly enhance patient comfort, particularly in individuals with fragile peripheral veins.

However, the clinical impact of 400 mgI/mL versus 300 mgI/mL remains a topic of debate. Some intra-individual studies in the chest have suggested that 300 mgI/mL agents provide slightly improved contrast enhancement and longer plateau times when the IDR and TID are held constant. Conversely, in abdominal CT, the 400 mgI/mL agent is often preferred for its ability to deliver a higher iodine mass for better lesion conspicuity and vascular opacification.

Tripartite Strategy for Obese Patients

In obese patients (BMI $\ge 30 kg/m^2$), a “tripartite strategy” has been proposed to manage the challenges of high radiation exposure and iodine load. This strategy combines:

1. High-Iodine-Concentration Contrast (400 mgI/mL): To maximize attenuation per unit volume.

2. 80-kVp Scanning: To leverage the K-edge effect for increased iodine signal.

3. Deep Learning Image Reconstruction (DLIR): To mitigate the increased image noise.

This approach has been shown to reduce the effective radiation dose by 48.6% and the total iodine load by 23.8% while maintaining 100% patient-level sensitivity for CAD detection compared to standard protocols.

Disruptive Innovation: Photon-Counting Detector CT (PCCT)

The most significant recent technological advancement in radiology is the introduction of Photon-Counting Detector CT (PCCT). PCCT directly counts individual X-ray photons and measures their energy, enabling energy-resolved imaging.

Virtual Monoenergetic Imaging (VMI) and Dose Reduction

The spectral information provided by PCCT allows for the routine reconstruction of virtual monoenergetic images (VMI). Low-keV VMIs (e.g., 40–50 keV) drastically improve iodine contrast, allowing for a substantial reduction in the ICM dose—estimated at 50% to 66%—while maintaining diagnostic-level attenuation for CCTA.

K-Edge Imaging and Material Decomposition

PCCT leverages the unique K-edge of elements to perform advanced material decomposition. This capability allows clinicians to clearly distinguish between iodine, calcium, and fat with remarkable precision. PCCT can also perform K-edge imaging to subtract calcium from the coronary lumen, reducing blooming artifacts. Furthermore, PCCT opens the door for multi-contrast imaging, where two or more contrasting elements (e.g., iodine and gadolinium) can be injected and independently mapped.

Safety, Renal Function, and Environmental Stewardship

The precision optimization of ICM delivery is not only a matter of diagnostic quality but also one of clinical safety and ethical responsibility.

Contrast-Induced Nephropathy (CIN)

The risk of post-contrast acute kidney injury (PC-AKI) or CIN remains a concern. High-concentration agents (400 mgI/mL) have been shown to have a greater influence on renal outer medulla oxygenation levels at 24 hours compared to lower concentrations, likely due to their higher viscosity and prolonged transit through the renal tubules. Therefore, the ability to reduce the TID through optimized protocols is a vital strategy for protecting renal health.

Environmental Impact and Sustainability

Healthcare is increasingly recognizing the environmental footprint of medical imaging. ICM are highly water-soluble and metabolically stable, making them difficult to remove during conventional water purification. Residual iodine in water sources can lead to the formation of toxic disinfection by-products. Minimizing ICM doses helps mitigate these environmental risks, promotes sustainable medical practices, and addresses potential supply chain concerns.

Conclusion: The Shift Toward Personalized Contrast Management

The optimization of iodinated contrast media delivery represents a critical evolution in radiological practice, moving from empirical “one-size-fits-all” approaches to a data-driven, personalized paradigm. The transition from total body weight to lean body weight as a dosing metric, the strategic adaptation of iodine delivery rates to tube voltage, and the clinical implementation of high-concentration agents like Iomeprol 400 reflect a nuanced understanding of bolus dynamics and individual patient physiology.

The integration of disruptive technologies—particularly Photon-Counting Detector CT and Deep Learning Image Reconstruction—is redefining the possibilities of contrast-enhanced imaging. These advancements allow for radical reductions in iodine load and radiation exposure without compromising, and often enhancing, diagnostic accuracy. Furthermore, the correlation between precision-quantified enhancement patterns and pathological findings, such as microvascular invasion in HCC and microvessel density in pancreatic cancer, positions CECT as a powerful quantitative tool for tissue characterization and treatment planning.

