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437 results on '"Alessi, S"'

1. Association between MRI-detected tumor ADC and risk of 5-year biochemical recurrence after radical prostatectomy

Author

Piccinelli, M.L., primary, Mistretta, F.A., additional, Luzzago, S., additional, Alessi, S., additional, Marvaso, G., additional, Lievore, E., additional, Vaccaro, C., additional, Guglielmo, O., additional, Graps, G., additional, Fontana, M., additional, Bianchi, R., additional, Brescia, A., additional, Bottero, D., additional, Ferro, M., additional, Jereczek-Fossa, B.A., additional, Petralia, G., additional, Musi, G., additional, and De Cobelli, O., additional

Published
2024
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3. OP12.05: Patient satisfaction with ultrasound, CT and WB‐DWI/MRI for preoperative ovarian cancer staging: a multicentre prospective survey

Author

Pinto, P., primary, Borcinova, M., additional, Wiesnerova, M., additional, Frühauf, F., additional, Burgetova, A., additional, Mašek, M., additional, Lambert, L., additional, Chiappa, V., additional, Franchi, D., additional, Testa, A. C., additional, Moro, F., additional, Avesani, G., additional, Panico, C., additional, Alessi, S., additional, Pricolo, P., additional, Vigorito, R., additional, Calareso, G., additional, Kocian, R., additional, Slama, J., additional, Fagotti, A., additional, Urbinati, A. M. Vidal, additional, Signorelli, M., additional, Valentin, L., additional, Cibula, D., additional, and Fischerová, D., additional

Published
2023
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4. PO-2112 Radiomics of diffusion-MRI for predicting Gleason Score in Prostate Cancer treated with radiotherapy

Author

Morelli, L., primary, Paganelli, C., additional, Marvaso, G., additional, Annunziata, S., additional, Parrella, G., additional, Pepa, M., additional, Zaffaroni, M., additional, Vicini, M.G., additional, Isaksson, L.J., additional, Corrao, G., additional, Pricolo, P., additional, Alessi, S., additional, Summers, P.E., additional, Cattani, F., additional, De Cobelli, O., additional, Orecchia, R., additional, Petralia, G., additional, Jereczek-Fossa, B.A., additional, and Baroni, G., additional

Published
2023
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6. High-performance prediction models for prostate cancer radiomics

Author

Isaksson, L.J., Repetto, M., Summers, P.E., Pepa, M., Zaffaroni, M., Vincini, M.G., Corrao, G., Mazzola, G.C., Rotondi, M., Bellerba, F., Raimondi, S., Haron, Z., Alessi, S., Pricolo, P., Mistretta, F.A., Luzzago, S., Cattani, F., Musi, G., De Cobelli, O., Cremonesi, M., Orecchia, R., La Torre, D., Marvaso, G., Petralia, G., and Jereczek-Fossa, B.A.

Subjects
Radiomics, Prostate cancer, Gradient boost, Deep learning, Settore MED/24 - Urologia
Published
2023

7. PO-2101 Added Value Of MRI Radiomics To Predict Pathological Status Of Prostate Cancer Patients

Author

Vincini, M.G, Marvaso, G., Isaksson, L.J, Zaffaroni, M., Pepa, M., Corrao, G., Summers, P.E., Repetto, M., Mazzola, G.C., Rotondi, M., Raimondi, S., Gandini, S., Volpe, S., Haron, Z., Alessi, S., Pricolo, P., Mistretta, F.A., Luzzago, S., Cattani, F., Musi, G., De Cobelli, O., Cremonesi, M., Orecchia, R., La Torre, D., Petralia, G., and Jereczek-Fossa, B.A.

Published
2023
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8. OC04.03: Preoperative assessment of non‐resectability in ovarian cancer according to ESGO criteria: a prospective multicentre study using imaging (ISAAC study).

Author

Moro, F., Pinto, P., Chiappa, V., Testa, A., Alcazar, J., Franchi, D., Frühauf, F., Burgetova, A., Mašek, M., Lambert, L., Arraiza, M., Altmanova, D., Avesani, G., Panico, C., Alessi, S., Pricolo, P., Vigorito, R., Calareso, G., Kocian, R., and Slama, J.

Subjects
DIFFUSION magnetic resonance imaging, RECEIVER operating characteristic curves, COMPUTED tomography, WHOLE body imaging, GYNECOLOGIC oncology, CANCER prognosis
Abstract

The article titled "OC04.03: Preoperative assessment of non-resectability in ovarian cancer according to ESGO criteria: a prospective multicentre study using imaging (ISAAC study)" presents the findings of a study conducted in five European gynecological oncology centers between 2018 and 2022. The study aimed to compare the effectiveness of abdominopelvic ultrasound, computed tomography (CT), and whole-body diffusion-weighted Magnetic Resonance Imaging (WB-DWI/MRI) in predicting surgical outcomes for patients with tubo-ovarian cancer. The results showed that ultrasound was non-inferior to CT and WB-DWI/MRI in predicting non-resectability when performed by experienced examiners. The study highlights the potential of ultrasound as a reliable imaging method for preoperative assessment in patients with tubo-ovarian cancer. [Extracted from the article]

Published
2024
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9. OC04.01: Prediction of non‐resectability in ovarian cancer patients using peritoneal cancer index: a prospective multicentre study using imaging (ISAAC study).

Author

Pinto, P., Moro, F., Chiappa, V., Testa, A.C., Franchi, D., Alcazar, J., Frühauf, F., Burgetova, A., Mašek, M., Lambert, L., Altmanova, D., Arraiza, M., Avesani, G., Panico, C., Alessi, S., Pricolo, P., Vigorito, R., Calareso, G., Kocian, R., and Slama, J.

Subjects
DIFFUSION magnetic resonance imaging, COMPUTED tomography, WHOLE body imaging, PERITONEAL cancer, CANCER patients, NEOADJUVANT chemotherapy
Abstract

This article presents the findings of a European multicentric observational cohort study that aimed to evaluate the performance of the peritoneal cancer index (PCI) using different imaging methods in assessing peritoneal carcinomatosis and predicting non-resectability in advanced tubo-ovarian cancer patients. The study compared the use of ultrasound, computed tomography (CT), and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) in calculating the PCI score. The results showed that ultrasound was non-inferior to CT in predicting non-resectability, and it was the best imaging method for determining preoperative PCI when performed by experienced examiners in dedicated oncological centers. [Extracted from the article]

Published
2024
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10. A novel nomogram predicting lymph node invasion among patients with prostate cancer: The importance of extracapsular extension at multiparametric magnetic resonance imaging

Author

Di Trapani, E, Luzzago, S, Peveri, G, Catellani, M, Ferro, M, Cordima, G, Mistretta, F, Bianchi, R, Cozzi, G, Alessi, S, Matei, D, Bagnardi, V, Petralia, G, Musi, G, De Cobelli, O, Di Trapani E., Luzzago S., Peveri G., Catellani M., Ferro M., Cordima G., Mistretta F. A., Bianchi R., Cozzi G., Alessi S., Matei D. V., Bagnardi V., Petralia G., Musi G., De Cobelli O., Di Trapani, E, Luzzago, S, Peveri, G, Catellani, M, Ferro, M, Cordima, G, Mistretta, F, Bianchi, R, Cozzi, G, Alessi, S, Matei, D, Bagnardi, V, Petralia, G, Musi, G, De Cobelli, O, Di Trapani E., Luzzago S., Peveri G., Catellani M., Ferro M., Cordima G., Mistretta F. A., Bianchi R., Cozzi G., Alessi S., Matei D. V., Bagnardi V., Petralia G., Musi G., and De Cobelli O.

Abstract

Purpose: To develop a novel risk tool that allows the prediction of lymph node invasion (LNI) among patients with prostate cancer (PCa) treated with robot-assisted radical prostatectomy (RARP) and extended pelvic lymph node dissection (ePLND). Methods: We retrospectively identified 742 patients treated with RARP + ePLND at a single center between 2012 and 2018. All patients underwent multiparametric magnetic resonance imaging (mpMRI) and were diagnosed with targeted biopsies. First, the nomogram published by Briganti et al. was validated in our cohort. Second, three novel multivariable logistic regression models predicting LNI were developed: (1) a complete model fitted with PSA, ISUP grade groups, percentage of positive cores (PCP), extracapsular extension (ECE), and Prostate Imaging Reporting and Data System (PI-RADS) score; (2) a simplified model where ECE score was not included (model 1); and (3) a simplified model where PI-RADS score was not included (model 2). The predictive accuracy of the models was assessed with the receiver operating characteristic-derived area under the curve (AUC). Calibration plots and decision curve analyses were used. Results: Overall, 149 patients (20%) had LNI. In multivariable logistic regression models, PSA (OR: 1.03; P= 0.001), ISUP grade groups (OR: 1.33; P= 0.001), PCP (OR: 1.01; P= 0.01), and ECE score (ECE 4 vs. 3 OR: 2.99; ECE 5 vs. 3 OR: 6.97; P< 0.001) were associated with higher rates of LNI. The AUC of the Briganti et al. model was 74%. Conversely, the AUC of model 1 vs. model 2 vs. complete model was, respectively, 78% vs. 81% vs. 81%. Simplified model 1 (ECE score only) was then chosen as the best performing model. A nomogram to calculate the individual probability of LNI, based on model 1 was created. Setting our cut-off at 5% we missed only 2.6% of LNI patients. Conclusions: We developed a novel nomogram that combines PSA, ISUP grade groups, PCP, and mpMRI-derived ECE score to predict the probability of LNI at fin

