Apparent diffusion coefficient (ADC) measurements may be more reliable and reproducible than lesion volume on diffusion-weighted images from patients with acute ischaemic stroke-implications for study design

APIS: a paired CT-MRI dataset for ischemic stroke segmentation - methods and challenges

Stroke, the second leading cause of mortality globally, predominantly results from ischemic conditions. Immediate attention and diagnosis, related to the characterization of brain lesions, play a crucial role in patient prognosis. Standard stroke protocols include an initial evaluation from a non-contrast CT to discriminate between hemorrhage and ischemia. However, non-contrast CTs lack sensitivity in detecting subtle ischemic changes in this phase. Alternatively, diffusion-weighted MRI studies provide enhanced capabilities, yet are constrained by limited availability and higher costs. Hence, we idealize new approaches that integrate ADC stroke lesion findings into CT, to enhance the analysis and accelerate stroke patient management. This study details a public challenge where scientists applied top computational strategies to delineate stroke lesions on CT scans, utilizing paired ADC information. Also, it constitutes the first effort to build a paired dataset with NCCT and ADC studies of acute ischemic stroke patients. Submitted algorithms were validated with respect to the references of two expert radiologists. The best achieved Dice score was 0.2 over a test study with 36 patient studies. Despite all the teams employing specialized deep learning tools, results reveal limitations of computational approaches to support the segmentation of small lesions with heterogeneous density.

Robust Ensemble of Two Different Multimodal Approaches to Segment 3D Ischemic Stroke Segmentation Using Brain Tumor Representation Among Multiple Center Datasets

Ischemic stroke segmentation at an acute stage is vital in assessing the severity of patients' impairment and guiding therapeutic decision-making for reperfusion. Although many deep learning studies have shown attractive performance in medical segmentation, it is difficult to use these models trained on public data with private hospitals' datasets. Here, we demonstrate an ensemble model that employs two different multimodal approaches for generalization, a more effective way to perform on external datasets. First, after we jointly train a segmentation model on diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) MR modalities, the model is inferred on the DWI images. Second, a channel-wise segmentation model is trained by concatenating the DWI and ADC images as input, and then is inferred using both MR modalities. Before training with ischemic stroke data, we utilized BraTS 2021, a public brain tumor dataset, for transfer learning. An extensive ablation study evaluates which strategy learns better representations for ischemic stroke segmentation. In our study, nnU-Net well-known for robustness is selected as our baseline model. Our proposed method is evaluated on three different datasets: the Asan Medical Center (AMC) I and II, and the 2022 Ischemic Stroke Lesion Segmentation (ISLES). Our experiments are widely validated over a large, multi-center, and multi-scanner dataset with a huge amount of 846 scans. Not only stroke lesion models can benefit from transfer learning using brain tumor data, but combining the MR modalities using different training schemes also highly improves segmentation performance. The method achieved a top-1 ranking in the ongoing ISLES'22 challenge and performed particularly well on lesion-wise metrics of interest to neuroradiologists, achieving a Dice coefficient of 78.69% and a lesion-wise F1 score of 82.46%. Also, the method was relatively robust on the AMC I (Dice, 60.35%; lesion-wise F1, 68.30%) and II (Dice; 74.12%; lesion-wise F1, 67.53%) datasets in different settings. The high segmentation accuracy of our proposed method could improve radiologists' ability to detect ischemic stroke lesions in MRI images. Our model weights and inference code are available on https://github.com/MDOpx/ISLES22-model-inference .

