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Purpose One of the major challenges in the management of familial hypercholesterolemia (FH) is the stratification of cardiovascular risk in asymptomatic subjects. Our purpose is to investigate the performance of clinical scoring systems, Montreal-FH-score (MFHS), SAFEHEART risk (SAFEHEART-RE) and FH risk score (FHRS) equations and Dutch Lipid Clinic Network (DLCN) diagnostic score, in predicting extent and severity of CAD at coronary computed tomography angiography (CCTA) in asymptomatic FH. Material and methods One-hundred and thirty-nine asymptomatic FH subjects were prospectively enrolled to perform CCTA. MFHS, FHRS, SAFEHEART-RE and DLCN were assessed for each patient. Atherosclerotic burden scores at CCTA (Agatston score [AS], segment stenosis score [SSS]) and CAD-RADS score were calculated and compared to clinical indices. Results Non-obstructive CAD was found in 109 patients, while 30 patients had a CAD-RADS ≥ 3. Classifying the two groups according to AS, values varied significantly for MFHS (p p p = 0.047), while according to SSS only MFHS and FHRS showed significant differences (p p MFHS proved to have the best discriminatory power (AUC = 0.819; 0.703–0.937, p p p Conclusions Greater values of MFHS, FHRS and SAFEHEART-RE are associated to higher risk of obstructive CAD and might help to select asymptomatic patients that should be referred to CCTA for secondary prevention.

Background: preoperative risk assessment of gastrointestinal stromal tumors (GISTS) is required for optimal and personalized treatment planning. Radiomics features are promising tools to predict risk assessment. The purpose of this study is to develop and validate an artificial intelligence classification algorithm, based on CT features, to define GIST’s prognosis as determined by the Miettinen classification. Methods: patients with histological diagnosis of GIST and CT studies were retrospectively enrolled. Eight morphologic and 30 texture CT features were extracted from each tumor and combined to obtain three models (morphologic, texture and combined). Data were analyzed using a machine learning classification (WEKA). For each classification process, sensitivity, specificity, accuracy and area under the curve were evaluated. Inter- and intra-reader agreement were also calculated. Results: 52 patients were evaluated. In the validation population, highest performances were obtained by the combined model (SE 85.7%, SP 90.9%, ACC 88.8%, and AUC 0.954) followed by the morphologic (SE 66.6%, SP 81.8%, ACC 76.4%, and AUC 0.742) and texture (SE 50%, SP 72.7%, ACC 64.7%, and AUC 0.613) models. Reproducibility was high of all manual evaluations. Conclusions: the AI-based radiomics model using a CT feature demonstrates good predictive performance for preoperative risk stratification of GISTs.

Objective To evaluate if an adequate bowel preparation for CT colonography, can be achieved without diet restriction, using a reduced amount of cathartic agent and fecal tagging. To investigate the influence of patients’ characteristics on bowel preparation and the impact on patients’ compliance. Methods In total, 1446 outpatients scheduled for elective CT colonography were prospectively enrolled. All patients had the same bowel preparation based on a reduced amount of cathartic agent (120 g of macrogol in 1.5 l of water) the day before the exam and a fecal tagging agent (60 ml of hyperosmolar oral iodinated agent) the day of the exam. No dietary restrictions were imposed before the exam. The bowel preparation was evaluated using a qualitative and quantitative score. Patients were grouped by age, gender, and presence of diverticula in both scores. Patients’ compliance has been evaluated with a questionnaire after the end of the exam and with a phone-calling interview the day after the exam. Results According to the qualitative score, adequate bowel preparation was achieved in 1349 patients (93.29%) and no statistical differences were observed among the subgroups of patients. Quantitative scores demonstrated that colon distension was significantly better in younger patients and without diverticula. A good patients’ compliance was observed and most patients (96.5%) were willing to repeat it. Conclusions The lack of diet restriction does not affect the quality of CTC preparation and good patient’s compliance could potentially increase the participation rate in CRC screening programs. Key Points • An adequate quality bowel preparation for CT colonography can be achieved without diet restriction, using a reduced amount of cathartic agent (120 g of macrogol in 1.5 l of water) and fecal tagging (60 ml of hyperosmolar oral iodinated agent). • A bowel preparation based on the combination of a reduced amount of cathartic agent and fecal tagging, without diet restriction, allows obtaining good quality in more than 90% of patients. • The bowel preparation scheme proposed reduces the distress and discomfort experienced by the patients improving adherence to CTC.

Fitz-Hugh-Curtis Syndrome is a rare disorder manifesting as a complication associated with Pelvic Inflammatory Disease. The initial presentation generally consists of concomitant right upper quadrant and lower abdominal pain. This syndrome is characterized by inflammation of the peritoneum with the involvement of hepatic capsule and the tissues surrounding the liver. Intrahepatic involvement is rare and not yet well investigated. An accurate interpretation of Computed Tomography and Magnetic Resonance Imaging findings is missing in the literature. This report presents a case of Fitz-Hugh-Curtis Syndrome in which Computed Tomography and Magnetic Resonance Imaging showed a region of heterogeneously decreased enhancement and abnormal signal intensity within the liver mimicking a lesion.

