Rapid kVp-switching DECT portal venous phase abdominal CT scans in patients with large body habitus: image quality considerations

Comparing fully automated AI body composition biomarkers at differing virtual monoenergetic levels using dual-energy CT

PURPOSE

To investigate the behavior of artificial intelligence (AI) CT-based body composition biomarkers at different virtual monoenergetic imaging (VMI) levels using dual-energy CT (DECT).

METHODS

This retrospective study included 88 contrast-enhanced abdominopelvic CTs acquired with rapid-kVp switching DECT. Images were reconstructed into five VMI levels (40, 55, 70, 85, 100 keV). Fully automated algorithms for quantifying CT number (HU) in abdominal fat (subcutaneous and visceral), skeletal muscle, bone, calcium (abdominal Agatston score), and organ size (area or volume) were applied. Biomarker median difference relative to 70 keV and interquartile range were reported by energy level to characterize variation. Linear regression was performed to calibrate non-70 keV data and to estimate their equivalent 70 keV biomarker attenuation values.

RESULTS

Relative to 70 keV, absolute median differences in attenuation-based biomarkers (excluding Agatston score) ranged 39-358, 12-102, 5-48, 9-75 HU for 40, 55, 85, 100 keV, respectively. For area-based biomarkers, differences ranged 6-15, 3-4, 2-7, 0-5 cm2 for 40, 55, 85, 100 keV. For volume-based biomarkers, differences ranged 12-34, 8-68, 12-52, 1-57 cm3 for 40, 55, 85, 100 keV. Agatston score behavior was more spurious with median differences ranging 70-204 HU. In general, VMI < 70 keV showed more variation in median biomarker measurement than VMI > 70 keV.

CONCLUSION

This study characterized the behavior of a fully automated AI CT biomarker toolkit across varying VMI levels obtained with DECT. The data showed relatively little biomarker value change when measured at or greater than 70 keV. Lower VMI datasets should be avoided due to larger deviations in measured value as compared to 70 keV, a level considered equivalent to conventional 120 kVp exams.

Beyond Conventional CT: Role of Dual-Energy CT in Monitoring Response to Therapy in Abdominal Malignancies

In the era of precision medicine, imaging plays a critical role in evaluating treatment response to various oncologic therapies. For decades, conventional morphologic assessments using cross-sectional imaging have been the standard for monitoring the effectiveness of systemic and locoregional therapies in patients with cancer. However, the development of new functional imaging tools has widened the scope of imaging from mere response assessment to patient selection and outcome prediction. Dual-energy CT (DECT), known for its superior material differentiation capabilities, shows promise in enhancing treatment response evaluation. DECT-based iodine quantification methods are increasingly being investigated as surrogates for assessing tumor vascularity and physiology, which is particularly important in patients undergoing emerging targeted therapies. The purpose of this review article is to discuss the current and emerging role of DECT in assessing treatment response in patients with malignant abdominal tumors. Keywords: CT-Dual Energy, Transcatheter Tumor Therapy, Tumor Response, Iodine Uptake, Therapeutic Response © RSNA, 2025.

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study

OBJECTIVES

To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an abdominal clinical study.

METHODS

An elliptical phantom with five different iodine concentrations (1-12 mgI/mL) was imaged five times with fast-kilovoltage-switching DECT for three target volume CT dose indexes. All images were reconstructed using filtered back-projection, iterative reconstruction (two levels), and DLIR algorithms. Measured and nominal iodine concentrations were compared among the algorithms. Contrast-enhanced CT of the abdomen with the same scanner was acquired in clinical patients. In arterial and portal venous phase images, iodine concentration, image noise, and coefficients of variation for four locations were retrospectively compared among the algorithms. One-way repeated-measures analyses of variance were used to evaluate differences in the iodine concentrations, standard deviations, coefficients of variation, and percentages of error among the algorithms.

RESULTS

In the phantom study, the measured iodine concentrations were equivalent among the algorithms: within ± 8% of the nominal values, with root-mean-square deviations of 0.08-0.36 mgI/mL, regardless of radiation dose. In the clinical study (50 patients; 35 men; mean age, 68 ± 11 years), iodine concentrations were equivalent among the algorithms for each location (all p > .99). Image noise and coefficients of variation were lower with DLIR than with the other algorithms (all p < .01).

CONCLUSIONS

The DLIR algorithm reduced image noise and variability of iodine concentration values compared with other reconstruction algorithms in the fast-kilovoltage-switching dual-energy CT.

KEY POINTS

• In the phantom study, standard deviations and coefficients of variation in iodine quantification were lower on images with the deep learning image reconstruction algorithm than on those with other algorithms. • In the clinical study, iodine concentrations of measurement location in the upper abdomen were consistent across four reconstruction algorithms, while image noise and variability of iodine concentrations were lower on images with the deep learning image reconstruction algorithm.

Dual-energy CT of acute bowel ischemia

Acute bowel ischemia is a condition with high mortality and requires rapid intervention to avoid catastrophic outcomes. Swift and accurate imaging diagnosis is essential because clinical findings are commonly nonspecific. Conventional contrast enhanced CT of the abdomen has been the imaging modality of choice to evaluate suspected acute bowel ischemia. However, subtlety of image findings and lack of non-contrast or arterial phase images can make correct diagnosis challenging. Dual-energy CT provides valuable information toward assessing bowel ischemia. Dual-energy CT exploits the differential X-ray attenuation at two different photon energy levels to characterize the composition of tissues and reveal the presence or absence of faint intravenous iodinated contrast to improve reader confidence in detecting subtle bowel wall enhancement. With the same underlying technique, virtual non-contrast images can help to show non-enhancing hyperdense hemorrhage of the bowel wall in intravenous contrast-enhanced scans without the need to acquire actual non-contrast scans. Dual-energy CT derived low photon energy (keV) virtual monoenergetic images emphasize iodine contrast and provide CT angiography-like images from portal venous phase scans to better evaluate abdominal arterial patency. In Summary, dual-energy CT aids diagnosing acute bowel ischemia in multiple ways, including improving visualization of the bowel wall and mesenteric vasculature, revealing intramural hemorrhage in contrast enhanced scans, or possibly reducing intravenous contrast dose.

Recognizing and Minimizing Artifacts at Dual-Energy CT

Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential.

Therapeutic response assessment in pancreatic ductal adenocarcinoma: society of abdominal radiology review paper on the role of morphological and functional imaging techniques

Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related death in the United States and is projected to be the second by 2030. Systemic combination chemotherapy is considered an essential first-line treatment for the majority of patients with PDA, in both the neoadjuvant and palliative settings. In addition, a number of novel therapies are being tested in clinical trials for patients with advanced PDA. In all cases, accurate and timely assessment of treatment response is critical to guide therapy, reduce drug toxicities and cost from a failing therapy, and aid adaptive clinical trials. Conventional morphological imaging has significant limitations, especially in the context of determining primary tumor response and resectability following neoadjuvant therapies. In this article, we provide an overview of current therapy options for PDA, highlight several morphological imaging findings that may be helpful to reduce over-staging following neoadjuvant therapy, and discuss a number of emerging imaging, and non-imaging, tools that have shown promise in providing a more precise quantification of disease burden and treatment response in PDA.