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Review Articles
Obesity and Metabolism
Neurocognitive Changes and Their Neural Correlates in Patients with Type 2 Diabetes Mellitus
Junghyun H Lee, Yera Choi, Chansoo Jun, Young Sun Hong, Han Byul Cho, Jieun E Kim, In Kyoon Lyoo
Endocrinol Metab. 2014;29(2):112-121.   Published online June 26, 2014
DOI: https://doi.org/10.3803/EnM.2014.29.2.112
  • 4,806 View
  • 49 Download
  • 34 Web of Science
  • 31 Crossref
AbstractAbstract PDFPubReader   

As the prevalence and life expectancy of type 2 diabetes mellitus (T2DM) continue to increase, the importance of effective detection and intervention for the complications of T2DM, especially neurocognitive complications including cognitive dysfunction and dementia, is receiving greater attention. T2DM is thought to influence cognitive function through an as yet unclear mechanism that involves multiple factors such as hyperglycemia, hypoglycemia, and vascular disease. Recent developments in neuroimaging methods have led to the identification of potential neural correlates of T2DM-related neurocognitive changes, which extend from structural to functional and metabolite alterations in the brain. The evidence indicates various changes in the T2DM brain, including global and regional atrophy, white matter hyperintensity, altered functional connectivity, and changes in neurometabolite levels. Continued neuroimaging research is expected to further elucidate the underpinnings of cognitive decline in T2DM and allow better diagnosis and treatment of the condition.

