Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Dec 17.
Published in final edited form as: Metabolism. 2019 Dec 18:154050. doi: 10.1016/j.metabol.2019.154050

Reversibility of Cerebral Blood Flow in Patients with Cushing’s Disease after Surgery Treatment

Hewei Cheng 1,2,#, Lu Gao 3,4,#, Bo Hou 5, Feng Feng 5, Xiaopeng Guo 3,4, Zihao Wang 3,4, Ming Feng 3,4, Bing Xing 3,4,*, Yong Fan 2,*
PMCID: PMC6938712  NIHMSID: NIHMS1547261  PMID: 31863780

Abstract

Background and objectives

Cushing’s disease (CD) patients have metabolic abnormalities in the brain caused by excessive exposure to endogenous cortisol. However, the reversibility of brain metabolism of CD patients after treatment remains largely unknown.

Methods

This study recruited 50 CD patients seeking treatment and 34 matched normal controls (NCs). The patients were treated with Transsphenoidal Adenomectomy (TSA) and reexamined 3 months later. Cerebral blood flow (CBF) of the patients were assessed using 3D pseudo-continuous arterial spin labelling (PCASL) imaging before the treatment and at the 3-month follow-up and were compared with CBF measures of the NCs using a whole-brain voxelwise group comparison method. For remitted patients, their CBF measures and hormone level measures, including adrenocorticotropic hormone (ACTH), 24-hour urinary free cortisol (24hUFC) and serum cortisol, were compared before and after the treatment. Finally, a correlation analysis was carried out to explore the relationship between changes of CBF and hormone level measures of the remitted CD patients.

Results

After the treatment, 45 patients reached remission. Compared with the NCs, the CD patients before the treatment exhibited significantly reduced CBF in cortical regions, including occipital lobe, parietal lobe, superior/middle/inferior temporal gyrus, superior/middle/inferior frontal gyrus, orbitofrontal cortex, precentral gyrus, middle/posterior cingulate gyrus, and rolandic operculum, as well as significantly increased CBF in subcortical structures, including caudate, pallidum, putamen, limbic lobe, parahippocampal gyrus, hippocampus, thalamus, and amygdala (p<0.01, false discovery rate corrected). For the remitted patients, the change in CBF before and after the treatment displayed a spatial pattern similar to the difference between the NCs and the CD patients before the treatment, and no significant difference in CBF was observed between the NCs and the remitted CD patients after the treatment. The changes of 24hUFC were significantly correlated with the changes of averaged CBF within the subcortical region in the remitted patients (p=0.01).

Conclusions

Our findings demonstrate that the brain metabolic abnormalities of CD patients are reversible when their hormone level changes towards normal after surgery treatment.

Keywords: Cushing’s disease, arterial spin labelling, reversibility, cerebral blood flow, cortisol

1. Introduction

Cushing’s disease (CD) is a rare neuroendocrine disorder characterized by excessive exposure to endogenous cortisol due to adrenocorticotropic hormone secreting pituitary adenoma [1, 2]. Transsphenoidal Adenomectomy (TSA) is the first line and safe treatment choice with a high remission rate for CD patients [3, 4].

Exposure to excess cortisol has a wide variety of adverse effects on brain biology in CD patients [5]. Brain structural and functional abnormalities associated with CD have been explored using a variety of neuroimaging techniques, including structural magnetic resonance imaging (sMRI) [6–9], diffusion tensor imaging (DTI) [8, 10, 11], functional magnetic resonance imaging (fMRI) [8, 12–15]. Recent studies have found that CD patients are associated with metabolic abnormalities in brain regions such as basal ganglia, medial/lateral prefrontal cortex, anteromedial temporal lobe, superior/inferior parietal lobule, medial occipital cortex, and precentral gyrus [16, 17], which are detrimental to brain health [18]. Particularly, a recent fluorodeoxyglucose (FDG)-positron emission tomography (PET) study has demonstrated that CD patients showed significantly increased FDG uptake in the basal ganglia, anteromedial temporal lobe, thalamus, precentral gyrus, and cerebellum, and decreased uptake in the medial and lateral frontal cortex, superior and inferior parietal lobule, medial occipital cortex, and insula [17]. However, the reversibility of metabolic effects is largely unknown in CD patients after the surgical treatment.

