Virtual Non-contrast Imaging in The Abdomen and The Pelvis: An Overview

The impact of deep learning image reconstruction of spectral CTU virtual non contrast images for patients with renal stones

Purpose

To compare image quality and detection accuracy of renal stones between deep learning image reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) reconstructed virtual non-contrast (VNC) images and true non-contrast (TNC) images in spectral CT Urography (CTU).

Methods

A retrospective analysis was conducted on images of 70 patients who underwent abdominal-pelvic CTU in TNC phase using non-contrast scan and contrast-enhanced corticomedullary phase (CP) and excretory phase (EP) using spectral scan. The TNC scan was reconstructed using ASIR-V70 % (TNC-AR70), contrast-enhanced scans were reconstructed using AR70, DLIR medium-level (DM), and high-level (DH) to obtain CP-VNC-AR70/DM/DH and EP-VNC-AR70/DM/DH image groups, respectively. CT value, image quality and kidney stones quantification accuracy were measured and compared among groups. The subjective evaluation was independently assessed by two senior radiologists using the 5-point Likert scale for image quality and lesion visibility.

Results

DH images were superior to AR70 and DM images in objective image quality evaluation. There was no statistical difference in the liver and spleen (both P > 0.05), or within 6HU in renal and fat in CT value between VNC and TNC images. EP-VNC-DH had the lowest image noise, highest SNR, and CNR, and VNC-AR70 images had better noise and SNR performance than TNC-AR70 images (all p < 0.05). EP-VNC-DH had the highest subjective image quality, and CP-VNC-DH performed the best in lesion visibility. In stone CT value and volume measurements, there was no statistical difference between VNC and TNC (P > 0.05).

Conclusion

The DLIR-reconstructed VNC images in CTU provide better image quality than the ASIR-V reconstructed TNC images and similar quantification accuracy for kidney stones for potential dose savings.The study highlights that deep learning image reconstruction (DLIR)-reconstructed virtual non-contrast (VNC) images in spectral CT Urography (CTU) offer improved image quality compared to traditional true non-contrast (TNC) images, while maintaining similar accuracy in kidney stone detection, suggesting potential dose savings in clinical practice.

Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications-Technical Background and Post-Processing Techniques

The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine. PCCT is a recent technology that enables a scanner to quantify the energy of each photon gathered by the detector. This method gives the possibility to decrease the radiation dose and increase the spatial and temporal resolutions of scans. Both of these techniques have found a wide range of applications in radiology, including vascular studies. In this narrative review, the authors present the principles of DECT and PCCT, outline their advantages and drawbacks, and briefly discuss the application of these methods in vascular radiology.

Systematic Review on Learning-based Spectral CT

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Dual-Energy Computed Tomography Applications in the Genitourinary Tract

By virtue of material differentiation capabilities afforded through dedicated postprocessing algorithms, dual-energy CT (DECT) has been shown to provide benefit in the evaluation of various diseases. In this article, we review the diagnostic use of DECT in the assessment of genitourinary diseases, with emphasis on its role in renal stone characterization, incidental renal and adrenal lesion characterization, retroperitoneal trauma, reduction of radiation, and contrast dose and cost-effectiveness potential. We also discuss future perspectives of the DECT scanning mode, including the use of novel contrast injection strategies and photon-counting detector computed tomography.

Photon-Counting Detector CT Angiography for Endoleak Detection After Endovascular Aortic Repair: Triphasic CT With True Noncontrast Versus Biphasic CT With Virtual Noniodine Imaging

OBJECTIVES

The aim of this study was to compare image quality and endoleak detection after endovascular abdominal aortic aneurysm repair between a triphasic computed tomography (CT) with true noncontrast (TNC) and a biphasic CT with virtual noniodine (VNI) images on photon-counting detector CT (PCD-CT).

MATERIALS AND METHODS

Adult patients after endovascular abdominal aortic aneurysm repair who received a triphasic examination (TNC, arterial, venous phase) on a PCD-CT between August 2021 and July 2022 were retrospectively included. Endoleak detection was evaluated by 2 blinded radiologists on 2 different readout sets (triphasic CT with TNC-arterial-venous vs biphasic CT with VNI-arterial-venous). Virtual noniodine images were reconstructed from the venous phase. The radiologic report with additional confirmation by an expert reader served as reference standard for endoleak presence. Sensitivity, specificity, and interreader agreement (Krippendorf α) were calculated. Image noise was assessed subjectively in patients using a 5-point scale and objectively calculating the noise power spectrum in a phantom.