Citations

Citations to this article as recorded by  
  • The level of serum retinol-binding protein is associated with diabetic mild cognitive impairment
    Wenjie Zhang, Yuqi Yuan, Xiaoxia Cui, Shihong Chen, Xianghua Zhuang
    Brain Research.2024; 1822: 148670.     CrossRef
  • Research Progress on Lipocalin-2 in Diabetic Encephalopathy
    Wenjie Zhang, Shihong Chen, Xianghua Zhuang
    Neuroscience.2023; 515: 74.     CrossRef
  • Voluntary Attention and Quality of Life in Patients With Type 1 and Type 2 Diabetes Mellitus: Differences in Changes Depending on Disease Type and Duration
    N. E. Tadevosyan, A. S. Khachunts, M. Gohargani, A. A. Sahakyan, A. A. Tumanyan
    Journal of Evolutionary Biochemistry and Physiology.2022; 58(2): 569.     CrossRef
  • Modifiable risk factors for neurocognitive and psychosocial problems after Hodgkin lymphoma
    AnnaLynn M. Williams, Sedigheh Mirzaei Salehabadi, Mengqi Xing, Nicholas S. Phillips, Matthew J. Ehrhardt, Rebecca Howell, Yutaka Yasui, Kevin C. Oeffinger, Todd Gibson, Eric J. Chow, Wendy Leisenring, Deokumar Srivastava, Melissa M. Hudson, Leslie L. Rob
    Blood.2022; 139(20): 3073.     CrossRef
  • Type 2 Diabetes Independent of Glycemic Control is Associated With Cognitive Impairments: Findings From NHANES
    Rozmin Jiwani, Brittany Dennis, Alfonso L. Neri, Chandler Bess, Sara Espinoza, Jing Wang, Monica C. Serra
    Clinical Nursing Research.2022; 31(7): 1225.     CrossRef
  • Diabetes and associated cognitive disorders: Role of the Hypothalamic-Pituitary Adrenal axis
    Nathalie Marissal-Arvy, Marie-Pierre Moisan
    Metabolism Open.2022; 15: 100202.     CrossRef
  • Inside the diabetic brain: Insulin resistance and molecular mechanism associated with cognitive impairment and its possible therapeutic strategies
    Bhaskar Jyoti Dutta, Shamsher Singh, Sanket Seksaria, Ghanshyam Das Gupta, Amrita Singh
    Pharmacological Research.2022; 182: 106358.     CrossRef
  • The role of LRP1 in Aβ efflux transport across the blood-brain barrier and cognitive dysfunction in diabetes mellitus
    Xue P, Long Zz, Jiang Gg, Wang Lp, Bian Cm, Wang Yl, M.F. Chen, Li W
    Neurochemistry International.2022; 160: 105417.     CrossRef
  • Childhood Neurotoxicity and Brain Resilience to Adverse Events during Adulthood
    AnnaLynn M. Williams, Yin Ting Cheung, Geehong Hyun, Wei Liu, Kirsten K. Ness, Matthew J. Ehrhardt, Daniel A. Mulrooney, Nickhill Bhakta, Pia Banerjee, Tara M. Brinkman, Daniel M. Green, Wassim Chemaitilly, I‐Chan Huang, Deokumar Srivastava, Melissa M. Hu
    Annals of Neurology.2021; 89(3): 534.     CrossRef
  • Metformin restores hippocampal neurogenesis and learning and memory via regulating gut microbiota in the obese mouse model
    Xiaoyi Ma, Wenchang Xiao, Hao Li, Pei Pang, Feixiao Xue, Lu Wan, Lei Pei, Huanhuan Yan
    Brain, Behavior, and Immunity.2021; 95: 68.     CrossRef
  • Promoting Successful Cognitive Aging: A Ten-Year Update
    Taylor J. Krivanek, Seth A. Gale, Brittany M. McFeeley, Casey M. Nicastri, Kirk R. Daffner
    Journal of Alzheimer's Disease.2021; 81(3): 871.     CrossRef
  • Association of Vitamin D Level and Nerve Conduction Study Parameters with Cognitive Function in Diabetic Neuropathy Patients
    Aida Fithrie, Fasihah Irfani Fitri, Muhammad Reza Putra
    Open Access Macedonian Journal of Medical Sciences.2021; 9(B): 72.     CrossRef
  • Insulin resistance takes center stage: a new paradigm in the progression of bipolar disorder
    Cynthia V. Calkin
    Annals of Medicine.2019; 51(5-6): 281.     CrossRef
  • Vitamin D Supplementation and Cognition in People with Type 2 Diabetes: A Randomized Control Trial
    Mary A. Byrn, William Adams, Sue Penckofer, Mary Ann Emanuele
    Journal of Diabetes Research.2019; 2019: 1.     CrossRef
  • Neurocognitive impairment in type 2 diabetes mellitus
    Marianna Karvani, P. Simos, S. Stavrakaki, D. Kapoukranidou
    Hormones.2019; 18(4): 523.     CrossRef
  • Benefits of combination low-dose pioglitazone plus fish oil on aged type 2 diabetes mice
    Yuzuru Iizuka, Hyounju Kim, Satoshi Hirako, Kanako Chiba, Masahiro Wada, Akiyo Matsumoto
    Journal of Food and Drug Analysis.2018; 26(4): 1265.     CrossRef
  • Association of ApoE Genetic Polymorphism and Type 2 Diabetes with Cognition in Non-Demented Aging Chinese Adults: A Community Based Cross-Sectional Study
