OBJECTIVES: To investigate the impact of prostate computed diffusion-weighted imaging (DWI) on image quality and tumour detection. METHODS: Forty-nine patients underwent 3-T magnetic resonance imaging using a pelvic phased-array coil before prostatectomy, including DWI with b values of 50 and 1,000 s/mm(2). Computed DW images with b value 1,500 s/mm(2) were generated from the lower b-value images. Directly acquired b-1,500 DW images were obtained in 39 patients. Two radiologists independently assessed DWI for image quality measures and location of the dominant lesion. A third radiologist measured tumour-to-peripheral-zone (PZ) contrast. Pathological findings from prostatectomy served as the reference standard. RESULTS: Direct and computed b-1,500 DWI showed better suppression of benign prostate tissue than direct b-1,000 DWI for both readers (P ≤ 0.024). However, computed b-1,500 DWI showed less distortion and ghosting than direct b-1,000 and direct b-1,500 DWI for both readers (P ≤ 0.067). Direct and computed b-1,500 images showed better sensitivity and positive predictive value (PPV) for tumour detection than direct b-1,000 images for both readers (P ≤ 0.062), with no difference in sensitivity or PPV between direct and computed b-1,500 images (P ≥ 0.180). Tumour-to-PZ contrast was greater on computed b-1,500 than on either direct DWI set (P < 0.001). CONCLUSION: Computed DWI of the prostate using b value ≥1,000 s/mm(2) improves image quality and tumour detection compared with acquired standard b-value images. KEY POINTS: • Diffusion weighted MRI is increasingly used for diagnosing and assessing prostate carcinoma. • Prostate computed DWI can extrapolate high b-value images from lower b values. • Computed DWI provides greater suppression of benign tissue than lower b-value images. • Computed DWI provides less distortion and artefacts than images using same b value. • Computed DWI provides better diagnostic performance than lower b-value images.
OBJECTIVES: To investigate the impact of prostate computed diffusion-weighted imaging (DWI) on image quality and tumour detection. METHODS: Forty-nine patients underwent 3-T magnetic resonance imaging using a pelvic phased-array coil before prostatectomy, including DWI with b values of 50 and 1,000 s/mm(2). Computed DW images with b value 1,500 s/mm(2) were generated from the lower b-value images. Directly acquired b-1,500 DW images were obtained in 39 patients. Two radiologists independently assessed DWI for image quality measures and location of the dominant lesion. A third radiologist measured tumour-to-peripheral-zone (PZ) contrast. Pathological findings from prostatectomy served as the reference standard. RESULTS: Direct and computed b-1,500 DWI showed better suppression of benign prostate tissue than direct b-1,000 DWI for both readers (P ≤ 0.024). However, computed b-1,500 DWI showed less distortion and ghosting than direct b-1,000 and direct b-1,500 DWI for both readers (P ≤ 0.067). Direct and computed b-1,500 images showed better sensitivity and positive predictive value (PPV) for tumour detection than direct b-1,000 images for both readers (P ≤ 0.062), with no difference in sensitivity or PPV between direct and computed b-1,500 images (P ≥ 0.180). Tumour-to-PZ contrast was greater on computed b-1,500 than on either direct DWI set (P < 0.001). CONCLUSION: Computed DWI of the prostate using b value ≥1,000 s/mm(2) improves image quality and tumour detection compared with acquired standard b-value images. KEY POINTS: • Diffusion weighted MRI is increasingly used for diagnosing and assessing prostate carcinoma. • Prostate computed DWI can extrapolate high b-value images from lower b values. • Computed DWI provides greater suppression of benign tissue than lower b-value images. • Computed DWI provides less distortion and artefacts than images using same b value. • Computed DWI provides better diagnostic performance than lower b-value images.
Authors: Diederik M Somford; Caroline M Hoeks; Christina A Hulsbergen-van de Kaa; Thomas Hambrock; Jurgen J Fütterer; J Alfred Witjes; Chris H Bangma; Henk Vergunst; Geert A Smits; Jorg R Oddens; Inge M van Oort; Jelle O Barentsz Journal: Invest Radiol Date: 2013-03 Impact factor: 6.016
Authors: Andrew B Rosenkrantz; Xiangtian Kong; Benjamin E Niver; Douglas S Berkman; Jonathan Melamed; James S Babb; Samir S Taneja Journal: AJR Am J Roentgenol Date: 2011-01 Impact factor: 3.959
Authors: Simon R J Bott; Hashim U Ahmed; Richard G Hindley; Ahmad Abdul-Rahman; Alex Freeman; Mark Emberton Journal: BJU Int Date: 2010-12 Impact factor: 5.588
Authors: Deanna L Langer; Theodorus H van der Kwast; Andrew J Evans; Laibao Sun; Martin J Yaffe; John Trachtenberg; Masoom A Haider Journal: Radiology Date: 2008-12 Impact factor: 11.105
Authors: Wennuan Liu; Sari Laitinen; Sofia Khan; Mauno Vihinen; Jeanne Kowalski; Guoqiang Yu; Li Chen; Charles M Ewing; Mario A Eisenberger; Michael A Carducci; William G Nelson; Srinivasan Yegnasubramanian; Jun Luo; Yue Wang; Jianfeng Xu; William B Isaacs; Tapio Visakorpi; G Steven Bova Journal: Nat Med Date: 2009-04-12 Impact factor: 53.440
Authors: Andrew B Rosenkrantz; Luke A Ginocchio; Daniel Cornfeld; Adam T Froemming; Rajan T Gupta; Baris Turkbey; Antonio C Westphalen; James S Babb; Daniel J Margolis Journal: Radiology Date: 2016-04-01 Impact factor: 11.105
Authors: Kinzya B Grant; Harsh K Agarwal; Joanna H Shih; Marcelino Bernardo; Yuxi Pang; Dagane Daar; Maria J Merino; Bradford J Wood; Peter A Pinto; Peter L Choyke; Baris Turkbey Journal: Abdom Imaging Date: 2015-03