Towards personalized diagnosis of Glioblastoma in Fluid-attenuated inversion recovery (FLAIR) by topological interpretable machine learning

Glioblastoma multiforme (GBM) is a fast-growing and highly invasive brain tumour, it tends to occur in adults between the ages of 45 and 70 and it accounts for 52 percent of all primary brain tumours. Usually, GBMs are detected by magnetic resonance images (MRI). Among MRI, Fluid-attenuated inversion recovery (FLAIR) sequence produces high quality digital tumour representation. Fast detection and segmentation techniques are needed for overcoming subjective medical doctors (MDs) judgment. In the present investigation, we intend to demonstrate by means of numerical experiments that topological features combined with textural features can be enrolled for GBM analysis and morphological characterization on FLAIR. To this extent, we have performed three numerical experiments. In the first experiment, Topological Data Analysis (TDA) of a simplified 2D tumour growth mathematical model had allowed to understand the bio-chemical conditions that facilitate tumour growth: the higher the concentration of chemical nutrients the more virulent the process. In the second experiment topological data analysis was used for evaluating GBM temporal progression on FLAIR recorded within 90 days following treatment (e.g., chemo-radiation therapy - CRT) completion and at progression. The experiment had confirmed that persistent entropy is a viable statistics for monitoring GBM evolution during the follow-up period. In the third experiment we had developed a novel methodology based on topological and textural features and automatic interpretable machine learning for automatic GBM classification on FLAIR. The algorithm reached a classification accuracy up to the 97%.Comment: 22 pages; 16 figure

Shared Molecular Mechanisms among Alzheimer’s Disease, Neurovascular Unit Dysfunction and Vascular Risk Factors: A Narrative Review

Alzheimer’s disease (AD) is the most common type of dementia, affecting 24 million individuals. Clinical and epidemiological studies have found several links between vascular risk factors (VRF), neurovascular unit dysfunction (NVUd), blood-brain barrier breakdown (BBBb) and AD onset and progression in adulthood, suggesting a pathogenetic continuum between AD and vascular dementia. Shared pathways between AD, VRF, and NVUd/BBB have also been found at the molecular level, underlining the strength of this association. The present paper reviewed the literature describing commonly shared molecular pathways between adult-onset AD, VRF, and NVUd/BBBb. Current evidence suggests that VRF and NVUd/BBBb are involved in AD neurovascular and neurodegenerative pathology and share several molecular pathways. This is strongly supportive of the hypothesis that the presence of VRF can at least facilitate AD onset and progression through several mechanisms, including NVUd/BBBb. Moreover, vascular disease and several comorbidities may have a cumulative effect on VRF and worsen the clinical manifestations of AD. Early detection and correction of VRF and vascular disease by improving NVUd/BBBd could be a potential target to reduce the overall incidence and delay cognitive impairment in AD

Sleep actigraphic patterns and cognitive status

none9noWe performed an actigraphic assessment of sleep characteristics in healthy subjects and patients with cognitive impairment. Thirty subjects were included and classified into controls (10 subjects), mild cognitive impairment (10 patients) and mild-to-moderate Alzheimer's disease (10 patients). Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Participants had a 7-day actigraphic record. Sleep parameters collected were time in bed, total sleep time, sleep efficiency, sleep latency, wakefulness after sleep onset, number of awakenings, and mean motor activity. Significant differences between mild cognitive impairment and controls patients were found for sleep latency (p = 0.05); Alzheimer's disease patients had significantly worse scores for Pittsburgh Sleep Quality Index (p = 0.01), time in bed (p = 0.001), total sleep time (p = 0.04), sleep latency, sleep efficiency, motor activity (p = 0.0001) and wakefulness after sleep onset (p = 0.001) compared to controls. When comparing Alzheimer's disease and mild cognitive impairment, differences were significant for sleep latency (p = 0.01), wakefulness after sleep onset (p = 0.004), sleep efficiency, number of awakenings and motor activity (p = 0.0001). In addition to showing a high prevalence of sleep alterations in subjects with cognitive impairment, our data suggest that they are evident from the earliest stages of cognitive decline. Further studies are needed to assess whether early correction of sleep alterations can positively influence the evolution of cognitive impairment. The opportunity to provide clinically meaningful information with a simple assessment of sleep characteristics based on actigraphy suggests that wider use of the approach in patients with cognitive decline should be considered.openBuratti, Laura; Camilletti, Roberta; Pulcini, Alessandra; Rocchi, Chiara; Viticchi, Giovanna; Falsetti, Lorenzo; Baldinelli, Sara; Fiori, Chiara; Silvestrini, MauroBuratti, Laura; Camilletti, Roberta; Pulcini, Alessandra; Rocchi, Chiara; Viticchi, Giovanna; Falsetti, Lorenzo; Baldinelli, Sara; Fiori, Chiara; Silvestrini, Maur

