Publications by authors named "Luca Saba"

354 Publications

Whole-Body MRI in Rheumatology: Major Advances and Future Perspectives.

Diagnostics (Basel) 2021 Sep 26;11(10). Epub 2021 Sep 26.

Department of Radiology, University Hospital of Cagliari, 09100 Cagliari, Italy.

Whole-body magnetic resonance imaging is constantly gaining more importance in rheumatology, particularly for what concerns the diagnosis, follow-up, and treatment response evaluation. Initially applied principally for the study of ankylosing spondylitis, in the last years, its use has been extended to several other rheumatic diseases. Particularly in the pediatric population, WB-MRI is rapidly becoming the gold-standard technique for the diagnosis and follow-up of both chronic recurrent multifocal osteomyelitis and juvenile spondyloarthritis. In this review, we analyze the benefits and limits of this technique as well as possible future applications.
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http://dx.doi.org/10.3390/diagnostics11101770DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534420PMC
September 2021

Review of imaging biomarkers for the vulnerable carotid plaque.

JVS Vasc Sci 2021 15;2:149-158. Epub 2021 May 15.

Stroke Diagnosis and Monitoring Division, AtheroPoint™, Roseville, Calif.

Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. As a result of the rapid technological evolution in medical imaging, several important steps have been taken in the field of carotid plaque imaging allowing us to visualize the carotid atherosclerotic plaque and its composition in great detail. For computed tomography, magnetic resonance imaging, positron emission tomography, and ultrasound scan, evidence has accumulated on novel imaging-based markers that confer information on carotid plaque vulnerability, such as intraplaque hemorrhage and lipid-rich necrotic cores. In terms of the imaging-based identification of individuals at high risk of stroke, routine assessments of such imaging markers are the way forward for improving current clinical practice. The current review highlights the main characteristics of the vulnerable plaque indicating their role in the etiology of ischemic stroke as identified by intensive plaque imaging.
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http://dx.doi.org/10.1016/j.jvssci.2021.03.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8489200PMC
May 2021

Atrial Strain by Feature-Tracking Cardiac Magnetic Resonance Imaging in Takotsubo Cardiomyopathy. Features, Feasibility, and Reproducibility.

Can Assoc Radiol J 2021 Oct 7:8465371211042497. Epub 2021 Oct 7.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), Monserrato (Cagliari), Italy.

Objectives: The purpose of this study was to investigate whether there may be a bi-atrial dysfunction in Takotsubo syndrome (TS) during the transient course of the disease, using cardiac magnetic resonance imaging feature tracking (CMR-FT) in analyzing bi-atrial strain.

Method: Eighteen TS patients and 13 healthy controls were studied. Reservoir, conduit, and booster bi-atrial functions were analyzed by CMR-FT. The correlation between LA and RA strain parameters was assessed. Intra- and inter-observer reproducibility was evaluated for all strain and strain rate (SR) parameters using intraclass correlation coefficients (ICCs) and Bland-Altman analysis.

Results: Atrial strain were feasible in all patients and controls. Takotsubo patients showed an impaired LA Reservoir strain (∊), LA Reservoir strain rate (SRs), LA and RA Conduit strain(∊), LA and RA conduit strain rate (SRe) in comparison with controls (P < 0.001 for all of them), while no differences were found as to LA and RA booster deformation parameters (∊ and SRa). Analysis of correlation showed that LA ∊, SRs, ∊, and SRe were positively correlated with corresponding RA strain measurements (P < 0.001, r = 0.61 and P = 0,03, r = 0,54, respectively). Reproducibility was good to excellent for all atrial strain and strain rate parameters (ICCs ranging from 0,50 to 0,96).

Conclusion: Atrial strain analysis using CMR-FT may be a useful tool to reveal new pathophysiological insights in Takotsubo cardiomyopathy. Additional studies, with a larger number of patients, are needed to confirm the possible role of these advanced CMR tools in characterizing TS patients.
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http://dx.doi.org/10.1177/08465371211042497DOI Listing
October 2021

The mid-term effects of carotid endarterectomy on cognition and regional neural activity analyzed with the amplitude of low frequency fluctuations technique.

Neuroradiology 2021 Sep 25. Epub 2021 Sep 25.

Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy.

Purpose: The study aims to evaluate the mid-term effects of carotid endarterectomy (CEA) on cognition and resting-state functional magnetic resonance imaging (rs-fMRI) using the Amplitude of Low Frequency Fluctuations (ALFF) technique.

Methods: In this observational study, patients eligible for CEA were prospectively included. On the same day, within 1 week of the CEA procedure performed and 12 months after the CEA procedure, all patients underwent (i) an MRI examination for rs-fMRI analysis and (ii) a cognitive evaluation using the Italian version of the Mini-Mental State Examination (MMSE) corrected for age and schooling. Pre-CEA and post-CEA MMSE scores were evaluated using paired sample t-tests, adopting a p-value < 0.05 as statistical threshold. The ALFF technique was used for analyzing the differences between pre-CEA and post-CEA rs-fMRI scans in terms of regional neural activation. This was accomplished by applying non-parametric statistics based on randomization/permutation for cluster-level inferences, adopting a cluster-mass p-value corrected for false discovery < 0.05 for cluster threshold, and a p-uncorrected < 0.01 for the voxel threshold.

Results: Twenty asymptomatic patients were enrolled. The mean MMSE score resulted improved following CEA procedure (p-value = 0.001). The ALFF analysis identified a single cluster of 6260 voxels of increased regional neural activity following CEA, and no cluster of reduced activity. The majority of voxels covered the right precentral gyrus, the right middle frontal gyrus, and the anterior division of the cingulate gyrus.

