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Objectives: To evaluate the non-inferiority of non-contrast CT compared to contrast-enhanced CT with both intravenous and rectal contrast application for the diagnosis of acute colonic diverticulitis. Methods: Five readers retrospectively evaluated the non-contrast and contrast-enhanced series of CTs of 205 consecutive patients with clinical suspicion of acute diverticulitis. Two randomized reading sessions, both containing all 205 cases as either contrast-enhanced or non-contrast (1:1) series, were performed with ≥8 weeks washout between them. The non-inferiority margin was set to 0.1. Results: The pooled prevalence (all readers) of diverticulitis was similar for non-contrast CT (63.9%, range: 60.5–65.0%) and contrast-enhanced CT (64.4%, 61.5–67.8%). Non-contrast CT was non-inferior for the diagnosis of diverticulitis (accuracy 0.90 [95% confidence interval: 0.89, 0.92]) compared to contrast-enhanced CT (0.92 [0.90, 0.94]; the difference in accuracy: −0.01 [−0.04, 0.01]) (normal deviate test: p-valueone-sided = 5.20 × 10−6). Sensitivities for perforation and abscess were slightly but significantly lower for the non-contrast CT than for the contrast-enhanced CT (differences: −0.15 [−0.20, −0.05], −0.17 [−0.27, −0.07]), while no differences in accuracies and specificities were observed. Conclusions: Non-contrast CT is non-inferior to contrast-enhanced CT (intravenous and rectal contrast) for the diagnosis of acute colonic diverticulitis. Contrast-enhanced CT is associated with significantly higher sensitivities for the presence of an abscess or perforation. [ABSTRACT FROM AUTHOR]

Background: Osteoporosis is commonly evaluated using dual-energy X-ray absorptiometry (DXA) for bone mineral density (BMD). Non-contrast computed tomography (CT) scans provide an alternative for opportunistic osteoporosis assessment. This study aimed to evaluate screening thresholds for osteoporosis based on CT attenuation values in Hounsfield units (HU) of L1–L4 vertebrae from CT scans of the abdominal region, compared to DXA assessments of the lumbar spine and hips. Methods: Conducted retrospectively over approximately two years, the analysis included 109 patients who had both CT and DXA scans within 12 months, excluding those with metal artifacts affecting the vertebrae. CT attenuation values in the trabecular region of the vertebrae were measured and compared among three groups based on the lowest T-score from DXA. Results: In a predominantly female cohort (mean age 66.3 years), the lowest CT attenuation values for L1–L4 vertebrae showed a moderate correlation with the lowest T-score, with a Pearson correlation coefficient of 0.542 (95% CI: 0.388, 0.667). A HU threshold of ≤142 at the L1 vertebra showed 91.9% sensitivity and 48.4% specificity, while a threshold of ≤160 HU showed 97.3% sensitivity and 31.3% specificity for screening osteoporosis. Conclusions: This study supports the use of non-contrast CT with these HU thresholds as an opportunistic tool for osteoporosis assessment. [ABSTRACT FROM AUTHOR]

The stone density (SD) is not the same in all parts of the stone due to the heterogeneous nature of the stone and the shock wave (SW) passes through tissues of many different densities until it reaches the stone. These factors affect the success of Extracorporeal Shock Wave Lithotripsy (ESWL). We aimed to evaluate the effect of the Variation Coefficient of Stone Density (VCSD) and Renal Cortical Tickness (RCT) on the success of ESWL. Between 2020 and 2023, 510 patients who underwent ESWL were divided into 2 groups treatment success (n:304) and treatment failure (n:206). Non-Contrast Computed Tomography (NCCT) imaging values of hydronephrosis degree of the kidney, stone location, stone volume (SV), stone-skin distance (SSD), SD, Standard deviation of Stone Density (SDSD), VCSD, RCT, Soft-Tissue Thickness (STT), Muscle Thickness (MT) were analyzed. VCSD value was obtained by dividing SDSD by SD. Along the SW, tissues were divided into three components: kidney (renal cortex), muscle and other soft tissues. RCT, MT and SSD were measured at three different angles (0°, 45°, and 90°) and these 3 lengths were averaged. In univariate analysis, Body Mass Index (BMI), SV, SD, VCSD, SSD, RCT and STT were demonstrated to affect ESWL success. In multivariate analysis, low BMI, SV, SD, RCT and large VCSD were significant independent predictors of ESWL success. Among these parameters, VCSD had the highest prediction accuracy, followed by SD, SV, RCT and BMI, respectively. This study demonstrated that VCSD value and RCT are predictive parameters in determining the treatment of patients with urinary calculi and selecting suitable ESWL candidates. [ABSTRACT FROM AUTHOR]

Abstract Background Pulmonary embolism (PE) is life-threatening and requires timely and accurate diagnosis, yet current imaging methods, like computed tomography pulmonary angiography, present limitations, particularly for patients with contraindications to iodinated contrast agents. We aimed to develop a quantitative texture analysis pipeline using machine learning (ML) based on non-contrast thoracic computed tomography (CT) scans to discover intensity and textural features correlated with regional lung perfusion (Q) physiology and pathology and synthesize voxel-wise Q surrogates to assist in PE diagnosis. Methods We retrospectively collected 99mTc-labeled macroaggregated albumin Q-SPECT/CT scans from patients suspected of PE, including an internal dataset of 76 patients (64 for training, 12 for testing) and an external testing dataset of 49 patients. Quantitative CT features were extracted from segmented lung subregions and underwent a two-stage feature selection pipeline. The prior-knowledge-driven preselection stage screened for robust and non-redundant perfusion-correlated features, while the data-driven selection stage further filtered features by fitting ML models for classification. The final classification model, trained with the highest-performing PE-associated feature combination, was evaluated in the testing cohorts based on the Area Under the Curve (AUC) for subregion-level predictability. The voxel-wise Q surrogate was then synthesized using the final selected feature maps (FMs) and model score maps (MSMs) to investigate spatial distributions. The Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used to assess the spatial consistency between FMs or MSMs and Q-SPECT scans. Results The optimal model performance achieved an AUC of 0.863 during internal testing and 0.828 on the external testing cohort. The model identified a combination containing 14 intensity and textural features that were non-redundant, robust, and capable of distinguishing between high- and low-functional lung regions. Spatial consistency assessment in the internal testing cohort showed moderate-to-high agreement between MSMs and reference Q-SPECT scans, with median SCC of 0.66, median DSCs of 0.86 and 0.64 for high- and low-functional regions, respectively. Conclusions This study validated the feasibility of using quantitative texture analysis and a data-driven ML pipeline to generate voxel-wise lung perfusion surrogates, providing a radiation-free, widely accessible alternative to functional lung imaging in managing pulmonary vascular diseases. Clinical trial number Not applicable.

PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its proper treatment are of great significance in curbing the deterioration and improving the prognosis of patients with ICH. This study aimed to develop an automated hybrid approach to predict hematoma expansion in ICH. METHODS: The transfer learning method was applied to build a hybrid model based on a convolutional neural network (CNN) to predict the expansion of hematoma. The model integrated (1) a CNN for automated hematoma segmentation and (2) a CNN-based classifier for hematoma expansion prediction that incorporated both 2-dimensional images and the radiomics features of the 3-dimensional hematoma shape. RESULTS: The radiomics feature module had the highest area under the receiver operating characteristic curve (AUC) of 0.58, a precision of 0, a recall of 0, and an average precision (AP) of 0.26. The ResNet50 and Inception_v3 modules had AUCs of 0.79 and 0.93, a precision of 0.56 and 0.86, a recall of 0.42 and 0.75, and an AP of 0.51 and 0.85, respectively. Radiomic with Inception_v3 and Radiomic with ResNet50 had AUCs of 0.95 and 0.81, a precision of 0.90 and 0.57, a recall of 0.79 and 0.17, and an AP of 0.87 and 0.69, respectively. CONCLUSION: A model using deep learning and radiomics was successfully developed. This model can reliably predict the hematoma expansion of ICH with a fully automated process based on non-contrast computed tomography imaging. Furthermore, the radiomics fusion with the Inception_v3 model had the highest accuracy.

