Dynamic contrast-enhanced MRI of benign prostatic hyperplasia and prostatic carcinoma: correlation with angiogenesis

Can the Gleason score be predicted in patients with prostate cancer? A dynamic contrast-enhanced MRI, (68)Ga-PSMA PET/CT, PSA, and PSA-density comparison study

PURPOSE

The present study aims to evaluate whether perfusion parameters in prostate magnetic resonance imaging (MRI), (68)Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT), prostate-specific antigen (PSA), and PSA density can be used to predict the lesion grade in patients with prostate cancer (PCa).

METHODS

The study included a total of 137 PCa cases in which 12-quadrant transrectal ultrasound-guided prostate biopsy (TRUSBx) was performed, the Gleason score (GS) was determined, and pre-biopsy multiparametric prostate MRI and (68)Ga-PSMA PET/CT examinations were undertaken. The patient population was evaluated in three groups according to the GS: (1) low risk; (2) intermediate risk; (3) high risk. The PSA, PSA density, pre-TRUSBx (68)Ga-PSMA PET/CT maximum standardized uptake value (SUVmax), perfusion MRI parameters [maximum enhancement, maximum relative enhancement, T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1)] were retrospectively evaluated.

RESULTS

There was no significant difference between the three groups in relation to the PSA, PSA density, and (68)Ga-PSMA PET/CT SUVmax (P > 0.05). However, the values of maximum enhancement, maximum relative enhancement (%), T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1) significantly differed among the groups. A moderate positive correlation was found among the prostate volume, PSA (r = 0.490), and (68)Ga-PSMA SUVmax (r = 0.322) in the patients. The wash-out rate (s-1) and wash-in rate (s-1) had the best diagnostic test performance (area under the curve: 89.1% and 78.4%, respectively).

CONCLUSION

No significant correlation was found between the (68)Ga-PSMA PET/CT SUVmax and the GS. The wash-out rate was more successful in estimating the pretreatment GS than the (68)Ga-PSMA PET/CT SUVmax.

From Pixels to Pathology: Employing Computer Vision to Decode Chest Diseases in Medical Images

Radiology has been a pioneer in the healthcare industry's digital transformation, incorporating digital imaging systems like picture archiving and communication system (PACS) and teleradiology over the past thirty years. This shift has reshaped radiology services, positioning the field at a crucial junction for potential evolution into an integrated diagnostic service through artificial intelligence and machine learning. These technologies offer advanced tools for radiology's transformation. The radiology community has advanced computer-aided diagnosis (CAD) tools using machine learning techniques, notably deep learning convolutional neural networks (CNNs), for medical image pattern recognition. However, the integration of CAD tools into clinical practice has been hindered by challenges in workflow integration, unclear business models, and limited clinical benefits, despite development dating back to the 1990s. This comprehensive review focuses on detecting chest-related diseases through techniques like chest X-rays (CXRs), magnetic resonance imaging (MRI), nuclear medicine, and computed tomography (CT) scans. It examines the utilization of computer-aided programs by researchers for disease detection, addressing key areas: the role of computer-aided programs in disease detection advancement, recent developments in MRI, CXR, radioactive tracers, and CT scans for chest disease identification, research gaps for more effective development, and the incorporation of machine learning programs into diagnostic tools.

Bridging the macro to micro resolution gap with angiographic optical coherence tomography and dynamic contrast enhanced MRI

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Dynamic Contrast-Enhanced MRI of Prostate Lesions of Simultaneous [68Ga]Ga-PSMA-11 PET/MRI: Comparison between Intraprostatic Lesions and Correlation between Perfusion Parameters

We aimed to retrospectively compare the perfusion parameters measured from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of prostate benign lesions and malignant lesions to determine the relationship between perfusion parameters. DCE-MRI was performed in patients with PCa who underwent simultaneous [68Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/MRI. Six perfusion parameters (arrival time (AT), time to peak (TTP), wash-in slope (W-in), wash-out slope (W-out), peak enhancement intensity (PEI), and initial area under the 60-s curve (iAUC)), and a semi-quantitative parameter, standardized uptake values maximum (SUVmax) were calculated by placing regions of interest in the largest area of the lesions. The DCE-MRI parameters between prostate benign and malignant lesions were compared. The DCE-MRI parameters in both the benign and malignant lesions subgroup with SUVmax ≤ 3.0 and SUVmax > 3.0 were compared. The correlation of DCE-MRI parameters was investigated. Malignant lesions demonstrated significantly shorter TTP and higher SUVmax than did benign lesions. In the benign and malignant lesions subgroup, perfusion parameters of lesions with SUVmax ≤ 3.0 show no significant difference to those with SUVmax > 3.0. DCE-MRI perfusion parameters show a close correlation with each other. DCE-MRI parameters reflect the perfusion characteristics of intraprostatic lesions with malignant lesions, demonstrating significantly shorter TTP. There is a moderate to strong correlation between DCE-MRI parameters. Semi-quantitative analysis reflects that malignant lesions show a significantly higher SUVmax than benign lesions.

Ancillary imaging and clinical features for the characterization of prostate lesions: A proposed approach to reduce false positives

The relatively low specificity and positive predictive value of the Prostate Imaging-Reporting and Data System (PI-RADS) can lead to considerable false-positive results and unnecessary biopsies. The aim of this study was to propose ancillary features (AFs) indicating clinically significant prostate cancer (csPCa) or benign tissues in PI-RADS category ≥3 lesions and determine the usefulness of these AFs in reducing false-positive assessments of suspicious lesions in men at csPCa risk. This was a retrospective study, which included 199 men. A 3T, including turbo spin echo T₂ -weighted, echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced (DCE) images, was used. Five AFs (prostate-specific antigen density ≥0.15 ng/mL² ; size ≥10 mm; heterogeneous T2 signal intensity; circumscribed nodule in the junction of peripheral and transition zone; and DCE time curves) indicating csPCa or non-csPCa were evaluated by three independent readers. The sensitivity and specificity of each AF were calculated. Inter-reader agreement was evaluated using κ statistics. Univariate and multivariate logistic regression analyses were conducted to determine significant AFs. The reduction in positive call rates and csPCa detection rates with combined AF use were calculated and compared with the findings obtained with PI-RADS use alone. The sensitivities and specificities of the AFs indicating csPCa were 72.1%-96.5% and 27.4%-75.2% for reader 1, 66.3%-96.5% and 23.9%-62.0% for reader 2, and 67.4%-96.5% and 34.5%-78.8% for reader 3, with moderate to substantial inter-reader agreement (Fleiss κ, 0.551-0.643). The combined use of two or more AFs for assessing PI-RADS ≥3 lesions resulted in a 19.6%-30.7% reduction in positive calls (p < .05) compared to PI-RADS use alone while preserving the csPCa detection rates (p ≥ .06) for three readers. The use of AFs in combination with PI-RADS can reduce positive calls and false positives without csPCa under-detection.