Conclusion: Mid-term cognitive improvements observed after CEA are associated to increased regional neural activity of several cerebral regions.
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http://dx.doi.org/10.1007/s00234-021-02815-7DOI Listing
September 2021

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review.

Comput Biol Med 2021 10 27;137:104803. Epub 2021 Aug 27.

Stroke Diagnosis and Monitoring Division, AtheroPoint™, Roseville, CA, USA. Electronic address:

Background: Artificial intelligence (AI) has served humanity in many applications since its inception. Currently, it dominates the imaging field-in particular, image classification. The task of image classification became much easier with machine learning (ML) and subsequently got automated and more accurate by using deep learning (DL). By default, DL consists of a single architecture and is termed solo deep learning (SDL). When two or more DL architectures are fused, the result is termed a hybrid deep learning (HDL) model. The use of HDL models is becoming popular in several applications, but no review of these uses has been designed thus far. Therefore, this study provides the first narrative HDL review by considering all facets of image classification using AI.

Approach: Our review employs a PRISMA search strategy using Google Scholar, PubMed, IEEE, and Elsevier Science Direct, through which 127 relevant HDL studies were considered. Based on the computer vision evolution, HDLs were subsequently classified into three categories (spatial, temporal, and spatial-temporal). Each study was then analyzed based on several attributes, including continent, publisher, hybridization of two DL or ML, architecture layout, application type, data set type, dataset size, feature extraction methodology, connecting classifier, performance evaluation metrics, and risk-of-bias.

Conclusion: The HDL models have shown stable and superior performance by taking the best aspects of two or more solo DL or fusion of DL with ML models. Our findings indicate that HDL is being applied aggressively to several medical and non-medical applications. Furthermore, risk-of-bias is highly debatable for DL and HDL models.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104803DOI Listing
October 2021

COVLIAS 1.0: Lung Segmentation in COVID-19 Computed Tomography Scans Using Hybrid Deep Learning Artificial Intelligence Models.

Diagnostics (Basel) 2021 Aug 4;11(8). Epub 2021 Aug 4.

Vascular Screening and Diagnostic Centre, University of Nicosia Medical School, Nicosia 2408, Cyprus.

Background: COVID-19 lung segmentation using Computed Tomography (CT) scans is important for the diagnosis of lung severity. The process of automated lung segmentation is challenging due to (a) CT radiation dosage and (b) ground-glass opacities caused by COVID-19. The lung segmentation methodologies proposed in 2020 were semi- or automated but not reliable, accurate, and user-friendly. The proposed study presents a COVID Lung Image Analysis System (COVLIAS 1.0, AtheroPoint™, Roseville, CA, USA) consisting of hybrid deep learning (HDL) models for lung segmentation.

Methodology: The COVLIAS 1.0 consists of three methods based on solo deep learning (SDL) or hybrid deep learning (HDL). SegNet is proposed in the SDL category while VGG-SegNet and ResNet-SegNet are designed under the HDL paradigm. The three proposed AI approaches were benchmarked against the National Institute of Health (NIH)-based conventional segmentation model using fuzzy-connectedness. A cross-validation protocol with a 40:60 ratio between training and testing was designed, with 10% validation data. The ground truth (GT) was manually traced by a radiologist trained personnel. For performance evaluation, nine different criteria were selected to perform the evaluation of SDL or HDL lung segmentation regions and lungs long axis against GT.

Results: Using the database of 5000 chest CT images (from 72 patients), COVLIAS 1.0 yielded AUC of , and (-value < 0.001), respectively within 5% range of GT area, for SegNet, VGG-SegNet, ResNet-SegNet, and NIH. The mean Figure of Merit using four models (left and right lung) was above . On benchmarking against the National Institute of Health (NIH) segmentation method, the proposed model demonstrated a and improvement in ResNet-SegNet, and improvement in VGG-SegNet for lung area, and lung long axis, respectively. The PE statistics performance was in the following order: . The HDL runs in <1 s on test data per image.

Conclusions: The COVLIAS 1.0 system can be applied in real-time for radiology-based clinical settings.
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http://dx.doi.org/10.3390/diagnostics11081405DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8392426PMC
August 2021

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis.

Diagnostics (Basel) 2021 Jul 21;11(8). Epub 2021 Jul 21.

Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy.

(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients' care in MS.
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http://dx.doi.org/10.3390/diagnostics11081310DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394408PMC
July 2021

Combined Microwave Ablation and Osteosynthesis for Long Bone Metastases.

Medicina (Kaunas) 2021 Aug 16;57(8). Epub 2021 Aug 16.

Department of Radiology, Policlinico Universitario, 09121 Cagliari, Italy.

The purpose of this study was to evaluate the feasibility, safety and efficacy of microwave ablation (MWA) in combination with open surgery nail positioning for the treatment of fractures or impending fractures of long bone metastases. Eleven patients (four men, seven women) with painful bone metastases of the humerus, femur or tibia with non-displaced fractures (one case) or impending fractures (10 cases) underwent open MWA in combination with osteosynthesis by locked nail positioning. Pain intensity was measured using a VAS score before and after treatment. CT or MRI were acquired at one month before and 1, 3, 6, 12 and 18 months after treatment. All procedures were successfully completed without major complications. The level of pain was significantly reduced one month after treatment. For the patients with humerus metastases, the complete recovery of arm use took 8 weeks, while for the patients with femoral metastases the complete recovery of walking capacity took 11 weeks. The VAS score ranged from 7 (4-9) before treatment to 1.5 (0-2.5) after treatment. During a mid-term follow-up of 18 months (range 4-29 months), none of the patients showed tumor relapse or new fractures in the treated site. Two patients died due to tumor disease progression. Results of this preliminary study suggest that combined MWA and surgical osteosynthesis with locked nails is a safe and effective treatment for pathological fractures or malignant impending fractures of long bone metastases of the humerus, femur and tibia. Further analyses with larger cohorts are warranted to confirm these findings.
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http://dx.doi.org/10.3390/medicina57080825DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398614PMC
August 2021

COVID-19 Disease, Women's Predominant Non-Heparin Vaccine-Induced Thrombotic Thrombocytopenia and Kounis Syndrome: A Passepartout Cytokine Storm Interplay.

