Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2–7 days (acute), and >7–90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables

DEVELOPING INTEGRATED MACHINE LEARNING MODELS FOR AUTOMATIC COMPUTER-AIDED DIAGNOSIS IN ISCHEMIC ACUTE STROKE MRI

Fast detection and quantification of lesion cores in diffusion weighted images (DWIs) has been highly anticipated in clinical and research communities for planning treatment of acute stroke. The recent emergence of successful machine learning (ML) methods, especially Deep Learning (DL), enables automatic Computer Aided Diagnosis (CAD) of stroke in DWIs. However, the lack of publicly available large-scale data and ML models in clinical acute stroke DWI application are still the bottlenecks. In this work, we established the first large annotated open-source database of 2,888 clinical acute stroke MRIs (Chapter 2) to train and develop ML models for automatic stroke lesion detection and segmentation in clinical acute stroke MRI (Chapter 3). For automatic measurement of infarcted arterial territories, the first digital 3D deformable brain arterial territory atlas was created (Chapter 4). In addition, a fully automatic ML system is created to generate automatic radiological reports (Chapter 5 and 6) for calculation of ASPECTS, prediction and quantification of infarcted arterial and anatomical regions, and estimation of hydrocephalus presented in acute stroke MRI. The complete ML system in this work runs locally in real time with minimal computational requirements. It is publicly available and readily useful for non-expert users

Added value of acute multimodal CT-based imaging (MCTI) : a comprehensive analysis

Introduction: MCTI is used to assess acute ischemic stroke (AIS) patients.We postulated that use of MCTI improves patient outcome regardingindependence and mortality.Methods: From the ASTRAL registry, all patients with an AIS and a non-contrast-CT (NCCT), angio-CT (CTA) or perfusion-CT (CTP) within24 h from onset were included. Demographic, clinical, biological, radio-logical, and follow-up caracteristics were collected. Significant predictorsof MCTI use were fitted in a multivariate analysis. Patients undergoingCTA or CTA&CTP were compared with NCCT patients with regards tofavourable outcome (mRS ≤ 2) at 3 months, 12 months mortality, strokemechanism, short-term renal function, use of ancillary diagnostic tests,duration of hospitalization and 12 months stroke recurrence

Clinical Findings and Outcome after Stroke. Including a Translational Stem Cell Therapy Perspective.

