Treatment response after radioembolisation in patients with hepatocellular carcinoma-An evaluation with dual energy computed-tomography

Dual-energy CT applications on liver imaging: what radiologists and radiographers should know? A systematic review

PURPOSE

This review aims to provide a comprehensive summary of DECT techniques, acquisition workflows, and post-processing methods. By doing so, we aim to elucidate the advantages and disadvantages of DECT compared to conventional single-energy CT imaging.

METHODS

A systematic search was conducted on MEDLINE/EMBASE for DECT studies in liver imaging published between 1980 and 2024. Information regarding study design and endpoints, patient characteristics, DECT technical parameters, radiation dose, iodinated contrast agent (ICA) administration and postprocessing methods were extracted. Technical parameters, including DECT phase, field of view, pitch, collimation, rotation time, arterial phase timing (from injection), and venous timing (from injection) from the included studies were reported, along with formal narrative synthesis of main DECT applications for liver imaging.

RESULTS

Out of the initially identified 234 articles, 153 met the inclusion criteria. Extensive variability in acquisition parameters was observed, except for tube voltage (80/140 kVp combination reported in 50% of articles) and ICA administration (1.5 mL/kg at 3-4 mL/s, reported in 91% of articles). Radiation dose information was provided in only 40% of articles (range: 6-80 mGy), and virtual non-contrast imaging (VNC) emerged as a common strategy to reduce the radiation dose. The primary application of DECT post-processed images was in detecting focal liver lesions (47% of articles), with predominance of study focusing on hepatocellular carcinoma (HCC) (27%). Furthermore, a significant proportion of the articles (16%) focused on enhancing DECT protocols, while 15% explored metastasis detection.

CONCLUSION

Our review recommends using 80/140 kVp tube voltage with 1.5 mL/kg ICA at 3-4 mL/s flow rate. Post-processing should include low keV-VMI for enhanced lesion detection, IMs for tumor iodine content evaluation, and VNC for dose reduction. However, heterogeneous literature hinders protocol standardization.

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques

OBJECTIVES

To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches.

METHODS

Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration.

RESULTS

Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001).

CONCLUSIONS

We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver.

CLINICAL RELEVANCE STATEMENT

Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging.

KEY POINTS

• Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Imaging in interventional oncology, the better you see, the better you treat

Imaging and image processing is the fundamental pillar of interventional oncology in which diagnostic, procedure planning, treatment and follow-up are sustained. Knowing all the possibilities that the different image modalities can offer is capital to select the most appropriate and accurate guidance for interventional procedures. Despite there is a wide variability in physicians preferences and availability of the different image modalities to guide interventional procedures, it is important to recognize the advantages and limitations for each of them. In this review, we aim to provide an overview of the most frequently used image guidance modalities for interventional procedures and its typical and future applications including angiography, computed tomography (CT) and spectral CT, magnetic resonance imaging, Ultrasound and the use of hybrid systems. Finally, we resume the possible role of artificial intelligence related to image in patient selection, treatment and follow-up.

Pseudo dual-energy CT-derived iodine mapping using single-energy CT data based on a convolution neural network

Objective

The objectives of this study are: (1) to develop a convolutional neural network model that yields pseudo high-energy CT (CTpseudo_high) from simple image processed low-energy CT (CTlow) images, and (2) to create a pseudo iodine map (IMpseudo) and pseudo virtual non-contrast (VNCpseudo) images for thoracic and abdominal regions.

Methods

Eighty patients who underwent dual-energy CT (DECT) examinations were enrolled. The data obtained from 55, 5, and 20 patients were used for training, validation, and testing, respectively. The ResUnet model was used for image generation model and was trained using CTlow and high-energy CT (CThigh) images. The proposed model performance was evaluated by calculating the CT values, image noise, mean absolute errors (MAEs), and histogram intersections (HIs).

Results

The mean difference in the CT values between CTpseudo_high and CThigh images were less than 6 Hounsfield unit (HU) for all evaluating patients. The image noise of CTpseudo_high was significantly lower than that of CThigh. The mean MAEs was less than 15 HU, and HIs were almost 1.000 for all the patients. The evaluation metrics of IM and VNC exhibited the same tendency as that of the comparison between CTpseudo_high and CThigh images.

