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Stancioiu F, Papadakis GZ, Lazopoulos G, Spandidos DA, Tsatsakis A, Floroiu M, Badiu C. Erratum: [Corrigendum] CD271 + stem cell treatment of patients with chronic stroke: A retrospective case series report. Exp Ther Med 2023; 26:544. [PMID: 37928505 PMCID: PMC10623212 DOI: 10.3892/etm.2023.12243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
[This corrects the article DOI: 10.3892/etm.2020.8948.].
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de Castro LF, Michel Z, Pan K, Taylor J, Szymczuk V, Paravastu S, Saboury B, Papadakis GZ, Li X, Milligan K, Boyce B, Paul SM, Collins MT, Boyce AM. Safety and Efficacy of Denosumab for Fibrous Dysplasia of Bone. N Engl J Med 2023; 388:766-768. [PMID: 36812441 PMCID: PMC10015375 DOI: 10.1056/nejmc2214862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Affiliation(s)
| | | | | | | | | | | | | | | | - Xiaobai Li
- National Institutes of Health, Bethesda, MD
| | | | - Brendan Boyce
- University of Rochester Medical Center, Rochester, NY
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3
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Aschner M, Mesnage R, Docea AO, Paoliello MMB, Tsatsakis A, Giannakakis G, Papadakis GZ, Vinceti SR, Santamaria A, Skalny AV, Tinkov AA. Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity. Neurotoxicology 2021; 89:9-11. [PMID: 34968636 DOI: 10.1016/j.neuro.2021.12.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 12/25/2021] [Indexed: 02/07/2023]
Abstract
Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, such as machine learning (ML) and artificial intelligence (AI) to the discipline. Specifically, we advance the notion that AI and ML will be helpful in identifying neurotoxic signatures, provide reliable data in predicting neurotoxicity in the context of genetic variability, and improve the understanding of neurotoxic outcomes associated with exposures to mixtures, to name a few.
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Affiliation(s)
- Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, United States.
| | - Robin Mesnage
- Gene Expression and Therapy Group, King's College London, Faculty of Life Sciences & Medicine, Department of Medical and Molecular Genetics, Guy's Hospital, London, SE1 9RT, UK
| | - Anca Oana Docea
- Department of Toxicology, University of Medicine and Pharmacy of Craiova, 200349, Craiova, Romania
| | | | - Aristides Tsatsakis
- Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003, Heraklion, Greece; Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991, Moscow, Russia
| | - Georgios Giannakakis
- Hybrid Molecular Imaging Unit (HMIU), Foundation for Research and Technology Hellas (FORTH), Greece
| | - Georgios Z Papadakis
- Hybrid Molecular Imaging Unit (HMIU), Foundation for Research and Technology Hellas (FORTH), Greece
| | - Silvio Roberto Vinceti
- University of Modena and Reggio Emilia: Universita degli Studi di Modena e Reggio Emilia, Italy
| | - Abel Santamaria
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, United States; Gene Expression and Therapy Group, King's College London, Faculty of Life Sciences & Medicine, Department of Medical and Molecular Genetics, Guy's Hospital, London, SE1 9RT, UK; Department of Toxicology, University of Medicine and Pharmacy of Craiova, 200349, Craiova, Romania; Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003, Heraklion, Greece; Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991, Moscow, Russia; Hybrid Molecular Imaging Unit (HMIU), Foundation for Research and Technology Hellas (FORTH), Greece; University of Modena and Reggio Emilia: Universita degli Studi di Modena e Reggio Emilia, Italy; World-Class Research Center "Digital Biodesign and Personalized Healthcare", IM Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia; K.G. Razumovsky Moscow State University of Technologies and Management, Moscow, Russia; IM Sechenov First Moscow State Medical University (Sechenov University), Moscow, 119146, Russia; Yaroslavl State University, Sovetskaya Str. 14, Yaroslavl, 150000, Russia
| | - Anatoly V Skalny
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", IM Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia; K.G. Razumovsky Moscow State University of Technologies and Management, Moscow, Russia
| | - Alexey A Tinkov
- IM Sechenov First Moscow State Medical University (Sechenov University), Moscow, 119146, Russia; Yaroslavl State University, Sovetskaya Str. 14, Yaroslavl, 150000, Russia
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Kontopodis EE, Papadaki E, Trivizakis E, Maris TG, Simos P, Papadakis GZ, Tsatsakis A, Spandidos DA, Karantanas A, Marias K. Emerging deep learning techniques using magnetic resonance imaging data applied in multiple sclerosis and clinical isolated syndrome patients (Review). Exp Ther Med 2021; 22:1149. [PMID: 34504594 PMCID: PMC8393268 DOI: 10.3892/etm.2021.10583] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/29/2021] [Indexed: 12/18/2022] Open
Abstract
Computer-aided diagnosis systems aim to assist clinicians in the early identification of abnormal signs in order to optimize the interpretation of medical images and increase diagnostic precision. Multiple sclerosis (MS) and clinically isolated syndrome (CIS) are chronic inflammatory, demyelinating diseases affecting the central nervous system. Recent advances in deep learning (DL) techniques have led to novel computational paradigms in MS and CIS imaging designed for automatic segmentation and detection of areas of interest and automatic classification of anatomic structures, as well as optimization of neuroimaging protocols. To this end, there are several publications presenting artificial intelligence-based predictive models aiming to increase diagnostic accuracy and to facilitate optimal clinical management in patients diagnosed with MS and/or CIS. The current study presents a thorough review covering DL techniques that have been applied in MS and CIS during recent years, shedding light on their current advances and limitations.
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Affiliation(s)
- Eleftherios E Kontopodis
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Efrosini Papadaki
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Eleftherios Trivizakis
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Thomas G Maris
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Panagiotis Simos
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Psychiatry and Behavioral Sciences, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Georgios Z Papadakis
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Aristidis Tsatsakis
- Centre of Toxicology Science and Research, Faculty of Medicine, University of Crete, 71003 Heraklion, Greece
| | - Demetrios A Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Apostolos Karantanas
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Kostas Marias
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece.,Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece
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Shekhar S, Irizarry-Caro JA, Sinaii N, Gahl W, Estrada-Veras JI, Dave R, Papadakis GZ, Patronas N, Stratakis CA, O’Brien K, Hannah-Shmouni F. Abnormal Pituitary Imaging and Associated Endocrine Dysfunctions in Erdheim-Chester Disease. J Endocr Soc 2021. [PMCID: PMC8090311 DOI: 10.1210/jendso/bvab048.1268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Abstract
Background: Erdheim Chester disease (ECD) is a rare histiocytic neoplasm associated with hypothalamic and pituitary infiltration and dysfunction. We determined the abnormal pituitary imaging (API) phenotypes in subjects with ECD and analyzed their associated endocrine dysfunctions. Methods: This was a cross-sectional examination of a natural history cohort study of 61 subjects with ECD performed at a tertiary care clinical research center. The diagnosis of ECD was based on clinical, molecular, and histopathological features. Enrolled subjects underwent baseline endocrine tests of anterior and posterior pituitary function in addition to pituitary imaging. The following variables were analyzed- age, sex, body mass index (BMI), BRAF V600E, hsCRP, ESR, pituitary hormone deficit number, diabetes insipidus (DI), and panhypopituitarism. Fisher’s exact test or t-test/Wilcoxon tests compared patients with and without API. Results: Sixty-one subjects with ECD (age ±SD: 54.3 ±10.9, 46 (75.4%) males) were studied. The prevalence of API was 32.8% (n=20), who were younger than those with normal imaging (50.3 ±10.5 vs 56.3 ±10.7 yrs, p=0.042). The most common pituitary imaging abnormalities included thickened pituitary stalk (18.03%, n=11/61), followed by pituitary encasement, small pituitary and abnormal morphology (6.55%, n= 4/61 for each). A higher prevalence of DI (45.0% vs 9.8%, p=0.003) and panhypopituitarism (45.0% vs 4.9%, p<0.001), and a higher number of pituitary deficits (median (IQR): 2.0 (0-2.5) vs 0 (0-1.0), p=0.007) were noted in patients with API compared to those with normal imaging. Other biochemical markers were similar between both groups. Conclusion: Abnormal pituitary imaging was commonly seen in ECD and was also associated with a younger age and hormone deficits suggesting associations with pituitary structure-function.
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Affiliation(s)
- Skand Shekhar
- NICHD and NIEHS, National Institutes of Health, Bethesda, MD, USA
| | | | - Ninet Sinaii
- Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - William Gahl
- NHGRI, National Institutes of Health, Bethesda, MD, USA
| | | | - Rahul Dave
- NHGRI, National Institutes of Health and Inova Fairfax VCU College of Medicine, Fairfax, VA, USA
| | | | - Nicholas Patronas
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), Heraklion, Greece
- Department of Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | | | - Kevin O’Brien
- NHGRI, National Institutes of Health, Bethesda, MD, USA
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6
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Klontzas ME, Kakkos GA, Papadakis GZ, Marias K, Karantanas AH. Advanced clinical imaging for the evaluation of stem cell based therapies. Expert Opin Biol Ther 2021; 21:1253-1264. [PMID: 33576278 DOI: 10.1080/14712598.2021.1890711] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Introduction: As stem cell treatments reach closer to the clinic, the need for appropriate noninvasive imaging for accurate disease diagnosis, treatment planning, follow-up, and early detection of complications, is constantly rising. Clinical radiology affords an extensive arsenal of advanced imaging techniques, to provide anatomical and functional information on the whole spectrum of stem cell treatments from diagnosis to follow-up.Areas covered: This manuscript aims at providing a critical review of major published studies on the utilization of advanced imaging for stem cell treatments. Uses of magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and positron emission tomography (PET) are reviewed and interrogated for their applicability to stem cell imaging.Expert opinion: A wide spectrum of imaging methods have been utilized for the evaluation of stem cell therapies. The majority of published techniques are not clinically applicable, using methods exclusively applicable to animals or technology irrelevant to current clinical practice. Harmonization of preclinical methods with clinical reality is necessary for the timely translation of stem cell therapies to the clinic. Methods such as diffusion weighted MRI, hybrid imaging, and contrast-enhanced ultrasound hold great promise and should be routinely incorporated in the evaluation of patients receiving stem cell treatments.
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Affiliation(s)
- Michail E Klontzas
- Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece
| | - George A Kakkos
- Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece
| | - Georgios Z Papadakis
- Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece.,Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), Heraklion, Crete, Greece.,Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), Heraklion, Crete, Greece.,Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Crete, Greece
| | - Apostolos H Karantanas
- Department of Medical Imaging, University Hospital of Heraklion, Crete, Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece.,Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), Heraklion, Crete, Greece.,Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
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7
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Hurley-Novatny A, Karantanas AH, Papadakis GZ, Bhattacharyya T, Jha S. Cross-Sectional Imaging Useful in Melorheostosis. JBMR Plus 2021; 5:e10472. [PMID: 33869990 PMCID: PMC8046147 DOI: 10.1002/jbm4.10472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 01/16/2021] [Accepted: 01/27/2021] [Indexed: 11/08/2022] Open
Abstract
Melorheostosis is a rare disease of bone overgrowth that is primarily diagnosed based on imaging studies. Recently, the association of different radiological patterns of the disease with distinct genetic cause was reported. Several case reports have described the radiological findings in patients with melorheostosis. However, the added value of cross‐sectional imaging with CT and MRI beyond X‐rays has not been investigated. The aim of the current study was to investigate this existing gap in knowledge. Forty patients with melorheostosis seen at the National Institute of Health Clinical Center were included in the study, and all their imaging studies were analyzed. The sequence of interpretation was X‐ray followed by CT and then MRI. CT images were extracted from whole‐body 18F‐sodium fluoride positron emission tomography/CT studies. The information from CT reclassified the initial X‐rays based radiological pattern in 13 patients. Additionally, CT comprehensively identified joint involvement and disease extent. In 76% of patients (n = 29) who underwent MRI, additional findings were noted, ranging from soft tissue edema to identification of soft tissue masses and incidental findings. MRI did not provide additional information on skeletal lesions beyond CT scans. However, it revealed the extension of soft tissue ossification into ischiofemoral space in four patients who complained of deep gluteal pain consistent with ischiofemoral impingement syndrome. In addition, MRI revealed soft tissue edema in 20 patients, 9 of whom had bone marrow edema and periosteal edema in the tibias consistent with shin splints. These findings suggest that select patients with melorheostosis should be evaluated with both CT and MRI, particularly patients in whom the distribution of pain does not correlate with the anatomic location of the disease in plain radiographs. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Amelia Hurley-Novatny
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health Bethesda Maryland USA.,Medical Scientist Training Program, Carver College of Medicine University of Iowa Iowa City Iowa USA
| | - Apostolos H Karantanas
- Department of Medical Imaging University Hospital, School of Medicine, University of Crete Heraklion Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science (ICS) Foundation for Research and Technology Hellas (FORTH) Heraklion Greece
| | - Georgios Z Papadakis
- Department of Medical Imaging University Hospital, School of Medicine, University of Crete Heraklion Greece.,Advanced Hybrid Imaging Systems, Institute of Computer Science (ICS) Foundation for Research and Technology Hellas (FORTH) Heraklion Greece
| | - Timothy Bhattacharyya
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health Bethesda Maryland USA
| | - Smita Jha
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health Bethesda Maryland USA.,Metabolic Diseases Branch National Institutes of Diabetes and Digestive and Kidney Diseases Bethesda Maryland USA
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8
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Wurth R, Tirosh A, Kamilaris CDC, Camacho J, Faucz FR, Maria AG, Berthon A, Papadakis GZ, Nilubol N, Hamimi A, Gharib AM, Demidowich A, Zilbermint M, Eisenhofer G, Braun L, Reincke M, Stratakis CA, Hannah-Shmouni F. Volumetric Modeling of Adrenal Gland Size in Primary Bilateral Macronodular Adrenocortical Hyperplasia. J Endocr Soc 2021; 5:bvaa162. [PMID: 33305158 PMCID: PMC7716656 DOI: 10.1210/jendso/bvaa162] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Indexed: 11/19/2022] Open
Abstract
CONTEXT Radiological characterization of adrenal size in primary bilateral macronodular adrenocortical hyperplasia (PBMAH) has not been previously investigated. OBJECTIVE We hypothesized that volumetric modeling of adrenal gland size may correlate with biochemical disease severity in patients with PBMAH. Secondary analysis of patients with concurrent primary aldosteronism (PA) was performed. DESIGN A retrospective cross-sectional analysis of 44 patients with PBMAH was conducted from 2000 to 2019. SETTING Tertiary care clinical research center. PATIENTS Patients were diagnosed with PBMAH based upon clinical, genetic, radiographic and biochemical characteristics. INTERVENTION Clinical, biochemical, and genetic data were obtained. Computed tomography scans were used to create volumetric models by manually contouring both adrenal glands in each slice using Vitrea Core Fx v6.3 software (Vital Images, Minnetonka, Minnesota). MAIN OUTCOME AND MEASURES 17-hydroxycorticosteroids (17-OHS), ARMC5 genetics, and aldosterone-to-renin ratio (ARR) were retrospectively obtained. Pearson test was used for correlation analysis of biochemical data with adrenal volume. RESULTS A cohort of 44 patients with PBMAH was evaluated, with a mean age (±SD) of 53 ± 11.53. Eight patients met the diagnostic criteria for PA, of whom 6 (75%) were Black. In the Black cohort, total adrenal volumes positively correlated with midnight cortisol (R = 0.76, P = 0.028), urinary free cortisol (R = 0.70, P = 0.035), and 17-OHS (R = 0.87, P = 0.0045), with a more pronounced correlation with left adrenal volume alone. 17-OHS concentration positively correlated with total, left, and right adrenal volume in patients harboring pathogenic variants in ARMC5 (R = 0.72, P = 0.018; R = 0.65, P = 0.042; and R = 0.73, P = 0.016, respectively). CONCLUSIONS Volumetric modeling of adrenal gland size may associate with biochemical severity in patients with PBMAH, with particular utility in Black patients.