A review of the role of MRI in diagnosis and treatment of early stage lung cancer

Despite magnetic resonance imaging (MRI) being a mainstay in the oncologic care for many disease sites, it has not routinely been used in early lung cancer diagnosis, staging, and treatment. While MRI provides improved soft tissue contrast compared to computed tomography (CT), an advantage in multiple organs, the physical properties of the lungs and mediastinum create unique challenges for lung MRI. Although multi-detector CT remains the gold standard for lung imaging, advances in MRI technology have led to its increased clinical relevance in evaluating early stage lung cancer. Even though positron emission tomography is used more frequently in this context, functional MR imaging, including diffusion-weighted MRI and dynamic contrast-enhanced MRI, are emerging as useful modalities for both diagnosis and evaluation of treatment response for lung cancer. In parallel with these advances, the development of combined MRI and linear accelerator devices (MR-linacs), has spurred the integration of MRI into radiation treatment delivery in the form of MR-guided radiotherapy (MRgRT). Despite challenges for MRgRT in early stage lung cancer radiotherapy, early data utilizing MR-linacs shows potential for the treatment of early lung cancer. In both diagnosis and treatment, MRI is a promising modality for imaging early lung cancer.

Hypoenhancing prostate cancers on dynamic contrast-enhanced MRI are associated with poor outcomes in high-risk patients: results of a hypothesis generating study

PURPOSE

To investigate the association of hypoenhancement on dynamic Contrast enhanced (DCE) with prostate cancer patient outcomes.

MATERIAL AND METHODS

This was a single-institution retrospective Institutional Review Board (IRB)-approved cohort study of 54 men who had prostate Magnetic Resonance Imaging (MRI) within 6 months of cancer diagnosis between 01/2012 to 03/2014. Two readers independently identified the dominant MRI-lesions utilizing Prostate Imaging-Reporting and Data System-version2- guidelines. These lesions were classified as hypoenhancing or hyperenhancing, compared to normal peripheral zone using quantitative DCE analysis. The t test for unequal sample sizes and the two-sample Wilcoxon rank-sum tests were used to compare groups. Logistic regression determined if DCE characteristics predict the development of metastases or prostate cancer death.

RESULTS

Time-to-progression was significantly shorter for hypoenhancing tumors (6.2 vs. 24.8 months, p = 0.05). Men with these lesions had a higher odds of having poor outcome (univariate logistic regression, odds ratio (OR) 6.79, 95% confidence interval (CI) 1.45-31.72, p = 0.02; multivariate analysis, OR 2.05, 95% CI 0.30-13.72, p = 0.47). Hypoenhancing tumors were larger (33.1 vs. 19.1 mm, p < 0.001) and more likely to be intermediate (Gleason scores 3 + 4 and 4 + 3) and high-grade (Gleason scores ≥ 4 + 4) prostate cancers (p = 0.05). Men in the hypoenhancing group had a higher mean prostate-specific antigen (PSA) value (87.6 vs. 24.8 ng/dL, p = 0.01) and PSA density (1.54 vs. 0.72, p = 0.03). The mean K_trans and k_ep of hypoenhancing lesion were lower when compared to hyperenhancing lesions (p = 0.03 and p = 0.04). V_e values did not differ (p = 0.25).

CONCLUSION

Men with hypoenhancing prostate cancers may have a worse prognosis than men with hyperenhancing tumors.

The Use of Dynamic Contrast-Enhanced Perfusion MRI in Differentiating Benign and Malignant Thyroid Nodules

To investigate the efficacy of perfusion magnetic resonance imaging (MRI) in benign-malignant differentiation of thyroid nodules. Images from 24 patients with thyroid masses were obtained using dynamic contrast enhanced MRI (DCE-MRI) at 3-T MR. DCE-MRI images were evaluated by post-processing of selected regions of interest (ROIs) on software, thus eliciting quantitative data for each voxel within the ROI. Ktrans, Ve, Kep, iAUC and chi² were calculated automatically. The DCE-MRI values of benign and malignant lesions were then compared. Mean Ktrans and iAUC values in malignant lesions were significantly lower than those in benign lesions (p = 0.028 and 0.049). Ktrans, Kep, and iAUC values in malignant lesions were statistically significantly lower than normal parenchyma values. In contrast to other tissues, the perfusion MRI findings of thyroid masses exhibit a decrease in Ktrans and iAUC values as malignancy increases. Perfusion MRI may be useful in differentiating benign and malignant thyroid nodules once a cut-off value has been determined by other studies.

Dynamic Contrast-Enhanced Imaging as a Prognostic Tool in Early Diagnosis of Prostate Cancer: Correlation with PSA and Clinical Stage

Background and Purpose

Although several methods have been developed to predict the outcome of patients with prostate cancer, early diagnosis of individual patient remains challenging. The aim of the present study was to correlate tumor perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical prognostic factors and further to explore the diagnostic value of DCE-MRI parameters in early stage prostate cancer.

Patients and Methods

Sixty-two newly diagnosed patients with histologically proven prostate adenocarcinoma were enrolled in our prospective study. Transrectal ultrasound-guided biopsy (12 cores, 6 on each lobe) was performed in each patient. Pathology was reviewed and graded according to the Gleason system. DCE-MRI was performed and analyzed using a two-compartmental model; quantitative parameters including volume transfer constant (K^trans), reflux constant (K_ep), and initial area under curve (iAUC) were calculated from the tumors and correlated with prostate-specific antigen (PSA), Gleason score, and clinical stage.

