Determination of the least amount of iodine load required for the detection of pancreatic adenocarcinoma at 80-kVp CT

Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction

PURPOSE

To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms.

METHOD

A total of 56 patients who underwent 80-kVp pancreatic protocol CT for pancreatic disease evaluation from January 2022 to July 2022 were included in this retrospective study. Among them, 20 PDACs were observed. The CT raw data were reconstructed using 40% adaptive statistical IR-Veo (hybrid-IR group) and DLIR at medium- and high-strength levels (DLIR-M and DLIR-H groups, respectively). The CT attenuation of the abdominal aorta, pancreas, and PDAC (if present) at the pancreatic phase and those of the portal vein and liver at the portal venous phase; background noise; signal-to-noise ratio (SNR) of these anatomical structures; and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. The confidence scores for the image noise, overall image quality, and visibility of PDAC were qualitatively assigned using a five-point scale. Quantitative and qualitative parameters were compared among the three groups using Friedman test.

RESULTS

The CT attenuation of all anatomical structures were comparable among the three groups (P = .26-.86), except that of the pancreas (P = .001). Background noise was lower (P <.001) and SNRs (P <.001) and tumor-to-pancreas CNR (P <.001) were higher in the DLIR-H group than those in the other two groups. The image noise, overall image quality, and visibility of PDAC were better in the DLIR-H group than in the other two groups (P <.001-.003).

CONCLUSION

In 80-kVp pancreatic CT protocol, DLIR at a high-strength level improved image quality and visibility of PDAC.

Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo)

Background

There is great variability between centers regarding contrast injection protocols. They should only be injected if they can provide useful information for diagnosis with the necessary and sufficient quantity of iodine. We wanted to know through this study if the use of iodinated contrast media is optimised in abdominal CT scans performed for cancer assessment in Lomé.

Materials and Methods

It was a cross-sectional, descriptive, and analytical study with a prospective collection over a period of 6 months in three CT units in Lomé. It involved abdominal CT scans performed for oncological evaluation. Data were reported as the mean ± standard deviation. The Pearson correlation coefficient, ANOVA, chi-square, and the Fisher test were used.

Results

A total of 218 examinations were recorded. The female sex represented 56.88% of the patients. The mean age was 50.92 ± 15.78 years. The mean weight was 70.46 ± 15.23 kg. The mean BMI was 24.91 ± 5.32 kg/m². The examinations were performed with a voltage of 120 kV in 195 cases (89.45%). The mean dose of injected iodine was 0.42 ± 0.09 gI/kg with a dose of 0.40 gI/kg at 80 kV and 0.45 gI/kg at 130 kV. The mean injection rate was 2.90 ± 0.34 mL/s. The mean injected volume was 83.19 ± 7.29 mL. The mean duration of the injection was 30.60 ± 7.39 s. The mean iodine delivery rate was 0.98 ± 0.17 gI/s. There was no saline injection in 152 cases (69.72%). Liver contrast enhancement was satisfactory in 94.5% of cases. There was a strong negative linear correlation between the dose of injected iodine and weight.

Conclusions

Optimization guidelines for the use of iodinated contrast media are not always applied. Therefore, monitoring and benchmarking programmes for iodinated contrast injection protocols that involve all radiology personnel should be implemented.

Simulated twin-phase pancreatic CT generated using single portal venous phase dual-energy CT acquisition in pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the diagnostic performance of a simulated twin-phase pancreatic protocol CT generated from a single portal venous phase (PVP) dual-energy CT (DECT) acquisition in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

In this retrospective study, we included 63 patients with PDAC who underwent pancreatic protocol (pancreatic phase [PP] and PVP) DECT. Two data sets were created from this original acquisition-(1) Standard protocol (50 keV PP/65 keV PVP) and (2) Simulated protocol (40 keV/65 keV PVP). Using a 5-point scale, three readers scored image quality, tumor conspicuity, and arterial involvement by the PDAC. Signal-to-noise ratio (SNR) of the pancreas and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. Qualitative scores, quantitative parameters, and radiation dose were compared between standard and simulated protocols.

RESULTS

No significant difference in detection rate of PDAC was seen between the standard (58/63, 92.1%) and simulated protocols (56/63, 88.9%) (P = 0.76). Subjective scoring for arterial involvement for celiac (P = 0.86), superior mesenteric (P = 0.88), splenic (P = 0.86), common hepatic (P = 0.52), gastroduodenal (P = 0.95), first jejunal (P = 0.48) arteries, and aorta (P = 1.00) were comparable between two protocols. The image quality (P = 0.14), the SNR of the pancreas (P = 0.15), and CNR (P = 0.54) were comparable between two protocols. The projected mean dose-length product (DLP) (629.6 ± 148.3 mGy cm) in the simulated protocol showed a 44% reduction in radiation dose compared to the standard protocol (mean DLP, 1123.3 ± 268.9 mGy cm) (P < 0.0001).

CONCLUSIONS

Low keV images generated from a PVP DECT acquisition allows creation of a twin-phase pancreatic protocol CT with comparable diagnostic accuracy for detecting PDAC with significant reduction in radiation dose. Reduced radiation dose is desirable in surveillance and screening for pancreatic diseases.