Dataset Information

Dual-Layer Spectral CT of Pancreas Ductal Adenocarcinoma: Can Virtual Monoenergetic Images of the Portal Venous Phase Be an Alternative to the Pancreatic-Phase Scan?

ABSTRACT:

Objectives:

To determine the performance of virtual monoenergetic images (VMIs) of the portal venous phase (PVP) compared with the pancreatic-phase image for pancreatic ductal adenocarcinoma (PDAC) evaluation.

Materials and methods:

This retrospective study enrolled 64 patients with PDAC who underwent pancreatic CT with dual-layer spectral CT between February 2018 and January 2020. A polychromatic pancreatic-phase image and VMIs at 40 (VMI40), 55 (VMI55), and 70 keV (VMI70) of the PVP were generated. The tumor-to-pancreas contrast-to-noise ratio (CNR), attenuation difference, peripancreatic vascular signal-to-noise ratio (SNR), and CNR were compared among the four images. Subjective image analysis was performed for tumor conspicuity, heterogeneity, size, and arterial invasion.

Results:

VMI40 and VMI55 demonstrated higher tumor-to-pancreas CNR, attenuation difference, and higher peripancreatic vascular CNR and SNR than the pancreatic-phase image and VMI70 (p < .001). On subjective analysis, VMI55 showed the best tumor conspicuity. Moreover, the inter-reader agreement for arterial invasion in VMIs from the PVP was not inferior to that in the pancreatic-phase image.

Conclusion:

For evaluating PDAC, the VMI55 of the PVP was superior to the pancreatic-phase image in terms of tumor conspicuity and peripancreatic vascular enhancement. Therefore, the VMI55 of the PVP could be an alternative to the pancreatic-phase scan in patients suspicious of PDAC.

SUBMITTER: Han Y

PROVIDER: S-EPMC9504095 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesQuantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition.MethodsFor this cross-sectional retrospective study, 234 lung-healthy patients who underwent spectral CT in four different contrast phases (non-enhanced, pulmonary arterial, systemic arterial, and venous phase) were recruited. Virtual monoenergetic images were reconstructed from 40-160 keV, on which attenuations of segmented lung parenchyma and airway walls combined for 5th-10th subsegmental generations were assessed in Hounsfield Units (HU) by an in-house software. The spectral attenuation curve slope between 40 and 100 keV (λHU) was calculated.ResultsMean lung density was higher at 40 keV compared to that at 100 keV in all groups (p < 0.001). λHU of lung attenuation was significantly higher in the systemic (1.7 HU/keV) and pulmonary arterial phase (1.3 HU/keV) compared to that in the venous phase (0.5 HU/keV) and non-enhanced (0.2 HU/keV) spectral CT (p < 0.001). Wall thickness and wall attenuation were higher at 40 keV compared to those at 100 keV for the pulmonary and systemic arterial phase (p ≤ 0.001). λHU for wall attenuation was significantly higher in the pulmonary arterial (1.8 HU/keV) and systemic arterial (2.0 HU/keV) compared to that in the venous (0.7 HU/keV) and non-enhanced (0.3 HU/keV) phase (p ≤ 0.002).ConclusionsSpectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition, and may separate arterial and venous enhancement. Further studies are warranted to analyze spectral CT for inflammatory airway diseases.Key points• Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition. • Spectral CT may separate arterial and venous enhancement of lung parenchyma and airway wall. • The contrast enhancement can be quantified by calculating the spectral attenuation curve slope from virtual monoenergetic images.

Project description:ObjectivesThe aim of this study was to assess the objective and subjective image characteristics of monoenergetic images (MEI[+]), using a noise-optimized algorithm at different kiloelectron volts (keV) compared to polyenergetic images (PEI), in patients with pancreatic ductal adenocarcinoma (PDAC).MethodsThis retrospective, institutional review board-approved study included 45 patients (18 male, 27 female; mean age 66 years; range, 42-96 years) with PDAC who had undergone a dual-energy CT (DECT) of the abdomen for staging. One standard polyenergetic image (PEI) and five MEI(+) images in 10-keV intervals, ranging from 40 to 80 keV, were reconstructed. Line-density profile analysis, as well as the contrast-to-noise ratio (CNR) of the tumor, the signal-to-noise ratio (SNR) of the regular pancreas parenchyma and the tumor, and the CNR of the three main peripancreatic vessels, was calculated. For subjective quality assessment, two readers independently assessed the images using a 5-point Likert scale. Reader reliability was evaluated using an intraclass correlation coefficient.ResultsLine-density profile analysis revealed the largest gradient in attenuation between PDAC and regular tissue in MEI(+) at 40 keV. Low-keV MEI(+)reconstructions at 40 and 50 keV increased CNR and SNR compared to PEI (40 keV: CNR 46.8 vs. 7.5; SNRPankreas 32.5 vs. 15.7; SNRLesion 13.5 vs. 8.6; p < 0.001). MEI(+) at 40 keV and 50 keV were consistently preferred by the observers (p < 0.05), showing a high intra-observer 0.937 (0.92-0.95) and inter-observer 0.911 (0.89-0.93) agreement.ConclusionMEI(+) reconstructions at 40 keV and 50 keV provide better objective and subjective image quality compared to conventional PEI of DECT in patients with PDAC.Key points• Low-keV MEI(+) reconstructions at 40 and 50 keV increase tumor-to-pancreas contrast compared to PEI. • Low-keV MEI(+) reconstructions improve objective and subjective image quality parameters compared to PEI. • Dual-energy post-processing might be a valuable tool in the diagnostic workup of patients with PDAC.

