Hypovascular pancreas head adenocarcinoma: CT texture analysis for assessment of resection margin status and high-risk features
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OBJECTIVES: To determine if CT texture analysis features are associated with hypovascular pancreas head adenocarcinoma (PHA) postoperative margin status, nodal status, grade, lymphovascular invasion (LVI), and perineural invasion (PNI). METHODS: This Research Ethics Board-approved retrospective cohort study included 131 consecutive patients with resected PHA. Tumors were segmented on preoperative contrast-enhanced CT. Tumor diameter and texture analysis features including mean, minimum and maximum Hounsfield units, standard deviation, skewness, kurtosis, and entropy and gray-level co-occurrence matrix (GLCM) features correlation and dissimilarity were extracted. Two-sample t test and logistic regression were used to compare parameters for prediction of margin status, nodal status, grade, LVI, and PNI. Diagnostic accuracy was assessed using receiver operating characteristic curves and Youden method was used to establish cutpoints. RESULTS: Margin status was associated with GLCM correlation (p = 0.012) and dissimilarity (p = 0.003); nodal status was associated with standard deviation (p = 0.026) and entropy (p = 0.031); grade was associated with kurtosis (p = 0.031); LVI was associated with standard deviation (p = 0.047), entropy (p = 0.026), and GLCM correlation (p = 0.033) and dissimilarity (p = 0.011). No associations were found for PNI (p > 0.05). Logistic regression yielded an area under the curve of 0.70 for nodal disease, 0.70 for LVI, 0.68 for grade, and 0.65 for margin status. Optimal sensitivity/specificity was as follows: nodal disease 73%/72%, LVI 72%/65%, grade 55%/83%, and margin status 63%/66%. CONCLUSIONS: CT texture analysis features demonstrate fair diagnostic accuracy for assessment of hypovascular PHA nodal disease, LVI, grade, and postoperative margin status. Additional research is rapidly needed to identify these high-risk features with better accuracy. KEY POINTS: • CT texture analysis features are associated with pancreas head adenocarcinoma postoperative margin status which may help inform treatment decisions as a negative resection margin is required for cure. • CT texture analysis features are associated with pancreas head adenocarcinoma nodal disease, a poor prognostic feature. • Indicators of more aggressive pancreas head adenocarcinoma biology including tumor grade and LVI can be diagnosed using CT texture analysis with fair accuracy.
