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Relative apparent diffusion coefficient: a promising tool to differentiate metastatic from benign lymph nodes in
Wei Xing1, Jing Sheng, Jie Chen
1Department of Radiology, the Third Affiliated Hospital of Suzhou University, Changzhou, Jiangsu 213003, China.
The relative apparent diffusion coefficient (rADC) shows improved accuracy in distinguishing metastatic from benign lymph nodes compared to standard ADC values in animal models. Muscles serve as a reliable reference site for rADC measurements.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Diffusion-weighted imaging (DWI) is utilized for lymphadenopathy characterization.
- Prior studies show variability in DWI for lymph node differentiation.
- The study aimed to compare apparent diffusion coefficient (ADC) and relative ADC (rADC) for differentiating metastatic and benign lymph nodes.
Purpose of the Study:
- To evaluate the diagnostic performance of ADC and rADC in distinguishing metastatic from benign lymph nodes.
- To determine the optimal region of interest (ROI) for reliable rADC measurements.
- To assess the utility of muscle tissue as a reference site for rADC calculation.
Main Methods:
- Apparent diffusion coefficients (ADCs) were measured in rabbit lymph nodes and quadriceps muscles.
- Relative ADC (rADC) was calculated as the ratio of lesion ADC to reference site ADC.
- Receiver operating characteristic (ROC) analysis compared the diagnostic accuracy of ADC and rADC.
Main Results:
- Good interobserver agreement (ICC=0.816) was achieved with a five-pixel ROI.
- Statistically significant differences in ADC and rADC values were observed between metastatic and benign lymph nodes.
- rADC demonstrated a greater area under the ROC curve than ADC, with 93% sensitivity and 90% specificity at an rADC cutoff of 0.640.
Conclusions:
- Muscle tissue provides a repeatable reference site for rADC measurements.
- rADC enhances diagnostic accuracy for detecting metastatic lymph nodes in animal models.
- rADC shows potential as a valuable tool in preclinical cancer imaging.
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