In the present study, we investigated cerebral blood flow (CBF) patterns of CD patients using 3D pseudo-continuous arterial spin labelling (PCASL) scans [19, 20] in order to test our hypothesis that CD patients have abnormal CBF that is reversible following a successful surgical treatment. Specifically, we adopted statistical analyses to identify metabolically abnormal brain regions of CD patients through comparing with normal controls (NCs) based on both cross-sectional and longitudinal neuroimaging data. Moreover, we examined whether the altered CBF pattern correlated with clinical measures, including adrenocorticotropic hormone (ACTH) [21], 24-hour urinary free cortisol (24hUFC), and serum cortisol, in order to explore association of the altered CBF pattern with clinical symptoms of CD.

2. Materials and methods

2.1. Participants

This study recruited 50 CD patients underwent TSA at the Department of Neurosurgery, Peking Union Medical College Hospital. Thirty four age-, sex-, and education level-matched NCs with no history of glucocorticoid treatment were also recruited. They were recruited through advertisements posted in supermarkets or on the Internet. The inclusion criteria for NCs were no past or present neurological/psychiatric disorders, diabetes, heart disease, atherosclerosis, hyperlipidemia, and no contraindications for MRI scanning such as implantable temporary transvenous pacing leads. The exclusion criteria included previous brain trauma, other neurological diseases, history of radiotherapy, and claustrophobia.

The pre-operative diagnosis of CD was made by experience endocrinologists with the help of dynamic enhanced pituitary MRI, low- and high-dose dexamethasone suppression tests, and/or inferior petrosal sinus sampling all together, in accord with the latest guidelines [22]. All 50 CD participants were treated with TSA and the post-operative diagnosis of CD was confirmed by pathology. The patients were asked to revisit the hospital for reexamination three months later. Serum cortisol, ACTH and 24hUFC before surgery and at the follow-up were measured by direct chemiluminescence immunoassays (Siemens Healthcare Diagnostics Inc., USA). Remission was defined as serum cortisol decreasing to < 5μg/dL within seven days of TSA [22]. All the subjects have signed the informed written consent after they were explained the nature of the study. This study was approved by the medical Ethics Committee of Peking Union Medical College Hospital.

MRI brain scans were collected for all the participants, including CD patients before operation and 3 months later, and NCs, by the same technician with the same scanning parameters. Five patients were excluded in a longitudinal study because four of them were not remitted, and one remitted patient didn’t have complete imaging data.

2.2. Imaging data acquisition

The MRI data was collected using an eight-channel phase-array head coil with a 3.0-T MR system (Discovery MR750, General Electric, Milwaukee, WI, USA) at Peking Union Medical College Hospital. Sagittal 3D T1-weighted images were acquired by using a brain volume (BRAVO) sequence (repetition time [TR]=7.2ms, echo time [TE]=3.2ms, inversion time [TI]=400ms, slice thickness=1.0mm with no gap between slices, flip angle=12°, in-place matrix=512×512, slices=172, field of view [FOV]=256×256mm2, voxel size=0.5×0.5×1.0mm3). A PCASL sequence with a 3D fast spin-echo acquisition and background suppression was used to collected PCASL scans (repetition time [TR]=4886ms, echo time [TE]=10.5ms, inversion time [TI]=2025ms, number of excitation=2, slice thickness=4mm with no gap between slices, in-place matrix=64×64, slices=40, field of view [FOV]=240×240mm2).

2.3. CBF computation

From the PCASL scans, CBF images were computed following a procedure described in a previous study [23]. The CBF images were nonlinearly registered to a T1 template in the Montreal Neurological Institute (MNI) space with resolution 3×3×3mm3 using DARTEL packages of SPM12 based on deformation fields of their co-registered T1-weighted images [24]. The MNI T1 template was created based on segmented gray matter (GM)/white matter (WM) images from T1-weighted images of all participants (NCs, CD patients before and after treatment) with DARTEL packages of SPM12 [24]. Each nonlinearly registered CBF image was removed of non-brain tissue and smoothed with 6mm full width at half maximum Gaussian kernel. For each smoothed CBF image, CBF value of each voxel was normalized by dividing the averaged CBF of the whole brain [25].

2.4. CBF statistical analyses

Group differences in CBF between NCs and CD patients before and after treatment were accessed by applying two-sample t tests to CBF images voxel-wisely with age, sex, and years of school education as nuisance variables. Changes in CBF of CD patients before and after treatment were identified by applying paired t tests to CBF images voxel-wisely with age, sex, years of school education, and years of disease duration as nuisance variables. For these statistical t tests, statistically significant differences/changes were identified with a threshold of p<0.01 using false discovery rate (FDR) correction for multiple comparisons.

