CT Parameters Research Articles

Evaluating the Knowledge of Radiation Exposure Parameters Among CT Technologists in Saudi Arabia: A Survey-Based Study on Adherence to ALARA Principles and Dose Optimization

Computed tomography is a crucial tool in modern healthcare, offering non-invasive imaging for diagnosis and monitoring. However, its widespread use raises concerns about radiation exposure. Adhering to the ALARA principle is vital to minimize risks while maintaining diagnostic quality. This study evaluates the knowledge of CT technologists in Saudi Arabia regarding radiation exposure parameters. A questionnaire-based survey was conducted, covering demographics, perceptions, and understanding of CT parameters. Statistical analysis revealed gaps in knowledge, particularly regarding dose optimization strategies and diagnostic reference levels. While most participants recognized the importance of adjusting parameters based on patient characteristics and clinical indications, deficiencies were observed in understanding specific parameters' effects on dose and image quality. Furthermore, a notable proportion of participants were unfamiliar with DRLs, indicating a need for improved education in this area. The study emphasizes the importance of interdisciplinary collaboration between radiologists, physicists, and technologists in protocol development and optimization.

Spectral CT in the evaluation of perineural invasion status in rectal cancer.

To investigate whether preoperative spectral CT quantitative parameters can assess perineural invasion (PNI) status in rectal cancer. Sixty-two patients diagnosed with rectal cancer who underwent preoperative spectral CT were retrospectively enrolled and divided into positive and negative PNI groups according to histopathologic results. The CT attenuation value (HU) of virtual monochromatic images (40-70keV), spectral curve slope (K(HU)), effective atomic number (Zeff), and iodine concentration (IC) from spectral CT were compared between these two groups using t test or rank sum test. A nomogram was established by incorporating the independent predictors to assess the overall diagnostic efficacy. The area under the ROC curves (AUCs) were compared using the DeLong test. The preoperative spectral CT parameters (40-70keV attenuation, K(HU), Zeff, and IC) were significantly higher in the PNI-positive group compared to the PNI-negative group (all p < 0.05). The highest predictive efficiency of PNI was observed at 40keV attenuation, with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.847, 81.8%, 72.5%, and 75.8%, respectively. Binary logistic regression demonstrated that the clinical feature (cN stage) and 40keV attenuation were independent predictors of PNI status. The nomogram incorporating these two predictors (cN stage and 40keV attenuation) exhibited the best evaluation efficacy, with an AUC, sensitivity, specificity, and accuracy of 0.885, 86.4%, 77.5%, and 80.6%. Spectral CT quantitative parameters proved valuable in the preoperative assessment of PNI status in rectal cancer patients. The combination of spectral CT parameters and clinical features could further enhance the diagnostic efficiency.

Clinical data and quantitative CT parameters combined with machine learning to predict short-term prognosis of severe COVID-19 in the elderly

Rationale and objectivesThis study aims to evaluate the effectiveness of integrating clinical data and quantitative CT parameters with machine learning techniques in forecasting the short-term outcomes of severe COVID-19 in elderly patients. Materials and methodsIn this retrospective study, we analyzed the clinical profiles and chest quantitative CT parameters of 239 elderly patients with severe COVID-19 admitted for treatment. The cohort included 61 deceased patients (death group) and 178 who recovered and were discharged (survival group). The participants were randomly assigned into a training group (n = 167) and a validation group (n = 72). Quantitative CT parameters were measured using the 3D-Slicer software. Univariate and multivariate logistic regression analyses identified independent risk factors for mortality. Predictive models were developed employing four machine learning algorithms: Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM). ResultsBoth univariate and multivariate logistic regression analyses revealed age, hypersensitive C-reactive protein (hs-CRP), and solid organ volume percentage (SOV%) as independent predictors of mortality. The Area Under the Curve (AUC) values for the LR, RF, DT, and SVM models in the training group were 0.795, 0.726, 0.854, and 0.589, respectively; for the validation group, they were 0.817, 0.634, 0.869, and 0.754, respectively. The DT algorithm outperformed other models in both the training and validation groups, emerging as the most effective predictive model in this study. ConclusionThe combination of clinical data and quantitative CT parameters with machine learning approaches is highly valuable in predicting the short-term prognosis of severe COVID-19 in the elderly. Among the various models tested, the Decision Tree algorithm-based model proved to be the most accurate and reliable in this context.

