Publications by authors named "Ken Wong"

78 Publications

P2Y12 inhibitors for the neurointerventionalist.

Interv Neuroradiol 2021 May 4:15910199211015042. Epub 2021 May 4.

Clinic for Neuroradiology, Klinikum Stuttgart, Stuttgart, Germany.

The use of antiplatelets is widespread in clinical practice. However, for neurointerventional procedures, protocols for antiplatelet use are scarce and practice varies between individuals and institutions. This is further complicated by the quantity of antiplatelet agents which differ in route of administration, dosage, onset of action, efficacy and ischemic and hemorrhagic complications. Clarifying the individual characteristics for each antiplatelet agent, and their associated risks, will increasingly become relevant as the practice of mechanical thrombectomy, stenting, coiling and flow diversion procedures grows. The aim of this review is to summarize the existing literature for the use of P2Y12 inhibitors in neurointerventional procedures, examine the quality of the evidence, and highlight areas in need of further research.
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http://dx.doi.org/10.1177/15910199211015042DOI Listing
May 2021

Glycoprotein IIb/IIIa inhibitors for the neurointerventionalist.

Interv Neuroradiol 2021 May 4:15910199211015038. Epub 2021 May 4.

Royal London Hospital, London, UK.

Antiplatelet therapies are commonly used in neurointerventional procedures. However, specific guidelines for their use in these settings is lacking and it can often be difficult to balance the potential risks and benefits of these medications. Considering the continued growth and adoption of neurointerventional procedures, it is crucial to understand the properties of these agents in order to use them safely. Large-scale clinical trials are still needed to clarify many of these aspects for this emerging field. However, the existing literature already provides insight into which antiplatelet drugs are of benefit to the neurointerventionalist as well as their associated risks of ischemic and hemorrhagic complications. Hence, this review focuses on the applications of GPIIb/IIIA inhibitors to neurointerventional procedures.
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http://dx.doi.org/10.1177/15910199211015038DOI Listing
May 2021

Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection.

AMIA Annu Symp Proc 2020 25;2020:593-601. Epub 2021 Jan 25.

IBM Almaden Research Center, San Jose, CA.

The application of deep learning algorithms in medical imaging analysis is a steadily growing research area. While deep learning methods are thriving in the medical domain, they seldom utilize the rich knowledge associated with connected radiology reports. The knowledge derived from these reports can be utilized to enhance the performance of deep learning models. In this work, we used a comprehensive chest X-ray findings vocabulary to automatically annotate an extensive collection of chest X-rays using associated radiology reports and a vocabulary-driven concept annotation algorithm. The annotated X-rays are used to train a deep neural network classifier for finding detection. Finally, we developed a knowledge-driven reasoning algorithm that leverages knowledge learned from X-ray reports to improve upon the deep learning module's performance on finding detection. Our results suggest that combining deep learning and knowledge from radiology reports in a hybrid framework can significantly enhance overall performance in the CXR finding detection.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075485PMC
January 2021

First multicenter experience using the Silk Vista flow diverter in 60 consecutive intracranial aneurysms: technical aspects.

J Neurointerv Surg 2021 Apr 8. Epub 2021 Apr 8.

Radiology- Interventional Neuroradiology, Hospital Universitario La Paz, Madrid, Spain.

Background: The aim of this study was to assess the technical success and procedural safety of the new Silk Vista device (SV) by evaluating the intraprocedural and periprocedural complication rate after its use in several institutions worldwide.

Methods: The study involved a retrospective review of multicenter data regarding a consecutive series of patients with intracranial aneurysms, treated with the SV between September 2020 and January 2021. Clinical, intra/periprocedural and angiographic data, including approach, materials used, aneurysm size and location, device/s, technical details and initial angiographic aneurysm occlusion, were analyzed.

Results: 60 aneurysms were treated with SV in 57 procedures. 66 devices were used, 3 removed and 63 implanted. The devices opened instantaneously in 60 out of 66 (91%) cases and complete wall apposition was achieved in 58 out of 63 (92%) devices implanted. In 4 out of 66 (6%) devices a partial opening of the distal end occurred, and in 5 (8%) devices incomplete apposition was reported. There were 3 (5%) intraprocedural thromboembolic events managed successfully with no permanent neurological morbidity, and 4 (7%) postprocedural events. There was no mortality in this study. The initial occlusion rates in the 60 aneurysms were as follows: O'Kelly-Marotta (OKM) A in 34 (57%) cases, OKM B in 15 (25%) cases, OKM C in 6 (10%) cases, and OKM D in 5 (8%) cases.

Conclusions: Our study demonstrated that the use of the new flow diverter Silk Vista for the treatment of intracranial aneurysms is feasible and technically safe.
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http://dx.doi.org/10.1136/neurintsurg-2021-017421DOI Listing
April 2021

Decline in subarachnoid haemorrhage volumes associated with the first wave of the COVID-19 pandemic.

Stroke Vasc Neurol 2021 Mar 26. Epub 2021 Mar 26.

Department of Radiology, Beaumont Hospital, Dublin, Ireland.

Background: During the COVID-19 pandemic, decreased volumes of stroke admissions and mechanical thrombectomy were reported. The study's objective was to examine whether subarachnoid haemorrhage (SAH) hospitalisations and ruptured aneurysm coiling interventions demonstrated similar declines.

