Combined diffusion-weighted and dynamic contrast-enhanced MRI for prostate cancer diagnosis--correlation with biopsy and histopathology

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Comparison of DCE-MRI parametric mapping using MP2RAGE and variable flip angle T1 mapping

Quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) measures the rate of transfer of contrast agent from the vascular space to the tissue space by fitting signal-time data to pharmacokinetic models. However, these models are very sensitive to errors in T₁ mapping. Accurate T₁ mapping is necessary for high quality quantitative DCE-MRI studies. This study compares magnetization prepared rapid (two) gradient echo sequence (MP2RAGE) T₁-mapping accuracy to the conventional variable flip angle (VFA) approach, and also determines the effect of the new T₁-mapping method on the K^trans parameter. VFA and MP2RAGE T₁ values were compared to the gold standard inverse recovery (IR) method in phantom over manually drawn ROIs. In vivo, ROIs were manually drawn over prostate and prostatic lesions. Average T₁ values over ROIs were compared and K^trans maps for each method were calculated via the extended Tofts model. VFA-T₁ maps overestimated T₁ values by up to 50% compared to gold standard IR T₁ values in phantom. MP2RAGE differed by up to 9%. MP2RAGE-T₁ and K^trans values were significantly different from VFA values over prostatic lesions (p < 0.05). K^trans was consistently underestimated using VFA compared to MP2RAGE (p < 0.05). MP2RAGE T₁ maps are shown to be more accurate, leading to more reliable pharmacokinetic modeling. This can potentially lead to better lesion characterization and improve clinical outcomes.

Magnetically‐activated lipid nanocarriers in biomedical applications: A review of current status and perspective

Magnetically-activated lipid nanocarriers have become a research hotspot in the field of biomedicine. Liposomes and other lipid-based carriers possess good biocompatibility as well as the ability to carrying therapeutic cargo with a range of physicochemical properties. Previous studies have demonstrated that magnetic materials have potential wide applications in clinical diagnosis and therapy, such as in MRI as contrast agents and in hyperthermic obliteration of cancer tissues. More recently magneto-thermal activation of lipid carriers to stimulate drug release has extended the range of further therapeutic benefits. Here, an overview of the current development of magnetically-activated lipid nanocarriers in the field of biomedicine is provided, including the methods of fabrication of the nanocarriers and their in vitro and in vivo performance. A discussion of the current barriers to translation of these materials as medicines is provided in the context of clinical and regulatory complexities of using magnetically responsive materials in therapeutic applications. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Biology-Inspired Nanomaterials > Lipid-Based Structures Implantable Materials and Surgical Technologies > Nanomaterials and Implants.

Canadian Association of Radiologists Prostate MRI White Paper

Prostate cancer is the most common malignancy and the third most common cause of death in Canadian men. In light of evolving diagnostic pathways for prostate cancer and the increased use of MRI, which now includes its use in men prior to biopsy, the Canadian Association of Radiologists established a Prostate MRI Working Group to produce a white paper to provide recommendations on establishing and maintaining a Prostate MRI Programme in the context of the Canadian healthcare system. The recommendations, which are based on available scientific evidence and/or expert consensus, are intended to maintain quality in image acquisition, interpretation, reporting and targeted biopsy to ensure optimal patient care. The paper covers technique, reporting, quality assurance and targeted biopsy considerations and includes appendices detailing suggested reporting templates, quality assessment tools and sample image acquisition protocols relevant to the Canadian healthcare context.

Dynamic Contrast Enhanced Study in Multiparametric Examination of the Prostate—Can We Make Better Use of It?

We sought to investigate whether quantitative parameters from a dynamic contrast-enhanced study can be used to differentiate cancer from normal tissue and to determine a cut-off value of specific parameters that can predict malignancy more accurately, compared to the obturator internus muscle as a reference tissue. This retrospective study included 56 patients with biopsy proven prostate cancer (PCa) after multiparametric magnetic resonance imaging (mpMRI), with a total of 70 lesions; 39 were located in the peripheral zone, and 31 in the transition zone. The quantitative parameters for all patients were calculated in the detected lesion, morphologically normal prostate tissue and the obturator internus muscle. Increase in the K_trans value was determined in lesion-to-muscle ratio by 3.974368, which is a cut-off value to differentiate between prostate cancer and normal prostate tissue, with specificity of 72.86% and sensitivity of 91.43%. We introduced a model to detect prostate cancer that combines K_trans lesion-to-muscle ratio value and iAUC lesion-to-muscle ratio value, which is of higher accuracy compared to individual variables. Based on this model, we identified the optimal cut-off value with 100% sensitivity and 64.28% specificity. The use of quantitative DCE pharmacokinetic parameters compared to the obturator internus muscle as reference tissue leads to higher diagnostic accuracy for prostate cancer detection.

Diagnostic performance of diffusion-weighted imaging combined with dynamic contrast-enhanced magnetic resonance imaging for prostate cancer: a systematic review and meta-analysis

BACKGROUND

The diagnostic performance of diffusion-weighted imaging (DWI) combined with dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) for the detection of prostate cancer (PCa) has not been studied systematically to date.

PURPOSE

To investigate the value of DWI combined with DCE-MRI quantitative analysis in the diagnosis of PCa.

MATERIAL AND METHODS

A systematic search was conducted through PubMed, MEDLINE, the Cochrane Library, and EMBASE databases without any restriction to language up to 10 December 2019. Studies that used a combination of DWI and DCE-MRI for diagnosing PCa were included.

RESULTS

Nine studies with 778 participants were included. The combination of DWI and DCE-MRI provide accurate performance in diagnosing PCa with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratios of 0.79 (95% confidence interval [CI] = 0.76-0.81), 0.85 (95% CI = 0.83-0.86), 6.58 (95% CI = 3.93-11.00), 0.24 (95% CI = 0.17-0.34), and 36.43 (95% CI = 14.41-92.12), respectively. The pooled area under the summary receiver operating characteristic curve was 0.9268. Moreover, 1.5-T MR scanners demonstrated a slightly better performance than 3.0-T scanners.

CONCLUSION

Combined DCE-MRI and DWI could demonstrate a highly accurate area under the curve, sensitivity, and specificity for detecting PCa. More studies with large sample sizes are warranted to confirm these results.

A rapid review of influential factors and appraised solutions on organ delineation uncertainties reduction in radiotherapy

Background and purpose.Accurate volume delineation plays an essential role in radiotherapy. Contouring is a potential source of uncertainties in radiotherapy treatment planning that could affect treatment outcomes. Therefore, reducing the degree of contouring uncertainties is crucial. The role of utilized imaging modality in the organ delineation uncertainties has been investigated. This systematic review explores the influential factors on inter-and intra-observer uncertainties of target volume and organs at risk (OARs) delineation focusing on the used imaging modality for these uncertainties reduction and the reported subsequent histopathology and follow-up assessment.Methods and materials.An inclusive search strategy has been conducted to query the available online databases (Scopus, Google Scholar, PubMed, and Medline). 'Organ at risk', 'target', 'delineation', 'uncertainties', 'radiotherapy' and their relevant terms were utilized using every database searching syntax. Final article extraction was performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Included studies were limited to the ones published in English between 1995 and 2020 and that just deal with computed tomography (CT) and magnetic resonance imaging (MRI) modalities.Results.A total of 923 studies were screened and 78 were included of which 31 related to the prostate 20 to the breast, 18 to the head and neck, and 9 to the brain tumor site. 98% of the extracted studies performed volumetric analysis. Only 24% of the publications reported the dose deviations resulted from variation in volume delineation Also, heterogeneity in studied populations and reported geometric and volumetric parameters were identified such that quantitative synthesis was not appropriate.Conclusion.This review highlightes the inter- and intra-observer variations that could lead to contouring uncertainties and impede tumor control in radiotherapy. For improving volume delineation and reducing inter-observer variability, the implementation of well structured training programs, homogeneity in following consensus and guidelines, reliable ground truth selection, and proper imaging modality utilization could be clinically beneficial.

Mapping prostatic microscopic anisotropy using linear and spherical b-tensor encoding: A preliminary study

Purpose:

Tensor-valued diffusion encoding provides more specific information than conventional diffusion-weighted imaging (DWI), but has mainly been applied in neuroimaging studies. This study aimed to assess its potential for the imaging of prostate cancer (PCa).

Methods:

Seventeen patients with histologically proven PCa were enrolled. DWI of the prostate was performed with linear and spherical tensor encoding using a maximal b-value of 1.5 ms/μm² and a voxel size of 3 × 3 × 4 mm³. The gamma-distribution model was used to estimate the mean diffusivity (MD), the isotropic kurtosis (MK_I), and the anisotropic kurtosis (MK_A). Regions of interest were placed in MR-defined cancerous tissues, as well as in apparently healthy tissues in the peripheral and transitional zones (PZs and TZs).

