Ultrasound muscle assessment for sarcopenia detection in inflammatory bowel disease: A prospective study.

BACKGROUND: Sarcopenia is prevalent in patients with inflammatory bowel disease (IBD) and impacts surgical and therapeutic outcomes; thus, effective diagnostic tools are needed to assess muscle mass and function in this population. METHODS: 153 consecutive patients were included, 100 in the training cohort and 53 in the study cohort. Three superficial muscles (rectus femoris = RF, rectus abdominis = RA, and biceps brachii = BB) were selected for the detection of sarcopenia using muscle ultrasound (US). The training cohort consisted of consecutive patients with or without IBD and was used to evaluate the feasibility and inter- and intra-observer variability of the US measurement. The study cohort consisted of only IBD patients and served to test US diagnostic accuracy. In the latter, muscle US, bioelectrical impedance analysis (BIA), and magnetic resonance imaging (MRI) were used to measure muscle parameters. RESULTS: Sarcopenia prevalence in IBD patients was 50%. Muscle US showed excellent inter-rater and intra-rater reliability (ICC >0.95) and a good diagnostic accuracy in detecting sarcopenia compared to BIA with area under the receiver operating characteristic curve (AUROC) values of 80% and 85% for RA and BB thickness, respectively. Moreover, an Ultrasound Muscle Index (USMI) was defined as the sum of the RA, BB, and RF thickness divided by the square of the patient's height, resulting in an AUROC of 81%. Muscle thresholds for sarcopenia were detected, with RA and USMI values correlated with the highest positive (84.3%) and negative (99%) predictive values, respectively. Additionally, the agreement between the US and MRI measurements of RA was excellent (ICC 0.96). CONCLUSIONS: The findings of this study emphasize the potential of muscle US as a reliable diagnostic tool for assessing sarcopenia in IBD patients. This research has significant implications for disease management in IBD patients and underscores the need for further investigations to validate these findings in larger cohorts.

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.

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.

Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department.

BACKGROUND: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly. METHODS: We aimed to test the diagnostic performance of an AI system in detecting COVID-19 pneumonia and typical bacterial pneumonia in patients who underwent a chest X-ray (CXR) and were admitted to the emergency department. The final dataset was composed of three sub-datasets: the first included all patients positive for COVID-19 pneumonia (n = 1140, namely "COVID-19+"), the second one included all patients with typical bacterial pneumonia (n = 500, "pneumonia+"), and the third one was composed of healthy subjects (n = 1000). Two radiologists were blinded to demographic, clinical, and laboratory data. The developed AI system was used to evaluate all CXRs randomly and was asked to classify them into three classes. Cohen's κ was used for interrater reliability analysis. The AI system's diagnostic accuracy was evaluated using a confusion matrix, and 95%CIs were reported as appropriate. RESULTS: The interrater reliability analysis between the most experienced radiologist and the AI system reported an almost perfect agreement for COVID-19+ (κ = 0.822) and pneumonia+ (κ = 0.913). We found 96% sensitivity (95% CIs = 94.9-96.9) and 79.8% specificity (76.4-82.9) for the radiologist and 94.7% sensitivity (93.4-95.8) and 80.2% specificity (76.9-83.2) for the AI system in the detection of COVID-19+. Moreover, we found 97.9% sensitivity (98-99.3) and 88% specificity (83.5-91.7) for the radiologist and 97.5% sensitivity (96.5-98.3) and 83.9% specificity (79-87.9) for the AI system in the detection of pneumonia+ patients. Finally, the AI system reached an accuracy of 93.8%, with a misclassification rate of 6.2% and weighted-F1 of 93.8% in detecting COVID+, pneumonia+, and healthy subjects. CONCLUSIONS: The AI system demonstrated excellent diagnostic performance in identifying COVID-19 and typical bacterial pneumonia in CXRs acquired in the emergency setting.

Liver metastases: The role of magnetic resonance imaging.

