Radiomics applications in cardiac imaging: a comprehensive review.

Radiomics is a new emerging field that includes extraction of metrics and quantification of so-called radiomic features from medical images. The growing importance of radiomics applied to oncology in improving diagnosis, cancer staging and grading, and improved personalized treatment, has been well established; yet, this new analysis technique has still few applications in cardiovascular imaging. Several studies have shown promising results describing how radiomics principles could improve the diagnostic accuracy of coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) in diagnosis, risk stratification, and follow-up of patients with coronary heart disease (CAD), ischemic heart disease (IHD), hypertrophic cardiomyopathy (HCM), hypertensive heart disease (HHD), and many other cardiovascular diseases. Such quantitative approach could be useful to overcome the main limitations of CCTA and MRI in the evaluation of cardiovascular diseases, such as readers' subjectiveness and lack of repeatability. Moreover, this new discipline could potentially overcome some technical problems, namely the need of contrast administration or invasive examinations. Despite such advantages, radiomics is still not applied in clinical routine, due to lack of standardized parameters acquisition, inconsistent radiomic methods, lack of external validation, and different knowledge and experience among the readers. The purpose of this manuscript is to provide a recent update on the status of radiomics clinical applications in cardiovascular imaging.

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

ABSTRACT: Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented various technical advances, such as automatic noise reduction filters, automatic exposure control, and refined imaging reconstruction algorithms.Focusing on imaging reconstruction, filtered back-projection has represented the standard reconstruction algorithm for over 3 decades, obtaining adequate image quality at standard radiation dose exposures. To overcome filtered back-projection reconstruction flaws in low-dose CT data sets, advanced iterative reconstruction algorithms consisting of either backward projection or both backward and forward projections have been developed, with the goal to enable low-dose CT acquisitions with high image quality. Iterative reconstruction techniques play a key role in routine workflow implementation (eg, screening protocols, vascular and pediatric applications), in quantitative CT imaging applications, and in dose exposure limitation in oncologic patients.Therefore, this review aims to provide an overview of the technical principles and the main clinical application of iterative reconstruction algorithms, focusing on the strengths and weaknesses, in addition to integrating future perspectives in the new era of artificial intelligence.

Adrenal Lesions: A Review of Imaging.

Adrenal lesions are frequently incidentally diagnosed during investigations for other clinical conditions. Despite being usually benign, nonfunctioning, and silent, they can occasionally cause discomfort or be responsible for various clinical conditions due to hormonal dysregulation; therefore, their characterization is of paramount importance for establishing the best therapeutic strategy. Imaging techniques such as ultrasound, computed tomography, magnetic resonance, and PET-TC, providing anatomical and functional information, play a central role in the diagnostic workup, allowing clinicians and surgeons to choose the optimal lesion management. This review aims at providing an overview of the most encountered adrenal lesions, both benign and malignant, including describing their imaging characteristics.

Diagnostic performance of CT lung severity score and quantitative chest CT for stratification of COVID-19 patients.

PURPOSE: Lung severity score (LSS) and quantitative chest CT (QCCT) analysis could have a relevant impact to stratify patients affected by COVID-19 pneumonia at the hospital admission. The study aims to assess LSS and QCCT performances in severity stratification of COVID-19 patients. MATERIALS AND METHODS: From April 19, 2020, until May 3, 2020, patients with chest CT suggestive for interstitial pneumonia and tested positive for COVID-19 were retrospectively enrolled and stratified for hospital admission as Group 1, 2 and 3 (home isolation, low intensive care and intensive care, respectively). For LSS, lungs were divided in 20 regions and visually assessed by two radiologists who scored for each region from non-lung involvement as 0, < 50% assigned as 1 and > 50% as 2. QCCT was performed with a dedicated software that extracts pulmonary involvement expressed in liters and percentage. LSS and QCCT were analyzed with ROC curve analysis to predict the performance of both methods. P values < 0.05 were considered statistically significant. RESULTS: Final population enrolled included 136 patients (87 males, mean age 66 ± 16), 19 patients in Group 1, 86 in Group 2 and 31 in Group 3. Significant differences for LSS were observed in almost all comparisons, especially in Group 1 vs 3 (AUC 0.850, P < 0,0001) and Group 1 + 2 vs 3 (AUC 0.783, P < 0,0001). QCCT showed significant results in almost all comparisons, especially between Group 1 vs 3 (AUC 0.869, P < 0,0001). LSS and QCCT comparison between Group 1 and Group 2 did not show significant differences. CONCLUSIONS: LSS and QCCT could represent promising tools to stratify COVID-19 patient severity at the admission.

Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review.

Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.

Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia.

PURPOSE: To evaluate the potential role of texture-based radiomics analysis in differentiating Coronavirus Disease-19 (COVID-19) pneumonia from pneumonia of other etiology on Chest CT. MATERIALS AND METHODS: One hundred and twenty consecutive patients admitted to Emergency Department, from March 8, 2020, to April 25, 2020, with suspicious of COVID-19 that underwent Chest CT, were retrospectively analyzed. All patients presented CT findings indicative for interstitial pneumonia. Sixty patients with positive COVID-19 real-time reverse transcription polymerase chain reaction (RT-PCR) and 60 patients with negative COVID-19 RT-PCR were enrolled. CT texture analysis (CTTA) was manually performed using dedicated software by two radiologists in consensus and textural features on filtered and unfiltered images were extracted as follows: mean intensity, standard deviation (SD), entropy, mean of positive pixels (MPP), skewness, and kurtosis. Nonparametric Mann-Whitney test assessed CTTA ability to differentiate positive from negative COVID-19 patients. Diagnostic criteria were obtained from receiver operating characteristic (ROC) curves. RESULTS: Unfiltered CTTA showed lower values of mean intensity, MPP, and kurtosis in COVID-19 positive patients compared to negative patients (p = 0.041, 0.004, and 0.002, respectively). On filtered images, fine and medium texture scales were significant differentiators; fine texture scale being most significant where COVID-19 positive patients had lower SD (p = 0.004) and MPP (p = 0.004) compared to COVID-19 negative patients. A combination of the significant texture features could identify the patients with positive COVID-19 from negative COVID-19 with a sensitivity of 60% and specificity of 80% (p = 0.001). CONCLUSIONS: Preliminary evaluation suggests potential role of CTTA in distinguishing COVID-19 pneumonia from other interstitial pneumonia on Chest CT.

Imaging of abdominal complications of COVID-19 infection.

Coronavirus disease 2019 (COVID-19) is a respiratory syndrome caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first described in Wuhan, Hubei Province, China in the last months of 2019 and then declared as a pandemic. Typical symptoms are represented by fever, cough, dyspnea and fatigue, but SARS-CoV-2 infection can also cause gastrointestinal symptoms (vomiting, diarrhoea, abdominal pain, loss of appetite) or be totally asymptomatic. As reported in literature, many patients with COVID-19 pneumonia had a secondary abdominal involvement (bowel, pancreas, gallbladder, spleen, liver, kidneys), confirmed by laboratory tests and also by radiological features. Usually the diagnosis of COVID-19 is suspected and then confirmed by real-time reverse-transcription-polymerase chain reaction (RT-PCR), after the examination of the lung bases of patients, admitted to the emergency department with abdominal symptoms and signs, who underwent abdominal-CT. The aim of this review is to describe the typical and atypical abdominal imaging findings in patients with SARS-CoV-2 infection reported since now in literature.

Post-Acute Sequelae of COVID-19 Pneumonia: Six-month Chest CT Follow-up.

Background The long-term post-acute pulmonary sequelae of COVID-19 remain unknown. Purpose To evaluate lung injury in patients affected by COVID-19 pneumonia at the 6-month follow-up CT examination compared with the baseline chest CT examination. Materials and Methods From March 19, 2020, to May 24, 2020, patients with moderate to severe COVID-19 pneumonia who had undergone baseline chest CT were prospectively enrolled at their 6-month follow-up. The CT qualitative findings, semiquantitative Lung Severity Score (LSS), and the well-aerated lung volume at quantitative chest CT (QCCT) analysis were analyzed. The performance of the baseline LSS and QCCT findings for predicting fibrosis-like changes (reticular pattern and/or honeycombing) at the 6-month follow-up chest CT examination was tested by using receiver operating characteristic curves. Univariable and multivariable logistic regression analyses were used to test clinical and radiologic features that were predictive of fibrosis-like changes. The multivariable analysis was performed with clinical parameters alone (clinical model), radiologic parameters alone (radiologic model), and the combination of clinical and radiologic parameters (combined model). Results One hundred eighteen patients who had undergone baseline chest CT and agreed to undergo follow-up chest CT at 6 months were included in the study (62 women; mean age, 65 years ± 12 [standard deviation]). At follow-up chest CT, 85 of 118 (72%) patients showed fibrosis-like changes and 49 of 118 (42%) showed ground-glass opacities. The baseline LSS (>14) and QCCT findings (≤3.75 L and ≤80%) showed excellent performance for predicting fibrosis-like changes at follow-up chest CT. In the multivariable analysis, the areas under the curve were 0.89 (95% CI: 0.77, 0.96) for the clinical model, 0.81 (95% CI: 0.68, 0.9) for the radiologic model, and 0.92 (95% CI: 0.81, 0.98) for the combined model. Conclusion At 6-month follow-up chest CT, 72% of patients showed late sequelae, in particular fibrosis-like changes. The baseline Lung Severity Score and the well-aerated lung volume at quantitative chest CT (QCCT) analysis showed excellent performance for predicting fibrosis-like changes at the 6-month chest CT (area under the curve, >0.88). Male sex, cough, lymphocytosis, and the well-aerated lung volume at QCCT analysis were significant predictors of fibrosis-like changes at 6 months, demonstrating an inverse correlation (area under the curve, 0.92). © RSNA, 2021 See also the editorial by Wells and Devaraj in this issue.

