[Update on endocarditis 2024]. / Update Endokarditis 2024.

Infective endocarditis (IE) is a life-threatening disease with an increasing incidence despite improved preventive measures. The revision of the European Society of Cardiology (ESC) guidelines on infective endocarditis in 2023 brings significant innovations in prevention, diagnostics, and treatment. Many measures for prophylaxis and prevention have been more clearly defined and given higher recommendation levels. In the diagnostics of IE the use of other imaging modalities besides echocardiography, such as cardiac computed tomography (CT), positron emission tomography (PET)/CT or single photon emission computed tomography (SPECT)/CT with radioactively labeled leukocytes was more strongly emphasized. The diagnostics and treatment of IE associated with a cardiac implantable electronic device (CIED) were also revised. An essential innovation is also the possibility of an outpatient antibiotic treatment for certain patients after initial treatment in hospital. The indications for surgery have also been revised and, in particular, the timing of surgery has been more clearly defined. This article provides an overview of the most important changes.

Target sign in COVID-19, radiological interpretation and diagnostic contribution of digital thoracic tomosynthesis.

INTRODUCTION: Our objectives are: To describe the radiological semiology, clinical-analytical features and prognosis related to the target sign (TS) in COVID-19. To determine whether digital thoracic tomosynthesis (DTT) improves the diagnostic ability of radiography. MATERIAL AND METHODS: Retrospective, descriptive, single-centre, case series study, accepted by our ethical committee. Radiological, clinical, analytical and follow-up characteristics of patients with COVID-19 and TS on radiography and DTT between November 2020 and January 2021 were analysed. RESULTS: Eleven TS were collected in 7 patients, median age 35 years, 57% male. All TS presented with a central nodule and a peripheral ring, and in at least 82%, the lung in between was of normal density. All TS were located in peripheral, basal regions and 91% in posterior regions. TS were multiple in 43%. Contiguous TS shared the peripheral ring. Other findings related to pneumonia were associated in 86% of patients. DTT detected 82% more TS than radiography. Only one patient underwent a CT angiography of the pulmonary arteries, positive for acute pulmonary thromboembolism. Seventy-one per cent presented with pleuritic pain. No distinctive laboratory findings or prognostic worsening were detected. CONCLUSIONS: TS in COVID-19 predominates in peripheral and declining regions and can be multiple. Pulmonary thromboembolism was detected in one case. It occurs in young people, frequently with pleuritic pain and does not worsen the prognosis. DTT detects more than 80 % of TS than radiography.

Right main pulmonary artery distensibility on dynamic ventilation CT and its association with respiratory function.

BACKGROUND: Heartbeat-based cross-sectional area (CSA) changes in the right main pulmonary artery (MPA), which reflects its distensibility associated with pulmonary hypertension, can be measured using dynamic ventilation computed tomography (DVCT) in patients with and without chronic obstructive pulmonary disease (COPD) during respiratory dynamics. We investigated the relationship between MPA distensibility (MPAD) and respiratory function and how heartbeat-based CSA is related to spirometry, mean lung density (MLD), and patient characteristics. METHODS: We retrospectively analyzed DVCT performed preoperatively in 37 patients (20 female and 17 males) with lung cancer aged 70.6 ± 7.9 years (mean ± standard deviation), 18 with COPD and 19 without. MPA-CSA was separated into respiratory and heartbeat waves by discrete Fourier transformation. For the cardiac pulse-derived waves, CSA change (CSAC) and CSA change ratio (CSACR) were calculated separately during inhalation and exhalation. Spearman rank correlation was computed. RESULT: In the group without COPD as well as all cases, CSACR exhalation was inversely correlated with percent residual lung volume (%RV) and RV/total lung capacity (r = -0.68, p = 0.003 and r = -0.58, p = 0.014). In contrast, in the group with COPD, CSAC inhalation was correlated with MLDmax and MLD change rate (MLDmax/MLDmin) (r = 0.54, p = 0.020 and r = 0.64, p = 0.004) as well as CSAC exhalation and CSACR exhalation. CONCLUSION: In patients with insufficient exhalation, right MPAD during exhalation was decreased. Also, in COPD patients with insufficient exhalation, right MPAD was reduced during inhalation as well as exhalation, which implied that exhalation impairment is a contributing factor to pulmonary hypertension complicated with COPD. RELEVANCE STATEMENT: Assessment of MPAD in different respiratory phases on DVCT has the potential to be utilized as a non-invasive assessment for pulmonary hypertension due to lung disease and/or hypoxia and elucidation of its pathogenesis. KEY POINTS: • There are no previous studies analyzing all respiratory phases of right main pulmonary artery distensibility (MPAD). • Patients with exhalation impairment decreased their right MPAD. • Analysis of MPAD on dynamic ventilation computed tomography contributes to understanding the pathogenesis of pulmonary hypertension due to lung disease and/or hypoxia in patients with expiratory impairment.