Results

K^trans (0.11 ± 0.02 min⁻¹ versus 0.16 ± 0.06 min⁻¹; p < 0.05), K_ep (0.38 ± 0.08 min⁻¹ versus 0.60 ± 0.23 min⁻¹; p < 0.01), and iAUC (14.33 ± 2.66 mmoL/L/min versus 17.40 ± 5.97 mmoL/L/min; p < 0.05) were all lower in the clinical stage T1c tumors (tumor number, n=11) than that of tumors in clinical stage T2 (n=58). Serum PSA correlated with both tumor K^trans (r=0.304, p < 0.05) and iAUC (r=0.258, p < 0.05).

Conclusions

Our study has confirmed that DCE-MRI is a promising biomarker that reflects the microcirculation of prostate cancer. DCE-MRI in combination with clinical prognostic factors may provide an effective new tool for the basis of early diagnosis and treatment decisions.

Bladder cancer diagnosis with CT urography: test characteristics and reasons for false-positive and false-negative results

PURPOSE

To determine test characteristics of CT urography for detecting bladder cancer in patients with hematuria and those undergoing surveillance, and to analyze reasons for false-positive and false-negative results.

METHODS

A HIPAA-compliant, IRB-approved retrospective review of reports from 1623 CT urograms between 10/2010 and 12/31/2013 was performed. 710 examinations for hematuria or bladder cancer history were compared to cystoscopy performed within 6 months. Reference standard was surgical pathology or 1-year minimum clinical follow-up. False-positive and false-negative examinations were reviewed to determine reasons for errors.

RESULTS

Ninety-five bladder cancers were detected. CT urography accuracy: was 91.5% (650/710), sensitivity 86.3% (82/95), specificity 92.4% (568/615), positive predictive value 63.6% (82/129), and negative predictive value was 97.8% (568/581). Of 43 false positives, the majority of interpretation errors were due to benign prostatic hyperplasia (n = 12), trabeculated bladder (n = 9), and treatment changes (n = 8). Other causes include blood clots, mistaken normal anatomy, infectious/inflammatory changes, or had no cystoscopic correlate. Of 13 false negatives, 11 were due to technique, one to a large urinary residual, one to artifact. There were no errors in perception.

CONCLUSION

CT urography is an accurate test for diagnosing bladder cancer; however, in protocols relying predominantly on excretory phase images, overall sensitivity remains insufficient to obviate cystoscopy. Awareness of bladder cancer mimics may reduce false-positive results. Improvements in CTU technique may reduce false-negative results.

The value of DCE-MRI in assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas

Background

To investigate dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas (EOCs).

Methods

7,12-dimethylbenz[A]anthracene (DMBA) was applied to induce EOCs in situ in 46 SD rats. Conventional MRI and DCE-MRI were performed to evaluate the morphology and perfusion features of the tumors, including the time-signal intensity curve (TIC), volume transfer constant (K^trans), rate constant (K_ep), extravascular extracellular space volume ratio (V_e) and initial area under the curve (IAUC). DCE-MRI parameters were correlated with histological grade, microvascular density (MVD), vascular endothelial growth factor (VEGF) and fraction of Ki67-positive cells and the serum level of cancer antigen 125 (CA125).

Results

Thirty-five of the 46 rats developed EOCs. DCE-MRI showed type III TIC more frequently than type II (29/35 vs. 6/35, p < 0.001) in EOCs. The two types of TIC of tumors had significant differences in the histological grade, MVD, expression of VEGF and Ki67, and the serum level of CA125 (all p < 0.01). K^trans, K_ep and IAUC values showed significant differences in different histological grades in overall and pairwise comparisons except for IAUC in grade 2 vs. grade 3 (all p < 0.01). There was no significant difference in V_e values among the three grade groups (p > 0.05). K^trans, K_ep and IAUC values were positively correlated with MVD, VEGF and Ki67 expression (all p < 0.01). V_e was not significantly correlated with MVD, VEGF expression, Ki67 expression and the CA125 level (all p > 0.05).

Conclusions

TIC types and perfusion parameters of DCE-MRI can reflect tumor grade, angiogenesis and cell proliferation to some extent, thereby helping treatment planning and predicting prognosis.

The value of dynamic contrast-enhanced MRI in characterizing complex ovarian tumors

BACKGROUND

The study aimed to investigate the utility of dynamic contrast enhanced MRI (DCE-MRI) in the differentiation of malignant, borderline, and benign complex ovarian tumors.

METHODS

DCE-MRI data of 102 consecutive complex ovarian tumors (benign 15, borderline 16, and malignant 71), confirmed by surgery and histopathology, were analyzed retrospectively. The patterns (I, II, and III) of time-signal intensity curve (TIC) and three semi-quantitative parameters, including enhancement amplitude (EA), maximal slope (MS), and time of half rising (THR), were evaluated and compared among benign, borderline, and malignant ovarian tumors. The types of TIC were compared by Pearson Chi-square χ ² between malignant and benign, borderline tumors. The mean values of EA, MS, and THR were compared using one-way ANOVA or nonparametric Kruskal-Wallis test.

RESULTS

Fifty-nine of 71 (83%) malignant tumors showed a type-III TIC; 9 of 16 (56%) borderline tumors showed a type-II TIC, and 10 of 15 (67%) benign tumors showed a type-II TIC, with a statistically significant difference between malignant and benign tumors (P < 0.001) and between malignant and borderline tumors (P < 0.001). MS was significantly higher in malignant tumors than in benign tumors and in borderline than in benign tumors (P < 0.001, P = 0.013, respectively). THR was significantly lower in malignant tumors than in benign tumors and in borderline than in benign tumors (P < 0.001, P = 0.007, respectively). There was no statistically significant difference between malignant and borderline tumors in MS and THR (P = 0.19, 0.153) or among malignant, borderline, and benign tumors in EA (all P > 0.05).

CONCLUSIONS

DCE-MRI is helpful for characterizing complex ovarian tumors; however, semi-quantitative parameters perform poorly when distinguishing malignant from borderline tumors.

