Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa (70 views visite)
Magn Reson Imaging (ISSN: 0730-725xlinking), 2019 Dec; 64: 71-76.
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Paper type Tipo di articolo: Journal Article, Observational Study
Impact factor: 2.037, 5-year impact factor Impact factor a 5 anni: 2.216
Url: Not available. Non disponibile.
Keywords Parole chiave: Mri, Machine Learning, Placenta Accrete Spectrum, Radiomics, Texture Analysis, Adult , Algorithms , Bayes Theorem , Female , Humans , Image Interpretation, Computer-Assisted Methods , Magnetic Resonance Imaging Methods , Placenta Diagnostic Imaging , Placenta Accreta Diagnostic Imaging , Placenta Previa Diagnostic Imaging , Predictive Value Of Tests , Pregnancy , Prenatal Diagnosis Methods , Reproducibility Of Results , Retrospective Studies , Sensitivity And Specificity
Affiliations Affiliazioni:
*** IBB - CNR ***
University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy., University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy. Electronic address: renato.cuocolo@unina.it., University of Naples "Federico II", Department of Neuroscience, Reproductive and Dentistry Sciences, Naples, Italy., University of Naples "Federico II", Department of Public Health, Naples, Italy., Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy.,
Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy.
References Riferimenti:
Not available. Non disponibili.
Magn Reson Imaging (ISSN: 0730-725xlinking), 2019 Dec; 64: 71-76.
Export to Esporta in BibTeX Export to Esporta in EndNote
Paper type Tipo di articolo: Journal Article, Observational Study
Impact factor: 2.037, 5-year impact factor Impact factor a 5 anni: 2.216
Url: Not available. Non disponibile.
Keywords Parole chiave: Mri, Machine Learning, Placenta Accrete Spectrum, Radiomics, Texture Analysis, Adult , Algorithms , Bayes Theorem , Female , Humans , Image Interpretation, Computer-Assisted Methods , Magnetic Resonance Imaging Methods , Placenta Diagnostic Imaging , Placenta Accreta Diagnostic Imaging , Placenta Previa Diagnostic Imaging , Predictive Value Of Tests , Pregnancy , Prenatal Diagnosis Methods , Reproducibility Of Results , Retrospective Studies , Sensitivity And Specificity
Affiliations Affiliazioni:
*** IBB - CNR ***
University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy., University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy. Electronic address: renato.cuocolo@unina.it., University of Naples "Federico II", Department of Neuroscience, Reproductive and Dentistry Sciences, Naples, Italy., University of Naples "Federico II", Department of Public Health, Naples, Italy., Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy.,
Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy.
References Riferimenti:
Not available. Non disponibili.
Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa
PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is that TA features may reflect histological abnormalities underlying PAS in patients with PP thus helping in differentiating positive from negative cases. MATERIALS AND METHODS: Pre-operative MRI examinations of 64 patients with PP of which 20 positive (12 accreta, 7 increta and 1 percreta) and 44 negative for PAS were retrospectively selected. Multiple (n = 3) rounded regions of interest (ROIs) were manually positioned on sagittal or coronal T2-weighted images over homogeneous placental tissue close to the placental-myometrial interface for each patient to extract TA features. After balancing the dataset with the Synthetic Minority Over-sampling Technique, training and testing sets were obtained using Hold-out with a 75/25% split. Different algorithms were applied on the training set using the wrapper method, which looks for the best combination of features based on the optimization of a heuristic function in order to get the highest accuracy, and a 10-fold Cross-validation. The accuracy of the best models was also assessed on the test set. Histology was used as the standard of reference. RESULTS: A total of 192 ROIs were positioned and a ROI-based analysis was then conducted. Among the different algorithms, k-nearest neighbors obtained the highest accuracy (98.1%), precision (98.7%), sensitivity (97.5%) and specificity (98.7%) while exploiting the lowest number of features (n = 26); conversely, the Naïve Bayes algorithm got the lowest scores showing an accuracy of 80.5%. CONCLUSION: ML analysis using MRI-derived TA features could be a feasible tool in the identification of placental tissue abnormalities underlying PAS in patients with PP. This approach might represent an additional tool in the clinical practice, thus expanding the application field of artificial intelligence to medical images.
PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is that TA features may reflect histological abnormalities underlying PAS in patients with PP thus helping in differentiating positive from negative cases. MATERIALS AND METHODS: Pre-operative MRI examinations of 64 patients with PP of which 20 positive (12 accreta, 7 increta and 1 percreta) and 44 negative for PAS were retrospectively selected. Multiple (n = 3) rounded regions of interest (ROIs) were manually positioned on sagittal or coronal T2-weighted images over homogeneous placental tissue close to the placental-myometrial interface for each patient to extract TA features. After balancing the dataset with the Synthetic Minority Over-sampling Technique, training and testing sets were obtained using Hold-out with a 75/25% split. Different algorithms were applied on the training set using the wrapper method, which looks for the best combination of features based on the optimization of a heuristic function in order to get the highest accuracy, and a 10-fold Cross-validation. The accuracy of the best models was also assessed on the test set. Histology was used as the standard of reference. RESULTS: A total of 192 ROIs were positioned and a ROI-based analysis was then conducted. Among the different algorithms, k-nearest neighbors obtained the highest accuracy (98.1%), precision (98.7%), sensitivity (97.5%) and specificity (98.7%) while exploiting the lowest number of features (n = 26); conversely, the Naïve Bayes algorithm got the lowest scores showing an accuracy of 80.5%. CONCLUSION: ML analysis using MRI-derived TA features could be a feasible tool in the identification of placental tissue abnormalities underlying PAS in patients with PP. This approach might represent an additional tool in the clinical practice, thus expanding the application field of artificial intelligence to medical images.
Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa
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Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa
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Acad Radiol (ISSN: 1076-6332linking), 2021 May; 28(5): 737-744.
Impact Factor: 2.488
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Zöllner FG, Dastrù W, Irrera P, Longo DL, Bennett KM, Beeman SC, Bretthorst GL, Garbow JR
* Analysis Protocol for Dynamic Contrast Enhanced (DCE) MRI of Renal Perfusion and Filtration (8 visite)
Methods Mol Biol (ISSN: 1064-3745linking), 2021; 2216: 637-653.
Impact Factor: 1.17
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Irrera P, Consolino L, Dastrù W, Pedersen M, Zöllner FG, Longo DL
* Dynamic Contrast Enhanced (DCE) MRI-Derived Renal Perfusion and Filtration: Experimental Protocol (8 visite)
Methods Mol Biol (ISSN: 1064-3745linking), 2021; 2216: 429-441.
Impact Factor: 1.17
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Stanzione A, Ricciardi C, Cuocolo R, Romeo V, Petrone J, Sarnataro M, Mainenti PP, Improta G, De Rosa F, Insabato L, Brunetti A, Maurea S
* MRI Radiomics for the Prediction of Fuhrman Grade in Clear Cell Renal Cell Carcinoma: a Machine Learning Exploratory Study (24 visite)
J Digit Imaging (ISSN: 0897-1889linking), 2020 Aug; 33(4): 879-887.
Impact Factor: 3.697
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Palma G, Monti S, Cella L
* Voxel-based analysis in radiation oncology: A methodological cookbook (50 visite)
Phys Med (ISSN: 1120-1797linking), 2020 Jan; 69: 192-204.
Impact Factor: 2.485
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Camera L, Pezzullo F, Acampora A, Liuzzi R, Rispo A, Nardone OM, Luglio G, Bucci L, Castiglione F, Brunetti A
* Multi-detector CT enterography in active inflammatory bowel disease: Image quality and diagnostic efficacy of a low-radiation high contrast protocol (75 visite)
Clin Imaging (ISSN: 0899-7071linking), 2019 Nov; 58: 27-33.
Impact Factor: 0.658
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Mainenti PP, Stanzione A, Guarino S, Romeo V, Ugga L, Romano F, Storto G, Maurea S, Brunetti A
* Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging (123 visite)
World J Gastroentero (ISSN: 1007-9327linking, 2219-2840), 2019 Sep 21; 25 (35 ): 5233-5256.
Impact Factor: 2.24
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Megna R, Cuocolo A, Petretta M
* Applications of Machine Learning in Medicine (119 visite)
Biomedical Journal Of Scientific & Technical Research, 2019 Aug 22; 20: 15350-15352.
Impact Factor: 0.548
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Kujawa A, Kim M, Demetriou E, Anemone A, Livio Longo D, Zaiss M, Golay X
* Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging (23 visite)
J Magn Reson (ISSN: 1090-7807linking), 2019 Mar; 300: 120-134.