Methods: We conducted a cross-sectional, retrospective, observational study across 6 continents, 37 countries and 140 comprehensive stroke centres. Patients with the diagnosis of SAH, aneurysmal SAH, ruptured aneurysm coiling interventions and COVID-19 were identified by prospective aneurysm databases or by International Classification of Diseases, 10th Revision, codes. The 3-month cumulative volume, monthly volumes for SAH hospitalisations and ruptured aneurysm coiling procedures were compared for the period before (1 year and immediately before) and during the pandemic, defined as 1 March-31 May 2020. The prior 1-year control period (1 March-31 May 2019) was obtained to account for seasonal variation.

Findings: There was a significant decline in SAH hospitalisations, with 2044 admissions in the 3 months immediately before and 1585 admissions during the pandemic, representing a relative decline of 22.5% (95% CI -24.3% to -20.7%, p<0.0001). Embolisation of ruptured aneurysms declined with 1170-1035 procedures, respectively, representing an 11.5% (95%CI -13.5% to -9.8%, p=0.002) relative drop. Subgroup analysis was noted for aneurysmal SAH hospitalisation decline from 834 to 626 hospitalisations, a 24.9% relative decline (95% CI -28.0% to -22.1%, p<0.0001). A relative increase in ruptured aneurysm coiling was noted in low coiling volume hospitals of 41.1% (95% CI 32.3% to 50.6%, p=0.008) despite a decrease in SAH admissions in this tertile.

Interpretation: There was a relative decrease in the volume of SAH hospitalisations, aneurysmal SAH hospitalisations and ruptured aneurysm embolisations during the COVID-19 pandemic. These findings in SAH are consistent with a decrease in other emergencies, such as stroke and myocardial infarction.
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http://dx.doi.org/10.1136/svn-2020-000695DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006491PMC
March 2021

Real-time polymerase chain reaction (PCR) cycle threshold and infection outcomes.

Infect Control Hosp Epidemiol 2021 Feb 24:1-7. Epub 2021 Feb 24.

Department of Infectious Diseases, Respiratory Institute, Cleveland Clinic, Cleveland, Ohio.

Objective: Clostridioides difficile infection (CDI) causes significant morbidity and mortality; however, the diagnosis of CDI remains controversial. The primary aim of our study was to evaluate the association of polymerase chain reaction (PCR) cycle threshold (Ct) values with CDI disease severity, recurrence, and mortality among adult patients with CDI.

Design: Retrospective cohort study.

Setting: Single tertiary-care hospital.

Patients: Adult patients diagnosed with hospital-onset, healthcare facility-associated CDI from June 2014 to September 2015.

Methods: We performed a retrospective chart review of included patients. Univariate and multivariable logistic regression methods were used to evaluate the association between Ct values and CDI severity, 8-week recurrence, and 30-day mortality.

Results: Among 318 included patients, 51% were male and the mean age was 62 years; ~32% of the patients developed severe CDI and 11% developed severe-complicated CDI. The 30-day all-cause mortality rate was 11% and the 8-week recurrence rate was 9.5%. The overall mean Ct value was 32.9 (range, 23-40). Multivariable analyses showed that lower values of PCR Ct were associated with increased odds of 30-day morality (odds ratio [OR] 0.83; 95% confidence interval [CI], 0.72-0.96) but were not independently associated with CDI severity (OR, 0.99; 95% CI, 0.90-1.09) or recurrence (OR, 0.88; 95% CI, 0.77-1.00).

Conclusions: Our findings suggest that PCR Ct values at the time of diagnosis may have a limited predictive value and utility in clinical decision making for inpatients with CDI. Larger, prospective studies across different patient populations are needed to confirm our findings.
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http://dx.doi.org/10.1017/ice.2020.1405DOI Listing
February 2021

Immune function in childhood cancer survivors: a Children's Oncology Group review.

Lancet Child Adolesc Health 2021 04 16;5(4):284-294. Epub 2021 Feb 16.

Fred Hutchinson Cancer Research Center, Clinical Research and Public Health Sciences Divisions, Seattle, WA, USA.

Childhood cancer and its treatment often impact the haematopoietic and lymphatic systems, with immunological consequences. Immunological assessments are not routinely included in surveillance guidelines for most survivors of childhood cancer, although a robust body of literature describes immunological outcomes, testing recommendations, and revaccination guidelines after allogeneic haematopoietic cell transplantation. Survivorship care providers might not fully consider the impaired recovery of a child's immune system after cancer treatment if the child has not undergone haematopoietic cell transplantation. We did a scoping review to collate the existing literature describing immune function after childhood cancer therapy, including both standard-dose chemotherapy and high-dose chemotherapy with haematopoietic cell rescue. This Review aims to summarise: the principles of immunology and testing of immune function; the body of literature describing immunological outcomes after childhood cancer therapy, with an emphasis on the risk of infection, when is testing indicated, and preventive strategies; and knowledge gaps and opportunities for future research.
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http://dx.doi.org/10.1016/S2352-4642(20)30312-6DOI Listing
April 2021

The Woven Endobridge as a treatment for acutely ruptured aneurysms: A review of the literature.

Interv Neuroradiol 2021 Jan 28:1591019921991397. Epub 2021 Jan 28.

Department of diagnostic and therapeutic neuroradiology, Centre Hospitalier Universitaire de Reims, Reims, France.

The Woven Endobridge (WEB; Microvention, Aliso Viejo, California, USA) is a relatively new device which has been shown to be safe and effective for the treatment of wide necked bifurcation aneurysms in multiple prospective Good Clinical Practice studies. However, the vast majority of aneurysms included in these studies have been unruptured. The aim of this review is to summarise the current evidence available on the treatment of ruptured aneurysms with the WEB.
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http://dx.doi.org/10.1177/1591019921991397DOI Listing
January 2021

Global impact of COVID-19 on stroke care.