Prostate MR Imaging: An Update

Improvements in prostate MR imaging techniques and the introduction of MR imaging-targeted biopsies have had central roles in prostate cancer (PCa) management. The role of MR imaging has progressed from largely staging patients with biopsy-proven PCa to detecting, characterizing, and guiding the biopsy of suspected PCa. These diagnostic advances, combined with improved therapeutic interventions, have led to a more sophisticated and individually tailored approach to patients' unique PCa profile. This review discusses the MR imaging, a standardized reporting scheme, and the role of fusion-targeted prostate biopsy.

Review of Prostate Imaging Reporting and Data System version 2

Prostate MRI has been a hot topic in recent years in large part due to the high incidence of prostate cancer worldwide. Advances in technology have allowed multiparametric MRI to improve lesion detection and characterization in prostate imaging. Additionally, prostate MRI has shown great promise in the detection of clinically significant cancer. In 2012, the European Society of Urogenital Radiology established clinical guidelines for multiparametric MRI of the prostate to facilitate a greater level of standardization and consistency, which became known as the Prostate Imaging Reporting and Data System (PI-RADS). Subsequently, the American College of Radiology, European Society of Urogenital Radiology and the AdMeTech Foundation jointly created PI-RADS version 2. This article focuses on summarizing the key points of PI-RADS version 2.

Are Dynamic Contrast-Enhanced Images Necessary for Prostate Cancer Detection on Multiparametric Magnetic Resonance Imaging?

BACKGROUND

To compare the results of magnetic resonance imaging (MRI) with and without contrast-enhanced sequences for the detection of clinically significant prostate cancer. The value of contrast in the MRI protocol for the detection of prostate tumors has been discussed in previous studies.

MATERIALS AND METHODS

We performed an institutional review board-approved, retrospective study of patients who had undergone prostate MRI followed by fusion biopsy during a 16-month period. The patients had undergone MRI on a 3-Tesla scanner with a phased-array coil using a routine multiparametric protocol: T2-weighted, diffusion, and dynamic postcontrast enhancement sequences. The examination films were read independently by 2 readers in 2 sessions: first without contrast-enhanced images and second with contrast-enhanced images. The images were graded according to the suspicion of clinically significant prostate cancer (scale, 1-5). The kappa coefficient was used to compare the readings with and without contrast. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for both readers were calculated using the biopsy findings as a reference standard. The level for statistical significance was set at P < .05.

RESULTS

A total of 118 patients were included, and clinically significant prostate cancer was found in 48 patients (40.7%). The MRI findings on both contrast-enhanced and noncontrast-enhanced images had no statistically significant differences for either reader (P > .05 for all levels of suspicion). The sensitivity ranged from 68.3% to 80.7%, specificity from 57.1% to 77.1%, positive predictive value from 29.9% to 38.8%, negative predictive value from 88.0% to 91.3%, and accuracy from 60.6% to 73.0%.

CONCLUSION

Our results show that contrast-enhanced sequences provide minimal or no increased value for the detection of clinically significant prostate cancer.

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.

Benign Conditions That Mimic Prostate Carcinoma: MR Imaging Features with Histopathologic Correlation

Multiparametric magnetic resonance (MR) imaging combines anatomic and functional imaging techniques for evaluating the prostate and is increasingly being used in diagnosis and management of prostate cancer. A wide spectrum of anatomic and pathologic processes in the prostate may masquerade as prostate cancer, complicating the imaging interpretation. The histopathologic and imaging findings of these potential mimics are reviewed. These entities include the anterior fibromuscular stroma, surgical capsule, central zone, periprostatic vein, periprostatic lymph nodes, benign prostatic hyperplasia (BPH), atrophy, necrosis, calcification, hemorrhage, and prostatitis. An understanding of the prostate zonal anatomy is helpful in distinguishing the anatomic entities from prostate cancer. The anterior fibromuscular stroma, surgical capsule, and central zone are characteristic anatomic features of the prostate with associated low T2 signal intensity due to dense fibromuscular tissue or complex crowded glandular tissue. BPH, atrophy, necrosis, calcification, and hemorrhage all have characteristic features with one or more individual multiparametric MR imaging modalities. Prostatitis constitutes a heterogeneous group of infective and inflammatory conditions including acute and chronic bacterial prostatitis, infective and noninfective granulomatous prostatitis, and malacoplakia. These entities are associated with variable clinical manifestations and are characterized by the histologic hallmark of marked inflammatory cellular infiltration. In some cases, these entities are indistinguishable from prostate cancer at multiparametric MR imaging and may even exhibit extraprostatic extension and lymphadenopathy, mimicking locally advanced prostate cancer. It is important for the radiologists interpreting prostate MR images to be aware of these pitfalls for accurate interpretation. Online supplemental material is available for this article.

PI-RADS version 2: what you need to know

Prostate cancer is the second most prevalent cancer in men worldwide and its incidence is expected to double by 2030. Multi-parametric magnetic resonance imaging (MRI) incorporating anatomical and functional imaging has now been validated as a means of detecting and characterising prostate tumours and can aid in risk stratification and treatment selection. The European Society of Urogenital Radiology (ESUR) in 2012 established the Prostate Imaging-Reporting and Data System (PI-RADS) guidelines aimed at standardising the acquisition, interpretation and reporting of prostate MRI. Subsequent experience and technical developments have highlighted some limitations, and a joint steering committee formed by the American College of Radiology, ESUR, and the AdMeTech Foundation have recently announced an updated version of the proposals. We summarise the main proposals of PI-RADS version 2, explore the evidence behind the recommendations, and highlight key differences for the benefit of those already familiar with the original.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Contribution of Histopathologic Tissue Composition to Quantitative MR Spectroscopy and Diffusion-weighted Imaging of the Prostate

PURPOSE

To determine associations of metabolite levels derived from magnetic resonance (MR) spectroscopic imaging (ie, hydrogen 1 [(1)H] MR spectroscopic imaging) and apparent diffusion coefficients (ADCs) from diffusion-weighted imaging with prostate tissue composition assessed by digital image analysis of histologic sections.