Background and Purpose: Stroke is one of the dominant causes of death and adult disability in the world. There is a need for novel therapeutic approaches to improve functional recovery and outcome after stroke, and experimental studies have shown that stem cell-based therapies (SCT) hold much potential in this regard. This thesis, comprising 5 papers, aims to explore and describe clinical symptoms, lesion appearance, and outcome after stroke to provide guidance and enhance possibilities for future clinical implementation of SCT. Methods: In Paper I, a consecutive series of first-ever ischemic stroke patients (n=108) were examined ≤4 days of stroke onset regarding: (i) neuroradiological characteristics, and (ii) stroke severity measured with National Institutes of Health Stroke Scale (NIHSS). In Papers II and V, available survivors (n=84) from Paper I were assessed after 3-5 years regarding: (i) the frequency and recovery of upper extremity motor impairment (UEMI) measured with NIHSS arm and hand motor items; ii) the relation of UEMI to activity limitations measured with modifed Rankin Scale (mRS) and participation restrictions evaluated with Stroke Impact Scale (SIS); and iii) their knowledge and attitude about SCT using a questionnaire on SCT for stroke. In Papers III and IV, 10-year survivors (n=145) from a population-based group of 416 first-ever stroke patients in the Lund Stroke Register were assessed regarding: (i) functional status measured with mRS and Barthel Index (BI); (ii) patient-reported outcome using the European Quality of Life-5 Dimensions (EQ-5D) and Short-Form 36 Health Survey (SF-36), and iii) cognitive function using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), including comparisons with age- and sex-matched non-stroke control persons (n=354) from the population study Gott Åldrande i Skåne.Results: In Paper I, the distance between the nearest margin of the infarct(s) to the subventricular zone (a known neurogenic area in the brain) was 0-2 mm in 51/102 patients with visible ischemic lesions on DW-MRI. Only 8 patients had infarcts predominantly confined to striatum (a commonly used lesion site in pre-clinical stroke studies with SCT), causing mild deficits with a median NIHSS of 3 (range 1-5). In Paper II, 56 (52%) of the stroke patients had UEMI (NIHSS arm/hand score ≥1) in the first days after stroke onset. Morever, 10/41 stroke survivors with UEMI at baseline and without recurrent stroke displayed residual UEMI after 3-5 years, whereas 31/41 individuals showed complete recovery. Post-stroke UEMI correlated to mRS (rs=0.49, p<0.001) and the SIS participation domain (rs=-0.38, p=0.001). In Paper III, 103 (71%) of the 10-year stroke survivors had mRS≤2, 106 (73%) had a BI score of 95-100, 105 (72%) reported no problems with self-care according to EQ-5D, and 90 (62%) had positive views about their general health status according to SF-36. In Paper IV, 75 (61%) out of 122 stroke survivors who completed the MoCA had a score of MoCA<25. The odds of having severe cognitive impairment (MMSE<23) were higher among stroke survivors than the controls (education-adjusted OR 2.48; 95% CI: 1.34-4.59; p=0.004). In Paper V, only 10 (12%) of the stroke survivors had prior knowledge of SCT, but 53 (63%) of the participants expressed positive attitudes towards SCT after having received standardized and neutral written information. Positive attitudes to SCT were associated with male gender (crude OR 3.74; 95% CI: 1.45-9.61; p=0.006) and higher degree of self-perceived stroke recovery according to the SIS (crude OR 1.02; 95% CI: 1.00-1.04; p=0.034).Conclusions: Optimized endogenous neurogenesis may have a therapeutic potential, and striatum should probably not be the primary target for SCT aiming for neuronal replacement. SCT targeting post-stroke UEMI may be clinically valuable, and UEMI recovery may be a suitable outcome in later-phase pivotal stroke trials studying the efficacy of SCT. A majority of long-term stroke survivors have a relatively good prognosis accompanied by positive self-perceptions about their health, and would probably not have been in need of SCT to improve functional outcome. However, early prognostic assessments are needed to detect stroke patients with poor expected functional recovery and outcome where SCT may be beneficial. Cognitive impairment is common among long-term stroke survivors and should be taken into account both in pre-clinical studies and in future clinical trials with SCT. Targeted patient information on SCT for stroke may be valuable to facilitate recruitment to clinical trials and reduce risks of selection bias

