@article{IBB_ID_54916, author={Petretta M, Megna R, Assante R, Zampella E, Nappi C, Gaudieri V, Mannarino T, Green R, Cantoni V, D, #xantonio A, Panico M, Acampa W, Cuocolo A}, title={External validation and update of the J-ACCESS model in an Italian cohort of patients undergoing stress myocardial perfusion imaging}, date={2023 Jan 4}, journal={J Nucl Cardiol (ISSN: 1071-3581linking)}, year={2023}, fullvolume={39}, volume={39}, pages={N/D--N/D}, url={}, abstract={BACKGROUND: Cardiovascular risk models are based on traditional risk factors and investigations such as imaging tests. External validation is important to determine reproducibility and generalizability of a prediction model. We performed an external validation of t the Japanese Assessment of Cardiac Events and Survival Study by Quantitative Gated SPECT (J-ACCESS) model, developed from a cohort of patients undergoing stress myocardial perfusion imaging. METHODS: We included 3623 patients with suspected or known coronary artery disease undergoing stress single-photon emission computer tomography (SPECT) myocardial perfusion imaging at our academic center between January 2001 and December 2019. RESULTS: In our study population, the J-ACCESS model underestimated the risk of major adverse cardiac events (cardiac death, nonfatal myocardial infarction, and severe heart failure requiring hospitalization) within three-year follow-up. The recalibrations and updated of the model slightly improved the initial performance: C-statistics increased from 0.664 to 0.666 and Brier score decreased from 0.075 to 0.073. Hosmer-Lemeshow test indicated a logistic regression fit only for the calibration slope (P = .45) and updated model (P = .22). In the update model, the intercept, diabetes, and severity of myocardial perfusion defects categorized coefficients were comparable with J-ACCESS. CONCLUSION: The external validation of the J-ACCESS model as well as recalibration models have a limited value for predicting of three-year major adverse cardiac events in our patients. The performance in predicting risk of the updated model resulted superimposable to the calibration slope model.}, keywords={Cad, Mpi, Spect, Diagnostic And Prognostic Application}, references={}, document_type={Journal Article}, affiliation={IRCCS Synlab SDN, Via Gianturco 113, 80142, Naples, Italy., Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. cuocolo@unina.it., }, ibbaffiliation={1}, } @article{IBB_ID_54915, author={Volpicelli F, Nappi C, Megna R, Volpe F, Ponsiglione A, Caiazzo E, Piscopo L, G, Mainolfi C, Vergara E, Imbriaco M, Klain M, Petretta M, Cuocolo A}, title={Qualification of Coronary Artery Atherosclerotic Burden and Muscle Mass: Comparison of Two Freely Available Software Programs}, date={2022}, journal={Eur J Nucl Med Mol Imaging}, year={2022}, fullvolume={24}, volume={24}, pages={S606--S606}, url={}, abstract={Sarcopenia and coronary calcification may have a relevant prognostic impact in oncological and nononcological patients. The use of freeware software is promising for quantitative evaluation of these parameters after whole-body positron emission tomography (PET)/computed tomography (CT) and might be useful for one-stop shop risk stratification without additional radiation ionizing burden and health care. In this study, we compared the assessment of CAC score and muscle mass in patients undergoing whole-body PET/CT by two semiautomatic freeware software, Horos and LIFEx for the evaluation of coronary artery calcium (CAC) score and muscle mass in patients undergoingwhole-body PET/CT.}, keywords={}, references={}, document_type={Abstract}, affiliation={1 Department of Advanced Biomedical Sciences, University of Naples “Federico II”, Naples, ITALY, 2 Institute of Biostructure and Bioimaging, National Council of Research, Naples, ITALY, 3 Department of Diagnostic Imaging, IRCCS Synlab SDN, Naples, ITALY.}, ibbaffiliation={1}, } @article{IBB_ID_54871, author={Nappi C, Megna R, Volpe F, Ponsiglione A, Caiazzo E, Piscopo L, Mainolfi CG, Vergara E, Imbriaco M, Klain M, Petretta M, Cuocolo A}, title={Quantification of Coronary Artery Atherosclerotic Burden and Muscle Mass: Exploratory Comparison of Two Freely Available Software Programs}, date={2022}, journal={Applied Sciences Mdpi}, year={2022}, fullvolume={6}, volume={6}, pages={N/D--N/D}, url={https://www.mdpi.com/2076-3417/12/11/5468}, abstract={Coronary artery calcification and sarcopenia may have a relevant prognostic impact in oncological and non-oncological patients. The use of freeware software is promising for quantitative evaluation of these parameters after whole-body positron emission tomography (PET)/computed tomography (CT) and might be useful for one-stop shop risk stratification without additional radiation ionizing burden and further charges to health care costs. In this study, we compared two semiautomatic freeware software tools (Horos Medical Image software and LIFEx) for the assessment of coronary artery calcium (CAC) score and muscle mass in 40 patients undergoing whole-body PET/CT. The muscle areas obtained by the two software programs were comparable, showing high correlation with Lin’s concordance coefficient (0.9997; 95% confidence intervals: 0.9995–0.9999) and very good agreement with Bland–Altman analysis (mean difference = 0.41 cm2, lower limit = -1.06 cm2, upper limit = 1.89) was also found. For CAC score, Lin’s concordance correlation coefficient was 0.9976 (95% confidence intervals: 0.9965–0.9984) and in a Bland–Altman analysis an increasing mean difference from 8 to 78 by the mean values (intercept = -0.050; slope = 0.054; p < 0.001) was observed, with a slight overestimation of Horos CAC score as compared to LIFEx, likely due to a different calculation method of the CAC score, with the ROI being equal for the two software programs. Our results demonstrated that off-line analysis performed with freeware software may allow a comprehensive evaluation of the oncological patient, making available the evaluation of parameters, such as muscle mass and calcium score, that may be relevant for the staging and prognostic stratification of these patients, beside standard data obtained by PET/CT imaging. For this purpose, the Horos and LIFEx software seem to be interchangeable.}, keywords={Calcium Score, Muscle Area, Sarcopenia, Positron Emission Tomography}, references={}, document_type={Journal Article}, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, 80131 Naples, Italy; Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; Department of Diagnostic Imaging, IRCCS Synlab SDN, 80131 Naples, Italy}, ibbaffiliation={1}, } @article{IBB_ID_54813, author={Megna R, Petretta M, Assante R, Zampella E, Nappi C, Gaudieri V, Mannarino T, D, #antonio A, Green R, Cantoni V, Arumugam P, Acampa W, Cuocolo A}, title={A Comparison among Different Machine Learning Pretest Approaches to Predict Stress-Induced Ischemia at PET/CT Myocardial Perfusion Imaging}, date={2021 Nov 27}, journal={Comput Math Methods Med (ISSN: 1748-670xlinking)}, year={2021}, fullvolume={58}, volume={58}, pages={3551756--3551756}, url={https://www.hindawi.com/journals/cmmm/2021/3551756/}, abstract={Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression to quantifying their relationship with the outcome; nevertheless, their predictive value is limited. In the present study, we aimed to investigate the value of different machine learning (ML) techniques for the evaluation of suspected CAD; having as gold standard, the presence of stress-induced ischemia by (82)Rb positron emission tomography/computed tomography (PET/CT) myocardial perfusion imaging (MPI) ML was chosen on their clinical use and on the fact that they are representative of different classes of algorithms, such as deterministic (Support vector machine and Naïve Bayes), adaptive (ADA and AdaBoost), and decision tree (Random Forest, rpart, and XGBoost). The study population included 2503 consecutive patients, who underwent MPI for suspected CAD. To testing ML performances, data were split randomly into two parts: training/test (80%) and validation (20%). For training/test, we applied a 5-fold cross-validation, repeated 2 times. With this subset, we performed the tuning of free parameters for each algorithm. For all metrics, the best performance in training/test was observed for AdaBoost. The Naïve Bayes ML resulted to be more efficient in validation approach. The logistic and rpart algorithms showed similar metric values for the training/test and validation approaches. These results are encouraging and indicate that the ML algorithms can improve the evaluation of pretest probability of stress-induced myocardial ischemia.