Results:

DWI with linear and spherical encoding yielded different image contrasts at high b-values, which enabled the estimation of MK_A and MK_I. Compared with healthy tissue (PZs and TZs combined) the cancers displayed a significantly lower MD (P < .05), higher MK_I (P < 10⁻⁵), and lower MK_A (P < .05). Compared with the TZ, tissue in the PZ showed lower MD (P < 10⁻³) and higher MK_A (P < 10⁻³). No significant differences were found between cancers of different Gleason scores, possibly because of the limited sample size.

Conclusion:

Tensor-valued diffusion encoding enabled mapping of MK_A and MK_I in the prostate. The elevated MK_I in PCa compared with normal tissues suggests an elevated heterogeneity in the cancers. Increased in-plane resolution could improve tumor delineation in future studies.

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294

A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

Arterial spin labelling as a gadolinium-free alternative in the detection of prostate cancer

PURPOSE

To determine the capability of Gadolinium-free arterial spin labelling (ASL) sequences as novel, contrast-free, non-invasive alternative perfusion imaging method to differentiate prostate cancer (PCA) from benign prostate tissue compared to conventional DCE MRI.

METHODS

Thirty men with histologically confirmed PCA were included in this prospectively enrolled single center cohort study. All patients received multiparametric MRI (T2, DWI, DCE) at 3 T with additional ASL of the PCA lesion. Primary endpoint was differentiability of PCA versus benign prostate tissue by signal intensities (SI) and contrast ratios (CR) in ASL in comparison to DCE. For DCE also Signal-Enhancement-Ratio (SER) of native and early contrast enhancement SI was assessed. Secondary objectives were differences regarding PCA localisation in peripheral (PZ) or transition zone (TZ) and PCA detection.

RESULTS

In both, ASL and DCE, average SI of PCA differed significantly from SI in benign tissue in the TZ and PZ (p < 0,01, respectively). ASL had significantly higher CR discerning PCA and benign tissue in PZ and TZ (PZ = 5.19; TZ = 6.45) compared to DCE SI (PZ = 1.61; TZ = 1.43) and DCE SER (PZ = 1.59; TZ = 1.43) (p < 0.01, respectively). In subjective evaluation, PCA could be detected in ASL in 28 patients, compared to 29 in DCE.

CONCLUSION

ASL had significantly higher CR differentiating PCA from benign tissue in PZ and TZ compared to DCE. Visual detection of PCA does not differ significantly between the two sequences. As perfusion gadolinium-based contrast media is seen more critical in the last few years, ASL seems to be a promising alternative to DCE in PCA detection.

The effect of hydrogen bonding on diffusion and permeability in UV-cured Polyacrylate-based networks for controlled release

Polyacrylates are important polymers widely used in pharmaceutical industry such as drug coatings due to their low cost, processability and ease of functionalisation. Chemical functionalities (e.g. H-bonding) can be easily included to modulate the transport of low molecular weight drug-like entities through the network. Understanding how such microscopic structural modifications determine macroscopic diffusion is critical for designing next generation responsive polymers. In this study pulsed field gradient (PFG) ¹H NMR measurements of the self-diffusion of a dye molecule (Eosin Y) in a series of polyacrylate networks with differing H-bonding strength were undertaken; it was found that the diffusion of Eosin Y is significantly reduced in networks with H-bonding. Detailed analyses by ¹H NMR relaxometry and double quantum (DQ) NMR show that H-bonding can also reduce polymer chain mobility. Furthermore, DSC thermoporometry showed a significant increase in the average network mesh size potentially due to the pre-organization of H-bonding containing monomer during network curing. By introducing the H-bonding disrupter, LiClO₄, it was found that the diffusivity of solute becomes positively correlated to the average mesh size across the series of networks. Hence, a modified diffusion model based on hydrodynamic theory is proposed to separate the direct (solute-network) H-bonding contribution to solute diffusion from the indirect contribution arising from monomer pre-ordering induced mesh size reduction. Finally, it is shown that the same direct and indirect contributions to microscopic diffusivity, arising from the H-bond strength of the co-monomers, also contribute significantly to the macroscopic membrane permeability which is similarly subject to H-bond disruption.

Histopathological features of prostate cancer conspicuity on multiparametric MRI: protocol for a systematic review and meta-analysis

INTRODUCTION

Multiparametric MRI (mpMRI) has improved risk stratification for men with suspected prostate cancer. Indeed, mpMRI-visible tumours tend to be larger and of higher pathological grade than mpMRI-invisible tumours; however, concern remains around significant cancer that is undetected by mpMRI. There has been considerable recent interest to investigate whether tumour conspicuity on mpMRI is associated with additional histopathological features (including cellular density, microvessel density and unusual prostate cancer subtypes), which may have important clinical implications in both diagnosis and prognosis. Furthermore, analysis of these features may help reveal the radiobiology that underpins the actual mechanisms of mpMRI visibility (and invisibility) of prostate tumours. Here, we describe a protocol for a systematic review of the histopathological basis of prostate cancer conspicuity on mpMRI.

METHODS AND ANALYSIS

A systematic search of the MEDLINE, PubMed, Embase and Cochrane databases will be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines will be used to guide screening, thematic reporting and conclusions drawn from all eligible studies. Included papers will be full-text, English-language articles, comparing the histopathological characteristics of mpMRI-visible lesions and mpMRI-invisible tumours. All studies published between January 1950 and January 2020 will be eligible for inclusion. Studies using confirmatory immunohistochemistry for the identification of immune subsets or structural components will be included. Study bias and quality will be assessed using a modified Newcastle-Ottawa scale. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist. If appropriate, a meta-analysis will be conducted comparing histopathological feature frequency between mpMRI-visible and mpMRI-invisible disease.

ETHICS AND DISSEMINATION

No ethical approval will be required as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals and presentations at national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42020176049.

Application of hierarchical clustering to multi-parametric MR in prostate: Differentiation of tumor and normal tissue with high accuracy

PURPOSE

Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretable way, in contrast to deep learning (DL) techniques.

METHODS

HC was constructed using mp-MR including intravoxel incoherent motion, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI from 40 tumor and normal tissues in peripheral zone (PZ) and 23 tumor and normal tissues in transition zone (TZ). HC model was optimized by assessing the combinations of several dissimilarity and linkage methods. Goodness of HC model was validated by internal methods.

RESULTS

Accuracy for differentiating tumor and normal tissue by optimal HC model was 96.3% in PZ and 97.8% in TZ, comparable to current clinical standards. Relationship between input (DWI and permeability parameters) and output (tumor and normal tissue cluster) was shown by heat maps, consistent with literature.

CONCLUSION

HC can accurately differentiate PCa and normal tissue, comparable to state-of-the-art diffusion based parameters. Contrary to DL techniques, HC is an operator-independent ML technique producing results that can be interpreted such that the results can be knowledgeably judged.

Prostatitis, the Great Mimicker of Prostate Cancer: Can We Differentiate Them Quantitatively With Multiparametric MRI?

OBJECTIVE. The purpose of this study was to investigate the diagnostic performance of semiquantitative and quantitative pharmacokinetic parameters and quantitative apparent diffusion coefficient (ADC) values obtained from prostate multiparametric MRI (mpMRI) to differentiate prostate cancer (PCa) and prostatitis objectively. MATERIALS AND METHODS. We conducted a retrospective review of patients with biopsy-proven PCa or prostatitis who underwent mpMRI study between January 2015 and February 2018. Mean ADC, forward volume transfer constant (K^trans), reverse volume transfer constant (k_ep), plasma volume fraction (V_p), extravascular extracellular space volume fraction (V_e), and time to peak (TTP) values were calculated for both lesions and contralateral normal prostate tissue. Signal intensity-time curves were analyzed. Lesion-to-normal prostate tissue ratios of pharmacokinetic parameters were also calculated. The diagnostic accuracy and cutoff points of all parameters were analyzed to differentiate PCa from prostatitis. RESULTS. A total of 138 patients (94 with PCa and 44 with prostatitis) were included in the study. Statistically, ADC, quantitative pharmacokinetic parameters (K^trans, k_ep, V_e, and V_p), their lesion-to-normal prostate tissue ratios, and TTP values successfully differentiated PCa and prostatitis. Surprisingly, we found that V_e values were significantly higher in prostatitis lesions. The combination of these parameters had 92.7% overall diagnostic accuracy. ADC, k_ep, and TTP made up the most successful combination for differential diagnosis. Analysis of the signal intensity-time curves showed mostly type 2 and type 3 enhancement curve patterns for patients with PCa. Type 3 curves were not seen in any prostatitis cases. CONCLUSION. Quantitative analysis of mpMRI differentiates PCa from prostatitis with high sensitivity and specificity, appears to have significant potential, and may improve diagnostic accuracy. In addition, evaluating these parameters does not cause any extra burden to the patients.

Quantitative imaging for radiotherapy purposes

Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.