Published
2021

11. PO-1360 Nutritional and inflammatory status as predictive biomarkers in oligorecurrent PCa (RADIOSA TRIAL)

Author

Zaffaroni, M., primary, Marvaso, G., additional, Corrao, G., additional, Gandini, S., additional, Pepa, M., additional, Vincini, M.G., additional, Zerini, D., additional, Castronovo, F.M., additional, Augugliaro, M., additional, Cattani, F., additional, Mistretta, F.A., additional, Luzzago, S., additional, Musi, G., additional, Alessi, S., additional, Fodor, C., additional, Petralia, G., additional, Pravettoni, G., additional, De Cobelli, O., additional, Orecchia, R., additional, and Jereczek-Fossa, B.A., additional

Published
2022
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12. PO-1772 Radiomic feature relevance in the prediction of pathological features of prostate cancer

Author

Isaksson, L.J., primary, Summers, P.E., additional, Pepa, M., additional, Zaffaroni, M., additional, Vincini, M.G., additional, Corrao, G., additional, Mazzola, G.C., additional, Rotondi, M., additional, Raimondi, S., additional, Gandini, S., additional, Volpe, S., additional, Haron, Z., additional, Alessi, S., additional, Pricolo, P., additional, Mistretta, F.A., additional, Luzzago, S., additional, Cattani, F., additional, Musi, G., additional, De Cobelli, O., additional, Cremonesi, M., additional, Orecchia, R., additional, Marvaso, G., additional, Petralia, G., additional, and Jereczek-Fossa, B.A., additional

Published
2022
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13. MO-0551 Short-term RT for early PCa with concomitant boost to the DIL (phase II trial AIRC-IG-13218)-updates

Author

Corrao, G., primary, Marvaso, G., additional, Pepa, M., additional, Zaffaroni, M., additional, Vincini, M.G., additional, Bellerba, F., additional, Gandini, S., additional, Volpe, S., additional, Rojas, D.P., additional, Zerini, D., additional, Fodor, C.I., additional, Pricolo, P., additional, Alessi, S., additional, Petralia, G., additional, Mistretta, F.A., additional, Cambria, R., additional, Cattani, F., additional, De Cobelli, O., additional, Orecchia, R., additional, and Jereczek-Fossa, B.A., additional

Published
2022
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14. MO-0385 Added value of MRI radiomics to predict pathological status of prostate cancer patients

Author

Marvaso, G., primary, Pepa, M., additional, Isaksson, L.J., additional, Summers, P.E., additional, Zaffaroni, M., additional, Vincini, M.G., additional, Corrao, G., additional, Mazzola, G.C., additional, Rotondi, M., additional, Raimondi, S., additional, Gandini, S., additional, Volpe, S., additional, Haron, Z., additional, Alessi, S., additional, Pricolo, P., additional, Mistretta, F.A., additional, Luzzago, S., additional, Cattani, F., additional, Musi, G., additional, De Cobelli, O., additional, Cremonesi, M., additional, Orecchia, R., additional, Petralia, G., additional, and Jereczek-Fossa, B.A., additional

Published
2022
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15. A novel nomogram to identify candidates for active surveillance amongst patients with International Society of Urological Pathology (ISUP) Grade Group (GG) 1 or ISUP GG2 prostate cancer, according to multiparametric magnetic resonance imaging findings

