Abdelkader Mahammedi M.D

Abdelkader Mahammedi M.D

University of Kentucky

H-index: 11

North America-United States

Abdelkader Mahammedi M.D Information

University

University of Kentucky

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Citations(all)

677

Citations(since 2020)

549

Cited By

273

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11

hIndex(since 2020)

11

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11

i10Index(since 2020)

11

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University of Kentucky

Abdelkader Mahammedi M.D Skills & Research Interests

Neuroradiology

Top articles of Abdelkader Mahammedi M.D

Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT

Background Outlining acutely infarcted tissue on non-contrast CT is a challenging task for which human inter-reader agreement is limited. We explored two different methods for training a supervised deep learning algorithm: one that used a segmentation defined by majority vote among experts and another that trained randomly on separate individual expert segmentations.Methods The data set consisted of 260 non-contrast CT studies in 233 patients with acute ischemic stroke recruited from the multicenter DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trial. Additional external validation was performed using 33 patients with matched stroke onset times from the University Hospital Lausanne. A benchmark U-Net was trained on the reference annotations of three experienced neuroradiologists to segment ischemic brain tissue using majority vote and random expert sampling …

Authors

Sophie Ostmeier,Brian Axelrod,Yongkai Liu,Yannan Yu,Bin Jiang,Nicole Yuen,Benjamin Pulli,Benjamin FJ Verhaaren,Hussam Kaka,Max Wintermark,Patrik Michel,Abdelkader Mahammedi,Christian Federau,Maarten G Lansberg,Gregory W Albers,Michael E Moseley,Gregory Zaharchuk,Jeremy J Heit

Journal

Journal of NeuroInterventional Surgery

Published Date

2024/2/1

USE-evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging

Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metrics, such as the Dice, are used as a metric to evaluate the performance of these models in order for results to be comparable.However, there is a mismatch between the distributions of cases and the difficulty level of segmentation tasks in public data sets compared to clinical practice. Common metrics used to assess performance fail to capture the impact of this mismatch, particularly when dealing with datasets in clinical settings that involve challenging segmentation tasks, pathologies with low signal, and reference annotations that are uncertain, small, or empty. Limitations of common metrics may result in ineffective machine learning research in designing and optimizing models. To effectively evaluate the clinical value of such …

Authors

Sophie Ostmeier,Brian Axelrod,Fabian Isensee,Jeroen Bertels,Michael Mlynash,Soren Christensen,Maarten G Lansberg,Gregory W Albers,Rajen Sheth,Benjamin FJ Verhaaren,Abdelkader Mahammedi,Li-Jia Li,Greg Zaharchuk,Jeremy J Heit

Journal

Medical Image Analysis

Published Date

2023/12/1

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists

We determined if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to neuroradiologists. Non-contrast CT (NCCT) examinations from 232 acute ischemic stroke patients who were enrolled in the DEFUSE 3 trial were included in this study. Three experienced neuroradiologists independently segmented hypodensity that reflected the ischemic core on each scan. The neuroradiologist with the most experience (expert A) served as the ground truth for deep learning model training. Two additional neuroradiologists’ (experts B and C) segmentations were used for data testing. The 232 studies were randomly split into training and test sets. The training set was further randomly divided into 5 folds with training and validation sets. A 3-dimensional CNN architecture was trained and optimized to predict the segmentations of expert A from …

Authors

Sophie Ostmeier,Brian Axelrod,Benjamin FJ Verhaaren,Soren Christensen,Abdelkader Mahammedi,Yongkai Liu,Benjamin Pulli,Li-Jia Li,Greg Zaharchuk,Jeremy J Heit

Journal

Scientific Reports

Published Date

2023/9/26

Abstract TMP69: Random Rater Sampling For Deep Learning Algorithm To Segment Acute Ischemic Stroke On Non-contrast Computed Tomography

