Associations Between Features of Nonstenosing Carotid Plaque on Computed Tomographic Angiography and Ischemic Stroke Subtypes

Background

Thromboembolism from nonstenosing carotid plaques may be an underrecognized cause of embolic strokes of undetermined source (ESUS). We evaluated the association between features of nonstenosing atherosclerotic plaque on computed tomographic angiography and ESUS.

Methods and Results

We identified consecutive acute ischemic stroke patients from 2011 to 2015 who had unilateral anterior territory infarction on brain magnetic resonance imaging and a neck computed tomographic angiography. We included ESUS cases and as controls, cardioembolic strokes. Patients with ≥50% internal carotid artery atherosclerotic stenosis ipsilateral to the stroke were excluded from this analysis. Reviewers blinded to infarct location and stroke cause retrospectively evaluated computed tomographic angiography studies for specific plaque features including thickness of the total, soft, and calcified plaque; presence of ulceration; and perivascular fat attenuation. Paired t tests and McNemar's test for paired data were used to compare plaque features ipsilateral versus contralateral to the side of infarction. Ninety‐one patients with ESUS or cardioembolic stroke were included in this study. Total plaque thickness was greater on the infarcted side (2.1±2.0 mm) than the contralateral side (1.2±1.5 mm) (P=0.006) among ESUS cases, but not among cardioembolic cases (1.9±1.6 mm versus 1.8±1.6 mm) (P=0.32).

Conclusions

Among ESUS cases, total plaque thickness was greater ipsilateral to the side of infarction than on the contralateral, stroke‐free side. No such side‐to‐side differences were apparent in cardioembolic strokes. Our findings suggest that nonstenosing large‐artery atherosclerotic plaques represent one underlying mechanism of ESUS.

Causes of Acute Stroke: A Patterned Approach

Acute stroke is a leading cause of morbidity and mortality in the United States. Acute ischemic strokes have been classified according to The Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification system, and this system aids in proper management. Nearly every patient who presents to a hospital with acute stroke symptoms has some form of emergent imaging. As such, imaging plays an important role in early diagnosis and management. This article reviews the imaging patterns of acute strokes, and how the infarct pattern and imaging characteristics can suggest an underlying cause.

Abstract WP92: Radiologist Inter-rater Reliability of Prehospital Alberta Stroke Program Early CT Scores on a Mobile Stroke Unit

Introduction: The computed tomography (CT) capabilities of mobile stroke units (MSUs) may facilitate prehospital triaging of patients with suspected large-vessel occlusion directly to thrombectomy-capable centers. However, little is known about the reliability of radiological interpretation of early ischemic changes on prehospital CTs.

Methods: We identified all patients transported by the NewYork-Presbyterian MSU to Weill Cornell Medical Center with the diagnosis of acute ischemic stroke, transient ischemic attack, or stroke mimic between October 3, 2016 and December 31, 2017. All patients underwent noncontrast head CT on board the MSU using a CereTom® scanner. As controls, we matched these patients 1:1 by diagnosis to patients who were transported by standard ambulance and underwent noncontrast brain CT in our emergency department (ED) over the same period. Two neuroradiologists, blinded to patients’ characteristics and final diagnosis, independently calculated Alberta Stroke Program Early CT Scores (ASPECTS) on all scans. Weighted percent agreement and Cohen’s κ were used to assess inter-rater reliability, and paired t-tests were used to compare these metrics between MSU and ED scans.

Results: Among 46 MSU patients and 46 ED patients, 52% had a diagnosis of acute ischemic stroke, 46% a diagnosis of stroke mimic, and 2% a diagnosis of transient ischemic attack. For ASPECTS score as a continuous outcome, the weighted inter-rater agreement was 98% for MSU scans versus 96% for ED scans (mean difference, 2%; 95% CI, -1% to 5%) and the weighted κ was 0.49 for MSU scans versus 0.54 for ED scans (mean difference, -0.05; 95% CI, -0.61 to 0.51). For ASPECTS score categorized as 0-4, 5-7, or 8-10, the weighted inter-rater agreement was 99% for MSU scans versus 97% for ED scans (mean difference, 2%; 95% CI, -2% to 7%) and the weighted κ was 0.66 for MSU scans versus 0.55 for ED scans (mean difference, 0.10; 95% CI, -0.87 to 1.08).