Int J Stroke 2021 Mar 29:1747493021991652. Epub 2021 Mar 29.

Neurology, Grady Memorial Hospital, Emory University, Atlanta, Georgia, USA.

Background: The COVID-19 pandemic led to profound changes in the organization of health care systems worldwide.

Aims: We sought to measure the global impact of the COVID-19 pandemic on the volumes for mechanical thrombectomy, stroke, and intracranial hemorrhage hospitalizations over a three-month period at the height of the pandemic (1 March-31 May 2020) compared with two control three-month periods (immediately preceding and one year prior).

Methods: Retrospective, observational, international study, across 6 continents, 40 countries, and 187 comprehensive stroke centers. The diagnoses were identified by their ICD-10 codes and/or classifications in stroke databases at participating centers.

Results: The hospitalization volumes for any stroke, intracranial hemorrhage, and mechanical thrombectomy were 26,699, 4002, and 5191 in the three months immediately before versus 21,576, 3540, and 4533 during the first three pandemic months, representing declines of 19.2% (95%CI, -19.7 to -18.7), 11.5% (95%CI, -12.6 to -10.6), and 12.7% (95%CI, -13.6 to -11.8), respectively. The decreases were noted across centers with high, mid, and low COVID-19 hospitalization burden, and also across high, mid, and low volume stroke/mechanical thrombectomy centers. High-volume COVID-19 centers (-20.5%) had greater declines in mechanical thrombectomy volumes than mid- (-10.1%) and low-volume (-8.7%) centers (p < 0.0001). There was a 1.5% stroke rate across 54,366 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.9% (784/20,250) of all stroke admissions.

Conclusion: The COVID-19 pandemic was associated with a global decline in the volume of overall stroke hospitalizations, mechanical thrombectomy procedures, and intracranial hemorrhage admission volumes. Despite geographic variations, these volume reductions were observed regardless of COVID-19 hospitalization burden and pre-pandemic stroke/mechanical thrombectomy volumes.
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http://dx.doi.org/10.1177/1747493021991652DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010375PMC
March 2021

Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images.

Sci Rep 2021 Jan 8;11(1):139. Epub 2021 Jan 8.

IBM Research - Almaden, 650 Harry Rd, San Jose, CA, 95120, USA.

Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. It is caused by the Hepatocellular carcinoma (HCC) in almost 90% of all cases. HCC is a malignant tumor and the most common histological type of the primary liver cancers. The detection and evaluation of viable tumor regions in HCC present an important clinical significance since it is a key step to assess response of chemoradiotherapy and tumor cell proportion in genetic tests. Recent advances in computer vision, digital pathology and microscopy imaging enable automatic histopathology image analysis for cancer diagnosis. In this paper, we present a multi-resolution deep learning model HistoCAE for viable tumor segmentation in whole-slide liver histopathology images. We propose convolutional autoencoder (CAE) based framework with a customized reconstruction loss function for image reconstruction, followed by a classification module to classify each image patch as tumor versus non-tumor. The resulting patch-based prediction results are spatially combined to generate the final segmentation result for each WSI. Additionally, the spatially organized encoded feature map derived from small image patches is used to compress the gigapixel whole-slide images. Our proposed model presents superior performance to other benchmark models with extensive experiments, suggesting its efficacy for viable tumor area segmentation with liver whole-slide images.
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http://dx.doi.org/10.1038/s41598-020-80610-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794421PMC
January 2021

Is This Contrast? Is This Blood? An Agreement Study on Post-thrombectomy Computed Tomography Scans.

Front Neurol 2020 22;11:593098. Epub 2020 Dec 22.

Ottawa Stroke Program, Department of Medicine (Neurology), University of Ottawa, Ottawa, ON, Canada.

Hemorrhagic transformation after acute ischemic stroke is a dreaded and severe complication of thrombolysis and thrombectomy. However, its detection on post-thrombectomy conventional non-contrast computed tomography (CT) scan can be complicated by the frequent (and sometimes concomitant) presence of contrast, resulting in changes in management. Our objective was to assess the inter- and intra-rater reliability for the detection of blood and/or contrast on day-1 post-thrombectomy CT scans. A total of 18 raters across 3 different specialties independently examined 30 post-thrombectomy CT scans selected from the Aspiration vs. STEnt-Retriever (ASTER) trial. They were asked to judge the presence of blood and contrast. Thirty days later, the same 18 raters again independently judged the 30 scans, in randomized order. Agreement was measured with Fleiss' and Cohen's statistics. Overall agreement on blood and/ or contrast presence was only fair, = 0.291 (95% CI = 0.273-0.309). There were 0 scans with consensus among the 18 readers on the presence of blood and/or contrast. However, intra-rater global agreement across all 18 physicians was relatively high, with a median kappa value of 0.675. This intra-rater consistency was seen across all specialties, regardless of level of training. Physician judgment for the presence of blood and/or contrast on day-1 post-thrombectomy non-contrast CT scan shows limited inter-observer reliability. Advanced imaging modalities may then be warranted for challenging clinical cases.
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http://dx.doi.org/10.3389/fneur.2020.593098DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783397PMC
December 2020

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.

JAMA Netw Open 2020 10 1;3(10):e2022779. Epub 2020 Oct 1.

IBM Research, Almaden, San Jose, California.

Importance: Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with automated preliminary read assistants could help expedite their workflows, improve accuracy, and reduce the cost of care.