Acute Stroke Care: Strategies For Improving Diagnostics

Stroke is one of the leading causes of death and disability, with a high incidence of over 11 million cases annually worldwide. Costs of treatment and rehabilitation, loss of work, and the hardships resulting from stroke are a major burden both at the individual and at the societal level. Importantly, stroke therapies need to be initiated early for them to be effective. Thrombolytic therapy and mechanical thrombectomy are early treatment options of ischemic stroke. In hemorrhagic stroke, optimization of hemodynamic and hemostatic parameters is central, and surgery is considered in a subset of patients. Efficient treatment of stroke requires early and precise recognition of stroke at all stages of the treatment chain. This includes identification of patients with suspected acute stroke by emergency medical dispatchers and emergency medical services staff, and precise admission diagnostics by the receiving on-call stroke team. Success requires grasping the complexity of stroke symptoms that depend on the brain areas affected, and the plethora of medical conditions that can mimic stroke. The Helsinki Ultra-acute Stroke Biomarker Study includes a cohort of 1015 patients transported to hospital due to suspected acute stroke, as candidates for revascularization therapies. Based on this cohort, this thesis work has explored new avenues to improve early stroke diagnostics in all stages of the treatment chain. In a detailed investigation into the identification of stroke by emergency medical dispatchers, we analyzed emergency phone calls with missed stroke identification. We also combined data on dispatch and EMS and hospital records to identify causes for missing stroke during emergency calls. Most importantly, we found that a patient’s fall at onset and patient confusion were strongly associated with missed identification. Regarding the Face Arm Speech Test (FAST), the most likely symptom to be misidentified was acute speech disturbance. Using prehospital blood sampling of stroke patients, and ultrasensitive measurement, we investigated the early dynamics of the plasma biomarkers glial fibrillary acidic protein (GFAP) and total tau. Utilizing serial sampling, we demonstrate for the first time that monitoring the early release rate of GFAP can improve the diagnostic performance of this biomarker for early differentiation between ischemic and hemorrhagic stroke. In our analysis of early GFAP levels, we were able to differentiate with high accuracy two-thirds of all patients with acute cerebral ischemia from those with hemorrhagic stroke, supporting further investigation of this biomarker as a promising point-of-care tool for prehospital stroke diagnostics. We performed a detailed review of the admission diagnostics of our cohort of 1015 patients to explore causes and predictors of admission misdiagnosis. We then investigated the consequences of misdiagnosis on outcomes. We demonstrate in this large cohort that the highly optimized and rapid admission evaluation in our hospital district (door-to-needle times below 20 minutes) did not compromise the accuracy and safety of admission evaluation. In addition, we discovered targets for improving future diagnostics. Finally, our detailed neuropathological investigation of a case of cerebral amyloid angiopathy (CAA) -related hemorrhage after stroke thrombolysis provided unique tissue-level evidence for this common vasculopathy as a notable risk factor for intracranial hemorrhagic complications in the setting of stroke. These findings support research to improve the diagnostics of CAA, and the prediction of hemorrhagic complications associated with stroke thrombolysis. In conclusion, these proposed targets and strategies will aid in the future improvement and development of this highly important field of diagnostics. Our proof-of-concept discoveries on early GFAP kinetics help guide further study into this diagnostic approach just as highly sensitive point-of-care GFAP measurement instruments are becoming available. Finally, our results support the safety of worldwide efforts to optimize emergency department door-to- needle times when care is taken to ensure sufficient expertise is in place, highlighting the role of the on-call vascular neurologist as a central diagnostic asset.Aivohalvaus on yksi yleisimpiä kuolinsyitä ja pitkäkestoisen työkyvyttömyyden aiheuttajia. Aivohalvauksen aiheuttamat hoito- ja kuntoutuskustannukset, työkyvyn menetys ja arkielämän vaikeudet ovat mittava taakka sekä yksilön, läheisten että yhteiskunnan tasoilla. Tehokkaiden hoitojen vaatima nopeus edellyttää aivohalvauksen varhaista ja tarkkaa tunnistamista hoitoketjun kaikilla askelmilla. Tässä väitöskirjatyössä etsittiin uusia keinoja aivohalvauksen varhaisdiagnostiikan kehittämiseksi hätäkeskuksessa, ensihoidossa ja vastaanottavan sairaalan HYKS:n päivystyspoliklinikalla. Yksityiskohtainen analyysi aivohalvauksen tunnistamisesta hätäkeskuksessa osoitti, että potilaan kaatuminen ja sekavuus olivat puutteellisen tunnistamisen keskeisiä tekijöitä. Face Arm Speech Test (FAST) -seulontaoireista puhehäiriö oli todennäköisimmin väärin tunnistettu. Akuuttivaiheen verinäytteitä ja äärimmäisen herkkää määritysmenetelmää hyödyntäen tutkimme kahden verestä mitattavan merkkiaineen, aivojen tukikudoksen tähtisolujen säikeisen happaman proteiinin (GFAP) ja taun varhaista dynamiikkaa aivohalvauspotilailla. Osoitimme ensimmäistä kertaa, että GFAP:n varhaisen vapautumisnopeuden seurantaa sarjanäytteistä voidaan hyödyntää parantamaan tämän merkkiaineen erottelukykyä iskeemisen ja hemorragisen aivokudosvaurion varhaisdiagnostiikassa. Tulokset viittaavat siihen, että GFAP merkkiaine voisi olla jatkossa kehitettävissä ambulansseissa hyödynnettäväksi pikaverikokeeksi, joka auttaisi aivohalvauksen eri muotojen varhaisessa erottelussa. Päivystysdiagnostiikkaan keskittyvässä osatyössä osoitimme ensimmäistä kertaa suuressa aineistossa, että sairaanhoitopiirissämme vuosia optimoitu erittäin nopea vastaanottoarviointi (liuotushoidon mediaaniviive alle 20 minuuttia sisältäen pään kuvauksen) ei vaaranna aivohalvauspotilaiden diagnostiikan tarkkuutta ja hoidon turvallisuutta. Tässä väitöskirjatyössä esitetyt kehityskohteet ja menetelmät auttavat tämän erittäin tärkeän diagnostisen alan tulevassa kehitystyössä. Työssä kuvatut tulokset sisältävät uraauurtavia havaintoja verestä mitattavan GFAP merkkiaineen kinetiikan käytöstä aivohalvauksen varhaisdiagnostiikassa ja tukevat sairaalapäivystysarvion diagnostista tarkkuutta HYKS:n tunnetusti erittäin nopeassa liuotushoitoketjussa

