Diffusion‐weighted imaging of the prostate and rectal wall: comparison of biexponential and monoexponential modelled diffusion and associated perfusion coefficients

Abstract

This study compares parameters from monoexponential and biexponential modelling of diffusion-weighted imaging of normal and malignant prostate tissue and normal rectal wall tissues. Fifty men with Stage Ic prostate cancer were studied using endorectal T(2)-weighted imaging and diffusion-weighted imaging with 11 diffusion-sensitive values (b-values = 0, 1, 2, 4, 10, 20, 50, 100, 200, 400, 800 s/mm(2)). Regions of interest were drawn within non-malignant central gland and peripheral zone, malignant prostate tissue and normal rectal wall tissue. Both a monoexponential and biexponential model was fitted over various b-value ranges, giving an apparent diffusion coefficient (ADC) from the monoexponential model and a diffusion coefficient, perfusion coefficient and perfusion fraction from the biexponential model. In all tissues, over the full range of b-values, the ADC from the monoexponential model was significantly higher than the corresponding diffusion coefficient from the biexponential model. As the minimum b-value increased, the ADC decreased and was equal to the diffusion coefficient for some b-value ranges. The biexponential model best described the data when low b-values were included, suggesting that there is a fast perfusion component. Neither model could distinguish between benign prostate tissues on the basis of diffusion coefficients, but the rectal wall tissue and malignant prostate tissue had significantly lower diffusion coefficients than normal prostate tissues. Perfusion coefficients and fractions were highly variable within the population, so their clinical utility may be limited, but removal of this variable perfusion component from reported diffusion coefficients is important when attributing clinical differences to diffusion within tissues.

Diffusion-weighted magnetic resonance imaging for monitoring prostate cancer progression in patients managed by active surveillance

“…In addition, data obtained using just the low (0-300) or high (300-800) b-values were also analysed separately to reflect fast (ADC fast ) and slow (ADC slow ) diffusion components [12]. Values for ADC all , ADC fast and ADC slow were calculated in patients who progressed to radical treatment (n517) and compared with values from those that did not (n533).…”

Diffusion weighted imaging in prostate cancer

“…Potentially benign conditions that may falsely lower ADC include: (1) various abnormal conditions, such as prostatitis and the compact fibromuscular stroma seen in benign prostatic hyperplasia [10,44], (2) susceptibility artefact at tissue boundaries [45] and at areas of haemorrhage (Fig. 6), (3) elevated vascular flow associated with tumour [29], as well as (4) organ motion [24].…”

“…The fast diffusion component (large-scale bulk movement of molecules secondary to capillary flow) is studied at lower b-values. The slow diffusion component (related to the cellularity of tissues) is studied at relatively higher b-values [45]. The bi-exponential method of diffusion analysis theoretically eliminates the effects of perfusion, reflecting tissue diffusion characteristics to a closer degree [45,65].…”

“…The slow diffusion component (related to the cellularity of tissues) is studied at relatively higher b-values [45]. The bi-exponential method of diffusion analysis theoretically eliminates the effects of perfusion, reflecting tissue diffusion characteristics to a closer degree [45,65]. For this method, an extended range of b-values (b>1,000 sec/ mm 2 ) needs to be acquired.…”

Noninvasive Quantification of Solid Tumor Microstructure Using VERDICT MRI

“…The intravoxel incoherent motion (IVIM) model (10) assumes that tissue water resides in two nonexchanging compartments: vascular (pseudo-diffusing water inside blood vessels) and nonvascular (diffusing water in and around cells). IVIM has been used to study various cancer types, such as breast (11), prostate (12), pancreatic (13), and kidney (14) tumors, showing improvement in data description compared with the ADC. However, while the IVIM model acknowledges and separates out the additional signal from vascular water, its description of diffusion in the cellular component of the tissue remains simplistic; just as for the ADC, it does not account for cellular geometry and compartmentalization.…”