Diffusion tensor imaging and resting state functional connectivity as advanced imaging biomarkers of outcome in infants with hypoxic-ischaemic encephalopathy treated with hypothermia

Therapeutic hypothermia confers significant benefit in term neonates with hypoxic-ischaemic encephalopathy (HIE). However, despite the treatment nearly half of the infants develop an unfavourable outcome. Intensive bench-based and early phase clinical research is focused on identifying treatments that augment hypothermic neuroprotection. Qualified biomarkers are required to test these promising therapies efficiently. This thesis aims to assess advanced magnetic resonance imaging (MRI) techniques, including diffusion tensor imaging (DTI) and resting state functional MRI (fMRI) as imaging biomarkers of outcome in infants with HIE who underwent hypothermic neuroprotection. FA values in the white matter (WM), obtained in the neonatal period and assessed by tract-based spatial statistics (TBSS), correlated with subsequent developmental quotient (DQ). However, TBSS is not suitable to study grey matter (GM), which is the primary site of injury following an acute hypoxic-ischaemic event. Therefore, a neonatal atlas-based automated tissue labelling approach was applied to segment central and cortical grey and whole brain WM. Mean diffusivity (MD) in GM structures, obtained in the neonatal period correlated with subsequent DQ. Although the central GM is the primary site of injury on conventional MRI following HIE; FA within WM tissue labels also correlated to neurodevelopmental performance scores. As DTI does not provide information on functional consequences of brain injury functional sequel of HIE was studied with resting state fMRI. Diminished functional connectivity was demonstrated in infants who suffered HIE, which associated with an unfavourable outcome. The results of this thesis suggest that MD in GM tissue labels and FA either determined within WM tissue labels or analysed with TBSS correlate to subsequent neurodevelopmental performance scores in infants who suffered HIE treated with hypothermia and may be applied as imaging biomarkers of outcome in this population. Although functional connectivity was diminished in infants with HIE, resting state fMRI needs further study to assess its utility as an imaging biomarker following a hypoxic-ischaemic brain injury.Open Acces

Macroscale imaging: a potential biomarker for post stroke functional outcome?

To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcomes. Multiple linear regression was used to assess the quality of prediction of the most informative model.To determine whether long-term functional outcomes in stroke patients can be predicted by the amount of acutely damaged white matter tracts. We collected acute behavioral and neuroimaging data from a group of first-time stroke patients and add those from the other(s) databases. (n=114 + n) within one week (check with the other DBs) post-stroke. Functional outcome was telephonically evaluated using the Stroke Impact Scale 3.0 at 12 months post-stroke. For each patient, we calculated the absolute number of white matter tracts affected by the ischemic lesion from our anatomical scans. We measured a numerical index that considers white matter tract density (WMTD index). We compared the ability of the WMTD index, considered individually, or within a series of prediction models including demographics and behavioral data), to predict chronic outcome. Multiple linear regression was used to assess the quality of prediction of the most informative model

The role of white matter disconnection in stroke as a predictor of clinical outcome after mechanical thrombectomy.