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Affiliation(s)
- Rachel Wurth
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Amit Tirosh
- Neuroendocrine Tumors Service, Division of Endocrinology, Diabetes and Metabolism, The Chaim Sheba Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Crystal D C Kamilaris
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Jancarlos Camacho
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Fabio R Faucz
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Andrea Gutierrez Maria
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Annabel Berthon
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Georgios Z Papadakis
- Foundation for Research and Technology (FORTH), Institute of Computer Science (ICS), Computational Biomedicine Laboratory, Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, Heraklion, Greece
| | - Naris Nilubol
- Surgical Oncology Program, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Ahmed Hamimi
- Biomedical and Metabolic Imaging Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Ahmed M Gharib
- Biomedical and Metabolic Imaging Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Andrew Demidowich
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Mihail Zilbermint
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
- Johns Hopkins University School of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Baltimore, MD, USA
- Johns Hopkins Community Physicians at Suburban Hospital, Bethesda, MD, USA
| | - Graeme Eisenhofer
- Institute of Clinical Chemistry and Laboratory Medicine, and Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität, Dresden, Germany
| | - Leah Braun
- Medizinische Klinik und Poliklinik IV, Division of Endocrinology, Klinikum der Universität, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Martin Reincke
- Medizinische Klinik und Poliklinik IV, Division of Endocrinology, Klinikum der Universität, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Constantine A Stratakis
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Fady Hannah-Shmouni
- Section on Endocrinology & Genetics (SEGEN), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
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9
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Kontopodis E, Marias K, Manikis GC, Nikiforaki K, Venianaki M, Maris TG, Mastorodemos V, Papadakis GZ, Papadaki E. Extended perfusion protocol for MS lesion quantification. Open Med (Wars) 2020; 15:520-530. [PMID: 33336007 PMCID: PMC7711864 DOI: 10.1515/med-2020-0100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 03/09/2020] [Accepted: 03/13/2020] [Indexed: 11/15/2022] Open
Abstract
This study aims to examine a time-extended dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocol and report a comparative study with three different pharmacokinetic (PK) models, for accurate determination of subtle blood-brain barrier (BBB) disruption in patients with multiple sclerosis (MS). This time-extended DCE-MRI perfusion protocol, called Snaps, was applied on 24 active demyelinating lesions of 12 MS patients. Statistical analysis was performed for both protocols through three different PK models. The Snaps protocol achieved triple the window time of perfusion observation by extending the magnetic resonance acquisition time by less than 2 min on average for all patients. In addition, the statistical analysis in terms of adj-R 2 goodness of fit demonstrated that the Snaps protocol outperformed the conventional DCE-MRI protocol by detecting 49% more pixels on average. The exclusive pixels identified from the Snaps protocol lie in the low k trans range, potentially reflecting areas with subtle BBB disruption. Finally, the extended Tofts model was found to have the highest fitting accuracy for both analyzed protocols. The previously proposed time-extended DCE protocol, called Snaps, provides additional temporal perfusion information at the expense of a minimal extension of the conventional DCE acquisition time.
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Affiliation(s)
- Eleftherios Kontopodis
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Kostas Marias
- Technological Educational Institute of Crete, Department of Informatics Engineering, Heraklion , Crete, Estavromenos, TK 71410, Greece
| | - Georgios C Manikis
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Katerina Nikiforaki
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Maria Venianaki
- Science and Technology Park of Crete, Gnosis Data Analysis, N. Plastira 100, Vassilika Vouton, GR-700 13, Heraklion, Greece
| | - Thomas G Maris
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Georgios Z Papadakis
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
| | - Efrosini Papadaki
- Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational Bio-Medicine Laboratory, N. Plastira 100, Vassilika Vouton, GR-700 13 Heraklion, Crete, Greece.,Department of Radiology, Medical School, University of Crete, P. O. Box 2208, Heraklion, Crete, Greece
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10
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Klontzas ME, Papadakis GZ, Marias K, Karantanas AH. Musculoskeletal trauma imaging in the era of novel molecular methods and artificial intelligence. Injury 2020; 51:2748-2756. [PMID: 32972725 DOI: 10.1016/j.injury.2020.09.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/14/2020] [Accepted: 09/15/2020] [Indexed: 02/08/2023]
Abstract
Over the past decade rapid advancements in molecular imaging (MI) and artificial intelligence (AI) have revolutionized traditional musculoskeletal radiology. Molecular imaging refers to the ability of various methods to in vivo characterize and quantify biological processes, at a molecular level. The extracted information provides the tools to understand the pathophysiology of diseases and thus to early detect, to accurately evaluate the extend and to apply and evaluate targeted treatments. At present, molecular imaging mainly involves CT, MRI, radionuclide, US, and optical imaging and has been reported in many clinical and preclinical studies. Although originally MI techniques targeted at central nervous system disorders, later on their value on musculoskeletal disorders was also studied in depth. Meaningful exploitation of the large volume of imaging data generated by molecular and conventional imaging techniques, requires state-of-the-art computational methods that enable rapid handling of large volumes of information. AI allows end-to-end training of computer algorithms to perform tasks encountered in everyday clinical practice including diagnosis, disease severity classification and image optimization. Notably, the development of deep learning algorithms has offered novel methods that enable intelligent processing of large imaging datasets in an attempt to automate decision-making in a wide variety of settings related to musculoskeletal trauma. Current applications of AI include the diagnosis of bone and soft tissue injuries, monitoring of the healing process and prediction of injuries in the professional sports setting. This review presents the current applications of novel MI techniques and methods and the emerging role of AI regarding the diagnosis and evaluation of musculoskeletal trauma.
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Affiliation(s)
- Michail E Klontzas
- Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece.
| | - Georgios Z Papadakis
- Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece; Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Radiology, School of Medicine, University of Crete, 70110 Greece.
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410, Heraklion, Crete, Greece.
| | - Apostolos H Karantanas
- Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece; Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013, Heraklion, Crete, Greece; Department of Radiology, School of Medicine, University of Crete, 70110 Greece.
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11
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Trivizakis E, Tsiknakis N, Vassalou EE, Papadakis GZ, Spandidos DA, Sarigiannis D, Tsatsakis A, Papanikolaou N, Karantanas AH, Marias K. Advancing COVID-19 differentiation with a robust preprocessing and integration of multi-institutional open-repository computer tomography datasets for deep learning analysis. Exp Ther Med 2020; 20:78. [PMID: 32968435 PMCID: PMC7500043 DOI: 10.3892/etm.2020.9210] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 09/11/2020] [Indexed: 12/15/2022] Open
Abstract
The coronavirus pandemic and its unprecedented consequences globally has spurred the interest of the artificial intelligence research community. A plethora of published studies have investigated the role of imaging such as chest X-rays and computer tomography in coronavirus disease 2019 (COVID-19) automated diagnosis. Οpen repositories of medical imaging data can play a significant role by promoting cooperation among institutes in a world-wide scale. However, they may induce limitations related to variable data quality and intrinsic differences due to the wide variety of scanner vendors and imaging parameters. In this study, a state-of-the-art custom U-Net model is presented with a dice similarity coefficient performance of 99.6% along with a transfer learning VGG-19 based model for COVID-19 versus pneumonia differentiation exhibiting an area under curve of 96.1%. The above was significantly improved over the baseline model trained with no segmentation in selected tomographic slices of the same dataset. The presented study highlights the importance of a robust preprocessing protocol for image analysis within a heterogeneous imaging dataset and assesses the potential diagnostic value of the presented COVID-19 model by comparing its performance to the state of the art.
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Affiliation(s)
- Eleftherios Trivizakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Nikos Tsiknakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Evangelia E. Vassalou
- Department of Medical Imaging, University Hospital of Heraklion, 71110 Heraklion, Greece
- Department of Radiology, Sitia District Hospital, 72300 Lasithi, Greece
| | - Georgios Z. Papadakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Demetrios A. Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Dimosthenis Sarigiannis
- HERACLES Research Center on the Exposome and Health, Centre for Interdisciplinary Research and Innovation, Aristotle University of Thessaloniki, 57001 Thermi, Greece
- University School for Advanced Studies IUSS, I-27100 Pavia, Italy
| | - Aristidis Tsatsakis
- Department of Forensic Sciences and Toxicology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Nikolaos Papanikolaou
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Computational Clinical Imaging Group, Centre for the Unknown, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Apostolos H. Karantanas
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
- Department of Medical Imaging, University Hospital of Heraklion, 71110 Heraklion, Greece
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece
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12
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Hartley IR, Miller CB, Papadakis GZ, Bergwitz C, Del Rivero J, Blau JE, Florenzano P, Berglund JA, Tassone J, Roszko KL, Moran S, Gafni RI, Isaacs R, Collins MT. Targeted FGFR Blockade for the Treatment of Tumor-Induced Osteomalacia. N Engl J Med 2020; 383:1387-1389. [PMID: 32905668 PMCID: PMC7561341 DOI: 10.1056/nejmc2020399] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Iris R Hartley
- National Institute of Dental and Craniofacial Research, Bethesda, MD
| | | | | | | | | | - Jenny E Blau
- National Institute of Diabetes and Digestive and Kidney Disease, Bethesda, MD
| | | | - Jason A Berglund
- University of Texas Health Science Center at Houston, Houston, TX
| | | | - Kelly L Roszko
- National Institute of Dental and Craniofacial Research, Bethesda, MD
| | | | - Rachel I Gafni
- National Institute of Dental and Craniofacial Research, Bethesda, MD
| | - Randi Isaacs
- Novartis Institutes of Biomedical Research, East Hanover, NJ
| | - Michael T Collins
- National Institute of Dental and Craniofacial Research, Bethesda, MD
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13
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Shekhar S, Sinaii N, Irizarry-Caro JA, Gahl WA, Estrada-Veras JI, Dave R, Papadakis GZ, Tirosh A, Abel BS, Klubo-Gwiezdzinska J, Skarulis MC, Gochuico BR, O’Brien K, Hannah-Shmouni F. Prevalence of Hypothyroidism in Patients With Erdheim-Chester Disease. JAMA Netw Open 2020; 3:e2019169. [PMID: 33119105 PMCID: PMC7596581 DOI: 10.1001/jamanetworkopen.2020.19169] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
IMPORTANCE Erdheim-Chester disease (ECD) is a rare non-Langerhans cell histiocytosis affecting multiple organs and commonly caused by somatic pathogenic variants in BRAF V600E and mitogen-activated protein kinase genes. Clinical features of ECD result from histiocytic involvement of various tissues; while endocrine involvement in ECD occurs frequently, the prevalence of central or primary hypothyroidism has not been thoroughly investigated. OBJECTIVE To assess hypothalamus-pituitary-thyroid (HPT) dysfunction in patients with ECD. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 61 patients with ECD who were enrolled in a natural history study at a tertiary care center between January 2011 and December 2018. ECD was diagnosed on the basis of clinical, genetic, and histopathological features. Data were analyzed in March 2020. EXPOSURE Diagnosis of ECD. MAIN OUTCOMES AND MEASURES Main outcome was the prevalence of thyroid dysfunction in adults with ECD compared with community estimates. Patients underwent baseline evaluation with a thyroid function test, including thyrotropin, free thyroxine (fT4), and total thyroxine (T4), and sellar imaging with magnetic resonance imaging or computed tomography scan. The association of HPT dysfunction was assessed for differences in age, sex, body mass index, BRAF V600E status, high sensitivity C-reactive protein level, sellar imaging, and pituitary hormonal dysfunction. RESULTS A total of 61 patients with ECD (46 [75%] men; mean [SD] age, 54.3 [10.9] years) were evaluated. Seventeen patients (28%) had hypothyroidism requiring levothyroxine therapy. The prevalence of both central and primary hypothyroidism were higher than community estimates (central hypothyroidism: 9.8% vs 0.1%; odds ratio, 109.0; 95% CI, 37.4-260.6; P < .001; primary hypothyroidism: 18.0% vs 4.7%; OR, 4.4; 95% CI, 2.1-8.7; P < .001). Patients with hypothyroidism (both primary and central), compared with patients with euthyroidism, had higher body mass index (median [interquartile range] 31.4 [28.3-38.3] vs 26.7 [24.4-31.9]; P = .004) and a higher prevalence of panhypopituitarism (7 [47%] vs 3 [7%]; P < .001). Among patients with hypothyroidism, those with central hypothyroidism, compared with patients with primary hypothyroidism, had a lower mean (SD) body mass index (28.3 [2.6] vs 36.3 [5.9]; P = .007) and higher frequencies of abnormal sellar imaging (5 [83%] vs 3 [27%]; P = .050) and panhypopituitarism (5 [83%] vs 3 [27%]; P = .050). CONCLUSIONS AND RELEVANCE In this cohort study, a higher prevalence of central and primary hypothyroidism was identified in patients with ECD compared with the community. There should be a low threshold for testing for hypothyroidism in patients with ECD, and treatment should follow standard guidelines.
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Affiliation(s)
- Skand Shekhar
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Ninet Sinaii
- Clinical Center, National Institutes of Health, Bethesda, Maryland
| | - Jorge A. Irizarry-Caro
- Universidad Central del Caribe School of Medicine, Bayamón, Puerto Rico
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - William A Gahl
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | | | - Rahul Dave
- Inova Fairfax-Virginia Commonwealth University College of Medicine, Falls Church
| | - Georgios Z. Papadakis
- Department of Radiology, Medical School, University of Crete, Heraklion, Greece
- Foundation for Research and Technology Hellas, Computational Biomedicine Laboratory, Heraklion, Greece
| | - Amit Tirosh
- Neuroendocrine Tumor Service, Sheba Medical Center, and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Brent S. Abel
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Joanna Klubo-Gwiezdzinska
- Thyroid Tumors and Functional Thyroid Disorders Section, Metabolic Disease Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland
| | - Monica C. Skarulis
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Bernadette R. Gochuico
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Kevin O’Brien
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Fady Hannah-Shmouni
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
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14
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Stancioiu F, Papadakis GZ, Lazopoulos G, Spandidos DA, Tsatsakis A, Floroiu M, Badiu C. CD271 + stem cell treatment of patients with chronic stroke: : A retrospective case series report. Exp Ther Med 2020; 20:2055-2062. [PMID: 32782517 PMCID: PMC7401309 DOI: 10.3892/etm.2020.8948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 06/25/2020] [Indexed: 12/12/2022] Open
Abstract
Patients with chronic stroke have currently little hope for motor improvement towards regaining independent activities of daily living; stem cell treatments offer a new treatment option and needs to be developed. Patients with chronic stroke (more than 3 months prior to stem cell treatment, mean 21.2 months post-stroke) were treated with CD271+ stem cells, 7 patients received autologous and 1 allogeneic cells from first degree relative; administration was intravenous in 1 and intrathecal in 7 patients. Each patient received a single treatment consisting of 2-5x106 cells/kg and they were followed up for up to 12 months. There were significant improvements in expressive aphasia (2/3 patients) spasticity (5/5, of which 2 were transient), and small improvements in motor function (2/8 patients). Although motor improvements were minor in our chronic stroke patients, improvements in aphasia and spasticity were significant and in the context of good safety we are advocating further administration and clinical studies of CD271+ stem cells not only in chronic stroke patients, but also for spastic paresis/plegia; a different, yet unexplored application is pulmonary emphysema.