Is dynamic contrast enhancement still necessary in multiparametric magnetic resonance for diagnosis of prostate cancer: a systematic review and meta-analysis

Background

The purpose of this study is to systematically review the literatures assessing the value of dynamic contrast enhancement (DCE) in the multiparametric magnetic resonance imaging (mpMRI) for the diagnosis of prostate cancer (PCa).

Methods

We searched Embase, PubMed and Web of science until January 2019 to extract articles exploring the possibilities whether the pre-biopsy biparametric magnetic resonance imaging (bpMRI) can replace the position of mpMRI in the diagnosis of PCa. The sensitivity and specificity of bpMRI were all included. The study quality was assessed by QUADAS-2. Bivariate random effects meta-analyses and a hierarchical summary receiver operating characteristic plot were performed for further study through Revman 5 and Stata12.

Results

After searching, we acquired 752 articles among which 45 studies with 5,217 participants were eligible for inclusion. The positive likelihood ratio for the detection of PCa was 2.40 (95% CI: 1.50–3.80) and the negative likelihood ratio was 0.31 (95% CI: 0.18–0.53). The sensitivity and specificity were 0.77 (95% CI: 0.73–0.81) and 0.81 (95% CI: 0.76–0.85) respectively. Based on our result, pooled specificity demonstrated little difference between bpMRI and mpMRI [bpMRI, 0.81 (95% CI, 0.76–0.85); mpMRI, 0.82 (95% CI, 0.72–0.88); P=0.169]. The sensitivity, however, indicated a significant difference between these two groups [bpMRI, 0.77 (95% CI, 0.73–0.81); mpMRI, 0.84 (95% CI, 0.78–0.89); P=0.001].

Conclusions

bpMRI with high b-value is a sensitive tool for diagnosing PCa. Consistent results were found in multiple subgroup analysis.

The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study

Objective

Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE).

Materials and methods

The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately.

Results

Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively.

Conclusion

DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.

Diagnostic evaluation of diffusion kurtosis imaging for prostate cancer: Detection in a biopsy population

PURPOSE

To prospectively assess the feasibility of diffusional kurtosis (DK) imaging for distinguishing prostate cancer(PCa) from benign prostate hyperplasia (BPH) in comparison with standard diffusion-weighted (DW) imaging, as well as low-from high-grade malignant regions.

MATERIALS AND METHODS

147 consecutive patients with suspected PCa underwent multi-parametric 1.5-TMR. Diffusion kurtosis imaging was acquired with with 5 b values (0,600,800,1600,and 2400sec/mm2).Region of interest (ROI)-based measurements were performed on ADC, D, and K map by two radiologists. Data were analyzed by using mixed-model analysis of variance and receiver operating characteristic curves. Correlations among the three parameters (ADC,D and K) in all patients, and correlations between three parameters with the tumor Gleason score (GS) in PCa group were analyzed using Pearson's correlation coefficient in peripheral zone(PZ) and transiton zone(TZ).

RESULTS

58 patients were proved with PCa (9 GS 3 + 3[PZ/TZ = 4/5], 49 GS ≥ 7 [PZ/TZ = 26/23]), and 89 patients were with BPH. ADC,D and K were able to distinguish benignance from tumor tissue both in PZ and TZ(P＜0.01), but performed poorly in neither differentiating low-(GS 3 + 3) from high-grade (GS≥3 + 4) disease, nor GS(3 + 4) from GS(4 + 3).There was a weak correlation between the GS and ADC, D (PZ:ADC r=-0.113, D r=-0.139; TZ:ADC r=-0.104,D r=-0.103), while a moderate correlation between the GS and K(PZ:K r = 0.492; TZ:K r = 0.433, P＜0.01).K had significantly greater area under the curve for differentiating PCa from BHP than ADC both in PZ and TZ.

CONCLUSION

DK model may add value in PCa detection and diagnosis, but none can differentiate low-from high-grade PCas (including GS=3+4 from GS=4+3).

Volumetric and Voxel-Wise Analysis of Dominant Intraprostatic Lesions on Multiparametric MRI

Introduction: Multiparametric MR imaging (mpMRI) has shown promising results in the diagnosis and localization of prostate cancer. Furthermore, mpMRI may play an important role in identifying the dominant intraprostatic lesion (DIL) for radiotherapy boost. We sought to investigate the level of correlation between dominant tumor foci contoured on various mpMRI sequences. Methods: mpMRI data from 90 patients with MR-guided biopsy-proven prostate cancer were obtained from the SPIE-AAPM-NCI Prostate MR Classification Challenge. Each case consisted of T2-weighted (T2W), apparent diffusion coefficient (ADC), and K^trans images computed from dynamic contrast-enhanced sequences. All image sets were rigidly co-registered, and the dominant tumor foci were identified and contoured for each MRI sequence. Hausdorff distance (HD), mean distance to agreement (MDA), and Dice and Jaccard coefficients were calculated between the contours for each pair of MRI sequences (i.e., T2 vs. ADC, T2 vs. K^trans, and ADC vs. K^trans). The voxel wise spearman correlation was also obtained between these image pairs. Results: The DILs were located in the anterior fibromuscular stroma, central zone, peripheral zone, and transition zone in 35.2, 5.6, 32.4, and 25.4% of patients, respectively. Gleason grade groups 1-5 represented 29.6, 40.8, 15.5, and 14.1% of the study population, respectively (with group grades 4 and 5 analyzed together). The mean contour volumes for the T2W images, and the ADC and K^trans maps were 2.14 ± 2.1, 2.22 ± 2.2, and 1.84 ± 1.5 mL, respectively. K^trans values were indistinguishable between cancerous regions and the rest of prostatic regions for 19 patients. The Dice coefficient and Jaccard index were 0.74 ± 0.13, 0.60 ± 0.15 for T2W-ADC and 0.61 ± 0.16, 0.46 ± 0.16 for T2W-K^trans. The voxel-based Spearman correlations were 0.20 ± 0.20 for T2W-ADC and 0.13 ± 0.25 for T2W-K^trans. Conclusions: The DIL contoured on T2W images had a high level of agreement with those contoured on ADC maps, but there was little to no quantitative correlation of these results with tumor location and Gleason grade group. Technical hurdles are yet to be solved for precision radiotherapy to target the DILs based on physiological imaging. A Boolean sum volume (BSV) incorporating all available MR sequences may be reasonable in delineating the DIL boost volume.

Assessment of solid components of borderline ovarian tumor and stage I carcinoma: added value of combined diffusion- and perfusion-weighted magnetic resonance imaging

Background

We sought to determine the value of combining diffusion-weighted (DW) and perfusion-weighted (PW) sequences with a conventional magnetic resonance (MR) sequence to assess solid components of borderline ovarian tumors (BOTs) and stage I carcinomas.

Methods

Conventional, DW, and PW sequences in the tumor imaging studies of 70 patients (BOTs, n=38; stage I carcinomas, n=32) who underwent surgery with pathologic correlation were assessed. Two independent radiologists calculated the parameters apparent diffusion coefficient (ADC), K^trans (vessel permeability), and V_e (cell density) for the solid components. The distribution on conventional MR sequence and mean, standard deviation, and 95% confidence interval of each DW and PW parameter were calculated. The inter-observer agreement among the two radiologists was assessed. Area under the receiver operating characteristic curve (AUC) and multivariate logistic regression were performed to compare the effectiveness of DW and PW sequences for average values and to characterize the diagnostic performance of combined DW and PW sequences.

Results

There were excellent agreements for DW and PW parameters between radiologists. The distributions of ADC, K^trans, and V_e values were significantly different between BOTs and stage I carcinomas, yielding AUCs of 0.58 and 0.68, 0.78 and 0.82, and 0.70 and 0.72, respectively, with ADC yielding the lowest diagnostic performance. The AUCs of the DW, PW, and combined PW and DW sequences were 0.71±0.05, 0.80±0.05, and 0.85±0.05, respectively.

Conclusion

Combining PW and DW sequences to a conventional sequence potentially improves the diagnostic accuracy in the differentiation of BOTs and stage I carcinomas.

Quantitative contrast-enhanced perfusion kinetics in multiparametric MRI in differentiating prostate cancer from chronic prostatitis: results from a pilot study

OBJECTIVE

The objectives of the study were to analyze the apparent diffusion coefficient (ADC), k^trans, k_ep metrics in dynamic contrast-enhanced multiparametric MRI (DCE-mpMRI) in biopsy proven cases of prostate cancer (PCa) and prostatitis and to establish "cut-off" values for various pharmacokinetic parameters that may distinguish PCa from chronic prostatitis.

METHODS

A retrospective review of all cases of PCa and chronic prostatitis patients, who underwent DCE-mpMRI in our institute was done from July 2017 to January 2019. Mean ADC, k^trans , k_ep for lesion "L" (ADCL, k^trans _L , k_epL) and normal prostate tissue "N" (ADCN, k^trans _N , k_epN ,) were calculated for each region of interest. Different ratios ADC ratio (defined as ADCL/ ADCN), k^trans ratio (k^trans _L/ k^trans _N), k_epratio (k_epL/k_epN) were calculated to differentiate PCa from chronic prostatitis.