Introduction: The delineation of volume and location of acute ischemic brain tissue (AIBT) on Non-Contrast CT (NCCT) increases the efficiency of endovascular treatment decisions. However, the manual segmentation of the AIBT on NCCT is a challenging task and suffers from low inter-expert agreement. Whether supervised deep convolutional neural networks (CNN) are more accurate than expert raters remain to be determined, and the optimal ground truth segmentation of AIBT is unclear given the low inter-expert agreement. We hypothesized that randomly sampling ground truth segmentations of expert raters would enable the CNN to better approximate an accurate ground truth and increase performance. Methods: The data set consisted of 200 NCCT images (Figure 1a)) of acute ischemic stroke patients presenting within 6-16h and consenting to the DEFUSE3 trial. Three experienced neuroradiologists …

Authors

Sophie Ostmeier,Benjamin F Verhaaren,Abdelkader Mahammedi,Soren Christensen,Greg W Albers,Maarten G Lansberg,Jeremy J Heit

Journal

Stroke

Published Date

2023/2

Lessons learned from evolving frameworks in adult glioblastoma

Glioblastoma (GBM) is the most common and aggressive malignant adult brain tumor. Significant effort has been directed to achieve a molecular subtyping of GBM to impact treatment. The discovery of new unique molecular alterations has resulted in a more effective classification of tumors and has opened the door to subtype-specific therapeutic targets. Morphologically identical GBM may have different genetic, epigenetic, and transcriptomic alterations and therefore different progression trajectories and response to treatments. With a transition to molecularly guided diagnosis, there is now a potential to personalize and successfully manage this tumor type to improve outcomes. The steps to achieve subtype-specific molecular signatures can be extrapolated to other neuroproliferative as well as neurodegenerative disorders.

Authors

Mirna Lechpammer,Abdelkader Mahammedi,Daniel A Pomeranz Krummel,Soma Sengupta

Published Date

2023/1/1

Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework

Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease and cognitive impairment at 1 year follow-up. Typical grading of EPVS is often challenging and time consuming and is usually based on a subjective visual rating scale. The purpose of the current study was to develop an interpretable, 3D neural network for grading enlarged perivascular spaces (EPVS) severity at the level of the basal ganglia using clinical-grade imaging in a heterogenous acute stroke cohort, in the context of total cerebral small vessel disease (CSVD) burden. T2-weighted images from a retrospective cohort of 262 acute stroke patients, collected in 2015 from 5 regional medical centers, were used for analyses. Patients were given a label of 0 for none-to-mild EPVS (< 10) and 1 for moderate-to-severe EPVS (≥ 10). A three-dimensional residual …

Authors

Brady J Williamson,Vivek Khandwala,David Wang,Thomas Maloney,Heidi Sucharew,Paul Horn,Mary Haverbusch,Kathleen Alwell,Shantala Gangatirkar,Abdelkader Mahammedi,Lily L Wang,Thomas Tomsick,Mary Gaskill-Shipley,Rebecca Cornelius,Pooja Khatri,Brett Kissela,Achala Vagal

Journal

Scientific Reports

Published Date

2022/1/17

The use of ARMCan app to improve the quality of life in breast cancer patients with chemobrain.

e13619Background: Breast cancer is the most diagnosed cancer in women with approximately 2 million women diagnosed in 2018. The 10-year survival rate is 78%. Breast cancer patients who undergo chemotherapy treatment can suffer neurocognitive impairment resulting in significant effects on their cognitive functioning. Chemotherapy-related dysfunction is known as “chemobrain”. Chemobrain is the basis of significant neurological morbidities in the breast cancer population. It causes difficulty in people being able to carry out activities of daily living and impacts people’s livelihoods and well-being. Studies have shown that music-based intervention can improve cognitive function. Methods: Since music-based interventions to specifically address chemo-related cognitive deficits have not been explored, we are conducting a pilot feasibility study to beta test the novel Active Receptive Music for Cancer patients …

Authors

Abigail N Koehler,Yehudit Rothman,Diego Gomez Enriquez,Michelle Kirschner,Rhonna Shatz,Abdelkader Mahammedi,Claudia B Rebola,Soma Sengupta

Published Date

2022/6/1

Non-inferiority of Deep Learning Acute Ischemic Stroke Segmentation on Non-Contrast CT Compared to Expert Neuroradiologists