MATERIALS AND METHODS

Institutional ethical review board approved this retrospective study and waived informed consent. Fifty-seven prostate cancer patients underwent an MR examination followed by prostatectomy. One hematoxylin and eosin-stained section of the resected prostate per patient was digitized and computationally segmented into nuclei, lumen, and combination of epithelial cytoplasm and stroma. On each stained section, regions of interest (ROIs) were chosen and matched to the corresponding ADC map and (1)H MR spectroscopic imaging voxels. ADC and two metabolite ratios (citrate [Cit], spermine [Spm], and creatine [Cr] to choline [Cho] and Cho to Cr plus Spm) were correlated with percentage areas of nuclei, lumen, and cytoplasm and stroma for peripheral zone (PZ), transition zone (TZ), and tumor tissue in both zones of the prostate by using a linear mixed-effect model and Spearman correlation coefficient (ρ).

RESULTS

ADC and (Cit + Spm + Cr)/Cho ratio showed positive correlation with percentage area of lumen (ρ = 0.43 and 0.50, respectively) and negative correlation with percentage area of nuclei (ρ = -0.29 and -0.26, respectively). The Cho/(Cr + Spm) ratio showed negative association with percentage area of lumen (ρ = -0.40) and positive association with area of nuclei (ρ = 0.26). Percentage areas of lumen and nuclei, (Cit + Spm + Cr)/Cho ratio, and ADC were significantly different (P < .001) between benign PZ (23.7 and 7.7, 8.83, and 1.58 × 10(-3) mm(2)/sec, respectively) and tumor PZ tissue (11.4 and 12.5, 5.13, and 1.20 × 10(-3) mm(2)/sec, respectively). These parameters were also significantly different between benign TZ (20.0 and 8.2, 6.50, and 1.26 × 10(-3) mm(2)/sec, respectively) and tumor TZ tissue (9.8 and 11.2, 4.36, and 1.03 × 10(-3) mm(2)/sec, respectively).

CONCLUSION

The observed correlation of (Cit + Spm + Cr)/Cho ratio and ADC of the prostate with its tissue composition indicates that components of this composition, such as percentage luminal area, contribute to the value of these MR parameters.

Comparison of Glioblastomas and Brain Metastases using Dynamic Contrast-Enhanced Perfusion MRI

PURPOSE

To compare glioblastoma and brain metastases using T1-weighted dynamic contrast-enhanced (DCE)-MRI perfusion technique.

METHODS

26 patients with glioblastoma and 32 patients with metastatic brain lesions with no treatment who underwent DCE-MRI were, retrospectively, analyzed. DCE perfusion parameters K(trans) and Vp were calculated for the whole tumor. Signal intensity time curves were quantified by calculating the area under the curve (AUC) and the logarithmic slope of the washout phase to explore the heterogeneous tumor characteristics.

RESULTS

Glioblastoma did not differ from all brain metastases in K(trans) (P = .34) or Vp (P = .47). Glioblastoma and melanoma metastases differed from hypovascular metastases in AUC and log slope of the washout phase of the signal intensity time curve (P < .05); however, glioblastoma and melanoma metastases did not differ from each other (AUC: P = .78, Log slope: P = .77). Glioblastoma and melanoma metastases differed from hypovascular metastases in the ratio of Voxelneg /Voxelpos (P< .03); however, they did not differ from each other. Glioblastoma and melanoma metastases differed from each other in Voxelneg_threshold at higher negative log slope threshold.

CONCLUSION

DCE-MRI showed that it has a potential to differentiate glioblastomas, melanoma metastases and hypovascular brain tumors. Logarithmic slope of the washout phase and AUC of the signal intensity time curve were shown to be the best discriminator between hypervascular and hypovascular neoplasms.

The role of pathology correlation approach in prostate cancer index lesion detection and quantitative analysis with multiparametric MRI

Rationale and Objectives

Development of imaging biomarkers often relies on their correlation with histopathology. Our aim was to compare two approaches for correlating pathology to multiparametric magnetic resonance (MR) imaging (mpMRI) for localization and quantitative assessment of prostate cancer (PCa) index tumor using whole mount (WM) pathology (WMP) as the reference.

Materials and Methods

Patients (N = 30) underwent mpMRI that included diffusion-weighted imaging and dynamic contrast-enhanced (DCE) MRI at 3 T before radical prostatectomy (RP). RP specimens were processed using WM technique (WMP) and findings summarized in a standard surgical pathology report (SPR). Histology index tumor volumes (HTVs) were compared to MR tumor volumes (MRTVs) using two approaches for index lesion identification on mpMRI using annotated WMP slides as the reference (WMP) and using routine SPR as the reference. Consistency of index tumor localization, tumor volume, and mean values of the derived quantitative parameters (mean apparent diffusion coefficient [ADC], K^trans, and v_e) were compared.

Results

Index lesions from 16 of 30 patients met the selection criteria. There was WMP/SRP agreement in index tumor in 13 of 16 patients. ADC-based MRTVs were larger (P < .05) than DCE-based MRTVs. ADC MRTVs were smaller than HTV (P < .005). There was a strong correlation between HTV and MRTV (Pearson r > 0.8; P < .05). No significant differences were observed in the mean values of K^trans and ADC between the WMP and SPR.

Conclusions

WMP correlation is superior to SPR for accurate localization of all index lesions. The use of WMP is however not required to distinguish significant differences of mean values of quantitative MRI parameters within tumor volume.

A comparison of arterial spin labeling perfusion MRI and DCE-MRI in human prostate cancer

