Value of 3-T magnetic resonance imaging in local staging of prostate cancer

Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy

Simple Summary

In this multicentric study, we tested the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting extracapsular extension (ECE) out of the prostate in order to plan surgical sparing of neurovascular bundles in radical prostatectomy. Univariate and multivariate logistic regression analyses were performed to identify other risk factors for ECE. We found that it has a good ability to exclude extracapsular extension but a poor ability to identify it correctly. Risk factors other than mpMRI that predicted ECE were as follows: prostatic specific antigen, digital rectal examination, ratio of positive cores, and biopsy grade group. We suggest that using mpMRI exclusively should not be recommended to decide on surgical approaches.

Abstract

The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique.

Multiparametric Magnetic Resonance Imaging in Evaluation of Clinically Significant Prostate Cancer

Aim  In this prospective study, we evaluate the role of multiparametric magnetic resonance imaging (mp-MRI) in the assessment of clinically significant prostate cancer at 1.5 T without endorectal coil (ERC).

Materials and Methods  Forty-five men with clinical suspicion of prostate cancer (prostate-specific antigen [PSA] level > 4 ng/mL, hard prostate on digital rectal examination, and suspicious area at transrectal ultrasound [TRUS]) were evaluated using the mp-MRI protocol over a period of 24 months. All cases were interpreted using the Prostate Imaging Reporting and Data System (PI-RADS) version 2 guidelines and correlated with histopathology.

Statistical Analysis Used  A chi-squared test was used for analysis of nominal/categorical variables and receiver operating characteristic (ROC) curve and one-way analysis of variance (ANOVA) test for continuous variables.

Results  The mean age was 67 years and the mean PSA was 38.2 ng/mL. Eighty percent had prostate cancer and 20% were benign (11% benign prostatic hyperplasia [BPH] and 9% chronic prostatitis). Eighty-six percent of all malignancies were in the peripheral zone. The PI-RADS score for T2-weighted (T2W) imaging showed good sensitivity (81%) but low specificity (67%). The PI-RADS score for diffusion weighted imaging (DWI) with sensitivity of 92% and specificity of 78% had a better accuracy overall than T2W imaging alone. The mean apparent diffusion coefficient (ADC) value (×10 ^–6 mm ² /s) was 732 ± 160 in prostate cancer, 1,009 ± 161 in chronic prostatitis, 1,142 ± 82 in BPH, and 663 in a single case of granulomatous prostatitis. Low ADC values (<936) have shown good correlation (area under curve [AUC]: 0.87) with the presence of cancer foci. Inverse correlation was observed between Gleason scores and ADC values. Dynamic contrast-enhanced (DCE) imaging has shown 100% sensitivity/negative predictive value (NPV), but moderate specificity (67%) in predicting malignancy. The final PI-RADS score had 100% sensitivity and NPV with good overall positive predictive value (PPV) of 95%.

Conclusions  T2W imaging and DWI remain the mainstays in diagnosis of prostate cancer with mp-MRI. DCE-MRI can be a problem-solving tool in case of equivocal findings. Because assessment with mp-MRI can be subjective, use of the newly developed PI-RADS version 2 scoring system is helpful in accurate interpretation.

The Evolution of MRI of the Prostate: The Past, the Present, and the Future

OBJECTIVE. The purpose of this article is to discuss the evolution of MRI in prostate cancer from the early 1980s to the current day, providing analysis of the key studies on this topic. CONCLUSION. The rapid diffusion of MRI technology has meant that residual variability remains between centers regarding the quality of acquisition and the quality and standardization of reporting.

Dosimetric feasibility of magnetic resonance (MR)-based dose calculation of prostate radiotherapy using multilevel threshold algorithm

Objective

The development of magnetic resonance (MR) imaging systems has been extended for the entire radiotherapy process. However, MR images provide voxel values that are not directly related to electron densities, thus MR images cannot be used directly for dose calculation. The aim of this study is to investigate the feasibility of dose calculations to be performed on MR images and evaluate the necessity of re-planning.

Methods

A prostate cancer patient was imaged using both MR and computed tomography (CT). The multilevel threshold (MLT) algorithm was used to categorise voxel values in the MR images into three segments (air, water and bone) with homogeneous Hounsfield units (HU). An intensity-modulated radiation therapy plan was generated from CT images of the patient. The plan was then copied to the segmented MR datasets and the doses were recalculated using pencil beam (PB) and collapsed cone (CC) algorithms and Monte Carlo (MC) modelling.