References

Berti, V., et al. (2025). Photon-counting detector CT: a disrupting innovation in medical imaging. European Radiology Experimental. https://pmc.ncbi.nlm.nih.gov/articles/PMC11936849/

Cademartiri, F. (2025). Principles and impact of precision optimization of iodinated contrast delivery in CT. Diagnostic Imaging. https://pmc.ncbi.nlm.nih.gov/articles/PMC11865897/

Wang, X., et al. (2025). Correlation between dynamic contrast-enhanced CT imaging signs and differentiation grade and microvascular invasion of hepatocellular carcinoma. Journal of Hepatocellular Carcinoma. https://www.dovepress.com/correlation-between-dynamic-contrast-enhanced-ct-imaging-signs-and-dif-peer-reviewed-fulltext-article-JHC

Bonnemain, B. (2021). History of contrast media: Celebrating the centenary of the use of Lipiodol® in radiology. Erciyes Medical Journal, 43(6), 626–630. https://jcpres.com/storage/upload/pdfs/EMJ_43_6_626_630.pdf

Journal of Neuroendovascular Therapy. (2022). Correlation between the CT Perfusion Parameter Values and Response to Recanalization in Patients with AIS. https://www.researchgate.net/publication/362346904_Correlation_between_the_CT_Perfusion_Parameter_Values_and_Response_to_Recanalization_in_Patients_with_Acute_Ischemic_Stroke

Wang, J-H., et al. (2014). Effects of iodinated contrast agents on renal oxygenation level. Blood Oxygenation Level Dependent MRI Study. https://pmc.ncbi.nlm.nih.gov/articles/PMC4236662/

PMC. (2024). Liver parenchyma contrast enhancement prediction model using machine learning. https://pmc.ncbi.nlm.nih.gov/articles/PMC10777297/

PMC. (2025). Iodine k-edge imaging photon-counting CT contrast optimization. https://pmc.ncbi.nlm.nih.gov/articles/PMC10259215/

PMC. (2015). Correlation between CT contrast enhancement and the histopathological grades and intratumoral angiogenesis in pancreatic carcinoma. https://pmc.ncbi.nlm.nih.gov/articles/PMC4503119/

MDPI. (2025). Detectability of iodine in mediastinal lesions on photon counting CT: A phantom study. Diagnostics. https://www.mdpi.com/2075-4418/15/6/696

Applied Radiology. (2023). Optimizing contrast injection for coronary CT angiography and functional cardiac CT. https://appliedradiology.com/articles/optimizing-contrast-injection-for-coronary-ct-angiography-and-functional-cardiac-ct

Cademartiri, F. (2025). Precision optimization of iodinated contrast media delivery in CT. Diagnostic Imaging. https://pmc.ncbi.nlm.nih.gov/articles/PMC11865897/

PMC. (2018). Boer formula should be the method of choice for LBW estimation in obese patients. https://pmc.ncbi.nlm.nih.gov/articles/PMC6110034/

PMC. (2025). Feasibility and performance of K-edge imaging of iodine and gadolinium on a clinically available photon-counting CT system. https://pmc.ncbi.nlm.nih.gov/articles/PMC12393656/

Spectral Photon Counting CT. (2026). Contrast agents K-edge imaging and molecular biomarkers. https://www.spectralphotoncountingct.com/fr/page/contrast-agents-k-edge-imaging

European Radiology Experimental. (2025). Photon-counting detector CT: a disrupting innovation in medical imaging. https://pmc.ncbi.nlm.nih.gov/articles/PMC11936849/

SAPUB. (2013). Abdominal CT: A radiologist-driven adjustment of the dose of contrast medium based on lean body weight. American Journal of Biomedical Engineering. http://article.sapub.org/10.5923.s.ajbe.201310.04.html