Objective: To assess the performance of artificial intelligence (AI) algorithms in realistic radiology workflows by performing an objective comparative evaluation of the preliminary reads of anteroposterior (AP) frontal chest radiographs performed by an AI algorithm and radiology residents.

Design, Setting, And Participants: This diagnostic study included a set of 72 findings assembled by clinical experts to constitute a full-fledged preliminary read of AP frontal chest radiographs. A novel deep learning architecture was designed for an AI algorithm to estimate the findings per image. The AI algorithm was trained using a multihospital training data set of 342 126 frontal chest radiographs captured in ED and urgent care settings. The training data were labeled from their associated reports. Image-based F1 score was chosen to optimize the operating point on the receiver operating characteristics (ROC) curve so as to minimize the number of missed findings and overcalls per image read. The performance of the model was compared with that of 5 radiology residents recruited from multiple institutions in the US in an objective study in which a separate data set of 1998 AP frontal chest radiographs was drawn from a hospital source representative of realistic preliminary reads in inpatient and ED settings. A triple consensus with adjudication process was used to derive the ground truth labels for the study data set. The performance of AI algorithm and radiology residents was assessed by comparing their reads with ground truth findings. All studies were conducted through a web-based clinical study application system. The triple consensus data set was collected between February and October 2018. The comparison study was preformed between January and October 2019. Data were analyzed from October to February 2020. After the first round of reviews, further analysis of the data was performed from March to July 2020.

Main Outcomes And Measures: The learning performance of the AI algorithm was judged using the conventional ROC curve and the area under the curve (AUC) during training and field testing on the study data set. For the AI algorithm and radiology residents, the individual finding label performance was measured using the conventional measures of label-based sensitivity, specificity, and positive predictive value (PPV). In addition, the agreement with the ground truth on the assignment of findings to images was measured using the pooled κ statistic. The preliminary read performance was recorded for AI algorithm and radiology residents using new measures of mean image-based sensitivity, specificity, and PPV designed for recording the fraction of misses and overcalls on a per image basis. The 1-sided analysis of variance test was used to compare the means of each group (AI algorithm vs radiology residents) using the F distribution, and the null hypothesis was that the groups would have similar means.

Results: The trained AI algorithm achieved a mean AUC across labels of 0.807 (weighted mean AUC, 0.841) after training. On the study data set, which had a different prevalence distribution, the mean AUC achieved was 0.772 (weighted mean AUC, 0.865). The interrater agreement with ground truth finding labels for AI algorithm predictions had pooled κ value of 0.544, and the pooled κ for radiology residents was 0.585. For the preliminary read performance, the analysis of variance test was used to compare the distributions of AI algorithm and radiology residents' mean image-based sensitivity, PPV, and specificity. The mean image-based sensitivity for AI algorithm was 0.716 (95% CI, 0.704-0.729) and for radiology residents was 0.720 (95% CI, 0.709-0.732) (P = .66), while the PPV was 0.730 (95% CI, 0.718-0.742) for the AI algorithm and 0.682 (95% CI, 0.670-0.694) for the radiology residents (P < .001), and specificity was 0.980 (95% CI, 0.980-0.981) for the AI algorithm and 0.973 (95% CI, 0.971-0.974) for the radiology residents (P < .001).

Conclusions And Relevance: These findings suggest that it is possible to build AI algorithms that reach and exceed the mean level of performance of third-year radiology residents for full-fledged preliminary read of AP frontal chest radiographs. This diagnostic study also found that while the more complex findings would still benefit from expert overreads, the performance of AI algorithms was associated with the amount of data available for training rather than the level of difficulty of interpretation of the finding. Integrating such AI systems in radiology workflows for preliminary interpretations has the potential to expedite existing radiology workflows and address resource scarcity while improving overall accuracy and reducing the cost of care.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.22779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547369PMC
October 2020

Left ventricular systolic dysfunction is associated with poor functional outcomes after endovascular thrombectomy.

J Neurointerv Surg 2020 Sep 3. Epub 2020 Sep 3.

Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany.

Background: Endovascular thrombectomy (ET) has transformed acute ischemic stroke (AIS) therapy in patients with large vessel occlusion (LVO). Left ventricular systolic dysfunction (LVSD) decreases global cerebral blood flow and predisposes to hypoperfusion. We evaluated the relationship between LVSD, as measured by LV ejection fraction (LVEF), and clinical outcomes in patients with anterior cerebral circulation LVO who underwent ET.

Methods: This multicenter retrospective cohort study examined anterior circulation LVO AIS patients from six international stroke centers. LVSD was measured by assessment of the echocardiographic LVEF using Simpson's biplane method of discs according to international guidelines. LVSD was defined as LVEF <50%. The primary outcome was defined as a good functional outcome using a modified Rankin Scale (mRS) of 0-2 at 3 months.

Results: We included 440 AIS patients with LVO who underwent ET. On multivariate analyses, pre-existing diabetes mellitus (OR 2.05, 95% CI 1.24 to 3.39;p=0.005), unsuccessful reperfusion (Treatment in Cerebral Infarction (TICI) grade 0-2a) status (OR 4.21, 95% CI 2.04 to 8.66; p<0.001) and LVSD (OR 2.08, 95% CI 1.18 to 3.68; p=0.011) were independent predictors of poor functional outcomes at 3 months. On ordinal (shift) analyses, LVSD was associated with an unfavorable shift in the mRS outcomes (OR 2.32, 95% CI 1.52 to 3.53; p<0.001) after adjusting for age and ischemic heart disease.

