Normalized Iodine Concentration Research Articles

Combination of clinical and spectral-CT iodine concentration for predicting liver metastasis in gastric cancer: a preliminary study.

This study aimed to determine the diagnostic efficacy of various indicators and models for the prediction of gastric cancer with liver metastasis. Clinical and spectral computed tomography (CT) data from 80 patients with gastric adenocarcinoma who underwent surgical resection were retrospectively analyzed. Patients were divided into metastatic and non-metastatic groups based on whether or not to occur liver metastasis, and the region of interest (ROI) was measured manually on each phase iodine map at the largest level of the tumor. Iodine concentration (IC), normalized iodine concentration (nIC), and clinical data of the primary gastric lesions were analyzed. Logistic regression analysis was used to construct the clinical indicator (CI) and clinical indicator-spectral CT iodine concentration (CI-Spectral CT-IC) Models, which contained all of the parameters with statistically significant differences between the groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the accuracy of the models. The metastatic group showed significantly higher levels of Cancer antigen125 (CA125), carcinoembryonic antigen (CEA), IC, and nIC in the arterial phase, venous phase, and delayed phase than the non-metastatic group (all p < 0.05). Normalized iodine concentration Venous Phase (nICVP) exhibited a favorable performance among all IC and nIC parameters for forecasting gastric cancer with liver metastasis (area under the curve (AUC), 0.846). The combination model of clinical data with significant differences and nICVP showed the best diagnostic accuracy for predicting liver metastasis from gastric cancer, with an AUC of 0.897. nICVP showed the best diagnostic efficacy for predicting gastric cancer with liver metastasis. Clinical Indicators-normalized ICVP model can improve the prediction accuracy for this condition.

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small cell lung cancer

PurposeTo explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small cell lung cancer (NSCLC). Materials and MethodsThis retrospective observational study included patients with intermediate or advanced NSCLC at the XXX Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups. ResultsSeventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity). ConclusionsThe pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

Predicting epidermal growth factor receptor mutations in non-small cell lung cancer through dual-layer spectral CT: a prospective study

ObjectiveTo determine whether quantitative parameters of detector-derived dual-layer spectral computed tomography (DLCT) can reliably identify epidermal growth factor receptor (EGFR) mutation status in patients with non-small cell lung cancer (NSCLC).MethodsPatients with NSCLC who underwent arterial phase (AP) and venous phase (VP) DLCT between December 2021 and November 2022 were subdivided into the mutated and wild-type EGFR groups following EGFR mutation testing. Their baseline clinical data, conventional CT images, and spectral images were obtained. Iodine concentration (IC), iodine no water (INW), effective atomic number (Zeff), virtual monoenergetic images, the slope of the spectral attenuation curve (λHU), enhancement degree (ED), arterial enhancement fraction (AEF), and normalized AEF (NAEF) were measured for each lesion.ResultsNinety-two patients (median age, 61 years, interquartile range [51, 67]; 33 men) were evaluated. The univariate analysis indicated that IC, normalized IC (NIC), INW and ED for the AP and VP, as well as Zeff and λHU for the VP were significantly associated with EGFR mutation status (all p < 0.05). INW(VP) showed the best diagnostic performance (AUC, 0.892 [95% confidence interval {CI}: 0.823, 0.960]). However, neither AEF (p = 0.156) nor NAEF (p = 0.567) showed significant differences between the two groups. The multivariate analysis showed that INW(AP) and NIC(VP) were significant predictors of EGFR mutation status, with the latter showing better performance (p = 0.029; AUC, 0.897 [95% CI: 0.816, 0.951] vs. 0.774 [95% CI: 0.675, 0.855]).ConclusionQuantitative parameters of DLCT can help predict EGFR mutation status in patients with NSCLC.Critical relevance statementQuantitative parameters of DLCT, especially NIC(VP), can help predict EGFR mutation status in patients with NSCLC, facilitating appropriate and individualized treatment for them.Key PointsDetermining EGFR mutation status in patients with NSCLC before starting therapy is essential.Quantitative parameters of DLCT can predict EGFR mutation status in NSCLC patients.NIC in venous phase is an important parameter to guide individualized treatment selection for NSCLC patients.Graphical

Dual-energy CT quantitative parameters to evaluate occult peritoneal metastasis in advanced gastric cancer preoperatively.