Project description:ObjectivesTo investigate whether the increased soft tissue contrast of virtual monoenergetic images (VMIs) obtained from a spectral detector computed tomography (SDCT) system improves washout assessment of arterially hyper-enhancing liver lesions.MethodsFifty-nine arterially hyper-enhancing lesions in 31 patients (age 65 ± 9 years, M/W 20/11) were included in this IRB-approved study. All patients underwent multi-phase SDCT for HCC screening. MRI, CEUS or biopsy within 3 months served as standard of reference to classify lesions as LiRADS 3 or 4/5. VMIs and conventional images (CIs) were reconstructed. Visual analysis was performed on 40, 60, and 80 kiloelectronvolt (keV) and CIs by 3 radiologists. Presence and visibility of washout were assessed; image quality and confidence of washout evaluation were evaluated on 5-point Likert scales. Signal-to-noise ratio (SNR), lesion-to-liver contrast-to-noise ratio (CNR) (|HUlesion-HUliver|/SDliver) and washout (|HUlesion-HUliver|) were calculated. Statistical assessment was performed using ANOVA and Wilcoxon test.ResultsOn subjective lesion analysis, the highest level of diagnostic confidence and highest sensitivity for the detection of lesion washout were found for 40-keV VMIs (40 keV vs. CI, 81.3 vs. 71.3%). Image quality parameters were significantly better in low-kiloelectronvolt VMIs than in CIs (p < 0.05; e.g. SNRliver: 40 keV vs. CIs, 12.5 ± 4.1 vs. 5.6 ± 1.6). In LiRADS 4/5 lesions, CNR and quantitative washout values were significantly higher in 40-keV VMIs compared to CIs (p < 0.05; e.g. CNR and washout in 40 keV vs. CIs, 2.3 ± 1.6 vs. 0.8 ± 0.5 and 29.0 ± 19.1 vs. 12.9 ± 6.9 HU, respectively).ConclusionBy increasing lesion contrast, low-kiloelectronvolt VMIs obtained from SDCT improve washout assessment of hyper-enhancing liver lesions with respect to washout visibility and diagnostic confidence.Key points• Low-kiloelectronvolt virtual monoenergetic images from spectral detector CT facilitate washout assessment in arterially hyper-enhancing liver lesions. • Image quality and quantitative washout parameters as well as subjective washout visibility and diagnostic confidence benefit from low-kiloelectronvolt virtual monoenergetic images.

Project description:ObjectivesTo evaluate the image quality and utility of virtual monoenergetic images (VMI) of dual-layer spectrum computed tomography (DLSCT) in assessing preoperative T-stage for early rectal adenocarcinoma (ERA).MethodsThis retrospective study included 67 ERA patients (mean age 62 ± 11.1 years) who underwent DLSCT and MR examination. VMI 40-200 keV and poly energetic image (PEI) were reconstructed. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor contrast of different energy levels were calculated and compared, respectively. Two radiologists independently assess the image quality of the VMIs and PEI using 5-point scales. The diagnostic accuracies of DLSCT and HR-MRI for ERA T-staging were evaluated and compared.ResultsThe maximum noise was observed at VMI 40 keV, and noise at VMI 40-200 keV in the arterial and venous phases showed no significant difference (all p > 0.05). The highest SNR and CNR were obtained at VMI 40 keV, significantly greater than other energy levels and PEI (all p < 0.05). Tumor contrast was more evident than PEI at 40-100 keV in the arterial phase and at 40 keV in the venous phase (all p < 0.05). When compared with PEI, VMI 40 keV yielded the highest scores for overall image quality, tumor visibility, and tumor margin delineation, especially in the venous phase (p < 0.05). The overall diagnostic accuracy of DLSCT and HR-MRI for T-stage was 65.67 and 71.64% and showed no significant difference (p > 0.05).ConclusionsVMI 40 keV improves image quality and accuracy in identifying lesions, providing better diagnostic information for ERA staging.Critical relevance statementLow-keV VMI from DLSCT can improve tumor staging accuracy for early rectal carcinoma, helping guide surgical intervention decisions, and has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC.Keypoints• Compared with PEI, low-keV VIM derived from DLSCT, particularly at the 40 keV, significantly enhanced the objective and subjective image quality of ERA. • Using VMI 40 keV helped increase lesion detectability, leading to improved diagnostic accuracy for ERA. • Low-keV VMI from DLSCT has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC.