Objective To evaluate the accuracy and reproducibility of hiatal surface area (HSA) measurement on dedicated multidetector computed tomography (MDCT) acquisition, in patients, previously subjected to laparoscopic sleeve gastrectomy (LSG), and affected by gastroesophageal reflux disease (GERD). Intraoperative HSA measurement was considered the reference standard. Methods Fifty-two candidates for laparoscopic hiatal hernia repair were prospectively included in the study. MDCT images were acquired during swallowing of oral iodinated contrast media and during strain. Measurements were performed by nine readers divided into three groups according to their experience. Results were compared with intraoperative measurements by means of Spearman correlation coefficient. Reproducibility was evaluated with intra- and interreader agreement by means of weighted Cohen’s kappa and intraclass correlation coefficient (ICC). Results Significant differences between MDCT and intraoperative HSA measurements were observed for swallowing imaging for less experienced readers (p = 0.037, 0.025, 0.028 and 0.019). No other statistically significant differences were observed (p > 0.05). The correlation between HSA measured intraoperatively and on MDCT was higher for strain imaging compared to swallowing (r = 0.94—0.92 vs 0.94—0.89). The overall reproducibility of MDCT HSA measurement was excellent (ICC of 0.95; 95% CI 0,8993 to 0,9840) independently of reader’s experience Conclusion HSA can be accurately measured on MDCT images. This method is reproducible and minimally influenced by reader experience. The preoperative measurement of HSA has potential advantages for surgeons in terms of correct approach to hiatal defects in obese patient.

In the past 20 years, Cardiac Computed Tomography (CCT) has become a pivotal technique for the noninvasive diagnostic work-up of coronary and cardiac diseases. Continuous technical and methodological improvements, combined with fast growing scientific evidence, have progressively expanded the clinical role of CCT. Recent large multicenter randomized clinical trials documented the high prognostic value of CCT and its capability to increase the cost-effectiveness of the management of patients with suspected CAD. In the meantime, CCT, initially perceived as a simple non-invasive technique for studying coronary anatomy, has transformed into a multiparametric “one-stop-shop” approach able to investigate the heart in a comprehensive way, including functional, structural and pathophysiological biomarkers. In this complex and revolutionary scenario, it is urgently needed to provide an updated guide for the appropriate use of CCT in different clinical settings. This manuscript, endorsed by the Italian Society of Medical and Interventional Radiology (SIRM) and by the Italian Society of Cardiology (SIC), represents the first of two consensus documents collecting the expert opinion of Radiologists and Cardiologists about current appropriate use of CCT.

To determine whether the quality of a low-volume reduced bowel preparation (LV-RBP) for CT Colonography (CTC) is noninferior to full-volume reduced bowel preparation (FV-RBP) regimen. In this randomized controlled trial, consecutive participants referred for CTC were randomly assigned to receive LV-RBP (52.5 g of PMF104 in 500 mL of water) or FV-RBP (105 g of PMF104 in 1000 mL of water). Images were independently reviewed by five blinded readers who rated the quality of bowel preparation from 0 (best score) to 3 (worst score). The primary outcome was the noninferiority of LV-RBP to FV-RBP in the proportion of colonic segments scored 0 for cleansing quality, with noninferiority margin of 10%. Volume of residual fluids, colonic distension, lesions and polyps detection rates and patient tolerability were secondary outcomes. From March 2019 to January 2020, 110 participants (mean age 65 years ± 14 [standard deviation]; 74 women) were allocated to LV-RBP (n = 55) or FV-RBP (n = 55) arms. There were 92% segment scored 0 in colon cleansing quality in LV-RBP and 94% in FV-RBP for prone scans, and 94% vs 92% for supine scans. Risk difference was – 2.1 (95% CI −5.9 to 1.7) and 1.5 (95% CI −2.4 to 5.4) for prone and supine positions, respectively. Residual fluids and colonic distension were also noninferior in LV-RBP. LV-RBP was associated with a lower number of evacuations during preparation (7 ± 5 vs 10 ± 6, p = 0.002). The LV-RBP for CTC demonstrated noninferior quality of colon cleansing with improved gastrointestinal tolerability compared to FV-RBP regimen.

Objectives The purpose of this study was to follow the long-term progression of diabetic cardiomyopathy by combining cardiac magnetic resonance (CMR) and molecular analysis. Background The evolution of diabetic cardiomyopathy to heart failure affects patients’morbidity and mortality. CMR is the gold standard to assess cardiac remodeling, but there is a lack of markers linked to the mechanism of diabetic cardiomyopathy progression. Methods Five-year longitudinal study on patients with type 2 diabetes mellitus (T2DM) enrolled in the CECSID (Cardiovascular Effects of Chronic Sildenafil in Men With Type 2 Diabetes) trial compared with nondiabetic age-matched controls. CMR with tagging together with metabolic and molecular assessments were performed at baseline and 5-year follow-up. Results A total of 79 men (age 64 ± 8 years) enrolled, comprising 59 men with T2DM compared with 20 nondiabetic age-matched controls. Longitudinal CMR with tagging showed an increase in ventricular mass (ΔLVMi = 13.47 ± 29.66 g/m2; p = 0.014) and a borderline increase in end-diastolic volume (ΔEDVi = 5.16 ± 14.71 ml/m2; p = 0.056) in men with T2DM. Cardiac strain worsened (Δσ = 1.52 ± 3.85%; p = 0.033) whereas torsion was unchanged (Δθ = 0.24 ± 4.04°; p = 0.737), revealing a loss of the adaptive equilibrium between strain and torsion. Contraction dynamics showed a decrease in the systolic time-to-peak (ΔTtP = −35.18 ± 28.81 ms; p Conclusions Within 5 years of diabetic cardiomyopathy onset, increasing cardiac hypertrophy is associated with progressive impairment in strain, depletion of the compensatory role of torsion, and changes in viscoelastic contraction dynamics. These changes are independent of glycemic control and paralleled by the up-regulation of specific microRNAs targeting the extracellular matrix. (Cardiovascular Effects of Chronic Sildenafil in Men With Type 2 Diabetes [CECSID]; NCT00692237 )

