Clinical Value of Dual-energy CT in Detection of Pancreatic Adenocarcinoma: Investigation of the Best Pancreatic Tumor Contrast to Noise Ratio

Improvement of image quality of laryngeal squamous cell carcinoma using noise-optimized virtual monoenergetic image and nonlinear blending image algorithms in dual-energy computed tomography

BACKGROUND

Dual-energy computed tomography (DECT) has been used to improve image quality of head and neck squamous cell carcinoma (SCC). This study aimed to assess image quality of laryngeal SCC using linear blending image (LBI), nonlinear blending image (NBI), and noise-optimized virtual monoenergetic image (VMI+) algorithms.

METHODS

Thirty-four patients with laryngeal SCC were retrospectively enrolled between June 2019 and December 2020. DECT images were reconstructed using LBI (80 kV and M_0.6), NBI, and VMI+ (40 and 55 keV) algorithms. Contrast-to-noise ratio (CNR), tumor delineation, and overall image quality were assessed and compared.

RESULTS

VMI+ (40 keV) had the highest CNR and provided better tumor delineation than VMI+ (55 keV), LBI, and NBI, while NBI provided better overall image quality than VMI+ and LBI (all corrected p < 0.05).

CONCLUSIONS

VMI+ (40 keV) and NBI improve image quality of laryngeal SCC and may be preferable in DECT examination.

White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

Metal artefact reduction for accurate tumour delineation in radiotherapy

BACKGROUND AND PURPOSE

Two techniques for metal artefact reduction for computed tomography were studied in order to identify their impact on tumour delineation in radiotherapy.

MATERIALS AND METHODS

Using specially designed phantoms containing metal implants (dental, spine and hip) as well as patient images, we investigated the impact of two methods for metal artefact reduction on (A) the size and severity of metal artefacts and the accuracy of Hounsfield Unit (HU) representation, (B) the visual impact of metal artefacts on image quality and (C) delineation accuracy. A metal artefact reduction algorithm (MAR) and two types of dual energy virtual monochromatic (DECT VM) reconstructions were used separately and in combination to identify the optimal technique for each implant site.

RESULTS

The artefact area and severity was reduced (by 48-76% and 58-79%, MAR and DECT VM respectively) and accurate Hounsfield-value representation was increased by 22-82%. For each energy, the observers preferred MAR over non-MAR reconstructions (p < 0.01 for dental and hip cases, p < 0.05 for the spine case). In addition, DECT VM was preferred for spine implants (p < 0.01). In all cases, techniques that improved target delineation significantly (p < 0.05) were identified.

CONCLUSIONS

DECT VM and MAR techniques improve delineation accuracy and the optimal of reconstruction technique depends on the type of metal implant.

Dual energy CT applications in pancreatic pathologies

Dual energy CT (DECT) is a technology that is gaining widespread acceptance, particularly for its abdominopelvic applications. Pancreatic pathologies are an ideal application for the many advantages offered by dual energy post-processing. This article reviews the current literature on dual energy CT pancreatic imaging, specifically in the evaluation of pancreatic adenocarcinoma, other solid and cystic pancreatic neoplasms, and pancreatitis. The advantages in characterization and quantification of enhancement, detection of subtle lesions, and potential reduction of imaging phases and contrast usage are reviewed. We also discuss directions for future research, and the ideal use of dual energy CT in routine clinical practice.

Quantitative and Qualitative Comparison of Single-Source Dual-Energy Computed Tomography and 120-kVp Computed Tomography for the Assessment of Pancreatic Ductal Adenocarcinoma

PURPOSE

The aim of this study was to compare contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) between pancreatic-phase dual-energy computed tomography (DECT) and 120-kVp CT for pancreatic ductal adenocarcinoma (PDA).

MATERIALS AND METHODS

Seventy-eight patients underwent multiphasic pancreatic imaging protocols for PDA (40, DECT; 38, 120-kVp CT [control]). Using pancreatic phase, CNR and SNR for PDA were obtained for DECT at monochromatic energies 50 through 80 keV, iodine material density images, and 120-kVp images. Using a 5-point scale (1, excellent; 5, markedly limited), images were qualitatively assessed by 2 radiologists in consensus for PDA detection, extension, vascular involvement, and noise. Wilcoxon signed rank and 2-sample tests were used to compare the qualitative measures, CNR and SNR, for DECT and 120-kVp images. Bonferroni correction was applied.