Evaluation of neuregulin-1's neuroprotection against ischemic injury in rats using diffusion tensor imaging

Stroke is a devastating neurovascular disorder that results in damage to neurons and white matter tracts. It has been previously demonstrated that neuregulin-1 (NRG-1) protects neurons from ischemic injury following stroke. Here, diffusion tensor imaging (DTI) was utilized to characterize the effects of NRG-1 treatment on cererbral infarction and integrity of white matter after ischemic insult using a permanent middle celebral artery occlusion (pMCAo) rat model. In the present study, sixteen Sprague-Dawley rats underwent pMCAo surgery and received either a single intra-arterial bolus (20 μg/kg) dose of NRG-1 or saline immediately prior to pMCAo. MRI including T2-weighted imaging and DTI was performed in the first 3 h post stroke, and repeated 48 h later. It is found that the stroke infarction was significantly reduced in the NRG-1 treated group. Also, NRG-1 prevented the reduction of fractional anisotropy (FA) in white matter tracts of fornix and corpus callosum (CC), indicating its protection of CC and fornix white matter bundles from ischemia insult. As a conclusion, the present DTI results demonstrate that NRG-1 has significantly neuroprotective effects in both cerebral cortex and white matter including corpus callosum and fornix during acute stroke. In particular, NRG-1 is more effective on stroke lesion with mild ischemia. As CC and fornix white matter bundles play critical roles in transcallosal connectivity and hippocampal projections respectively in the central nervous system, the findings could provide complementary information for better understanding the biological mechanism of NRG-1's neuroprotection in ischemic tissues and neurobehavioral effects.

Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric

This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.

Apparent diffusion coefficient thresholds and diffusion lesion volume in acute stroke

BACKGROUND

Apparent diffusion coefficient (ADC) thresholds are used to determine acute stroke lesion volume, but the reliability of this approach and comparability to the volume of the magnetic resonance diffusion-weighted imaging (MR-DWI) hyperintense lesion is unclear.

METHODS

We prospectively recruited and clinically assessed patients who had experienced acute ischemic stroke and performed DWI less than 24 hours and at 3 to 7 days after stroke. We compared the volume of the manually outlined DW hyperintense lesion (reference standard) with lesion volumes derived from 3 commonly used ADC thresholds: .55 × 10(-3)/mm(2)/second(-1), .65 × 10(-3)/mm(2)/second(-1), and .75 × 10(-3)/mm(2)/second(-1), with and without "editing" of erroneous tissue. We compared the volumes obtained by reference standard, "raw," and "edited" thresholds.

RESULTS

Among 33 representative patients, the acute DWI lesion volume was 15,284 mm(3); the median unedited/edited ADC volumes were 52,972/2786 mm(3), 92,707/6,987 mm(3), and 227,681/unmeasureable mm(3) (.55 × 10(-3)/mm(2)/second(-1), .65 × 10(-3)/mm(2)/second(-1), and .75 × 10(-3)/mm(2)/second(-1) thresholds, respectively). Subacute lesions gave similar differences. These differences between edited and unedited diffusion-weighted imaging and ADC volumes were statistically significant.

CONCLUSIONS

Threshold-derived ADC volumes require substantial manual editing to avoid over- or underestimating the visible DWI lesion and should be used with caution.

Multicentre imaging measurements for oncology and in the brain

Multicentre imaging studies of brain tumours (and other tumour and brain studies) can enable a large group of patients to be studied, yet they present challenging technical problems. Differences between centres can be characterised, understood and minimised by use of phantoms (test objects) and normal control subjects. Normal white matter forms an excellent standard for some MRI parameters (e.g. diffusion or magnetisation transfer) because the normal biological range is low (<2-3%) and the measurements will reflect this, provided the acquisition sequence is controlled. MR phantoms have benefits and they are necessary for some parameters (e.g. tumour volume). Techniques for temperature monitoring and control are given. In a multicentre study or treatment trial, between-centre variation should be minimised. In a cross-sectional study, all groups should be represented at each centre and the effect of centre added as a covariate in the statistical analysis. In a serial study of disease progression or treatment effect, individual patients should receive all of their scans at the same centre; the power is then limited by the within-subject reproducibility. Sources of variation that are generic to any imaging method and analysis parameters include MR sequence mismatch, B(1) errors, CT effective tube potential, region of interest generation and segmentation procedure. Specific tissue parameters are analysed in detail to identify the major sources of variation and the most appropriate phantoms or normal studies. These include dynamic contrast-enhanced and dynamic susceptibility contrast gadolinium imaging, T(1), diffusion, magnetisation transfer, spectroscopy, tumour volume, arterial spin labelling and CT perfusion.