Rationale: Mechanical thrombectomy is a promising approach to acute treatment in large vessel occlusion (LVO) ischemic stroke. This technique has shown to be safe and effective when performed both in early and late-window trials. Several clinical and mainly volumetric, radiological features are used as prognostic factors for functional outcome and patient eligibility. However, emerging evidence supports the idea that lesion topography is strongly associated with prognosis and functional brain recovery. The aim of this study is to examine the role of clinical (i.e. mRS and NIHSS) vs. standard volume-based lesion (i.e. ASPECTS, core, penumbra and final lesion volume) vs. topological radiological (i.e. white matter structural disconnection) features, in patients eligible for acute mechanical thrombectomy. Materials and methods: We selected a group of patients (n=50) who underwent acute mechanical thrombectomy over 47 months, from January 2018 to November 2021, and occurred at the Stroke Unit and Clinica Neurologica of the Hospital of Padova. They were studied with the modified Rankin Scale (mRS) and the National Institutes of Health Stroke Scale (NIHSS) both at admission (pre) and at discharge (post), then, again with the mRS at 90 days from the acute event. The lesions were manually segmented on structural MRI and CT scans using the program ITK-SNAP. Four models were performed through a linear regression analysis. Specifically, we computed a baseline clinical model (M1) based on demographics, pre-stroke mRS and admission NIHSS. Then we added commonly used (standard) radiological parameters of lesion or perfusion damage (core, penumbra, ASPECTS) (M2). Therefore, we added information about the white matter structural disconnection to clinical variables (M3). Finally, we tested a baseline clinical +early recovery model (M4), which included age, pre-mRS, admission NIHSS, and post-mRS. The lesions were normalized in atlas space and displayed to study their distribution and structural disconnections (SDC). Results: The mean baseline mRS was 0.48±0.90, while the mean 90-day mRS was 2.18±1.81. The linear regression analysis showed a significant positive correlation between 90-day mRS and clinical variables (pre-mRS, NIHSS at presentation, post-mRS), while radiological variables (ASPECTS, core, and penumbra volume) did not seem to be associated with functional outcome. The results of the ANOVA analysis showed that, between the four models tested, M4 (including age, pre-mRS, NIHSS at presentation, and post-mRS as independent variables) was the one providing the highest adjusted R-squared [Adj.R-squared=0.614] and explained 62% of the variance in outcome prediction. At a voxel-wise level, we found a significant positive correlation between brain recovery (Delta 90-day mRS-pre-mRS) and damage, affecting predominantly the left corticospinal tract and the corresponding structural white matter disconnection (SDC), which also extended to the cingulum and, bilaterally, to the callosal commissure. Conclusion: In our sample, acute clinical status represents the most valuable prognostic factor. Interestingly, while radiological (i.e. volumetric and semi-quantitative) features, such as ASPECTS, core, and penumbra volume, did not show any significant correlation with 90-day mRS, structural white matter disconnection and lesion topography, in particular of the left corticospinal tract, were associated with a poorer recovery after endovascular treatment. These results could have important future implications in pre-treatment patients’ selection and in post-treatment post stroke rehabilitation.​Rationale: Mechanical thrombectomy is a promising approach to acute treatment in large vessel occlusion (LVO) ischemic stroke. This technique has shown to be safe and effective when performed both in early and late-window trials. Several clinical and mainly volumetric, radiological features are used as prognostic factors for functional outcome and patient eligibility. However, emerging evidence supports the idea that lesion topography is strongly associated with prognosis and functional brain recovery. The aim of this study is to examine the role of clinical (i.e. mRS and NIHSS) vs. standard volume-based lesion (i.e. ASPECTS, core, penumbra and final lesion volume) vs. topological radiological (i.e. white matter structural disconnection) features, in patients eligible for acute mechanical thrombectomy. Materials and methods: We selected a group of patients (n=50) who underwent acute mechanical thrombectomy over 47 months, from January 2018 to November 2021, and occurred at the Stroke Unit and Clinica Neurologica of the Hospital of Padova. They were studied with the modified Rankin Scale (mRS) and the National Institutes of Health Stroke Scale (NIHSS) both at admission (pre) and at discharge (post), then, again with the mRS at 90 days from the acute event. The lesions were manually segmented on structural MRI and CT scans using the program ITK-SNAP. Four models were performed through a linear regression analysis. Specifically, we computed a baseline clinical model (M1) based on demographics, pre-stroke mRS and admission NIHSS. Then we added commonly used (standard) radiological parameters of lesion or perfusion damage (core, penumbra, ASPECTS) (M2). Therefore, we added information about the white matter structural disconnection to clinical variables (M3). Finally, we tested a baseline clinical +early recovery model (M4), which included age, pre-mRS, admission NIHSS, and post-mRS. The lesions were normalized in atlas space and displayed to study their distribution and structural disconnections (SDC). Results: The mean baseline mRS was 0.48±0.90, while the mean 90-day mRS was 2.18±1.81. The linear regression analysis showed a significant positive correlation between 90-day mRS and clinical variables (pre-mRS, NIHSS at presentation, post-mRS), while radiological variables (ASPECTS, core, and penumbra volume) did not seem to be associated with functional outcome. The results of the ANOVA analysis showed that, between the four models tested, M4 (including age, pre-mRS, NIHSS at presentation, and post-mRS as independent variables) was the one providing the highest adjusted R-squared [Adj.R-squared=0.614] and explained 62% of the variance in outcome prediction. At a voxel-wise level, we found a significant positive correlation between brain recovery (Delta 90-day mRS-pre-mRS) and damage, affecting predominantly the left corticospinal tract and the corresponding structural white matter disconnection (SDC), which also extended to the cingulum and, bilaterally, to the callosal commissure. Conclusion: In our sample, acute clinical status represents the most valuable prognostic factor. Interestingly, while radiological (i.e. volumetric and semi-quantitative) features, such as ASPECTS, core, and penumbra volume, did not show any significant correlation with 90-day mRS, structural white matter disconnection and lesion topography, in particular of the left corticospinal tract, were associated with a poorer recovery after endovascular treatment. These results could have important future implications in pre-treatment patients’ selection and in post-treatment post stroke rehabilitation

