Diagnostic value of ADC in patients with prostate cancer: influence of the choice of b-values. Eur Radiol. 2012;22:1820-1828. [PMID: 22527373 DOI: 10.1007/s00330-012-2432-3]

High b value (2,000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3 Tesla: comparison with 1,000 s/mm2 for tumor conspicuity and discrimination of aggressiveness

Objective

The objective of our study was to investigate tumor conspicuity and the discrimination potential for tumor aggressiveness on diffusion-weighted magnetic resonance imaging (DW-MRI) with high b value at 3-T.

Materials and Methods

The institutional review board approved this study and waived the requirement for informed consent. A total of 50 patients with prostate cancer (69 cancer foci; 48 in the PZ, 20 in the TZ, and one in whole prostate) who underwent multiparametric prostate MRI including DW-MRI (b values: 0, 1000 s/mm² and 0, 2000 s/mm²) on a 3-T system were included. Lesion conspicuity score (LCS) using visual assessment (1 = invisible for surrounding normal site; 2 = slightly high intensity; 3 = moderately high; and 4 = very high) and tumor-normal signal intensity ratio (TNR) were assessed, and apparent diffusion coefficient (ADC, ×10⁻³ mm²/s) of the tumor regions and normal regions were measured.

Results

Mean LCS and TNR at 0, 2000 s/mm² was significantly higher than those at 0, 1000 s/mm² (p<0.001 for both). In addition, ADC at both 0, 1000 and 0, 2000 s/mm² was found to distinguish intermediate or high risk cancer with Gleason score ≥7 from low risk cancer with Gleason score ≤6 (p<0.001 for both). Furthermore, ADC of tumor regions correlated with Gleason score at both 0, 1000 s/mm² (ρ = −0.602; p<0.001) and 0, 2000 s/mm² (ρ = −0.645; p<0.001).

Conclusions

For tumor conspicuity and characterization of prostate cancer on DW-MRI of 3-T MRI, b = 0, 2000 s/mm² is more useful than b = 0, 1000 s/mm².

Apparent diffusion coefficient for prostate cancer imaging: impact of B values

OBJECTIVE

The purpose of this article is to investigate the effect of b values on apparent diffusion coefficient (ADC) values estimated from 1.5-T diffusion-weighted MRI (DWI) of the prostate acquired with an endorectal coil in distinguishing prostate cancer from normal-tissue regions of interest (ROIs) and the correlation of ADC values with the tumor Gleason score.

MATERIALS AND METHODS

Pretreatment DWI studies were analyzed retrospectively in 51 consecutive patients with prostate cancer with either two (b=0 and 1000 s/mm2; n=26 patients) or five (b=0, 50, 200, 1500, and 2000 s/mm2; n=25 patients) b values. In 45 normal peripheral-zone ROIs and 65 prostate cancer ROIs (14 in the central gland), ADC values were estimated by use of several combinations of two or five b values and a monoexponential model. We used the area under the receiver operating characteristic curve to characterize the effectiveness of ADC values in distinguishing prostate cancer from normal-tissue ROIs, and we calculated Spearman rank-order correlation between ADC values and the Gleason score.

RESULTS

ADC values were often significantly different (p<0.001) when estimated from different combinations of two or five b values. However, except when both b values were less than or equal to 200 mm2/s or greater than or equal to 1500 mm2/s, the AUC value for distinguishing prostate cancer from normal-tissue ROIs was similar (0.88-0.93). The correlation coefficients between ADC values and the Gleason score were between -0.30 and -0.68.

CONCLUSION

The choice of b values can significantly affect ADC estimates. ADC values can produce a similar discriminant performance in distinguishing prostate cancer from normal-tissue ROIs and in correlation with the Gleason score, but an appropriate ADC cutoff value needs to be selected specifically for each b-value combination.

Diffusion-weighted MRI and its role in prostate cancer

In the last 5 years, the multiparametric approach has been investigated as the method for the MRI of prostate cancer. In multiparametric MRI of the prostate, at least two functional MRI techniques, such as diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI, are combined with conventional MRI, such as T2 -weighted imaging. DW-MRI has the ability to qualitatively and quantitatively represent the diffusion of water molecules by the apparent diffusion coefficient, which indirectly reflects tissue cellularity. DW-MRI is characterized by a short acquisition time without the administration of contrast medium. Thus, DW-MRI has the potential to become established as a noninvasive diagnostic method for tumor detection and localization, tumor aggressiveness, local staging and local recurrence after various therapies. Accordingly, radiologists should recognize the principles of DW-MRI, the methods of image acquisition and the pitfalls of image interpretation.

Whole body MRI: improved lesion detection and characterization with diffusion weighted techniques

Diffusion-weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole-body MRI. Theory, b-value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole-body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b-values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation.

Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study

PURPOSE

To evaluate the potential utility of a number of parameters obtained at T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced multiparametric magnetic resonance (MR) imaging for computer-aided diagnosis (CAD) of prostate cancer and assessment of cancer aggressiveness.

MATERIALS AND METHODS

In this institutional review board-approved HIPAA-compliant study, multiparametric MR images were acquired with an endorectal coil in 48 patients with prostate cancer (median age, 62.5 years; age range, 44-73 years) who subsequently underwent prostatectomy. A radiologist and a pathologist identified 104 regions of interest (ROIs) (61 cancer ROIs, 43 normal ROIs) based on correlation of histologic and MR findings. The 10th percentile and average apparent diffusion coefficient (ADC) values, T2-weighted signal intensity histogram skewness, and Tofts K(trans) were analyzed, both individually and combined, via linear discriminant analysis, with receiver operating characteristic curve analysis with area under the curve (AUC) as figure of merit, to distinguish cancer foci from normal foci. Spearman rank-order correlation (ρ) was calculated between cancer foci Gleason score (GS) and image features.

RESULTS

AUC (maximum likelihood estimate ± standard error) values in the differentiation of prostate cancer from normal foci of 10th percentile ADC, average ADC, T2-weighted skewness, and K(trans) were 0.92 ± 0.03, 0.89 ± 0.03, 0.86 ± 0.04, and 0.69 ± 0.04, respectively. The combination of 10th percentile ADC, average ADC, and T2-weighted skewness yielded an AUC value for the same task of 0.95 ± 0.02. GS correlated moderately with 10th percentile ADC (ρ = -0.34, P = .008), average ADC (ρ = -0.30, P = .02), and K(trans) (ρ = 0.38, P = .004).

CONCLUSION

The combination of 10th percentile ADC, average ADC, and T2-weighted skewness with CAD is promising in the differentiation of prostate cancer from normal tissue. ADC image features and K(trans) moderately correlate with GS.