Synergistic insights: the integrated role of CT/CTP and clinical parameters in hemorrhagic transformation prediction.

Acute ischemic stroke presents significant challenges in healthcare, notably due to the risk and poor prognosis associated with hemorrhagic transformation (HT). Currently, there is a notable gap in the early clinical stage for a valid and reliable predictive model for HT. This single-center retrospective study analyzed data from 224 patients with acute ischemic stroke due to large vessel occlusion. We collected comprehensive clinical data, CT, and CTP parameters. A predictive model for HT was developed, incorporating clinical indicators alongside imaging data, and its efficacy was evaluated using decision curve analysis and calibration curves. In addition, we have also built a free browser-based online calculator based on this model for HT prediction. The study identified atrial fibrillation and hypertension as significant risk factors for HT. Patients with HT showed more extensive initial ischemic damage and a smaller ischemic penumbra. Our novel predictive model, integrating clinical indicators with CT and CTP parameters, demonstrated superior predictive value compared to models based solely on clinical indicators. The research highlighted the intricate interplay of clinical and imaging parameters in HT post-thrombectomy. It established a multifaceted predictive model, enhancing the understanding and management of acute ischemic stroke. Future studies should focus on validating this model in broader cohorts, further investigating the causal relationships, and exploring the nuanced effects of these parameters on patient outcomes post-stroke.

Preliminary differentiation of benign and malignant gastric wall thickening using dual-layer spectral-detector CT.

Dual-layer spectral-detector computed tomography (DLCT) may have the potential to evaluate gastric wall thickening. To evaluate the efficacy of DLCT quantitative parameters in differentiating between benign and malignant thickening of the gastric wall. A total of 58 patients with "gastric wall thickening" who underwent multi-phase abdominal enhanced DLCT scans were included in this study. Of these patients, 33 were malignant and 25 were benign. Parameters such as iodine concentration (IC), effective atomic number (Zeff), and attenuation of the lesions were measured during the arterial phase (AP) and venous phase (VP). Binary logistic regression was employed to calculate the combined prediction probabilities. The accuracy of the DLCT parameters was assessed using receiver operating characteristic (ROC) curves. The values of IC, nIC, Zeff, normalized Zeff, and attenuation in the AP and VP were significantly higher (all P < 0.05) in the malignant group compared to the benign group. The ROC curves revealed that the IC, Zeff, and attenuation in the VP exhibited high diagnostic performance, with area under the ROC curve (AUC) values of 0.864, 0.862, and 0.840, respectively. The new combination of these three factors and gastric wall thickness had an AUC of 0.884, and the sensitivity and specificity were determined to be 81.8% and 92.0%, respectively. Spectral CT parameters, particularly the combination of gastric wall thickness, attenuation, IC, and Zeff in VP, have value in distinguishing between benign and malignant gastric wall thickening.

Automated Comprehensive CT Assessment of the Risk of Diabetes and Associated Cardiometabolic Conditions.