Conclusions: In a sample of 96 patients, which limited our power to detect small differences, we found no substantial difference in the inter-rater reliability of ASPECTS scores obtained from MSU CTs versus ED CTs.

Effect of Clinical History on Interpretation of Computed Tomography for Acute Stroke

Objective

We assessed whether providing detailed clinical information alongside computed tomography (CT) images improves their interpretation for acute stroke.

Methods

Using the prospective Cornell AcutE Stroke Academic Registry, we randomly selected 100 patients who underwent noncontrast head CT within 6 hours of transient ischemic attack or minor acute ischemic stroke and underwent magnetic resonance imaging (MRI) within 6 hours of the CT. Three radiologist investigators evaluated each of the 100 CT studies twice, once with and once without accompanying information on medical history, signs, and symptoms. In random sequence, each study was interpreted in one condition (ie, with or without detailed accompanying information) and then after a 4-week washout period, in the opposite condition. Using MRI diffusion-weighted imaging (DWI) as the reference standard, we classified CT interpretations as correct (true positives or negatives) or incorrect (false positives or negatives). We used logistic regression with sandwich estimators to compare the proportion of correct interpretations.

Results

In patients with DWI-defined infarcts, acute ischemia was called on 20% of CTs with detailed history and 18% without history. In patients without infarcts, the absence of ischemia was called on 77% of CTs with history and 77% without history. The proportion of correct interpretations of CTs accompanied by detailed clinical history (49%) did not differ significantly from those without history (47%; odds ratio: 1.1; 95% confidence interval: 0.8-1.4).

Conclusions

Reported findings on head CT for evaluation of suspected acute ischemic stroke were similar regardless of whether detailed clinical history was provided.

Abstract TP60: Effect of Clinical History in Radiologist Interpretation of Computed Tomography for Acute Stroke

Introduction: Computed tomography (CT) is widely used for suspected acute ischemic stroke. Radiologists often interpret these scans with limited information and may benefit from more complete knowledge of the clinical situation.

Hypothesis: Providing detailed clinical information improves the interpretation of CTs for acute stroke.

Methods: In the prospective Cornell AcutE Stroke Academic Registry (CAESAR), we randomly selected 100 patients who underwent noncontrast head CT within 6 hours of transient ischemic attack (TIA) or minor acute ischemic stroke (National Institutes of Health Stroke Scale score ≤3) and underwent magnetic resonance imaging (MRI) within 6 hours of the CT. Three radiologists each twice evaluated CT studies both with and without accompanying information on the patient’s medical history, neurological deficit, and symptom time course. In random sequence, each study was interpreted by each radiologist in one condition (i.e., with or without detailed accompanying information), and then after a 4-week washout period, the same study was interpreted again by each radiologist in the opposite condition. Using MRI diffusion weighted imaging (DWI) as the reference standard for brain infarction, we classified CT interpretations as correct (true positives or true negatives) or incorrect (false positives or false negatives). McNemar’s test was used to compare the proportion of correct interpretations in the condition with detailed clinical information versus the condition without detailed information.

Results: In patients with DWI-defined infarcts, acute ischemia was correctly called on 20% (95% confidence interval [CI], 14-27%) of CTs with detailed history versus 18% (95% CI, 12-25%) without history. In patients without infarcts, the absence of acute ischemia was correctly called on 77% (95% CI, 70-84%) of CTs with history and 77% (95% CI, 69-83%) without history. The proportion of correct interpretations of CTs accompanied by detailed clinical history (49% [95% CI, 43-54%]) did not differ significantly from those without history (47% [95% CI, 42-53%]) ( P = 0.67).

Conclusions: Reported findings on head CT for evaluation of suspected acute ischemic stroke were similar regardless of whether detailed clinical history was provided.

Abstract TP58: A Novel Deep Learning Approach for Automated Diagnosis of Cerebral Infarction on Computed Tomography

Introduction: Deep learning is a novel machine learning approach that enables automated extraction and classification of imaging features. We aimed to use deep learning to enhance detection of brain infarction.

