Rectal gas-induced susceptibility artefacts on prostate diffusion-weighted MRI with epi read-out at 3.0 T: does a preparatory micro-enema improve image quality?

Strategies for improving image quality in prostate MRI

Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.

Picture Perfect: The Status of Image Quality in Prostate MRI

Magnetic resonance imaging is the gold standard imaging modality for the diagnosis of prostate cancer (PCa). Image quality is a fundamental prerequisite for the ability to detect clinically significant disease. In this critical review, we separate the issue of image quality into quality improvement and quality assessment. Beginning with the evolution of technical recommendations for scan acquisition, we investigate the role of patient preparation, scanner factors, and more advanced sequences, including those featuring Artificial Intelligence (AI), in determining image quality. As means of quality appraisal, the published literature on scoring systems (including the Prostate Imaging Quality score), is evaluated. Finally, the application of AI and teaching courses as ways to facilitate quality assessment are discussed, encouraging the implementation of future image quality initiatives along the PCa diagnostic and monitoring pathway. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Machine learning based prediction of image quality in prostate MRI using rapid localizer images

Purpose

Diagnostic performance of prostate MRI depends on high-quality imaging. Prostate MRI quality is inversely proportional to the amount of rectal gas and distention. Early detection of poor-quality MRI may enable intervention to remove gas or exam rescheduling, saving time. We developed a machine learning based quality prediction of yet-to-be acquired MRI images solely based on MRI rapid localizer sequence, which can be acquired in a few seconds.

Approach

The dataset consists of 213 (147 for training and 64 for testing) prostate sagittal T2-weighted (T2W) MRI localizer images and rectal content, manually labeled by an expert radiologist. Each MRI localizer contains seven two-dimensional (2D) slices of the patient, accompanied by manual segmentations of rectum for each slice. Cascaded and end-to-end deep learning models were used to predict the quality of yet-to-be T2W, DWI, and apparent diffusion coefficient (ADC) MRI images. Predictions were compared to quality scores determined by the experts using area under the receiver operator characteristic curve and intra-class correlation coefficient.

Results

In the test set of 64 patients, optimal versus suboptimal exams occurred in 95.3% (61/64) versus 4.7% (3/64) for T2W, 90.6% (58/64) versus 9.4% (6/64) for DWI, and 89.1% (57/64) versus 10.9% (7/64) for ADC. The best performing segmentation model was 2D U-Net with ResNet-34 encoder and ImageNet weights. The best performing classifier was the radiomics based classifier.

Conclusions

A radiomics based classifier applied to localizer images achieves accurate diagnosis of subsequent image quality for T2W, DWI, and ADC prostate MRI sequences.

Addressing image misalignments in multi-parametric prostate MRI for enhanced computer-aided diagnosis of prostate cancer

Prostate cancer (PCa) diagnosis on multi-parametric magnetic resonance images (MRI) requires radiologists with a high level of expertise. Misalignments between the MRI sequences can be caused by patient movement, elastic soft-tissue deformations, and imaging artifacts. They further increase the complexity of the task prompting radiologists to interpret the images. Recently, computer-aided diagnosis (CAD) tools have demonstrated potential for PCa diagnosis typically relying on complex co-registration of the input modalities. However, there is no consensus among research groups on whether CAD systems profit from using registration. Furthermore, alternative strategies to handle multi-modal misalignments have not been explored so far. Our study introduces and compares different strategies to cope with image misalignments and evaluates them regarding to their direct effect on diagnostic accuracy of PCa. In addition to established registration algorithms, we propose 'misalignment augmentation' as a concept to increase CAD robustness. As the results demonstrate, misalignment augmentations can not only compensate for a complete lack of registration, but if used in conjunction with registration, also improve the overall performance on an independent test set.

Application of a validated prostate MRI deep learning system to independent same-vendor multi-institutional data: demonstration of transferability

OBJECTIVES

To evaluate a fully automatic deep learning system to detect and segment clinically significant prostate cancer (csPCa) on same-vendor prostate MRI from two different institutions not contributing to training of the system.

MATERIALS AND METHODS

In this retrospective study, a previously bi-institutionally validated deep learning system (UNETM) was applied to bi-parametric prostate MRI data from one external institution (A), a PI-RADS distribution-matched internal cohort (B), and a csPCa stratified subset of single-institution external public challenge data (C). csPCa was defined as ISUP Grade Group ≥ 2 determined from combined targeted and extended systematic MRI/transrectal US-fusion biopsy. Performance of UNETM was evaluated by comparing ROC AUC and specificity at typical PI-RADS sensitivity levels. Lesion-level analysis between UNETM segmentations and radiologist-delineated segmentations was performed using Dice coefficient, free-response operating characteristic (FROC), and weighted alternative (waFROC). The influence of using different diffusion sequences was analyzed in cohort A.