Predicting healthcare high-cost users using data mining methods

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe increase in healthcare costs is, perhaps, one of the most important issues that governments and organizations face nowadays. An ageing population and technological advancements are the key reasons for this phenomenon. In this scenario, proactive measures are very important. This work aimed to improve the effectiveness of the prevention by helping the identification of the most probable high-cost users of health services in future years. Data from 2015 to 2019 of approximately 30,000 Central Bank of Brazil’s Health Program’s enrollees were used to train, validate and test four types of models, considering the kind of high-cost users (simple or cost-bloomers, i.e., non-high-cost in previous periods) and the time-span between predictors and the dependent variable (none or one year), an innovation suggested by other authors. Different percentual cut-off points to define highcost were used, and up to 67% of high-risk users’ expenses could be correctly captured. Results confirmed the importance of previous costs data for this kind of prediction and showed that costbloomers and one-year time-span approaches reach good performance, creating opportunities to improve users’ health outcomes while contributing to the fiscal sustainability of private and public health systems

Use of thrombolytic therapy beyond current recommendations for acute ischaemic stroke

In Chapter 1, I introduce ischaemic stroke, thrombolytic therapy, thrombolysis trials and then discuss the rationale for exclusion criteria in stroke thrombolysis guidelines.In Chapter 2, I describe methods for examining outcomes in patients that are currently recommended for exclusions from receiving alteplase for acute ischaemic stroke. In Chapter 3, I examine Virtual International Stroke Trials Archive (VISTA) data to test whether current European recommendation suggesting exclusion of elderly patients (older than 80 years) from thrombolysis for acute ischaemic stroke is justified. Employing non-randomised controlled comparison of outcomes, I show better outcomes amongst all patients (P 30 years. Outcomes assessed by National Institutes of Health Scale (NIHSS) score and dichotomised modified Rankin Scale score are consistently similar. In Chapter 4, I compare thrombolysed patients in Safe Implementation of Thrombolysis in Stroke International Stroke Thrombolysis Register (SITS-ISTR) with VISTA non-thrombolysed patients ("comparators" or "controls") and test exactly similar question as in Chapter 3. Distribution of scores on modified Rankin scale are better amongst all thrombolysis patients than controls (odds ratio 1.6, 95% confidence interval 1.5 to 1.7; Cochran-Mantel-Haenszel P80 (OR 1.4, 95% CI 1.3 to 1.6; P<0.001; n=3439). Odds ratios are consistent across all 10 year age ranges above 30, and benefit is significant from age 41 to 90; dichotomised outcomes (score on modified Rankin scale 0-1 v 2-6; 0-2 v 3-6; and 6 (death) versus rest) are consistent with the results of ordinal analysis. These findings are consistent with results from VISTA reported in Chapter 3. Age alone should not be a criterion for excluding patients from receiving thrombolytic therapy.In Chapter 5, I employ VISTA data to examine whether patients having diabetes and previous stroke have improved outcomes from use of alteplase in acute ischaemic stroke. Employing a non-randomised controlled comparison, I show that the functional outcomes are better for thrombolysed patients versus nonthrombolysed comparators amongst non-diabetic (P < 0.0001; OR 1.4 [95% CI 1.3-1.6]) and diabetic (P = 0.1; OR 1.3 [95% CI1.05-1.6]) patients. Similarly, outcomes are better for thrombolysed versus nonthrombolysed patients who have not had a prior stroke (P < 0.0001; OR 1.4 [95% CI1.2-1.6]) and those who have (P = 0.02; OR 1.3 [95% CI1.04-1.6]). There is no interaction of diabetes and prior stroke with treatment (P = 0.8). Neurological outcomes (NIHSS) are consistent with functional outcomes (mRS). In Chapter 6, I undertake a non-randomised controlled comparison of SITS-ISTR data with VISTA controls and examine whether patients having diabetes and previous stroke have improved outcomes from use of alteplase in acute ischaemic stroke. I show that adjusted mRS outcomes are better for