Biomedicines 2021 Aug 5;9(8). Epub 2021 Aug 5.

Vaccines and Biotechnology, Scottsville, VA 24590, USA.

Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitute one of the deadliest pandemics in modern history demonstrating cardiovascular, gastrointestinal, hematologic, mucocutaneous, respiratory, neurological, renal and testicular manifestations and further complications. COVID-19-induced excessive immune response accompanied with uncontrolled release of cytokines culminating in cytokine storm seem to be the common pathogenetic mechanism of these complications. The aim of this narrative review is to elucidate the relation between anaphylaxis associated with profound hypotension or hypoxemia with pro-inflammatory cytokine release. COVID-19 relation with Kounis syndrome and post-COVID-19 vaccination correlation with heparin-induced thrombocytopenia with thrombosis (HITT), especially serious cerebral venous sinus thrombosis, were also reviewed.

Methods: A current literature search in PubMed, Embase and Google databases was performed to reveal the pathophysiology, prevalence, clinical manifestation, correlation and treatment of COVID-19, anaphylaxis with profuse hypotension, Kounis acute coronary syndrome and thrombotic events post vaccination.

Results: The same key immunological pathophysiology mechanisms and cells seem to underlie COVID-19 cardiovascular complications and the anaphylaxis-associated Kounis syndrome. The myocardial injury in patients with COVID-19 has been attributed to coronary spasm, plaque rupture and microthrombi formation, hypoxic injury or cytokine storm disposing the same pathophysiology with the three clinical variants of Kounis syndrome. COVID-19-interrelated vaccine excipients as polysorbate, polyethelene glycol (PEG) and trometamol constitute potential allergenic substances.

Conclusion: Better acknowledgement of the pathophysiological mechanisms, clinical similarities, multiorgan complications of COVID-19 or other viral infections as dengue and human immunodeficiency viruses along with the action of inflammatory cells inducing the Kounis syndrome could identify better immunological approaches for prevention, treatment of the COVID-19 pandemic as well as post-COVID-19 vaccine adverse reactions.
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http://dx.doi.org/10.3390/biomedicines9080959DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391920PMC
August 2021

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.

Ann Transl Med 2021 Jul;9(14):1206

Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.

Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most.
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http://dx.doi.org/10.21037/atm-20-7676DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8350643PMC
July 2021

Correlation between computed tomography angiography and histology of carotid artery atherosclerosis: Can semi-automated imaging software predict a plaque's composition?

Interv Neuroradiol 2021 Aug 16:15910199211031093. Epub 2021 Aug 16.

Department of Cardiovascular Medicine, 6915Mayo Clinic, USA.

Background: Using computed tomography angiography to differentiate between components of carotid atherosclerotic lesions remains largely elusive. This study sought to validate a semi-automated software for computed tomography angiography plaque analysis using histologic comparisons.

Materials And Methods: A retrospective review was performed of consecutive patients that underwent a carotid endarterectomy, with pre-procedural computed tomography angiography imaging of the cervical arterial vasculature available for review. Images were evaluated using a commercially-available software package, which produced segmented analyses of intraplaque components (e.g. intraplaque hemorrhage, lipid-rich necrotic core, and calcifications). On imaging, each component was assessed in terms of its (1) presence or absence, and (2) both volume and proportion of the total plaque volume (if present). On histological evaluation of carotid endarterectomy specimens, each component was evaluated as an estimated proportion of total plaque volume.

Results: Of 80 included patients, 30 (37.5%) were female. The average age was 69.7 years (SD = 9.1). Based on imaging, intraplaque hemorrhage was the smallest contributor to plaque composition (1.2% of volumes on average). Statistically significant linear associations were noted between the proportion of intraplaque hemorrhage, lipid-rich necrotic core, and calcifications on histology and the volume of each component on imaging ( values ranged from 0.0008 to 0.01). Area under curve were poor for intraplaque hemorrhage and lipid-rich necrotic core (0.59 and 0.61, respectively) and acceptable for calcifications (0.73).

Conclusion: Semi-automated analyses of computed tomography angiography have limited diagnostic accuracy in the detection of intraplaque hemorrhage and lipid-rich necrotic core in carotid artery plaques. However, volumetric imaging measurements of different components corresponded with histologic analysis.
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http://dx.doi.org/10.1177/15910199211031093DOI Listing
August 2021

Obstructive and Nonobstructive Hypertrophic Cardiomyopathy: Differences in Global and Segmental Myocardial Strain by Cardiac Magnetic Resonance Feature Tracking.

J Thorac Imaging 2021 Aug 12. Epub 2021 Aug 12.

Department of Radiology, University of Cagliari Department of Radiology, Azienda Ospedaliera Brotzu, Cagliari Radiology Department, Miulli Hospital, Acquaviva delle Fonti Department of Radiology, IRCCS San Raffaele Scientific Institute Centro Cardiologico Monzino, IRCCS, Milan, Italy Department of Cardiology, Mater Misericordiae University Hospital, Dublin, Ireland Point-of-Care Devices, Global Biomedical Technologies, Roseville, CA.