2.5. Correlation analysis between CBF and clinical measures

Correlation analysis was carried out to explore the relationship between CBF of regions of interest (ROIs) and clinical measures of CD patients before treatment as well as the relationship between changes in CBF and clinical measures of remitted CD patients before and after treatment. The clinical measures of interest include ACTH, 24hUFC, and serum cortisol. The ROIs were brain regions that were different in CBF between NCs and CD patients before treatment, or those with significant changes in CBF after treatment.

Particularly, a general linear model with age, sex, years of school education, and years of disease duration as covariates was used to estimate correlation between each clinical measure and mean CBF of ROIs of the CD patients before treatment. A statistically significant threshold was set at p<0.05 using FDR correction for multiple comparisons.

For the remitted CD patients, correlations between changes of each clinical measure and the mean CBF value of ROIs were computed using a general linear model with age, sex, years of school education, years of disease duration, and the corresponding clinical measure before treatment as covariates. The change of each clinical measure was calculated as the post-treatment value minus the pre-treatment value divided by the pre-treatment value, and the change of average CBF value of each ROI was calculated in the same way. Statistically significant correlations were determined at a threshold of p<0.05 using FDR correction for multiple comparisons.

3. Results

3.1. Demographics and clinical characteristics

After the treatment, 45 patients reached remission. Demographic and clinical data of the participants were summarized in Table 1. No significant group difference was observed in age, sex, or years of education between the NCs and CD patients before and after the treatment. For the remitted CD patients, their clinical measures, including ACTH, 24hUFC, and serum cortisol, were significantly different before and after the treatment (p<1.22e-03, paired t test).

Table 1.

Demographic and clinical data of the participants.

Characteristics NCs (N=34; Mean±SD) Pre-treatment CDs (N=50; Mean±SD) Post-treatment CDs (N=45; Mean±SD) NCs vs. Pre-treatment CDs p NCs vs. Post-treatment CDs p
Age (years) 35.56±9.52 31.70±10.04 32.56±10.20 0.08 0.19
Sex (male/female) 10/24 10/40 10/35 0.32 0.47
Years of school education 13.50±2.93 12.78±3.05 12.78±3.16 0.28 0.30
ACTH (pg/ml) – 101.07±170.05 27.82±34.46 – –
24hUFC (ug/day) – 745.24±652.84 89.37±146.76 – –
serum cortisol (ug/dl) – 26.65±9.32 6.23±5.50 – –
Open in a new tab

Abbreviations: NCs, normal controls; CDs, patients with Cushing’s disease; ACTH, adrenocorticotropic hormone; 24hUFC, 24-hour urinary free cortisol; SD, standard deviation.

Group differences in age and years of school education between NCs and the CD patients before and after treatment were examined using two-sample t tests.

Group differences in sex between NCs and the CD patients before and after treatment were examined using chi-square test.

3.2. Abnormal CBF pattern of CD patients

Fig. 1 shows brain regions with significant differences in CBF between the NCs and the CD patients before treatment (p<0.01, FDR corrected). Compared with the NCs, the CD patients had increased CBF in subcortical structures, including caudate, pallidum, putamen, limbic lobe, parahippocampal gyrus, hippocampus, thalamus, and amygdala. On the contrary, CD patients had reduced CBF in cortical regions, including superior/middle/inferior occipital gyrus, lingual gyrus, calcarine cortex, cuneus, superior/inferior parietal lobule, supramarginal gyrus, angular gyrus, postcentral gyrus, precuneus, superior/middle/inferior temporal gyrus, superior/middle/inferior frontal gyrus, orbitofrontal cortex, precentral gyrus, middle/posterior cingulate gyrus, and rolandic operculum. Table 2 summarizes all the brain regions with significant differences in CBF between NCs and CD patients before treatment.

Fig. 1.

Fig. 1.

Open in a new tab

Brain regions with significantly different CBF between NCs and CD patients before treatment (p<0.01, FDR corrected). The color bars indicate the scale for the t-statistics. The warm color denotes the significantly increased CBF in CD patients (Pres-NCs>0), and the cold color denotes the significantly reduced CBF in CD patients (Pres-NCs<0). Abbreviations: CBF, cerebral blood flow; CD, Cushing’s disease; NCs, normal controls; Pres, patients with Cushing’s disease before operation.

Table 2.

Brain regions with significantly different CBF between NCs and CD patients before treatment.

