Publications by authors named "Francesco Sardanelli"

296 Publications

Abdominal obesity phenotype is associated with COVID-19 chest X-ray severity score better than BMI-based obesity.

Eat Weight Disord 2021 Apr 5. Epub 2021 Apr 5.

Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami, Coral Gables, FL, USA.

Purpose: Chest X-ray (CXR) severity score and BMI-based obesity are predictive risk factors for COVID-19 hospital admission. However, the relationship between abdominal obesity and CXR severity score has not yet been fully explored.

Methods: This retrospective cohort study analyzed the association of different adiposity indexes, including waist circumference and body mass index (BMI), with CXR severity score in 215 hospitalized patients with COVID-19.

Results: Patients with abdominal obesity showed significantly higher CXR severity scores and had higher rates of CXR severity scores ≥ 8 compared to those without abdominal obesity (P < 0.001; P = 0.001, respectively). By contrast, patients with normal weight, with overweight and those with BMI-based obesity showed no significant differences in either CXR severity scores or in the rates of CXR severity scores ≥ 8 (P = 0.104; P = 0.271, respectively). Waist circumference and waist-to-height ratio (WHtR) correlated more closely with CXR severity scores than BMI (r = 0.43, P < 0.001; r = 0.41, P < 0.001; r = 0.17, P = 0.012, respectively). The area under the curves (AUCs) for waist circumference and WHtR were significantly higher than that for BMI in identifying a high CXR severity score (≥ 8) (0.68 [0.60-0.75] and 0.67 [0.60-0.74] vs 0.58 [0.51-0.66], P = 0.001). A multivariate analysis indicated abdominal obesity (risk ratio: 1.75, 95% CI: 1.25-2.45, P < 0.001), bronchial asthma (risk ratio: 1.73, 95% CI: 1.07-2.81, P = 0.026) and oxygen saturation at admission (risk ratio: 0.96, 95% CI: 0.94-0.97, P < 0.001) as the only independent factors associated with high CXR severity scores.

Conclusion: Abdominal obesity phenotype is associated with a high CXR severity score better than BMI-based obesity in hospitalized patients with COVID-19. Therefore, when visiting the patient in a hospital setting, waist circumference should be measured, and patients with abdominal obesity should be monitored closely. Level of evidence Cross-sectional descriptive study, Level V.
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http://dx.doi.org/10.1007/s40519-021-01173-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020829PMC
April 2021

Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia.

Diagnostics (Basel) 2021 Mar 16;11(3). Epub 2021 Mar 16.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.

We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.
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http://dx.doi.org/10.3390/diagnostics11030530DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000736PMC
March 2021

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

Neuroimage Clin 2021 Mar 7;30:102616. Epub 2021 Mar 7.

Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.

White matter hyperintensities (WMHs) on T-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T-weighted images (Tw) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and Tw-hypointense/nonTw-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular Tw-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in Tw reveals specific associations with cognitive performance.
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http://dx.doi.org/10.1016/j.nicl.2021.102616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995650PMC
March 2021

CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.

Radiology 2021 Mar 16:204141. Epub 2021 Mar 16.

From Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy (S.S., L.A.C., F.S.); Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Via del Vespro 127, 90127 Palermo, Italy (D.A.); Unit of Radiology, IRCCS Istituto Ortopedico Galeazzi, Via R. Galeazzi 4, 20161 Milano, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy (A.C., C.M., S.G., F.S., F.S., L.M.S.); Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Mazzini 18, 28100 Novara, Italy (R.A., A.C., P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Via Leonida Bissolati 57, 25124 Brescia, Italy (C.B., L.M.); Radiology Department, Ospedale SS. Annunziata, Via Giovanni Vicini 2, 44042 Cento, Italy (A.B., R.R.); DIMET, Università degli Studi del Piemonte Orientale, Via Solaroli 17, 28100 Novara, Italy (A.C.); Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milano, Italy (S.C., E.D., C.D.B., G.D.P., I.V.); High Speciality Center for Dietetics, Nutritional Education and Cardiometabolic Prevention, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy (A.E.M.); Division of Interventional Radiology, IRCCS Istituto Europeo di Oncologia - IEO, Via Ripamonti 435, 20141 Milano, Italy (G.M.); Department of Oncology and Hematology-Oncology, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milano, Italy (G.M., A.V.); ASST Grande Ospedale Metropolitano Niguarda, Piazza dell'Ospedale Maggiore 3, 20162 Milano, Italy (A.V., V.T.).

Background Lower muscle mass is a known predictor of unfavorable outcome, but its prognostic impact on COVID-19 patients is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in COVID-19 patients. Materials and Methods Clinical/laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed COVID-19, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. Extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation of paravertebral muscles were measured on axial CT images at T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation odds ratios (OR) with 95% confidence intervals (CIs), were used to build four models to predict ICU admission and death, tested and compared using receiver operating characteristic curve (ROC) analysis. Results A total 552 patients (364 men; median age 65 years, interquartile range 54-75) were included. In a CT-based model, lower-than-median T5 paravertebral muscle area showed the highest ORs for ICU admission (OR 4.8, 95% CI 2.7-8.5; <.001) and death (OR 2.3, 95% CI 1.0-2.9; =.027). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle area still showed the highest ORs both for ICU admission (OR 4.3; 95% CI 2.5-7.7; <.001) and death (OR 2.3, 95% CI 1.3-3.7; =.001). At ROC analysis, the CT-based model and the model including clinical variables showed the same area under the curve (AUC) for ICU admission prediction (AUC 0.83, =.380) and were not different in predicting death (AUC 0.86 versus AUC 0.87, respectively, =.282). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT was independently associated with ICU admission and hospital mortality.
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http://dx.doi.org/10.1148/radiol.2021204141DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7971428PMC
March 2021

Subcutaneous, Paracardiac, and Epicardial Fat CT Density Before/After Contrast Injection: Any Correlation with CAD?

J Clin Med 2021 Feb 12;10(4). Epub 2021 Feb 12.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milano, Italy.

