Annals of surgical oncology · 2017
CT Density in the Pancreas is a Promising Imaging Predictor for Pancreatic Ductal Adenocarcinoma.
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Fukuda Yasunari, Yamada Daisaku, Eguchi Hidetoshi, Hata Tomoki, Iwagami Yoshifumi, Noda Takehiro, Asaoka Tadafumi, Kawamoto Koichi, Gotoh Kunihito, Kobayashi Shogo, Takeda Yutaka, Tanemura Masahiro, Mori Masaki, Doki Yuichiro
Аннотация
BACKGROUND: Fatty pancreas (FP) was recently recognized as a risk factor for pancreatic ductal adenocarcinoma (PDAC). It is unclear whether computed tomography (CT) can be used to make a FP diagnosis. This study investigated whether CT could provide a predictive value for PDAC by diagnosing FP.
METHODS: The study included 183 consecutive patients who underwent distal pancreatectomy from February 2007 to January 2017, including 75 cases of PDAC and 108 cases of other pancreatic disease. Pancreatic CT density (pancreatic index; PI) at the initial diagnosis was calculated by dividing the CT number in the pancreas by the number in the spleen. To assess whether CT could be used to detect FP, 43 cases were evaluated pathologically for FP. We investigated the correlation between FP and PI, and determined the optimal PI cutoff value for detecting FP using receiver operating characteristics analysis. We then investigated whether the PI value could be used as a predictor for PDAC.
RESULTS: Fourteen cases (32.6%) were pathologically diagnosed with FP. PI was significantly lower in the FP group versus the non-FP group (0.51 vs. 0.83; p = 0.0049). ROC analysis indicated that the PI had good diagnostic accuracy for FP diagnosis (cutoff value 0.70; sensitivity 0.79, specificity 0.79). Low PI (≤0.70) was identified in the multivariate analysis as an independent risk factor for PDAC (odds ratio 2.31; p = 0.023).
CONCLUSIONS: PI was strongly associated with pathological FP, which was independently associated with PDAC. PI shows promise as an imaging predictor for PDAC.
METHODS: The study included 183 consecutive patients who underwent distal pancreatectomy from February 2007 to January 2017, including 75 cases of PDAC and 108 cases of other pancreatic disease. Pancreatic CT density (pancreatic index; PI) at the initial diagnosis was calculated by dividing the CT number in the pancreas by the number in the spleen. To assess whether CT could be used to detect FP, 43 cases were evaluated pathologically for FP. We investigated the correlation between FP and PI, and determined the optimal PI cutoff value for detecting FP using receiver operating characteristics analysis. We then investigated whether the PI value could be used as a predictor for PDAC.
RESULTS: Fourteen cases (32.6%) were pathologically diagnosed with FP. PI was significantly lower in the FP group versus the non-FP group (0.51 vs. 0.83; p = 0.0049). ROC analysis indicated that the PI had good diagnostic accuracy for FP diagnosis (cutoff value 0.70; sensitivity 0.79, specificity 0.79). Low PI (≤0.70) was identified in the multivariate analysis as an independent risk factor for PDAC (odds ratio 2.31; p = 0.023).
CONCLUSIONS: PI was strongly associated with pathological FP, which was independently associated with PDAC. PI shows promise as an imaging predictor for PDAC.