Objectives To evaluate the recommendations for multiparametric prostate MRI (mp-MRI) interpretation introduced in the recently updated Prostate Imaging Reporting and Data System version 2 (PI-RADSv2), and investigate the impact of pathologic tumour volume on prostate cancer (PCa) detectability on mpMRI. Methods This was an institutional review board (IRB)-approved, retrospective study of 150 PCa patients who underwent mp-MRI before prostatectomy; 169 tumours ≥0.5-mL (any Gleason Score [GS]) and 37 tumours <0.5-mL (GS ≥4+3) identified on whole-mount pathology maps were located on mp-MRI consisting of T2-weighted imaging (T2WI), diffusion-weighted (DW)-MRI, and dynamic contrast-enhanced (DCE)-MRI. Corresponding PI-RADSv2 scores were assigned on each sequence and combined as recommended by PI-RADSv2. We calculated the proportion of PCa foci on whole-mount pathology correctly identified with PI-RADSv2 (dichotomized scores 1–3 vs. 4–5), stratified by pathologic tumour volume. Results PI-RADSv2 allowed correct identification of 118/125 (94 %; 95 %CI: 90–99 %) peripheral zone (PZ) and 42/44 (95 %; 95 %CI: 89–100 %) transition zone (TZ) tumours ≥0.5 mL, but only 7/27 (26 %; 95 %CI: 10–42 %) PZ and 2/10 (20 %; 95 %CI: 0–52 %) TZ tumours with a GS ≥4+3, but <0.5 mL. DCE-MRI aided detection of 4/125 PZ tumours ≥0.5 mL and 0/27 PZ tumours <0.5 mL. Conclusions PI-RADSv2 correctly identified 94–95 % of PCa foci ≥0.5 mL, but was limited for the assessment of GS ≥4+3 tumours ≤0.5 mL. DCE-MRI offered limited added value to T2WI+DW-MRI.
Segmentation of anatomical structures and pathologies is inherently ambiguous. For instance, structure borders may not be clearly visible or different experts may have different styles of annotating. The majority of current state-of-the-art methods do not account for such ambiguities but rather learn a single mapping from image to segmentation. In this work, we propose a novel method to model the conditional probability distribution of the segmentations given an input image. We derive a hierarchical probabilistic model, in which separate latent variables are responsible for modelling the segmentation at different resolutions. Inference in this model can be efficiently performed using the variational autoencoder framework. We show that our proposed method can be used to generate significantly more realistic and diverse segmentation samples compared to recent related work, both, when trained with annotations from a single or multiple annotators. The code for this paper is freely available at https://github.com/baumgach/PHiSeg-code.
Background Recent studies have reported the additive value of combined gallium 68 (Ga)labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (hereafter called Ga-PSMA-11) PET/MRI for the detection and localization of primary prostate cancer compared with multiparametric MRI. Purpose To compare the diagnostic accuracy and interrater agreement of multiparametric MRI and Ga-PSMA-11 PET/MRI for the detection of extracapsular extension (ECE) and seminal vesicle infiltration (SVI) in patients with prostate cancer. Materials and Methods Retrospective analysis of 40 consecutive men who underwent multiparametric MRI and Ga-PSMA-11 PET/MRI within 6 months for suspected prostate cancer followed by radical prostatectomy between April 2016 and July 2018. Four readers blinded to clinical and histopathologic findings rated the probability of ECE and SVI at multiparametric MRI and PET/MRI by using a five-point Likert-type scale. The prostatectomy specimen served as the reference standard. Accuracy was assessed with a multireader multicase analysis and by calculating reader-average areas under the receiver operating characteristics curve (AUCs), sensitivity, and specificity for ordinal and dichotomized data in a region-specific and patient-specific approach. Interrater agreement was assessed with the Fleiss multirater. Results For multiparametric MRI versus PET/MRI in ECE detection, respectively, AUC, sensitivity, and specificity in the region-specific analysis were 0.67 and 0.75 (.07), 28% (21 of 76) and 47% (36 of 76) (.09), and 94% (529 of 564) and 90% (509 of 564) (.007). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.66 and 0.73 (.19), 46% (22 of 48) and 69% (33 of 48) (.04), and 75% (84 of 112) and 67% (75 of 112) (.19), respectively. For multiparametric MRI versus PET/MRI in SVI detection, respectively, AUC, sensitivity, and specificity of the region-specific analysis were 0.66 and 0.74 (.21), 35% (seven of 20) and 50% (10 of 20) (.25), and 98% (295 of 300) and 94% (282 of 300) (< .001). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.65 and 0.79 (.25), 35% (seven of 20) and 55% (11 of 20) (.20), and 98% (137 of 140) and 94% (131 of 140) (.07), respectively. Interrater reliability for multiparametric MRI versus PET/MRI did not differ for ECE (, 0.46 vs 0.40; = .24) and SVI (, 0.23 vs 0.33; = .39). Conclusion Our results suggest that gallium 68 (Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (Ga-PSMA-11) PET/MRI and multiparametric MRI perform similarly for local staging of prostate cancer in patients with intermediate-to-high-risk prostate cancer. The increased sensitivity of Ga-PSMA-11 PET/MRI for the detection of extracapsular disease comes at the cost of a slightly reduced specificity.