Adipose tissue, in particular epicardial adipose tissue, has been identified as a potential biomarker of cardiovascular pathologies such as coronary artery disease (CAD) in the light of its metabolic activity and close anatomic and pathophysiologic relationship to the heart. Our purpose was to evaluate epicardial adipose tissue density at both unenhanced and contrast-enhanced computed tomography (CT), along with CT densities of paracardiac and subcutaneous adipose tissue, as well as the relations of such densities with CAD. We retrospectively reviewed patients who underwent cardiac CT at our institution for CAD assessment. We segmented regions of interest on epicardial, paracardiac, and subcutaneous adipose tissue on unenhanced and contrast-enhanced scans. A total of 480 patients were included, 164 of them presenting with CAD. Median epicardial adipose tissue density measured on contrast-enhanced scans (-81.5 HU; interquartile range -84.9 to -78.0) was higher than that measured on unenhanced scans (-73.4 HU; -76.9 to -69.4) ( < 0.001), whereas paracardiac and subcutaneous adipose tissue densities were not ( ≥ 0.055). Patients with or without CAD, did not show significant differences in density of epicardial, paracardiac, and subcutaneous adipose tissue either on unenhanced or contrast-enhanced scans ( ≥ 0.092). CAD patients may experience different phenomena (inflammation, fibrosis, increase in adipose depots) leading to rises or drops in epicardial adipose tissue density, resulting in variations that are difficult to detect.
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http://dx.doi.org/10.3390/jcm10040735DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918165PMC
February 2021

AI applications to medical images: From machine learning to deep learning.

Phys Med 2021 Mar 1;83:9-24. Epub 2021 Mar 1.

Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy; Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy. Electronic address:

Purpose: Artificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context.

Methods: A narrative review has been performed including a critical assessment of articles published between 1989 and 2021 that guided challenging sections.

Results: We first illustrate the architectural characteristics of machine learning (ML)/radiomics and deep learning (DL) approaches. For ML/radiomics, the phases of feature selection and of training, validation, and testing are described. DL models are presented as multi-layered artificial/convolutional neural networks, allowing us to directly process images. The data curation section includes technical steps such as image labelling, image annotation (with segmentation as a crucial step in radiomics), data harmonization (enabling compensation for differences in imaging protocols that typically generate noise in non-AI imaging studies) and federated learning. Thereafter, we dedicate specific sections to: sample size calculation, considering multiple testing in AI approaches; procedures for data augmentation to work with limited and unbalanced datasets; and the interpretability of AI models (the so-called black box issue). Pros and cons for choosing ML versus DL to implement AI applications to medical imaging are finally presented in a synoptic way.

Conclusions: Biomedicine and healthcare systems are one of the most important fields for AI applications and medical imaging is probably the most suitable and promising domain. Clarification of specific challenging points facilitates the development of such systems and their translation to clinical practice.
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http://dx.doi.org/10.1016/j.ejmp.2021.02.006DOI Listing
March 2021

MRI-Derived Tumour-to-Breast Volume Is Associated with the Extent of Breast Surgery.

Diagnostics (Basel) 2021 Jan 30;11(2). Epub 2021 Jan 30.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy.

The tumour-to-breast volume ratio (TBVR) is a metric that may help surgical decision making. In this retrospective Ethics-Committee-approved study, we assessed the correlation between magnetic resonance imaging (MRI)-derived TBVR and the performed surgery. The TBVR was obtained using a fully manual method for the segmentation of the tumour volume (TV) and a growing region semiautomatic method for the segmentation of the whole breast volume (WBV). Two specifically-trained residents (R1 and R2) independently segmented T1-weighted datasets of 51 cancer cases in 51 patients (median age 57 years). The intraobserver and interobserver TBVR reproducibility were calculated. Mann-Whitney , Spearman correlations, and Bland-Altman statistics were used. Breast-conserving surgery (BCS) was performed in 31/51 cases (61%); mastectomy was performed in 20/51 cases (39%). The median TBVR was 2.08‰ (interquartile range 0.70-9.13‰) for Reader 1, and 2.28‰ (interquartile range 0.71-9.61‰) for Reader 2, with an 84% inter-reader reproducibility. The median segmentation times were 54 s for the WBV and 141 s for the TV. Significantly-lower TBVR values were observed in the breast-conserving surgery group (median 1.14‰, interquartile range 0.49-2.55‰) than in the mastectomy group (median 10.52‰, interquartile range 2.42-14.73‰) for both readers ( < 0.001). Large scale prospective studies are needed in order to validate MRI-derived TBVR as a predictor of the type of breast surgery.
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http://dx.doi.org/10.3390/diagnostics11020204DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912531PMC
January 2021

Bone strain index as a predictor of further vertebral fracture in osteoporotic women: An artificial intelligence-based analysis.

PLoS One 2021 8;16(2):e0245967. Epub 2021 Feb 8.

Villa Santa Maria Foundation, Tavernerio (CO), Italy.

Background: Osteoporosis is an asymptomatic disease of high prevalence and incidence, leading to bone fractures burdened by high mortality and disability, mainly when several subsequent fractures occur. A fragility fracture predictive model, Artificial Intelligence-based, to identify dual X-ray absorptiometry (DXA) variables able to characterise those patients who are prone to further fractures called Bone Strain Index, was evaluated in this study.

Methods: In a prospective, longitudinal, multicentric study 172 female outpatients with at least one vertebral fracture at the first observation were enrolled. They performed a spine X-ray to calculate spine deformity index (SDI) and a lumbar and femoral DXA scan to assess bone mineral density (BMD) and bone strain index (BSI) at baseline and after a follow-up period of 3 years in average. At the end of the follow-up, 93 women developed a further vertebral fracture. The further vertebral fracture was considered as one unit increase of SDI. We assessed the predictive capacity of supervised Artificial Neural Networks (ANNs) to distinguish women who developed a further fracture from those without it, and to detect those variables providing the maximal amount of relevant information to discriminate the two groups. ANNs choose appropriate input data automatically (TWIST-system, Training With Input Selection and Testing). Moreover, we built a semantic connectivity map usingthe Auto Contractive Map to provide further insights about the convoluted connections between the osteoporotic variables under consideration and the two scenarios (further fracture vs no further fracture).