To determine if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to neuroradiologists. Non-contrast CT (NCCT) examinations from 232 acute ischemic stroke patients who were enrolled in the DEFUSE 3 trial were included in this study. Three experienced neuroradiologists independently segmented hypodensity that reflected the ischemic core on each scan. The neuroradiologist with the most experience (expert A) served as the ground truth for deep learning model training. Two additional neuroradiologists (experts B and C) segmentations were used for data testing. The 232 studies were randomly split into training and test sets. The training set was further randomly divided into 5 folds with training and validation sets. A 3-dimensional CNN architecture was trained and optimized to predict the segmentations of expert A from NCCT. The performance of the model was assessed using a set of volume, overlap, and distance metrics using non-inferiority thresholds of 20%, 3ml, and 3mm. The optimized model trained on expert A was compared to test experts B and C. We used a one-sided Wilcoxon signed-rank test to test for the non-inferiority of the model-expert compared to the inter-expert agreement. The final model performance for the ischemic core segmentation task reached a performance of 0.46+-0.09 Surface Dice at Tolerance 5mm and 0.47+-0.13 Dice when trained on expert A. Compared to the two test neuroradiologists the model-expert agreement was non-inferior to the inter-expert agreement, p < 0.05. The CNN accurately delineates the hypodense …

Authors

Sophie Ostmeier,Brian Axelrod,Benjamin FJ Verhaaren,Soren Christensen,Abdelkader Mahammedi,Yongkai Liu,Benjamin Pulli,Li-Jia Li,Greg Zaharchuk,Jeremy J Heit

Journal

arXiv preprint arXiv:2211.15341

Published Date

2022/11/24

Small vessel disease, a marker of brain health: what the radiologist needs to know

Small vessel disease, a disorder of cerebral microvessels, is an expanding epidemic and a common cause of stroke and dementia. Despite being almost ubiquitous in brain imaging, the clinicoradiologic association of small vessel disease is weak, and the underlying pathogenesis is poorly understood. The STandards for ReportIng Vascular changes on nEuroimaging (STRIVE) criteria have standardized the nomenclature. These include white matter hyperintensities of presumed vascular origin, recent small subcortical infarcts, lacunes of presumed vascular origin, prominent perivascular spaces, cerebral microbleeds, superficial siderosis, cortical microinfarcts, and brain atrophy. Recently, the rigid categories among cognitive impairment, vascular dementia, stroke, and small vessel disease have become outdated, with a greater emphasis on brain health. Conventional and advanced small vessel disease imaging …

Authors

A Mahammedi,LL Wang,BJ Williamson,P Khatri,B Kissela,RP Sawyer,R Shatz,V Khandwala,A Vagal

Published Date

2022/5/1

Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists

Purpose To develop a deep learning model to segment the acute ischemic infarct on non-contrast Computed Tomography (NCCT). Materials and Methods In this retrospective study, 227 Head NCCT examinations from 200 patients enrolled in the multicenter DEFUSE 3 trial were included. Three experienced neuroradiologists (experts A, B and C) independently segmented the acute infarct on each study. The dataset was randomly split into 5 folds with training and validation cases. A 3D deep Convolutional Neural Network (CNN) architecture was optimized for the data set properties and task needs. The input to the model was the NCCT and the output was a segmentation mask. The model was trained and optimized on expert A. The outcome was assessed by a set of volume, overlap and distance metrics. The predicted segmentations of the best model and expert A were compared to experts B and C. Then we used …

Authors

Sophie Ostmeier,Jeremy J Heit,Brian Axelrod,Li-Jia Li,Greg Zaharchuk,Benjamin FJ Verhaaren,Abdelkader Mahammedi,Soren Christensen,Maarten G Lansberg

Journal

arXiv e-prints

Published Date

2022/11

Pearls & Oy-sters: Pivoting Treatment Regimens of Pediatric Atypical Teratoid Rhabdoid Tumors to Optimize Care in Adult ATRT: A Case Report

Atypical teratoid rhabdoid tumor (ATRT) is a highly malignant embryonal tumor of the CNS, largely affecting pediatric patients, with exceedingly rare cases in adults at an estimated annual incidence of 1/1,000,000. We report a unique case of ATRT in a 43-year-old female patient who first presented with progressive focal headaches. Imaging revealed a sellar mass with suprasellar extensions, which was partially removed via a transsphenoidal resection. The tumor aggressively recurred just 1 month postoperatively. Her care team pursued a novel treatment plan by using a slightly modified COG ACNS 0332 regimen, which involved radiation, followed by 4 cycles of monthly chemotherapy including vincristine, cyclophosphamide, and cisplatin. Hematopoietic stem cells were collected between radiation and chemotherapy in the event that the patient required stem cell salvage therapy postadjuvant chemotherapy. The …