ObjectivesTo assess the value of new magnetic resonance imaging (MRI) techniques in cervical cancer.MethodsWe searched PubMed and MEDLINE and reviewed articles published from 1990 to 2016 to identify studies that used MRI techniques, such as diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and dynamic contrast enhancement (DCE) MRI, to assess parametric invasion, to detect lymph node metastases, tumour subtype and grading, and to detect and predict tumour recurrence.ResultsSeventy-nine studies were included. The additional use of DWI improved the accuracy and sensitivity of the evaluation of parametrial extension. Most studies reported improved detection of nodal metastases. Functional MRI techniques have the potential to assess tumour subtypes and tumour grade differentiation, and they showed additional value in detecting and predicting treatment response. Limitations included a lack of technical standardisation, which limits reproducibility.ConclusionsNew advanced MRI techniques allow improved analysis of tumour biology and the tumour microenvironment. They can improve TNM staging and show promise for tumour classification and for assessing the risk of tumour recurrence. They may be helpful for developing optimised and personalised therapy for patients with cervical cancer.Teaching points • Conventional MRI plays a key role in the evaluation of cervical cancer. • DWI improves tumour delineation and detection of nodal metastases in cervical cancer. • Advanced MRI techniques show promise regarding histological grading and subtype differentiation. • Tumour ADC is a potential biomarker for response to treatment.
Purpose To investigate the effects of androgen-deprivation therapy (ADT) on MRI parameters and evaluate their associations with measures of treatment response. Materials and Methods This study included 30 men with histopathologically-confirmed prostate cancer who underwent MRI before and after start of ADT. Thirty-four tumours were volumetrically assessed on DW-MRI (n=32) and DCE-MRI (n=18), along with regions of interest in benign prostatic tissue, to calculate apparent diffusion coefficient (ADC) and transfer constant (Ktrans) values. Changes in MRI parameters and correlations with clinical parameters (change in prostate-specific antigen [PSA], treatment duration, PSA nadir) were assessed. Results Prostate volume and PSA values decreased significantly through therapy (p<0.001). ADC values increased significantly in tumour and decreased in benign prostatic tissue (p<0.05). Relative changes in ADC and absolute post-therapeutic ADC values differed significantly between tumour and benign tissue (p<0.001). Ktrans decreased significantly only in tumour (p<0.001); relative Ktrans changes and post-therapeutic values did not differ significantly between tumour and benign tissue. The relative change in tumour ADC correlated significantly with the PSA decrease. No changes were associated with treatment duration or PSA nadir. Conclusion Multi-parametric MRI shows significant, measurable changes in tumour and benign prostate caused by ADT and may help in monitoring treatment response.