Background: To evaluate the diagnostic performance of a Machine Learning (ML) algorithm based on Texture Analysis (TA) parameters in the prediction of Pathological Complete Response (pCR) to Neoadjuvant Chemoradiotherapy (nChRT) in Locally Advanced Rectal Cancer (LARC) patients. Methods: LARC patients were prospectively enrolled to undergo pre- and post-nChRT 3T MRI for initial loco-regional staging. TA was performed on axial T2-Weighted Images (T2-WI) to extract specific parameters, including skewness, kurtosis, entropy, and mean of positive pixels. For the assessment of TA parameter diagnostic performance, all patients underwent complete surgical resection, which served as a reference standard. ROC curve analysis was carried out to determine the discriminatory accuracy of each quantitative TA parameter to predict pCR. A ML-based decisional tree was implemented combining all TA parameters in order to improve diagnostic accuracy. Results: Forty patients were considered for final study population. Entropy, kurtosis and MPP showed statistically significant differences before and after nChRT in patients with pCR; in particular, when patients with Pathological Partial Response (pPR) and/or Pathological Non-Response (pNR) were considered, entropy and skewness showed significant differences before and after nChRT (all p < 0.05). In terms of absolute value changes, pre- and post-nChRT entropy, and kurtosis showed significant differences (0.31 ± 0.35, in pCR, −0.02 ± 1.28 in pPR/pNR, (p = 0.04); 1.87 ± 2.19, in pCR, −0.06 ± 3.78 in pPR/pNR (p = 0.0005); 107.91 ± 274.40, in pCR, −28.33 ± 202.91 in pPR/pNR, (p = 0.004), respectively). According to ROC curve analysis, pre-treatment kurtosis with an optimal cut-off value of ≤3.29 was defined as the best discriminative parameter, resulting in a sensitivity and specificity in predicting pCR of 81.5% and 61.5%, respectively. Conclusions: TA parameters extracted from T2-WI MRI images could play a key role as imaging biomarkers in the prediction of response to nChRT in LARC patients. ML algorithms can be used to efficiently combine all TA parameters in order to improve diagnostic accuracy.

Cyclic GMP–phosphodiesterase type 5 (PDE5) inhibition has been shown to counteract maladaptive cardiac changes triggered by diabetes in some but not all studies. We performed a single-center, 20-week, double-blind, randomized, placebo-controlled trial (NCT01803828) to assess sex differences in cardiac remodeling after PDE5 inhibition in patients with diabetic cardiomyopathy. A total of 122 men and women (45 to 80 years) with long-duration (>3 years) and well-controlled type 2 diabetes mellitus (T2DM; HbA1c < 86 mmol/mol) were selected according to echocardiographic signs of cardiac remodeling. Patients were randomly assigned (1:1) to placebo or oral tadalafil (20 mg, once daily). The primary outcome was to evaluate sex differences in cardiac torsion change. Secondary outcomes were changes in cardiovascular, metabolic, immune, and renal function. At 20 weeks, the treatment-by-sex interaction documented an improvement in cardiac torsion (−3.40°, −5.96; −0.84, P = 0.011) and fiber shortening (−1.19%, −2.24; −0.14, P = 0.027) in men but not women. The primary outcome could not be explained by differences in cGMP concentrations or tadalafil pharmacodynamics. In both sexes, tadalafil improved hsa-miR-199-5p expression, biomarkers of cardiovascular remodeling, albuminuria, renal artery resistive index, and circulating Klotho concentrations. Immune cell profiling revealed an improvement in low-grade chronic inflammation: Classic CD14 ++ CD16 − monocytes reduced, and Tie2 + monocytes increased. Nine patients (14.5%) had minor adverse reactions after tadalafil administration. Continuous PDE5 inhibition could offer a strategy to target cardiorenal complications of T2DM, with sex- and tissue-specific responses. Further studies are needed to confirm Klotho and hsa-miR-199-5p as markers for T2DM complications.