Impact Factor:
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Larobina M, Solla R, Megna R
* Quantitative characterization of tumors in PET: a comparison of three texture analysis software packages (250 visite)
European Journal Of Nuclear Medicine And Molecular Imaging, 2019; 46(Suppl1): EPS112-EPS112.
Impact Factor: 7.2
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Barone R, Alaimo S, Messina M, Pulvirenti A, Bastin J, Group MIMIC-A, F , Frye RE, Rizzo (mimic-ag A, Fiumara R, Meli C, Gulisano M, Maugeri F, Prato A, Russo G, Tabbì G
* A Subset of Patients With Autism Spectrum Disorders Show a Distinctive Metabolic Profile by Dried Blood Spot Analyses (156 visite) (PDF 96 visite)
Front Psychiatry (ISSN: 1664-0640linking), 2018 Dec 7; 9: 636-636.
Impact Factor: 2.857
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Romeo V, Maurea S, Cuocolo R, Petretta M, Mainenti PP, Verde F, Coppola M, Dell'Aversana S, Brunetti A
* Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach (172 visite)
J Magn Reson Imaging (ISSN: 1522-2586electronic, 1053-1807linking), 2018 Jul; 48(1): 198-204.
Impact Factor: 1.302
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Monti S, Pacelli R, Cella L, Palma G
* Inter-patient image registration algorithms to disentangle regional dose bioeffects (296 visite) (PDF 154 visite)
Sci Rep (ISSN: 2045-2322linking), 2018 Mar 20; 8(1): 4915-4918.
Impact Factor: 4.259
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Larobina M, Salvatore B, Fonti R, Solla R, Murino L, Del Vecchio S, Pace L
* F-18-FDG PET/CT texture analysis in patients with head and neck cancer (195 visite)
European Journal Of Nuclear Medicine And Molecular Imaging, 2018; 45(Suppl1): PW043-PW043.
Impact Factor: 7.2
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Monti S, Borrelli P, Tedeschi E, Cocozza S, Palma G
* RESUME: Turning an SWI acquisition into a fast qMRI protocol (286 visite)
Plosone (ISSN: 1932-6203, 1932-6203electronic, 1932-6203linking), 2017 Dec 20; 12(12): e0189933-e0189933.
Impact Factor: 2.766
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Ribaldone DG, Dileo I, Pellicano R, Resegotti A, Fagoonee S, Vernero M, Saracco G, Astegiano M
* Severe ulcerative colitis: predictors of response and algorithm proposal for rescue therapy (197 visite)
Irish J Med Sci (ISSN: 0021-1265), 2017 Jul 29; 187(2): 385-392.
Impact Factor: 1.045
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Longo DL, Aime S
* A generalized ratiometric chemical exchange saturation transfer (CEST) MRI approach for mapping renal pH using iopamidol (208 visite)
Magn Reson Med (ISSN: 0740-3194, 1522-2594electronic, 0740-3194linking), 2017 Jul 07; 79(3): 1553-1558.
Impact Factor: 4.082
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Granata D, Amato U, Alfano B
* MRI denoising by nonlocal means on multi-GPU (294 visite)
J Real-Time Image Pr (ISSN: 1861-8200), 2016; N/D: 1-11.
Impact Factor: 2.01
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Palma G, Tedeschi E, Borrelli P, Cocozza S, Russo C, Liu S, Ye Y, Comerci M, Alfano B, Salvatore M, Haacke EM, Mancini M
* A Novel Multiparametric Approach to 3D Quantitative MRI of the Brain (596 visite) (PDF 253 visite)
Plosone (ISSN: 1932-6203, 1932-6203electronic, 1932-6203linking), 2015 Aug 18; 10(8): e0134963-e0134963.
Impact Factor: 3.057
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Pacelli R, Oh JH, Deasy JO, Conson M, D'Avino V, Picardi M, Pressello MC, Boboc G, Battistini R, Donato V, Cella L
* Machine learning-based prediction of late radiation induced lung toxicity in Hodgkin's lymphoma survivors (245 visite)
Radiother Oncol (ISSN: 0167-8140, 1879-0887), 2015 Apr 01; 115: 473-473.
Impact Factor: 4.817
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Borrelli P, Palma G, Comerci M, Alfano B
* Unbiased noise estimation and denoising in parallel magnetic resonance imaging (408 visite) (PDF 282 visite)
Icassp - Ieee International Conference On Acoustics - Speech And Signal Processing - Proceedings (ISSN: 1520-6149, 1520-61499781479928927), 2014 May; 10.1109/ICASSP.201: 1230-1234.