Background CT performed for various clinical indications has the potential to predict cardiometabolic diseases. However, the predictive ability of individual CT parameters remains underexplored. Purpose To evaluate the ability of automated CT-derived markers to predict diabetes and associated cardiometabolic comorbidities. Materials and Methods This retrospective study included Korean adults (age ≥ 25 years) who underwent health screening with fluorine 18 fluorodeoxyglucose PET/CT between January 2012 and December 2015. Fully automated CT markers included visceral and subcutaneous fat, muscle, bone density, liver fat, all normalized to height (in meters squared), and aortic calcification. Predictive performance was assessed with area under the receiver operating characteristic curve (AUC) and Harrell C-index in the cross-sectional and survival analyses, respectively. Results The cross-sectional and cohort analyses included 32166 (mean age, 45 years ± 6 [SD], 28833 men) and 27 298 adults (mean age, 44 years ± 5 [SD], 24 820 men), respectively. Diabetes prevalence and incidence was 6% at baseline and 9% during the 7.3-year median follow-up, respectively. Visceral fat index showed the highest predictive performance for prevalent and incident diabetes, yielding AUC of 0.70 (95% CI: 0.68, 0.71) for men and 0.82 (95% CI: 0.78, 0.85) for women and C-index of 0.68 (95% CI: 0.67, 0.69) for men and 0.82 (95% CI: 0.77, 0.86) for women, respectively. Combining visceral fat, muscle area, liver fat fraction, and aortic calcification improved predictive performance, yielding C-indexes of 0.69 (95% CI: 0.68, 0.71) for men and 0.83 (95% CI: 0.78, 0.87) for women. The AUC for visceral fat index in identifying metabolic syndrome was 0.81 (95% CI: 0.80, 0.81) for men and 0.90 (95% CI: 0.88, 0.91) for women. CT-derived markers also identified US-diagnosed fatty liver, coronary artery calcium scores greater than 100, sarcopenia, and osteoporosis, with AUCs ranging from 0.80 to 0.95. Conclusion Automated multiorgan CT analysis identified individuals at high risk of diabetes and other cardiometabolic comorbidities. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pickhardt in this issue.

Prognostic value of CT findings for conservative treatment failure in adhesive small bowel obstruction.

This study aimed to identify the radiological CT findings that are significantly correlated with the outcome of conservative management with oral water-soluble contrast medium in patients presenting with Adhesive Small Bowel Obstruction (ASBO) to the Emergency Room. In this retrospective single-center study, we considered all consecutive patients admitted to the ER from February 2019 to February 2023 for ASBO with an available contrast-enhanced CT scan performed at diagnosis and treated with conservative management. The investigated CT findings were type and location of transition zone, ASBO degree, fat notch sign, beak sign, small bowel feces sign, presence of peritoneal free fluidand pneumatosis intestinalis. Radiological parameters were analyzed using univariable and multivariable logistic regression to test the significant association between the CT parameters and the target. Among the 106 included patients (median age 74.5years), conservative treatment was effective in 59 (55.7%) and failed in 47 (44.3%), needing delayed surgery. In the failure group, there was a higher prevalence of patients who had previous ASBO episodes (p = 0.03), a greater proportion of females (p = 0.04) and a longer hospital stay (p < 0.001). At multivariable analysis, two CT findings were significantly correlated with failure of conservative treatment: fat notch sign (OR = 2.95; p = 0.04) and beak sign (OR = 3.42; p = 0.04). Two radiological signs correlate with failure of non-operative management in ASBO, suggesting their importance in surgical decision-making. Patients presenting with these signs are at higher risk of unsuccessful conservative treatment and may require undelayed surgical intervention.

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (AECOPD) based on deep-learning (DL) features. We performed a retrospective study on 219 patients with COPD who underwent inspiratory and expiratory HRCT scans. By recording the acute respiratory events of the previous year, these patients were further divided into non-AECOPD group and AECOPD group according to the presence of acute exacerbation events. Sixty-nine quantitative CT (QCT) parameters of emphysema and airway were calculated by NeuLungCARE software, and 2,000 DL features were extracted by VGG-16 method. The logistic regression method was employed to identify AECOPD patients, and 29 patients of external validation cohort were used to access the robustness of the results. The model 3-B achieved an area under the receiver operating characteristic curve (AUC) of 0.933 and 0.865 in the testing cohort and external validation cohort, respectively. Model 3-I obtained AUC of 0.895 in the testing cohort and AUC of 0.774 in the external validation cohort. Model 7-B combined clinical characteristics, QCT parameters, and DL features achieved the best performance with an AUC of 0.979 in the testing cohort and demonstrating robust predictability with an AUC of 0.932 in the external validation cohort. Likewise, model 7-I achieved an AUC of 0.938 and 0.872 in the testing cohort and external validation cohort, respectively. DL features extracted from HRCT scans can effectively predict acute exacerbation phenotype in COPD patients.