To explore whether dual-energy CT (DECT) quantitative parameters could provide analytic value for the diagnosis of patients with occult peritoneal metastasis (OPM) in advanced gastric cancer preoperatively. This retrospective study included 219 patients with advanced gastric cancer and DECT scans. The patient's clinical data and DECT related iodine concentration (IC) parameters and effective atomic number (Zeff) were collated and analyzed among noun-peritoneal metastasis (NPM), OPM and radiologically peritoneal metastasis (RPM) groups. The predictive performance of the DECT parameters was compared with that of the conventional CT features and clinical characteristics through evaluating area under curve of the precision-recall (AUC-PR), F1 score, balanced accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Borrmann IV type diagnosed on CT and serum tumor indicator CA125 index were statistically different between the NPM and OPM groups. DECT parameters included IC, normalized IC (NIC), and Zeff of PM group were lower than the NPM group. The DECT predictive nomogram combined three independent DECT parameters produced a better diagnostic performance than the conventional CT feature Borrmann IV type and serum CA125 index in AUC-PR with 0.884 vs 0.368 vs 0.189, but similar to the combined indicator which was based on the DECT parameters, the conventional CT feature, and serum CA125 index in AUC-PR with 0.884 vs 0.918. The lower quantitative NIC, IC ratio, and Zeff on DECT was associated with peritoneal metastasis in advanced gastric cancer and was promising to identify patients with OPM noninvasively.

Prediction of pathological activity in Crohn's disease based on dual-energy CT enterography.

To explore the feasibility of predicting the pathological activity of Crohn's disease (CD) based on dual-energy CT enterography (DECTE). The clinical, endoscopic, imaging and pathological data of 55 patients with CD scanned by DECTE were retrospectively analyzed; the pathological results were used as a reference standard to classify the diseased bowel segments into active and inactive phases. The normalized iodine concentration (NIC), energy-spectrum curve slope K, dual energy index (DEI), fat fraction (FF) of the arterial phases and venous phases were compared. To assess the parameters' predictive ability, receiver-operating characteristic curves were used. The Delong test was used to compare the differences between the diagnostic efficiency of each parameter. A total of 84 intestinal segments were included in the study, including 54 active intestinal segments and 30 inactive intestinal segments. The NIC, energy-spectrum curve slope K and DEI were significantly different between active and inactive bowel segments in the arterial and venous phases (P < 0.05), while FF were not significantly different (P > 0.05). The largest area under the curve (AUC) of NIC, energy-spectrum curve slope K and DEI were higher in arterial phase than in venous phase. For identifying the intestinal activity of CD, the maximum AUC of NIC in arterial phase was 0.908, with a sensitivity of 0.833 and a specificity of 0.800, and the DEI in arterial phase had the highest sensitivity (0.944). The NIC, energy-spectrum curve slope K and DEI can effectively distinguish the active and inactive phases of the intestinal segments of CD patients and provide good assistance for determining further treatment.

Preliminary Experience with Virtual Monoenergetic Imaging and Iodine Mapping in the Primary Staging of Endometrial Cancer.

This study investigated whether virtual monoenergetic images (VMIs) and iodine mapping based on dual-energy CT (DECT) provide advantages in the assessment of endometrial cancer. A dual-source DECT was performed for primary staging of histologically proven endometrioid adenocarcinoma in 21 women (66.8 ± 12.0 years). In addition to iodine maps, VMIs at 40, 50, 60, 70, and 80 keV were reconstructed from polyenergetic images (PEIs). Objective analysis comprised the measurement of tumor contrast, contrast-to-noise ratio, and normalized iodine concentration (NIC). In addition, three radiologists independently rated tumor conspicuity. The highest tumor contrast (106.6 ± 45.0 HU) and contrast-to-noise ratio (4.4 ± 2.0) was established for VMIs at 40 keV. Tumor contrast in all VMIs ≤ 60 keV was higher than in PEIs (p < 0.001). The NIC of malignant tissue measured in iodine maps was substantially lower compared with a healthy myometrium (0.3 ± 0.1 versus 0.6 ± 0.1 mg/mL; p < 0.001). Tumor conspicuity was highest in 40 keV datasets, whereas no difference was found among PEIs and VMIs at 60 and 70 keV (p ≥ 0.334). Interobserver agreement was good, indicated by an intraclass correlation coefficient of 0.824 (0.772-0.876; p < 0.001). In conclusion, computation of VMIs at 40 keV and color-coded iodine maps aids the assessment of endometroid adenocarcinoma in primary staging.

