Prediction of colorectal tumor grade and invasion depth through narrow-band imaging scoring

ARTICLE HIGHLIGHTS

Research background

Colonoscopy is currently the most useful examination method for finding, diagnosing, and treating colorectal lesions. When a lesion is found by colonoscopy, the surgeon must first determine whether it is nontumorous or tumorous. If it is tumorous, it must be assessed as adenoma or cancer. If it is cancer, it is essential to diagnose its depth. Intramucosal carcinomas are unlikely to metastasize, while carcinomas that invade into the submucosa (SM) are more likely to metastasize to the lymph nodes. Carcinomas with a depth of SM invasion < 1000 μm almost never metastasize, while those with a depth of SM invasion ≥ 1000 μm are more likely to metastasize. Accordingly, distinguishing which lesions have a depth of SM invasion < 1000 μm (indicated for endoscopic therapy) is important when selecting a treatment.

Narrow-band imaging (NBI) was recently developed as a novel form of image-enhanced endoscopy that has several advantages over chromoendoscopy. Not only is pigment not used, NBI allows for the acquisition of endoscopic images with a uniform mucosal pattern across images. Further, vascular findings in the mucosal surface, which are difficult to observe with chromoendoscopy, can be enhanced and observed in more detail with NBI. Several studies have reported that using NBI to observe the fine architecture of a lesion’s surface (surface pattern) and microvessels (vascular pattern) is useful for diagnosing the grade and depth of colorectal tumors. However, all of these studies placed endoscopic findings into categories expressed as numbers or letters. These can be difficult to use in actual clinical practice, particularly for inexperienced endoscopists. If the important findings observed using NBI can be appropriately selected and quantified, it would enable more precise predictions of colorectal tumor grade and depth, which would be extremely useful in deciding treatment strategies, including for endoscopic resection.

Research motivation

Several NBI-based classification systems have been proposed earlier. However, these systems are difficult to rely upon due to subjectivity and inter-observer variability. There is therefore a need to identify a more objective classification that can be easily interpreted by endoscopists during routine clinical practice.

Research objectives

We therefore wanted to determine a model for predicating tumor grade using NBI scores. We developed a multivariate statistical model for predicting tumor grades and invasion depths from NBI-finding scores. We determined the utility of this model in patients with a range of colorectal lesions and propose an efficient prediction model for diagnosing colorectal lesions and differentiating malignant lesions from pre-malignant adenomas. Such a model would then help clinicians determine the most appropriate therapeutic strategies.

Research methods

This was a retrospective examination of the correlations between NBI findings and histopathological findings at the site of colorectal tumorous lesions that were endoscopically or surgically resected after regular observation with colonoscopy and observation with NBI magnifying endoscopy. NBI findings and the tumor grade and depth of invasion at the site examined with NBI were analyzed using multivariate analysis based on a logistic regression model. The results were used to create a model for predicting tumor grade and depth. In addition, we performed the first-ever examination of correlations between colorectal tumor NBI findings and histopathological architecture.

Research results

This study demonstrated the usefulness of using statistical methods to score NBI findings to determine tumor grade. Using findings of both the surface pattern and vascular pattern, we created a model for predicting the grade and depth of colorectal tumors. Another novel finding of this study came from the comparison of colorectal tumor NBI findings and tissue architecture. Because clear contrast of vascular patterns can be obtained using NBI, it is possible to obtain relatively uniform images under any conditions. However, when observing surface patterns, the findings that are evaluated changed depending on the angle and rate of magnification. Therefore, further research is required to overcome these issues. This study was limited by only including Japanese subjects and because it was a single-center, retrospective study. Going forward, a prospective study that includes other institutions should be conducted.

Research conclusions

The NBI finding scoring system proposed in this study could be a useful marker for predicting tumor grade and depth of invasion in colorectal tumors, which could also be applied in deciding treatment plans. The sensitivity and specificity of this predictive model can be adjusted by changing the total score to suit the goal of the NBI examination. Previous results have indicated that to efficiently and precisely carry out endoscopic diagnostics and decide treatment plans for colorectal tumors, NBI should be performed first, then the sensitivity of the tumor grade predictive model should be increased to pick up as many carcinomas as possible. Next, the specificity of the depth predictive model should be increased to reduce over-surgery. Finally, chromoendoscopy should be used to observe the remaining lesions to diagnose their pit patterns. The results of this study indicate that “irregularity,” an NBI finding useful for diagnosing colorectal tumor grade, may reflect the presence of size disparities and irregular pathways in glandular ducts. An “avascular area” could reflect an amorphous region arising from reduced glandular duct density caused by exposure to a desmoplastic reaction. Further, “disrupted vessels,” an NBI finding useful in diagnosing the depth of tumor invasion, may indirectly reflect degeneration or prolapse of the lining epithelium caused by deep invasion of the tumor and consequent loss of the muscularis mucosae, which leads to fragility of the tumor surface. “Thick vessels” may reflect vascular congestion in the SM layer caused by massive tumor invasion.

Research perspectives

It would be helpful to conduct a prospective study that includes more cases using the predictive model proposed in this study.