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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2021, Vol. 15 Issue (6) : 913-921    https://doi.org/10.1007/s11684-021-0874-1
RESEARCH ARTICLE
18F-FDG-PET glucose hypometabolism pattern in patients with epileptogenic hypothalamic hamartoma
Chao Lu1,2, Kailiang Wang1,2, Fei Meng1,2, Yihe Wang1,2, Yongzhi Shan1,2(), Penghu Wei1,2(), Guoguang Zhao1,2,3()
1. Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
2. China International Neuroscience Institute (CHINA-INI), Beijing 100053, China
3. Center of Epilepsy, Beijing Institute for Brain Disorder, Beijing 100069, China
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Abstract

Epileptogenic hypothalamic hamartoma is characterized by intractable gelastic seizures. A systematic analysis of the overall brain metabolic pattern in patients with hypothalamic hamartoma (HH) could facilitate the understanding of the epileptic brain network and the associated brain damage effects of HH. In this study, we retrospectively evaluated 27 patients with epileptogenic HH (8 female patients; age, 2–33 years) by using 18F-fluorodeoxyglucose-positron emission tomography. The correlations among tomography result, seizure type, sex, and structural magnetic resonance imaging were assessed. Whole metabolic patterns and voxel-based morphometry findings were assessed by group analysis with healthy controls. Assessment of the whole metabolic pattern in patients with HH revealed several regional metabolic reductions in the cerebrum and an overall metabolic reduction in the cerebellum. In addition, areas showing hypometabolism in the neocortex were more widely distributed ipsilaterally than contralaterally to the HH. Reductions in glucose metabolism and gray matter volume in the neocortex were predominant ipsilateral to the HH. In conclusion, the glucose hypometabolism pattern in patients with epileptogenic HH involved the neocortex, subcortical regions, and cerebellum. The characteristics of glucose hypometabolism differed across seizure type and sex. Reductions in glucose metabolism and structural changes may be based on different mechanisms, but both are likely to occur ipsilateral to the HH in the neocortex. We hypothesized that the dentato-rubro-thalamic tract and cerebro-ponto-cerebellar tract, which are responsible for intercommunication between the cerebral cortex, subcortical regions, and cerebellar regions, may be involved in a pathway related to seizure propagation, particularly gelastic seizures, in patients with HH.

Keywords hypothalamic hamartoma      gelastic seizure      fluorodeoxyglucose-positron emission tomography      voxel-based morphometry     
Corresponding Author(s): Yongzhi Shan,Penghu Wei,Guoguang Zhao   
Just Accepted Date: 29 October 2021   Online First Date: 23 November 2021    Issue Date: 27 December 2021
 Cite this article:   
Chao Lu,Kailiang Wang,Fei Meng, et al. 18F-FDG-PET glucose hypometabolism pattern in patients with epileptogenic hypothalamic hamartoma[J]. Front. Med., 2021, 15(6): 913-921.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-021-0874-1
https://academic.hep.com.cn/fmd/EN/Y2021/V15/I6/913
HH ?patients Healthy controls ?(PET group) Healthy controls ?(VBM group)
Total number 27 25 31
Age ?(year (mean±SD)) 3–33 ?(12±11) 31–68 ?(44±16) 18–29 ?(24±3)
Sex (n)
?Male 19 10 10
?Female 8 15 21
Seizure type (n)
?GS 26
?FBTCS 15
?FIAS 4
?TBS 8
Tab.1  Demographic data
Fig.1  Differences in whole brain metabolic patterns between patients with hypothalamic hamartoma (HH) and healthy controls (P<0.01; two-sample t-test). The red-yellow color indicates a decrease in the metabolism. (A) three-dimensional (3-D) surface view of metabolic maps. Hypometabolism is mainly distributed in the right hemisphere ipsilateral to the HH, involving the frontal lobe, temporal lobe, parietal lobe, and occipital lobe. Meanwhile, hypometabolism is seen in small parts of the contralateral temporal and parietal lobes. Moreover, hypometabolism is seen in the bilateral cerebellum. (B) Axial view maps are more detailed than the 3-D surface view maps. Apart from the surface, bilateral regions, such as the thalamus, red nucleus, and globus pallidus, are also involved in the hypometabolic pattern. (C) Sagittal view maps show distinct involvement of the bilateral cingulum, an essential part of the default mode network, the thalamus, and the cerebellum, which are connected by the dentato-rubro-thalamic tract. (D) Coronal view maps. L, left; R, right.