Background Quantitative cardiovascular magnetic resonance T1-mapping is increasingly used for myocardial tissue characterization. However, the lack of standardization limits direct comparability between centers and wider roll-out for clinical use or trials. Purpose To develop a quality assurance (QA) program assuring standardized T1 measurements for clinical use. Methods MR phantoms manufactured in 2013 were distributed, including ShMOLLI T1-mapping and reference T1 and T2 protocols. We first studied the T1 and T2 dependency on temperature and phantom aging using phantom datasets from a single site over 4 years. Based on this, we developed a multiparametric QA model, which was then applied to 78 scans from 28 other multi-national sites. Results T1 temperature sensitivity followed a second-order polynomial to baseline T1 values (R2 > 0.996). Some phantoms showed aging effects, where T1 drifted up to 49% over 40 months. The correlation model based on reference T1 and T2, developed on 1004 dedicated phantom scans, predicted ShMOLLI-T1 with high consistency (coefficient of variation 1.54%), and was robust to temperature variations and phantom aging. Using the 95% confidence interval of the correlation model residuals as the tolerance range, we analyzed 390 ShMOLLI T1-maps and confirmed accurate sequence deployment in 90%(70/78) of QA scans across 28 multiple centers, and categorized the rest with specific remedial actions. Conclusions The proposed phantom QA for T1-mapping can assure correct method implementation and protocol adherence, and is robust to temperature variation and phantom aging. This QA program circumvents the need of frequent phantom replacements, and can be readily deployed in multicenter trials., Highlights • CMR T1 correlated with reference T1 and T2; this derives the QA model for T1-map. • The proposed QA model is robust to temperature variations and phantom aging. • This QA method requires no frequent phantom replacements. • The T1-map QA program can be readily deployed in multicenter trials.

The use of artificial intelligence (AI) and radiomics in the healthcare setting to advance disease diagnosis and management and facilitate the creation of new therapeutics is gaining popularity. Given the vast amount of data collected during cancer therapy, there is significant concern in leveraging the algorithms and technologies available with the underlying goal of improving oncologic care. Radiologists will attain better precision and effectiveness with the advent of AI technology, making machine-assisted medical services a valuable and important option for future oncologic medical care. As a result, it is critical to figure out which specific radiology activities are best positioned to gain from AI and radiomics models and methods of oncologic imaging, while also considering the algorithms' capabilities and constraints. Our purpose is to overview the current evidence and future prospects of AI and radiomics algorithms used in oncologic imaging efforts with an emphasis on the three most frequent cancers worldwide, i.e., lung cancer, breast cancer and colorectal cancer. We discuss how AI and radiomics could be used to detect and characterize cancers and assess therapy response.

Objective The aim of this study was to perform a meta-analysis assessing the diagnostic yield of computed tomography (CT) for the identification of coronavirus disease 2019 (COVID-19) using repeated reverse transcriptase polymerase chain reaction testing or confirmed true-negative state as reference standard. Methods In May 2020, we interrogated the MEDLINE, Embase, and CENTRAL databases. Pooled sensitivity, specificity, and diagnostic odds ratios of CT for COVID-19 identification were computed. Cumulative positive predictive value (PPV) and negative predictive value, stratified by disease prevalence, were calculated. Results Ten articles were included (1332 patients). Pooled sensitivity, specificity, and summary diagnostic odds ratio of CT were 82% [95% confidence interval (CI), 79%-84%], 68% (95% CI, 65%-71%), and 18 (95% CI, 9.8-32.8). The PPV and negative predictive value were 54% (95% CI, 30%-77%) and 94% (95% CI, 88%-99%) at a COVID-19 prevalence lower than 40%, and 80% (95% CI, 62%-91%) and 77% (95% CI, 68%-85%) at a prevalence higher than 40%. Conclusion CT yields higher specificity and PPV, albeit lower sensitivity, than previously reported for the identification of COVID-19.

The aim of this study was to evaluate the appropriateness of the cardiac computed tomography angiography (CCTA) prescriptions according to the “2010-Appropriate-Use-Criteria-for-Cardiac-Computed-Tomography-Angiography” (AUCCTA) and “Clinical-indication-for-CCTA” (CICCTA) among different specialities (Cardiologist [CA], General Practitioner [GP], Other Specialists [OS]) and prescribers’ age. This is a single-centre, single-arm, cohort study. We prospectively enrolled 815 patients (October 2012–May 2019) who underwent a radiological outpatient visit, before CCTA examination. Prescriptions to the examination were categorized as follows: Appropriate (A), Uncertain (U) and Inappropriate (Ina), according to AUCCTA and I, II, III and Inv for CICCTA. This categorization was stratified according to CA, GP and OS and prescribers’ age. CCTA was performed in patients whom indications belong to A/U categories. Eight hundred and fifteen CCTA prescriptions were analysed. An yearly increase in prescriptions was found in the eight-year observational period (2012/2019 projection: 72 vs 223). Considering AUCCTA, indication A was 540/815 (66.3%), indication U was 113/815 (13.9%) and Ina accounted for 162/815 (19.9%; 128/162 [79.0%] indications with stress test listed as criterium of inappropriateness). Only U indications decreased over years (p = 0.003). Regarding CICCTA, 501/815 (61.5%) patients were categorized as I, 144/815 (17.7%) as II, 102/815 (12.5%) as III, 67/815 (8.2%) were INV and 1/815 (0.1%) were non-classified. Clinical referrals were CA in 495/786 (63.0%), GPs in 57/786 (7.3%) GP and OS in 234/786 (29.8%) [p

