Publications by authors named "Daniel S Chow"

33 Publications

Validation of a Deep Learning Tool in the Detection of Intracranial Hemorrhage and Large Vessel Occlusion.

Front Neurol 2021 29;12:656112. Epub 2021 Apr 29.

Department of Radiological Sciences, University of California, Irvine, Irvine, CA, United States.

Recently developed machine-learning algorithms have demonstrated strong performance in the detection of intracranial hemorrhage (ICH) and large vessel occlusion (LVO). However, their generalizability is often limited by geographic bias of studies. The aim of this study was to validate a commercially available deep learning-based tool in the detection of both ICH and LVO across multiple hospital sites and vendors throughout the U.S. This was a retrospective and multicenter study using anonymized data from two institutions. Eight hundred fourteen non-contrast CT cases and 378 CT angiography cases were analyzed to evaluate ICH and LVO, respectively. The tool's ability to detect and quantify ICH, LVO, and their various subtypes was assessed among multiple CT vendors and hospitals across the United States. Ground truth was based off imaging interpretations from two board-certified neuroradiologists. There were 255 positive and 559 negative ICH cases. Accuracy was 95.6%, sensitivity was 91.4%, and specificity was 97.5% for the ICH tool. ICH was further stratified into the following subtypes: intraparenchymal, intraventricular, epidural/subdural, and subarachnoid with true positive rates of 92.9, 100, 94.3, and 89.9%, respectively. ICH true positive rates by volume [small (<5 mL), medium (5-25 mL), and large (>25 mL)] were 71.8, 100, and 100%, respectively. There were 156 positive and 222 negative LVO cases. The LVO tool demonstrated an accuracy of 98.1%, sensitivity of 98.1%, and specificity of 98.2%. A subset of 55 randomly selected cases were also assessed for LVO detection at various sites, including the distal internal carotid artery, middle cerebral artery M1 segment, proximal middle cerebral artery M2 segment, and distal middle cerebral artery M2 segment with an accuracy of 97.0%, sensitivity of 94.3%, and specificity of 97.4%. Deep learning tools can be effective in the detection of both ICH and LVO across a wide variety of hospital systems. While some limitations were identified, specifically in the detection of small ICH and distal M2 occlusion, this study highlights a deep learning tool that can assist radiologists in the detection of emergent findings in a variety of practice settings.
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http://dx.doi.org/10.3389/fneur.2021.656112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116960PMC
April 2021

Outcomes of Artificial Intelligence Volumetric Assessment of Kidneys and Renal Tumors for Preoperative Assessment of Nephron Sparing Interventions.

J Endourol 2021 Apr 13. Epub 2021 Apr 13.

University of California Irvine School of Medicine, 12219, Radiological Sciences, Orange, California, United States.

Background Renal cell carcinoma is the most common kidney cancer and the 13th most common cause of cancer death worldwide. Partial nephrectomy and percutaneous ablation, increasingly utilized to treat small renal masses and preserve renal parenchyma, require precise preoperative imaging interpretation. We sought to develop and evaluate a convolutional neural network (CNN), a type of deep learning artificial intelligence, to act as a surgical planning aid by determining renal tumor and kidney volumes via segmentation on single-phase computed tomography (CT). Materials and Methods After institutional review board approval, the CT images of 319 patients were retrospectively analyzed. Two distinct CNNs were developed for (1) bounding cube localization of the right and left hemi-abdomen and (2) segmentation of the renal parenchyma and tumor within each bounding cube. Training was performed on a randomly selected cohort of 269 patients. CNN performance was evaluated on a separate cohort of 50 patients using Sorensen-Dice coefficients (which measures the spatial overlap between the manually segmented and neural network derived segmentations) and Pearson correlation coefficients. Experiments were run on a GPU-optimized workstation with a single NVIDIA GeForce GTX Titan X (12GB, Maxwell architecture). Results Median Dice coefficients for kidney and tumor segmentation were 0.970 and 0.816, respectively; Pearson correlation coefficients between CNN-generated and human-annotated estimates for kidney and tumor volume were 0.998 and 0.993 (p < 0.001), respectively. End-to-end trained CNNs were able to perform renal parenchyma and tumor segmentation on a new test case in an average of 5.6 seconds. Conclusions Initial experience with automated deep learning artificial intelligence demonstrates that it is capable of rapidly and accurately segmenting kidneys and renal tumors on single-phase contrast-enhanced CT scans and calculating tumor and renal volumes.
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http://dx.doi.org/10.1089/end.2020.1125DOI Listing
April 2021

Neuroanatomical Correlates Underlying the Association Between Maternal Interleukin 6 Concentration During Pregnancy and Offspring Fluid Reasoning Performance in Early Childhood.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 Mar 23. Epub 2021 Mar 23.

Development, Health and Disease Research Program, University of California, Irvine, California; Department of Pediatrics, University of California, Irvine, California; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Medical Psychology, Berlin, Germany. Electronic address:

Background: Maternal inflammation during pregnancy can alter offspring brain development and influence risk for disorders commonly accompanied by deficits in cognitive functioning. We therefore examined associations between maternal interleukin 6 (IL-6) concentrations during pregnancy and offspring cognitive ability and concurrent magnetic resonance imaging-based measures of brain anatomy in early childhood. We further examined newborn brain anatomy in secondary analyses to consider whether effects are evident soon after birth and to increase capacity to differentiate effects of pre- versus postnatal exposures.

Methods: IL-6 concentrations were quantified in early (12.6 ± 2.8 weeks), mid (20.4 ± 1.5 weeks), and late (30.3 ± 1.3 weeks) pregnancy. Offspring nonverbal fluid intelligence (Gf) was assessed at 5.2 ± 0.6 years using a spatial reasoning task (Wechsler Preschool and Primary Scale of Intelligence-Matrix) (n = 49). T1-weighted magnetic resonance imaging scans were acquired at birth (n = 89, postmenstrual age = 42.9 ± 2.0 weeks) and in early childhood (n = 42, scan age = 5.1 ± 1.0 years). Regional cortical volumes were examined for a joint association between maternal IL-6 and offspring Gf performance.

