Imaging findings of primary vaginal malignancies by dual-layer spectral detector CT: description of two patients.
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ABSTRACT:
SUBMITTER: Cui Y
PROVIDER: S-EPMC10784025 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Imaging findings of primary vaginal malignancies by dual-layer spectral detector CT: description of two patients.
Cui Yuanyuan Y Zhang Zhengwei Z Zhang Xiaohui X Zhao Baolian B Shi Xiaolei X Zhu Zhi Z Liu Xiaojun X Liu Shiyuan S Xiao Yi Y
Quantitative imaging in medicine and surgery 20231117 1
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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.
| S-EPMC11651995 | biostudies-literature
Project description:ObjectiveTo assess the diagnostic value of spectral parameters in differentiating adrenal adenomas from metastases based on dual-layer detector spectral CT (DLSCT).Materials and methodsPatients with adenomas or metastases who underwent enhanced DLSCT of the adrenals were enrolled. The CT values of virtual non-contrast images (CTVNC), iodine density (ID) values, and Z-effective (Z-eff) values, the normalized iodine density (NID) values, slopes of spectral HU curves (s-SHC), and iodine-to-CTVNC ratios of the tumors were measured in each phase. Receiver operating characteristic (ROC) curves were used to compare the diagnostic values.ResultsNinety-nine patients with 106 adrenal lesions (63 adenomas, 43 metastases) were included. In the venous phase, all spectral parameters were significantly different between adenomas and metastases (all p < 0.05). The combined spectral parameters showed a better diagnostic performance in the venous phase than in other phase (p < 0.05). The iodine-to-CTVNC value had a larger area under the ROC curve (AUC) than the other spectral parameters in the differential diagnosis of adenomas and metastases, with a diagnostic sensitivity and specificity of 74.4% and 91.9%, respectively. In the differential diagnosis of lipid-rich adenomas, lipid-poor adenomas and metastases, the CTVNC value and s-SHC value also had a larger AUC than the other spectral parameters, with a diagnostic sensitivity of 97.7%, 79.1% and specificity of 91.2%, 93.1%, respectively.ConclusionOn DLSCT, the combined spectral parameters in the venous phase could help better distinguish adrenal adenomas from metastases. The iodine-to-CTVNC, CTVNC and s-SHC values had the highest AUC values in differentiating adenomas, lipid-rich adenomas and lipid-poor adenomas from metastases, respectively.
| S-EPMC10423139 | biostudies-literature
Project description:ObjectiveTo construct and validate a prediction model based on dual-layer detector spectral CT (DLCT) and clinico-radiologic features to predict the microsatellite instability (MSI) status of gastric cancer (GC) and to explore the relationship between the prediction results and patient prognosis.MethodsA total of 264 GC patients who underwent preoperative DLCT examination were randomly allocated into the training set (n = 187) and validation set (n = 80). Clinico-radiologic features and DLCT parameters were used to build the clinical and DLCT model through multivariate logistic regression analysis. A combined DLCT parameter (CDLCT) was constructed to predict MSI. A combined prediction model was constructed using multivariate logistic regression analysis by integrating the significant clinico-radiologic features and CDLCT. The Kaplan-Meier survival analysis was used to explore the prognostic significant of the prediction results of the combined model.ResultsIn this study, there were 70 (26.52%) MSI-high (MSI-H) GC patients. Tumor location and CT_N staging were independent risk factors for MSI-H. In the validation set, the area under the curve (AUC) of the clinical model and DLCT model for predicting MSI status was 0.721 and 0.837, respectively. The combined model achieved a high prediction efficacy in the validation set, with AUC, sensitivity, and specificity of 0.879, 78.95%, and 75.4%, respectively. Survival analysis demonstrated that the combined model could stratify GC patients according to recurrence-free survival (p = 0.010).ConclusionThe combined model provides an efficient tool for predicting the MSI status of GC noninvasively and tumor recurrence risk stratification after surgery.Critical relevance statementMSI is an important molecular subtype in gastric cancer (GC). But MSI can only be evaluated using biopsy or postoperative tumor tissues. Our study developed a combined model based on DLCT which could effectively predict MSI preoperatively. Our result also showed that the combined model could stratify patients according to recurrence-free survival. It may be valuable for clinicians in choosing appropriate treatment strategies to avoid tumor recurrence and predicting clinical prognosis in GC.Key points• Tumor location and CT_N staging were independent predictors for MSI-H in GC. • Quantitative DLCT parameters showed potential in predicting MSI status in GC. • The combined model integrating clinico-radiologic features and CDLCT could improve the predictive performance. • The prediction results could stratify the risk of tumor recurrence after surgery.
