Completeness of reporting in abstracts of randomized controlled trials assessing interventional radiology for liver disease.

PURPOSE: To assess the completeness of reporting in abstracts of published randomized controlled trials (RCTs) assessing interventional radiology (IR) for liver disease; to assess whether publication of the 2017 CONSORT update for nonpharmacological treatments (NPT) resulted in changes in abstract reporting; and to identify factors associated with better reporting. MATERIAL AND METHODS: MEDLINE and Embase were searched to identify RCTs of IR for liver disease (January 2015-September 2020). Two reviewers assessed the completeness of abstract reporting according to the CONSORT-NPT-2017-update. The primary outcome was the mean number of CONSORT items completely reported among 10 items reported in <50% of the abstracts published in 2015. A time series analysis assessed the evolution trend over time. A multivariate regression model was used to identify factors associated with better reporting. RESULTS: A total of 107 abstracts of RCTs published in 61 journals were included. Overall, 74% (45/61) of journals endorsed the main CONSORT guidelines, of which 60% (27/45) had a policy to implement them. The mean number of primary outcome items completely reported increased by 0.19 over the study period. The publication of the CONSORT-NPT update did not lead to an increase in the trend of items reported (increase of 0.04 items/month before vs. 0.02 after, P=0.41). Factors associated with more complete reporting were impact factor (OR=1.13; 95%CI:1.07-1.18) and endorsement of CONSORT with an implementation policy (OR=8.29; 95%CI:2.04-33.65). CONCLUSION: Completeness of reporting is incomplete in abstracts of trials of IR liver disease and did not improve after publication of the CONSORT-NPT-2017 update with abstract guidance.

Performance of non-invasive biomarkers compared with invasive methods for risk prediction of posthepatectomy liver failure in hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure (PHLF) is a rare but dreaded complication. The aim was to test whether a combination of non-invasive biomarkers (NIBs) and CT data could predict the risk of PHLF in patients who underwent resection of hepatocellular carcinoma (HCC). METHODS: Patients with HCC who had liver resection between 2012 and 2020 were included. A relevant combination of NIBs (NIB model) to model PHLF risk was identified using a doubly robust estimator (inverse probability weighting combined with logistic regression). The adjustment variables were body surface area, ASA fitness grade, male sex, future liver remnant (FLR) ratio, difficulty of liver resection, and blood loss. The reference invasive biomarker (IB) model comprised a combination of pathological analysis of the underlying liver and hepatic venous pressure gradient (HVPG) measurement. Various NIB and IB models for prediction of PHLF were fitted and compared. NIB model performances were validated externally. Areas under the curve (AUCs) were corrected using bootstrapping. RESULTS: Overall 323 patients were included. The doubly robust estimator showed that hepatitis C infection (odds ratio (OR) 4.33, 95 per cent c.i. 1.29 to 9.20; P = 0.001), MELD score (OR 1.26, 1.04 to 1.66; P = 0.001), fibrosis-4 score (OR 1.36, 1.06 to 1.85; P = 0.001), liver surface nodularity score (OR 1.55, 1.28 to 4.29; P = 0.031), and FLR volume ratio (OR 0.99, 0.97 to 1.00; P = 0.014) were associated with PHLF. Their combination (NIB model) was fitted externally (2-centre cohort, 165 patients) to model PHLF risk (AUC 0.867). Among 129 of 323 patients who underwent preoperative HVPG measurement, NIB and IB models had similar performances (AUC 0.753 versus 0.732; P = 0.940). A well calibrated nomogram was drawn based on the NIB model (AUC 0.740). The risk of grade B/C PHLF could be ruled out in patients with a cumulative score of less than 160 points. CONCLUSION: The NIB model provides reliable preoperative evaluation with performance at least similar to that of invasive methods for PHLF risk prediction.

Whole-body low-dose computed tomography (WBLDCT) in staging and re-staging of multiple myeloma.

