Quaderni MOX
Pubblicazioni
del Laboratorio di Modellistica e Calcolo Scientifico MOX. I lavori riguardano prevalentemente il campo dell'analisi numerica, della statistica e della modellistica matematica applicata a problemi di interesse ingegneristico. Il sito del Laboratorio MOX è raggiungibile
all'indirizzo mox.polimi.it
Trovati 1251 prodotti
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77/2022 - 31/10/2022
Ziarelli, G.; Dede', L.; Parolini, N.; Verani, M.; Quarteroni, A.
Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: an application to the Italian scenario. | Abstract | | In the context of SARS-CoV-2 pandemic, mathematical modelling has played a fundamental role for making forecasts, simulating scenarios and evaluating the impact of preventive political, social and pharmaceutical measures. Optimal control theory can be a useful tool based on solid mathematical bases to plan the vaccination campaign in the direction of eradicating the pandemic as fast as possible. The aim of this work is to explore the optimal prioritisation order for planning vaccination campaigns able to achieve specific goals, as the reduction of the amount of infected, deceased and hospitalized in a fixed time frame, among age classes. For this purpose, we introduce an age stratified SIR-like epidemic compartmental model settled in an abstract framework for modelling two-doses vaccination campaigns and conceived with the description of COVID19 disease. Overall, we formalize an optimal control framework adopting the model as state problem by acting on the administrations of vaccine-doses. An extensive campaign of numerical tests, featured in the Italian scenario and calibrated on available data from Dipartimento di Protezione Civile Italiana, shows that the presented framework can be a valuable tool to support the planning of vaccination campaigns minimizing specific goals. |
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76/2022 - 25/10/2022
Spreafico, M.; Ieva, F.; Fiocco, M.
Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models | Abstract | | Due to the presence of multiple types of adverse events with different levels of severity, the analysis of longitudinal toxicity data is a difficult task in cancer studies. In this work, a novel approach based on latent Markov models and compositional data techniques is proposed. The latent status of interest is the Latent Overall Toxicity (LOTox) condition of each patient. The main objectives are to identify different latent states of overall toxicity burden and to investigate the evolution of individual toxicity risk during cancer treatment. This methodology is applied to osteosarcoma treatment data to provide novel techniques that may support medical decisions in childhood cancer therapy. |
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75/2022 - 19/10/2022
Rea, F.; Savaré, L; Franchi, M.; Corrao, G; Mancia, G
Adherence to Treatment by Initial Antihypertensive Mono and Combination Therapies | Abstract | | BACKGROUND
Aim of our study was to compare adherence to antihypertensive drug
therapy between newly treated patients in whom monotherapy or a
2-drug single-pill combination (SPC) was initially dispensed.
METHODS
The 63,448 residents of Lombardy Region (Italy), aged 40–80 years,
who were newly treated with antihypertensive drugs during 2016,
were identified and followed for 1 year after the first prescription. The
outcome of interest was adherence to drug therapy that was measured
according to the “proportion of days covered” (PDC) criterion, i.e.,
the ratio between the number of days in which the drug was available
and the days of follow-up. Patients who had a PDC >75% and
<25% were defined as highly and poorly adherent to drug therapy,
respectively. Log-binomial regression models were fitted to compare
the propensity to treatment adherence between the initial therapeutic
strategies, after adjusting for baseline demographic and clinical
covariates.
RESULTS
About 46% and 17% of patients showed high and poor adherence, respectively.
Compared with patients under initial monotherapy (85%),
those who were initially treated with a SPC (15%) had higher propensity
to be highly adherent and a lower propensity to be poorly adherent
to antihypertensive treatment (risk ratio: 1.18, 95% confidence interval
1.16–1.21; 0.42, 0.39–0.45, respectively). This was the case regardless the
sex, the age, the patient clinical status, and with almost any type of SPC.
CONCLUSIONS
In a real-life setting, patients who were initially prescribed a 2-drug
SPC exhibited more frequently a good adherence to antihypertensive
treatment than those starting with a single drug.
NOTE: This work has been partially carried out while one of the authors (L. Savarè) was affiliated with MOX Laboratory |
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74/2022 - 19/10/2022
Salvador, M.; Regazzoni, F.; Dede', L.; Quarteroni, A.
Fast and robust parameter estimation with uncertainty quantification for the cardiac function | Abstract | | Parameter estimation and uncertainty quantification are crucial in computational cardiology, as they enable the construction of digital twins that faithfully replicate the behavior of physical patients. Robust and efficient mathematical methods must be designed to fit many model parameters starting from a few, possibly non-invasive, noisy observations. Moreover, the effective clinical translation requires short execution times and a small amount of computational resources. In the framework of Bayesian statistics, we combine Maximum a Posteriori estimation and Hamiltonian Monte Carlo to find an approximation of model parameters and their posterior distributions. To reduce the computational effort, we employ an accurate Artificial Neural Network surrogate of 3D cardiac electromechanics model coupled with a 0D cardiocirculatory model. Fast simulations and minimal memory requirements are achieved by using matrix-free methods, automatic differentiation and automatic vectorization. Furthermore, we account for the surrogate modeling error and measurement error. We perform three different in silico test cases, ranging from the ventricular function to the entire cardiovascular system, involving whole-heart mechanics, arterial and venous circulation. The proposed method is robust when high levels of signal-to-noise ratio are present in the quantities of interest in combination with a random initialization of the model parameters in suitable intervals. As a matter of fact, by employing a single central processing unit on a standard laptop and a few hours of computations, we attain small relative errors for all model parameters and we estimate posterior distributions that contain the true values inside the 90% credibility regions. With these benefits, our approach meets the requirements for clinical exploitation, while being compliant with Green Computing practices. |
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73/2022 - 19/10/2022
Spreafico, M.; Gasperoni, F.; Barbati, G.; Ieva, F.; Scagnetto, A.; Zanier, L.; Iorio, A.; Sinagra, G.; Di Lenarda, A.
