Near Focus NBI-Driven Artificial Intelligence for the Diagnosis of Gastro-Oesophageal Reflux Disease
Condition: Gastro Esophageal Reflux
MeSH terms: Gastroesophageal Reflux
Study type: Observational

Summary: 
      Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising
      secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four
      phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux
      Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The
      definition of these phenotype have evolved with the addition of diagnostic tests and methods
      of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al.,
      2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal
      lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Studies have shown a relation
      of increased IPCL numbers with GORD. This study aims to build a fully autmoated AI model
      using Near-Focus NBI images on patients with symptoms suggestive of GORD phenotyped in
      accordance with the Lyon Consensus.
    

Detailed description: 
      Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising
      secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four
      phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux
      Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The
      definition of these phenotype have evolved with the addition of diagnostic tests and methods
      of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al.,
      2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal
      lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Complications of GORD, such as
      peptic stricture and Barrett's oesophagus, can be readily diagnosed using WLE. The diagnosis
      of reflux oesophagitis with standard-definition WLE is well described in the Los Angeles (LA)
      classification (Armstrong et al., 1996) and validated (Lundell et al., 1999) with LA grades C
      and D confirmatory of GORD (Gyawali et al., 2018). Furthermore, AET is demonstrated to
      increase with LA classification A to D (Lundell et al., 1999). There is, however, only a
      modest inter-observer agreement between LA grades (Kappa coefficient 0.4), especially A and
      B. Furthermore LA grade A oesophagitis is detected in up to 17.0% of asymptomatic patients
      (Nozu and Komiyama, 2008; Zagari et al., 2008). A diagnosis of GORD and decisions for
      anti-reflux surgery cannot be made on this basis, mandating pH testing to confirm GORD.

      Narrow Band Imaging

      Imaging of the gastro-oesophageal junction using high definition Olympus H260 scope using the
      LA classification of GORD with WLE and NBI demonstrated improvement in overall interobserver
      reproducibility when used in a combination compared with WLE alone; k 0.62 vs 0.45
      (<0.05)(Lee et al., 2007). Features identified using digital magnification NBI at the
      squamo-columnar junction in cases of EO (n=41; LA grade A and B), NERD (n=36) and controls
      (n=32) include micro-erosions (100% EO; 52.8% NERD; 23.3% controls), increased vascularity
      (95.1% EO; 91.7% NERD; 36.7% controls) and round pit patterns (4.9% EO; 5.6% NERD; 70%
      controls). Increased vascularity combined with absence of round pit pattern distinguishes
      NERD from controls with sensitivity and specificity 86.1% and 83.3%. Inter-observer agreement
      in this single centre study was good for increased vascularity (k=0.95) and micro erosions
      (k=0.89) but low for pit pattern (k=0.59) (Fock et al., 2009).

      Intra-papillary capillary loops (IPCLs) are mucosal capillaries arising from the submucosal
      vein to the papilla, usually arranged in a regular 'dot' like fashion approximately
      100micrometres apart (Inoue, 2001). The visualisation of oesophageal IPCLs with NBI is well
      documented and form the basis of a NBI classification for squamous neoplasia (Inoue et al.,
      2015). IPCL morphology changes have been proposed in patients being investigated for NERD, in
      particular dilatation and elongation of IPCLs in patients with NERD with magnification NBI
      (Kato et al., 2006).

      NBI with optical magnification for the diagnosis of GORD has been evaluated in 2 studies
      (Sharma et al., 2007; Lv et al., 2013). Sharma et al performed a feasibility trial with
      Olympus Q240Z with quadrantic examination of the distal 5cm by WLE then NBI in n=50 GORD (EO
      n=30; NERD n=20) and controls (n=30). Similar to Fock et al, the presence of microerosions
      and hypervascularity was significantly higher amongst GORD. IPCL number and morphology of
      tortuosity, dilatation were seen significantly more in GORD versus control. These findings
      were consistent in independent comparison of EO and NERD versus controls. ROC analysis
      thresholds for best sensitivity and specificity (respectively) for NERD were maximum
      ipcl/field 131 (90%, 70%), min 99 (85%, 70%) and average 117 (90%, 70%) (Sharma et al.,
      2007).

      Lv et al used the Olympus GIF-H260Z to evaluate NERD (n=40), EO (n=40), Barrett's (n=40) and
      healthy controls (n=40). IPCL number, morphology (prolonged/dilated/tortuous), microerosions,
      round pit pattern above or below the SCJ, were recorded as features of reflux. Significant
      differences were found with increased IPCL number, microerosions, non-round pit patterns
      below the SCJ in GERD (NERD/EO and BE) patients compared to controls and fewer microerosions
      in NERD patients compared to RE (Lv et al., 2013).

      The definition of NERD in all studies to date, however, is variable and largely based on
      symptom evaluation, response to PPI and the absence of mucosal lesions at endoscopic
      examination without standardisation using pH studies.

      Artificial Intelligence

      To date there is one study evaluating the use of ANNs in predicting GORD based on 45
      variables including demographics, medical history, health status, symptoms scores. All
      patients underwent OGD, 24-pH studies performed in those with no mucosal lesion at endoscopy:
      103 GORD patient (62 with reflux oesophagitis and 41 with AET>5%) and n=56 FH patients GORD.
      The ANN demonstrated an accuracy of 100% compared to 78% using conventional statistical
      regression analysis (Pace et al., 2005). While these are optimistic findings, the proportion
      of training and test data used was not specified and further evaluation with larger datasets
      is clearly warranted. There are no image-driven AI models for the diagnosis of GORD to date.
      Machine learning with endoscopic images is a pathway of great interest as described in
      section 1.7.7, with IPCLs as a potential target, based on previous studies of NBI for the
      diagnosis of GORD. CNNs involving IPCL detection and morphology have been recently reported
      in the context of a pilot study for the computer assisted diagnosis of oesophageal early
      squamous cell cancer using segmentation technology with accuracy matching expert endoscopists
      (Zhao et al., 2018). The image segmentation technique of Adaptive Local Thresholding has been
      demonstrated to be useful in vessel detection in retinal photographs making this as
      attractive technique for IPCLs (Jiang and Mojon, 2003).
    

Intervention name(s): wireless pH capsule recording
Intervention type(s): Diagnostic Test
Intervention description(s): wireless pH capsule recording for up to 96 hours
Observational model: Cohort
Time perspective: Prospective
Sampling method: Probability Sample
Study population: 
        Consecutive patients attending the Gastroenterology department for the investigation of
        symptoms suggestive of Gastro-Oesophageal Reflux Disease (GORD) were approached for
        recruitment. Patients had to have symptoms including heartburn, regurgitation or
        chest/epigastric pain for a minimum of 3 months.