Pathologic Subtypes of Ampullary Adenocarcinoma: Value of Ampullary MDCT for Noninvasive Preoperative Differentiation. AJR Am J Roentgenol. 2017;208:W71-W78. [PMID: 28095024 DOI: 10.2214/ajr.16.16723]

Analysis of Pancreatobiliary and Intestinal Type Periampullary Carcinomas Using Volumetric Apparent Diffusion Coefficient Histograms

RATIONALE AND OBJECTIVES

Magnetic resonance imaging plays an important role in the evaluation of patients with known or suspected periampullary masses. The utilization of volumetric apparent diffusion coefficient (ADC) histogram evaluation for the entire lesion eradicates the potential for subjectivity in the region of interest placement, thus guaranteeing the accuracy of computation and repeatability.

PURPOSE

To investigate the value of volumetric ADC histogram analysis in the differentiation of intestinal-type (IPAC) and pancreatobiliary-type periampullary adenocarcinomas (PPAC).

MATERIALS AND METHODS

This retrospective study included 69 patients with histopathologically confirmed periampullary adenocarcinoma (54 PPAC and 15 IPAC). Diffusion-weighted imaging was obtained at b values of 1000 mm²/s. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated independently by two radiologists. Using the interclass correlation coefficient, the interobserver agreement was evaluated.

RESULTS

The ADC parameters for the PPAC group were all lower than those of the IPAC group. The PPAC group had higher variance, skewness, and kurtosis than the IPAC group. However, the difference between the kurtosis (P = .003), the 5th (P = .032), 10th (P = .043), and 25th (P = .037) percentiles of ADC values was statistically significant. The area under the curve (AUC) of the kurtosis was the highest (AUC=0.752; cut-off value=-0.235; sensitivity=61.1%; specificity=80.0%).

CONCLUSION

Volumetric ADC histogram analysis with b values of 1000 mm²/s can discriminate subtypes noninvasively before surgery.

Prediction of tumor recurrence and poor survival of ampullary adenocarcinoma using preoperative clinical and CT findings

OBJECTIVES

To predict poor survival and tumor recurrence in patients with ampullary adenocarcinoma using preoperative clinical and CT findings.

MATERIALS AND METHODS

A total of 216 patients with ampullary adenocarcinoma who underwent preoperative CT and surgery were retrospectively included. CT was assessed by two radiologists. Clinical and histopathological characteristics including histologic subtypes were investigated. A Cox proportional hazard model and the Kaplan-Meier method were used to identify disease-free survival (DFS) and overall survival (OS). A nomogram was created based on the multivariate analysis. The optimal cutoff size of the tumor was evaluated and validated by internal cross validation.

RESULTS

The median OS was 62.8 ± 37.9, and the median DFS was 54.3 ± 41.2 months. For OS, tumor size (hazard ratio [HR] 2.79, p < 0.001), papillary bulging (HR 0.63, p = 0.049), organ invasion on CT (HR 1.92, p = 0.04), male sex (HR 1.59, p = 0.046), elevated CA 19-9 (HR 1.92, p = 0.01), pT stage (HR 2.45, p = 0.001), and pN stage (HR 3.04, p < 0.001) were important predictors of survival. In terms of recurrence, tumor size (HR 2.37, p = 0.04), pT stage (HR 1.76, p = 0.03), pN stage (HR 2.23, p = 0.001), and histologic differentiation (HR 4.31, p = 0.008) were important predictors of recurrence. In terms of tumor size on CT, 2.65 cm and 3.15 cm were significant cutoff values for poor OS and RFS (p < 0.001).

CONCLUSION

Preoperative clinical and CT findings were useful to predict the outcomes of ampullary adenocarcinoma. In particular, tumor size, papillary bulging, organ invasion on CT, male sex, and elevated CA 19-9 were important predictors of poor survival after surgery.

KEY POINTS

• Clinical staging based on preoperative clinical information and CT findings can be useful to predict the prognosis of ampullary adenocarcinoma patients. • In terms of survival, tumor size (HR 2.79), papillary bulging (HR 0.63), organ invasion on CT (HR 1.92), male sex (HR 1.59), and elevated CA 19-9 (HR 1.92) were important clinical predictors of poor survival. • Tumor size on CT was of special importance for both poor overall survival and disease-free survival, with optimal cutoff values of 2.65 cm and 3.15 cm, respectively (p < 0.001).