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Affiliation(s)
| | - Georgios Z. Papadakis
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - George Lazopoulos
- Department of Cardiothoracic Surgery, University General Hospital of Heraklion, 71003 Heraklion, Greece
| | - Demetrios A. Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Aristidis Tsatsakis
- Laboratory of Toxicology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Marius Floroiu
- Cardiovascular Surgery Department, Angiomedica Hospital, 020657 Bucharest, Romania
| | - Corin Badiu
- CI Parhon Institute of Endocrinology, 011863 Bucharest, Romania
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15
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Tu TW, Kovacs ZI, Sundby M, Witko JA, Papadakis GZ, Reid WC, Hammoud DA, Frank JA. Diffusion Tensor Imaging and Chemical Exchange Saturation Transfer MRI Evaluation on the Long-Term Effects of Pulsed Focused Ultrasound and Microbubbles Blood Brain Barrier Opening in the Rat. Front Neurosci 2020; 14:908. [PMID: 32982680 PMCID: PMC7478124 DOI: 10.3389/fnins.2020.00908] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 08/05/2020] [Indexed: 11/16/2022] Open
Abstract
Blood-brain barrier opening (BBBO) with pulsed Focused Ultrasound (pFUS) and microbubbles (MB) has received increasing interest as a method for neurotherapeutics of the central nervous system. In general, conventional MRI [i.e., T2w, T2∗w, gadolinium (Gd) enhanced T1w] is used to monitor the effects of pFUS+MB on BBBO and/or assess whether sonication results in parenchymal damage. This study employed multimodal MRI techniques and 18F-Fludeoxyglucose (FDG) PET to evaluate the effects of single and multiple weekly pFUS+MB sessions on morphology and glucose utilization levels in the rat cortex and hippocampus. pFUS was performed with 0.548 MHz transducer with a slow infusion over 1 min of OptisonTM (5–8 × 107 MB) in nine focal points in cortex and four in hippocampus. During pFUS+MB treatment, Gd-T1w was performed at 3 T to confirm BBBO, along with subsequent T2w, T2∗w, DTI and glucose CEST (glucoCEST)-weighted imaging by high field 9.4 T and compared with FDG-PET and immunohistochemistry. Animals receiving a single pFUS+MB exhibited minimal hypointense voxels on T2∗w. Brains receiving multiple pFUS+MB treatments demonstrated persistent T2w and T2∗ abnormalities associated with changes in DTI and glucoCEST when compared to contralateral parenchyma. Decreased glucoCEST contrast was substantiated by FDG-PET in cortex following multiple sonications. Immunohistochemistry showed significantly dilated vessels and decreased neuronal glucose transporter (GLUT3) expression in sonicated cortex and hippocampus without changes in neuronal counts. These results suggest the importance to standardize MRI protocols in concert with advanced imaging techniques when evaluating long term effects of pFUS+MB BBBO in clinical trials for neurological diseases.
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Affiliation(s)
- Tsang-Wei Tu
- Molecular Imaging Laboratory, Department of Radiology, Howard University College of Medicine, Washington, DC, United States.,Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.,Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD, United States
| | - Zsofia I Kovacs
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.,Institute for Biomedical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland
| | - Maggie Sundby
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States
| | - Jaclyn A Witko
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.,Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD, United States
| | - Georgios Z Papadakis
- Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States
| | - William C Reid
- Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States
| | - Dima A Hammoud
- Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States
| | - Joseph A Frank
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, United States.,National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (NIH), Bethesda, MD, United States
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16
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Z Papadakis G, Kochiadakis G, Lazopoulos G, Marias K, Klapsinos N, Hannah-Shmouni F, G Igoumenaki G, Konstantinos Nikolouzakis T, Kteniadakis S, A Spandidos D, H Karantanas A. Targeting vulnerable atherosclerotic plaque via PET-tracers aiming at cell-surface overexpression of somatostatin receptors. Biomed Rep 2020; 13:9. [PMID: 32765848 PMCID: PMC7391298 DOI: 10.3892/br.2020.1316] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 06/15/2020] [Indexed: 01/13/2023] Open
Abstract
Cardiovascular disease (CD) is the leading cause of death in the developed world, with major atherothrombotic events, being mainly attributed to the rupture of unstable, vulnerable atherosclerotic lesions, leading to blood flow obstruction. Since unstable atherosclerotic plaques frequently do not cause hemodynamically significant blood flow restriction, conventional stress imaging tests cannot depict the vulnerable, high-risk for rupture atherosclerotic lesions. Therefore, molecular imaging techniques targeting specific pathophysiologic features related to atherosclerotic plaque rupture mechanism, hold promise for precise and individualized treatment strategies of CD. In the current report, we describe in a patient diagnosed with pancreatic neuroendocrine tumor, the selective uptake of 68Ga-DOATATE by an atherosclerotic lesion in the thoracic aorta. This data indicates that 68Ga-DOTATATE, which is a positron emitting tomography tracer, targeting the recruitment of macrophages taking place in the vulnerable plaque, could potentially serve as an imaging probe for the detection of high-risk, prone to rupture plaques.
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Affiliation(s)
- Georgios Z Papadakis
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece.,Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | | | - George Lazopoulos
- Department of Cardiothoracic Surgery, University General Hospital of Heraklion, University of Crete, Medical School, 71003 Heraklion, Greece
| | - Kostas Marias
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - Nikolaos Klapsinos
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - Fady Hannah-Shmouni
- Internal Medicine-Endocrinology, Hypertension and Metabolic Genetics, Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892, USA
| | - Georgia G Igoumenaki
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | | | | | - Demetrios A Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Apostolos H Karantanas
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece.,Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
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17
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Stancioiu F, Papadakis GZ, Kteniadakis S, Izotov BN, Coleman MD, Spandidos DA, Tsatsakis A. A dissection of SARS‑CoV2 with clinical implications (Review). Int J Mol Med 2020; 46:489-508. [PMID: 32626922 PMCID: PMC7307812 DOI: 10.3892/ijmm.2020.4636] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 06/09/2020] [Indexed: 02/06/2023] Open
Abstract
We are being confronted with the most consequential pandemic since the Spanish flu of 1918‑1920 to the extent that never before have 4 billion people quarantined simultaneously; to address this global challenge we bring to the forefront the options for medical treatment and summarize SARS‑CoV2 structure and functions, immune responses and known treatments. Based on literature and our own experience we propose new interventions, including the use of amiodarone, simvastatin, pioglitazone and curcumin. In mild infections (sore throat, cough) we advocate prompt local treatment for the naso‑pharynx (inhalations; aerosols; nebulizers); for moderate to severe infections we propose a tried‑and‑true treatment: the combination of arginine and ascorbate, administered orally or intravenously. The material is organized in three sections: i) Clinical aspects of COVID‑19; acute respiratory distress syndrome (ARDS); known treatments; ii) Structure and functions of SARS‑CoV2 and proposed antiviral drugs; iii) The combination of arginine‑ascorbate.
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Affiliation(s)
| | | | | | - Boris Nikovaevich Izotov
- Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991 Moscow, Russia
| | - Michael D. Coleman
- School of Life and Health Sciences, Aston University, B4 7ET Birmingham, UK
| | | | - Aristidis Tsatsakis
- Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991 Moscow, Russia
- Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003 Heraklion, Greece
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18
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Tsiknakis N, Trivizakis E, Vassalou EE, Papadakis GZ, Spandidos DA, Tsatsakis A, Sánchez-García J, López-González R, Papanikolaou N, Karantanas AH, Marias K. Interpretable artificial intelligence framework for COVID-19 screening on chest X-rays. Exp Ther Med 2020; 20:727-735. [PMID: 32742318 PMCID: PMC7388253 DOI: 10.3892/etm.2020.8797] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 05/27/2020] [Indexed: 02/07/2023] Open
Abstract
COVID-19 has led to an unprecedented healthcare crisis with millions of infected people across the globe often pushing infrastructures, healthcare workers and entire economies beyond their limits. The scarcity of testing kits, even in developed countries, has led to extensive research efforts towards alternative solutions with high sensitivity. Chest radiological imaging paired with artificial intelligence (AI) can offer significant advantages in diagnosis of novel coronavirus infected patients. To this end, transfer learning techniques are used for overcoming the limitations emanating from the lack of relevant big datasets, enabling specialized models to converge on limited data, as in the case of X-rays of COVID-19 patients. In this study, we present an interpretable AI framework assessed by expert radiologists on the basis on how well the attention maps focus on the diagnostically-relevant image regions. The proposed transfer learning methodology achieves an overall area under the curve of 1 for a binary classification problem across a 5-fold training/testing dataset.
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Affiliation(s)
- Nikos Tsiknakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Eleftherios Trivizakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Evangelia E. Vassalou
- Department of Medical Imaging, University Hospital of Heraklion, 71110 Heraklion, Greece
- Department of Radiology, District Hospital, 72300 Lasithi, Greece
| | - Georgios Z. Papadakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Demetrios A. Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Aristidis Tsatsakis
- Department of Forensic Sciences and Toxicology, Medical School, University of Crete, 71003 Heraklion, Greece
| | | | | | - Nikolaos Papanikolaou
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Computational Clinical Imaging Group, Centre for the Unknown, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Apostolos H. Karantanas
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
- Department of Medical Imaging, University Hospital of Heraklion, 71110 Heraklion, Greece
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece
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19
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Trivizakis E, Papadakis GZ, Souglakos I, Papanikolaou N, Koumakis L, Spandidos DA, Tsatsakis A, Karantanas AH, Marias K. Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review). Int J Oncol 2020; 57:43-53. [PMID: 32467997 PMCID: PMC7252460 DOI: 10.3892/ijo.2020.5063] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 05/05/2020] [Indexed: 12/11/2022] Open
Abstract
The new era of artificial intelligence (AI) has introduced revolutionary data-driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision-support systems. These advances have created unprecedented momentum in computational medical imaging applications and have given rise to new precision medicine research areas. Radiogenomics is a novel research field focusing on establishing associations between radiological features and genomic or molecular expression in order to shed light on the underlying disease mechanisms and enhance diagnostic procedures towards personalized medicine. The aim of the current review was to elucidate recent advances in radiogenomics research, focusing on deep learning with emphasis on radiology and oncology applications. The main deep learning radiogenomics architectures, together with the clinical questions addressed, and the achieved genetic or molecular correlations are presented, while a performance comparison of the proposed methodologies is conducted. Finally, current limitations, potentially understudied topics and future research directions are discussed.
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Affiliation(s)
- Eleftherios Trivizakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Georgios Z Papadakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Ioannis Souglakos
- Laboratory of Translational Oncology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Nikolaos Papanikolaou
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Lefteris Koumakis
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Demetrios A Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Aristidis Tsatsakis
- Laboratory of Forensic Sciences and Toxicology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Apostolos H Karantanas
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
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20
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Papadakis GZ, Sadowksi SM, Karantanas AH, Millo C. Complementary role of 18F-FDG and 68Ga-DOTATATE PET/CT in the surveillance of patients with von Hippel-Lindau syndrome. Ann Gastroenterol 2020; 33:323. [PMID: 32382240 PMCID: PMC7196616 DOI: 10.20524/aog.2020.0465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 02/23/2020] [Indexed: 11/27/2022] Open
Affiliation(s)
- Georgios Z Papadakis
- Department of Radiology, Medical School, University of Crete, Heraklion, Crete, Greece (Georgios Z. Papadakis, Apostolos H. Karantanas).,Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), Heraklion, Crete, Greece (Georgios Z. Papadakis, Apostolos H. Karantanas)
| | - Samira M Sadowksi
- Department of Thoracic and Endocrine Surgery, University Hospital of Geneva and Faculty of Medicine, University of Geneva, Geneva, Switzerland (Samira S. Sadowksi)
| | - Apostolos H Karantanas
- Department of Radiology, Medical School, University of Crete, Heraklion, Crete, Greece (Georgios Z. Papadakis, Apostolos H. Karantanas).,Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), Heraklion, Crete, Greece (Georgios Z. Papadakis, Apostolos H. Karantanas)
| | - Corina Millo
- Positron Emission Tomography (PET) Department, Clinical Center (CC), National Institutes of Health (NIH), Bethesda, Maryland, USA (Corina Millo)
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21
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Tirosh A, RaviPrakash H, Papadakis GZ, Tatsi C, Belyavskaya E, Charalampos L, Lodish MB, Bagci U, Stratakis CA. Computerized Analysis of Brain MRI Parameter Dynamics in Young Patients With Cushing Syndrome-A Case-Control Study. J Clin Endocrinol Metab 2020; 105:dgz303. [PMID: 31875913 PMCID: PMC7089850 DOI: 10.1210/clinem/dgz303] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 12/22/2019] [Indexed: 02/04/2023]
Abstract
BACKGROUND Young patients with Cushing Syndrome (CS) may develop cognitive and behavioral alterations during disease course. METHODS To investigate the effects of CS on the brain, we analyzed consecutive MRI scans of patients with (n = 29) versus without CS (n = 8). Multiple brain compartments were processed for total and gray/white matter (GM/WM) volumes and intensities, and cortical volume, thickness, and surface area. Dynamics (last/baseline scans ratio per parameter) were analyzed versus cortisol levels and CS status (persistent, resolved, and non-CS). RESULTS Twenty-four-hour urinary free cortisol (24hUFC) measurements had inverse correlation with the intensity of subcortical GM structures and of the corpus callosum, and with the cerebral WM intensity. 24hUFC dynamics had negative correlation with volume dynamics of multiple cerebral and cerebellar structures. Patients with persistent CS had less of an increase in cortical thickness and WM intensity, and less of a decrease in WM volume compared with patients with resolution of CS. Patients with resolution of their CS had less of an increase in subcortical GM and cerebral WM volumes, but a greater increase in cortical thickness of frontal lobe versus controls. CONCLUSION Changes in WM/GM consistency, intensity, and homogeneity in patients with CS may correlate with CS clinical consequences better than volume dynamics alone.
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Affiliation(s)
- Amit Tirosh
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- NET Service and Endocrine Oncology Bioinformatics Lab, Sheba Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Ramat Gan, Israel
| | - Harish RaviPrakash
- Center for Research in Computer Vision (CRCV), University of Central Florida, Orlando, Florida
| | - Georgios Z Papadakis
- Computational Biomedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology (FORTH), Heraklion, Crete, Greece
- Skeletal Clinical Studies Unit, National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health (NIH), Bethesda, Maryland
- Department of Medical Imaging, Heraklion University Hospital, Medical School, University of Crete, Heraklion, Crete, Greece
| | - Christina Tatsi
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Elena Belyavskaya
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Lyssikatos Charalampos
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Maya B Lodish
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Ulas Bagci
- Center for Research in Computer Vision (CRCV), University of Central Florida, Orlando, Florida
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
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22
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Kalemaki MS, Karantanas AH, Exarchos D, Detorakis ET, Zoras O, Marias K, Millo C, Bagci U, Pallikaris I, Stratis A, Karatzanis I, Perisinakis K, Koutentakis P, Kontadakis GA, Spandidos DA, Tsatsakis A, Papadakis GZ. PET/CT and PET/MRI in ophthalmic oncology (Review). Int J Oncol 2020; 56:417-429. [PMID: 31939615 PMCID: PMC6959466 DOI: 10.3892/ijo.2020.4955] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 12/31/2019] [Indexed: 12/16/2022] Open
Abstract
Orbital and ocular anatomy is quite complex, consisting of several tissues, which can give rise to both benign and malignant tumors, while several primary neoplasms can metastasize to the orbital and ocular space. Early detection, accurate staging and re-staging, efficient monitoring of treatment response, non-invasive differentiation between benign and malignant lesions, and accurate planning of external radiation treatment, are of utmost importance for the optimal and individualized management of ophthalmic oncology patients. Addressing these challenges requires the employment of several diagnostic imaging techniques, such as high-definition digital fundus photography, ultrasound imaging, optical coherence tomography, optical coherence tomography (OCT)-angiography, computed tomography (CT) and magnetic resonance imaging (MRI). In recent years, technological advances have enabled the development of hybrid positron emission tomography (PET)/CT and PET/MRI systems, setting new standards in cancer diagnosis and treatment. The capability of simultaneously targeting several cancer-related biochemical procedures using positron emitting-radiopharmaceuticals, while morphologically characterizing lesions by CT or MRI, together with the intrinsic quantitative capabilities of PET-imaging, provide incremental diagnostic information, enabling accurate, highly efficient and personalized treatment strategies. Aim of the current review is to discuss the current applications of hybrid PET/CT and PET/MRI imaging in the management of patients presenting with the most commonly encountered orbital and ocular tumors.
