Multiscale drainage dynamics with Haines jumps monitored by stroboscopic 4D X-ray microscopy.

Slow multiphase flow in porous media is intriguing because its underlying dynamics is almost deterministic, yet depends on a hierarchy of spatiotemporal processes. There has been great progress in the experimental study of such multiphase flows, but three-dimensional (3D) microscopy methods probing the pore-scale fluid dynamics with millisecond resolution have been lacking. Yet, it is precisely at these length and time scales that the crucial pore-filling events known as Haines jumps take place. Here, we report four-dimensional (4D) (3D + time) observations of multiphase flow in a consolidated porous medium as captured in situ by stroboscopic X-ray micro-tomography. With a total duration of 6.5 s and 2 kHz frame rate, our experiments provide unprecedented access to the multiscale liquid dynamics. Our tomography strategy relies on the fact that Haines jumps, although irregularly spaced in time, are almost deterministic, and therefore repeatable during imbibition-drainage cycling. We studied the time-dependent flow pattern in a porous medium consisting of sintered glass shards. Exploiting the repeatability, we could combine the radiographic projections recorded under different angles during successive cycles into a 3D movie, allowing us to reconstruct pore-scale events, such as Haines jumps, with a spatiotemporal resolution that is two orders of magnitude higher than was hitherto possible. This high resolution allows us to explore the detailed interfacial dynamics during drainage, including fluid-front displacements and velocities. Our experimental approach opens the way to the study of fast, yet deterministic mesoscopic processes also other than flow in porous media.

X-ray 3D imaging-based microunderstanding of granular mixtures: Stiffness enhancement by adding small fractions of soft particles.

This research focuses on performing ultrasound propagation measurements and micro-X-ray computed tomography (µXRCT) imaging on prestressed granular packings prepared with biphasic mixtures of monodisperse glass and rubber particles at different compositions/fractions. Ultrasound experiments employing piezoelectric transducers, mounted in an oedometric cell (complementing earlier triaxial cell experiments), are used to excite and detect longitudinal ultrasound waves through randomly prepared mixtures of monodisperse stiff/soft particles. While the fraction of the soft particles is increasing linearly from zero, the effective macroscopic stiffness of the granular packings transits nonlinearly and nonmonotonically toward the soft limit, remarkably via an interesting stiffer regime for small rubber fractions between 0.1 ≲ ν ≲ 0.2. The contact network of dense packings, as accessed from µXRCT, plays a key role in understanding this phenomenon, considering the structure of the network, the chain length, the grain contacts, and the particle coordination. While the maximum stiffness is due to surprisingly shortened chains, the sudden drop in elastic stiffness of the mixture packings, at ν ≈ 0.4, is associated with chains of particles that include both glass and rubber particles (soft chains); for ν ≲ 0.3, the dominant chains include only glass particles (hard chains). At the drop, ν ≈ 0.4, the coordination number of glass and rubber networks is approximately four and three, respectively, i.e., neither of the networks are jammed, and the chains need to include particles from another species to propagate information.

Bronchial tree of the human embryo: Examination based on a mammalian model.

The symmetry of the right and left bronchi, proposed in a previous comparative anatomical study as the basic model of the mammalian bronchial tree, was examined to determine if it applied to the embryonic human bronchial tree. Imaging data of 41 human embryo specimens at Carnegie stages (CS) 16-23 (equivalent to 6-8 weeks after fertilization) belonging to the Kyoto collection were obtained using phase-contrast X-ray computed tomography. Three-dimensional bronchial trees were then reconstructed from these images. Bronchi branching from both main bronchi were labeled as dorsal, ventral, medial, or lateral systems based on the branching position with numbering starting cranially. The length from the tracheal bifurcation to the branching point of the labeled bronchus was measured, and the right-to-left ratio of the same labeled bronchus in both lungs was calculated. In both lungs, the human embryonic bronchial tree showed symmetry with an alternating pattern of dorsal and lateral systems up to segmental bronchus B9 as the basic shape, with a more peripheral variation. This pattern is similar to that described in adult human lungs. Bronchial length increased with the CS in all labeled bronchi, whereas the right-to-left ratio was constant at approximately 1.0. The data demonstrated that the prototype of the human adult bronchial branching structure is formed and maintained in the embryonic stage. The morphology and branching position of all lobar bronchi and B6, B8, B9, and the subsegmental bronchus of B10 may be genetically determined. On the other hand, no common structures between individual embryos were found in the peripheral branches after the subsegmental bronchus of B10, suggesting that branch formation in this region is influenced more by environmental factors than by genetic factors.