Clusters Brain regions Location Cluster size (mm3) Peak MNI coordinates Peak t value
Brain regions with increased CBF in CD patients
Cluster 1 Caudate/Pallidum/Putamen/Limbic lobe/Parahippocampal gyrus/Hippocampus/Thalamus L 3807/270/3321/5130/162/4266/1836 −9, −15, 6 7.58
Cluster 2 Caudate/Pallidum/Putamen/Limbic lobe/Parahippocampal gyrus/Hippocampus/Thalamus R 4293/675/3618/1053/2889/3267/2133 12, −15, 9 7.92
Cluster 3 Amygdala R 756 24, −9, −12 5.04
Brain regions with decreased CBF in CD patients
Cluster 4 Superior occipital gyrus/Middle occipital gyrus/Inferior occipital gyrus/Lingual gyrus/Calcarine cortex/Cuneus L 7128/13392/1512/351/5697/7371 −9, −93, 24 −8.27
Cluster 5 Superior occipital gyrus/Middle occipital gyrus/Inferior occipital gyrus/Lingual gyrus/Calcarine cortex/Cuneus R 7992/11016/918/1323/5643/7992 24, −90, 18 −8.45
Cluster 6 Superior parietal lobule/Inferior parietal lobule/Supramarginal gyrus/Angular gyrus/Postcentral gyrus/Precuneus L 7155/4320/1215/2727/486/6075 −24, −78, 45 −7.60
Cluster 7 Superior parietal lobule/Inferior parietal lobule/Supramarginal gyrus/Angular gyrus/Postcentral gyrus/Precuneus R 7452/4428/6318/6318/1188/10719 21, −72, 51 −7.95
Cluster 8 Superior temporal gyrus/Middle temporal gyrus/Inferior temporal gyrus L 1134/6966/837 −57, −60, 15 −5.66
Cluster 9 Superior temporal gyrus/Middle temporal gyrus/Inferior temporal gyrus R 3699/10584/2187 45, −72, 24 −6.82
Cluster 10 Superior frontal gyrus/Middle frontal gyrus/Inferior frontal gyrus/Orbitofrontal cortex/Precentral gyrus R 5940/14175/810/405/1377 24, 54, 12 −6.34
Cluster 11 Middle cingulate gyrus/Posterior cingulate gyrus L 702/216 0, −45, 42 −5.33
Cluster 12 Middle cingulate gyrus/Posterior cingulate gyrus R 729/216 3, −45, 36 −4.59
Cluster 13 Rolandic operculum R 486 60, −18, 15 −3.65
Open in a new tab

Abbreviations: CD, Cushing’s disease; NCs, normal controls; CBF, cerebral blood flow; L, left hemisphere; R, right hemisphere.

No statistically significant difference in CBF was observed between the NCs and the remitted CD patients after treatment (p<0.01, FDR corrected). However, a similar trend was observed in the brain regions with different CBF between the NCs and the remitted CD patients after treatment as shown in Fig. 2 (p<0.05, uncorrected).

Fig. 2.

Fig. 2.

Open in a new tab

Brain regions with different CBF between NCs and the remitted CD patients after treatment (p<0.05, uncorrected). The color bars indicate the scale for the t-statistics. The warm color denotes the increased CBF in CD patients after operation (Posts-NCs>0), and the cold color denotes the reduced CBF in CD patients after operation (Posts-NCs<0). Abbreviations: CBF, cerebral blood flow; CD, Cushing’s disease; NCs, normal controls; Posts, patients with Cushing’s disease after treatment.

3.3. Changes in CBF of the remitted CD patients after treatment

Fig. 3 shows brain regions with significant changes in CBF of the remitted CD patients after treatment (p<0.01, FDR corrected). Compared with CBF measures before treatment, the remitted CD patients after treatment exhibited decreased CBF in subcortical structures, whereas the CBF in these brain structures are increased in CD patients before treatment. Meanwhile, the remitted CD patients after treatment had increased CBF in cortical regions, including superior/middle occipital gyrus, lingual gyrus, calcarine cortex, cuneus, superior/inferior parietal lobule, angular gyrus, precuneus, middle temporal gyrus, superior/middle/inferior frontal gyrus, orbitofrontal cortex, precentral gyrus, and middle/posterior cingulate gyrus. These brain regions were almost identical to those with decreased CBF in the CD patients before treatment.

Fig. 3.

Fig. 3.

Open in a new tab

Brain regions with significantly altered CBF in CD patients before and after treatment (p<0.01, FDR corrected). The color bars indicate the scale for the t-statistics. The warm color denotes the reduced CBF in the remitted CD patients after treatment (Pres-Posts>0), and the cold color denotes the increased CBF of the remitted CD patients after treatment (Pres-Posts<0). Abbreviations: CBF, cerebral blood flow; CD, Cushing’s disease; Posts, patients with Cushing’s disease after treatment; Pres, patients with Cushing’s disease before treatment.

