Diffusion‐weighted imaging of the prostate: Comparison of b1000 and b2000 image sets for index lesion detection
Year: 2013
Type: article
Study design: Observational Study
Abstract: PURPOSE: To compare tumor detection on acquired diffusion-weighted (DW) images and apparent diffusion coefficient (ADC) maps, obtained using b-values of 1000 s/mm(2) and 2000 s/mm(2) , using radical prostatectomy as the reference. MATERIALS AND METHODS: In all, 29 prostate cancer patients who underwent 3T magnetic resonance imaging (MRI) including DW imaging using b-values of 1000 s/mm(2) and 2000 s/mm(2) were included. Two radiologists independently evaluated four image sets during different sessions and recorded the location and diameter of the dominant lesion: DW images acquired using b-values of 1000 s/mm(2) and 2000 s/mm(2) and ADC maps calculated using maximal b-values of 1000 s/mm(2) and 2000 s/mm(2) . Findings were correlated with the location and diameter of the dominant lesion at prostatectomy. Tumor-to-PZ contrast was also calculated, unblinded to pathology. RESULTS: Both readers achieved significantly higher sensitivity for DW images obtained using a b-value of 2000 s/mm(2) than 1000 s/mm(2) (P < 0.001), although there was no difference in sensitivity between ADC maps calculated using the two b-values (P ≥ 0.309). Tumor-to-PZ contrast was higher for DW images using a b-value of 2000 s/mm(2) (P = 0.067), although it was not different between the two corresponding ADC maps (P = 0.544). For both readers, correlations with tumor diameters were higher for either ADC map (r = 0.59-0.73) than for either acquired DW image set (r = 0.03-0.57). CONCLUSION: Use of a b-value of 2000 s/mm(2) compared with a b-value of 1000 s/mm(2) resulted in improved tumor sensitivity and higher tumor-to-PZ contrast on the acquired DW images, although performance of the ADC maps corresponding with the two b-values was similar. Correlation with tumor size was greater for either ADC map than for either acquired DW image set.
DOI: 10.1002/jmri.24016
Institution: NYU Langone Health
Language: English
Topic: MRI in cancer diagnosis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W1524482419