Morphogenesis of the pulmonary vein and left atrial appendage in human embryos and early fetuses.

The left atrium wall has several origins, including the body, appendage, septum, atrial-ventricular canal, posterior wall, and venous component. Here, we describe the morphogenesis of left atrium based on high-resolution imaging (phase-contrast X-ray computed tomography and magnetic resonance imaging). Twenty-three human embryos and 19 fetuses were selected for this study. Three-dimensional cardiac images were reconstructed, and the pulmonary veins and left atrium, including the left atrial appendage, were evaluated morphologically and quantitatively. The positions of the pericardial reflections were used as landmarks for the border of the pericardial cavity. The common pulmonary vein was observed in three specimens at Carnegie stages 17-18. The pericardium was detected at the four pulmonary veins (left superior, left inferior, right superior, and right inferior pulmonary veins) at one specimen at Carnegie stage 18 and all larger specimens, except the four samples. Our results suggest that the position of the pericardial reflections was determined at two pulmonary veins (right and left pulmonary vein) and four pulmonary veins almost simultaneously when the dorsal mesocardial connection between the embryo and heart regressed. The magnetic resonance images and reconstructed heart cavity images confirmed that the left atrium folds were present at the junction between the body and venous component. Three-dimensional reconstruction showed that the four pulmonary veins entered the dorsal left atrium tangentially from the lateral to the medial direction. More specifically, the right pulmonary veins entered at a greater angle than the left pulmonary veins. The distance between the superior and inferior pulmonary veins was shorter than that between the left and right pulmonary veins. Three-dimensional reconstruction showed that the venous component increased proportionally with growth. No noticeable differences in discrimination between the right and left parts of the venous component emerged, while the junction between the venous component and body gradually became inconspicuous but was still recognizable by the end of the observed early fetal period. The left superior pulmonary vein had the smallest cross-sectional area and most flattened shape, whereas the other three were similar in area and shape. The left atrial appendage had a large volume in the center and extended to the periphery as a lobe-like structure. The left atrial appendage orifice increased in the area and tended to become flatter with growth. The whole left atrium volume^(1/3) increased almost proportionally with growth, parallel to the whole heart volume. This study provided a three-dimensional and quantitative description of the developmental process of the left atrium, comprising the venous component and left atrial appendage formation, from the late embryonic to the early fetal stages.

Evaluation of computed tomography in the diagnosis of ultrasound-proven diaphragm dysfunction.

INTRODUCTION: Computed tomography (CT) is routinely employed on the evaluation of dyspnea, yet limited data exist on its assessment of diaphragmatic muscle. This study aimed to determine the capability of CT in identifying structural changes in the diaphragm among patients with ultrasound-confirmed diaphragmatic dysfunction. METHODS: Diaphragmatic ultrasounds conducted between 2018 and 2021 at our center in Marseille, France, were retrospectively collected. Diaphragmatic pillars were measured on CT scans at the L1 level and the celiac artery. Additionally, the difference in height between the two diaphragmatic domes in both diaphragmatic dysfunction cases and controls was measured and compared. RESULTS: A total of 65 patients were included, comprising 24 with diaphragmatic paralysis, 13 with diaphragmatic weakness, and 28 controls. In the case group (paralysis and weakness) with left dysfunctions (n = 24), the CT thickness of the pillars at the level of L1 and the celiac artery was significantly thinner compared with controls (2.0 mm vs. 7.4 mm and 1.8 mm vs. 3.1 mm, p < 0.001 respectively). Significantly different values were observed for paralysis (but not weakness) in the right dysfunction subgroup (n = 15) (2.6 mm vs. 7.4 mm and 2.2 mm vs. 3.8 mm, p < 0.001 respectively, for paralysis vs. controls). Regardless of the side of dysfunction, a significant difference in diaphragmatic height was observed between cases and controls (7.70 cm vs. 1.16 cm and 5.51 cm vs. 1.16 cm, p < 0.001 for right and left dysfunctions, respectively). Threshold values determined through ROC curve analyses for height differences between the two diaphragmatic domes, indicative of paralysis or weakness in the right dysfunctions, were 4.44 cm and 3.51 cm, respectively. Similarly for left dysfunctions, the thresholds were 2.70 cm and 2.48 cm, respectively, demonstrating good performance (aera under the curve of 1.00, 1.00, 0.98, and 0.79, respectively). CONCLUSION: In cases of left diaphragmatic dysfunction, as well as in paralysis associated with right diaphragmatic dysfunction, CT revealed thinner pillars. Additionally, a notable increase in the difference in diaphragmatic height demonstrated a strong potential to identify diaphragmatic dysfunction, with specific threshold values.