The objective of this study is to evaluate the prognostic features of multiple myeloma (MM) using whole-body low-dose computed tomography (WBLDCT). One hundred three patients with biopsy-proven MM who underwent WBLDCT were retrospectively enrolled. The evolution of osteolytic lesions overtime was performed by measuring the maximum axial diameter at the baseline (T0) and the end of follow-up (Te), by using a cut-off value of 10 mm. The location and dimension of up to three lesions were registered. The time-to-fracture (TTF) was recorded. Sixty-three percent of patients presented a focal pattern, 22% a diffuse pattern, and 15% a combined one. Seventy-two percent of patients with lesions ≤ 10 mm presented stability, 27% a dimensional increase, and 1% a decrease. Patients with lesions >10 mm showed a statistically significant difference regarding the mean difference of axial diameter between T0 and Te (p = 0.015). Patients with lesions >10 mm showed an odds ratio (OR) of 29.8 (95%CIs 3.8-230.5) to develop at least one fracture. Mean TTF was significantly lower in patients with lesions >10 mm in comparison with lesions ≤ 10 mm (9 ± 3 vs 23 ± 7 months, respectively, p = 0.011). WBLDCT represents a reliable imaging-based tool for proper management of MM patients, showing that diffuse form or small lytic lesions may deserve a less frequent follow-up.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia.

OBJECTIVES: To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes. METHODS: All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated. RESULTS: A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05). CONCLUSION: The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation. KEY POINTS: • Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.

Influence of injection rate in determining the development of artifacts during the acquisition of dynamic arterial phase in Gd-EOB-DTPA MRI studies.

OBJECTIVE: To assess whether different Gd-EOB-DTPA injection rates could influence the development of artifacts during the arterial phase of liver MRI studies. MATERIALS AND METHODS: All Gd-EOB-DTPA liver MRI studies performed for different clinical indications at a single tertiary referral center were retrospectively evaluated. Each examination was acquired on a 1.5 T scanner with T1 In- and Out-of-Phase, T2 with and without fat-saturation, DWI, and 3D-T1 fat-sat dynamic sequences. Patients were divided into two groups according to the injection rate (1 ml/s and 1.5 ml/s). A single radiologist recorded the presence or absence of artifacts during different acquisition phases, respectively: (1) all examination; (2) only during the arterial phase; (3) only during the portal-venous phase; (4) both in arterial and portal-venous phases. From a total of 748 MRI studies performed, 229 were excluded due to the presence of artifacts during the entire examination. The remaining 519 MRI studies were divided into two groups according to the injection rate. RESULTS: The first group (flow rate = 1 ml/s) was composed by 312 (60.1%) patients and the second group (flow rate = 1.5 ml/s) by 207 (39.9%) patients. In the first group, 2 (0.6%) patients showed artifacts in all dynamic sequences; 13 (4%) only in the arterial phase, 16 (5%) only in the portal-venous phase, and 38 (12%) both in arterial and portal-venous phases; a total of 243 (78%) showed no artifacts. In the second group, 3 (1.5%) patients had artifacts in all dynamic sequences, 82 (40%) only in the arterial phase, 20 (10%) only in the portal-venous phase, and 53 (25%) both in arterial and portal-venous phases; a total of 49 (23.5%) showed no artifacts. A significant difference between the two groups regarding the absence of artifacts in all examination and the presence of artifacts only during the arterial phase was found (p < 0.001). CONCLUSION: The development of artifacts during the arterial phase of Gd-EOB-DTPA liver MRI studies could be related to the injection rate and its reduction may help to decrease the incidence of artifacts.

Acute pulmonary embolism in hospitalized patients with SARS-CoV-2-related pneumonia: multicentric experience from Italian endemic area.

PURPOSE: To analyze pulmonary embolism (PE) on chest computed tomography pulmonary angiography (CTPA) in hospitalized patients affected by SARS-CoV-2, according to the severity of lung disease based both on temporal CT features changes and on CT-severity lung involvement (CT-severity score), along with the support of clinical and laboratory findings. METHODS: We retrospectively enrolled a total of 170 patients with confirmed SARS-CoV-2 infection who underwent CTPA examination for PE suspicion. Pulmonary arteries diameters, right ventricle/left ventricle (RV/LV) ratio, presence, absence, and distribution of PE, pulmonary artery obstructive index (PAO index), and lobe involvement were recorded. All CT scans were reviewed to assess temporal CT changes and the COVID CT-severity score. RESULTS: A total of 76 out of 170 patients (44.7%) developed PE without having any major risk factors for venous thromboembolism. The most severe pulmonary arteries involvement, expressed in terms of PAO Index, occurred in those patients with markedly elevated D-dimer and C-reactive protein (CRP) values and those patients with an advanced temporal stage of lung disease. The majority PE-positive patients were hospitalized in non-intensive wards. PE-positive patients showed a slightly higher hospitalization time in comparison with PE-negative ones. In the three months of study, overall 85.9% of patients were discharged while 14.1% died, of whom 13 PE-positive (54.2%). CONCLUSIONS: Patients hospitalized for SARS-CoV-2 infection present a higher cumulative incidence of PE compared to the general population of hospitalized patients, regardless of the severity of lung inflammation or the temporal stage of the disease.