Results: Average maternal IL-6 concentration during pregnancy was inversely associated with offspring Gf performance after adjusting for socioeconomic status and the quality of the caregiving and learning environment (R = 13%; p = .02). Early-childhood pars triangularis volume was jointly associated with maternal IL-6 and childhood Gf (p < .001). An association also was observed between maternal IL-6 and newborn pars triangularis volume (R = 6%; p = .02).

Conclusions: These findings suggest that the origins of variation in child cognitive ability can, in part, trace back to maternal conditions during the intrauterine period of life and support the role of inflammation as an important component of this putative biological pathway.
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http://dx.doi.org/10.1016/j.bpsc.2021.03.007DOI Listing
March 2021

Predictive Values of Location and Volumetric MRI Injury Patterns for Neurodevelopmental Outcomes in Hypoxic-Ischemic Encephalopathy Neonates.

Brain Sci 2020 Dec 16;10(12). Epub 2020 Dec 16.

Department of Radiological Sciences, Center for Artificial Intelligence in Diagnostic Medicine (CADIM), University of California, Irvine, CA 92697, USA.

Hypoxic-ischemic encephalopathy (HIE) is a severe neonatal complication with up to 40-60% long-term morbidity. This study evaluates the distribution and burden of MRI changes as a prognostic indicator of neurodevelopmental (ND) outcomes at 18-24 months in HIE infants who were treated with therapeutic hypothermia (TH). Term or late preterm infants who were treated with TH for HIE were analyzed between June 2012 and March 2016. Brain MRI scans were obtained from 107 TH treated infants. For each infant, diffusion weighted brain image (DWI) sequences from a 3T Siemens scanner were obtained for analysis. Of the 107 infants, 36 of the 107 infants (33.6%) had normal brain MR images, and 71 of the 107 infants (66.4%) had abnormal MRI findings. The number of clinical seizures was significantly higher in the abnormal MRI group ( < 0.001) than in the normal MRI group. At 18-24 months, 76 of the 107 infants (70.0%) showed normal ND stages, and 31 of the 107 infants (29.0%) exhibited abnormal ND stages. A lesion size count >500 was significantly associated with abnormal ND. Similarly, the total lesion count was larger in the abnormal ND group (14.16 vs. 5.29). More lesions in the basal ganglia (BG) and thalamus areas and a trend towards more abnormal MRI scans were significantly associated with abnormal ND at 18-24 months. In addition to clinical seizure, a larger total lesion count and lesion size as well as lesion involvement of the basal ganglia and thalamus were significantly associated with abnormal neurodevelopment at 18-24 months.
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http://dx.doi.org/10.3390/brainsci10120991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765589PMC
December 2020

Development and external validation of a prognostic tool for COVID-19 critical disease.

PLoS One 2020 9;15(12):e0242953. Epub 2020 Dec 9.

Department of Radiological Sciences, University of California, Irvine, California, United States of America.

Background: The rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.

Methods: This is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.

Results: Of a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.

Conclusions And Relevance: We present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242953PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725393PMC
December 2020

Updates on Deep Learning and Glioma: Use of Convolutional Neural Networks to Image Glioma Heterogeneity.

Neuroimaging Clin N Am 2020 Nov 18;30(4):493-503. Epub 2020 Sep 18.

Department of Radiology, Lenox Hill Hospital, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, 100 East 77th Street, New York, NY 10075, USA. Electronic address:

Deep learning represents end-to-end machine learning in which feature selection from images and classification happen concurrently. This articles provides updates on how deep learning is being applied to the study of glioma and its genetic heterogeneity. Deep learning algorithms can detect patterns in routine and advanced MR imaging that elude the eyes of neuroradiologists and make predictions about glioma genetics, which impact diagnosis, treatment response, patient management, and long-term survival. The success of these deep learning initiatives may enhance the performance of neuroradiologists and add greater value to patient care by expediting treatment.
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http://dx.doi.org/10.1016/j.nic.2020.07.002DOI Listing
November 2020

Impact of COVID-19 on Acute Stroke Presentation at a Comprehensive Stroke Center.

Front Neurol 2020 14;11:850. Epub 2020 Aug 14.

Department of Radiological Sciences, University of California, Irvine Medical Center, Orange, CA, United States.

COVID-19 has impacted healthcare in many ways, including presentation of acute stroke. Since time-sensitive thrombolysis is essential for reducing morbidity and mortality in acute stroke, any delays due to the pandemic can have serious consequences. We retrospectively reviewed the electronic medical records for patients presenting with acute ischemic stroke at a comprehensive stroke center in March-April 2020 (the early months of COVID-19) and compared to the same time period in 2019. Stroke metrics such as incidence, time to arrival, and immediate outcomes were assessed. There were 48 acute ischemic strokes (of which 7 were transfers) in March-April 2020 compared to 64 (of which 12 were transfers) in 2019. The average last known well to arrival time (±SD) for stroke codes was 1,041 (±1682.1) min in 2020 and 554 (±604.9) min in 2019. Of the patients presenting directly to the ED with a known last known well time, 27.8% (10/36) presented in the first 4.5 h in 2020, in contrast to 40.5% (15/37) in 2019. Patients who died comprised 10.4% of the stroke cohort in 2020 (5/48) compared to 6.3% in 2019 (4/64). During the first 2 months of COVID-19, there were fewer overall stroke cases who presented to our hospital, and of these cases, there was delayed presentation in comparison to the same time period in 2019. Recognizing how stroke presentation may be affected by COVID-19 would allow for optimization of established stroke triage algorithms in order to ensure safe and timely delivery of stroke care during a pandemic.
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http://dx.doi.org/10.3389/fneur.2020.00850DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456804PMC
August 2020

Applications of Artificial Intelligence to Prostate Multiparametric MRI (mpMRI): Current and Emerging Trends.

Cancers (Basel) 2020 May 11;12(5). Epub 2020 May 11.

Department of Radiology, University of California, Irvine, Orange, CA 92868-3201, USA.

Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists' accuracy and speed.
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http://dx.doi.org/10.3390/cancers12051204DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281682PMC
May 2020

Glioma-Induced Alterations in Neuronal Activity and Neurovascular Coupling during Disease Progression.

Cell Rep 2020 04;31(2):107500

Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA. Electronic address:

Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.
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http://dx.doi.org/10.1016/j.celrep.2020.03.064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443283PMC
April 2020

Deep Learning AI Applications in the Imaging of Glioma.

Top Magn Reson Imaging 2020 Apr;29(2):115-0

Department of Radiology, Northwell Health and the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell and Lenox Hill Hospital, NY, NY.

This manuscript will review emerging applications of artificial intelligence, specifically deep learning, and its application to glioblastoma multiforme (GBM), the most common primary malignant brain tumor. Current deep learning approaches, commonly convolutional neural networks (CNNs), that take input data from MR images to grade gliomas (high grade from low grade) and predict overall survival will be shown. There will be more in-depth review of recent articles that have applied different CNNs to predict the genetics of glioma on pre-operative MR images, specifically 1p19q codeletion, MGMT promoter, and IDH mutations, which are important criteria for the diagnosis, treatment management, and prognostication of patients with GBM. Finally, there will be a brief mention of current challenges with DL techniques and their application to image analysis in GBM.
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http://dx.doi.org/10.1097/RMR.0000000000000237DOI Listing
April 2020

Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging.

Cancers (Basel) 2019 Jun 14;11(6). Epub 2019 Jun 14.

Department of Radiology, University of California, Irvine, Orange, CA 92868-3201, USA.

Radiographic assessment with magnetic resonance imaging (MRI) is widely used to characterize gliomas, which represent 80% of all primary malignant brain tumors. Unfortunately, glioma biology is marked by heterogeneous angiogenesis, cellular proliferation, cellular invasion, and apoptosis. This translates into varying degrees of enhancement, edema, and necrosis, making reliable imaging assessment challenging. Deep learning, a subset of machine learning artificial intelligence, has gained traction as a method, which has seen effective employment in solving image-based problems, including those in medical imaging. This review seeks to summarize current deep learning applications used in the field of glioma detection and outcome prediction and will focus on (1) pre- and post-operative tumor segmentation, (2) genetic characterization of tissue, and (3) prognostication. We demonstrate that deep learning methods of segmenting, characterizing, grading, and predicting survival in gliomas are promising opportunities that may enhance both research and clinical activities.
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http://dx.doi.org/10.3390/cancers11060829DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627902PMC
June 2019

Extent of BOLD Vascular Dysregulation Is Greater in Diffuse Gliomas without Isocitrate Dehydrogenase 1 R132H Mutation.

Radiology 2018 06 24;287(3):965-972. Epub 2018 Jan 24.

From the Department of Neurological Surgery (Z.K.E., M.L.O., J.N.B.), Gabriele Bartoli Brain Tumor Research Laboratory (Z.K.E., J.N.B., P.C.), Department of Pathology and Cell Biology (P.C.), and Department of Radiology (A.L., J.G.), Columbia University Medical Center, 710 W 168th St, Room B404, New York, NY 10032; Department of Radiology, Northwell Health, Manhasset, NY (C.I.H.); Department of Neurological Surgery, Oregon Health and Science University, Portland, OR (S.G.B.); and Department of Radiology, University of California-Irvine, Irvine, Calif (D.S.C.).

Purpose To determine the effect that R132H mutation status of diffuse glioma has on extent of vascular dysregulation and extent of residual blood oxygen level-dependent (BOLD) abnormality after surgical resection. Materials and Methods This study was an institutional review board-approved retrospective analysis of an institutional database of patients, and informed consent was waived. From 2010 to 2017, 39 treatment-naïve patients with diffuse glioma underwent preoperative echo-planar imaging and BOLD functional magnetic resonance imaging. BOLD vascular dysregulation maps were made by identifying voxels with time series similar to tumor and dissimilar to healthy brain. The spatial overlap between tumor and vascular dysregulation was characterized by using the Dice coefficient, and areas of BOLD abnormality outside the tumor margins were quantified as BOLD-only fraction (BOF). Linear regression was used to assess effects of R132H status on the Dice coefficient, BOF, and residual BOLD abnormality after surgical resection. Results When compared with R132H wild-type (R132H-) gliomas, R132H-mutated (R132H+) gliomas showed greater spatial overlap between BOLD abnormality and tumor (mean Dice coefficient, 0.659 ± 0.02 [standard error] for R132H+ and 0.327 ± 0.04 for R132H-; P < .001), less BOLD abnormality beyond the tumor margin (mean BOF, 0.255 ± 0.03 for R132H+ and 0.728 ± 0.04 for R132H-; P < .001), and less postoperative BOLD abnormality (residual fraction, 0.046 ± 0.0047 for R132H+ and 0.397 ± 0.045 for R132H-; P < .001). Receiver operating characteristic curve analysis showed high sensitivity and specificity in the discrimination of R132H+ tumors from R132H- tumors with calculation of both Dice coefficient and BOF (area under the receiver operating characteristic curve, 0.967 and 0.977, respectively). Conclusion R132H mutation status is an important variable affecting the extent of tumor-associated vascular dysregulation and the residual vascular dysregulation after surgical resection. RSNA, 2018 Online supplemental material is available for this article.
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http://dx.doi.org/10.1148/radiol.2017170790DOI Listing
June 2018

Beyond the embolus: "do not miss" diffusion abnormalities of ischaemic and non-ischaemic neurological disease.

Insights Imaging 2017 Dec 6;8(6):573-580. Epub 2017 Oct 6.

Department of Radiology, University of Colorado School of Medicine, Aurora, CO, 80045, USA.