3.4. Relationship between CBF and clinical measures

As shown in Fig. 4, the changes of 24hUFC were positively correlated with the changes of averaged CBF within the subcortical region (r=0.41, p=0.01). No significant correlation was observed for other measures.

Fig. 4.

Fig. 4.

Open in a new tab

Significant correlation between changes in averaged CBF of the subcortical region and 24hUFC of the remitted CD patients (p<0.05, FDR corrected). (A) Multi-slice view of the subcortical region whose changes of the mean CBF significantly correlated with changes of 24hUFC in remitted CD patients, (B) scatter plot for the significant correlation between changes in averaged CBF and 24hUFC of the remitted CD patients. The changed values of 24hUFC in (B) were adjusted by removing covariates, including age, sex, years of school education, years of disease duration, and the 24hUFC before treatment, in correlation analysis. Abbreviations: CBF, cerebral blood flow; CD, Cushing’s disease; 24hUFC, 24-hour urinary free cortisol.

4. Discussion

The present study investigated the CBF changes of CD patients before and after surgery treatment based on longitudinal CBF data. To our knowledge, this is the first study to explore reversibility of CBF of CD patients after surgery treatment. Before the treatment, CD patients had increased CBF in subcortical structures and decreased CBF in cortical regions compared with NCs. The remitted patients had restored CBF in the brain after the treatment, and no significant difference was observed in CBF between the remitted patients and NCs. Importantly, changes in 24hUFC were positively correlated with changes of CBF in the subcortical region in the remitted patients after the treatment, suggesting that the change of subcortical CBF of CD patients was associated with their change of 24hUFC.

Our cross-sectional data analysis has revealed that the CD patients had altered CBF patterns, suggesting that CD patients have abnormal metabolism. Our results are largely consistent with existing findings [16, 17]. Particularly, a recent study investigated the metabolism of ventromedial prefrontal cortex (vmPFC) of CD patients using 1H-MRS technique and found that CD patients had lower metabolic rate in vmPFC than NCs [16]. Another study reported that CD patients exhibited increased metabolic rate in brain regions such as putamen, hippocampus, amygdala, thalamus, parahippocampal gyrus, limbic lobe, cerebellum, precentral gyrus, and paracentral lobule using PET, and decreased metabolic rate in other brain regions including medial/superior/middle/inferior frontal cortex, superior/inferior parietal lobule, medical occipital cortex, cingulate gyrus, and insula [17]. We found that CD patients had increased metabolic rate in extra brain regions, including superior/middle/inferior occipital gyrus, superior/middle/inferior temporal gyrus, postcentral gyrus, precuneus, orbitofrontal cortex, precentral gyrus, and rolandic operculum.

Glucocorticoid receptors are widely distributed throughout the brain including both subcortical regions and cortical regions [26], and the whole brain is vulnerable to the excessive glucocorticoid exposure in CD patients. Consequently, the chronic stimulating effects of excess glucocorticoid in CD patients might directly result in their metabolic abnormalities throughout the brain found in the present study. We found that CD patients had decreased metabolic rate in superior, middle and inferior temporal gyrus, which was not reported in previous studies [16, 17]. The abnormal metabolism in these brain regions might be indirectly affected by excess glucocorticoid, which could regulate the serotonin 1A receptors distributed in temporal lobe [27].

For the remitted CD patients, their clinical measures, including ACTH, 24hUFC, and serum cortisol, were significantly reduced after the treatment, and their CBF changed towards normal in that no statistically significant difference in CBF was observed between the remitted CD patients and NCs. Our findings demonstrated that surgical operation was an effective way to treat the CD by resecting pituitary adenoma [3, 4]. Therefore, metabolic abnormalities caused by chronic stimulations of excess glucocorticoid are reversible in CD patients during the short-term postoperative period. Longer follow-up is needed to confirm if the reversibility of energy metabolism is permanent [2].

For the remitted CD patients, their changes of 24hUFC were positively correlated with changes of CBF in the subcortical region. This finding demonstrated that the chronic stimulating effects on subcortical region caused by cortisol were associated with its CBF changes, and our longitudinal study strengthens previous cross-sectional studies [17, 28]. The amygdala and hippocampus, part of the limbic system and being rich in glucocorticoid receptors, participate in regulating the activity of the hypothalamic-pituitary-adrenal axis to secrete cortisol [29]. The limbic system might be responsible for suppressing cortisol secretion under the condition of exposure to excess glucocorticoid in CD patients.