OBJECTIVE The objective of this study was to investigate whether the apparent diffusion coefficient (ADC) value from DWI and the forward volume transfer constant (Ktrans) value from dynamic contrast-enhanced MRI independently predict prostate cancer aggressiveness, and to determine whether the combination of both parameters performs better than either parameter alone in assessing tumor aggressiveness before treatment. MATERIALS AND METHODS This retrospective study included 158 men with histopathologically confirmed prostate cancer who underwent 3-T MRI before undergoing prostatectomy in 2011. Whole-mount step-section pathologic maps identified 195 prostate cancer foci that were 0.5 mL or larger; these foci were then volumetrically assessed to calculate the per-tumor ADC and Ktrans values. Associations between MRI and histopathologic parameters were assessed using Spearman correlation coefficients, univariate and multivariable logistic regression, and AUCs. RESULTS The median ADC and Ktrans values showed moderate correlation only for tumors for which the Gleason score (GS) was 4 + 4 or higher (ρ = 0.547; p = 0.042). The tumor ADC value was statistically significantly associated with all dichotomized GSs (p < 0.005), including a GS of 3 + 3 versus a GS of 3 + 4 or higher (AUC, 0.693; p = 0.001). The tumor Ktrans value differed statistically significantly only between tumors with a GS of 3 + 3 and those with a primary Gleason grade of 4 (p ≤ 0.015), and it made a statistically significant in differentiating tumors with a GS of 4 + 3 or higher (AUC, 0.711; p < 0.001) and those with a GS of 4 + 4 or higher (AUC, 0.788; p < 0.001) from lower-grade tumors. Combining ADC and Ktrans values improved diagnostic performance in characterizing tumors with a GS of 4 + 3 or higher and those with a GS of 4 + 4 or higher (AUC, 0.739 and 0.856, respectively; p< 0.01). CONCLUSION Although the ADC value helped to differentiate between all GSs, the Ktrans value was only a benefit in characterizing more aggressive tumors. Combining these parameters improves their performance in identifying patients with aggressive tumors who may require radical treatment.
Purpose To compare morphological and functional MRI metrics and determine which ones perform best in assessing response to neoadjuvant chemoradiotherapy (CRT) in rectal cancer. Materials and methods This retrospective study included 24 uniformly-treated patients with biopsy-proven rectal adenocarcinoma who underwent MRI, including diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) sequences, before and after completion of CRT. On all MRI exams, two experienced readers independently measured longest and perpendicular tumour diameters, tumour volume, tumour regression grade (TRG) and tumour signal intensity ratio on T2-weighted imaging, as well as tumour volume and apparent diffusion coefficient on DW-MRI and tumour volume and transfer constant Ktrans on DCE-MRI. These metrics were correlated with histopathological percent tumour regression in the resected specimen (%TR). Inter-reader agreement was assessed using the concordance correlation coefficient (CCC). Results For both readers, post-treatment DW-MRI and DCE-MRI volumetric tumour assessments were significantly associated with %TR; DCE-MRI volumetry showed better inter-reader agreement (CCC=0.700) than DW-MRI volumetry (CCC=0.292). For one reader, mrTRG, post-treatment T2 tumour volumetry and assessments of volume change made with T2, DW-MRI and DCE-MRI were also significantly associated with %TR. Conclusion Tumour volumetry on post-treatment DCE-MRI and DW-MRI correlated well with %TR, with DCE-MRI volumetry demonstrating better inter-reader agreement.
PURPOSE: To externally validate recently published prostate cancer risk calculators (PCa-RCs) incorporating multiparametric magnetic resonance imaging (mpMRI) for the prediction of clinically significant prostate cancer (csPCa) and compare their performance to mpMRI-naïve PCa-RCs. MATE-RIAL AND METHODS: Men without previous PCa diagnosis undergoing transperineal template saturation prostate biopsy with fusion-guided targeted biopsy between 11/2014 and 03/2018 in our academic tertiary referral center were identified. Any Gleason pattern 4 was defined to be csPCa. Predictors (age, PSA, DRE, prostate volume, family history, previous prostate biopsy and highest region of interest according to PIRADS) were retrospectively collected. Four mpMRI-PCa-RCs and two mpMRI-naïve PCa-RCs were evaluated for their discrimination, calibration and clinical net benefit using a ROC analysis, calibration plots and a decision curve analysis, respectively. RESULTS: Out of 468 men, 193 (41%) were diagnosed with csPCa. Three mpMRI-PCa-RCs showed similar discrimination with area-underneaththe-receiver-operating-characteristic-curves (AUC) from 0.83 to 0.85, which was significantly higher than the other PCa-RCs (AUCs: 0.69-0.74). Calibration-in-the-large showed minimal deviation from the true amount of csPCa by 2% for two mpMRI-PCa-RCs, while the other PCa-RCs showed worse calibration (11-27%). A clinical net benefit could only be observed for three mpMRI-PCa-RCs at biopsy thresholds 15%, while none of the six investigated PCa-RCs demonstrated clinical utility against a biopsy all strategy at thresholds <15%. CONCLUSIONS: Performance of the mpMRI-PCa-RCs varies, but they generally outperform mpMRI-naïve PCa-RCs in regard to discrimination, calibration and clinical usefulness. External validation in other biopsy settings is highly encouraged.
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