Methods: Patients with acute ischemic stroke admitted to our institution between 2011-2015 were prospectively registered in an IRB-approved database. On a subset of these patients, radiologists annotated the images by marking infarct area. Data was split randomly into a training set and test set (80:20). Deep learning models, including a 3D multi-scale fully convolutional neural network, were developed and trained on the training set and independently tested on the test set. The performance of this model was compared to the expert consensus interpretation. Diagnostic test characteristics including the area under the curve (AUC) for the deep learning algorithm were calculated both at a voxel and imaging-study level. Computer-generated heat maps were created to denote the possibility of infarct.

Results: The study group included 114 patients (training set n = 92, test set n = 22). In the training set of 5,888 images, infarction was present in 602 (10.2%) images. In the testing set of 920 images, infarction was present in 130 (14.1%) images. A total of 1.5 billion voxels were used to train the model. The AUC for the deep learning algorithm for voxel accuracy was 0.973 (95% CI 0.972-0.974). Voxel accuracy, sensitivity, and specificity were 92%, 93%, and 92%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) were 86% and 92%, respectively. The AUC for the deep learning algorithm for automated diagnosis of infarction at the imaging-study level was 0.91 (95% CI 0.90-0.94). Diagnostic accuracy, sensitivity, and specificity were 88%, 65%, and 91%, respectively. PPV and NPV were 49% and 95%, respectively.

Conclusions: A machine-learned algorithm employing a novel deep learning algorithm enabled accurate diagnosis of brain infarction.

Association between Carotid Plaque Features on CTA and Cerebrovascular Ischemia: A Systematic Review and Meta-Analysis

BACKGROUND

CTA is a widely available imaging examination that may allow the evaluation of high-risk carotid plaque features.

PURPOSE

Our aim was to evaluate the association between specific carotid plaque features on CTA and ipsilateral cerebrovascular ischemia.

DATA SOURCES

We performed a systematic review of Ovid MEDLINE, Ovid Embase, Scopus, and the Cochrane Library from inception to March 2016 for articles that evaluated the relationship between CTA-detected carotid plaque features and ischemic events, defined as ipsilateral ischemic stroke or transient ischemic attack.

STUDY SELECTION

Sixteen studies were ultimately included after screening 12,557.

DATA ANALYSIS

Two readers recorded data from each study and assessed the study quality with all disagreements resolved by a third reader. A random-effects OR was used to evaluate the association between cerebrovascular ischemia and each of the evaluated plaque features.

DATA SYNTHESIS

We found significant positive relationships with cerebrovascular ischemia for the presence of soft plaque (OR, 2.9; 95% CI, 1.4-6.0), plaque ulceration (OR, 2.2; 95% CI, 1.4-3.4), and increased common carotid artery wall thickness (OR, 6.2; 95% CI, 2.5-15.6). We found a significant negative relationship between calcified plaque and ipsilateral ischemia (OR, 0.5; 95% CI, 0.4-0.7).

LIMITATIONS

We found heterogeneity in the existing literature secondary to lack of standardized plaque features and clinical definitions.

CONCLUSIONS

Soft plaque, plaque ulceration, and increased common carotid artery wall thickness on CTA are associated with ipsilateral cerebrovascular ischemia, while calcified plaque is negatively associated with downstream ischemic events.

Hepatocellular carcinoma detection: diagnostic performance of a simulated abbreviated MRI protocol combining diffusion-weighted and T1-weighted imaging at the delayed phase post gadoxetic acid

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of a "simulated" abbreviated MRI (AMRI) protocol using diffusion-weighted imaging (DWI) and T1-weighted (T1w) imaging obtained at the hepatobiliary phase (HBP) post gadoxetic acid injection alone and in combination, compared to dynamic contrast-enhanced (CE)-T1w imaging for the detection of hepatocellular carcinoma (HCC).

METHODS

This was an IRB approved HIPAA compliant retrospective single institution study including patients with liver disease who underwent gadoxetic acid-enhanced MRI for HCC diagnosis. Three independent observers assessed 2 sets of images (full CE-set and AMRI including DWI+T1w-HBP). Diagnostic performance of T1w-HBP and DWI alone and in combination was compared to that of CE-set. All imaging sets included unenhanced T1w and T2w sequences. A preliminary analysis was performed to assess cost savings of AMRI protocol compared to a full MRI study.