Multimaterial decomposition in dual-energy CT for characterization of clots from acute ischemic stroke patients.

BACKGROUND: Nowadays, there is no method to quantitatively characterize the material composition of acute ischemic stroke thrombi prior to intervention, but dual-energy CT (DE-CT) offers imaging-based multimaterial decomposition. We retrospectively investigated the material composition of thrombi ex vivo using DE-CT with histological analysis as a reference. METHODS: Clots of 70 patients with acute ischemic stroke were extracted by mechanical thrombectomy and scanned ex vivo in formalin-filled tubes with DE-CT. Multimaterial decomposition in the three components, i.e., red blood cells (RBC), white blood cells (WBC), and fibrin/platelets (F/P), was performed and compared to histology (hematoxylin/eosin staining) as reference. Attenuation and effective Z values were assessed, and histological composition was compared to stroke etiology according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria. RESULTS: Histological and imaging analysis showed the following correlation coefficients for RBC (r = 0.527, p < 0.001), WBC (r = 0.305, p = 0.020), and F/P (r = 0.525, p < 0.001). RBC-rich thrombi presented higher clot attenuation in Hounsfield units than F/P-rich thrombi (51 HU versus 42 HU, p < 0.01). In histological analysis, cardioembolic clots showed less RBC (40% versus 56%, p = 0.053) and more F/P (53% versus 36%, p = 0.024), similar to cryptogenic clots containing less RBC (34% versus 56%, p = 0.006) and more F/P (58% versus 36%, p = 0.003) than non-cardioembolic strokes. No difference was assessed for the mean WBC portions in all TOAST groups. CONCLUSIONS: DE-CT has the potential to quantitatively characterize the material composition of ischemic stroke thrombi. RELEVANCE STATEMENT: Using DE-CT, the composition of ischemic stroke thrombi can be determined. Knowledge of histological composition prior to intervention offers the opportunity to define personalized treatment strategies for each patient to accomplish faster recanalization and better clinical outcomes. KEY POINTS: • Acute ischemic stroke clots present different recanalization success according to histological composition. • Currently, no method can determine clot composition prior to intervention. • DE-CT allows quantitative material decomposition of thrombi ex vivo in red blood cells, white blood cells, and fibrin/platelets. • Histological clot composition differs between stroke etiology. • Insights into the histological composition in situ offer personalized treatment strategies.

N-(2,3-dihydroxypropyl) carbamoyl side chain: a potentially significant factor for recurrent iodinated contrast medium-related adverse drug reactions.

PURPOSE: To determine whether switching to contrast media based on the sharing of N-(2,3-dihydroxypropyl) carbamoyl side chain reduces the recurrence of iodinated contrast media (ICM)-associated adverse drug reactions (ADRs). MATERIALS AND METHODS: This single-center retrospective study included 2133 consecutive patients (mean age ± SD, 56.1 ± 11.4 years; male, 1052 [49.3%]) who had a history of ICM-associated ADRs and underwent contrast-enhanced CT examinations. The per-patient and per-exam-based recurrence ADR rates were compared between cases of switching and non-switching the ICM from ICMs that caused the previous ADRs, and between cases that used ICMs with common and different carbamoyl side chains from ICMs that caused the previous ADRs. Downgrade rates (no recurrence or the occurrence of ADR less severe than index ADRs) were also compared. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analysis were additionally performed. RESULTS: In per-patient analysis, switching of ICM showed a lower recurrence rate (switching, 10.4% [100/965] vs. non-switching, 28.4% [332/1168]), with the adjusted odds ratio (OR) of 0.27 (95% CI: 0.21, 0.34; p < 0.001). The result was consistent in PSM (OR, 0.29 [95% CI: 0.22, 0.39]; p < 0.001), IPTW (OR, 0.28 [95% CI: 0.22, 0.36]; p < 0.001), and in per-exam analysis (5.5% vs. 13.8%; OR, 0.32 [95% CI: 0.27, 0.37]; p < 0.001). There was lower per-exam recurrence (5.0% [195/3938] vs. 7.8% [79/1017]; OR, 0.63 [95% CI: 0.47, 0.83]; p = 0.001) and higher downgrade rates (95.6% [3764/3938] vs. 93.3% [949/1017]; OR, 1.51 [95% CI: 1.12, 2.03]; p = 0.006) when using different side chain groups. CONCLUSION: Switching to an ICM with a different carbamoyl side chain reduced the recurrent ADRs and their severity during subsequent examinations. CLINICAL RELEVANCE STATEMENT: Switching to an iodinated contrast media with a different carbamoyl side chain reduced the recurrent adverse drug reactions and their severity during subsequent examinations.

Influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting detector CT.

The goal of this experimental study was to quantify the influence of helical pitch and gantry rotation time on image quality and file size in ultrahigh-resolution photon-counting CT (UHR-PCCT). Cervical and lumbar spine, pelvis, and upper legs of two fresh-frozen cadaveric specimens were subjected to nine dose-matched UHR-PCCT scan protocols employing a collimation of 120 × 0.2 mm with varying pitch (0.3/1.0/1.2) and rotation time (0.25/0.5/1.0 s). Image quality was analyzed independently by five radiologists and further substantiated by placing normed regions of interest to record mean signal attenuation and noise. Effective mAs, CT dose index (CTDIvol), size-specific dose estimate (SSDE), scan duration, and raw data file size were compared. Regardless of anatomical region, no significant difference was ascertained for CTDIvol (p ≥ 0.204) and SSDE (p ≥ 0.240) among protocols. While exam duration differed substantially (all p ≤ 0.016), the lowest scan time was recorded for high-pitch protocols (4.3 ± 1.0 s) and the highest for low-pitch protocols (43.6 ± 15.4 s). The combination of high helical pitch and short gantry rotation times produced the lowest perceived image quality (intraclass correlation coefficient 0.866; 95% confidence interval 0.807-0.910; p < 0.001) and highest noise. Raw data size increased with acquisition time (15.4 ± 5.0 to 235.0 ± 83.5 GByte; p ≤ 0.013). Rotation time and pitch factor have considerable influence on image quality in UHR-PCCT and must therefore be chosen deliberately for different musculoskeletal imaging tasks. In examinations with long acquisition times, raw data size increases considerably, consequently limiting clinical applicability for larger scan volumes.

Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation.

OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules. METHODS AND MATERIALS: In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty. RESULTS: The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group. CONCLUSION: The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance. CLINICAL RELEVANCE STATEMENT: Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction. KEY POINTS: • Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm. • Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse. • Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.

Predicting microvascular invasion in small (≤ 5 cm) hepatocellular carcinomas using radiomics-based peritumoral analysis.

OBJECTIVE: We assessed the predictive capacity of computed tomography (CT)-enhanced radiomics models in determining microvascular invasion (MVI) for isolated hepatocellular carcinoma (HCC) ≤ 5 cm within peritumoral margins of 5 and 10 mm. METHODS: Radiomics software was used for feature extraction. We used the least absolute shrinkage and selection operator (LASSO) algorithm to establish an effective model to predict patients' preoperative MVI status. RESULTS: The area under the curve (AUC) values in the validation sets for the 5- and 10-mm radiomics models concerning arterial tumors were 0.759 and 0.637, respectively. In the portal vein phase, they were 0.626 and 0.693, respectively. Additionally, the combined radiomics model for arterial tumors and the peritumoral 5-mm margin had an AUC value of 0.820. The decision curve showed that the combined tumor and peritumoral radiomics model exhibited a somewhat superior benefit compared to the traditional model, while the fusion model demonstrated an even greater advantage, indicating its significant potential in clinical application. CONCLUSION: The 5-mm peritumoral arterial model had superior accuracy and sensitivity in predicting MVI. Moreover, the combined tumor and peritumoral radiomics model outperformed both the individual tumor and peritumoral radiomics models. The most effective combination was the arterial phase tumor and peritumor 5-mm margin combination. Using a fusion model that integrates tumor and peritumoral radiomics and clinical data can aid in the preoperative diagnosis of the MVI of isolated HCC ≤ 5 cm, indicating considerable practical value. CRITICAL RELEVANCE STATEMENT: The radiomics model including a 5-mm peritumoral expansion is a promising noninvasive biomarker for preoperatively predicting microvascular invasion in patients diagnosed with a solitary HCC ≤ 5 cm. KEY POINTS: • Radiomics features extracted at a 5-mm distance from the tumor could better predict hepatocellular carcinoma microvascular invasion. • Peritumoral radiomics can be used to capture tumor heterogeneity and predict microvascular invasion. • This radiomics model stands as a promising noninvasive biomarker for preoperatively predicting MVI in individuals.

Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction.

BACKGROUND: To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR). METHODS: Conventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used. RESULTS: Significantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010). CONCLUSIONS: DL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients. RELEVANCE STATEMENT: DL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application. KEY POINTS: • Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. • A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. • DL-MAR showed best image quality and diagnostic confidence. • Highest contrast-to-noise ratios were observed on the DL-MAR images.

ESR Essentials: Imaging of sacroiliitis-practice recommendations by ESSR.

Sacroiliitis is commonly seen in patients with axial spondyloarthritis, in whom timely diagnosis and treatment are crucial to prevent irreversible structural damage. Imaging has a prominent place in the diagnostic process and several new imaging techniques have been examined for this purpose. We present a summary of updated evidence-based practice recommendations for imaging of sacroiliitis. MRI remains the imaging modality of choice for patients with suspected sacroiliitis, using at least four sequences: coronal oblique T1-weighted and fluid-sensitive sequences, a perpendicular axial oblique sequence, and a sequence for optimal evaluation of the bone-cartilage interface. Both active inflammatory and structural lesions should be described in the report, indicating location and extent. Radiography and CT, especially low-dose CT, are reasonable alternatives when MRI is unavailable, as patients are often young. This is particularly true to evaluate structural lesions, at which CT excels. Dual-energy CT with virtual non-calcium images can be used to depict bone marrow edema. Knowledge of normal imaging features in children (e.g., flaring, blurring, or irregular appearance of the articular surface) is essential for interpreting sacroiliac joint MRI in children because these normal processes can simulate disease. CLINICAL RELEVANCE STATEMENT: Sacroiliitis is a potentially debilitating disease if not diagnosed and treated promptly, before structural damage to the sacroiliac joints occurs. Imaging has a prominent place in the diagnostic process. We present a summary of practice recommendations for imaging of sacroiliitis, including several new imaging techniques. KEY POINTS: • MRI is the modality of choice for suspected inflammatory sacroiliitis, including a joint-line-specific sequence for optimal evaluation of the bone-cartilage interface to improve detection of erosions. • Radiography and CT (especially low-dose CT) are reasonable alternatives when MRI is unavailable. • Knowledge of normal imaging features in children is mandatory for interpretation of MRI of pediatric sacroiliac joints.

Post-mortem skeletal survey (PMSS) versus post-mortem computed tomography (PMCT) for the detection of corner metaphyseal lesions (CML) in children.

OBJECTIVES: Corner metaphyseal lesions (CMLs) are specific for child abuse but challenging to detect on radiographs. The accuracy of CT for CML detection is unknown. Our aim was to compare diagnostic accuracy for CML detection on post-mortem skeletal surveys (PMSS, plain radiography) versus post-mortem CT (PMCT). METHODS: A 10-year retrospective review was performed at a children's hospital for patients having PMSS, PMCT and histopathological correlation (reference standard) for suspected CMLs. Twenty-four radiologists independently reported the presence or absence of CMLs in all cases in a blinded randomised cross-over design across two rounds. Logistic regression models were used to compare accuracy between modalities. RESULTS: Twenty CMLs were reviewed for each of the 10 subjects (200 metaphyses in all). Among them, 20 CMLs were confirmed by bone histopathology. Sensitivity for these CMLs was significantly higher for PMSS (69.6%, 95% CI 61.7 to 76.7) than PMCT (60.5%, 95% CI 51.9 to 68.6). Using PMSS for detection of CMLs would yield one extra correct diagnosis for every 11.1 (95% CI 6.6 to 37.0) fractured bones. In contrast, specificity was higher on PMCT (92.7%, 95% CI 90.3 to 94.5) than PMSS (90.5%, 95% CI 87.6 to 92.8) with an absolute difference of 2.2% (95% CI 1.0 to 3.4, p < 0.001). More fractures were reported collectively by readers on PMSS (785) than on PMCT (640). CONCLUSION: PMSS remains preferable to PMCT for CML evaluation. Any investigation of suspected abuse or unexplained deaths should include radiographs of the limbs to exclude CMLs. CLINICAL RELEVANCE STATEMENT: In order to avoid missing evidence that could indicate child abuse as a contributory cause for death in children, radiographs of the limbs should be performed to exclude CMLs, even if a PMCT is being acquired. KEY POINTS: • Corner metaphyseal lesions (CMLs) are indicative for abuse, but challenging to detect. Skeletal surveys (i.e. radiographs) are standard practice; however, accuracy of CT is unknown. • Sensitivity for CML detection on radiographs is significantly higher than CT. • Investigation of unexplained paediatric deaths should include radiographs to exclude CMLs even if CT is also being performed.

