FDG-PET/CT Brain Findings in a Patient With Macrophagic Myofasciitis

Gucht, Axel Van Der; Aoun-Sebaiti, Mehdi; Kauv, Paul; Guedj, Éric; Aouizerate, Jessie; Verger, Antoine; Gherardi, Romain K.; Bachoud‐Lévi, Anne‐Catherine; Authier, François‐Jérôme; Itti, Emmanuel

doi:10.1007/s13139-015-0371-z

Cited by 6 publications

(7 citation statements)

References 11 publications

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“…Cognitive dysfunction was associated and can be the prominent clinical feature 6. In our case, there was not any clinical suggestion of cognitive disorder.…”

Section: Discussioncontrasting

confidence: 44%

Macrophagic myofasciitis: a challenging diagnosis

Santos¹,

Santos

Rebelo

et al. 2018

BMJ Case Reports

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A 25-year-old man admitted for generalised muscle pain with an insidious onset 3 years ago. He had exercise intolerance and decrease in muscle strength, requiring gait support. He was previously healthy, with no chronic medication or recent history of drugs or toxics. National vaccination plan actualised with hepatitis B and tetanus vaccines administered 10 and 2 years, respectively, before symptom onset. No analytical, imaging or electromyography changes were found. Muscle biopsy revealed an inflammatory infiltrate predominantly macrophagic with aluminium deposits suggestive of macrophagic myofasciitis (MMF). It is probably associated with vaccines previously administered. MMF lesion can be regarded as pathological only if detected at least 18 months after last aluminic immunisation, as our case illustrates.

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“…Cognitive dysfunction was associated and can be the prominent clinical feature 6. In our case, there was not any clinical suggestion of cognitive disorder.…”

Section: Discussioncontrasting

confidence: 44%

Macrophagic myofasciitis: a challenging diagnosis

Santos¹,

Santos

Rebelo

et al. 2018

BMJ Case Reports

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“…identification of hypoperfusion in this region by routine image interpretation difficult. In contrast, with 18 F-FDG PET/CT, the spatial pattern of cerebral glucose hypometabolism is the predominant imaging feature in MMF patients (P , 0.001) and can be easily diagnosed by routine interpretation (17). Probably for similar reasons of differing tracer uptake mechanisms, perfusion imaging with statistical parametric mapping analysis was able to identify periventricular abnormalities in the subset of patients with callosal dysfunction, suggesting impairment of a subcortical connection between the cerebral hemispheres; in contrast, 18 F-FDG imaging, which measures glucose consumption in neuron bodies, was unable to identify dysfunction in the periventricular areas in patients with callosal dysfunction.…”

Section: Discussionmentioning

confidence: 94%

“…Also, a significant decrease in the uptake of 18 F-FDG, in a symmetric pattern involving the occipital lobes, temporal lobes, and cerebellum, was recently found during the diagnostic workup of marked cognitive impairment, diffuse myalgias, and sensory/visual disorders in a 44-y-old woman with histopathologic features of MMF at deltoid muscle biopsy (17).…”

mentioning

confidence: 79%

Brain ¹⁸F-FDG PET Metabolic Abnormalities in Patients with Long-Lasting Macrophagic Myofascitis

Gucht¹,

Sebaiti²,

Guedj³

et al. 2016

J Nucl Med

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The aim of this study was to characterize brain metabolic abnormalities in patients with macrophagic myofascitis (MMF) and the relationship with cognitive dysfunction through the use of PET with 18 F-FDG. Methods: 18 F-FDG PET brain imaging and a comprehensive battery of neuropsychological tests were performed in 100 consecutive MMF patients (age [mean 6 SD], 45.9 6 12 y; 74% women). Images were analyzed with statistical parametric mapping (SPM12). Through the use of analysis of covariance, all 18 F-FDG PET brain images of MMF patients were compared with those of a reference population of 44 healthy subjects similar in age (45.4 6 16 y; P 5 0.87) and sex (73% women; P 5 0.88). The neuropsychological assessment identified 4 categories of patients: those with no significant cognitive impairment (n 5 42), those with frontal subcortical (FSC) dysfunction (n 5 29), those with Papez circuit dysfunction (n 5 22), and those with callosal disconnection (n 5 7). Results: In comparison with healthy subjects, the whole population of patients with MMF exhibited a spatial pattern of cerebral glucose hypometabolism (P , 0.001) involving the occipital lobes, temporal lobes, limbic system, cerebellum, and frontoparietal cortices, as shown by analysis of covariance. The subgroup of patients with FSC dysfunction exhibited a larger extent of involved areas (35,223 voxels vs. 13,680 voxels in the subgroup with Papez circuit dysfunction and 5,453 voxels in patients without cognitive impairment). Nonsignificant results were obtained for the last subgroup because of its small population size. Conclusion: Our study identified a peculiar spatial pattern of cerebral glucose hypometabolism that was most marked in MMF patients with FSC dysfunction. Further studies are needed to determine whether this pattern could represent a diagnostic biomarker of MMF in patients with chronic fatigue syndrome and cognitive dysfunction.