Authors

Rohan Rao,Abigail Koehler,Yehudit Rothman,Brandi Turner,Jamie Denlinger,Melissa Erickson,Matthew Hagen,Timothy S Braverman,Abdelkader Mahammedi,Karl Golnik,Mario Zuccarello,Yair M Gozal,E Randolph Broun,Susan N Chi,Soma Sengupta

Journal

Neurology

Published Date

2022/4/26

Imaging of Headache Attributed to Vascular Disorders

This article will focus on imaging pearls and pitfalls of vascular causes of headaches. These include aneurysms, vascular malformations, vasculitides, and cerebral venous thrombosis.

Authors

Lily L Wang,Abdelkader Mahammedi,Achala S Vagal

Published Date

2022/8/1

Role of imaging in rare COVID-19 vaccine multiorgan complications

As of September 18th, 2021, global casualties due to COVID-19 infections approach 200 million, several COVID-19 vaccines have been authorized to prevent COVID-19 infection and help mitigate the spread of the virus. Despite the vast majority having safely received vaccination against SARS-COV-2, the rare complications following COVID-19 vaccination have often been life-threatening or fatal. The mechanisms underlying (multi) organ complications are associated with COVID-19, either through direct viral damage or from host immune response (i.e., cytokine storm). The purpose of this manuscript is to review the role of imaging in identifying and elucidating multiorgan complications following SARS-COV-2 vaccination—making clear that, in any case, they represent a minute fraction of those in the general population who have been vaccinated. The authors are both staunch supporters of COVID-19 vaccination …

Authors

Riccardo Cau,Cesare Mantini,Lorenzo Monti,Lorenzo Mannelli,Emanuele Di Dedda,Abdelkader Mahammedi,Refky Nicola,John Roubil,Jasjit S Suri,Giulia Cerrone,Daniela Fanni,Gavino Faa,Alessandro Carriero,Angelo Scuteri,Marco Francone,Luca Saba

Published Date

2022/3/14

Imaging appearance of migraine and tension type headache

Headache disorders rank third among the worldwide causes of disability, measured in years of life lost to disability. 1 Primary headaches, such as migraine-type headache (MTH) and tension-type headache (TTH), are the most prevalent type of headache disorders. According to the Global Burden of Disease Study 2010 (GBD2010), TTH and migraine were reported as the second (20.1%) and third (14.7%) most prevalent disorders in the world, respectively,(after dental caries first). 2 The global prevalence of TTH is 40% and migraine 10%. 3MTH is a common and chronic condition with multifactorial neurovascular etiologies characterized by recurrent paroxysmal attacks of throbbing headache with or without autonomic nervous system dysfunction. According to the International Classification of Headache Disorders, 3rd Edition (ICHD-III beta) criteria, 4 the characteristics of MTH and TTH are well distinct (Table 1). In …

Authors

Abdelkader Mahammedi,Lily L Wang,Achala S Vagal

Published Date

2022/8/1

Association between CT angiogram collaterals and CT perfusion in delayed time windows for large vessel occlusion ischemic strokes

Background and PurposeCollateral flow can determine ischemic core and tissue at risk. Using the Interventional Management of Stroke (IMS) III trial data, we explored the relationship between computed tomography angiogram (CTA) collateral status and CT perfusion (CTP) parameters. MethodsBaseline CTA collaterals were trichotomized as good, intermediate, and poor, and CTP studies were analyzed to quantify ischemic core, tissue at risk, and mismatch ratios. Kruskal–Wallis and Spearman tests were used to measure the strength of association and correlation between CTA collaterals and CTP parameters. ResultsA total of 95 patients had diagnostic CTP studies in the IMS III trial. Of these, 53 patients had M1/M2 middle cerebral artery±intracranial internal carotid artery occlusion, where baseline CTA collateral grading was performed. CTA collaterals were associated with smaller CTP measured ischemic core …