Visualizing the structural and chemical heterogeneity of fruit and vegetables using advanced imaging techniques: fundamentals, instrumental aspects, applications and future perspectives.

Fruit and vegetables (F&V) are vastly complicated products with highly diverse chemical and structural characteristics. Advanced imaging techniques either combine imaging with spectral information or can provide excellent tissue penetration, and enable the possibility to target, visualize and even qualify the chemical and physical (structural) heterogeneity within F&V. In this review, visible and/or near infrared hyperspectral imaging, Fourier transform infrared microspectroscopic imaging, Raman imaging, X-ray and magnetic resonance imaging to reveal chemical and structural information in a spatial context of F&V at the macro- (entire products), meso- (tissues), and micro- (individual cells) scales are comprehensively summarized. In addition, their basic concepts and operational procedures, particularly sample preparation and instrumental parameter adjustments, are addressed. Finally, future challenges and perspectives of these techniques are put forward. These imaging techniques are powerful tools to assess the biochemical and structural heterogeneity of F&V. Cost reduction, sensor fusion and data sharing platforms are future trends. More emphasis on aspects of knowledge and extension at the level of academia and research, especially on how to select techniques, choose operational parameters and prepare samples, are important to overcome barriers for the wider adoption of these techniques to improve the evaluation of F&V quality.

Hyperspectral imaging reveals chemical heterogeneity of fruit and vegetables.Imaging techniques provide spatial insights in fruit and vegetables at multiple scales.Future trends are cost reduction, sensor fusion and data sharing.Instrumental adjustment and sample preparation should receive more attention.

Feasibility of virtual non-iodine coronary calcium scoring on dual source photon-counting coronary CT angiography: a dynamic phantom study.

BACKGROUND: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans. METHODS: In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60-75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI. RESULTS: For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671-0.853). CONCLUSION: In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial. CLINICAL RELEVANCE STATEMENT: Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice. KEY POINTS: Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates. Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed. Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.

Survey of CT radiation doses and iodinated contrast medium administration: an international multicentric study.

OBJECTIVE: To assess the relationship between intravenous iodinated contrast media (ICM) administration usage and radiation doses for contrast-enhanced (CE) CT of head, chest, and abdomen-pelvis (AP) in international, multicenter settings. METHODS: Our international (n = 16 countries), multicenter (n = 43 sites), and cross-sectional (ConRad) study had two parts. Part 1: Redcap survey with questions on information related to CT and ICM manufacturer/brand and respective protocols. Part 2: Information on 3,258 patients (18-96 years; M:F 1654:1604) who underwent CECT for a routine head (n = 456), chest (n = 528), AP (n = 599), head CT angiography (n = 539), pulmonary embolism (n = 599), and liver CT examinations (n = 537) at 43 sites across five continents. The following information was recorded: hospital name, patient age, gender, body mass index [BMI], clinical indications, scan parameters (number of scan phases, kV), IV-contrast information (concentration, volume, flow rate, and delay), and dose indices (CTDIvol and DLP). RESULTS: Most routine chest (58.4%) and AP (68.7%) CECT exams were performed with 2-4 scan phases with fixed scan delay (chest 71.4%; AP 79.8%, liver CECT 50.7%) following ICM administration. Most sites did not change kV across different patients and scan phases; most CECT protocols were performed at 120-140 kV (83%, 1979/2685). There were no significant differences between radiation doses for non-contrast (CTDIvol 24 [16-30] mGy; DLP 633 [414-702] mGy·cm) and post-contrast phases (22 [19-27] mGy; 648 [392-694] mGy·cm) (p = 0.142). Sites that used bolus tracking for chest and AP CECT had lower CTDIvol than sites with fixed scan delays (p < 0.001). There was no correlation between BMI and CTDIvol (r2 ≤ - 0.1 to 0.1, p = 0.931). CONCLUSION: Our study demonstrates up to ten-fold variability in ICM injection protocols and radiation doses across different CT protocols. The study emphasizes the need for optimizing CT scanning and contrast protocols to reduce unnecessary contrast and radiation exposure to patients. CLINICAL RELEVANCE STATEMENT: The wide variability and lack of standardization of ICM media and radiation doses in CT protocols suggest the need for education and optimization of contrast usage and scan factors for optimizing image quality in CECT. KEY POINTS: There is a lack of patient-centric CT protocol optimization taking into consideration mainly patients' size. There is a lack of correlation between ICM volume and CT radiation dose across CT protocol. A ten-fold variation in iodine-load for the same CT protocol in sites suggests a lack of standardization.