Given the rapid evolution and technological advances in the diagnosis and treatment of acute ischaemic stroke (AIS), including the proliferation of comprehensive stroke centres and increasing emphasis on interventional stroke therapies, the need for prompt recognition of stroke due to acute large vessel occlusion has received significant attention in the recent literature. Diffusion-weighted imaging (DWI) is the gold standard for the diagnosis of acute ischaemic stroke, as images appear positive within minutes of ischaemic injury, and a high signal-to-noise ratio enables even punctate infarcts to be readily detected. DWI lesions resulting from a single arterial embolic occlusion or steno-occlusive lesion classically lateralise and conform to a specific arterial territory. When there is a central embolic source (e.g. left atrial thrombus), embolic infarcts are often found in multiple vascular territories. However, ischaemic disease arising from aetiologies other than arterial occlusion will often not conform to an arterial territory. Furthermore, there are several important entities unrelated to ischaemic disease that can present with abnormal DWI and which should not be confused with infarct. This pictorial review explores the scope and typical DWI findings of select neurologic conditions beyond acute arterial occlusion, which should not be missed or misinterpreted.

Teaching Points: • DWI abnormalities due to acute arterial occlusion must be promptly identified. • DWI abnormalities not due to arterial occlusion will often not conform to an arterial territory. • Several important non-ischaemic entities can present on DWI and should not be confused with infarct.
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http://dx.doi.org/10.1007/s13244-017-0574-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5707221PMC
December 2017

Confirmed case of levamisole-associated multifocal inflammatory leukoencephalopathy in a cocaine user.

J Neuroimmunol 2017 04 2;305:128-130. Epub 2017 Feb 2.

University of California, San Francisco, Department of Neurology, San Francisco, CA, USA.

Levamisole is a common adulterant in cocaine and has previously been associated with a variety of serious complications including multifocal inflammatory leukoencephalopathy (MIL). There have been several reports of MIL in patients taking cocaine and, though suspected, the presence of levamisole was not confirmed. We present a case of a 63-year-old woman presenting with stupor and spastic quadraparesis found to have urine positive for cocaine and levamisole. An MRI brain revealed innumerable FLAIR hyperintensities with restricted diffusion and incomplete ring-enhancement. This is the first case to confirm the presence of levamisole in a patient with MIL associated with cocaine use.
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http://dx.doi.org/10.1016/j.jneuroim.2017.01.018DOI Listing
April 2017

Wernicke-Like Encephalopathy Associated With Ifosfamide.

Neurohospitalist 2017 Jan 23;7(1):49-50. Epub 2016 Mar 23.

Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA.

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http://dx.doi.org/10.1177/1941874416637407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167088PMC
January 2017

Predicting Glioblastoma Recurrence by Early Changes in the Apparent Diffusion Coefficient Value and Signal Intensity on FLAIR Images.

AJR Am J Roentgenol 2017 Jan 11;208(1):57-65. Epub 2016 Oct 11.

1 Department of Radiology, Columbia University Medical Center, 622 W 168th St, PB-1-301, New York, NY 10032.

Objective: Recurrence of glioblastoma multiforme (GBM) arises from areas of microscopic tumor infiltration that have yet to disrupt the blood-brain barrier. We hypothesize that these microscopic foci of invasion cause subtle variations in the apparent diffusion coefficient (ADC) and FLAIR signal detectable with the use of computational big-data modeling.

Materials And Methods: Twenty-six patients with native GBM were studied immediately after undergoing gross total tumor resection. Within the peritumoral region, areas of future GBM recurrence were identified through coregistration of follow-up MRI examinations. The likelihood of tumor recurrence at each individual voxel was assessed as a function of signal intensity on ADC maps and FLAIR images. Both single and combined multivariable logistic regression models were created.

Results: A total of 419,473 voxels of data (105,477 voxels of data within tumor recurrence and 313,996 voxels of data on surrounding peritumoral edema) were analyzed. For future areas of recurrence, a 9.5% decrease in the ADC value (p < 0.001) and a 9.2% decrease in signal intensity on FLAIR images (p < 0.001) were shown, compared with findings for the surrounding peritumoral edema. Logistic regression revealed that the amount of signal loss on both ADC maps and FLAIR images correlated with the likelihood of tumor recurrence. A combined multiparametric logistic regression model was more specific in the prediction of tumor recurrence than was either single-variable model alone.

Conclusion: Areas of future GBM recurrence exhibit small but highly statistically significant differences in signal intensity on ADC maps and FLAIR images months before the development of abnormal enhancement occurs. A multiparametric logistic model calibrated to these changes can be used to estimate the burden of microscopic nonenhancing tumor and predict the location of recurrent disease. Computational big-data modeling performed at the voxel level is a powerful technique capable of discovering important but subtle patterns in imaging data.
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http://dx.doi.org/10.2214/AJR.16.16234DOI Listing
January 2017

Aggressive resection at the infiltrative margins of glioblastoma facilitated by intraoperative fluorescein guidance.

J Neurosurg 2017 Jul 7;127(1):111-122. Epub 2016 Oct 7.

Departments of 1 Neurological Surgery.

OBJECTIVE Extent of resection is an important prognostic factor in patients undergoing surgery for glioblastoma (GBM). Recent evidence suggests that intravenously administered fluorescein sodium associates with tumor tissue, facilitating safe maximal resection of GBM. In this study, the authors evaluate the safety and utility of intraoperative fluorescein guidance for the prediction of histopathological alteration both in the contrast-enhancing (CE) regions, where this relationship has been established, and into the non-CE (NCE), diffusely infiltrated margins. METHODS Thirty-two patients received fluorescein sodium (3 mg/kg) intravenously prior to resection. Fluorescence was intraoperatively visualized using a Zeiss Pentero surgical microscope equipped with a YELLOW 560 filter. Stereotactically localized biopsy specimens were acquired from CE and NCE regions based on preoperative MRI in conjunction with neuronavigation. The fluorescence intensity of these specimens was subjectively classified in real time with subsequent quantitative image analysis, histopathological evaluation of localized biopsy specimens, and radiological volumetric assessment of the extent of resection. RESULTS Bright fluorescence was observed in all GBMs and localized to the CE regions and portions of the NCE margins of the tumors, thus serving as a visual guide during resection. Gross-total resection (GTR) was achieved in 84% of the patients with an average resected volume of 95%, and this rate was higher among patients for whom GTR was the surgical goal (GTR achieved in 93.1% of patients, average resected volume of 99.7%). Intraoperative fluorescein staining correlated with histopathological alteration in both CE and NCE regions, with positive predictive values by subjective fluorescence evaluation greater than 96% in NCE regions. CONCLUSIONS Intraoperative administration of fluorescein provides an easily visualized marker for glioma pathology in both CE and NCE regions of GBM. These findings support the use of fluorescein as a microsurgical adjunct for guiding GBM resection to facilitate safe maximal removal.
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http://dx.doi.org/10.3171/2016.7.JNS16232DOI Listing
July 2017

Glioblastoma Induces Vascular Dysregulation in Nonenhancing Peritumoral Regions in Humans.