Identification of risk factors for acute exacerbation of idiopathic pulmonary fibrosis based on baseline high-resolution computed tomography: a prospective observational study

BackgroundThis study aimed to investigate risk factors for acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) based on baseline high-resolution computed tomography (HRCT).MethodsThis prospective observational study enrolled patients with IPF treated at the General Hospital of Ningxia Medical University between January 2019 and January 2021. HRCT-derived quantitative parameters at baseline were analyzed.ResultsA total of 102 patients [92 (90.2%) males with a mean age of 67 years] with IPF were included, with a median follow-up of 32 (24-40.5) months. AE occurred in 30 (29.4%) IPF patients. Multivariable logistic regression analysis identified Doppler transthoracic echocardiography suggestive of pulmonary hypertension (PH) (13.43; 95% CI: 4.18–41.09; P < 0.001), honeycombing (OR 1.08; 95% CI: 1.02–1.14; P = 0.013), and whole lung volume (OR 0.99; 95% CI: 0.99-1.00; P = 0.037) as independent risk factors for AE-IPF. The combination of PH, honeycombing, whole lung volume, and the percentage of predicted forced vital capacity (FVC% pred) showed a high area under the curve from receiver operating characteristic curves of 0.888, with a sensitivity of 90% and specificity of 78%.ConclusionsThis study emphasizes that quantitative CT parameters (honeycombing, whole lung volume) may serve as risk factors for AE-IPF. The combination of honeycombing, whole lung volume, FVC% pred, and PH may aid in predicting AE-IPF.

Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: Ktrans (transfer constant), Ve (extravascular and extracellular space), and Vi (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (rrm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: Ve and Ki-67 (rrm = -0.17, P < .001), Ve and HIF-1α (rrm = -0.12, P < .001), Ktrans and CD45 (rrm = 0.13, P < .001), Vi and CD45 (rrm = 0.16, P < .001), and Vi and Ki-67 (rrm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (rrm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.

Impact of CT-relevant skeletal muscle parameters on post-liver transplantation survival in patients with hepatocellular carcinoma.

The specific CT-related skeletal muscle parameters predictive of postoperative survival in liver transplant (LT) patients with hepatocellular carcinoma (HCC) remain unclear. There is increasing evidence supporting the role of fatty acids and their lipid intermediates in regulating skeletal muscle mass and function, the relationship between lipoprotein subfractions and body composition remains unclear. Adult patients with HCC who underwent LT between January 2015 and September 2022 were retrospectively analyzed. CT parameters, including skeletal muscle index (SMI), psoas muscle index (PMI), skeletal muscle density (SMD), visceral and subcutaneous adipose tissue (VAT and SAT), and the VAT/SAT ratio at the L3 level, and lipid profiles, were assessed prior to LT. Of the 284 LT patients with HCC, 224 underwent CT (L3 level) within 3months of LT, and 82 (37%) were diagnosed with myosteatosis. Patients with myosteatosis exhibited significantly lower 1- and 3-year survival rates (p = 0.002, p = 0.01), a trend persisting even beyond the Milan criteria (p = 0.004, p = 0.04). After adjusting for covariates, SMD demonstrated a significant negative correlation with post-transplant survival (HR: 0.90, [95% Confidence Interval(CI): 0.83-0.98], C-statistic: 0.78, p = 0.009). Pearson's correlation analysis revealed a positive correlation between high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A1(ApoA1) levels and SMD. Multivariate stepwise regression analysis demonstrated that every 10 Hounsfield unit decrease in SMD was associated with a 0.16mmol/L decrease in HDL-C and a 0.18g/L decrease in ApoA1. Routine abdominal CT scans for assessing skeletal muscle density before LT were significantly associated with post-transplant mortality. Furthermore, abnormal HDL-C and ApoA1 levels before LT were associated with myosteatosis.