Results: TWIST system selected 5 out of 13 available variables: age, menopause age, BMI, FTot BMC, FTot BSI. With training testing procedure, ANNs reached predictive accuracy of 79.36%, with a sensitivity of 75% and a specificity of 83.72%. The semantic connectivity map highlighted the role of BSI in predicting the risk of a further fracture.

Conclusions: Artificial Intelligence is a useful method to analyse a complex system like that regarding osteoporosis, able to identify patients prone to a further fragility fracture. BSI appears to be a useful DXA index in identifying those patients who are at risk of further vertebral fractures.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245967PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870050PMC
February 2021

Dual-energy CT performance in acute pulmonary embolism: a meta-analysis.

Eur Radiol 2021 Feb 8. Epub 2021 Feb 8.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Lombardia, Italy.

Objectives: To evaluate the diagnostic performance of dual-energy computed tomography (DECT) with regard to its post-processing techniques, namely linear blending (LB), iodine maps (IM), and virtual monoenergetic (VM) reconstructions, in diagnosing acute pulmonary embolism (PE).

Methods: This meta-analysis was conducted according to PRISMA. A systematic search on MEDLINE and EMBASE was performed in December 2019, looking for articles reporting the diagnostic performance of DECT on a per-patient level. Diagnostic performance meta-analyses were conducted grouping study parts according to DECT post-processing methods. Correlations between radiation or contrast dose and publication year were appraised.

Results: Seventeen studies entered the analysis. Only lobar and segmental acute PE were considered, subsegmental acute PE being excluded from analysis due to data heterogeneity or lack of data. LB alone was assessed in 6 study parts accounting for 348 patients, showing a pooled sensitivity of 0.87 and pooled specificity of 0.93. LB and IM together were assessed in 14 study parts accounting for 1007 patients, with a pooled sensitivity of 0.89 and pooled specificity of 0.90. LB, IM, and VM together were assessed in 2 studies (for a total 144 patients) and showed a pooled sensitivity of 0.90 and pooled specificity of 0.90. The area under the curve for LB alone, and LB together with IM was 0.93 (not available for studies using LB, IM and VM because of paucity of data). Radiation and contrast dose did not decrease with increasing year of publication.

Conclusions: Considering the published performance of single-energy CT in diagnosing acute PE, either dual-energy or single-energy computed tomography can be comparably used for the detection of acute PE.

Key Points: • Dual-energy CT displayed pooled sensitivity and specificity of 0.87 and 0.93 for linear blending alone, 0.89 and 0.90 for linear blending and iodine maps, and 0.90 and 0.90 for linear blending iodine maps, and virtual monoenergetic reconstructions. • The performance of dual-energy CT for patient management is not superior to that reported in literature for single-energy CT (0.83 sensitivity and 0.96 specificity). • Dual-energy CT did not yield substantial advantages in the identification of patients with acute pulmonary embolism compared to single-energy techniques.
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http://dx.doi.org/10.1007/s00330-020-07633-8DOI Listing
February 2021

Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.

Eur Radiol Exp 2021 02 2;5(1). Epub 2021 Feb 2.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.

Background: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy.

Methods: We used for training and validation an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals (Centres 1 and 2). We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non-COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as the reference standard.

Results: At 10-fold cross-validation, our deep learning model classified COVID-19 and non-COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74-0.81), 0.82 specificity (95% CI 0.78-0.85), and 0.89 area under the curve (AUC) (95% CI 0.86-0.91). For the independent dataset, deep learning showed 0.80 sensitivity (95% CI 0.72-0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73-0.87), and 0.81 AUC (95% CI 0.73-0.87). Radiologists' reading obtained 0.63 sensitivity (95% CI 0.52-0.74) and 0.78 specificity (95% CI 0.61-0.90) in Centre 1 and 0.64 sensitivity (95% CI 0.52-0.74) and 0.86 specificity (95% CI 0.71-0.95) in Centre 2.

Conclusions: This preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of deep learning for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.
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http://dx.doi.org/10.1186/s41747-020-00203-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850902PMC
February 2021

Why is appropriate healthcare inaccessible for many European breast cancer patients? - The EBCC 12 manifesto.

Breast 2021 Feb 2;55:128-135. Epub 2021 Jan 2.

Iridium Kankernetwerk and University of Antwerp, Wilrijk, Antwerp, Belgium. Electronic address:

In Europe, inappropriate reimbursement and funding rules and regulations act as disincentives to best breast cancer care or, at worst, hinder best care. This problem was the focus of the 12th European Breast Cancer Conference (EBCC) manifesto, discussed during the virtual conference. As patient involvement is indispensable in driving changes to clinical practice, Europa Donna the European patient advocacy group was closely involved in the 12th manifesto. Reimbursement policies have rarely evolved with advances in breast cancer care such as outpatient (ambulatory) care rather than inpatient admission, use of oral or subcutaneous anti-cancer drugs rather than day-hospital intravenous administration, oncoplastic surgery techniques to minimize mastectomy rates, breast reconstructive surgery, risk-reducing surgery for BRCA mutation carriers, or use of hypo-fractionated breast radiation therapy. Although each European country, region and centre will have to understand how their reimbursement policies may hinder best care and find their own solutions, the problems are similar throughout Europe and some solutions can be broadly applied. This manifesto is not calling for more funding or demanding changes that will result in more expensive care. Reimbursement, if better aligned with guidelines and optimal clinical practice, will deliver more cost-effective healthcare. This will release resources, support more equitable use of finite funding and resources, so allowing more European breast cancer patients to benefit from evidence-based treatment recommended by national and international guidelines.
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http://dx.doi.org/10.1016/j.breast.2020.12.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817501PMC
February 2021

Late gadolinium enhancement in patients with Tetralogy of Fallot: A systematic review.

Eur J Radiol 2021 Mar 6;136:109521. Epub 2021 Jan 6.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; Department of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy.

Purpose: The aim of this study is to review the literature concerning myocardial late gadolinium enhancement (LGE) with cardiac magnetic resonance in patients with Tetralogy of Fallot (ToF), with regards to its prevalence, characteristics and clinical relevance.

Methods: We performed a systematic search, aiming to retrieve original articles that evaluated LGE in ToF, running a search string on MEDLINE and EMBASE in November 2019 and November 2020. Papers were then selected by two independent, blinded readers based on title and abstract, and then on full-text reading, and articles which did not include LGE evaluation were excluded. From each included paper two readers extracted descriptive data concerning technical parameters of LGE acquisition, LGE description and clinical significance.

Results: 18 articles were eventually included in our review. The included studies observed that a higher amount of right ventricular LGE relates with higher right ventricular volumes, lower ejection fraction and a higher pulmonary regurgitant fraction, thus acting as a marker of progressive impairment of myocardial function. Moreover, LGE in ToF patients correlated with the onset of arrhythmias, and with serum biomarkers indicative of myocardial stress and fibrosis.

Conclusions: LGE could be used in the follow-up repaired ToF patients as its appraisal can provide information concerning cardiac dysfunction. Moreover, it may be ideal to aim towards a common framework for standardizing assessment and quantification of LGE in ToF patients.
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http://dx.doi.org/10.1016/j.ejrad.2021.109521DOI Listing
March 2021

Pulmonary thromboembolism in coronavirus disease 2019 patients undergoing thromboprophylaxis.

Medicine (Baltimore) 2021 Jan;100(1):e24002

Unit of Radiology.

Abstract: We aimed to investigate the prevalence of pulmonary thromboembolism (PTE) and its association with clinical variables in a cohort of hospitalized coronavirus disease 2019 (COVID-19) patients receiving low-molecular-weight heparin (LMWH) at prophylactic dosage.In this retrospective observational study we included COVID-19 patients receiving prophylactic LMWH from admission but still referred for lower-limbs venous Doppler ultrasound (LL-US) and computed tomography pulmonary angiography (CTPA) for clinical PTE suspicion. A dedicated radiologist reviewed CTPA images to assess PTE presence/extension.From March 1 to April 30, 2020, 45 patients were included (34 men, median age 67 years, interquartile range [IQR] 60-76). Twenty-seven (60%) had PTE signs at CTPA, 17/27 (63%) with bilateral involvement, none with main branch PTE. In 33/45 patients (73%) patients LL-US was performed before CTPA, with 3 patients having superficial vein thrombosis (9%, none with CTPA-confirmed PTE) and 1 patient having deep vein thrombosis (3%, with CTPA-confirmed PTE). Thirty-three patients (73%) had at least one comorbidity, mainly hypertension (23/45, 51%) and cardiovascular disease (15/45, 33%). Before CTPA, 5 patients had high D-dimer (11.21 μg/mL, IQR 9.10-13.02), 19 high fibrinogen (550 mg/dL, IQR 476-590), 26 high interleukin-6 (79 pg/mL, IQR 31-282), and 11 high C-reactive protein (9.60 mg/dL, IQR 6.75-10.65), C-reactive protein being the only laboratory parameter significantly differing between patients with and without PTE (P = .002)High PTE incidence (60%) in COVID-19 hospitalized patients under prophylactic LMWH could substantiate further tailoring of anticoagulation therapy.
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http://dx.doi.org/10.1097/MD.0000000000024002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793450PMC
January 2021

Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients.

Obes Res Clin Pract 2021 Jan-Feb;15(1):89-92. Epub 2020 Dec 11.

Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy; Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy.

We retrospectively investigated, in 62 consecutive hospitalised COVID-19 patients (aged 70 ± 14 years, 40 males), the prognostic value of CT-derived subcutaneous adipose tissue and visceral adipose tissue (VAT) metrics, testing them in four predictive models for admission to intensive care unit (ICU), with and without pre-existing comorbidities. Multivariate logistic regression identified VAT score as the best ICU admission predictor (odds ratios 4.307-12.842). A non-relevant contribution of comorbidities at receiver operating characteristic analysis (area under the curve 0.821 for the CT-based model, 0.834 for the one including comorbidities) highlights the potential one-stop-shop prognostic role of CT-derived lung and adipose tissue metrics.
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http://dx.doi.org/10.1016/j.orcp.2020.12.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836243PMC
February 2021

White Matter Hyperintensities Quantification in Healthy Adults: A Systematic Review and Meta-Analysis.

J Magn Reson Imaging 2020 Dec 20. Epub 2020 Dec 20.

Department of Radiology, Stanford University School of Medicine, Stanford, California, USA.

Background: Although white matter hyperintensities (WMH) volumetric assessment is now customary in research studies, inconsistent WMH measures among homogenous populations may prevent the clinical usability of this biomarker.

Purpose: To determine whether a point estimate and reference standard for WMH volume in the healthy aging population could be determined.

Study Type: Systematic review and meta-analysis.

Population: In all, 9716 adult subjects from 38 studies reporting WMH volume were retrieved following a systematic search on EMBASE.

Field Strength/sequence: 1.0T, 1.5T, or 3.0T/fluid-attenuated inversion recovery (FLAIR) and/or proton density/T -weighted fast spin echo sequences or gradient echo T -weighted sequences.

Assessment: After a literature search, sample size, demographics, magnetic field strength, MRI sequences, level of automation in WMH assessment, study population, and WMH volume were extracted.

Statistical Tests: The pooled WMH volume with 95% confidence interval (CI) was calculated using the random-effect model. The I statistic was calculated as a measure of heterogeneity across studies. Meta-regression analysis of WMH volume on age was performed.

Results: Of the 38 studies analyzed, 17 reported WMH volume as the mean and standard deviation (SD) and were included in the meta-analysis. Mean and SD of age was 66.11 ± 10.92 years (percentage of men 50.45% ± 21.48%). Heterogeneity was very high (I = 99%). The pooled WMH volume was 4.70 cm (95% CI: 3.88-5.53 cm ). At meta-regression analysis, WMH volume was positively associated with subjects' age (β = 0.358 cm per year, P < 0.05, R = 0.27).