Radiomics in Oncology, Part 2: Thoracic, Genito-Urinary, Breast, Neurological, Hematologic and Musculoskeletal Applications.

Radiomics has the potential to play a pivotal role in oncological translational imaging, particularly in cancer detection, prognosis prediction and response to therapy evaluation. To date, several studies established Radiomics as a useful tool in oncologic imaging, able to support clinicians in practicing evidence-based medicine, uniquely tailored to each patient and tumor. Mineable data, extracted from medical images could be combined with clinical and survival parameters to develop models useful for the clinicians in cancer patients' assessment. As such, adding Radiomics to traditional subjective imaging may provide a quantitative and extensive cancer evaluation reflecting histologic architecture. In this Part II, we present an overview of radiomic applications in thoracic, genito-urinary, breast, neurological, hematologic and musculoskeletal oncologic applications.

Radiomics in Oncology, Part 1: Technical Principles and Gastrointestinal Application in CT and MRI.

Radiomics has been playing a pivotal role in oncological translational imaging, particularly in cancer diagnosis, prediction prognosis, and therapy response assessment. Recently, promising results were achieved in management of cancer patients by extracting mineable high-dimensional data from medical images, supporting clinicians in decision-making process in the new era of target therapy and personalized medicine. Radiomics could provide quantitative data, extracted from medical images, that could reflect microenvironmental tumor heterogeneity, which might be a useful information for treatment tailoring. Thus, it could be helpful to overcome the main limitations of traditional tumor biopsy, often affected by bias in tumor sampling, lack of repeatability and possible procedure complications. This quantitative approach has been widely investigated as a non-invasive and an objective imaging biomarker in cancer patients; however, it is not applied as a clinical routine due to several limitations related to lack of standardization and validation of images acquisition protocols, features segmentation, extraction, processing, and data analysis. This field is in continuous evolution in each type of cancer, and results support the idea that in the future Radiomics might be a reliable application in oncologic imaging. The first part of this review aimed to describe some radiomic technical principles and clinical applications to gastrointestinal oncologic imaging (CT and MRI) with a focus on diagnosis, prediction prognosis, and assessment of response to therapy.

Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients.

Iterative reconstructions (IR) might alter radiomic features extraction. We aim to evaluate the influence of Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on CT radiomic features. Patients who underwent unenhanced abdominal CT (Revolution Evo, GE Healthcare, USA) were retrospectively enrolled. Raw data of filtered-back projection (FBP) were reconstructed with 10 levels of ASIR-V (10-100%). CT texture analysis (CTTA) of liver, kidney, spleen and paravertebral muscle for all datasets was performed. Six radiomic features (mean intensity, standard deviation (SD), entropy, mean of positive pixel (MPP), skewness, kurtosis) were extracted and compared between FBP and all ASIR-V levels, with and without altering the spatial scale filter (SSF). CTTA of all organs revealed significant differences between FBP and all ASIR-V reconstructions for mean intensity, SD, entropy and MPP (all p < 0.0001), while no significant differences were observed for skewness and kurtosis between FBP and all ASIR-V reconstructions (all p > 0.05). A per-filter analysis was also performed comparing FBP with all ASIR-V reconstructions for all six SSF separately (SSF0-SSF6). Results showed significant differences between FBP and all ASIR-V reconstruction levels for mean intensity, SD, and MPP (all filters p < 0.0315). Skewness and kurtosis showed no differences for all comparisons performed (all p > 0.05). The application of incremental ASIR-V levels affects CTTA across various filters. Skewness and kurtosis are not affected by IR and may be reliable quantitative parameters for radiomic analysis.