Neuroimaging in acute ischaemic stroke: insights into unanswered questions of pathophysiology

The treatment of acute ischaemic stroke is based on the principle that there is ischaemic but still potentially salvageable tissue that could be rescued if blood flow could be restored quickly. It is assumed that salvage might only be possible in the first few hours, and that infarct expansion is a direct result of failed recanalization of the main artery. This concept arose from experimental work in the 1970s, supported more recently by studies using imaging to identify penumbral tissue. However, although magnetic resonance diffusion and perfusion imaging is a way of imaging penumbral tissue and has been around for over a decade, it is not an easy technique to apply in practice and its use has produced conflicting results. Computed tomography perfusion, and any other tissue perfusion imaging technique, is likely to encounter the same difficulties. Indeed many factors, other than the presence of a diffusion-perfusion mismatch acutely, may determine or influence ultimate tissue fate even days after the stroke, and in turn, clinical outcome. Many of these potential influences are beginning to emerge from studies using different forms of imaging at later times after stroke. This review will explore the information now emerging from imaging studies in large artery ischaemic stroke to summarize knowledge to date and indicate unresolved issues for the future.

Correlating lesion size and location to deficits after ischemic stroke: the influence of accounting for altered peri-necrotic tissue and incidental silent infarcts

BACKGROUND

Investigators frequently quantify and evaluate the location and size of stroke lesions to help uncover cerebral anatomical correlates of deficits observed after first-ever stroke. However, it is common to discover silent infarcts such as lacunes in patients identified clinically as 'first-ever' stroke, and it is unclear if including these incidental findings may impact lesion-based investigations of brain-behaviour relationships. There is also debate concerning how to best define the boundaries of necrotic stroke lesions that blend in an ill-defined way into surrounding tissue, as it is unclear whether including this altered peri-necrotic tissue region may influence studies of brain-behaviour relationships. Therefore, for patients with clinically overt stroke, we examined whether including altered peri-necrotic tissue and incidental silent strokes influenced either lesion volume correlations with a measure of sensorimotor impairment or the anatomical localization of this impairment established using subtraction lesion analysis.

METHODS

Chronic stroke lesions of 41 patients were manually traced from digital T1-MRI to sequentially include the: necrotic lesion core, altered peri-necrotic tissue, silent lesions in the same hemisphere as the index lesion, and silent lesions in the opposite hemisphere. Lesion volumes for each region were examined for correlation with motor impairment scores, and subtraction analysis was used to highlight anatomical lesion loci associated with this deficit.

RESULTS

For subtraction lesion analysis, including peri-necrotic tissue resulted in a larger region of more frequent damage being seen in the basal ganglia. For correlational analysis, only the volume of the lesion core was significantly associated with motor impairment scores (r = -0.35, p = 0.025). In a sub-analysis of patients with small subcortical index lesions, adding silent lesions in the opposite hemisphere to the volume of the index stroke strengthened the volume-impairment association.

CONCLUSIONS

Including peri-necrotic tissue strengthened lesion localization analysis, but the influence of peri-necrotic tissue and incidental lesions on lesion volume correlations with motor impairment was negligible barring a small index lesion. Overall, the potential influence of incidental lesions and peri-necrotic tissue on brain-behaviour relationships may depend on the characteristics of the index stroke and on whether one is examining the relationship between lesion volume and impairment or lesion location and impairment.

