Calibration of myocardial T2 and T1 against iron concentration.

BACKGROUND: The assessment of myocardial iron using T2* cardiovascular magnetic resonance (CMR) has been validated and calibrated, and is in clinical use. However, there is very limited data assessing the relaxation parameters T1 and T2 for measurement of human myocardial iron. METHODS: Twelve hearts were examined from transfusion-dependent patients: 11 with end-stage heart failure, either following death (n=7) or cardiac transplantation (n=4), and 1 heart from a patient who died from a stroke with no cardiac iron loading. Ex-vivo R1 and R2 measurements (R1=1/T1 and R2=1/T2) at 1.5 Tesla were compared with myocardial iron concentration measured using inductively coupled plasma atomic emission spectroscopy. RESULTS: From a single myocardial slice in formalin which was repeatedly examined, a modest decrease in T2 was observed with time, from mean (± SD) 23.7 ± 0.93 ms at baseline (13 days after death and formalin fixation) to 18.5 ± 1.41 ms at day 566 (p<0.001). Raw T2 values were therefore adjusted to correct for this fall over time. Myocardial R2 was correlated with iron concentration [Fe] (R2 0.566, p<0.001), but the correlation was stronger between LnR2 and Ln[Fe] (R2 0.790, p<0.001). The relation was [Fe] = 5081•(T2)-2.22 between T2 (ms) and myocardial iron (mg/g dry weight). Analysis of T1 proved challenging with a dichotomous distribution of T1, with very short T1 (mean 72.3 ± 25.8 ms) that was independent of iron concentration in all hearts stored in formalin for greater than 12 months. In the remaining hearts stored for <10 weeks prior to scanning, LnR1 and iron concentration were correlated but with marked scatter (R2 0.517, p<0.001). A linear relationship was present between T1 and T2 in the hearts stored for a short period (R2 0.657, p<0.001). CONCLUSION: Myocardial T2 correlates well with myocardial iron concentration, which raises the possibility that T2 may provide additive information to T2* for patients with myocardial siderosis. However, ex-vivo T1 measurements are less reliable due to the severe chemical effects of formalin on T1 shortening, and therefore T1 calibration may only be practical from in-vivo human studies

An Effective Fuzzy Recommender System for Fund-raising Management

In the social economics field that deals with the nonprofit organizations (NPOs), the fund-raising is a crucial activity that requires the management of a great number of quantitative and qualitative information regarding Donors and Contacts (i.e., potential donors). This data is normally stored in a structured database (DB) by each NPO, and it is clear that their effective processing by data science methods significantly improves the performances of the fund-raising campaigns. For this reason, the use of rigorous mathematical methods and decision support systems (DSS) has been playing a very important role in this context. The process of fund-raising is very complex and in part different depending on the characteristics of each organization. However, a common important feature is the role of the Contacts, and therefore, the method for turning the Contacts into actual Donors contextualized in the so-called giving pyramid is crucial from a strategic point of view. Recently, a recommender system (RS) has been proposed to optimize the Contacts’ management, by computing the similarity of each Contact with respect to the Donors. In this contribution, we enhance and complete this model by considering both a large DB and two significant extensions of the model, obtaining in this way an effective and whole fuzzy RS. With respect to the DB, the availability of information is effectively exploited. As for the algorithm, a proper similarity measure is defined, based on the specificity of the context. Moreover, a complete estimation of the Contacts’ characteristics is taken into account, by considering not only the frequency but the averaged amount of the gift as well, in the context of a nonparametric approach. The experimental results show the effectiveness of the proposed system