}, keywords={}, references={}, document_type={Journal Article}, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy., IRCCS-SDN, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy., Department of Nuclear Medicine, Central Manchester Foundation Trust, Manchester, UK., }, ibbaffiliation={1}, } @article{IBB_ID_54781, author={Megna R, Petretta M, Assante R, Zampella E, Nappi C, Gaudieri V, Mannarino T, Green R, Cantoni V, Buongiorno P, D, #antonio A, Acampa W, Cuocolo A}, title={External validation of the CRAX2MACE model in an Italian cohort of patients with suspected coronary artery disease undergoing stress myocardial perfusion imaging}, date={2021 Nov 3}, journal={J Nucl Cardiol (ISSN: 1071-3581linking, 1532-6551electronic)}, year={2021}, fullvolume={61}, volume={61}, pages={N/D--N/D}, url={}, abstract={BACKGROUND: Prevention and development of diagnostic and therapeutic techniques reduced morbidity and mortality for coronary artery disease (CAD). In this context, the cardiovascular risk assessment for major adverse cardiac events (MACE) at 2-year (CRAX2MACE) model for prediction of 2-year major adverse cardiac events was developed. We performed an external validation of this model. METHODS: We included 1003 patients with suspected CAD undergoing stress-rest single-photon emission computed tomography myocardial perfusion imaging at our academic center between March 2015 and April 2019. RESULTS: Considering the occurrence of MACE (death from any cause, acute myocardial infarction, or late coronary revascularization), for the CRAX2MACE model the area under the receiver operating characteristic curve was 0.612 and the Brier score was 0.061. The Hosmer-Lemeshow test estimated a non-optimal fit (χ(2) 28, P < .001). Considering only hard events (cardiac death, acute myocardial infarction), the external validation of the CRAX2MACE model revealed a Brier score of 0.053 and an area under the receiver operating characteristic curve of 0.621. Hosmer-Lemeshow test was calculated by deciles and showed a poor fit (χ(2) 31, P < .001). CONCLUSION: CRAX2MACE model had a limited value for predicting 2-year major adverse cardiovascular events in an external validation cohort of patients with suspected CAD.}, keywords={Cad, Diagnostic And Prognostic Application, Mpi, Spect}, references={}, document_type={Journal Article}, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy., IRCCS-SDN, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. cuocolo@unina.it., }, ibbaffiliation={1}, } @article{IBB_ID_54774, author={Megna R}, title={Inferring a cause-effect relationship between lockdown restrictions and COVID-19 pandemic trend during the first wave}, date={2021 Nov}, journal={Health Policy (ISSN: 0168-8510, 0168-8510linking)}, year={2021}, fullvolume={84}, volume={84}, pages={1441--1447}, url={https://www.sciencedirect.com/science/article/pii/S0168851021002414}, abstract={The large number of infected persons due to the COVID-19 pandemic and the need of hospital care for many of them induced the majority of world governments to implement lockdown measures. We developed an analytical model to evaluate the trend of the SARS-CoV-2 pandemic. This model was applied to the first four months of the epidemiological data of the most affected countries in Europe and Russia, in order to evaluate the effect of the lockdown on the epidemic curves during the first wave. According to our model, the difference between the beginning of the lockdown and the slope change of the curve representing the daily distribution of counts was: Germany and Spain 6 days, France 7 days, the United Kingdom 9 days, Italy 21 days, and Russia 30 days. On the basis of these results, we infer a possible cause-effect relationship between the lockdown imposed in countries taken into account and the curve representing the daily distribution of new cases. Lockdown measures imposed by governments slowed the spread of the pandemic and reduced the number of infected persons. In economic terms, the damage was considerable, with entire production sectors in crisis. On the other hand, the efforts and innovations implemented to produce vaccines and effective treatments against the pandemic could be applied also in other fields of public health.}, keywords={Covid-19, Sars-Cov-2, Lockdown, Modelling, Health Policy, Public Health, Communicable Disease Control , Humans , Pandemics Prevention, Spain Epidemiology}, references={}, document_type={Research, Journal Article}, affiliation={National Research Council, Institute of Biostructure and Bioimaging, Via Tommaso de Amicis, Naples 80145, Italy. Electronic address: rosario.megna@cnr.it.}, ibbaffiliation={1}, } @article{IBB_ID_54561, author={Larobina M, Megna R, Solla R}, title={Comparison of three freeware software packages for (18)F-FDG PET texture feature calculation}, date={2021 Jul}, journal={Jpn J Radiol (ISSN: 1867-1071linking)}, year={2021}, fullvolume={70}, volume={70}, pages={710--719}, url={https://rdcu.be/cg24I}, abstract={PURPOSE: To compare texture feature estimates obtained from (18)F-FDG-PET images using three different software packages. METHODS: PET images from 15 patients with head and neck cancer were processed with three different freeware software: CGITA, LIFEx, and Metavol. For each lesion, 38 texture features were extracted from each software package. To evaluate the statistical agreement among the features across packages a non-parametric Kruskal-Wallis test was used. Differences in the features between each couple of software were assessed using a subsequent Dunn test. Correlation between texture features was evaluated via the Spearman coefficient. RESULTS: Twenty-three of 38 features showed a significant agreement across the three software (P < 0.05). The agreement was better between LIFEx vs. Metavol (36 of 38) and worse between CGITA and Metavol (24 of 38), and CGITA vs. LIFEx (23 of 38). All features resulted correlated (ρ >  = 0.70, P < 0.001) in comparing LIFEx vs. Metavol. Seven of 38 features were found not in agreement and slightly or not correlated (ρ < 0.70, P < 0.001) in comparing CGITA vs. LIFEx, and CGITA vs. Metavol. CONCLUSION: Some texture discrepancies across software packages exist. Our findings reinforce the need to continue the standardization process, and to succeed in building a reference dataset to be used for comparisons.}, keywords={Oncology, Positron Emission Tomography, Radiomics, Texture, Aged , Female , Fluorodeoxyglucose F18 , Head And Neck Neoplasms Diagnostic Imaging , Humans , Middle Aged , Phantoms, Positron Emission Tomography Computed Tomography Methods Standards , Radiographic Image Enhancement Methods Standards , Software Validation}, references={}, document_type={Journal Article, Comparative Study , Evaluation Study}, affiliation={Institute of Biostructures and Bioimaging, National Research Council (CNR), Via Tommaso de Amicis, 95, 80145, Napoli, Italy., Institute of Biostructures and Bioimaging, National Research Council (CNR), Via Tommaso de Amicis, 95, 80145, Napoli, Italy. rosario.megna@cnr.it., }, ibbaffiliation={1}, } @article{IBB_ID_54597, author={Ricciardi C, Cuocolo R, Megna R, Cesarelli M, Petretta M}, title={Machine learning analysis: general features, requirements and cardiovascular applications}, date={2021 May 4}, journal={Minerva Cardiol Angiol (ISSN: 2724-5772linking, 2724-5683linking)}, year={2021}, fullvolume={34}, volume={34}, pages={N/D--N/D}, url={}, abstract={Artificial intelligence represents the science which will probably change the future of medicine by solving actually challenging issues. In this special article, the general features of machine learning are discussed. First, a background explanation regarding the division of artificial intelligence, machine learning and deep learning is given and a focus on the structure of machine learning subgroups is shown. The traditional process of a machine learning analysis is described, starting from the collection of data, across features engineering, modelling and till the validation and deployment phase. Due to the several applications of machine learning performed in literature in the last decades and the lack of some guidelines, the need of a standardization for reporting machine learning analysis results emerged. Some possible standards for reporting machine learning results are identified and discussed deeply; these are related to study population (number of subjects), repeatability of the analysis, validation, results, comparison with current practice. The way to the use of machine learning in clinical practice is open and the hope is that, with emerging technology and advanced digital and computational tools, available from hospitalization and subsequently after discharge, it will also be possible, with the help of increasingly powerful hardware, to build assistance strategies useful in clinical practice.}, keywords={}, references={}, document_type={Journal Article}, affiliation={Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy - carloricciardi.93@gmail.com. Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy. Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy. Department of Information Technology and Electrical Engineering, University of Naples Federico II, Naples, Italy. Bioengineering Unit, Institute of Care and Scientific Research Maugeri, Pavia, Italy. IRCCS SDN, Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54474, author={Nappi C, Megna R, Acampa W, Assante R, Zampella E, Gaudieri V, Mannarino T, Green R, Cantoni V, Petretta M, Cuocolo A}, title={Effects of the COVID-19 pandemic on myocardial perfusion imaging for ischemic heart disease}, date={2021 Feb}, journal={Eur J Nucl Med (ISSN: 1619-7070linking, 1619-7070print, 1619-7089electronic)}, year={2021}, fullvolume={65}, volume={65}, pages={421--427}, url={https://link.springer.com/article/10.1007%2Fs00259-020-04994-6}, abstract={PURPOSE: We assessed the effects of the COVID-19 pandemic on myocardial perfusion imaging (MPI) for ischemic heart disease during the lockdown imposed by the Italian Government. METHODS: We retrospectively reviewed the number and the findings of stress single-photon emission computed tomography (SPECT)-MPI performed between February and May 2020 during the COVID-19 pandemic at the University of Napoli Federico II. The number and the findings of stress SPECT-MPI studies acquired in the corresponding months of the years 2017, 2018, and 2019 were also evaluated for direct comparison. RESULTS: The number of stress SPECT-MPI studies performed during the COVID-19 pandemic (n = 123) was significantly lower (P < 0.0001) compared with the mean yearly number of procedures performed in the corresponding months of the years 2017, 2018, and 2019 (n = 413). Yet, the percentage of abnormal stress SPECT-MPI studies was similar (P = 0.65) during the pandemic (36%) compared with the mean percentage value of the corresponding period of the years 2017, 2018, and 2019 (34%). CONCLUSION: The number of stress SPECT-MPI studies was significantly reduced during the COVID-19 pandemic compared with the corresponding months of the previous 3 years. The lack of difference in the prevalence of abnormal SPECT-MPI studies between the two study periods strongly suggests that many patients with potentially abnormal imaging test have been missed during the pandemic.}, keywords={Covid-19, Ischemic Heart Disease, Sars-Cov-2, Spect-Mpi, Southern Italy, Aged, Covid-19 Epidemiology, Female, Humans, Middle Aged, Myocardial Ischemia Diagnostic Imaging, Myocardial Perfusion Imaging Statistics, Numerical Data, Quarantine Statistics, Tomography, Emission-Computed, Single-Photon Statistics}, references={}, document_type={Journal Article}, affiliation={Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy. National Council of Research, Institute of Biostructure and Bioimaging, Naples, Italy. Department of Translational Medical Sciences, University Federico II, Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54441, author={Ponsiglione A, Nappi C, Imbriaco M, Ascione R, Megna R, Petretta M, Cuocolo A}, title={Cardiac magnetic resonance imaging during the COVID-19 pandemic: A southern Italian single-center experience}, date={2021}, journal={Eur J Radiol Open (ISSN: 2352-0477electronic, 2352-0477linking)}, year={2021}, fullvolume={81}, volume={81}, pages={100319--100319}, url={https://www.sciencedirect.com/science/article/pii/S2352047720301088}, abstract={PURPOSE: We aimed to assess the impact of COVID-19 pandemic on cardiac magnetic resonance (CMR) imaging studies performed during the lockdown imposed by the Italian Government from March 2020 to May 2020. MATERIALS AND METHOD: We reviewed the number and the findings of CMR scans performed during the COVID-19 pandemic between March and May 2020 at University of Naples Federico II. The number and the findings of CMR studies acquired in the corresponding months of 2017, 2018 and 2019 were also assessed for direct comparison. RESULTS: A total of 117 CMR studies was considered, including the procedures performed during the pandemic (n = 18) and those performed in the corresponding months of the prior 3 years (n = 99). The number of CMR studies performed during the COVID-19 pandemic was significantly (P < .01) lower compared to the mean number (n = 33) of the procedures performed in the corresponding months of 2017-2019. The percentage of abnormal CMR studies was similar (P = 0.73) during the pandemic (67 %) compared to that found in the corresponding months of 2017-2019 (70 %) suggesting that many abnormal tests were missed due to the lockdown. CONCLUSION: The number of CMR studies was significantly reduced during the COVID-19 pandemic compared to the corresponding period of the previous three years. The lack of difference in the prevalence of abnormal CMR studies between the two study time intervals strongly suggests that many patients with potentially abnormal imaging test have been missed during the pandemic.}, keywords={Cmr, Cardiac Magnetic Resonance, Covid-19, Cardiac Magnetic Resonance Imaging, Lge, Late Gadolinium Enhancement, Sars-Cov-2, Stir, Short Tau Inversion Recovery, Southern Italy}, references={}, document_type={Journal Article}, affiliation={Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy Institute of Biostructure and Bioimaging, National Research Council of Italy, Via De Amicis 95, 80145, Naples, Italy Department of Translational Medical Sciences, University of Naples Federico II, Via Pansini 5, 80131, Naples, Italy}, ibbaffiliation={1}, } @article{IBB_ID_54132, author={Megna R, Zampella E, Assante R, Nappi C, Gaudieri V, Mannarino T, Cantoni V, Green R, Daniele S, Mainolfi CG, Acampa W, Petretta M, Cuocolo A}, title={Temporal trends of abnormal myocardial perfusion imaging in a cohort of Italian subjects: Relation with cardiovascular risk factors}, date={2020 Dec}, journal={J Nucl Cardiol (ISSN: 1071-3581linking, 1532-6551electronic)}, year={2020}, fullvolume={311}, volume={311}, pages={2167--2177}, url={}, abstract={BACKGROUND: The frequency of abnormal stress single-photon emission computed tomography myocardial perfusion imaging (MPS) has decreased over the past decades despite an increase in the prevalence of cardiovascular risk factors. This study evaluated the temporal trend of abnormal stress MPS and its relationship with risk factors in a cohort of Italian subjects. METHODS: We included all patients who underwent clinically indicated stress MPS at our academic center between January 2006 and December 2017. Patients were assessed for change in demographics, clinical symptoms, risk factors, and frequency of abnormal and ischemic MPS. RESULTS: A total of 8,886 stress MPS studies were performed (3,350 abnormal). Age, male gender, diabetes, smoking, and angina were independent predictors of abnormal MPS. There was a slight decline in the frequency of abnormal (from 39 to 36%, P < 0.05) and ischemic (from 25 to 22%, P < 0.01) MPS during the study period, while the percentage of patients with hypertension, hypercholesterolemia, smoking, and angina increased. The Cochran-Mantel-Haenszel test indicates that the likelihood of having an abnormal MPS did not change over time for age, diabetes, smoking, and a history of coronary artery disease (CAD), increased for hypertension and hypercholesterolemia and decreased for male compared to female gender. CONCLUSIONS: In our cohort of Italian subjects, there was a slight temporal decline in the frequency of abnormal and ischemic MPS despite an increase over time in the prevalence of many cardiac risk factors. These results strengthen the need to develop more effective strategies for appropriately referring patients to cardiac imaging procedures.}, keywords={Cad, Mpi, Spect, Diagnostic And Prognostic Application, }, references={}, document_type={Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy., Department of Translational Medical Sciences, University Federico II, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. cuocolo@unina.it., }, ibbaffiliation={1}, } @article{IBB_ID_54398, author={Megna R}, title={First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast}, date={2020 Oct 1}, journal={Glob Health Res Policy (ISSN: 2397-0642linking)}, year={2020}, fullvolume={257}, volume={257}, pages={43--43}, url={https://ghrp.biomedcentral.com/articles/10.1186/s41256-020-00170-3}, abstract={ Background The first outbreak of COVID-19 in Italy occurred during the second half of February 2020 in some areas in the North of the country. Due to the high contagiousness of the infection, further spread by asymptomatic people, Italy has become in a few weeks the country with the greatest number of infected people in the world. The large number of severe cases among infected people in Italy led to the hospitalization of thousands of patients, with a heavy burden on the National Health Service. Methods We analyzed data provided daily by Italian Authorities for the period from 24 February 2020 to 30 March 2020. Considering such information, we developed a forecast model in real-time, based on the cumulative log-logistic distribution. Results A total of 101,739 infected individuals were confirmed until 30 March 2020, of which 14,620 recovered or discharged, and 11,591 deaths. Until the same date patients quarantined at home were 43,752, whereas hospitalized patients were 31,776, of which 3981 in intensive care. The active cases (i.e. the number of patients not yet recovered until that date) were 75,528. The forecast model estimated a number of infected persons for Italy of 234,000 about, and a duration of the epidemic of approximately 4 months. Conclusions One month after the first outbreaks there seemed to be the first signs of a decrease in the number of infections, showing that we could be now facing the descending phase of the epidemic. The forecast obtained thanks to our model could be used by decision-makers to implement coordinative and collaborative efforts in order to control the epidemic. The pandemic due to novel Coronavirus must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states. }, keywords={Covid-19, Epidemiology, Forecast In Real-Time, Forecast Model, Outbreak, Sars-Cov-2, }, references={}, document_type={Original