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Blue laser imaging combined with JNET (Japan NBI Expert Team) classification for pathological prediction of colorectal laterally spreading tumors

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Abstract

Background

Blue laser imaging (BLI) can provide useful information on colorectal laterally spreading tumors (LSTs) by visualizing the surface and vessel patterns in detail. The present research aimed to evaluate the diagnostic performance of BLI-combined JNET (Japan NBI Expert Team) classification for identifying LSTs.

Methods

This retrospective, multicenter study included 172 LSTs consisted of 6 hyperplastic polyps/sessile serrated polyps, 94 low-grade dysplasias (LGD), 60 high-grade dysplasias (HGD), 6 superficial submucosal invasive (m-SMs) carcinomas, and 4 deep submucosal invasive carcinomas. The relationship between the JNET classification and the histologic findings of these lesions were then analyzed.

Results

For all LSTs, non-experts and experts had a 79.7% and 90.7% accuracy for Type 2A (P = 0.004), a sensitivity of 94.7% and 96.8% (P = 0.718), and a specificity of 61.5% and 83.3% (P = 0.002) for prediction of LGD, respectively. The results also demonstrated 80.8% and 91.3% accuracy for Type 2B (P = 0.005), a sensitivity of 65.2% and 83.3% (P = 0.017), and a specificity of 90.6% and 96.2% (P = 0.097) for predicting HGD or m-SMs. For LST-granular (LST-G) lesions, Type 2A in experts had higher specificity (65.6% vs. 83.6%, P = 0.022) and accuracy (81.8% vs. 91.2%, P = 0.022). Type 2B in experts only had higher accuracy (82.5% vs. 92.0%, P = 0.019). However, no significant differences were noted for any comparisons between non-experts and experts for LST-non-granular (LST-NG) lesions.

Conclusions

BLI combined with JNET classification was an effective method for the precise prediction of pathological diagnosis in patients with LSTs. Diagnostic performance of JNET classification by experts was better than that by non-experts for all examined LST or LST-G lesions when delineating between Type 2A and 2B, but there was no difference for the identification of LST-NG lesions by these two groups.

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Acknowledgements

We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Funding

Funding was provided by National Natural Science Foundation of China (Grant No. 81800495).

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Authors and Affiliations

  1. Department of Gastroenterology, Shenzhen Hospital of Southern Medical University, Shenzhen, Guangdong, China

    Si-lin Huang

  2. Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China

    Wen-xin Tan, Qun Peng, Hai-tao Qing, Qiang Zhang & Wei-guang Qiao

  3. Department of Gastroenterology, The People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China

    Wen-hua Zhang

  4. Department of Gastroenterology, Nanhai Hospital, Southern Medical University, Foshan, Guangdong, China

    Jun Wu, Liang-dou Lin, Zhi-bin Lu & Yu Chen

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  1. Si-lin Huang
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Correspondence to Wei-guang Qiao.

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Si-lin Huang, Wen-xin Tan, Qun Peng, Wen-hua Zhang, Hai-tao Qing, Qiang Zhang, Jun Wu, Liang-dou Lin, Zhi-bin Lu, Yu Chen, Wei-guang Qiao have no conflicts of interest or financial ties to disclose.

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Huang, Sl., Tan, Wx., Peng, Q. et al. Blue laser imaging combined with JNET (Japan NBI Expert Team) classification for pathological prediction of colorectal laterally spreading tumors. Surg Endosc 35, 5430–5440 (2021). https://doi.org/10.1007/s00464-020-08027-z

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