Diagnostic accuracy of multiparametric magnetic resonance imaging combined with clinical parameters in the detection of clinically significant prostate cancer: A novel diagnostic model.

OBJECTIVES: To evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging in the detection of prostate cancer, according to Prostate Imaging Reporting and Data System, and the usefulness of combining clinical parameters to improve patients' risk assessment. METHODS: Overall, 201 patients underwent multiparametric magnetic resonance imaging investigation with a 3-T magnet and a 32-channel body coil based on triplanar high-resolution T2-weighted, diffusion-weighted and T1-weighted dynamic contrast-enhanced imaging before, during and after intravenous administration of paramagnetic contrast agent. Random transrectal ultrasound-guided biopsy was carried out for all eligible patients. If a Prostate Imaging Reporting and Data System ≥3 lesion was present, a targeted biopsy with magnetic resonance imaging-transrectal ultrasound fusion-guided system was carried out. RESULTS: Sensitivity, specificity, positive predictive value and negative predictive value of Prostate Imaging Reporting and Data System ≥3 lesions for the detection of prostate cancer were 65.1%, 54.9%, 43.1% and 75.0% respectively, with an accuracy of 64.2% (55.1-72.7%). At uni- and multivariate analysis, age ≥70 years and prostate-specific antigen density ≥0.15 ng/mL/mL were significantly associated with prostate cancer. A new risk model named "modified Prostate Imaging Reporting and Data System" was created considering age and prostate-specific antigen density in addition to the Prostate Imaging Reporting and Data System score showing an improved correlation with prostate cancer compared with the Prostate Imaging Reporting and Data System alone (area under curve 71.4%, 95% confidence interval 62.2-80.5 vs area under curve 62.6%, 95% confidence interval 52.1-73; P ≤ 0.0001). CONCLUSIONS: The accuracy of Prostate Imaging Reporting and Data System alone in the diagnosis of prostate cancer might be suboptimal, whereas a novel risk model based on the combination of multiparametric magnetic resonance imaging data with clinical parameters could offer higher discrimination and improve the ability of diagnosing clinically significant disease.

Improvements and future perspective in diagnostic tools for neuroendocrine neoplasms.

INTRODUCTION: Neuroendocrine neoplasms (NENs) represent a complex group of tumors arising from neuroendocrine cells, characterized by heterogeneous behavior and challenging diagnostics. Despite advancements in medical technology, NENs present a major challenge in early detection, often leading to delayed diagnosis and variable outcomes. This review aims to provide an in-depth analysis of current diagnostic methods as well as the evolving and future directions of diagnostic strategies for NENs. AREA COVERED: The review extensively covers the evolution of diagnostic tools for NENs, from traditional imaging and biochemical tests to advanced genomic profiling and next-generation sequencing. The emerging role of technologies such as artificial intelligence, machine learning, and liquid biopsies could improve diagnostic precision, as could the integration of imaging modalities such as positron emission tomography (PET)/magnetic resonance imaging (MRI) hybrids and innovative radiotracers. EXPERT OPINION: Despite progress, there is still a significant gap in the early diagnosis of NENs. Bridging this diagnostic gap and integrating advanced technologies and precision medicine are crucial to improving patient outcomes. However, challenges such as low clinical awareness, limited possibility of noninvasive diagnostic tools and funding limitations for rare diseases like NENs are acknowledged.

Diagnostic performance of an AI algorithm for the detection of appendicular bone fractures in pediatric patients.