Purpose: To evaluate any significant differences in myocardial strain between hypertrophic obstructive cardiomyopathy (HOCM) and nonobstructive ones (HNCM), as assessed by cardiac magnetic resonance feature tracking (CMR-FT).

Materials And Methods: A total of 17 patients (mean age: 54±14 y) with echocardiographic diagnosis of HOCM (left ventricular outflow tract obstruction peak gradient ≥30 mm Hg), 19 patients (mean age: 49±16 y) with HNCM (peak gradient <30 mm Hg), and 18 age-matched and gender-matched healthy controls (mean age: 42±14 y). All patients underwent cardiac MRI with SSFP-cine to assess left ventricular global and segmental strain analysis by CMR-FT. Late gadolinium enhancement (LGE) sequences were used for semiautomatic quantification of LGE volume, mass, and percentage.

Results: The magnitude of global radial, circumferential, and longitudinal strain as well as strain rate were significantly lower in all patients in comparison to controls (P<0.001), except for radial and circumferential strain between HOCM and controls (P=0.270; P=0.154). The latter strain parameters were significantly higher in HOCM than HNCM (radial strain: 31.67±7.55 vs. 21.26±7.10, P<0.001; circumferential strain: -17.94±2.78 vs. -13.46±3.42, P<0.001). Radial and circumferential strain and circumferential diastolic strain rate were higher in mid-anterior (P<0.001), mid-anteroseptal (P<0.001), and all apical segments (P<0.005) between the 2 groups of patients. Moreover, longitudinal strain was higher only in apical segments in HOCM (P<0.02).

Conclusions: HOCM patients showed higher left ventricular apical, mid-anterior, and mid-anteroseptal strain parameters compared with HNCM. These differences were independent of corresponding segmental thickness and LGE amount.
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http://dx.doi.org/10.1097/RTI.0000000000000612DOI Listing
August 2021

Systematic Review of Artificial Intelligence in Acute Respiratory Distress Syndrome for COVID-19 Lung Patients: A Biomedical Imaging Perspective.

IEEE J Biomed Health Inform 2021 Aug 11;PP. Epub 2021 Aug 11.

SARS-CoV-2 has infected over ~165 million people worldwide causing Acute Respiratory Distress Syndrome (ARDS) and has killed ~3.4 million people. Artificial Intelligence (AI) has shown to benefit in the biomedical image such as X-ray/Computed Tomography in diagnosis of ARDS, but there are limited AI-based systematic reviews (aiSR). The purpose of this study is to understand the Risk-of-Bias (RoB) in a non-randomized AI trial for handling ARDS using novel AtheroPoint-AI-Bias (AP(ai)Bias). Our hypothesis for acceptance of a study to be in low RoB must have a mean score of 80% in a study. Using the PRISMA model, 42 best AI studies were analyzed to understand the RoB. Using the AP(ai)Bias paradigm, the top 19 studies were then chosen using the raw-cutoff of 1.9. This was obtained using the intersection of the cumulative plot of mean score vs. study and score distribution. Finally, these studies were benchmarked against ROBINS-I and PROBAST paradigm. Our observation showed that AP(ai)Bias, ROBINS-I, and PROBAST had only 32%, 16%, and 26% studies, respectively in low-moderate RoB (cutoff>2.5), however none of them met the RoB hypothesis. Further, the aiSR analysis recommends six primary and six secondary recommendations for the non-randomized AI for ARDS. The primary recommendations for improvement in AI-based ARDS design inclusive of (i) comorbidity, (ii) inter-and intra-observer variability studies, (iii) large data size, (iv) clinical validation, (v) granularity of COVID-19 risk, and (vi) cross-modality scientific validation. The AI is an important component for diagnosis of ARDS and the recommendations must be followed to lower the RoB.
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http://dx.doi.org/10.1109/JBHI.2021.3103839DOI Listing
August 2021

Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound.

Comput Biol Med 2021 09 2;136:104721. Epub 2021 Aug 2.

Stroke Diagnostic and Monitoring Division, AtheroPoint™, Roseville, CA, USA. Electronic address:

The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an essential part of stroke risk stratification. Previous segmented methods used AtheroEdge™ 2.0 (AtheroPoint™, Roseville, CA) for the common carotid artery (CCA). This study focuses on automated plaque segmentation in the internal carotid artery (ICA) using solo deep learning (SDL) and hybrid deep learning (HDL) models. The methodology consists of a novel design of 10 types of SDL/HDL models (AtheroEdge™ 3.0 systems (AtheroPoint™, Roseville, CA) with a depth of four layers each. Five of the models use cross-entropy (CE)-loss, and the other five models use Dice similarity coefficient (DSC)-loss functions derived from UNet, UNet+, SegNet, SegNet-UNet, and SegNet-UNet+. The K10 protocol (Train:Test:90%:10%) was applied for all 10 models for training and predicting (segmenting) the plaque region, which was then quantified to compute the plaque area in mm. Further, the data augmentation effect was analyzed. The database consisted of 970 ICA B-mode US scans taken from 99 moderate to high-risk patients. Using the difference area threshold of 10 mm between ground truth (GT) and artificial intelligence (AI), the area under the curve (AUC) values were 0.91, 0.911, 0.908, 0.905, and 0.898, all with a p-value of <0.001 (for CE-loss models) and 0.883, 0.889, 0.905, 0.889, and 0.907, all with a p-value of <0.001 (for DSC-loss models). The correlations between the AI-based plaque area and GT plaque area were 0.98, 0.96, 0.97, 0.98, and 0.97, all with a p-value of <0.001 (for CE-loss models) and 0.98, 0.98, 0.97, 0.98, and 0.98 (for DSC-loss models). Overall, the online system performs plaque segmentation in less than 1 s. We validate our hypothesis that HDL and SDL models demonstrate comparable performance. SegNet-UNet was the best-performing hybrid architecture.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104721DOI Listing
September 2021

Global Fractional Anisotropy: Effect on Resting-state Neural Activity and Brain Networking in Healthy Participants.