Authors

Achala Vagal,Bijoy K Menon,Lydia D Foster,Anthony Livorine,Sharon D Yeatts,Emmad Qazi,Chris d’Esterre,Junzi Shi,Andrew M Demchuk,Michael D Hill,David S Liebeskind,Thomas Tomsick,Mayank Goyal

Journal

Stroke

Published Date

2016/2

Complete response of a patient with a mismatch repair deficient aggressive pituitary adenoma to immune checkpoint inhibitor therapy: a case report

CONCLUSION:APA is a tumor with frequent recurrence and a short median expected length of survival. Here, we demonstrate the utility of immunotherapy in a single case report of APA, with complete resolution of recurrent APA and improved survival compared with life expectancy.ABBREVIATIONS:ACTH adrenocorticotropic hormoneAPA aggressive pituitary adenomaCTLA cytotoxic T-lymphocyte-associated proteinICI immune checkpoint inhibitorIHC immunohistochemicalMMR mismatch repairMMRd mismatch repair deficientPC pituitary carcinomaTMZ temozolomide.Pituitary tumors comprise 10% to 25% of intracranial neoplasms; although most are benign, approximately 35% are invasive and a small portion malignant. 1-3 Aggressive pituitary adenomas (APAs) are characterized by a high Ki-67 index, rapid growth, and resistance to treatment. 4, 5 Pituitary carcinoma (PC) is defined by metastasis, typically …

Authors

Sanjit Shah,Saima Manzoor,Yehudit Rothman,Matthew Hagen,Luke Pater,Karl Golnik,Abdelkader Mahammedi,Andrew L Lin,Ruchi Bhabhra,Jonathan A Forbes,Soma Sengupta

Journal

Neurosurgery

Published Date

2022/8/1

Brain and lung imaging correlation in patients with COVID-19: could the severity of lung disease reflect the prevalence of acute abnormalities on neuroimaging? A global …

PURPOSEOur aim was to study the association between abnormal findings on chest and brain imaging in patients with coronavirus disease 2019 (COVID-19) and neurologic symptoms.MATERIALS AND METHODSIn this retrospective, international multicenter study, we reviewed the electronic medical records and imaging of hospitalized patients with COVID-19 from March 3, 2020, to June 25, 2020. Our inclusion criteria were patients diagnosed with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and available chest CT and brain imaging. The 5 lobes of the lungs were individually scored on a scale of 0–5 (0 corresponded to no involvement and 5 corresponded to >75% involvement). A CT lung severity score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement).RESULTSA total of 135 …

Authors

A Mahammedi,A Ramos,N Bargalló,M Gaskill,S Kapur,L Saba,H Carrete,S Sengupta,E Salvador,A Hilario,Y Revilla,M Sanchez,M Perez-Nuñez,S Bachir,B Zhang,L Oleaga,J Sergio,L Koren,P Martin-Medina,L Wang,M Benegas,F Ostos,G Gonzalez-Ortega,P Calleja,G Udstuen,B Williamson,V Khandwala,S Chadalavada,D Woo,A Vagal

Journal

American Journal of Neuroradiology

Published Date

2021/6/1

Shapeshifter: The Diverse Clinical and Radiologic Phenotypes Associated with MOG Antibody-Associated Disease (1573)

Objective: To define the clinical, radiologic, and laboratory features of MOG antibody-associated disease (MOGAD). Background: MOGAD is an autoimmune demyelinating disease of the central nervous system, defined by autoantibodies to myelin oligodendrocyte glycoprotein (MOG). MOGAD classically presents with recurrent optic neuritis (ON) and longitudinally extensive transverse myelitis (LETM) in adults. However, the full spectrum of the recently described disease is unknown. Design/Methods: Records of all patients treated in our neuroimmunology clinic, which serves the Greater Cincinnati and Northern Kentucky regions, were searched using the Epic SlicerDicer tool. All records with positive testing for IgG antibodies against MOG, as measured by fluorescence-activated cell sorting (FACS), were included in this retrospective chart review. No records were excluded on the basis of clinical or radiologic features. Following abstraction, case descriptors were verified by two independent …

Authors

Samuel Marcucci,Rosemarie Walch,Ameneh Zare Shahabadi,Abdelkader Mahammedi,Roman Kassa,Lawrence Goldstick,Allison Jordan,Aram Zabeti

Published Date

2021/4/13

BRMP-03. Pituitary carcinoma: a case of dramatic response to immunotherapy (ipilimumab+ nivolumab) after failure with temozolomide

INTRODUCTION Pituitary carcinoma (PC) accounts for just 0.1% of all pituitary tumors, often recurs following resection, and has a median reported survival of 1 year. Current treatment guidelines are not standardized but combine surgical resection, radiation therapy, and chemotherapy [1]. Temozolomide is the only chemotherapeutic with documented effectiveness, and the only recommended agent for aggressive pituitary carcinomas in ESE clinical guidelines [3]. CASE: A 57-year-old male presented with visual deterioration over a three-month period. Ophthalmologic evaluation revealed bitemporal visual field deficits. MRI brain W/WO demonstrated a sellar mass suspected to be pituitary macroadenoma with displacement of the stalk and optic nerve impingement (Figure 1a). The patient underwent stereotactic endoscopic transsphenoidal resection of the mass [2]. Postoperative MRI demonstrated gross total …

Authors

Sanjit Shah,Saima Manzoor,Yehudit Rothman,Matthew Hagen,Luke Prater,Karl Golnik,Abdelkader Mahammedi,Andrew Lin,Ruchi Bhabhra,Jonathan Forbes,Soma Sengupta

Journal

Neuro-Oncology

Published Date

2021/11/2

Reuse of molecules for glioblastoma therapy

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor. The current standard of care for GBM is the Stupp protocol which includes surgical resection, followed by radiotherapy concomitant with the DNA alkylator temozolomide; however, survival under this treatment regimen is an abysmal 12–18 months. New and emerging treatments include the application of a physical device, non-invasive ‘tumor treating fields’ (TTFs), including its concomitant use with standard of care; and varied vaccines and immunotherapeutics being trialed. Some of these approaches have extended life by a few months over standard of care, but in some cases are only available for a minority of GBM patients. Extensive activity is also underway to repurpose and reposition therapeutics for GBM, either alone or in combination with the standard of care. In this review, we present select molecules that target different pathways and are at various stages of clinical translation as case studies to illustrate the rationale for their repurposing-repositioning and potential clinical use.

Authors

Abigail Koehler,Aniruddha Karve,Pankaj Desai,Jack Arbiser,David R Plas,Xiaoyang Qi,Renee D Read,Atsuo T Sasaki,Vaibhavkumar S Gawali,Donatien K Toukam,Debanjan Bhattacharya,Laura Kallay,Daniel A Pomeranz Krummel,Soma Sengupta

Published Date

2021/1/28

INNV-42. ACTIVE VS RECEPTIVE MUSIC LISTENING THERAPY IN BREAST CANCER PATIENTS USING ARMCAN

Secondary brain tumors and neurocognitive damage from radiation or chemotherapy are often the commonest neuro-oncological problems in cancer. Breast cancer is the most commonly diagnosed cancer in women, with approximately 2 million women diagnosed in 2018.1 The 10-year survival rate for women diagnosed with breast cancer is 78%(World Cancer Research Fund, 2018). Although the 10-year survival rate is high, women who undergo chemotherapy can experience neurocognitive impairment resulting in significant effects of their cognitive functioning. 2 Chemo related dysfunction is known as “chemobrain” or “chemofog.” Chemobrain can result in difficulty with attention, daily activities of living, and memory. This impacts people’s livelihoods and affects their general well-being. Current research on the topic of chemobrain in breast cancer survivors is minimal. However, this study aims to reduce the post …

Authors

Soma Sengupta,Claudia Rebola,Rhonna Shatz,Abigail Koehler,Yehudit Rothman,Abdelkader Mahammedi,Michelle Kirschner

Journal

Neuro-Oncology

Published Date

2021/11

Neurofibromatosis type 2 (NF2) and the implications for vestibular schwannoma and meningioma pathogenesis