The Relationship between Quantitative Parameters of Dual-energy CT and HIF-1α Expression in Non-Small Cell Lung Cancer.

This study aimed to investigate whether there is a correlation between quantitative parameters of dual-energy computed tomography (DECT) and the relative expression of HIF-1&#945; in patients with non-small cell lung cancer (NSCLC) to preliminarily explore the value of DECT in evaluating the hypoxia of tumor microenvironment and tumor biological behavior and provide more information for the treatment of NSCLC. This retrospective research included 36 patients with pathologically confirmed NSCLC who underwent dual-energy enhanced CT scans. The quantitative parameters of DECT were analyzed, including iodine concentration, water concentration, the CT values corresponding to 40keV, 70keV, 100keV, and 130keV in arterial and venous phases, and the normalized iodine concentration and the slope of the energy spectrum curve were calculated. Postoperative specimens underwent HIF immunohistochemical staining by two pathologists. Spearman correlation analysis was adopted as the statistical methodology. The data were analyzed by SPSS26.0 statistical software. Water concentration (r=0.659, P&#60;0.001 and r= 0.632, P&#60;0.001, the CT values corresponding to 100keV (r=0.645, P&#60;0.001 and r= 0.566, P&#60;0.001) and 130keV (r=0.687, P&#60;0.001 and r= 0.682, P&#60;0.001) in arterial and venous phases, and CT value of 70keV in arterial phase (r=0.457, P=0.005) were positively correlated with HIF-1&#945; expression level. There was no correlation among iodine concentration, standardized iodine concentration, CT value of 40keV, λHU, and HIF-1&#945; expression in arterial and venous levels (P >0.05). The quantitative parameters of DECT have a certain correlation with HIF-1&#945; expression in NSCLC. Moreover, it has been demonstrated that DECT can be used to predict hypoxia in tumor tissues and the prognosis of lung cancer patients.

Non-electrocardiography-gated dual-energy cardiac CT angiography for assessment of left atrial appendage thrombus

ObjectiveTo explore the diagnosis value of a low dose, dual-energy cardiac computed tomography angiography (CTA) with non-electrocardiography-gated (non-ECG-gated) in detecting left atrial appendage thrombus. MethodsConsecutive patients with atrial fibrillation who underwent cardiac CTA protocol (dual-energy scan for arterial phase and conventional scan for delayed phase) were prospectively enrolled. LAA lesions were proved by clinical comprehensive diagnosis, the final study included 18 cases with LAA thrombus and 48 cases with circulatory stasis. Quantitative parameters derived from dual-energy images were measured for the LAA lesions, including the conventional CT attenuation value (CT value), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number values (Zeff) and energy spectrum curve slope (Slope). The differences between LAA thrombus group and circulatory stasis group were compared by independent t-test or Wilcoxon rank sum test regarding to the normality test. The diagnosis performance of the dual-energy parameters was assessed using receiver operating characteristic (ROC) curve analysis and area under curve (AUC). ResultsAll the dual-energy parameters were demonstrated significantly difference between LAA thrombus and circulatory stasis group (P＜0.05), and showed better diagnostic performance than the conventional CT value. ROC analysis revealed IC was the most predictive parameter with AUC equal to 0.836. The radiation dose in the arterial phase was (2.64 ​± ​0.66) mSv. ConclusionDual-energy CTA scanning shows convincing diagnostic performance in detecting left atrial appendage thrombus with lower radiation dose, and may help reduce the need for delayed phase scan.