Conclusion: Anterior circulation LVO AIS patients with LVSD have poorer outcomes after ET, suggesting the need to consider cardiac factors for ET, the degree of monitoring and prognostication post-procedure.
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http://dx.doi.org/10.1136/neurintsurg-2020-016216DOI Listing
September 2020

Fever in a traveler returning from Ethiopia.

Authors:
Ken Koon Wong

Cleve Clin J Med 2020 01 2;87(1):31-42. Epub 2020 Jan 2.

Assistant Program Director and Director of Assessment and Evaluation, Department of Medicine, and Departments of Internal Medicine and Infectious Disease, Cleveland Clinic Akron General, Akron, OH

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http://dx.doi.org/10.3949/ccjm.87a.19017DOI Listing
January 2020

Endosaccular flow disruption: where are we now?

J Neurointerv Surg 2019 Oct 13;11(10):1024-1025. Epub 2019 Jun 13.

Radiology, University Hospital Reims, Reims, France.

Endosaccular flow disruption is an innovative method of treating wide-necked complex aneurysms. Currently four types of devices have obtained the CE mark for use within Europe. These are the Woven EndoBridge device (WEB), the Luna Aneurysm Embolization System, the Medina Embolic Device (Medtronic), and the Contour Neurovascular System. The aim of this article is to provide an overview of these devices and to summarize the evidence in the literature pertaining to the treatment of intracranial aneurysms with them.
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http://dx.doi.org/10.1136/neurintsurg-2018-014623DOI Listing
October 2019

The Silk Vista Baby: Initial experience and report of two cases.

Interv Neuroradiol 2019 Oct 31;25(5):530-538. Epub 2019 Mar 31.

Department of Interventional Neuroradiology, The Royal London Hospital, London, UK.

In this report, we present two cases using a novel flow diverter, the Silk Vista Baby, to treat aneurysms successfully, both ruptured and unruptured, that would have been difficult to treat using alternative flow diverters. We describe the clinical and radiological features, outcome and the unique features of the Silk Vista Baby flow diverter.
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http://dx.doi.org/10.1177/1591019919839196DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777101PMC
October 2019

Vessel wall enhancement of a ruptured intra-nidal aneurysm in a brain arteriovenous malformation.

Interv Neuroradiol 2019 Jun 14;25(3):310-314. Epub 2019 Feb 14.

1 Department of Interventional Neuroradiology, The Royal London Hospital, London, UK.

Ruptured arteriovenous malformations are a frequently encountered pathology with significant associated morbidity and mortality. Identifying and securing the rupture point is mandatory; however, this can often be difficult. Black blood vessel wall magnetic resonance imaging is a promising technique for identifying ruptured saccular aneurysms and has been used in cases of multiple aneurysms. Here we describe a case of using this imaging technique to identify the rupture point in a ruptured arteriovenous malformation with histopathological correlation.
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http://dx.doi.org/10.1177/1591019918824796DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547198PMC
June 2019

Drug Treatment Value in a Changing Oncology Landscape: A Literature and Provider Perspective.

J Manag Care Spec Pharm 2019 Feb;25(2):246-259

2 Novartis Pharmaceuticals, East Hanover, New Jersey.

Background: The U.S. health care system's transition to a value-based reimbursement model holds important implications for medical innovation, care delivery, and value-based assessments of therapeutic interventions. This transition has been especially noteworthy in oncology, with substantial ongoing changes to payer reimbursement and the provider landscape, as well as the introduction of value frameworks to guide drug treatment decision making. The implications of these changes for provider assessments of drug value and evidence needs remain unclear.

Objectives: To understand provider perspectives on drug value assessment and the utility of existing oncology value frameworks by identifying (a) key value-based trends in the evolving oncology landscape, (b) provider definitions of drug value, (c) the role of existing value frameworks in provider decision making, and (d) future provider evidence needs for making value-based treatment decisions.

Methods: We conducted a literature review to identify existing oncology value frameworks and definitions of drug treatment value in oncology. Using a structured discussion guide informed by this literature review, we conducted 12 telephone-based in-depth interviews in November and December 2017 with U.S. oncology providers involved in organizational drug treatment and formulary decision making within their practices. Responses to interview questions were analyzed and reported as averages and percentages across participants.

Results: Of 293 publications identified by keyword searches, 35 relevant articles were identified. Among these, the literature review identified no common definition for providers to assess drug value. Interview research participants described large ongoing changes in the oncology provider landscape, with economic pressures from payers as the foremost leading factor. Although 5 value frameworks were found in the literature, interviews found that in practice few providers consider these value frameworks to be key influences when evaluating treatment or formulary decisions. Furthermore, while 83% of participants' organizations employed some form of internal clinical pathways, only the minority (25%) with pathways integrated in their electronic medical record (EMR) systems saw these pathways as significantly affecting clinicians' drug treatment decision making. To aid the ongoing shift from volume-based to value-based care, we found that, rather than value frameworks, providers are looking for patient-level tools to make more appropriate drug decisions.

Conclusions: Payer reimbursement pressures are leading to radical changes in the oncology provider landscape, and there is a need for improved guidance for providers in assessing drug value. In particular, this study identifies the need for a timely and multifaceted summary of information required to assess the value of alternative treatment options for a given patient. Manufacturers also need to make significant strides to help generate and improve the dissemination of evidence to support the value of their therapies.