Cluster Region MNI coordinate (mm)? T value
X Y Z
(1) Cingulum_Post_L 2 –42 30 12.54
Cingulum_Post_R 4.39 –40 30 11.79
(2) Frontal_Mid_R 32 6 50 7.82
Supp_Motor_Area_R 8 15.65 48 7.19
Precentral_R 34.64 1.99 50 6.5
(3) Angular_R 36.59 –66.28 40 8.3
Angular_L –39.52 –70.18 30 6.87
Occipital_Mid_L –38 –74 32 7.82
(4) Temporal_Mid_L –54 –32 –12 6.97
Temporal_Mid_R 55.13 –32 –14 8.14
(5) Hippocampus_R 28.78 –9.17 –24 7.6
Hippocampus_L –20 –6 –26 7.36
(6) ParaHippocampal_R 24.88 –10.69 –28 8.62
ParaHippocampal_L –21.95 –10 –30 6.78
(7) Amygdala_L –22.93 –3.86 –26 6.75
Amygdala_R 27.81 –2.88 –24 6.47
(8) Thalamus_L –3.42 –12.84 –2 8.67
Thalamus_R 8.29 –8.73 –2 8.71
(9) Mid_brain _L –2.44 –20.44 –6 8.6
Mid_brain _R 7.32 –17.51 –8 7.92
Brianstem –0.49 –32.14 –16 6.88
(10) Cerebellum_L –33.66 –60 –46.82 7.79
Cerebellum_R 36.59 –64 –45.84 9.45
Tab.2  Brain regions showing significant metabolic differences between patients and healthy controls
Fig.2  Metabolic differences according to seizure type and sex (P<0.01). The red-yellow color indicates the decrease in metabolism, and the blue-green color indicates the increase in metabolism. (A) Metabolic difference between the different seizure types. HH patients with focal to bilateral tonic?clonic seizure (FBTCS) show significant hypometabolism on both sides of the precentral gyrus and insular lobe ipsilateral to the HH and hypermetabolism in the right cerebellum compared with the non-FBTCS patients. (B) Metabolic difference between sexes. Female patients show significant hypometabolism in the bilateral frontal lobes and parietal lobes, right temporal lobe, and left cingulate gyrus and hypermetabolism in the bilateral superior parietal lobes and left precentral gyrus compared with the male patients. L, left; R, right.
Fig.3  Voxel-based morphometry (VBM) results of HH patients and healthy controls (P<0.01, two-sample t-test). Gray matter volume (GMV) decrease is shown in blue-green, and GMV increase is shown in red-yellow. (A) 3-D surface view of VBM results. HH patients show significant GMV decrease in the hemisphere ipsilateral to HH and GMV increase in the hemisphere contralateral to HH, especially in the regions of the frontal and temporal lobes. Overall, the GMV in the cerebellum increases. (B) Axial view maps showing more details than 3-D surface view maps. L, left; R, right.
1 K Wagner, A Schulze-Bonhage, H Urbach, M Trippel, TS Spehl, F Buschmann, B Metternich, I Ofer, PT Meyer, L Frings. Reduced glucose metabolism in neocortical network nodes remote from hypothalamic hamartomas reflects cognitive impairment. Epilepsia 2017; 58(Suppl 2): 41–49
https://doi.org/10.1111/epi.13757 pmid: 28591477
2 GN Breningstall. Gelastic seizures, precocious puberty, and hypothalamic hamartoma. Neurology 1985; 35(8): 1180–1183
https://doi.org/10.1212/WNL.35.8.1180 pmid: 4022351
3 D Wang, Y Shan, F Bartolomei, P Kahane, Y An, M Li, H Zhang, X Fan, S Ou, Y Yang, P Wei, C Lu, Y Wang, J Du, L Ren, Y Wang, G Zhao. Electrophysiological properties and seizure networks in hypothalamic hamartoma. Ann Clin Transl Neurol 2020; 7(5): 653–666
https://doi.org/10.1002/acn3.51033 pmid: 32298053
4 P Kahane, P Ryvlin, D Hoffmann, L Minotti, AL Benabid. From hypothalamic hamartoma to cortex: what can be learnt from depth recordings and stimulation? Epileptic Disord 2003; 5(4): 205–217
pmid: 14975789
5 J Wu, L Xu, DY Kim, JM Rho, PA St John, LF Lue, S Coons, K Ellsworth, L Nowak, E Johnson, H Rekate, JF Kerrigan. Electrophysiological properties of human hypothalamic hamartomas. Ann Neurol 2005; 58(3): 371–382