Performance of Lung-RADS in different target populations: a systematic review and meta-analysis.

OBJECTIVES: Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations. METHODS: We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses. RESULTS: A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90-0.99) and pooled specificity was 0.90 (95% CI: 0.87-0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92-0.99] vs. 0.84 [95% CI: 0.50-0.96]) and lower specificity (0.87 [95% CI: 0.85-0.88] vs. 0.95 (95% CI: 0.92-0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91-0.99] vs. 0.91 [95% CI: 0.67-0.98]) and lower specificity (0.88 [95% CI: 0.85-0.90] vs. 0.93 [95% CI: 0.88-0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83-0.96) and specificity was 0.81 (95% CI: 0.67-0.90). CONCLUSION: Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence. CLINICAL RELEVANCE STATEMENT: Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence. KEY POINTS: • High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations.

Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics.

OBJECTIVES: In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. METHODS: Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. RESULTS: This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset's 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson's correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. CONCLUSIONS: Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. CLINICAL RELEVANCE STATEMENT: The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. KEY POINTS: • Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. • Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. • Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase.

Automatic personal identification using a single CT image.

OBJECTIVES: Computer vision (CV) mimics human vision, enabling computers to automatically compare radiological images from recent examinations with a large image database for unique identification, crucial in emergency scenarios involving unknown patients or deceased individuals. This study aims to extend a CV-based personal identification method from orthopantomograms (OPGs) to computed tomography (CT) examinations using single CT slices. METHODS: The study analyzed 819 cranial computed tomography (CCT) examinations from 722 individuals, focusing on single CT slices from six anatomical regions to explore their potential for CV-based personal identification in 69 procedures. CV automatically identifies and describes interesting features in images, which can be recognized in a reference image and then designated as matching points. In this study, the number of matching points was used as an indicator for identification. RESULTS: Across six different regions, identification rates ranged from 41/69 (59%) to 69/69 (100%) across over 700 possible identities. Comparison of images from the same individual achieved higher matching points, averaging 6.32 ± 0.52% (100% represents the maximum possible matching points), while images of different individuals averaged 0.94 ± 0.15%. Reliable matching points are found in the teeth, maxilla, cervical spine, skull bones, and paranasal sinuses, with the maxillary sinuses and ethmoidal cells being particularly suitable for identification due to their abundant matching points. CONCLUSION: Unambiguous identification of individuals based on a single CT slice is achievable, with maxillary sinus CT slices showing the highest identification rates. However, metal artifacts, especially from dental prosthetics, and various head positions can hinder identification. CLINICAL RELEVANCE STATEMENT: Radiology possesses a multitude of reference images for a CV database, facilitating automated CV-based personal identification in emergency examinations or cases involving unknown deceased individuals. This enhances patient care and communication with relatives by granting access to medical history. KEY POINTS: Unknown individuals in radiology or forensics pose challenges, addressed through automatic CV-based identification methods. A single CT slice highlighting the maxillary sinuses is particularly effective for personal identification. Radiology plays a pivotal role in automated personal identification by leveraging its extensive image database.