PURPOSE: To evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm, previously trained using both adult and pediatric patients, for the detection of acute appendicular fractures in the pediatric population on conventional X-ray radiography (CXR). MATERIALS AND METHODS: In this retrospective study, anonymized extremities CXRs of pediatric patients (age <17 years), with or without fractures, were included. Six hundred CXRs (maintaining the positive-for-fracture and negative-for-fracture balance) were included, grouping them per body part (shoulder/clavicle, elbow/upper arm, hand/wrist, leg/knee, foot/ankle). Follow-up CXRs and/or second-level imaging were considered as reference standard. A deep learning algorithm interpreted CXRs for fracture detection on a per-patient, per-radiograph, and per-location level, and its diagnostic performance values were compared with the reference standard. AI diagnostic performance was computed by using cross-tables, and 95 % confidence intervals [CIs] were obtained by bootstrapping. RESULTS: The final cohort included 312 male and 288 female with a mean age of 8.9±4.5 years. Three undred CXRs (50 %) were positive for fractures, according to the reference standard. For all fractures, the AI tool showed a per-patient 91.3% (95%CIs = 87.6-94.3) sensitivity, 76.7% (71.5-81.3) specificity, and 84% (82.1-86.0) accuracy. In the per-radiograph analysis the AI tool showed 85% (81.9-87.8) sensitivity, 88.5% (86.3-90.4) specificity, and 87.2% (85.7-89.6) accuracy. In the per-location analysis, the AI tool identified 606 bounding boxes: 472 (77.9 %) were correct, 110 (18.1 %) incorrect, and 24 (4.0 %) were not-overlapping. CONCLUSION: The AI algorithm provides good overall diagnostic performance for detecting appendicular fractures in pediatric patients.

Cross-sectional imaging after pancreatic surgery: The dialogue between the radiologist and the surgeon.

Pancreatic surgery is nowadays considered one of the most complex surgical approaches and not unscathed from complications. After the surgical procedure, cross-sectional imaging is considered the non-invasive reference standard to detect early and late compilations, and consequently to address patients to the best management possible. Contras-enhanced computed tomography (CECT) should be considered the most important and useful imaging technique to evaluate the surgical site. Thanks to its speed, contrast, and spatial resolution, it can help reach the final diagnosis with high accuracy. On the other hand, magnetic resonance imaging (MRI) should be considered as a second-line imaging approach, especially for the evaluation of biliary findings and late complications. In both cases, the radiologist should be aware of protocols and what to look at, to create a robust dialogue with the surgeon and outline a fitted treatment for each patient.

Non-invasive imaging biomarkers in chronic liver disease.

Chronic liver disease (CLD) is a global and worldwide clinical challenge, considering that different underlying liver entities can lead to hepatic dysfunction. In the past, blood tests and clinical evaluation were the main noninvasive tools used to detect, diagnose and follow-up patients with CLD; in case of clinical suspicion of CLD or unclear diagnosis, liver biopsy has been considered as the reference standard to rule out different chronic liver conditions. Nowadays, noninvasive tests have gained a central role in the clinical pathway. Particularly, liver stiffness measurement (LSM) and cross-sectional imaging techniques can provide transversal information to clinicians, helping them to correctly manage, treat and follow patients during time. Cross-sectional imaging techniques, namely computed tomography (CT) and magnetic resonance imaging (MRI), have plenty of potential. Both techniques allow to compute the liver surface nodularity (LSN), associated with CLDs and risk of decompensation. MRI can also help quantify fatty liver infiltration, mainly with the proton density fat fraction (PDFF) sequences, and detect and quantify fibrosis, especially thanks to elastography (MRE). Advanced techniques, such as intravoxel incoherent motion (IVIM), T1- and T2- mapping are promising tools for detecting fibrosis deposition. Furthermore, the injection of hepatobiliary contrast agents has gained an important role not only in liver lesion characterization but also in assessing liver function, especially in CLDs. Finally, the broad development of radiomics signatures, applied to CT and MR, can be considered the next future approach to CLDs. The aim of this review is to provide a comprehensive overview of the current advancements and applications of both invasive and noninvasive imaging techniques in the evaluation and management of CLD.

Functional liver imaging score (FLIS) can predict adverse events in HCC patients.