Author

Luzzago, S, de Cobelli, O, Cozzi, G, Peveri, G, Bagnardi, V, Catellani, M, Di Trapani, E, Mistretta, F, Pricolo, P, Conti, A, Alessi, S, Marvaso, G, Ferro, M, Matei, D, Renne, G, Jereczek-Fossa, B, Petralia, G, Musi, G, Luzzago S., de Cobelli O., Cozzi G., Peveri G., Bagnardi V., Catellani M., Di Trapani E., Mistretta F. A., Pricolo P., Conti A., Alessi S., Marvaso G., Ferro M., Matei D. -V., Renne G., Jereczek-Fossa B. A., Petralia G., Musi G., Luzzago, S, de Cobelli, O, Cozzi, G, Peveri, G, Bagnardi, V, Catellani, M, Di Trapani, E, Mistretta, F, Pricolo, P, Conti, A, Alessi, S, Marvaso, G, Ferro, M, Matei, D, Renne, G, Jereczek-Fossa, B, Petralia, G, Musi, G, Luzzago S., de Cobelli O., Cozzi G., Peveri G., Bagnardi V., Catellani M., Di Trapani E., Mistretta F. A., Pricolo P., Conti A., Alessi S., Marvaso G., Ferro M., Matei D. -V., Renne G., Jereczek-Fossa B. A., Petralia G., and Musi G.

Abstract

Objectives: To develop a novel nomogram to identify candidates for active surveillance (AS) that combines clinical, biopsy and multiparametric magnetic resonance imaging (mpMRI) findings; and to compare its predictive accuracy to, respectively: (i) Prostate Cancer Research International: Active Surveillance (PRIAS) criteria, (ii) Johns Hopkins (JH) criteria, (iii) European Association of Urology (EAU) low-risk classification, and (iv) EAU low-risk or low-volume with International Society of Urological Pathology (ISUP) Grade Group (GG) 2 classification. Patients and Methods: We selected 1837 patients with ISUP GG1 or GG2 prostate cancer (PCa), treated with radical prostatectomy (RP) between 2012 and 2018. The outcome of interest was the presence of unfavourable disease (i.e., clinically significant PCa [csPCa]) at RP, defined as: ISUP GG (Formula presented.) 3 and/or pathological T stage (pT) ≥3a and/or pathological N stage (pN) 1. First, logistic regression models including PRIAS, JH, EAU low-risk, and EAU low-risk or low-volume ISUP GG2 binary classifications (not eligible vs eligible) were used. Second, a multivariable logistic regression model including age, prostate-specific antigen density (PSA-D), ISUP GG, and the percentage of positive cores (Model 1) was fitted. Third, Prostate Imaging-Reporting and Data System (PI-RADS) score (Model 2), extracapsular extension (ECE) score (Model 3) and PI-RADS + ECE score (Model 4) were added to Model 1. Only variables associated with higher csPCa rates in Model 4 were retained in the final simplified Model 5. The area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analyses were used. Results: Of the 1837 patients, 775 (42.2%) had csPCa at RP. Overall, 837 (47.5%), 986 (53.7%), 348 (18.9%), and 209 (11.4%) patients were eligible for AS according to, respectively, the EAU low-risk, EAU low-risk or low-volume ISUP GG2, PRIAS, and JH criteria. The proportion of csPCa amongst the E

Published
2020

20. Conditional survival of patients with low-risk prostate cancer: Temporal changes in active surveillance permanence according to risk stratification

Author

Mistretta, F., primary, Luzzago, S., additional, Piccinelli, M.L., additional, Alessi, S., additional, Cozzi, G., additional, Cioffi, A., additional, Fontana, M., additional, Bottero, D., additional, Marvaso, G., additional, Ferro, M., additional, Matei, D.V., additional, Jereczek Fossa, B.A., additional, Petralia, G., additional, Musi, G., additional, and De Cobelli, O., additional

Published
2022
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28. Comparison of automated segmentation techniques for magnetic resonance images of the prostate

Author

Pepa, M., primary, Isaksson, J. Lars, additional, Zaffaroni, M., additional, Summers, P.E., additional, Marvaso, G., additional, Raimondi, S., additional, Gandini, S., additional, Volpe, S., additional, Rojas, D.P., additional, Zerini, D., additional, Haron, Z., additional, Pricolo, P., additional, Alessi, S., additional, Mistretta, F.A., additional, Luzzago, S., additional, Cattani, F., additional, De Cobelli, O., additional, Cassano, E., additional, Cremonesi, M., additional, Bellomi, M., additional, Orecchia, R., additional, Petralia, G., additional, and Jereczek-Fossa, B.A., additional

Published
2021
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31. OC04.02: Prediction of non‐resectability in ovarian cancer using the predictive index value score: a prospective multicentre study using imaging (ISAAC study).