Background: Pulmonary embolism (PE) is life-threatening and requires timely and accurate diagnosis, yet current imaging methods, like computed tomography pulmonary angiography, present limitations, particularly for patients with contraindications to iodinated contrast agents. We aimed to develop a quantitative texture analysis pipeline using machine learning (ML) based on non-contrast thoracic computed tomography (CT) scans to discover intensity and textural features correlated with regional lung perfusion (Q) physiology and pathology and synthesize voxel-wise Q surrogates to assist in PE diagnosis. Methods: We retrospectively collected 99mTc-labeled macroaggregated albumin Q-SPECT/CT scans from patients suspected of PE, including an internal dataset of 76 patients (64 for training, 12 for testing) and an external testing dataset of 49 patients. Quantitative CT features were extracted from segmented lung subregions and underwent a two-stage feature selection pipeline. The prior-knowledge-driven preselection stage screened for robust and non-redundant perfusion-correlated features, while the data-driven selection stage further filtered features by fitting ML models for classification. The final classification model, trained with the highest-performing PE-associated feature combination, was evaluated in the testing cohorts based on the Area Under the Curve (AUC) for subregion-level predictability. The voxel-wise Q surrogate was then synthesized using the final selected feature maps (FMs) and model score maps (MSMs) to investigate spatial distributions. The Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used to assess the spatial consistency between FMs or MSMs and Q-SPECT scans. Results: The optimal model performance achieved an AUC of 0.863 during internal testing and 0.828 on the external testing cohort. The model identified a combination containing 14 intensity and textural features that were non-redundant, robust, and capable of distinguishing between high- and low-functional lung regions. Spatial consistency assessment in the internal testing cohort showed moderate-to-high agreement between MSMs and reference Q-SPECT scans, with median SCC of 0.66, median DSCs of 0.86 and 0.64 for high- and low-functional regions, respectively. Conclusions: This study validated the feasibility of using quantitative texture analysis and a data-driven ML pipeline to generate voxel-wise lung perfusion surrogates, providing a radiation-free, widely accessible alternative to functional lung imaging in managing pulmonary vascular diseases. Clinical trial number: Not applicable. [ABSTRACT FROM AUTHOR]

Assessing the extent of damage to the posterior limb of the internal capsule (PLIC) is important for early prediction of clinical outcomes in intracerebral hemorrhage (ICH) patients. Currently, using MRI to reconstruct the extent of damage to PLIC is not suitable for quick assessment of prognosis in emergency settings. We aimed to investigate whether the PLIC damage quantified by non-contrast computed tomography (NCCT) is associated with clinical outcomes after basal ganglia intracerebral hemorrhage (BG-ICH). This study retrospectively included 146 BG-ICH patients from the Department of Neurosurgery at the Second Affiliated Hospital of Chongqing Medical University. The damage to the PLIC was quantified using Tangency X measured by NCCT. The importance of features is determined using the Boruta algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Multivariate logistic regression models were established to examine the impact of PLIC damage on outcomes. Restricted Cubic Splines (RCS) were used to explore potential nonlinear relationships, and Receiver Operating Characteristic (ROC) curves were used to compare the predictive performance of Tangency X with other scoring systems for 6-month neurological outcomes (poor outcomes [mRS: 3–6]). In the multivariate logistic regression adjusting for all covariates, Tangency X was independently associated with an increased risk of poor outcomes (OR = 1.32, 95% CI: 1.17–1.52) in BG-ICH patients. There is a nonlinear relationship between Tangency X and poor outcomes. Specifically, the risk of poor outcomes increases by 1.29 times (OR = 1.29, 95% CI: 1.09–1.67) for each additional 1 mm increase in Tangency X beyond 4 mm. We next observed that the AUC for Tangency X in predicting poor outcomes is 0.8511. The extent of PLIC damage measured by NCCT may represent a promising predictor of poor outcomes after BG-ICH. [ABSTRACT FROM AUTHOR]

Purpose: Machine learning (ML) models were constructed according to noncontrast computed tomography (NCCT) images as well as clinical and laboratory information to assess risk stratification for the occurrence of hemorrhagic transformation (HT) in acute ischemic stroke (AIS) patients. Methods: A retrospective cohort was constructed with 180 AIS patients who were diagnosed at two centers between January 2019 and October 2023 and were followed for HT outcomes. Patients were analyzed for clinical risk factors for developing HT, infarct texture features were extracted from NCCT images, and the radiomics score (Rad-score) was calculated. Then, five ML models were established and evaluated, and the optimal ML algorithm was used to construct the clinical, radiomics, and clinical-radiomics models. Receiver operating characteristic (ROC) curves were used to compare the performance of the three models in predicting HT. Results: Based on the outcomes of the AIS patients, 104 developed HT, and the remaining 76 had no HT. The HT group consisted of 27 hemorrhagic infarction (HI) and 77 parenchymal-hemorrhage (PH). Patients with HT had a greater neutrophil-to-lymphocyte ratio (NLR), baseline National Institutes of Health Stroke Scale (NIHSS) score, infarct volume, and Rad-score and lower Alberta stroke program early CT score (ASPECTS) (all p < 0.01) than patients without HT. The best ML algorithm for building the model was logistic regression. In the training and validation cohorts, the AUC values for the clinical, radiomics, and clinical-radiomics models for predicting HT were 0.829 and 0.876, 0.813 and 0.898, and 0.876 and 0.957, respectively. In subgroup analyses with different treatment modalities, different infarct sizes, and different stroke time windows, the assessment accuracy of the clinical-radiomics model was not statistically meaningful (all p > 0.05), with an overall accuracy of 79.5%. Moreover, this model performed reliably in predicting the PH and HI subcategories, with accuracies of 82.9 and 92.9%, respectively. Conclusion: ML models based on clinical and NCCT radiomics characteristics can be used for early risk evaluation of HT development in AIS patients and show great potential for clinical precision in treatment and prognostic assessment. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the correlation between serum potassium (K+) concentration upon admission and the presence of the Island Sign (IS) in cranial CT scans of patients diagnosed with Hypertensive Intracerebral Hemorrhage (HICH), including the potential presence of a nonlinear relationship. Methods: This investigation constituted a single-center cross-sectional study. We systematically gathered comprehensive general clinical characteristics, biological indicators, and imaging data from a cohort of 330 patients diagnosed with HICH. These patients received treatment within the neurosurgery department of Chongqing Emergency Medical Center during the period spanning from July 1, 2018, to July 7, 2023. Our primary objective was to scrutinize the potential connection between serum K+ concentration upon admission and the presence of the IS observed in cranial CT scans. To meticulously address this inquiry, we employed logistic regression modeling, thereby meticulously evaluating the correlation aforementioned. Moreover, in order to delve deeper into the intricacies of the relationship, we extended our analysis by employing a smoothed curve-fitting model to meticulously authenticate the potential nonlinear interrelation between these two critical variables. Results: In this investigation, a total of 330 patients diagnosed with HICH were ultimately enrolled, exhibiting an average age of 58.4 ± 13.1 years, comprising 238 (72.1%) males and 92 (27.9%) females. Among these participants, 118 individuals (35.7%) presented with the IS upon admission cranial CT scans, while 212 patients (64.3%) did not exhibit this characteristic. Upon comprehensive multifactorial adjustments, a non-linear association was uncovered between serum K+ concentration and the presence of IS. Notably, an inflection point was identified at approximately 3.54 mmol/L for serum K+ concentration. Prior to the patient's serum K+ concentration reaching around 3.54 mmol/L upon admission, a discernible trend was observed--every 0.1 mmol/L increment in serum K+ concentration was associated with an 8% decrease in the incidence of IS (OR: 0.914, 95% CI: 0.849--0.983, p = 0.015). Conclusion: The findings of this study underscore a negative association between reduced serum K+ concentration upon admission and the occurrence of the IS on cranial CT scans among patients diagnosed with hypertensive cerebral hemorrhage. Furthermore, this negative correlation appears to manifest within the realm of a non-linear relationship. This study elucidates the potential significance of serum K+ concentration levels among patients with HICH, highlighting the role they play. Moreover, the maintenance of a physiological equilibrium in serum K+ concentrations emerges as a conceivable protective factor for individuals within the stroke population. [ABSTRACT FROM AUTHOR]

Background: Hypertensive disorders remain among the most significant complications of pregnancy. Neurological complications of eclampsia are a major contributor to morbidity and mortality that is associated with eclampsia. Neuroimaging studies have revolutionized visualization of hypertensive encephalopathy aids in timely intervention and a favorable maternal and perinatal outcome. Aims and Objectives: (1) To study the spectrum of neuroimaging findings in patients with eclampsia. (2) To correlate these findings with the maternal outcome. Materials and Methods: A prospective observational study was undertaken in the Department of Obstetrics and Gynecology, Mysore Medical College and research institute Mysore, for 18 months. All the eclamptic mothers during the study were included in the study. They were studied in terms of neuroimaging and its correlation with maternal outcomes. Results: The incidence of eclampsia was 7.14% which is relatively high, attributed to the fact that being a tertiary care center many cases are referred. Higher incidence was seen in primigravida (72.4%) and lower maternal age of 18–20 years (48%). Cesarean section was indicated in 50% of deliveries indicating immediate action was necessary for better fetomaternal outcome. They presented with varied imminent symptoms such as headache in 20.4%, vomiting in 22.4%, and visual blurring in 22.4%. About 50% presented with altered sensorium. On non-contrast computed tomography brain, 64.3% (63) had normal findings, 17.3% (17) had posterior reversible encephalopathy syndrome (PRES) with a sensitivity of 68.42% and specificity of 85%, whereas on magnetic resonance imaging (MRI) brain, 36.26% had no abnormalities, 40.81% had PRES with a sensitivity of 86.84%, and specificity of 85%. About 58.6% had an uneventful maternal outcome. The others were hemolysis, elevated liver enzymes, and low platelet syndrome seen in 9.18% of patients, acute kidney injury in 6.12%, postpartum hemorrhage seen in 5.1%. The maternal mortality rate was 7.66%, the most common cause of death was intracranial hemorrhage. Conclusion: The common neuroimaging findings in eclampsia are cerebral edema, PRES, cerebral venous thrombosis, infarcts, hemorrhage, and hypertensive leukoencephalopathy. Although some abnormalities seen in neuroimaging studies are incidental and transient without chronic neurologic sequelae, both CT and MRI findings correlate with the clinical presentation and maternal outcome but MRI correlates better compared to CT and can be a better imaging modality in eclampsia patients and is indicated in all patients of eclampsia.

