Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning

CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the perfusion parameters to determine the tissue status. We pursue a data-driven and deconvolution-free approach, where a deep neural network learns to predict the final infarct volume directly from the native CTP images and metadata such as the time parameters and treatment. This would allow clinicians to simulate various treatments and gain insight into predicted tissue status over time. We demonstrate on a multicenter dataset that our approach is able to predict the final infarct and effectively uses the metadata. An ablation study shows that using the native CTP measurements instead of the deconvolved measurements improves the prediction.Comment: Accepted for publication in Medical Image Analysi

n- исчисление – реалистичная формализация класса переписывающих систем

Предложен новый формализм типизированного η-исчисления в качестве теоретической основы для по-строения специальных классов систем программирования на основе переписывающих правил. Форма-лизм использует упорядоченные неконфлюэнтные множества правил переписывания и взаимодействие с программным окружением, что позволяет расширить возможности программирования динамических приложений

Acquisition time and reproducibility of continuous arterial spin-labeling perfusion imaging at 3 T

SUMMARY: Arterial spin-labeling (ASL) is a relatively new and noninvasive MR imaging technique, used to measure cerebral blood flow (CBF). Scanning time and reproducibility remain important issues in the clinical applicability of ASL. We expected both to benefit from higher field strengths. We describe that when performing ASL at 3T, 20 averages suffice to obtain steady and reproducible CBF values. Scanning time can be as short as 3 minutes. A rterial spin labeling (ASL) is a noninvasive MR imaging technique, used for visualization and quantification of cerebral perfusion. Cerebral blood flow (CBF) values measured by ASL are comparable with CBF values measured by conventional techniques (eg, positron-emission tomography or susceptibility-weighted MR imaging). ASL is based on magnetic labeling of arterial blood water protons, which are used as an endogenous tracer of flow. Magnetic inversion takes place in a plane proximal to the brain. The decay rate of the labeled spins is sufficiently long to visualize perfusion of brain vasculature and microvasculature. Perfusion images are obtained by subtraction of successively acquired labeled and nonlabeled control images. In general, 40 to 60 paired acquisitions are averaged to improve perfusion signal intensity. ASL sequences differ in the way magnetic labeling is applied and are commonly classified as continuous or pulsed ASL (CASL or PASL, respectively). In CASL, continuous adiabatic inversion of spins is applied. In PASL, labeling is performed at once over a wide spatial range. Pseudocontinuous ASL (pCASL) has been introduced recently and uses a series of discrete labeling pulses. 1-8 Despite its advantages, scanning time and reproducibility remain important issues in the clinical applicability of ASL. The use of higher-field strengths could overcome these issues because of increased signal-to-noise ratio, prolonged T1-weighted relaxation time of labeled blood, and better spatial and temporal resolution. Also, we hypothesized that acquisition-related reproducibility of ASL will improve at higher-field strengths, whereas physiology-related reproducibility will not change. Previous CASL reproducibility studies were performed at 1.5T with test-retest timeframes of at least 1 hour. Technique After approval of the local ethics committee and written informed consent from all volunteers, we scanned 10 volunteers (5 men; age range, 25-33 years) without known cerebrovascular disease during 3 different sessions within 3 weeks. Each session protocol consisted of 2 CASL sequences preceded by MR angiography. All scans were performed on a 3T Intera MR scanner with a transmit-receive head coil from the manufacturer (Philips Medical Systems, Best, the Netherlands). The 3D time-of-flight MR angiography was obtained to allow for careful planning of the labeling plane perpendicular to the distal ascending portion of the internal carotid and basilar arteries, 10 -20 mm below the circle of Willis. For the ASL sequences, we implemented the amplitude-modulated CASL approach described by Alsop and Detre 5 , without compromising clinical specific absorption rate levels. We used spin-echo single-shot echo-planar imaging. The imaging volume was positioned parallel to the labeling plane with its center 60 mm above the labeling plane. ASL parameters were TR, 4500 ms; TE, 32ms; flip angle, 90°; FOV, 210 ϫ 210; section thickness, 7 mm with 1-mm gap; matrix size, 64 ϫ 45 (reconstructed to 64 ϫ 64); 50 averages; labeling duration, 2.0 s; radiofrequency pulse amplitude, 3.5 T; gradient strength, 2.5 mT/m; modulation frequency, 250 Hz; and postlabeling delay, 1.2 to 2.2 s. FSL (FMRIB-Software-Library, Functional Magnetic Resonance Imaging of the Brain Centre, Department of Clinical Neurology, University of Oxford, Oxford, UK) was used for off-line data processing. f ϭ ⌬MR 1a 2␣M con {e ϪwR1a Ϫ e Ϫ(ϩW)R1a } in which f is CBF (mL/g/s), ␣ is the labeling efficiency at 3T (0.68), 7 is the blood-brain partition coefficient (0.98 mL/g), ⌬M is the difference between labeled image and control image intensity, R 1a is the longitudinal relaxation time of blood (0.67 s Ϫ1 ), M con is the average control image intensity, ⌻ is the labeling duration (2 s), and w is the postlabeling delay (1.2-2.2 s)

Stroke Etiology and Thrombus Computed Tomography Characteristics in Patients With Acute Ischemic Stroke:A MR CLEAN Registry Substudy