CEM immediately after contrast-enhanced CT: a one-step staging of breast cancer.

BACKGROUND: Contrast-enhanced mammography (CEM) is a promising technique. We evaluated the diagnostic potential of CEM performed immediately after contrast-enhanced computed tomography (CE-CT). METHODS: Fifty patients with breast cancer underwent first CE-CT and then CEM without additional contrast material injection. Two independent radiologists evaluated CEM images. The sensitivity of CEM for detecting index and additional malignant lesions was compared with that of mammography/ultrasonography by the McNemar test, using histopathology as a reference standard. Interobserver agreement for detection of malignant lesions, for classifying index tumors, and for evaluating index tumor size and extent was assessed using Cohen κ. Pearson correlation was used for correlating index tumor size/extent at CEM or mammography/ultrasonography with histopathology. RESULTS: Of the 50 patients, 30 (60%) had unifocal disease while 20 (40%) had multicentric or multifocal disease; 5 of 20 patients with multicentric disease (25%) had bilateral involvement, for a total of 78 malignant lesions, including 72 (92%) invasive ductal and 6 (8%) invasive lobular carcinomas. Sensitivity was 63/78 (81%, 95% confidence interval 70.27-88.82) for unenhanced breast imaging and 78/78 (100%, 95.38-100) for CEM (p < 0.001). The interobserver agreement for overall detection of malignant lesions, for classifying index tumor, and for evaluating index tumor size/extent were 0.94, 0.95, and 0.86 κ, respectively. For index tumor size/extent, correlation coefficients as compared with histological specimens were 0.50 for mammography/ultrasonography and 0.75 for CEM (p ≤ 0.010). CONCLUSIONS: CEM acquired immediately after CE-CT without injection of additional contrast material showed a good performance for local staging of breast cancer. RELEVANCE STATEMENT: When the CEM suite is near to the CE-CT acquisition room, CEM acquired immediately after, without injection of additional contrast material, could represent a way for local staging of breast cancer to be explored in larger prospective studies. KEY POINTS: • CEM represents a new accurate tool in the field of breast imaging. • An intravenous injection of iodine-based contrast material is required for breast gland evaluation. • CEM after CE-CT could provide a one-stop tool for breast cancer staging.

Pulmonary CT perfusion robustly measures cardiac output in the context of multilevel pulmonary occlusion: a porcine study.

BACKGROUND: To validate pulmonary computed tomography (CT) perfusion in a porcine model by invasive monitoring of cardiac output (CO) using thermodilution method. METHODS: Animals were studied at a single center, using a Swan-Ganz catheter for invasive CO monitoring as a reference. Fifteen pigs were included. Contrast-enhanced CT perfusion of the descending aorta and right and left pulmonary artery was performed. For variation purposes, a balloon catheter was inserted to block the contralateral pulmonary vascular bed; additionally, two increased CO settings were created by intravenous administration of catecholamines. Finally, stepwise capillary occlusion was performed by intrapulmonary arterial injection of 75-µm microspheres in four stages. A semiautomatic selection of AFs and a recirculation-aware tracer-kinetics model to extract the first-pass of AFs, estimating blood flow with the Stewart-Hamilton method, was implemented. Linear mixed models (LMM) were developed to calibrate blood flow calculations accounting with individual- and cohort-level effects. RESULTS: Nine of 15 pigs had complete datasets. Strong correlations were observed between calibrated pulmonary (0.73, 95% confidence interval [CI] 0.6-0.82) and aortic blood flow measurements (0.82, 95% CI, 0.73-0.88) and the reference as well as agreements (± 2.24 L/min and ± 1.86 L/min, respectively) comparable to the state of the art, on a relatively wide range of right ventricle-CO measurements. CONCLUSIONS: CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by referencing the invasive CO. RELEVANCE STATEMENT: Possible clinical applications of CT perfusion for measuring CO could be in acute pulmonary thromboembolism or to assess right ventricular function to show impairment or mismatch to the left ventricle. KEY POINTS: • CT perfusion measures flow in vessels. • CT perfusion measures cumulative cardiac output in the aorta and pulmonary vessels. • CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by using the invasive CO as a reference standard.