RESULTS

Iodine material density image had significantly higher CNR and SNR for PDA than any monochromatic energy images (P < 0.0001) and the 120-kVp images. Qualitatively, 70-keV images were rated highest in the categories of tumor extension and vascular invasion and were similar to 120-kVp images.

CONCLUSIONS

Our results indicate that DECT improves PDA lesion conspicuity compared with routine 120-kVp CT, which may allow for better detection of PDA.

Impact of dual-energy CT prior to radioembolization (RE)

BACKGROUND

Depiction of the exact arterial liver anatomy as well as identifying potential extrahepatic non-target vessels is crucial for a successful preparation of radioembolization (RE).

PURPOSE

To compare the diagnostic impact of dual-energy computed tomography (DECT) to digital subtraction angiography prior to RE.

MATERIAL AND METHODS

DECT was applied in 46 patients with hepatocellular carcinoma (HCC) prior to RE. Eighty kV DE as well as reconstructed 120 kV equivalent DE datasets were evaluated in comparison to correlating digital subtraction angiography (DSA) datasets. Two radiologists evaluated in consensus the delineation of liver arteries and extrahepatic non-target vessels utilizing a 4-point scale (4 = excellent delineation; 1 = non-diagnostic). In addition, the arterial vascularization of liver segment IV was evaluated and classified: signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR; liver arteries to adjacent liver tissue) were obtained via ROI analysis.

RESULTS

Both imaging techniques (DECT, DSA) enabled high-quality assessment of all analyzed liver arteries. Out of the two CT datasets, 80 kVp-DE datasets offered superior delineation of the right gastric artery (3.5 ± 0.7 vs. 2.5 ± 0.5), the vascularization of segment IV (3.9 ± 0.2 vs. 3.3 ± 0.5) as well as potential extrahepatic non-target vessels (3.9 ± 0.1 vs. 3.3 ± 0.5). In accordance to the results of the qualitative analysis, 80 kVp-DE datasets also yielded higher SNR (34.84 vs. 29.31) and CNR (28.29 vs. 21.8) values in comparison to the 120 kVp datasets.

CONCLUSION

Eighty kVp DECT enables a significantly better assessment of the arteries of the upper abdomen for therapy planning in comparison to correlating 120 kVp datasets. This may allow for identification of potential extrahepatic non-target vessels and assessment of target volume for therapy planning prior to DSA.

Application of computed tomography virtual noncontrast spectral imaging in evaluation of hepatic metastases: a preliminary study

Objective:

The objective was to qualitatively and quantitatively evaluate hepatic metastases using computed tomography (CT) virtual noncontrast (VNC) spectral imaging in a retrospective analysis.

Methods:

Forty hepatic metastases patients underwent CT scans including the conventional true noncontrast (TNC) and the tri-phasic contrast-enhanced dual energy spectral scans in the hepatic arterial, portal venous, and equilibrium phases. The tri-phasic spectral CT images were used to obtain three groups of VNC images including in the arterial (VNCa), venous (VNCv), and equilibrium (VNCe) phase by the material decomposition process using water and iodine as a base material pair. The image quality and the contrast-to-noise ratio (CNR) of metastasis of the four groups were compared with ANOVA analysis. The metastasis detection rates with the four nonenhanced image groups were calculated and compared using the Chi-square test.

Results:

There were no significant differences in image quality among TNC, VNCa and VNCv images (P > 0.05). The quality of VNCe images was significantly worse than that of other three groups (P < 0.05). The mean CNR of metastasis in the TNC and VNCs images was 1.86, 2.42, 1.92, and 1.94, respectively; the mean CNR of metastasis in VNCa images was significantly higher than that in other three groups (P < 0.05), while no statistically significant difference was observed among VNCv, VNCe and TNC images (P > 0.05). The metastasis detection rate of the four nonenhanced groups with no statistically significant difference (P > 0.05).

Conclusions:

The quality of VNCa and VNCv images is identical to that of TNC images, and the metastasis detection rate in VNC images is similar to that in TNC images. VNC images obtained from arterial phase show metastases more clearly. Thus, VNCa imaging may be a surrogate to TNC imaging in hepatic metastasis diagnosis.