RESULTS

One hundred ten patients (7 women; age, 76 ± 8 years) with 41 endoleaks were included. Endoleak detection was comparable between both readout sets with a sensitivity and specificity of 0.95/0.84 (TNC) versus 0.95/0.86 (VNI) for reader 1 and 0.88/0.98 (TNC) versus 0.88/0.94 (VNI) for reader 2. Interreader agreement for endoleak detection was substantial (TNC: 0.716, VNI: 0.756). Subjective image noise was comparable between TNC and VNI (4; IQR [4, 5] vs 4; IQR [4, 5], P = 0.44). In the phantom, noise power spectrum peak spatial frequency was similar between TNC and VNI (both f peak = 0.16 mm -1 ). Objective image noise was higher in TNC (12.7 HU) as compared with VNI (11.5 HU).

CONCLUSIONS

Endoleak detection and image quality were comparable using VNI images in biphasic CT as compared with TNC images in triphasic CT offering the possibility to reduce scan phases and radiation exposure.

Addressing Challenges of Opportunistic Computed Tomography Bone Mineral Density Analysis

Computed tomography (CT) offers advanced biomedical imaging of the body and is broadly utilized for clinical diagnosis. Traditionally, clinical CT scans have not been used for volumetric bone mineral density (vBMD) assessment; however, computational advances can now leverage clinically obtained CT data for the secondary analysis of bone, known as opportunistic CT analysis. Initial applications focused on using clinically acquired CT scans for secondary osteoporosis screening, but opportunistic CT analysis can also be applied to answer research questions related to vBMD changes in response to various disease states. There are several considerations for opportunistic CT analysis, including scan acquisition, contrast enhancement, the internal calibration technique, and bone segmentation, but there remains no consensus on applying these methods. These factors may influence vBMD measures and therefore the robustness of the opportunistic CT analysis. Further research and standardization efforts are needed to establish a consensus and optimize the application of opportunistic CT analysis for accurate and reliable assessment of vBMD in clinical and research settings. This review summarizes the current state of opportunistic CT analysis, highlighting its potential and addressing the associated challenges.

Computed tomography of hyper-attenuated liver: Pictorial essay

Demonstration of a very dense or hyper-attenuated liver on the pre-contrast CT images of the abdomen can be an unexpected finding. It may present as a diagnostic challenge if the underlying cause of it is not apparent from the provided clinical history. There are about 12 different pathologic conditions that are associated with deposition of radiopaque elements within the hepatic parenchyma, resulting in diffuse or multi-lobar hyperdense appearance of the liver on abdominal radiographs and CT. Most of them are drug-induced or iatrogenic in nature, while others are the sequelae of genetic disorders like thalassemia, Wilson's disease, and primary hemochromatosis. This pictorial essay will present the CT appearance and etiology of hyper-attenuated liver in various clinical entities.

CT in non-traumatic acute abdominal emergencies: Comparison of unenhanced acquisitions and single-energy iodine mapping for the characterization of bowel wall enhancement

Objectives

To evaluate the benefit of unenhanced CT and single energy iodine mapping (SIM) to conventional contrast-enhanced CT for bowel wall enhancement characterization in an acute abdomen setting.

Methods

CT images from 45 patients with a suspected acute abdomen who underwent abdominopelvic CT from April 2018 to June 2018 were analyzed retrospectively by two independent radiologists. These patients had been referred by emergency department physicians in a context of acute abdominal pain and had a confirmed etiological diagnosis. Three image sets were evaluated separately (portal phase images alone; portal phase images and unenhanced images, portal phase images, and single energy iodine maps). Diagnostic accuracy and confidence were assessed. Quantitative analysis of bowel wall enhancement was also performed.

Results

The number of correct diagnoses increased by 8% and 12% with unenhanced images and 6% and 13% with SIM for readers 1 and 2, respectively, compared to the portal phase only. There was an improvement in the confidence of the etiological diagnosis with the number of certain diagnoses increasing from 23% to 100%, which was statistically significant for reader 2 and of borderline significance for reader 1 (P = 0.002 and 0.052, respectively) when unenhanced phase and SIM were added. The inter-rater agreement improved when unenhanced and portal phase images were associated, compared to portal phase images alone (kappa = 0.652 [ICC=0.482-0.822] and 0.42 [ICC=0.241-0.607] respectively).

Conclusion

SIM and unenhanced images improve the reproducibility and the diagnostic confidence to diagnose ischemic and inflammatory/infectious bowel wall thickening compared to portal phase images alone.

Summary sentence

The analysis of unenhanced and SIM images in association with portal phase images improves the reproducibility and the radiologist's confidence in the etiological diagnosis of acute non-traumatic bowel wall thickening in adults.