AJR Am J Roentgenol 2016 May 23;206(5):1073-81. Epub 2016 Mar 23.

1 Department of Radiology, College of Physicians and Surgeons, Columbia University, New York, NY.

Objective: Glioblastoma is an invasive primary brain malignancy that typically infiltrates the surrounding tissue with malignant cells. It disrupts cerebral blood flow through a variety of biomechanical and biochemical mechanisms. Thus, neuroimaging focused on identifying regions of vascular dysregulation may reveal a marker of tumor spread. The purpose of this study was to use blood oxygenation level-dependent (BOLD) functional MRI (fMRI) to compare the temporal dynamics of the enhancing portion of a tumor with those of brain regions without apparent tumors.

Materials And Methods: Patients with pathologically proven glioblastoma underwent preoperative resting-state BOLD fMRI, T1-weighted contrast-enhanced MRI, and FLAIR MRI. The contralesional control hemisphere, contrast-enhancing tumor, and peritu-moral edema were segmented by use of structural images and were used to extract the time series of these respective regions. The parameter estimates (beta values) for the two regressors and resulting z-statistic images were used as a metric to compare the similarity of the tumor dynamics to those of other brain regions.

Results: The time course of the contrast-enhancing tumor was significantly different from that of the rest of the brain (p < 0.05). Similarly, the control signal intensity was significantly different from the tumor signal intensity (p < 0.05). Notably, the temporal dynamics in the peritumoral edema, which did not contain enhancing tumor, were most similar to the those of enhancing tumor than to those of control regions.

Conclusion: The findings show that the disruption in vascular regulation induced by a glioblastoma can be detected with BOLD fMRI and that the spatial distribution of these disruptions is localized to the immediate vicinity of the tumor and peritumoral edema.
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http://dx.doi.org/10.2214/AJR.15.14529DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5235899PMC
May 2016

Hypofractionated radiation therapy versus standard fractionated radiation therapy with concurrent temozolomide in elderly patients with newly diagnosed glioblastoma.

Pract Radiat Oncol 2016 Sep-Oct;6(5):306-314. Epub 2015 Dec 4.

Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York; Department of Neurological Surgery, Columbia University Medical Center, New York, New York.

Purpose: Adjuvant hypofractionated radiation therapy (HRT) for elderly patients with newly diagnosed glioblastoma (GBM) is a reasonable option compared with standard fractionation radiation therapy (SFRT). Outcomes in patients receiving HRT in the presence of temozolomide (TMZ) compared with SFRT with TMZ are unclear. We examined HRT for GBM with TMZ in comparison to SFRT with TMZ.

Methods And Materials: We conducted a retrospective analysis of patients ≥60 years of age with newly diagnosed GBM who received SFRT or HRT from 1994 to 2014 in the postoperative setting. Inclusion criteria included SFRT (60 Gy/30 fractions or 59.4 Gy/33 fractions) versus HRT (40 Gy/15 fractions).

Results: In this cohort, 158 patients were treated with SFRT versus 26 with HRT. Median survival in patients receiving SFRT compared with HRT was 430 and 475 days (P = .550), respectively. Ninety-five percent of the SFRT patients received TMZ versus 100% of those treated with HRT. Patients receiving HRT were older (median, 72 vs 66 years). All HRT patients were treated with the intensity modulated radiation therapy (IMRT) technique versus SFRT, in which 57% had IMRT. Multivariate Cox regression showed decreased overall survival (OS) associated with patient age >70 (hazard ratio [HR], 1.84), lower Karnofsky performance status (HR, 5.25), biopsy versus surgical resection (HR, 4.18), radiation therapy planning technique 3- or 2-dimensional planning versus IMRT (HR, 1.91; HR, 3.40, respectively). Analysis restricted to patients receiving IMRT-based planning showed no difference in OS between HRT and SFRT. For patients receiving TMZ, there was no survival difference between those treated with HRT and those treated with SFRT.

Conclusions: Elderly GBM patients receiving HRT and those receiving SFRT had similar OS. Subset analysis patients receiving concurrent TMZ showed no difference in OS between the HRT and SFRT groups.
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http://dx.doi.org/10.1016/j.prro.2015.12.001DOI Listing
March 2017

A Modern Radiotherapy Series of Survival in Hispanic Patients with Glioblastoma.

World Neurosurg 2016 Apr 31;88:260-269. Epub 2015 Dec 31.

Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York, USA; Department of Neurological Surgery, Columbia University Medical Center, New York, New York, USA.

Background: Studies have shown racial differences in cancer outcomes. We investigate whether survival differences existed in Hispanic patients with glioblastoma (GBM) compared with other ethnicities from our modern radiotherapy series, because no study to date has focused on outcomes in this group after radiation therapy.

Methods: We retrospectively evaluated 428 patients diagnosed with GBM from 1996 to 2014 at our institution, divided into 4 groups based on self-report: white, black, Hispanic, and Asian/Indian. The primary outcome was overall survival. We analyzed differences in prognostic factors among the whole cohort compared with the Hispanic cohort alone.

Results: Baseline characteristics of the 4 racial groups were comparable. With a median follow-up of 387 days, no survival differences were seen by Kaplan-Meier analysis. Median overall survival for Hispanic patients was 355 days versus 450 days for the entire cohort. Factors significant for patient outcomes in the entire cohort differed slightly from those specific to Hispanic patients. Low Karnofsky Performance Status was significant on multivariate analysis in the whole population, but not in Hispanic patients. Extent of resection, recursive partitioning analysis class, and radiation therapy total dose were significant on multivariate analysis in both the whole population and Hispanic patients.

Conclusions: We found that Hispanic patients with GBM had no difference in survival compared with other ethnicities in our cohort. Differences exist in factors associated with outcomes on single and multivariate analysis for Hispanic patients with GBM compared with the entire cohort. Additional studies focusing on Hispanic patients will aid in more personalized treatment approaches in this group.
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http://dx.doi.org/10.1016/j.wneu.2015.12.081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255496PMC
April 2016

Big Data and the Future of Radiology Informatics.

Acad Radiol 2016 Jan 6;23(1):30-42. Epub 2015 Nov 6.

Department of Radiology, Temple University School of Medicine, Philadelphia, Pennsylvania.

Rapid growth in the amount of data that is electronically recorded as part of routine clinical operations has generated great interest in the use of Big Data methodologies to address clinical and research questions. These methods can efficiently analyze and deliver insights from high-volume, high-variety, and high-growth rate datasets generated across the continuum of care, thereby forgoing the time, cost, and effort of more focused and controlled hypothesis-driven research. By virtue of an existing robust information technology infrastructure and years of archived digital data, radiology departments are particularly well positioned to take advantage of emerging Big Data techniques. In this review, we describe four areas in which Big Data is poised to have an immediate impact on radiology practice, research, and operations. In addition, we provide an overview of the Big Data adoption cycle and describe how academic radiology departments can promote Big Data development.
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http://dx.doi.org/10.1016/j.acra.2015.10.004DOI Listing
January 2016

Timing of Adjuvant Radiotherapy in Glioblastoma Patients: A Single-Institution Experience With More Than 400 Patients.

Neurosurgery 2016 May;78(5):676-82

*Department of Radiation Oncology, Columbia University Medical Center, New York, New York;‡Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York;§Department of Neurological Surgery, Columbia University Medical Center, New York, New York;¶Department of Radiology, Columbia University Medical Center, New York, New York;‖The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, New York;#Division of Pediatric Hematology/Oncology and Stem Cell Transplantation, Department of Pediatrics, Columbia University Medical Center, New York, New York;**Department of Neurology, Columbia University Medical Center, New York, New York.

Background: The standard of care for patients with newly diagnosed glioblastoma (GBM) is maximal safe resection followed by adjuvant radiation therapy (RT) and temozolomide (TMZ).

Objective: To investigate whether the timing of adjuvant RT after surgery affected outcome in patients with GBM.

Methods: We retrospectively reviewed all patients with a diagnosis of GBM at our institution. A total of 447 patients were included in our analysis. Patients were divided into 3 equal groups based on the interval between surgery and RT. The primary outcome was overall survival (OS).

Results: Patients who began RT less than 21 days after surgery tended to be older, have a lower a Karnofsky Performance Status score, and higher recursive partitioning analysis class. These patients were more likely to have undergone biopsy only and received 3-dimensional conformal RT or 2-dimensional RT. The median OS for patients who started RT less than 21 days after surgery, between 21 and 32 days after surgery, and more than 32 days after surgery was 374, 465, and 478 days, respectively (P = .004). On multivariate Cox regression analysis, Karnofsky Performance Status score lower than 70, undergoing biopsy only, recursive partitioning analysis classes IV and V/VI, use of less than 36 Gy RT, and lack of TMZ chemotherapy were predictors of worse OS. The interval between surgery and RT was not significantly associated with OS on multivariate analysis.

Conclusion: Patients who begin RT less than 21 days after surgery tend to have worse prognostic factors than those who begin RT later. When accounting for significant covariates, the effect of timing between surgery and RT is not significant.
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http://dx.doi.org/10.1227/NEU.0000000000001036DOI Listing
May 2016

Increased rates of authorship in radiology publications: a bibliometric analysis of 142,576 articles published worldwide by radiologists between 1991 and 2012.

AJR Am J Roentgenol 2015 Jan;204(1):W52-7

1 Department of Radiology, Columbia University Medical Center, New York, NY.

Unlabelled: OBJECTIVE; There is evidence in academic medicine that the number of authors per paper has increased over time. The goal of this study was to quantitatively analyze authorship trends in the field of radiology over 20 years.

Materials And Methods: A search of the National Library of Medicine MEDLINE database was conducted to identify articles published by radiology departments between 1991 and 2012. Country of origin, article study design, and journal impact factor were recorded. The increase in number of authors per paper was assessed by linear and nonlinear regression. Pearson correlation was used to assess the relation between journal impact factor and number of authors.

Results: A total of 142,576 articles and 699,257 authors were identified during the study period. The mean number of authors per paper displayed linear growth from 3.9 to 5.7 (p < 0.0001). The proportion of single authors declined from 11% in 1991 to 4.4% in 2012. The number of clinical trials increased in a linear pattern, review articles in an exponential pattern, and case reports in a logistic pattern (p < 0.0001 for each). Countries with the highest number of authors per paper were Japan, Italy, and Germany. The number of articles funded by the U.S. National Institutes of Health (NIH) displayed exponential growth and of non-NIH-funded articles displayed linear growth (p < 0.0001 for each). A negligible relation was observed between journal impact factor and number of authors (Pearson r = 0.1066).

Conclusion: Radiology has had a steady increase in mean number of authors per paper since the early 1990s that has varied by study design. The increase is probably multi-factorial and includes components of author inflation and increasing complexity of research. Findings support the need for reemphasis of authorship criteria to preserve authorship value and accountability.
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http://dx.doi.org/10.2214/AJR.14.12852DOI Listing
January 2015

Value of gadolinium-enhanced MRI in detection of acute appendicitis in children and adolescents.

