Congenital Renal Arteriovenous Malformation: Diagnostic Clues and Methods.
Seung-Kwon ChoiGyeong Eun MinDong-Gi LeePublished in: Medicina (Kaunas, Lithuania) (2021)
Background and objectives: Renal arteriovenous malformation (AVM) is a rare disease and is difficult to be diagnosed by conventional methods because of its rarity. In this study, we investigated the diagnostic clues, and made an algorithm for the better diagnosis of renal AVM. Materials and Methods: We reviewed 13 patients who were diagnosed with AVM by using renal angiography from 1986 to 2020 at our institutes. We evaluated clinical features, diagnostic tools, treatment modalities, and outcomes after the treatment of patients. Results: All patients were female, and the mean age was 36.9 years (range 19 to 54 years). Twelve (92.3%) patients complained of gross hematuria. Four (30.8%) patients showed symptoms in relation with pregnancy and delivery. Angiographic findings demonstrated cirsoid type in 10 patients and aneurysmal type in 3 patients. Among the 11 patients who underwent computed tomography, AVMs were detected in 3 (27.3%) patients. Renal duplex Doppler was performed in 6 patients, and all of these patients were diagnosed with AVM, demonstrating a vascular turbulence or blood-rich area. Twelve patients were initially treated with transarterial embolization. Nephrectomy was performed in two patients due to persistent bleeding with hypovolemic shock. Conclusions: We should consider possible AVMs in patients who were not detected by conventional work up for hematuria, especially in mid-aged, pregnant, or recently delivered women. Renal duplex Doppler might be the optimal diagnostic modality in these patients. Our diagnostic algorithm could be aid to diagnosis and treatment for renal AVM patients.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- magnetic resonance imaging
- type diabetes
- pregnant women
- machine learning
- patient reported outcomes
- depressive symptoms
- high resolution
- physical activity
- high speed
- preterm birth
- deep learning
- patient reported
- robot assisted
- pregnancy outcomes
- image quality