Data Conclusion: The lack of standardization in the definition of WMH together with the high technical variability in assessment may explain a large component of the observed heterogeneity. Currently, volumes of WMH in healthy subjects are not comparable between studies and an estimate and reference interval could not be determined.

Level Of Evidence: 1 TECHNICAL EFFICACY STAGE: 1.
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http://dx.doi.org/10.1002/jmri.27479DOI Listing
December 2020

Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study.

Eur Radiol Exp 2020 12 15;4(1):68. Epub 2020 Dec 15.

Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy.

Background: Integration of imaging and clinical parameters could improve the stratification of COVID-19 patients on emergency department (ED) admission. We aimed to assess the extent of COVID-19 pulmonary abnormalities on chest x-ray (CXR) using a semiquantitative severity score, correlating it with clinical data and testing its interobserver agreement.

Methods: From February 22 to April 8, 2020, 926 consecutive patients referring to ED of two institutions in Northern Italy for suspected SARS-CoV-2 infection were reviewed. Patients with reverse transcriptase-polymerase chain reaction positive for SARS-CoV-2 and CXR images on ED admission were included (295 patients, median age 69 years, 199 males). Five readers independently and blindly reviewed all CXRs, rating pulmonary parenchymal involvement using a 0-3 semiquantitative score in 1-point increments on 6 lung zones (range 0-18). Interobserver agreement was assessed with weighted Cohen's κ, correlations between median CXR score and clinical data with Spearman's ρ, and the Mann-Whitney U test.

Results: Median score showed negative correlation with SpO (ρ = -0.242, p < 0.001), positive correlation with white cell count (ρ = 0.277, p < 0.001), lactate dehydrogenase (ρ = 0.308, p < 0.001), and C-reactive protein (ρ = 0.367, p < 0.001), being significantly higher in subsequently dead patients (p = 0.003). Considering overall scores, readers' pairings yielded moderate (κ = 0.449, p < 0.001) to almost perfect interobserver agreement (κ = 0.872, p < 0.001), with better interobserver agreement between readers of centre 2 (up to κ = 0.872, p < 0.001) than centre 1 (κ = 0.764, p < 0.001).

Conclusions: Proposed CXR pulmonary severity score in COVID-19 showed moderate to almost perfect interobserver agreement and significant but weak correlations with clinical parameters, potentially furthering CXR integration in patients' stratification.
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http://dx.doi.org/10.1186/s41747-020-00195-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735892PMC
December 2020

Lean body weight versus total body weight to calculate the iodinated contrast media volume in abdominal CT: a randomised controlled trial.

Insights Imaging 2020 Dec 9;11(1):132. Epub 2020 Dec 9.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.

Objectives: Iodinated contrast media (ICM) could be more appropriately dosed on patient lean body weight (LBW) than on total body weight (TBW).

Methods: After Ethics Committee approval, trial registration NCT03384979, patients aged ≥ 18 years scheduled for multiphasic abdominal CT were randomised for ICM dose to LBW group (0.63 gI/kg of LBW) or TBW group (0.44 gI/kg of TBW). Abdominal 64-row CT was performed using 120 kVp, 100-200 mAs, rotation time 0.5 s, pitch 1, Iopamidol (370 mgI/mL), and flow rate 3 mL/s. Levene, Mann-Whitney U, and χ tests were used. The primary endpoint was liver contrast enhancement (LCE).

Results: Of 335 enrolled patients, 17 were screening failures; 44 dropped out after randomisation; 274 patients were analysed (133 LBW group, 141 TBW group). The median age of LBW group (66 years) was slightly lower than that of TBW group (70 years). Although the median ICM-injected volume was comparable between groups, its variability was larger in the former (interquartile range 27 mL versus 21 mL, p = 0.01). The same was for unenhanced liver density (IQR 10 versus 7 HU) (p = 0.02). Median LCE was 40 (35-46) HU in the LBW group and 40 (35-44) HU in the TBW group, without significant difference for median (p = 0.41) and variability (p = 0.23). Suboptimal LCE (< 40 HU) was found in 64/133 (48%) patients in the LBW group and 69/141 (49%) in the TBW group, but no examination needed repeating.

Conclusions: The calculation of the ICM volume to be administered for abdominal CT based on the LBW does not imply a more consistent LCE.
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http://dx.doi.org/10.1186/s13244-020-00920-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726088PMC
December 2020

Breast cancer screening: in the era of personalized medicine, age is just a number.

Quant Imaging Med Surg 2020 Dec;10(12):2401-2407

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.

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http://dx.doi.org/10.21037/qims-2020-26DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596396PMC
December 2020

Accuracy and inter-reader agreement of breast MRI for cancer staging using 0.08 mmol/kg of gadobutrol.

Clin Imaging 2021 Apr 10;72:154-161. Epub 2020 Nov 10.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy. Electronic address:

Background: Evidence on gadolinium brain accumulation after contrast-enhanced MRI prompted research in dose reduction.

Purpose: To estimate accuracy and inter-reader reproducibility of tumor size measurement in breast MRI using 0.08 mmol/kg of gadobutrol.

Methods: We retrospectively analyzed all women who underwent 1.5-T breast MRI for cancer staging at our department with 0.08 mmol/kg of gadobutrol. Two readers (R1 and R2, 12 and 3 years-experience) measured the largest lesion diameter. Accuracy was estimated both as correlation with pathology and rate of absolute (>5 mm) overestimation and underestimation, inter-reader reproducibility using the Bland-Altman method. Data are given as median and interquartile range.

Results: Thirty-six patients were analyzed (median age 56 years, 49-66) for a total of 38 lesions, 24 (63%) mass enhancement, 14 (37%) non-mass enhancement. Histopathological median size (mm) of all lesions was 15 (9-25): 13 (9-19) for mass lesions, 19 (11-39) for non-mass lesions. On MRI, R1 measured (mm) 14 (10-22) for all lesions, 13 (10-19) for mass lesions, 19 (11-49) for non-mass lesions. MRI-pathology correlation was very high for all lesion categories (ρ ≥ 0.766). On MRI, R1 overestimated lesion size in 6 cases (16%), and underestimated in 3 (8%); R2, overestimated 7 cases (18%) and underestimated 3 cases (8%). At inter-reader reproducibility analysis (mm): bias 0.9, coefficient of reproducibility 13 for all lesions; -0.1 and 6 for mass lesions; 2.5 and 20 for non-mass lesions.

Conclusions: Breast MRI may be performed using 0.08 mmol/kg of gadobutrol with high accuracy and acceptable inter-reader agreement.
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http://dx.doi.org/10.1016/j.clinimag.2020.11.014DOI Listing
April 2021

Computed tomography-derived myocardial extracellular volume: an early biomarker of cardiotoxicity in esophageal cancer patients undergoing radiation therapy.

Insights Imaging 2020 Nov 23;11(1):120. Epub 2020 Nov 23.

Department of Biomedical Sciences for Health, Università Degli Studi Di Milano, Via Mangiagalli 31, 20133, Milano, Italy.

Objectives: We aimed to assess extracellular volume (ECV) through non-gated, contrast-enhanced computed tomography (CT) before and after radiation therapy (RT) in patients with esophageal cancer (EC).

Materials And Methods: EC patients who had undergone CT before and after RT were retrospectively assessed. Patients with preexisting cardiovascular disease or with heavily artifacted CT were excluded. ECV was calculated using density values for the myocardial septum and blood pool. Data were reported as mean and standard deviation or median and interquartile range according to their distribution; t test or Wilcoxon and Pearson r or Spearman ρ were subsequently used.

Results: Twenty-one patients with stage ≥ IB EC, aged 64 ± 18 years, were included. Mean and maximum RT doses were 21.2 Gy (16.9-24.1) and 42.5 Gy (41.8-49.2), respectively. At baseline (n = 21), hematocrit was 39% ± 4%, ECV 27.9% ± 3.5%; 35 days (30-38) after RT (n = 20), hematocrit was 36% ± 4%, lower than at baseline (p = 0.002), ECV 30.3% ± 8.3%, higher than at baseline (p = 0.081); at follow-up 420 days (244-624) after RT (n = 13), hematocrit was 36% ± 5%, lower than at baseline (p = 0.030), ECV 31.4% ± 4.5%, higher than at baseline (p = 0.011). No patients showed signs of overt cardiotoxicity. ECV early after RT was moderately positively correlated with maximum RT dose (ρ = 0.50, p = 0.036).

Conclusions: In EC patients, CT-derived myocardial ECV was increased after RT and may thus appear as a potential early biomarker of cardiotoxicity.
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http://dx.doi.org/10.1186/s13244-020-00922-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683763PMC
November 2020

MRI physics and technical issues: Where do Italian radiographers search for information?

J Med Imaging Radiat Sci 2021 03 16;52(1):104-111. Epub 2020 Nov 16.

Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy; Department of Biomedical Sciences for Health, Università degli Studi di Milano, San Donato Milanese, Italy.

Introduction: Our aim was to investigate the means radiographers and radiographers in training (RTrs) use to seek information on magnetic resonance imaging (MRI) physics and technical issues.

Methods: An estimated 3000 radiographers and RTrs were reached by e-mail. We proposed an online survey with eight English-language multiple choice questions investigating how often radiographers have doubts about MRI physics or technical issues, where and what kind of information they search for, and on which websites. The statistical χ test was used.

Results: We obtained 300 answers from European professionals (228 radiographers, 72 RTrs) from 9 European countries, with 288 of 300 (96%) responses coming from Italy. Within the Italian respondents, 41% of RTrs have doubts about MRI physics versus 56% of radiographers (p = 0.028). Basic MRI sequences details are more searched by RTrs (36%) than radiographers (22%) (p = 0.088), as well as clinical protocols (64% versus 44%, p = 0.054). Radiographers and RTrs mostly search on the Internet (74% versus 81%, p = 0.404); "older colleagues" are more frequently asked for information by RTrs (27% versus 61%, p = 0.001), they consult the "MRI manufacturer" less frequently (11% versus 34%, p = 0.001); and 66% of radiographers and 72% of RTrs search "in mother-language and English" (p = 0.590). For clinical protocols RTrs prefer the website mriquestions.com (17% versus 44%, p = 0.001). Websites most used were: mriquestions.com (41%), radiopaedia.org (31%), and mrimaster.com (13%). In addition, 30 respondents mentioned using the Italian site fermononrespiri.com.

Conclusion: Italian radiographers and RTrs frequently search for information about MRI physics and technical issues, with slight differences between groups regarding sources and clinical protocols. Protocol setting, and MRI physics and sequences seem to be the main limitations of RTr knowledge. To remedy this gap, more time on training/university lectures and a rethinking of the practical training activities is required.
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http://dx.doi.org/10.1016/j.jmir.2020.10.005DOI Listing
March 2021

Practical approach to imaging diagnosis of biliary atresia, Part 1: prenatal ultrasound and magnetic resonance imaging, and postnatal ultrasound.

Pediatr Radiol 2021 Feb 17;51(2):314-331. Epub 2020 Nov 17.

Aix Marseille Université, AP-HM, Equipe d'Accueil 3279 - IFR 125, Hôpital Timone Enfants, Service d'Imagerie Pédiatrique et Prénatale, Marseille, France.