Neuroscience 2021 09 6;472:103-115. Epub 2021 Aug 6.

Department of Radiology, AOU Cagliari, University of Cagliari, Italy.

The global fractional anisotropy (gFA) is a structural marker of white matter myelination and integrity. Previous studies already evidenced that aging-related reduced integrity of specific white matter tracts is associated with decreased functional connectivity in several hubs. However, the correlations between gFA and functional brain connectivity remain unknown. In this cross-sectional study, we analyzed structural and functional MR datasets of 79 healthy participants from the Leipzig Study for Mind-Body-Emotion Interactions. DTI model-based method was used to quantify gFA values. We tested associations between gFA, age, and gender. The fractional amplitude of low-frequency fluctuations (fALFF) and ROI-to-ROI connectivity were analyzed in a regression model for evaluating the effects of gFA on brain activity and networking, respectively. A negative correlation was found between gFA and age (ρ = -0.343; p = 0.002). No statistically significant correlation as found between gFA and gender (p = 0.229). Higher values of gFA were associated with increased brain regional activity, including areas of the default mode network. There was a higher degree of correlation between some regions, particularly those that conform to the limbic system. Our study demonstrates that gFA influences regional neural activity and brain networking on resting, particularly the limbic system.
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http://dx.doi.org/10.1016/j.neuroscience.2021.07.021DOI Listing
September 2021

The association between white matter hyperintensities, cognition and regional neural activity in healthy subjects.

Eur J Neurosci 2021 08 4;54(4):5427-5443. Epub 2021 Aug 4.

Department of Radiology, AOU Cagliari, University of Cagliari, Cagliari, Italy.

White matter hyperintensities (WMH) are common findings that can be found in physiological ageing. Several studies suggest that the disruption of white matter tracts included in WMH could induce abnormal functioning of the respective linked cortical structures, with consequent repercussion on the cerebral functions, included the cognitive sphere. In this cross-sectional research, we analysed the effects of the total WMH burden (tWMHb) on resting-state functional magnetic resonance imaging (rs-fMRI) and cognition. Functional and structural MR data, as well as the scores of the trail making test subtests A (TMT-A) and B (TMT-B) of 75 healthy patients, were extracted from the public available Leipzig Study for Mind-Body-Emotion Interactions dataset. tWMHb was extracted from structural data. Spearman's correlation analyses were made for investigating correlations between WMHb and the scores of the cognitive tests. The fractional amplitude of low-frequency fluctuations (fALFF) method was applied for analysing the rs-fMRI data, adopting a multiple regression model for studying the effects of tWMHb on brain activity. Three different subanalyses were conducted using different statistical methods. We observed statistically significant correlations between WMHb and the scores of the cognitive tests. The fALFF analysis revealed that tWMHb is associated with the reduction of regional neural activity of several brain areas (in particular the prefrontal cortex, precuneus and cerebellar crus I/II). We conclude that our findings clarify better the relationships between WMH and cognitive impairment, evidencing that tWMHb is associated with impairments of the neurocognitive function in healthy subjects by inducing a diffuse reduction of the neural activity.
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http://dx.doi.org/10.1111/ejn.15403DOI Listing
August 2021

Management of patients with asymptomatic carotid stenosis may need to be individualized: a multidisciplinary call for action. Republication of J Stroke 2021;23:202-212

Int Angiol 2021 07 27. Epub 2021 Jul 27.

Department of Neurology & Stroke Program, University of Maryland School of Medicine, Baltimore, MD, USA.

The optimal management of patients with asymptomatic carotid stenosis (ACS) is the subject of extensive debate. According to the 2017 European Society for Vascular Surgery guidelines, carotid endarterectomy should (Class IIa; Level of Evidence: B) or carotid artery stenting may be considered (Class IIb; Level of Evidence: B) in the presence of one or more clinical/imaging characteristics that may be associated with an increased risk of late ipsilateral stroke (e.g. silent embolic infarcts on brain computed tomography/magnetic resonance imaging, progression in the severity of ACS, a history of contralateral transient ischemic attack/stroke, microemboli detection on transcranial Doppler, etc.), provided documented perioperative stroke/death rates are <3% and the patient's life expectancy is >5 years. Besides these clinical/imaging characteristics, there are additional individual, ethnic/racial or social factors that should probably be evaluated in the decision process regarding the optimal management of these patients, such as individual patient needs/patient choice, patient compliance with best medical treatment, patient sex, culture, race/ethnicity, age and comorbidities, as well as improvements in imaging/operative techniques/outcomes. The present multispecialty position paper will present the rationale why the management of patients with ACS may need to be individualized.
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http://dx.doi.org/10.23736/S0392-9590.21.04751-9DOI Listing
July 2021

Emerging role of artificial intelligence in stroke imaging.

Expert Rev Neurother 2021 Jul 20;21(7):745-754. Epub 2021 Jul 20.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), Di Cagliari - Polo Di Monserrato, S.s. 554 Monserrato (Cagliari), Italy.