Functional knee phenotypes appear to be more suitable for the Chinese OA population compared with CPAK classification: A study based on 3D CT reconstruction models.

PURPOSE: The aim of this study was to investigate the distribution of coronal plane alignment of the knee (CPAK) classification and functional knee phenotypes in a Chinese osteoarthritis (OA) population and to compare different lower limb alignment targets according to the distribution characteristics to find suitable total knee arthroplasty (TKA) bone cut strategies for the Chinese OA patients. METHODS: The computed tomography (CT) images were retrospectively collected and the three-dimensional (3D) models were reconstructed from 434 Chinese OA patients, including 93 males and 341 females, with a mean age of 66.4 ± 9.3 years. Femoral mechanical angle (FMA), tibial mechanical angle (TMA) and mechanical hip-knee-ankle angle (mHKA) were measured on the 3D models. Arithmetic hip-knee-ankle angle (aHKA) was calculated using FMA plus TMA, and joint line obliquity was calculated as 180 + TMA-FMA. The CPAK according to MacDessi and the functional knee phenotypes according to Hirschmann were performed. In addition, the suitable TKA bone cut strategies were explored according to the phenotypes and based on the characteristics of different alignment targets, such as mechanical alignment, anatomic alignment (AA), kinematic alignment, restricted KA (rKA) and adjusted MA (aMA). Statistical differences were determined using the independent-samples t-test or the two independent-samples Wilcoxon test, with p < 0.05 considered statistically significant. RESULTS: The Chinese OA population showed a varus alignment tendency (mHKA = 172.1° ± 7.2°), to which the TMA was a major contributor (TMA = 84.7° ± 4.4° vs. FMA = 91.3° ± 3.2°). The mHKA was on average 3.9° more varus than the aHKA. A total of 140 functional knee phenotypes were found and 45.6% were concentrated in VARFMA3°-NEUFMA0° to VARTMA3°-NEUTMA0°. More than 70% of patients had different FMA and TMA phenotypes. There were 92.9% of CPAK distributed in types I to IV, with type I accounting for 53.9%. The FMA phenotypes were less changed if the aMA and rKA were chosen, and the TMA phenotypes were less changed if the AA and rKA were chosen. CONCLUSION: Compared with the CPAK, the functional knee phenotypes were more suitable for the Chinese OA population with a wide distribution and a varus tendency, and it seemed more appropriate to choose aMA and rKA as TKA alignment targets for resection. LEVEL OF EVIDENCE: Level Ⅲ.

ESR Essentials: diagnosis of hepatocellular carcinoma-practice recommendations by ESGAR.

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy and a leading cause of cancer related death worldwide. Current guidelines for the noninvasive diagnosis of HCC are provided by the European Association for the Study of the Liver (EASL), the American Association for the Study of Liver Diseases (AASLD) which endorsed the Liver Imaging Reporting and Data System (LI-RADS) algorithm, the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC), and the Asian-Pacific Association for the Study of the Liver (APASL). These allow the diagnosis of HCC in high-risk patients in the presence of typical imaging features on contrast-enhanced CT, MRI, or contrast-enhanced ultrasound. Size, non-rim arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, and growth are major imaging features and they should be combined for the diagnosis of HCC. This article provides concise and relevant practice recommendations aimed at general radiologist audience, summarizing the best practice and informing on the essential imaging criteria for the diagnosis of HCC, while also discussing the high-risk population criteria, imaging modalities, and imaging features according to the current guidelines. KEY POINTS: • Noninvasive diagnosis of hepatocellular carcinoma (HCC) can be provided only in patients at high risk. • Contrast-enhanced CT or MRI are the first-line imaging exams for the diagnosis of HCC. • Major imaging features should be combined to provide the diagnosis of definitive HCC.