    Jie Zhen, Tong Lin, Xiaochen Huang, Huiqiang Zhang, Shengqi Dong, Yifan Wu, Linlin Song, Rong Xiao, Linhong Yuan
    Aging and disease.2018; 9(3): 346.     CrossRef
  • Chronic Health Conditions and Neurocognitive Function in Aging Survivors of Childhood Cancer: A Report from the Childhood Cancer Survivor Study
    Yin Ting Cheung, Tara M Brinkman, Chenghong Li, Yasmin Mzayek, Deokumar Srivastava, Kirsten K Ness, Sunita K Patel, Rebecca M Howell, Kevin C Oeffinger, Leslie L Robison, Gregory T Armstrong, Kevin R Krull
    JNCI: Journal of the National Cancer Institute.2018; 110(4): 411.     CrossRef
  • Diabetes, Depression, and Cognition: a Recursive Cycle of Cognitive Dysfunction and Glycemic Dysregulation
    Sheila Black, Kyle Kraemer, Avani Shah, Gaynell Simpson, Forrest Scogin, Annie Smith
    Current Diabetes Reports.2018;[Epub]     CrossRef
  • Hypoglycemia is associated with dementia in elderly patients with type 2 diabetes mellitus: An analysis based on the Korea National Diabetes Program Cohort
    Sang Ouk Chin, Sang Youl Rhee, Suk Chon, Sei Hyun Baik, Yongsoo Park, Moon Suk Nam, Kwan Woo Lee, Ki Hong Chun, Jeong-taek Woo, Young Seol Kim
    Diabetes Research and Clinical Practice.2016; 122: 54.     CrossRef
  • Bipolar disorders, type 2 diabetes mellitus, and the brain
    Tomas Hajek, Roger McIntyre, Martin Alda
    Current Opinion in Psychiatry.2016; 29(1): 1.     CrossRef
  • 1,5-Anhydro-D-Glucitol Could Reflect Hypoglycemia Risk in Patients with Type 2 Diabetes Receiving Insulin Therapy
    Min Kyeong Kim, Hye Seung Jung, Soo Heon Kwak, Young Min Cho, Kyong Soo Park, Seong Yeon Kim
    Endocrinology and Metabolism.2016; 31(2): 284.     CrossRef
  • Insulin in the nervous system and the mind: Functions in metabolism, memory, and mood
    Seung-Hwan Lee, Janice M. Zabolotny, Hu Huang, Hyon Lee, Young-Bum Kim
    Molecular Metabolism.2016; 5(8): 589.     CrossRef
  • Toll-like receptor 2 and type 2 diabetes
    Zahra Sepehri, Zohre Kiani, Ali Akbar Nasiri, Farhad Kohan
    Cellular & Molecular Biology Letters.2016;[Epub]     CrossRef
  • Long-term Variability in Glycemic Control Is Associated With White Matter Hyperintensities in APOE4 Genotype Carriers With Type 2 Diabetes
    Abigail Livny, Ramit Ravona-Springer, Anthony Heymann, Rachel Priess, Tammar Kushnir, Galia Tsarfaty, Leeron Rabinov, Reut Moran, Hadass Hoffman, Itzik Cooper, Lior Greenbaum, Jeremy Silverman, Mary Sano, Sterling C. Johnson, Barbara B. Bendlin, Michal Sc
    Diabetes Care.2016; 39(6): 1056.     CrossRef
  • DIABETES MELLITUS Y SU ASOCIACIÓN CON DETERIORO COGNITIVO Y DEMENCIA
    Gonzalo Muñoz A., Christina Degen, Johannes Schröder, Pablo Toro E.
    Revista Médica Clínica Las Condes.2016; 27(2): 266.     CrossRef
  • Blood electrolyte disturbances during severe hypoglycemia in Korean patients with type 2 diabetes
    Mi Yeon Kang
    The Korean Journal of Internal Medicine.2015; 30(5): 648.     CrossRef
  • Whenever You Lose Connection, Take Intranasal Insulin?
    Antje Gottschalk, Björn Ellger
    Diabetes.2015; 64(3): 687.     CrossRef
  • Spatial Patterns of Structural Brain Changes in Type 2 Diabetic Patients and Their Longitudinal Progression With Intensive Control of Blood Glucose
    Guray Erus, Harsha Battapady, Tianhao Zhang, James Lovato, Michael E. Miller, Jeff D. Williamson, Lenore J. Launer, R. Nick Bryan, Christos Davatzikos
    Diabetes Care.2015; 38(1): 97.     CrossRef
  • Articles in 'Endocrinology and Metabolism' in 2014
    Won-Young Lee
    Endocrinology and Metabolism.2015; 30(1): 47.     CrossRef
  • Cerebrolysin reverses hippocampal neural atrophy in a mice model of diabetes mellitus type 1
    Lizzette Sanchez‐Vega, Ismael Juárez, Maria De Jesus Gomez‐Villalobos, Gonzalo Flores
    Synapse.2015; 69(6): 326.     CrossRef
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Adrenal gland
Differential Diagnosis of Adrenal Mass Using Imaging Modality: Special Emphasis on F-18 Fluoro-2-Deoxy-D-Glucose Positron Emission Tomography/Computed Tomography
Hong Je Lee, Jaetae Lee
Endocrinol Metab. 2014;29(1):5-11.   Published online March 14, 2014
DOI: https://doi.org/10.3803/EnM.2014.29.1.5
  • 4,106 View
  • 30 Download
  • 7 Web of Science
  • 6 Crossref
AbstractAbstract PDFPubReader   

