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Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

ABSTRACT: Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction.The aim of the study was to understand whether neurobiological factors predict hot flashes.[18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) brain scans coregistered with structural magnetic resonance imaging were used to determine whether metabolic activity in the insula and hypothalamic thermoregulatory and estrogen-feedback regions measured before and in response to AET predict hot flashes. Findings were correlated with CYP2D6 genotype because of CYP2D6 polymorphism associations with tamoxifen-induced hot flashes.We measured regional cerebral metabolic rate of glucose uptake (rCMRglu) in the insula and hypothalamus on FDG-PET.Of 18 women without hot flashes who began AET, new-onset hot flashes were reported by 10 (55.6%) and were detected objectively in nine (50%) participants. Prior to the use of all AET, rCMRglu in the insula (P ? 0.01) and hypothalamic thermoregulatory (P = 0.045) and estrogen-feedback (P = 0.007) regions was lower in women who reported developing hot flashes. In response to AET, rCMRglu was further reduced in the insula in women developing hot flashes (P ? 0.02). Insular and hypothalamic rCMRglu levels were lower in intermediate than extensive CYP2D6 metabolizers.Trait neurobiological characteristics predict hot flashes. Genetic variability in CYP2D6 may underlie the neurobiological predisposition to hot flashes induced by AET.

SUBMITTER: Joffe H

PROVIDER: S-EPMC3791433 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

Joffe Hadine H Deckersbach Thilo T Lin Nancy U NU Makris Nikos N Skaar Todd C TC Rauch Scott L SL Dougherty Darin D DD Hall Janet E JE

The Journal of clinical endocrinology and metabolism 20120620 9

<h4>Context</h4>Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction.<h4>Objective</h4>The aim of the ...[more]

PMID: 22723326

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Project description:BACKGROUND:Standardized treatment in pediatric patients with Hodgkin's lymphoma (HL) follows risk stratification by tumor stage, erythrocyte sedimentation rate and tumor bulk. We aimed to identify quantitative parameters from pretherapeutic FDG-PET to assist prediction of response to induction chemotherapy. METHODS:Retrospective analysis in 50 children with HL (f:18; m:32; median age, 14.8 [4-18] a) consecutively treated according to EuroNet-PHL-C1 (n?=?42) or -C2 treatment protocol (n?=?8). Total metabolic tumor volume (MTV) in pretherapeutic FDG-PET was defined using a semi-automated, background-adapted threshold. Metabolic (SUVmax, SUVmean, SUVpeak, total lesion glycolysis [MTV*SUVmean]) and heterogeneity parameters (asphericity [ASP], entropy, contrast, local homogeneity, energy, and cumulative SUV-volume histograms) were derived. Early response assessment (ERA) was performed after 2 cycles of induction chemotherapy according to treatment protocol and verified by reference rating. Prediction of inadequate response (IR) in ERA was based on ROC analysis separated by stage I/II (1 and 26 patients) and stage III/IV disease (7 and 16 patients) or treatment group/level (TG/TL) 1 to 3. RESULTS:IR was seen in 28/50 patients (TG/TL 1, 6/12 patients; TG/TL 2, 10/17; TG/TL 3, 12/21). Among all PET parameters, MTV best predicted IR; ASP was the best heterogeneity parameter. AUC of MTV was 0.84 (95%-confidence interval, 0.69-0.99) in stage I/II and 0.86 (0.7-1.0) in stage III/IV. In patients of TG/TL 1, AUC of MTV was 0.92 (0.74-1.0); in TG/TL 2 0.71 (0.44-0.99), and in TG/TL 3 0.85 (0.69-1.0). Patients with high vs. low MTV had IR in 86 vs. 0% in TG/TL 1, 80 vs. 29% in TG/TL 2, and 90 vs. 27% in TG/TL 3 (cut-off, >?80 ml, >?160 ml, >?410 ml). CONCLUSIONS:In this explorative study, high total MTV best predicted inadequate response to induction therapy in pediatric HL of all pretherapeutic FDG-PET parameters - in both low and high stages as well as the 3 different TG/TL. TRIAL REGISTRATION:Ethics committee number: EA2/151/16 (retrospectively registered).

