Multiparametric MRI for prostate cancer detection: Preliminary results on quantitative analysis of dynamic contrast enhanced imaging, diffusion-weighted imaging and spectroscopy imaging

Quantification of Multi-Parametric Magnetic Resonance Imaging Based on Radiomics Analysis for Differentiation of Benign and Malignant Lesions of Prostate

Background

The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers' opinions.

Objective

The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference.

Material and Methods

It is an analytical research that 27 patients underwent the mp-MRI examination, including T1- and T2- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used.

Results

An accuracy, sensitivity and specificity of 92.6%, 95.2% and 83.3%, respectively, were achieved from a subset of radiomics features obtained from T2-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions.

Conclusion

Quantification of mp-MRI (T2-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions.

Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer

Background Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 requires multiparametric MRI of the prostate, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging sequences; however, the contribution of DCE imaging remains unclear. Purpose To assess whether DCE imaging in addition to apparent diffusion coefficient (ADC) and normalized T2 values improves PI-RADS version 2.0 for prediction of clinically significant prostate cancer (csPCa). Materials and Methods In this retrospective study, clinically reported PI-RADS lesions in consecutive men who underwent 3-T multiparametric MRI (T2-weighted, DWI, and DCE MRI) from May 2015 to September 2016 were analyzed quantitatively and compared with systematic and targeted MRI-transrectal US fusion biopsy. The normalized T2 signal (nT2), ADC measurement, mean early-phase DCE signal (mDCE), and heuristic DCE parameters were calculated. Logistic regression analysis indicated the most predictive DCE parameters for csPCa (Gleason grade group ≥2). Receiver operating characteristic parameter models were compared using the Obuchowski test. Recursive partitioning analysis determined ADC and mDCE value ranges for combined use with PI-RADS. Results Overall, 260 men (median age, 64 years [IQR, 58-69 years]) with 432 lesions (csPCa [n = 152] and no csPCa [n = 280]) were included. The mDCE parameter was predictive of csPCa when accounting for the ADC and nT2 parameter in the peripheral zone (odds ratio [OR], 1.76; 95% CI: 1.30, 2.44; P = .001) but not the transition zone (OR, 1.17; 95% CI: 0.81, 1.69; P = .41). Recursive partitioning analysis selected an ADC cutoff of 0.897 × 10^-3 mm²/sec (P = .04) as a classifier for peripheral zone lesions with a PI-RADS score assessed on the ADC map (hereafter, ADC PI-RADS) of 3. The mDCE parameter did not differentiate ADC PI-RADS 3 lesions (P = .11), but classified lesions with ADC PI-RADS scores greater than 3 with low ADC values (less than 0.903 × 10^-3 mm²/sec, P < .001) into groups with csPCa rates of 70% and 97% (P = .008). A lesion size cutoff of 1.5 cm and qualitative DCE parameters were not defined as classifiers according to recursive partitioning (P > .05). Conclusion Quantitative or qualitative dynamic contrast-enhanced MRI was not relevant for Prostate Imaging Reporting and Data System (PI-RADS) 3 lesion risk stratification, while quantitative apparent diffusion coefficient (ADC) values were helpful in upgrading PI-RADS 3 and PI-RADS 4 lesions. Quantitative ADC measurement may be more important for risk stratification than current methods in future versions of PI-RADS. © RSNA, 2022 Online supplemental material is available for this article See also the editorial by Goh in this issue.

Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when

This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm² and high signal-to-noise ratio (SNR) that traditionally MRI systems are not able to acquire and therefore there are generally amplified anatomical distortions on the images due to less homogeneity of the field. Advances in both hardware and software on modern MRI scanners have currently enabled ultra-high b-value imaging and offered the ability to apply DKI to multiple extracranial sites. Previous studies have evaluated the ability of DKI to characterize and discriminate tumor grade compared to conventional DWI. Additionally, in several studies the DKI sequences used were based on planar echo (EPI) acquisition, which is susceptible to motion, metal and air artefacts and prone to low SNRs and distortions, leading to low quality images for some small lesions, which may affect the accuracy of the results. Another problem is the optimal b-value of DKI, which remains to be explored and not yet standardized, as well as the manual selection of the ROI, which could affect the accuracy of some parameters.