Research, Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy}, ibbaffiliation={1}, } @article{IBB_ID_54356, author={Megna R, Nappi C, Gaudieri V, Mannarino T, Assante R, Zampella E, Green R, Cantoni V, D'Antonio A, Arumugam P, Acampa W, Petretta M, Cuocolo A}, title={Diagnostic value of clinical risk scores for predicting normal stress myocardial perfusion imaging in subjects without coronary artery calcium}, date={2020 Jun 29}, journal={J Nucl Cardiol (ISSN: 1071-3581linking, 1532-6551electronic)}, year={2020}, fullvolume={109}, volume={109}, pages={N/D--N/D}, url={}, abstract={ Abstract Background: We evaluated if risk scores commonly used to predict the absence of significant stenosis at coronary computed tomography (CT) angiography are useful to predict a normal stress myocardial perfusion imaging (MPI) study. Methods: Our cohort included a total of 1422 consecutive patients with zero coronary artery calcium score (ZCS) who underwent 82 Rb PET/CT for evaluation of suspected coronary artery disease (CAD). Predictive models were constructed as reported by Genders et al. and Alshahrani et al., and the probability of abnormal summed stress score (SSS) and of reduced myocardial perfusion reserve (MPR) based on these risk scores was assessed. Results: In the overall population, the prevalence of abnormal SSS was 0.10 and the prevalence of reduced MPR was 0.17 (both P < .001).The observed frequencies of abnormal SSS and reduced MPR vs the probabilities predicted by the Genders and Alshahrani models were above the diagonal identity line, highlighting an underestimation of the observed occurrence by these models. The areas under the receiver operating characteristic curve of the Genders and Alshahrani models indicated lack of discriminative ability for predicting abnormal SSS (0.547 and 0.527) and reduced MPR (0.509 and 0.538). The Hosmer-Lemeshow test revealed that both models underestimated the observed occurrence of abnormal SSS and reduced MPR. Conclusions: Available models were unable to identify among patients with ZCS those with a low probability of a normal stress MPI study. Thus, an optimal approach to rule out from MPI patients without detectable coronary calcium still needs to be improved. }, keywords={Cad, Mpi, Diagnostic And Prognostic Application, }, references={}, document_type={Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy. Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. Department of Nuclear Medicine, Central Manchester Foundation Trust, Manchester, UK. Department of Translational Medical Sciences, University Federico II, Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54338, author={Cassiano MT, Lanzillo R, Alfano B, Costabile T, Comerci M, Prinster A, Moccia M, Megna R, Morra VB, Quarantelli M, Brunetti A}, title={Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis}, date={2020 Jan 30}, journal={Neuroimage Clin (ISSN: 2213-1582linking, 2213-1582electronic)}, year={2020}, fullvolume={186}, volume={186}, pages={102201--102201}, url={}, abstract={BACKGROUND: Regional analyses of markers of microstructural gray matter (GM) changes, including relaxation rates, have shown inconsistent correlations with physical and cognitive impairment in MS. OBJECTIVE: To assess voxelwise the correlation of the R1 and R2 relaxation rates with the physical and cognitive impairment in MS. METHODS: GM R1 and R2 relaxation rate maps were obtained in 241 relapsing-remitting MS patients by relaxometric segmentation of MRI studies. Correlations with the Expanded Disability Status Scale (EDSS) and the percentage of impaired cognitive test (Brief Repeatable Battery and Stroop Test, available in 186 patients) were assessed voxelwise, including voxel GM content as nuisance covariate to remove the effect of atrophy on the correlations. RESULTS: Extensive clusters of inverse correlation between EDSS and R2 were detected throughout the brain, while inverse correlations with R1 were mostly limited to perirolandic and supramarginal cortices. Cognitive impairment correlated negatively with R1, and to a lesser extent with R2, in the middle frontal, mesial temporal, midcingulate and medial parieto-occipital cortices. CONCLUSION: In relapsing-remitting MS patients, GM microstructural changes correlate diffusely with physical disability, independent of atrophy, with a preferential role of the sensorimotor cortices. Neuronal damage in the limbic system and dorsolateral prefrontal cortices correlates with cognitive dysfunction.}, keywords={Atrophy, Cognitive Impairment, Multiple Sclerosis, Quantitative Mri, Relapsing Remitting, Relaxation Rates, }, references={}, document_type={Journal Article, Research Support, Non-U. S. Gov'T, }, affiliation={Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini, 5, 80131 Naples, Italy. Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy. Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54279, author={Megna R, Assante R, Zampella E, Gaudieri V, Nappi C, Cuocolo R, Mannarino T, Genova A, Green R, Cantoni V, Acampa W, Petretta M, Cuocolo A}, title={Pretest models for predicting abnormal stress single-photon emission computed tomography myocardial perfusion imaging}, date={2019 Nov 11}, journal={J Nucl Cardiol (ISSN: 1071-3581linking, 1532-6551electronic)}, year={2019}, fullvolume={161}, volume={161}, pages={N/D--N/D}, url={}, abstract={BACKGROUND: The frequency of abnormal stress SPECT myocardial perfusion imaging (MPS) decreased over the past decades despite an increase in the prevalence of cardiovascular risk factors. These findings strengthen the need to develop more effective strategies for appropriately referring patients with suspected coronary artery disease (CAD) to cardiac imaging. The aim of this study was to develop pretest assessment models for predicting abnormal stress MPS. METHODS: We included 5,601 consecutive patients with suspected CAD, who underwent stress MPS at our academic center. Two different models were considered: a basic model including age, gender, and anginal symptoms; and a clinical model including also diabetes, hypertension, hypercholesterolemia, smoking, and family history of CAD. RESULTS: In patients with abnormal MPS, the basic model classified more than 75% of patients as intermediate risk, whereas only 23% were incorrectly classified as low risk. In patients with normal MPS, 45% were correctly classified as low risk and none as high risk. Basic and clinical models had a limited discriminating capacity (area under the receiver operating characteristic curve 0.644 for basic model and 0.647 for clinical model) between individuals with and without abnormal stress MPS. The decision curve analysis demonstrates a high net benefit across a range of threshold probabilities from ~ 15% to ~30% for both models. CONCLUSIONS: A pretest risk stratification based on traditional cardiovascular risk factors has a limited value for predicting an abnormal stress MPS in patients with suspected CAD. However, selecting a proper threshold probability enhances the appropriateness of referral to stress MPS.}, keywords={Cad, Mpi, Spect, Diagnostic And Prognostic Application, }, references={}, document_type={Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy., Department of Translational Medical Sciences, University Federico II, Naples, Italy., Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy. cuocolo@unina.it., }, ibbaffiliation={1}, } @article{IBB_ID_54277, author={Megna R, Cuocolo A, Petretta M}, title={Applications of Machine Learning in Medicine}, date={2019 Aug 22}, journal={Biomedical Journal Of Scientific & Technical Research}, year={2019}, fullvolume={132}, volume={132}, pages={15350--15352}, url={}, abstract={Machine Learning is a branch of artificial intelligence that provides algorithms able to learn automatically, improve from experience, and make previsions. In the last years several machine learning algorithims have been developed in medical field, from imaging to big data analysis, obtaining applications for both diagnosis and prognosis. In this mini review, we report three our applications of machine learning in medicine: the first regards the research and classification of pulmunary nodules in computer tomography studies; the second, based on magnetic resonance studies, provides a classification method to be use as an aid in multiple sclerosis diagnosis; the third concerns the probability to be pos-itives to miocardial perfusion imaging, using demographic and clinical data of patients.