RESULTS

174 patients including 62 with 80 HCCs were assessed. Equivalent per-patient sensitivity and negative predictive value (NPV) were observed for DWI (85.5% and 92.2%, pooled data) and T1w-HBP (89.8% and 94.2%) (P = 0.1-0.7), while these were significantly lower for the full AMRI protocol (DWI+T1w-HBP, 80.6% and 80%, P = 0.02) when compared to CE-set (90.3% and 94.9%). Higher specificity and positive predictive value were observed for CE-set vs. AMRI (P = 0.02). The estimated cost reduction of AMRI versus full MRI ranged between 30.7 and 49.0%.

CONCLUSION

AMRI using DWI and T1w-HBP has a clinically acceptable sensitivity and NPV for HCC detection. This could serve as the basis for a future study assessing AMRI for HCC screening and surveillance.

Gadolinium Enhancement in Intracranial Atherosclerotic Plaque and Ischemic Stroke: A Systematic Review and Meta-Analysis

Background

Gadolinium enhancement on high‐resolution magnetic resonance imaging (MRI) has been proposed as a marker of inflammation and instability in intracranial atherosclerotic plaque. We performed a systematic review and meta‐analysis to summarize the association between intracranial atherosclerotic plaque enhancement and acute ischemic stroke.

Methods and Results

We searched the medical literature to identify studies of patients undergoing intracranial vessel wall MRI for evaluation of intracranial atherosclerotic plaque. We recorded study data and assessed study quality, with disagreements in data extraction resolved by a third reader. A random‐effects odds ratio was used to assess whether, in any given patient, cerebral infarction was more likely in the vascular territory supplied by an artery with MRI‐detected plaque enhancement as compared to territory supplied by an artery without enhancement. We calculated between‐study heterogeneity using the Cochrane Q test and publication bias using the Begg‐Mazumdar test. Eight articles published between 2011 and 2015 met inclusion criteria. These studies provided information about plaque enhancement characteristics from 295 arteries in 330 patients. We found a significant positive relationship between MRI enhancement and cerebral infarction in the same vascular territory, with a random effects odds ratio of 10.8 (95% CI 4.1–28.1, P<0.001). No significant heterogeneity (Q=11.08, P=0.14) or publication bias (P=0.80) was present.

Conclusions

Intracranial plaque enhancement on high‐resolution vessel wall MRI is strongly associated with ischemic stroke. Evaluation for plaque enhancement on MRI may be a useful test to improve diagnostic yield in patients with ischemic strokes of undetermined etiology.

Hepatocellular carcinoma: IVIM diffusion quantification for prediction of tumor necrosis compared to enhancement ratios

Purpose

To correlate intra voxel incoherent motion (IVIM) diffusion parameters of liver parenchyma and hepatocellular carcinoma (HCC) with degree of liver/tumor enhancement and necrosis; and to assess the diagnostic performance of diffusion parameters vs. enhancement ratios (ER) for prediction of complete tumor necrosis.

Patients and methods

In this IRB approved HIPAA compliant study, we included 46 patients with HCC who underwent IVIM diffusion-weighted (DW) MRI in addition to routine sequences at 3.0 T. True diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (PF) and apparent diffusion coefficient (ADC) were quantified in tumors and liver parenchyma. Tumor ER were calculated using contrast-enhanced imaging, and degree of tumor necrosis was assessed using post-contrast image subtraction. IVIM parameters and ER were compared between HCC and background liver and between necrotic and viable tumor components. ROC analysis for prediction of complete tumor necrosis was performed.

Results

79 HCCs were assessed (mean size 2.5 cm). D, PF and ADC were significantly higher in HCC vs. liver (p < 0.0001). There were weak significant negative/positive correlations between D/PF and ER, and significant correlations between D/PF/ADC and tumor necrosis (for D, r 0.452, p < 0.001). Among diffusion parameters, D had the highest area under the curve (AUC 0.811) for predicting complete tumor necrosis. ER outperformed diffusion parameters for prediction of complete tumor necrosis (AUC > 0.95, p < 0.002).