The methodological strengths of this study include a longitudinal design with both imaging data and clinical variables. Previous studies have documented metabolic abnormalities of CD patients in both subcortical and cortical regions using cross-sectional imaging data [16, 17]. However, due to their cross-sectional design, these studies did not assess reversibility of metabolic effects of CD patients after surgical treatment. The present longitudinal study provided valuable evidence that the CD patient’s CBF is reversible after successful treatment. Different from the existing studies that adopted PET and 1H-MRS techniques, the CD patient’s brain metabolism was assessed using 3D PCASL that is noninvasive and therefore has great potential in clinical application.

The current study has several limitations. Firstly, our study mainly investigated the metabolic reversibility of CD patients. Studies of their functional or structural reversibility may provide complementary information to the present study. In addition, the sample size of the current study is moderate. A large sample is necessary to obtain more representative findings although it is difficult due to the rareness of CD. The present study investigated short-time effects of cortisol normalization on cerebral blood flow in CD patients. However, long-time effects of cortisol normalization on cerebral blood flow remain unknown and merit further investigation. Since some symptoms of Cushing Syndrome persist even after the resolution of hypercortisolism, we plan to investigate the long-term dynamic changes of the brain metabolism by collecting long-term follow-up data of the patients participated in the present study. Besides brain studies of functional or structural reversibility, there might be changes in behavior and psychological symptoms and these changes might correlate with changes in cerebral blood flow to specific regions of the brain. Such correlations merit further investigation. Another interesting study is to investigate if the short-term CBF changes are predictive for long-term treatment outcomes of the CD patients using machine learning tools [30–32].

In conclusion, this is the first study to investigate brain metabolic changes of CD patients after surgery treatment using a noninvasive 3D PCASL technique. Our results revealed that the brain CBF and hormone levels (ACTH, 24hUFC and serum cortisol) were altered in CD patients and could be restored towards normality after surgical treatment by pituitary adenoma resection. The changes of CBF were closely associated with changes of cortisol level (i.e., 24hUFC) in the remitted CD patients after treatment. These findings suggest that abnormalities in brain metabolic rate are important biomarkers in CD patients, which may pave new avenues for postoperative interventions and assessments for CD patients especially if the short-term CBF changes are predictive for long-term outcomes of the CD patients.

Table 3.

Brain regions with significant different CBF between CD patients before and after operation.

Clusters Brain regions Location Cluster size (mm3) Peak MNI coordinates Peak t value
Brain regions of decreased CBF in CD patients after operation
Cluster 1 Caudate/Pallidum/Putamen/Limbic lobe/Parahippocampal gyrus/Hippocampus/Thalamus L 3726/297/1836/3753/1080/3591/162 −9, 18, −6 5.91
Cluster 2 Caudate/Pallidum/Putamen/Limbic lobe/Parahippocampal gyrus/Hippocampus/Thalamus R 5103/945/3348/6615/3294/2997/891 12, 21, −3 6.51
Cluster 3 Amygdala R 1269 21, −6, −12 5.29
Brain regions of increased CBF in CD patients after operation
Cluster 4 Superior occipital gyrus/Middle occipital gyrus/Lingual gyrus/Calcarine cortex/Cuneus L 4455/7668/648/5508/5454 −6, −69, 24 −6.24
Cluster 5 Superior occipital gyrus/Middle occipital gyrus/Lingual gyrus/Calcarine cortex/Cuneus R 4914/6318/351/4887/4482 33, −72, 27 −5.94
Cluster 6 Superior parietal lobule/Inferior parietal lobule/Angular gyrus/Postcentral gyrus/Precuneus L 6507/3186/243/1647/11880 −3, −60, 51 −6.73
Cluster 7 Superior parietal lobule/Inferior parietal lobule/Angular gyrus/Postcentral gyrus/Precuneus R 5967/3456/810/297/12258 30, −51, 51 −6.71
Cluster 8 Middle temporal gyrus L 243 −42, −69, 18 −3.56
Cluster 9 Middle temporal gyrus R 1566 48, −60, 18 −4.08
Cluster 10 Superior frontal gyrus/Middle frontal gyrus/Inferior frontal gyrus/Precentral gyrus L 810/7695/675/2970 −27, 21, 51 −6.00
Cluster 11 Superior frontal gyrus/Middle frontal gyrus/Inferior frontal gyrus/Orbitofrontal cortex/Precentral gyrus R 3618/11637/675/324/1053 27, −9, 60 −6.12
Cluster 12 Middle cingulate gyrus/Posterior cingulate gyrus L 2457/1620 −3, −36, 48 −6.00
Cluster 13 Middle cingulate gyrus/Posterior cingulate gyrus R 918/594 3, 36, 48 −5.97
Open in a new tab

Abbreviations: CD, Cushing’s disease; CBF, cerebral blood flow; L, left hemisphere; R, right hemisphere.