Conclusions

Our results indicated that the proposed model enables to obtain the DECT images and material-specific images from only single-energy CT images.

Advances in knowledges

We constructed the CNN-based model which can generate pseudo DECT image and DECT-derived material-specific image using only simple image-processed CTlow images for the thoracic and abdominal regions.

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

Dual energy CT applications in oncological imaging

Cancer is the second leading cause of death in the United States, killing more than 600.000 people each year.¹ Despite several screening programs available, cancer diagnosis is often made incidentally during imaging studies performed for other reasons. Once the diagnosis is made, treatment assessment and surveillance of these patients heavily rely on radiological tools. Computed tomography (CT) in particular is one of the most commonly ordered modalities due to wide availability even in the most remote locations, and fast results. However, conventional CT often cannot definitively characterize a neoplastic lesion unless it was tailored toward answering a specific question. Furthermore, characterizing small lesions can be difficult with CT. An innovative technique called dual-energy CT (DECT) offers solutions to some of the challenges of conventional CT in oncological imaging.

Spectral detector CT applications in advanced liver imaging

OBJECTIVE

Spectral detector CT (SDCT) has many applications in advanced liver imaging. If appropriately utilized, this technology has the potential to improve image quality, provide new diagnostic information, and allow for decreased radiation dose. The purpose of this review is to familiarize radiologists with the uses of SDCT in liver imaging.

CONCLUSION

SDCT has a variety of post-processing techniques, which can be used in advanced liver imaging and can significantly add value in clinical practice.

Advanced CT techniques for assessing hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth-most common cancer in the world, and hepatic dynamic CT studies are routinely performed for its evaluation. Ongoing studies are examining advanced imaging techniques that may yield better findings than are obtained with conventional hepatic dynamic CT scanning. Dual-energy CT-, perfusion CT-, and artificial intelligence-based methods can be used for the precise characterization of liver tumors, the quantification of treatment responses, and for predicting the overall survival rate of patients. In this review, the advantages and disadvantages of conventional hepatic dynamic CT imaging are reviewed and the general principles of dual-energy- and perfusion CT, and the clinical applications and limitations of these technologies are discussed with respect to HCC. Finally, we address the utility of artificial intelligence-based methods for diagnosing HCC.

Inter-scan and inter-scanner variation of quantitative dual-energy CT: evaluation with three different scanner types

OBJECTIVES

To investigate inter-scan and inter-scanner variation of iodine concentration (IC) and attenuation in virtual monoenergetic images at 65 keV (HU_65keV) in patients with repeated abdominal examinations on dual-source (dsDECT), rapid kV switching (rsDECT), and dual-layer detector DECT (dlDECT).

METHODS

We retrospectively included 131 patients who underwent two abdominal DECT examinations on the same scanner (dsDECT: n = 46, rsDECT: n = 45, dlDECT: n = 40). IC and HU_65keV were measured by placing regions of interest in the liver, spleen, kidneys, aorta, portal vein, and inferior vena cava. Overall IC and HU_65keV for each scanner, their inter-scan differences and proportional variation were calculated and compared between scanner types.

RESULTS

The three scanner-specific cohorts showed similar weight, body diameter, age, sex, and contrast media injection parameters as well as inter-scan differences hereof (p range: 0.23-0.99). Absolute inter-scan differences of HU_65keV and IC were comparable between scanners (p range: 0.08-1.0). Overall inter-scan variation was significantly higher in IC than HU_65keV (p < 0.05). For the liver, rsDECT showed significantly lower inter-scan variation of IC compared to dsDECT/dlDECT (p = 0.005/0.01), while for the spleen, this difference was only significant compared to dsDECT (p = 0.015). Normalizing IC of the liver to the portal vein and of the spleen to the aorta did not significantly reduce inter-scan variation (p = 0.97 and 0.50).

