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Purpose: To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients. Materials and Methods: 30 female patients (mean age, 63.12 ± 14.2 years) diagnosed with breast cancer who underwent pre-operative chest DECT were included. To establish a reference standard, the study correlated histologic repots after lymphadenectomy or confirming metastasis in previous/follow-up examinations. Iodine concentration and fat fraction were determined through region-of-interest measurements on venous DECT iodine maps. Receiver operating characteristic curve analysis was conducted to identify the optimal threshold for differentiating between metastatic and non-metastatic lymph nodes. Results: A total of 168 lymph nodes were evaluated, divided into axillary (metastatic: 46, normal: 101) and intramammary (metastatic: 10, normal: 11). DECT-based fat fraction values exhibited significant differences between metastatic (9.56 ± 6.20%) and non-metastatic lymph nodes (41.52 ± 19.97%) (p < 0.0001). Absolute iodine concentrations showed no significant differences (2.25 ± 0.97 mg/mL vs. 2.08 ± 0.97 mg/mL) (p = 0.7999). The optimal fat fraction threshold for diagnosing metastatic lymph nodes was determined to be 17.75%, offering a sensitivity of 98% and a specificity of 94%. Conclusions: DECT fat fraction analysis emerges as a promising method for identifying metastatic lymph nodes, overcoming the morpho-volumetric limitations of conventional CT regarding lymph node assessment. This innovative approach holds potential for improving pre-operative lymph node evaluation in breast cancer patients, offering enhanced diagnostic accuracy.

Dual-layer Dual-Energy CT (dl-DECT) allows one to create virtual non-contrast (VNC) reconstructions from contrast-enhanced CT scans, with a consequent decrease of the radiation dose. This study aims to assess the reliability of VNC for the diagnostic evaluation of renal masses in comparison with true non-contrast (TNC) images. The study cohort included 100 renal masses in 40 patients who underwent dl-DECT between June and December 2021. Attenuation values and standard deviations were assessed through the drawing of regions of interest on TNC and VNC images reconstructed from corticomedullary and nephrographic phases. A Wilcoxon signed-rank test was performed in order to assess equivalence of data and Spearman’s Rho correlation coefficient to evaluate correlations between each parameter. The diagnostic accuracy of VNC was estimated through the performance of receiver operating characteristic (ROC) curve analysis. Differences between attenuation values were, respectively, 74%, 18%, 5% and 3% (TNC-VNCcort), and 74%, 15%, 9% and 2% (TNC-VNCneph). The Wilcoxon signed-rank test demonstrated the equivalence of attenuation values between the TNC and VNC images. The diagnostic performance of VNC images in the depiction of kidney simple cysts remains high compared to TNC (VNCcort-AUC: 0.896; VNCneph-AUC: 0.901, TNC-AUC: 0.903). In conclusion, quantitative analysis of attenuation values showed a strong agreement between VNC and TNC images in the evaluation of renal masses.

Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods:Fifty CCTA datasets (30 men; mean age: 61.6 ± 12.3 years) acquired with a DLCT system were reconstructed using virtual monoenergetic images (VMI) from 40 to 100 keV with 10 keV increment and compared with conventional images. An analysis of objective image quality was performed, evaluating the signal- and contrast-to-noise ratio. For the subjective assessment, two readers used a 5-point Likert scoring system to evaluate sharpness, noise, demarcation of coronary plaques, vascular contrast, and an overall score. Furthermore, coronary stenoses were analyzed for each vessel to describe the diagnostic agreement between monoenergetic images and conventional images. Results: The objective image analysis showed that all reconstructions from 70 keV to 40 keV show higher SNR (from 61.33 ± 12.46 to 154.22 ± 42.91, respectively) and CNR (from 51.45 ± 11.19 to 135.63 ± 39.38, respectively) compared with conventional images (all p < 0.001). The 40 keV monoenergetic images obtained the best average score for sharpness, vascular contrast, and for the overall impression (all with p < 0.001). The detection and grading of stenoses of the coronary arteries with conventional and monoenergetic images at 70 keV and 40 keV showed an overall excellent interobserver agreement (k= 0.81 [0.72–0.91]).Conclusions: The 40 keV virtual monoenergetic images obtained with a DLCT system allow the objective and subjective image quality of coronary CT angiography to be improved.

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 (m

The technological development of Artificial Intelligence (AI) has grown rapidly in recent years. The applications of AI to cardiovascular imaging are various and could improve the radiologists’ workflow, speeding up acquisition and post-processing time, increasing image quality and diagnostic accuracy. Several studies have already proved AI applications in Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance, including automatic evaluation of calcium score, quantification of coronary stenosis and plaque analysis, or the automatic quantification of heart volumes and myocardial tissue characterization. The aim of this review is to summarize the latest advances in the field of AI applied to cardiovascular CT and MR imaging.

Barium inhalation usually relates to accidental aspiration during radiological procedures with an oral contrast agent. When present, barium lung deposits are visible as high-density opacities on chest X-ray or CT scan due to high atomic number, and they may be indistinguishable from calcifications. Dual-layer spectral CT has shown good material differentiation capabilities, due to its increased high-Z element range and smaller spectral separation between low- and high-energy spectral data. We present the case of a 17-year-old female with a history of tracheoesophageal fistula, who underwent chest CT angiography on a dual-layer spectral platform. Despite the close Z numbers and K-edge energy levels of the two different contrast materials, spectral CT was able to identify barium lung deposits from a previous swallowing study and to clearly distinguish them from calcium and the surrounding iodine-containing structures.