The liver is one of the organs most commonly involved in metastatic disease, especially due to its unique vascularization. It's well known that liver metastases represent the most common hepatic malignant tumors. From a practical point of view, it's of utmost importance to evaluate the presence of liver metastases when staging oncologic patients, to select the best treatment possible, and finally to predict the overall prognosis. In the past few years, imaging techniques have gained a central role in identifying liver metastases, thanks to ultrasonography, contrast-enhanced computed tomography (CT), and magnetic resonance imaging (MRI). All these techniques, especially CT and MRI, can be considered the non-invasive reference standard techniques for the assessment of liver involvement by metastases. On the other hand, the liver can be affected by different focal lesions, sometimes benign, and sometimes malignant. On these bases, radiologists should face the differential diagnosis between benign and secondary lesions to correctly allocate patients to the best management. Considering the above-mentioned principles, it's extremely important to underline and refresh the broad spectrum of liver metastases features that can occur in everyday clinical practice. This review aims to summarize the most common imaging features of liver metastases, with a special focus on typical and atypical appearance, by using MRI.

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.

Radiomics in colorectal cancer patients.

The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant chemotherapy benefit in patients with a high risk of recurrence is challenging. Radiological images can represent a source of data that can be analyzed by using automated computer-based techniques, working on numerical information coded within Digital Imaging and Communications in Medicine files: This image numerical analysis has been named "radiomics". Radiomics allows the extraction of quantitative features from radiological images, mainly invisible to the naked eye, that can be further analyzed by artificial intelligence algorithms. Radiomics is expanding in oncology to either understand tumor biology or for the development of imaging biomarkers for diagnosis, staging, and prognosis, prediction of treatment response and diseases monitoring and surveillance. Several efforts have been made to develop radiomics signatures for colorectal cancer patient using computed tomography (CT) images with different aims: The preoperative prediction of lymph node metastasis, detecting BRAF and RAS gene mutations. Moreover, the use of delta-radiomics allows the analysis of variations of the radiomics parameters extracted from CT scans performed at different timepoints. Most published studies concerning radiomics and magnetic resonance imaging (MRI) mainly focused on the response of advanced tumors that underwent neoadjuvant therapy. Nodes status is the main determinant of adjuvant chemotherapy. Therefore, several radiomics model based on MRI, especially on T2-weighted images and ADC maps, for the preoperative prediction of nodes metastasis in rectal cancer has been developed. Current studies mostly focused on the applications of radiomics in positron emission tomography/CT for the prediction of survival after curative surgical resection and assessment of response following neoadjuvant chemoradiotherapy. Since colorectal liver metastases develop in about 25% of patients with colorectal carcinoma, the main diagnostic tasks of radiomics should be the detection of synchronous and metachronous lesions. Radiomics could be an additional tool in clinical setting, especially in identifying patients with high-risk disease. Nevertheless, radiomics has numerous shortcomings that make daily use extremely difficult. Further studies are needed to assess performance of radiomics in stratifying patients with high-risk disease.

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).

Chest CT opportunistic biomarkers for phenotyping high-risk COVID-19 patients: a retrospective multicentre study.

OBJECTIVE: To assess the value of opportunistic biomarkers derived from chest CT performed at hospital admission of COVID-19 patients for the phenotypization of high-risk patients. METHODS: In this multicentre retrospective study, 1845 consecutive COVID-19 patients with chest CT performed within 72 h from hospital admission were analysed. Clinical and outcome data were collected by each center 30 and 80 days after hospital admission. Patients with unknown outcomes were excluded. Chest CT was analysed in a single core lab and behind pneumonia CT scores were extracted opportunistic data about atherosclerotic profile (calcium score according to Agatston method), liver steatosis (≤ 40 HU), myosteatosis (paraspinal muscle F < 31.3 HU, M < 37.5 HU), and osteoporosis (D12 bone attenuation < 134 HU). Differences according to treatment and outcome were assessed with ANOVA. Prediction models were obtained using multivariate binary logistic regression and their AUCs were compared with the DeLong test. RESULTS: The final cohort included 1669 patients (age 67.5 [58.5-77.4] yo) mainly men 1105/1669, 66.2%) and with reduced oxygen saturation (92% [88-95%]). Pneumonia severity, high Agatston score, myosteatosis, liver steatosis, and osteoporosis derived from CT were more prevalent in patients with more aggressive treatment, access to ICU, and in-hospital death (always p < 0.05). A multivariable model including clinical and CT variables improved the capability to predict non-critical pneumonia compared to a model including only clinical variables (AUC 0.801 vs 0.789; p = 0.0198) to predict patient death (AUC 0.815 vs 0.800; p = 0.001). CONCLUSION: Opportunistic biomarkers derived from chest CT can improve the characterization of COVID-19 high-risk patients. CLINICAL RELEVANCE STATEMENT: In COVID-19 patients, opportunistic biomarkers of cardiometabolic risk extracted from chest CT improve patient risk stratification. KEY POINTS: • In COVID-19 patients, several information about patient comorbidities can be quantitatively extracted from chest CT, resulting associated with the severity of oxygen treatment, access to ICU, and death. • A prediction model based on multiparametric opportunistic biomarkers derived from chest CT resulted superior to a model including only clinical variables in a large cohort of 1669 patients suffering from SARS- CoV2 infection. • Opportunistic biomarkers of cardiometabolic comorbidities derived from chest CT may improve COVID-19 patients' risk stratification also in absence of detailed clinical data and laboratory tests identifying subclinical and previously unknown conditions.

