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Tytuł:
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MRI Predictors of Malignant Transformation in Patients with Inverted Papilloma: A Decision Tree Analysis Using Conventional Imaging Features and Histogram Analysis of Apparent Diffusion Coefficients.
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Autorzy:
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Suh CH; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Lee JH; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea. .
Chung MS; Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea.
Xu XQ; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Sung YS; Clinical Research Center, Asan Medical Center, Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul, Korea.
Chung SR; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Choi YJ; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Baek JH; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
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Źródło:
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Korean journal of radiology [Korean J Radiol] 2021 May; Vol. 22 (5), pp. 751-758. Date of Electronic Publication: 2020 Nov 30.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Publication: October 2008-: Seoul, Korea : Korean Society of Radiology
Original Publication: Seoul, Korea : Korean Radiological Society, 2000-August 2008.
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MeSH Terms:
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Decision Trees*
Diffusion Magnetic Resonance Imaging*
Carcinoma, Squamous Cell/*diagnosis
Papilloma, Inverted/*diagnosis
Adult ; Aged ; Area Under Curve ; Carcinoma, Squamous Cell/pathology ; Female ; Head/diagnostic imaging ; Humans ; Male ; Middle Aged ; Neck/diagnostic imaging ; Papilloma, Inverted/pathology ; ROC Curve ; Retrospective Studies ; Sensitivity and Specificity
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References:
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Contributed Indexing:
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Keywords: Diffusion; Inverted papilloma; Magnetic resonance imaging
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Entry Date(s):
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Date Created: 20201208 Date Completed: 20210601 Latest Revision: 20210601
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Update Code:
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20240104
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PubMed Central ID:
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PMC8076834
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DOI:
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10.3348/kjr.2020.0576
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PMID:
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33289362
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Objective: Preoperative differentiation between inverted papilloma (IP) and its malignant transformation to squamous cell carcinoma (IP-SCC) is critical for patient management. We aimed to determine the diagnostic accuracy of conventional imaging features and histogram parameters obtained from whole tumor apparent diffusion coefficient (ADC) values to predict IP-SCC in patients with IP, using decision tree analysis.
Materials and Methods: In this retrospective study, we analyzed data generated from the records of 180 consecutive patients with histopathologically diagnosed IP or IP-SCC who underwent head and neck magnetic resonance imaging, including diffusion-weighted imaging and 62 patients were included in the study. To obtain whole tumor ADC values, the region of interest was placed to cover the entire volume of the tumor. Classification and regression tree analyses were performed to determine the most significant predictors of IP-SCC among multiple covariates. The final tree was selected by cross-validation pruning based on minimal error.
Results: Of 62 patients with IP, 21 (34%) had IP-SCC. The decision tree analysis revealed that the loss of convoluted cerebriform pattern and the 20th percentile cutoff of ADC were the most significant predictors of IP-SCC. With these decision trees, the sensitivity, specificity, accuracy, and C-statistics were 86% (18 out of 21; 95% confidence interval [CI], 65-95%), 100% (41 out of 41; 95% CI, 91-100%), 95% (59 out of 61; 95% CI, 87-98%), and 0.966 (95% CI, 0.912-1.000), respectively.
Conclusion: Decision tree analysis using conventional imaging features and histogram analysis of whole volume ADC could predict IP-SCC in patients with IP with high diagnostic accuracy.
Competing Interests: The authors have no potential conflicts of interest to disclose.
(Copyright © 2021 The Korean Society of Radiology.)