}, keywords={, }, references={}, document_type={Mini Review, }, affiliation={}, ibbaffiliation={1}, } @article{IBB_ID_54193, author={Pota M, Esposito M, Megna R, De Pietro G, Quarantelli M, Brescia Morra V, Alfano B}, title={Multivariate fuzzy analysis of brain tissue volumes and relaxation rates for supporting the diagnosis of relapsing-remitting multiple sclerosis}, date={2019 Aug}, journal={Biomedical Signal Processing And Control}, year={2019}, fullvolume={422}, volume={422}, pages={N/D--N/D}, url={https://doi.org/10.1016/j.bspc.2019.101591}, abstract={Multiple Sclerosis (MS) is a chronic neuroinflammatory disorder of the brain and spinal cord, widely studied nowadays, due to its relevant prevalence in the population. Even though no cure exists, an earlier and more adequate choice of treatment could delay its evolution and prevent irreversible sequelae and disability progression. Currently, Magnetic Resonance Imaging (MRI) represents an essential nonclinical tool for the detection of a hallmark of the disease, i.e. the presence of demyelinating lesions within cerebral white matter (WM), and, consequently, for the diagnosis of MS early within its course. However, errors in estimating lesions can contribute to a wrong diagnosis, if only the WM lesion load is taken into account, with a more relevant impact in individuals with a reduced lesion load at an initial clinical event, delaying the start of a treatment until a second clinical relapse or after confirming, successively, dissemination In this context, this work proposes an innovative system, employing a multivariate analysis approach, with the aim of mining and integrating multiple sensitive neuroimaging markers, including but not limited to the WM lesion load, into classification models for supporting a more robust diagnosis of Relapsing-Remitting-MS (RR-MS) already at an initial clinical event. To this aim, a retrospective study of 81 patients with diagnosis of RR-MS (39 males and 42 females, 37.3 ± 8.1 years old, age range 20–58) and 29 healthy people of comparable age and gender (15 males and 14 females, 39.7 ± 11.1 years old, age range 22–57) is used. All the individuals were enrolled at Multiple Sclerosis Centre of the “Federico II” University Hospital (Naples, Italy). A machine learning method based on both statistics and Fuzzy Logic, already validated for its desirable characteristics, is applied to volumetric }, keywords={, }, references={}, document_type={Journal Article, }, affiliation={Multiple Sclerosis (MS) is a chronic neuroinflammatory disorder of the brain and spinal cord, widely studied nowadays, due to its relevant prevalence in the population. Even though no cure exists, an earlier and more adequate choice of treatment could delay its evolution and prevent irreversible sequelae and disability progression. Currently, Magnetic Resonance Imaging (MRI) represents an essential nonclinical tool for the detection of a hallmark of the disease, i.e. the presence of demyelinating lesions within cerebral white matter (WM), and, consequently, for the diagnosis of MS early within its course. However, errors in estimating lesions can contribute to a wrong diagnosis, if only the WM lesion load is taken into account, with a more relevant impact in individuals with a reduced lesion load at an initial clinical event, delaying the start of a treatment until a second clinical relapse or after confirming, successively, dissemination In this context, this work proposes an innovative system, employing a multivariate analysis approach, with the aim of mining and integrating multiple sensitive neuroimaging markers, including but not limited to the WM lesion load, into classification models for supporting a more robust diagnosis of Relapsing-Remitting-MS (RR-MS) already at an initial clinical event. To this aim, a retrospective study of 81 patients with diagnosis of RR-MS (39 males and 42 females, 37.3 ± 8.1 years old, age range 20–58) and 29 healthy people of comparable age and gender (15 males and 14 females, 39.7 ± 11.1 years old, age range 22–57) is used. All the individuals were enrolled at Multiple Sclerosis Centre of the “Federico II” University Hospital (Naples, Italy). A machine learning method based on both statistics and Fuzzy Logic, already validated for its desirable characteristics, is applied to volumetric }, ibbaffiliation={1}, } @article{IBB_ID_53994, author={Megna R, Alfano B, Lanzillo R, Costabile T, Comerci M, Vacca G, Carotenuto A, Moccia M, Servillo G, Prinster A, Brescia Morra V, Quarantelli M}, title={Brain tissue volumes and relaxation rates in multiple sclerosis: implications for cognitive impairment}, date={2019 Feb}, journal={J Neurol (ISSN: 1432-1459electronic, 0340-5354linking, 0340-5354print)}, year={2019}, fullvolume={14}, volume={14}, pages={361--368}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057892300&doi=10.1007%2fs00415-018-9139-6&partnerID=40&md5=bf99419b069eaf1cde0674024267c8e7}, abstract={OBJECTIVE: Both normal gray matter atrophy and brain tissue relaxation rates, in addition to total lesion volume, have shown significant correlations with cognitive test scores in multiple sclerosis (MS). Aim of the study was to assess the relative contributions of macro- and microstructural changes of both normal and abnormal brain tissues, probed, respectively, by their volumes and relaxation rates, to the cognitive status and physical disability of MS patients. METHODS: MRI studies from 241 patients with relapsing-remitting MS were retrospectively analyzed by fully automated multiparametric relaxometric segmentation. Ordinal backward regression analysis was applied to the resulting volumes and relaxation rates of both normal (gray matter, normal-appearing white matter and CSF) and abnormal (T2-weighted lesions) brain tissues, controlling for age, sex and disease duration, to identify the main independent contributors to the cognitive status, as measured by the percentage of failed tests at a cognitive test battery (Rao's Brief Repeatable Battery and Stroop test, available in 186 patients), and to the physical disability, as assessed by the Expanded Disability Status Scale (EDSS). RESULTS: The R1 relaxation rate (a putative marker of tissue disruption) of the MS lesions appeared the single most significant contributor to cognitive impairment (p }, keywords={Atrophy, Cognitive Impairment, Multiple Sclerosis, Quantitative Mri, Relapsing, Remitting, Relaxation Rates, Relapsing Remitting, Adolescent , Adult , Cognitive Dysfunction Physiopathology , Female , Gray Matter Diagnostic Imaging Pathology , Humans , Magnetic Resonance Imaging Methods , Middle Aged , Relapsing-Remitting Diagnostic Imaging Pathology Physiopathology , Severity Of Illness Index , White Matter Diagnostic Imaging Pathology , Young Adult, }, references={}, document_type={Journal Article, }, affiliation={Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy., Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy., Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy. quarante@unina.it., Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54298, author={Megna R, Petretta M, Alfano B, Cantoni V, Green R, Daniele S, Acampa W, Nappi C, Gaudieri V, Assante R, Zampella E, Mazziotti E, Mannarino T, Buongiorno P, Cuocolo A}, title={A New Relational Database Including Clinical Data and Myocardial Perfusion Imaging Findings in Coronary Artery Disease}, date={2019}, journal={Curr Med Imaging Rev (ISSN: 1573-4056linking)}, year={2019}, fullvolume={38}, volume={38}, pages={661--671}, url={http://dx.doi.org/10.2174/1573405614666180807110829}, abstract={BACKGROUND: The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging. METHODS: We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer. RESULTS: There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate. CONCLUSION: The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.}, keywords={Database, Postgresql, Cardiac Imaging, Coronary Artery Disease, Myocardial Perfusion, Single-Photon Emission Computed Tomography, }, references={}, document_type={Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy. Department of Translational Medical Sciences, University of Naples Federico II, Naples, Italy. Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.}, ibbaffiliation={1}, } @article{IBB_ID_54243, author={Megna R, Petretta M, Alfano B, Cantoni V, Green R, Daniele S, Acampa W, Nappi C, Gaudieri V, Assante R, Zampella E, Mazziotti E, Mannarini T, Buongiorno P, Cuocolo A}, title={A new relational database including clinical data and myocardial perfusion imaging findings in subjects with suspected or known coronary artery disease}, date={2019}, journal={Current Medical Imaging}, year={2019}, fullvolume={116}, volume={116}, pages={661--671}, url={http://www.eurekaselect.com/164395}, abstract={Background: The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging. Methods: We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer. Results: There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate. Conclusion: The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.}, keywords={Database, Postgresql, Cardiac Imaging, Single-Photon Emission Computed Thomography, Myocardial Perfusion, Coronary Artery Disease Defect, }, references={}, document_type={Research Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.  Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy.  