Literature DB >> 28157066

Multiparametric MRI in detection and staging of prostate cancer.

Lars Boesen1.   

Abstract

BACKGROUND: Prostate cancer (PCa) is the second leading cause of cancer-related mortality and the most frequently diagnosed male malignant disease among men in the Nordic countries. The manifestation of PCa ranges from indolent to highly aggressive disease and due to this high variation in PCa progression, the diagnosis and subsequent treatment planning can be challenging. The current diagnostic approach with PSA testing and digital rectal examination followed by transrectal ultrasound biopsies (TRUS-bx) lack in both sensitivity and specificity in PCa detection and offers limited information about the aggressiveness and stage of the cancer. Scientific work supports the rapidly growing use of multiparametric magnetic resonance imaging (mp-MRI) as the most sensitive and specific imaging tool for detection, lesion characterisation and staging of PCa. However, the experience with mp-MRI in PCa management in Denmark has been very limited. Therefore, we carried out this PhD project based on three original studies to evaluate the use of mp-MRI in detection, assessment of biological aggression and staging of PCa in a Danish setup with limited experience in mp-MRI prostate diagnostics. The aim was to assess whether mp-MRI could 1) improve the overall detection rate of clinically significant PCa previously missed by TRUS-bx, 2) identify patients with extracapsular tumour extension and 3) categorize the histopathological aggressiveness based on diffusion-weighted imaging.
MATERIAL AND METHODS: Study I included patients with a history of negative TRUS-bx and persistent suspicion of PCa scheduled for repeated biopsies. Mp-MRI was performed prior to the biopsies and analysed for suspicious lesions. All lesions were scored according to the PIRADS classification from the European Society of Urogenital Radiology's (ESUR) MR prostate guidelines. The lesions were given a sum of scores (ranging 3-15) and classified overall on a Likert five-point scale according to the probability of clinically significant malignancy being present. All patients underwent systematic TRUS-bx (ten cores) and visual mp-MRI-targeted biopsies (mp-MRI-bx) under TRUS-guidance of any mp-MRI-suspicious lesion not hit on systematic TRUS-bx. Study II included patients with clinically localised PCa (cT1-T2) determined by digital rectal examination and/or TRUS and scheduled for radical prostatectomy (RP). Mp-MRI was performed prior to RP, and all lesions were evaluated according to the PIRADS classification and the extracapsular extension (ECE) risk scoring from the ESUR MR prostate guidelines. The images were evaluated by two readers with different experience in mp-MRI interpretation. An mp-MRI T-stage (cTMRI) and an ECE risk score were assigned. Additionally, suspicion of ECE was dichotomised into either organ-confined disease or ECE based on tumour characteristics and personal opinion incorporating functional imaging findings. The RP histopathological results served as standard reference. Study III included patients from study II, where mean ADCtumour values from all malignant tumour foci ≥ 5 mm identified on histopathology were measured on the corresponding diffusion-weighted imaging ADCmap. An ADCbenign value was obtained from a non-cancerous area using the histopathological map as a reference to calculate the ADCratio (ADCtumour divided by ADCbenign). The ADC measurements (ADCtumour and ADCratio values) were correlated with the Gleason score (GS) from each tumour foci.
RESULTS: Eighty-three patients were included in study I. PCa was found in 39/83 (47%) and both the PIRADS summation score and the over-all Likert classification showed a high correlation with biopsy results (p < 0.0001). Five patients (13%) had PCa detected only on mp-MRI-bx outside the systematic biopsy areas (p = 0.025) and another 7 patients (21%) had an overall GS upgrade of at least one grade (p = 0.037) based on the mp-MRI-bx. Clinical significant PCa was found in 37/39 patients according to the Epstein criteria (2004). Eighty-seven patients were included in study II and underwent mp-MRI before RP. The correlation between cTMRI and pT showed a spearman rho correlation of 0.658 (p < 0.001) and 0.306 (p = 0.004) with a weighted kappa of 0.585 [CI 0.44;0.73] and 0.22 [CI 0.09;0.35] for reader A and reader B, respectively. The prevalence of ECE after RP was 31/87 (36%). ECE risk scoring showed an AUC of 0.65-0.86 on the ROC-curve for readers and a sensitivity, specificity and diagnostic accuracy of 81% (CI 63;93),78% (CI 66;88) and 79% at the best cut-off level (risk score ≥ 4) for the most experienced reader. When tumour characteristics were influenced by personal opinion and functional imaging, the sensitivity, specificity and diagnostic accuracy for prediction of ECE changed to 74% (CI 55;88), 88% (CI 76;95) and 83% for reader A and 61% (CI 0.42;0.78), 77% (CI 0.64;0.87) and 71% for reader B, respectively. Seventy-one patients were included in study III. The association between ADC measurements and GS showed a significantly negative correlation (p < 0.001) with spearman rho for ADCtumour (-0.421) and ADCratio (-0.649), respectively. There was a statistical significant difference between both ADC measurements and the GS groups for all tumours (p < 0.001). ROC-curve analysis showed an overall AUC of 0.73 (ADCtumour) to 0.80 (ADCratio) in discriminating GS 6 from GS ≥ 7 (3+4) tumours. The AUC remained virtually unchanged at 0.72 (ADCtumour), but increased to 0.90 (ADCratio) when discriminating GS ≤ 7 (3+4) from GS ≥ 7 (4+3).
CONCLUSION: Mp-MRI prior to repeated biopsies can improve the detection rate of clinically significant PCa and allow for a more accurate GS by combining standard TRUS-bx with mp-MRI-targeted biopsies under visual TRUS-guidance. Mp-MRI can provide valuable information about the histopathological aggressiveness of a PCa lesion and the tumour stage with possible ECE can be assessed in the pre-therapeutic setting providing important additional information for optimal patient-tailored treatment planning.

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Year:  2017        PMID: 28157066

Source DB:  PubMed          Journal:  Dan Med J        ISSN: 2245-1919            Impact factor:   1.240


  14 in total

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3.  Radiomics-based machine-learning method to diagnose prostate cancer using mp-MRI: a comparison between conventional and fused models.

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4.  Automatic Needle Segmentation and Localization in MRI With 3-D Convolutional Neural Networks: Application to MRI-Targeted Prostate Biopsy.

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Journal:  IEEE Trans Med Imaging       Date:  2018-10-18       Impact factor: 10.048

5.  mEPE-score: a comprehensive grading system for predicting pathologic extraprostatic extension of prostate cancer at multiparametric magnetic resonance imaging.

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7.  Applicability of readout-segmented echoplanar diffusion weighted imaging for prostate MRI.

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8.  Correlation of Prostate-Imaging Reporting and Data Scoring System scoring on multiparametric prostate magnetic resonance imaging with histopathological factors in radical prostatectomy material in Turkish prostate cancer patients: a multicenter study of the Urooncology Association.

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Journal:  Prostate Int       Date:  2020-02-08

9.  What is the consistency between the results of needle biopsy and prostatectomy specimen pathology results? A pilot study

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Review 10.  Surface impact on nanoparticle-based magnetic resonance imaging contrast agents.

Authors:  Weizhong Zhang; Lin Liu; Hongmin Chen; Kai Hu; Ian Delahunty; Shi Gao; Jin Xie
Journal:  Theranostics       Date:  2018-04-03       Impact factor: 11.556

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