CT Density Research Articles

Clinical, functional, and opportunistic CT metrics of sarcopenia at the point of imaging care: analysis of all-cause mortality.

This study examines clinical, functional, and CT metrics of sarcopenia and all-cause mortality in older adults undergoing outpatient imaging. The study included outpatients ≥ 65years of age undergoing CT or PET/CT at a tertiary care institution. Assessments included screening questionnaires for sarcopenia (SARC-F) and frailty (FRAIL scale), and measurements of grip strength and usual gait speed (6m course). Skeletal muscle area (SMA), index (SMI, area/height2) and density (SMD) were measured on CT at T12 and L3. A modified SMI was also examined (SMI-m, area/height). Mortality risk was studied with Cox proportional hazard analysis. The study included 416 patients; mean age 73.8years [sd 6.2]; mean follow-up 2.9years (sd 1.34). Abnormal grip, SARC-F, and FRAIL scale assessments were associated with higher mortality risk (HR [95%CI] = 2.0 [1.4-2.9], 1.6 [1.1-2.3], 2.0 [1.4-2.8]). Adjusting for age, higher L3-SMA, T12-SMA, T12-SMI and T12-SMI-m were associated with lower mortality risk (HR [95%CI] = 0.80 [0.65-0.90], 0.76 [0.64-0.90], 0.84 [0.70-1.00], and 0.80 [0.67-0.90], respectively). T12-SMD and L3-SMD were not predictive of mortality. After adjusting for abnormal grip strength and FRAIL scale assessments, T12-SMA and T12-SMI-m remained predictive of mortality risk (HR [95%CI] = 0.83 [0.70-1.00] and 0.80 [0.67-0.97], respectively). CT areal metrics were weaker predictors of all-cause mortality than clinical and functional metrics of sarcopenia in our older patient cohort; a CT density metric (SMD) was not predictive. Of areal CT metrics, SMI (area/height2) appeared to be less effective than non-normalized SMA or SMA normalized by height1.

Prediction of Basal Ganglia Hematoma Expansion Based on Radiomics and Clinical Characteristics: A Novel Multivariate Predictive Nomogram

Background. This study is aimed at formulating and authenticating a pioneering nomogram integrating noncontrast computed tomography (NCCT) mean CT densities (m-CTD) of hematoma, morphological indicators from NCCT hematoma, and clinical manifestations to foresee hematoma expansion (HE) in patients suffering from spontaneous basal ganglia hemorrhage (BGH). Methods. A predictive model was constructed by retrospectively evaluating the data from 406 patients. This model was externally validated using an independent dataset of 174 patients. Multivariate logistic regression analysis was deployed to discern independent prognostic indicators and to generate a nomogram for HE prediction. Model calibration was examined using 1000 bootstrap samples for internal validation. Results. Multivariate logistic regression disclosed that m-CTD (odds ratio (OR) 0.846, 95% confidence interval (CI) 0.782-0.909), baseline hematoma volume (BHV) (OR 1.055, 95% CI 1.017-1.095), NCCT blend sign (BS) (OR 3.320, 95% CI 1.704-6.534), NCCT black hole sign (BHS) (OR 2.468, 95% CI 1.293-4.729), systolic blood pressure (SBP) (OR 1.027, 95% CI 1.014-1.040), and homocysteine (Hcy) (OR 1.075, 95% CI 1.038-1.114) were independent predictors of HE. The area under the curve (AUC) for the training and validation datasets yielded 0.874 and 0.883, respectively. The calibration curve for the nomogram closely approximated the optimal diagonal. The decision curve analysis (DCA) indicated that the prediction model offers substantial net benefits. Conclusions. The innovative predictive nomogram, leveraging radiomics and clinical traits of hematoma, presents a potent and noninvasive tool for HE risk stratification. The method of quantifying mean hematoma density holds significant prognostic value in forecasting HE.

Estimation of Bone Mineral Density in the Femoral Neck and Lumbar Spine using Texture Analysis of Chest and Pelvis Computed Tomography Hounsfield Unit.