Objective: There are several factors affecting the success of shockwave lithotripsy (SWL), which is still one of the first-line treatments for renal stones smaller than 2 cm. The aim of this study was to evaluate the effect of thickness and density measurements obtained by computed tomography (CT) for various tissues within the route of shockwaves on the outcome of SWL treatment success. Materials and Methods: The data of 89 patients who underwent SWL for renal pelvic stones smaller than 2 cm between July 2020 and September 2021 were prospectively evaluated. Age, sex, body mass index, stone volume, stone density, skin-to-stone distance, tissue thickness and density, hydronephrosis, number of shockwaves, and SWL success were recorded. Patients were divided into two groups according to SWL success: SWL success and SWL failure groups. Demographic data and CT parameters were compared between the groups. Results: Stone-free status (

Background: Hypertensive disorders remain among the most significant complications of pregnancy. Neurological complications of eclampsia are a major contributor to morbidity and mortality that is associated with eclampsia. Neuroimaging studies have revolutionized visualization of hypertensive encephalopathy aids in timely intervention and a favorable maternal and perinatal outcome. Aims and Objectives: (1) To study the spectrum of neuroimaging findings in patients with eclampsia. (2) To correlate these findings with the maternal outcome. Materials and Methods: A prospective observational study was undertaken in the Department of Obstetrics and Gynecology, Mysore Medical College and research institute Mysore, for 18 months. All the eclamptic mothers during the study were included in the study. They were studied in terms of neuroimaging and its correlation with maternal outcomes. Results: The incidence of eclampsia was 7.14% which is relatively high, attributed to the fact that being a tertiary care center many cases are referred. Higher incidence was seen in primigravida (72.4%) and lower maternal age of 18–20 years (48%). Cesarean section was indicated in 50% of deliveries indicating immediate action was necessary for better fetomaternal outcome. They presented with varied imminent symptoms such as headache in 20.4%, vomiting in 22.4%, and visual blurring in 22.4%. About 50% presented with altered sensorium. On non-contrast computed tomography brain, 64.3% (63) had normal findings, 17.3% (17) had posterior reversible encephalopathy syndrome (PRES) with a sensitivity of 68.42% and specificity of 85%, whereas on magnetic resonance imaging (MRI) brain, 36.26% had no abnormalities, 40.81% had PRES with a sensitivity of 86.84%, and specificity of 85%. About 58.6% had an uneventful maternal outcome. The others were hemolysis, elevated liver enzymes, and low platelet syndrome seen in 9.18% of patients, acute kidney injury in 6.12%, postpartum hemorrhage seen in 5.1%. The maternal mortality rate was 7.66%, the most common cause of death was intracranial hemorrhage. Conclusion: The common neuroimaging findings in eclampsia are cerebral edema, PRES, cerebral venous thrombosis, infarcts, hemorrhage, and hypertensive leukoencephalopathy. Although some abnormalities seen in neuroimaging studies are incidental and transient without chronic neurologic sequelae, both CT and MRI findings correlate with the clinical presentation and maternal outcome but MRI correlates better compared to CT and can be a better imaging modality in eclampsia patients and is indicated in all patients of eclampsia. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare the diagnostic ability of contrast-enhanced computed tomography (CECT) and CECT combined with non-contrast computed tomography (NCT) for intraabdominal organ injury in patients with blunt abdominal injury. Material and Methods: Overall, 195 adult patients having had blunt abdominal trauma underwent CT at this institution; from 2016 and 2021. All CT images were retrospectively reviewed by two radiologists. The efficacy of detection of organ injuries and the degree of intra-abdominal injury were recorded. The radiologists scored their diagnostic confidence for each CT image dataset on a five-point scale: inter-observer agreement was also calculated. Results: All included patients underwent CT for blunt abdominal trauma. The most common cause of injury was motorcycle accident (59.5%), with patients being predominantly male: the mean patient age was 44 years. Hemoperitoneum was the most common CT finding, with a significantly higher detection rate on CECT combined with NCT than on CECT alone. There was no statistically significant difference in the diagnostic efficacy of the detected organ injury nor other types of organ injuries between CECT alone and CECT combined with NCT. Nevertheless, the accuracy of CECT in detecting hemoperitoneum may diminish in patients with severe fatty liver disease; especially in the perihepatic region. Conclusion: CECT alone is a potential tool for detecting abdominal injuries in patients with blunt trauma. NCT provides no additional benefits in detecting organ injury; except in cases of severe fatty liver disease. NCT is recommended as an optional protocol; particularly for patients with obesity.

Non-contrast computed tomography (NCCT) of the brain is critical to patients with acute ischemic stroke who receive thrombolysis and thrombectomy. It can help identify reperfusion-related hemorrhage, edema which need intervention. It also can guide the timing and intensity of antithrombotic therapy. Rapid, accurate, and automated detection and segmentation of acute ischemic lesions after endovascular therapy (EVT) are highly needed. In this work, we propose a novel encoder-decoder network for fully automatic segmentation of acute ischemic lesions after EVT on NCCT, which is named ISCT-EDN. NCCT images of AIS (acute ischemic stroke) patients who underwent EVT in a multicenter cohort study were collected in this study. ISCT-EDN takes hierarchical network as backbone. Feature pyramid network (FPN) is designed to aggregate features from multi stages of backbone. Reasonable feature fusion strategy is considered in FPN to enhance multi-level propagation. In addition, to overcome the limitation of fixed geometric structure of convolution for multi-range dependency exploitation, non-local parallel decoder is introduced with deformable convolution and self-attention. The proposed model was compared with 7 segmentation models which are commonly used in the medical domain and the performance was superior to other models in in the segmentation of post-treatment infarct lesions on NCCT images of AIS patients after EVT. [ABSTRACT FROM AUTHOR]

Background: Detecting occlusions of coronary artery bypass grafts using non-contrast computed tomography (CT) series is understudied and underestimated. Purpose: To evaluate morphological findings for the diagnosis of chronic coronary artery bypass graft occlusion on non-contrast CT and investigate performance statistics for potential use cases. Material and Methods: Seventy-three patients with coronary artery bypass grafts who had CT angiography of the chest (non-contrast and arterial phases) were retrospectively included. Two readers applied pre-set morphologic findings to assess the patency of a bypass graft on non-contrast series. These findings included vessel shape (linear-band like), collapsed lumen and surgical graft marker without a visible vessel. Performance was tested using the simultaneously acquired arterial phase series as the ground truth. Results: The per-patient diagnostic accuracy for occlusion was 0.890 (95% confidence interval = 0.795–0.951). Venous grafts overall had an 88% accuracy. None of the left internal mammary artery to left anterior descending artery arterial graft occlusions were detected. The negative likelihood ratio for an occluded graft that is truly patent was 0.121, demonstrating a true post-test probability of 97% for identifying a patent graft as truly patent given a prevalence of 20% occlusion at a median 8.4 years post-surgery. Neither years post-surgery, nor number of vessels was associated with a significant decrease in reader accuracy. Conclusion: Evaluation of coronary bypass grafts for chronic occlusion on non-contrast CT based off vessel morphology is feasible and accurate for venous grafts. Potential use cases include low-intermediate risk patients with chest pain or shortness of breath for whom non-contrast CT was ordered, or administration of iodine-based contrast is contraindicated. [ABSTRACT FROM AUTHOR]