Perfusion MRI has the potential to provide pathophysiological biomarkers for the evaluating, staging and therapy monitoring of prostate cancer. The objective of this study was to explore the feasibility of noninvasive arterial spin labeling (ASL) to detect prostate cancer in the peripheral zone and to investigate the correlation between the blood flow (BF) measured by ASL and the pharmacokinetic parameters K(trans) (forward volume transfer constant), kep (reverse reflux rate constant between extracellular space and plasma) and ve (the fractional volume of extracellular space per unit volume of tissue) measured by dynamic contrast-enhanced (DCE) MRI in patients with prostate cancer. Forty-three consecutive patients (ages ranging from 49 to 86 years, with a median age of 74 years) with pathologically confirmed prostate cancer were recruited. An ASL scan with four different inversion times (TI = 1000, 1200, 1400 and 1600 ms) and a DCE-MRI scan were performed on a clinical 3.0 T GE scanner. BF, K(trans), kep and ve maps were calculated. In order to determine whether the BF values in the cancerous area were statistically different from those in the noncancerous area, an independent t-test was performed. Spearman's bivariate correlation was used to assess the relationship between BF and the pharmacokinetic parameters K(trans), kep and ve. The mean BF values in the cancerous areas (97.1 ± 30.7, 114.7 ± 28.7, 102.3 ± 22.5, 91.2 ± 24.2 ml/100 g/min, respectively, for TI = 1000, 1200, 1400, 1600 ms) were significantly higher (p < 0.01 for all cases) than those in the noncancerous regions (35.8 ± 12.5, 42.2 ± 13.7, 53.5 ± 19.1, 48.5 ± 13.5 ml/100 g/min, respectively). Significant positive correlations (p < 0.01 for all cases) between BF and the pharmacokinetic parameters K(trans), kep and ve were also observed for all four TI values (r = 0.671, 0.407, 0.666 for TI = 1000 ms; 0.713, 0.424, 0.698 for TI = 1200 ms; 0.604, 0.402, 0.595 for TI = 1400 ms; 0.605, 0.422, 0.548 for TI = 1600 ms). It can be seen that the quantitative ASL measurements show significant differences between cancerous and benign tissues, and exhibit strong to moderate correlations with the parameters obtained using DCE-MRI. These results show the promise of ASL as a noninvasive alternative to DCE-MRI.

Clinical application of contrast enhanced ultrasound to diagnose benign prostatic hyperplasia

Abstract

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4852383312229155

Potential of hybrid ¹⁸F-fluorocholine PET/MRI for prostate cancer imaging

PURPOSE

To report the first results of hybrid (18)F-fluorocholine PET/MRI imaging for the detection of prostate cancer.

METHODS

This analysis included 26 consecutive patients scheduled for prostate PET/MRI before radical prostatectomy. The examinations were performed on a hybrid whole-body PET/MRI scanner. The MR acquisitions which included T2-weighted, diffusion-weighted and dynamic contrast-enhanced sequences were followed during the same session by whole-body PET scans. Parametric maps were constructed to measure normalized T2-weighted intensity (nT2), apparent diffusion coefficient (ADC), volume transfer constant (K (trans)), extravascular extracellular volume fraction (v e) and standardized uptake values (SUV). With pathology as the gold standard, ROC curves were calculated using logistic regression for each parameter and for the best combination with and without PET to obtain a MR model versus a PETMR model.

RESULTS

Of the 26 patients initially selected, 3 were excluded due to absence of an endorectal coil (2 patients) or prosthesis artefacts (1 patient). In the whole prostate, the area under the curve (AUC) for SUVmax, ADC, nT2, K (trans) and v e were 0.762, 0.756, 0.685, 0.611 and 0.529 with a best threshold at 3.044 for SUVmax and 1.075 × 10(-3) mm(2)/s for ADC. The anatomical distinction between the transition zone and the peripheral zone showed the potential of the adjunctive use of PET. In the peripheral zone, the AUC of 0.893 for the PETMR model was significantly greater (p = 0.0402) than the AUC of 0.84 for the MR model only. In the whole prostate, no relevant correlation was observed between ADC and SUVmax. The SUVmax was not affected by the Gleason score.

CONCLUSION

The performance of a hybrid whole-body (18)F-fluorocholine PET/MRI scan in the same session combined with a prostatic MR examination did not interfere with the diagnostic accuracy of the MR sequences. The registration of the PET data and the T2 anatomical MR sequence data allowed precise localization of hypermetabolic foci in the prostate. While in the transition zone the adenomatous hyperplasia interfered with cancer detection by PET, the quantitative analysis tool performed well for cancer detection in the peripheral zone.

Qianliening capsule inhibits benign prostatic hyperplasia angiogenesis via the HIF-1α signaling pathway

Angiogenesis plays an important role in the progression and development of benign prostatic hyperplasia (BPH), and has become a promising target for BPH treatment. The hypoxia-inducible factor-1α (HIF-1α) signaling pathway promotes the process of angiogenesis, contributing to the growth and progression of a number of hyperplasia diseases, including BPH. Qianliening capsule (QC) is a traditional Chinese formula that has been used clinically in China to treat BPH for a number of years. Recently, QC was demonstrated to inhibit prostatic cell growth and induce apoptosis in vivo and in vitro via regulating the epidermal growth factor/signal transducer and activator of transcription 3 signaling pathway and mitochondrion-dependent apoptosis pathway. However, the mechanisms underlying the anti-BPH effect remain largely unknown. To further elucidate the mechanism of QC activity in BPH treatment, a rat BPH model established by injecting testosterone following castration was established and the effect of QC on prostatic tissue angiogenesis was evaluated, as well as the underlying molecular mechanisms. QC was shown to reduce the prostatic index in BPH rats, but without affecting the body weight, demonstrating that QC is effective in the treatment of BPH and without apparent toxicity. In addition, QC treatment significantly reduced the intraprostatic microvessel density, indicating antiangiogenesis activity in vivo. In addition, treatment with QC inhibited the expression of HIF-1α in BPH rats, as well as the expression of vascular endothelial growth factor and basic fibroblast growth factor. Therefore, for the first time, the present study hypothesized that QC inhibits angiogenesis in prostatic tissue of BPH rats via the inhibition of the HIF-1α signaling pathway, which may be one of the mechanisms in which QC treats BPH.