Project description:ImportanceThe mechanisms underlying the association between chronic stress and higher mortality among individuals with cancer remain incompletely understood.ObjectiveTo test the hypotheses that among individuals with active head and neck cancer, that higher stress-associated neural activity (ie. metabolic amygdalar activity [AmygA]) at cancer staging associates with survival.DesignRetrospective cohort study.SettingAcademic Medical Center (Massachusetts General Hospital, Boston).Participants240 patients with head and neck cancer (HNCA) who underwent 18F-FDG-PET/CT imaging as part of initial cancer staging.Measurements18F-FDG uptake in the amygdala was determined by placing circular regions of interest in the right and left amygdalae and measuring the mean tracer accumulation (i.e., standardized uptake value [SUV]) in each region of interest. Amygdalar uptake was corrected for background cerebral activity (mean temporal lobe SUV).ResultsAmong individuals with HNCA (age 59±13 years; 30% female), 67 died over a median follow-up period of 3 years (IQR: 1.7-5.1). AmygA associated with heightened bone marrow activity, leukocytosis, and C-reactive protein (P<0.05 each). In adjusted and unadjusted analyses, AmygA associated with subsequent mortality (HR [95% CI]: 1.35, [1.07-1.70], P = 0.009); the association persisted in stratified subset analyses restricted to patients with advanced cancer stage (P<0.001). Individuals within the highest tertile of AmygA experienced a 2-fold higher mortality rate compared to others (P = 0.01). The median progression-free survival was 25 months in patients with higher AmygA (upper tertile) as compared with 36.5 months in other individuals (HR for progression or death [95%CI], 1.83 [1.24-2.68], P = 0.001).Conclusions and relevanceAmygA, quantified on routine 18F-FDG-PET/CT images obtained at cancer staging, independently and robustly predicts mortality and cancer progression among patients with HNCA. Future studies should test whether strategies that attenuate AmygA (or its downstream biological consequences) may improve cancer survival.

Project description:BackgroundTo investigate the diagnostic and prognostic performances of 18F-FDG PET/CT measures of metabolic tumour burden in patients with neurofibromatosis type-1 (NF1), suspect of malignant transformation.MethodsThis retrospective study included 49 patients (15-60 years old, 30 women) with a diagnosis of NF1, followed in our Reference Centre for Rare Neuromuscular Diseases, who presented clinical signs of tumour progression (pain, neurological deficit, tumour growth). Quantitative metabolic parameters were measured on 149 tumoral targets, using semi-automatic software and the best cut off values to predict transformation was assessed by Receiver Operating Characteristics (ROC) analysis. Prognostic value of PET/CT metabolic parameters was assessed by Kaplan-Meier estimates of overall survival.ResultsLesions were histologically documented in 40 patients: a sarcomatous transformation was found in 16, a dysplastic neurofibroma (NF) in 7, and a benign NF in 17; in the remaining 9 patients, a minimal follow-up of 12 mo (median 59 mo) confirmed the absence of transformation. The optimal cut off values for detection of malignant transformation were, in decreasing order of area under the ROC curves, a tumour-to-liver (T/L) ratio >2.5, SUVmax > 4.5, total lesion glycolysis (TLG) > 377, total metabolic tumour volume (TMTV) > 88 cm3, and heterogeneity index (HIsuv) > 1.69. The best prognostic marker was the TLG: the 4-y estimates of survival were 97% [95% CI, 90% - 100%] in patients with TLG ? 377 vs. 27% [95% CI, 5% - 49%] in patients with TLG > 377 (P < 0.0001; ?2 27.85; hazard ratio 13.27 [95% CI, 3.72-47.35]). T/L ratio, SUVmax and TMTV demonstrated slightly lower performance to predict survival, with ?2 ranging 14.41-19.12. The HIsuv index was not predictive of survival.ConclusionOur study demonstrates that TLG and TMTV, as PET/CT measures of metabolic tumour burden, may be used clinically to identify sarcomatous transformation in patients with NF1 and predict overall survival, with a higher specificity for the TLG. Conventional measures such as the SUVmax, and T/L ratio also demonstrate high prognostic value.

Project description:IntroductionMetabolic brain network analysis based on graph theory using FDG PET imaging is potentially useful for investigating brain activity alternation due to metabolism changes in different stages of Alzheimer's disease (AD). Most studies on metabolic network construction have been based on group data. Here a novel approach in building an individual metabolic network was proposed to investigate individual metabolic network abnormalities.MethodFirst, a weighting matrix was calculated based on the interregional effect size difference of mean uptake between a single subject and average normal controls (NCs). Then the weighting matrix for a single subject was multiplied by a group-based connectivity matrix from an NC cohort. To study the performance of the proposed individual metabolic network, inter- and intra-hemispheric connectivity patterns in the groups of NC, sMCI (stable mild cognitive impairment), pMCI (progressive mild cognitive impairment), and AD using the proposed individual metabolic network were constructed and compared with those from the group-based results. The network parameters of global efficiency and clustering coefficient and the network density score (NDS) in the default-mode network (DMN) of generated individual metabolic networks were estimated and compared among the disease groups in AD.ResultsOur results show that the intra- and inter-hemispheric connectivity patterns estimated from our individual metabolic network are similar to those from the group-based method. In particular, the key patterns of occipital-parietal and occipital-temporal inter-regional connectivity deficits detected in the groupwise network study for differentiating different disease groups in AD were also found in the individual network. A reduction trend was observed for network parameters of global efficiency and clustering coefficient, and also for the NDS from NC, sMCI, pMCI, and AD. There was no significant difference between NC and sMCI for all network parameters.ConclusionWe proposed a novel method in constructing the individual metabolic network using a single-subject FDG PET image and a group-based NC connectivity matrix. The result has shown the effectiveness and feasibility of the proposed individual metabolic network in differentiating disease groups in AD. Future studies should include investigation of inter-individual variability and the correlation of individual network features to disease severities and clinical performance.

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Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

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Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

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