Department of Translational Medical Sciences, University Federico II, Naples, Italy. }, ibbaffiliation={1}, } @article{IBB_ID_54247, author={Larobina M, Solla R, Megna R}, title={Quantitative characterization of tumors in PET: a comparison of three texture analysis software packages}, date={2019}, journal={European Journal Of Nuclear Medicine And Molecular Imaging}, year={2019}, fullvolume={274}, volume={274}, pages={EPS112--EPS112}, url={}, abstract={}, keywords={, }, references={}, document_type={Conference Proceedings - Eanm'19 - 32nd Annual Congress Of The European-Association-Of-Nuclear-Medicine, Barcelona, Spain, Oct 12-16, 2019, }, affiliation={}, ibbaffiliation={1}, } @article{IBB_ID_53615, author={Esposito M, Minutolo A, Megna R, Forastiere M, Magliulo M, De Pietro G}, title={A smart mobile, self-configuring, context-aware architecture for personal health monitoring}, date={2018}, journal={Engineering Applications Of Artificial Intelligence}, year={2018}, fullvolume={155}, volume={155}, pages={136--156}, url={}, abstract={The last decade has witnessed an exponential increase in older adult population suffering from chronic life-long diseases and needing healthcare. This situation has highlighted a need to revolutionize healthcare and provide innovative, efficient, and affordable solutions to patients at any time and from anywhere in an economic and friendly manner. The recent developments in sensing, mobile, and embedded devices have attracted considerable attention toward mobile health monitoring applications. However, existing architectures aimed at facilitating the realization of these mobile applications have shown to be not suitable to address all these challenging issues: (i) the seamless integration of heterogeneous devices; (ii) the estimation of vital parameters not measurable directly or measurable with a low accuracy; (iii) the extraction of context information pertaining to the patient’s activity to be used for the interpretation of vital parameters; (iv) the correlation of physiological and contextual information to detect suspicious anomalies and supply alerts; (v) the notification of anomalies to doctors and caregivers only when their detection is accurate and appropriate. In light of the above, this paper presents a smart mobile, selfconfiguring, context-aware architecture devised to enable the rapid prototyping of personal health monitoring applications for different scenarios, by exploiting commercial wearable sensors and mobile devices as well as knowledge-based technologies. This architecture is organized as a composition of four tiers that operate on a layered fashion and it exploits an ontology-based data model to ensure intercommunication among these tiers and the monitoring applications built on the top of them. The proposed architecture has been implemented for mobile devices equipped with the Android platform and evaluated with respect to its modifiability by employing the ALMA (Architecture Level Modifiability Analysis) method, highlighting its capability of being rapidly customized, personalized or eventually modified by software developers in order to prototype, with a reduced effort, novel health monitoring applications on the top of its components. Finally, it has been employed to build, as case study, a mobile application aimed at monitoring and managing cardiac arrhythmias, such as bradycardia and tachycardia, confirming its effectiveness with respect to a real scenario.}, keywords={Heart Rate, Spo2, Pedometer, Health Monitoring, }, references={Agarwal, A., Furht, B., Conatser, M., Baechle, C., 2013. Secure mobile framework for monitoring medical sensor data. In: Handbook of Medical and Healthcare Technologies. 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A health monitoring system using smart phones and wearable sensors. Int. J. ARM 8 (2), 29–35. Giffen, R., Fung, M.F.K., Rotaru, M., 2015. Remote patient monitoring to improve health: challenges and opportunities. In: Proceedings of the 25th Annual International Conference on Computer Science and Software Engineering. IBM Corp., pp. 277–280. Gruber, T., 1995. Towards principles for the design of ontologies used for knowledge sharing. Int. J. Hum. Comput. Stud. 43, 907–928. Guarino, N., 1995. Formal ontology, conceptual analysis and knowledge representation. Int. J. Hum.-Comput. Stud. 43, 625–640. Guarino, N., 1997. Understanding and building, using ontologies. Int. J. Hum.- Comput. Habetha, J., 2006. The MyHeart project-fighting cardiovascular diseases by prevention and early diagnosis. In: Conf Proc IEEE Eng Med Biol Soc, pp. 6746–6749. Henry, J.E., Cain, J.P., 1997. A quantitative comparison of perfective and corrective software maintenance. J. Softw. Maint.: Res. 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Physiol. 109 (3), Tudor-Locke, C., Burkett, L., Reis, J.P., Ainsworth, B.E., Macera, C.A., Wilson, D.K., 2005. How many days of pedometer monitoring predict weekly physical activity in adults?. Prev. Med. 40 (3), 293–298. Uschold, M., Gruninger, M., 1996. Ontologies: principles, methods and applications. Knowl. Eng. Rev. 11 (2), 93–136. Villarreal, V., Fontecha, J., Hervas, R., Bravo, J., 2014. Mobile and ubiquitous architecture for the medical control of chronic diseases through the use of intelligent devices: using the architecture for patients with diabetes. Future Gener. Comput. Syst. 34, 161–175. World Health Organization, 2002. Active Ageing: A Policy Framework: A Contribution of the Second United Nations World Assembly on Ageing. World Health Organization, Zadeh, L.A., 1965. Fuzzy sets. Inf. Control 8, 338–353.}, document_type={Journal Article, }, affiliation={National Research Council of Italy — Institute for High Performance Computing and Networking (ICAR), Via P. Castellino 111, 80131 Naples, Italy;  Neatec S.p.A., Via Campi Flegrei, 34, 80078 Pozzuoli, Italy}, ibbaffiliation={1}, } @article{IBB_ID_53616, author={Megna R, Petretta M, Alfano B, Cantoni V, Green R, Daniele S, Acampa W, Nappi C, Gaudieri V, Assante R, Zampella E, Mazziotti E, Mannarini T, Buongiorno P, Cuocolo A}, title={A new relational database including clinical data and myocardial perfusion imaging findings in subjects with suspected or known coronary artery disease}, date={2017 May}, journal={European Heart Journal - Cardiovascular Imaging}, year={2017}, fullvolume={284}, volume={284}, pages={i37--i37}, url={}, abstract={ Background: Stress myocardial perfusion imaging (MPI) provides prognostic infor- mation for clinical decision-making in subjects with suspected or known coronary artery disease (CAD) Purpose: The aim of this study was to test a relational database including clinical and imaging data of subjects with suspected or known CAD undergoing stress MPI between Jan. 2002 and Dec. 2014 and to assess the impact of age and gender on MPI findings Materials and Methods: We developed a relational database (PostgreSQL 9.2) including the clinical and imaging data of 7563 subjects. Databases included: anam- nesis informations; other clinical and instrumental (e.g. ECG, echocardiography) fea- tures; pre-test likelihood of disease by Cadenza; post-processing MPI results; follow- up information. Data were arranged according to a logic of aggregation and stored in 12 tables. Epidemiological statistics analysis was performed using R statistical software Results: Of the overall study population, 68% were male and 32% female. Abnormal findings were observed in 46% of male subjects showing 35% fixed defect, 32% reversible defects and 33% mixed perfusion defects. In female subjects, 19% showed MPI abnormal findings, of these 29% with fixed, 43% with reversible and 28% with mixed perfusion defects. The number of test performed increased from 198 to 689 (slope6std¼44.467.3, p}, keywords={Database, Postgresql, Myocardial Perfusion Imaging, Clinical Data, Cardiac Imaging, Single-Photon Emission Computed Thomography, Coronary Artery Disease Defect, }, references={}, document_type={Poster, Research Journal Article, }, affiliation={National Research Council, Institute of Biostructure and Bioimaging, Naples, Italy; Federico II University of Naples, Department of Translational Medical Sciences,Naples, Italy; }, ibbaffiliation={1}, } @article{IBB_ID_53612, author={Magliulo M, Megna R, Cella L, Liuzzi R, Palma G, Pacelli R}, title={Feasibility Study of Outpatient Monitoring by Fitness Activity Trackers in a Radiation Oncology Department}, date={2016 Oct}, journal={International Journal Of Radiation Oncology}, year={2016}, fullvolume={144}, volume={144}, pages={299--299}, url={}, abstract={Purpose/Objective(s): To monitor Radiation Oncology (RO) patient workflow and at to obtain an index of the quality of life of patient during radiation treatment. Information and Communication Technology monitoring devices (ICT-MD), through a Pervasive Computing Approach (PCA), allow the localization of patient and at the same time the archiving of diverse biometrical data such as heart rate, one of the most robust, noninvasive measure of stress response. Here we describe a pilot study on the introduction of ICT-MD in a RO Department. Materials/Methods: For our application, we focused on Activity Tracker (ACT) bracelet (Amiigo, Amiigo Inc., Salt Lake City, UT), an ICT-MD able to measure SpO2 variation, acceleration and skin temperature without any patient interaction according to PCA paradigm. We selected an inexpensive ACT designed mainly for the fitness consumer market that provides a set of application program interfaces (APIs) for direct readout of sensor data, making the raw data available. An in-house software program was developed in Matlab (MathWorks, Natick, MA) for biometric raw data processing for indirect data measurements (heart rate). The builtin Bluetooth connection is used for patient presence detection and transmission of the collected information to the receivers installed in the RO Department. A first detector is used to recognize the patient and to automatically update his/her data in the health record system. A second receiver is in the LINAC room to limit patient exchange and treatment errors. The integrated hardware/software prototype has been accordingly set up at our institution. Results: Tests on the prototype has been successfully performed for each single component, for each combination of components and for the whole system. More than 50% of the collected biometric series turned out to be clean enough for Matlab post processing. The heart rate estimates were positively assessed against the ECG gold standard (5-10% discrepancies). The accelerometer acquisitions were exploited for a covariate analysis with heart rate series in order to enhance the specificity, e.g. by distinguishing between a physiological heart rate acceleration from a pathological condition. None of the 80 tests performed in RO Department for presence detection and identification failed. Conclusion: The realized prototype has been fully validated and its performance revealed encouraging to ameliorate the efficiency of RO patient work-flow management. Furthermore, the system is suitable for monitoring patient distress during the whole radiation treatment course. The proved feasibility of the framework warrants its application in the clinical practice.