Interstitial lung disease (ILD) remains a major cause of morbidity and mortality in systemic sclerosis (SSc). Study aim is to characterize and quantify SSc-ILD by using Computer-Aided Lung Informatics for Pathology Evaluation and Rating (CALIPER). Secondly, our objective is to evaluate which radiological pattern is predictive of lung function decline at 12 months follow-up. In the prospective study (IRB 5435), 66 SSc patients underwent high-resolution computerized tomography (HRCT) at baseline. HRCT was performed according to standard protocol using a CT 64GE light speed VCT power scanner. CALIPER classified lung parenchyma on volume units. Every volume unit was classified into radiological parenchymal patterns (honeycombing, reticular and ground glass). Pulmonary function tests (PFTs) were performed at baseline and after 12 months of follow-up. Cigarette smoking and other lung diseases unrelated to SSc are exclusion criteria. CALIPER analysis showed normal lung parenchyma 87.4 ± 9.8%, ground glass 2.8 ± 5.3%, reticular 4 ± 5.7%, and honeycombing 1 ± 1%. In multiple regression analysis, FEV1 (p 0.0001), FVC (p = 0.001), and DLCO (p 0.0001) measurements at baseline showed a negative correlation with the reticular pattern percentage. At follow-up, DLCO reduction showed a positive correlation (p 0.001) with the percentage of ground glass pattern (r = 0.33, beta coefficient = 0.51). In the ROC curve analysis, ground glass score is a good predictor (0.75, p = 0.009; 95% CI 0.59-0.91) of DLCO worsening, defined as a decrease of more than 10% of DLCO. Using a cutoff ≥ 4.5 for ground glass score, the RR for DLCO worsening is 6.8 (p 0.01; 95% CI 1.6-29.2). The results of this study show that CALIPER is useful not only for quantifying lung damage but also for assessing worsening PFTs, but larger studies are needed to confirm these preliminary data.Key Points• At baseline reticular pattern showed negative correlation with PFTs• At follow-up ground glass pattern predicts worsening of DLCO• CALIPER is a useful to quantify lung damage.

Purpose Our purpose is to assess Multiparametric Ultrasound (MPUS) efficacy for evaluation of carotid plaque vulnerability and carotid stenosis degree in comparison with Computed Tomography angiography (CTA) and histology. Material and methods 3D-Arterial Analysis is a 3D ultrasound software that automatically provides the degree of carotid stenosis and a colorimetric map of carotid plaque vulnerability. We enrolled 106 patients who were candidates for carotid endarterectomy. Prior to undergoing surgery, all carotid artery plaques were evaluated with Color-Doppler-US (CDUS), Contrast-Enhanced Ultrasound (CEUS), and 3D Arterial analysis (3DAA) US along with Computerized Tomographic Angiography (CTA) to assess the carotid artery stenosis degree. Post-surgery, the carotid specimens were fixed with 10% neutral buffered formalin solution, embedded in paraffin and used for light microscopic examination to assess plaque vulnerability morphological features. Results The results of the CTA examinations revealed 91 patients with severe carotid stenoses with a resultant diagnostic accuracy of 82.3% for CDUS, 94.5% for CEUS, 98.4% for 3DAA, respectively. The histopathological examination showed 71 vulnerable plaques with diagnostic accuracy values of 85.8% for CDUS, 93.4% for CEUS, 90.3% for 3DAA, 92% for CTA, respectively. Conclusions The combination of CEUS and 3D Arterial Analysis may provide a powerful new clinical tool to identify and stratify “at-risk” patients with atherosclerotic carotid artery disease, identifying vulnerable plaques. These applications may also help in the postoperative assessment of treatment options to manage cardiovascular risks.

The aim of this study was to develop and validate a decision support model using data mining algorithms, based on morphologic features derived from MRI images, to discriminate between complete responders (CR) and non-complete responders (NCR) patients after neoadjuvant chemoradiotherapy (CRT), in a population of patients with locally advanced rectal cancer (LARC).Two populations were retrospectively enrolled: group A (65 patients) was used to train a data mining decision tree algorithm whereas group B (30 patients) was used to validate it. All patients underwent surgery; according to the histology evaluation, patients were divided in CR and NCR. Staging and restaging MRI examinations were retrospectively analysed and seven parameters were considered for data mining classification. Five different classification methods were tested and evaluated in terms of sensitivity, specificity, accuracy and AUC in order to identify the classification model able to achieve the best performance. The best classification algorithm was subsequently applied to group B for validation: sensitivity, specificity, positive and negative predictive value, accuracy and ROC curve were calculated. Inter and intra-reader agreement were calculated.Four features were selected for the development of the classification algorithm: MRI tumor regression grade (MR-TRG), staging volume (SV), tumor volume reduction rate (TVRR) and signal intensity reduction rate (SIRR). The decision tree J48 showed the highest efficiency: when applied to group B, all the CR and 18/21 NCR were correctly classified (sensitivity 85.71%, specificity 100%, PPV 100%, NPV 94.2%, accuracy 95.7%, AUC 0.833). Both inter- and intra-reader evaluation showed good agreement (κ 0.6).The proposed decision support model may help in distinguishing between CR and NCR patients with LARC after CRT.