Acknowledgements

This study was funded by China Postdoctoral Science Foundation (2019M650567), Clinical Application Research of Capital Characteristic Fund from the Beijing Municipal Science and Technology Commission (Z151100004015099), Science and Technology Research Project of Chongqing Education Commission (KJQN201900624), National Science Foundation of China (61902047), and NIH grant R01EB022573.

Footnotes

Conflict of Interest

The authors have no conflicts of interest relevant to this article to disclose.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Reference

  • [1].Newell-Price J, Bertagna X, Grossman AB, Nieman LK. Cushing’s syndrome. The Lancet. 2006;367:1605–17. [DOI] [PubMed] [Google Scholar]
  • [2].Pivonello R, De Martino MC, De Leo M, Simeoli C, Colao A. Cushing’s disease: the burden of illness. Endocrine. 2017;56:10–8. [DOI] [PubMed] [Google Scholar]
  • [3].Kelly DF. Transsphenoidal surgery for Cushing’s disease: a review of success rates, remission predictors, management of failed surgery, and Nelson’s Syndrome. Neurosurg Focus 2007;23:E5. [DOI] [PubMed] [Google Scholar]
  • [4].Theodoropoulou M, Reincke M. Tumor-directed therapeutic targets in Cushing disease. Journal of Clinical Endocrinology & Metabolism. 2019;104:925–33. [DOI] [PubMed] [Google Scholar]
  • [5].Andela CD, van Haalen FM, Ragnarsson O, Papakokkinou E, Johannsson G, Santos A, et al. Cushing’s syndrome causes irreversible effects on the human brain: A systematic review of structural and functional MRI studies. European Journal of Endocrinology. 2017;173:R1–R14. [DOI] [PubMed] [Google Scholar]
  • [6].Andela CD, van der Werff SJ, Pannekoek JN, van den Berg SM, Meijer OC, van Buchem MA, et al. Smaller grey matter volumes in the anterior cingulate cortex and greater cerebellar volumes in patients with long-term remission of Cushing’s disease: A case–control study. European Journal of Endocrinology. 2013;169:811–9. [DOI] [PubMed] [Google Scholar]
  • [7].Burkhardt T, Lüdecke D, Spies L, Wittmann L, Westphal M, Flitsch J . Hippocampal and cerebellar atrophy in patients with Cushing’s disease. Neurosurgical Focus 2015;39:1–7. [DOI] [PubMed] [Google Scholar]
  • [8].Jiang H, Ren J, He NY, Liu C, Sun YH, Jian FF, et al. Volumetric magnetic resonance imaging analysis in patients with short‐term remission of Cushing’s disease. Clinical Endocrinology. 2017;87:367–74. [DOI] [PubMed] [Google Scholar]
  • [9].Santos A, Granell E, Gómez-Ansón B, Crespo I, Pires P, Vives-Gilabert Y, et al. Depression and anxiety scores are associated with amygdala volume in Cushing’s syndrome: Preliminary study. BioMed Research International. 2017;2017:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10].Pires P, Santos A, Vives-Gilabert Y, Webb S, Sainz-Ruiz A, Resmini E, et al. White matter alterations in the brains of patients with active, remitted, and cured Cushing syndrome: A DTI study. American Journal of Neuroradiology. 2015;36:1043–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].van der Werff SJ, Andela CD, Pannekoek JN, Meijer OC, van Buchem MA, Rombouts SA, et al. Widespread reductions of white matter integrity in patients with long-term remission of Cushing’s disease. NeuroImage: Clinical. 2014;4:659–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Stomby A, Salami A, Dahlqvist P, Evang JA, Ryberg M, Bollerslev J, et al. Elevated resting-state connectivity in the medial temporal lobe and the prefrontal cortex among patients with Cushing’s syndrome in remission. European Journal of Endocrinology. 2019;180:329–38. [DOI] [PubMed] [Google Scholar]
  • [13].Wang X, Zhou T, Wang P, Zhang L, Feng S, Meng X, et al. Dysregulation of resting-state functional connectivity in patients with Cushing’s disease. Neuroradiology. 2019:1–10. [DOI] [PubMed] [Google Scholar]
  • [14].Van Der Werff SJ, Pannekoek JN, Andela CD, Meijer OC, Van Buchem MA, Rombouts SA, et al. Resting-state functional connectivity in patients with long-term remission of Cushing’s disease. Neuropsychopharmacology. 2015;40:1888–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Ragnarsson O, Stomby A, Dahlqvist P, Evang JA, Ryberg M, Olsson T, et al. Decreased prefrontal functional brain response during memory testing in women with Cushing’s syndrome in remission. Psychoneuroendocrinology. 2017;82:117–25. [DOI] [PubMed] [Google Scholar]
