Sema BAYKARA, Murad ATMACA, Osman MERMİ, Hanefi YILDIRIM, Murat BAYKARA

Magnetic resonance imaging histogram analysis of corpus callosum in a functional neurological disorder

Background/aim: The aim of the present study was to examine and compare the corpus callosum (CC) via histogram analysis (HA) on T1-weighted MR images of patients diagnosed with Functional Neurological Disorder (FND) and healthy controls. Materials and methods: The study group included 19 female patients diagnosed with FND, and the control group included 20 healthy subjects. All participants were scanned with a 1.5 T MR scanner. A high-resolution structural image of the entire brain was obtained with sagittal 3D spiral fast spin echo T1-weighted images. Gray level intensity, standard deviation of the histogram, entropy, uniformity, skewness, and kurtosis values were determined with texture analysis. A student’s t-test was used to compare the group data. P < 0.05 was accepted as statistically significant. Results: It was determined that the mean gray level intensity, standard deviation of the histogram, entropy calculated by the maximum, median and variance and size M percentage values were higher in patients with FND. Kurtosis and size U percentages values were lower in patients with FND. Conclusion: In the present study, analysis of CC with T1-weighted MR image HA demonstrated significant differences between FND patients and healthy controls. The study findings indicated that HA is a beneficial technique for demonstrating textural variations between the CCs of patients with FND and healthy controls using MR images.Key words: Conversion disorder, somatoform disorders, corpus callosum, histogram, magnetic resonance imaging