RESULTS

Total of biopsy proven 14 cases of PCa and 18 cases of chronic prostatitis were included in the study. For k^trans ratio, the optimal cut-off was at 1.49 units where sensitivity was 85.7%, specificity was 61.1 % and Youden's index was 0.468 %. Similarly, optimal cut-offs determined for k_ep lesion was 0.86 (sensitivity 85.7%, specificity 66.7%, J = 0.524) and for k_ep ratio was 1.34 units (sensitivity 78.6%, specificity 66.7%, J = 0.543).

CONCLUSION

DCE-mpMRI metrics could differentiate between PCa and chronic prostatitis with good specificity and sensitivity, while ProstateImaging Reporting and Data System v. 2 alone, did not differentiate between these patterns.

ADVANCES IN KNOWLEDGE

k^trans ratio, k_ep lesion and k_ep ratio can differentiate PCa from chronic prostatitis.

Revisiting quantitative multi-parametric MRI of benign prostatic hyperplasia and its differentiation from transition zone cancer

PURPOSE

This study investigates the multiparametric MRI (mpMRI) appearance of different types of benign prostatic hyperplasia (BPH) and whether quantitative mpMRI is effective in differentiating between prostate cancer (PCa) and BPH.

MATERIALS AND METHODS

Patients (n = 60) with confirmed PCa underwent preoperative 3T MRI. T2-weighted, multi-echo T2-weighted, diffusion weighted and dynamic contrast enhanced images (DCE) were obtained prior to undergoing prostatectomy. PCa and BPH (cystic, glandular or stromal) were identified in the transition zone and matched with MRI. Quantitative mpMRI metrics: T2, ADC and DCE-MRI parameters using an empirical mathematical model were measured.

RESULTS

ADC values were significantly lower (p < 0.001) in PCa compared to all BPH types and can differentiate between PCa and BPH with high accuracy (AUC = 0.87, p < 0.001). T2 values were significantly lower (p < 0.001) in PCa compared to cystic BPH only, while glandular (p = 0.27) and stromal BPH (p = 0.99) showed no significant difference from PCa. BPH mimics PCa in the transition zone on DCE-MRI evidenced by no significant difference between them. mpMRI values of glandular (ADC = 1.31 ± 0.22 µm²/ms, T2 = 115.7 ± 37.3 ms) and cystic BPH (ADC = 1.92 ± 0.43 µm²/ms, T2 = 242.8 ± 117.9 ms) are significantly different. There was no significant difference in ADC (p = 0.72) and T2 (p = 0.46) between glandular and stromal BPH.

CONCLUSIONS

Multiparametric MRI and specifically quantitative ADC values can be used for differentiating PCa and BPH, improving PCa diagnosis in the transition zone. However, DCE-MRI metrics are not effective in distinguishing PCa and BPH. Glandular BPH are not hyperintense on ADC and T2 as previously thought and have similar quantitative mpMRI measurements to stromal BPH. Glandular and cystic BPH appear differently on mpMRI and are histologically different.

Multiparametric MRI to improve detection of prostate cancer compared with transrectal ultrasound-guided prostate biopsy alone: the PROMIS study

BACKGROUND

Men with suspected prostate cancer usually undergo transrectal ultrasound (TRUS)-guided prostate biopsy. TRUS-guided biopsy can cause side effects and has relatively poor diagnostic accuracy. Multiparametric magnetic resonance imaging (mpMRI) used as a triage test might allow men to avoid unnecessary TRUS-guided biopsy and improve diagnostic accuracy.

OBJECTIVES

To (1) assess the ability of mpMRI to identify men who can safely avoid unnecessary biopsy, (2) assess the ability of the mpMRI-based pathway to improve the rate of detection of clinically significant (CS) cancer compared with TRUS-guided biopsy and (3) estimate the cost-effectiveness of a mpMRI-based diagnostic pathway.

DESIGN

A validating paired-cohort study and an economic evaluation using a decision-analytic model.

SETTING

Eleven NHS hospitals in England.

PARTICIPANTS

Men at risk of prostate cancer undergoing a first prostate biopsy.

INTERVENTIONS

Participants underwent three tests: (1) mpMRI (the index test), (2) TRUS-guided biopsy (the current standard) and (3) template prostate mapping (TPM) biopsy (the reference test).

MAIN OUTCOME MEASURES

Diagnostic accuracy of mpMRI, TRUS-guided biopsy and TPM-biopsy measured by sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using primary and secondary definitions of CS cancer. The percentage of negative magnetic resonance imaging (MRI) scans was used to identify men who might be able to avoid biopsy.

RESULTS

Diagnostic study - a total of 740 men were registered and 576 underwent all three tests. According to TPM-biopsy, the prevalence of any cancer was 71% [95% confidence interval (CI) 67% to 75%]. The prevalence of CS cancer according to the primary definition (a Gleason score of ≥ 4 + 3 and/or cancer core length of ≥ 6 mm) was 40% (95% CI 36% to 44%). For CS cancer, TRUS-guided biopsy showed a sensitivity of 48% (95% CI 42% to 55%), specificity of 96% (95% CI 94% to 98%), PPV of 90% (95% CI 83% to 94%) and NPV of 74% (95% CI 69% to 78%). The sensitivity of mpMRI was 93% (95% CI 88% to 96%), specificity was 41% (95% CI 36% to 46%), PPV was 51% (95% CI 46% to 56%) and NPV was 89% (95% CI 83% to 94%). A negative mpMRI scan was recorded for 158 men (27%). Of these, 17 were found to have CS cancer on TPM-biopsy. Economic evaluation - the most cost-effective strategy involved testing all men with mpMRI, followed by MRI-guided TRUS-guided biopsy in those patients with suspected CS cancer, followed by rebiopsy if CS cancer was not detected. This strategy is cost-effective at the TRUS-guided biopsy definition 2 (any Gleason pattern of ≥ 4 and/or cancer core length of ≥ 4 mm), mpMRI definition 2 (lesion volume of ≥ 0.2 ml and/or Gleason score of ≥ 3 + 4) and cut-off point 2 (likely to be benign) and detects 95% (95% CI 92% to 98%) of CS cancers. The main drivers of cost-effectiveness were the unit costs of tests, the improvement in sensitivity of MRI-guided TRUS-guided biopsy compared with blind TRUS-guided biopsy and the longer-term costs and outcomes of men with cancer.

LIMITATIONS

The PROstate Magnetic resonance Imaging Study (PROMIS) was carried out in a selected group and excluded men with a prostate volume of > 100 ml, who are less likely to have cancer. The limitations in the economic modelling arise from the limited evidence on the long-term outcomes of men with prostate cancer and on the sensitivity of MRI-targeted repeat biopsy.

CONCLUSIONS

Incorporating mpMRI into the diagnostic pathway as an initial test prior to prostate biopsy may (1) reduce the proportion of men having unnecessary biopsies, (2) improve the detection of CS prostate cancer and (3) increase the cost-effectiveness of the prostate cancer diagnostic and therapeutic pathway. The PROMIS data set will be used for future research; this is likely to include modelling prognostic factors for CS cancer, optimising MRI scan sequencing and biomarker or translational research analyses using the blood and urine samples collected. Better-quality evidence on long-term outcomes in prostate cancer under the various management strategies is required to better assess cost-effectiveness. The value-of-information analysis should be developed further to assess new research to commission.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN16082556 and NCT01292291.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 39. See the NIHR Journals Library website for further project information. This project was also supported and partially funded by the NIHR Biomedical Research Centre at University College London (UCL) Hospitals NHS Foundation Trust and UCL and by The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research Biomedical Research Centre and was co-ordinated by the Medical Research Council's Clinical Trials Unit at UCL (grant code MC_UU_12023/28). It was sponsored by UCL. Funding for the additional collection of blood and urine samples for translational research was provided by Prostate Cancer UK.