Impact of atrial fibrillation in critically ill patients admitted to a stepdown unit

Background: Limited data are available on the clinical course of patients with history of atrial fibrillation (AF) when admitted in an intensive care environment. We aimed to describe the occurrence of major adverse events in AF patients admitted to a stepdown care unit (SDU) and to analyse clinical factors associated with outcomes, impact of dicumarolic oral anticoagulant (OAC) therapy impact and performance of clinical risk scores in this setting. Materials and methods: Single-centre, observational retrospective analysis on a population of subjects with AF history admitted to a SDU. Therapeutic failure (composite of transfer to ICU or death) was considered the main study outcome. Occurrence of stroke and major bleeding (MH) was considered as secondary outcomes. The performance of clinical risk scores was evaluated. Results: A total of 1430 consecutive patients were enrolled. 194 (13.6%) reported the main outcome. Using multivariate logistic regression, age (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.01-1.05), acute coronary syndrome (OR:3.10, 95% CI: 1.88-5.12), cardiogenic shock (OR:10.06, 95% CI: 5.37-18.84), septic shock (OR:5.19,95%CI:3.29-18.84), acute respiratory failure (OR:2.49, 95% CI: 1.67-3.64) and OAC use (OR: 1.61, 95% CI: 1.02-2.55) were independently associated with main outcome. OAC prescription was associated with stroke risk reduction and to both MH and main outcome risk increase. CHA2 DS2 -VASc (c-index: 0.545, P = .117 for stroke) and HAS-BLED (c-index:0.503, P = .900 for MH) did not significantly predict events occurrence. Conclusions: In critically ill AF patients admitted to a SDU, adverse outcomes are highly prevalent. OAC use is associated to an increased risk of therapeutic failure, clinical scores seem unhelpful in predicting stroke and MH, suggesting a highly individualized approach in AF management in this setting

Ipsilateral and contralateral carotid stenosis contribute to the outcome of reperfusion treatment for ischemic stroke

IntroductionIpsilateral and contralateral carotid stenosis (ICS, CCS) influence acute ischemic stroke (AIS) severity and prognosis. Few data are available about their impact on reperfusion therapies efficacy. Aim of this study was to evaluate the impact of ICS and CCS on the effect of intravenous thrombolysis (IT), mechanical thrombectomy (MT) or both and of antiplatelet therapy (AT).MethodsWe enrolled all the consecutive patients admitted for AIS to our stroke unit and submitted to IT, MT, IT+MT, or AT. We established the presence of a significant ICS or CCS (≥70%) by ultrasound examination or brain angio-CT, or MRI. Clinical and instrumental information were collected; delta National Institutes of Health Stroke Scale (NIHSS) from pre-treatment to patients' discharge was employed as the main outcome measure.ResultsIn total, 460 subjects were enrolled, 86 with ICS and 38 with CCS. We observed a significant linear trend of delta (NIHSS) between carotid stenosis categories for patients undergoing IT (p = 0.011), MT (p = 0.046), and MT+IT (p = 0.040), but no significant trend among subjects receiving no reperfusion treatments was observed (p = 0.174).DiscussionAccording to our findings, ICS and CCS negatively influence AIS patients' outcome treated by interventional therapies. ICS might exert an unfavorable effect both by cerebral hypoperfusion and by continuous microembolization toward ischemic area, while CCS is probable involved in reducing the collateral circles effectiveness. The importance of early carotid stenosis detection and treatment should then be reevaluated not only to manage the prevention approaches but also to obtain insights about post-stroke treatment strategies efficacy

Validation of a self-reported instrument to assess work-related difficulties in patients with migraine: the HEADWORK questionnaire

