Utility of Magnetic Resonance Imaging for Differentiating Necrotizing Fasciitis from Severe Cellulitis: A Magnetic Resonance Indicator for Necrotizing Fasciitis (MRINEC) Algorithm.
Min-Chul KimSujin KimEun Been ChoGuen Young LeeSeong Ho ChoiSeon Ok KimJin Won ChungPublished in: Journal of clinical medicine (2020)
We developed a new magnetic resonance indicator for necrotizing fasciitis (MRINEC) algorithm for differentiating necrotizing fasciitis (NF) from severe cellulitis (SC). All adults with suspected NF between 2010 and 2018 in a tertiary hospital in South Korea were enrolled. Sixty-one patients were diagnosed with NF and 28 with SC. Among them, 34 with NF and 15 with SC underwent magnetic resonance imaging (MRI). The MRINEC algorithm, a two-step decision tree including T2 hyperintensity of intermuscular deep fascia and diffuse T2 hyperintensity of deep peripheral fascia, diagnosed NF with 94% sensitivity (95% confidence interval (CI), 80-99%) and 60% specificity (95% CI, 32-84%). The algorithm accurately diagnosed all 15 NF patients with a high (≥8) laboratory risk indicator for necrotizing fasciitis (LRINEC) score. Among the five patients with an intermediate (6-7) LRINEC score, sensitivity and specificity were 100% (95% CI, 78-100%) and 0% (95% CI, 0-84%), respectively. Finally, among the 29 patients with a low (≤5) LRINEC score, the algorithm had a sensitivity and specificity of 88% (95% CI, 62-98%) and 69% (95% CI, 39-91%), respectively. The MRINEC algorithm may be a useful adjuvant method for diagnosing NF, especially when NF is suspected in patients with a low LRINEC score.
Keyphrases
- signaling pathway
- lps induced
- magnetic resonance imaging
- magnetic resonance
- pi k akt
- machine learning
- nuclear factor
- contrast enhanced
- oxidative stress
- deep learning
- inflammatory response
- end stage renal disease
- chronic kidney disease
- early stage
- newly diagnosed
- ejection fraction
- toll like receptor
- high grade
- drug induced
- peritoneal dialysis