We present a practical approach to imaging in suspected biliary atresia, an inflammatory cholangiopathy of infancy resulting in progressive fibrosis and obliteration of extrahepatic and intrahepatic bile ducts. Left untreated or with failure of the Kasai procedure, biliary atresia progresses towards biliary cirrhosis, end-stage liver failure and death by age 3. Differentiation of biliary atresia from other nonsurgical causes of neonatal cholestasis is challenging because there is no single method for diagnosing biliary atresia, and clinical, laboratory and imaging features of this disease overlap with those of other causes of neonatal cholestasis. Concerning imaging, our systematic literature review shows that ultrasonography is the main tool for pre- and neonatal diagnosis. Key prenatal features, when present, are non-visualisation of the gallbladder, cyst in the liver hilum, heterotaxy syndrome and irregular gallbladder walls. Postnatal imaging features have a very high specificity when present, but a variable sensitivity. Triangular cord sign and abnormal gallbladder have the highest sensitivity and specificity. The presence of macro- or microcyst or polysplenia syndrome is highly specific but less sensitive. The diameter of the hepatic artery and hepatic subcapsular flow are less reliable. When present in the context of acholic stools, dilated intrahepatic bile ducts rule out biliary atresia. Importantly, a normal US exam does not rule out biliary atresia. Signs of chronic hepatopathy and portal hypertension (portosystemic derivations such as patent ductus venosus, recanalised umbilical vein, splenomegaly and ascites) should be actively identified for - but are not specific for - biliary atresia.
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http://dx.doi.org/10.1007/s00247-020-04840-9DOI Listing
February 2021

Do we still need breast cancer screening in the era of targeted therapies and precision medicine?

Insights Imaging 2020 Sep 25;11(1):105. Epub 2020 Sep 25.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.

Breast cancer (BC) is the most common female cancer and the second cause of death among women worldwide. The 5-year relative survival rate recently improved up to 90% due to increased population coverage and women's attendance to organised mammography screening as well as to advances in therapies, especially systemic treatments. Screening attendance is associated with a mortality reduction of at least 30% and a 40% lower risk of advanced disease. The stage at diagnosis remains the strongest predictor of recurrences. Systemic treatments evolved dramatically over the last 20 years: aromatase inhibitors improved the treatment of early-stage luminal BC; targeted monoclonal antibodies changed the natural history of anti-human epidermal growth factor receptor 2-positive (HER2) disease; immunotherapy is currently investigated in patients with triple-negative BC; gene expression profiling is now used with the aim of personalising systemic treatments. In the era of precision medicine, it is a challenging task to define the relative contribution of early diagnosis by screening mammography and systemic treatments in determining BC survival. Estimated contributions before 2000 were 46% for screening and 54% for treatment advances and after 2000, 37% and 63%, respectively. A model showed that the 10-year recurrence rate would be 30% and 25% using respectively chemotherapy or novel treatments in the absence of screening, but would drop to 19% and 15% respectively if associated with mammography screening. Early detection per se has not a curative intent and systemic treatment has limited benefit on advanced stages. Both screening mammography and systemic therapies continue to positively contribute to BC prognosis.
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http://dx.doi.org/10.1186/s13244-020-00905-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7519022PMC
September 2020

Chest x-ray in the COVID-19 pandemic: Radiologists' real-world reader performance.

Eur J Radiol 2020 Nov 10;132:109272. Epub 2020 Sep 10.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Italy. Electronic address:

Purpose: To report real-world diagnostic performance of chest x-ray (CXR) readings during the COVID-19 pandemic.

Methods: In this retrospective observational study we enrolled all patients presenting to the emergency department of a Milan-based university hospital from February 24th to April 8th 2020 who underwent nasopharyngeal swab for reverse transcriptase-polymerase chain reaction (RT-PCR) and anteroposterior bedside CXR within 12 h. A composite reference standard combining RT-PCR results with phone-call-based anamnesis was obtained. Radiologists were grouped by CXR reading experience (Group-1, >10 years; Group-2, <10 years), diagnostic performance indexes were calculated for each radiologist and for the two groups.

Results: Group-1 read 435 CXRs (77.0 % disease prevalence): sensitivity was 89.0 %, specificity 66.0 %, accuracy 83.7 %. Group-2 read 100 CXRs (73.0 % prevalence): sensitivity was 89.0 %, specificity 40.7 %, accuracy 76.0 %. During the first half of the outbreak (195 CXRs, 66.7 % disease prevalence), overall sensitivity was 80.8 %, specificity 67.7 %, accuracy 76.4 %, Group-1 sensitivity being similar to Group-2 (80.6 % versus 81.5 %, respectively) but higher specificity (74.0 % versus 46.7 %) and accuracy (78.4 % versus 69.0 %). During the second half (340 CXRs, 81.8 % prevalence), overall sensitivity increased to 92.8 %, specificity dropped to 53.2 %, accuracy increased to 85.6 %, this pattern mirrored in both groups, with decreased specificity (Group-1, 58.0 %; Group-2, 33.3 %) but increased sensitivity (92.7 % and 93.5 %) and accuracy (86.5 % and 81.0 %, respectively).

Conclusions: Real-world CXR diagnostic performance during the COVID-19 pandemic showed overall high sensitivity with higher specificity for more experienced radiologists. The increase in accuracy over time strengthens CXR role as a first line examination in suspected COVID-19 patients.
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http://dx.doi.org/10.1016/j.ejrad.2020.109272DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481070PMC
November 2020

Right ventricular strain in repaired Tetralogy of Fallot with regards to pulmonary valve replacement.

Eur J Radiol 2020 Oct 28;131:109235. Epub 2020 Aug 28.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy. Electronic address:

Purpose: To assess right ventricular (RV) myocardial strain both globally and segmentally through feature-tracking cardiac magnetic resonance (CMR) in patients with Tetralogy of Fallot (ToF), with regards to pulmonary valve replacement (PVR).

Methods: After Ethics Committee approval, we retrospectively included 46 consecutive ToF patients who had two CMR examinations performed at our institution between March 2014 and June 2019. We divided patients into those who had not undergone PVR between the two CMR examinations (Group-0), and those who had (Group-1). Ventricular volumes were quantified on cine sequences, and strain was calculated through feature-tracking, using the previously traced segmentations. RV longitudinal and radial strain were assessed both globally and separately for the septum and free wall. Variations were normalized for intercurrent years, differences were appraised with t-tests or Mann-Whitney U.

