scholarly journals ADC mapping with 12 b values: an improved technique for image quality in diffusion prostate MRI

2019 ◽  
Author(s):  
Lucas Scatigno Saad ◽  
George de Queiroz Rosas ◽  
Homero José de Farias e Melo ◽  
Henrique Armando Azevedo Gabriele ◽  
Jacob Szejnfeld

AbstractPurposeTo compare diffusion images and coefficients obtained with 4 b-value versus 12 b-value apparent diffusion coefficient (ADC) mapping for characterization of prostate lesions and how these coefficients relate and compare to the PI-RADS™ classification and Gleason grading system.MethodsPatients with indications for prostate cancer testing (n=158) underwent multiparametric 3T magnetic resonance imaging (MRI). Two diffusion sequences were acquired, one with 4 b values and one with 12 b values. ADC maps were calculated for each (ADC4 and ADC12) and the respective coefficients were tested for correlation with PI-RADS™ classification and Gleason score.ResultsThe ADC12 sequence produced images of superior quality and sharpness than ADC4. Normal-area means (ADC4, 1793.3×10−6mm2/s; ADC12, 1100×10−6mm2/s) were significantly lower than those of lesion areas (ADC4, 1105.9×10−6mm2/s; ADC12, 689.4×10−6mm2/s) (p<0.001). Both techniques behaved similarly and correlated well with PI-RADS™ classification, distinguishing scores 3, 4, and 5 and with means tending to decline with increasing Gleason grade. ADC12 mapping yielded higher specificity than ADC4 (82.6% vs. 72.3%).ConclusionsDiffusion with 12 values is a viable technique for examination of the prostate. It produced higher-quality images than current techniques and correlates well with PI-RADS™ classification and Gleason score.

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 594
Author(s):  
Anna Damascelli ◽  
Francesca Gallivanone ◽  
Giulia Cristel ◽  
Claudia Cava ◽  
Matteo Interlenghi ◽  
...  

Radiomics allows the extraction quantitative features from imaging, as imaging biomarkers of disease. The objective of this exploratory study is to implement a reproducible radiomic-pipeline for the extraction of a magnetic resonance imaging (MRI) signature for prostate cancer (PCa) aggressiveness. One hundred and two consecutive patients performing preoperative prostate multiparametric magnetic resonance imaging (mpMRI) and radical prostatectomy were enrolled. Multiparametric images, including T2-weighted (T2w), diffusion-weighted and dynamic contrast-enhanced images, were acquired at 1.5 T. Ninety-three imaging features (Ifs) were extracted from segmentation of index lesion. Ifs were ranked based on a stability rank and redundant Ifs were excluded. Using unsupervised hierarchical clustering, patients were grouped on the basis of similar radiomic patterns, whose association with Gleason Grade Group (GGG), extracapsular extension (ECE), and nodal involvement (pN) was tested. Signatures composed by IFs from T2w-images and Apparent Diffusion Coefficient (ADC) maps were tested for the prediction of GGG, ECE, and pN. T2w radiomic pattern was associated with pN, ECE, and GGG (p = 0.027, 0.05, 0.03) and ADC radiomic pattern was associated with GGG (p = 0.004). The best performance was reached by the signature combing IFs from multiparametric images (0.88, 0.89, and 0.84 accuracy for GGG, pN, and ECE). A reliable multiparametric MRI radiomic signature was extracted, potentially able to predict PCa aggressiveness, to be further validated on an independent sample.


1989 ◽  
Vol 17 (4_part_1) ◽  
pp. 613-616 ◽  
Author(s):  
G. Allan Johnson ◽  
Robert R. Maronpot

Magnetic resonance imaging (MRI) is a new imaging technique used in clinical diagnosis. This paper describes extension of the technique to basic research applications–specifically detecting and characterizing chemically-induced liver neoplasms and foci of cellular alteration. Two systems have been built that allow spatial microscopic resolution–more than 100,000 x greater than that of earlier efforts. Use of spin-lattice (T1) and spin-spin (T2) relaxation times permits detailed characterization of the tissue.


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