Apparent diffusion coefficient-based histogram analysis differentiates histological subtypes of periampullary adenocarcinoma

BACKGROUND

For periampullary adenocarcinoma, the histological subtype is a better prognostic predictor than the site of tumor origin. Intestinal-type periampullary adenocarcinoma (IPAC) is reported to have a better prognosis than the pan-creatobiliary-type periampullary adenocarcinoma (PPAC). However, the classification of histological subtypes is difficult to determine before surgery. Apparent diffusion coefficient (ADC) histogram analysis is a noninvasive, non-enhanced method with high reproducibility that could help differentiate the two subtypes.

AIM

To investigate whether volumetric ADC histogram analysis is helpful for distinguishing IPAC from PPAC.

METHODS

Between January 2015 and October 2018, 476 consecutive patients who were suspected of having a periampullary tumor and underwent magnetic resonance imaging (MRI) were reviewed in this retrospective study. Only patients who underwent MRI at 3.0 T with different diffusion-weighted images (b-values = 800 and 1000 s/mm²) and who were confirmed with a periampullary adenocarcinoma were further analyzed. Then, the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values and ADC_min, ADC_max, kurtosis, skewness, and entropy were obtained from the volumetric histogram analysis. Comparisons were made by an independent Student's t-test or Mann-Whitney U test. Multiple-class receiver operating characteristic curve analysis was performed to determine and compare the diagnostic value of each significant parameter.

RESULTS

In total, 40 patients with histopathologically confirmed IPAC (n = 17) or PPAC (n = 23) were enrolled. The mean, 5th, 25th, 50th, 75th, 90th, and 95th percentiles and ADC_max derived from ADC₁₀₀₀ were significantly lower in the PPAC group than in the IPAC group (P < 0.05). However, values derived from ADC₈₀₀ showed no significant difference between the two groups. The 75th percentile of ADC₁₀₀₀ values achieved the highest area under the curve (AUC) for differentiating IPAC from PPAC (AUC = 0.781; sensitivity, 91%; specificity, 59%; cut-off value, 1.50 × 10^-3 mm²/s).

CONCLUSION

Volumetric ADC histogram analysis at a b-value of 1000 s/mm² might be helpful for differentiating the histological subtypes of periampullary adenocarcinoma before surgery.

Assessment of tumor heterogeneity: Differentiation of periampullary neoplasms based on CT whole-lesion histogram analysis

PURPOSE

To investigate the utility of whole-lesion histogram analysis from multidetector computed tomography (MDCT) for discrimination of duodenal adenocarcinoma (DAC), pancreatic ductal adenocarcinoma (PDAC) and gastrointestinal stromal tumor (GIST) around the periampullary area.

MATERIALS AND METHODS

171 patients suspicious of periampullary tumors were examined by MDCT (arterial and venous phases) and treated with surgery. A total of 74 patients were finally included in this retrospective study (26 DACs, 20 PDACs, and 28 GISTs). The interobserver agreement was evaluated by intra-class correlation coefficient (ICC) test between two radiologists. Volumetric histogram analysis based on CT Kinetics software was performed on enhanced MDCT images that recorded different histogram parameters of arterial and venous phases, including mean, median, 10th, 25th, 75th, and 90th percentiles, as well as skewness, kurtosis and entropy. The extracted histogram parameters were compared between DAC, PDAC and GIST respectively by Mann-Whitney U tests with Bonferroni corrections. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic ability of each significant parameter and the area under the curve (AUC) was calculated.

RESULTS

The whole-lesion CT histogram analysis demonstrated significant differences between DAC, PDAC, and GIST with different histogram features on both arterial and venous phase scans (all P < 0.05). In the ROC analysis, the 90th percentile of venous phase demonstrated the highest AUC of 0.854 (P < 0.001) for discriminating DAC from PDAC. Excellent discriminators of periampullary tumors were noted among the histogram features, namely the 90th percentile of arterial phase, which demonstrated AUCs of 0.809 and 0.936 (P < 0.001) respectively for distinguishing DAC and PDAC from GIST.

CONCLUSION

The whole-lesion CT histogram analysis could be useful for differential diagnosis of DAC, PDAC and GIST arising from the periampullary area. Further assessment is warranted to investigate the clinical role of histogram analysis based on MDCT.