Diagnostic performance and image quality of an image-based denoising algorithm applied to radiation dose-reduced CT in diagnosing acute appendicitis.

PURPOSE: To evaluate diagnostic performance and image quality of ultralow-dose CT (ULDCT) in diagnosing acute appendicitis with an image-based deep-learning denoising algorithm (IDLDA). METHODS: This retrospective multicenter study included 180 patients (mean ± standard deviation, 29 ± 9 years; 91 female) who underwent contrast-enhanced 2-mSv CT for suspected appendicitis from February 2014 to August 2016. We simulated ULDCT from 2-mSv CT, reducing the dose by at least 50%. Then we applied an IDLDA on ULDCT to produce denoised ULDCT (D-ULDCT). Six radiologists with different experience levels (three board-certified radiologists and three residents) independently reviewed the ULDCT and D-ULDCT. They rated the likelihood of appendicitis and subjective image qualities (subjective image noise, diagnostic acceptability, and artificial sensation). One radiologist measured image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). We used the receiver operating characteristic (ROC) analyses, Wilcoxon's signed-rank tests, and paired t-tests. RESULTS: The area under the ROC curves (AUC) for diagnosing appendicitis ranged 0.90-0.97 for ULDCT and 0.94-0.97 for D-ULDCT. The AUCs of two residents were significantly higher on D-ULDCT (AUC difference = 0.06 [95% confidence interval, 0.01-0.11; p = .022] and 0.05 [0.00-0.10; p = .046], respectively). D-ULDCT provided better subjective image noise and diagnostic acceptability to all six readers. However, the response of board-certified radiologists and residents differed in artificial sensation (all p ≤ .003). D-ULDCT showed significantly lower image noise, higher SNR, and higher CNR (all p < .001). CONCLUSION: An IDLDA can provide better ULDCT image quality and enhance diagnostic performance for less-experienced radiologists.

Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).

PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use of SilverBeam filter and deep learning reconstruction algorithm allows for reduced radiation dose chest CT scanning in patients with lymphangioleiomyomatosis (LAM). MATERIAL AND METHODS: In a single-center prospective study, 60 consecutive patients with LAM underwent chest CT at standard and ultra-low radiation doses. Standard dose scan was performed with standard copper filter and ultra-low dose scan was performed with SilverBeam filter. Scans were reconstructed using a soft tissue kernel with deep learning reconstruction (AiCE) technique and using a soft tissue kernel with hybrid iterative reconstruction (AIDR3D). Cyst scores were quantified by semi-automated software. Signal-to-noise ratio (SNR) was calculated for each reconstruction. Data were analyzed by linear correlation, paired t-test, and Bland-Altman plots. RESULTS: Patients averaged 49.4 years and 100% were female with mean BMI 26.6 ± 6.1 kg/m2. Cyst score measured by AiCE reconstruction with SilverBeam filter correlated well with that of AIDR3D reconstruction with standard filter, with a 1.5% difference, and allowed for an 85.5% median radiation dosage reduction (0.33 mSv vs. 2.27 mSv, respectively, p < 0.001). Compared to standard filter with AIDR3D, SNR for SilverBeam AiCE images was slightly lower (3.2 vs. 3.1, respectively, p = 0.005). CONCLUSION: SilverBeam filter with deep learning reconstruction reduces radiation dosage of chest CT, while maintaining accuracy of cyst quantification as well as image quality in cystic lung disease. CLINICAL RELEVANCE STATEMENT: Radiation dosage from chest CT can be significantly reduced without sacrificing image quality by using silver filter in combination with a deep learning reconstructive algorithm. KEY POINTS: • Deep learning reconstruction in chest CT had no significant effect on cyst quantification when compared to conventional hybrid iterative reconstruction. • SilverBeam filter reduced radiation dosage by 85.5% compared to standard dose chest CT. • SilverBeam filter in coordination with deep learning reconstruction maintained image quality and diagnostic accuracy for cyst quantification when compared to standard dose CT with hybrid iterative reconstruction.

Artificial intelligence for assessment of vascular involvement and tumor resectability on CT in patients with pancreatic cancer.

