Virtual Monoenergetic Imaging of Lower Extremities Using Dual-Energy CT Angiography in Patients with Diabetes Mellitus

Background: Type 2 diabetes mellitus (DM) is the most common metabolic disorder in the world and an important risk factor for peripheral arterial disease (PAD). CT angiography represents the method of choice for the diagnosis, pre-operative planning, and follow-up of vascular disease. Low-energy dual-energy CT (DECT) virtual mono-energetic imaging (VMI) has been shown to improve image contrast, iodine signal, and may also lead to a reduction in contrast medium dose. In recent years, VMI has been improved with the use of a new algorithm called VMI+, able to obtain the best image contrast with the least possible image noise in low-keV reconstructions. Purpose: To evaluate the impact of VMI+ DECT reconstructions on quantitative and qualitative image quality in the evaluation of the lower extremity runoff. Materials and Methods: We evaluated DECT angiography of lower extremities in patients suffering from diabetes who had undergone clinically indicated DECT examinations between January 2018 and January 2023. Images were reconstructed with standard linear blending (F_0.5) and low VMI+ series were generated from 40 to 100 keV, in an interval of 15 keV. Vascular attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for objective analysis. Subjective analysis was performed using five-point scales to evaluate image quality, image noise, and diagnostic assessability of vessel contrast. Results: Our final study cohort consisted of 77 patients (41 males). Attenuation values, CNR, and SNR were higher in 40-keV VMI+ reconstructions compared to the remaining VMI+ and standard F_0.5 series (HU: 1180.41 ± 45.09; SNR: 29.91 ± 0.99; CNR: 28.60 ± 1.03 vs. HU 251.32 ± 7.13; SNR: 13.22 ± 0.44; CNR: 10.57 ± 0.39 in standard F_0.5 series) (p < 0.0001). Subjective image rating was significantly higher in 55-keV VMI+ images compared to the other VMI+ and standard F_0.5 series in terms of image quality (mean score: 4.77), image noise (mean score: 4.39), and assessability of vessel contrast (mean value: 4.57) (p < 0.001). Conclusions: DECT 40-keV and 55-keV VMI+ showed the highest objective and subjective parameters of image quality, respectively. These specific energy levels for VMI+ reconstructions could be recommended in clinical practice, providing high-quality images with greater diagnostic suitability for the evaluation of lower extremity runoff, and potentially needing a lower amount of contrast medium, which is particularly advantageous for diabetic patients.

[1]  Simon S. Martin,et al.  Dual-Energy CT for the Detection of Portal Vein Thrombosis: Improved Diagnostic Performance Using Virtual Monoenergetic Reconstructions , 2022, Diagnostics.

[2]  J. Shu,et al.  Dual-layer spectral detector CT for contrast agent concentration, dose and injection rate reduction: Utility in imaging of the superior mesenteric artery. , 2022, European Journal of Radiology.

[3]  Zhengyu Jin,et al.  Utilisation of virtual non-contrast images and virtual mono-energetic images acquired from dual-layer spectral CT for renal cell carcinoma: image quality and radiation dose , 2022, Insights into Imaging.

[4]  R. Serra,et al.  The Impact of Chronic Kidney Disease on Peripheral Artery Disease and Peripheral Revascularization , 2021, International journal of general medicine.

[5]  A. Kambadakone,et al.  Optimized Bolus Threshold for Dual-Energy CT Angiography with Monoenergetic Images: A Randomized Clinical Trial. , 2021, Radiology.

[6]  R. Meuli,et al.  Reduced-iodine-dose dual-energy coronary CT angiography: qualitative and quantitative comparison between virtual monochromatic and polychromatic CT images , 2021, European Radiology.

[7]  César Martín,et al.  Pathophysiology of Type 2 Diabetes Mellitus , 2020, International journal of molecular sciences.

[8]  Simon S. Martin,et al.  Can Dual-energy CT-based Virtual Monoenergetic Imaging Improve the Assessment of Hypodense Liver Metastases in Patients With Hepatic Steatosis? , 2020, Academic radiology.

[9]  J. Berger,et al.  Chronic kidney disease and outcomes of lower extremity revascularization for peripheral artery disease. , 2019, Atherosclerosis.

[10]  T. Hansen,et al.  Diabetes as a cardiovascular risk factor: An overview of global trends of macro and micro vascular complications , 2019, European journal of preventive cardiology.

[11]  Simon S. Martin,et al.  Measurement Reliability and Diagnostic Accuracy of Virtual Monoenergetic Dual-Energy CT in Patients with Colorectal Liver Metastases. , 2019, Academic radiology.

[12]  Simon S. Martin,et al.  Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications. , 2019, The British journal of radiology.

[13]  Alfredo E Farjat,et al.  Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization. , 2019, Radiology.

[14]  M. Mazzei,et al.  Dual-Energy CT Iodine Mapping and 40-keV Monoenergetic Applications in the Diagnosis of Acute Bowel Ischemia: A Necessary Clarification. , 2019, AJR. American journal of roentgenology.

[15]  D. Sahani,et al.  Virtual Monochromatic Dual-Energy Aortoiliac CT Angiography With Reduced Iodine Dose: A Prospective Randomized Study. , 2019, AJR. American journal of roentgenology.