AJR Am J Roentgenol 2014 Nov;203(5):W543-8

1 Department of Radiology, Columbia University Medical Center, New York, NY.

Objective: The aim of this study was to determine both the value of gadolinium-enhanced MRI in children with suspected acute appendicitis and the best sequences for detecting acute appendicitis, to thereby decrease imaging time.

Materials And Methods: This was a retrospective review of pediatric patients with suspected appendicitis who had undergone MRI at our institution between 2010 and 2011 after an indeterminate ultrasound examination. MRI examinations included T1-weighted unenhanced and contrast-enhanced, T2-weighted, and balanced steady-state free precession (SSFP) sequences in axial and coronal planes. Sequences were reviewed together and individually by five radiologists who were blinded to the final diagnosis. Radiologists were asked to score their confidence of appendicitis diagnosis using a 5-point scale. The diagnostic performance of each MR sequence was obtained by comparing the mean area under the curve (AUC) using receiver operating characteristic (ROC) analysis.

Results: A total of 49 patients with clinically suspected appendicitis were included, of whom 16 received a diagnosis of appendicitis. The mean AUCs for reviewing all sequences together, contrast-enhanced sequences alone, T2-weighted sequences alone, and balanced SSFP alone were 0.984, 0.979, 0.944, and 0.910, respectively. No significant difference was observed between reviewing all sequences together versus contrast-enhanced sequences alone (p = 0.90) and T2-weighted sequences alone (p = 0.23). A significant difference was observed between contrast-enhanced sequences and balanced SSFP (p < 0.03).

Conclusion: Gadolinium-enhanced images and T2-weighted images are most helpful in the assessment of acute appendicitis in the pediatric population. These findings have led to protocol modifications that have reduced imaging time.
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http://dx.doi.org/10.2214/AJR.13.12093DOI Listing
November 2014

Intermediate outcomes and predictors of efficacy in the radiofrequency ablation of 100 pathologically proven renal cell carcinomas.

J Vasc Interv Radiol 2014 Nov 28;25(11):1682-8; quiz 1689. Epub 2014 Jul 28.

Department of Radiology, David Geffen School of Medicine at the University of California, Los Angeles, 757 Westwood Plaza, Suite 2125, Los Angeles, CA 90095.

Purpose: To determine oncologic outcomes and predictors of primary efficacy, including RENAL nephrometry scores (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to polar lines), after percutaneous radiofrequency (RF) ablation of proven renal cell carcinoma (RCC).

Materials And Methods: Patients who underwent percutaneous computed tomography- and ultrasound-guided RF ablation for histologically proven RCC from 2004 to 2011 were evaluated. Clinical data, pathologic findings, technical details, and outcomes were reviewed. Univariate and multivariate logistic regression analysis was performed to determine predictors of primary technique effectiveness and complications. Local tumor progression-free, metastasis-free, and overall survival were calculated. One hundred RCC lesions underwent 115 RF ablation sessions in 84 patients. Median follow-up was 24 months (mean, 27 mo; range, 1-106 mo).

Results: Efficacy of RF ablation was defined per International Working Group of Image-Guided Tumor Ablation criteria. Total, primary, and secondary technique effectiveness rates were 95% (95 of 100), 86% (86 of 100), and 9% (nine of 100), respectively. Primary efficacy was associated with size (P < .001), proximity to collecting system (P = .001), RENAL nephrometry score (P < .001), and number of ablation zones (P < .001). Complications occurred in 13% of patients, without procedure-related deaths. The median 2.1-year local progression-free, metastasis-free, disease-specific, and overall survival rates were 86%, 98.7%, 100%, and 97.6%, respectively.

Conclusions: Percutaneous image-guided RF ablation for RCC provides excellent intermediate oncologic control. Location, size, proximity to the collecting system, low RENAL nephrometry score, and number of ablation zones predict primary efficacy.
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http://dx.doi.org/10.1016/j.jvir.2014.06.013DOI Listing
November 2014

An evaluation of the sensitivity of MRI at detecting hepatocellular carcinoma in cirrhotic patients utilizing an explant reference standard.

Clin Imaging 2014 Sep-Oct;38(5):693-7. Epub 2014 Jun 4.

Columbia University, Dept. of Radiology, HP-3-305, NY, NY 10032, United States. Electronic address:

Objective: To evaluate the sensitivity of magnetic resonance imaging (MRI) at detecting hepatocellular carcinoma (HCC).

Materials And Methods: MRIs performed within 120 days of transplant, and pathology, were reviewed.

Results: Of the 87 patients included in the final analysis, 58 had HCC at explant (106 total HCCs). The per-patient and per-lesion sensitivity was 74.1% (43/58) and 81.1% (86/106), respectively. The sensitivity based on size <1cm, 1-2 cm, and >2 cm was 80.0% (28/35), 77.2% (44/57), and 100% (14/14).

Conclusion: MRI accurately detects HCC, including HCCs <2 cm. In our study population, the imaging disease staging was concordant with pathological staging in 80% of patients.
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http://dx.doi.org/10.1016/j.clinimag.2014.05.014DOI Listing
May 2015

Nephrogenic systemic fibrosis risk and liver disease.

Int J Nephrol 2014 23;2014:679605. Epub 2014 Mar 23.

Department of Radiology, Columbia University, New York Presbyterian Hospital, 622 West 168th Street, PB-1-301, New York, NY 10032, USA.

Objective. Evaluate the incidence of nephrogenic systemic fibrosis (NSF) in patients with liver disease in the peritransplant period. Materials and Methods. This IRB approved study retrospectively reviewed patients requiring transplantation for cirrhosis, hepatocellular carcinoma (HCC), or both from 2003 to 2013. Records were reviewed identifying those having gadolinium enhanced MRI within 1 year of posttransplantation to document degree of liver disease, renal disease, and evidence for NSF. Results. Gadolinium-enhanced MRI was performed on 312 of 837 patients, including 23 with severe renal failure (GFR < 30 mL/min/1.73 cm(2)) and 289 with GFR > 30. Two of 23 patients with renal failure developed NSF compared to zero NSF cases in 289 patients with GFR > 30 (0/289; P < 0.003). High dose gadodiamide was used in the two NSF cases. There was no increased incidence of NSF with severe liver disease (1/71) compared to nonsevere liver disease (1/241; P = 0.412). Conclusion. Renal disease is a risk factor for NSF, but in our small sample our evidence suggests liver disease is not an additional risk factor, especially if a low-risk gadolinium agent is used. Noting that not all patients received high-risk gadolinium, a larger study focusing on patients receiving high-risk gadolinium is needed to further evaluate NSF risk in liver disease in the peritransplant period.
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http://dx.doi.org/10.1155/2014/679605DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981185PMC
April 2014

Prevalence and timing of bend relief disconnection in patients supported by the late version HeartMate II left ventricular assist device.