Dual-energy computed tomography in the early evaluation of acute radiation pneumonia

ObjectiveTo investigate the value of dual-energy dual-source computed tomography (DSCT) in evaluating pulmonary perfusion changes before and after radiotherapy for esophageal cancer, and its clinical use in the early diagnosis of acute radiation pneumonia (ARP).MethodsWe selected 45 patients with pathologically confirmed esophageal cancer who received radiotherapy (total irradiation dose of 60 Gy). Dual-energy DSCT scans were performed before and after radiotherapy and the normalized iodine concentrations (NIC) in the lung fields of the areas irradiated with doses of > 20 Gy, 10–20 Gy, 5–10 Gy, and < 5 Gy were measured. We also checked for the occurrence of ARP in the patients, and the differences in NIC values and NIC reduction rates before and after radiotherapy were calculated and statistically analyzed.ResultsA total of 16 of the 45 patients developed ARP. The NIC values in the lung fields of all patients decreased at different degrees after radiotherapy, and the NIC values in the area where ARP developed, decreased significantly. The rate of NIC reduction and incidence rate of ARP increased gradually with the increasing irradiation dose, and the inter-group difference in NIC reduction rate was statistically significant (P < 0.05). Based on the receiver operating characteristic (ROC) curve analysis, the areas under the curves of NIC reduction rate versus ARP occurrence in the V5-10 Gy, V10-20 Gy, and V> 20 Gy groups were 0.780, 0.808, and 0.772, respectively. Sensitivity of diagnosis was 81.3%, 75.0%, and 68.8% and the specificity was 65.5%, 82.8%, and 79.3%, when taking 12.50%, 16.50%, and 26.0% as the diagnostic thresholds, respectively. The difference in NIC values in the lung fields of V<5 Gy before and after radiotherapy was not statistically significant (P > 0.05).ConclusionThe dual-energy DSCT could effectively evaluate pulmonary perfusion changes after radiotherapy for esophageal cancer, and the NIC reduction rate was useful as a reference index to predict ARP and provide further reference for decisions in clinical practice.

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

ObjectiveTo 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 methodsData 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.ResultsComputed 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.ConclusionsThe 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 statementThe 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.Graphical

Spectral CT vs. diffusion-weighted imaging for the quantitative prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer.

To compare the performance of spectral CT and diffusion-weighted imaging (DWI) for predicting pathologic response after neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC). This was a retrospective analysis drawn from a prospective dataset. Sixty-five patients who underwent baseline concurrent triple-phase enhanced spectral CT and DWI-MRI and standard NAC plus radical gastrectomy were enrolled, and those with poor images were excluded. The tumor regression grade (TRG) was the reference standard, and patients were classified as responders (TRG 0 + 1) or non-responders (TRG 2 + 3). Quantitative iodine concentration (IC), normalized IC (nIC), and apparent diffusion coefficient (ADC) were measured by placing a freehand region of interest manually on the maximal two-dimensional plane. Their differences between responders and non-responders were compared. The performances of significant parameters were evaluated by the receiver operating characteristic analysis. The correlations between parameters and TRG status were explored through Spearman correlation coefficient test. Kaplan-Meier survival analysis was adopted to analyze their relationship with patient survival. nICDP and ADC were associated with the TRG and yielded comparable performances for predicting TRG categories, with area under the curve (AUC) of 0.674 and 0.673, respectively. Their combination achieved a significantly increased AUC of 0.770 (p ; 0.05) and was associated with patient disease-free survival, with hazard ratio of 2.508 (1.043-6.029). Spectral CT and DWI were equally useful imaging techniques for predicting pathologic response to NAC in LAGC. The combination of nICDP and ADC gained significant incremental benefits and was related to patient disease-free survival. Spectral CT and DWI-based quantitative measurements are effective markers for predicting the pathologic regression outcomes of locally advanced gastric cancer patients after neoadjuvant chemotherapy. • The pathologic tumor regression grade, the standard criteria for treatment response after neoadjuvant chemotherapy in gastric cancer patients, is difficult to predict early. • The quantitative parameters of normalized iodine concentration at delay phase and apparent diffusion coefficients were correlated with pathologic response; their combination demonstrated incremental benefits and was associated with patient disease-free survival. • Spectral CT and DWI are equally useful imaging modalities for predicting tumor regression grade after neoadjuvant chemotherapy in patients with locally advanced gastric cancer.