Predictive quantitative multidetector computed tomography models for characterization of renal cell carcinoma subtypes and differentiation from renal oncocytoma: nomogram algorithmic approach analysis

BackgroundOur objective is to develop an algorithmic approach using predictive models to discriminate between common solid renal masses, including renal cell carcinoma [RCC] subtypes and renal oncocytoma [RO], using multiphase computed tomography [CT].MethodsWe retrospectively analyzed a group of solid renal masses between January 2011 and January 2023 regarding the CT attenuation values using a multiphase multidetector CT and clinical parameters. Inclusion criteria included patients who had four phases of CT with a partial or radical nephrectomy. Exclusion criteria were patients with biphasic or one-phase CT, poor imaging quality, patients under surveillance, radiofrequency ablation, or indeterminate pathology findings as oncocytic tumor variants. We divided our cohort into training and internal validation sets.ResultsOur results revealed that a total of 467 cases, 351 patients assigned for the training cohort and 116 cases assigned for validation cohort. There is a significant difference between hypervascular clear RCC [CRCC and RO] and hypovascular chromophobe and papillary [ChRCC and PRCC] masses in both training and validation sets, AUC = 0.95, 0.98, respectively. The predictive model for differentiation between CRCC and RO showed AUC = 0.83, 0.85 in both training and validation sets, respectively. At the same time, the discrimination of ChRCC from PRCC showed AUC = 0.94 in the training set and 0.93 in the validation cohort.ConclusionsUsing the largest sample to our knowledge, we developed a three-phase analytical approach to initiate a practical method to discriminate between different solid renal masses that can be used in daily clinical practice.

Enhancement on CT for preoperative diagnosis of metastatic lymph nodes in thyroid cancer: a comparison across experience levels.

To investigate the diagnostic performance and interobserver agreement of quantitative CT parameters indicating strong lymph node (LN) enhancement in differentiated thyroid cancer (DTC), comparing them with qualitative analysis by radiologists of varying experience. This study included 463 LNs from 399 patients with DTC. Three radiologists independently analyzed strong LN enhancement on CT. Qualitative analysis of strong enhancement was defined as LN cortex showing greater enhancement than adjacent muscles on the arterial phase. Quantitative analysis included the mean attenuation value (MAV) of LN on arterial phase (LNA) and venous phase (LNV), LNA normalized to the common carotid artery (NAVCCA), internal jugular vein (NAVIJV), and sternocleidomastoid muscle (NAVSCM), attenuation difference [AD; (LNA - MAVSCM)], and relative washout ratio [((LNA - LNV)/LNA) × 100]. The interobserver agreement and diagnostic performance of the quantitative and qualitative analyses were evaluated. Interobserver agreement was excellent for all quantitative CT parameters (ICC, 0.83-0.94) and substantial for qualitative assessment (κ = 0.61). All CT parameters except for LNV showed good diagnostic performance for metastatic LNs (AUC, 0.81-0.85). NAVCCA (0.85, 95% CI: 0.8-0.9) and AD (0.85, 95% CI: 0.81-0.89) had the highest AUCs. All quantitative parameters except for NAVIJV had significantly higher AUCs than qualitative assessments by inexperienced radiologists, with no significant difference from assessments by an experienced radiologist. Quantitative assessment of LN enhancement on arterial phase CT showed higher interobserver agreement and AUC values than qualitative analysis by inexperienced radiologists, supporting the need for a standardized quantitative CT parameter-based model for determining strong LN enhancement. When assessing strong LN enhancement in DTC, quantitative CT parameters indicating strong enhancement can improve interobserver agreement, regardless of experience level. Therefore, the development of a standardized diagnostic model based on quantitative CT parameters might be necessary. Accurate preoperative assessment of LN metastasis in thyroid cancer is crucial. Quantitative CT parameters indicating strong LN enhancement demonstrated excellent interobserver agreement and good diagnostic performance. Quantitative assessment of contrast enhancement offers a more objective model for the identification of metastatic LNs.