Disclosures: Funding for this work was provided by Novartis Pharmaceuticals. The study sponsor was involved in study design, data interpretation, and data review. All authors contributed to the development of the manuscript and maintained control over the final content. Sasane, Howe, Wong, and Zacker were employees of Novartis at the time of this study. Frois, Jarvis, and Grice are or have been employed by Analysis Group, which received a grant from Novartis for this research. At the time of this study, Analysis Group received funding from multiple manufacturers with oncology products in their portfolio during this time period, including, but not limited to, Astellas and Genentech.
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http://dx.doi.org/10.18553/jmcp.2019.25.2.246DOI Listing
February 2019

Building medical image classifiers with very limited data using segmentation networks.

Med Image Anal 2018 10 4;49:105-116. Epub 2018 Aug 4.

IBM Research - Almaden Research Center, San Jose, CA, USA. Electronic address:

Deep learning has shown promising results in medical image analysis, however, the lack of very large annotated datasets confines its full potential. Although transfer learning with ImageNet pre-trained classification models can alleviate the problem, constrained image sizes and model complexities can lead to unnecessary increase in computational cost and decrease in performance. As many common morphological features are usually shared by different classification tasks of an organ, it is greatly beneficial if we can extract such features to improve classification with limited samples. Therefore, inspired by the idea of curriculum learning, we propose a strategy for building medical image classifiers using features from segmentation networks. By using a segmentation network pre-trained on similar data as the classification task, the machine can first learn the simpler shape and structural concepts before tackling the actual classification problem which usually involves more complicated concepts. Using our proposed framework on a 3D three-class brain tumor type classification problem, we achieved 82% accuracy on 191 testing samples with 91 training samples. When applying to a 2D nine-class cardiac semantic level classification problem, we achieved 86% accuracy on 263 testing samples with 108 training samples. Comparisons with ImageNet pre-trained classifiers and classifiers trained from scratch are presented.
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http://dx.doi.org/10.1016/j.media.2018.07.010DOI Listing
October 2018

Using an Evidence-Informed Framework and a Self-Assessment Tool to Drive Priority Setting and Action toward Senior-Friendly Care.

Healthc Q 2018 Apr;21(1):25-30

Executive director at the Regional Geriatric Program of Toronto, program director at the University of Toronto Geriatric Medicine postgraduate training program and associate professor at the University of Toronto Department of Medicine. She can be contacted at

Since 2011, Ontario hospitals have been engaged in the Senior Friendly Hospital (SFH) Strategy led by the Regional Geriatric Program (RGP) of Toronto, in partnership with Ontario's Local Health Integration Networks (LHINs) and the RGPs of Ontario. Using the SFH Framework as a foundation, improvement in Ontario hospitals has been driven by the identification of common priorities, sharing of resources and best practices, and the development of quality indicators. We document this progress through a second environmental scan of hospitals conducted in 2014 that highlights significant advancement in all five domains of the SFH Framework. Key learnings will be shared on how this framework and its self-assessment tool helped drive practice change.
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http://dx.doi.org/10.12927/hcq.2018.25524DOI Listing
April 2018

A Meshfree Representation for Cardiac Medical Image Computing.

IEEE J Transl Eng Health Med 2018 18;6:1800212. Epub 2018 Jan 18.

B. Thomas Golisano College of Computing and Information SciencesRochester Institute of TechnologyRochesterNY14623USA.

The prominent advantage of meshfree method, is the way to build the representation of computational domain, based on the nodal points without any explicit meshing connectivity. Therefore, meshfree method can conveniently process the numerical computation inside interested domains with large deformation or inhomogeneity. In this paper, we adopt the idea of meshfree representation into cardiac medical image analysis in order to overcome the difficulties caused by large deformation and inhomogeneous materials of the heart. In our implementation, as element-free Galerkin method can efficiently build a meshfree representation using its shape function with moving least square fitting, we apply this meshfree method to handle large deformation or inhomogeneity for solving cardiac segmentation and motion tracking problems. We evaluate the performance of meshfree representation on a synthetic heart data and an in-vivo cardiac MRI image sequence. Results showed that the error of our framework against the ground truth was 0.1189 ± 0.0672 while the error of the traditional FEM was 0.1793 ± 0.1166. The proposed framework has minimal consistency constraints, handling large deformation and material discontinuities are simple and efficient, and it provides a way to avoid the complicated meshing procedures while preserving the accuracy with a relatively small number of nodes.
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http://dx.doi.org/10.1109/JTEHM.2018.2795022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794334PMC
January 2018

Comparative Antimicrobial Efficacy of Two Hand Sanitizers in Intensive Care Units Common Areas: A Randomized, Controlled Trial.

Infect Control Hosp Epidemiol 2018 03 31;39(3):267-271. Epub 2018 Jan 31.

1Department of Infectious Diseases,Medicine Institute,Cleveland Clinic,Cleveland,Ohio.