Background and Purpose - If a relationship between stroke etiology and thrombus computed tomography characteristics exists, assessing these characteristics in clinical practice could serve as a useful additional diagnostic tool for the identification of stroke subtype. Our purpose was to study the association of stroke etiology and thrombus computed tomography characteristics in patients with acute ischemic stroke due to a large vessel occlusion. Methods - For 1429 consecutive patients enrolled in the MR CLEAN Registry, we determined stroke cause as defined by the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) criteria. The association of stroke etiology with the hyperdense artery sign, clot burden score, and thrombus location was estimated with univariable and multivariable binary and ordinal logistic regression. Additionally, for 367 patients with available thin-section imaging, we assessed the association of stroke etiology with absolute and relative thrombus attenuation, distance from internal carotid artery-terminus to thrombus, thrombus length, and thrombus attenuation increase with univariable and multivariable linear regression. Results - Compared with cardioembolic strokes, noncardioembolic strokes were associated with presence of hyperdense artery sign (odds ratio, 2.2 [95% CI, 1.6-3.0]), lower clot burden score (common odds ratio, 0.4 [95% CI, 0.3-0.6]), shift towards a more proximal thrombus location (common odds ratio, 0.2 [95% CI, 0.2-0.3]), higher absolute thrombus attenuation (β, 3.6 [95% CI, 0.9-6.4]), decrease in distance from the ICA-terminus (β, -5.7 [95% CI, -8.3 to -3.0]), and longer thrombi (β, 8.6 [95% CI, 6.5-10.7]), based on univariable analysis. Thrombus characteristics of strokes with undetermined cause were similar to those of cardioembolic strokes. Conclusions - Thrombus computed tomography characteristics of cardioembolic stroke are distinct from those of noncardioembolic stroke. Additionally, our study supports the general hypothesis that many cryptogenic strokes have a cardioembolic cause. Further research should focus on the use of thrombus computed tomography characteristics as a diagnostic tool for stroke cause in clinical practice

Cardiac output, cerebral blood flow and cognition in patients with severe aortic valve stenosis undergoing transcatheter aortic valve implantation:design and rationale of the CAPITA study

Background : Approximately one-third of patients with symptomatic severe aortic valve stenosis who are scheduled for transcatheter aortic valve implantation (TAVI) have some degree of cognitive impairment. TAVI may have negative cognitive effects due to periprocedural micro-emboli inducing cerebral infarction. On the contrary, TAVI may also have positive cognitive effects due to increases in cardiac output and cerebral blood flow (CBF). However, studies that systematically assess these effects are scarce. Therefore, the main aim of this study is to assess cerebral and cognitive outcomes in patients with severe aortic valve stenosis undergoing TAVI. Study design : In the prospective CAPITA (CArdiac OutPut, Cerebral Blood Flow and Cognition In Patients With Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation) study, cerebral and cognitive outcomes are assessed in patients undergoing TAVI. One day before and 3 months after TAVI, patients will undergo echocardiography (cardiac output, valve function), brain magnetic resonance imaging (CBF, structural lesions) and extensive neuropsychological assessment. To assess longer-term effects of TAVI, patients will again undergo echocardiography and neuropsychological assessment 1 year after the procedure. The co-primary outcome measures are change in CBF (in ml/100 g per min) and change in global cognitive functioning (Z-score) between baseline and 3‑month follow-up. Secondary objectives include change in cardiac output, white matter hyperintensities and other structural brain lesions. (ClinicalTrials.gov identifier NCT05481008) Conclusion : The CAPITA study is the first study designed to systematically assess positive and negative cerebral and cognitive outcomes after TAVI. We hypothesise that TAVI improves cardiac output, CBF and cognitive functioning.</p

Effect of first pass reperfusion on outcome in patients with posterior circulation ischemic stroke

BACKGROUND: First pass reperfusion (FPR), that is, excellent reperfusion (expanded treatment in cerebral ischemia (eTICI) 2C-3) in one pass, after endovascular treatment (EVT) of an occluded artery in the anterior circulation, is associated with favorable clinical outcome, even when compared with multiple pass excellent reperfusion (MPR). In patients with posterior circulation ischemic stroke (PCS), the same association is expected, but currently unknown. We aimed to assess characteristics associated with FPR and the influence of FPR versus MPR on outcomes in patients with PCS. METHODS: We used data from the MR CLEAN Registry, a prospective observational study. The effect of FPR on 24-hour National Institutes of Health Stroke Scale (NIHSS) score, as percentage reduction, and on modified Rankin Scale (mRS) scores at 3 months, was tested with linear and ordinal logistic regression models. RESULTS: Of 224 patients with PCS, 45 patients had FPR, 47 had MPR, and 90 had no excellent reperfusion (eTICI <2C). We did not find an association between any of the patient, imaging, or treatment characteristics and FPR. FPR was associated with better NIHSS (-45% (95% CI: -65% to -12%)) and better mRS scores (adjusted common odds ratio (acOR): 2.16 (95% CI: 1.23 to 3.79)) compared with no FPR. Outcomes after FPR were also more favorable compared with MPR, but the effect was smaller and not statistically significant (NIHSS: -14% (95% CI: -51% to 49%), mRS acOR: 1.50 (95% CI: 0.75 to 3.00)). CONCLUSIONS: FPR in patients with PCS is associated with favorable clinical outcome in comparison with no FPR. In comparison with MPR, the effect of FPR was no longer statistically significant. Nevertheless, our data support the notion that FPR should be the treatment target to pursue in every patient treated with EVT

Non-Conventional Approaches To Property Value Assessment

Lack of precision is common in property value assessment. Recently non-conventional methods, such as neural networks based methods, have been introduced in property value assessment as an attempt to better address this lack of precision and uncertainty. Although fuzzy logic has been suggested as another possible solution, no other artificial intelligence methods have been applied to real estate value assessment other than neural network based methods. This paper presents the results of using two new non-conventional methods, fuzzy logic and memory-based reasoning, in evaluating residential property values for a real data set. The paper compares the results with those obtained using neural networks and multiple regression. Methods of feature reduction, such as principal component analysis and variable selection, have also been used for possible improvement of the final results.&nbsp; The results indicate that no single one of the new methods is consistently superior for the given data set