Quantitative measurements of dual-energy CT parameters in the diagnosis of osteoporosis - a highly sensitive and specific technique: An observational study.

With the aging of the population in our society, osteoporosis (OP) has become one of the chronic diseases that seriously threaten the physical health of the elderly, leading to a heavy burden on healthcare. In recent years, with the continuous development of dual-energy CT (DECT) technology, quantitative measurements of DECT parameters, which is highly sensitive to OP, provides accurate results, is convenient and cost-effective, and is expected to be widely used in bone density testing. This study was aimed to explore the value of quantitative measurements of DECT parameters in diagnosing OP, in order to better guide clinical judgments and treatment. A total of 187 patients who underwent dual-energy X-ray and DECT examinations at Tianjin hospital between January 2022 and June 2023 were included as participants in this study. The bone mineral density (BMD) values of the lumbar spine (L1-L4) were determined using dual-energy X-ray absorptiometry. Simultaneously, CT scans of the lumbar spine (L1-L4) were conducted to measure the CT values of contrast media (CM), mixed-energy image CT values (regular CT value [rCT]), calcium concentration (CaD), as well as fat fraction (FF). Pearson correlation analysis was used to examine the relationship between the quantitative measurements of L1 to L4 vertebral bodies obtained from DECT and BMD. The values of CM, rCT, and CaD in the OP group were all lower than those in the non-OP group with statistical significance (P < .001). Conversely, the fat fraction parameter value in the OP group was significantly higher in contrast with the non-OP group (P = .004); there was a positive correlation between CM, rCT, CaD, and BMD values (R = 0.579, P < .001; R = 0.604, P < .001; R = 0.563, P < .001); CM, rCT, and CaD had high diagnostic value for OP, as evidenced by AUCs of 0.935 (95% CI: 0.900-0.971), 0.956 (95% CI: 0.925-0.987), and 0.926 (95% CI: 0.858-0.954), respectively, all with P values < .001. Quantitative measurement of DECT parameters showed a high sensitivity as well as a high specificity in the diagnosis of OP. It is also highly feasible and holds significant clinical diagnostic value, making it a suitable candidate for widespread application.

CT image quality and dose optimization by combining tube voltage, dose reduction setting and ASIR-V (explorative study using VCT phantom)

Utilization of ASIR-V software to improve CT scan images with lower exposure factor settings has enormous potential to produce CT scan images with minimal dose and optimal image quality. Otherwise, the excessive use of iterative reconstruction may lead to poor image quality. The purpose of this study was to determine the differences in radiation dose and image quality in the combination of tube voltage, dose reduction and ASIR-V settings and giving recommendation out of it. This type of research is quasi-experimental with a pretest posttest design. VCT Quality Assurance phantom scanned with abdominal CT parameters with the combination of tube voltage variations and dose reduction settings then reconstructed using ASIR-V. Image quality data including noise, LCD and HCR obtained were analyzed by using the paired t-test statistical test. The lowest dose (2.01 mGy) resulted from the combination of tube voltage setting 80 kV, 60% dose reduction, and the dose reduction in the treatment group was in the range of 49% - 87%. The lowest noise was produced by a combination of tube voltage settings of 80 kV, 60% dose reduction, and 100% ASIR-V and noise reduction in the treatment group in the range of 15% -68%. There are significant differences in low contrast detectability of image obtained from 15 combination of tube voltage settings, and dose reduction setting after ASIR-V reconstruction on CT scans. Meanwhile, there are significant differences of extreme contrast spatial resolution in 13 combinations of the tube voltage and dose reduction setting after ASIR-V reconstruction showed. Decreasing the tube voltage and increasing the dose reduction value results in a lesser radiation dose accompanied by a decrease in image quality, while the application of ASIR-V is proven to improve the quality of CT scan images including noise and low contrast detectability, in the other hand the excessive use of ASIR-V may also decrease high contrast spatial resolution of the image. The combination of image quality that is closest to the image quality of the control group is a combination of tube voltage settings of 120 kV, 60% dose reduction and 60% ASIR-V which produces a radiation dose of 6.37 mGy.