CONCLUSIONS

Iodine measurements across different DECT scanners show inter-scan variation which is higher compared to variation of attenuation values. Inter-scanner differences in longitudinal variation and overall iodine concentration depend on the scanner pairs and organs assessed and should be acknowledged in clinical and scientific DECT applications.

KEY POINTS

• All scanner types showed comparable inter-scan variation of attenuation, while for iodine, the rapid kV switching DECT showed lower variability in the liver and spleen. • Iodine concentration showed higher inter-scan variation than attenuation measurements; normalization to vessels did not significantly improve inter-scan reproducibility of iodine concentration in parenchymal organs. • Differences between the three scanner types regarding overall iodine concentration and attenuation obtained from both timepoints were within the range of average intra-patient, inter-scan differences for most assessed organs and vessels.

Optimizing the Combination of Immunotherapy and Trans-Arterial Locoregional Therapy for Stages B and C Hepatocellular Cancer

Hepatocellular carcinoma (HCC), the most common primary hepatic malignancy worldwide, is the second leading cause of cancer-related death. Underlying liver dysfunction and advanced stage of disease require treatments to be optimally timed and implemented to minimize hepatic parenchymal damage while maximizing disease response and quality of life. Locoregional therapies (LRTs) such as trans-arterial chemo- and radio-embolization remain effective for intermediate liver-only and advanced HCC disease (i.e., Barcelona-Clinic liver cancer stages B and C) not amendable to primary resection or ablation. Additionally, these minimally invasive interventions have been shown to augment the immune system. This and the recent success of immune-oncologic treatments for HCC have generated interest in applying these therapies in combination with such locoregional interventions to improve patient outcomes and response rates. This report reviews the use of trans-arterial LRTs with immunotherapy for stages B and C HCC, potential biomarkers, and imaging methods for assessing the response and safety of such combinations.

Classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on multi-phase CT scans

Liver and bile duct cancers are leading causes of worldwide cancer death. The most common ones are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Influencing factors and prognosis of HCC and ICC are different. Precise classification of these two liver cancers is essential for treatment and prevention plans. The aim of this study is to develop a machine-based method that differentiates between the two types of liver cancers from multi-phase abdominal computerized tomography (CT) scans. The proposed method consists of two major steps. In the first step, the liver is segmented from the original images using a convolutional neural network model, together with task-specific pre-processing and post-processing techniques. In the second step, by looking at the intensity histograms of the segmented images, we extract features from regions that are discriminating between HCC and ICC, and use them as an input for classification using support vector machine model. By testing on a dataset of labeled multi-phase CT scans provided by Maharaj Nakorn Chiang Mai Hospital, Thailand, we have obtained 88% in classification accuracy. Our proposed method has a great potential in helping radiologists diagnosing liver cancer.

Dual-Energy CT-Derived Volumetric Iodine Concentration for the Assessment of Therapeutic Response after Microwave Ablation in a Rabbit Model with Intrahepatic VX2 Tumor

PURPOSE

To evaluate whether changes in volumetric iodine concentration (VIC) could serve as a suitable predictor of therapeutic response to microwave (MW) ablation in a rabbit intrahepatic VX2 tumor model.

MATERIALS AND METHODS

Sixteen intrahepatic VX2 tumors were transplanted in 8 New Zealand White rabbits treated with MW ablation. Contrast-enhanced dual-energy CT scans were obtained at baseline and follow-up. Therapeutic response assessment by modified Response Evaluation Criteria In Solid Tumors (mRECIST), Choi criteria, and VIC changes was performed. An intraclass correlation coefficient (ICC) was used to characterize consistency of assessment results among the criteria used. Technical success was evaluated with explant pathologic findings as a reference. Correlations between technical success and variations in diameter, CT density, and VIC were analyzed.

RESULTS

Disease control was observed in 4, 8, and 10 of the 16 tumors per mRECIST, Choi criteria, and VIC changes, respectively. VIC exhibited strong consistency (ICC = 0.807, P < .0001) with Choi criteria. According to explant pathology, technical success was achieved in 10 of the 16 tumors. There was a moderate correlation between VIC changes and technical success (r = 0.532, P = .034), and no correlation was found between technical success and variations in diameter or CT density.

