Colorectal carcinoma: Ex vivo evaluation using q-space imaging; Correlation with histopathologic findings

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Abstract

Background:

Although the prognosis of colorectal carcinoma (CRC) patients depends on the histologic grade (HG) and lymph node metastasis (LNM), accurate preoperative assessment of these prognostic factors is often difficult.

Purpose:

To assess the HG and extent of LNM by q-space imaging (QSI) for preoperative diagnosis of CRC.

Study Type:

Prospective.

Specimen:

A total of 20 colorectal tissue samples containing adenocarcinomas and resected lymph nodes (LNs).

Field Strength/Sequence:

QSI was performed with a 3T MRI system using a diffusion-weighted echo-planar imaging sequence: repetition time, 10,000 msec; echo time, 216 or 210 msec; field of view, 113 × 73.45 mm; matrix, 120 × 78; section thickness, 4 mm; and 11 b values ranging from 0 to 9000 s/mm2.

Assessment:

The mean displacement (MDP; μm), zero-displacement probability (ZDP; arbitrary unit [a.u.]), kurtosis (K; a.u.), and apparent diffusion coefficient (ADC) were analyzed by two observers and compared with histopathologic findings.

Statistical Tests:

Spearman's rank correlation coefficient, Mann–Whitney U-test, and ROC curve analyses.

Results:

For all 20 carcinomas, the MDP, ZDP, K, and ADC were 8.87 ± 0.37 μm, 82.0 ± 6.2 a.u., 74.3 ± 3.0 a.u., and 0.219 ± 0.040 × 10−3 mm2/s, respectively. The MDP (r = –0.768; P < 0.001), ZDP (r = 0.768; P < 0.001), and K (r = 0.785; P < 0.001) were significantly correlated with the HG of CRC, but not the ADC (r = 0.088; P = 0.712). There were also significant differences in the MDP, ZDP, and K between metastatic and nonmetastatic LNs (all, P < 0.001), but not the ADC (P = 0.082). In the HG of CRC and LNM, the area under the curve was significantly greater for MDP, ZDP, and K than for ADC.

Data Conclusion:

QSI provides useful diagnostic information to assess the HG and extent of LNM in CRC.

Data Conclusion:

Level of Evidence: 1

Data Conclusion:

Technical Efficacy: Stage 2

Data Conclusion:

J. Magn. Reson. Imaging 2018.

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