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Diagnostic value of tumor blood flow and its histogram analysis obtained with pCASL to differentiate sinonasal malignant lymphoma from squamous cell carcinoma

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Title: Diagnostic value of tumor blood flow and its histogram analysis obtained with pCASL to differentiate sinonasal malignant lymphoma from squamous cell carcinoma
Authors: Fujima, Noriyuki Browse this author →KAKEN DB
Kameda, Hiroyuki Browse this author
Tsukahara, Akiko Browse this author
Yoshida, Daisuke Browse this author
Sakashita, Tomohiro Browse this author →KAKEN DB
Homma, Akihiro Browse this author →KAKEN DB
Tha, Khin Khin Browse this author →KAKEN DB
Kudo, Kohsuke Browse this author →KAKEN DB
Shirato, Hiroki Browse this author →KAKEN DB
Keywords: Tumor blood flow
Pseudo-continuous arterial spin labeling
Squamous cell carcinoma
Malignant lymphoma
Issue Date: Nov-2015
Publisher: Elsevier
Journal Title: European journal of radiology
Volume: 84
Issue: 11
Start Page: 2187
End Page: 2193
Publisher DOI: 10.1016/j.ejrad.2015.07.026
PMID: 26277497
Abstract: Objectives: To investigate the diagnostic value of tumor blood flow (TBF) obtained with pseudocontinuous arterial spin labeling (pCASL) for the differentiation of squamous cell carcinoma (SCC) and malignant lymphoma (ML) in the nasal or sinonasal cavity. Methods: Thirty-three patients with SCC and 6 patients with ML in the nasal or sinonasal cavity were retrospectively analyzed. Quantitative TBF values were obtained using whole-tumor region of interest (ROI) from pCASL data. The histogram analysis of TBF values within the tumor ROI was also performed by calculating the coefficient of variation (CV), kurtosis, and skewness. The mean TBF value, histogram CV, kurtosis and skewness of the patients with SCC were compared with those of the ML patients. The diagnostic accuracy to differentiate SCC from ML was also calculated by receiver operating characteristic (ROC) curve analysis. In addition, multiple logistic regression models were also performed to determine their independent predictive value, and diagnostic accuracy with the combined use of these parameters. Results: Between the SCC and ML groups, significant differences were observed in mean TBF, CV, and kurtosis, but not in skewness. In ROC curve analysis, the diagnostic accuracy values for the differentiation of SCC from ML in mean TBF, CV, and kurtosis were all 0.87, respectively. Multiple logistic regression models revealed TBF and CV were respectively independent predictive value. With the combination of these parameters, the diagnostic accuracy was elevated to 0.97. Conclusions: The TBF value and its histogram analysis obtained with pCASL can help differentiate SCC and ML.
Rights: © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Type: article (author version)
Appears in Collections:北海道大学病院 (Hokkaido University Hospital) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
国際連携研究教育局 : GI-CoRE (Global Institution for Collaborative Research and Education : GI-CoRE) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 藤間 憲幸

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