Objective: To determine the diagnostic value of ultrasound signs of urinary stones less than or equal to 10 mm and to determine clinico-radiological variants of ureteric colic. Methods: A total of 455 ultrasound investigations were performed in patients referring to emergency department with urolithiasis and symptoms suspected of ureteric colic between January 2021 and May 2021. In addition to microscopic evaluation of urine sediment to detect different crystals and non-contrast spiral computed tomography to detect stones, B-mode and color Doppler sonography was performed to assess the presence of acoustic shadow (AS) and twinkle artifacts (TA) as possible signs of stone(s) in ureter. Results: While the sensitivity and specificity of AS and TA were higher than 90% in patients with stones greater than 5 mm; positive prognostic values of these parameters were found to be extremely low for stones with sizes of 1–3 mm with specificity and sensitivity values not exceeding 53%. The sensitivity and specificity of AS and TA in the upper and lower ureters were higher for stones greater than or equal to 5 than for compared to those less than 5 mm. At the same time, the diagnostic values of TA and AS for middle ureter stones were very limited. The most prevalent clinico-radiological variants of ureteric colic were types I, III, and V being observed in 39%, 28% and 21% cases, respectively. Conclusion: Our results demonstrate that TA and AS parameters seem to have a very low sensitivity and specificity in the diagnosis of urinary stones less than 5 mm. The diagnostic value of TA and AS increase significantly in stones greater than or equal to 5 mm. Therefore, clinicians need to be very careful for overestimating the diagnostic values of TA and AS for stones less than 5 mm and non-contrast spiral computed tomography must be the method of choice for patients presenting to emergency department with ureteric colic.

Key points The model simultaneously segments infarcts and estimates ASPECTS by using baseline CT. A mirror-assembly module plus dual-path DCNN model improved the segmentation efficiency. We evaluated the model in a multi-reader and multicenter (MRMC) setting.

Background: Agatston scoring, the traditional method for measuring coronary artery calcium, is limited in its ability to accurately quantify low‐density calcifications, among other things. The inaccuracy of Agatston scoring is likely due partly to the arbitrary thresholding requirement of Agatston scoring. Purpose: A calcium quantification technique that removes the need for arbitrary thresholding and is more accurate, sensitive, reproducible, and robust is needed. Improvements to calcium scoring will likely improve patient risk stratification and outcome. Methods: The integrated Hounsfield technique was adapted for calcium scoring (integrated calcium mass). Integrated calcium mass requires no thresholding and includes all calcium information within an image. This study utilized phantom images acquired by G van Praagh et al., with calcium hydroxyapatite (HA) densities in the range of 200–800 mgHAcm−3 to measure calcium according to integrated calcium mass and Agatston scoring. The calcium mass was known, which allowed for accuracy, reproducibility, sensitivity, and robustness comparisons between integrated calcium mass and Agatston scoring. Multiple CT vendors (Canon, GE, Philips, Siemens) were used during the image acquisition phase, which provided a more robust comparison between the two calcium scoring techniques. Three calcification inserts of different diameters (1, 3, and 5 mm) and different HA densities (200, 400, and 800 mgHAcm−3) were placed within the phantom. The effect of motion was also analyzed using a dynamic phantom. All dynamic phantom calcium inserts were 5.0 ± 0.1 mm in diameter with a length of 10.0 ± 0.1 mm. The four different densities were 196 ± 3, 380 ± 2, 408 ± 2, and 800 ± 2 mgHAcm−3. Results: Integrated calcium mass was more accurate than Agatston scoring for stationary scans (RMSEIntegrated=2.87$RMS{E}_{Integrated} = 2.87$, RMSEAgatson=4.07$RMS{E}_{Agatson} = 4.07$) and motion affected scans (RMSEIntegrated=9.70$RMS{E}_{Integrated} = 9.70$, RMSEAgatson=19.98$RMS{E}_{Agatson} = 19.98$). On average, integrated calcium mass was more reproducible than Agatston scoring for two of the CT vendors. The percentage of false‐negative and false‐positive calcium scores were lower for integrated calcium mass (15.00%, 0.00%) than Agatston scoring (28.33%, 6.67%). Integrated calcium mass was more robust to changes in scan parameters than Agatston scoring. Conclusions: The results of this study indicate that integrated calcium mass is more accurate, reproducible, and sensitive than Agatston scoring on a variety of different CT vendors. The substantial reduction in false‐negative scores for integrated calcium mass is likely to improve risk‐stratification for patients undergoing calcium scoring and their potential outcome. [ABSTRACT FROM AUTHOR]

Objectives: Evaluation of safety, efficacy, and feasibility of emergency extracorporeal shockwave lithotripsy (eESWL) in combating obstructing stones with colic on emergency basis. Materials and methods: From November 2019 to November 2021, 102 subjects underwent emergency ESWL for obstructing ureteric and renal stones with colic within 24 h of presentation. Results: Patients in this study belonged to age group of 18–67 years with mean being 39 years consisting of 85 males and 22 females (M:F = 85:22). Mean stone dimensions were 8.26 mm in length and 7.65 mm in width. A total of 42 patients had their stone in kidney or upper ureter while 24 patients had stone in mid ureter and remaining patients (n = 36) had stone in lower ureter. About 65 patients had their stone completely cleared after single ESWL session while 20 patients required multiple sessions to achieve complete clearance. Of these 17 patients (16.67%) were not rendered stone free even after three sessions and had to undergo ureteroscopic lithotripsy (URSL). Overall Stone Free Rate (SFR) was 83.33%. For stone attenuation of ⩽900 HU, SFR was 97.18% while for >900 HU it was only 51.61%. Conclusion: eESWL is safe, feasible, and efficacious noninvasive alternative for definitive management of obstructing ureteral and renal stones with colic as far as stone clearance and rapid and definitive pain relief are concerned and that too with very minimal morbidity without the need for admission and hence can reduce the prolonged waiting period for endoscopic stone surgery in any high-volume tertiary care hospital. Length, width, and attenuation of stone were found to be the main factors dictating the success of eESWL. [ABSTRACT FROM AUTHOR]

Introduction and objectivesSomalia was predicted to be in the global stone belt with high urolithiasis prevalence. We aimed to determine the prevalence of urolithiasis and their demographic and computer tomography (CT) characteristics among subjects under CT scans in Mogadishu, Somalia. Materials and Methods: From March 2014 to November 2022, a total of 7,276 patients who underwent an abdominopelvic non-contrast CT scan for various indications were retrospectively reviewed. The mean age was 45.6 years with a standard deviation of 21.1 (range, 0.2–110 years). Patients were subdivided into two categories: adults (≥18 years) and pediatric (≤17 years).ResultsOf the 7,276 patients, 1,075 (14.8%) were diagnosed with urolithiasis. Among those with urolithiasis, 702 (65.3%) were male patients, and 373 (34.7%) were female patients. Among them, adults accounted for 92.7%, while children were 7.3%. Renal stones (nephrolithiasis) were the most common, representing 57% followed by ureteric stones at 35.5%, making upper urinary stones 92.5%. Approximately 70 patients (6.5%) had bladder stones; of these, 26 of them (37%) were accompanied by benign prostatic hyperplasia (BPH). There were 10 urethral stones (0.9%) recorded in the study, all were found in male patients, 8 localized in prostatic urethra, and 2 in the bulbar urethra. The overall mean stone size was 13.2 mm, and 60% of them ranged from 5 to 22 mm. Only 24% of the patients were asymptomatic. Single stones were almost 70%, while staghorn calculi were 8.2%. More than 60% of the patients with urolithiasis showed some degree of hydronephrosis ranging between mild to severe.ConclusionA CT scan-based urolithiasis prevalence indicates 14.8% in Mogadishu, Somalia, and these results are consistent with the probability calculation of the weights-of-evidence (WofE) methodology based on several risk factors including temperature, climate change, mineral deposit, drinking water quality, and distribution of carbonated rocks. Considering the high prevalence of the disease, Somalia needs to invest more in prevention and treatment facilities while also training urologists that are capable of utilizing minimally invasive techniques in the country.