| S-EPMC10509117 | biostudies-literature
Project description:ObjectivesTo evaluate the diagnostic accuracy of liver dual-layer spectral-detector CT (SDCT) derived parameters of liver parenchyma for grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF).MethodsAltogether, 320 consecutive subjects who underwent MRI-PDFF and liver SDCT examinations were recruited and prospectively enrolled from four Chinese hospital centers. Participants were classified into normal (n = 152), mild steatosis (n = 110), and moderate/severe(mod/sev) steatosis (n = 58) groups based on MRI-PDFF. SDCT liver parameters were evaluated using conventional polychromatic CT images (CTpoly), virtual mono-energetic images at 40 keV (CT40kev), the slope of the spectral attenuation curve (λ), the effective atomic number (Zeff), and liver to spleen attenuation ratio (L/S ratio). Linearity between SDCT liver parameters and MRI-PDFF was examined using Spearman correlation. Cutoff values for SDCT liver parameters in determining steatosis grades were identified using the area under the receiver-operating characteristic curve analyses.ResultsSDCT liver parameters demonstrated a strong correlation with PDFF, particularly Zeff (rs = -0.856; p < 0.001). Zeff achieved an area under the curve (AUC) of 0.930 for detecting the presence of steatosis with a sensitivity of 89.4%, a specificity of 82.4%, and an AUC of 0.983 for detecting mod/sev steatosis with a sensitivity of 93.1%, a specificity of 93.5%, the corresponding cutoff values were 7.12 and 6.94, respectively. Zeff also exhibited good diagnostic performance for liver steatosis grading in subgroups, independent of body mass index.ConclusionSDCT liver parameters, particularly Zeff, exhibit excellent diagnostic accuracy for grading steatosis.Critical relevance statementDual-layer SDCT parameter, Zeff, as a more convenient and accurate imaging biomarker may serve as an alternative indicator for MRI-based proton density fat fraction, exploring the stage and prognosis of liver steatosis, and even metabolic risk assessment.Key pointsLiver biopsy is the standard for grading liver steatosis, but is limited by its invasive nature. The diagnostic performance of liver steatosis using SDCT-Zeff outperforms conventional CT parameters. SDCT-Zeff accurately and noninvasively assessed the grade of liver steatosis.
| S-EPMC11327236 | biostudies-literature
Project description:PurposeThis study aimed to evaluate the differences between pericoronary adipose tissue (PCAT) attenuation at different measured locations in evaluating coronary atherosclerosis using spectral computed tomography (CT) and to explore valuable imaging indicators.MethodsA total of 330 patients with suspicious coronary atherosclerosis were enrolled and underwent coronary CT angiography with dual-layer spectral detector CT (SDCT). Proximal and peri-plaque fat attenuation index (FAI) of stenosis coronary arteries were measured using both conventional images (CIs) and virtual monoenergetic images (VMIs) ranging from 40 keV to 100 keV. The slopes of the spectral attenuation curve (λ) of proximal and peri-plaque PCAT at three different monoenergetic intervals were calculated. Additionally, peri-plaque FAI on CI and virtual non-contrast images, and effective atomic number were measured manually.ResultsA total of 231 coronary arteries with plaques and lumen stenosis were finally enrolled. Peri-plaque FAICI and FAIVMI were significantly higher in severe stenosis than in mild and moderate stenosis (p < 0.05), while peri-plaque λ, proximal FAI, and proximal λ were not statistically different. Proximal FAI, peri-plaque FAI, and peri-plaque λ were significantly higher in low-density non-calcified plaque (LD-NCP) and non-calcified plaque (NCP) than in calcified plaque (p < 0.01). Peri-plaque FAI was the highest in the LD-NCP group, while proximal FAI was the highest in the NCP group. In severe stenosis and in LD-NCP, peri-plaque FAI was significantly higher than proximal FAI (p < 0.05). The manually measured parameters related to peri-plaque PCAT attenuation had a positive correlation with the results of peri-plaque FAI measured automatically.ConclusionPeri-plaque PCAT has more value in assessing coronary atherosclerosis than proximal PCAT. Peri-plaque PCAT attenuation is expected to be used as a standard biomarker for evaluating plaque vulnerability and hemodynamic characteristics.