Impact Factor: 0
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Pedicini P, Fiorentino A, Improta G, Nappi A, Salvatore M, Storto G
* Estimate of the accelerated proliferation by protein tyrosine phosphatase (PTEN) over expression in postoperative radiotherapy of head and neck squamous cell carcinoma (276 visite)
Clin Transl Oncol (ISSN: 1699-048x), 2013 Nov; 15(11): 919-924.
Impact Factor: 1.6
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Cammisa M, Correra A, Andreotti G, Cubellis MV
* Identification and analysis of conserved pockets on protein surfaces (1116 visite)
Bmc Bioinformatics (ISSN: 1471-2105), 2013 Apr 22; 14: S9-S9.
Impact Factor: 2.672
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Petretta M, Acampa W, Daniele S, Petretta MP, Nappi C, Assante R, Zampella E, Costanzo P, Perrone-Filardi P, Cuocolo A
* Transient ischemic dilation in SPECT myocardial perfusion imaging for prediction of severe coronary artery disease in diabetic patients (462 visite)
J Nucl Cardiol (ISSN: 1071-3581, 1532-6551, 1532-6551electronic), 2013 Feb; 20(1): 45-52.
Impact Factor: 2.645
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Cesarelli M, Bifulco P, Romano M, Fratini A, D'Addio G, Clemente F
* Spline interpolation to evaluate foveation parameters in Congenital Nystagmus recordings (166 visite)
2013 E Health And Bioengineering Conference, 2013; N/D: N/D-N/D.
Impact Factor: 0
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Cella L, Liuzzi R, Conson M, D'Avino V, Salvatore M, Pacelli R
* Development of multivariate NTCP models for radiation-induced hypothyroidism: A comparative analysis (421 visite) (PDF 216 visite)
Radiat Oncol Radiation Oncology (ISSN: 1748-717x), 2012 Dec 27; 7(1): 224-224.
Impact Factor: 2.107
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Selvan SE, Amato U, Gallivan KA, Qi C, Carfora MF, Larobina M, Alfano B
* Descent algorithms on oblique manifold for source-adaptive ICA contrast (337 visite) (PDF 206 visite)
Ieee Trans Neural Networks Learn Sys (ISSN: 2162-237x, 2162-2388), 2012 Dec; 23(12): 1930-1947.
Impact Factor: 3.766
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Petretta M, Cuocolo A
Prediction models for risk classification in cardiovascular disease (393 visite)
Eur J Nucl Med (ISSN: 1619-7089, 1619-7070, 0340-6997), 2012 Dec; 39(12): 1959-1969.
Impact Factor: 5.114
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Sasaki T, Ito H, Kimura Y, Arakawa R, Takano H, Seki C, Kodaka F, Fujie S, Takahata K, Nogami T, Suzuki M, Fujiwara H, Takahashi H, Nakao R, Fukumura T, Varrone A, Halldin C, Nishikawa T, Suhara T
* Quantification of dopamine transporter in human brain using PET with 18F-FE-PE2I (379 visite)
J Nucl Med (ISSN: 0161-5505, 1535-5667, 1535-5667electronic), 2012 Jul; 53(7): 1065-1073.
Impact Factor: 5.774
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Greco A, Petretta MP, Larobina M, Gargiulo S, Panico M, Nekolla SG, Esposito G, Petretta M, Brunetti A, Cuocolo A
* Reproducibility and accuracy of non-invasive measurement of infarct size in mice with high-resolution PET/CT (365 visite)
J Nucl Cardiol (ISSN: 1532-6551, 1071-3581, 1532-6551electronic), 2012 Jun; 19(3): 492-499.
Impact Factor: 2.847
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Cantisani M, Vitiello M, Falanga A, Finamore E, Galdiero M, Galdiero S
* Peptides complementary to the active loop of porin P2 from Haemophilus influenzae modulate its activity (466 visite)
Int J Nanomed (ISSN: 1178-2013, 1176-9114, 1178-2013electronic), 2012; 7: 2361-2371.