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“…Few functional SPECT and PET studies have investigated this cognitive disorder [ 6 – 8 ]. A peculiar spatial pattern of a cerebral glucose hypometabolism involving occipito-temporal cortex and cerebellum have been reported [ 7 ]; however, the full pattern is not systematically present in routine interpretation of scans, and with varying degrees of severity depending on the cognitive profile of patients [ 8 ]. Thus, the identification of an individual biomarker is needed.…”

Section: Introductionmentioning

confidence: 99%

Cerebral 18F-FDG PET in macrophagic myofasciitis: An individual SVM-based approach

Blanc-Durand¹,

Gucht²,

Guedj³

et al. 2017

PLoS ONE

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IntroductionMacrophagic myofasciitis (MMF) is an emerging condition with highly specific myopathological alterations. A peculiar spatial pattern of a cerebral glucose hypometabolism involving occipito-temporal cortex and cerebellum have been reported in patients with MMF; however, the full pattern is not systematically present in routine interpretation of scans, and with varying degrees of severity depending on the cognitive profile of patients. Aim was to generate and evaluate a support vector machine (SVM) procedure to classify patients between healthy or MMF 18F-FDG brain profiles.Methods18F-FDG PET brain images of 119 patients with MMF and 64 healthy subjects were retrospectively analyzed. The whole-population was divided into two groups; a training set (100 MMF, 44 healthy subjects) and a testing set (19 MMF, 20 healthy subjects). Dimensionality reduction was performed using a t-map from statistical parametric mapping (SPM) and a SVM with a linear kernel was trained on the training set. To evaluate the performance of the SVM classifier, values of sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and accuracy (Acc) were calculated.ResultsThe SPM12 analysis on the training set exhibited the already reported hypometabolism pattern involving occipito-temporal and fronto-parietal cortices, limbic system and cerebellum. The SVM procedure, based on the t-test mask generated from the training set, correctly classified MMF patients of the testing set with following Se, Sp, PPV, NPV and Acc: 89%, 85%, 85%, 89%, and 87%.ConclusionWe developed an original and individual approach including a SVM to classify patients between healthy or MMF metabolic brain profiles using 18F-FDG-PET. Machine learning algorithms are promising for computer-aided diagnosis but will need further validation in prospective cohorts.

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FDG-PET/CT Brain Findings in a Patient With Macrophagic Myofasciitis

Cited by 6 publications

References 11 publications

Macrophagic myofasciitis: a challenging diagnosis

Macrophagic myofasciitis: a challenging diagnosis

Brain ¹⁸F-FDG PET Metabolic Abnormalities in Patients with Long-Lasting Macrophagic Myofascitis

Cerebral 18F-FDG PET in macrophagic myofasciitis: An individual SVM-based approach

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FDG-PET/CT Brain Findings in a Patient With Macrophagic Myofasciitis

Cited by 6 publications

References 11 publications

Macrophagic myofasciitis: a challenging diagnosis

Macrophagic myofasciitis: a challenging diagnosis

Brain 18F-FDG PET Metabolic Abnormalities in Patients with Long-Lasting Macrophagic Myofascitis

Cerebral 18F-FDG PET in macrophagic myofasciitis: An individual SVM-based approach

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Brain ¹⁸F-FDG PET Metabolic Abnormalities in Patients with Long-Lasting Macrophagic Myofascitis