This study aimed to establish an academic basis for using a computed tomography (CT) model for predicting osteoporosis in the clinical setting by illustrating the effectiveness of morphometric texture analysis. We introduce texture analysis and quantitative approaches using CT Hounsfield units (HU) to screen osteoporosis. From March 6th, 2013, to August 11th, 2020, a total of 4,333 cases (1,766 patients) were included in the study. After applying exclusion criteria concerning the patient status and scan interval between CT and DXA, we selected only 1,647 samples (736 patients) and analyzed both their CT and DXA bone mineral density (BMD) results. BMD was measured in the femoral neck and L1 spine body. A region of interest (ROI) was extracted from each patient's CT as the maximum trabecular area of the L1 spine body and femoral neck. A total of 45 texture features were extracted from every ROI using gray-level co-occurrence matrices. Machine-learning techniques, including linear regression (LR) and artificial neural network (ANN), were applied to predict BMD. We assigned samples to (1) Set 1 (857 lumbar spine samples in chest model, L1 spine DXA BMD), (2) Set 2 (392 lumbar spine samples in lumbar spine CT model, L1 spine DXA BMD), (3) Set 3 (1,249 lumbar spine samples in both chest and lumbar spine CT model, L1 spine DXA BMD), (4) Set 4 (398 femoral neck samples in hip and pelvis CT model, femoral neck DXA BMD), and (5) Set 5 (a total of 1,647 samples). When we applied LR, the correlation coefficients between estimated and reference values for Sets 1, 2, 3, and 4 were 0.783, 0.784, 0.757, and 0.652, respectively. For total samples (Set 5), LR and ANN provided correlation coefficients of 0.707 and 0.782, respectively. The modality using morphometric texture analysis with CT HU can be an additional diagnostic tool for osteoporosis and an alternative for DXA.

Evaluation of the clinical behavior of unclassified renal cell carcinoma and its imaging findings on computed tomography and magnetic resonance imaging based on World Health Organization (WHO) 2022

ObjectivesTo ascertain the clinical behaviors of unclassified renal cell carcinoma (RCC) and its characteristic imaging findings on CT and MRI.MethodsSubjects in this retrospective study were 10 patients who had received a histological diagnosis of unclassified RCC based on World Health Organization (WHO) 2022 and who had undergone CT and/or MRI prior to surgery. In terms of clinical behaviors, TNM classification, stage, postoperative recurrence, time to recurrence, and postoperative survival were evaluated. In terms of imaging findings, tumor size, growth pattern, CT density, dynamic contrast-enhancement (DCE) pattern, internal appearance, presence of a pseudocapsule, and signal intensity on MRI were evaluated. We compared clinical behaviors and imaging findings, and investigated associations between them.ResultsOne patient could not be followed-up due to death from other causes. Postoperative recurrence was observed in 4 patients, all of whom had Stage 3 RCC. In the remaining 5 patients without recurrence, all 5 patients showed Stage 2 or below. On imaging, unclassified RCC tended to be large (58.7 mm) and solid (100%), and heterogeneous interiors (80%), cystic degeneration (80%) and high intensity on diffusion-weighted imaging (DWI) (71.4%) were common. Comparing patients with and without recurrence, the following findings tended to differ between recurrence and recurrence-free groups: tumor size (73.4 ± 33.9 mm vs. 50.2 ± 33.9 mm, P = 0.286), growth pattern (invasive: 100% vs. 0%, expansive: 0% vs. 100%, P = 0.008 each), DCE pattern (progressive enhancement pattern, 66.7% vs. 0%, washout pattern, 0% vs. 66.7%, P = 0.135 each) and presence of a pseudocapsule (25% vs. 80%, P = 0.167).ConclusionThe clinical behavior of unclassified RCC varies widely. Although imaging findings are also variable, findings of large, heterogeneous tumors with cystic degeneration and high intensity on DWI were common. Several imaging findings such as large size, invasive growth, progressive enhancement pattern and no pseudocapsule may enable prediction of prognosis in unclassified RCC.

Prognostic impact of lung computed tomography density in cardiogenic shock patients with veno-arterial extracorporeal membrane oxygenation.