Radiological assessment of secondary biliary tree lesions: an update

Objective

To conduct a systematic literature review of imaging techniques and findings in patients with peribiliary liver metastasis.

Methods

Several electronic datasets were searched from January 1990 to June 2017 to identify studies assessing the use of different imaging techniques for the detection and staging of peribiliary metastases.

Results

The search identified 44 studies, of which six met the inclusion criteria and were included in the systematic review. Multidetector computed tomography (MDCT) is the technique of choice in the preoperative setting and during the follow-up of patients with liver tumors. However, the diagnostic performance of MDCT for the assessment of biliary tree neoplasms was low compared with magnetic resonance imaging (MRI). Ultrasound (US), without and with contrast enhancement (CEUS), is commonly employed as a first-line tool for evaluating focal liver lesions; however, the sensitivity and specificity of US and CEUS for both the detection and characterization are related to operator expertise and patient suitability. MRI has thus become the gold standard technique because of its ability to provide morphologic and functional data. MRI showed the best diagnostic performance for the detection of peribiliary metastases.

Conclusions

MRI should be considered the gold standard technique for the radiological assessment of secondary biliary tree lesions.

Evaluation of relationships between the final Gleason score, PI-RADS v2 score, ADC value, PSA level, and tumor diameter in patients that underwent radical prostatectomy due to prostate cancer

INTRODUCTION

This study aimed to investigate the relationship between the serum PSA level, Gleason score (GS), PI-RADS v2 score, tumor ADC_min value, and the largest tumor diameter in patients that underwent radical prostatectomy (RP) due to prostate cancer (PCa) and to comparatively evaluate the variables of these parameters in clinically significant and insignificant PCa groups.

MATERIALS AND METHODS

The mpMRI examinations of the patients who underwent RP due to PCa were retrospectively evaluated. According to the final GS, the lesions were divided into two groups as clinically significant (GS ≥ 7) and insignificant (GS ≤ 6). The PSA value, tumor ADC_min value, tumor diameter, and PI-RADS score were compared between the clinically significant and nonsignificant PCa groups using Student's t-test. The correlations between the serum PSA level, GS, PI-RADS v2 score, tumor ADC_min value, and tumor diameter were evaluated separately (Pearson's correlation analysis was used for peripheral gland tumors, and Spearman's correlation analysis for central gland tumors). A ROC analysis was undertaken to evaluate the efficacy of the tumor ADC_min, diameter and PSA values in differentiating clinically significant and nonsignificant tumors.

RESULTS

In both central and peripheral gland tumors, there was a correlation between the PSA level, tumor diameter, PI-RADS score, ADC_min value, and GS at various levels (poor, moderate, and high). In central gland tumors, there was no significant difference between the two groups in terms of the PSA value and PI-RADS scores (p > 0.05), but the ADC_min value and diameter of the tumor significantly differed (p < 0.05). For peripheral gland tumors, significant differences were observed in all parameters (p < 0.05). The cut-off values for the peripheral and central gland tumors are as follows: lesion diameter, 13.5 mm and 19 mm; tumor ADC_min, 0.709 × 10^-3 mm²/s and 0.874 × 10^-3 mm²/s; and PSA level, 8.47 ng/ml and 11.10 ng/ml, respectively.

CONCLUSION

The current PI-RADS v2 scoring system can be inadequate in distinguishing clinically significant and insignificant groups in central gland tumors. A separate cut-off value of the tumor diameter should be determined for central and peripheral gland tumors. Tumor ADC_min values can be used as a predictive parameter. The PSA cut-off value should be kept lower in peripheral gland tumors.

Lost in translation: lessons learned from the "demise" of MRSI of the prostate

At times, technologies fail for reasons other than an inability to deliver on their promises. The iconic Blackberry, for example, was once coined "Research in Motion", sold tens of millions of units, and then "disappeared" from the market because it did not accompany the new trends in design. Promising technologies may also "disappear" in the medical field. What follows is the tale of the rise and fall of proton magnetic resonance spectroscopic imaging (¹H MRSI) of the prostate.

Investigating the role of DCE-MRI, over T2 and DWI, in accurate PI-RADS v2 assessment of clinically significant peripheral zone prostate lesions as defined at radical prostatectomy

PURPOSE

PI-RADS v2 dictates that dynamic contrast-enhanced (DCE) imaging be used to further classify peripheral zone (PZ) cases that receive a diffusion-weighted imaging equivocal score of three (DWI3), a positive DCE resulting in an increase in overall assessment score to a four, indicative of clinically significant prostate cancer (csPCa). However, the accuracy of DCE in predicting csPCa in DWI3 PZ cases is unknown. This study sought to determine the frequency with which DCE changes the PI-RADS v2 DWI3 assessment category, and to determine the overall accuracy of DCE-MRI in equivocal PZ DWI3 lesions.

MATERIALS AND METHODS

This is a retrospective study of patients with pathologically proven PCa who underwent prostate mpMRI at 3T and subsequent radical prostatectomy. PI-RADS v2 assessment categories were determined by a radiologist, aware of a diagnosis of PCa, but blinded to final pathology. csPCa was defined as a Gleason score ≥ 7 or extra prostatic extension at pathology review. Performance characteristics and diagnostic accuracy of DCE in assigning a csPCa assessment in PZ lesions were calculated.

RESULTS

A total of 271 men with mean age of 59 ± 6 years mean PSA 6.7 ng/mL were included. csPCa was found in 212/271 (78.2%) cases at pathology, 209 of which were localized in the PZ. DCE was necessary to further classify (45/209) of patients who received a score of DWI3. DCE was positive in 29/45 cases, increasing the final PI-RADS v2 assessment category to a category 4, with 16/45 having a negative DCE. When compared with final pathology, DCE was correct in increasing the assessment category in 68.9% ± 7% (31/45) of DWI3 cases.

CONCLUSION

DCE increases the accuracy of detection of csPCa in the majority of PZ lesions that receive an equivocal PI-RADS v2 assessment category using DWI.

Prostate MRI using an external phased array wearable pelvic coil at 3T: comparison with an endorectal coil

PURPOSE

To evaluate T2w and DWI image quality using a wearable pelvic coil (WPC) compared with an endorectal coil (ERC).

METHODS

Twenty men consecutively presenting to our prostate cancer MRI clinic were prospectively consented to be scanned using a wearable pelvic coil then an endorectal coil and pelvic phased array coil at 3T. Eighteen patients were suitable for inclusion. Axial T2w images were obtained using the WPC and ERC, and DWI images were obtained using the WPC, ERC, and PPA. Analysis was performed in consensus by two readers with experience in prostate MRI. The readers scored the T2w images using six qualitative criteria and the DWI images using five criteria. Signal-to-noise ratio (SNR) was also measured.

RESULTS

T2w artifact severity was greater for an ERC than a WPC (p = 0.003). There was no significant difference in T2w qualititatve image quality by other measures. The distinction of zonal anatomy on DWI was superior for an ERC compared with both a WPC and a PPA (p = 0.018 and p < 0.001 respectively), and there was no significant difference in DWI image quality by other measures. SNR was significantly higher for ERC imaging for both T2w and DWI.

CONCLUSION

WPC imaging provides comparable image quality to that of an ERC, potentially reducing the need for an ERC. WPC imaging shows reduced T2w artifact severity and inferior DWI zonal anatomy distinction compared with an ERC. Imaging with a WPC produces a lower SNR than an ERC.

Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference

Background

This study evaluated the performance of histogram analysis in the time course of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for differentiating cancerous tissues from benign tissues in the prostate.

Methods

We retrospectively analyzed the histograms of DCE-MRI of 30 patients. Histograms within regions of interest(ROI) in the peripheral zone (PZ) and transitional zone (TZ) were separately analyzed. The maximum difference wash-in slope (MWS) and delay phase slope (DPS) were defined for each voxel. Differences in histogram parameters, namely the mean, standard deviation (SD), the coefficient of variation (CV), kurtosis, skewness, interquartile range (IQR), percentile (P10, P25, P75, P90, and P90P10), Range, and modified full width at half-maximum (mFWHM) between cancerous and benign tissues were assessed.

