Clinical Collaborations

In this page some clinical applications carried out within scientific collaborations with clinicians and/or scientists from different fields are presented.

 

  • Optical measures for non invasive screening

Breast density is a strong independent risk factor for breast cancer. At present it is assessed through mammography, thus implying the use of ionizing radiation. The ability to non-invasively identify high-risk women could allow earlier design of personalized screening paths and preventive interventions. Optical techniques can provide functional and structural information on tissue in absolutely non-invasive way.

We study the statistical power in predicting high risk for developing breast cancer using optical spectroscopy data that assess both tissue composition in terms of key constituents and scattering parameters related to the microscopic structure of tissue and specifically to breast density.

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Related  Publications & Pre Prints

  1. Taroni, P., Quarto,G., Pifferi, A., Ieva, F., Paganoni, A.M., Abbate, F., Balestreri, N., Menna, S., Cassano, E., Cubeddu, R., “Optical Identification of Subjects at High Risk for Developing Breast Cancer” Journal of Biomedical Optics Letters. 18 (6) 2013.

 

  • Statistical regression method for the analysis of fNIRS data

Functional near-infrared spectroscopy (fNIRS) is an optical technique able to monitor the cerebral hemodynamic at the cortical level. Exploiting the low absorption of biological tissues in the red and near-infrared wavelengths fNIRS can investigate the human head down to some centimeters under the skin, through different tissues, until reaching the cerebral cortex. Because of the fact that oxy and deoxyhemoglobin (O2Hb and HHb) are the main chromophores at this wavelength range, fNIRS can provide a direct measure of these two blood compounds, allowing a better comprehension of the blood dynamics during a functional activation. This is a powerful advantage, in contrast with the information given by the gold standard neuroimaging technique, the functional magnetic resonance imaging (fMRI), where the blood oxygen level dependent (BOLD) signal is only nonlinearly linked to the oxygen level in the brain.

We fit statistical regression models able to detect and explain, both on simulated and real data the functional response of activated/non-activated brain channels.

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From left to right: row signals of oxy haemoglobin over time for a single patient (panel 1); exclusion criterion for activated channels, based on the relationship among mean AUC and AUC standard deviation of different channels (panel 2); boxplots of AUC of different channels (panel 3); p-values indicating activation of the channels (panel 4).

Related Publications & Pre Prints

  1. Bonomini V., Re R., Zucchelli L., Ieva F., Spinelli L., Contini D., Paganoni A.M., Torricelli A. (2015) A new linear regression method for statistical analysis of fNIRS data. Biomedical Optics Express, 6 (2): 616-630  doi:10.1364/BOE.6.000615
  • Models for Interpretation of differences in serial test results from individuals

Population-based reference intervals have very limited value for the interpretation of laboratory results when analytes display high biological individuality. In these cases, the longitudinal evaluation of individual results using the Reference Change Value (RCV) is the recommended approach. However, the traditional model for RCV calculation requires a Gaussian frequency distribution of data and risks to overestimate the parameter if a correlation between within-subject serial measurements is present.

We study, propose and validate an alternative nonparametric statistical model for interpretation of differences in serial results from an individual, overcoming data distribution and correlation issues.

Figure 1 AFigure 2 AFigure 3 A

Related Publications & Pre Prints

  1. Braga, F.,  Ferraro, S., Ieva, F., Paganoni, A.M., Panteghini, M. (2015) A new robust statistical model for interpretation of differences in serial test results from an individual. Clinical Chemistry and Laboratory Medicine, 53(5): 815-822
  • Evaluation of the expression of cyto-chemokine profiles

Aim of the ongoing scientific program is the evaluation of the expression of cyto-chemokine profiles in different pathologies such as cervical neoplastic lesions and ST-segment elevation myocardial infarction. Data are explored and analyzed by means of different statistical methodologies for pattern recognition , parametric and non parametric classification, aiming at the detection of some cyto-chemokines as prognostic factors for the pathology under study.

