Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Medical Imaging
  4. Volume 20, Issue 1
  5. Article
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
file format pdf download PDF
side by side viewer icon HTML

Abstract

Objectives:

This study aimed to investigate the pancreatic morphology and clinical characteristics to predict risk factors of type 2 diabetes mellitus (T2DM) based on magnetic resonance imaging.

Methods:

A total of 89 patients (T2DM group) and 68 healthy controls (HC group) were included. The T2DM group was divided into a long-term T2DM group and a short-term T2DM group according to whether the illness duration was more than 5 years. The clinical characteristics were collected, including sex, age, fasting plasma glucose, glycosylated hemoglobin, and lipoproteins. The pancreatic morphological characteristics, including the diameters of the pancreatic head, neck, body, and tail, the angle of the pancreaticobiliary junction (APJ), and the types of pancreaticobiliary junction were measured. The risk prediction model was established by logistic regression analysis.

Results:

In the long-term T2DM group, the pancreatic diameters were smaller than the other two groups. In the short-term T2DM group, the diameters of the pancreatic tail and body were smaller than the HC group. The APJ, very low-density lipoprotein, and triglyceride levels in the two T2DM groups were greater than the HC group, and the APJ of the short-term T2DM group was smaller than the long-term T2DM group. Pancreatic diameters showed a negative correlation with illness duration. Logistic regression analysis revealed pancreatic body diameter was a protective factor, and APJ was a risk factor for T2DM. Prediction model accuracy was 90.20%.

Conclusions:

The morphology of the pancreas is helpful to predict the risk of the onset of T2DM. The risk of onset of T2DM increases with smaller pancreatic body diameter and higher APJ.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Loading

Article metrics loading...

/content/journals/cmir/10.2174/0115734056304038240515101952
2024-06-13
2025-06-16

  • From This Site

    /content/journals/cmir/10.2174/0115734056304038240515101952
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
The full text of this item is not currently available.