Results

γEvaluation showed that the percentage of points in regions of interest withγ<1 (3%/3 mm) were more than 94% in the segmented MR. Compared with the planning CT plan, the segmented MR plan resulted in a dose difference of –0·3, 0·8 and –1·3% when using PB, CC and MC algorithms, respectively.

Conclusion

The segmentation and conversion of MR images into HU data using the MLT algorithm, used in this feasibility study, can be used for dose calculation. This method can be used as a dosimetric assessment tool and can be easily implemented in the clinic.

The role of imaging in the diagnosis of primary prostate cancer

Ultrasound and magnetic resonance imaging (MRI) are key imaging modalities in prostate cancer diagnosis. MRI offers a range of intrinsic contrast mechanisms (T2, diffusion-weighted imaging (DWI), MR spectroscopy (MRS)) and extrinsic contrast-generating options based on tumour vascular state following injection of weakly paramagnetic agents such as gadolinium. Together these parameters are referred to as multiparametric (mp)MRI and are used for detecting and guiding biopsy and staging prostate cancer. Although sensitivity of mpMRI is <75% for disease detection, specificity is >90% and a standardised reporting system together with MR-guided targeted biopsy is the optimal diagnostic pathway. Shear wave ultrasound elastography is a new technique which also holds promise for future studies. This article describes the developments in imaging the primary site of prostate cancer and reviews their current and future utility for screening, diagnosis and T-staging the disease.

Interpretation and reporting multiparametric prostate MRI: a primer for residents and novices

Multiparametric MRI has developed as a tool for prostate cancer lesion detection, characterization, staging, surveillance, and imaging of local recurrence. Given the disease frequency and the growing importance of imaging, as reliance on PSA declines, radiologists involved in prostate MRI imaging must become proficient with the fundamentals of multiparametric prostate MRI (T2WI, DWI, DCE-MRI, and MR spectroscopy). Interpretation and reporting must yield accuracy, consistency, and add value to clinical care. This review provides a primer to novices and trainees learning about multiparametric prostate MRI. MRI technique is presented along with the use of particular MRI sequences. Relevant prostate anatomy is outlined and imaging features of prostate cancer with staging are discussed. Finally structured reporting is introduced, and some limitations of prostate MRI are discussed.

Multiparametric magnetic resonance imaging of prostate cancer

In India, prostate cancer has an incidence rate of 3.9 per 100,000 men and is responsible for 9% of cancer-related mortality. It is the only malignancy that is diagnosed with an apparently blind technique, i.e., transrectal sextant biopsy. With increasing numbers of high-Tesla magnetic resonance imaging (MRI) equipment being installed in India, the radiologist needs to be cognizant about endorectal MRI and multiparametric imaging for prostate cancer. In this review article, we aim to highlight the utility of multiparamteric MRI in prostate cancer. It plays a crucial role, mainly in initial staging, restaging, and post-treatment follow-up.

Magnetic resonance imaging for prostate cancer clinical application

As prostate cancer is a biologically heterogeneous disease for which a variety of treatment options are available, the major objective of prostate cancer imaging is to achieve more precise disease characterization. In clinical practice, magnetic resonance imaging (MRI) is one of the imaging tools for the evaluation of prostate cancer, the fusion of MRI or dynamic contrast-enhanced MRI (DCE-MRI) with magnetic resonance spectroscopic imaging (MRSI) is improving the evaluation of cancer location, size, and extent, while providing an indication of tumor aggressiveness. This review summarizes the role of MRI in the application of prostate cancer and describes molecular MRI techniques (including MRSI and DCE-MRI) for aiding prostate cancer management.

Prostate cancer imaging: what the urologist wants to know

No consensus exists at present regarding the use of imaging for the evaluation of prostate cancer. Ultrasonography is mainly used for biopsy guidance and magnetic resonance imaging is the mainstay in evaluating the extent of local tumor. Computed tomography and radionuclide bone scanning are mainly reserved for assessment of advanced disease. Positron emission tomography is gaining acceptance in the evaluation of treatment response and recurrence. The combination of anatomic, functional, and metabolic imaging modalities has promise to improve treatment. This article reviews current imaging techniques and touches on the evolving technologies being used for detection and follow-up of prostate cancer.