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Related Publications & Pre Prints

  1. Taroni, P., Paganoni, A.M., Ieva,  F., Pifferi, A., Quarto, G., Abbate, F., Cassano,  E., Cubeddu, R. (2016) Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study, Scientific Reports. In press
  2. De Monte, L., Woermann, S., Brunetto,  E., Heltai, S., Magliacane, G., Reni, M.,  Paganoni, A.M., Recalde, H., Mondino, A., Aleotti, F., Balzano, G., Algul, H., Doglioni, C., Protti, M.P. (2016) Basophils recruitment into tumor draining lymph nodes correlates with predominant Th2 inflammation and reduced survival in pancreatic cancer, Cancer Research. 76 (7), 1792-1803
  3. Braga, F., Ferraro, S., Ieva, F., Paganoni, A. M., Panteghini, M. (2015) A new robust statistical model for interpretation of differences in serial test results from an individual, Clinical Chemistry and Laboratory Medicine, In press
  4. Bonomini V., Re R., Zucchelli L., Ieva F., Spinelli L., Contini D., Paganoni A.M., Torricelli A. (2015) A new linear regression method for statistical analysis of fNIRS data, Biomedical Optics Express, Vol. 6, No. 2, 615-630
  5. Di Lullo, G., Ieva, F., Longhi, R., Paganoni, A.M., Protti, M.P. (2012) Estimating point and interval frequency of antigen-specific CD4+ T cells based on short in vitro expansion and improved Poisson distribution analysis, PLos One. 7(8), e42340.
  6. Ammirati, E., Cannistraci, C.V., Cristell, N.A., Vecchio, V., Palini, A.G., Tornvall, P., Paganoni, A.M., Miendlarzewska, E.A., Sangalli, L.M., Monello, A., Pernow, J., Björnstedt Bennermo, M., Marenzi, G., Hu, D., Uren, N.G., Ravasi, T., Cianflone, D. Manfredi, A., Maseri, A. (2012) Identification and Predictive Value of IL6(+)IL10(+)Cytokine Patterns in ST-Elevation Acute Myocardial Infarction, Circulation Research. 111, 1336-1348
  7. de Lalla, C., Rinaldi, A., Montagna, D., Azzimonti, L., Bernardo, M.E., Sangalli, L.M., Paganoni, A.M., Maccario, R., Di Cesare-Merlone, A., Zecca, M., Locatelli, F., Dellabona, P., Casorati, G. (2011) Invariant Natural Killer T-cell reconstitution in pediatric leukemia patients given HLA-haploidentical stem cell transplantation defines distinct CD4+ and CD4- subset dynamics and associates with the remission state, The Journal of Immunology. 186, 7, 4490-4499.
  8. Seresini, S., Origoni, Caputo, L., Lillo, F., Longhi, R., Vantini, S., Paganoni, A.M., Protti, M. P. (2010) CD4+ T cells against human papilloma virus-18 E7 in patients with high-grade cervical lesions associate with the absence of the virus in the cervix, Immunology, 131, 1, 89-98.
  9. Seresini, S., Origoni, M., Lillo, F., Caputo, L. , Paganoni, A.M., Vantini, S., Longhi, R., Taccagni, G., Ferrari, A., Secchi, P., Protti, M.P., (2007) IFN-g Produced by Human Papilloma Virus-18 E6 Specific CD4+ T Cells Predicts the Clinical Outcome after Surgery in Patients with High-Grade Cervical Lesions, The Journal of Immunology, 179, 7176-7183.

 

Theses

Dr. Jacopo Cotta Ramusino, MD Thesis in Mathematical Engineering (2015)
Statistical analysis of optical data for tumour diagnosis

Dr. Viola Bonomini, MD Thesis in Mathematical Engineering (2014)
Statistical analysis of fNIRS data: an application to cerebral hemodinamic activity

Dr. Paolo Zanini, MD Thesis in Mathematical Engineering (2009)
Modelli statistici per lo studio della Fibrillazione Atriale