Diseases of the Brain, Head and Neck, Spine 2020–2023

This open access book offers an essential overview of brain, head and neck, and spine imaging. Over the last few years, there have been considerable advances in this area, driven by both clinical and technological developments. Written by leading international experts and teachers, the chapters are disease-oriented and cover all relevant imaging modalities, with a focus on magnetic resonance imaging and computed tomography. The book also includes a synopsis of pediatric imaging. IDKD books are rewritten (not merely updated) every four years, which means they offer a comprehensive review of the state-of-the-art in imaging. The book is clearly structured and features learning objectives, abstracts, subheadings, tables and take-home points, supported by design elements to help readers navigate the text. It will particularly appeal to general radiologists, radiology residents, and interventional radiologists who want to update their diagnostic expertise, as well as clinicians from other specialties who are interested in imaging for their patient care

Brain dysconnectome: a potential biomarker for functional outcome after mechanical thrombectomy

Mechanical thrombectomy (MT) is a safe and effective procedure that has improved the prognosis of patients with large vessel obstruction (LVO) stroke. Even though we select patients based on various clinical and imaging criteria, more than half of those undergoing this procedure remain with severe disability. Several factors, both pre-treatment (pre-stroke mRS, NIHSS, event-recanalization time, ASPECTS, core/ penumbra volumes) and post-treatment (TICI, NIHSS, final infarct volume, complications) have been identified as predictors of outcome. Among these factors, the volume of the lesion and the size of the hypo-perfused region of the brain are used to make individual decisions about treatment. In retrospective studies, the volume of the lesion weakly correlates with clinical outcomes, while lesion location is more predictive. In addition measures of large-scale (brain networks) disruption have been developed based on the concept of structural and functional disconnection, i.e., the ensemble of structural and functional connections that are directly or indirectly damaged by the focal injury. These disconnection measures have been shown to be strongly predictive of acute impairment and recovery of function. Here we plan to measure in a group of patients with LVO who underwent MT the relationship between outcome (3 month-mRS) and the location of the lesion or its effect on structural and functional networks. To examine whether the outcome is more related to the vascular distribution stroke or their effects on structural-functional brain networks, we mapped the lesions onto a vascular atlas, a gray matter functional regions’ atlas, or a white matter structural connections’ atlas. Then using multi-variate statistical models, we tested which atlas was more predictive of clinical outcome. The same analysis was then applied to structural and functional disconnection patterns. A total of n=66 patients underwent MT at the Neurology Unit of Padua hospital from January 2019 to June 2022. They were examined with the mRS and the NIHSS at admission and discharge. The mRS was also administered at three months post-stroke for measuring clinical outcomes. The location and volume of the lesions were measured from CT, and FLAIR MRI scans performed after MT and manually segmented using the software ITK-SNAP. We computed voxel-wise maps of structural and functional disconnections that were significantly related to functional outcomes. We also investigated the relationship between lesion location computed on three different atlases (vascular, functional grey matter, and structural white matter atlas) and 3-month mRS. The mean pre-event mRS was 0.5±0.9, post-MT mRS was 3.1±1.9, at three-month mRS was 2.5±2.1. A voxel-wise analysis of the functional disconnection showed a significant involvement of the sensory-motor network (SMN) (R2= 0.340), the visual network (VIS)(R2= 0.379), and the dorsal attention network (DAN)(R2=0.318). The voxel-wise structural disconnection analysis localized sensorimotor pathways and long-range association pathways. The prediction of lesion topography on clinical outcome was more robust for the functional atlas (R2=0.382), followed by the structural atlas (R2=0.338), while the vascular atlas provided the lowest prediction (R2=0.146). Structural disconnection performed