Principles and Applications of Dual-Layer Spectral CT in Gastrointestinal Imaging.

The advance in technology allows for the development of different CT scanners in the field of dual-energy computed tomography (DECT). In particular, a recently developed detector-based technology can collect data from different energy levels, thanks to its layers. The use of this system is suited for material decomposition with perfect spatial and temporal registration. Thanks to post-processing techniques, these scanners can generate conventional, material decomposition (including virtual non-contrast (VNC), iodine maps, Z-effective imaging, and uric acid pair images) and virtual monoenergetic images (VMIs). In recent years, different studies have been published regarding the use of DECT in clinical practice. On these bases, considering that different papers have been published using the DECT technology, a review regarding its clinical application can be useful. We focused on the usefulness of DECT technology in gastrointestinal imaging, where DECT plays an important role.

Association of chronic statin use, myopenia, myosteatosis and major morbidity in surgical patients with upper gastrointestinal cancer.

Derangements of body composition affect surgical outcomes. Chronic statin use may induce muscle wasting and impair muscle tissue quality. Aim of this study was to evaluate the association of chronic statin use, skeletal muscle area (SMA), myosteatosis and major postoperative morbidity. Between 2011 and 2021, patients undergoing pancreatoduodenectomy or total gastrectomy for cancer, and using statins since at least 1 year, were retrospective studied. SMA and myosteatosis were measured at CT scan. The cut-off for SMA and myosteatosis were determined using ROC curve and considering severe complications as the binary outcome. The presence of myopenia was defined when SMA was lower that the cut-off. A multivariable logistic regression was applied to assess the association between several factors and severe complications. After a matching procedure (1:1) for key baseline risk factors (ASA; age; Charlson comorbidity index; tumor site; intraoperative blood loss), a final sample of 104 patients, of which 52 treated and 52 not treated with statins, was obtained. The median age was 75 years, with an ASA score ≥ 3 in 63% of the cases. SMA (OR 5.119, 95% CI 1.053-24.865) and myosteatosis (OR 4.234, 95% CI 1.511-11.866) below the cut-off values were significantly associated with major morbidity. Statin use was predictive of major complication only in patients with preoperative myopenia (OR 5.449, 95% CI 1.054-28.158). Myopenia and myosteatosis were independently associated with an increased risk of severe complications. Statin use was associated with a higher risk of having major morbidity only in the subgroup of patients with myopenia.

Imaging in Gastric Cancer: Current Practice and Future Perspectives.

Gastric cancer represents one of the most common oncological causes of death worldwide. In order to treat patients in the best possible way, the staging of gastric cancer should be accurate. In this regard, endoscopy ultrasound (EUS) has been considered the reference standard for tumor (T) and nodal (N) statuses in recent decades. However, thanks to technological improvements, computed tomography (CT) has gained an important role, not only in the assessment of distant metastases (M status) but also in T and N staging. In addition, magnetic resonance imaging (MRI) can contribute to the detection and staging of primary gastric tumors thanks to its excellent soft tissue contrast and multiple imaging sequences without radiation-related risks. In addition, MRI can help with the detection of liver metastases, especially small lesions. Finally, positron emission tomography (PET) is still considered a useful diagnostic tool for the staging of gastric cancer patients, with a focus on nodal metastases and peritoneal carcinomatosis. In addition, it may play a role in the treatment of gastric cancer in the coming years thanks to the introduction of new labeling peptides. This review aims to summarize the most common advantages and pitfalls of EUS, CT, MRI and PET in the TNM staging of gastric cancer patients.