Results

In the TZ, CV for ROIs of 7.5 and 10mm was the only significantly different parameter of the MWS (P = 0.034 and P = 0.004, respectively), whereas many parameters of the DPS (mean, skewness, P10, P25, P50, P75 and P90) differed significantly (P = <0.001–0.016 and area under the curve [AUC] = 0.73–0.822). In the PZ, all parameters of the MWS exhibited significant differences, except kurtosis and skewness in the ROI of 7.5mm(P = <0.001–0.017 and AUC = 0.865–0.898). SD, IQR, mFWHM, P90P10 and Range were also significant differences in the DPS (P = 0.001–0.035).

Conclusion

The histogram analysis of DCE-MRI is a potentially useful approach for differentiating prostate cancer from normal tissues. Different histogram parameters of the MWS and DPS should be applied in the TZ and PZ.

Prostate imaging features that indicate benign or malignant pathology on biopsy

Accurate diagnosis of clinically significant prostate cancer is essential in identifying patients who should be offered treatment with curative intent. Modifications to the Gleason grading system in recent years show that accurate grading and reporting at needle biopsy can improve identification of clinically significant prostate cancers. Extracapsular extension of prostate cancer has been demonstrated to be an adverse prognostic factor with greater risk of metastatic spread than organ-confined disease. Tumor volume may be an independent prognostic factor and should be considered in conjunction with other factors. Multi-parametric magnetic resonance imaging (MP-MRI) has become an increasingly important tool in the diagnosis and characterization of prostate cancer. MP-MRI allows T2-weighted (T2W) anatomical imaging to be combined with functional and physiological assessment. Diffusion-weighted imaging (DWI) has shown greater sensitivity, specificity and negative predictive value compared to prostate specific antigen (PSA) testing and T2W imaging alone and has a more positive correlation with Gleason score and tumour volume. Dynamic gadolinium contrast-enhanced (DCE) imaging can exhibit difficulties in distinguishing prostatitis from malignancy in the peripheral zone, and between benign prostatic hyperplasia (BPH) and malignancies in the transition zone (TZ). Computer aided diagnosis utilizes software to aid radiologists in detecting and diagnosing abnormalities from diagnostic imaging. New techniques of quantitative MRI, such as VERDICT MRI use tissue-specific factors to delineate different cellular and microstructural phenotypes, characterizing tissue properties with greater detail. Proton MR spectroscopic imaging (MRSI) is a more technically challenging imaging modality than DCE and DWI MRI. Over the last decade, choline and prostate-specific membrane antigen (PSMA) positron emission tomography (PET) have developed as better tools for staging than conventional imaging. While hyperpolarized MRI shows promise in improving the imaging and differentiation of benign and malignant lesions there is further work required. Accurate reading and interpretation of diagnostic investigations is key to accurate identification of abnormal areas requiring biopsy, sparing those in whom benign or indolent disease can be managed by non-invasive means. Embracing and advancing existing technologies is essential in furthering this process.

Multiparametric MRI reporting using Prostate Imaging Reporting and Data System version 2.0 (PI-RADSv2) retains clinical efficacy in a predominantly post-biopsy patient population

Objective

To evaluate the efficacy of multiparametric magnetic resonance imaging (mp-MRI) using Prostate Imaging Reporting and Data System version 2.0 (PI-RADSv2) definitions in detecting organ-confined prostate cancer.

Methods

All patients who underwent radical prostatectomy between January 1, 2014 and December 30, 2014 were identified. All underwent mp-MRI within 180 days before surgery. Those with prior pelvic irradiation or androgen deprivation therapy were excluded. Fully embedded, whole-mount histopathology was centrally reviewed and correlated with imaging for tumour location, Gleason score (GS) and stage.

