Related Experiment Video For MR imaging
Updated: Feb 11, 2026
Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
Published on: August 19, 2021
Improving lymph node characterization in staging malignant lymphoma using first-order ADC texture analysis from
Katja N De Paepe1, Frederik De Keyzer1, Pascal Wolter2
1Deparment of Radiology, University Hospitals Leuven, Belgium.
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/mm2 ).
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 (ADCmean ) was compared with first-order ADC texture parameters: standard deviation (ADCstdev ), kurtosis (ADCkurt ), and skewness (ADCskew ). Additional subanalyses focused on the accuracy of ADCmean 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:
ADCmean (P = 0.008), ADCskew and ADCkurt differed significantly between benign and malignant nodes (P < 0.001), while ADCstdev didn't (P = 0.21). ADCskew was the best discriminating parameter, with 79% sensitivity, 86% specificity, 83% accuracy, 85% PPV, and 81% NPV. In every volume category, ADCskew yielded the highest accuracy (88% in 0-25th percentile volume, 75% in 25th -75th percentile, 93% in 75-100th percentile). On a per-region basis, ADCskew accuracy varied 13.6% between nodal regions, while ADCmean , ADCkurt , and ADCstdev 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 ADCmean . ADCskew 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.
More Related Videos
12:53Collection and Processing of Lymph Nodes from Large Animals for RNA Analysis: Preparing for Lymph Node Transcriptomic Studies of Large Animal Species
Published on: May 19, 2018
09:10Generation of Lymph Node-fat Pad Chimeras for the Study of Lymph Node Stromal Cell Origin
Published on: December 16, 2013
Related Concept Videos
01:23Detailed Structure and Function of Lymph Nodes
From a histological perspective, lymph nodes can be split into two main areas: the superficial cortex and the deep medulla. The outer cortex is populated by dendritic cells, macrophages, and B lymphocytes, which are densely packed into follicles. When these B-lymphocytes are presented...
01:14Node Analysis for AC Circuits
To unravel the complexities of this system, nodal analysis is employed, a powerful technique founded on Kirchhoff's current law (KCL), which remains valid for phasors. AC circuits can effectively be...
01:12Diffusion
01:21Diffusion
01:25Shape and Texture of Coarse Aggregate
00:57Weighted Mean
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...