Patients diagnosed with neurofibromatosis type 2 (NF2) are extremely likely to develop meningiomas, in addition to vestibular schwannomas. Meningiomas are a common primary brain tumor; many NF2 patients suffer from multiple meningiomas. In NF2, patients have mutations in the NF2 gene, specifically with loss of function in a tumor-suppressor protein that has a number of synonymous names, including: Merlin, Neurofibromin 2, and schwannomin. Merlin is a 70 kDa protein that has 10 different isoforms. The Hippo Tumor Suppressor pathway is regulated upstream by Merlin. This pathway is critical in regulating cell proliferation and apoptosis, characteristics that are important for tumor progression. Mutations of the NF2 gene are strongly associated with NF2 diagnosis, leading to benign proliferative conditions such as vestibular schwannomas and meningiomas. Unfortunately, even though these tumors are benign, they are associated with significant morbidity and the potential for early mortality. In this review, we aim to encompass meningiomas and vestibular schwannomas as they pertain to NF2 by assessing molecular genetics, common tumor types, and tumor pathogenesis.

Authors

Suha Bachir,Sanjit Shah,Scott Shapiro,Abigail Koehler,Abdelkader Mahammedi,Ravi N Samy,Mario Zuccarello,Elizabeth Schorry,Soma Sengupta

Published Date

2021/1/12

Complications in COVID-19 patients: Characteristics of pulmonary embolism

ObjectiveThe purpose of this study is to evaluate chest CT imaging features, clinical characteristics, laboratory values of COVID-19 patients who underwent CTA for suspected pulmonary embolism. We also examined whether clinical, laboratory or radiological characteristics could be associated with a higher rate of PE.Materials and methodsThis retrospective study included 84 consecutive patients with laboratory-confirmed SARS-CoV-2 who underwent CTA for suspected PE. The presence and localization of PE as well as the type and extent of pulmonary opacities on chest CT exams were examined and correlated with the information on comorbidities and laboratory values for all patients.ResultsOf the 84 patients, pulmonary embolism was discovered in 24 patients. We observed that 87% of PE was found to be in lung parenchyma affected by COVID-19 pneumonia. Compared with no-PE patients, PE patients …

Authors

Riccardo Cau,Alberto Pacielli,Homayounieh Fatemeh,Paolo Vaudano,Chiara Arru,Paola Crivelli,Giuseppe Stranieri,Jasjit S Suri,Lorenzo Mannelli,Maurizio Conti,Abdelkader Mahammedi,Mannudeep Kalra,Luca Saba

Journal

Clinical Imaging

Published Date

2021/9/1

Progressive myelopathy in myelin oligodendrocyte glycoprotein antibody-associated disease: A new mimicker of progressive multiple sclerosis?

Background MOG-IgG-associated disease (MOGAD) in adults typically presents as a monophasic or relapsing optic, spinal, or opticospinal neuroinflammatory syndrome. Current recommendations discourage testing for MOG-IgG in patients with clinical or paraclinical findings more typical of MS, or in patients with a progressive clinical course. However, this approach may impede identification of the full phenotypic spectrum of this recently described disorder.Methods We retrospectively reviewed charts of 39 MOG-IgG-seropositive patients from two Ohio-based neuroimmunology centers to identify unusual disease patterns. Those with a progressive course were included in this case series.Results We describe five cases of progressive myelopathy associated with MOG-IgG. Most patients had features suggestive of MS, including typical MRI and cerebrospinal fluid findings. However, MOG-IgG positive patients with …

Authors

Samuel B Marcucci,Mohamed Elkasaby,Rosemarie Walch,Ameneh Zare-Shahabadi,Abdelkader Mahammedi,Hesham Abboud,Aram Zabeti

Journal

Multiple Sclerosis and Related Disorders

Published Date

2021/7/1

Imaging of neurologic disease in hospitalized patients with COVID-19: an Italian multicenter retrospective observational study

Of 725 consecutive hospitalized patients with coronavirus disease 2019, 108 (15%) had acute neurologic symptoms necessitating neurologic imaging.

