Predictive value of tumor vessel density from enhanced spiral CT scan for lymph node and distant metastasis of colorectal cancer / 中华胃肠外科杂志
Chinese Journal of Gastrointestinal Surgery
;
(12): 448-450, 2013.
Article
in Chinese
| WPRIM
| ID: wpr-357214
ABSTRACT
<p><b>OBJECTIVE</b>To test whether the tumor vessel density (TVD) from the enhanced spiral CT can preoperatively predict nodal status and distant metastasis of colorectal cancer.</p><p><b>METHODS</b>Forty cases of colorectal cancer patients who received surgical treatment were included in this study. The three dimensional tumor vessels were reconstructed by an enhanced CT 64-slice spiral CT and its AW4.4 image processing platform. The TVD was measured by the 1000 high-resolution color graphics pathological analysis system. The TVD level was compared between different tumor size, classification, and TNM stage. The postoperative pathological staging was taken as golden standard.</p><p><b>RESULTS</b>The sensitivity, specificity and accuracy for direct prediction of lymph node metastasis by the enhanced CT 64-slice spiral CT was 74.1%(20/27), 53.8%(7/13) and 67.5%(27/40) respectively. The TVD from the reconstructed three dimensional tumor vessels in the group with lymph node metastasis was significantly higher than that without metastasis(0.070±0.046 vs. 0.037±0.013, P<0.05). The TVD in the distant metastasis group was significantly higher than that without distant metastasis (0.130±0.032 vs. 0.049±0.030, P<0.01). No difference of TVD was found between different tumor size, invasion depth, and differentiation type.</p><p><b>CONCLUSION</b>TVD level from the reconstructed three dimensional tumor vessels can indicate lymph node and distant metastasis of colorectal cancer.</p>
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Colorectal Neoplasms
/
Tomography, Spiral Computed
/
Lymph Nodes
/
Lymphatic Metastasis
/
Neoplasm Staging
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Chinese Journal of Gastrointestinal Surgery
Year:
2013
Type:
Article
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