Project description:ObjectiveMeasurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application in clinical practice due to its time-consuming segmentation process. We aimed to develop and validate a deep learning algorithm (DLA) for fully automated liver and spleen segmentation using portal venous phase CT images in various liver conditions.Materials and methodsA DLA for liver and spleen segmentation was trained using a development dataset of portal venous CT images from 813 patients. Performance of the DLA was evaluated in two separate test datasets: dataset-1 which included 150 CT examinations in patients with various liver conditions (i.e., healthy liver, fatty liver, chronic liver disease, cirrhosis, and post-hepatectomy) and dataset-2 which included 50 pairs of CT examinations performed at ours and other institutions. The performance of the DLA was evaluated using the dice similarity score (DSS) for segmentation and Bland-Altman 95% limits of agreement (LOA) for measurement of the volumetric indices, which was compared with that of ground truth manual segmentation.ResultsIn test dataset-1, the DLA achieved a mean DSS of 0.973 and 0.974 for liver and spleen segmentation, respectively, with no significant difference in DSS across different liver conditions (p = 0.60 and 0.26 for the liver and spleen, respectively). For the measurement of volumetric indices, the Bland-Altman 95% LOA was -0.17 ± 3.07% for liver volume and -0.56 ± 3.78% for spleen volume. In test dataset-2, DLA performance using CT images obtained at outside institutions and our institution was comparable for liver (DSS, 0.982 vs. 0.983; p = 0.28) and spleen (DSS, 0.969 vs. 0.968; p = 0.41) segmentation.ConclusionThe DLA enabled highly accurate segmentation and volume measurement of the liver and spleen using portal venous phase CT images of patients with various liver conditions.

Project description:BackgroundEarly rectal neoplasms can be treated endoscopically with good prognosis, yet usually present with unspecific or an absence of signs and symptoms and are detected largely by invasive endoscopy with less compliance to screening. The purpose of this cross-sectional study was to explore the diagnostic value of dual-layer spectral detector computed tomography (DSCT) imaging for early rectal neoplasm.MethodsPatients who underwent DSCT for evaluation of rectal lesion or routine examination between September 2022 to September 2023 at West China Hospital were prospectively included and identified as group A (control, n=76), group B (rectal advanced adenomas and ≤T1 rectal cancer, n=59), and group C (≥T2 staging rectal cancer, n=74). Lesion visualization was graded to assess image quality. Spectral quantitative measurement, such as Hounsfield unit (HU)40 keV, HU70 keV, iodine concentration (IC), effective atomic number (Zeff), and the slope of spectral curve (λ), was analyzed and compared. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic efficacy of spectral parameters. A comparison of ROC curves was applied to test the significance of differences between the area under the curves (AUCs).ResultsCompared to poly-energetic images (PEIs), the multiple parameters from DSCT were of greater capability to recognize rectal lesions. There were significant differences in HU40 keV (208.01±43.60 vs. 255.53±45.16), HU70 keV (87.06±18.55 vs. 100.78±18.26), IC [1.91 (1.71, 2.28) vs. 2.58±0.49], Zeff [8.33 (8.25, 8.50) vs. 8.61±0.20], and λ [3.80 (3.41, 4.52) vs. 5.16±1.00] between the early neoplastic lesions in rectum and the advanced rectal cancer (P<0.001). Significant correlations were found between the DSCT parameters and tumor staging (P<0.001). Furthermore, the AUCs of IC, Zeff, λ, and HUPEI were all above 0.90 for early rectal neoplasm detection, with additional capability of discriminating early rectal neoplasm from advanced rectal cancer.ConclusionsDSCT improved tumor conspicuity and the detection of the early rectal neoplastic lesion, suggesting that it is a promising screening tool in clinical practice.