| S-EPMC10964482 | biostudies-literature
Project description:BackgroundThe accurate assessment of lymph node metastasis (LNM) is crucial for the staging, treatment, and prognosis of lung cancer. In this study, we explored the potential value of dual-layer spectral detector computed tomography (SDCT) quantitative parameters in the prediction of LNM in non-small cell lung cancer (NSCLC).MethodsIn total, 91 patients presenting with solid solitary pulmonary nodules (8 mm < diameter ≤30 mm) with pathologically confirmed NSCLC (57 without LNM, and 34 with LNM) were enrolled in the study. The patients' basic clinical data and the SDCT morphological features were analyzed using the chi-square test or Fisher's exact test. The Mann-Whitney U-test and independent sample t-test were used to analyze the differences in multiple SDCT quantitative parameters between the non-LNM and LNM groups. The diagnostic efficacy of the corresponding parameters in predicting LNM in NSCLC was evaluated by plotting the receiver operating characteristic (ROC) curves. A multivariate logistic regression analysis was conducted to determine the independent predictive factors of LNM in NSCLC. Interobserver agreement was assessed using intraclass correlation coefficients (ICCs) and Bland-Altman plots.ResultsThere were no significant differences between the non-LNM and LNM groups in terms of age, sex, and smoking history. Lesion size and vascular convergence sign differed significantly between the two groups (P<0.05), but there were no significant differences in the six tumor markers. The SDCT quantitative parameters [SAR40keV, SAR70keV, Δ40keV, Δ70keV, CER40keV, CER70keV, NEF40keV, NEF70keV, λ, normalized iodine concentration (NIC) and NZeff] were significantly higher in the non-LNM group than the LNM group (P<0.05). The ROC analysis showed that CER40keV, NIC, and CER70keV had higher diagnostic efficacy than other quantitative parameters in predicting LNM [areas under the curve (AUCs) =0.794, 0.791, and 0.783, respectively]. The multivariate logistic regression analysis showed that size, λ, and NIC were independent predictive factors of LNM. The combination of size, λ, and NIC had the highest diagnostic efficacy (AUC =0.892). The interobserver repeatability of the SDCT quantitative and derived quantitative parameters in the study was good (ICC: 0.801-0.935).ConclusionsThe SDCT quantitative parameters combined with the clinical data have potential value in predicting LNM in NSCLC. The size + λ + NIC combined parameter model could further improve the prediction efficacy of LNM.
| S-EPMC10784007 | biostudies-literature
Project description:ObjectivesTo assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC).MethodsA total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy.ResultsIntra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NICAP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NICVP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHUAP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHUVP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NICAP[0.20 (0.10) vs 0.13 (0.08)], NICVP[0.35 (0.07) vs 0.31 (0.11)], and λHUAP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NICAP, NICVP, λHUAP, and λHUVP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NICAP, NICVP, and λHUAP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05).ConclusionsThe quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.
| S-EPMC9564703 | biostudies-literature
Project description:PurposeThe purpose of this study was to investigate the clinical feasibility of spectral analyses using dual-layer detector spectral computed tomography (CT) in acute intracerebral haemorrhage (ICH).Material and methodsWe retrospectively reviewed patients with acute ICH who underwent CT angiography on a dual-layer detector spectral CT scanner. A spectral data analysis was performed to detect contrast enhancement in or adjacent to acute ICH by using spectral image reconstructions including monoenergetic (MonoE), virtual noncontrast (VNC), and iodine overlay fusion images. We also acquired a spectral plot to assess material differentiation within lesions.ResultsAmong the 30 patients, the most common cause of acute ICH was chronic hypertension (18/30, 60%) followed by trauma (5/30, 16.7%), brain tumour (3/30, 10%), Moyamoya disease (2/30, 6.7%), and haemorrhagic diathesis from anticoagulation therapy (2/30, 6.7%). Of 30 patients, 13 showed suboptimal iodine suppression in the subcalvarial spaces on VNC images compared with true noncontrast images. The CT angiographic spot sign within the acute ICH was detected in four patients (4/30, 13.3%). All three tumours were metastatic and included lung cancer (n = 2) and hepatocellular carcinoma (n = 1) which showed conspicuous delineation of an enhancing tumour portion in the spectral analysis. Spectral analyses allowed the discrimination of acute haemorrhage and iodine with enhanced lesion visualization on the MonoE images obtained at lower keVs (less than 70 keV) and spectral plot.ConclusionsEven though the image quality of VNC is perceived to be inferior, it is feasible to evaluate acute ICH in clinical settings using dual-layer detector spectral CT. The MonoE images taken at lower keVs were useful for depicting contrast enhancing lesion, and spectral plot might be helpful for material differentiation in patients with acute ICH.