RESULTS

In 250/250/140 exams in cohorts A/B/C, differences in ROC AUC were insignificant with 0.80 (95% CI: 0.74-0.85)/0.87 (95% CI: 0.83-0.92)/0.82 (95% CI: 0.75-0.89). At sensitivities of 95% and 90%, UNETM achieved specificity of 30%/50% in A, 44%/71% in B, and 43%/49% in C, respectively. Dice coefficient of UNETM and radiologist-delineated lesions was 0.36 in A and 0.49 in B. The waFROC AUC was 0.67 (95% CI: 0.60-0.83) in A and 0.7 (95% CI: 0.64-0.78) in B. UNETM performed marginally better on readout-segmented than on single-shot echo-planar-imaging.

CONCLUSION

For same-vendor examinations, deep learning provided comparable discrimination of csPCa and non-csPCa lesions and examinations between local and two independent external data sets, demonstrating the applicability of the system to institutions not participating in model training.

CLINICAL RELEVANCE STATEMENT

A previously bi-institutionally validated fully automatic deep learning system maintained acceptable exam-level diagnostic performance in two independent external data sets, indicating the potential of deploying AI models without retraining or fine-tuning, and corroborating evidence that AI models extract a substantial amount of transferable domain knowledge about MRI-based prostate cancer assessment.

KEY POINTS

• A previously bi-institutionally validated fully automatic deep learning system maintained acceptable exam-level diagnostic performance in two independent external data sets. • Lesion detection performance and segmentation congruence was similar on the institutional and an external data set, as measured by the weighted alternative FROC AUC and Dice coefficient. • Although the system generalized to two external institutions without re-training, achieving expected sensitivity and specificity levels using the deep learning system requires probability thresholds to be adjusted, underlining the importance of institution-specific calibration and quality control.

Quality assessment of prostate MRI by PI-QUAL score: Inter-reader agreement and impact on prostate cancer local staging at 3 Tesla

PURPOSE

To evaluate whether the Prostate Imaging Quality (PI-QUAL) score impacts prostate cancer (PCa) staging on MRI. The secondary goal was to test inter-reader agreement among radiologists experienced in prostate imaging.

METHOD

A retrospective, single-center study with patients who underwent 3 Tesla prostate MRI scans and were submitted to radical prostatectomy (RP) between January 2018 and November 2021 and were eligible for our study. Extraprostatic extension (EPE) data were collected from original MR reports (EPEm) and pathological reports of RP specimens (EPEp). Three expert prostate radiologists (ESUR/ESUI criteria R1, R2, R3) independently evaluated all MRI exams according to PI-QUAL score for image quality (1 to 5; 1: poor, 5: excellent), blinded to original imaging reports and clinical data. We studied the diagnostic performance of MRI using pooled data from PI-QUAL scores (≤3 vs. ≥4). We also performed univariate and multivariate analyses to assess the PI-QUAL score impact on local PCa staging. Cohen's K and Tau-b Kendall tests were used to assess the inter-reader agreement for PI-QUAL score, T2WI, DWI, and DCE.

RESULTS

Our final cohort included 146 patients, of which 27.4% presented EPE on pathology. We observed no impact of imaging quality on accuracy for EPE prediction: AUC of 0.750 (95% CI 0.26-1) for PI-QUAL ≤ 3 and 0.705 (95% CI 0.618-0.793) for PI-QUAL ≥ 4. The multivariate analysis demonstrated a correlation of EPEm (OR 3.25, p 0.001) and ISUP grade group (OR 1.89, p 0.012) to predict EPEp. The inter-reader agreement was moderate to substantial (0.539 for R1-R2, 0.522 for R2-R3, and 0.694 for R1-R3).

CONCLUSION

Our clinical impact evaluation showed no direct correlation between MRI quality by PI-QUAL score and accuracy in detecting EPE in patients undergoing RP. Additionally, we had moderate to a substantial inter-reader agreement for the PI-QUAL score.