A phase and frequency alignment protocol for 1H MRSI data of the prostate

(1)H MRSI of the prostate reveals relative metabolite levels that vary according to the presence or absence of tumour, providing a sensitive method for the identification of patients with cancer. Current interpretations of prostate data rely on quantification algorithms that fit model metabolite resonances to individual voxel spectra and calculate relative levels of metabolites, such as choline, creatine, citrate and polyamines. Statistical pattern recognition techniques can potentially improve the detection of prostate cancer, but these analyses are hampered by artefacts and sources of noise in the data, such as variations in phase and frequency of resonances. Phase and frequency variations may arise as a result of spatial field gradients or local physiological conditions affecting the frequency of resonances, in particular those of citrate. Thus, there are unique challenges in developing a peak alignment algorithm for these data. We have developed a frequency and phase correction algorithm for automatic alignment of the resonances in prostate MRSI spectra. We demonstrate, with a simulated dataset, that alignment can be achieved to a phase standard deviation of 0.095  rad and a frequency standard deviation of 0.68  Hz for the citrate resonances. Three parameters were used to assess the improvement in peak alignment in the MRSI data of five patients: the percentage of variance in all MRSI spectra explained by their first principal component; the signal-to-noise ratio of a spectrum formed by taking the median value of the entire set at each spectral point; and the mean cross-correlation between all pairs of spectra. These parameters showed a greater similarity between spectra in all five datasets and the simulated data, demonstrating improved alignment for phase and frequency in these spectra. This peak alignment program is expected to improve pattern recognition significantly, enabling accurate detection and localisation of prostate cancer with MRSI.

Modalities for imaging of prostate cancer

Prostate cancer is the second most common cause of cancer deaths among males in the United States. Prostate screening by digital rectal examination and prostate-specific antigen has shifted the diagnosis of prostate cancer to lower grade, organ confined disease, adding to overdetection and overtreatment of prostate cancer. The new challenge is in differentiating clinically relevant tumors from ones that may otherwise never have become evident if not for screening. The rapid evolution of imaging modalities and the synthesis of anatomic, functional, and molecular data allow for improved detection and characterization of prostate cancer. However, the appropriate use of imaging is difficult to define, as many controversial studies regarding each of the modalities and their utilities can be found in the literature. Clinical practice patterns have been slow to adopt many of these advances as a result. This review discusses the more established imaging techniques, including Ultrasonography, Magnetic Resonance Imaging, MR Spectroscopy, Computed Tomography, and Positron Emission Tomography. We also review several promising techniques on the horizon, including Dynamic Contrast-Enhanced MRI, Diffuse-Weighted Imaging, Superparamagnetic Nanoparticles, and Radionuclide Scintigraphy.

Update on prostate imaging

Successful and accurate imaging of prostate cancer is integral to its clinical management from detection and staging to subsequent monitoring. Various modalities are used including ultrasound, computed tomography, and magnetic resonance imaging, with the greatest advances seen in the field of magnetic resonance.

Incremental value of magnetic resonance imaging in the advanced management of prostate cancer

Prostate cancer is a major public health burden throughout the world. The high incidence of prostate cancer, combined with earlier detection and downstaging at the time of diagnosis, and the slow natural progression and biological heterogeneity of the disease, has made its management a complex and controversial issue. There is growing demand for patient-specific therapies that can minimize treatment morbidity while maximizing treatment benefits. There are a number of clinical parameters and clinical nomograms to help with the choice of treatment. Magnetic resonance imaging (MRI) is a technique which makes safer, more individualized therapies possible due to high spatial resolution, superior contrast resolution, multiplanar capability, and a large field of view. Other MRI techniques such as MR spectroscopic imaging, dynamic contrast-enhanced MRI or perfusion MRI, and diffusion-weighted imaging complement MRI by reflecting tissue biochemistry, Brownian motion of water molecules, and capillary wall permeability, respectively. This editorial review highlights the incremental value of MRI in the advanced management of prostate cancer to non-invasively improve cancer staging, biologic potential, treatment planning, therapy response, local recurrence, and to guide target biopsy for clinical suspected cancer with previous negative biopsy. Finally, some future prospects for MRI in prostate cancer management are given.