Multiparametric magnetic resonance imaging of prostate cancer

Pictorial review on abdominal applications of ferumoxytol in MR imaging

Though gadolinium-based contrast agents are the most widely used contrast media in MR for clinical use, problems with nephrogenic systemic fibrosis and tissue deposition render their safety debatable, at least in a selected patient population. Ferumoxytol has the potential to be used as an alternate contrast medium for various clinical applications across multiple organs. It has prolonged intravascular signal and delayed intracellular macrophage uptake which are unique properties compared to gadolinium-based agents. This pictorial review aims to review the current and potential clinical applications of ferumoxytol as a contrast agent in abdominal MR imaging.

Accuracy of Diffusion Weighted Images and MR Spectroscopy in Prostate Lesions - Our Experience with Endorectal Coil on 1.5 T MRI

INTRODUCTION

Prostatic cancer is most commonly seen in individuals greater than 65 years of age. The incidence rates are constantly increasing.

AIM

To assess the accuracy of the non-contrast sequences {Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopy (MRS)} in the multiparametric Magnetic Resonance Imaging (mp-MRI) in identifying and differentiating benign and malignant prostate lesions using endorectal coil on 1.5 T MRI.

MATERIALS AND METHODS

Twenty-six patients with clinical indications for prostate lesions were evaluated using endorectal coil on 1.5 T MRI. DWI and MRS were obtained in all the lesions. Signal change on T2 weighted images, Apparent Diffusion Coefficient (ADC) values and choline + creatinine to citrate ratios (Cho+Cr/Ci) of the lesions were obtained for all the patients. All the patients underwent Transrectal Ultrasound (TRUS) guided biopsy within one week of MRI study. Signal change on T2 weighted images, DWI and Cho+Cr/Ci ratios were correlated with the histopathological findings using appropriate statistical analysis (Wilson score).

RESULTS

Of the 26 patients, seven had benign pathology and 19 had malignant pathology on the histopathological examination. Sensitivity and specificity (89.5% and 85.7% respectively) of the diagnosis of malignancy based on DWI were quite good. Positive and negative predictive values were also very much acceptable (94.4% and 75% respectively). Though, MRS had good sensitivity and Positive Predictive Value (PPV) (84.2% and 76.2% respectively), specificity and Negative Predictive Value (NPV) were poor (28.6% and 40% respectively). Accuracy of imaging diagnosis based on combining T2, DWI and MRS was same as that of results based on T2 signal alone (80.8%) and had higher sensitivity and lower specificity than DWI alone (94.7% and 42.9% respectively). Receiver Operating Characteristic (ROC) curves were calculated for ADC values and Cho+Cr/Ci ratios. The Area Under the Curve (AUC) for ADC is 0.74 and for Cho+Cr/Ci is 0.70.

CONCLUSION

Comparing the accuracy of the non-contrast sequences T2, DWI and MRS in identifying and differentiating benign and malignant lesions, giving weightage to the MRS in mp-MRI reduces the negative predictive value. The diagnosis of malignancy based on diffusion restriction was quite good and it can be the workhorse for prostate cancer detection as a shortened mp-MRI.

Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology

Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34) of patients with peripheral-zone and whole-gland models, respectively, compared with ADC alone. Model-based CBS maps for cancer detection showed improved visualization of cancer location and extent. Conclusion Quantitative multiparametric MR imaging models developed by using coregistered correlative histopathologic data yielded a voxel-wise CBS that outperformed single quantitative MR imaging parameters for detection of prostate cancer, especially when the models were assessed at the individual level. (©) RSNA, 2016 Online supplemental material is available for this article.