  • [16].Crespo I, Santos A, Gómez-Ansón B, López-Mourelo O, Pires P, Vives-Gilabert Y, et al. Brain metabolite abnormalities in ventromedial prefrontal cortex are related to duration of hypercortisolism and anxiety in patients with Cushing’s syndrome. Endocrine. 2016;53:848–56. [DOI] [PubMed] [Google Scholar]
  • [17].Liu S, Wang Y, Xu K, Ping F, Li F, Wang R, et al. Voxel-based comparison of brain glucose metabolism between patients with Cushing’s disease and healthy subjects. NeuroImage: Clinical. 2018;17:354–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Boutari C, Bouzoni E, Joshi A, Stefanakis K, Farr OM, Mantzoros CS. Metabolism updates: New directions, techniques, and exciting research that is broadening the horizons. Metabolism-Clinical and Experimental. 2019;in Press. [DOI] [PubMed] [Google Scholar]
  • [19].Jezzard P, Chappell MA, Okell TW. Arterial spin labeling for the measurement of cerebral perfusion and angiography. Journal of Cerebral Blood Flow & Metabolism. 2018;38:603–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Zhao L, Alsop DC, Detre JA, Dai W. Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors. Journal of Cerebral Blood Flow & Metabolism. 2019;39:302–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Farr OM, Mantzoros CS. Old and newtools to study human brain physiology: Current state, future directions and implications for metabolic regulation. Metabolism-Clinical and Experimental. 2019;99:iii–viii. [DOI] [PubMed] [Google Scholar]
  • [22].Nieman LK, Biller BM, Findling JW, Murad MH, Newell-Price J, Savage MO, et al. Treatment of Cushing’s syndrome: An endocrine society clinical practice guideline. The Journal of Clinical Endocrinology & Metabolism. 2015;100:2807–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Xu G, Rowley HA, Wu G, Alsop DC, Shankaranarayanan A, Dowling M, et al. Reliability and precision of pseudo‐continuous arterial spin labeling perfusion MRI on 3.0 T and comparison with 15O‐water PET in elderly subjects at risk for Alzheimer’s disease. NMR in Biomedicine. 2010;23:286–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Ashburner J A fast diffeomorphic image registration algorithm. NeuroImage. 2007;38:95–113. [DOI] [PubMed] [Google Scholar]
  • [25].Aslan S, Lu H. On the sensitivity of ASL MRI in detecting regional differences in cerebral blood flow. Magnetic Resonance Imaging. 2010;28:928–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Forget H, Lacroix A, Somma M, Cohen H, Cognitive decline in patients with Cushing’s syndrome. Journal of the International Neuropsychological Society. 2000;6:20–9. [DOI] [PubMed] [Google Scholar]
  • [27].López JF, Chalmers DT, Little KY, Watson SJ. Regulation of serotonin1A, glucocorticoid, and mineralocorticoid receptor in rat and human hippocampus: Implications for the neurobiology of depression. Biological Psychiatry. 1998;43:547–73. [DOI] [PubMed] [Google Scholar]
  • [28].Liu S, Wang Y, Xu K, Ping F, Wang R, Li F, et al. Brain glucose metabolism is associated with hormone level in Cushing’s disease: A voxel-based study using FDG-PET. NeuroImage: Clinical. 2016;12:415–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Chow Y, Masiak J, Mikołajewska E, Mikołajewski D, Wójcik GM, Wallace B, et al. Limbic brain structures and burnout—A systematic review. Advances in Medical Sciences. 2018;63:192–8. [DOI] [PubMed] [Google Scholar]
  • [30].Li H, Wolk DA, Fan Y. EARLY PREDICTION OF COGNITIVE DECLINE BASED ON BRAIN MRI IMAGES USING A DEEP LEARNING SURVIVAL ANALYSIS MODEL. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association. 2019;15:P1551–P2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Jing R, Li P, Ding Z, Lin X, Zhao R, Shi L, et al. Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients. Human Brain Mapping. 2019;40:3930–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Fan Y, Rao H, Hurt H, Giannetta J, Korczykowski M, Shera D, et al. Multivariate examination of brain abnormality using both structural and functional MRI. NeuroImage. 2007;36:1189–99. [DOI] [PubMed] [Google Scholar]

RESOURCES