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients.

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques.

To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to testdifferent normalization approaches. Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration. Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001). We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution.Afternormalization, the scanner type stillhad a significant effect on iodine variability in the pancreas and liver. Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging. • Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Value of dual-layer spectral detector CT in predicting lymph node metastasis of non-small cell lung cancer.

The 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). In 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. There 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). The 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.

Baseline parameters of spectral CT could predict tumor response to transcatheter arterial chemoembolization in hepatocellular carcinoma patients

ObjectiveThe present study aimed to assess the diagnostic efficacy of baseline spectral computed tomography (CT) parameters in predicting tumor response to transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC). MethodsData were collected from 91 consecutive patients with HCC between June 2020 and July 2023. An independent samples t-test was performed to compare the demographic and spectral CT variables between the groups. Predictors were screened using binary logistic regression, and the diagnostic efficacy of the baseline parameters for predicting the response to TACE in patients with HCC was analyzed using receiver operating characteristic (ROC) curves. ResultsA total of 91 patients with HCC were included in the present study, categorized into response (n ​= ​52; men, 48 (92.3 ​%); age, 58.72 ​± ​11.16 years) and non-response (n ​= ​39; men, 36 (92.31 ​%); age, 59.50 ​± ​10.10 years) groups based on the evaluation criteria. There was a statistically significant difference in both iodine concentration (IC) and normalized IC (NIC) between the two groups (P ​< ​0.05), and we found that the mean values of the three IC and NIC phases in the non-response group were significantly lower than those in the response group. The arterial, portal, and delayed phase ICs and NICs had significant positive effects on the response to TACE in patients with HCC (P ​< ​0.05). Baseline spectral CT parameters, including IC and NIC, had satisfactory diagnostic efficacy for predicting tumor response to TACE (area under the curve [AUC] of baseline spectral parameters ranged from 0.698 to 0.879). The results of the DeLong test indicated no statistical differences between the AUC of all the parameters and models. ConclusionThe present study found that the baseline spectral CT parameters could be surrogate imaging markers for predicting tumor response to TACE.

Mono+ algorithm assessment of the diagnostic value of dual-energy CT for high-risk factors for colorectal cancer: a preliminary study.

Risk factors for colorectal cancer (CRC) affect the way patients are subsequently treated and their prognosis. Dual-energy computerized tomography (DECT) is an advanced imaging technique that enables the quantitative evaluation of lesions. This study aimed to evaluate the quality of DECT images based on the Mono+ algorithm in CRC, and based on this, to assess the value of DECT in the diagnosis of CRC risk factors. This prospective study was performed from 2021 to 2023. A dual-phase DECT protocol was established for consecutive patients with primary CRC. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall image quality, lesion delineation, and image noise of the dual-phase DECT images were assessed. Next, the optimal energy-level image was selected to analyze the iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, electron density, dual-energy index (DEI), and slope of the energy spectrum curve within the tumor for the high- and low-risk CRC groups. A multifactor binary logistic regression analysis was used to construct a differential diagnostic regression model for high- and low-risk CRC, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the diagnostic value of the model. A total of 74 patients were enrolled in this study, of whom 41 had high-risk factors and 33 had low-risk factors. The SNR and CNR were best at 40 keV virtual monoenergetic imaging (VMI) based on the Mono+ algorithm (VMI+) (SNR 8.79±1.27, P<0.001; CNR 14.89±1.77, P=0.027). The overall image quality and lesion contours were best at 60 keV VMI+ and 40 keV VMI+, respectively (P=0.001). Among all the DECT parameters, the arterial phase (AP)-IC, NIC, DEI, energy spectrum curve, and venous phase-NIC differed significantly between the two groups. The AP-IC was the optimal DECT parameter for predicting high- and low-risk CRC with AUC, sensitivity, specificity, and cut-off values of 0.96, 97.06%, 87.80%, and 2.94, respectively, and the 95% confidence interval (CI) of the AUC was 0.88-0.99. Integrating the clinical factors and DECT parameters, the AUC, sensitivity, specificity, and predictive accuracy of the model were 0.99, 100.00%, 92.68%, and 94.67%, respectively, and the 95% CI of the AUC was 0.93-1.00. The DECT parameters based on 40 keV noise-optimized VMI+ reconstruction images depicted the CRC tumors best, and the clinical DECT model may have significant implications for the preoperative prediction of high-risk factors in CRC patients.

