Quantitative parameters in novel spectral computed tomography: Assessment of Ki-67 expression in patients with gastric adenocarcinoma

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating differentiation grade and lymphovascular and perineural invasion in colorectal adenocarcinoma

PURPOSE

To explore the predictive value of dual-layer spectral detector CT (SDCT) quantitative parameters for determining differentiation grade, lymphovascular invasion (LVI) and perineural invasion (PNI) in colorectal adenocarcinoma (CRAC) patients.

METHODS

A total of 106 eligible patients with CRAC were included in this study. Spectral parameters, including CT values at 40 and 100 keV, the effective atomic number (Zeff), the iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and the normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP), were compared according to the differentiation grade and the status of LVI and PNI. The diagnostic accuracies of the quantitative parameters with statistical significance were determined via receiver operating characteristic (ROC) curves, and the area under the curve (AUC) was calculated.

RESULTS

There were 57 males and 49 females aged 43-86 (69 ± 10) years. The measured values of the spectral quantitative parameters of the CRAC were consistent within the observer (ICC range: 0.800-0.926). The 40 keV-AP, IC-AP, NIC-AP, 40 keV-VP, and IC-VP were significantly different among the different differentiation grades in the CRAC (P = 0.040, AUC = 0.673; P = 0.035, AUC = 0.684; P = 0.031, AUC = 0.639; P = 0.044, AUC = 0.663 and P = 0.035, AUC = 0.666, respectively). A statistically significant difference was observed in 40 keV-VP, 100 keV-VP, Zeff-VP, IC-VP, and λHU-VP between LVI-positive and LVI-negative patients (P = 0.003, AUC = 0.688; P = 0.015, AUC = 0.644; P = 0.001, AUC = 0.688; P = 0.001, AUC = 0.703 and P = 0.003, AUC = 0.677, respectively). There were no statistically significant differences in the values of the spectral parameters of the PNI state of patients with CRAC (P > 0.05).

CONCLUSION

The quantitative parameters of SDCT had good diagnostic efficacy in differentiating between different grades and statuses of LVI in patients with CRAC; however, SDCT did not have value for identifying the state of PNI.

A nomogram model of spectral CT quantitative parameters and clinical characteristics predicting lymphovascular invasion of gastric cancer

Objective

The study established a nomogram based on quantitative parameters of spectral computed tomography (CT) and clinical characteristics, aiming to evaluate its predictive value for preoperative lymphovascular invasion (LVI) in gastric cancer (GC).

Methods

From December 2019 to December 2021, 171 patients with pathologically confirmed GC were retrospectively collected with corresponding clinical data and spectral CT quantitative data. Patients were divided into LVI-positive and LVI-negative groups based on their pathological results. The univariate and multivariate logistic regression analyses were used to identify the risk factors and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were adopted to evaluate the predictive accuracy of nomogram.

Results

Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification (P = 0.039), CA724 (P = 0.007), tumor thickness (P = 0.031), and iodine concentration in the venous phase (VIC) (P = 0.004) were identified as independent factors for LVI in GC patients. The nomogram was established based on the four factors, which had a potent predictive accuracy in the training, internal validation and external validation cohorts, with the area under the ROC curve (AUC) of 0.864 (95% CI, 0.798-0.930), 0.964 (95% CI, 0.903-1.000) and 0.877 (95% CI, 0.759-0.996), respectively.

Conclusion

This study constructed a comprehensive nomogram consisting spectral CT quantitative parameters and clinical characteristics of GC, which exhibited a robust efficiency in predicting LVI in GC patients.

Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters

OBJECTIVE

To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve.

RESULTS

Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency.

CONCLUSIONS

The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients.

CRITICAL RELEVANCE STATEMENT

The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression.

KEY POINTS

• Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.

Performance of dual-layer spectrum CT virtual monoenergetic images to assess early rectal adenocarcinoma T-stage: comparison with MR

OBJECTIVES

To 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).

METHODS

This 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.

RESULTS

The 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).

CONCLUSIONS

VMI 40 keV improves image quality and accuracy in identifying lesions, providing better diagnostic information for ERA staging.

CRITICAL RELEVANCE STATEMENT

Low-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.