Wang, X., et al. (2025). Correlation Between Dynamic Contrast-Enhanced CT Imaging Signs and Differentiation Grade and MVI of HCC. Journal of Hepatocellular Carcinoma. https://www.dovepress.com/correlation-between-dynamic-contrast-enhanced-ct-imaging-signs-and-dif-peer-reviewed-fulltext-article-JHC

Zhang, Q., et al. (2025). Tripartite strategy for dual reduction of radiation and iodine dose in obese CCTA. Sir Run Run Shaw Hospital. https://pmc.ncbi.nlm.nih.gov/articles/PMC12582828/

Quantitative Imaging in Medicine and Surgery. (2025). Individualized contrast media dosing protocols in abdominal multiphasic contrast-enhanced CT. https://qims.amegroups.org/article/view/149318/pdf

PMC. (2026). Optimizing the iodinated contrast medium dose while maintaining diagnostically adequate image quality. https://pmc.ncbi.nlm.nih.gov/articles/PMC12575512/

ClinicalTrials.gov. (2011). Diagnostic accuracy of cardiac CT perfusion compared to PET imaging. https://clinicaltrials.gov/study/NCT01434043

MDPI. (2025). Detectability of iodine in mediastinal lesions on photon counting CT: A phantom study. https://www.mdpi.com/2075-4418/15/6/696

PMC. (2014). Side effects of radiographic contrast media. https://pmc.ncbi.nlm.nih.gov/articles/PMC4034507/

ResearchGate. (2010). Intra-individual comparison of different contrast media concentrations in MDCT. https://www.researchgate.net/publication/41562944_Intra-individual_comparison_of_different_contrast_media_concentrations_300_mg_370_mg_and_400_mg_iodine_in_MDCT

Quantitative Imaging in Medicine and Surgery. (2025). Personalized contrast volume calculation algorithm for low tube voltage CCTA. https://qims.amegroups.org/article/view/25201/html

GE HealthCare. (2026). GE HealthCare’s Photonova Spectra photon-counting CT receives FDA clearance. https://www.gehealthcare.com/about/newsroom/press-releases/ge-healthcares-photonova-spectra-photon-counting-ct-receives-fda-clearance

Journal of Nuclear Medicine Technology. (2019). Iodinated contrast agents: Properties and behavior. https://tech.snmjournals.org/content/47/3/189

PubMed. (2010). Intra-individual comparison of different contrast media concentrations (300 mg, 370 mg and 400 mg iodine) in MDCT. https://pubmed.ncbi.nlm.nih.gov/20182733/

US Cardiology. (2009). Iodinated contrast media safety review. https://www.uscjournal.com/articles/iodinated-contrast-media-safety-review

SATMED Health. (2026). Innovation in radiology: Commitment to advancing image quality and safety. https://www.satmed-health.com/

SciSpace. (2023). Abdominal CT: A radiologist-driven adjustment of the dose. https://scispace.com/papers/abdominal-ct-a-radiologist-driven-adjustment-of-the-dose-of-2xdvwhpcf8

MPO Magazine. (2026). FDA Oks GE HealthCare’s Photonova Spectra Photon-Counting CT System. https://www.mpo-mag.com/breaking-news/fda-oks-ge-healthcares-photonova-spectra-photon-counting-ct-system/

Gallo, C., et al. (2025). Diagnostic Accuracy of Coronary CT Angiography in Ruling Out Significant CAD in Candidates for TAVI. https://pmc.ncbi.nlm.nih.gov/articles/PMC12564097/

SATMED Health. (2026). Direct-to-Factory Manufacturing: Designed Globally, Crafted with Precision. https://www.satmed-health.com/about-us/

PMC. (2026). Iodinated contrast media: From clinical use to environmental concern and treatment possibilities. https://pmc.ncbi.nlm.nih.gov/articles/PMC12899356/

ResearchGate. (2026). Iodinated Contrast Media—From Clinical Use to Environmental Concern. https://www.researchgate.net/publication/400483924_Iodinated_Contrast_Media-From_Clinical_Use_to_Environmental_Concern_and_Treatment_Possibilities