ESR Essentials: characterisation and staging of adnexal masses with MRI and CT-practice recommendations by ESUR.

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery. This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities. KEY POINTS: MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians. CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery. Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.

Prevalence and clinical implications of coronary artery calcium scoring on non-gated thoracic computed tomography: a systematic review and meta-analysis.

OBJECTIVES: Coronary artery calcifications (CACs) indicate the presence of coronary artery disease. CAC can be found on thoracic computed tomography (CT) conducted for non-cardiac reasons. This systematic review and meta-analysis of non-gated thoracic CT aims to assess the clinical impact and prevalence of CAC. METHODS: Online databases were searched for articles assessing prevalence, demographic characteristics, accuracy and prognosis of incidental CAC on non-gated thoracic CT. Meta-analysis was performed using a random effects model. RESULTS: A total of 108 studies (113,406 patients) were included (38% female). Prevalence of CAC ranged from 2.7 to 100% (pooled prevalence 52%, 95% confidence interval [CI] 46-58%). Patients with CAC were older (pooled standardised mean difference 0.88, 95% CI 0.65-1.11, p < 0.001), and more likely to be male (pooled odds ratio [OR] 1.95, 95% CI 1.55-2.45, p < 0.001), with diabetes (pooled OR 2.63, 95% CI 1.95-3.54, p < 0.001), hypercholesterolaemia (pooled OR 2.28, 95% CI 1.33-3.93, p < 0.01) and hypertension (pooled OR 3.89, 95% CI 2.26-6.70, p < 0.001), but not higher body mass index or smoking. Non-gated CT assessment of CAC had excellent agreement with electrocardiogram-gated CT (pooled correlation coefficient 0.96, 95% CI 0.92-0.98, p < 0.001). In 51,582 patients, followed-up for 51.6 ± 27.4 months, patients with CAC had increased all cause mortality (pooled relative risk [RR] 2.13, 95% CI 1.57-2.90, p = 0.004) and major adverse cardiovascular events (pooled RR 2.91, 95% CI 2.26-3.93, p < 0.001). When CAC was present on CT, it was reported in between 18.6% and 93% of reports. CONCLUSION: CAC is a common, but underreported, finding on non-gated CT with important prognostic implications. CLINICAL RELEVANCE STATEMENT: Coronary artery calcium is an important prognostic indicator of cardiovascular disease. It can be assessed on non-gated thoracic CT and is a commonly underreported finding. This represents a significant population where there is a potential missed opportunity for lifestyle modification recommendations and preventative therapies. This study aims to highlight the importance of reporting incidental coronary artery calcium on non-gated thoracic CT. KEY POINTS: • Coronary artery calcification is a common finding on non-gated thoracic CT and can be reliably identified compared to gated-CT. • Coronary artery calcification on thoracic CT is associated with an increased risk of all cause mortality and major adverse cardiovascsular events. • Coronary artery calcification is frequently not reported on non-gated thoracic CT.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography.

OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance. METHODS: This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke. RESULTS: Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618). CONCLUSION: ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography. CLINICAL RELEVANCE STATEMENT: In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis. KEY POINTS: • The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Prediction models for differentiating benign from malignant liver lesions based on multiparametric dual-energy non-contrast CT.