PDF

___

1. Aybek S, Nicholson TR, O’Daly O, Zelaya F, Kanaan RA et al. Emotion-motion interactions in conversion disorder: an FMRI study. PloS one 2015; 10 (4): e0123273. doi: 10.1371/journal. pone.0123273
2. Association AP. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). Washington DC, USA: American Psychiatric Pub; 2013.
3. Atmaca M, Aydin A, Tezcan E, Poyraz AK, Kara B. Volumetric investigation of brain regions in patients with conversion disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2006; 30 (4): 708-713. doi: 10.1016/j. pnpbp.2006.01.011
4. Atmaca M, Baykara S, Mermi O, Yildirim H., Akaslan U. Pituitary volumes are changed in patients with conversion disorder. Brain Imaging and Behavior 2016; 10 (1): 92-95. doi: 10.1007/s11682-015-9368-6
5. Giedd JN, Raznahan A, Mills KL, Lenroot RK. Review: magnetic resonance imaging of male/female differences in human adolescent brain anatomy. Biology of Sex Differences 2012; 3 (1): 19. doi: 10.1186/2042-6410-3-19
6. Vuilleumier P, Chicherio C, Assal F, Schwartz S, Slosman D et al. Functional neuroanatomical correlates of hysterical sensorimotor loss. Brain 2001; 124 (Pt 6): 1077-1090. doi:10.1093/brain/124.6.1077
7. Baumann O, Mattingley JB. Functional topography of primary emotion processing in the human cerebellum. NeuroImage 2012; 61 (4): 805-811. doi: 10.1016/j.neuroimage.2012.03.044
8. Byrd SE, Radkowski MA, Flannery A, McLone DG. The clinical and radiological evaluation of absence of the corpus callosum. European Journal of Radiology 1990; 10 (1): 65-73. doi: 10.1016/0720-048X(90)90091-O
9. McLeod NA, Williams JP, Machen B, Lum GB. Normal and abnormal morphology of the corpus callosum. Neurology 1987; 37 (7): 1240-1242. doi: 10.1212/wnl.37.7.1240
10. Bhatia MS, Saha R, Doval N. Delusional disorder in a patient with corpus callosum agenesis. Journal of Clinical and Diagnostic Research 2016; 10 (12): VD01-VD02. doi: 10.7860/ JCDR/2016/21803.9059
11. Randall PL. Schizophrenia, abnormal connection, and brain evolution. Medical Hypotheses 1983; 10 (3): 247-280. doi: 10.1016/0306-9877(83)90114-7
12. Castellano G, Bonilha L, Li LM, Cendes F. Texture analysis of medical images. Clinical Radiolology 2004; 59 (12): 1061-1069. doi: 10.1016/j.crad.2004.07.008
13. Baykara M, Koca TT, Demirel A, Berk E. Magnetic resonance imaging evaluation of the median nerve using histogram analysis in carpal tunnel syndrome. Neurological Sciences and Neurophysiology 2018; 35 (3): 145-150. doi: 10.5152/ NSN.2018.11280
14. Haralick RM. Statistical and structural approaches to texture. Proceedings of the IEEE 1979; 67 (5): 786-804. doi: 10.1109/ PROC.1979.11328
15. McLaren CE, Chen WP, Nie K, Su MY. Prediction of malignant breast lesions from MRI features: a comparison of artificial neural network and logistic regression techniques. Academic Radiology 2009; 16 (7): 842-851. doi: 10.1016/j. acra.2009.01.029
16. Aerts HJ, Bussink J, Oyen WJ, van Elmpt W, Folgering AM et al. Identification of residual metabolic-active areas within NSCLC tumours using a pre-radiotherapy FDG-PET-CT scan: a prospective validation. Lung Cancer 2012; 75 (1): 73-76. doi: 10.1016/j.lungcan.2011.06.003
17. Yang D, Rao G, Martinez J, Veeraraghavan A, Rao A. Evaluation of tumor-derived MRI-texture features for discrimination of molecular subtypes and prediction of 12-month survival status in glioblastoma. Medical Physics 2015; 42 (11): 6725-6735. doi: 10.1118/1.4934373
18. Tixier F, Hatt M, Le Rest CC, Le Pogam A, Corcos L et al. Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET. Journal of Nuclear Medicine 2012; 53 (5): 693-700. doi: 10.2967/ jnumed.111.099127
19. Molina D, Perez-Beteta J, Luque B, Arregui E, Calvo M et al. Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival. The British Journal of Radiology 2016; 89 (1064): 20160242. doi: 10.1259/bjr.20160242
20. David AS, Wacharasindhu A, Lishman WA. Severe psychiatric disturbance and abnormalities of the corpus callosum: review and case series. Journal of Neurology, Neurosurgery & Psychiatry 1993; 56 (1): 85-93. doi: 10.1136/jnnp.56.1.85
21. Yu H, Caldwell C, Mah K, Poon I, Balogh J et al. Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images. International Journal of Radiation Oncology, Biology, Physics 2009; 75 (2): 618-625. doi: 10.1016/j.ijrobp.2009.04.043
22. Ganeshan B, Miles KA, Young RC, Chatwin CR. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver. European Journal of Radiology 2009; 70 (1): 101-110. doi: 10.1016/j. ejrad.2007.12.005
23. Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles K. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. European Radiology 2012; 22 (4): 796-802. doi:10.1007/s00330- 011-2319-8