Results

There were 39 patients included, of which 35 (90%) had mp-MRI done post-biopsy. A total of 93 cancer foci were identified on whole-mount pathology, of which mp-MRI detected 63 (68%). Of those detected by mp-MRI, 14 were PI-RADS 3 (n = 6 for GS 6, n = 8 for GS 7, no GS ≥ 8) and 49 were PI-RADS 4–5 (n = 7 for GS 6, n = 33 for GS 7, and n = 9 for GS ≥ 8). There were 30 (32%) cancer foci missed by mp-MRI (n = 15 for GS 6, n = 13 for GS 7 and n = 2 for GS ≥ 8). A lesion classified as PI-RADS 4–5 predicted a higher grade cancer on pathology as compared to PI-RADS 3 (for GS 7 lesions, odds ratio [OR] = 3.53, 95% CI: 0.93–13.45, p = 0.064). The mp-MRI size detection limit was 20 mm² and 100 mm² for 50% and 75% probability of cancer, respectively. In associating with radiological and pathologic stage, the weighted Kappa value was 0.69 (p < 0.0001). The sensitivity and positive predictive values for this study were 68% (95% CI: 57%–77%) and 78% (95% CI: 67%–86%), respectively.

Conclusion

In this predominantly post-biopsy cohort, mp-MRI using PI-RADSv2 reporting has a reasonably high diagnostic accuracy in detecting clinically significant prostate cancer.

Quantitative parameters in dynamic contrast-enhanced magnetic resonance imaging for the detection and characterization of prostate cancer

Objectives

to assess the diagnostic accuracy of quantitative parameters of DCE-MRI in multi-parametric MRI (mpMRI) in comparison to the histopathology (including Gleason grade) of prostate cancer.

Patients and methods

150 men with suspected prostate cancer (abnormal digital rectum examination and or elevated prostate-specific antigen) received pre-biopsy 3T mpMRI and were recruited into peer-reviewed, protocol-based prospective study. The DCE-MRI quantitative parameters (K^trans (influx transfer constant) and k_ep (efflux rate constant)) of the cancerous and normal areas were recorded using four different kinetic models employing Olea Sphere (Olea Medical, La Ciotat, France). The correlation between these parameters and the histopathology of the lesions (biopsy and in a sub-cohort 41 radical prostatectomy specimen) was assessed.

Results

The quantitative parameters showed a significant difference between non-cancerous (benign) and cancerous lesions (Gleason score≥3+3) in the prostate gland. The cut-off values for prostate cancer differentiation were: K^trans (0.205 min⁻¹) and k_ep (0.665 min⁻¹) in the extended Tofts model (ET) and K^trans(0.205 min⁻¹ and k_ep (0.63 min⁻¹) in the Lawrence and Lee delay (LD) models respectively. The mean K^trans value also showed a difference between low-grade cancer (Gleason score=3+3) and high-grade cancer (Gleason score ≥ 3+4). With the addition of DCE-MRI quantitative parameters, the sensitivity of the PIRAD scoring system was increased from 56.6% to 92.1% (K^trans_ET), 93.1% (k_ep_ET), 91.0%, (K^trans_LD) and 89.4% (k_ep_LD).

Conclusion

Quantitative DCE-MRI parameters improved the diagnostic performance of conventional MRI in distinguishing normal and prostate cancers, including characterization of grade of cancers. The ET and LD models in post-image processing analysis provided better cut-off values for prostate cancer differentiation than the other quantitative DCE-MRI parameters.

A systematic review on multiparametric MR imaging in prostate cancer detection

BACKGROUND

Literature data suggest that multi-parametric Magnetic Resonance Imaging (MRI), including morphologic T2-weigthed images (T2-MRI) and functional approaches such as Dynamic Contrast Enhanced-MRI (DCE-MRI), Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopic Imaging (MRSI), give an added value in the prostate cancer localization and local staging.

METHODS

We performed a systematic review of literature about the role and the potentiality of morphological and functional MRI in prostate cancer, also in a multimodal / multiparametric approach, and we reported the diagnostic accuracy results for different imaging modalities and for different MR coil settings: endorectal coil (ERC) and phased array coil (PAC). Forest plots and receiver operating characteristic curves were performed. Risk of bias and the applicability at study level were calculated.