Pulmonary complications often occur in patients receiving veno-arterial extracorporeal membrane oxygenation (VA ECMO). However, the prognostic impact of lung damage has not been fully elucidated. This single-center retrospective observational study targeted patients with cardiogenic shock who received VA ECMO between 2012 and 2021. This study included 65 patients who underwent chest computed tomography (CT) on VA ECMO, followed by escalation to central mechanical circulatory support (MCS) with left ventricular venting. The average density of lung CT images was measured using region-of-interest methods, and the primary endpoint was 180-day all-cause death after escalation to the central MCS. Twenty-two patients (34%) developed 180-day all-cause death. According to the Cox regression analysis, age (hazard ratio [HR], 1.08; 95% confidence interval [CI], 1.03-1.14; p = 0.001), ischemic etiology (HR, 5.53; 95% CI, 2.09-14.62; p < 0.001), duration of VA ECMO support (HR, 1.19; 95% CI, 1.00-1.40; p = 0.045), and lung CT density (≥ -481 Hounsfield unit [HU]) (HR, 6.33; 95% CI, 2.26-17.72; p < 0.001) were independently associated with all-cause death. Receiver operating characteristic curve analysis determined that lung CT density ≥ -481 HU is an optimal cutoff value for predicting all-cause death (area under the curve [AUC], 0.72). The 180-day overall survival rate for patients with high lung CT density (≥ -481 HU) was significantly lower than that for those with low lung CT density (< -481 HU) (44.4% vs. 81.6%, respectively, p = 0.002). Higher lung CT density could be a useful predictor of death in patients with VA ECMO requiring central MCS escalation.

Can virtual non-contrast imaging replace true non-contrast imaging in multiphase scanning of the neck region?

Dual-energy computed tomography (DECT) is an advanced imaging method that enables reconstruction of virtual non-contrast (VNC) images from a contrast-enhanced acquisition. This has the potential to reduce radiation exposure by eliminating the need for a true non-contrast (TNC) phase. The purpose is to evaluate the feasibility of VNC images in the neck region. A total of 100 patients underwent a DECT scan as part of diagnostic workup of primary hyperparathyroidism. VNC images were reconstructed from 30s (arterial) and 50s (venous) post-contrast scans. Regions of interest (ROIs) were placed in thyroid tissue, lymph node, carotid artery, jugular vein, fat, and sternocleidomastoid muscle. Mean densities of all anatomical structures were compared between VNC and TNC images. For all anatomical structures except the thyroid gland, the difference in mean density between TNC and VNC images was less than 15 HU. The mean difference in density between TNC and VNC images of the thyroid was 53.2 HU (95% CI 46.8; 59.6, p = <0.001). This study demonstrated an acceptable agreement in density between true non-contrast and virtual non-contrast images for most anatomical structures in the neck region. Therefore, VNC images may have the potential to replace TNC images in the neck. However, due to significant differences in CT density of thyroid tissue, true non-contrast imaging cannot be directly substituted by virtual non-contrast imaging when examining the thyroid and its surrounding tissue.

A Risk Score for Predicting the Necessity of Surgical Necrosectomy in the Treatment of Infected Necrotizing Pancreatitis

BackgroundFor infected necrotizing pancreatitis (INP), percutaneous catheter drainage (PCD) is now widely acknowledged as the initial intervention in a step-up approach, followed, if necessary, by minimally invasive necrosectomy or even open pancreatic necrosectomy. However, an overemphasis on PCD may cause a patient’s condition to deteriorate, leading to missed surgical opportunities or even death. This study aimed to develop a simple and convenient scoring tool for assessing the need for surgery in INP patients who received PCD procedures. MethodsIn an observational study conducted between April 2015 and December 2020, PCD was utilized as the initial step to treat 143 consecutive INP patients. A surgical necrosectomy was performed when the patient failed to respond. Risk factors of PCD failure (i.e., need for surgical necrosectomy) were identified by multivariate logistic regression models. An integer-based risk scoring tool was developed using the β coefficients derived from the logistic regression model. ResultsIn 62 (43.4%) patients, PCD was successful, while the remaining 81 (56.6%) individuals required subsequent surgical necrosectomy. In the multivariate model, organ failure, percentage of pancreatic necrosis, extrapancreatic necrosis volume, and mean CT density of extrapancreatic necrosis volume were associated with a need for surgical necrosectomy. A predictive scoring tool based on these four factors demonstrated an area under the receiver operating characteristic curve (AUC) of 0.893. Under the scoring tool, a total score of 4 or more indicates a high possibility of surgical necrosectomy being required (at least 80%). Using the coordinates of the receiver operating characteristic curve (ROC), the sensitivity and specificity at this threshold are 0.802 and 0.903, respectively. ConclusionsA risk score model integrating organ failure, percentage of pancreatic necrosis, extrapancreatic necrosis volume, and mean CT density of extrapancreatic necrosis volume can identify INP patients at high risk for necrosectomy. The straightforward risk assessment tool assists clinicians in stratifying INP patients and making more judicious medical decisions.

The estimation of coronary artery calcium thickness by computed tomography angiography based on optical coherence tomography measurements.

Optical coherence tomography (OCT) is recommended to be the most appropriate modality in assessing calcium thickness, however, it has limitations associated with infrared attenuation. Although coronary computed tomography angiography (CCTA) detects calcification, it has low resolution and hence not recommended to measure the calcium size. The aim of this study was to devise a simple algorithm to estimate calcium thickness based on the CCTA image. A total of 68 patients who had CCTA for suspected coronary artery disease and subsequently went on to have OCT were included in the study. 238 lesions of them divided into derivation and validation dataset at 2:1 ratio (47 patients with 159 lesions and 21 with 79, respectively) were analyzed. A new method was developed to estimate calcium thickness from the maximum CT density within the calcification and compared with calcium thickness measured by OCT. Maximum Calcium density and measured calcium-border CT density had a good correlation with a linear equation of y = 0.58x + 201 (r = 0.892, 95% CI 0.855-0.919, p < 0.001). The estimated calcium thickness derived from this equation showed strong agreement with measured calcium thickness in validation and derivation dataset (r2 = 0.481 and 0.527, 95% CI 0.609-0.842 and 0.497-0.782, p < 0.001 in both, respectively), more accurate than the estimation by full width at half maximum and inflection point method. In conclusion, this novel method provided the estimation of calcium thickness more accurately than conventional methods.

Cortical Laminar Necrosis: Imaging Features and Etiological Oorientation

Cortical laminar necrosis corresponds to neuronal ischemic remodeling with gliosis and accumulation of lipid-rich macrophages secondary to various etiologies: hypoxia, prolonged arterial hypotension, hypoglycemia, status epilepticus or arrest. Diffusion and T2 (FLAIR) show cortical and basal ganglia hypersignal from the first 24 hours. T1 shows cerebral edema during the first two weeks and a characteristic spontaneous cortical and basal ganglia hypersignal delayed and transient (3rd week). On T2*, the cortical lesions do not show any asignal, which makes it possible to differentiate them from a hemorrhagic transformation. Cortical contrast can be observed from the first weeks and for several months (up to 9 months in case of focal ischemia) and translates a rupture of the blood-brain barrier. In CT, hypodense and hyperdense gyriform density abnormalities are seen depending on the time.

Association between coronary inflammation measured by FAT attenuation index and CT features of atheromatous plaque vulnerability

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This research has been funded by the research grant Intel-FAT, proposal registration code PN-III-P4-ID-PCE-2020-2861, contract number PCE 206/2021, Project funded by the European Union and the Government of Romania through the Ministry of European Funds, and the Doctoral School of the “George Emil Palade” University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, Romania. Background Coronary computed tomography angiography (CCTA) is a rapidly evolving tool for the assessment of coronary artery disease (CAD), being able to characterise not only the degree of coronary artery stenosis but also the presence and severity of coronary plaque vulnerability. Fat attenuation index (FAI) is a recently developed marker of coronary inflammation, based on the gradient of CT density at the level of pericoronary fat. Purpose The aim of our study is to investigate the correlation between (1) coronary inflammation as assessed by FAI score, and (2) vulnerability degree of atheromatous coronary plaques, as assesses by presence and severity of CT features of vulnerability at the level of coronary plaques. Methods A total of 54 patients who underwent 128-slice CCTA for chest pain, and having at least one vulnerable coronary plaque, were enrolled in the study. Vulnerable plaques were defined as plaques showing at least one of the following on CT scan: low attenuation plaque, napkin-ring sign, spotty calcifications, or positive remodeling. In total, 114 vulnerable plaques were identified and analyzed using the advanced via Syngo.via Frontier software. FAI score was determined using the FAI technology patented by Caristo. Results The FAI score of coronary inflamamtion was significantly correlated with the total plaque volume at the level of left anterior descendent artery (LAD) (p = 0,01), respectively with the calcified plaque volume at the level of the circumflex artery (p = 0,02). Receiver operating characteristic (ROC) analysis for the correlation between the FAI score and the presence of the Napkin Ring Sign (NRS) showed a significant correlation for plaques located on LAD (AUC 0,729; 95%CI 0,585 – 0,845; p = 0,01), and lefty circumflex artery (AUC 0,745; 95%CI 0,601–0,859; p = 0,032), but not for the right coronary artery (AUC 0,636; 95%CI 0,487–0,767; p = 0,25). Furthermore, the ROC analysis identified a good correlation between the FAI score and the presence of spotty calcification or positive coronary remodeling (AUC 0,777, p = 0,0004, respectively AUC 0,717, p = 0,0081). Conclusion Coronary inflammation measured by FAT attenuation index is significantly correlated with the presence of CT vulnerability features in the coronary tree.

Virtopsy visualisation: Mixed data gradient model for more accurate thin bone visualization in 3D rendering

Conventional 3D rendering methods of computed tomography (CT) as well as post-mortem data CT (PMCT) sometimes do not seem to be authentic enough, especially for relatively thin bones. This can be a problem when imaging intact anatomy and considering fractures of the facial or temporal bones, where defects or holes may be visualized instead of thin bone structures. The technical aspect of this is that all currently used visualization methods (volume rendering, cinematic rendering and particle tracing, shaded surfaces and iso-surfaces) are defined by a CT-density threshold, whereas the user at least implicitly expects the bone to have a certain minimum density CT. However, some bone regions, typically those with relatively thin bone, do not meet these expectations, and lowering the threshold for visualization then results in all sorts of non-bone tissue being seen in the rendered images. To provide a more authentic PMCT visualization of bone, we identified a mixed data gradient model that improves the data from CT by increasing the CT density of low-density bone regions (but not of non-bone tissues). That delivers more satisfactory results for otherwise unmodified volume rendering. As pre-processing before 3D rendering, both hard and soft kernel data are used to obtain a 3D density map, a grayscale co-occurrence matrix is determined using a 3x3x3 kernel as the 3D gradient map, and these are then combined to obtain the final gradient model for mixed data.

Elastic Modulus and Its Relation to Apparent Mineral Density in Juvenile Equine Bones of the Lower Limb.

Density-modulus relationships are necessary to develop finite element models of bones that may be used to evaluate local tissue response to different physical activities. It is unknown if juvenile equine trabecular bone may be described by the same density-modulus as adult equine bone, and how the density-modulus relationship varies with anatomical location and loading direction. To answer these questions, trabecular bone cores from the third metacarpal (MC3) and proximal phalanx (P1) bones of juvenile horses (age <1 yr) were machined in the longitudinal (n = 134) and transverse (n = 90) directions and mechanically tested in compression. Elastic modulus was related to apparent computed tomography density of each sample using power law regressions. We found that density-modulus relationships for juvenile equine trabecular bone were significantly different for each anatomical location (MC3 versus P1) and orientation (longitudinal versus transverse). Use of the incorrect density-modulus relationship resulted in increased root mean squared percent error of the modulus prediction by 8-17%. When our juvenile density-modulus relationship was compared to one of an equivalent location in adult horses, the adult relationship resulted in an approximately 80% increase in error of the modulus prediction. Moving forward, more accurate models of young bone can be developed and used to evaluate potential exercise regimens designed to encourage bone adaptation.

Peritumoral Adipose Tissue Density Predicts the Malignancy in cT1 Renal Masses.