: The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clinical practice and accelerate the mining of vital data that could expand recognition of patients with stroke, forecast of treatment responses and patient outcomes.: In this review, the authors provide an up-to-date review of AI in stroke, analyzing the latest papers on this subject. These have been divided in two main groups: stroke diagnosis and outcome prediction.: The highest value of AI is its capability to merge, select and condense a large amount of clinical and imaging features of a single patient and to associate these with fitted models that have gone through robust assessment and optimization with large cohorts of data to support clinical decision making.
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http://dx.doi.org/10.1080/14737175.2021.1951234DOI Listing
July 2021

Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia.

Clin Imaging 2021 Jul 1;80:58-66. Epub 2021 Jul 1.

Azienda Ospedaliera Universitaria di Cagliari, Cagliari, Italy.

Purpose: Comparison of deep learning algorithm, radiomics and subjective assessment of chest CT for predicting outcome (death or recovery) and intensive care unit (ICU) admission in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Methods: The multicenter, ethical committee-approved, retrospective study included non-contrast-enhanced chest CT of 221 SARS-CoV-2 positive patients from Italy (n = 196 patients; mean age 64 ± 16 years) and Denmark (n = 25; mean age 69 ± 13 years). A thoracic radiologist graded presence, type and extent of pulmonary opacities and severity of motion artifacts in each lung lobe on all chest CTs. Thin-section CT images were processed with CT Pneumonia Analysis Prototype (Siemens Healthineers) which yielded segmentation masks from a deep learning (DL) algorithm to derive features of lung abnormalities such as opacity scores, mean HU, as well as volume and percentage of all-attenuation and high-attenuation (opacities >-200 HU) opacities. Separately, whole lung radiomics were obtained for all CT exams. Analysis of variance and multiple logistic regression were performed for data analysis.

Results: Moderate to severe respiratory motion artifacts affected nearly one-quarter of chest CTs in patients. Subjective severity assessment, DL-based features and radiomics predicted patient outcome (AUC 0.76 vs AUC 0.88 vs AUC 0.83) and need for ICU admission (AUC 0.77 vs AUC 0.0.80 vs 0.82). Excluding chest CT with motion artifacts, the performance of DL-based and radiomics features improve for predicting ICU admission.

Conclusion: DL-based and radiomics features of pulmonary opacities from chest CT were superior to subjective assessment for differentiating patients with favorable and adverse outcomes.
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http://dx.doi.org/10.1016/j.clinimag.2021.06.036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247202PMC
July 2021

Anderson-fabry disease: role of traditional and new cardiac MRI techniques.

Br J Radiol 2021 Aug 8;94(1124):20210020. Epub 2021 Jul 8.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), Cagliari, Italy.

Anderson-Fabry (FD) disease is a rare X-linked disorder caused by different mutations in the Galactosidase α (GLA) gene, which leads to α-galactosidase A enzyme deficiency and the storage of glycosphingolipids in different kinds of organs, included the heart. This results in myocardial inflammation and left ventricular hypertrophy (LVH) and fibrosis. Echocardiography and cardiac magnetic resonance (C-MRI), in particular with new techniques, such as mapping analysis, late gadolinium enhancement (LGE) assessment and strain imaging, are important tools that allow a correct diagnosis, discriminating FD from other hypertrophic heart conditions. C-MRI is able to detect tissue alterations in the early stages of the disease, when an appropriate treatment could be more effective, and it has a fundamental role in monitoring therapy.
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http://dx.doi.org/10.1259/bjr.20210020DOI Listing
August 2021

A deep look into radiomics.

Radiol Med 2021 Oct 2;126(10):1296-1311. Epub 2021 Jul 2.

Academic Radiology, Department of Translational Research, University of Pisa, Via Roma 67, 56126, Pisa, Italy.

Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into radiomics, from the basis, deeply discussed from a technical point of view, through the main applications, to the challenges that have to be addressed to translate this process in clinical practice. A detailed description of the main techniques used in the various steps of radiomics workflow, which includes image acquisition, reconstruction, pre-processing, segmentation, features extraction and analysis, is here proposed, as well as an overview of the main promising results achieved in various applications, focusing on the limitations and possible solutions for clinical implementation. Only an in-depth and comprehensive description of current methods and applications can suggest the potential power of radiomics in fostering precision medicine and thus the care of patients, especially in cancer detection, diagnosis, prognosis and treatment evaluation.
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http://dx.doi.org/10.1007/s11547-021-01389-xDOI Listing
October 2021

Identifying the Vulnerable Carotid Atherosclerotic Plaque in Patients With Asymptomatic Carotid Stenosis.

Angiology 2021 Jul 2:33197211028416. Epub 2021 Jul 2.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari, Cagliari, Italy.

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http://dx.doi.org/10.1177/00033197211028416DOI Listing
July 2021

Observational study on healthcare workers protection in the angiographic suite during the SARS-CoV-2 pandemic: before and during vax era.

J Public Health Res 2021 Jun 16. Epub 2021 Jun 16.

Azienda Ospedaliera Ospedale Maggiore della Carità di Novara, Novara.

Background: Since the first case of Coronavirus Disease 2019 (COVID-19) in Italy, all the hospital facilities had to reform their daily activities. Amidst them, the Interventional Radiology Department in the "Azienda Ospedaliera Universitaria" of Novara (Italy) had to create a dedicated protocol for the patent's management during the pandemic.

Design And Methods: The time interval between February 2020 and March 2021 was divided into three different periods and we reported the evolution of our safety protocol, the changes in our daily activities and the rates of Sars-CoV-2 infection among the healthcare workers (HCW) of the Angiographic Suite. Personnel who had positive partners/family members or who had established close contacts of another nature outside the workplace were excluded from the study, in order to reduce any bias.