Conclusion

D has a reasonable diagnostic performance for predicting complete tumor necrosis, however lower than that of contrast-enhanced imaging.

Abdominal 4D flow MR imaging in a breath hold: combination of spiral sampling and dynamic compressed sensing for highly accelerated acquisition

PURPOSE

To develop a highly accelerated phase-contrast cardiac-gated volume flow measurement (four-dimensional [4D] flow) magnetic resonance (MR) imaging technique based on spiral sampling and dynamic compressed sensing and to compare this technique with established phase-contrast imaging techniques for the quantification of blood flow in abdominal vessels.

MATERIALS AND METHODS

This single-center prospective study was compliant with HIPAA and approved by the institutional review board. Ten subjects (nine men, one woman; mean age, 51 years; age range, 30-70 years) were enrolled. Seven patients had liver disease. Written informed consent was obtained from all participants. Two 4D flow acquisitions were performed in each subject, one with use of Cartesian sampling with respiratory tracking and the other with use of spiral sampling and a breath hold. Cartesian two-dimensional (2D) cine phase-contrast images were also acquired in the portal vein. Two observers independently assessed vessel conspicuity on phase-contrast three-dimensional angiograms. Quantitative flow parameters were measured by two independent observers in major abdominal vessels. Intertechnique concordance was quantified by using Bland-Altman and logistic regression analyses.

RESULTS

There was moderate to substantial agreement in vessel conspicuity between 4D flow acquisitions in arteries and veins (κ = 0.71 and 0.61, respectively, for observer 1; κ = 0.71 and 0.44 for observer 2), whereas more artifacts were observed with spiral 4D flow (κ = 0.30 and 0.20). Quantitative measurements in abdominal vessels showed good equivalence between spiral and Cartesian 4D flow techniques (lower bound of the 95% confidence interval: 63%, 77%, 60%, and 64% for flow, area, average velocity, and peak velocity, respectively). For portal venous flow, spiral 4D flow was in better agreement with 2D cine phase-contrast flow (95% limits of agreement: -8.8 and 9.3 mL/sec, respectively) than was Cartesian 4D flow (95% limits of agreement: -10.6 and 14.6 mL/sec).

CONCLUSION

The combination of highly efficient spiral sampling with dynamic compressed sensing results in major acceleration for 4D flow MR imaging, which allows comprehensive assessment of abdominal vessel hemodynamics in a single breath hold.

Interim FDG PET/CT to predict progression-free survival (PFS) better than clinical and baseline metabolic measurements in Hodgkin lymphoma (cHL)

8555

Background: Previous studies in cHL have demonstrated that conventional methods to risk stratify patients into various prognostic groups and predict PFS may not be sufficient to individualize therapy. Metabolic parameters using FDG-PET may be helpful for developing a prognostic algorithm and predict PFS. Objectives: To determine the best predictor of PFS among various variables of tm metabolic measurements at baseline and at interim PET/CT compared to conventional methods in cHL patients. Methods: Retrospective evaluation of prospectively acquired data in 58 cHL pts, all stages [IIB-IV:41%, >IPS-3:24%, unfavorable (UF):44%]. Eligibility: PET/CT prior to and after 1 cycle (PET1) ABVD therapy, imaging at 60min+15min, follow-up>24 mo. Baseline PET parameters including metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, and SULpeak were determined using gradient method (PETVCAR2, GE Healthcare, WI). Data were also evaluated at PET1 for %ΔMTV, %ΔSUVmax, %ΔTLG, PERCIST criteria and visually with Deauville 5-PS. Variables were correlated with PFS. Results: Median follow-up: 32.2 mo. Of 58 pts 14 relapsed (median PFS:6.5 mo). Results for PFS are displayed in the Table. No baseline conventional (stage, IPS, UF vs F) or PET variable was associated with PFS. The best predictor of PFS was Deauville 5-PS at PET1. PERCIST and %ΔTLG using gradient method trended toward significance. Conclusions: Deauville 5-PS best predicts PFS at PET1 in cHL. Neither baseline PET nor conventional prognostic factors correlated with PFS in this group of cHL pts. Risk-stratification of cHL using tumor metabolic volumetry and PERCIST criteria may require a larger sample size and further assessment of various methodologies. [Table: see text]