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Journals / Erciyes Medical Journal / 2022 / Cilt: 44 - Sayı: 2

A Comparison of Automated Segmentation and Manual Tracing of Magnetic Resonance Imaging to Quantify Lateral Ventricle Volumes

Niyazi ACER
Serap BAŞTEPE GRAY
Ahmet Turan ILICA
Burak Oğuzhan KARAPINAR
Esra AKKUŞ YETKİN
Funda İPEKTEN
Levent DEĞİRMENCİOĞLU
Burcu KAMAŞAK
Pages
148–155
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

LV volume values can provide valuable data related to the volumetric dependencies of the anatomical structures in various clinical conditions that can now be easily obtained using automated tools.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: Ventricular volume measurements have been proposed as a useful biomarker for several neurological diseases.
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Key Findings & Data:The goal of this study was to compare the performance of 3 fully-automated tools, volBrain (http://volbrain.upv.es), ALVIN (Automatic Lateral Ventricle Delineation) (https://sites.google.com/site/mrilateralventricle/), and MRICloud (http://mricloud.org), with expert hand tracing to quantify lateral ventricle (LV) volume using magnetic resonance images.
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Conclusion & Impact:LV volume values can provide valuable data related to the volumetric dependencies of the anatomical structures in various clinical conditions that can now be easily obtained using automated tools.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Objective: Ventricular volume measurements have been proposed as a useful biomarker for several neurological diseases. The goal of this study was to compare the performance of 3 fully-automated tools, volBrain (http://volbrain.upv.es), ALVIN (Automatic Lateral Ventricle Delineation) (https://sites.google.com/site/mrilateralventricle/), and MRICloud (http://mricloud.org), with expert hand tracing to quantify lateral ventricle (LV) volume using magnetic resonance images. Materials and Methods: The sample comprised 24 healthy subjects (age: 25.1±5.7 years, all male). Volumes derived from each automated measurement were compared to hand tracing results performed by 2 specialists to assess the percent volume difference using the intraclass correlation coefficient (ICC), concordance correlation coefficient (CCC), Dice index value, and Bland-Altman analysis. Results: The ICC agreement of the Manual_1 and Manual_2 was very good (0.979), and there was no statistically significant difference (p>0.001). The volume difference of all methods was similar. The CCC with MRICloud and ALVIN was higher than that of volBrain. Bland-Altman plots indicated that the 3 automated methods demonstrated acceptable agreement. Conclusion: Compared with hand tracing, the LV volumes generated by MRICloud were more accurate than those of volBrain and ALVIN. LV volume values can provide valuable data related to the volumetric dependencies of the anatomical structures in various clinical conditions that can now be easily obtained using automated tools.

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Cite This Article

ACER, N., GRAY, S. B., ILICA, A. T., KARAPINAR, B. O., YETKİN, E. A., İPEKTEN, F., DEĞİRMENCİOĞLU, L., KAMAŞAK, B. (2022). A Comparison of Automated Segmentation and Manual Tracing of Magnetic Resonance Imaging to Quantify Lateral Ventricle Volumes. Erciyes Medical Journal, Cilt: 44 - Sayı: 2, 148–155. https://ajindex.com/articles/502103

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References (11)

  1. Milovanović N, Damjanović A, Puškaš L, Milovanović S, Barišić J, Mališ M, et al. Reliability of the bicaudate parameter in the revealing of the enlarged lateral Ventricles in schizophrenia patients. Psychiatr Danub 2018; 30(2): 150–6
  2. Zidan M, Boban J, Bjelan M, Todorović A, Stankov Vujanić T, Semnic M, et al. Thalamic volume loss as an early sign of amnestic mild cognitive impairment. J Clin Neurosci 2019; 68: 168–73
  3. Ertekin T, Acer N, Köseoğlu E, Zararsız G, Sönmez A, Gümüş K, et al. Total intracranial and lateral ventricle volumes measurement in Alzheimer’s disease: A methodological study. J Clin Neurosci 2016; 34: 133–9
  4. Kocaman H, Acer N, Köseoğlu E, Gültekin M, Dönmez H. Evaluation of intracerebral ventricles volume of patients with Parkinson’s disease using the atlas-based method: A methodological study. J Chem Neuroanat 2019; 98: 124–30
  5. Doring TM, Kubo TT, Cruz LC Jr, Juruena MF, Fainberg J, Domingues RC, et al. Evaluation of hippocampal volume based on MR imaging in patients with bipolar affective disorder applying manual and automatic segmentation techniques. J Magn Reson Imaging 2011; 33(3): 565–72
  6. Hedderich DM, Spiro JE, Goldhardt O, Kaesmacher J, Wiestler B, Yakushev I, et al. Increasing diagnostic accuracy of mild cognitive impairment due to Alzheimer’s disease by user-independent, web-based whole-brain volumetry. J Alzheimers Dis 2018; 65(4): 1459–67
  7. Palancı Ö, Kalaycıoğlu A, Acer N, Eyüpoğlu İ, Çakmak V. Volume calculation of brain structures in migraine disease by using mristudio. NeuroQuantology 2018; 16(10): 8–13
  8. Sánchez-Benavides G, Gómez-Ansón B, Sainz A, Vives Y, Delfino M, Peña-Casanova J. Manual validation of FreeSurfer’s automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer disease subjects. Psychiatry Res 2010; 181(3): 219–25
  9. Kim JH, Choi DS, Kim S, Shin HS, Seo H, Choi HC, et al. Evaluation of hippocampal volume based on various inversion time in normal adults by manual tracing and automated segmentation methods. Investigative Magnetic Resonance Imaging 2015; 19(2): 67–75
  10. Manjon JV, Coupe P. volBrain: An online MRI brain volumetry system. Front Neuroinform 2016; 10: 30
  11. Næss-Schmidt E, Tietze A, Blicher JU, Petersen M, Mikkelsen IK, Coupé P, et al. Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification. Int J Comput Assist Radiol Surg 2016; 11(11): 1979–91