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Affiliation(s)
- Maria S Kalemaki
- Department of Ophthalmology, Venizeleio General Hospital of Heraklion, 71409 Heraklion, Greece
| | | | - Dimitris Exarchos
- Department of CT‑MRI and PET/CT, Evangelismos Hospital, 10676 Athens, Greece
| | - Efstathios T Detorakis
- Department of Ophthalmology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Odysseas Zoras
- Department of Surgical Oncology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Kostas Marias
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - Corina Millo
- Positron Emission Tomography Department, Clinical Center (CC), National Institutes of Health (NIH), Bethesda, MD 20814, USA
| | - Ulas Bagci
- Center for Research in Computer Vision (CRCV), University of Central Florida (UCF), Orlando, FL 32816, USA
| | - Ioannis Pallikaris
- Department of Ophthalmology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Andreas Stratis
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - Ioannis Karatzanis
- Foundation for Research and Technology Hellas (FORTH), Computational Biomedicine Laboratory (CBML), 70013 Heraklion, Greece
| | - Kostas Perisinakis
- Department of Medical Physics, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Pavlos Koutentakis
- Department of Ophthalmology, Venizeleio General Hospital of Heraklion, 71409 Heraklion, Greece
| | - Georgios A Kontadakis
- Department of Ophthalmology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Demetrios A Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Aristidis Tsatsakis
- Laboratory of Forensic Sciences and Toxicology, Medical School, University of Crete, 71003 Heraklion, Greece
| | - Georgios Z Papadakis
- Department of Radiology, Medical School, University of Crete, 71003 Heraklion, Greece
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23
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Shekhar S, Gubbi S, Papadakis GZ, Nilubol N, Hannah-Shmouni F. Adrenocortical carcinoma and pulmonary embolism from tumoral extension. Endocrinol Diabetes Metab Case Rep 2019; 2019:EDM190095. [PMID: 31765326 PMCID: PMC6893304 DOI: 10.1530/edm-19-0095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 11/05/2019] [Indexed: 01/26/2023] Open
Abstract
SUMMARY Adrenococortical carcinoma (ACC) is a rare cancer, occurring at the rate of one case in two million person years. Cushing syndrome or a mixed picture of excess androgen and glucocorticoid production are the most common presentations of ACC. Other uncommon presentations include abdominal pain and adrenal incidentalomas. In the present report, a 71-year-old male presented with abdominal pain and was eventually diagnosed with ACC. He was found to have pulmonary thromboembolism following an investigation for hypoxemia, with the tumor thrombus extending upto the right atrium. This interesting case represents the unique presentation of a rare tumor, which if detected late or left untreated is associated with poor outcomes, highlighting the need for a low index of suspicion for ACC when similar presentations are encountered in clinical practice. LEARNING POINTS ACC is a rare but aggressive tumor. ACC commonly presents with rapid onset of hypercortisolism, combined hyperandrogenism and hypercortisolism, or uncommonly with compressive symptoms. Clinicians should have a low index of suspicion for ACC in patients presenting with rapid onset of symptoms related to hypercortisolism and/or hyperandrogenism. Venous thromboembolism and extension of the tumor thrombus to the right side of the heart is a very rare but serious complication of ACC that clinicans should be wary of. The increased risk of venous thromboembolism in ACC could be explained by direct tumor invasion, tumor thrombi or hypercoagulability secondary to hypercortisolism. Early diagnosis and prompt treatment can improve the long-term survival of patients with ACC.
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Affiliation(s)
- Skand Shekhar
- Section on Endocrinology & Genetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Sriram Gubbi
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Georgios Z Papadakis
- Department of Medical Imaging, Heraklion University Hospital, Medical School, University of Crete, Crete, Greece
- Computational Biomedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), Heraklion, Greece
| | - Naris Nilubol
- Surgical Oncology Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Fady Hannah-Shmouni
- Section on Endocrinology & Genetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
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24
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Trivizakis E, Ioannidis GS, Melissianos VD, Papadakis GZ, Tsatsakis A, Spandidos DA, Marias K. A novel deep learning architecture outperforming 'off‑the‑shelf' transfer learning and feature‑based methods in the automated assessment of mammographic breast density. Oncol Rep 2019; 42:2009-2015. [PMID: 31545461 PMCID: PMC6787954 DOI: 10.3892/or.2019.7312] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 09/10/2019] [Indexed: 11/06/2022] Open
Abstract
Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false‑negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre‑screening stratification and risk assessment. In this study, we propose and evaluate advanced machine learning methodologies aiming at an objective and reliable method for breast density scoring from routine mammographic images. The proposed image analysis pipeline incorporates texture [Gabor filters and local binary pattern (LBP)] and gradient‑based features [histogram of oriented gradients (HOG) as well as speeded‑up robust features (SURF)]. Additionally, transfer learning approaches with ImageNet trained weights were also used for comparison, as well as a convolutional neural network (CNN). The proposed CNN model was fully trained on two open mammography datasets and was found to be the optimal performing methodology (AUC up to 87.3%). Thus, the findings of this study indicate that automated density scoring in mammograms can aid clinical diagnosis by introducing artificial intelligence‑powered decision‑support systems and contribute to the 'democratization' of healthcare by overcoming limitations, such as the geographic location of patients or the lack of expert radiologists.
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Affiliation(s)
- Eleftherios Trivizakis
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology‑Hellas (FORTH), 70013 Heraklion, Greece
| | - Georgios S Ioannidis
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology‑Hellas (FORTH), 70013 Heraklion, Greece
| | - Vasileios D Melissianos
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology‑Hellas (FORTH), 70013 Heraklion, Greece
| | - Georgios Z Papadakis
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology‑Hellas (FORTH), 70013 Heraklion, Greece
| | - Aristidis Tsatsakis
- Department of Forensic Sciences and Laboratory of Toxicology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Demetrios A Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Kostas Marias
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology‑Hellas (FORTH), 70013 Heraklion, Greece
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25
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Papadakis GZ, Manikis GC, Karantanas AH, Florenzano P, Bagci U, Marias K, Collins MT, Boyce AM. 18 F-NaF PET/CT IMAGING IN FIBROUS DYSPLASIA OF BONE. J Bone Miner Res 2019; 34:1619-1631. [PMID: 31116487 PMCID: PMC6744316 DOI: 10.1002/jbmr.3738] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 03/20/2019] [Accepted: 03/27/2019] [Indexed: 12/13/2022]
Abstract
Fibrous dysplasia (FD) is a mosaic skeletal disorder resulting in fractures, deformity, and functional impairment. Clinical evaluation has been limited by a lack of surrogate endpoints capable of quantitating disease activity. The purpose of this study was to investigate the utility of 18 F-NaF PET/CT imaging in quantifying disease activity in patients with FD. Fifteen consecutively evaluated subjects underwent whole-body 18 F-NaF PET/CT scans, and FD burden was assessed by quantifying FD-related 18 F-NaF activity. 18 F-NaF PET/CT parameters obtained included (i) SUVmax (standardized uptake value [SUV] of the FD lesion with the highest uptake); (ii) SUVmean (average SUV of all 18 F-NaF-positive FD lesions); (iii) total volume of all 18 F-NaF-positive FD lesions (TV); and (iv) total FD lesion activity determined as the product of TV multiplied by SUVmean (TA = TV × SUVmean ) (TA). Skeletal outcomes, functional outcomes, and bone turnover markers were correlated with 18 F-NaF PET/CT parameters. TV and TA of extracranial FD lesions correlated strongly with skeletal outcomes including fractures and surgeries (p values ≤ 0.003). Subjects with impaired ambulation and scoliosis had significantly higher TV and TA values (P < 0.05), obtained from extracranial and spinal lesions, respectively. Craniofacial surgeries correlated with TV and TA of skull FD lesions (P < 0.001). Bone turnover markers, including alkaline phosphatase, N-telopeptides, and osteocalcin, were strongly correlated with TV and TA (P < 0.05) extracted from FD lesions in the entire skeleton. No associations were identified with SUVmax or SUVmean . Bone pain and age did not correlate with 18 F-NaF PET/CT parameters. FD burden evaluated by 18 F-NaF-PET/CT facilitates accurate assessment of FD activity, and correlates quantitatively with clinically-relevant skeletal outcomes. © 2019 American Society for Bone and Mineral Research.
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Affiliation(s)
- Georgios Z Papadakis
- Foundation for Research and Technology (FORTH), Institute of Computer Science (ICS), Heraklion, Greece.,Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health, Bethesda, MD, USA.,Department of Radiology, Medical School, University of Crete, Heraklion, Greece
| | - Georgios C Manikis
- Foundation for Research and Technology (FORTH), Institute of Computer Science (ICS), Heraklion, Greece
| | - Apostolos H Karantanas
- Foundation for Research and Technology (FORTH), Institute of Computer Science (ICS), Heraklion, Greece.,Department of Radiology, Medical School, University of Crete, Heraklion, Greece
| | - Pablo Florenzano
- Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health, Bethesda, MD, USA.,Endocrinology Department, Facultad de Medicina, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Ulas Bagci
- Center for Research in Computer Vision, University of Central Florida, Orlando, FL, USA
| | - Kostas Marias
- Foundation for Research and Technology (FORTH), Institute of Computer Science (ICS), Heraklion, Greece
| | - Michael T Collins
- Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health, Bethesda, MD, USA
| | - Alison M Boyce
- Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health, Bethesda, MD, USA
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26
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Kontopodis E, Venianaki M, Manikis GC, Nikiforaki K, Salvetti O, Papadaki E, Papadakis GZ, Karantanas AH, Marias K. Investigating the Role of Model-Based and Model-Free Imaging Biomarkers as Early Predictors of Neoadjuvant Breast Cancer Therapy Outcome. IEEE J Biomed Health Inform 2019; 23:1834-1843. [DOI: 10.1109/jbhi.2019.2895459] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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27
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Sinharay S, Tu TW, Kovacs ZI, Schreiber-Stainthorp W, Sundby M, Zhang X, Papadakis GZ, Reid WC, Frank JA, Hammoud DA. In vivo imaging of sterile microglial activation in rat brain after disrupting the blood-brain barrier with pulsed focused ultrasound: [18F]DPA-714 PET study. J Neuroinflammation 2019; 16:155. [PMID: 31345243 PMCID: PMC6657093 DOI: 10.1186/s12974-019-1543-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 07/09/2019] [Indexed: 12/26/2022] Open
Abstract
Background Magnetic resonance imaging (MRI)-guided pulsed focused ultrasound combined with the infusion of microbubbles (pFUS+MB) induces transient blood-brain barrier opening (BBBO) in targeted regions. pFUS+MB, through the facilitation of neurotherapeutics’ delivery, has been advocated as an adjuvant treatment for neurodegenerative diseases and malignancies. Sterile neuroinflammation has been recently described following pFUS+MB BBBO. In this study, we used PET imaging with [18F]-DPA714, a biomarker of translocator protein (TSPO), to assess for neuroinflammatory changes following single and multiple pFUS+MB sessions. Methods Three groups of Sprague-Dawley female rats received MRI-guided pFUS+MB (Optison™; 5–8 × 107 MB/rat) treatments to the left frontal cortex and right hippocampus. Group A rats were sonicated once. Group B rats were sonicated twice and group C rats were sonicated six times on weekly basis. Passive cavitation detection feedback (PCD) controlled the peak negative pressure during sonication. We performed T1-weighted scans immediately after sonication to assess efficiency of BBBO and T2*-weighted scans to evaluate for hypointense voxels. [18F]DPA-714 PET/CT scans were acquired after the BBB had closed, 24 h after sonication in group A and within an average of 10 days from the last sonication in groups B and C. Ratios of T1 enhancement, T2* values, and [18F]DPA-714 percent injected dose/cc (%ID/cc) values in the targeted areas to the contralateral brain were calculated. Histological assessment for microglial activation/astrocytosis was performed. Results In all groups, [18F]DPA-714 binding was increased at the sonicated compared to non-sonicated brain (%ID/cc ratios > 1). Immunohistopathology showed increased staining for microglial and astrocytic markers in the sonicated frontal cortex compared to contralateral brain and to a lesser extent in the sonicated hippocampus. Using MRI, we documented BBB disruption immediately after sonication with resolution of BBBO 24 h later. We found more T2* hypointense voxels with increasing number of sonications. In a longitudinal group of animals imaged after two and after six sonications, there was no cumulative increase of neuroinflammation on PET. Conclusion Using [18F]DPA-714 PET, we documented in vivo neuroinflammatory changes in association with pFUS+MB. Our protocol (utilizing PCD feedback to minimize damage) resulted in neuroinflammation visualized 24 h post one sonication. Our findings were supported by immunohistochemistry showing microglial activation and astrocytosis. Experimental sonication parameters intended for BBB disruption should be evaluated for neuroinflammatory sequelae prior to implementation in clinical trials. Electronic supplementary material The online version of this article (10.1186/s12974-019-1543-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sanhita Sinharay
- Hammoud Laboratory, Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health, 10 Center Drive, Building 10, Room 1C-368, Bethesda, MD, 20892, USA.,University of Texas, MD Anderson Cancer Center, Houston, USA
| | - Tsang-Wei Tu
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,Department of Radiology, Howard University, Washington DC, USA
| | - Zsofia I Kovacs
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.,Institute for Biomedical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland
| | - William Schreiber-Stainthorp
- Hammoud Laboratory, Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health, 10 Center Drive, Building 10, Room 1C-368, Bethesda, MD, 20892, USA
| | - Maggie Sundby
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Xiang Zhang
- Imaging Probe Development Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Rockville, MD, USA
| | - Georgios Z Papadakis
- Hammoud Laboratory, Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health, 10 Center Drive, Building 10, Room 1C-368, Bethesda, MD, 20892, USA.,Department of Radiology, University of Crete and Department of Medical Imaging Heraklion University Hospital, Crete, Greece
| | - William C Reid
- Hammoud Laboratory, Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health, 10 Center Drive, Building 10, Room 1C-368, Bethesda, MD, 20892, USA
| | - Joseph A Frank
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.,National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | - Dima A Hammoud
- Hammoud Laboratory, Center for Infectious Disease Imaging, Clinical Center, National Institutes of Health, 10 Center Drive, Building 10, Room 1C-368, Bethesda, MD, 20892, USA.