Relationship of pre-surgery metabolic and physiological MR imaging parameters to survival for patients with untreated GBM

Glioblastoma Multiforme (GBM) are heterogeneous lesions, both in terms of their appearance on anatomic images and their response to therapy. The goal of this study was to evaluate the prognostic value of parameters derived from physiological and metabolic images of these lesions. Fifty-six patients with GBM were scanned immediately before surgical resection using conventional anatomical MR imaging and, where possible, perfusion-weighted imaging, diffusion-weighted imaging, and proton MR spectroscopic imaging. The median survival time was 517 days, with 15 patients censored. Absolute anatomic lesion volumes were not associated with survival but patients for whom the combined volume of contrast enhancement and necrosis was a large percentage of the T2 hyperintense lesion had relatively poor survival. Other volumetric parameters linked with less favorable survival were the volume of the region with elevated choline to N-acetylaspartate index (CNI) and the volume within the T2 lesion that had apparent diffusion coefficient (ADC) less than 1.5 times that in white matter. Intensity parameters associated with survival were the maximum and the sum of levels of lactate and of lipid within the CNI lesion, as well as the magnitude of the 10th percentile of the normalized ADC within the contrast-enhancing lesion. Patients whose imaging parameters indicating that lesions with a relatively large percentage with breakdown of the blood brain barrier or necrosis, large regions with abnormal metabolism or areas with restricted diffusion have relatively poor survival. These parameters may provide useful information for predicting outcome and for the stratification of patients into high or low risk groups for clinical trials.

Repeatability of echo-planar-based diffusion measurements of the human prostate at 3 T

Echo-planar-based diffusion-weighted imaging (DWI) of the prostate is increasingly being suggested as a viable technique, complementing information derived from conventional magnetic resonance imaging methods for use in tissue discrimination. DWI has also been suggested as a potentially useful tool in the assessment of tumor response to treatment. In this study, the repeatability of apparent diffusion coefficient (ADC) values obtained from both DWI and diffusion tensor imaging (DTI) has been assessed as a precursor to determining the magnitude of treatment-induced changes required for reliable detection. The repeatability values of DWI and DTI were found to be similar, with ADC values repeatable to within 35% or less over a short time period of a few minutes and a longer time period of a month. Fractional anisotropy measurements were found to be less repeatable (between 26% and 71%), and any changes duly recorded in longitudinal studies must therefore be treated with a degree of caution.

Acute Ischemic Stroke Lesion Measurement on Diffusion-weighted Imaging–Important Considerations in Designing Acute Stroke Trials With Magnetic Resonance Imaging

BACKGROUND

In acute ischemic stroke, magnetic resonance diffusion-weighted imaging (DWI) is increasingly used to select patients for inclusion or as a surrogate outcome marker in clinical trials, or in routine practice. Little is known of what factors might affect DWI lesion size measurement. We examined morphologic factors that might affect DWI lesion measurement.

METHODS

On DWI obtained less than 24 hours after stroke, we categorized lesions according to DWI appearance (solitary or multifocal; well-defined or ill-defined edges), lesion size (</>5 cm(3)), and time to imaging (<6, 6-12, and 12-24 hours). Two observers (senior neuroradiologist; less-experienced imaging neuroscientist) measured all lesions. In 4 representative cases we assessed DWI lesion volume using two apparent diffusion coefficient thresholds (0.55 and 0.65 x 10(-3) mm(2)/s).

RESULTS

Among 63 patients (33% imaged < 6 hours after stroke), the neuroradiologist measured larger lesion volumes than the imaging neuroscientist (median 4.29 v 3.50 cm(3), respectively, P < .01). Differences between observers were greatest in patients scanned within 6 hours of stroke, in multifocal ill-defined or large lesions (all P < .01). Both apparent diffusion coefficient thresholds underestimated lesion extent and included remote normal tissue, particularly in multifocal ill-defined large lesions.

CONCLUSION

DWI lesion characteristics influence lesion volume measurement. Large, multifocal, ill-defined DWI lesions obtained in less than 6 hours have the greatest variability. Trials using DWI should account for this in their study design.