https://doi.org/10.1002/ana.20580 pmid: 16130091
6 SG Mueller, KD Laxer, N Cashdollar, S Buckley, C Paul, MW Weiner. Voxel-based optimized morphometry (VBM) of gray and white matter in temporal lobe epilepsy (TLE) with and without mesial temporal sclerosis. Epilepsia 2006; 47(5): 900–907
https://doi.org/10.1111/j.1528-1167.2006.00512.x pmid: 16686655
7 DS Barron, PM Fox, AR Laird, JL Robinson, PT Fox. Thalamic medial dorsal nucleus atrophy in medial temporal lobe epilepsy: a VBM meta-analysis. Neuroimage Clin 2013; 2: 25–32
https://doi.org/10.1016/j.nicl.2012.11.004 pmid: 24179755
8 A Labate, A Cerasa, A Gambardella, U Aguglia, A Quattrone. Hippocampal and thalamic atrophy in mild temporal lobe epilepsy: a VBM study. Neurology 2008; 71(14): 1094–1101
https://doi.org/10.1212/01.wnl.0000326898.05099.04 pmid: 18824674
9 MR Ponisio, JM Zempel, BK Day, LN Eisenman, MM Miller-Thomas, MD Smyth, RE Hogan. The role of SPECT and PET in epilepsy. AJR Am J Roentgenol 2021; 216(3): 759–768
https://doi.org/10.2214/AJR.20.23336 pmid: 33474983
10 K Shang, J Wang, X Fan, B Cui, J Ma, H Yang, Y Zhou, G Zhao, J Lu. Clinical value of hybrid TOF-PET/MR imaging-based multiparametric imaging in localizing seizure focus in patients with MRI-negative temporal lobe epilepsy. AJNR Am J Neuroradiol 2018; 39(10): 1791–1798
https://doi.org/10.3174/ajnr.A5814 pmid: 30237304
11 S Vickery, WD Hopkins, CC Sherwood, SJ Schapiro, RD Latzman, S Caspers, C Gaser, SB Eickhoff, R Dahnke, F Hoffstaedter. Chimpanzee brain morphometry utilizing standardized MRI preprocessing and macroanatomical annotations. eLife 2020; 9: e60136
https://doi.org/10.7554/eLife.60136 pmid: 33226338
12 F Lamarche, AS Job, P Deman, M Bhattacharjee, D Hoffmann, C Gallazzini-Crépin, S Bouvard, L Minotti, P Kahane, O David. Correlation of FDG-PET hypometabolism and SEEG epileptogenicity mapping in patients with drug-resistant focal epilepsy. Epilepsia 2016; 57(12): 2045–2055
https://doi.org/10.1111/epi.13592 pmid: 27861778
13 S Lagarde, M Boucekine, A McGonigal, R Carron, D Scavarda, A Trebuchon, M Milh, L Boyer, F Bartolomei, E. Guedj Relationship between PET metabolism and SEEG epileptogenicity in focal lesional epilepsy. 2020; 47: 3130–3142
https://doi.org/10.1007/s00259-020-04791-1
14 PH Wei, Y An, XT Fan, YH Wang, YF Yang, LK Ren, YZ Shan, GG Zhao. Stereoelectroencephalography-guided radiofrequency thermocoagulation for hypothalamic hamartomas: preliminary evidence. World Neurosurg 2018; 114: e1073–e1078
https://doi.org/10.1016/j.wneu.2018.03.148 pmid: 29605700
15 KA Fenoglio, J Wu, DY Kim, TA Simeone, SW Coons, H Rekate, JM Rho, JF Kerrigan. Hypothalamic hamartoma: basic mechanisms of intrinsic epileptogenesis. Semin Pediatr Neurol 2007; 14(2): 51–59
https://doi.org/10.1016/j.spen.2007.03.002 pmid: 17544947
16 D Wang, Y Shan, F Bartolomei, P Kahane, Y An, M Li, H Zhang, X Fan, S Ou, Y Yang, P Wei, C Lu, Y Wang, J Du, L Ren, Y Wang, G Zhao. Electrophysiological properties and seizure networks in hypothalamic hamartoma. Ann Clin Transl Neurol 2020; 7(5): 653–666
https://doi.org/10.1002/acn3.51033 pmid: 32298053
17 P Ryvlin, C Ravier, S Bouvard, F Mauguire, D Le Bars, A Arzimanoglou, J Petit, P Kahane. Positron emission tomography in epileptogenic hypothalamic hamartomas. Epileptic Disord 2003; 5(4): 219–227
pmid: 14975790
18 YF Yang, PH Wei, F Meng, Y An, XT Fan, YH Wang, D Wang, LK Ren, YZ Shan, GG Zhao. Glucose metabolism characteristics of extra-hypothalamic cortex in patients with hypothalamic hamartomas (HH) undergoing epilepsy evaluation: a retrospective study of 16 cases. Front Neurol 2021; 11: 587622