Background: The degree to which work-related difficulties are recognized in headache research is poor and often carried out with inadequate information such as "reduced ability to work as usual", which do not capture at all the variety of difficulties and the factors that impact over them. The aim of this paper is to present the validation of the HEADWORK questionnaire, which addresses the amount and severity of difficulties in work-related tasks and the factors that impact over them.Methods: We developed a set of items based on a previous literature review and patients' focus groups and tested it on a wide set of patients with episodic and chronic migraine attending eight different Italian headache centers. HEADWORK factor structure was assessed with exploratory and confirmatory factor analysis; internal consistency and construct validity were addressed as well.Results: The validation sample (N= 373) was mostly composed of patients with episodic migraine without aura (64.3%) and of females (81%). Factor analysis retrieved two different scales: "Work-related difficulties", composed of eleven items which explain 67.1% of the total variance, and "Factors contributing to work difficulties", composed of six items which explain 52.1% of the total variance. Both HEADWORK subscales have good measurement properties, with higher scores being associated to higher disability, lower quality of life, lower productivity, higher headache frequency and pain intensity.Conclusions: HEADWORK is a 17-item, two-scale questionnaire addressing the impact of migraine on work-related difficulties in terms of difficulties in general or specific skills, and the factors contributing to these difficulties, defined as negative impact on work tasks. It can be used to address disability weights for the purpose of calculating the burden of migraine, and to assess the balance between therapeutic and side effects of medication on productivity

Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation

Critically ill patients affected by atrial fibrillation are at high risk of adverse events: however, the actual risk stratification models for haemorrhagic and thrombotic events are not validated in a critical care setting. With this paper we aimed to identify, adopting topological data analysis, the risk factors for therapeutic failure (in-hospital death or intensive care unit transfer), the in-hospital occurrence of stroke/TIA and major bleeding in a cohort of critically ill patients with pre-existing atrial fibrillation admitted to a stepdown unit; to engineer newer prediction models based on machine learning in the same cohort. We selected all medical patients admitted for critical illness and a history of pre-existing atrial fibrillation in the timeframe 01/01/2002-03/08/2007. All data regarding patients' medical history, comorbidities, drugs adopted, vital parameters and outcomes (therapeutic failure, stroke/TIA and major bleeding) were acquired from electronic medical records. Risk factors for each outcome were analyzed adopting topological data analysis. Machine learning was used to generate three different predictive models. We were able to identify specific risk factors and to engineer dedicated clinical prediction models for therapeutic failure (AUC: 0.974, 95%CI: 0.934-0.975), stroke/TIA (AUC: 0.931, 95%CI: 0.896-0.940; Brier score: 0.13) and major bleeding (AUC: 0.930:0.911-0.939; Brier score: 0.09) in critically-ill patients, which were able to predict accurately their respective clinical outcomes. Topological data analysis and machine learning techniques represent a concrete viewpoint for the physician to predict the risk at the patients' level, aiding the selection of the best therapeutic strategy in critically ill patients affected by pre-existing atrial fibrillation

Stroke territory and atherosclerosis in ischemic stroke patients with a history of migraine with aura

IntroductionThe mechanisms subtending the increased stroke risk in migraine with aura (MA) are not fully understood. Our study aims to evaluate if the clinical profile in stroke patients with MA differentiates from those without MA.MethodsWe retrieved the prospective registered electronic clinical dossiers of adult patients younger than 60 years with acute ischemic stroke admitted in four hospitals between January 2016 and June 2022. Patients were classified by the history of MA (MA+ and MA–).ResultsWe identified 851 stroke patients (59 MA+, 6.9%). Compared to MA−, MA+ patients were characterized by younger age (44.0 ± 10.6 vs 50.1 ± 8.2 years), female sex (59.3% vs 29.0%), and affected by cryptogenic (OR 2.594 95% CI 1.483–4.537), and cerebellar stroke (OR 3.218 95% CI 1.657–6.250; p ≤ 0.001 for all comparisons). After adjusting for age and sex, MA+ patients presented less frequently hypertension (OR 0.349 95% CI 0.167–0.470; p=0.005) and dyslipidemia (OR 0.523 95% CI 0.280–0.974; p = 0.041). After adjusting also for risk factors, the MA+ group had less frequently symptomatic large vessel stenosis (OR 0.126 95% CI 0.017–0,924; p = 0.042) and clinical atherosclerosis (OR 0.103 95% CI 0.014–0.761; p = 0.026), while intima–media thickness did not differ (p = 0.395).DiscussionCryptogenic and cerebellar stroke and fewer vascular risk factors and clinical atherosclerosis seem to characterize stroke patients with MA