References

  1. ZhuangM. RaoL. ChenY. XiaoS. XiaH. YangJ. LvX. QinD. ZhuC. Controlled SPION-exosomes loaded with quercetin preserves pancreatic beta cell survival and function in type 2 diabetes mellitus.Int. J. Nanomedicine2023185733574810.2147/IJN.S42241637849640
     [Google Scholar]
  2. SunH. SaeediP. KarurangaS. PinkepankM. OgurtsovaK. DuncanB.B. SteinC. BasitA. ChanJ.C.N. MbanyaJ.C. PavkovM.E. RamachandaranA. WildS.H. JamesS. HermanW.H. ZhangP. BommerC. KuoS. BoykoE.J. MaglianoD.J. IDF diabetes atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045.Diabetes Res. Clin. Pract.202218310911910.1016/j.diabres.2021.10911934879977
     [Google Scholar]
  3. Otero SanchezL. ChenY. LassaillyG. Exploring the links between types 2 diabetes and liver-related complications: A comprehensive review.United European Gastroenterol. J.202312224025138103189
     [Google Scholar]
  4. LiJ. YangG. ZhangQ. LiuZ. JiangX. XinY. Function of Akkermansia muciniphila in type 2 diabetes and related diseases.Front. Microbiol.202314117240010.3389/fmicb.2023.117240037396381
     [Google Scholar]
  5. WangL. PengW. ZhaoZ. ZhangM. ShiZ. SongZ. ZhangX. LiC. HuangZ. SunX. WangL. ZhouM. WuJ. WangY. Prevalence and treatment of diabetes in China, 2013-2018.JAMA2021326242498250610.1001/jama.2021.2220834962526
     [Google Scholar]
  6. Echouffo-TcheuguiJ.B. PerreaultL. JiL. Dagogo-JackS. Diagnosis and management of prediabetes.JAMA2023329141206121610.1001/jama.2023.406337039787
     [Google Scholar]
  7. ZhangK. YangC. ZhouX. LiangJ. GuoJ. LiM. ZhangY. ShaoS. SunP. LiK. HuangJ. ChenF. LiangX. SuD. TRIM21 ameliorates hepatic glucose and lipid metabolic disorders in type 2 diabetes mellitus by ubiquitination of PEPCK1 and FASN.Cell. Mol. Life Sci.202380616810.1007/s00018‑023‑04820‑w37249651
     [Google Scholar]
  8. OteroA. BecerrilS. MartínM. CienfuegosJ.A. ValentíV. MoncadaR. CatalánV. Gómez-AmbrosiJ. BurrellM.A. FrühbeckG. RodríguezA. Effect of guanylin peptides on pancreas steatosis and function in experimental diet-induced obesity and after bariatric surgery.Front. Endocrinol.202314118545610.3389/fendo.2023.118545637274331
     [Google Scholar]
  9. LiuC. LiY. GuanT. LaiY. ShenY. ZeyaweidingA. ZhaoH. LiF. MaimaitiT. ACE2 polymorphisms associated with cardiovascular risk in Uygurs with type 2 diabetes mellitus.Cardiovasc. Diabetol.201817112710.1186/s12933‑018‑0771‑330227878
     [Google Scholar]
  10. SunS. TaoS. XiX. JiangT. ZhuQ. ZhouY. LiH. Analysis of the predictive value of the geriatric nutritional risk index for osteoporosis in elderly patients with T2DM: A single-center retrospective study.J. Orthop. Surg. Res.202318176010.1186/s13018‑023‑04237‑y37805606
     [Google Scholar]
  11. WangL. WangZ.H. LiuL.P. Value of Hcy combined with Framingham score for predicting macrovascular disease in elderly patients with type 2 diabetes.Medicine202310240e3540110.1097/MD.000000000003540137800767
     [Google Scholar]
  12. BlotG. KaradayiR. PrzegralekL. SartorisT.M. Charles-MessanceH. AugustinS. NegrierP. BlondF. Muñiz-RuvalcabaF.P. Rivera-de la ParraD. VignaudL. CouturierA. SahelJ.A. AcarN. Jimenez-CoronaA. DelarasseC. GarfiasY. SennlaubF. GuillonneauX. Perilipin 2–positive mononuclear phagocytes accumulate in the diabetic retina and promote PPARγ-dependent vasodegeneration.J. Clin. Invest.202313319e16134810.1172/JCI16134837781924
     [Google Scholar]
  13. ChaudharyR. LikidlilidA. PeerapatditT. TresukosolD. SrisumaS. RatanamaneechatS. SriratanasathavornC. Apolipoprotein E gene polymorphism: Effects on plasma lipids and risk of type 2 diabetes and coronary artery disease.Cardiovasc. Diabetol.20121113610.1186/1475‑2840‑11‑3622520940
     [Google Scholar]
  14. MénégautL. LaubrietA. CrespyV. LeleuD. PilotT. Van DongenK. de BarrosJ.P.P. GautierT. PetitJ.M. ThomasC. NguyenM. SteinmetzE. MassonD. Inflammation and oxidative stress markers in type 2 diabetes patients with advanced carotid atherosclerosis.Cardiovasc. Diabetol.202322124810.1186/s12933‑023‑01979‑137710315