Background: The presence of diffusion-weighted imaging (DWI) and fluidattenuated inversion recovery (FLAIR) mismatch was used to determine eligibility for intravenous thrombolysis in clinical trials. However, due to the restricted availability of MRI and the ambiguity of image assessment, it is not widely implemented in clinical practice. Methods: A total of 222 acute ischemic stroke patients underwent non-contrast computed tomography (NCCT), DWI, and FLAIR within 1 h of one another. Human experts manually segmented ischemic lesions on DWI and FLAIR images and independently graded the presence of DWI-FLAIR mismatch. Deep learning (DL) models based on the nnU-net architecture were developed to predict ischemic lesions visible on DWI and FLAIR images using NCCT images. Inexperienced neurologists evaluated the DWI-FLAIR mismatch on NCCT images without and with the model's results. Results: The mean age of included subjects was 71.8 ± 12.8 years, 123 (55%) were male, and the baseline NIHSS score was a median of 11 [IQR, 6-18]. All images were taken in the following order: NCCT - DWI - FLAIR, starting after a median of 139 [81-326] min after the time of the last known well. Intravenous thrombolysis was administered in 120 patients (54%) after NCCT. The DL model's prediction on NCCT images revealed a Dice coefficient and volume correlation of 39.1% and 0.76 for DWI lesions and 18.9% and 0.61 for FLAIR lesions. In the subgroup with 15 mL or greater lesion volume, the evaluation of DWI-FLAIR mismatch from NCCT by inexperienced neurologists improved in accuracy (from 0.537 to 0.610) and AUC-ROC (from 0.493 to 0.613). Conclusion: The DWI-FLAIR mismatch may be reckoned using NCCT images through advanced artificial intelligence techniques. [ABSTRACT FROM AUTHOR]

Introduction: Percutaneous Nephrolithotomy (PCNL) is the preferred method for treating large or complex renal calculi. Despite positive results and apparent benefits over the prone position, there are few randomised trials comparing the supine and prone positions. Aim: To evaluate the effectiveness of PCNL in prone and supine positions in terms of operative time, stone-free rate, hospital stay, postoperative complications, and the level of haemoglobin drop. Materials and Methods: The study was conducted from December 2020 to December 2022, at the Department of Urology, Mamata Medical College in Khammam, Telangana, India. Patients with renal stones diagnosed by Non-Contrast Computed Tomography (NCCT) Kidney Ureter Bladder (KUB) and meeting the inclusion criteria were enrolled. Patient demographic data, operative time, stone-free rate, haemoglobin level drop, postoperative fever, and hospital stay in prone and supine positions were recorded. Statistical tests like chi-square or Fisher-exact test were used to compare proportions, and the student t-test was used to compare means. Results: The overall operative time was 79.50 minutes in the prone group and 66.78 minutes in the supine group (p=0.0213). The average hospital stay was 2.68 days in the prone group and 2.72 days in the supine group (p=0.2432). Fall in haemoglobin levels, size of stones extracted, and stone-free rate at three months between the two groups (p>0.05) showed insignificant relation. Furthermore, there was no significant difference in complications between the two groups (p>0.05). Conclusion: PCNL performed with the patient in the supine position requires significantly less time during surgery. There was no significant difference in terms of stone-free rate, hospital stay, fall in haemoglobin levels, and complications between the supine and prone groups.

Background: 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. Methods: 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. Results: 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%. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Purpose: Our aim is to build and validate a clinical-radiomic model for noninvasive liver steatosis prediction based on non-contrast computed tomography (CT). Methods: We retrospectively reviewed 342 patients with suspected NAFLD diagnoses between January 2019 and July 2020 who underwent non-contrast CT and liver biopsy. Radiomics features from hepatic and splenic regions-ofinterests (ROIs) were extracted based on abdominal non-contrast CT imaging. The radiomics signature was constructed based on reproducible features by adopting the least absolute shrinkage and selection operator (LASSO) regression. Then, multivariate logistic regression analysis was applied to develop a combined clinical-radiomic nomogram integrating radiomics signature with several independent clinical predictors in a training cohort of 124 patients between January 2019 and December 2019. The performance of models was determined by the area under the receiver operating characteristic curves and calibration curves. We conducted an internal validation during 103 consecutive patients between January 2020 and July 2020. Results: The radiomics signature was composed of four steatosis-related features and positively correlated with pathologic liver steatosis grade (p < 0.01). In both subgroups (Group One, none vs. steatosis; Group Two, none/mild vs. moderate/severe steatosis), the clinical-radiomic model performed best within the validation cohort with an AUC of 0.734 and 0.930, respectively. The calibration curve confirmed the concordance of excellent models. Conclusion: We developed a robust clinical-radiomic model for accurate liver steatosis stage prediction in a non-invasive way, which may improve the clinical decision-making ability. [ABSTRACT FROM AUTHOR]

Purpose: Hematoma volume is the strongest predictor of patient outcome after intracerebral hemorrhage (ICH). The aim of this study was to validate novel fully automated software for quantification of ICH volume on non-contrast computed tomography (CT). Methods: The population was defined from the Swedish Stroke Register (RS) and included all patients with an ICH diagnosis during 2016–2019 in Region Skåne. Hemorrhage volume on their initial head CT was measured using ABC/2 and manual segmentation (Sectra IDS7 volume measurement tool) and the automated volume quantification tool (qER–NCCT) by Qure.ai. The first 500 were examined by two independent readers. Results: A total of 1649 ICH patients were included. The qER–NCCT had 97% sensitivity in identifying ICH. In total, there was excellent agreement between volumetric measurements of ICH volumes by qER–NCCT and manual segmentation by interclass correlation (ICC = 0.96), and good agreement (ICC = 0.86) between qER–NCCT and ABC/2 method. The qER–NCCT showed volume underestimation, mainly in large (> 30 ml) heterogenous hemorrhages. Interrater agreement by (ICC) was 0.996 (95% CI: 0.99–1.00) for manual segmentation. Conclusion: Our study showed excellent agreement in volume quantification between the fully automated software qER–NCCT and manual segmentation of ICH on NCCT. The qER–NCCT would be an important additive tool by aiding in early diagnostics and prognostication for patients with ICH and in provide volumetry on a population-wide level. Further refinement of the software should address the underestimation of ICH volume seen in a portion of large, heterogenous, irregularly shaped ICHs. [ABSTRACT FROM AUTHOR]

Background: Upper urinary tract calculi are common with multi-modalities of treatment, with continuous invention of new modalities; one of these modalities is Extracorporeal shock wave lithotripsy [ESWL], which considered the modality of choice for renal stones less than 10mm with the advantage of being less invasive compared to other modalities.Aim of the work: To identify the factors based on Non-Contrast Computed Tomography [NCCT] that will predict the success of shock wave lithotripsy for renal stones.Patients and methods: A retrospective, single arm interventional study conducted by reviewing the medical files of all patients who underwent SWL for renal stones in the past 2 years. The study included 120 patients [82 males, 38 females; mean age: 52.1 y]. SWL was carried out. After three sessions, failure of disintegration was defined as no fragmentation of the stone. Univariate and multivariate analyses were used to assess the impact of patients' sex, age, and body mass index] as well as the stones' laterality, position, volume, mean attenuation value, and skin-to-stone distance on disintegration.Result: The success rate of extracorporeal SWL at 3 mo. was 91.66% [110 of 120 patients]; 100 patients were stone free and 10 had residual fragments 1000 HU and/or large skin-to-stone distance [SSD].

Objective: This study aimed to develop a deep learning (DL) model to improve the diagnostic performance of EIC and ASPECTS in acute ischemic stroke (AIS). Methods: Acute ischemic stroke patients were retrospectively enrolled from 5 hospitals. We proposed a deep learning model to simultaneously segment the infarct and estimate ASPECTS automatically using baseline CT. The model performance of segmentation and ASPECTS scoring was evaluated using dice similarity coefficient (DSC) and ROC, respectively. Four raters participated in the multi-reader and multicenter (MRMC) experiment to fulfill the region-based ASPECTS reading under the assistance of the model or not. At last, sensitivity, specificity, interpretation time and interrater agreement were used to evaluate the raters' reading performance. Results: In total, 1391 patients were enrolled for model development and 85 patients for external validation with onset to CT scanning time of 176.4 ± 93.6 min and NIHSS of 5 (IQR 2–10). The model achieved a DSC of 0.600 and 0.762 and an AUC of 0.876 (CI 0.846–0.907) and 0.729 (CI 0.679–0.779), in the internal and external validation set, respectively. The assistance of the DL model improved the raters' average sensitivities and specificities from 0.254 (CI 0.22–0.26) and 0.896 (CI 0.884–0.907), to 0.333 (CI 0.301–0.345) and 0.915 (CI 0.904–0.926), respectively. The average interpretation time of the raters was reduced from 219.0 to 175.7 s (p = 0.035). Meanwhile, the interrater agreement increased from 0.741 to 0.980. Conclusions: With the assistance of our proposed DL model, radiologists got better performance in the detection of AIS lesions on NCCT. Key points: The model simultaneously segments infarcts and estimates ASPECTS by using baseline CT. A mirror-assembly module plus dual-path DCNN model improved the segmentation efficiency. We evaluated the model in a multi-reader and multicenter (MRMC) setting. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneous intracerebral hemorrhage(sICH) using deep convolutional neural networks. Methods: A total of 377 consecutive patients with sICH from center 1 and 91 patients from center 2 (external validation set) were included. A receiver operating characteristic (ROC) analysis was performed to determine the critical value of dHU for predicting poor outcome at 90 days. Modified Rankin score (mRS) >3 or >2 was defined as the primary and secondary poor outcome, respectively. Two multivariate models were developed to test whether dHU was an independent predictor of the two unfavorable functional outcomes. Results: The ROC analysis showed that a dHU >2.5 was a critical value to predict the poor outcomes (mRS >3) in sICH. The sensitivity, specificity, and accuracy of dHU >2.5 for poor outcome prediction were 37.5%, 86.0%, and 70.6%, respectively. In multivariate models developed after adjusting for all elements of the ICH score and hematoma expansion, dHU >2.5 was an independent predictor of both primary and secondary poor outcomes (OR = 2.61, 95% CI [1.32,5.13], P = 0.006; OR = 2.63, 95% CI [1.36,5.10], P = 0.004, respectively). After adjustment for all possible significant predictors (p 2.5 had a positive association with primary and secondary poor outcomes (OR = 3.25, 95% CI [1.52,6.98], P = 0.002; OR = 3.42, 95% CI [1.64,7.15], P = 0.001). Conclusions: The dHU of hematoma based on serial CT scans is independently associated with poor outcomes after acute sICH, which may help predict clinical evolution and guide therapy for sICH patients.