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.

Liver involvement in patients with COVID-19 infection: A comprehensive overview of diagnostic imaging features.

During the first wave of the pandemic, coronavirus disease 2019 (COVID-19) infection has been considered mainly as a pulmonary infection. However, different clinical and radiological manifestations were observed over time, including involvement of abdominal organs. Nowadays, the liver is considered one of the main affected abdominal organs. Hepatic involvement may be caused by either a direct damage by the virus or an indirect damage related to COVID-19 induced thrombosis or to the use of different drugs. After clinical assessment, radiology plays a key role in the evaluation of liver involvement. Ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) may be used to evaluate liver involvement. US is widely available and it is considered the first-line technique to assess liver involvement in COVID-19 infection, in particular liver steatosis and portal-vein thrombosis. CT and MRI are used as second- and third-line techniques, respectively, considering their higher sensitivity and specificity compared to US for assessment of both parenchyma and vascularization. This review aims to the spectrum of COVID-19 liver involvement and the most common imaging features of COVID-19 liver damage.

The usefulness of preoperative CT in colon cancer staging: impact of radiologists' experience.

PURPOSE: To assess the agreement between radiologists in the detection of specific features related to T- and N-stage and evaluate accuracy in colon cancer staging. METHODS: Patients who underwent contrast-enhanced computed tomography (CECT) before surgery were enrolled and evaluated by three radiologists with different experience. Pathological data were used as the reference standard. Tumor location, presence of tumor bulging, fat stranding, lateroconal fascia invasion, enlarged vessels, axial short diameter of the biggest node, shape, enhancement pattern, intranodal necrosis, and cluster were collected. Reliability analysis was performed with κ statistics and intraclass correlation coefficients (ICCs). Logistic regressions were used to determine independent predictors associated with staging. RESULTS: Seventy five patients were evaluated. The reliability analysis was moderate to substantial for tumor location (κ = 0.853), T staging (κ = 0.531), tumor bulging (κ = 0.478), fat stranding (κ = 0.490), lateroconal fascia invasion (κ = 0.436), enlarged vessels (κ = 0.401), the axial short diameter of the biggest node (ICC = 0.732), shape (κ = 0.484), enhancement pattern (κ = 0.431), intranodal necrosis (κ = 0.606), and cluster (κ = 0.358). For all readers, sensitivity was higher for T3 lesions (60-69%) and specificity was higher for T2 and T4 lesions (84.5-90.0% and 82.4-85.1%). The diagnostic accuracy was acceptable for all lesions and among all readers (50.7-92.1%). The lateroconal fascia invasion and enlarged vessels resulted as independent predictor factors (OR = 3.292 and OR = 2.651) for T staging, while nodes' cluster and dimension as independent predictor factors of N staging [OR = 3.798 and OR = 1.083]. CONCLUSION: Reader's experience is one of the most important factors associated with the correct classification of colon cancer. Moreover, CECT can help depict radiological features independently associated with the T and N stages.

A quantitative MRCP-derived score for medium-term outcome prediction in primary sclerosing cholangitis.

BACKGROUND: Magnetic resonance cholangiopancreatography (MRCP) is the gold standard for diagnosis of patients with primary sclerosing cholangitis (PSC). The semi-quantitative MRCP-derived Anali scores proposed for risk stratification, have poor-to-moderate inter-reader agreement. AIMS: To evaluate the prognostic performance of quantitative MRCP metrics in PSC. METHODS: This is a retrospective study of PSC patients undergoing MRCP. Images were processed using MRCP+ software (Perspectum Ltd, Oxford) that provides quantitative biliary features, semi-automatically extracted by artificial intelligence-driven analysis of MRCP-3D images. The prognostic value of biliary features has been assessed for all hepato-biliary complications. RESULTS: 87 PSC patients have been included in the analysis. Median follow-up from MRCP to event/censoring of 30.9 months (Q1-Q3=13.6-46.6). An adverse outcome occurred in 27 (31.0%) patients. The number of biliary strictures (HR=1.05 per unit, 95%CI 1.02-1.08, p < 0.0001), spleen length (HR=1.16 per cm, 95%CI 1.01-1.34, p = 0.039), adjusted for height, age at MRCP, and time from diagnosis to MRCP predicted higher risk of hepatobiliary complications. These were incorporated into a the quantitative MRCP-derived PSC (qMRCP-PSC) score (C-statistic=0.80). After 3-fold cross-validation, qMRCP-PSC outperformed the Anali score in our cohort (C-statistic of 0.78 vs 0.64) and enabled the discrimination of survival of PSC patients (log-rank p < 0.0001). CONCLUSIONS: The qMRCP-PSC score identified patients at higher risk of hepatobiliary complications and outperformed the available radiological scores. It represents a novel quantitative biomarker for disease monitoring and a potential surrogate endpoint for clinical trials.