Adrenal incidentalomas are adrenal masses serendipitously detected during an imaging study performed for reasons unrelated to suspicion of adrenal disease. The incidence of adrenal incidentalomas has increased because of the widespread use of various imaging modalities. In oncology patients with adrenal incidentalomas, the characterization of the adrenal masses is challenging because nearly 50% of incidental adrenal masses are metastatic lesions that need special medical attention. Although unenhanced computed tomography (CT) densitometry, chemical shift magnetic resonance imaging (MRI), delayed contrast-enhanced CT and CT histogram analysis have been used as sensitive and specific modalities for differentiating benign from malignant adrenal masses, F-18 fluoro-2-deoxy-D-glucose positron emission tomography (F-18 FDG PET)/CT is a highly accurate imaging modality compared to CT or MRI, especially when these two imaging modalities are combined. In addition, a semiquantitative analysis using standardized uptake value ratio further improves the diagnostic accuracy of F-18 FDG PET/CT in differentiating benign from malignant adrenal masses. Thus, F-18 FDG PET/CT is very helpful for determining the best therapeutic management, especially for assessing the need for surgery.

Citations

Citations to this article as recorded by  
  • The F-18 FDG PET/CT evaluation of the metastatic adrenal lesions of the non-lung cancer tumors compared with pathology results
    Zehra Pınar Koç, Pınar Pelin Özcan, Emel Sezer, Kadir Eser, Tuba Kara
    Egyptian Journal of Radiology and Nuclear Medicine.2022;[Epub]     CrossRef
  • Dual time point [18F]Flurodeoxyglucose (FDG) Positron Emission Tomography (PET)/Computed Tomography (CT) with water gastric distension in differentiation between malignant and benign gastric lesions
    Hussein Farghaly, Mohamed Alshareef, Abdullah Alqarni, Mohamed Sayed, Hatem Nasr
    European Journal of Radiology Open.2020; 7: 100268.     CrossRef
  • 18F-FDG PET/CT Imaging of Adrenal Liposarcoma
    Rang Wang, Qiuping Fan, Rong Tian
    Clinical Nuclear Medicine.2020; 45(7): 570.     CrossRef
  • Characterization of adrenocortical tumors by 18F-FDG PET/CT: Does steroid hormone hypersecretion status modify the uptake pattern?
    Nunzia Cinzia Paladino, Carole Guérin, Aoïfe Lowery, Andrea Attard, Wassim Essamet, Eveline Slotema, Isabelle Morange, Frédéric Castinetti, Thierry Brue, Anderson Loundou, David Taïeb, Frédéric Sebag
    Surgical Oncology.2018; 27(2): 231.     CrossRef
  • Articles in 'Endocrinology and Metabolism' in 2014
    Won-Young Lee
    Endocrinology and Metabolism.2015; 30(1): 47.     CrossRef
  • Adrenal masses in oncology patients
    Rodney H Reznek
    Cancer Imaging.2014;[Epub]     CrossRef
Close layer
Original Article
Correlation between Pituitary Insufficiency and Magnetic Resonance Imaging Finding in Non-Functioning Pituitary Adenomas.
Hyun Min Kim, Cheol Ryong Ku, Eun Young Lee, Woo Kyung Lee, Jung Soo Lim, Sena Hwang, Mi Jung Lee, Seung Ku Lee, Sun Ho Kim, Eun Jig Lee
Endocrinol Metab. 2010;25(4):310-315.   Published online December 1, 2010
DOI: https://doi.org/10.3803/EnM.2010.25.4.310
  • 2,058 View
  • 28 Download
  • 1 Crossref
AbstractAbstract PDF
BACKGROUND
Non-functioning pituitary adenomas (NFPAs) are characterized by the absence of clinical and biochemical evidence of pituitary hormone hypersecretion, and these tumors constitute approximately one third of all the tumors of the anterior pituitary. Recently, hormonal deficiencies have gradually evolved to become the leading presenting signs and symptoms in patients with NFPAs. We investigated pituitary hormonal insufficiencies according to the magnetic resonance imaging (MRI) findings in patients with NFPA. METHODS: We evaluated the patients who were newly diagnosed with NFPA from 1997 through 2009. Among them, we analyzed 387 patients who were tested for their combined pituitary function and who underwent MRI. The severity of the hypopituitarism was determined by the number of deficient axes of the pituitary hormones. On the MRI study, the maximal diameter of the tumor, Hardy's classification, the thickness of the pituitary gland and the presence of stalk compression were evaluated. RESULTS: The mean age was 46.85 +/- 12.93 years (range: 15-86) and 186 patients (48.1%) were male. As assessed on MRI, the tumor diameter was 27.87 +/- 9.93 mm, the thickness of the normal pituitary gland was 1.42 +/- 2.07 mm and stalk compression was observed in 201 patients (51.9%). Hypopituitarism was observed in 333 patients (86.0%). Deficiency for each pituitary hormone was most severe in the patients with Hardy type IIIA. Hypopituitarism was severe in the older age patients (P = 0.001) and the patients with a bigger tumor size (P < 0.001) and the presence of stalk compression (P < 0.001). However, the patients who had a thicker pituitary gland showed less severe hypopituitarism (P < 0.001). Multivariate analysis showed that age, tumor diameter and the thickness of pituitary gland were important determinants for pituitary deficiency (P = 0.004, P < 0.001, P = 0.022, respectively). CONCLUSION: The results suggest that the hormonal deficiencies in patient with NFPA were correlated with the MRI findings, and especially the tumor diameter and preservation of the pituitary gland.

Citations

Citations to this article as recorded by  
  • Clinical Parameters to Distinguish Silent Corticotroph Adenomas from Other Nonfunctioning Pituitary Adenomas
    Daham Kim, Cheol Ryong Ku, Se Hee Park, Ju Hyung Moon, Eui Hyun Kim, Sun Ho Kim, Eun Jig Lee
    World Neurosurgery.2018; 115: e464.     CrossRef
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