Not only the frequency of surgery for small renal masses has increased secondary to the improvements and frequent use of imaging techniques but also the frequency of detection of benign lesions in nephrectomy specimens has increased as well. We aimed to assess the predictive value of computed tomography density of perirenal adipose tissue and peritumoral adipose tissue in distinguishing between benign and malignant renal masses. The current study included 116 patients who underwent nephrectomy for renal masses between January 2015 and December 2020. Clinicodemographic and preoperative computed tomography features and final pathological findings of the patients were recorded. According to the final pathological results, the patients were divided into 2 groups benign (n = 32) and malignant (n = 84). Groups were compared statistically in terms of perirenal adipose tissue and peritumoral adipose tissue density. The median tumor size was 5.00 cm. The rate of benign tumors was higher in female patients (P = .005). The median peritumoral adipose tissue density among cT1 and cT1a tumors was higher in the malignant group (P < .001, for each). At a cutoff value of 97.50 Hounsfield Units, the peritumoral adipose tissue density had a sensitivity of 83.0% and a specificity of 79.2% for predicting the presence of malignant tumors in ≤7 cm renal masses. Using a cutoff value of -97.50 Hounsfield Units, the peritumoral adipose tissue density had a sensitivity of 88.9% and a specificity of 83.3% for predicting the presence of malignant tumors in ≤4 cm renal masses. The peritumoral adipose tissue density in the preoperative computed tomography images predicts the malignancy in cT1 renal masses.

Application of the microtomography technique in density studies of prehistoric and historical human skeletal materials

AbstractBone density is not a standard parameter examined during anthropological analysis, although researchers increasingly attempt to assess bone mineral density (BMD) in prehistoric populations. Computed tomography (CT) has great potential in this type of research. Micro CT is a precise and universal tool for bone density measurement based on CT value (attenuation factor of the X‐rays at a given point in space). Thirty‐four archaeological human radial bone samples from four chronologically and geographically different sites from southern Poland were examined here. Real BMD was measured (mass/volume) and compared with BMD obtained with the use of CT value results to verify correlation between those two parameters. The micro CT density values were estimated with an uncertainty of less than 0.03 g/cm3 in more than 75% of samples. This method does not require any special sample preparation and any substitute of soft tissues. This technique enables measurement of the cortical and cancellous bone separately in even partial or damaged bones.

Muscle quality determined by computed tomography predicts short-term and long-term survival after liver transplantation

Sarcopenia, the loss of muscle mass and quality, contributes to worse clinical outcome in patients with end-stage liver disease, but its impact on short- and long-term survival remains insufficiently understood. The aim of this study was to evaluate the development of computed tomography (CT) muscle parameters and their impact on short-term and long-term survival after liver transplantation. This retrospective study included patients with liver transplantation between 2011 and 2015 and a pre-transplant CT scan. Clinical characteristics, CT muscle mass and density were assessed pre-transplant, and in available CT scans at short-term (11 months) and long-term follow-up (56 months). Overall, 93/152 (61%) patients (109 male, 55 ± 10 years) suffered from sarcopenia pre-transplant. In short- (n = 50) and long-term follow-up (n = 52) the muscle mass (− 2.65 cm2/m2 95% CI [− 4.52, − 0.77], p = 0.007; − 2.96 cm2/m2 [− 4.7, − 1.23], p = 0.001, respectively), and muscle density (− 3 HU [− 6, − 1], p = 0.007; − 2 HU [− 4, 0], p = 0.069) decreased. Myosteatosis was associated with a higher post-transplant mortality (survival probability: 3 months 72% vs. 95%, 1 year 63% vs. 90%, 5 years 54% vs. 84%, p = 0.001), while muscle mass was not. In conclusion, muscle mass and quality did not improve after transplant. Muscle quality predicts short- and long-term survival and could help to identify a patient’s risk profile.