Author

Moro, F., Pinto, P., Chiappa, V., Testa, A., Alcazar, J., Franchi, D., Frühauf, F., Burgetova, A., Mašek, M., Lambert, L., Arraiza, M., Altmanova, D., Avesani, G., Panico, C., Alessi, S., Pricolo, P., Vigorito, R., Calareso, G., Roman, K., and Slama, J.

Subjects
DIFFUSION magnetic resonance imaging, RECEIVER operating characteristic curves, COMPUTED tomography, MAGNETIC resonance imaging, SMALL intestine, CONTRAST-enhanced magnetic resonance imaging
Abstract

This article discusses a study conducted in European gynecological oncology centers to evaluate the performance of different imaging methods in predicting non-resectability in patients with suspected tubo-ovarian cancer. The study used a laparoscopy-based scoring system called the Predictive Index Value (PIV) score, which assesses the presence of disease in six predefined intra-abdominal sites. The imaging methods evaluated were ultrasound (US), contrast-enhanced computed tomography (CT), and whole-body magnetic resonance imaging with diffusion-weighted sequence (WB-DWI/MRI). The results showed that all three imaging methods had similar performance in predicting non-resectable tumors, with US being a viable alternative to MRI or CT when performed by experienced examiners in dedicated oncological centers. [Extracted from the article]

Published
2024
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32. The immunohistochemical expression of leptin in lymph node metastasis from laryngeal squamous cell carcinoma (SCC)

Author

Gargano R, Verro ., D'Alessi S, Florena AM, Galletti F, Galletti B, Greco G, Ferrara S, Gargano R, Verro ., D'Alessi S, Florena AM, Galletti F, Galletti B, Greco G, and Ferrara S

Subjects
Leptin, Settore MED/31 - Otorinolaringoiatria, Adipokine, Head and neck tumor, Predictive factor
Abstract

Introduction: Leptin is a proteohormone produced predominantly by white adipocytes and primarily known for its key role in the control of food intake and sense of satiety. From its discover leptin has been found in different body districts, involved in always new functions and processes. In the last years numerous relationships between leptin and cancer has been found. The aim of this study is to test the leptin positivity in human primitive laryngeal squamous cell carcinoma (SCC) and in its lymph node metastasis. Materials and methods: Leptin positivity was detected by immunohistochemical analysis on pathological samples from 18 patients subjected to laryngectomy and neck dissection for SCC. Results: During the study we pointed out a statistically significant relationship (p < 0.05) between leptin positivity levels and tumor differentiation grade, in particular we observed that a decrease in tumor leptin production correlates with higher level of cancer histological dedifferentiation. Conclusion: Our research on leptin expression in laryngeal squamous neoplastic pathology is aimed to the attempt of establishing a more precise patient risk stratification thanks to a new marker able to give a contribution to the identification of patient with poor prognosis and at risk of failure of actual standard therapy.

Published
2020

35. Outcomes of serial multiparametric magnetic resonance imaging in patients managed with Active Surveillance for prostate cancer

Author

Luzzago, S., primary, Piccinelli, M.L., additional, Fontana, M., additional, Botticelli, F.M.G., additional, Cozzi, G., additional, Mistretta, F.A., additional, Catellani, M., additional, Bianchi, R., additional, Cioffi, A., additional, Di Trapani, E., additional, Pricolo, P., additional, Alessi, S., additional, Brescia, A., additional, Ferro, M., additional, Matei, D.V., additional, Petralia, G., additional, Musi, G., additional, and de Cobelli, O., additional

Published
2021
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36. Active surveillance for prostate cancer: comparison between incidental tumors vs. tumors diagnosed at prostate biopsies

Author

Piccinelli, M.L., primary, Luzzago, S., additional, Fontana, M., additional, Botticelli, F.M.G., additional, Mistretta, F.A., additional, Catellani, M., additional, Di Trapani, E., additional, Bianchi, R., additional, Cozzi, G., additional, Cioffi, A., additional, Pricolo, P., additional, Alessi, S., additional, Cordima, G., additional, Ferro, M., additional, Matei, D.V., additional, Petralia, G., additional, Musi, G., additional, and de Cobelli, O., additional

Published
2021
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37. PO-1935 CLINICAL OUTCOMES AND RADIO-BIOLOGICAL FEATURES CORRELATION IN EARLY PCa: AN EXPLORATORY ANALYSIS

Author

Corrao, G., primary, Marvaso, G., additional, Zaffaroni, M., additional, Fodor, C.I., additional, Volpe, S., additional, Bergamaschi, L., additional, Zerini, D., additional, Vingiani, A., additional, Petralia, G., additional, Alessi, S., additional, Pricolo, P., additional, Renne, G., additional, Orecchia, R., additional, and Jereczek-Fossa, B.A., additional