Multidimensional MR spectroscopic imaging of prostate cancer in vivo

Prostate cancer (PCa) is the second most common type of cancer among men in the United States. A major limitation in the management of PCa is an inability to distinguish, early on, cancers that will progress and become life threatening. One-dimensional (1D) proton ((1)H) MRS of the prostate provides metabolic information such as levels of choline (Ch), creatine (Cr), citrate (Cit), and spermine (Spm) that can be used to detect and diagnose PCa. Ex vivo high-resolution magic angle spinning (HR-MAS) of PCa specimens has revealed detection of more metabolites such as myo-inositol (mI), glutamate (Glu), and glutamine (Gln). Due to the J-modulation and signal overlap, it is difficult to quantitate Spm and other resonances in the prostate clearly by single- and multivoxel-based 1D MR spectroscopy. This limitation can be minimized by adding at least one more spectral dimension by which resonances can be spread apart, thereby increasing the spectral dispersion. However, recording of multivoxel-based two-dimensional (2D) MRS such as J-resolved spectroscopy (JPRESS) and correlated spectroscopy (L-COSY) combined with 2D or three-dimensional (3D) magnetic resonance spectroscopic imaging (MRSI) using conventional phase-encoding can be prohibitively long to be included in a clinical protocol. To reduce the long acquisition time required for spatial encoding, the echo-planar spectroscopic imaging (EPSI) technique has been combined with correlated spectroscopy to give four-dimensional (4D) echo-planar correlated spectroscopic imaging (EP-COSI) as well as J-resolved spectroscopic imaging (EP-JRESI) and the multi-echo (ME) variants. Further acceleration can be achieved using non-uniform undersampling (NUS) and reconstruction using compressed sensing (CS). Earlier versions of 2D MRS, theory of 2D MRS, spectral apodization filters, newer developments and the potential role of multidimensional MRS in PCa detection and management will be reviewed here.

Practical dynamic contrast enhanced MRI in small animal models of cancer: data acquisition, data analysis, and interpretation

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) consists of the continuous acquisition of images before, during, and after the injection of a contrast agent. DCE-MRI allows for noninvasive evaluation of tumor parameters related to vascular perfusion and permeability and tissue volume fractions, and is frequently employed in both preclinical and clinical investigations. However, the experimental and analytical subtleties of the technique are not frequently discussed in the literature, nor are its relationships to other commonly used quantitative imaging techniques. This review aims to provide practical information on the development, implementation, and validation of a DCE-MRI study in the context of a preclinical study (though we do frequently refer to clinical studies that are related to these topics).

Impact of delay after biopsy and post-biopsy haemorrhage on prostate cancer tumour detection using multi-parametric MRI: a multi-reader study

AIM

To assess impact of haemorrhage and delay after biopsy on prostate tumour detection using multi-parametric (MP) magnetic resonance imaging (MRI) assessment.

MATERIALS AND METHODS

Forty-four patients underwent prostate MRI at 1.5 T using a pelvic phased-array coil, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging, before prostatectomy. Three radiologists independently reviewed images during four sessions [T2WI, DWI, DCE, and all parameters combined (MP-MRI)] to assess for tumour in each sextant. In a separate session, readers reviewed T1WI to score the extent of haemorrhage per sextant. Accuracy was assessed using logistic regression for correlated data.

RESULTS

There was no significant difference in accuracy between readers for any session (p ≥ 0.166), and results were averaged across the three readers for remaining comparisons. Accuracy was significantly greater for MP-MRI than for any parameter alone (p ≤ 0.020). For T2WI alone, there was a trend toward decreased sensitivity in sextants with extensive haemorrhage (p = 0.072). However, accuracy, sensitivity, and specificity were otherwise similar for sextants with and without extensive haemorrhage for all sessions (p = 0.192-0.934). No session showed a significant improvement in accuracy, sensitivity, or specificity in cases with delay after biopsy of over 4 weeks compared with shorter delay.

CONCLUSION

Extensive haemorrhage and short delay after biopsy did not negatively impact accuracy for tumour detection using MP-MRI. Further studies using MP-MRI protocols and interpretation schemes from other institutions are required to confirm these observations.

Prostate cancer foci detected on multiparametric magnetic resonance imaging are histologically distinct from those not detected

PURPOSE

We identified histological differences between prostate cancer foci that are detected and missed using multiparametric magnetic resonance imaging.

MATERIALS AND METHODS

A total of 49 patients who underwent multiparametric magnetic resonance imaging, including T2-weighted imaging, including diffusion weighted imaging and dynamic contrast enhanced imaging, before prostatectomy were enrolled in the study. One radiologist identified areas highly suspicious for tumor. One pathologist identified and categorized tumors in terms of size, Gleason score, solid tumor growth, intermixed benign glands, loose stroma, desmoplastic stroma and a high malignant epithelium-to-stroma ratio. Differences between detected and missed tumors were assessed using logistic regression analyses based on generalized estimating equations for correlated data.

RESULTS

All histological features showed significant differences between detected and missed tumors on multiparametric magnetic resonance imaging (p<0.0001). Independent predictors of detection on multivariate analysis were size (OR 5.38, p=0.0077), Gleason score (OR 5.12, p=0.0094) and solid growth (OR 17.83, p<0.0001). Size, Gleason score and loose stroma were significant predictors of identification with diffusion weighted imaging on univariate analysis (p≤0.0245), while Gleason score (OR 17.05, p=0.0212) and solid growth (OR 34.90, p=0.0103) were independent predictors of identification with diffusion weighted imaging on multivariate analysis. Identification with T2-weighted imaging was associated with size and Gleason score (p≤0.01876). Identification with dynamic contrast enhanced imaging was associated with intermixed benign epithelium, loose stroma and a high malignant epithelium-to-stroma ratio (p≤0.0499). No combination of features served as independent predictors on multivariate analysis for T2-weighted imaging or dynamic contrast enhanced imaging.

CONCLUSIONS

There are fundamental histological differences between detected and missed prostate tumors using magnetic resonance imaging. Insights into these differences may facilitate the prospective role of magnetic resonance imaging in counseling and treatment selection for patients with prostate cancer.

Usefulness of prebiopsy multifunctional and morphologic MRI combined with free-to-total prostate-specific antigen ratio in the detection of prostate cancer

OBJECTIVE

The purpose of the study was to assess the predictive value for prostate cancer of MRI using morphologic (T2-weighted imaging [T2WI]) and functional (MR spectroscopy [MRS], diffusion-weighted imaging [DWI], and dynamic contrast-enhanced [DCE] MRI) sequences and the free-to-total prostate-specific antigen (PSA) ratio, alone and combined.

MATERIALS AND METHODS

This retrospective study included 70 patients (PSA level, > 4 ng/mL; free-to-total PSA ratio, < 20%) who underwent endorectal 1.5-T MRI before biopsy. We graded the likelihood of cancer on a 5-point scale. Imaging data were compared with histologic results on biopsy or prostatectomy. Accuracies were estimated from the area under receiver operating characteristic using the hemiprostate as the unit of analysis. A p value less than 0.05 denoted statistical significance.