| S-EPMC5675383 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is commonly assessed by computed tomography (CT), but the associated radiation exposure is a major concern. This study aimed to quantitatively and qualitatively compare the image quality of virtual non-contrast (VNC) images reconstructed from arterial and portal venous phases with that of true non-contrast (TNC) images in patients with CRC to assess the potential of TNC images to replace VNC images, thereby reducing the radiation dose.MethodsA total of 69 patients with postoperative pathologically confirmed CRC at the West China Hospital of Sichuan University between May 2022 and April 2023 were enrolled in this cross-sectional study. The CT protocol included the acquisition of TNC images, arterial and portal venous phase images; the VNC images were reconstructed from the two postcontrast phase images. Several parameters, including the CT attenuation value, absolute attenuation error, imaging noise [standard deviation (SD)], signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR), were measured in multiple abdominal structures for both the TNC and VNC images. Two blinded readers assessed the subjective image quality using a five-point scale. Interobserver agreement was evaluated using interclass correlation coefficients (ICCs). The paired t-test and Wilcoxon signed-rank test were used to compare the objective and subjective results between the TNC and VNC images. Individual measurements of radiation doses for the TNC scan and contrast scan protocols were recorded.ResultsA total of 2,070 regions of interest (ROIs) of the 69 patients were analyzed. Overall, the VNC images exhibited significantly lower attenuation values and SD values than the TNC images in all tissues, except for the abdominal aorta, portal vein, and spleen. The mean absolute attenuation errors between the VNC and TNC images were all less than 10 Hounsfield units (HU). The percentages of absolute attenuation errors less than 5 and 10 HU in the VNC images from the arterial phase (VNCa) were 78.99% and 97.97%, respectively, while those from the portal venous phase (VNCp) were 81.59% and 96.96%, respectively. The absolute attenuation errors between the TNC and VNCa images were smaller than those between the TNC and VNCp images for tumors [VNCaerror: 2.77, interquartile range (IQR) 1.77-4.22; VNCperror: 3.27, IQR 2.68-4.30; P=0.002]. The SNR values and CNR values in the VNC images were significantly higher than those in the TNC images for all tissues, except for the portal vein and spleen. The image quality was rated as excellent (represented by a score of 5) in the majority of the TNC and VNC images; however, the VNC images scored lower than the TNC images. Eliminating the TNC phase resulted in a reduction of approximately 37.99% in the effective dose (ED).ConclusionsThe VNC images provided accurate CT attenuation, good image quality, and lower radiation doses than the TNC images in CRC, and the VNCa images showed minimal differences in the CT attenuation of the tumors.
| S-EPMC11400675 | biostudies-literature
Project description:BackgroundExtracellular volume (ECV) fraction has been used in cardiovascular diseases, pancreatic fibrosis, and hepatic fibrosis. The diagnostic value of ECV for focal lung lesions remains to be explored. The aim of this study was to evaluate the feasibility of ECV derived from a dual-layer detector computed tomography (DLCT) to differentiate lung cancer (LC) from benign lung lesions (BLLs).MethodsRetrospectively, 128 consecutive patients with pathologically confirmed LC (n=86) or BLLs (n=42) were included. Conventional computed tomography (CT) characteristics and spectral CT parameters were assessed. All patients' hematocrits were measured to correct contrast volume distributions in blood while calculating ECV. After performing logistic regression analysis, a conventional CT-based model (Model A), DLCT-based model (Model B), combined diagnostic models (Model C), and an ECV-based model (Model D) were developed. The diagnostic effectiveness of each model was examined using the receiver operating characteristic (ROC) curve and their corresponding 95% confidence intervals (CIs). The area under the curve (AUC) of each model was compared using the DeLong test.ResultsCertain conventional CT features (such as lesion size, lobulation, spiculation, pleural indentation, and enlarged lymph nodes) differed significantly between the LC and BLL groups (all P<0.05). Statistical differences were found in the following DLCT parameters (all P<0.05): effective atomic number (Zeff) (non-enhancement), electron density (ED) (non-enhancement), ECV, iodine concentration (IC), and normalized iodine concentration (NIC). Models A, B, C, and D had AUCs of 0.801 [95% confidence interval (CI): 0.721-0.866], 0.805 (95% CI: 0.726-0.870), 0.925 (95% CI: 0.865-0.964), and 0.754 (95% CI: 0.671-0.826), respectively. The AUC of Model D (ECV) showed no significant difference from that of Models A and B (DeLong test, P>0.05).ConclusionsThe ECV derived from DLCT may be a potential new method to differentiate LC from BLLs, broadening the scope of ECV in clinical research.
| S-EPMC10722081 | biostudies-literature