In the past 20 years, cardiac computed tomography (CCT) has become a pivotal technique for the noninvasive diagnostic workup of coronary and cardiac diseases. Continuous technical and methodological improvements, combined with fast growing scientific evidence, have progressively expanded the clinical role of CCT. Randomized clinical trials documented the value of CCT in increasing the cost-effectiveness of the management of patients with acute chest pain presenting in the emergency department, also during the pandemic. Beyond the evaluation of stents and surgical graft patency, the anatomical and functional coronary imaging have the potential to guide treatment decision-making and planning for complex left main and three-vessel coronary disease. Furthermore, there has been an increasing demand to use CCT for preinterventional planning in minimally invasive procedures, such as transcatheter valve implantation and mitral valve repair. Yet, the use of CCT as a roadmap for tailored electrophysiological procedures has gained increasing importance to assure maximum success. In the meantime, innovations and advanced postprocessing tools have generated new potential applications of CCT from the simple coronary anatomy to the complete assessment of structural, functional and pathophysiological biomarkers of cardiac disease. In this complex and revolutionary scenario, it is urgently needed to provide an updated guide for the appropriate use of CCT in different clinical settings. This manuscript, endorsed by the Italian Society of Cardiology (SIC) and the Italian Society of Medical and Interventional Radiology (SIRM), represents the second of two consensus documents collecting the expert opinion of cardiologists and radiologists about current appropriate use of CCT.

Purpose: to study the possible association of CT-derived quantitative Epicardial Adipose Tissue (EAT) and glycemia at the admission, with severe outcomes in patients with COVID-19.Methods: 229 patients consecutively hospitalized for COVID-19 from March 1st to June 30th2020 were studied.Non contrast chest CT scans, to confirm diagnosis of pneumonia, were performed. EAT volume (cm3) and attenuation (Hounsfield units) were measured using a CT post-processing software. The primary outcome was acute respiratory distress syndrome (ARDS) or in-hospital death.Results: The primary outcome occurred in 56,8% patients. Fasting blood glucose was significantly higher in the group ARDS/death than in the group with better prognosis [114 (98-144) vs 101 (91-118) mg/dl, p=0,001]. EAT volume was higher in patients with vs without the primary outcome [103 (69,25;129,75) vs 78,95 (50,7;100,25) cm3, p Conclusions: Our findings suggest that both blood glucose and EAT, measurable and modifiable targets, could allow the early identification of subjects at greater risk of developing severe complications.

Imaging is fundamental in the management of colorectal cancer (CRC). Contrast-enhanced computed tomography (CECT) and contrast-enhanced magnetic resonance (CEMR) are the imaging modalities recommended to stage and restage CRC. The aim of this review is to summarize the most relevant studies published on the role of contrast-enhanced imaging for the management of CRC. There are published data demonstrating the accuracy of CECT and CEMR for local staging of both colon and rectal cancer, as well as for the evaluation of distant metastases. Moreover, different aspects of these methods, in particular perfusion techniques, are emerging as prognostic biomarkers. The optimization of contrast media injection protocols is essential to ensure reproducibility and high image quality. Contrast-enhanced imaging is mandatory in the management of CRC both for the evaluation of the primary tumor and of distant metastases.

This JACC Scientific Expert Panel provides consensus recommendations for an update of the cardiovascular magnetic resonance (CMR) diagnostic criteria for myocardial inflammation in patients with suspected acute or active myocardial inflammation (Lake Louise Criteria) that include options to use parametric mapping techniques. While each parameter may indicate myocardial inflammation, the authors propose that CMR provides strong evidence for myocardial inflammation, with increasing specificity, if the CMR scan demonstrates the combination of myocardial edema with other CMR markers of inflammatory myocardial injury. This is based on at least one T2-based criterion (global or regional increase of myocardial T2 relaxation time or an increased signal intensity in T2-weighted CMR images), with at least one T1-based criterion (increased myocardial T1, extracellular volume, or late gadolinium enhancement). While having both a positive T2-based marker and a T1-based marker will increase specificity for diagnosing acute myocardial inflammation, having only one (i.e., T2-based OR T1-based) marker may still support a diagnosis of acute myocardial inflammation in an appropriate clinical scenario, albeit with less specificity. The update is expected to improve the diagnostic accuracy of CMR further in detecting myocardial inflammation.

Background Familial hypercholesterolemia (FH) may arise from deleterious monogenic variants in FH‐causing genes as well as from a polygenic cause. We evaluated the relationships between monogenic FH and polygenic hypercholesterolemia in influencing the long‐term response to therapy and the risk of atherosclerosis. Methods and Results A cohort of 370 patients with clinically diagnosed FH were screened for monogenic mutations and a low‐density lipoprotein‐rising genetic risk score >0.69 to identify polygenic cause. Medical records were reviewed to estimate the response to lipid‐lowering therapies and the occurrence of major atherosclerotic cardiovascular events during a median follow‐up of 31.0 months. A subgroup of patients (n=119) also underwent coronary computed tomographic angiography for the evaluation of coronary artery calcium score and severity of coronary stenosis as compared with 135 controls. Two hundred nine (56.5%) patients with hypercholesterolemia were classified as monogenic (FH/M+), 89 (24.1%) as polygenic, and 72 (19.5%) genetically undefined (FH/M−). The response to lipid‐lowering therapy was poorest in monogenic, whereas it was comparable in patients with polygenic hypercholesterolemia and genetically undetermined. Mean coronary artery calcium score and the prevalence of coronary artery calcium >100 units were significantly higher in FH/M+ as compared with both FH/M− and controls. Finally, after adjustments for confounders, we observed a 5‐fold higher risk of incident major atherosclerotic cardiovascular events in FH/M+ (hazard ratio, 4.8; 95% CI, 1.06–21.36; P adj =0.041). Conclusions Monogenic cause of FH is associated with lower response to conventional cholesterol‐lowering therapies as well as with increased burden of coronary atherosclerosis and risk of atherosclerotic‐related events. Genetic testing for hypercholesterolemia is helpful in providing important prognostic information.