Results: A total of 35 HCWs served in 355 patient procedures on Sars-CoV-2 positive patients from February 2020 to March 2021. During the year there was a reduction in the morbidity rate first from 7.9% to 1.4% and then currently reaching 0%.

Conclusions: Dedicated routes, elevators, establishing Filter Areas and a clear demarcation between clean and contaminated areas, Dressing and undressing procedures, Cleaning procedures and the obligation to always wear a surgical mask during the working shift are essential to prevent in-hospital infection. The vaccines' arrival seems to further reduce the risk for healthcare workers, but it is still necessary to take docile precautions in view of the new mutations of the virus.
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http://dx.doi.org/10.4081/jphr.2021.2265DOI Listing
June 2021

Volume of White Matter Hyperintensities, and Cerebral Micro-Bleeds.

J Stroke Cerebrovasc Dis 2021 Aug 6;30(8):105905. Epub 2021 Jun 6.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato, Cagliari 09045, Italy. Electronic address:

Purpose: In the past years the significance of white matter hyperintensities (WMH) has gained raising attention because it is considered a marker of severity of different pathologies. Another condition that in the last years has been assessed in the neuroradiology field is cerebral microbleeds (CMB). The purpose of this work was to evaluate the association between the volume of WMH and the presence and characteristics of CMB.

Material And Methods: Sixty-five consecutive (males 45; median age 70) subjects were retrospectively analyzed with a 1.5 Tesla scanner. WMH volume was quantified with a semi-automated procedure considering the FLAIR MR sequences whereas the CMB were studied with the SWI technique and CMBs were classified as absent (grade 1), mild (grade 2; total number of CMBs: 1-2), moderate (grade 3; total number of CMBs: 3-10), and severe (grade 4; total number of CMBs: >10). Moreover, overall number of CMBs and the maximum diameter were registered.

Results: Prevalence of CMBs was 30.76% whereas WMH 81.5%. Mann-Whitney test showed a statistically significant difference in WMH volume between subjects with and without CMBs (p < 0.001). Pearson analysis showed significant correlation between CMB grade, number and maximum diameter and WMH. The better ROC area under the curve (Az) was obtained by the hemisphere volume with a 0.828 (95% CI from 0.752 to 0,888; SD = 0.0427; p value = 0.001). The only parameters that showed a statistically significant association in the logistic regression analysis were Hemisphere volume of WMH (p = 0.001) and Cholesterol LDL (p = 0.0292).

Conclusion: In conclusion, the results of this study suggest the presence of a significant correlation between CMBs and volume of WMH. No differences were found between the different vascular territories.
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http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2021.105905DOI Listing
August 2021

Management of Patients with Asymptomatic Carotid Stenosis May Need to Be Individualized: A Multidisciplinary Call for Action.

J Stroke 2021 May 31;23(2):202-212. Epub 2021 May 31.

Department of Neurology & Stroke Program, University of Maryland School of Medicine, Baltimore, MD, USA.

The optimal management of patients with asymptomatic carotid stenosis (ACS) is the subject of extensive debate. According to the 2017 European Society for Vascular Surgery guidelines, carotid endarterectomy should (Class IIa; Level of Evidence: B) or carotid artery stenting may be considered (Class IIb; Level of Evidence: B) in the presence of one or more clinical/imaging characteristics that may be associated with an increased risk of late ipsilateral stroke (e.g., silent embolic infarcts on brain computed tomography/magnetic resonance imaging, progression in the severity of ACS, a history of contralateral transient ischemic attack/stroke, microemboli detection on transcranial Doppler, etc.), provided documented perioperative stroke/death rates are <3% and the patient's life expectancy is >5 years. Besides these clinical/imaging characteristics, there are additional individual, ethnic/racial or social factors that should probably be evaluated in the decision process regarding the optimal management of these patients, such as individual patient needs/patient choice, patient compliance with best medical treatment, patient sex, culture, race/ethnicity, age and comorbidities, as well as improvements in imaging/operative techniques/outcomes. The present multispecialty position paper will present the rationale why the management of patients with ACS may need to be individualized.
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http://dx.doi.org/10.5853/jos.2020.04273DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189852PMC
May 2021

A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework.

J Digit Imaging 2021 06 2;34(3):581-604. Epub 2021 Jun 2.

Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, 95661, USA.

Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide. Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial infarction and stroke. The two primary image-based phenotypes used for monitoring the atherosclerosis burden is carotid intima-media thickness (cIMT) and plaque area (PA). Earlier segmentation and measurement methods were based on ad hoc conventional and semi-automated digital imaging solutions, which are unreliable, tedious, slow, and not robust. This study reviews the modern and automated methods such as artificial intelligence (AI)-based. Machine learning (ML) and deep learning (DL) can provide automated techniques in the detection and measurement of cIMT and PA from carotid vascular images. Both ML and DL techniques are examples of supervised learning, i.e., learn from "ground truth" images and transformation of test images that are not part of the training. This review summarizes (1) the evolution and impact of the fast-changing AI technology on cIMT/PA measurement, (2) the mathematical representations of ML/DL methods, and (3) segmentation approaches for cIMT/PA regions in carotid scans based for (a) region-of-interest detection and (b) lumen-intima and media-adventitia interface detection using ML/DL frameworks. AI-based methods for cIMT/PA segmentation have emerged for CVD/stroke risk monitoring and may expand to the recommended parameters for atherosclerosis assessment by carotid ultrasound.
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http://dx.doi.org/10.1007/s10278-021-00461-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329154PMC
June 2021

Role of artificial intelligence in cardiovascular risk prediction and outcomes: comparison of machine-learning and conventional statistical approaches for the analysis of carotid ultrasound features and intra-plaque neovascularization.