PURPOSE: To assess the performance of FLIS in predicting adverse outcomes, namely post-hepatectomy liver failure (PHLF) and death, in patients who underwent liver surgery for malignancies. METHODS: All consecutive patients who underwent liver resection and 1.5 T gadoxetic acid MR were enrolled. PHLF and overall survival (OS) were collected. Two radiologists with 18 and 8 years of experience in abdominal imaging, blinded to clinical data, evaluated all images. Radiologists evaluated liver parenchymal enhancement (EnQS), biliary contrast excretion (ExQS), and signal intensity of the portal vein relative to the liver parenchyma (PVsQs). Reliability analysis was computed with Cohen's Kappa. Cox regression analysis was calculated to determine which factors are associated with PHLF and OS. Area Under the Receiver Operating Characteristic curve (AUROC) was computed. RESULTS: 150 patients were enrolled, 58 (38.7 %) in the HCC group and 92 (61.3 %) in the non-HCC group. The reliability analysis between the two readers was almost perfect (κ = 0.998). The multivariate Cox analysis showed that only post-surgical blood transfusions and major resection were associated with adverse events [HR=8.96 (7.98-9.88), p = 0.034, and HR=0.99 (0.781-1.121), p = 0.032, respectively] in the whole population. In the HCC group, the multivariable Cox analysis showed that blood transfusions, major resection and FLIS were associated with adverse outcomes [HR=13.133 (2.988-55.142), p = 0.009, HR=0.987 (0.244-1.987), p = 0.021, and HR=1.891 (1.772-3.471), p = 0.039]. The FLIS AUROC to predict adverse outcomes was 0.660 (95 %CIs = 0.484-0.836), with 87 % sensitivity and 33.3 % specificity (81.1-94.4 and 22.1-42.1). CONCLUSIONS: FLIS can be considered a promising tool to preoperative depict patients at risk of PHLF and death.

Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm.

Aim: To evaluate the dose reduction and image quality of low-dose, low-contrast media volume in computed tomography (CT) examinations reconstructed with the model-based iterative reconstruction (MBIR) algorithm in comparison with the hybrid iterative (HIR) one. Methods: We prospectively enrolled a total of 401 patients referred for cardiovascular CT, evaluated with a 256-MDCT scan with a low kVp (80 kVp) reconstructed with an MBIR (study group) or a standard HIR protocol (100 kVp-control group) after injection of a fixed dose of contrast medium volume. Vessel contrast enhancement and image noise were measured by placing the region of interest (ROI) in the left ventricle, ascending aorta; left, right and circumflex coronary arteries; main, right and left pulmonary arteries; aortic arch; and abdominal aorta. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Subjective image quality obtained by consensus was assessed by using a 4-point Likert scale. Radiation dose exposure was recorded. Results: HU values of the proximal tract of all coronary arteries; main, right and left pulmonary arteries; and of the aorta were significantly higher in the study group than in the control group (p < 0.05), while the noise was significantly lower (p < 0.05). SNR and CNR values in all anatomic districts were significantly higher in the study group (p < 0.05). MBIR subjective image quality was significantly higher than HIR in CCTA and CTPA protocols (p < 0.05). Radiation dose was significantly lower in the study group (p < 0.05). Conclusions: The MBIR algorithm combined with low-kVp can help reduce radiation dose exposure, reduce noise, and increase objective and subjective image quality.

Radiomics and liver: Where we are and where we are headed?

Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.

Preoperative detection of hepatocellular carcinoma's microvascular invasion on CT-scan by machine learning and radiomics: A preliminary analysis.

INTRODUCTION: Microvascular invasion (MVI) is the main risk factor for overall mortality and recurrence after surgery for hepatocellular carcinoma (HCC).The aim was to train machine-learning models to predict MVI on preoperative CT scan. METHODS: 3-phases CT scans were retrospectively collected among 4 Italian centers. DICOM files were manually segmented to detect the liver and the tumor(s). Radiomics features were extracted from the tumoral, peritumoral and healthy liver areas in each phase. Principal component analysis (PCA) was performed to reduce the dimensions of the dataset. Data were divided between training (70%) and test (30%) sets. Random-Forest (RF), fully connected MLP Artificial neural network (neuralnet) and extreme gradient boosting (XGB) models were fitted to predict MVI. Prediction accuracy was estimated in the test set. RESULTS: Between 2008 and 2022, 218 preoperative CT scans were collected. At the histological specimen, 72(33.02%) patients had MVI. First and second order radiomics features were extracted, obtaining 672 variables. PCA selected 58 dimensions explaining >95% of the variance.In the test set, the XGB model obtained Accuracy = 68.7% (Sens: 38.1%, Spec: 83.7%, PPV: 53.3% and NPV: 73.4%). The neuralnet showed an Accuracy = 50% (Sens: 52.3%, Spec: 48.8%, PPV: 33.3%, NPV: 67.7%). RF was the best performer (Acc = 96.8%, 95%CI: 0.91-0.99, Sens: 95.2%, Spec: 97.6%, PPV: 95.2% and NPV: 97.6%). CONCLUSION: Our model allowed a high prediction accuracy of the presence of MVI at the time of HCC diagnosis. This could lead to change the treatment allocation, the surgical extension and the follow-up strategy for those patients.

Evaluation of the reliability and usability of CARE-Radiology: A descriptive-analytic study.