Published
2021
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38. PD-0930 Comparison of automated segmentation techniques for magnetic resonance images of the prostate

Author

Pepa, M., primary, Isaksson, J.L., additional, Zaffaroni, M., additional, Summers, P.E., additional, Marvaso, G., additional, Lo Presti, G., additional, Raimondi, S., additional, Gandini, S., additional, Volpe, S., additional, Rojas, D.P., additional, Zerini, D., additional, Haron, Z., additional, Pricolo, P., additional, Alessi, S., additional, Mistretta, F.A., additional, Luzzago, S., additional, Cattani, F., additional, De Cobelli, O., additional, Cassano, E., additional, Cremonesi, M., additional, Bellomi, M., additional, Orecchia, R., additional, Petralia, G., additional, and Jereczek-Fossa, B.A., additional

Published
2021
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39. A novel nomogram predicting lymph node invasion among patients with prostate cancer: The importance of extracapsular extension at multiparametric magnetic resonance imaging

Author

Di Trapani, E., primary, Luzzago, S., additional, Peveri, G., additional, Catellani, M., additional, Ferro, M., additional, Cordima, G., additional, Mistretta, F.A., additional, Bianchi, R., additional, Cozzi, G., additional, Alessi, S., additional, Matei, D.V., additional, Bagnardi, V., additional, Petralia, G., additional, Musi, G., additional, and De Cobelli, O., additional

Published
2021
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42. Influence of polymer electrospun nanofibers on thermal properties of epoxy resins

Author

Alessi S., Di Filippo M., Dispenza C., Alessi S., Di Filippo M., and Dispenza C.

Subjects
thermal propertie, epoxy resins, electrospinning
Abstract

Electrospinning of polymers has gained surging interest in the last decades due to its wide range of applications in different fields, such as sensors, electronic devices, separation systems, biomedical materials. Still there are only few reports on the use of these nanofibers as reinforcement in polymer composites. In this paper, solution electrospinning was employed to produce nanofibrous mats impregnating two epoxy resins to form “monolayer“systems, with the aim to study the influence of the nanofibers on both the curing behaviour and the morphology of the resin systems. Three polymers were chosen for producing electrospun mats, a polysulfone (PSF), a polyamide Nylon 6,6 (Ny66) and a polyacrilonitrile (PAN). The nanofibrous mats were employed to produce mat/epoxy monolayers by soaking the mat in two different epoxy resin systems, one in lab-synthesized-high performance, and the other commercial-low performance. The results show a different extent of swelling of the electronspun mats, as derived by morphological analysis. The observation of the fractured surfaces also indicates the formation of several fracture planes or phase separation phenomena, suggesting the possibility of dissipation of fracture energy by the epoxy/mat nanocomposites. Additionally, for all resin/mat arrangements, thermal analysis indicates no significant interference of the mat with the cure reactions of the resins and only slight changes of the glass transition temperatures.

Published
2019

49. PO-1197: Short-term high precision RT for early PCa with SIB to the DIL: QoL assessment (AIRC IG 13218)

Author

Marvaso, G., primary, Gugliandolo, S.G., additional, Corrao, G., additional, Volpe, S., additional, Riva, G., additional, Rojas, D.P., additional, Zerini, D., additional, Pepa, M., additional, Pricolo, P., additional, Alessi, S., additional, Petralia, G., additional, Cattani, F., additional, De Cobelli, O., additional, Orecchia, R., additional, and Jereczek-Fossa, B.A., additional

Published
2020
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50. PO-1576: Assessment of mpMRI-based radiomics tools in PCa for cancer aggressiveness prediction, AIRC IG-

Author

Pepa, M., primary, Gugliandolo, S.G., additional, Isaksson, L.J., additional, Marvaso, G., additional, Raimondi, S., additional, Botta, F., additional, Gandini, S., additional, Ciardo, D., additional, Volpe, S., additional, Riva, G., additional, Rojas, D.P., additional, Zerini, D., additional, Pricolo, P., additional, Alessi, S., additional, Petralia, G., additional, Summers, P., additional, Mistretta, A.F., additional, Luzzago, S., additional, Cattani, F., additional, De Cobelli, O., additional, Cassano, E., additional, Cremonesi, M., additional, Bellomi, M., additional, Orecchia, R., additional, and Jereczek-Fossa, B.A., additional

Published
2020
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