Int J Cardiovasc Imaging 2021 May 29. Epub 2021 May 29.

Stroke Diagnosis and Monitoring Division, AtheroPoint™, Roseville, CA, 95661, USA.

The aim of this study was to compare machine learning (ML) methods with conventional statistical methods to investigate the predictive ability of carotid plaque characteristics for assessing the risk of coronary artery disease (CAD) and cardiovascular (CV) events. Focused carotid B-mode ultrasound, contrast-enhanced ultrasound, and coronary angiography were performed on 459 participants. These participants were followed for 30 days. Plaque characteristics such as carotid intima-media thickness (cIMT), maximum plaque height (MPH), total plaque area (TPA), and intraplaque neovascularization (IPN) were measured at baseline. Two ML-based algorithms-random forest (RF) and random survival forest (RSF) were used for CAD and CV event prediction. The performance of these algorithms was compared against (i) univariate and multivariate analysis for CAD prediction using the area-under-the-curve (AUC) and (ii) Cox proportional hazard model for CV event prediction using the concordance index (c-index). There was a significant association between CAD and carotid plaque characteristics [cIMT (odds ratio (OR) = 1.49, p = 0.03), MPH (OR = 2.44, p < 0.0001), TPA (OR = 1.61, p < 0.0001), and IPN (OR = 2.78, p < 0.0001)]. IPN alone reported significant CV event prediction (hazard ratio = 1.24, p < 0.0001). CAD prediction using the RF algorithm reported an improvement in AUC by ~ 3% over the univariate analysis with IPN alone (0.97 vs. 0.94, p < 0.0001). Cardiovascular event prediction using RSF demonstrated an improvement in the c-index by ~ 17.8% over the Cox-based model (0.86 vs. 0.73). Carotid imaging phenotypes and IPN were associated with CAD and CV events. The ML-based system is superior to the conventional statistically-derived approaches for CAD prediction and survival analysis.
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http://dx.doi.org/10.1007/s10554-021-02294-0DOI Listing
May 2021

Metabolomic analysis of plasma from breast tumour patients. A pilot study.

J Public Health Res 2021 May 25. Epub 2021 May 25.

Department of Medical Sciences and Public Health, University of Cagliari.

Background: Patients at risk of breast cancer are submitted to mammography, resulting in a classification of the lesions following the Breast Imaging Reporting and Data System (BI-RADS®). Due to BI-RADS 3 classification problems and the great uncertainty of the possible evolution of this kind of tumours, the integration of mammographic imaging with other techniques and markers of pathology, as metabolic information, may be advisable.

Design And Methods: Our study aims to evaluate the possibility to quantify by gas chromatography-mass spectrometry (GC-MS) specific metabolites in the plasma of patients with mammograms classified from BI-RADS 3 to BI-RADS 5, to find similarities or differences in their metabolome. Samples from BI-RADS 3 to 5 patients were compared with samples from a healthy control group. This pilot project aimed at establishing the sensitivity of the metabolomic classification of blood samples of patients undergoing breast radiological analysis and to support a better classification of mammographic cases.

Results: Metabolomic analysis revealed a panel of metabolites more abundant in healthy controls, as 3-aminoisobutyric acid, cholesterol, cysteine, stearic, linoleic and palmitic fatty acids. The comparison between samples from BI-RADS 3 and BI-RADS 5 patients, revealed the importance of 4-hydroxyproline, found in higher amount in BI-RADS 3 subjects.

Conclusion: Although the low sample number did not allow the attainment of high validated statistical models, some interesting data were obtained, revealing the potential of metabolomics for an improvement in the classification of different mammographic lesions.
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http://dx.doi.org/10.4081/jphr.2021.2304DOI Listing
May 2021

Complications in COVID-19 patients: Characteristics of pulmonary embolism.

Clin Imaging 2021 Sep 18;77:244-249. Epub 2021 May 18.

Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato s.s. 554, Monserrato (Cagliari) 09045, Italy. Electronic address:

Objective: The purpose of this study is to evaluate chest CT imaging features, clinical characteristics, laboratory values of COVID-19 patients who underwent CTA for suspected pulmonary embolism. We also examined whether clinical, laboratory or radiological characteristics could be associated with a higher rate of PE.

Materials And Methods: This retrospective study included 84 consecutive patients with laboratory-confirmed SARS-CoV-2 who underwent CTA for suspected PE. The presence and localization of PE as well as the type and extent of pulmonary opacities on chest CT exams were examined and correlated with the information on comorbidities and laboratory values for all patients.

Results: Of the 84 patients, pulmonary embolism was discovered in 24 patients. We observed that 87% of PE was found to be in lung parenchyma affected by COVID-19 pneumonia. Compared with no-PE patients, PE patients showed an overall greater lung involvement by consolidation (p = 0.02) and GGO (p < 0.01) and a higher level of D-Dimer (p < 0,01). Moreover, the PE group showed a lower level of saturation (p = 0,01) and required more hospitalization (p < 0,01).

Conclusion: Our study showed a high incidence of PE in COVID-19 pneumonia. In 87% of patients, PE was found in lung parenchyma affected by COVID-19 pneumonia with a worse CT severity score and a greater number of lung lobar involvement compared with non-PE patients. CT severity, lower level of saturation, and a rise in D-dimer levels could be an indication for a CTPA.

Advances In Knowledge: Certain findings of non-contrast chest CT could be an indication for a CTPA.
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http://dx.doi.org/10.1016/j.clinimag.2021.05.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130594PMC
September 2021
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