Introduction A more structured role of radiographers is advisable to speed up the management of patients with suspected COVID-19. The purpose of our study was to evaluate the diagnostic performance of radiographers in the detection of COVID-19 pneumonia on chest CT using CO-RADS descriptors. Methods CT images of patients who underwent RT-PCR and chest CT due to COVID-19 suspicion between March and July 2020 were analysed retrospectively. Six readers, including two radiologists, two highly experienced radiographers and two less experienced radiographers, independently scored each CT using the CO-RADS lexicon. ROC curves were used to investigate diagnostic accuracy, and Fleiss’κ statistics to evaluate inter-rater agreement. Results 714 patients (419 men; 295 women; mean age: 64 years ±19SD) were evaluated. CO-RADS> 3 was identified as optimal diagnostic threshold. Highly experienced radiographers achieved an average sensitivity of 58.7% (95%CI: 52.5–64.7), an average specificity of 81.8% (95%CI: 77.9–85.2), and a mean AUC of 0.72 (95%CI: 0.68–0.75). Among less experienced radiographers, an average sensitivity of 56.3% (95%CI: 50.1–62.2) and an average specificity of 81.5% (95%CI: 77.6–84.9) were observed, with a mean AUC of 0.71 (95%CI: 0.68–0.74). Consultant radiologists achieved an average sensitivity of 60.0% (95%CI: 53.7–65.8), an average specificity of 81.7% (95%CI: 77.8–85.1), and a mean AUC of 0.73 (95%CI: 0.70–0.77). Conclusion Radiographers can adequately recognise the classic appearances of COVID-19 on CT, as described by the CO-RADS assessment scheme, in a way comparable to expert radiologists. Implications for practice Radiographers, as the first healthcare professionals to evaluate CT images in patients with suspected SARS-CoV-2 infection, could diagnose COVID-19 pneumonia by means of a categorical reporting scheme at CT in a reliable way, hence playing a primary role in the early management of these patients.

PURPOSE: To assess the potential role of computed tomography (CT) texture analysis (CTTA) in identifying vulnerable patients with carotid artery atherosclerosis. METHODS: In this case-control pilot study, 12 patients with carotid atherosclerosis and a subsequent history of transient ischemic attack or stroke were age and sex matched with 12 control cases with asymptomatic carotid atherosclerosis (follow-up time 103.58 ± 9.2 months). CTTA was performed using a commercially available research software package (TexRAD) by an operator blinded to clinical data. CTTA comprised a filtration-histogram technique to extract features at different scales corresponding to spatial scale filter (fine = 2 mm, medium = 3 mm, coarse = 4 mm), followed by quantification using histogram-based statistical parameters: mean, kurtosis, skewness, entropy, standard deviation, and mean value of positive pixels. A single axial slice was selected to best represent the largest cross-section of the carotid bifurcation or the greatest degree of stenosis, in presence of an atherosclerotic plaque, on each side. RESULTS: CTTA revealed a statistically significant difference in skewness between symptomatic and asymptomatic patients at the medium (0.22 ± 0.35 vs - 0.18 ± 0.39, p < 0.001) and coarse (0.23 ± 0.22 vs 0.03 ± 0.29, p = 0.003) texture scales. At the fine-texture scale, skewness (0.20 ± 0.59 vs - 0.18 ± 0.58, p = 0.009) and standard deviation (366.11 ± 117.19 vs 300.37 ± 82.51, p = 0.03) were significant before correction. CONCLUSION: Our pilot study highlights the potential of CTTA to identify vulnerable patients in stroke and TIA. CT texture may have the potential to act as a novel risk stratification tool in patients with carotid atherosclerosis.