RESULTS

Thirty three papers were identified for the systematic review. Sensitivity and specificity values were, respectively, for T2-MRI of 75% and of 60%, for DCE-MRI of 80% and of 72%, for MRSI of 89% and of 69%, for combined T2-MRI and DCE-MRI of 87% and of 46%, for combined T2-MRI and MRSI of 79% and of 57%, for combined T2-MRI, DWI and DCE-MRI of 81% and of 84%, and for combined MRSI and DCE-MRI of 83% and of 83%. For MRI studies performed with ERC we obtained a pooled sensitivity and specificity of 81% and of 66% while the pooled values for MRI studies performed with PAC were of 78% and of 64%, respectively (p>0.05 at McNemar test). No studies were excluded from the analysis based on the quality assessment.

CONCLUSIONS

ERC use yielded no additional benefit in terms of prostate cancer detection accuracy compared to multi-channel PAC use (71% versus 68%) while the use of additional functional imaging techniques (DCE-MRI, DWI and MRSI) in a multiparametric MRI protocol improves the accuracy of prostate cancer detection allowing both the early cure and the guidance of biopsy.

Prebiopsy multiparametric MRI-based risk score for predicting prostate cancer in biopsy-naive men with prostate-specific antigen between 4-10 ng/mL

BACKGROUND

Risk calculators have traditionally utilized serum prostate-specific antigen (PSA) values in addition to clinical variables to predict the likelihood of prostate cancer (PCa).

PURPOSE

To develop a prebiopsy multiparametric MRI (mpMRI)-based risk score (RS) and a statistical equation for predicting the risk of PCa in biopsy-naive men with serum PSA between 4-10 ng/mL that may help reduce unnecessary biopsies.

STUDY TYPE

Prospective cross-sectional study.

SUBJECTS

In all, 137 consecutive men with PSA between 4-10 ng/mL underwent prebiopsy mpMRI (diffusion-weighted [DW]-MRI and MR spectroscopic imaging [MRSI]) during 2009-2015 were recruited for this study.

FIELD STRENGTH/SEQUENCE

1.5T (Avanto, Siemens Health Care, Erlangen, Germany); T₁ -weighted, T₂ -weighted, DW-MRI, and MRSI sequences were used.

ASSESSMENT

All eligible patients underwent mpMRI-directed, cognitive-fusion transrectal ultrasound (TRUS)-guided biopsies.

STATISTICAL TESTS

An equation model and an RS were developed using receiver operating characteristic (ROC) curve analysis and a multivariable logistic regression approach. A 10-fold crossvalidation and simulation analyses were performed to assess diagnostic performance of various combinations of mpMRI parameters.

RESULTS

Of 137 patients, 32 were diagnosed with PCa on biopsy. Multivariable analysis, adjusted with positive pathology, showed apparent diffusion coefficient (ADC), metabolite ratio, and PSA as significant predictors of PCa (P < 0.05). A statistical equation was derived using these predictors. A simple 6-point mpMRI-based RS was derived for calculating the risk of PCa and it showed that it is highly predictive for PCa (odds ratio = 3.74, 95% confidence interval [CI]: 2.24-6.27, area under the curve [AUC] = 0.87). Both models (equation and RS) yielded high predictive performance (AUC ≥0.85) on validation analysis.

DATA CONCLUSION

A statistical equation and a simple 6-point mpMRI-based RS can be used as a point-of-care tool to potentially help limit the number of negative biopsies in men with PSA between 4 and 10 ng/mL.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1227-1236.