Application evaluation of DCE-MRI combined with quantitative analysis of DWI for the diagnosis of prostate cancer

The present study aimed to investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with quantitative analysis of diffusion weighted imaging (DWI) for the diagnosis of prostate cancer (PCa). A total of 81 patients with prostatic diseases, including PCa (n=44) and benign prostatic hyperplasia (BPH, n=37), were imaged with T1 weighted imaging (T1WI), T2 weighted imaging (T2WI), DWI and DCE-MRI. The blood vessel permeability parameters volume transfer rate constant (K^trans), back flow rate constant (K_ep), extravascular extracellular space volume fraction (V_e), plasma volume fraction (V_p) and apparent diffusion coefficient (ADC) were measured, and compared between the two groups. The efficiency of these tools for the diagnosis of PCa was analyzed by receiver operating characteristic curve analysis. The efficiency of ADC combined with blood vessel permeability parameters in the diagnosis of PCa was analyzed by logistic regression. The correlation between these parameters and the Gleason score was evaluated by Spearman correlation analysis in the PCa group. The results demonstrated that, compared with the BPH group, K^trans, K_ep, V_e and V_p were higher, and ADC was lower in the PCa group (P<0.05). The combination of K_ep and ADC offered the highest diagnosis efficiency [area under the curve (AUC=0.939)]. However, the combination of three parameters did not significantly improve the diagnostic efficiency. A subtle improvement in diagnostic efficiency was observed when four parameters (K^trans + K_ep + V_e + ADC) were combined (AUC=0.940), which was significantly higher than with one parameter. The ADC value of the PCa group was negatively correlated with the primary Gleason pattern, secondary Gleason pattern and the total Gleason score in PCa (r=−0.665, −0.456 and −0.714, respectively; P<0.001). The V_p in the PCa group was slightly negatively correlated with the primary Gleason pattern of PCa (r=−0.385; P<0.05); however, no significant correlation was found with secondary Gleason pattern and the total Gleason score. The present study revealed that the combination of DCE-MRI quantitative analysis and DWI was efficient for PCa diagnosis. This may be because DCE-MRI and DWI can noninvasively detect water motility in tumor tissues and alterations in permeability during tumor neovascularization. The present study demonstrated that K_ep and ADC values may be used as predictive parameters for PCa diagnosis, which may help differentiate benign from malignant prostate lesions.

Multimodal PET/MRI Imaging Results Enable Monitoring the Side Effects of Radiation Therapy

Radiotherapy is one of the most frequently applied treatments in oncology. Tissue-absorbed ionizing radiation damages not only targeted cells but the surrounding cells too. The consequent long-term induced oxidative stress, irreversible tissue damage, or second malignancies draw attention to the urgent need of a follow-up medical method by which personalized treatment could be attained and the actually dose-limiting organ could be monitored in the clinical practice. We worked out a special hemisphere irradiation technique for mice which mimics the radiation exposure during radiotherapy. We followed up the changes of possible brain imaging biomarkers of side effects, such as cerebral blood flow, vascular endothelial function, and cellular metabolic processes for 60 days. BALB/c mice were divided into two groups (n=6 per group) based on the irradiation doses (5 and 20 Gy). After the irradiation procedure arterial spin labeling (ASL), diffusion-weighted imaging (DWI) in magnetic resonance modality and [¹⁸F]fluoro-deoxy-D-glucose positron emission tomography (FDG-PET) scans of the brain were obtained at several time points (3, 7, 30, and 60 days after the irradiation). Significant physiological changes were registered in the brain of animals following the irradiation by both applied doses. Elevated standard uptake values were detected all over the brain by FDG-PET studies 2 months after the irradiation. The apparent diffusion coefficients from DWI scans significantly decreased one month after the irradiation procedure, while ASL studies did not show any significant perfusion changes in the brain. Altogether, our sensitive multimodal imaging protocol seems to be an appropriate method for follow-up of the health status after radiation therapy. The presented approach makes possible parallel screening of healthy tissues and the effectiveness of tumor therapy without any additional radiation exposure.

Lighting-Up Tumor for Assisting Resection via Spraying NIR Fluorescent Probe of γ-Glutamyltranspeptidas

For the precision resection, development of near-infrared (NIR) fluorescent probe based on specificity identification tumor-associated enzyme for lighting-up the tumor area, is urgent in the field of diagnosis and treatment. Overexpression of γ-glutamyltranspeptidase, one of the cell-membrane enzymes, known as a biomarker is concerned with the growth and progression of ovarian, liver, colon and breast cancer compared to normal tissue. In this work, a remarkable enzyme-activated NIR fluorescent probe NIR-SN-GGT was proposed and synthesized including two moieties: a NIR dicyanoisophorone core as signal reporter unit; γ-glutamyl group as the specificity identification site. In the presence of γ-GGT, probe NIR-SN-GGT was transformed into NIR-SN-NH₂, the recovery of Intramolecular Charge Transfer (ICT), liberating the NIR fluorescence signal, which was firstly employed to distinguish tumor tissue and normal tissues via simple “spraying” manner, greatly promoting the possibility of precise excision. Furthermore, combined with magnetic resonance imaging by T2 weight mode, tumor transplanted BABL/c mice could be also lit up for first time by NIR fluorescence probe having a large stokes, which demonstrated that probe NIR-SN-GGT would be a useful tool for assisting surgeon to diagnose and remove tumor in clinical practice.

Feasibility of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using Low-Dose Gadolinium: Comparative Performance With Standard Dose in Prostate Cancer Diagnosis

OBJECTIVES

This study investigates whether administration of low doses of gadolinium-based contrast agent (GBCA) for dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can be as effective as a standard dose in distinguishing prostate cancer (PCa) from benign tissue. In addition, we evaluated the combination of kinetic parameters from the low- and high-dose injection as a new diagnostic marker.

MATERIALS AND METHODS

Patients (n = 17) with histologically confirmed PCa underwent preoperative 3 T MRI. Dynamic contrast-enhanced MRI images were acquired at 8.3-second temporal resolution with a low dose (0.015 mmol/kg) and close to the standard dose (0.085 mmol/kg) of gadobentate dimeglumine bolus injections. Low-dose images were acquired for 3.5 minutes, followed by a 5-minute gap before acquiring standard dose images for 8.3 minutes. The data were analyzed qualitatively to investigate whether lesions could be detected based on early focal enhancement and quantitatively by fitting signal intensity as a function of time with an empirical mathematical model to obtain a maximum enhancement projection (MEP) and signal enhancement rate (α).

RESULTS

Both low- and standard-dose DCE-MRI showed similar sensitivity (13/26 = 50%) and lesion conspicuity score (4.0 ± 1.0 vs 4.2 ± 0.9; P = 0.317) for PCa diagnosis on qualitative analysis. Prostate cancer showed significantly increased α compared with benign tissue for low (9.98 ± 5.84 vs 5.12 ± 2.95 s) but not for standard (4.27 ± 2.20 vs 3.35 ± 1.48 s) dose. The ratio of low-dose α to standard-dose α was significantly greater (P = 0.02) for PCa (2.8 ± 2.3) than for normal prostate (1.6 ± 0.9), suggesting changes in water exchange and T2* effects associated with cancer. In addition, decreases in the percentage change in T1 relaxation rate as a function of increasing contrast media concentration (ie, the "saturation effect") can also contribute to the observed differences in high-dose and low-dose α. Area under the receiver operating characteristic curve for differentiating PCa from benign tissue using α was higher for low dose (0.769) compared with standard dose (0.625). There were no significant differences between MEP calculated for PCa and normal tissue at the low and standard doses. Moderate significant Pearson correlation for DCE parameters, MEP (r = 0.53) and α (r = 0.58), was found between low and standard doses of GBCA.

CONCLUSIONS

These preliminary results suggest that DCE-MRI with a low GBCA dose distinguishes PCa from benign prostate tissue more effectively than does the standard GBCA dose, based on signal enhancement rate. Diagnostic accuracy is similar on qualitative assessment. Prostate cancer diagnosis may be feasible with DCE-MRI with low-dose GBCA. In addition, comparison of enhancement kinetics after low and high doses of contrast media may provide diagnostically useful information.

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.

Assessment of the need for DCE MRI in the detection of dominant lesions in the whole gland: Correlation between histology and MRI of prostate cancer

The purpose of this study was to evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) in the detection of dominant prostate tumors with multi-parametric MRI of the whole gland. Combined diffusion tensor imaging (DTI) and DCE MRI from 16 patients with biopsy-proven prostate cancer and no previous treatment were acquired with a 3.0-T MRI scanner prior to radical prostatectomy, and used to identify dominant tumors. MRI results were validated by whole-mount histology. Paired t-test and Wilcoxon test, logistic generalized linear mixed effect models and receiver operating characteristic (ROC) analyses were used for the estimation of the statistical significance of the results. In the peripheral zone (PZ), the areas under the ROC curve (ROC-AUC) were 0.98 (sensitivity, 96%; specificity, 98%) for DTI, 0.96 (sensitivity, 92%; specificity, 97%) for DCE and 0.99 (sensitivity, 98%; specificity, 98%) for DTI + DCE. In the entire prostate, the ROC-AUC values were 0.96 (sensitivity, 84%; specificity, 95%) for DTI, 0.87 (sensitivity, 45%; specificity, 94%) for DCE and 0.96 (sensitivity, 88%; specificity, 98%) for DTI + DCE. The increase in ROC-AUC by the addition of DCE was not statistically significant in either PZ or the entire prostate. The results of this study have shown that DTI identified dominant tumors with high accuracy in both PZ and the entire prostate, whereas the inclusion of DCE MRI had no significant impact on the identification of either PZ or entire prostate dominant lesions. Our results suggest that the inclusion of DCE MRI may not increase the accuracy of dominant lesion detection, allowing for faster, better tolerated imaging studies.