Objective To conduct a multireader validation study to evaluate the interobserver variability and the diagnostic accuracy for the lung involvement by COVID-19 of COVID-19 Reporting and Data System (CO-RADS) score. Methods This retrospective study included consecutive symptomatic patients who underwent chest CT and reverse transcriptase-polymerase chain reaction (RT-PCR) from March 2020 to May 2020 for suspected COVID-19. Twelve readers with different levels of expertise independently scored each CT using the CO-RADS scheme for detecting pulmonary involvement by COVID-19. Receiver operating characteristic (ROC) curves were computed to investigate diagnostic yield. Fleiss’ kappa statistics was used to evaluate interreader agreement. Results A total of 572 patients (mean age, 63 ± 20 [standard deviation]; 329 men; 142 patients with COVID-19 and 430 patients without COVID-19) were evaluated. There was a moderate agreement for CO-RADS rating among all readers (Fleiss’ K = 0.43 [95% CI 0.42–0.44]) with a substantial agreement for CO-RADS 1 category (Fleiss’ K = 0.61 [95% CI 0.60–0.62]) and moderate agreement for CO-RADS 5 category (Fleiss’ K = 0.60 [95% CI 0.58–0.61]). ROC analysis showed the CO-RADS score ≥ 4 as the optimal threshold, with a cumulative area under the curve of 0.72 (95% CI 66–78%), sensitivity 61% (95% CI 52–69%), and specificity 81% (95% CI 77–84%). Conclusion CO-RADS showed high diagnostic accuracy and moderate interrater agreement across readers with different levels of expertise. Specificity is higher than previously thought and that could lead to reconsider the role of CT in this clinical setting. Key Points • COVID-19 Reporting and Data System (CO-RADS) demonstrated a good diagnostic accuracy for lung involvement by COVID-19 with an average AUC of 0.72 (95% CI 67–75%). • When a threshold of ≥ 4 was used, sensitivity and specificity were 61% (95% CI 52–69%) and 81% (95% CI 76–84%), respectively. • There was an overall moderate agreement for CO-RADS rating across readers with different levels of expertise (Fleiss’ K = 0.43 [95% CI 0.42–0.44]). Electronic supplementary material The online version of this article (10.1007/s00330-020-07273-y) contains supplementary material, which is available to authorized users.

Background People living with HIV (PLWH) are prone to develop sub-clinical Cardiovascular (CV) disease, despite the effectiveness of combined Antiretroviral Therapy (cART). Algorithms developed to predict CV risk in the general population could be inaccurate when applied to PLWH. Myocardial Extra-Cellular Matrix (ECM) expansion, measured by computed tomography, has been associated with an increased CV vulnerability in HIV-negative population. Measurement of Myocardial Extra-Cellular Volume (ECV) by computed tomography or magnetic resonance, is considered a useful surrogate for clinical evaluation of ECM expansion. In the present study, we aimed to determine the extent of cardiovascular involvement in asymptomatic HIV-infected patients with the use of a comprehensive cardiac computed tomography (CCT) approach. Materials and methods In the present study, ECV in low atherosclerotic CV risk PLWH was compared with ECV of age and gender matched HIV- individuals. 53 asymptomatic HIV + individuals (45 males, age 48 (42.5–48) years) on effective cART (CD4 + cell count: 450 cells/µL (IQR: 328–750); plasma HIV RNA: Results The ECV was significantly higher in HIV + patients than in the control group (ECV: 31% (IQR: 28%-31%) vs. 27.4% (IQR: 25%-28%), p p = 0.014) and the years of exposure to HIV infection (standardized β = 0.53 (0.4–0.92), p p 10 years). Moreover, ECV was independently associated with age of participants (standardized β = 0.42 (0.33–0.89), p = 0.084). Conclusions HIV infection and exposure to antiretrovirals play a detrimental role on ECV expansion. An increase in ECV indicates ECM expansion, which has been associated to a higher CV risk in the general population. The non-invasive evaluation of ECM trough ECV could represent an important tool to further understand the relationship between HIV infection, cardiac pathophysiology and the increased CV risk observed in PLWH.

The purpose of this study was to follow the long-term progression of diabetic cardiomyopathy by combining cardiac magnetic resonance (CMR) and molecular analysis.The evolution of diabetic cardiomyopathy to heart failure affects patients'morbidity and mortality. CMR is the gold standard to assess cardiac remodeling, but there is a lack of markers linked to the mechanism of diabetic cardiomyopathy progression.Five-year longitudinal study on patients with type 2 diabetes mellitus (T2DM) enrolled in the CECSID (Cardiovascular Effects of Chronic Sildenafil in Men With Type 2 Diabetes) trial compared with nondiabetic age-matched controls. CMR with tagging together with metabolic and molecular assessments were performed at baseline and 5-year follow-up.A total of 79 men (age 64 ± 8 years) enrolled, comprising 59 men with T2DM compared with 20 nondiabetic age-matched controls. Longitudinal CMR with tagging showed an increase in ventricular mass (ΔLVMi = 13.47 ± 29.66 g/mWithin 5 years of diabetic cardiomyopathy onset, increasing cardiac hypertrophy is associated with progressive impairment in strain, depletion of the compensatory role of torsion, and changes in viscoelastic contraction dynamics. These changes are independent of glycemic control and paralleled by the up-regulation of specific microRNAs targeting the extracellular matrix. (Cardiovascular Effects of Chronic Sildenafil in Men With Type 2 Diabetes [CECSID]; NCT00692237).

The typical findings on CT in patients affected by novel COVID-19 (coronavirus disease 2019) pneumonia are characterized by ground-glass opacities and/or air space consolidation mainly bilateral and peripherical in distribution, including crazy paving pattern and reversed halo sign. We hereby describe a case of an adolescent male tested positive for COVID-19 with mild respiratory symptoms and presenting with pneumomediastinum as the only CT finding.