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Improving lymph node characterization in staging malignant lymphoma using first‐order ADC texture analysis from whole‐body diffusion‐weighted MRI
Author(s) -
De Paepe Katja N.,
De Keyzer Frederik,
Wolter Pascal,
Bechter Oliver,
Dierickx Daan,
Janssens Ann,
Verhoef Gregor,
Oyen Raymond,
Vandecaveye Vincent
Publication year - 2018
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.26034
Subject(s) - medicine , effective diffusion coefficient , nuclear medicine , lymph node , diffusion mri , receiver operating characteristic , radiology , population , magnetic resonance imaging , pathology , environmental health
Background Correct staging and treatment initiation in malignant lymphoma depends on accurate lymph node characterization. However, nodal assessment based on conventional and diffusion‐weighted (DWI) MRI remains challenging, particularly in smaller nodes. Purpose To evaluate first‐order apparent diffusion coefficient (ADC) texture parameters compared to mean ADC for lymph node characterization in non‐Hodgkin lymphoma (NHL) using whole‐body DWI (WB‐DWI). Study Type Retrospective. Population Twenty‐eight patients with NHL. Field Strength/Sequence 3T whole‐body DWI using two b‐values (0–1000 s/mm 2 ). Assessment Regions of interest were drawn on the three most hyperintense lymph nodes on b1000‐images, irrespective of size, in all nodal body regions. Diagnostic performance of mean ADC (ADC mean ) was compared with first‐order ADC texture parameters: standard deviation (ADC stdev ), kurtosis (ADC kurt ), and skewness (ADC skew ). Additional subanalyses focused on the accuracy of ADC mean and ADC texture parameters in different lymph node volumes and nodal regions. Statistical Tests Benign and malignant nodes were compared using Mann–Whitney U ‐tests with 18‐Fluoro‐deoxyglucose positron emission tomography computed tomography and bone marrow biopsy as reference standard. Receiver operating characteristic analyses were performed to determine cutoff values and calculate sensitivity, specificity, accuracy, and positive and negative predictive value (PPV, NPV). Results ADC mean ( P = 0.008), ADC skew and ADC kurt differed significantly between benign and malignant nodes ( P < 0.001), while ADC stdev didn't ( P = 0.21). ADC skew was the best discriminating parameter, with 79% sensitivity, 86% specificity, 83% accuracy, 85% PPV, and 81% NPV. In every volume category, ADC skew yielded the highest accuracy (88% in 0–25 th percentile volume, 75% in 25 th –75 th percentile, 93% in 75–100 th percentile). On a per‐region basis, ADC skew accuracy varied 13.6% between nodal regions, while ADC mean , ADC kurt , and ADC stdev showed interregional variation of 17.4%, 20.3%, and 14.9%, respectively. Data Conclusion First‐order ADC texture analysis with WB‐DWI improved lymph node characterization compared to ADC mean . ADC skew was the most accurate and robust discriminatory parameter over all lymph node volumes and nodal body regions. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:897–906.