Optimization of contrast medium volume for abdominal CT in oncologic patients: prospective comparison between fixed and lean body weight-adapted dosing protocols.

BACKGROUND: Patient body size represents the main determinant of parenchymal enhancement and by adjusting the contrast media (CM) dose to patient weight may be a more appropriate approach to avoid a patient over dosage of CM. To compare the performance of fixed-dose and lean body weight (LBW)-adapted contrast media dosing protocols, in terms of image quality and parenchymal enhancement. RESULTS: One-hundred cancer patients undergoing multiphasic abdominal CT were prospectively enrolled in this multicentric study and randomly divided in two groups: patients in fixed-dose group (n = 50) received 120 mL of CM while in LBW group (n = 50) the amount of CM was computed according to the patient's LBW. LBW protocol group received a significantly lower amount of CM (103.47 ± 17.65 mL vs. 120.00 ± 0.00 mL, p < 0.001). Arterial kidney signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and pancreatic CNR were significantly higher in LBW group (all p ≤ 0.004). LBW group provided significantly higher arterial liver, kidney, and pancreatic contrast enhancement index (CEI) and portal venous phase kidney CEI (all p ≤ 0.002). Significantly lower portal vein SNR and CNR were observed in LBW-Group (all p ≤ 0.020). CONCLUSIONS: LBW-adapted CM administration for abdominal CT reduces the volume of injected CM and improves both image quality and parenchymal enhancement.

Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients.

INTRODUCTION: COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. MATERIALS AND METHODS: From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p < 0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis. RESULTS: Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66 ± 16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63 ± 15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55 ± 0.26L vs 0.43 ± 0.23L, p = 0.0005) and fibrotic alterations (0.05 ± 0.03 L vs 0.04 ± 0.03 L, p < 0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p < 0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p < 0.001), respectively. CONCLUSIONS: Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.

Typical and atypical COVID-19 computed tomography findings.

In December 2019 a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 was identified and the disease associated was named coronavirus disease 2019 (COVID-19). Fever, cough, myalgia, fatigue associated to dyspnea represent most common clinical symptoms of the disease. The reference standard for diagnosis of severe acute respiratory syndrome coronavirus 2 infection is real time reverse-transcription polymerase chain reaction test applied on respiratory tract specimens. Despite of lower specificity, chest computed tomography (CT), as reported in manifold scientific studies, showed high sensitivity, therefore it may help in the early detection, management and follow-up of COVID-19 pneumonia. Patients affected by COVID-19 pneumonia usually showed on chest CT some typical features, such as: Bilateral ground glass opacities characterized by multilobe involvement with posterior and peripheral distribution; parenchymal consolidations with or without air bronchogram; interlobular septal thickening; crazy paving pattern, represented by interlobular and intralobular septal thickening surrounded by ground-glass opacities; subsegmental pulmonary vessels enlargement (> 3 mm). Halo sign, reversed halo sign, cavitation and pleural or pericardial effusion represent some of atypical findings of COVID-19 pneumonia. On the other hand lymphadenopathy's and bronchiectasis' frequency is unclear, indeed conflicting data emerged in literature. Radiologists play a key role in recognition of high suspicious findings of COVID-19 on chest CT, both typical and atypical ones. Thus, the aim of this review is to illustrate typical and atypical CT findings of COVID-19.

Chest CT Features of COVID-19 in Rome, Italy.