CONCLUSIONS

Compared with mRECIST and Choi criteria, dual-energy CT-derived VIC allowed for better prediction of therapeutic response after MW ablation and could provide a potential imaging biomarker of tumor response to MW ablation in patients with hepatocellular carcinoma.

Hepatocellular Carcinoma: Diagnosis, Treatment Algorithms, and Imaging Appearance after Transarterial Chemoembolization

Hepatocellular carcinoma (HCC) is a common cause of cancer-related death, with incidence increasing worldwide. Unfortunately, the overall prognosis for patients with HCC is poor and many patients present with advanced stages of disease that preclude curative therapies. Diagnostic and interventional radiologists play a key role in the management of patients with HCC. Diagnostic radiologists can use contrast-enhanced computed tomography (CT), magnetic resonance imaging, and ultrasound to diagnose and stage HCC, without the need for pathologic confirmation, by following established criteria. Once staged, the interventional radiologist can treat the appropriate patients with percutaneous ablation, transarterial chemoembolization, or radioembolization. Follow-up imaging after these liver-directed therapies for HCC can be characterized according to various radiologic response criteria; although, enhancement-based criteria, such as European Association for the Study of the Liver and modified Response Evaluation Criteria in Solid Tumors, are more reflective of treatment effect in HCC. Newer imaging technologies like volumetric analysis, dual-energy CT, cone beam CT and perfusion CT may provide additional benefits for patients with HCC.

Multi-detector CT: Liver protocol and recent developments

Multi-detector computed tomography is today the workhorse in the evaluation of the vast majority of patients with known or suspected liver disease. Reasons for that include widespread availability, robustness and repeatability of the technique, time-efficient image acquisitions of large body volumes, high temporal and spatial resolution as well as multiple post-processing capabilities. However, as the technique employs ionizing radiation and intravenous iodine-based contrast media, the associated potential risks have to be taken into account. In this review article, liver protocols in clinical practice are discussed with emphasis on optimisation strategies. Furthermore, recent developments such as perfusion CT and dual-energy CT and their applications are presented.

Material density iodine images in dual-energy CT: Detection and characterization of hypervascular liver lesions compared to magnetic resonance imaging

PURPOSE

To determine the diagnostic potential of Material Density (MD) iodine images in dual-energy CT (DECT) for the detection and characterization of hypervascular liver lesions compared to monenergetic 65keV images, using MRI as the standard.

MATERIALS AND METHODS

The study complied with HIPAA guidelines and was approved by the institutional review board. Fifty-two patients (36 men, 16 women; age range, 29-87 years) with 236 hypervascular liver lesions (benign, n=31; malignant, n=205; mean diameter, 29.4mm; range: 6-90.6mm) were included. All of them underwent both contrast-enhanced single-source DECT and contrast-enhanced abdominal MRI within three months. Late arterial phase CT imaging was performed with dual energies of 140 and 80kVp. Protocol A showed monoenergetic 65keV images, and protocol B presented MD-iodine images. Three radiologists qualitatively evaluated randomized images, and lesion detection, characterization, and reader confidence were recorded. Liver-to-lesion ratio (LLR) and contrast-to-noise ratio (CNR) were assessed on protocol A, protocol B, and MRI. Paired t-tests were used to compare LLR, CNR, and the number of detected lesions.

RESULTS

LLR was significantly increased in protocol B (2.8±2.33) compared to protocol A (0.77±0.55) and MRI (0.61±0.66). CNR was significantly higher in protocol B (0.08±0.04) compared to protocol A (0.01±0.01) and MRI (0.01±0.01). All three observers correctly identified more liver lesions using protocol B vs protocol A: 83.13% vs 63.64%, 84.57% vs 68.09%, and 79.37% vs 65.52%. There was no significant difference between the three observers in classification of a lesion as benign or malignant. However, higher diagnostic confidence was reported more frequently by the experienced radiologist when using protocol B vs protocol A (84.6% vs 75%).

CONCLUSION

MD-iodine images in DECT help to increase the conspicuity and detection of hypervascular liver lesions.