Palaeoenvironmental and palaeoclimatic inferences based on X-ray computer tomography: a case study of alkaline lake deposits in Hungary

Widely distributed freshwater carbonate sediments, i.e., limestone, dolomitic limestone and dolomite, developed in inter-dune alkaline ponds of the Danube-Tisza Interfluve in the centre of the Carpathian Basin during the Holocene. The key parameters that determine the formation of any given type of carbonate mineral (calcite, dolomite) are temperature, evaporation rate, pH and ion concentrations, in addition to CO2 absorption by aquatic plants. CT analysis is capable of recording small-scale density variations attributable to compositional differences of sedimentary rocks. As the type and proportion of rock-forming minerals and other components is an artifact of past environmental and climatic conditions, CT values may act as potential palaeoenvironmental proxies. The present study compares variations in rock-forming components obtained for freshwater carbonates utilizing the CT method with already available geochemical and palaeoecological proxy data. Variations in molluscan ecology and isotope geochemistry, sedimentation times and CTbased rock density values all indicate the relevance of millennial-scale, climate-driven changes in carbonate formation. As previously observed, the emergence of colder conditions in the North Atlantic, which resulted in increased cyclonic activity and heavier rainfall in western Europe and the Danube watershed area between 10.3 and 9.3 kyr cal BP, resulted in the emergence of humid conditions favouring a rise in the groundwater table at our site and precipitation of calcite from pore waters as opposed to high-magnesium calcite. This is clearly reflected in a negative shift in CT density values in our dated rock samples.

Noncontrast Computed Tomography Markers Associated with Hematoma Expansion: Analysis of a Multicenter Retrospective Study

Hematoma expansion (HE) is a significant predictor of poor outcomes in patients with intracerebral hemorrhage (ICH). Non-contrast computed tomography (NCCT) markers in ICH are promising predictors of HE. We aimed to determine the association of the NCCT markers with HE by using different temporal HE definitions. We utilized Risa-MIS-ICH trial data (risk stratification and minimally invasive surgery in acute intracerebral hemorrhage). We defined four HE types based on the time to baseline CT (BCT) and the time to follow-up CT (FCT). Hematoma volume was measured by software with a semi-automatic edge detection tool. HE was defined as a follow-up CT hematoma volume increase of >6 mL or a 33% hematoma volume increase relative to the baseline CT. Multivariable regression analyses were used to determine the HE parameters. The prediction potential of indicators for HE was evaluated using receiver-operating characteristic analysis. The study enrolled 158 patients in total. The time to baseline CT was independently associated with HE in one type (odds ratio (OR) 0.234, 95% confidence interval (CI) 0.077-0.712, p = 0.011), and the blend sign was independently associated with HE in two types (OR, 6.203-6.985, both p < 0.05). Heterogeneous density was independently associated with HE in all types (OR, 6.465-88.445, all p < 0.05) and was the optimal type for prediction, with an area under the curve of 0.674 (p = 0.004), a sensitivity of 38.9%, and specificity of 96.0%. In specific subtypes, the time to baseline CT, blend sign, and heterogeneous density were independently associated with HE. The association between NCCT markers and HE is influenced by the temporal definition of HE. Heterogeneous density is a stable and robust predictor of HE in different subtypes of hematoma expansion.

CT-based three-dimensional invasiveness analysis of adenocarcinoma presenting as pure ground-glass nodules.

We invest computed tomography (CT) image differences between non-invasive adenocarcinomas (NIAs) and invasive adenocarcinomas (IAs) presenting as pure ground glass nodules (GGNs). From 2013 to 2019, 48 pure GGNs were surgically resected in 45 patients. Of these, 40 were pathologically diagnosed as non-small cell lung cancers (NSCLCs). We assessed them using the Synapse Vincent (Fujifilm Co., Ltd., Tokyo, Japan) three-dimensional (3D) analysis system; we drew histograms of the CT densities. We calculated the maximum, minimum, means, and standard deviations of the densities. The proportions of GGNs of high CT density were compared between the two groups. The diagnostic performance was investigated via receiver operating curve (ROC) analysis. Of the 40 pure GGNs, 20 were NIAs (4 adenocarcinomas in situ and 16 minimally IAs) and 20 IAs. Significant correlations were evident between histological invasiveness and the maximum and mean CT densities and the standard deviation. Neither the nodule volume nor the minimum CT density significantly predicted invasiveness. A CT volume density proportion >-300 Hounsfield units optimally predicted the invasiveness of pure GGNs; the cutoff was 5.41% with a sensitivity of 85% and a specificity of 95%. CT density reflected the invasiveness of pure GGNs. A CT volume proportion density >-300 Hounsfield units may significantly predict histological invasiveness.