better than functional disconnection in predicting outcomes (respectively R2=0.339 and R2=0.205). Stroke lesion topography is a strong prognostic factor of outcome at three months when computed on an atlas of functional and structural networks, as compared to a vascular-based atlas. These findings indicate that pre-treatment evaluations for MT shall take into consideration the network structure of the brain and less its vascular supply. Structural disconnection measures are of high prognostic value. Future studies will define the prognostic value of a network-based atlas in a pre-treatment setting.Mechanical thrombectomy (MT) is a safe and effective procedure that has improved the prognosis of patients with large vessel obstruction (LVO) stroke. Even though we select patients based on various clinical and imaging criteria, more than half of those undergoing this procedure remain with severe disability. Several factors, both pre-treatment (pre-stroke mRS, NIHSS, event-recanalization time, ASPECTS, core/ penumbra volumes) and post-treatment (TICI, NIHSS, final infarct volume, complications) have been identified as predictors of outcome. Among these factors, the volume of the lesion and the size of the hypo-perfused region of the brain are used to make individual decisions about treatment. In retrospective studies, the volume of the lesion weakly correlates with clinical outcomes, while lesion location is more predictive. In addition measures of large-scale (brain networks) disruption have been developed based on the concept of structural and functional disconnection, i.e., the ensemble of structural and functional connections that are directly or indirectly damaged by the focal injury. These disconnection measures have been shown to be strongly predictive of acute impairment and recovery of function. Here we plan to measure in a group of patients with LVO who underwent MT the relationship between outcome (3 month-mRS) and the location of the lesion or its effect on structural and functional networks. To examine whether the outcome is more related to the vascular distribution stroke or their effects on structural-functional brain networks, we mapped the lesions onto a vascular atlas, a gray matter functional regions’ atlas, or a white matter structural connections’ atlas. Then using multi-variate statistical models, we tested which atlas was more predictive of clinical outcome. The same analysis was then applied to structural and functional disconnection patterns. A total of n=66 patients underwent MT at the Neurology Unit of Padua hospital from January 2019 to June 2022. They were examined with the mRS and the NIHSS at admission and discharge. The mRS was also administered at three months post-stroke for measuring clinical outcomes. The location and volume of the lesions were measured from CT, and FLAIR MRI scans performed after MT and manually segmented using the software ITK-SNAP. We computed voxel-wise maps of structural and functional disconnections that were significantly related to functional outcomes. We also investigated the relationship between lesion location computed on three different atlases (vascular, functional grey matter, and structural white matter atlas) and 3-month mRS. The mean pre-event mRS was 0.5±0.9, post-MT mRS was 3.1±1.9, at three-month mRS was 2.5±2.1. A voxel-wise analysis of the functional disconnection showed a significant involvement of the sensory-motor network (SMN) (R2= 0.340), the visual network (VIS)(R2= 0.379), and the dorsal attention network (DAN)(R2=0.318). The voxel-wise structural disconnection analysis localized sensorimotor pathways and long-range association pathways. The prediction of lesion topography on clinical outcome was more robust for the functional atlas (R2=0.382), followed by the structural atlas (R2=0.338), while the vascular atlas provided the lowest prediction (R2=0.146). Structural disconnection performed better than functional disconnection in predicting outcomes (respectively R2=0.339 and R2=0.205). Stroke lesion topography is a strong prognostic factor of outcome at three months when computed on an atlas of functional and structural networks, as compared to a vascular-based atlas. These findings indicate that pre-treatment evaluations for MT shall take into consideration the network structure of the brain and less its vascular supply. Structural disconnection measures are of high prognostic value. Future studies will define the prognostic value of a network-based atlas in a pre-treatment setting