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Papadakis GZ, Karantanas AH, Tsiknakis M, Tsatsakis A, Spandidos DA, Marias K. Deep learning opens new horizons in personalized medicine. Biomed Rep 2019; 10:215-217. [PMID: 30988951 PMCID: PMC6439426 DOI: 10.3892/br.2019.1199] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 03/06/2019] [Indexed: 12/11/2022] Open
Abstract
Although the idea of the personalization of patient care dates back to the time of Hippocrates, recent advances in diagnostic medical imaging and molecular medicine are gradually transforming healthcare services, by offering information and diagnostic tools enabling individualized patient management. Facilitating personalized / precision medicine requires taking into account multiple heterogenous parameters, such as sociodemographics, gene variability, environmental and lifestyle factors. Therefore, one of the most critical challenges in personalized medicine is the need to transform large, multi-modal data into decision support tools, capable of bridging the translational gap to the clinical setting. Towards these challenges, deep learning (DL) provides a novel approach, which enables obtaining or developing high-accuracy, multi-modal predictive models, that allow the implementation of the personalized medicine vision in the near future. DL is a highly effective strategy in addressing these challenges, with DL-based models leading to unprecedented results, matching or even improving state-of-the-art prediction/detection rates based on both intuitive and non-intuitive disease descriptors. These results hold promise for significant socio-economic benefits from the application of DL personalized medicine.
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Affiliation(s)
- Georgios Z. Papadakis
- Computational Biomedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Medical Imaging, Heraklion University Hospital, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Apostolos H. Karantanas
- Computational Biomedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Department of Medical Imaging, Heraklion University Hospital, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Manolis Tsiknakis
- Technological Educational Institute of Crete, Department of Informatics Engineering, 71410 Heraklion, Greece
| | - Aristidis Tsatsakis
- Centre of Toxicology Science and Research, Faculty of Medicine, University of Crete, 71003 Heraklion, Greece
| | - Demetrios A. Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 70013 Heraklion, Greece
| | - Kostas Marias
- Computational Biomedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece
- Technological Educational Institute of Crete, Department of Informatics Engineering, 71410 Heraklion, Greece
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Hammoud DA, Boulougoura A, Papadakis GZ, Wang J, Dodd LE, Rupert A, Higgins J, Roby G, Metzger D, Laidlaw E, Mican JM, Pau A, Lage S, Wong CS, Lisco A, Manion M, Sheikh V, Millo C, Sereti I. Increased Metabolic Activity on 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography in Human Immunodeficiency Virus-Associated Immune Reconstitution Inflammatory Syndrome. Clin Infect Dis 2019; 68:229-238. [PMID: 30215671 PMCID: PMC6321853 DOI: 10.1093/cid/ciy454] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Accepted: 05/23/2018] [Indexed: 12/17/2022] Open
Abstract
Background Immune reconstitution inflammatory syndrome (IRIS) represents an unexpected inflammatory response shortly after initiation of antiretroviral therapy (ART) in some human immunodeficiency virus (HIV)-infected patients with underlying neoplasia or opportunistic infections, including tuberculosis. We hypothesized that IRIS is associated with increased glycolysis and that 18F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) could help identify high-risk subjects. Methods In this prospective cohort study, 30 HIV-infected patients (CD4+ count <100 cells/µL) underwent FDG-PET/CT scans at baseline and 4-8 weeks after ART initiation. Ten patients developed IRIS (6 mycobacterial). Results At baseline, total glycolytic activity, total lesion volume, and maximum standardized uptake values (SUVs) of pathologic FDG uptake (reflective of opportunistic disease burden) were significantly higher in IRIS vs non-IRIS (P = .010, .017, and .029, respectively) and significantly correlated with soluble inflammatory biomarkers (interferon-γ, myeloperoxidase, tumor necrosis factor, interleukin 6, soluble CD14). Baseline bone marrow (BM) and spleen FDG uptake was higher in mycobacterial IRIS specifically. After ART initiation, BM and spleen mean SUV decreased in non-IRIS (P = .004, .013) but not IRIS subjects. Our results were supported by significantly higher glucose transporter 1 (Glut-1) expression of CD4+ cells and monocytes after ART initiation in IRIS/mycobacterial IRIS compared with non-IRIS patients. Conclusions We conclude that increased pathologic metabolic activity on FDG-PET/CT prior to ART initiation is associated with IRIS development and correlates with inflammatory biomarkers. Abnormally elevated BM and spleen metabolism is associated with mycobacterial IRIS, HIV viremia, and Glut-1 expression on CD4+ cells and monocytes. Clinical Trials Registration NCT02147405.
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Affiliation(s)
- Dima A Hammoud
- Center for Infectious Diseases Imaging, Clinical Center, National Institutes of Health (NIH)
| | - Afroditi Boulougoura
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Georgios Z Papadakis
- Center for Infectious Diseases Imaging, Clinical Center, National Institutes of Health (NIH)
| | - Jing Wang
- Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc, National Cancer Institute, Frederick
| | - Lori E Dodd
- Biostatistics Research Branch, NIAID, NIH, Bethesda
| | - Adam Rupert
- Leidos Biomedical Research Inc, Frederick National Laboratory for Cancer Research
| | - Jeanette Higgins
- Leidos Biomedical Research Inc, Frederick National Laboratory for Cancer Research
| | - Gregg Roby
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Dorinda Metzger
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Elizabeth Laidlaw
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - JoAnn M Mican
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Alice Pau
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Silvia Lage
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Chun-Shu Wong
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Andrea Lisco
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Maura Manion
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Virginia Sheikh
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
| | - Corina Millo
- Positron Emission Tomography Department, Clinical Center, NIH, Bethesda, Maryland
| | - Irini Sereti
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Bethesda
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Jha S, Fratzl-Zelman N, Roschger P, Papadakis GZ, Cowen EW, Kang H, Lehky TJ, Alter K, Deng Z, Ivovic A, Flynn L, Reynolds JC, Dasgupta A, Miettinen M, Lange E, Katz J, Klaushofer K, Marini JC, Siegel RM, Bhattacharyya T. Distinct Clinical and Pathological Features of Melorheostosis Associated With Somatic MAP2K1 Mutations. J Bone Miner Res 2019; 34:145-156. [PMID: 30138550 PMCID: PMC7577747 DOI: 10.1002/jbmr.3577] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 08/02/2018] [Accepted: 08/16/2018] [Indexed: 12/31/2022]
Abstract
Melorheostosis is a rare hyperostotic disease of the long bones classically characterized by a "dripping candle-wax" radiographic appearance. We recently described somatic activating mutations in MAP2K1 as a cause of melorheostosis. Here, we report distinguishing characteristics of patients with MAP2K1-positive melorheostosis. Fifteen unrelated patients with radiographic appearance of melorheostosis underwent paired biopsies of affected and unaffected bone for whole-exome sequencing, histology, and cell culture. Eight patients with mutations in MAP2K1 in affected bone were compared to the seven MAP2K1-negative patients to identify distinguishing characteristics. Patients with MAP2K1-positive melorheostosis had a distinct phenotype with classic "dripping candle-wax" appearance on radiographs (p = 0.01), characteristic vascular lesions on skin overlying affected bone (p = 0.01), and higher prevalence of extraosseous mineralization and joint involvement (p = 0.04 for both). Melorheostotic bone from both MAP2K1-positive and MAP2K1-negative patients showed two zones of distinct morphology-an outer segment of parallel layers of primary lamellar bone and a deeper zone of intensely remodeled highly porous osteonal-like bone. Affected bone from MAP2K1-positive patients showed excessive osteoid (p = 0.0012), increased number of osteoblasts (p = 0.012) and osteoclasts (p = 0.04), and increased vascularity on histology in comparison to paired unaffected bone which was not seen in affected bone in most MAP2K1-negative patients. The identification of a distinct phenotype of patients with MAP2K1-positive melorheostosis demonstrates clinical and genetic heterogeneity among patients with the disease. Further studies are needed to better understand the underlying pathophysiology and associated skin findings. © 2018 American Society for Bone and Mineral Research.
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Affiliation(s)
- Smita Jha
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA.,Program in Reproductive and Adult Endocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Nadja Fratzl-Zelman
- Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of Vienna Regional Health Insurance Fund (WGKK), and Allgemeine Unfallversicherungsanstalt (AUVA; the Austrian Workers' Compensation Board) Trauma Center Meidling, 1st Medical Department Hanusch Hospital, Vienna, Austria
| | - Paul Roschger
- Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of Vienna Regional Health Insurance Fund (WGKK), and Allgemeine Unfallversicherungsanstalt (AUVA; the Austrian Workers' Compensation Board) Trauma Center Meidling, 1st Medical Department Hanusch Hospital, Vienna, Austria
| | - Georgios Z Papadakis
- Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Computational Bio-Medicine Laboratory (CBML), Heraklion, Crete, Greece.,National Institute of Dental and Craniofacial Research (NIDCR), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Edward W Cowen
- Dermatology Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Heeseog Kang
- Section on Heritable Disorders of Bone and Extracellular Matrix, National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Tanya J Lehky
- Electromyography (EMG) Section, National Institutes of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Katharine Alter
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Zuoming Deng
- Biodata Mining and Discovery Section, Office of Science and Technology, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Aleksandra Ivovic
- Immunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Lauren Flynn
- National Institutes of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - James C Reynolds
- Nuclear Medicine Division, Radiology and Imaging Sciences, National Institutes of Health (NIH) Clinical Center, Bethesda, MD, USA
| | - Abhijit Dasgupta
- Clinical Trials and Outcomes Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Markku Miettinen
- Surgical Pathology, Laboratory of Pathology, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Eileen Lange
- Office of the Clinical Director, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - James Katz
- Office of the Clinical Director, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Klaus Klaushofer
- Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of Vienna Regional Health Insurance Fund (WGKK), and Allgemeine Unfallversicherungsanstalt (AUVA; the Austrian Workers' Compensation Board) Trauma Center Meidling, 1st Medical Department Hanusch Hospital, Vienna, Austria
| | - Joan C Marini
- Section on Heritable Disorders of Bone and Extracellular Matrix, National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Richard M Siegel
- Immunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Timothy Bhattacharyya
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health (NIH), Bethesda, MD, USA
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Jha S, Laucis N, Kim L, Malayeri A, Dasgupta A, Papadakis GZ, Karantanas A, Torres M, Bhattacharyya T. CT analysis of anatomical distribution of melorheostosis challenges the sclerotome hypothesis. Bone 2018; 117:31-36. [PMID: 30218789 PMCID: PMC11060331 DOI: 10.1016/j.bone.2018.09.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 08/17/2018] [Accepted: 09/09/2018] [Indexed: 12/29/2022]
Abstract
Melorheostosis (MEL) is a rare disease of high bone mass with patchy skeletal distribution affecting the long bones. We recently reported somatic mosaic mutations in MAP2K1 in 8 of 15 patients with the disease. The unique anatomic distribution of melorheostosis is of great interest. The disease remains limited to medial or lateral side of the extremity with proximo-distal progression. This pattern of distribution has historically been attributed to sclerotomes (area of bone which is innervated by a single spinal nerve level). In a further analysis of our study on MEL, 30 recruited patients underwent whole body CT scans to characterize the anatomic distribution of the disease. Two radiologists independently reviewed these scans and compared it to the proposed map of sclerotomes. We found that the disease distribution conformed to the distribution of a single sclerotome in only 5 patients (17%). In another 12 patients, the lesions spanned parts of contiguous sclerotomes but did not involve the entire extent of the sclerotomes. Our findings raise concerns about the sclerotomal hypothesis being the definitive explanation for the pattern of anatomic distribution in MEL. We believe that the disease distribution can be explained by clonal proliferation of a mutated skeletal progenitor cell along the limb axis. Studies in mice models on clonal proliferation in limb buds mimic the patterns seen in melorheostosis. We also support this hypothesis by the dorso-ventral confinement of melorheostotic lesion in a patient with low allele frequency of MAP2K1-positive osteoblasts and low skeletal burden of the disease. This suggests that the mutation occurred after the formation of dorso-ventral plane. Further studies on limb development are needed to better understand the etiology, pathophysiology and pattern of disease distribution in all patients with MEL.
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Affiliation(s)
- Smita Jha
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, United States of America; Program in Reproductive and Adult Endocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States of America.
| | - Nicholas Laucis
- Diagnostic Radiology, Henry Ford Health System, Detroit, MI, United States of America
| | - Lauren Kim
- Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, United States of America
| | - Ashkan Malayeri
- Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, United States of America
| | - Abhijit Dasgupta
- Clinical Trials and Outcomes Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, United States of America
| | - Georgios Z Papadakis
- Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Computational Bio-Medicine Laboratory (CBML), Heraklion, Crete, Greece
| | | | - Miguel Torres
- Programa de Biologia del Desarrollo Cardiovascular, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Instituto de Salud Carlos III, E-28029 Madrid, Spain
| | - Timothy Bhattacharyya
- Clinical and Investigative Orthopedics Surgery Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, United States of America
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Nikolouzakis TK, Vassilopoulou L, Fragkiadaki P, Sapsakos TM, Papadakis GZ, Spandidos DA, Tsatsakis AM, Tsiaoussis J. Improving diagnosis, prognosis and prediction by using biomarkers in CRC patients (Review). Oncol Rep 2018; 39:2455-2472. [PMID: 29565457 PMCID: PMC5983921 DOI: 10.3892/or.2018.6330] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 03/21/2018] [Indexed: 12/17/2022] Open
Abstract
Colorectal cancer (CRC) is among the most common cancers. In fact, it is placed in the third place among the most diagnosed cancer in men, after lung and prostate cancer, and in the second one for the most diagnosed cancer in women, following breast cancer. Moreover, its high mortality rates classifies it among the leading causes of cancer‑related death worldwide. Thus, in order to help clinicians to optimize their practice, it is crucial to introduce more effective tools that will improve not only early diagnosis, but also prediction of the most likely progression of the disease and response to chemotherapy. In that way, they will be able to decrease both morbidity and mortality of their patients. In accordance with that, colon cancer research has described numerous biomarkers for diagnostic, prognostic and predictive purposes that either alone or as part of a panel would help improve patient's clinical management. This review aims to describe the most accepted biomarkers among those proposed for use in CRC divided based on the clinical specimen that is examined (tissue, faeces or blood) along with their restrictions. Lastly, new insight in CRC monitoring will be discussed presenting promising emerging biomarkers (telomerase activity, telomere length and micronuclei frequency).
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Affiliation(s)
| | - Loukia Vassilopoulou
- Laboratory of Forensic Sciences and Toxicology, Medical School, University of Crete, 71409 Heraklion, Crete, Greece
| | - Persefoni Fragkiadaki
- Laboratory of Forensic Sciences and Toxicology, Medical School, University of Crete, 71409 Heraklion, Crete, Greece
| | - Theodoros Mariolis Sapsakos
- Laboratory of Anatomy and Histology, Nursing School, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Georgios Z. Papadakis
- Foundation for Research and Technology Hellas (FORTH), Institute of Computer Sciences (ICS), Computational Biomedicine Laboratory (CBML), 71003 Heraklion, Crete, Greece
| | - Demetrios A. Spandidos
- Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Crete, Greece
| | - Aristides M. Tsatsakis
- Laboratory of Forensic Sciences and Toxicology, Medical School, University of Crete, 71409 Heraklion, Crete, Greece
| | - John Tsiaoussis
- Laboratory of Anatomy-Histology-Embryology, Medical School, University of Crete, 71110 Heraklion, Greece
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Xu Z, Gao M, Papadakis GZ, Luna B, Jain S, Mollura DJ, Bagci U. Joint solution for PET image segmentation, denoising, and partial volume correction. Med Image Anal 2018; 46:229-243. [PMID: 29627687 PMCID: PMC6080255 DOI: 10.1016/j.media.2018.03.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 03/15/2018] [Accepted: 03/17/2018] [Indexed: 10/17/2022]
Abstract
Segmentation, denoising, and partial volume correction (PVC) are three major processes in the quantification of uptake regions in post-reconstruction PET images. These problems are conventionally addressed by independent steps. In this study, we hypothesize that these three processes are dependent; therefore, jointly solving them can provide optimal support for quantification of the PET images. To achieve this, we utilize interactions among these processes when designing solutions for each challenge. We also demonstrate that segmentation can help in denoising and PVC by locally constraining the smoothness and correction criteria. For denoising, we adapt generalized Anscombe transformation to Gaussianize the multiplicative noise followed by a new adaptive smoothing algorithm called regional mean denoising. For PVC, we propose a volume consistency-based iterative voxel-based correction algorithm in which denoised and delineated PET images guide the correction process during each iteration precisely. For PET image segmentation, we use affinity propagation (AP)-based iterative clustering method that helps the integration of PVC and denoising algorithms into the delineation process. Qualitative and quantitative results, obtained from phantoms, clinical, and pre-clinical data, show that the proposed framework provides an improved and joint solution for segmentation, denoising, and partial volume correction.
