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J Gastroenterol. 2004 Jun;39(6):534-43.

Correlations between lymph node metastasis and depth of submucosal invasion in submucosal invasive colorectal carcinoma: a Japanese collaborative study.

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  • 1Department of Surgical and Molecular Pathology, Dokkyo University School of Medicine, 880 Kitakobayashi, Mibu, Shimotsuga, 321-0293, Tochigi, Japan.

Abstract

BACKGROUND:

Depth of submucosal invasion (SM depth) in submucosal invasive colorectal carcinoma (SICC) is considered an important predictive factor for lymph node metastasis. However, no nationwide reports have clarified the relationship between SM depth and rate of lymph node metastasis. Our aim was to investigate the correlations between lymph node metastasis and SM depth in SICC.

METHODS:

SM depth was measured for 865 SICCs that were surgically resected at six institutions throughout Japan. For pedunculated SICC, the level 2 line according to Haggitt's classification was used as baseline and the SM depth was measured from this baseline to the deepest portion in the submucosa. When the deepest portion of invasion was limited to above the baseline, the case was defined as a head invasion. For nonpedunculated SICC, when the muscularis mucosae could be identified, the muscularis mucosae was used as baseline and the vertical distance from this line to the deepest portion of invasion represented SM depth. When the muscularis mucosae could not be identified due to carcinomatous invasion, the superficial aspect of the SICC was used as baseline, and the vertical distance from this line to the deepest portion was determined.

RESULTS:

For pedunculated SICC, rate of lymph node metastasis was 0% in head invasion cases and stalk invasion cases with SM depth <3000 micro m if lymphatic invasion was negative. For nonpedunculated SICC, rate of lymph node metastasis was also 0% if SM depth was <1000 micro m.

CONCLUSIONS:

These results clarified rates of lymph node metastasis in SICC according to SM depth, and may contribute to defining therapeutic strategies for SICC.

PMID:
15235870
[PubMed - indexed for MEDLINE]
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