Authors

Abdelkader Mahammedi,Luca Saba,Achala Vagal,Michela Leali,Andrea Rossi,Mary Gaskill,Soma Sengupta,Bin Zhang,Alessandro Carriero,Suha Bachir,Paola Crivelli,Alessio Paschè,Enrico Premi,Alessandro Padovani,Roberto Gasparotti

Journal

Radiology

Published Date

2020/11

Neurological manifestations and neuroimaging features of COVID-19 patients: a multicenter italian experience

Methods: In this retrospective, multicenter study from Italy, we reviewed the electronic medical records and imaging of hospitalized COVID-19 patients from February 29, 2020 to April 4, 2020. Our inclusion criteria included patients with acute neurological manifestations requiring brain imaging.Findings: A total of 725 COVID-19 patients were reviewed. Out of these, 108 (14.9%) fit our inclusion criteria. The commonest neurological manifestations were altered mental status 64 (59.3%), acute cerebrovascular disease 34 (31.5%), headache 13 (12.0%) and epilepsy 10 (9.2%). The neuroimaging hallmark of these patients were acute ischemic 34 (31.5%) and hemorrhagic cerebrovascular disease 6 (5.6%). Additional neuroimaging findings included acute toxic encephalopathy, posterior reversible encephalopathy syndrome (PRES), hypoxic-ischemic encephalopathy (HIE), cerebral venous thrombosis, cranial and caudal nerve enhancement, exacerbation of demyelinating disease and nonspecific encephalitis. There was a statistical significant difference (P< 0.006) between the prevalence of altered mental status and age of patient.Interpretation: Neurological complications with associated abnormal neuroimaging findings are not uncommon in COVID-19. Neurologists and neuro-radiologists should be aware of the broad-spectrum of neuroimaging and neurologic disease that can be associated with COVID-19.

Authors

Abd Mah,Luca Saba,Achala Vagal,Michela Leali,Andrea Rossi,Mary Gaskill,Soma Sengupta,Bin Zhang,Alessandro Carriero,Suha Bachir,Paola Crivelli,Alessio Paschè,Enrico Premi,Alessandro Padovani,Roberto Gasparotti

Published Date

2020/4/22

Tumor habitat–derived radiomic features at pretreatment MRI that are prognostic for progression-free survival in glioblastoma are associated with key morphologic attributes at …

Purpose To identify radiomic features extracted from the tumor habitat on routine MR images that are prognostic for progression-free survival (PFS) and to assess their morphologic basis with corresponding histopathologic attributes in glioblastoma (GBM). Materials and Methods In this retrospective study, 156 pretreatment GBM MR images (gadolinium-enhanced T1-weighted, T2-weighted, and fluid-attenuated inversion recovery [FLAIR] images) were curated. Of these 156 images, 122 were used for training (90 from The Cancer Imaging Archive and 32 from the Cleveland Clinic, acquired between December 1, 2011, and May 1, 2018) and 34 were used for validation. The validation set was obtained …

Authors

Ruchika Verma,Ramon Correa,Virginia B Hill,Volodymyr Statsevych,Kaustav Bera,Niha Beig,Abdelkader Mahammedi,Anant Madabhushi,Manmeet Ahluwalia,Pallavi Tiwari

Journal

Radiology: Artificial Intelligence

Published Date

2020/11/11

See List of Professors in Abdelkader Mahammedi M.D University(University of Kentucky)

Abdelkader Mahammedi M.D FAQs

What is Abdelkader Mahammedi M.D's h-index at University of Kentucky?

The h-index of Abdelkader Mahammedi M.D has been 11 since 2020 and 11 in total.

What are Abdelkader Mahammedi M.D's top articles?

The articles with the titles of

Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT

USE-evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists

Abstract TMP69: Random Rater Sampling For Deep Learning Algorithm To Segment Acute Ischemic Stroke On Non-contrast Computed Tomography

Lessons learned from evolving frameworks in adult glioblastoma

Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework

The use of ARMCan app to improve the quality of life in breast cancer patients with chemobrain.

Non-inferiority of Deep Learning Acute Ischemic Stroke Segmentation on Non-Contrast CT Compared to Expert Neuroradiologists

...

are the top articles of Abdelkader Mahammedi M.D at University of Kentucky.

What are Abdelkader Mahammedi M.D's research interests?

The research interests of Abdelkader Mahammedi M.D are: Neuroradiology

What is Abdelkader Mahammedi M.D's total number of citations?

Abdelkader Mahammedi M.D has 677 citations in total.

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