Evaluation of spinal-paraspinal parameters to determine segmentation of the vertebrae

被引:1
|
作者
Peker, Elif [1 ]
Hursoy, Nur [1 ]
Akkaya, Habip E. [1 ]
Unal, Sena [1 ]
Gulpinar, Basak [1 ]
Arikan, Bilgesu [1 ]
Anamurluoglu, Ezgi [1 ]
Erden, Ilhan M. [1 ]
机构
[1] Ankara Univ, Fac Med, Ankara, Turkey
关键词
lumbosacral transitional vertebra; MRI; sacralisation; lumbarisation; LUMBOSACRAL TRANSITIONAL VERTEBRAE; AORTIC BIFURCATION; IDENTIFICATION; CLASSIFICATION; VERIFICATION; PREVALENCE; VARIANTS; MRI;
D O I
10.5114/pjr.2019.90227
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: We aimed to evaluate whether lumbar vertebrae can be correctly numbered using auxiliary parameters. Material and methods: Vertebra corpus shape, O'Driscoll classification, lumbosacral axis angle, last two square vertebra dimensions, orifice of right renal artery (RRA), orifice of celiac truncus (CT), orifice of superior mesenteric artery (SMA), vena cava inferior confluence (CVC), abdominal aorta bifurcation (AB), and iliolumbar ligament were evaluated in this study. Results: Lumbosacral transitional vertebrae (LSTV) were observed in 13 (9%) patients. The most common locations of the paraspinal parameters were: RRA: L1 vertebrae (45%), SMA: L1 vertebrae (66%), CT: T12 vertebrae (46%), AB: L4 vertebrae (63%), and CVC: L4 vertebrae (52%). Conclusions: According to the results of our study, no single parameter in the magnetic resonance imaging can accurately indicate the number of vertebrae without counting the levels. As a result, we believe that these parameters may be suspicious in terms of the presence of LSTV rather than the correct level.
引用
收藏
页码:E470 / E477
页数:8
相关论文
共 50 条
  • [31] AN EVALUATION OF MYELOMERES AND SEGMENTATION OF THE CHICK-EMBRYO SPINAL-CORD
    LIM, TM
    JAQUES, KF
    STERN, CD
    KEYNES, RJ
    DEVELOPMENT, 1991, 113 (01): : 227 - 238
  • [32] An Experimental Evaluation of Preprocessing Parameters for GA Based OCR Segmentation
    Bacchuwar, Ketan S.
    Singh, Amarjot
    Bansal, Gaurav
    Tiwari, Saurav
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL II, 2010, : 417 - 420
  • [33] N-Net: 3D Fully Convolution Network-Based Vertebrae Segmentation from CT Spinal Images
    Zhou, Wenhui
    Lin, Lili
    Ge, Guangtao
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2019, 33 (06)
  • [34] Evaluation of Paraspinal Muscle Degeneration on Pain Relief after Percutaneous Epidural Adhesiolysis in Patients with Degenerative Lumbar Spinal Disease
    Kang, Misun
    Kim, Shin Hyung
    Jo, Minju
    Jung, Hyun Eom
    Bae, Jungbin
    Kim, Hee Jung
    MEDICINA-LITHUANIA, 2023, 59 (06):
  • [35] Evaluation of Risk Factors for Vertebral Compression Fracture after Carbon-Ion Radiotherapy for Primary Spinal and Paraspinal Sarcoma
    Matsumoto, Yoshihiro
    Shinoto, Makoto
    Endo, Makoto
    Setsu, Nokitaka
    Iida, Keiichiro
    Fukushi, Jun-Ichi
    Kawaguchi, Kenichi
    Okada, Seiji
    Bekki, Hirofumi
    Imai, Reiko
    Kamada, Tadashi
    Shioyama, Yoshiyuki
    Nakashima, Yasuharu
    BIOMED RESEARCH INTERNATIONAL, 2017, 2017
  • [36] A Supervised and Fuzzy-based Approach to Determine Optimal Multi-resolution Image Segmentation Parameters
    Tong, Hengjian
    Maxwell, Travis
    Zhang, Yun
    Dey, Vivek
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2012, 78 (10): : 1029 - 1044
  • [37] A METHOD HOW TO DETERMINE PARAMETERS ARISING IN A SMOLDERING EVOLUTION EQUATION BY IMAGE SEGMENTATION FOR EXPERIMENT'S MOVIES
    Goto, Maika
    Kuwana, Kazunori
    Uegata, Yasuhide
    Yazaki, Shigetoshi
    DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S, 2021, 14 (03): : 881 - 891
  • [38] Automatic Tuning of Image Segmentation Parameters by Means of Fuzzy Feature Evaluation
    Khan, Arif ul Maula
    Mikut, Ralf
    Schweitzer, Brigitte
    Weiss, Carsten
    Reischl, Markus
    SYNERGIES OF SOFT COMPUTING AND STATISTICS FOR INTELLIGENT DATA ANALYSIS, 2013, 190 : 459 - 467
  • [39] Evaluation of a Wearable Device to Determine Cardiorespiratory Parameters From Surface Diaphragm Electromyography
    Rafols-de-Urquia, Magda
    Estrada, Luis
    Estevez-Piorno, Josep
    Sarlabous, Leonardo
    Jane, Raimon
    Torres, Abel
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2019, 23 (05) : 1964 - 1971
  • [40] Spinal Cord Stimulation for Heart Failure: Preclinical Studies to Determine Optimal Stimulation Parameters for Clinical Efficacy
    John C. Lopshire
    Douglas P. Zipes
    Journal of Cardiovascular Translational Research, 2014, 7 : 321 - 329