Evaluation of microcirculation in asymptomatic cerebral infarction with multi-parameter imaging of spectral CT

OBJECTIVE

To investigate the role of spectral CT multiparametric imaging in the evaluation of cerebral microcirculatory perfusion.

METHODS

The imaging data of 145 patients with asymptomatic cerebral infarction confirmed by MR were retrospectively analyzed, and all cases underwent head CTA and cranial CT perfusion imaging (CTP) on double-layer detector spectral CT. Single energy level images (MonoE45 keV), iodine density maps, and effective atomic number maps were reconstructed based on spectral CTA data, and CT values, iodine density values, and effective atomic number values were measured in the infarcted area, healthy control area, centrum semiovale and posterior limb of the internal capsule, respectively; perfusion values, such as cerebral blood volume (CBV) values, cerebral blood flow (CBF) values, time to peak (TTP) values, and mean passage time, were measured in the above-mentioned areas on CTP images. (TTP) values, and mean time to passage (MTT) values. CT values, iodine density values, effective atomic number values, and perfused CBV, CBF, TTP, and MTT values were compared between the infarcted area and the healthy side, the center of the hemianopia, and the posterior limb of the internal capsule. The role of spectral CT parameters and perfusion parameters in the evaluation of asymptomatic cerebral infarction was analyzed.

RESULTS

CT values, iodine density values, and effective atomic number values were statistically different between the infarcted area and the healthy side; CT values, iodine density values, and effective atomic number values were not statistically different between the infarcted side and the healthy side of the hemispheric centrum and the posterior limb of the internal capsule; CBV and CBF were statistically different between the infarcted side and the healthy side, and MTT and TTP were not statistically different. There were statistically significant differences in TTP between the infarcted area and the healthy side of the hemiaxial center, and no statistically significant differences in CBV, CBF, and MTT. There were no statistical differences in CBV, CBF, TTP, and MTT in the inner capsule area. ROC curve analysis of spectral CT-related parameters and CT perfusion parameters for the diagnosis of asymptomatic cerebral infarction: area under the curve of MonoE 45Kv 0.71, area under the curve of iodine density values 0.76, area under the curve of effective atomic number values 0.74; area under the curve of CBV value 0.64, area under the curve of CBF value 0.61, area under the curve of MTT value 0.50, The area under the TTP curve was 0.52. The area under the ROC curve of the multivariate logistic regression model based on spectral parameters is 0.76, which is higher than that of the logistic regression model with perfusion parameters (P < 0.05).

CONCLUSION

Spectral CT can better demonstrate small intracranial ischemic lesions, and iodine density values have a better evaluation of microcirculation in asymptomatic cerebral infarcts.

Quantitative parameters in novel spectral computed tomography for assessing gastric cancer and cell proliferation

OBJECTIVES

To investigate the diagnostic ability of novel spectral CT-derived parameters for gastric cancer histological types and Ki-67 expression.

METHODS

A total of 72 patients with histologically proven gastric cancer (GC) were retrospectively included in this study. All patients underwent dual-phase enhanced abdominal spectral CT. The arterial (AP) and venous phase (VP) slope of the spectral curve (λHU), iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff) and iodine-no-water concentration were retrospectively compared between patients with low and high Ki-67 expression levels and with different histological types in GC patients. The ROI was outlined independently by two senior physicians, and the average of three measurements at the largest level was taken. In addition, interobserver reproducibility was assessed by Bland-Altman analysis. Correlations between quantitative parameters and Ki-67 expression levels were assessed by Spearman's correlation coefficients.

RESULTS

The values between the mucinous group and nonmucinous carcinoma group were significantly different in both phases. The IC, NIC, and iodine-no-water concentration in the VP were significantly different among the Ki-67_L, Ki-67_M, and Ki-67_H groups. Spearman rank correlation analysis demonstrated a positive correlation between Ki-67 expression levels and IC, NIC, and iodine-no-water concentration in the VP, with correlation coefficients of 0.304, 0.424, and 0.322, respectively.

CONCLUSION

Quantitative spectral parameters can discriminate between low and high Ki-67 expression and different histological types in GC. The NIC, IC and iodine-no-water concentration can be useful parameters for evaluating of Ki-67 expression levels.