Multiparametric MRI for the detection of local recurrence of prostate cancer in the setting of biochemical recurrence after low dose rate brachytherapy

PURPOSE

Prostate multiparametric magnetic resonance imaging (mpMRI) has utility in detecting post-radiotherapy local recurrence. We conducted a multireader study to evaluate the diagnostic performance of mpMRI for local recurrence after low dose rate (LDR) brachytherapy.

METHODS

A total of 19 patients with biochemical recurrence after LDR brachytherapy underwent 3T endorectal coil mpMRI with T2-weighted imaging, dynamic contrast-enhanced imaging (DCE) and diffusion-weighted imaging (DWI) with pathologic confirmation. Prospective reads by an experienced prostate radiologist were compared with reads from 4 radiologists of varying experience. Readers identified suspicious lesions and rated each MRI detection parameter. MRI-detected lesions were considered true-positive with ipsilateral pathologic confirmation. Inferences for sensitivity, specificity, positive predictive value (PPV), kappa, and index of specific agreement were made with the use of bootstrap resampling.

RESULTS

Pathologically confirmed recurrence was found in 15 of 19 patients. True positive recurrences identified by mpMRI were frequently located in the transition zone (46.7%) and seminal vesicles (30%). On patient-based analysis, average sensitivity of mpMRI was 88% (standard error [SE], 3.5%). For highly suspicious lesions, specificity of mpMRI was 75% (SE, 16.5%). On lesion-based analysis, the average PPV was 62% (SE, 6.7%) for all lesions and 78.7% (SE, 10.3%) for highly suspicious lesions. The average PPV for lesions invading the seminal vesicles was 88.8% (n=13). The average PPV was 66.6% (SE, 5.8%) for lesions identified with T2-weighted imaging, 64.9% (SE, 7.3%) for DCE, and 70% (SE, 7.3%) for DWI.

CONCLUSION

This series provides evidence that mpMRI after LDR brachytherapy is feasible with a high patient-based cancer detection rate. Radiologists of varying experience demonstrated moderate agreement in detecting recurrence.

The efficacy and utilisation of preoperative multiparametric magnetic resonance imaging in robot-assisted radical prostatectomy: does it change the surgical dissection plan?

Objective

We investigated the effect of the use of multiparametric prostate magnetic resonance imaging (mp-MRI) on the dissection plan of the neurovascular bundle and the oncological results of our patients who underwent robot-assisted radical prostatectomy.

Material and methods

We prospectively evaluated 60 consecutive patients, including 30 patients who had (Group 1), and 30 patients who had not (Group 2) mp-MRI before robot-assisted radical prostatectomy. Based on the findings of mp-MRI, the dissection plan was changed as intrafascial, interfascial, and extrafascial in the mp-MRI group. Two groups were compared in terms of age, prostate-specific antigen (PSA), Gleason sum scores and surgical margin positivity.

Results

There was no statistically significant difference between the two groups in terms of age, PSA, biopsy Gleason score, final pathological Gleason score and surgical margin positivity. mp-MRI changed the initial surgical plan in 18 of 30 patients (60%) in Group 1. In seventeen of these patients (56%) surgical plan was changed from non-nerve sparing to interfascial nerve sparing plan. In one patient dissection plan was changed to non-nerve sparing technique which had extraprostatic extension on final pathology. Surgical margin positivity was similar in Groups 1, and 2 (16% and 13%, respectively) although, Group 1 had higher number of high- risk patients. mp-MRI confirmed the primary tumour localisation in the final pathology in 27 of of 30 patients (90%).

Conclusion

Preoperative mp-MRI effected the decision to perform a nerve-sparing technique in 56% of the patients in our study; moreover, changing the dissection plan from non-nerve-sparing technique to a nerve sparing technique did not increase the rate of surgical margin positivity.

Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging

Multiparametric magnetic resonance imaging (MP-MRI), including diffusion-weighted imaging, is commonly used to diagnose prostate cancer. This radiology–pathology study correlates prostate cancer grade and morphology with common b-value combinations for calculating apparent diffusion coefficient (ADC). Thirty-nine patients undergoing radical prostatectomy were recruited for MP-MRI prior to surgery. Diffusion imaging was collected with seven b-values, and ADC was calculated. Excised prostates were sliced in the same orientation as the MRI using 3-D printed slicing jigs. Whole-mount slides were digitized and annotated by a pathologist. Annotated samples were aligned to the MRI, and ADC values were extracted from annotated peripheral zone (PZ) regions. A receiver operating characteristic (ROC) analysis was performed to determine accuracy of tissue type discrimination and optimal ADC b-value combination. ADC significantly discriminates Gleason (G) G4-5 cancer from G3 and other prostate tissue types. The optimal b-values for discriminating high from low-grade and noncancerous tissue in the PZ are 50 and 2000, followed closely by 100 to 2000 and 0 to 2000. Optimal ADC cut-offs are presented for dichotomized discrimination of tissue types according to each b-value combination. Selection of b-values affects the sensitivity and specificity of ADC for discrimination of prostate cancer.

Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth

BACKGROUND

Prostate cancer (PCa) diagnosis by means of multiparametric magnetic resonance imaging (mpMRI) is a current challenge for the development of computer-aided detection (CAD) tools. An innovative CAD-software (Watson Elementary™) was proposed to achieve high sensitivity and specificity, as well as to allege a correlate to Gleason grade.

AIM/OBJECTIVE

To assess the performance of Watson Elementary™ in automated PCa diagnosis in our hospital´s database of MRI-guided prostate biopsies.

METHODS

The evaluation was retrospective for 104 lesions (47 PCa, 57 benign) from 79, 64.61±6.64 year old patients using 3T T2-weighted imaging, Apparent Diffusion Coefficient (ADC) maps and dynamic contrast enhancement series. Watson Elementary™ utilizes signal intensity, diffusion properties and kinetic profile to compute a proportional Gleason grade predictor, termed Malignancy Attention Index (MAI). The analysis focused on (i) the CAD sensitivity and specificity to classify suspect lesions and (ii) the MAI correlation with the histopathological ground truth.

RESULTS

The software revealed a sensitivity of 46.80% for PCa classification. The specificity for PCa was found to be 75.43% with a positive predictive value of 61.11%, a negative predictive value of 63.23% and a false discovery rate of 38.89%. CAD classified PCa and benign lesions with equal probability (P 0.06, χ2 test). Accordingly, receiver operating characteristic analysis suggests a poor predictive value for MAI with an area under curve of 0.65 (P 0.02), which is not superior to the performance of board certified observers. Moreover, MAI revealed no significant correlation with Gleason grade (P 0.60, Pearson´s correlation).

CONCLUSION

The tested CAD software for mpMRI analysis was a weak PCa biomarker in this dataset. Targeted prostate biopsy and histology remains the gold standard for prostate cancer diagnosis.

Comparison of Prostate Imaging Reporting and Data System versions 1 and 2 for the Detection of Peripheral Zone Gleason Score 3 + 4 = 7 Cancers

OBJECTIVE

The objective of our study was to compare Prostate Imaging Reporting and Data System version 1 (PI-RADSv1) and Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for the detection of peripheral zone (PZ) Gleason score 3 + 4 = 7 cancers.

MATERIALS AND METHODS

Forty-seven consecutive patients with 52 PZ Gleason score 3 + 4 = 7 cancers that were 0.5 cm³ or larger underwent radical prostatectomy (RP) and 3-T MRI between 2012 and 2015. Two blinded radiologists (readers 1 and 2) retrospectively assigned PI-RADSv1 sequence (T2-weighted imaging, DWI, dynamic contrast-enhanced MRI [DCE-MRI]) and sum scores and PI-RADSv2 assessment categories. A third blinded radiologist (reader 3) measured apparent diffusion coefficient (ADC) ratio (ADC of tumor / ADC of normal PZ) using RP-MRI maps. Sensitivity, false-positive rate, and overall accuracy were compared using McNemar test. Pearson correlation was performed.

RESULTS

Using PI-RADSv1, reader 1 detected 86.5% (45/52) of the cancers and reader 2, 76.9% (40/52) of the cancers. Using PI-RADSv2, reader 1 detected 78.9% (41/52) and reader 2, 67.3% (35/52). Reader 1 detected 7.7% (4/52) and reader 2 detected 9.6% (5/52) more tumors using PI-RADSv1 due to T2-weighted imaging score ≥ 4 or DCE-MRI score ≥ 3. Sensitivity was higher for PI-RADSv1 (p = 0.01 and 0.03, readers 1 and 2). False-positive rates were higher with PI-RADSv1 than with PI-RADSv2 (1.8% vs 0.9% for reader 1; 3.6% vs 1.8% for reader 2) without significant differences in false-positive rate (p = 0.41 and 0.25) or overall accuracy (p = 0.06 and 0.23). PI-RADSv1 sum scores correlated strongly with PI-RADSv2 categories (B = 0.78-0.93, p < 0.0001). The mean ADC ratio was 0.61 ± 0.14 mm²/s with no difference between visible and nonvisible tumors (p = 0.06-0.5). Interobserver agreement was moderate for PI-RADSv2 (κ = 0.41) and ranged from slight to substantial for PI-RADSv1 (T2-weighted imaging, κ = 0.32; DWI, κ = 0.52; DCE-MRI, κ = 0.13).