Purpose: Detection of early-stage liver fibrosis has direct clinical implications on patient management and treatment. The aim of this paper is to develop a non-invasive, cost-effective method for classifying liver disease between "non-fibrosis" (F0) and "fibrosis" (F1–F4), and to evaluate the classification performance quantitatively. Methods: Image data from 75 patients who underwent a simultaneous liver biopsy and non-contrast CT examination were used for this study. Non-contrast CT image texture features such as wavelet-based features, standard deviation of variance filter, and mean CT number were calculated in volumes of interest (VOIs) positioned within the liver parenchyma. In addition, a combined feature was calculated using logistic regression with L2-norm regularization to further improve fibrosis detection. Based on the final pathology from the liver biopsy, the patients were labelled either as "non-fibrosis" or "fibrosis". Receiver-operating characteristic (ROC) curve, area under the ROC curve (AUROC), specificity, sensitivity, and accuracy were determined for the algorithm to differentiate between "non-fibrosis" and "fibrosis". Results: The combined feature showed the highest classification performance with an AUROC of 0.86, compared to the wavelet-based feature (AUROC, 0.76), the standard deviation of variance filter (AUROC, 0.65), and mean CT number (AUROC, 0.84). The combined feature's specificity, sensitivity, and accuracy were 0.66, 0.88, and 0.76, respectively, showing the most promising results. Conclusion: A new non-invasive and cost-effective method was developed to classify liver diseases between "non-fibrosis" (F0) and "fibrosis" (F1–F4). The proposed method makes it possible to detect liver fibrosis in asymptomatic patients using non-contrast CT images for better patient management and treatment. [ABSTRACT FROM AUTHOR]

Background: Sonography has been considered an excellent diagnostic imaging technique for the detection of both opaque and nonopaque renal calculi. The sonographic diagnosis of a calculus is usually based on the demonstration of a highly echogenic focus with an associated acoustic shadow. To compare the detection of urinary stones using standard gray scale ultrasound for diagnostic accuracy using the color Doppler "twinkling sign". Material and methods: In our study 90 consecutive patients with various abdominal pathologies (not directly linked to renal lithiasis) were included in our study. All patients then underwent US at our department. Color Doppler US was performed using a red-and-blue color map and power Doppler US using a pink color map with a standardized Doppler protocol to detect the twinkling artifact. For color Doppler, gain was set to the point just below the threshold for color noise and the pulse repetition frequency (= velocity scale) was set to 64 cm/sec to eliminate color flow signals from renal blood flow. The color window size was adjusted to cover the whole renal sinus. Doppler imaging began with continuous sweeps of the renal sinus in the longitudinal and transverse planes. Result: On abdominal CT scans, 81 selected patients showed 90 renal lithiasis equal to or smaller than 5 mm. The diameter of renal lithiasis ranged from 2.6 to 5.0 mm (average diameter 4.1 mm). Out of 90 CT positive lithiasis, 50 (55.6%) were absolutely positive on gray-scale. Out of the 50 lithiasis, 14 were hyperechogenic foci with posterior shadow cone, but with a slight echogenicity difference, 50 showed both posterior shadow cone and a marked echogenicity difference, and 24 showed a marked echogenicity difference without posterior shadow cone. So, the posterior shadow cone appeared 40 out of 50 times, while marked echogenicity difference was detected 84 times. Conclusion: The stone size obtained by US was almost the same as that detected by NCCT; however, US is a limited imaging modality in detecting urinary tract stone, especially when used by an inexperienced radiologist, and in the case of smaller stone size, increased weight, and low grade of hydronephrosis. [ABSTRACT FROM AUTHOR]

Objective: Elasticity of the skeletal system in children and degenerative changes in adults are responsible for SCIWORA. The purpose of this study was to determine those degenerative changes on CT scan that predispose adults to SCIWORA, their correlation with MRI findings, clinical presentation and recovery. Materials and Methods: This prospective study was conducted over a period of 1.5 years and 30 patients were enrolled. Apart from the demographic profile, mode of injury, clinical symptoms, ASIA at admission, X-ray, CT and MRI findings were noted. All patients were managed conservatively and were followed up after 3 months. NCCT and MRI findings were correlated with each other, with clinical presentation and with recovery. Recovery was defined as any improvement in ASIA class. Statistical Analysis: Data was collected and organized. For normally distributed data parametric test and for others non-parametric test was used. Kendall tau rank correlation coefficient was used to measure the ordinal association between two measured quantities. Results: 28 (93.3%) patients were males and 2 (6.7%) were females. Patients with osteoporosis and/or osteophytes (n = 16) had a higher incidence of development of cord edema or non-haemorrhagic contusion (n = 15) (P = 0.028) while patients with canal stenosis and/or ligamentous calcification (n = 14) had a higher incidence of development of haemorrhagic contusion (n = 12) (P = 0.04). Patients with canal stenosis and/or ligament calcification showed significantly less recovery (n = 3) when compared with patients of osteophytes and/or osteoporosis (n = 6) (P = 0.04). Disc abnormality was seen in 1 patient only. 9 patients showed recovery and maximum recovery was seen in ASIA D (n = 4) class while no patient recovered in ASIA A class. Conclusion: Osteoporosis, osteophytes, canal stenosis and ligament calcification are the factors that predispose adults to SCIWORA. The final outcome seems to be poorer in cases of canal stenosis when compared with osteophytes and osteoporosis. NCCT findings can be used as an adjunct to MRI to predict clinical presentation, severity and recovery in adult SCIWORA. [ABSTRACT FROM AUTHOR]

ABSTRACT Background: Among patients with acute ischemic stroke with a mismatch between deficit severity and infarct volume, thrombectomy performed within a 6-24 hours time window has efficacy and safety similar to treatment within 6 hours. However, whether magnetic resonance imaging with T2 diffusion-weighted imaging (DWI) is feasible remains to be validated. Objective: To investigate prognosis among stroke patients receiving endovascular treatment (EVT) within 6 hours and 6-24 hours using non-contrasted computed tomography (NCCT) and DWI. Methods: Overall, 209 anterior-circulation ischemic stroke patients with large-vessel occlusion who underwent EVT were divided into ≤ 6 hours and 6-24 hours groups. Patients presenting symptoms within 6 hours were treated if their NIHSS score was ≥ 7 and ASPECTS score was ≥ 5, whereas those with wake-up stroke (WUS) or presenting symptoms 6-24 hours after last seen well (WUS/late-presenting stroke, LPS) were managed if their NIHSS score was ≥ 7 and ASPECTS score was ≥ 5. Results: The percentages of patients undergoing intracranial stenting and intracranial ballooning without stenting significantly differed between two groups (p < 0.001). Grades 0, 1, 2a and 2b recanalization rates did not differ between the 6 hours and 6-24 hours groups (all p > 0.05). Grade 3 recanalization rate in the 6 hours group was significantly lower than in the 6-24 hours group (p = 0.043). The 3-month Rankin Scale score did not significantly differ between the two groups (p = 0.629). Conclusions: EVT is a safe and effective treatment for patients with WUS and LPS selected through NCCT and DWI-based simple imaging.