[16]  Simon S. Martin,et al.  Dual-energy CT in early acute pancreatitis: improved detection using iodine quantification , 2018, European Radiology.

[17]  S. Hedayati,et al.  Management of Traditional Cardiovascular Risk Factors in CKD: What Are the Data? , 2018, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[18]  Simon S. Martin,et al.  Dual-energy CT in patients with colorectal cancer: Improved assessment of hypoattenuating liver metastases using noise-optimized virtual monoenergetic imaging. , 2018, European journal of radiology.

[19]  R. Hammerstingl,et al.  Dual-energy CT in patients with abdominal malignant lymphoma: impact of noise-optimised virtual monoenergetic imaging on objective and subjective image quality. , 2018, Clinical radiology.

[20]  Simon S. Martin,et al.  Iodine quantification to distinguish hepatic neuroendocrine tumor metastasis from hepatocellular carcinoma at dual-source dual-energy liver CT. , 2018, European journal of radiology.

[21]  F. Pfeiffer,et al.  Dual-layer spectral computed tomography: Virtual non-contrast in comparison to true non-contrast images. , 2018, European journal of radiology.

[22]  Savvas Nicolaou,et al.  Dual-Energy CT Iodine Mapping and 40-keV Monoenergetic Applications in the Diagnosis of Acute Bowel Ischemia. , 2018, AJR. American journal of roentgenology.

[23]  Simon S. Martin,et al.  Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis. , 2018, European journal of radiology.

[24]  J. Berger,et al.  Primary Prevention of Cardiovascular Disease in Diabetes Mellitus. , 2017, Journal of the American College of Cardiology.

[25]  Keith T. Chan,et al.  Dual-energy CT Aortography with 50% Reduced Iodine Dose Versus Single-energy CT Aortography with Standard Iodine Dose. , 2016, Academic radiology.

[26]  Julian L Wichmann,et al.  Dual-Energy Computed Tomography Angiography of the Lower Extremity Runoff: Impact of Noise-Optimized Virtual Monochromatic Imaging on Image Quality and Diagnostic Accuracy , 2016, Investigative radiology.

[27]  P. Garimella,et al.  Peripheral artery disease and chronic kidney disease: clinical synergy to improve outcomes. , 2014, Advances in chronic kidney disease.

[28]  Martin Sedlmair,et al.  Assessment of an Advanced Image-Based Technique to Calculate Virtual Monoenergetic Computed Tomographic Images From a Dual-Energy Examination to Improve Contrast-To-Noise Ratio in Examinations Using Iodinated Contrast Media , 2014, Investigative radiology.

[29]  Thomas Henzler,et al.  Optimization of kiloelectron volt settings in cerebral and cervical dual-energy CT angiography determined with virtual monoenergetic imaging. , 2014, Academic radiology.

[30]  S. Schoenberg,et al.  Value of monoenergetic low-kV dual energy CT datasets for improved image quality of CT pulmonary angiography. , 2014, European journal of radiology.

[31]  M. Khamaisi,et al.  Why Is Diabetes Mellitus a Risk Factor for Contrast-Induced Nephropathy? , 2013, BioMed research international.

[32]  Thomas Flohr,et al.  Spectral optimization of chest CT angiography with reduced iodine load: experience in 80 patients evaluated with dual-source, dual-energy CT. , 2013, Radiology.

[33]  L. Appel,et al.  Risk factors for peripheral arterial disease among patients with chronic kidney disease. , 2012, The American journal of cardiology.

[34]  Christian Reiterer,et al.  Dual-energy CT angiography in peripheral arterial occlusive disease—accuracy of maximum intensity projections in clinical routine and subgroup analysis , 2011, European Radiology.

[35]  S. Schoenberg,et al.  Dual-Energy CT Angiography in Peripheral Arterial Occlusive Disease , 2009, CardioVascular and Interventional Radiology.

[36]  C. Catalano,et al.  Infrarenal aortic and lower-extremity arterial disease: diagnostic performance of multi-detector row CT angiography. , 2004, Radiology.

[37]  C. Fox,et al.  High Prevalence of Peripheral Arterial Disease in Persons With Renal Insufficiency: Results From the National Health and Nutrition Examination Survey 1999–2000 , 2004, Circulation.

[38]  W. Kannel,et al.  Diabetes, Intermittent Claudication, and Risk of Cardiovascular Events: The Framingham Study , 1989, Diabetes.

[39]  A. Macovski,et al.  Energy-selective reconstructions in X-ray computerised tomography , 1976, Physics in medicine and biology.

[40]  J. Leipsic,et al.  Reduced iodine load at CT pulmonary angiography with dual-energy monochromatic imaging: comparison with standard CT pulmonary angiography--a prospective randomized trial. , 2012, Radiology.

[41]  M. Goicoechea,et al.  Subclinical peripheral arterial disease in patients with chronic kidney disease: prevalence and related risk factors. , 2005, Kidney international. Supplement.

[42]  J. Gross,et al.  Diabetic nephropathy: diagnosis, prevention, and treatment. , 2005, Diabetes care.

[43]  Peripheral Arterial Disease in People With Diabetes , 2003 .