24. Yamashita K, Yoshiura T, Hiwatashi A, Togao O, Kikuchi K et al. The radiological diagnosis of fenestral otosclerosis: the utility of histogram analysis using multidetector row CT. European Archives of Oto-Rhino-Laryngology 2014; 271 (12): 3277-3282. doi: 10.1007/s00405-014-2933-6
25. Reynolds EH. Hysteria, conversion and functional disorders: a neurological contribution to classification issues. The British Journal of Psychiatry 2012; 201 (4): 253-254. doi: 10.1192/bjp. bp.111.107219
26. Voon V, Brezing C, Gallea C, Hallett M. Aberrant supplementary motor complex and limbic activity during motor preparation in motor conversion disorder. Movement Disorders 2011; 26 (13): 2396-2403.doi: 10.1002/mds.23890
27. Aybek S, Nicholson TR, Draganski B, Daly E, Murphy DG et al. Grey matter changes in motor conversion disorder. Journal of Neurology, Neurosurgery, and Psychiatry 2014; 85 (2): 236-238. doi: 10.1136/jnnp-2012-304158
28. Hassa T, Sebastian A, Liepert J, Weiller C, Schmidt R et al. Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder. NeuroImage Clinical 2017; 15: 143-150. doi: 10.1016/j.nicl.2017.04.004
29. David AS, Wacharasindhu A, Lishman WA. Severe psychiatric disturbance and abnormalities of the corpus callosum: review and case series. Journal of Neurology, Neurosurgery, and Psychiatry 1993; 56 (1): 85-93. doi: 10.1136/jnnp.56.1.85
30. Demartini B, Petrochilos P, Ricciardi L, Price G, Edwards MJ et al. The role of alexithymia in the development of functional motor symptoms (conversion disorder). Journal of Neurology, Neurosurgery, and Psychiatry 2014; 85 (10): 1132-1137.doi: 10.1136/jnnp-2013-307203
31. Huber M, Herholz K, Habedank B, Thiel A, Müller-Küppers M et al. Different patterns of regional brain activation during emotional stimulation in alexithymics in comparison with normal controls. Psychotherapie Psychosomatik Medizinische Psychologie 2002; 52 (11): 469-478. doi: 10.1055/s-2002-35276
32. Wu JC, Buchsbaum MS, Johnson JC, Hershey TG, Wagner EA et al. Magnetic resonance and positron emission tomography imaging of the corpus magnetic resonance and positron emission tomography imaging of the corpus callosum: size, shape and metabolic rate in unipolar depression. Journal of Affective Disorders 1993; 28 (1): 15-25. doi: 10.1016/0165- 0327(93)90073-s
33. Lyoo IK, Kwon JS, Lee SJ, Han MH, Chang CGet al. Decrease in genu of the corpus callosum in medication-naive, early-onset dysthymia and depressive personality disorder. Biological Psychiatry 2002; 52 (12): 1134-1143. doi: 10.1016/s0006- 3223(02)01436-1
34. Thomas AJ, Perry R, Barber R, Kalaria RN, O’brien JT. Pathologies and pathological mechanisms for white matter hyperintensities in depression. Annals of the New York Academy of Sciences 2002; 977 (1): 333-339. doi: 10.1111/ j.1749-6632.2002.tb04835.x
35. Nery-Fernandes F, Rocha MV, Jackowski A, Ladeia G, Guimarães JL et al. Reduced posterior corpus callosum area in suicidal and non-suicidal patients with bipolar disorder. Journal of Affective Disorders 2012; 142 (1-3): 150-155.doi: 10.1016/j.jad.2012.05.001
36. Lent R, Schmidt SL. The ontogenesis of the forebrain commissures and the determination of brain asymmetries. Progress in Neurobiology 1993; 40 (2): 249-276. doi: 10.1016/0301-0082(93)90024-m
37. Schutter DJ, Harmon-Jones E. The corpus callosum: a commissural road to anger and aggression. Neuroscience and Biobehavioral Reviews 2013; 37 (10 Pt 2): 2481-2488. doi: 10.1016/j.neubiorev.2013.07.013
38. Radulescu E, Ganeshan B, Shergill SS, Medford N, Chatwin C et al. Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia. Psychiatry Research 2014; 223 (3): 179-186. doi: 10.1016/j.pscychresns.2014.05.014
39. Ganeshan B, Miles KA, Young RC, Chatwin CR. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver. European Journal of Radiology 2009; 20 (4): 101-110. doi: 10.1016/j.ejrad.2007.12.005
40. Latha M, Kavitha G. Segmentation and texture analysis of structural biomarkers using neighborhood-clusteringbased level set in MRI of the schizophrenic brain. Magnetic Resonance Materials in Physics, Biology and Medicine 2018; 31 (4): 483-499. doi: 10.1007/s10334-018-0674-z
41. Reyes‐Haro D, García‐Alcocer G, Miledi R, García‐Colunga J. Uptake of serotonin by adult rat corpus callosum is partially reduced by common antidepressants. Journal of Neuroscience Research 2003; 74 (1): 97-102. doi: 10.1002/jnr.10724
42. Ganeshan B, Miles KA, Young RC, Chatwin CR. Hepatic entropy and uniformity: additional parameters that can potentially increase the effectiveness of contrast enhancement during abdominal CT. Clinical Radiology 2007; 62 (8): 761- 768. doi: 10.1016/j.crad.2007.03.004