OBJECTIVES: To create prediction models (PMs) for distinguishing between benign and malignant liver lesions using quantitative data from dual-energy CT (DECT) without contrast agents. MATERIALS AND METHODS: This retrospective study included patients with liver lesions who underwent DECT, including non-contrast-enhanced scans. Benign lesions included hepatic hemangioma, whereas malignant lesions included hepatocellular carcinoma, metastatic liver cancer, and intrahepatic cholangiocellular carcinoma. Patients were divided into derivation and validation groups. In the derivation group, two radiologists calculated ten multiparametric data using univariate and multivariate logistic regression to generate PMs. In the validation group, two additional radiologists measured the parameters to assess the diagnostic performance of PMs. RESULTS: The study included 121 consecutive patients (mean age 67.4 ± 13.8 years, 80 males), with 97 in the derivation group (25 benign and 72 malignant) and 24 in the validation group (7 benign and 17 malignant). Oversampling increased the benign lesion sample to 75, equalizing the malignant group for building PMs. All parameters were statistically significant in univariate analysis (all p < 0.05), leading to the creation of five PMs in multivariate analysis. The area under the curve for the five PMs of two observers was as follows: PM1 (slope K, blood) = 0.76, 0.74; PM2 (slope K, fat) = 0.55, 0.51; PM3 (effective-Z difference, blood) = 0.75, 0.72; PM4 (slope K, blood, fat) = 0.82, 0.78; and PM5 (slope K, effective-Z difference, blood) = 0.90, 0.87. PM5 yielded the best diagnostic performance. CONCLUSION: Multiparametric non-contrast-enhanced DECT is a highly effective method for distinguishing between liver lesions. CLINICAL RELEVANCE STATEMENT: The utilization of non-contrast-enhanced DECT is extremely useful for distinguishing between benign and malignant liver lesions. This approach enables physicians to plan better treatment strategies, alleviating concerns associated with contrast allergy, contrast-induced nephropathy, radiation exposure, and excessive medical expenses. KEY POINTS: Distinguishing benign from malignant liver lesions with non-contrast-enhanced CT would be desirable. This model, incorporating slope K, effective Z, and blood quantification, distinguished benign from malignant liver lesions. Non-contrast-enhanced DECT has benefits, particularly in patients with an iodine allergy, renal failure, or asthma.

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

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 < 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.

Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning.

BACKGROUND: Radiological age assessment using reference studies is inherently limited in accuracy due to a finite number of assignable skeletal maturation stages. To overcome this limitation, we present a deep learning approach for continuous age assessment based on clavicle ossification in computed tomography (CT). METHODS: Thoracic CT scans were retrospectively collected from the picture archiving and communication system. Individuals aged 15.0 to 30.0 years examined in routine clinical practice were included. All scans were automatically cropped around the medial clavicular epiphyseal cartilages. A deep learning model was trained to predict a person's chronological age based on these scans. Performance was evaluated using mean absolute error (MAE). Model performance was compared to an optimistic human reader performance estimate for an established reference study method. RESULTS: The deep learning model was trained on 4,400 scans of 1,935 patients (training set: mean age = 24.2 years ± 4.0, 1132 female) and evaluated on 300 scans of 300 patients with a balanced age and sex distribution (test set: mean age = 22.5 years ± 4.4, 150 female). Model MAE was 1.65 years, and the highest absolute error was 6.40 years for females and 7.32 years for males. However, performance could be attributed to norm-variants or pathologic disorders. Human reader estimate MAE was 1.84 years and the highest absolute error was 3.40 years for females and 3.78 years for males. CONCLUSIONS: We present a deep learning approach for continuous age predictions using CT volumes highlighting the medial clavicular epiphyseal cartilage with performance comparable to the human reader estimate.

Research on the Development of Methods for Detection of Substandard and Falsified Medicines by Clarifying Their Pharmaceutical Characteristics Using Modern Technology.

The existence of substandard and falsified medicines threatens people's health and causes economic losses as well as a loss of trust in medicines. As the distribution of pharmaceuticals becomes more globalized and the spread of substandard and falsified medicines continues worldwide, pharmaceutical security measures must be strengthened. To eradicate substandard and falsified medicines, our group is conducting fact-finding investigations of medicines distributed in lower middle-income countries (LMICs) and on the Internet. From the perspective of pharmaceutics, such as physical assessment of medicines, we are working to clarify the actual situation and develop methods to detect substandard and falsified medicines. We have collected substandard and falsified medicines distributed in LMICs and on the Internet and performed pharmacopoeial tests, mainly using HPLC, which is a basic analytic method. In addition to quality evaluation, we have evaluated the applicability of various analytic methods, including observation of pharmaceuticals using an electron microscope, Raman scattering analysis, near-IR spectroscopic analysis, chemical imaging, and X-ray computed tomography (CT) to detect substandard and falsified medicines, and we have clarified their limitations. We also developed a small-scale quality screening method using statistical techniques. We are engaged in the development of methods to monitor the distribution of illegal medicines and evolve research in forensic and policy science. These efforts will contribute to the eradication of substandard and falsified medicines. Herein, I describe our experience in the development of detection methods and elucidation of the pharmaceutical status of substandard and falsified medicines using novel technologies.