https://doi.org/10.3389/fneur.2020.587622 pmid: 33519673
19 C McCormick, AB Protzner, AJ Barnett, M Cohn, TA Valiante, MP McAndrews. Linking DMN connectivity to episodic memory capacity: what can we learn from patients with medial temporal lobe damage? Neuroimage Clin 2014; 5: 188–196
https://doi.org/10.1016/j.nicl.2014.05.008 pmid: 25068108
20 CY Hu, X Gao, L Long, X Long, C Liu, Y Chen, Y Xie, C Liu, B Xiao, ZY Hu. Altered DMN functional connectivity and regional homogeneity in partial epilepsy patients: a seventy cases study. Oncotarget 2017; 8(46): 81475–81484
https://doi.org/10.18632/oncotarget.20575 pmid: 29113406
21 A Mohan, AJ Roberto, A Mohan, A Lorenzo, K Jones, MJ Carney, L Liogier-Weyback, S Hwang, KAB Lapidus. The significance of the default mode network (DMN) in neurological and neuropsychiatric disorders: a review. Yale J Biol Med 2016; 89(1): 49–57
pmid: 27505016
22 KL Wang, W Hu, TH Liu, XB Zhao, CL Han, XT Xia, JG Zhang, F Wang, FG Meng. Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy. CNS Neurosci Ther 2019; 25(3): 396–408
https://doi.org/10.1111/cns.13073 pmid: 30298594
23 F Chassoux, E Artiges, F Semah, S Desarnaud, A Laurent, E Landré, P Gervais, B Devaux, OB Helal. Determinants of brain metabolism changes in mesial temporal lobe epilepsy. Epilepsia 2016; 57(6): 907–919
https://doi.org/10.1111/epi.13377 pmid: 27061896
24 P Iannetti, A Spalice, U Raucci, G Atzei, C Cipriani. Gelastic epilepsy: video-EEG, MRI and SPECT characteristics. Brain Dev 1997; 19(6): 418–421
https://doi.org/10.1016/S0387-7604(97)00042-9 pmid: 9339871
25 K Usami, R Matsumoto, N Sawamoto, H Murakami, M Inouchi, T Fumuro, A Shimotake, T Kato, T Mima, H Shirozu, H Masuda, H Fukuyama, R Takahashi, S Kameyama, A Ikeda. Epileptic network of hypothalamic hamartoma: an EEG-fMRI study. Epilepsy Res 2016; 125: 1–9
https://doi.org/10.1016/j.eplepsyres.2016.05.011 pmid: 27295078
26 J Parvizi, SW Anderson, CO Martin, H Damasio, AR Damasio. Pathological laughter and crying: a link to the cerebellum. Brain 2001; 124(9): 1708–1719
https://doi.org/10.1093/brain/124.9.1708 pmid: 11522574
27 AE Elyas, DO Bulters, OC Sparrow. Pathological laughter and crying in patients with pontine lesions. J Neurosurg Pediatr 2011; 8(6): 544–547
https://doi.org/10.3171/2011.8.PEDS11265 pmid: 22132910
28 L Zhang, B Cao, QQ Wei, R Ou, B Zhao, J Yang, Y Wu, H Shang. Pathological laughter and crying in multiple system atrophy with different subtypes: frequency and related factors. J Affect Disord 2021; 283: 60–65
https://doi.org/10.1016/j.jad.2020.12.096 pmid: 33517229
29 S Striano, P Striano. Clinical features and evolution of the gelastic seizures-hypothalamic hamartoma syndrome. Epilepsia 2017; 58(Suppl 2): 12–15
https://doi.org/10.1111/epi.13753 pmid: 28591476
30 I Savic, J Engel Jr. Structural and functional correlates of epileptogenesis—does gender matter? Neurobiol Dis 2014; 70: 69–73
https://doi.org/10.1016/j.nbd.2014.05.028 pmid: 24943053
31 G Chételat, B Landeau, F Eustache, F Mézenge, F Viader, V de la Sayette, B Desgranges, JC Baron. Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study. Neuroimage 2005; 27(4): 934–946
https://doi.org/10.1016/j.neuroimage.2005.05.015 pmid: 15979341
32 TE Losey, SC Beeman, YT Ng, JF Kerrigan, LC Baxter. White matter density is increased in patients with hypothalamic hamartoma and multiple seizure types. Epilepsy Res 2011; 93(2–3): 212–215
https://doi.org/10.1016/j.eplepsyres.2010.12.006 pmid: 21232922
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