Ultrasound Versus Computed Tomography for Diaphragmatic Thickness and Skeletal Muscle Index during Mechanical Ventilation.

Background: Diaphragmatic alterations occurring during mechanical ventilation (MV) can be monitored using ultrasound (US). The performance of computed tomography (CT) to evaluate diaphragmatic thickness is limited. Further, the association between muscle mass and outcome is increasingly recognized. However, no data are available on its correlation with diaphragmatic thickness. We aimed to determine correlation and agreement of diaphragmatic thickness between CT and US; and its association with muscle mass and MV parameters. Methods: Prospective observational study. US measurements of the diaphragmatic thickness were collected in patients undergoing MV within 12 h before or after performing a CT scan of the thorax and/or upper abdomen. Data on skeletal muscle index (SMI), baseline, and ventilatory data were recorded and correlated with US and CT measures of diaphragmatic thickness. Agreement was explored between US and CT data. Results: Twenty-nine patients were enrolled and the diaphragm measured by CT resulted overall thicker than US-based measurement of the right hemidiaphragm. The US thickness showed the strongest correlation with the left posterior pillar at CT (r = 0.49, p = 0.008). The duration of the controlled MV was negatively correlated with US thickness (r = -0.45, p = 0.017), the thickness of the right anterior pillar (r = -0.41, p = 0.029), and splenic dome by CT (r = -0.43, p = 0.023). SMI was positively correlated with US diaphragmatic thickness (r = 0.50, p = 0.007) and inversely correlated with the duration of MV before enrollment (r = -0.426, p = 0.027). Conclusions: CT scan of the left posterior pillar can estimate diaphragmatic thickness and is moderately correlated with US measurements. Both techniques show that diaphragm thickness decreases with MV duration. The diaphragmatic thickness by US showed a good correlation with SMI.

Inter-observer agreement and image quality of model-based algorithm applied to the Coronary Artery Disease-Reporting and Data System score.

PURPOSE: To evaluate the inter-observer agreement of the CAD-RADS reporting system and compare image quality between model-based iterative reconstruction algorithm (MBIR) and standard iterative reconstruction algorithm (IR) of low-dose cardiac computed tomography angiography (CCTA). METHODS: One-hundred-sixty patients undergone a 256-slice MDCT scanner using low-dose CCTA combined with prospective ECG-gated techniques were enrolled. CCTA protocols were reconstructed with both MBIR and IR. Each study was evaluated by two readers using the CAD-RADS lexicon. Vessels enhancement, image noise, signal-to-noise (SNR), and contrast-to-noise (CNR) were computed in the axial native images, and inter-observer agreement was assessed. Radiation dose exposure as dose-length product (DLP) and effective dose were finally reported. RESULTS: The reliability analysis between the two readers was almost perfect for all CAD-RADS standard categories. Moreover, a significantly higher value of subjective qualitative analysis, SNR, and CNR in MBIR images compared to IR were found, due to a lower noise level (all p < 0.05). The mean DLP measured was 63.9 mGy*cm, and the mean effective dose was 0.9 mSv. CONCLUSION: Inter-observer agreement of CAD-RADS was excellent confirming the importance, the feasibility, and the reproducibility of the CAD-RADS scoring system for CCTA. Moreover, lower noise and higher image quality with MBIR compared to IR were found. IMPLICATIONS FOR PRACTICE: MBIR, by reducing noise and improving image quality, can help a better assessment of CAD-RADS, in comparison with standard IR algorithm.