Results: 30 patients belonged to Group-0 and 16 to Group-1. Median age was 22 years (interquartile range [IQR] 17-29 years) in Group-0, and 21 years (IQR 16-29 years) in Group-1. No significant differences were reported in RV strain between groups (p ≥ 0.254) except for RV septal radial strain, significantly higher (p = 0.010) in Group-0 (24.2 %, IQR 10.1-52.4 %) than in Group-1 (6.0 %, IQR -3.3-23.3 %) at the second CMR. Both global and segmental RV strains decreased over time in both groups, and yearly variations did not differ significantly (p ≥ 0.081) between groups.

Conclusions: While PVR performed at the appropriate timing eases the burden on the RV allowing for a reduction in volumes, RV strain seems to continuously deteriorate as in patients who do not undergo PVR.
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http://dx.doi.org/10.1016/j.ejrad.2020.109235DOI Listing
October 2020

Diagnosis of left atrial appendage thrombus in patients with atrial fibrillation: delayed contrast-enhanced cardiac CT.

Eur Radiol 2021 Mar 4;31(3):1236-1244. Epub 2020 Sep 4.

Department of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.

Objectives: The current reference standard for diagnosing LAA thrombi is transesophageal echocardiography (TEE), a semi-invasive technique. We aimed to devise an optimal protocol for cardiac computed tomography (CCT) in diagnosing left atrial appendage (LAA) thrombus in patients with atrial fibrillation (AF), using TEE as reference standard.

Methods: Two hundred sixty consecutive patients referred for radiofrequency ablation for AF were prospectively enrolled. All patients underwent CCT and TEE within 2 hours. The CCT protocol included one standard angiographic phase and three delayed acquisitions at 1-, 3-, and 6-min after contrast injection. Thrombi were defined as persisting defects at 6-min delayed acquisition.

Results: TEE demonstrated spontaneous contrast in 52 (20%) patients and thrombus in 10 (4%). In 63 patients (24%), CCT demonstrated LAA early filling defects at angiographic phase. Among them, 15 (6%) had a persistent defect at 1-min, 12 (5%) at 3-min, and 10 (4%) at 6-min. All 10 thrombi diagnosed on TEE were correctly identified by delayed CCT, without any false positives. For all phases, sensitivity and negative predictive were 100%. Specificity increased from 79% for the angiographic phase to 100% at 6-min. Positive predictive value increased from 16% to 100%. Estimated radiation exposure was 2.08 ± 0.76 mSv (mean ± standard deviation) for the angiographic phase and 0.45 ± 0.23 mSv for each delayed phase.

Conclusion: A CCT protocol adding a 6-min delayed phase to the angiographic phase can be considered optimized for the diagnosis of LAA thrombi, with a low radiation dose.

Key Points: • In patients with persistent atrial fibrillation referred for ablation procedures, a cardiac CT examination comprising an angiographic-phase acquisition and, in case of filling defects, a 6-min delayed phase may help reduce the need for transesophageal echocardiography. • Cardiac CT would provide morphological and volumetric data, along with the potential to exclude the presence of thrombi in the left atrial appendage.
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http://dx.doi.org/10.1007/s00330-020-07172-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880950PMC
March 2021

Epicardial Fat Inflammation in Severe COVID-19.

Obesity (Silver Spring) 2020 12 15;28(12):2260-2262. Epub 2020 Oct 15.

Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.

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http://dx.doi.org/10.1002/oby.23019DOI Listing
December 2020

Breast arterial calcifications as a biomarker of cardiovascular risk: radiologists' awareness, reporting, and action. A survey among the EUSOBI members.

Eur Radiol 2021 Feb 27;31(2):958-966. Epub 2020 Aug 27.

Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, Milan, 20133, Italy.

Objectives: To investigate the knowledge of radiologists on breast arterial calcifications (BAC) and attitude about BAC reporting, communication to women, and subsequent action.

Methods: An online survey was offered to EUSOBI members, with 17 questions focused on demographics, level of experience, clinical setting, awareness of BAC association with cardiovascular risk, mammographic reporting, modality of BAC assessment, and action habits. Descriptive statistics were used.

Results: Among 1084 EUSOBI members, 378 (34.9%) responded to the survey, 361/378 (95.5%) radiologists, 263 females (69.6%), 112 males (29.6%), and 3 (0.8%) who did not specify their gender. Of 378 respondents, 305 (80.7%) declared to be aware of BAC meaning in terms of cardiovascular risk and 234 (61.9%) to routinely include BAC in mammogram reports, when detected. Excluding one inconsistent answer, simple annotation of BAC presence was declared by 151/233 (64.8%), distinction between low versus extensive BAC burden by 59/233 (25.3%), and usage of an ordinal scale by 22/233 (9.5%) and of a cardinal scale by 1/233 (0.4%). Among these 233 radiologists reporting BAC, 106 (45.5%) declared to orally inform the woman and, in case of severe BAC burden, 103 (44.2%) to investigate cardiovascular history, and 92 (39.5%) to refer the woman to a cardiologist.

Conclusion: Among EUSOBI respondents, over 80% declared to be aware of BAC cardiovascular meaning and over 60% to include BAC in the report. Qualitative BAC assessment predominates. About 40% of respondents who report on BAC, in the case of severe BAC burden, investigate cardiovascular history and/or refer the woman to a cardiologist.

Key Points: • Of 1084 EUSOBI members, 378 (35%) participated: 81% of respondents are aware of breast arterial calcification (BAC) cardiovascular meaning and 62% include BAC in the mammogram report. • Of those reporting BAC, description of presence was declared by 65%, low versus extensive burden distinction by 25%, usage of an ordinal scale by 10%, and of a cardinal scale by 0.4%; 46% inform the woman and, in case of severe BAC burden, 44% examine cardiovascular history, and 40% refer her to a cardiologist. • European breast radiologists may be ready for large-scale studies to ascertain the role of BAC assessment in the comprehensive framework of female cardiovascular disease prevention.
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http://dx.doi.org/10.1007/s00330-020-07136-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813731PMC
February 2021