Objective: Although the guideline indicates that total kidney volume (TKV) is an important detection indicator in patients with autosomal dominant polycystic kidney disease (ADPKD), this study attempted to demonstrate that renal parenchymal information, combined with parenchymal volume and radiomics features, may have more valuable clinical guiding significance. Methods: A totals of 340 ADPKD patients with normal renal function were prospectively collected and followed-up for five years, with renal function tests and non-contrast computed tomography (CT) performed every six months. The relationship between renal function impairment and renal parenchymal volume (RPV) as along with radiomics features was explored using a multiple linear regression model and multiple logistic regression. Then, a combined model of RPV with radiomics features was constructed to comprehensively evaluate its predictive value. Results: Compared with TKV, decreased RPV presented a closer relationship with renal function impairment, namely, with the impairment rate (RPV: 82.3% vs. TVK: 67.1%) and eGFR (RPV: r = 0.614, p < 0.001 vs. TKV: r = -0.452, p < 0.001), and showed higher predictive power (RPV: AUC = 0.752 [95%CI 0.692–0.805], p < 0.001 vs. TKV: AUC = 0.711 [95%CI 0.649–0.768], p < 0.001). Correspondingly, the radiomics analysis that was derived from the renal parenchyma also showed a satisfactory result (AUC = 0.849 [95%Cl 0.797–0.892], p < 0.001). Importantly, the predictive power for renal function impairment was further improved in the combined model of RPV and radiomics features (AUC = 0.902 [95%Cl 0.857–0.937], p < 0.001). Conclusion: Renal parenchyma information may be a sensitive biomarker of renal function impairment in ADPKD, which can provide a new approach for clinically monitoring renal function, and may greatly improve the pre-hospital prevention and treatment effects. [ABSTRACT FROM AUTHOR]

Background and Purpose: The ability of attenuation value of the non-hypodense region of hematoma in non-contrast computed tomography (NCCT) for predicting hematoma expansion (HE) remains unclear. Our purpose is to explore this relationship. Methods: Two cohorts of patients were collected for analysis. The region where we measured hematoma attenuation values was limited to the non-hypodense region that was not adjacent to the normal brain tissue on NCCT. The critical attenuation value was derived via receiver operating characteristic (ROC) curve analysis in the derivation cohort and its predictive ability was validated in the validation cohort. Independent relationships between predictors, such as critical attenuation value of the non-hypodense region and HE were analyzed using the least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic analysis. Results: The results showed that the attenuation value <64 Hounsfield units (HU) was independently associated with HE [odds ratio (OR), 4.118; 95% confidential interval (CI), 1.897–9.129, p < 0.001] and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) for predicting HE were 36.11%, 81.71%, 1.97, 0.78, 44.8%, 75.7%, and 0.589, respectively. Conclusions: Our research explored and validated the relationship between the attenuation value of the non-hypodense region of hematoma and HE. The attenuation value < 64 HU was an appropriate indicator of early HE. [ABSTRACT FROM AUTHOR]

Purpose: Non-contrast computed tomography (NCCT) is a first-line imaging technique for determining treatment options for acute ischemic stroke (AIS). However, its poor contrast and signal-to-noise ratio limit the diagnosis accuracy for radiologists, and automated AIS lesion segmentation using NCCT also remains a challenge. In this paper, we propose R2U-RNet, a novel model for AIS lesion segmentation using NCCT. Methods: We used an in-house retrospective NCCT dataset with 261 AIS patients with manual lesion segmentation using follow-up diffusion-weighted images. R2U-RNet is based on an R2U-Net backbone with a novel residual refinement unit. Each input image contains two image channels from separate preprocessing procedures. The proposed model incorporates multiscale focal loss to mitigate the class imbalance problem and to leverage the importance of different levels of details. A proposed noisy-label training scheme is utilized to account for uncertainties in the manual annotations. Results: The proposed model outperformed several iconic segmentation models in AIS lesion segmentation using NCCT, and our ablation study demonstrated the efficacy of the proposed model. Statistical analysis of segmentation performance revealed significant effects of regional stroke occurrence and side of the stroke, suggesting the importance of region-specific information for automated segmentation, and the potential influence of the hemispheric difference in clinical data. Conclusion: This study demonstrated the potentials of R2U-RNet model for automated NCCT AIS lesion segmentation. The proposed model can serve as a tool for accelerating AIS diagnoses and improving the treatment quality of AIS patients. [ABSTRACT FROM AUTHOR]

Objective: To describe special algorithm for the semi-autonomous 3-dimensional reconstruction of the pelvicalyceal system based on native computed tomography images of patients with upper urinary tract obstruction. Materials and Methods: Fifty patients with renal colic fitting to inclusion criteria were enrolled. All patients underwent computed tomography urography to perform 3-dimensional reconstruction of the pelvicalyceal system on the affected size based on excretory phase representing "gold standard" and on native phase, which was performed via Medical Imaging Interaction Toolkit program updated with the described algorithm. Five urologists estimated their similarities and the potential use of non-contrast models for interventional planning. Contralateral non-distended pelvicalyceal system was reconstructed to evaluate the viability of the proposed technology in such cases. Surface areas of contrast and non-contrast models were compared. Distended pelvicalyceal system of 1 patient was used to reconstruct virtual endoscopic view. Obtained 3-dimensional non-contrast pelvicalyceal system models were analyzed by an engineer for suitability for 3-dimensional printing. Results: The average surface area of contrast and non-contrast models was 3513 and 3371 mm², respectively (P = .0818). Non-contrast 3-dimensional reconstruction was possible with all distended pelvicalyceal systems and with 9 non-distended cases. Properties of non-contrast models were estimated as 4.3 out of 5. Obtained models were suitable for their intraluminal reconstruction and potential 3-dimensional printing. Conclusion: Described semi-autonomous approach allows for 3-dimensional reconstruction of dilated pelvicalyceal system based on non-contrast computed tomography images. [ABSTRACT FROM AUTHOR]

Early endovascular thrombectomy leads to improved outcomes for patients with proximal occlusions when started within 6 h from onset of symptoms. We present a case illustrating the flow of events for a patient who underwent endovascular thrombectomy in our centre after conventional imaging – a brain non-contrast computed tomography (NCCT) and CT angiogram (CTA) – achieving a door-to-groin time of 195 min. The patient is a 65-year-old who presented with signs and symptoms of a left middle cerebral artery (MCA) territory infarct. His National Institute of Health Stroke Scale (NIHSS) score was 15 on presentation and his brain NCCT showed an Alberta Stroke Programme Early CT Score (ASPECTS) of 8. His CTA showed a left MCA distal M1 occlusion with focal calcification and stenosis of the proximal left internal carotid artery. He was subsequently thrombosed and underwent thrombectomy successfully, with a door-to-groin-puncture time of 195 min. A TICI 2b reperfusion was achieved. His NIHSS score improved to 9 over the next 2 days. For cases with straightforward NCCT and CTA with no contraindications, endovascular thrombectomy should be pursued without delay. A review of the current available literature for the usage of NCCT and CTA as well as the importance of ASPECTS scoring in patient selection for endovascular thrombectomy was included.

Background and PurposeThe ability of attenuation value of the non-hypodense region of hematoma in non-contrast computed tomography (NCCT) for predicting hematoma expansion (HE) remains unclear. Our purpose is to explore this relationship.MethodsTwo cohorts of patients were collected for analysis. The region where we measured hematoma attenuation values was limited to the non-hypodense region that was not adjacent to the normal brain tissue on NCCT. The critical attenuation value was derived via receiver operating characteristic (ROC) curve analysis in the derivation cohort and its predictive ability was validated in the validation cohort. Independent relationships between predictors, such as critical attenuation value of the non-hypodense region and HE were analyzed using the least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic analysis.ResultsThe results showed that the attenuation value

Background: Accurate risk stratification of patients with intracerebral hemorrhage (ICH) could help refine adjuvant therapy selection and better understand the clinical course. We aimed to evaluate the value of radiomics features from hematomal and perihematomal edema areas for prognosis prediction and to develop a model combining clinical and radiomic features for accurate outcome prediction of patients with ICH. Methods: This multicenter study enrolled patients with ICH from January 2016 to November 2021. Their outcomes at 3 months were recorded based on the modified Rankin Scale (good, 0–3; poor, 4–6). Independent clinical and radiomic risk factors for poor outcome were identified through multivariate logistic regression analysis, and predictive models were developed. Model performance and clinical utility were evaluated in both internal and external cohorts. Results: Among the 1098 ICH patients evaluated (mean age, 60 ± 13 years), 703 (64 %) had poor outcomes. Age, hemorrhage volume and location, and Glasgow Coma Scale (GCS) were independently associated with outcomes. The area under the receiver operating characteristic curve (AUC) of the clinical model was 0.881 in the external validation cohort. Addition of the Rad-score (combined hematoma and perihematomal edema area) improved predictive accuracy and model performance (AUC, 0.893), net reclassification improvement, 0.140 (P