thrombolysed versus non-thrombolysed comparators amongst patients with diabetes mellitus (OR 1.45[95% CI1.30-1.62], N=5354), previous stroke (OR 1.55[95% CI1.40-1.72], N=4986), or concomitant diabetes mellitus and previous stroke (OR 1.23 [95% CI 0.996-1.52], P=0.05, N=1136), all CMH p<0.0001. These are comparable to outcomes between thrombolysed and non-thrombolysed comparators amongst patients suffering neither diabetes mellitus nor previous stroke: OR=1.53(95%CI 1.42-1.63), p<0.0001, N=19339. There are no interaction between diabetes mellitus and previous stroke with alteplase treatment (t-PA*DM*PS, p=0.5). Present data supports results obtained from the analyses of VISTA data in chapter 5. There is no statistical evidence to recommend exclusion of patients with diabetes and previous stroke from receiving alteplase.In Chapter 7, I examine VISTA data to test whether exclusion of patients having a mild or severe stroke at baseline would be justified. Stratifying baseline stroke severity for quintiles of NIHSS scores, I observe that there are significant associations of use of alteplase with improved outcomes for baseline NIHSS levels from 5 to 24 (p<0.05). This association lose significance for baseline NIHSS categories 1 to 4 (P = 0.8; OR, 1.1; 95% CI, 0.3-4.4; N = 8/161) or ≥ 25 (P = 0.08; OR, 1.1; 95% CI, 0.7-1.9; N = 64/179) when sample sizes are small and confidence interval wide. These findings fail to provide robust evidence to support the use of alteplase in the mild or severe stroke patients, though potential for benefit appears likely.In Chapter 8, I present a meta-analysis of trials that investigated mismatch criteria for patients’ selection to examine whether present evidence supports delayed thrombolysis amongst patients selected according to mismatch criteria. I collate outcome data for patients who were enrolled after 3 hours of stroke onset in thrombolysis trials and had mismatch on pre-treatment imaging. I compare favourable outcome, reperfusion and/or recanalisation, mortality, and symptomatic intracerebral haemorrhage between the thrombolysed and non-thrombolysed groups of patients and the probability of a favourable outcome among patients with successful reperfusion and clinical findings for 3 to 6 versus 6 to 9 hours from post stroke onset. I identify articles describing the DIAS, DIAS II, DEDAS, DEFUSE, and EPITHET trials, giving a total of 502 mismatch patients thrombolysed beyond 3 hours. The combined adjusted odds ratios (a-ORs) for favourable outcomes are greater for patients who had successful reperfusion (a-OR=5.2; 95% CI, 3 to 9; I2=0%). Favourable clinical outcomes are not significantly improved by thrombolysis (a-OR=1.3; 95% CI, 0.8 to 2.0; I2=20.9%). Odds for reperfusion/recanalisation are increased amongst patients who received thrombolytic therapy (a-OR=3.0; 95% CI, 1.6 to 5.8; I2=25.7%). The combined data show a significant increase in mortality after thrombolysis (a-OR=2.4; 95% CI, 1.2 to 4.9; I2=0%), but this is not confirmed when I exclude data from desmoteplase doses that are abandoned in clinical development (a-OR=1.6; 95% CI, 0.7 to 3.7; I2=0%). Symptomatic intracerebral haemorrhage is significantly increased after thrombolysis (a-OR=6.5; 95% CI, 1.2 to 35.4; I2=0%) but not significant after exclusion of abandoned doses of desmoteplase (a-OR=5.4; 95% CI, 0.9 to 31.8; I2=0%). Delayed thrombolysis amongst patients selected according to mismatch imaging is associated with increased reperfusion/recanalisation. Recanalisation/reperfusion is associated with improved outcomes. However, delayed thrombolysis in mismatch patients was not confirmed to improve clinical outcome, although a useful clinical benefit remains possible. Thrombolysis carries a significant risk of symptomatic intracerebral haemorrhage and possibly increased mortality. Criteria to diagnose mismatch are still evolving. Validation of the mismatch selection paradigm is required with a phase III trial. Pending these results, delayed treatment, even according to mismatch selection, cannot be recommended as part of routine care.In Chapter 9, I summarise the findings of my research, discuss its impact on the research community, and discuss weaknesses inherent in registry data and limitation of statistical methods. Then, I elaborate the future directions I may take to further research on the theme of this thesis.