CONCLUSION

There was no difference in overall detection of cancers comparing PI-RADSv1 and PI-RADSv2; however, PI-RADSv1 sequence scores on T2-weighted imaging and DCE-MRI detected approximately 10% more tumors that were otherwise underestimated on DWI and using PI-RADSv2 decision-tree rules.

Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 IEEE Trans. Image Process. 19 2444-55, Litjens et al 2014 IEEE Trans. Med. Imaging 33 1083-92, Liu et al 2013 SPIE Medical Imaging (International Society for Optics and Photonics) p 86701G, Moradi et al 2012 J. Magn. Reson. Imaging 35 1403-13, Niaf et al 2014 IEEE Trans. Image Process. 23 979-91, Niaf et al 2012 Phys. Med. Biol. 57 3833, Peng et al 2013a SPIE Medical Imaging (International Society for Optics and Photonics) p 86701H, Peng et al 2013b Radiology 267 787-96, Wang et al 2014 BioMed. Res. Int. 2014). This paper presents an automated method based on multimodal convolutional neural networks (CNNs) for two PCa diagnostic tasks: (1) distinguishing between cancerous and noncancerous tissues and (2) distinguishing between clinically significant (CS) and indolent PCa. Specifically, our multimodal CNNs effectively fuse apparent diffusion coefficients (ADCs) and T2-weighted MP-MRI images (T2WIs). To effectively fuse ADCs and T2WIs we design a new similarity loss function to enforce consistent features being extracted from both ADCs and T2WIs. The similarity loss is combined with the conventional classification loss functions and integrated into the back-propagation procedure of CNN training. The similarity loss enables better fusion results than existing methods as the feature learning processes of both modalities are mutually guided, jointly facilitating CNN to 'see' the true visual patterns of PCa. The classification results of multimodal CNNs are further combined with the results based on handcrafted features using a support vector machine classifier. To achieve a satisfactory accuracy for clinical use, we comprehensively investigate three critical factors which could greatly affect the performance of our multimodal CNNs but have not been carefully studied previously. (1) Given limited training data, how can these be augmented in sufficient numbers and variety for fine-tuning deep CNN networks for PCa diagnosis? (2) How can multimodal MP-MRI information be effectively combined in CNNs? (3) What is the impact of different CNN architectures on the accuracy of PCa diagnosis? Experimental results on extensive clinical data from 364 patients with a total of 463 PCa lesions and 450 identified noncancerous image patches demonstrate that our system can achieve a sensitivity of 89.85% and a specificity of 95.83% for distinguishing cancer from noncancerous tissues and a sensitivity of 100% and a specificity of 76.92% for distinguishing indolent PCa from CS PCa. This result is significantly superior to the state-of-the-art method relying on handcrafted features.

Multiparametric Magnetic Resonance Imaging of the Prostate for Tumour Detection and Local Staging: Imaging in 1.5T and Histopathologic Correlation

PURPOSE

The study sought to prospectively evaluate which technique among T2-weighted images, dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), diffusion-weighted (DW) MRI, or a combination of the 2, is best suited for prostate cancer detection and local staging.

METHODS

Twenty-seven consecutive patients with biopsy-proven adenocarcinoma of the prostate underwent MRI on a 1.5T scanner with a surface phased-array coil prior radical prostatectomy. Combined anatomical and functional imaging was performed with the use of T2-weighted sequences, DCE MRI, and DW MRI. We compared the imaging results with whole mount histopathology.

RESULTS

For the multiparametric approach, significantly higher sensitivity values, that is, 53% (95% confidence interval [CI]: 41.0-64.1) were obtained as compared with each modality alone or any combination of the 3 modalities (P < .05). The specificity for this multiparametric approach, being 90.3% (95% CI: 86.3-93.3) was not significantly higher (P < .05) as compared with the values of the combination of T2+DCE MRI, DW+DCE MRI, or DCE MRI alone. Among the 3 techniques, DCE had the best performance for tumour detection in both the peripheral and the transition zone. High negative predictive value rates (>86%) were obtained for both tumour detection and local staging.

CONCLUSIONS

The combination of T2-weighted sequences, DCE MRI, and DW MRI yields higher diagnostic performance for tumour detection and local staging than can any of these techniques alone or even any combination of them.

Multiparametric approach with diffusion-weighted imaging and dynamic contrast-enhanced MRI: a comparison study for differentiating between benign and malignant bone lesions in adults

AIM

To evaluate and compare the diagnostic performance of quantitative parameters derived from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating benign and malignant bone tumours.

MATERIALS AND METHODS

Fifty-five patients (age range, 21-82 years; mean age, 55 years) underwent pretreatment MRI. Apparent diffusion coefficient (ADC) values were calculated by DWI. The DCE-MRI data were analysed for the volume transfer constant (K^trans), extravascular extracellular volume fraction (V_e), and volume rate constant (K_ep), and K^trans/ADC ratio. Each parameter's performance was evaluated using the area under the receiver operating characteristic (ROC) curv (AUC), and their AUCs were compared. ROC curves were analysed and each parameter's optimal cut-off value was determined, from which each parameter was evaluated for sensitivity, specificity, accuracy, and positive and negative predictive values. The odds ratio (OR) with 95% confidence interval for detecting malignant bone lesions after adjusting the age factor of each parameter was estimated.

RESULTS

All parameter values (except V_e) were significantly different between benign and malignant bone tumours (p<0.05). The K^trans had a significantly greater AUC than V_e (p=0.03). The K^trans/ADC and K_ep had the best sensitivity (0.917) and specificity (0.632), respectively. The K_ep and K^trans/ADC had the best positive (0.811) and negative (0.769) predictive values, respectively. The OR was highest for K^trans/ADC (17.38; p=0.0013).

CONCLUSION

The K^trans, K_ep, ADC, and K^trans/ADC could help to detect malignant lesions from bone tumours and K^trans/ADC appears to be the superior variable among them.

DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness

PURPOSE

To quantify Tofts model (TM) and shutter-speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to Prostate Imaging and Reporting and Data System (PI-RADS) classification for the assessment of PCa aggressiveness.

MATERIALS AND METHODS

Fifty PCa patients (mean age 60 years old) who underwent MRI at 3.0T followed by prostatectomy were included in this Institutional Review Board-approved retrospective study. DCE-MRI parameters (K^trans , v_e , k_ep [TM&SSM] and intracellular water molecule lifetime τ_i [SSM]) were determined in PCa and PZ. Differences in DCE-MRI parameters between PCa and PZ, and between models were assessed using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis for differentiation between PCa and PZ was performed for individual and combined DCE-MRI parameters. Diagnostic performance of DCE-MRI parameters for identification of aggressive PCa (Gleason ≥8, grade group [GG] ≥3 or pathology stage pT3) was assessed using ROC analysis and compared with PI-RADSv2 scores.

RESULTS

DCE-MRI parameters were significantly different between TM and SSM and between PZ and PCa (P < 0.037). Diagnostic performances of TM and SSM for differentiation of PCa from PZ were similar (highest AUC TM: K^trans +k_ep 0.76, SSM: τ_i +k_ep 0.80). PI-RADS outperformed TM and SSM DCE-MRI for identification of Gleason ≥8 lesions (AUC PI-RADS: 0.91, highest AUC DCE-MRI: K^trans +τ_i SSM 0.61, P = 0.002). The diagnostic performance of PI-RADS and DCE-MRI for identification of GG ≥3 and pT3 PCa was not significantly different (P > 0.213).

CONCLUSION

SSM DCE-MRI did not increase the diagnostic performance of DCE-MRI for PCa characterization. PI-RADS outperformed both TM and SSM DCE-MRI for identification of aggressive cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:837-849.

In Vivo 3T Magnetic Resonance Imaging Using a Biologically Specific Contrast Agent for Prostate Cancer: A Nude Mouse Model

We characterized in vivo a functional superparamagnetic iron-oxide magnetic resonance contrast agent that shortens the T2 relaxation time in magnetic resonance imaging (MRI) of prostate cancer xenografts. The agent was developed by conjugating Molday ION™ carboxyl-6 (MIC6), with a deimmunized mouse monoclonal antibody (muJ591) targeting prostate-specific membrane antigen (PSMA). This functional contrast agent could be used as a noninvasive method to detect prostate cancer cells that are PSMA positive and more readily differentiate them from surrounding tissues for treatment. The functional contrast agent was injected intravenously into mice and its effect was compared to both MIC6 (without conjugated antibody) and phosphate-buffered saline (PBS) injection controls. MR imaging was performed on a clinical 3T MRI scanner using a multiecho spin echo (MESE) sequence to obtain T2 relaxation time values. Inductively coupled plasma atomic emission spectroscopy was used to confirm an increase in elemental iron in injected mice tumours relative to controls. Histological examination of H&E stained tissues showed normal morphology of the tissues collected.