Background: Unenhanced computed tomography (CT) is a frequently used imaging method in patients who are evaluated in the emergency department with suspected cerebral vein thrombosis (CVT).Objectives: The aim of this study was to investigate the usefulness of the Hounsfield unit (HU) value determined by CT and its ratio to the patient's hematocrit (Htc) value in the diagnosis of cerebral vein thrombosis.Methods: This retrospective study evaluated 41 patients with acute cerebral venous sinus thrombosis and 41 age- and sex-matched control participants. Two experienced observers independently evaluated the CT scan and measured the attenuation of the dural sinuses.Results: There was no significant difference in age, gender, hemoglobin, and Htc values between the two groups. The mean HU value was 75 ± 7 HU in the CVT group and 52 ± 6 HU in the control group (p < 0.001). The mean HU/Htc ratio was 1.9 ± 0.3 in the CVT group and 1.3 ± 0.1 in the control group (p < 0.001). The optimal threshold value for HU was determined as 66, and sensitivity at this value was 93%, and specificity was 98%. The optimal threshold value for HU/Htc was determined as 1.64, and the sensitivity at this value was 90% and the specificity was 100%.Conclusion: Hyperattenuation in the dural sinuses and the HU/Htc ratio in unenhanced brain CT scans have high diagnostic value in detecting CVT. [ABSTRACT FROM AUTHOR]

To investigate the feasibility of pre-procedural morphological assessment of coronary artery calcification in severely calcified lesions with electrocardiography (ECG)-gated non-contrast computed tomography (CT). Severely calcified coronary arteries in patients who underwent ECG-gated non-contrast CT prior to optical coherence tomography (OCT)-guided percutaneous coronary intervention (PCI) were studied retrospectively. CT and OCT data were co-registered by marking landmark structures such as side branches and reviewed side by side with cross-sectional images. The maximum calcium angle (MCA) and presence of nodular calcification (NC) were evaluated. A total of 496 cross-sections in 16 lesions were included in this analysis. The Pearson correlation coefficient between CT- and OCT-derived MCA was 0.92 (p < 0.001). Bland-Altman plots of OCT-derived MCA in relation to CT-derived MCA showed a mean bias of 4.8 degrees with 95% limits of agreement of - 69.7 to 79.4 degrees. Sensitivity, specificity, and positive and negative predictive values of CT in identifying MCA > 270 degrees were 90.3%, 79.7%, 92.1%, and 97.4%, respectively. Sensitivity, specificity, and positive and negative predictive values of CT in identifying NC were 73.3%, 97.5%, 47.8%, and 99.2%, respectively. ECG-gated non-contrast coronary CT might be helpful to obtain detailed information of severe coronary artery calcification before PCI. [ABSTRACT FROM AUTHOR]

Background: Early hematoma expansion (HE) occurs in patients with intracerebral hemorrhage (ICH) within the first few hours from ICH onset. Hematoma expansion has been considered as an independent predictor of poor clinical outcome and mortality after ICH. Island sign (IS) on the non-contrast computed tomography (NCCT) appears to increase the rate of detection of HE. However, there is insufficient evidence to declare that IS is an independent predictor for ICH patients prognosis and classification.Objectives: To investigate whether IS on NCCT could predict HE and functional outcome following ICH.Methods: Major databases were systematically searched, including PubMed, EMBASE, Cochrane library, and the Chinese database (CNKI, VIP, and Wanfang databases). Studies about the associations between IS and HE or IS and clinical outcome were included. The pooled result used the odds ratio (OR) with a 95% confidence interval (CI) as effect size. Heterogeneity and publication bias were assessed. Subgroup analysis and meta-regression were applied to detect potential factors of heterogeneity.Results: Eleven studies with 4,310 patients were included in the final analysis. The average incidence rate of IS and HE were 21.58 and 33%, respectively. The ideal timing for assessing HE was also not uniform or standardized. We separately performed two meta-analyses. First, 10 studies were included to estimate the association between IS and HE. The pooled OR was statistically significant (OR = 7.61, 95% CI = 3.10–18.67, P < 0.001). Second, four studies were included in the meta-analysis, and the pooled result showed that IS had a significantly positive relationship with poor outcome (OR = 3.83, 95% CI = 2.51–5.85, P < 0.001).Conclusions: This meta-analysis showed that NCCT IS is of great importance and value for evaluation of HE and poor outcome in patients with ICH. Future studies should focus on developing consensus guidelines, and more studies with large sample size and longitudinal design are needed to validate the conclusions.

The aim of this study was to develop a convolutional neural network (CNN) that automatically detects and segments intra-arterial thrombi on baseline non-contrast computed tomography (NCCT) scans. We retrospectively collected computed tomography (CT)-scans of patients with an anterior circulation large vessel occlusion (LVO) from the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands trial, both for training (n = 86) and validation (n = 43). For testing we included patients with (n = 58) and without (n = 45) an LVO from our comprehensive stroke center. Ground truth was established by consensus between two experts using both CT angiography and NCCT. We evaluated the CNN for correct identification of a thrombus, its location and thrombus segmentation and compared these with the results of a neurologist in training and expert neuroradiologist. Sensitivity of the CNN thrombus detection was 0.86, vs. 0.95 and 0.79 for the neuroradiologists. Specificity was 0.65 for the network vs. 0.58 and 0.82 for the neuroradiologists. The CNN correctly identified the location of the thrombus in 79% of the cases, compared to 81% and 77% for the neuroradiologists. The sensitivity and specificity for thrombus identification and the rate for correct thrombus location assessment by the CNN were similar to those of expert neuroradiologists. [ABSTRACT FROM AUTHOR]

Background: The Alberta Stroke Program Early CT Score (ASPECTS) is a systematic method of assessing the extent of early ischemic change on non-contrast computed tomography in patients with acute ischemic stroke. Our objective was to validate an automated ASPECTS scoring method we recently developed on a large data set. Materials and methods: We retrospectively collected 602 acute ischemic stroke patients' non-contrast computed tomography scans. Expert ASPECTS readings on non-contrast computed tomography were compared to automated ASPECTS. Statistical analyses on the total ASPECTS, region level ASPECTS, and dichotomized ASPECTS (≤4 vs. >4) score were conducted. Results: In total, 602 scans were evaluated and 6020 (602 × 10) ASPECTS regions were scored. Median time from stroke onset to computed tomography was 114 min (interquartile range: 73–183 min). Total ASPECTS for the 602 patients generated by the automated method agreed well with expert readings (intraclass correlation coefficient): 0.65 (95% confidence interval (CI): 0.60–0.69). Region level analysis showed that the automated method yielded accuracy of 81.25%, sensitivity of 61.13% (95% CI: 58.4%–63.8%), specificity of 86.56% (95% CI: 85.6%–87.5%), and area under curve of 0.74 (95% CI: 0.73–0.75). For dichotomized ASPECTS (≤4 vs. >4), the automated method demonstrated sensitivity 97.21% (95% CI: 95.4%–98.4%), specificity 57.81% (95% CI: 44.8%–70.1%), accuracy 93.02%, and area under the curve of 0.78 (95% CI: 0.74–0.81). For each individual region (M1–6, lentiform, insula, and caudate), the automated method demonstrated acceptable performance. Conclusion: The automated system we developed approached the stroke expert in performance when scoring ASPECTS on non-contrast computed tomography scans of acute ischemic stroke patients. [ABSTRACT FROM AUTHOR]

Background: Early hematoma expansion (HE) occurs in patients with intracerebral hemorrhage (ICH) within the first few hours from ICH onset. Hematoma expansion has been considered as an independent predictor of poor clinical outcome and mortality after ICH. Island sign (IS) on the non-contrast computed tomography (NCCT) appears to increase the rate of detection of HE. However, there is insufficient evidence to declare that IS is an independent predictor for ICH patients prognosis and classification. Objectives: To investigate whether IS on NCCT could predict HE and functional outcome following ICH. Methods: Major databases were systematically searched, including PubMed, EMBASE, Cochrane library, and the Chinese database (CNKI, VIP, and Wanfang databases). Studies about the associations between IS and HE or IS and clinical outcome were included. The pooled result used the odds ratio (OR) with a 95% confidence interval (CI) as effect size. Heterogeneity and publication bias were assessed. Subgroup analysis and meta-regression were applied to detect potential factors of heterogeneity. Results: Eleven studies with 4,310 patients were included in the final analysis. The average incidence rate of IS and HE were 21.58 and 33%, respectively. The ideal timing for assessing HE was also not uniform or standardized. We separately performed two meta-analyses. First, 10 studies were included to estimate the association between IS and HE. The pooled OR was statistically significant (OR = 7.61, 95% CI = 3.10–18.67, P < 0.001). Second, four studies were included in the meta-analysis, and the pooled result showed that IS had a significantly positive relationship with poor outcome (OR = 3.83, 95% CI = 2.51–5.85, P < 0.001). Conclusions: This meta-analysis showed that NCCT IS is of great importance and value for evaluation of HE and poor outcome in patients with ICH. Future studies should focus on developing consensus guidelines, and more studies with large sample size and longitudinal design are needed to validate the conclusions. [ABSTRACT FROM AUTHOR]