}, keywords={Radiation Oncology, Patient Monitoring, Fitness Activity Trackers, }, references={}, document_type={Poster, }, affiliation={National Research Council, Institute of Biostructures and Bioimaging, Napoli, Italy, Federico II University School of Medicine, Department of Advanced Biomedical Sciences, Napoli, Italy}, ibbaffiliation={1}, } @article{IBB_ID_53268, author={Gramanzini M, Gargiulo S, Zarone F, Megna R, Apicella A, Aversa R, Salvatore M, Mancini M, Sorrentino R, Brunetti A}, title={Combined microcomputed tomography, biomechanical and histomorphometric analysis of the peri-implant bone: a pilot study in minipig model}, date={2016 Jun}, journal={Dent Mater (ISSN: 0109-5641, 0109-5641linking)}, year={2016}, fullvolume={84}, volume={84}, pages={794--806}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969234313&doi=10.1016%2fj.dental.2016.03.025&partnerID=40&md5=024078f340dbde6c191b42be91a25f76}, abstract={OBJECTIVES: To present a practical approach that combines biomechanical tests, microcomputed tomography (μCT) and histomorphometry, providing quantitative results on bone structure and mechanical properties in a minipig model, in order to investigate the specific response to an innovative dental biomaterial. METHODS: Titanium implants with innovative three-dimensional scaffolds were inserted in the tibias of 4 minipigs. Primary stability and osseointegration were investigated by means of insertion torque (IT) values, resonance frequency analysis (RFA), bone-to-implant contact (BIC), bone mineral density (BMD) and stereological measures of trabecular bone. RESULTS: A significant positive correlation was found between IT and RFA (r=0.980, p=0.0001). BMD at the implant sites was 18% less than the reference values (p=0.0156). Peri-implant Tb.Th was 50% higher, while Tb.N was 50% lower than the reference zone (p}, keywords={Dental Implant, Histomorphometry, Insertion Torque, Minipig Model, Resonance Frequency Analysis, Muct, Animals, Dental Implantation, Endosseous, Humans, Osseointegration, Pilot Projects, Reproducibility Of Results, Swine, Miniature, X-Ray Microtomography, μct, }, references={}, document_type={Journal Article, }, affiliation={Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145 Naples, Italy; CEINGE scarl, Via G. Salvatore 486, 80145 Naples, Italy. Electronic address: matteo.gramanzini@ibb.cnr.it., Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145 Naples, Italy; CEINGE scarl, Via G. Salvatore 486, 80145 Naples, Italy. Electronic address: sara.gargiulo@ibb.cnr.it., Department of Neurosciences, Reproductive and Odontostomatological Sciences, School of Medicine, University "Federico II", Via Pansini 5, 80131 Naples, Italy. Electronic address: fernandozarone@mac.com., Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145 Naples, Italy. Electronic address: rosario.megna@ibb.cnr.it., Department of Architecture and Industrial Design, Second University of Naples, Borgo San Lorenzo, 81031 Aversa, Italy. Electronic address: antonio.apicella@unina2.it., Department of Architecture and Industrial Design, Second University of Naples, Borgo San Lorenzo, 81031 Aversa, Italy. Electronic address: raffaella.aversa@unina2.it., IRCCS SDN, Via E. Gianturco 113, 80143 Naples, Italy. Electronic address: marsalva@unina.it., Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145 Naples, Italy. Electronic address: marcello.mancini@ibb.cnr.it., Department of Neurosciences, Reproductive and Odontostomatological Sciences, School of Medicine, University "Federico II", Via Pansini 5, 80131 Naples, Italy; Department of Architecture and Industrial Design, Second University of Naples, Borgo San Lorenzo, 81031 Aversa, Italy. Electronic address: errestino@libero.it., Department of Advanced Medical Sciences, University "Federico II", Via Pansini 5, 80145 Naples, Italy; CEINGE scarl, Via G. Salvatore 486, 80145 Naples, Italy. Electronic address: brunetti@unina.it., CEINGE scarl, Via G. Salvatore 486, 80145 Naples, Italy. Electronic address: matteo.gramanzini@ibb.cnr.it. Department of Neuroscien}, ibbaffiliation={1}, } @article{IBB_ID_53614, author={Gargiulo S, Gramanzini M, Coda ARD, Megna R, Panico M, Mancini M, Pappata S}, title={Animal Care in a Mouse Model of Amyotrophic Lateral Sclerosis Studied with [18F]DPA-714 Micro-PET/CT}, date={2016 Feb}, journal={Comparative Medicine}, year={2016}, fullvolume={259}, volume={259}, pages={76--76}, url={}, abstract={SOD1G93A mice are a transgenic model of Amyotrophic lateral sclerosis (ALS) to investigate in vivo neuroinflammation with innovative translocator protein radioligands and positron emission tomography (PET). The possibility to perform serial studies in the same animal, from the asymptomatic to the advanced stages, is highly desirable. Alterations of nutrition, hydration and of cardiovascular hemodynamics provide challenges for researchers and can adversely affect imaging studies. 10 hemyzigous SOD1G93A mice (aged 71-137 days) were evaluated at different clinical stages (CS, score range: 0-4) by [18F]DPA-714 PET/CT (GE Healthcare eXplore Vista, resolution: 1.8 mm FWHM/200 μm). 5 mice were longitudinally monitored. Weight, body condition (BCS, 0-5) and dehydration were daily monitored. From CS and BCS scored as 2, palatable source of hydration and energy were left on cage floor. Glucose 5% /Ringer lactate or NaCl 0.9% solutions (1-3 ml/day) with multivitaminic supplement were provided parenterally. Mice were housed in dry cage with soft bed, avoiding social isolation. Ocular discharges and ulcerative lesions were cleaned (NaCl 0.9%; iodopovidone). Imaging studies were performed under inhalant anesthesia (isoflurane 2% and oxygen 2 L/min). Radiotracer uptake (SUV) was measured on PET/CT fusion images in the cerebellum, brainstem, spinal cord normalized to those of the frontal cortex using Osirix software. In the single PET/CT group, 3 mice died after imaging study (CS: 1-2; BCS 3; weight gain +2.87g), while 2 mice were euthanized after 6 days (CS: 4; BCS 2; weight loss -3.04g). Mice performed from 2 to 5 imaging sessions, with a mean survival of 6 days after the last PET/CT (CS: 2-4; BCS 2-3; weight loss -1.68g). SUV showed an increased trend overtime in brainstem compared to age-matched controls. These findings underlie the relevant role played by the special care of transgenic murine models in order to improve longitudinal studies and minimize confounding variables. The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° HEALTH-F2-2011-278850 (INMiND). }, keywords={Mouse Model, Amyotrophic Lateral Sclerosis, [18f]dpa-714, Micro-Pet, Aisal Symposium, }, references={}, document_type={Poster, }, affiliation={Institute of Biostructures and Bioimages of National Council of Research, Naples, Italy; CEINGE scarl, Naples, Italy}, ibbaffiliation={1}, } @article{IBB_ID_53613, author={Gargiulo S, Gramanzini M, Megna R, Mancini M}, title={Noninvasive Ovarian Imaging in the Murine Models Using Ultrasound Biomicroscopy}, date={2016 Feb}, journal={Comparative Medicine}, year={2016}, fullvolume={259}, volume={259}, pages={76--76}, url={}, abstract={The laboratory mouse is a well-accepted model for reproductive biology studies and findings made in mice have been commonly translated to humans. C57BL/6J and BALB/c strains provide a robust experimental platform for polycystic ovary syndrome and ovarian cancer research in women. Serial assessment of ovarian morphometry and follicle dynamics may be performed non-invasively and reliably in mice by Ultrasound Biomicroscopy (UBM), with a near microscopic resolution. Our pilot study focused on the utility of UBM in murine models to measure size of ovaries and to count ovarian follicles over time. Three C57Bl/6J and two BALB/c adult mice (> 8 weeks of age) were housed in standard conditions, with free access to food and water. Spontaneous estrous cycle was longitudinally evaluated by transcutaneous UBM (Vevo 770, VisualSonics, Toronto, Canada; center frequency of 40 MHz; focal depth of 6 mm, spatial resolution of 30 um) on a time period of 8-15 consecutive days. Mice were anesthetized with 1.5% isoflurane in oxygen and fixed in sternal recumbency on a heated stage. Trichotomy was performed over the thoracolumbar area, and acoustic gel was applied to the skin. Images of both ovaries were obtained in sagittal and axial scans, and processed offline using ImageJ software. Ovarian diameters, area, volume and follicles identification were obtained. To imaging results comparison, the phase of the estrous cycle was assessed in BALB/c mice by vaginal cytology. Ovaries were consistently localized in all mice, with a 10 minutes scan time. The changes of the follicles pattern and number overtime have wave-like fashion. In conclusion, UBM is a suitable method for measuring and for identifying the patterns in follicle development, ovulation and regression in mice in vivo, and to monitor the potential efficacy of novel therapies in murine models of ovarian pathologies.