Diffusion Weighted Imaging in Magnetic Resonance Imaging for Prostate Cancer Diagnosis: Current Efficiency as a Standalone Sequence for an Unenhanced MRI Experience - a Pilot Study

Autor: Adela Nechifor-Boilă, Călin Bogdan Chibelean, Angela Borda, Ioan Alin Nechifor-Boilă, Andrada Loghin
Rok vydání: 2016
Předmět:
Zdroj: Acta Medica Marisiensis, Vol 62, Iss 1, Pp 47-50 (2016)
ISSN: 2247-6113
DOI: 10.1515/amma-2015-0111
Popis: Objective: Diffusion Weighted Imaging (DWI) is the main sequence in the multiparametric prostate MRI protocol together with T2 and dynamic contrast-enhanced T1, leading to detection rates up to 60% in prostate cancer diagnosis. However, the use of intravenous contrast can have severe side-effects, making the use of unenhanced MRI sequences essential. The aim of our study was to assess the feasibility and efficiency of DWI as a standalone MRI technique for prostate cancer diagnosis. Methods: We performed a prospective cohort study at our department (09.2014-05.2015) and formed a study lot consisting in five prostate cancer patients that were scheduled for radical prostatectomy. Multiparametric MRI was performed (with DWI and T2 sequences) and the images were interpreted according to the PI-RADS system. The final histopathological result after prostatectomy served as gold standard. Results: A series of 9 lesions were detected and analyzed on DWI. At qualitative interpretation, DWI had a sensitivity of 85.7% and a specificity of 50%. The corresponding positive and negative likelihood ratios were 1.71 and 0.286, respectively (p=0.417). ADC analysis revealed a mean value of 1.2*10-3mm2/s for the benign lesions while the corresponding value was 0.8*10-3 for the malignant ones, regardless of tumor size and Gleason scoring. Conclusion: DWI is a feasible technique in the current clinical environment, with a good sensitivity and a medium specificity. Furthermore, an association to the anatomical T2 sequence could enhance the diagnostic efficiency of DWI and should be assessed in larger studies.
Databáze: OpenAIRE