In vitro blood sample assessment: investigating correlation of laboratory hemoglobin and spectral properties of dual-energy CT measurements (ρ/Z)

Abstract Objectives Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection. Methods DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured. Results Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37–0.49) and attenuation (r-values 0.59–0.83) while no correlation was observed for Zeff (r-values −0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value &lt; 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined. Conclusion In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection. Clinical relevance statement By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice. Key Points Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection. Graphical Abstract

Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer

PurposeTo evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC). MethodFor this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed. Results60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871. ConclusionSpectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.

Postoperative 3D computed tomographic evaluation of 92 calcaneal fracture reduction using the sinus tarsi technique and fixation with 3.5mm cortical screws.

Fixation of calcaneus through the sinus tarsi approach is increasingly popular due to the lower rate of wound complications. The use of postoperative CT provided a better evaluation tool than using plain radiography. Our objective of the present study is to evaluate the quality of fracture reductions by postoperative 3D CT scans after surgical intervention using the sinus tarsi approach and fixation with 3.5 cortical screws. Between January 2018 and April 2020, 86 consecutive patients with 92 closed displaced intra-articular calcaneal fractures underwent ORIF with 3.5mm screws constructed via a minimally invasive sinus tarsi approach by a single foot and ankle surgeon. The preoperative radiographic assessment found 36 joint depression type and 56 tongue type fractures according to the Essex-Lopresti classification. Preoperative CT assessment found 82 type II and 10 type III according to the Sander classification. Analysis of pre- and postoperative CT parameters showed that the height of the posterior facet, the length of the posterior facet, Gissane, and Bohler's angle were significantly improved. In addition, the means of posterior facet step-off in postoperative CT was 1.07, and 72% of posterior facet reductions were < 2mm step-offs. With postoperative CT scan assessment, the treatment of displaced intra-articular calcaneal fracture with 3.5mm screws via sinus tarsi approach has achieved good quality of reduction. Therefore, the screws-only technique is an option for treating calcaneal fracture with less soft tissue damage and implant cost.

Diagnostic value of one-stop CT energy spectrum and perfusion for angiogenesis in colon and rectum cancer

ObjectiveEvaluation of the predictive value of one-stop energy spectrum and perfusion CT parameters for microvessel density (MVD) in colorectal cancer cancer foci.MethodsClinical and CT data of 82 patients with colorectal cancer confirmed by preoperative colonoscopy or surgical pathology in our hospital from September 2019 to November 2022 were collected and analyzed retrospectively. Energy spectrum CT images were measured using the Protocols general module of the GSI Viewer software of the GE AW 4.7 post-processing workstation to measure the CT values of the arterial and venous phase lesions and the neighboring normal intestinal wall in a single energy range of 40 kev∼140 kev, and the slopes of the energy spectrum curves (λ) were calculated between 40 kev-90 kev; Iodine concentration (IC), Water concentration (WC), Effective-Z (Eff-Z) and Normalized iodine concentration (NIC) were measured by placing a region of interest (ROI) on the iodine concentration map and water concentration map at the lesion and adjacent to the normal intestinal wall.Perfusion CT images were scanned continuously and dynamically using GSI Perfusion software and analyzed by applying CT Perfusion 4.0 software.Blood volume (BV), blood flow (BF), surface permeability (PS), time to peak (TTP), and mean transit time (MTT) were measured respectively in the lesion and adjacent normal colorectal wall. Based on the pathological findings, the tumors were divided into a low MVD group (MVD < 35/field of view, n = 52 cases) and a high MVD group (MVD ≥ 35/field of view, n = 30 cases) using a median of 35/field of view as the MVD grouping criterion. The collected data were statistically analyzed, the subjects’ operating characteristic curve (ROC) was plotted, and the area under curve (AUC), sensitivity, specificity, and Yoden index were calculated for the predicted efficacy of each parameter of the energy spectrum and perfusion CT and the combined parameters.ResultsThe CT values, IC, NIC, λ, Eff-Z of 40kev∼140kev single energy in the arterial and venous phase of colorectal cancer in the high MVD group were higher than those in the low MVD group, and the differences were all statistically significant (p < 0.05). The AUC of each single-energy CT value in the arterial phase from 40 kev to 120 kev for determining the high or low MVD of colorectal cancer was greater than 0.8, indicating that arterial stage has a good predictive value for high or low MVD in colorectal cancer; AUC for arterial IC, NIC and IC + NIC were all greater than 0.9, indicating that in arterial colorectal cancer, both single and combined parameters of spectral CT are highly effective in predicting the level of MVD. The AUC of 40 kev to 90 kev single-energy CT values in the intravenous phase was greater than 0.9, and its diagnostic efficacy was more representative; The AUC of IC and NIC in venous stage were greater than 0.8, which indicating that the IC and NIC energy spectrum parameters in venous stage colorectal cancer have a very good predictive value for the difference between high and low MVDs, with the greatest diagnostic efficacy in IC.The values of BV and BF in the high MVD group were higher than those in the low MVD group, and the differences were statistically significant (P < 0.05), and the AUC of BF, BV, and BV + BF were 0.991, 0.733, and 0.997, respectively, with the highest diagnostic efficacy for determining the level of MVD in colorectal cancer by BV + BF.ConclusionOne-stop CT energy spectrum and perfusion imaging technology can accurately reflect the MVD in living tumor tissues, which in turn reflects the tumor angiogenesis, and to a certain extent helps to determine the malignancy, invasion and metastasis of living colorectal cancer tumor tissues based on CT energy spectrum and perfusion parameters.

Defining Surgical Difficulty During Open Right Lobe Donor Hepatectomy and its Prediction Using Preoperative Donor Computed Tomography Morphometry

BackgroundThere is no accepted way to define difficult donor hepatectomy (DiffDH) during open right living donor hepatectomy (ORLDH). There are also no studies exploring association between DiffDH and early donor outcomes or reliable pre-operative predictors of DiffDH. MethodsConsecutive ORLDH performed over 18 months at a single center were included. Intra-operative parameters were used to develop an objective definition of DiffDH. The impact of DiffDH on early postoperative outcomes and achievement of textbook outcome (TO) was evaluated. Donor morphometry data on axial and coronal sections of donor CT at the level of portal bifurcation were collected. Donor and graft factors predictive of DiffDH were evaluated using univariate and multivariate logistic regression. ResultsOne hundred and eleven donors (Male-40.5%, Age-34± 9.5 years) underwent ORLDH during the study period. Difficulty score was constructed using five intra-operative parameters i.e. operating time, transection time, estimated blood loss, need for intra-operative vasopressors and need for Pringle maneuver. Donors were classified as DiffDH (score ≥ 2) or Standard DH (score<2). Twenty nine donors (26%) were classified as DiffDH. DiffDH donors suffered greater all cause morbidity (p=0.004) but not major morbidity (Clavien-Dindo score>2; p=0.651), more peri-operative transfusion (p=0.013), increased post-operative SIRS (p=0.034), delay in achieving full oral diet (p=0.047) and a 70% reduced chance of achieving TO as compared to StDH (p=0.007). On logistic regression analysis, increasing right lobe antero-posterior depth (RLdepth) was identified as an independent predictor of DiffDH (Odds ratio- 2.0(95% ci =1.2,3.3), p<0.006). ROC curve analysis identified RLdepth>14 cms as the best predictor of DiffDH (Sensitivity-79%, specificity-66%, Area under curve=0.803, p<0.001). ConclusionWe report a novel definition of DiffDH and show that it is associated with worse post-operative outcomes, including a lesser chance of achieving TO. We also report that DiffDH can be predicted from readily available donor CT parameters.