}, keywords={Ovarian Imaging, Murine Models, Ultrasound Biomicroscopy, Aisal Symposium, }, references={}, document_type={Poster, }, affiliation={Institute of Biostructures and Bioimages of National Council of Research, Naples, Italy;  CEINGE scarl, Naples, Italy}, ibbaffiliation={1}, } @article{IBB_ID_51026, author={Gargiulo S, Gramanzini M, Megna R, Greco A, Albanese S, Manfredi C, Brunetti A}, title={Evaluation of growth patterns and body composition in C57Bl/6J mice using dual energy X-ray absorptiometry}, date={2014 Jul}, journal={Biomed Res Int (ISSN: 2314-6133, 2314-6141)}, year={2014}, fullvolume={407}, volume={407}, pages={253067--253067}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84904615488&partnerID=40&md5=ebfaadfbbb1159c100a9f9a2e28671c3}, abstract={The normal growth pattern of female C57BL/6J mice, from 5 to 30 weeks of age, has been investigated in a longitudinal study. Weight, body surface area (BS), and body mass index (BMI) were evaluated in forty mice. Lean mass and fat mass, bone mineral content (BMC), and bone mineral density (BMD) were monitored by dual energy X-ray absorptiometry (DEXA). Weight and BS increased linearly (16.15 ± 0.64 - 27.64 ± 1.42 g; 51.13 ± 0.74 - 79.57 ± 2.15 cm2, P < 0.01), more markedly from 5 to 9 weeks of age (P < 0.001). BMD showed a peak at 17 weeks (0.0548 ± 0.0011 g/cm2 m, P < 0.01). Lean mass showed an evident gain at 9 (15.8 ± 0.8 g, P < 0.001) and 25 weeks (20.5 ± 0.3 g, P < 0.01), like fat mass from 13 to 17 weeks (2.0 ± 0.4 - 3.6 ± 0.7 g, P < 0.01). BMI and lean mass index (LMI) reached the highest value at 21 weeks (3.57 ± 0.02 - 0.284 ± 0.010 g/cm2, resp.), like fat mass index (FMI) at 17 weeks (0.057 ± 0.009 g/cm2) (P < 0.01). BMI, weight, and BS showed a moderate positive correlation (0.45-0.85) with lean mass from 5 to 21 weeks. Mixed linear models provided a good prediction for lean mass, fat mass, and BMD. This study may represent a baseline reference for a future comparison of wild-type C57BL/6J mice with models of altered growth. © 2014 Sara Gargiulo et al.}, keywords={Animal Experiment, Animal Model, Article, Body Composition, Body Mass, Body Surface, Body Weight, Bone Density, Controlled Study, Dual Energy X Ray Absorptiometry, Fat Mass, Female, Growth, Lean Body Weight, Longitudinal Study, Mouse, Nonhuman, C57bl Mouse, Confidence Interval, Development And Aging, Nonparametric Test, Photon Absorptiometry, Procedures, Regression Analysis, Growth And Development, Mice, Inbred C57bl, Statistics, Methods, }, references={Champy, M., Selloum, M., Zeitler, V., Caradec, C., Jung, B., Rousseau, S., Pouilly, L., Auwerx, J., Genetic background determines metabolic phenotypes in the mouse (2008) Mammalian Genome, 19 (5), pp. 318-331. , 10.1007/s00335-008-9107-z 2-s2.0-4924912786 Drake, T.A., Schadt, E., Hannani, K., Kabo, J.M., Krass, K., Colinayo, V., Greaser III, L.E., Lusis, A.J., Genetic loci determining bone density in mice with diet-induced atherosclerosis (2001) Physiological Genomics, 2001 (5), pp. 205-215 Ishida, B.Y., Blanche, P.J., Nichols, A.V., Yashar, M., Paigen, B., Effects of atherogenic diet consumption on lipoproteins in mouse strains C57BL/6 and C3H (1991) Journal of Lipid Research, 32 (4), pp. 559-568. , 2-s2.0-0025778287 Paigen, B., Genetics of responsiveness to high-fat and high-cholesterol diets in the mouse (1995) The American Journal of Clinical Nutrition, 62 (2), pp. 458S-462S. , 2-s2.0-0029163399 Beamer, W.G., Donahue, L.R., Rosen, C.J., Baylink, D.J., Genetic variability in adult bone density among inbred strains of mice (1996) Bone, 18 (5), pp. 397-403. , DOI 10.1016/8756-3282(96)00047-6 Klein, R.F., Mitchell, S.R., Phillips, T.J., Belknap, J.K., Orwoll, E.S., Quantitative trait loci affecting peak bone mineral density in mice (1998) Journal of Bone and Mineral Research, 13 (11), pp. 1648-1656. , DOI 10.1359/jbmr.1998.13.11.1648 Nunez, N.P., Carpenter, C.L., Perkins, S.N., Berrigan, D., Jaque, S.V., Ingles, S.A., Bernstein, L., Hursting, S.D., Extreme obesity reduces bone mineral density: Complementary evidence from mice and women (2007) Obesity, 15 (8), pp. 1980-1987 Brodt, M.D., Ellis, C.B., Silva, M.J., Growing C57B1/6 mice increase whole bone mechanical properties by increasing geometric and material properties (1999) Journal of Bone and Mineral Research, 14 (12), pp. 2159-2166 Corva, P.M., Medrano, J.F., Diet effects on weight gain and body composition in high growth (hg / hg) mice (2000) Physiol Genomics, 3 (1), pp. 17-23. , 2-s2.0-0034729572 Sjogren, K., Hellberg, N., Bohlooly-Y, M., Savendahl, L., Johansson, M.S., Berglindh, T., Bosaeus, I., Ohlsson, C., Body fat content can be predicted in vivo in mice using a modified dual-energy X-ray absorptiometry technique (2001) Journal of Nutrition, 131 (11), pp. 2963-2966 Rieusset, J., Seydoux, J., Anghel, S.I., Escher, P., Michalik, L., Tan, N.S., Metzger, D., Desvergne, B., Altered growth in male peroxisome proliferator-activated receptor γ (PPARγ) heterozygous mice: Involvement of PPARγ in a negative feedback regulation of growth hormone action (2004) Molecular Endocrinology, 18 (10), pp. 2363-2377. , DOI 10.1210/me.2003-0325 Price, C., Herman, B.C., Lufkin, T., Goldman, H.M., Jepsen, K.J., Genetic variation in bone growth patterns defines adult mouse bone fragility (2005) Journal of Bone and Mineral Research, 20 (11), pp. 1983-1991. , DOI 10.1359/JBMR.050707 Reed, D.R., Bachmanov, A.A., Tordoff, M.G., Forty mouse strain survey of body composition (2007) Physiology and Behavior, 91 (5), pp. 593-600. , DOI 10.1016/j.physbeh.2007.03.026, PII S0031938407001151 Chen, W., Wilson, J.L., Khaksari, M., Cowley, M.A., Enriori, P.J., Abdominal fat analyzed by DEXA scan reflects visceral body fat and improves the phenotype description and the assessment of metabolic risk in mice (2012) The American Journal of Physiology - 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(1998) British Journal of Radiology, 71 (SEPT.), pp. 934-943 Kelly, T.L., Wilson, K.E., Heymsfield, S.B., Dual energy X-ray absorptiometry body composition reference values from NHANES (2009) PLoS ONE, 4 (9). , e7038 10.1371/journal.pone.0007038 2-s2.0-70349280466 Meeuwsen, S., Horgan, G.W., Elia, M., The relationship between BMI and percent body fat, measured by bioelectrical impedance, in a large adult sample is curvilinear and influenced by age and sex (2010) Clinical Nutrition, 29 (5), pp. 560-566. , 10.1016/j.clnu.2009.12.011 2-s2.0-77957341769 Boeke, C.E., Oken, E., Kleinman, K.P., Rifas-Shiman, S.L., Taveras, E.M., Gillman, M.W., Correlations among adiposity measures in school-aged children (2013) BMC Pediatrics, 13 (1), p. 99. , 10.1186/1471-2431-13-99 2-s2.0-84879242615 Ishimori, N., Li, R., Kelmenson, P.M., Korstanje, R., Walsh, K.A., Churchill, G.A., Forsman-Semb, K., Paigen, B., Quantitative trait loci that determine plasma lipids and obesity in C57BL/6J and 129S1/SvImJ inbred mice (2004) Journal of Lipid Research, 45 (9), pp. 1624-1632. , DOI 10.1194/jlr.M400098-JLR200 Borecki, I.B., Bonney, G.E., Rice, T., Bouchard, C., Rao, D.C., Influence of genotype-dependent effects of covariates on the outcome of segregation analysis of the body mass index (1993) American Journal of Human Genetics, 53 (3), pp. 676-687 Mahabir, S., Baer, D., Johnson, L.L., Roth, M., Campbell, W., Clevidence, B., Taylor, P.R., Body Mass Index, percent body fat, and regional body fat distribution in relation to leptin concentrations in healthy, non-smoking postmenopausal women in a feeding study (2007) Nutrition Journal, 6, p. 3. , DOI 10.1186/1475-2891-6-3 Vitarius, J.A., Sehayek, E., Breslow, J.L., Identification of quantitative trait loci affecting body composition in a mouse intercross (2006) Proceedings of the National Academy of Sciences of the United States of America, 103 (52), pp. 19860-19865. , DOI 10.1073/pnas.0609232103}, document_type={Journal Article, }, affiliation={Institute of Biostructures and Bioimages, National Council of Research of Naples, Via De Amicis 95, 80145 Naples, Italy CEINGE-Biotecnologie Avanzate Scarl, Via G. Salvatore 486, 80145 Naples, Italy Department of Advanced Biomedical Sciences, Federico II University, Via Pansini 5, 80131 Naples, Italy Department of Neurosciences, Reproductive and Odontostomatological Sciences, Federico II University, Via Pansini 5, 80131 Naples, Italy}, ibbaffiliation={1}, }