Preliminary exploration of the correlation between spectral computed tomography quantitative parameters and spread through air spaces in lung adenocarcinoma.

The invasive pattern called spread through air spaces (STAS) is linked to an unfavorable prognosis in patients with lung adenocarcinoma (LUAD). Using computed tomography (CT) signs alone to assess STAS is subjective and lacks quantitative evaluation, whereas spectral CT can provide quantitative analysis of tumors. The aim of this study was to investigate the association between spectral CT quantitative parameters and STAS in LUAD. We retrospectively collected consecutive patients with LUAD who underwent surgical resection and preoperative spectral CT scan at our institution. The quantitative parameters included CT values at 40, 70, and 100 keV [CT40keVa/v, CT70keVa/v, and CT100keVa/v (a: arterial; v: venous)]; iodine concentration (ICa/ICv); normalized iodine concentration (NICa/NICv); and slope λHU of the spectral curve (λHUa/λHUv). Clinical and CT features of the patients were also collected. Statistical analysis was performed to identify the quantitative parameters, clinical and CT features that were significantly correlated with STAS status. We evaluated the diagnostic performance of significant factors or models which combined quantitative parameters and CT features, using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. We enrolled a total of 47 patients, with 32 positive and 15 negative for STAS. The results revealed that CT100keVa (P=0.002), CT100keVv (P=0.007), pathologic stage (P=0.040), tumor density (P<0.001), spiculation (P=0.003), maximum solid component diameter (P=0.008), and the consolidation/tumor ratio (CTR) (P=0.001) were significantly correlated with STAS status. The tumor density demonstrated a superior diagnostic capability [AUC =0.824, 95% confidence interval (CI): 0.709-0.939, sensitivity =59.4%, specificity =100.0%] compared to other variables. CT100keVa exhibited the best diagnostic performance (AUC =0.779, 95% CI: 0.633-0.925, sensitivity =78.1%, specificity =80.0%) among the quantitative parameters. Combination models were then constructed by combining the quantitative parameters with CT features. The total combined model showed the highest diagnostic efficiency (AUC =0.952, 95% CI: 0.894-1.000, sensitivity =90.6%, specificity =86.7%). Spectral CT quantitative parameters CT100keVa and CT100keVv may be potentially useful parameters in distinguishing the STAS status in LUAD.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating Ki-67 and human epidermal growth factor receptor 2 expression in colorectal adenocarcinoma.