Peribiliary liver metastases MR findings

We described magnetic resonance (MR) features of peribiliary metastasis and of periductal infiltrative cholangiocarcinoma. We assessed 35 patients, with peribiliary lesions, using MR 4-point confidence scale. T1-weighted (T1-W), T2-weighted (T2-W) and diffusion-weighted images (DWI) signal intensity, enhancement pattern during arterial, portal, equilibrium and hepatobiliary phase were assessed. We identified 24 patients with periductal-infiltrating cholangiocellular carcinoma. The lesions in 34 patients appeared as a single tissue, while in a single patient, the lesions appeared as multiple individual lesions. According to the confidence scale, the median value was 4 for T2-W, 4 for DWI, 3.6 for T1-W in phase, 3.6 for T1-W out phase, 3 for MRI arterial phase, 3.2 for MRI portal phase, 3.2 for MRI equilibrium phase and 3.6 for MRI hepatobiliary phase. According to Bismuth classification, all lesions were type IV. In total, 19 (54.3%) lesions were periductal, 15 (42.9%) lesions were intraperiductal, and 1 (2.8%) lesion was periductal intrahepatic. All lesions showed hypointense signal in T1-W and in ADC maps and hyperintense signal in T2-W and DWI. All lesions showed a progressive contrast enhancement. There was no significant difference in signal intensity and contrast enhancement among all metastases and among all metastases with respect to CCCs, for all imaging acquisitions (p value >0.05). MRI is the method of choice for biliary tract tumors thanks to the possibility to obtain morphological and functional evaluations. T2-W and DW sequences have highest diagnostic performance. MRI does not allow a correct differential diagnosis among different histological types of metastasis and between metastases and CCC.

Dynamic contrast-enhanced MR imaging pharmacokinetic parameters as predictors of treatment response of brain metastases in patients with lung cancer

OBJECTIVES

To determine the diagnostic accuracy of pharmacokinetic parameters measured by dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in predicting the response of brain metastases to antineoplastic therapy in patients with lung cancer.

METHODS

Forty-four consecutive patients with lung cancer, harbouring 123 newly diagnosed brain metastases prospectively underwent conventional 3-T MRI at baseline (within 1 month before treatment), during the early (7-10 weeks) and midterm (5-7 months) post-treatment period. An additional DCE MRI sequence was performed during baseline and early post-treatment MRI to evaluate baseline pharmacokinetic parameters (K ^trans, k _ep, v _e, v _p) and their early variation (∆K ^trans, ∆k _ep, ∆v _e, ∆v _p). The objective response was judged by the volume variation of each metastasis from baseline to midterm MRI. ROC curve analysis determined the best DCE MRI parameter to predict the objective response.

RESULTS

Baseline DCE MRI parameters were not associated with the objective response. Early ∆K ^trans, ∆v _e and ∆v _p were significantly associated with the objective response (p = 0.02, p = 0.001 and p = 0.02, respectively). The best predictor of objective response was ∆v _e with an area under the curve of 0.93 [95% CI = 0.87, 0.99].

CONCLUSIONS

DCE MRI and early ∆v _e may be a useful tool to predict the objective response of brain metastases in patients with lung cancer.

KEY POINTS

• DCE MRI could predict the response of brain metastases from lung cancer • ∆v _e was the best predictor of response • DCE MRI could be used to individualize patients' follow-up.

Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2

OBJECTIVES

To evaluate the diagnostic performance of different mathematical models and different b-value ranges of diffusion-weighted imaging (DWI) in peripheral zone prostate cancer (PZ PCa) detection.

METHODS

Fifty-six patients with histologically proven PZ PCa who underwent DWI-magnetic resonance imaging (MRI) using 21 b-values (0-4500 s/mm2) were included. The mean signal intensities of the regions of interest (ROIs) placed in benign PZs and cancerous tissues on DWI images were fitted using mono-exponential, bi-exponential, stretched-exponential, and kurtosis models. The b-values were divided into four ranges: 0-1000, 0-2000, 0-3200, and 0-4500 s/mm2, grouped as A, B, C, and D, respectively. ADC, <D>, D*, f, DDC, α, Dapp, and Kapp were estimated for each group. The adjusted coefficient of determination (R2) was calculated to measure goodness-of-fit. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of the parameters.

RESULTS

All parameters except D* showed significant differences between cancerous tissues and benign PZs in each group. The area under the curve values (AUCs) of ADC were comparable in groups C and D (p = 0.980) and were significantly higher than those in groups A and B (p< 0.05 for all). The AUCs of ADC and Kapp in groups B and C were similar (p = 0.07 and p = 0.954), and were significantly higher than the other parameters (p< 0.001 for all). The AUCs of ADC in group D was slightly higher than Kapp (p = 0.002), and both were significantly higher than the other parameters (p< 0.001 for all).

CONCLUSIONS

ADC derived from conventional mono-exponential high b-value (3200 s/mm2) models is an optimal parameter for PZ PCa detection.