RESULTS

The model combining all variables was more accurate than each variable alone (95.2% vs 73.5% for T2WI, 76.0% for MRS, 81.8% for DWI, 75.6% for DCE-MRI, and 78.8% for free-to-total PSA ratio). The complete model had accuracy similar to that of combining two imaging variables with free-to-total PSA ratio, especially free-to-total PSA ratio, T2WI, and DWI (94.0%); and free-to-total PSA ratio, DWI, and MRS (93.8%); with negative predictive values of 91.0% and 89.5%, respectively. The best models combining two imaging variables (MRS and DWI, 85.8%; T2WI and DWI, 84.8%) had accuracy that was similar to that of the combination of all imaging variables (87.3%) and higher than that of the best individual imaging variable (DWI, 81.8%), but lower than that of the complete model.

CONCLUSION

The combination of at least one functional technique with free-to-total PSA ratio is more accurate than combining only imaging variables in cancer detection. The use of more than two imaging variables does not increase the detection rate. Functional MRI has the potential to help avoid a large number of negative biopsies.

A Bayesian hierarchical model for DCE-MRI to evaluate treatment response in a phase II study in advanced squamous cell carcinoma of the head and neck

OBJECT

Pharmacokinetic parameters from dynamic contrast-enhanced MRI (DCE-MRI) were used to assess the perfusion effects due to treatment response using a tyrosine kinase inhibitor. A Bayesian hierarchical model (BHM) is proposed, as an alternative to voxel-wise estimation procedures, to test for a treatment effect while explicitly modeling known sources of variability.

MATERIALS AND METHODS

Nine subjects from a randomized, blinded, placebo-controlled, multicenter, phase II study of lapatinib were examined before and after treatment. Kinetic parameters were estimated, with an extended compartmental model and subject-specific arterial input function, on a voxel-by-voxel basis.

RESULTS

The group treated with lapatinib had a decrease in median K(trans) of 0.17 min⁻¹, when averaged across all voxels in the tumor ROIs, compared with no change in the placebo group based on nonlinear regression. A hypothesis test of equality between pre- and posttreatment K (trans) could not be rejected against a one-sided alternative (P = 0.09). Equality between median K(trans) in placebo and lapatinib groups posttreatment could also not be rejected using the BHM (P = 0.32). Across all scans acquired in the study, estimates of K(trans) at one site were greater on average than those at the other site by including a site effect in the BHM. The inter-voxel variability is of similar order (within 15%) when compared to the inter-patient variability.

CONCLUSION

Though the study contained a small number of subjects and no significant difference was found, the Bayesian hierarchical model provided estimates of variability from known sources in the study and confidence intervals for all estimated parameters. We believe the BHM provides a straightforward and thorough interrogation of the imaging data at the level of voxels, patients or sites in this multicenter clinical study.

Multi-parametric MR imaging of transition zone prostate cancer: Imaging features, detection and staging

Magnetic resonance (MR) imaging has been increasingly used in the evaluation of prostate cancer. As studies have suggested that the majority of cancers arise from the peripheral zone (PZ), MR imaging has focused on the PZ of the prostate gland thus far. However, a considerable number of cancers (up to 30%) originate in the transition zone (TZ), substantially contributing to morbidity and mortality. Therefore, research is needed on the TZ of the prostate gland. Recently, MR imaging and advanced MR techniques have been gaining acceptance in evaluation of the TZ. In this article, the MR imaging features of TZ prostate cancers, the role of MR imaging in TZ cancer detection and staging, and recent advanced MR techniques will be discussed in light of the literature.

Prostate tissue composition and MR measurements: investigating the relationships between ADC, T2, K(trans), v(e), and corresponding histologic features

PURPOSE

To investigate relationships between magnetic resonance (MR) imaging measurements and the underlying composition of normal and malignant prostate tissue.

MATERIALS AND METHODS

Twenty-four patients (median age, 63 years; age range, 44-72 years) gave informed consent to be examined for this research ethics board-approved study. Before undergoing prostatectomy, patients were examined with T2-weighted, diffusion-weighted, T2 mapping, and dynamic contrast material-enhanced MR imaging at 1.5 T. Maps of apparent diffusion coefficient (ADC), T2, volume transfer constant (K(trans)), and extravascular extracellular space (v(e)) were calculated. Whole-mount hematoxylin-eosin-stained sections were generated and digitized at histologic resolution. Percentage areas of tissue components (nuclei, cytoplasm, stroma, luminal space) were measured by using image segmentation. Corresponding regions on MR images and histologic specimens were defined by using anatomically defined segments in peripheral zone (PZ) and central gland tissue. Cancer and normal PZ regions were identified at histopathologic analysis. Each MR parameter-histologic tissue component pair was assessed by using linear mixed-effects models, and cancer versus normal PZ values were compared by using nonparametric tests.

RESULTS

ADC and T2 were inversely related to percentage area of nuclei and percentage area of cytoplasm and positively related to percentage area of luminal space (P < or = .01). These trends were reversed for K(trans) (P < .001). K(trans) had a significantly negative (P = .01) slope versus percentage area of stroma, and v(e) had a positive (P = .008) slope versus percentage area of stroma. The v(e) was inversely proportional to the percentage area of nuclei (P = .05). All MR imaging parameters (P < or = .05) and the percentage areas of all tissue components (P < or = .001) except stroma (P > .48) were significantly different between cancer and normal PZ tissue.

CONCLUSION

MR imaging-derived parameters measured in the prostate were significantly related to the proportion of specific histologic components that differ between normal and malignant PZ tissue. These relationships may help define imaging-related histologic prognostic parameters for prostate cancer.

Advances in imaging diagnosis of pancreatic cancer

Early diagnosis of pancreatic carcinoma is very important for effective management of the disease. The imaging techniques traditionally used for diagnosis of pancreatic carcinoma include computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound imaging. In recent years, some new imaging techniques, such as Positron emission tomography (PET)-CT fusion and magnetic resonance spectroscopy (MRS), have been developed. These new imaging techniques play a crucial role in the early diagnosis of pancreatic carcinoma.