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Affiliation(s)
- Ziyue Xu
- Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Mingchen Gao
- Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Georgios Z Papadakis
- Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Brian Luna
- University of California at Irvine, Irvine, CA, USA
| | - Sanjay Jain
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel J Mollura
- Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Ulas Bagci
- University of Central Florida, Orlando, FL, USA.
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Tirosh A, Papadakis GZ, Millo C, Hammoud D, Sadowski SM, Herscovitch P, Pacak K, Marx SJ, Yang L, Nockel P, Shell J, Green P, Keutgen XM, Patel D, Nilubol N, Kebebew E. Prognostic Utility of Total 68Ga-DOTATATE-Avid Tumor Volume in Patients With Neuroendocrine Tumors. Gastroenterology 2018; 154:998-1008.e1. [PMID: 29155309 PMCID: PMC5847442 DOI: 10.1053/j.gastro.2017.11.008] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 10/29/2017] [Accepted: 11/06/2017] [Indexed: 01/08/2023]
Abstract
BACKGROUND & AIMS Survival times vary among patients with neuroendocrine tumors (NETs) - even among those with the same site, stage, and grade of primary tumor. This makes it difficult to select treatment for patients with unresectable NETs because some patients can survive decades without treatment. 68Gallium-DOTATATE positron emission tomography with computed tomography (68Ga-DOTATATE PET/CT) is a sensitive imaging technique for detection of NETs. We investigated the prognostic accuracy of 68Ga-DOTATATE PET/CT-based analysis of tumor volume in patients with NETs. METHODS We performed a prospective study of 184 patients with NETs (128 [69.6%] with metastases and 11 patients [6.0%] with locally advanced disease) at the National Institutes of Health Clinical Center (Bethesda, MD) from 2013 through 2017. All patients underwent 68Ga-DOTATATE PET/CT image analysis and total 68Ga-DOTATATE-Avid tumor volume (68Ga-DOTATATE TV) was determined. We also measured fasting serum chromogranin A, neuron-specific enolase, gastrin, glucagon, vasoactive intestinal peptide, pancreatic polypeptide, and 24-hour urinary 5-hydroxyindoleacetic acid levels in all patients. Disease progression was defined as a new lesion or a growth of a known lesion during the interval between baseline 68Ga-DOTATATE PET/CT scan and follow-up imaging (14.0 ± 6.1 months; range, 1-35 months). The primary outcomes were progression-free survival (PFS) and disease-specific mortality during a median follow-up time of 18 months (range, 4-35 months). RESULTS We found an inverse correlation between quartiles of 68Ga-DOTATATE TV and PFS (P = .001) and disease-specific survival (P = .002). A 68Ga-DOTATATE TV of 7.0 mL or more was associated with higher odds of disease progression (hazard ratio, 3.0; P = .04). A 68Ga-DOTATATE TV of 35.8 mL or more was associated with increased risk of disease-specific death (hazard ratio, 10.6) in multivariable analysis (P = .01), as well as in subgroup analysis of patients with pancreatic NETs. CONCLUSIONS In a prospective study, we demonstrated the prognostic utility of 68Ga-DOTATATE TV in a large cohort of patients with NETs, in terms of PFS and disease-specific mortality.
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Affiliation(s)
- Amit Tirosh
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; Sackler Faculty of Medicine, Tel Aviv University, Israel
| | - Georgios Z Papadakis
- PET Imaging Center, National Institutes of Health Clinical Center, Bethesda, Maryland; Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), Crete, Greece
| | - Corina Millo
- PET Imaging Center, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Dima Hammoud
- PET Imaging Center, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Samira M Sadowski
- Endocrine and Thoracic Surgery, University Hospitals of Geneva, Geneva, Switzerland
| | - Peter Herscovitch
- PET Imaging Center, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Karel Pacak
- National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Stephen J Marx
- National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Lily Yang
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Pavel Nockel
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Jasmine Shell
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Patience Green
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Xavier M Keutgen
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; Department of Surgery, Rush University Medical Center, Chicago, Illinois
| | - Dhaval Patel
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Naris Nilubol
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Electron Kebebew
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland; Department of Surgery, The George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia.
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Papadakis GZ, Jha S, Bhattacharyya T, Millo C, Tu TW, Bagci U, Marias K, Karantanas AH, Patronas NJ. 18F-NaF PET/CT in Extensive Melorheostosis of the Axial and Appendicular Skeleton With Soft-Tissue Involvement. Clin Nucl Med 2017; 42:537-539. [PMID: 28319505 DOI: 10.1097/rlu.0000000000001647] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Melorheostosis is a rare, nonhereditary, benign, sclerotic bone dysplasia with no sex predilection, typically occurring in late childhood or early adulthood, which can lead to substantial functional morbidity, depending on the sites of involvement. We report on a patient with extensive melorheostosis in the axial and appendicular skeleton, as well as in the soft tissues, who was evaluated with whole-body F-NaF PET/CT scan. All melorheostotic lesions of the skeleton and of the ossified soft-tissue masses demonstrated intensely increased F-NaF activity, suggesting the application of this modality in assessing and monitoring the disease activity.
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Affiliation(s)
- Georgios Z Papadakis
- From the *Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, MD; †Foundation for Research and Technology Hellas, Institute of Computer Science, Computational Biomedicine Laboratory, Heraklion, Crete, Greece; ‡National Institute of Arthritis and Musculoskeletal and Skin Diseases and §PET Department, Clinical Center, National Institutes of Health, Bethesda, MD; ∥Center for Research in Computer Vision, Electrical and Computer Science Department, University of Central Florida, Orlando, FL; and ¶Department of Radiology, Medical School, University of Crete, Crete, Greece
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Hannah-Shmouni F, Papadakis GZ, Stratakis CA, Blau J. Enlarging hypermetabolic nodule: benign non-functional adrenocortical adenoma. BMJ Case Rep 2017; 2017:bcr-2017-220820. [PMID: 29248879 DOI: 10.1136/bcr-2017-220820] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Affiliation(s)
- Fady Hannah-Shmouni
- Section on Endocrinology and Genetics, National Institute of Child Health and Human Development, Bethesda, Maryland, USA
| | - Georgios Z Papadakis
- Section on Endocrinology and Genetics, National Institute of Child Health and Human Development, Bethesda, Maryland, USA.,Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Computational Biomedicine Laboratory, Heraklion, Crete, Greece
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, National Institute of Child Health and Human Development, Bethesda, Maryland, USA
| | - Jenny Blau
- Section on Endocrinology and Genetics, National Institute of Child Health and Human Development, Bethesda, Maryland, USA
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Nitipir C, Niculae D, Orlov C, Barbu MA, Popescu B, Popa AM, Pantea AMS, Stanciu AE, Galateanu B, Ginghina O, Papadakis GZ, Izotov BN, Spandidos DA, Tsatsakis AM, Negrei C. Update on radionuclide therapy in oncology. Oncol Lett 2017; 14:7011-7015. [PMID: 29344129 PMCID: PMC5754838 DOI: 10.3892/ol.2017.7141] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 09/21/2017] [Indexed: 12/22/2022] Open
Abstract
Unstable isotopes and their capacity to emit ionizing radiation have been employed in clinical practice not only for diagnostic, but also for therapeutic purposes, with significant contribution in several fields of medicine and primarily in the management of oncologic patients. Their efficacy is associated with their ability to provide the targeted delivery of ionizing radiation for a determined duration. These compounds can be used for curative or palliative treatment, as well as for a diagnostic-therapeutic (theranostic) approach. This review summarises the most recent trends in radionuclide treatment for several malignancies, including prostate cancer, neuroendocrine tumours, and hematological and thyroid malignancies, in which radionuclide-based therapies have been employed with high effectiveness.
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Affiliation(s)
- Cornelia Nitipir
- Oncology Department, Elias University Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 011461 Bucharest, Romania.,Hygiene Department, 'Carol Davila' University of Medicine and Pharmacy, 050463 Bucharest, Romania
| | - Dana Niculae
- Radiopharmaceuticals Research Centre, Horia Hulubei National Institute for Physics and Nuclear Engineering, 077125 Magurele, Romania
| | - Cristina Orlov
- Oncology Department, Elias University Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 011461 Bucharest, Romania
| | - Maria Alexandra Barbu
- Oncology Department, Elias University Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 011461 Bucharest, Romania
| | - Bogdan Popescu
- Oncology Department, Elias University Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 011461 Bucharest, Romania
| | - Ana Maria Popa
- Oncology Department, Elias University Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 011461 Bucharest, Romania
| | | | - Adina Elena Stanciu
- Department of Carcinogenesis and Molecular Biology, Institute of Oncology, 022328 Bucharest, Romania
| | - Bianca Galateanu
- Department of Biochemistry and Molecular Biology, University of Bucharest, 050095 Bucharest, Romania
| | - Octav Ginghina
- Department of Surgery, Faculty of Dental Medicine, 'Sf. Ioan' Clinical Emergency Hospital, 'Carol Davila' University of Medicine and Pharmacy, 042122 Bucharest, Romania
| | - Georgios Z Papadakis
- Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Computational Biomedicine Laboratory (CBML), 71003 Heraklion, Greece
| | - Boris N Izotov
- Department of Analytical Toxicology, Pharmaceutical Chemistry and Pharmacognosy, Sechenov University, 119991 Moscow, Russia
| | - Demetrios A Spandidos
- Laboratory of Clinical Virology, University of Crete Medical School, 71003 Heraklion, Greece
| | - Aristides M Tsatsakis
- Department of Toxicology and Forensic Sciences, University of Crete Medical School, 71003 Heraklion, Greece
| | - Carolina Negrei
- Departament of Toxicology, Faculty of Pharmacy, 'Carol Davila' University of Medicine and Pharmacy, 020956 Bucharest, Romania
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Faucz FR, Tirosh A, Tatsi C, Berthon A, Hernández-Ramírez LC, Settas N, Angelousi A, Correa R, Papadakis GZ, Chittiboina P, Quezado M, Pankratz N, Lane J, Dimopoulos A, Mills JL, Lodish M, Stratakis CA. Somatic USP8 Gene Mutations Are a Common Cause of Pediatric Cushing Disease. J Clin Endocrinol Metab 2017; 102:2836-2843. [PMID: 28505279 PMCID: PMC5546857 DOI: 10.1210/jc.2017-00161] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 05/08/2017] [Indexed: 12/22/2022]
Abstract
CONTEXT Somatic mutations in the ubiquitin-specific protease 8 (USP8) gene have been recently identified as the most common genetic alteration in patients with Cushing disease (CD). However, the frequency of these mutations in the pediatric population has not been extensively assessed. OBJECTIVE We investigated the status of the USP8 gene at the somatic level in a cohort of pediatric patients with corticotroph adenomas. DESIGN AND METHODS The USP8 gene was fully sequenced in both germline and tumor DNA samples from 42 pediatric patients with CD. Clinical, biochemical, and imaging data were compared between patients with and without somatic USP8 mutations. RESULTS Five different USP8 mutations (three missense, one frameshift, and one in-frame deletion) were identified in 13 patients (31%), all of them located in exon 14 at the previously described mutational hotspot, affecting the 14-3-3 binding motif of the protein. Patients with somatic mutations were older at disease presentation [mean 5.1 ± 2.1 standard deviation (SD) vs 13.1 ± 3.6 years, P = 0.03]. Levels of urinary free cortisol, midnight serum cortisol, and adrenocorticotropic hormone, as well as tumor size and frequency of invasion of the cavernous sinus, were not significantly different between the two groups. However, patients harboring somatic USP8 mutations had a higher likelihood of recurrence compared with patients without mutations (46.2% vs 10.3%, P = 0.009). CONCLUSION Somatic USP8 gene mutations are a common cause of pediatric CD. Patients harboring a somatic mutation had a higher likelihood of tumor recurrence, highlighting the potential importance of this molecular defect for the disease prognosis and the development of targeted therapeutic options.
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Affiliation(s)
- Fabio R. Faucz
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Amit Tirosh
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
- Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Christina Tatsi
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Annabel Berthon
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Laura C. Hernández-Ramírez
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Nikolaos Settas
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Anna Angelousi
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Ricardo Correa
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Georgios Z. Papadakis
- Department of Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, Maryland 20814
| | - Prashant Chittiboina
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20824
| | - Martha Quezado
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, Minnesota 55455
| | - John Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, Minnesota 55455
| | - Aggeliki Dimopoulos
- Epidemiology Branch, Division of Intramural Population Health Research, National Institutes of Health, Rockville, Maryland 20852
| | - James L. Mills
- Epidemiology Branch, Division of Intramural Population Health Research, National Institutes of Health, Rockville, Maryland 20852
| | - Maya Lodish
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
| | - Constantine A. Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
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Tirosh A, Papadakis GZ, Chittiboina P, Lyssikatos C, Belyavskaya E, Keil M, Lodish MB, Stratakis CA. 3D Volumetric Measurements of GH Secreting Adenomas Correlate with Baseline Pituitary Function, Initial Surgery Success Rate, and Disease Control. Horm Metab Res 2017; 49:440-445. [PMID: 28472827 PMCID: PMC6309337 DOI: 10.1055/s-0043-107245] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
There is scarce data on the clinical utility of volume measurement for growth hormone (GH)-secreting pituitary adenomas. The current study objective was to assess the association between pituitary adenoma volumes and baseline endocrine evaluation, initial surgical success rate, and disease control among patients with acromegaly. A retrospective cohort study was conducted at a clinical research center including patients with acromegaly due to GH-secreting pituitary adenomas. Baseline hormonal evaluation and adenoma characteristics according to MRI were collected. Volumetric measurements of pituitary adenomas were performed using a semi-automated lesion segmentation and tumor-volume assessment tools. Rates of post-operative medical treatment, radiation therapy, and re-operation were gathered from the patients' medical records. Twenty seven patients (11 females) were included, median age 21.0 years (interquartile range 29 years, range 3-61 years). Patients harboring adenomas with a volume <2 000 mm3 had higher chance to achieve disease remission [94.1% (n=16) vs. 50.0% (n=4), p<0.05]. Adenoma volumes positively correlated with baseline plasma GH levels before and after oral glucose administration, and with plasma IGF-I and PRL levels. Adenoma volume had negative correlation with morning plasma cortisol levels. Finally, patients harboring larger adenomas required 2nd surgery and/or medical treatment more often compared with subjects with smaller adenomas. Accurate 3D volume measurement of GH-secreting pituitary adenomas may be used for the prediction of initial surgery success and for disease control rates among patients with a GH-secreting pituitary adenomas and performs better than standard size assessments.