J Heart Lung Transplant 2013 Mar 16;32(3):320-5. Epub 2013 Jan 16.

Columbia University Medical Center, New York, New York, NY 11032, USA.

Background: On April 4, 2012, the U.S. Food and Drug Administration issued a Class 1R recall of the HeartMate II (Thoratec Corporation, Pleasanton, CA) left ventricular assist device (LVAD) due to spontaneous detachment of the bend relief from its intended position in patients implanted with the most recent version of the HM II. This study examined the incidence and timing of outflow graft bend relief disconnection in patients implanted with the HM II LVAD.

Methods: All patients supported with the modified version of the HM II LVAD were asked to report for dedicated abdominal X-ray imaging to assess the position of the bend relief. Also performed was a retrospective review of X-ray images of all patients who had previously been supported with this version but had since received a transplant, undergone LVAD explant, or died.

Results: Between March 9, 2011, and April 9, 2012, 59 patients underwent primary implant with the modified version HM II. Follow up X-ray images were available for 56 patients (95%). The bend relief was found fully disconnected in 6 of 56 (11%) and partially disconnected in 13 (23%). Two of 6 patients (33%) with full bend relief disconnection and 1 of 13 of the initially partially disconnected patients (7.7%) required urgent surgical intervention due to symptoms of hemolysis and/or heart failure.

Conclusions: Bend relief disconnection is common and may be observed immediately after implant but may also develop over time. Full bend relief disconnect may present with hemolysis and/or heart failure symptoms and often requires surgical revision. Surveillance abdominal X-ray imaging should be performed routinely on all patients who were implanted with the modified version HM II.
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http://dx.doi.org/10.1016/j.healun.2012.11.016DOI Listing
March 2013

Changes in stroke research productivity: A global perspective.

Surg Neurol Int 2012 15;3:27. Epub 2012 Feb 15.

Department of Radiology, Columbia University, New York Presbyterian Medical Center, New York, NY 10032, USA.

Background: While stroke is the second leading cause of death worldwide, little work has been done to quantify the growth and progress of stroke publications. The purpose of this study is to quantitatively analyze trends in the stroke literature over the past 12 years, specifically examining changes in worldwide productivity and study methodology.

Methods: The study was a retrospective bibliometric analysis of all stroke articles published between 1996 and 2008 indexed in MEDLINE. Country of origin, MEDLINE-defined methodology, specialty of the first author, and funding sources (for US articles) were recorded. Growth was analyzed by using linear and nonlinear regression.

Results: Total articles numbered 32,309 during the study period, with leading global contributors including the United States with 8795 (27.2%) articles, Japan with 2757 (8.5%) articles, and the United Kingdom with 2629 (8.1%) articles. Growth globally and in the United States followed a linear pattern at 209.9 and 56.2 articles per year, respectively (both P < 0.001). Review articles and clinical trials numbered 5932 (18.4%) and 2934 (9.1%), respectively. Clinical trials followed an exponential growth pattern of 7.7% per year (P < 0.001). Regarding specialty influence, pain management and rehabilitation had the largest proportional growth in clinical trials from 4 to 51 articles.

Conclusions: Within the stroke literature, we observed continued growth worldwide, sustained growth in the United States, and a steady increase in the number of clinical trials, especially by pain management and rehabilitation.
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http://dx.doi.org/10.4103/2152-7806.92941DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3307235PMC
October 2012

Research productivity in neurosurgery: trends in globalization, scientific focus, and funding.

J Neurosurg 2011 Dec 26;115(6):1262-72. Epub 2011 Aug 26.

Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California 90095-7039, USA.

Object: While research is important for the survival, growth, and expansion of neurosurgery, little work has been done to quantify the status and trends of neurosurgical publications. The purpose of this bibliometric study was to quantitatively analyze trends in neurosurgical publications, including changes in worldwide productivity, study methodology, subspecialty topic, and funding.

Methods: This was a retrospective bibliometric study using MEDLINE to record all publications between 1996 and 2009 by first authors affiliated with neurosurgical departments. Country of origin, MEDLINE-defined methodology, study topic, and funding sources (for US articles) were recorded. Linear regression was used to derive growth rates.

Results: Total articles numbered 53,425 during the study period, with leading global contributors including the US with 16,943 articles (31.7%) and Japan with 10,802 articles (20.2%). Countries demonstrating rapid growth in productivity included China (121.9 ± 9.98%/year, p < 0.001), South Korea (50.5 ± 4.7%/year, p < 0.001), India (19.4 ± 1.8%/year, p < 0.001), and Turkey (25.3 ± 2.8%/year, p < 0.001). While general research articles, case reports, and review articles have shown steady growth since 1996, clinical trials and randomized controlled trials have declined to 2004 levels. The greatest overall subspecialty growth was seen in spine surgery. Regarding funding, relative contribution of National Institutes of Health (NIH)-funded publications decreased from 30.2% (290 of 959) to 22.5% (356 of 1229) between 1996 and 2009.

Conclusions: Neurosurgical publications demonstrate continued increases in productivity as well as in global expansion, although US contributions remain dominant. Two challenges that the neurosurgical community is facing include the preponderance of case reports and review articles and the relative decline in NIH funding for US neurosurgical publications, as productivity has outpaced government financial support.
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http://dx.doi.org/10.3171/2011.8.JNS11857DOI Listing
December 2011
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