Adherence to disease-modifying therapy in patients hospitalized for HF: findings from a community-based study | Abstract | | Background. Previous studies of polypharmacy (PP) for Heart Failure (HF) patients were based on surveys of highly selected populations and methods for estimating adherence in PP have widely varied. Moreover, adherence has been evaluated only in terms of physician’s prescriptions.
Aim. Describe pharmacological guidelines compliance in a real-world HF cohort based on effective patient’s drugs purchases and estimate the impact of PP adherence on survival.
Methods and Results. Between 2009 and 2015, patients hospitalized with a HF diagnosis and with at least one purchase post-discharge of angiotensin-converting enzyme inhibitors, ACE, or angiotensin receptor blockers, ARB, or beta-blocking, BB, or anti-aldosterone agents, AA, were recruited from an administrative database. Adherence was evaluated using two measures (Proportion of Days Covered, PDC, Medical Possession Ratio, MPR). A new measure of PP adherence was introduced, the Patient Adherence Indicator (PAI). A Cox model was estimated to quantify impact of PAI on survival. The most common drug combination was ACE/ARB and BB (58.1%) and the less frequent was ARB and AA (11.5%). Triplet ACE/ARB, BB and AA was purchased at least once by 27.3% of patients. Mean daily dosages were inferior to the target dosages for all drugs. From 41% to 58% of patients showed a poor poly-adherence measured by the PAI index.
Conclusions. Patients assume daily doses lower than the target dosages. PDC and MPR showed differences related to the specific drugs classes but were not prognostically different when combined into the PAI index. Adjusting for patient’s characteristics and intermediate events, PP non-adherence was significantly associated with lower survival. |
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72/2022 - 19/10/2022
Spreafico, M.; Ieva, F.; Arlati, F.; Capello, F.; Fatone, F.; Fedeli, F.; Genalti, G.; Anninga, J.; Gelderblom, H.; Fiocco, M.
Novel longitudinal multiple overall toxicity score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma | Abstract | | Aim: This work is intended to study the evolution of chemotherapy-induced toxicity over treatment, introducing a new method for summarize multiple toxic adverse events (AEs), i.e., the longitudinal Multiple Overall Toxicity (MOTox) score. A retrospective analysis of patients from MRC BO06/EORTC 80931 Randomized Controlled Trial for osteosarcoma was conducted.
Methods: Patients were randomised to six cycles of conventional versus dose-intense regimens of doxorubicin and cisplatin. Non-haematological toxicity data were collected prospectively and graded according to the Common Terminology Criteria for Adverse Events (CTCAE). The MOTox score was defined by condensing the worst AE and the overall toxic condition, including a time dimension. Multivariate models were constructed to assess the evolution of high overall toxicity, examining cycle-by-cycle the impact of personalized characteristics, such as achieved chemotherapy dose, previous toxic events, or biochemical factors.
Results: The flexible longitudinal depiction of MOTox score represents the strength of our method. A cycle-by-cycle dimension allowed to reconstruct different evolution patterns over treatment, leading to informative ramifications on patients’ health statuses. Patient’s toxic history played an important role in the quality of life over therapy, showing an autoregressive impact of previous toxicity. Conventional regimen had to be preferred to dose-intense one in terms of toxic AEs in the first half of the treatment.
Conclusion: This study shows that working in this direction is a difficult but profitable approach. The flexibility of our method, added to a cooperation with medical staff, could lead to improvements in the definition of useful tools for health care assessment and treatment planning. |
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71/2022 - 19/10/2022
Calabrò, D.; Lupo Pasini, M.; Ferro, N.; Perotto, S.
A deep learning approach for detection and localization of leaf anomalies | Abstract | | The detection and localization of possible diseases in crops are usually automated by resorting to supervised deep learning approaches. In this work, we tackle these goals with unsupervised models, by applying three different types of autoencoders to a specific open-source dataset of healthy and unhealthy pepper and cherry leaf images. CAE, CVAE and VQ-VAE autoencoders are deployed to screen unlabeled images of such a dataset, and compared in terms of image reconstruction, anomaly removal, detection and localization. The vector-quantized variational architecture turns out to be the best performing one with respect to all these targets. |
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70/2022 - 19/10/2022
Andrini, D.; Balbi, V.; Bevilacqua, G.; Lucci, G.; Pozzi, G.; Riccobelli, D.
Mathematical modelling of axonal cortex contractility | Abstract | | The axonal cortex is composed of a regular structure of F-actin and spectrin able to contract thanks to myosin II motors. Such an active tension is of fundamental importance in controlling the physiological shape of axons. Recent experiments show that axons modulate the contraction of the cortex when subject to mechanical deformations, exhibiting a non-trivial coupling between the hoop and the axial active tension. However, the underlying mechanisms are still poorly understood. In this paper, we propose a continuum model of the axon based on the active strain theory. By using the Coleman-Noll procedure, we shed light on the coupling between the hoop and the axial active strain through the Mandel stress tensor. We propose a qualitative analysis of the system under the simplifying assumption of incompressibility, showing the existence of a stable equilibrium solution. In particular, our results show that the axon regulates the active contraction to maintain a homeostatic stress state. Finally, we propose numerical simulations of the model, using a more suitable compressible constitutive law. The results are compared with experimental data, showing an excellent quantitative agreement. |
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