Impact Factor: 3.463
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Alfano B, Comerci M, Larobina M, Prinster A, Hornak JP, Selvan SE, Amato U, Quarantelli M, Tedeschi G, Brunetti A, Salvatore M
* An MRI digital brain phantom for validation of segmentation methods (459 visite) (PDF 652 visite)
Med Image Anal (ISSN: 1361-8415, 1361-8423, 1361-8415linking), 2011 Jun; 15(3): 329-339.
Impact Factor: 4.424
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Ceccarelli M, Speranza A, Grimaldi D, Lamonaca F
* A Computer Vision Approach to Micro-Nucleus automatic detection and surface measurements (377 visite)
Vols 1 3i2mtc (ISSN: 0018-9456), 2010 Sep 10; 59(9): 2383-2390.
Impact Factor: 1.79
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Galdiero S, Falanga A, Vitiello M, Raiola L, Russo L, Pedone C, Isernia C, Galdiero M
* The presence of a single N-terminal histidine residue enhances the fusogenic properties of a Membranotropic peptide derived from herpes simplex virus type 1 glycoprotein (454 visite)
Jbc Papers (ISSN: 1083-351x, 0021-9258, 0021-9258linking), 2010 May 28; 285(22): 17123-17136.
Impact Factor: 5.328
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Slomka PJ, Le Meunier L, Hayes SW, Acampa W, Oba M, Haemer GG, Berman DS, Germano G
* Comparison of Myocardial Perfusion (82)Rb PET Performed with CT- and Transmission CT-Based Attenuation Correction (237 visite)
J Nucl Med (ISSN: 0161-5505, 1535-5667, 1535-5667electronic), 2008 Dec; 49(12): 1992-1998.
Impact Factor: 6.662
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Migliore T, Parrella LS, Caputi A, Silvestri N, Romano R, Pace L, Imbriaco M, Losi MA, Betocchi S
* Pathogenesis of hypertrophic cardiomyopathy. Impact of growth factors on left ventricular anatomy (338 visite)
Minerva Cardioangiol (ISSN: 0026-4725), 2008 Feb; 56(1): 13-20.
Impact Factor: 0.481
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Del Guerra A, Bartoli A, Belcari N, Herbert D, Motta A, Vaiano A, Di Domenico G, Sabba N, Moretti E, Zavattini G, Lazzarotti M, Sensi L, Larobina M
* Performance evaluation of the fully engineered YAP-(S)PET scanner for small animal imaging (255 visite)
Ieee Transactions On Nuclear Science (ISSN: 0018-9499), 2006 Jun; 53(3): 1078-1083.
Impact Factor: 1.497
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Barone V, De Rienzo F, Langella E, Menziani MC, Rega N, Sola M
* A computational protocol to probe the role of solvation effects on the reduction potential of azurin mutants (237 visite)
Proteins (ISSN: 0887-3585, 1097-0134, 1097-0134electronic), 2006 Jan 1; 62(1): 262-269.
Impact Factor: 3.73
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Storto G, Cirillo P, Eufrasia Vicario ML, Pellegrino T, Sorrentino AR, Petretta M, Galasso G, De Sanctis V, Piscione F, Cuocolo A
* Estimation of coronary flow reserve by Tc-99m sestamibi imaging in patients with coronary artery disease: Comparison with the results of intracoronary Doppler technique (356 visite)
J Nucl Cardiol (ISSN: 1071-3581, 1532-6551, 1532-6551electronic), 2004 Nov; 11(6): 682-688.
Impact Factor: 1.849
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Del Guerra A, Bartoli A, Belcari N, Herbert D, Motta A, Vaiano A, Di Domenico G, Sabba N, Moretti E, Zavattini G, Lazzarotti M, Sensi L, Larobina M
* Performance evaluation of the fully engineered YAP-(S)PET scanner for small animal imaging (385 visite)
2004 Ieee Nuclear Science Symposium Conference Record Vols 1 7, 2004; 5: 2990-2994.
Impact Factor: 0
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Vitagliano L, Berisio R, Mastrangelo A, Mazzarella L, Zagari A
* Preferred proline puckerings in cis and trans peptide groups: Implications for collagen stability (481 visite)
Protein Sci (ISSN: 0961-8368, 1469-896xelectronic), 2001 Dec; 10(12): 2627-2632.
Impact Factor: 3.472
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45 Records (39 escludendo Abstract e Conferenze).
Impact factor totale: 126.11 (104.221 escludendo Abstract e Conferenze).
Impact factor a 5 anni totale: 111.288 (103.008 escludendo Abstract e Conferenze).
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