Background The standard for diagnosis of severe acute respiratory syndrome coronavirus 2 is a reverse transcription polymerase chain reaction (RT-PCR) test, but chest CT may play a complimentary role in the early detection of Coronavirus Disease 2019 (COVID-19) pneumonia. Purpose To investigate CT features of patients with COVID-19 in Rome, Italy, and to compare the accuracy of CT with that of RT-PCR. Materials and Methods In this prospective study from March 4, 2020, until March 19, 2020, consecutive patients suspected of having COVID-19 infection and respiratory symptoms were enrolled. Exclusion criteria were contrast material-enhanced chest CT performed for vascular indications, patients who refused chest CT or hospitalization, and severe CT motion artifact. All patients underwent RT-PCR and chest CT. Diagnostic performance of CT was calculated using RT-PCR as the reference standard. Chest CT features were calculated in a subgroup of patients with positive RT-PCR and CT findings. CT features of hospitalized patients and patients in home isolation were compared using the Pearson χ2 test. Results The study population included 158 consecutive participants (83 male, 75 female; mean age, 57 years ± 17 [standard deviation]). Of the 158 participants, fever was observed in 97 (61%), cough was observed in 88 (56%), dyspnea was observed in 52 (33%), lymphocytopenia was observed in 95 (60%), increased C-reactive protein level was observed in 139 (88%), and elevated lactate dehydrogenase level was observed in 128 (81%). Sensitivity, specificity, and accuracy of CT were 97% (95% confidence interval [CI]: 88%, 99%) (60 of 62), 56% (95% CI: 45%, 66%) (54 of 96), and 72% (95% CI: 64%, 78%) (114 of 158), respectively. In the subgroup of 58 participants with positive RT-PCR and CT findings, ground-glass opacities were present in all 58 (100%), both multilobe and posterior involvement were present in 54 (93%), bilateral pneumonia was present in 53 (91%), and subsegmental vessel enlargement (>3 mm) was present in 52 (89%). Conclusion The typical pattern of COVID-19 pneumonia in Rome, Italy, was peripheral ground-glass opacities with multilobe and posterior involvement, bilateral distribution, and subsegmental vessel enlargement (>3 mm). Chest CT had high sensitivity (97%) but lower specificity (56%). © RSNA, 2020.

Handy Hints About Raynaud's Phenomenon in Children: A Critical Review.

Raynaud's phenomenon (RP) is a vasospastic disorder characterized by recurrent self-limited episodes of skin pallor, cyanosis, and hyperemia caused by paroxysmal spasms in the small arteries of the fingers and toes and can occur in any age group. Hands, feet, nose, ears, and nipples can be affected. The diagnosis is made clinically, assessing varying degrees of ischemia in the involved areas of skin, but this transient ischemia may also herald the onset of connective tissue disease. Investigation is recommended when RP starts in childhood to exclude an underlying autoimmune condition and close follow-up for its development. Management of RP in children includes conservative and pharmacologic treatments.

Lung Involvement in Children with Hereditary Autoinflammatory Disorders.

Short-lived systemic inflammatory reactions arising from disrupted rules in the innate immune system are the operating platforms of hereditary autoinflammatory disorders (HAIDs). Multiple organs may be involved and aseptic inflammation leading to disease-specific phenotypes defines most HAIDs. Lungs are infrequently involved in children with HAIDs: the most common pulmonary manifestation is pleuritis in familial Mediterranean fever (FMF) and tumor necrosis factor receptor-associated periodic syndrome (TRAPS), respectively caused by mutations in the MEFV and TNFRSF1A genes, while interstitial lung disease can be observed in STING-associated vasculopathy with onset in infancy (SAVI), caused by mutations in the TMEM173 gene. The specific pleuropulmonary diseases may range from sub-clinical abnormalities during inflammatory flares of FMF and TRAPS to a severe life-threatening disorder in children with SAVI.

Critical Overview of the Risk Scoring Systems to Predict Non-Responsiveness to Intravenous Immunoglobulin in Kawasaki Syndrome.

Kawasaki syndrome (KS) is the most relevant cause of heart disease in children living in developed countries. Intravenous immunoglobulin (IVIG) has a preventive function in the formation of coronary artery abnormalities and a poor strictly-curative action in established coronary damage. More than two decades ago, the Harada score was set to assess which children with KS should be subject to administration of IVIG, evaluating retrospectively a large cohort of patients with regard to age, sex and laboratory data. Nowadays, high dose IVIG is administered to all children with a confirmed diagnosis of KS, but a tool for predicting non-responsiveness to the initial infusion of IVIG has not been found. The prediction of IVIG resistance is a crucial issue, as recognising these high-risk patients should consent the administration of an intensified initial treatment in combination with IVIG in order to prevent coronary injuries. Few reports have focused on factors, referring to both clinical parameters and laboratory data at the onset of KS, in order to predict which patients might be IVIG non-responsive. We have analysed three different risk scores which were formulated to predict IVIG resistance in Japanese children with typical KS, but their application in non-Japanese patients or in those with incomplete and atypical patterns of the disease has been studied in a fragmentary way. Overall, our analysis showed that early and definite ascertainment of likely IVIG non-responders who require additional therapies reducing the development of coronary artery involvement in children with KS is still a challenge.