Anticancer research · 2018
Relationship Among Tumor Attenuation Value of Pre-contrast Computed Tomography (CT), Washout Rate and Constituent Cells in Adrenal Adenoma: Proposition of a New Approach for Diagnosing Adrenal Adenoma on Dynamic CT.
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Nishie Akihiro, Sugimoto Masaaki, Asayama Yoshiki, Ishigami Kousei, Ushijima Yasuhiro, Takayama Yukihisa, Okamoto Daisuke, Fujita Nobuhiro, Yokomizo Akira, Tatsugami Katsunori, Honda Hiroshi
Аннотация
AIM: To elucidate the relationship among tumor attenuation of pre-contrast-enhanced (TApre) computed tomography (CT), washout rate and clear cell ratio (CCR) in adrenal adenoma (AA) and propose a new approach for diagnosing AA on dynamic CT.
MATERIALS AND METHODS: The training set consisted of 43 AAs and 15 non-AAs, while the validation set comprised 44 AAs and 11 non-AAs. Using the training set, the pairwise correlation between CCR, TApre and washout rate in AA was evaluated by linear regression analysis. A predictive formula for diagnosing AA was established by multiple logistic regression analysis using washout rate and TApre. Using the validation set, the diagnostic performance of this formula was investigated by comparing with the conventional diagnostic criteria: TApre ≤10 HU or washout rate ≥an optimal threshold calculated in the training set.
RESULTS: Washout rate increased as CCR decreased, and as TApre increased. The formula predicting the probability of AA was: p(AA)=1/{1+exp(-1.5257+0.4923× TApre-0.3264×washout rate)}. Diagnostic performance of this formula was sensitivity of 93.2% and accuracy of 89.1%, while for the conventional diagnostic criteria, sensitivity was 81.8-86.4% and accuracy 81.8-83.6%.
CONCLUSION: The diagnostic potential of dynamic CT for diagnosing AA may be improved by changing the threshold of washout rate based on substituting TApre for CCR.
MATERIALS AND METHODS: The training set consisted of 43 AAs and 15 non-AAs, while the validation set comprised 44 AAs and 11 non-AAs. Using the training set, the pairwise correlation between CCR, TApre and washout rate in AA was evaluated by linear regression analysis. A predictive formula for diagnosing AA was established by multiple logistic regression analysis using washout rate and TApre. Using the validation set, the diagnostic performance of this formula was investigated by comparing with the conventional diagnostic criteria: TApre ≤10 HU or washout rate ≥an optimal threshold calculated in the training set.
RESULTS: Washout rate increased as CCR decreased, and as TApre increased. The formula predicting the probability of AA was: p(AA)=1/{1+exp(-1.5257+0.4923× TApre-0.3264×washout rate)}. Diagnostic performance of this formula was sensitivity of 93.2% and accuracy of 89.1%, while for the conventional diagnostic criteria, sensitivity was 81.8-86.4% and accuracy 81.8-83.6%.
CONCLUSION: The diagnostic potential of dynamic CT for diagnosing AA may be improved by changing the threshold of washout rate based on substituting TApre for CCR.