A comparison of computed tomography imaging with histopathology in the sensitivity and correlation of evaluating coronary arterial calcification.

The sensitivity and correlation of coronary computed tomography angiography (CTA) as compared with histopathology are unknown in evaluating coronary arterial calcification. In this study, we retrospectively evaluated qualitatively and quantitatively the sensitivity and correlation of coronary CTA compared with histopathology in assessing coronary arterial calcification. This study was conducted on 12 randomly selected cadavers aged over 40 years at the time of death, and 53 segments of coronary arteries from these 12 cadavers were obtained from the Human Anatomy Laboratory of Tianjin Medical University. The artery segments were scanned using contrasted-enhanced dual-source computed tomography (DSCT) with an axial slice thickness of 0.6 mm. Coronary artery calcification in a coronary segment was defined as the presence of 1 or more voxels with a CT density >130 Hounsfield units. According to the arc of calcification in the cross section of the coronary artery wall, calcified plaques were divided into three categories: mild, moderate, and severe calcification. The coronary artery stenosis caused by calcified plaque was observed and calculated with multiplanar reconstruction (MPR), maximum density projection, volume rendering (VR), and cross-sectional reconstruction. After CT enhancement scanning, the coronary artery specimens were cut into 4-mm long segments and embedded in paraffin for pathological staining. Pathological classification and coronary artery stenosis measured with pathological analysis were used as comparison criteria. Histopathology detected 69 Vb-type plaques, while DSCT detected 57 calcified plaques. The sensitivity of CT for detecting mild, moderate, and severe calcified plaques were 88.3% [95% confidence interval (CI): 74.1-95.6%], 100% (95% CI: 69.8-100%), and 100% (95% CI: 73.2-100%), respectively. DSCT had a significant (P<0.001) correlation with histopathology in quantifying coronary artery stenosis caused by mild, moderate, and severe calcified plaques (R2=0.9278, R2=0.9158, R2=0.7923, respectively). Compared with histopathology, DSCT overestimated coronary artery stenosis caused by mild, moderate, and severe calcified plaques (3.2%±2.0%, 4.9%±4.7%, and 14.7%±8.2%, respectively; P<0.05). DSCT contrast enhancement scanning can detect and characterize coronary artery calcification with a good correlation with histopathologic quantification of coronary artery stenosis caused by different types of calcified plaques, even though coronary CTA may overestimate the stenosis.

Multimodality imaging to identify lipid-rich coronary plaques and predict periprocedural myocardial injury: Association between near-infrared spectroscopy and coronary computed tomography angiography.

This study compares the efficacy of coronary computed tomography angiography (CCTA) and near-infrared spectroscopy intravascular ultrasound (NIRS-IVUS) in patients with significant coronary stenosis for predicting periprocedural myocardial injury during percutaneous coronary intervention (PCI). We prospectively enrolled 107 patients who underwent CCTA before PCI and performed NIRS-IVUS during PCI. Based on the maximal lipid core burden index for any 4-mm longitudinal segments (maxLCBI4mm) in the culprit lesion, we divided the patients into two groups: lipid-rich plaque (LRP) group (maxLCBI4mm ≥ 400; n = 48) and no-LRP group (maxLCBI4mm < 400; n = 59). Periprocedural myocardial injury was a postprocedural cardiac troponin T (cTnT) elevation of ≥5 times the upper limit of normal. The LRP group had a significantly higher cTnT (p = 0.026), lower CT density (p < 0.001), larger percentage atheroma volume (PAV) by NIRS-IVUS (p = 0.036), and larger remodeling index measured by both CCTA (p = 0.020) and NIRS-IVUS (p < 0.001). A significant negative linear correlation was found between maxLCBI4mm and CT density (rho = -0.552, p < 0.001). Multivariable logistic regression analysis identified maxLCBI4mm [odds ratio (OR): 1.006, p = 0.003] and PAV (OR: 1.125, p = 0.014) as independent predictors of periprocedural myocardial injury, while CT density was not an independent predictor (OR: 0.991, p = 0.22). CCTA and NIRS-IVUS correlated well to identify LRP in culprit lesions. However, NIRS-IVUS was more competent in predicting the risk of periprocedural myocardial injury.