Comparative Analysis of the Incremental Benefit of Chromoendoscopy in Addition to High Definition White Light (HD-WL)and Narrow Band Imaging (NBI) for the Prediction of Submucosal Invasive Cancer Within Laterally Spreading Lesions (LSLs) and in Determining the Presence of Residual or Recurrent Adenoma at a Post Endoscopic Resection Scar
Comparative Analysis of the Incremental Benefit of Chromoendoscopy in Addition to High Definition White Light (HD-WL)and Narrow Band Imaging (NBI) for the Prediction of Submucosal Invasive Cancer Within Laterally Spreading Lesions (LSLs) and in Determining the Presence of Residual or Recurrent Adenoma at a Post Endoscopic Resection Scar
To compare the incremental benefit of chromoendoscopy in addition to high definition white light and narrow band imaging in predicting submucosal invasion within laterally spreading lesions in the colon and in determining the presence of residual or recurrent adenoma at the post endoscopic resection scar
Wide-field (WF) EMR is now accepted as a safe and effective alternative to surgery for removal of large (>20mm) laterally spreading lesions (LSLs).
Assessment of the risk of submucosal invasive cancer (SMIC) is paramount to determining whether a lesion should be attempted for resection by endoscopic mucosal resection (EMR). Lesions that are at high risk for invading the submucosa should either be referred for surgery or in selected cases may be removed by endoscopic submucosal dissection (ESD) in an en bloc fashion to assess SMIC accurately. Tools to assess the likelihood of SMIC endoscopically include analysis of the Kudo pit-pattern (KPP) combined with assessment of morphology as per Paris classification.
KPP analysis is useful to predict histology based on the microarchitecture of pits, epithelial crests or ridges. It thus provides an assessment of risk of sub-mucosal invasion of superficial lesions. There are five categories; with Type 1 and 2 being non-tumours i.e. benign lesion, as compared to Type 3-5 which are tumours ranging from pre-cancerous adenomas (tubular or villous adenoma) to invasive cancer.
Assessment of lesion morphology at WF-EMR using the Paris Classification and analysis of the surface pit-pattern are an integral part of identifying lesions suitable for EMR.
As per the Paris Classification superficial lesions in the colon are divided into; polypoid, non-polypoid and mixed types. Non-polypoid lesions are further divided into slightly raised (0-IIa), flat (0-IIb), depressed surface (0-IIc) or mixed types such as a flat lesion with a nodule (0-IIa+b). The later generally have a greater risk for sub-mucosal invasion (SMI) than polypoid lesions and can be as high as 35-40%. Flat lesions are referred to as laterally spreading lesions (LSLs) if greater than 10mm. There are two distinct subtypes; non-granular vs granular. Granular LSLs exhibit a lower risk of SMI as compared to non-granular LSLs.
Expert opinion suggests that differentiating the KPP in large LSLs (>20mm) requires chromoendoscopy or magnifying endoscopy. This can be a time intensive process. New advances in optics focusing on manipulating the wavelength of the light source; e.g. narrow band imaging (NBI) with the Olympus platform or Fujinon intelligent colour enhancement (FICE) with Fuji have become readily available, and show potential, particularly when combined with magnification, in discriminating the KPP and therefore predicting risk for SMIC. These technologies essentially provide virtual chromoendoscopy. Their diagnostic accuracy has been shown to be comparable to indigo-carmine chromoendoscopy. Both chromoendoscopy and NBI have shown superiority in accurately differentiating between neoplastic and non-neoplastic lesions as compared to high definition white light (HD-WL) endoscopy. In addition NBI has been shown to have a negative predictive value of 98% in assessing residual or recurrent adenoma (RRA) at an EMR scar.
No studies to date have assessed the use of chromoendoscopy and the subsequent benefit of high-definition imaging (HD-WL + NBI) in predicting SMIC and RRA at an EMR scar.
Inclusion Criteria:
Exclusion Criteria: