Moyamoya syndrome may result from psoriasis: Four case reports

BACKGROUND Moyamoya syndrome(MMS)is a group of diseases that involves more than one underlying disease and is accompanied by moyamoya vascular phenomena.Psoriasis is a chronic immune skin disease closely linked to high blood pressure and heart disease.However,psoriasis-related MMS has not been reported.CASE SUMMARY We collected data on patients with stroke due to MMS between January 2017 and December 2019 and identified four cases of psoriasis.Case histories,imaging,and hematological data were collected.The average age of the initial stroke onset was 58.25±11.52 years;three cases of hemorrhagic and one case of ischemic stroke were included.The average duration from psoriasis confirmation to the initial MMS-mediated stroke onset was 17±3.56 years.All MMS-related stenoses involved the bilateral cerebral arteries:Suzuki grade III in one case,grade IV in two cases,and grade V in one case.Abnormally elevated plasma interleukin-6 levels were observed in four patients.Two patients had abnormally elevated immunoglobulin E levels,and two had thrombocytosis.All four patients received medication instead of surgery.With an average follow-up time of 2 years,two causing transient ischemic attacks occurred in two patients,and no hemorrhagic events occurred.CONCLUSION Psoriasis may be a potential risk factor for MMS.Patients with psoriasis should be screened for MMS when they present with neurological symptoms.

Moyamoya Syndrome in Post-Transplant Children with Type 1 Neurofibromatosis and Congenital Nephrotic Syndrome

Background: Neurofibromatosis (NF) is a genetic disorder of the nervous system that affects the development and growth of neuronal tissues. It is characterized by the development of malignant and benign tumors of the peripheral nerves and meningiomas, and the clinical manifestations can vary, including cerebral vascular compromise that precipitates symptoms characteristic of Moyamoya syndrome. The behavior of a posttransplant child with type 1 NF who presents with characteristics of Moyamoya syndrome and is a carrier of a WT1 genetic mutation is unknown, which is why the report was made. Case Report: A child with type I NF with a history of cryptorchidism, hypospadias, bilateral sensorineural hearing loss, and chronic renal failure was arising from a congenital nephrotic syndrome due to a WT1 gene mutation at 3 years of age began renal replacement therapy initially with chronic ambulatory peritoneal dialysis and hemodialysis for refractory peritonitis. He underwent two episodes of transient ischemic attack (TIA) characterized by right hemiparesis during hemodialysis therapy and during six months post-kidney transplantation present a similar episode. Studies for other causes were negative, and imaging studies show characteristics of NF-related vasculitis, cortical lesions, and focal lesions in the left frontal subcortical white matter with annular enhancement and subcortical edema in the parasagittal region of the left parietal lobe, as well as a decrease in flow in the cortical branches of the middle cerebral artery were described. After four weeks, the clinical manifestations of hemiparesis completely disappeared without leaving any sequels continuing with the regular immunosuppression of the everolimus, mycophenolate and low dose steroids. Conclusion: These findings are suggestive of small and mediumsized vessel vasculitis compatible with Moyamoya syndrome in child post-transplantation associated with arteriopathy by NF.

Recognition of moyamoya disease and its hemorrhagic risk using deep learning algorithms:sourced from retrospective studies

Although intracranial hemorrhage in moyamoya disease can occur repeatedly,predicting the disease is difficult.Deep learning algorithms developed in recent years provide a new angle for identifying hidden risk factors,evaluating the weight of different factors,and quantitatively evaluating the risk of intracranial hemorrhage in moyamoya disease.To investigate whether convolutional neural network algorithms can be used to recognize moyamoya disease and predict hemorrhagic episodes,we retrospectively selected 460 adult unilateral hemispheres with moyamoya vasculopathy as positive samples for diagnosis modeling,including 418 hemispheres with moyamoya disease and 42 hemispheres with moyamoya syndromes.Another 500 hemispheres with normal vessel appearance were selected as negative samples.We used deep residual neural network(ResNet-152)algorithms to extract features from raw data obtained from digital subtraction angiography of the internal carotid artery,then trained and validated the model.The accuracy,sensitivity,and specificity of the model in identifying unilateral moyamoya vasculopathy were 97.64±0.87%,96.55±3.44%,and 98.29±0.98%,respectively.The area under the receiver operating characteristic curve was 0.990.We used a combined multi-view conventional neural network algorithm to integrate age,sex,and hemorrhagic factors with features of the digital subtraction angiography.The accuracy of the model in predicting unilateral hemorrhagic risk was 90.69±1.58%and the sensitivity and specificity were 94.12±2.75%and 89.86±3.64%,respectively.The deep learning algorithms we proposed were valuable and might assist in the automatic diagnosis of moyamoya disease and timely recognition of the risk for re-hemorrhage.This study was approved by the Institutional Review Board of Huashan Hospital,Fudan University,China(approved No.2014-278)on January 12,2015.