     [Google Scholar]
  15. ManoharS.M. VaikasuvuS.R. DeepthiK. SachanA. NarasimhaS.R. An association of hyperglycemia with plasma malondialdehyde and atherogenic lipid risk factors in newly diagnosed Type 2 diabetic patients.J. Res. Med. Sci.2013182899323914207
     [Google Scholar]
  16. TenenbaumA. KlempfnerR. FismanE.Z. Hypertriglyceridemia: A too long unfairly neglected major cardiovascular risk factor.Cardiovasc. Diabetol.201413115910.1186/s12933‑014‑0159‑y25471221
     [Google Scholar]
  17. MartínezM.S. ManzanoA. OlivarL.C. NavaM. SalazarJ. D’MarcoL. OrtizR. ChacínM. Guerrero-WyssM. Cabrera de BravoM. CanoC. BermúdezV. AngaritaL. The role of the α cell in the pathogenesis of diabetes: A world beyond the mirror.Int. J. Mol. Sci.20212217950410.3390/ijms2217950434502413
     [Google Scholar]
  18. SaishoY. β-cell dysfunction: Its critical role in prevention and management of type 2 diabetes.World J. Diabetes20156110912410.4239/wjd.v6.i1.10925685282
     [Google Scholar]
  19. YiJ. XuF. LiT. LiangB. LiS. FengQ. LongL. Quantitative study of 3T MRI qDixon-WIP applied in pancreatic fat infiltration in patients with type 2 diabetes mellitus.Front. Endocrinol.202314114011110.3389/fendo.2023.114011136875489
     [Google Scholar]
  20. MacauleyM. PercivalK. ThelwallP.E. HollingsworthK.G. TaylorR. Altered volume, morphology and composition of the pancreas in type 2 diabetes.PLoS One2015105e012682510.1371/journal.pone.012682525950180
     [Google Scholar]
  21. SilvaM.E.R. VezozzoD.P. UrsichM.J.M. RochaD.M. CerriG.G. WajchenbergB.L. Ultrasonographic abnormalities of the pancreas in IDDM and NIDDM patients.Diabetes Care19931691296129710.2337/diacare.16.9.12968404436
     [Google Scholar]
  22. WangL. JiaH. LinG. ZhengS. Magnetic resonance imaging investigation of age-related morphological changes in the pancreases of 226 Chinese.Aging Med.20214429730310.1002/agm2.1218534964011
     [Google Scholar]
  23. SherifiF. BexhetiS. GashiZ. BajraktariI. ShatriJ. LahuA. Anatomic variations of pancreaticobiliary union.Open Access Maced. J. Med. Sci.20186698899110.3889/oamjms.2018.19629983789
     [Google Scholar]
  24. LiuN. HuangX.H. ZhangX.M. DongG.L. JingZ.L. GaoC.L. TangM.Y. The angle of pancreaticobiliary junction correlates with acute pancreatitis: A magnetic resonance cholangiopancreatography study.Quant. Imaging Med. Surg.20155340140626029643
     [Google Scholar]
  25. YangQ. ZhangR. GaoY. ZhouC. KongW. TaoW. ZhangG. ShangL. Computed tomography findings in patients with pulmonary tuberculosis and diabetes at an infectious disease hospital in China: A retrospective cross-sectional study.BMC Infect. Dis.202323143610.1186/s12879‑023‑08386‑737370020
     [Google Scholar]
  26. KoJ. Skudder-HillL. PriyaS. KimitaW. BharmalS.H. PetrovM.S. Associations between intra-pancreatic fat deposition, pancreas size, and pancreatic enzymes in health and after an attack of acute pancreatitis.Obes. Facts2022151708210.1159/00051962134753126
     [Google Scholar]
  27. PaudelS. ChaudharyB. RegmiP.R. KayasthaP. MaharjanS. AdhikariG. Abnormal anatomic variation of pancreaticobiliary union in magnetic resonance cholangiopancreatography department of radiology and imaging in a tertiary care centre: A descriptive cross-sectional study.JNMA J. Nepal Med. Assoc.202361257434610.31729/jnma.794437203918
     [Google Scholar]
  28. HaoZ. HuangX. LiuX. HeF. ShaoH. Association analysis between different diabetic family history and gender with diagnosed age of type 2 diabetes mellitus: A cross-sectional study in tianjin, China.Inquiry20225910.1177/0046958022108636435348394
     [Google Scholar]
  29. LuJ. GuoM. WangH. PanH. WangL. YuX. ZhangX. Association between pancreatic atrophy and loss of insulin secretory capacity in patients with type 2 diabetes mellitus.J. Diabetes Res.201920191610.1155/2019/637123131467928