OBJECTIVE Contaminated hands of healthcare workers (HCWs) are an important source of transmission of healthcare-associated infections. Alcohol-based hand sanitizers, while effective, do not provide sustained antimicrobial activity. The objective of this study was to compare the immediate and persistent activity of 2 hand hygiene products (ethanol [61% w/v] plus chlorhexidine gluconate [CHG; 1.0% solution] and ethanol only [70% v/v]) when used in an intensive care unit (ICU). DESIGN Prospective, randomized, double-blinded, crossover study SETTING Three ICUs at a large teaching hospital PARTICIPANTS In total, 51 HCWs involved in direct patient care were enrolled in and completed the study. METHODS All HCWs were randomized 1:1 to either product. Hand prints were obtained immediately after the product was applied and again after spending 4-7 minutes in the ICU common areas prior to entering a patient room or leaving the area. The numbers of aerobic colony-forming units (CFU) were compared for the 2 groups after log transformation. Each participant tested the alternative product after a 3-day washout period. RESULTS On bare hands, use of ethanol plus CHG was associated with significantly lower recovery of aerobic CFU, both immediately after use (0.27 ± 0.05 and 0.88 ± 0.08 log10 CFU; P = .035) and after spending time in ICU common areas (1.81 ± 0.07 and 2.17 ± 0.05 log10 CFU; P<.0001). Both the antiseptics were well tolerated by HCWs. CONCLUSIONS In comparison to the ethanol-only product, the ethanol plus CHG sanitizer was associated with significantly lower aerobic bacterial counts on hands of HCWs, both immediately after use and after spending time in ICU common areas. CLINICAL TRIAL IDENTIFIER Clinicaltrials.gov identifier NCT02258412 Infect Control Hosp Epidemiol 2018;39:267-271.
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http://dx.doi.org/10.1017/ice.2017.293DOI Listing
March 2018

Diagnostic testing methods for Clostridium difficile infection: A statewide survey of Ohio acute care hospitals.

Am J Infect Control 2017 Mar 28;45(3):306-307. Epub 2016 Oct 28.

Department of Infectious Diseases, Cleveland Clinic, Medicine Institute, Cleveland, OH; Medicine Institute Center for Value Based Care Research, Cleveland Clinic, Cleveland, OH. Electronic address:

We surveyed Ohio acute care hospitals on laboratory testing used for diagnosis of Clostridium difficile infection (CDI). Of 146 hospitals surveyed, 109 (84%) used nucleic acid amplification tests (NAATs) as stand-alone diagnostic assays. Only 53 (42.4%) hospitals using NAATs had a mechanism in place to prevent repeat CDI testing.
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http://dx.doi.org/10.1016/j.ajic.2016.09.007DOI Listing
March 2017

Pancreatic Tumor Growth Prediction With Elastic-Growth Decomposition, Image-Derived Motion, and FDM-FEM Coupling.

IEEE Trans Med Imaging 2017 01 2;36(1):111-123. Epub 2016 Aug 2.

Pancreatic neuroendocrine tumors are abnormal growths of hormone-producing cells in the pancreas. Unlike the brain which is protected by the skull, the pancreas can be significantly deformed by its surrounding organs. Consequently, the tumor shape differences observable from images at different time points arise from both tumor growth and pancreatic motion, and tumor growth model personalization may be compromised if such motion is ignored. Therefore, we incorporate pancreatic motion information derived from deformable image registration in model personalization. For more accurate mechanical interactions between tumor growth and pancreatic motion, elastic-growth decomposition is used with a hyperelastic constitutive law to model the mass effect, which allows growth modeling while conserving the mechanical properties. Furthermore, a way of coupling the finite difference method and the finite element method is proposed to greatly reduce the computation time. With both 2-[F]-fluoro-2-deoxy-D-glucose positron emission tomographic and contrast-enhanced computed tomographic images, functional, structural, and motion data are combined for a patient-specific model. Experiments on synthetic and clinical data show the importance of image-derived motion on estimating pathophysiologically plausible mechanical properties and the promising performance of our framework. From seven patient data sets, the recall, precision, Dice coefficient, relative volume difference, and average surface distance between the personalized tumor growth simulations and the measurements were 83.2 ±8.8%, 86.9 ±8.3%, 84.4 ±4.0%, 13.9 ±9.8%, and 0.6 ±0.1 mm, respectively.
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http://dx.doi.org/10.1109/TMI.2016.2597313DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5316467PMC
January 2017

Regional infarction identification from cardiac CT images: a computer-aided biomechanical approach.

Int J Comput Assist Radiol Surg 2016 Sep 12;11(9):1573-83. Epub 2016 Apr 12.

Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA.

Purpose: Regional infarction identification is important for heart disease diagnosis and management, and myocardial deformation has been shown to be effective for this purpose. Although tagged and strain-encoded MR images can provide such measurements, they are uncommon in clinical routine. On the contrary, cardiac CT images are more available with lower costs, but they only provide motion of cardiac boundaries and additional constraints are required to obtain the myocardial strains. The goal of this study is to verify the potential of contrast-enhanced CT images on computer-aided regional infarction identification.

Methods: We propose a biomechanical approach combined with machine learning algorithms. A hyperelastic biomechanical model is used with deformable image registration to estimate 3D myocardial strains from CT images. The regional strains and CT image intensities are input to a classifier for regional infarction identification. Cross-validations on ten canine image sequences with artificially induced infarctions were used to study the performances of using different feature combinations and machine learning algorithms.

Results: Radial strain, circumferential strain, first principal strain, and image intensity were shown to be discriminative features. The highest identification accuracy ([Formula: see text] %) was achieved when combining radial strain with image intensity. Random forests gave better results than support vector machines on less discriminative features. Random forests also performed better when all strains were used together.

Conclusion: Although CT images cannot directly measure myocardial deformation, with the use of a biomechanical model, the estimated strains can provide promising identification results especially when combined with CT image intensity.
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http://dx.doi.org/10.1007/s11548-016-1404-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5527562PMC
September 2016

Pancreatic Tumor Growth Prediction with Multiplicative Growth and Image-Derived Motion.