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Affiliation(s)
- Amit Tirosh
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- Sackler school of medicine, Tel Aviv University, Israel
| | - Georgios Z. Papadakis
- Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Prashant Chittiboina
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Charalampos Lyssikatos
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Elena Belyavskaya
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Meg Keil
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Maya B. Lodish
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Constantine A. Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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Buty M, Xu Z, Wu A, Gao M, Nelson C, Papadakis GZ, Teomete U, Celik H, Turkbey B, Choyke P, Mollura DJ, Bagci U, Folio LR. Quantitative Image Quality Comparison of Reduced- and Standard-Dose Dual-Energy Multiphase Chest, Abdomen, and Pelvis CT. ACTA ACUST UNITED AC 2017; 3:114-122. [PMID: 28856247 PMCID: PMC5573232 DOI: 10.18383/j.tom.2017.00002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel–Lindau disease (N = 26) and renal cell carcinoma (N = 10). We investigated density, morphometric, and structural differences between scans both at tissue (fat, bone) and organ levels (liver, heart, spleen, lung). To quantify structural variations caused by image quality differences, we propose using the following metrics: dice similarity coefficient, structural similarity index, Hausdorff distance, gradient magnitude similarity deviation, and weighted spectral distance. Pearson correlation coefficient and Welch 2-sample t test were used for quantitative comparisons of organ morphometry and to compare density distribution of tissue, respectively. For qualitative evaluation, 2-sided Kendall Tau test was used to assess agreement among readers. Both qualitative and quantitative evaluations were designed to examine significance of image differences for clinical tasks. Qualitative judgment served as an overall assessment, whereas detailed quantifications on structural consistency, intensity homogeneity, and texture similarity revealed more accurate and global difference estimations. Qualitative and quantitative results indicated no significant image quality degradation. Our study concludes that low(er)-dose CT scans can be routinely used because of no significant loss in quantitative image information compared with standard-dose CT scans.
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Affiliation(s)
- Mario Buty
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Ziyue Xu
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Aaron Wu
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Mingchen Gao
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Chelyse Nelson
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Georgios Z Papadakis
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Uygar Teomete
- Bluefield Regional Medical Center, Bluefield, West Virginia
| | - Haydar Celik
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Baris Turkbey
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Peter Choyke
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Daniel J Mollura
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
| | - Ulas Bagci
- Center for Research in Computer Vision, University of Central Florida, Orlando, Florida
| | - Les R Folio
- National Institutes of Health, Radiology and Imaging Sciences Bethesda, Maryland
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Tirosh A, Papadakis GZ, Millo C, Sadowski SM, Herscovitch P, Pacak K, Marx SJ, Yang L, Nockel P, Shell J, Green P, Keutgen XM, Patel D, Nilubol N, Kebebew E. Association between neuroendocrine tumors biomarkers and primary tumor site and disease type based on total 68Ga-DOTATATE-Avid tumor volume measurements. Eur J Endocrinol 2017; 176:575-582. [PMID: 28289088 PMCID: PMC5430160 DOI: 10.1530/eje-16-1079] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Revised: 02/08/2017] [Accepted: 02/14/2017] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To determine the association between neuroendocrine tumor (NET) biomarker levels and the extent of disease as assessed by 68Ga DOTATATE PET/CT imaging. DESIGN A retrospective analysis of a prospective database of patients with NETs. METHODS Fasting plasma chromogranin A (CgA), neuron-specific enolase (NSE), gastrin, glucagon, vasoactive intestinal peptide (VIP) and pancreatic polypeptide (PP), and 24-h urinary 5-hydroxyindoleacetic acid (5-HIAA) levels were measured. Correlation between biomarkers and total 68Ga-DOTATATE-avid tumor volume (TV) was analyzed. RESULTS The analysis included 232 patients. In patients with pancreatic NETs (n = 112), 68Ga-DOTATATE TV correlated with CgA (r = 0.6, P = 0.001, Spearman). In patients with multiple endocrine neoplasia type 1 (n = 39), 68Ga-DOTATATE TV correlated with glucagon (r = 0.5, P = 0.01) and PP levels (r = 0.5, P = 0.049). In patients with von Hippel-Lindau (n = 24), plasma VIP (r = 0.5, P = 0.02) and PP levels (r = 0.7, P < 0.001) correlated with 68Ga-DOTATATE TV. In patients with small intestine NET (SINET, n = 74), 68Ga-DOTATATE TV correlated with CgA (r = 0.5, P = 0.02) and 5-HIAA levels (r = 0.7, P < 0.001), with 5-HIAA ≥8.1 mg/24 h associated with metastatic disease with high positive (81.8%) and negative (85.7%) predictive values (P = 0.001). 68Ga-DOTATATE TV in patients with NET of unknown primary (n = 16) and those with NET of other primary location (n = 30) correlated with 5-HIAA levels (r = 0.8, P = 0.002 and r = 0.7, P = 0.02 respectively). CONCLUSIONS Our data supports the use of specific NET biomarkers based on the site of the primary NET and the presence of hereditary syndrome-associated NET. High urinary 5-HIAA levels indicate the presence of metastatic disease in patients with SINET.
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Affiliation(s)
- Amit Tirosh
- Section on Medical Neuroendocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
- Sackler Faculty of Medicine, Tel Aviv University, Israel
| | - Georgios Z. Papadakis
- PET-Department, National Institutes of Health Clinical Center, Bethesda, Maryland
- Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), Crete, Greece
| | - Corina Millo
- PET-Department, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Samira M. Sadowski
- Endocrine and Thoracic Surgery, University Hospitals of Geneva, Geneva, Switzerland
| | - Peter Herscovitch
- PET-Department, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Karel Pacak
- Section on Medical Neuroendocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Stephen J. Marx
- Section on Medical Neuroendocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
| | - Lily Yang
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Pavel Nockel
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Jasmine Shell
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Patience Green
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Xavier M. Keutgen
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
- Department of Surgery, Rush University Medical Center, Chicago, Illinois
| | - Dhaval Patel
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Naris Nilubol
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Electron Kebebew
- Endocrine Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
- Department of Surgery, The George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia
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Papadakis GZ, Mavroudis D, Georgoulias V, Souglakos J, Alegakis AK, Samonis G, Bagci U, Makrigiannakis A, Zoras O. Serum IGF-1, IGFBP-3 levels and circulating tumor cells (CTCs) in early breast cancer patients. Growth Horm IGF Res 2017; 33:28-34. [PMID: 28258988 DOI: 10.1016/j.ghir.2017.02.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 01/19/2017] [Accepted: 02/15/2017] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Insulin-like growth factor (IGF)-axis is involved in human oncogenesis and metastasis development for various solid tumors including breast cancer. Aim of this study was to assess the association between IGF-1, IGF-binding protein-3 (IGFBP-3) serum levels and the presence of circulating tumor cells (CTCs) in the peripheral blood of women diagnosed with early breast cancer (EBC), before and after adjuvant chemotherapy. DESIGN 171 patients with early-stage breast adenocarcinomas were retrospectively evaluated. Immunoradiometric (IRMA) assays were employed for the in-vitro determination of IGF-1 and IGFBP-3 serum levels in blood samples collected after surgical treatment and before initiation of adjuvant chemotherapy. CTCs' presence was assessed through detection of cytokeratin-19 (CK-19) mRNA transcripts using quantitative real time reverse transcription polymerase chain reaction (RT-PCR). IGF-1, IGFBP-3 serum levels were correlated with CTCs' presence before and after adjuvant chemotherapy as well as with tumor characteristics including tumor size, axillary lymph node status, oestrogen (ER)/progestorene (PR) and human epidermural growth factor receptor 2 (HER2) receptor status. Log-rank test was applied to investigate possible association between IGF-1, IGFBP-3 serum levels and disease-free interval (DFI) and overall survival (OS). RESULTS Before initiation of adjuvant therapy IGF-1, IGFBP-3 serum levels were moderately associated (Spearman's rho=0.361, p<0.001) with each other, while presenting significant differences across age groups (all p values<0.05). IGF-1 serum levels did not correlate with the presence of CTCs before initiation (p=0.558) or after completion (p=0.474) of adjuvant chemotherapy. Similarly, IGFBP-3 serum levels did not show significant association with detectable CTCs either before (p=0.487) or after (p=0.134) completion of adjuvant chemotherapy. There was no statistically significant association between the clinical outcome of patients in terms of DFI, OS and IGF-1(DFI: p=0.499; OS: p=0.220) or IGFBP-3 (DFI: p=0.900; OS: p=0.406) serum levels. CONCLUSIONS IGF-1 and IGFBP-3 serum levels before initiation of adjuvant chemotherapy are not indicative of CTCs' presence in the blood and do not correlate with clinical outcome of women with early-stage breast cancer.
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Affiliation(s)
- Georgios Z Papadakis
- Faculty of Medicine, University of Crete, Greece; Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center (CC), National Institutes of Health (NIH), Bethesda, MD 20892, USA.
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University General Hospital of Heraklion, School of Medicine, University of Crete, Greece; Laboratory of Tumor Cell Biology, School of Medicine, University of Crete, Greece
| | - Vasilios Georgoulias
- Department of Medical Oncology, University General Hospital of Heraklion, School of Medicine, University of Crete, Greece; Laboratory of Tumor Cell Biology, School of Medicine, University of Crete, Greece
| | - John Souglakos
- Department of Medical Oncology, University General Hospital of Heraklion, School of Medicine, University of Crete, Greece; Laboratory of Tumor Cell Biology, School of Medicine, University of Crete, Greece
| | - Athanasios K Alegakis
- Center of Toxicology Science & Research, Division of Morphology, Medical School, University of Crete, Heraklion, Crete, Greece
| | - George Samonis
- Department of Internal Medicine, University of Crete, Heraklion, Greece
| | - Ulas Bagci
- Center for Research in Computer Vision (CRCV), Electrical and Computer Science Department, University of Central Florida (UCF), Orlando, FL 32816, USA
| | - Antonis Makrigiannakis
- Department of Obstetrics and Gynecology, Medical School, University of Crete, Heraklion, Greece
| | - Odysseas Zoras
- Department of Surgical Oncology, University Hospital of Heraklion, Crete, Greece
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Fowlkes B, Ghanouni P, Sanghvi N, Coussios C, Lyon PC, Gray M, Mannaris C, Victor MDS, Stride E, Cleveland R, Carlisle R, Wu F, Middleton M, Gleeson F, Aubry JF, Pauly KB, Moonen C, Vortman J, Ghanouni P, Sharabi S, Daniels D, Last D, Guez D, Levy Y, Volovick A, Grinfeld J, Rachmilevich I, Amar T, Zibly Z, Mardor Y, Harnof S, Plaksin M, Weissler Y, Shoham S, Kimmel E, Naor O, Farah N, Shoham S, Paeng DG, Xu Z, Snell J, Quigg AH, Eames M, Jin C, Everstine AC, Sheehan JP, Lopes BS, Kassell N, Looi T, Khokhlova V, Mougenot C, Hynynen K, Drake J, Slayton M, Amodei RC, Compton K, McNelly A, Latt D, Slayton M, Amodei RC, Compton K, Kearney J, Melodelima D, Dupre A, Chen Y, Perol D, Vincenot J, Chapelon JY, Rivoire M, Guo W, Ren G, Shen G, Neidrauer M, Zubkov L, Weingarten MS, Margolis DJ, Lewin PA, McDannold N, Sutton J, Vykhodtseva N, Livingstone M, Kobus T, Zhang YZ, Vykhodtseva N, McDannold N, Schwartz M, Huang Y, Lipsman N, Jain J, Chapman M, Sankar T, Lozano A, Hynynen K, Schwartz M, Yeung R, Huang Y, Lipsman N, Jain J, Chapman M, Lozano A, Hynynen K, Damianou C, Papadopoulos N, Volovick A, Grinfeld J, Levy Y, Brokman O, Zadicario E, Brenner O, Castel D, Wu SY, Grondin J, Zheng W, Heidmann M, Karakatsani ME, Sánchez CJS, Ferrera V, Konofagou EE, Damianou C, Yiannakou M, Cho H, Lee H, Han M, Choi JR, Lee T, Ahn S, Chang Y, Park J, Ellens N, Partanen A, Farahani K, Airan R, Carpentier A, Canney M, Vignot A, Lafon C, Chapelon JY, Delattre JY, Idbaih A, Odéen H, Bolster B, Jeong EK, Parker DL, Gaur P, Feng X, Fielden S, Meyer C, Werner B, Grissom W, Marx M, Ghanouni P, Pauly KB, Weber H, Taviani V, Pauly KB, Ghanouni P, Hargreaves B, Tanaka J, Kikuchi K, Ishijima A, Azuma T, Minamihata K, Yamaguchi S, Nagamune T, Sakuma I, Takagi S, Santin MD, Marsac L, Maimbourg G, Monfort M, Larrat B, François C, Lehéricy S, Tanter M, Aubry JF, Karakatsani ME, Samiotaki G, Wang S, Acosta C, Feinberg ER, Konofagou EE, Kovacs ZI, Tu TW, Papadakis GZ, Reid WC, Hammoud DA, Frank JA, Kovacs ZI, Kim S, Jikaria N, Bresler M, Qureshi F, Frank JA, Xia J, Tsui PS, Liu HL, Plata JC, Fielden S, Sveinsson B, Hargreaves B, Meyer C, Pauly KB, Plata JC, Salgaonkar VA, Adams M, Diederich C, Ozhinsky E, Bucknor MD, Rieke V, Partanen A, Mikhail A, Severance L, Negussie AH, Wood B, de Greef M, Schubert G, Moonen C, Ries M, Poorman ME, Dockery M, Chaplin V, Dudzinski SO, Spears R, Caskey C, Giorgio T, Grissom W, Costa MM, Papaevangelou E, Shah A, Rivens I, Box C, Bamber J, ter Haar G, Burks SR, Nagle M, Nguyen B, Bresler M, Frank JA, Burks SR, Nagle M, Nguyen B, Bresler M, Kim S, Milo B, Frank JA, Le NM, Song S, Zhou K, Nabi G, Huang Z, Ben-Ezra S, Rosen S, Mihcin S, Strehlow J, Karakitsios I, Le N, Schwenke M, Demedts D, Prentice P, Haase S, Preusser T, Melzer A, Mestas JL, Chettab K, Gomez GS, Dumontet C, Werle B, Lafon C, Marquet F, Bour P, Vaillant F, Amraoui S, Dubois R, Ritter P, Haïssaguerre M, Hocini M, Bernus O, Quesson B, Livneh A, Kimmel E, Adam D, Robin J, Arnal B, Fink M, Tanter M, Pernot M, Khokhlova TD, Schade GR, Wang YN, Kreider W, Simon J, Starr F, Karzova M, Maxwell A, Bailey MR, Khokhlova V, Lundt JE, Allen SP, Sukovich JR, Hall T, Xu Z, Schade GR, Wang YN, Khokhlova TD, May P, Lin DW, Bailey MR, Khokhlova V, Constans C, Deffieux T, Tanter M, Aubry JF, Park EJ, Ahn YD, Kang SY, Park DH, Lee JY, Vidal-Jove J, Perich E, Ruiz A, Jaen A, Eres N, del Castillo MA, Myers R, Kwan J, Coviello C, Rowe C, Crake C, Finn S, Jackson E, Carlisle R, Coussios C, Pouliopoulos A, Li C, Tinguely M, Tang MX, Garbin V, Choi JJ, Lyon PC, Mannaris C, Gray M, Folkes L, Stratford M, Carlisle R, Wu F, Middleton M, Gleeson F, Coussios C, Nwokeoha S, Carlisle R, Cleveland R, Wang YN, Khokhlova TD, Li T, Farr N, D’Andrea S, Starr F, Gravelle K, Chen H, Partanen A, Lee D, Hwang JH, Tardoski S, Ngo J, Gineyts E, Roux JP, Clézardin P, Melodelima D, Conti A, Magnin R, Gerstenmayer M, Lux F, Tillement O, Mériaux S, Penna SD, Romani GL, Dumont E, Larrat B, Sun T, Power C, Zhang YZ, Sutton J, Miller E, McDannold N, Sapozhnikov O, Tsysar S, Yuldashev PV, Khokhlova V, Svet V, Kreider