     [Google Scholar]
  30. TurnerR.C. CullC.A. FrighiV. HolmanR.R. UK Prospective Diabetes Study (UKPDS) Group Glycemic control with diet, sulfonylurea, metformin, or insulin in patients with type 2 diabetes mellitus: Progressive requirement for multiple therapies (UKPDS 49).JAMA1999281212005201210.1001/jama.281.21.200510359389
     [Google Scholar]
  31. WangX. LongD. HuX. GuoN. Gentiopicroside modulates glucose homeostasis in high-fat-diet and streptozotocin-induced type 2 diabetic mice.Front. Pharmacol.202314117236010.3389/fphar.2023.117236037601073
     [Google Scholar]
  32. InaishiJ. SaishoY. Beta-cell mass in obesity and type 2 diabetes, and its relation to pancreas fat: A mini-review.Nutrients20201212384610.3390/nu1212384633339276
     [Google Scholar]
  33. YangT. LiuY. LiL. ZhengY. WangY. SuJ. YangR. LuoM. YuC. Correlation between the triglyceride-to-high-density lipoprotein cholesterol ratio and other unconventional lipid parameters with the risk of prediabetes and Type 2 diabetes in patients with coronary heart disease: A RCSCD-TCM study in China.Cardiovasc. Diabetol.20222119310.1186/s12933‑022‑01531‑735659300
     [Google Scholar]
  34. IwaiM. YoshinoG. MatsushitaM. MoritaM. MatsubaK. KazumiT. BabaS. Abnormal lipoprotein composition in normolipidemic diabetic patients.Diabetes Care199013779279610.2337/diacare.13.7.7922201502
     [Google Scholar]
  35. AliduH. DapareP.P.M. QuayeL. AmiduN. BaniS.B. BanyehM. Insulin resistance in relation to hypertension and dyslipidaemia among men clinically diagnosed with type 2 diabetes.BioMed Res. Int.2023202311010.1155/2023/887322637274075
     [Google Scholar]
  36. BenerA. OzdenkayaY. Al-HamaqA.O.A.A. BarisikC.C. OzturkM. Low vitamin D deficiency associated with thyroid disease among type 2 diabetic mellitus patients.J. Clin. Med. Res.201810970771410.14740/jocmr3507w30116441
     [Google Scholar]
  37. NiY.H. SongL.J. XiaoB. Magnetic resonance imaging for acute pancreatitis in type 2 diabetes patients.World J. Clin. Cases202311307268727610.12998/wjcc.v11.i30.726837969447
     [Google Scholar]
  38. ZhongS. DuQ. LiuN. ChenY. YangT. QinS. JiangY. HuangX. Developing a CT-based radiomics nomogram for predicting post-acute pancreatitis diabetes mellitus incidence.Br. J. Radiol.20239611522023038210.1259/bjr.2023038237750855
     [Google Scholar]
  39. AtkinsonM.A. Campbell-ThompsonM. KusmartsevaI. KaestnerK.H. Organisation of the human pancreas in health and in diabetes.Diabetologia202063101966197310.1007/s00125‑020‑05203‑732894306
     [Google Scholar]
  40. CovingtonB.A. ChenW. Animal models for understanding the mechanisms of beta cell death during type 2 diabetes pathogenesis.Biomedicines202412347310.3390/biomedicines1203047338540087
     [Google Scholar]
  41. JoshiR.D. DhakalC.K. Predicting type 2 diabetes using logistic regression and machine learning approaches.Int. J. Environ. Res. Public Health20211814734610.3390/ijerph1814734634299797
     [Google Scholar]
  42. ZouQ. QuK. LuoY. YinD. JuY. TangH. Predicting diabetes mellitus with machine learning techniques.Front. Genet.2018951510.3389/fgene.2018.0051530459809
     [Google Scholar]
/content/journals/cmir/10.2174/0115734056304038240515101952
Loading
Risk Prediction of Type 2 Diabetes Mellitus by MRI-based Pancreatic Morphology and Clinical Characteristics: A Cross-sectional Study
Curr. Med. Imaging 20, e15734056304038 (2024); https://doi.org/10.2174/0115734056304038240515101952
/content/journals/cmir/10.2174/0115734056304038240515101952
/content/journals/cmir/10.2174/0115734056304038240515101952
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Angle of the pancreaticobiliary junction; Diameter; MRCP; MRI; Pancreatic morphology; Type 2 diabetes mellitus

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test