AIM: The study aimed to evaluate the reliability and usability of the CARE-Radiology checklist in assessing radiological case reports and provide a basis for its broader adoption and optimization. METHODS: Ten randomly selected radiological case reports published in scientific journals in 2020 were evaluated using the CARE-Radiology checklist. Twenty-six experts from 10 countries were invited to independently assess all ten reports. The reliability of the checklist was measured using Fleiss' Kappa, and Cronbach's alpha coefficient. Usability was evaluated by recording the time taken to complete the assessments and requesting the evaluators to rate each item on a Likert scale for its easiness of use. RESULTS: The median time for evaluating one radiological case report was 15 min. The overall agreement among evaluators showed moderate reliability with a Kappa value of 0.47 and a Cronbach's alpha of 0.51. The mean compliance rate for the items of CARE-Radiology was 61.8%, with some items exceeding 90% compliance. Items related to abstracts and keywords had the lowest compliance rates. The evaluators found most items easy to understand, with a few exceptions. CONCLUSIONS: The CARE-Radiology checklist is relatively easy for researchers to use and understand. Continuous feedback is necessary for future revisions and updates, to enhance the effectiveness of the checklist, and to improve user experience.

Role of Imaging in the Management of Patients with SARS-CoV-2 Lung Involvement Admitted to the Emergency Department: A Systematic Review.

During the waves of the coronavirus disease (COVID-19) pandemic, emergency departments were overflowing with patients suffering with suspected medical or surgical issues. In these settings, healthcare staff should be able to deal with different medical and surgical scenarios while protecting themselves against the risk of contamination. Various strategies were used to overcome the most critical issues and guarantee quick and efficient diagnostic and therapeutic charts. The use of saliva and nasopharyngeal swab Nucleic Acid Amplification Tests (NAAT) in the diagnosis of COVID-19 was one of the most adopted worldwide. However, NAAT results were slow to report and could sometimes create significant delays in patient management, especially during pandemic peaks. On these bases, radiology has played and continues to play an essential role in detecting COVID-19 patients and solving differential diagnosis between different medical conditions. This systematic review aims to summarize the role of radiology in the management of COVID-19 patients admitted to emergency departments by using chest X-rays (CXR), computed tomography (CT), lung ultrasounds (LUS), and artificial intelligence (AI).

Radiological findings in non-surgical recurrent hepatocellular carcinoma: From locoregional treatments to immunotherapy.

Since hepatocellular carcinoma (HCC) represents an important cause of mortality and morbidity all over the world. Currently, it is fundamental not only to achieve a curative treatment but also to manage in the best way any possible recurrence. Even if the latest update of the Barcelona Clinic Liver Cancer guidelines for HCC treatment has introduced new locoregional techniques and confirmed others as well-established clinical practices, there is still no consensus about the treatment of recurrent HCC (RHCC). Locoregional treatments and medical therapy represent two of the most widely accepted approaches for disease control, especially in the advanced stage of liver disease. Different medical treatments are now approved, and others are under investigation. On this basis, radiology plays a central role in the diagnosis of RHCC and the assessment of response to locoregional treatments and medical therapy for RHCC. This review summarized the actual clinical practice by underlining the importance of the radiological approach both in the diagnosis and treatment of RHCC.

Gynaecological Causes of Acute Pelvic Pain: Common and Not-So-Common Imaging Findings.

In female patients, acute pelvic pain can be caused by gynaecological, gastrointestinal, and urinary tract pathologies. Due to the variety of diagnostic possibilities, the correct assessment of these patients may be challenging. The most frequent gynaecological causes of acute pelvic pain in non-pregnant women are pelvic inflammatory disease, ruptured ovarian cysts, ovarian torsion, and degeneration or torsion of uterine leiomyomas. On the other hand, spontaneous abortion, ectopic pregnancy, and placental disorders are the most frequent gynaecological entities to cause acute pelvic pain in pregnant patients. Ultrasound (US) is usually the first-line diagnostic technique because of its sensitivity across most common aetiologies and its lack of radiation exposure. Computed tomography (CT) may be performed if ultrasound findings are equivocal or if a gynaecologic disease is not initially suspected. Magnetic resonance imaging (MRI) is an extremely useful second-line technique for further characterisation after US or CT. This pictorial review aims to review the spectrum of gynaecological entities that may manifest as acute pelvic pain in the emergency department and to describe the imaging findings of these gynaecological conditions obtained with different imaging techniques.