Daily On-Line Set-Up Correction in 3D-Conformal Radiotherapy: Is It Feasible?

Aims and background The aim of this report was to investigate the feasibility in terms of treatment time prolongation of an on-line no-action level correction protocol, based on daily electronic portal image verification. Methods and study design The occupation of a linear accelerator (LINAC) delivering 3-D conformal treatments was monitored for two weeks (from Monday to Friday, 10 working days). An electronic portal image device I-View (Elekta, UK) was used for setup verification. Single-exposure portal images were acquired daily using the initial 8 monitor units delivered for each treatment field. Translational deviations of isocenter position larger than 5 mm or 7 mm, for radical or palliative treatments, respectively, were immediately corrected. In order to estimate the extra workload involved with the on-line protocol, the time required for isocenter check and table correction was specifically monitored. Results Forty-eight patients were treated. In all, 482 fractions had electronic portal images taken. Two hundred and forty-five setup corrections were made (50.8% of all fractions). The occupation of the LINAC lasted 106 h on the whole. Twelve h and 25 min (11.7% of LINAC occupation time) were spent for portal image verification and setup correction. On the average, 4.3 fractions per hour were carried out. Conclusions When used by trained therapists, ideally, portal imaging may be carried out before each fraction, requiring approximately 10% of LINAC occupation time

Scarto vs Risorsa. Proposte per la rigenerazione dei residui urbani. Team RAP

Lo studio affronta il tema della rigenerazione di comparti urbani in disuso, con l’obiettivo di orientare il concetto di recupero, verso una visione più ampia e circolare delle trasformazioni urbane. Il workshop RE-LIVE con la proposta per la riqualificazione urbana del comparto ENPAM di via Medici del Vascello a Milano ha rappresentato l’occasione per sviluppare una proposta metodologica coerente con il carattere multidisciplinare del gruppo di lavoro; elaborando un modello meta-progettuale in grado di innescare un processo di recupero “atipico” dei “residui” urbani. Residui che tornano ad essere risorsa strategica, sì come motore di nuove economie, ma soprattutto in ragione delle potenzialità che queste aree offrono per [ri]attivare relazioni materiali e immateriali tra l’uomo e l’ambiente che lo circonda. Il processo proposto, costruito a partire dalle peculiarità del caso di studio, si caratterizza in un approccio metodologico adattivo, flessibile e multiscalare, in grado di agire a diversi livelli di intervento per la riattivazione economica, ambientale e sociale dell’area. La costruzione del modello meta-progettuale di riferimento, dopo una prima fase di indagine, ha visto la definizione di macro-temi di orientamento [recupero atipico, connessione reticolare, gestione/presidio ed abitare fluido], dai quali derivano le misure-obiettivo per definire le linee guida di azione strategica -con particolare riferimento alle tematiche dell’innovazione tecnologica, di sostenibilità e comfort ambientale, del riuso e dell’economia circolare- integrata e in grado di dialogare con le rinnovate esigenze tipologiche e sociali dell’abitare contemporaneo [indoor e outdoor]. Il processo proposto si configura come un metodo aperto che intende il progetto come “servizio” per l’attivazione di un modello replicabile anche al di fuori dei confini del comparto oggetto dello studio

TMS-EEG perturbation biomarkers for Alzheimer’s disease patients classification

Abstract The combination of TMS and EEG has the potential to capture relevant features of Alzheimer’s disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45–80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients’ classification as well as longitudinal disease tracking