OBJECTIVE: This study aimed to develop and evaluate an automatic model using artificial intelligence (AI) for quantifying vascular involvement and classifying tumor resectability stage in patients with pancreatic ductal adenocarcinoma (PDAC), primarily to support radiologists in referral centers. Resectability of PDAC is determined by the degree of vascular involvement on computed tomography scans (CTs), which is associated with considerable inter-observer variability. METHODS: We developed a semisupervised machine learning segmentation model to segment the PDAC and surrounding vasculature using 613 CTs of 467 patients with pancreatic tumors and 50 control patients. After segmenting the relevant structures, our model quantifies vascular involvement by measuring the degree of the vessel wall that is in contact with the tumor using AI-segmented CTs. Based on these measurements, the model classifies the resectability stage using the Dutch Pancreatic Cancer Group criteria as either resectable, borderline resectable, or locally advanced (LA). RESULTS: We evaluated the performance of the model using a test set containing 60 CTs from 60 patients, consisting of 20 resectable, 20 borderline resectable, and 20 locally advanced cases, by comparing the automated analysis obtained from the model to expert visual vascular involvement assessments. The model concurred with the radiologists on 227/300 (76%) vessels for determining vascular involvement. The model's resectability classification agreed with the radiologists on 17/20 (85%) resectable, 16/20 (80%) for borderline resectable, and 15/20 (75%) for locally advanced cases. CONCLUSIONS: This study demonstrates that an AI model may allow automatic quantification of vascular involvement and classification of resectability for PDAC. RELEVANCE STATEMENT: This AI model enables automated vascular involvement quantification and resectability classification for pancreatic cancer, aiding radiologists in treatment decisions, and potentially improving patient outcomes. KEY POINTS: • High inter-observer variability exists in determining vascular involvement and resectability for PDAC. • Artificial intelligence accurately quantifies vascular involvement and classifies resectability for PDAC. • Artificial intelligence can aid radiologists by automating vascular involvement and resectability assessments.

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

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

Risk of hematologic malignant neoplasms from head CT radiation in children and adolescents presenting with minor head trauma: a nationwide population-based cohort study.

OBJECTIVES: The carcinogenic risks of CT radiation in children and adolescents remain debated. We aimed to assess the carcinogenic risk of CTs performed in children and adolescents with minor head trauma. METHODS: In this nationwide population-based cohort study, we included 2,411,715 patients of age 0-19 with minor head trauma from 2009 to 2017. We excluded patients with elevated cancer risks or substantial past medical radiation exposure. Patients were categorized into CT-exposed or CT-unexposed group according to claim codes for head CT. The primary outcome was development of hematologic malignant neoplasms. Secondary outcomes included development of malignant solid neoplasms and benign neoplasms in the brain. We measured the incidence rate ratio (IRR) and incidence rate difference (IRD) using G-computation with Poisson regression adjusting for age, sex, hospital setting, and the type of head trauma. RESULTS: Hematologic malignant neoplasms developed in 100 of 216,826 patients during 1,303,680 person-years in the CT-exposed group and in 808 of 2,194,889 patients during 13,501,227 person-years in the CT-unexposed group. For hematologic malignant neoplasms, the IRR was 1.29 (95% CI, 1.03-1.60) and the IRD was 1.71 (95% CI, 0.04-3.37) per 100,000 person-years at risk. The majority of excess hematologic malignant neoplasms were leukemia (IRR, 1.40 [98.3% CI, 1.05-1.87]; IRD, 1.59 [98.3% CI, 0.02-3.16] per 100,000 person-years at risk). There were no between-group differences for secondary outcomes. CONCLUSIONS: Radiation exposure from head CTs in children and adolescents with minor head trauma was associated with an increased incidence of hematologic malignant neoplasms. CLINICAL RELEVANCE STATEMENT: Our study provides a quantitative grasp of the risk conferred by CT examinations in children and adolescents, thereby providing the basis for cost-benefit analyses and evidence-driven guidelines for patient triaging in head trauma. KEY POINTS: • This nationwide population-based cohort study showed that radiation exposure from head CTs in children and adolescents was associated with a higher incidence of hematologic malignant neoplasms. • The incidence rate of hematologic malignant neoplasms in the CT-exposed group was 29% higher than that in the CT-unexposed group (IRR, 1.29 [95% CI, 1.03-1.60]), and there were approximately 1.7 excess neoplasms per 100,000 person-years at risk in the CT-exposed group (IRD, 1.71 [0.04-3.37]). • Our study provides a quantified grasp of the risk conferred by CT examinations in children and adolescents, while controlling for biases observed in previous studies via specifying CT indication and excluding patients with predisposing conditions for cancer development.