Inf Process Med Imaging 2015 ;24:501-13

Pancreatic neuroendocrine tumors are abnormal growths of hormone-producing cells in the pancreas. Different from the brain in the skull, the pancreas in the abdomen can be largely deformed by the body posture and the surrounding organs. In consequence, both tumor growth and pancreatic motion attribute to the tumor shape difference observable from images. As images at different time points are used to personalize the tumor growth model, the prediction accuracy may be reduced if such motion is ignored. Therefore, we incorporate the image-derived pancreatic motion to tumor growth personalization. For realistic mechanical interactions, the multiplicative growth decomposition is used with a hyperelastic constitutive law to model tumor mass effect, which allows growth modeling without compromising the mechanical accuracy. With also the FDG-PET and contrast-enhanced CT images, the functional, structural, and motion data are combined for a more patient-specific model. Experiments on synthetic and clinical data show the importance of image-derived motion on estimating physiologically plausible mechanical properties and the promising performance of our framework. From six patient data sets, the recall, precision, Dice coefficient, relative volume difference, and average surface distance were 89.8 ± 3.5%, 85.6 ± 7.5%, 87.4 ± 3.6%, 9.7 ± 7.2%, and 0.6 ± 0.2 mm, respectively.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5527563PMC
http://dx.doi.org/10.1007/978-3-319-19992-4_39DOI Listing
September 2015

Sight-threatening intraocular pressure due to an upper arm dialysis fistula.

Lancet 2015 Jul;386(9988):101-2

Royal London Hospital, London, UK; Moorfields Eye Hospital, London, UK.

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http://dx.doi.org/10.1016/S0140-6736(15)61003-0DOI Listing
July 2015

Management of hip fractures pre- and post-Major Trauma Centre activation.

Injury 2015 Oct 2;46(10):1975-7. Epub 2015 Jul 2.

Orthopaedic Trauma Unit, Cambridge University Hospitals NHS Foundation Trust, United Kingdom. Electronic address:

Introduction: In April 2012, the activation of the regional trauma networks in England was carried out to improve the organisation of trauma care. NHS Trusts that could meet the highest standard of care to complex trauma were designated Major Trauma Centres (MTCs). MTCs receive patients fulfilling certain triage criteria, as well as secondary transfers from nearby trauma units. While complex trauma care is streamlined with this new organisation, the impact this would have on the rest of the trauma workload within MTCs as well as non-MTC hospitals is uncertain. We investigate whether the management of hip fracture cases had suffered as a result of a trauma unit becoming a MTC.

Methods: Summary data was collated from the National Hip Fracture Database website for the periods of April 2011-April 2012 (the 'pre-MTC' activation period) and April 2012-April 2013 (the 'post-MTC' activation period). As our primary outcome, we compared the time to surgery within 36h between MTCs and non-MTCs for the periods detailed above. Other outcome measures were: reasons for delay to surgery, length of acute stay, proportion of cases meeting Best Practice Tariff criteria.

Results: A total of 54,897 and 55,998 fNOF patients were included for all hospitals in England in the pre- and post-MTC periods respectively. For MTCs, a weighted mean average of 66.6% patients had surgery within 36h in the pre-MTC period versus 71.4% of patients in the post MTC period (p<0.0001). For non-MTCs, a weighted mean average of 70.0% of patients had surgery within 36h in the pre-MTC period versus 73.8% of patients in the post-MTC period (p<0.0001). Non-MTCs in both pre- and post-MTC activation periods were therefore better in percentage of patients receiving surgery within 36h.

Discussion: The data presented suggests that the creation of MTCs has not had a deleterious effect on the management of hip fracture patients. This paper aims to stimulate the important discussion of maintaining a consistently improving standard throughout the spectrum of trauma care, in conjunction with the development of regional Major Trauma Networks.
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http://dx.doi.org/10.1016/j.injury.2015.06.030DOI Listing
October 2015

Tumor growth prediction with reaction-diffusion and hyperelastic biomechanical model by physiological data fusion.

Med Image Anal 2015 Oct 17;25(1):72-85. Epub 2015 Apr 17.

Clinical Image Processing Service, Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA. Electronic address:

The goal of tumor growth prediction is to model the tumor growth process, which can be achieved by physiological modeling and model personalization from clinical measurements. Although image-driven frameworks have been proposed with promising results, several issues such as infinitesimal strain assumptions, complicated personalization procedures, and the lack of functional information, may limit their prediction accuracy. In view of these issues, we propose a framework for pancreatic neuroendocrine tumor growth prediction, which comprises a FEM-based tumor growth model with coupled reaction-diffusion equation and nonlinear biomechanics. Physiological data fusion of structural and functional images is used to improve the subject-specificity of model personalization, and a derivative-free global optimization algorithm is adopted to facilitate the complicated model and accommodate flexible choices of objective functions. With this flexibility, we propose an objective function accounting for both the tumor volume difference and the root-mean-squared error of intracellular volume fractions. Experiments were performed on synthetic and clinical data to verify the parameter estimation capability and the prediction performance. Comparisons of using different biomechanical models and objective functions were also performed. From the experimental results of eight patient data sets, the average recall, precision, Dice coefficient, and relative volume difference between predicted and measured tumor volumes were 84.5 ± 6.9%, 85.8 ± 8.2%, 84.6 ± 1.7%, and 14.2 ± 8.4%, respectively.
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http://dx.doi.org/10.1016/j.media.2015.04.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4540673PMC
October 2015

Low incidence of Clostridium difficile infection (CDI) in patients treated with outpatient parenteral antimicrobial therapy (OPAT).

Infect Control Hosp Epidemiol 2015 Jan;36(1):110-2

1Department of Infectious Diseases,Medicine Institute,Cleveland Clinic,Cleveland,OH 44195.

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http://dx.doi.org/10.1017/ice.2014.6DOI Listing
January 2015