W, Li D, Pellegrino A, Petrinic N, Siviour C, Jerusalem A, Cleveland R, Yuldashev PV, Karzova M, Cunitz BW, Dunmire B, Kreider W, Sapozhnikov O, Bailey MR, Khokhlova V, Inserra C, Guedra M, Mauger C, Gilles B, Solovchuk M, Sheu TWH, Thiriet M, Zhou Y, Neufeld E, Baumgartner C, Payne D, Kyriakou A, Kuster N, Xiao X, McLeod H, Melzer A, Dillon C, Rieke V, Ghanouni P, Parker DL, Payne A, Khokhova VA, Yuldashev PV, Sinilshchikov I, Andriyakhina Y, Khokhlova TD, Kreider W, Maxwell A, Sapozhnikov O, Partanen A, Rybyanets A, Shvetsova N, Berkovich A, Shvetsov I, Sapozhnikov O, Khokhlova V, Shaw CJ, Rivens I, Civale J, Giussani D, ter Haar G, Lees C, Bour P, Marquet F, Ozenne V, Toupin S, Quesson B, Dumont E, Ozhinsky E, Salgaonkar V, Diederich C, Rieke V, Kaye E, Monette S, Maybody M, Srimathveeravalli G, Solomon S, Gulati A, Preusser T, Haase S, Bezzi M, Jenne JW, Lango T, Levy Y, Müller M, Sat G, Tanner C, Zangos S, Günther M, Melzer A, Lafon C, Dinh AH, Niaf E, Bratan F, Guillen N, Souchon R, Lartizien C, Crouzet S, Rouviere O, Chapelon JY, Han Y, Wang S, Konofagou EE, Payen T, Palermo C, Sastra S, Chen H, Han Y, Olive K, Konofagou EE, van Breugel JM, de Greef M, Mougenot C, van den Bosch MA, Moonen C, Ries M, Gerstenmayer M, Magnin R, Fellah B, Le Bihan D, Larrat B, Gerstenmayer M, Magnin R, Mériaux S, Le Bihan D, Larrat B, Allen SP, Hernandez-Garcia L, Cain CA, Hall T, Lyka E, Elbes D, Coviello C, Cleveland R, Coussios C, Zhou K, Le NM, Li C, Huang Z, Tamano S, Jimbo H, Azuma T, Yoshizawa S, Fujiwara K, Itani K, Umemura SI, Damianou C, Yiannakou M, Ellens N, Partanen A, Stoianovici D, Farahani K, Zaini Z, Takagi R, Yoshizawa S, Umemura SI, Zong S, Shen G, Watkins R, Pascal-Tenorio A, Adams M, Plata JC, Salgaonkar V, Jones P, Butts-Pauly K, Diederich C, Bouley D, Rybyanets A, Ren G, Guo W, Shen G, Chen Y, Lin CY, Hsieh HY, Wei KC, Liu HL, Garnier C, Renault G, Farr N, Partanen A, Negussie AH, Mikhail A, Seifabadi R, Wilson E, Eranki A, Kim P, Wood B, Lübke D, Jenne JW, Huber P, Günther M, Lübke D, Georgii J, Schwenke M, Dresky CV, Haller J, Günther M, Preusser T, Jenne JW, Eranki A, Farr N, Partanen A, Yarmolenko P, Negussie AH, Sharma K, Celik H, Wood B, Kim P, Li G, Qiu W, Zheng H, Tsai MY, Chu PC, Liu HL, Webb T, Vyas U, Pauly KB, Walker M, Zhong J, Looi T, Waspe AC, Drake J, Hodaie M, Yang FY, Huang SL, Zur Y, Volovick A, Assif B, Aurup C, Kamimura H, Wang S, Chen H, Acosta C, Carneiro AA, Konofagou EE, Volovick A, Grinfeld J, Castel D, Rothlübbers S, Schwaab J, Tanner C, Mihcin S, Houston G, Günther M, Jenne JW, Ozhinsky E, Bucknor MD, Rieke V, Azhari H, Weiss N, Sosna J, Goldberg SN, Barrere V, Melodelima D, Jang KW, Burks SR, Kovacs ZI, Tu TW, Lewis B, Kim S, Nagle M, Jikaria N, Frank JA, Zhou Y, Wang X, Ahn YD, Park EJ, Park DH, Kang SY, Lee JY, Suomi V, Konofagou EE, Edwards D, Cleveland R, Larrabee Z, Eames M, Hananel A, Aubry JF, Rafaely B, Volovick A, Grinfeld J, Kimmel E, Debbiny RE, Dekel CZ, Assa M, Kimmel E, Menikou G, Damianou C, Mouratidis P, Rivens I, ter Haar G, Pineda-Pardo JA, de Pedro MDÁ, Martinez R, Hernandez F, Casas S, Oliver C, Pastor P, Vela L, Obeso J, Greillier P, Zorgani A, Souchon R, Melodelima D, Catheline S, Lafon C, Solovov V, Vozdvizhenskiy MO, Orlov AE, Wu CH, Sun MK, Shih TT, Chen WS, Prieur F, Pillon A, Mestas JL, Cartron V, Cebe P, Chansard N, Lafond M, Lafon C, Inserra C, Seya PM, Chen WS, Bera JC, Boissenot T, Larrat B, Fattal E, Bordat A, Chacun H, Guetin C, Tsapis N, Maruyama K, Unga J, Suzuki R, Fant C, Lafond M, Rogez B, Ngo J, Lafon C, Mestas JL, Afadzi M, Myhre OF, Vea S, Bjørkøy A, Yemane PT, van Wamel A, Berg S, Hansen R, Angelsen B, Davies C. International Society for Therapeutic Ultrasound Conference 2016. J Ther Ultrasound 2017. [PMCID: PMC5374646 DOI: 10.1186/s40349-016-0079-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
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Hussein S, Green A, Watane A, Reiter D, Chen X, Papadakis GZ, Wood B, Cypess A, Osman M, Bagci U. Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans. IEEE Trans Med Imaging 2017; 36:734-744. [PMID: 28114010 PMCID: PMC6421081 DOI: 10.1109/tmi.2016.2636188] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
In this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification of these tissues at the whole-body and body-region levels. We propose a patient-specific automatic adiposity analysis system with two modules. In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT). This process relies conventionally on manual or semi-automated segmentation, leading to inefficient solutions. Our novel framework addresses this challenge by proposing an unsupervised learning method to separate VAT from SAT in the abdominal region for the clinical quantification of central obesity. This step is followed by a context driven label fusion algorithm through sparse 3D Conditional Random Fields (CRF) for volumetric adiposity analysis. In the second module, we automatically detect, segment, and quantify brown adipose tissue (BAT) using PET scans because unlike WAT, BAT is metabolically active. After identifying BAT regions using PET, we perform a co-segmentation procedure utilizing asymmetric complementary information from PET and CT. Finally, we present a new probabilistic distance metric for differentiating BAT from non-BAT regions. Both modules are integrated via an automatic body-region detection unit based on one-shot learning. Experimental evaluations conducted on 151 PET/CT scans achieve state-of-the-art performances in both central obesity as well as brown adiposity quantification.
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Kalogeraki A, Lazopoulos G, Papadakis GZ, Tamiolakis D, Karvela-Kalogeraki I, Karvelas-Kalogerakis M, Segredakis J, Chalkiadakis GE. Cytology of Pericardial Effusion due to Malignancy. ACTA ACUST UNITED AC 2017; 54:179-183. [PMID: 27658166 DOI: 10.1515/rjim-2016-0026] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Indexed: 12/31/2022]
Abstract
BACKGROUND Malignant pericardial effusion occurs in one tenth of all cancers. It is a very serious disorder that is mainly a secondary process due to metastasis because primary neoplasms of the pericardium such as mesotheliomas, sarcomas being exceedingly rare [corrected]. Pericardial effusion specimens are uncommon and to the best of our knowledge the current study is the largest systematic evaluation of pericardial fluid cytology performed to date. MATERIAL AND METHODS Pericardial effusion specimens from 145 patients collected over a 25 [corrected] year period were studied by cytology [corrected]. The minimum pericardial fluid volume used for adequate cytologic diagnosis in these patients was more than 60 mL. RESULTS Cytological diagnosis revealed malignant pericardial exudates in 100% of the studied patients [corrected]. CONCLUSIONS Cytology provides an immediate and accurate means of diagnosis. Immunocytology is very important
in the diagnostic evaluation.
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Tirosh A, Lodish MB, Lyssikatos C, Belyavskaya E, Papadakis GZ, Stratakis CA. Circadian Plasma Cortisol Measurements Reflect Severity of Hypercortisolemia in Children with Different Etiologies of Endogenous Cushing Syndrome. Horm Res Paediatr 2017; 87:295-300. [PMID: 28433999 PMCID: PMC5506540 DOI: 10.1159/000464463] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Accepted: 02/21/2017] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND The utility of circadian cortisol variation in estimating the degree of hypercortisolemia in different forms of endogenous Cushing syndrome (CS) has not been evaluated in children yet. METHODS A retrospective cohort study, including children who underwent surgery due to CS (n = 115), was divided into children with a pituitary adenoma (Cushing disease) (n = 88), primary adrenal CS (n = 21), or ectopic adrenocorticotropin- or corticotropin-releasing hormone (ACTH-/CRH)-secreting tumors (n = 6). Circadian plasma cortisol measurements were obtained at 11: 30 p.m. and at midnight, and at 7: 30 and 8: 00 a.m. The ratios between the morning and late-night concentrations were calculated. RESULTS Plasma cortisol early-morning and midnight (AM/PM) ratios negatively correlated with 24-h urinary free cortisol (UFC) collections among the full study population and in each of the individual etiologies. Plasma ACTH concentrations positively correlated with plasma cortisol AM/PM ratios among patients with ACTH-independent CS. Finally, patients with primary pigmented nodular adrenocortical disease showed no correlation between UFC collections and the plasma cortisol AM/PM ratio, in contrast with other etiologies for primary adrenal CS, which showed a strong negative correlation between them. CONCLUSION Our study shows the association between the plasma cortisol AM/PM ratio and the degree of hypercortisolemia in children with CS.
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Affiliation(s)
- Amit Tirosh
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Maya B. Lodish
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Charalampos Lyssikatos
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Elena Belyavskaya
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Georgios Z. Papadakis
- Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Constantine A. Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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Karageorgiadis AS, Lyssikatos C, Belyavskaya E, Papadakis GZ, Patronas NJ, Lodish MB, Stratakis CA. Case 1: Poor Growth With Presence of a Pituitary Lesion in an 11-year-old Boy. Pediatr Rev 2017; 38:44-45. [PMID: 28044033 PMCID: PMC6343498 DOI: 10.1542/pir.2014-0135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Affiliation(s)
- Alexander S Karageorgiadis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.,Department of Pediatrics, Georgetown University Hospital, Washington, DC
| | - Charalampos Lyssikatos
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Elena Belyavskaya
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Georgios Z Papadakis
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Nicholas J Patronas
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Maya B Lodish
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
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Akbeyaz IH, Tirosh A, Robinson C, Broadney MM, Papadakis GZ, Belyavskaya E, Lyssikatos C, Lodish MB, Stratakis CA. Spontaneously Resolving Hyperreninemic Hypertension Caused by Accessory Renal Artery Stenosis in a 13-Year-Old Girl: A Case Report. J Clin Hypertens (Greenwich) 2017; 19:100-102. [PMID: 27528003 PMCID: PMC6341473 DOI: 10.1111/jch.12893] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 07/04/2016] [Indexed: 11/28/2022]
Abstract
The authors describe the clinical investigation and progress of a 13-year-old girl diagnosed with hypertension 4 years prior to her admission. A thorough history was taken and physical examination performed. Laboratory analysis and relevant radiological evaluation were obtained in order to determine the etiology for suspected secondary hypertension, and later to differentiate between the possible causes of hyperreninemic hypertension. The patient had an accessory left renal artery, presumptively leading to renin secretion by the underperfused kidney. The patient was treated medically with spontaneous resolution of her hypertension and near normalization of plasma renin activity. On repeat imaging, the artery was not demonstrated. The authors concluded that the diagnosis of hyperreninemic hypertension in young ages should prompt investigation for the etiology. However, cautious observation is a valid option that might lead to spontaneous resolution.
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Affiliation(s)
- Ismail Hakki Akbeyaz
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
- Istanbul Dr. Lutfi Kırdar Kartal Eğitim ve Araştırma HastanesiIstanbulTurkey
| | - Amit Tirosh
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Cemre Robinson
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Miranda M. Broadney
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Georgios Z. Papadakis
- Radiology and Imaging SciencesWarren Grant Magnuson Clinical CenterNational Institutes of HealthBethesdaMD
| | - Elena Belyavskaya
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Charalampos Lyssikatos
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Maya B. Lodish
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Constantine A. Stratakis
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
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Papadakis GZ, Holland SM, Quezado M, Patronas NJ. Adrenal cryptococcosis in an immunosuppressed patient showing intensely increased metabolic activity on 18F-FDG PET/CT. Endocrine 2016; 54:834-836. [PMID: 27473097 PMCID: PMC5107323 DOI: 10.1007/s12020-016-1040-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 06/24/2016] [Indexed: 12/17/2022]
Abstract
Disseminated cryptococcosis most commonly occurs in immunosuppressed patients and can rarely affect the adrenal glands. We report on a patient with biopsy proven bilateral adrenal cryptococcosis resulting in primary adrenal insufficiency, which was evaluated with whole-body positron emission tomography/computed tomography scan using 18F-FDG. Both enlarged adrenal glands presented intensely increased 18F-FDG activity in the periphery, while central necrotic regions were photopenic. Although diagnosis was established by adrenal gland biopsy, 18F-FDG positron emission tomography/computed tomography scan can significantly contribute to the assessment of disease activity and monitoring of treatment response. Furthermore, fungal infections should always be considered when encountering hypermetabolic adrenal masses, especially in the setting of immunodeficient patients.
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Affiliation(s)
- Georgios Z Papadakis
- Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center (CC), National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Steven M Holland
- Immunopathogenesis Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Martha Quezado
- Department of Pathology, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Nicholas J Patronas
- Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center (CC), National Institutes of Health (NIH), Bethesda, MD, 20892, USA.
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Papadakis GZ, Millo C, Stratakis CA. Benign hormone-secreting adenoma within a larger adrenocortical mass showing intensely increased activity on 18F-FDG PET/CT. Endocrine 2016; 54:269-270. [PMID: 27154873 PMCID: PMC5071121 DOI: 10.1007/s12020-016-0969-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Accepted: 04/20/2016] [Indexed: 11/30/2022]
Abstract
Adrenal adenomas usually show 18F-FDG activity less than that of the liver parenchyma. However, lipid-poor and hormone-secreting adenomas have been reported to show mild 18F-FDG avidity. We report on a 51-year-old female with clinical symptoms of hypercortisolemia and a large right adrenal mass detected on CT. Post-contrast CT images showed an enhancing focus in the lower pole of the mass, with corresponding markedly increased activity on 18F-FDG PET/CT. Right adrenalectomy was performed and histology revealed a benign adenoma, indicating that functioning benign adenomas can show intensely increased metabolic activity on 18F-FDG mimicking malignancy.
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Affiliation(s)
- Georgios Z Papadakis
- Radiology and Imaging Sciences, Warren Grant Magnuson Clinical Center (CC), National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Corina Millo
- Division of Nuclear Medicine, RAD&IS; Clinical Center, National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver, National Institute of Child Health and Human Development, Building 10, CRC, Room 1-3330, MSC1103, Bethesda, MD, 20892, USA.
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