title: Temporal and spectral properties of esophageal mucosal blood perfusion: a comparison between normal subjects and nutcracker esophagus patients.
abstract: BACKGROUND
  The mechanism of esophageal pain in patients with nutcracker esophagus (NE) and other esophageal motor disorders is not known. Our recent study shows that baseline esophageal mucosal perfusion, measured by laser Doppler perfusion monitoring, is lower in NE patients compared to controls. The goal of our current study was to perform a more detailed analysis of esophageal mucosal blood perfusion (EMBP) waveform of NE patients and controls to determine the optimal EMBP biomarkers that combined with suitable statistical learning models produce robust discrimination between the two groups.
  
  
  METHODS
  Laser Doppler recordings of 10 normal subjects (mean age 43 ± 15 years, 8 males) and 10 patients (mean age 47 ± 5.5 years., 8 males) with NE were analyzed. Time and frequency domain features were extracted from the first twenty-minute recordings of the EMBP waveforms, statistically ranked according to four independent evaluation criterions, and analyzed using two statistical learning models, namely, logistic regression (LR) and support vector machines (SVM).
  
  
  RESULTS
  The top three ranked predictors between the two groups were the 0.5 and 0.75 perfusion quantile values followed by the surface of the EMBP power spectrum in the frequency domain. ROC curve ranking produced a cross-validated AUC (area under the curve) of 0.93 for SVM and 0.90 for LR.
  
  
  CONCLUSIONS
  We show that as a group NE patients have lower perfusion values compared to controls, however, there is an overlap between the two groups, suggesting that not all NE patients suffer from low mucosal perfusion levels.
authors: Division of Gastroenterology, Department of Medicine, University of California, San Diego, CA, USA.
authors: A
authors: A
authors: Zifan
authors: Division of Gastroenterology, Department of Medicine, University of California, San Diego, CA, USA.
authors: Y
authors: Y
authors: Jiang
authors: Division of Gastroenterology, Department of Medicine, University of California, San Diego, CA, USA.
authors: R K
authors: RK
authors: Mittal
mesh_terms: D000328:Adult; D001783:Blood Flow Velocity / Q000502:physiology*; D015154:Esophageal Motility Disorders / Q000175:diagnosis* / Q000503:physiopathology*; D000071041:Esophageal Mucosa / Q000098:blood supply* / Q000502:physiology*; D004947:Esophagus / Q000098:blood supply / Q000502:physiology; D005260:Female; D006801:Humans; D017078:Laser-Doppler Flowmetry / Q000379:methods; D008297:Male; D008365:Manometry / Q000379:methods; D008875:Middle Aged; D013997:Time Factors
keywords: esophageal wall blood perfusion; machine learning; nutcracker esophagus; time and frequency domain predictors