Ki-67 and human epidermal growth factor receptor 2 (HER2) are key biomarkers in evaluating the prognosis of colorectal adenocarcinoma (CRAC). The purpose of this study was to investigate the value of quantitative parameters in dual-layer spectral detector computed tomography (SDCT) for evaluating the expression of Ki-67 and HER2 in CRAC. In this retrospective, cross-sectional study, 88 eligible patients with pathologically confirmed CRAC were selected from Taicang Hospital of Traditional Chinese Medicine between May 2021 and April 2023. The study participants underwent enhanced SDCT of the whole abdomen within 2 weeks before to surgery, did not receive antitumor therapy, and had complete immunohistochemical (IHC) indexes. Patients with nonadenocarcinoma pathologic types, poor quality of spectral CT images, or no complete immunohistochemistry results were excluded. Spectral parameters including CT values at 40 and 100 keV, effective atomic number, iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP) were analyzed for their value in distinguishing between the high and low expression of Ki-67 and HER2-positive and -negative status in CRAC. The statistical significance of the SDCT parameters between the different groups of Ki-67 expression and those of HER2 status was assessed with the Mann-Whitney test. Spearman correlation analysis was used to analyze the correlation between the SDCT parameters and the extent of Ki-67 expression and HER2 expression status. The receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated. The SDCT parameters of CT values at 40 keV, effective atomic number, IC, and the λHU in the VP showed significant differences between the Ki-67 high- and low-expression groups in CRAC (P=0.035, P=0.041, P=0.036, and P=0.044, respectively), with AUCs of 0.639 [95% confidence interval (CI): 0.512-0.766], 0.634 (95% CI: 0.508-0.761), 0.638 (95% CI: 0.510-0.766), and 0.633 (95% CI: 0.504-0.762), respectively. The expression of CRAC Ki-67 was positively correlated with CT values at 40 keV (r=0.227; P=0.034), effective atomic number (r=0.219; P=0.040), IC (r=0.225; P=0.035), and the λHU in VP (r=0.216; P=0.043). SDCT parameter values showed no statistical difference between negative and positive expression in HER2 (all P values >0.05). There was no significant correlation between SDCT parameters and the expression of HER2 in CRAC (all P values >0.05). The quantitative parameters of SDCT in the VP provide valuable information for distinguishing between the low expression and high expression of Ki-67 in CRAC.

Novel biomarkers based on dual-energy computed tomography for risk stratification of very early distant metastasis in colorectal cancer after surgery.

Very early distant metastasis (VEDM) for patients with colorectal cancer (CRC) following surgery suggests failure of local treatment strategy and few biomarkers are available for its effective risk stratification. This study aimed to explore the potential of quantitative dual-energy computed tomography (DECT) spectral parameters and build models to predict VEDM. Consecutive patients suspected of having CRC and with a clinical indication for enhanced CT from April 2021 to July 2022 at a single institution were prospectively enrolled to undertake spectral CT scanning. The spectral features were extracted by two reviewers and intraclass correlation coefficient (ICC) was used for interobserver agreement evaluation. A total of 16 spectral parameters, including unenhanced effective atomic number, triphasic iodine concentrations (ICs)/normalized ICs (NICs)-A/V/E/1/NIC-A/V/E/spectral curve slopes (λ-A/V/E), two arterial enhancement fractions (AEFs), and venous enhancement fraction (VEF), were determined for analysis. Patients with and without VEDM after surgery were matched using propensity score matching (PSM). The diagnostic performance was assessed using the area under the curve (AUC). Models of multiple modalities were generated. In total, 222 patients were included (141 males, age range, 32-83 years) and 13 patients developed VEDM. Interobserver agreement ranged from good to excellent (ICC, 0.773-0.964). A total of three spectral parameters (VEF, λ-V, and 1/NIC-V) exhibited significant discriminatory ability (P<0.05) in predicting VEDM, with AUCs of 0.822 [95% confidence interval (CI): 0.667-0.926], 0.738 (95% CI: 0.573-0.866), and 0.713 (95% CI: 0.546-0.846) and optimal cutoff points of 67.16%, 2.46, and 2.44, respectively. The performance of these spectral parameters was validated in the entire cohort; the combined spectral model showed comparable efficiency to the combined clinical model [AUC, 0.771 (95% CI: 0.622-0.919) vs. 0.779 (95% CI: 0.663-0.894), P>0.05]; the clinical-spectral model achieved further improved AUC of 0.887 (95% CI: 0.812-0.962), which was significantly higher than the combined clinical model (P=0.015), yet not superior to the combined spectral model (P=0.078). Novel spectral parameters showed potential in predicting VEDM in CRC following surgery in this preliminary study, which were closely related with spectral perfusion in the venous phase. However, further studies with larger samples are warranted.

Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas

PurposeThe purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA. Materials and methodsSixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29–78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models. ResultsThe 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73–0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66–0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74–0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74–0.93) (P = 0.60). ConclusionBoth whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.