Differential diagnosis of prostate cancer and noncancerous tissue in the peripheral zone and central gland using the quantitative parameters of DCE-MRI: A meta-analysis

BACKGROUND

The objective of this meta-analysis was to evaluate the clinical usefulness of K, Kep, and Ve values in the differential diagnosis of prostate cancer (PCa) and noncancerous tissue in the peripheral zone (PZ) and central gland (CG).

METHODS

A search was conducted of the PubMed, MEDLINE, EMBASE, Cochrane Library, China National Knowledge Infrastructure, and Wanfang databases from January 2000 to October 2015 using the search terms "prostate cancer," " dynamic contrast-enhanced (DCE)," "magnetic resonance imaging," "K," "Kep," and "Ve." Studies were selected and included according to strict eligibility criteria. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were used to compare K, Kep, and Ve values between PCa and noncancerous tissue.

RESULTS

Fourteen studies representing 484 patients highly suspicious for prostate adenocarcinoma were selected for the meta-analysis. We found that K values measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) were significantly higher in PCa tissue than in noncancerous tissue in the PZ (SMD 1.57, 95% CI 0.98-2.16; z = 5.21, P <0.00001) and CG (SMD 1.19, 95% CI 0.46-1.91; z = 3.21, P = 0.001). Kep values measured by DCE-MRI were significantly higher in PCa than in noncancerous tissue in the PZ (SMD 1.41, 95% CI 0.92-1.91; z = 5.59, P < 0.00001) and CG (SMD 1.57, 95% CI 0.69-2.46; z = 3.49, P = 0.0005). Ve values generated by DCE-MRI were slightly higher in PCa than in noncancerous tissue in the PZ (SMD 0.72, 95% CI 0.17-1.27; z = 2.58, P = 0.010), but sensitivity analysis found that the Ve value was unstable for differentiation between PCa and noncancerous PZ tissue. However, there was no significant difference in the Ve value between PCa and noncancerous CG tissue (SMD -0.29, 95% CI -1.18, 0.59; z = 0.65, P = 0.51).

CONCLUSION

Our meta-analysis shows that K and Kep were the most reliable parameters for differentiating PCa from noncancerous tissue and were critical for evaluation of the internal structure of cancer. The Ve value was not helpful for distinguishing PCa from noncancerous CG tissue; its ability to distinguish between PCa and noncancerous PZ tissue remains uncertain.

Dynamic contrast-enhanced MRI of the prostate: An intraindividual assessment of the effect of temporal resolution on qualitative detection and quantitative analysis of histopathologically proven prostate cancer

PURPOSE

To assess the effects of temporal resolution (R_T ) in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on qualitative tumor detection and quantitative pharmacokinetic parameters in prostate cancer.

MATERIALS AND METHODS

This retrospective Institutional Review Board (IRB)-approved study included 58 men (64 ± 7 years). They underwent 3T prostate MRI showing dominant peripheral zone (PZ) tumors (24 with Gleason ≥ 4 + 3), prior to prostatectomy. Continuously acquired DCE utilizing GRASP (Golden-angle RAdial Sparse Parallel) was retrospectively reconstructed at R_T of 1.4 sec, 3.7 sec, 6.0 sec, 9.7 sec, and 14.9 sec. A reader placed volumes-of-interest on dominant tumors and benign PZ, generating quantitative pharmacokinetic parameters (k^trans , v_e ) at each R_T . Two blinded readers assessed each R_T for lesion presence, location, conspicuity, and reader confidence on a 5-point scale. Data were assessed by mixed-model analysis of variance (ANOVA), generalized estimating equation (GEE), and receiver operating characteristic (ROC) analysis.

RESULTS

R_T did not affect sensitivity (R1_all : 69.0%-72.4%, all P_adj  = 1.000; R1_{GS≥4 + 3} : 83.3-91.7%, all P_adj  = 1.000; R2_all : 60.3-69.0%, all P_adj  = 1.000; R2_{GS≥4 + 3} : 58.3%-79.2%, all P_adj  = 1.000). R1 reported greater conspicuity of GS ≥ 4 + 3 tumors at R_T of 1.4 sec vs. 14.9 sec (4.29 ± 1.23 vs. 3.46 ± 1.44; P_adj  = 0.029). No other tumor conspicuity pairwise comparison reached significance (R1_all : 2.98-3.43, all P_adj ≥ 0.205; R2_all : 2.57-3.19, all P_adj ≥ 0.059; R1_{GS≥4 + 3} : 3.46-4.29, all other P_adj ≥ 0.156; R2_{GS≥4 + 3} : 2.92-3.71, all P_adj ≥ 0.439). There was no effect of R_T on reader confidence (R1_all : 3.17-3.34, all P_adj  = 1.000; R2_all : 2.83-3.19, all P_adj ≥ 0.801; R1_{GS≥4 + 3} : 3.79-4.21, all P_adj  = 1.000; R2_{GS≥4 + 3} : 3.13-3.79, all P_adj  = 1.000). k^trans and v_e of tumor and benign tissue did not differ across R_T (all adjusted P values [P_adj ] = 1.000). R_T did not significantly affect area under the curve (AUC) of K^trans or v_e for differentiating tumor from benign (all P_adj  = 1.000).

CONCLUSION

Current PI-RADS recommendations for R_T of 10 seconds may be sufficient, with further reduction to the stated PI-RADS preference of R_T ≤ 7 seconds offering no benefit in tumor detection or quantitative analysis.

LEVEL OF EVIDENCE

3 J. MAGN. RESON. IMAGING 2017;45:1464-1475.

Diagnostic value of integrated PET/MRI for detection and localization of prostate cancer: Comparative study of multiparametric MRI and PET/CT

PURPOSE

To evaluate the diagnostic value of integrated positron emission tomography/magnetic resonance imaging (PET/MRI) compared with conventional multiparametric MRI and PET/computed tomography (CT) for the detailed and accurate segmental detection/localization of prostate cancer.

MATERIALS AND METHODS

Thirty-one patients who underwent integrated PET/MRI using ¹⁸ F-choline and ¹⁸ F-FDG with an integrated PET/MRI scanner followed by radical prostatectomy were included. The prostate was divided into six segments (sextants) according to anatomical landmarks. Three radiologists noted the presence and location of cancer in each sextant on four different image interpretation modalities in consensus (1, multiparametric MRI; 2, integrated ¹⁸ F-FDG PET/MRI; 3, integrated ¹⁸ F-choline PET/MRI; and 4, combined interpretation of 1 and ¹⁸ F-FDG PET/CT). Sensitivity, specificity, accuracy, positive and negative predictive values, likelihood ratios, and diagnostic performance based on the DOR (diagnostic odds ratio) and NNM (number needed to misdiagnose) were evaluated for each interpretation modality, using the pathologic result as the reference standard. Detection rates of seminal vesicle invasion and extracapsular invasion were also evaluated.

RESULTS

Integrated ¹⁸ F-choline PET/MRI showed significantly higher sensitivity than did multiparametric MRI alone in high Gleason score patients (77.0% and 66.2%, P = 0.011), low Gleason score patients (66.7% and 47.4%, P = 0.007), and total patients (72.5% and 58.0%, P = 0.008) groups. Integrated ¹⁸ F-choline PET/MRI and ¹⁸ F-FDG PET/MRI showed similar sensitivity and specificity to combined interpretation of multiparametric MRI and ¹⁸ F-FDG PET/CT (for sensitivity, 58.0%, 63.4%, 72.5%, and 68.7%, respectively, and for specificity, 87.3%, 80.0%, 81.8%, 72.7%, respectively, in total patient group). However, integrated ¹⁸ F-choline PET/MRI showed the best diagnostic performance (as DOR, 11.875 in total patients, 27.941 in high Gleason score patients, 5.714 in low Gleason score groups) among the imaging modalities, regardless of Gleason score. Integrated ¹⁸ F-choline PET/MRI showed higher sensitivity and diagnostic performance than did integrated ¹⁸ F-FDG PET/MRI (as DOR, 6.917 in total patients, 15.143 in high Gleason score patients, 3.175 in low Gleason score groups) in all three patient groups.

CONCLUSION

Integrated PET/MRI carried out using a dedicated integrated PET/MRI scanner provides better sensitivity, accuracy, and diagnostic value for detection/localization of prostate cancer compared to multiparametric MRI. Generally, integrated ¹⁸ F-choline PET/MRI shows better sensitivity, accuracy, and diagnostic performance than does integrated ¹⁸ F-FDG PET/MRI as well as combined interpretation of multiparametric MRI with ¹⁸ F-FDG PET/CT.

LEVEL OF EVIDENCE

2 J. Magn. Reson. Imaging 2017;45:597-609.

Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2017;45:323-336.