Bone Mineral Density Derived from Cardiac CT Scans: Using Contrast Enhanced Scans for Opportunistic Screening.

PURPOSE: Osteoporosis is under-diagnosed and often co-exists with other diseases. Very low bone mineral density (BMD) indicates risk of osteoporosis and opportunistic screening for low BMD in CT-scans has been suggested. In a non-contrast enhanced thoracic CT scan, the scan-field-of-view includes vertebrae enabling BMD estimation. However, many CT scans are obtained by administration of contrast material. If the impact of contrast enhancement on BMD measurements could be quantified, considerably more patients are eligible for screening. METHODS: This study investigated the impact of intravenous contrast on thoracic BMD measurements in cardiac CT scans pre- and post-contrast, including different contrast trigger levels of 130 and 180 Hounsfield units (HU). BMD was measured using quantitative CT with asynchronous calibration. RESULTS: In 195 participants undergoing cardiac CT (mean age 57±9 years, 37 % females) contrast increased mean thoracic BMD from 116±33 mg/cm3 (non-enhanced CT) to 130±38 mg/cm3 (contrast-enhanced CT) (p<0.001). Using clinical cut-off values for very low (<80 mg/cm3) and low BMD (<120 mg/cm3) showed that 24 % (47/195 participants) were misclassified when BMD was measured on contrast-enhanced CT-scans. Of the misclassified patients, 6 % (12/195 participants) were categorized as having low BMD despite having very low BMD on the non-enhanced images. Contrast-CT using a higher contrast trigger level showed a significant increase in BMD compared to the lower trigger level (119±32 vs. 135±40 mg/cm3, p<0.01). CONCLUSION: For patients undergoing cardiac CT, using contrast-enhanced images to assess BMD entails substantial overestimation. Contrast protocol trigger levels also affect BMD measurements. Adjusting for these factors is needed before contrast-enhanced images can be used clinically. MINI ABSTRACT: Osteoporosis is under-diagnosed. Contrast-enhanced CT made to examine other diseases might be utilized simultaneously for bone mineral density (BMD) screening. These scans, however, likely entails overestimation of BMD due to the effect of contrast. Adjusting for this effect is needed before contrast-enhanced images can be implemented clinically for BMD screening.

Nomogram for the preoperative prediction of Ki-67 expression and prognosis in stage IA lung adenocarcinoma based on clinical and multi-slice spiral computed tomography features.

OBJECTIVE: This study developed and validated a nomogram utilizing clinical and multi-slice spiral computed tomography (MSCT) features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma. Additionally, we assessed the predictive accuracy of Ki-67 expression levels, as determined by our model, in estimating the prognosis of stage IA lung adenocarcinoma. MATERIALS AND METHODS: We retrospectively analyzed data from 395 patients with pathologically confirmed stage IA lung adenocarcinoma. A total of 322 patients were divided into training and internal validation groups at a 6:4 ratio, whereas the remaining 73 patients composed the external validation group. According to the pathological results, the patients were classified into high and low Ki-67 labeling index (LI) groups. Clinical and CT features were subjected to statistical analysis. The training group was used to construct a predictive model through logistic regression and to formulate a nomogram. The nomogram's predictive ability and goodness-of-fit were assessed. Internal and external validations were performed, and clinical utility was evaluated. Finally, the recurrence-free survival (RFS) rates were compared. RESULTS: In the training group, sex, age, tumor density type, tumor-lung interface, lobulation, spiculation, pleural indentation, and maximum nodule diameter differed significantly between patients with high and low Ki-67 LI. Multivariate logistic regression analysis revealed that sex, tumor density, and maximum nodule diameter were significantly associated with high Ki-67 expression in stage IA lung adenocarcinoma. The calibration curves closely resembled the standard curves, indicating the excellent discrimination and accuracy of the model. Decision curve analysis revealed favorable clinical utility. Patients with a nomogram-predicted high Ki-67 LI exhibited worse RFS. CONCLUSION: The nomogram utilizing clinical and CT features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma demonstrated excellent performance, clinical utility, and prognostic significance, suggesting that this nomogram is a noninvasive personalized approach for the preoperative prediction of Ki-67 expression.