Prostate MRI and image Quality: It is time to take stock

Multiparametric magnetic resonance imaging (mpMRI) plays a vital role in prostate cancer diagnosis and management. With the increase in use of mpMRI, obtaining the best possible quality images has become a priority. The Prostate Imaging Reporting and Data System (PI-RADS) was introduced to standardize and optimize patient preparation, scanning techniques, and interpretation. However, the quality of the MRI sequences depends not only on the hardware/software and scanning parameters, but also on patient-related factors. Common patient-related factors include bowel peristalsis, rectal distension, and patient motion. There is currently no consensus regarding the best approaches to address these issues and improve the quality of mpMRI. New evidence has been accrued since the release of PI-RADS, and this review aims to explore the key strategies which aim to improve prostate MRI quality, such as imaging techniques, patient preparation methods, the new Prostate Imaging Quality (PI-QUAL) criteria, and artificial intelligence on prostate MRI quality.

[Prostate Imaging Reporting and Data System (PI-RADS) v 2.1: Overview and Critical Points]

The technical parameters and imaging interpretation criteria of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) using multiparametric MRI (mpMRI) are updated in PI-RADS v2.1. These changes have been an expected improvement for prostate cancer evaluation, although some issues remain unsolved, and new issues have been raised. In this review, a brief overview of PI-RADS v2.1 is and several critical points are discussed as follows: the need for more detailed protocols of mpMRI, lack of validation of the revised transition zone interpretation criteria, the need for clarification for the revised diffusion-weighted imaging and dynamic contrast-enhanced imaging criteria, anterior fibromuscular stroma and central zone assessment, assessment of background signal and tumor aggressiveness, changes in the structured report, the need for the parameters for imaging quality and performance control, and indications for expansion of the system to include other indications.

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.

Rectal preparation significantly improves prostate imaging quality: Assessment of the PI-QUAL score with visual grading characteristics

PURPOSE

To investigate the effects of a rectal preparation regimen, that consisted of a rectal cleansing enema and an endorectal gel filling protocol, on prostate imaging quality (PI-QUAL).

METHODS

Multiparametric MRI (mpMRI) was performed in 150 consecutive patients divided into two groups of 75 patients. One group received a rectal preparation with a cleansing enema and endorectal gel filling (median age 65.3 years, median PSA level 6 ng/ml). The other patient group did not receive such a preparation (median age 64 years, median PSA level 6 ng/ml). Two uroradiologists independently rated general image quality and lesion visibility on diffusion-weighted imaging (DWI), T2-weighted (T2w), and dynamic contrast-enhanced (DCE) images using a five-point ordinal scale. In addition, two uroradiologists assigned PI-QUAL scores, using the dedicated scoring sheet. Data sets were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/ area under the curve (AUC) analysis.

RESULTS

VGC revealed significantly better general image quality for DWI (AUC R1 0.708 (0.628-0.779 CI, p < 0.001; AUC R2 0.687 (0.606-0.760 CI, p < 0.001) and lesion visibility for both readers (AUC R1 0.729 (0.607-0.831 CI, p < 0.001); AUC R2 0.714 (0.590-0.818CI, p < 0.001) in the preparation group. For T2w imaging, rectal preparation resulted in significantly better lesion visibility for both readers (R1 0.663 (0.537-0.774 CI, p = 0.014; R2 0.663 (0.537-0.774 CI, p = 0.014)). Averaged PI-QUAL scores were significantly improved with rectal preparation (AUC R3/R4 0.667, CI 0.581-0.754, p < 0.001).

CONCLUSION

Rectal preparation significantly improved prostate imaging quality (PI-QUAL) and lesion visibility. Hence, a rectal preparation regimen consisting of a rectal cleansing enema and an endorectal gel filling could be considered.

Influence of Enema and Dietary Restrictions on Prostate MR Image Quality: A Multireader Study

PURPOSE

To evaluate the effect of enema and dietary restrictions on prostate MR image quality metrics and to assess inter-reader agreement for these metrics.

METHODS

This retrospective study included 195 men divided into groups based on their compliance with preparation instructions before prostate MRI (Enema + Diet, n = 98; Enema, n = 42; Diet, n = 35; Control [no compliance], n = 20). Four readers independently assessed six image quality metrics on a 5-point scale. Between-group comparisons were made using Wilcoxon rank sum test. Inter-reader agreement was calculated using Fleiss' kappa.

RESULTS

Compared with the Control group, image quality with respect to rectal stool/gas, distortion of diffusion-weighted images, overall image quality, and confidence in assessment was higher in the Enema + Diet, Enema, and Diet groups (p  < 0.05 for all comparisons). The Enema + Diet and Enema groups had significantly higher scores than the Diet group for rectal stool/gas (p < 0.001 and 0.005, respectively). The Enema + Diet and Diet groups had higher scores than the Control group for rectal peristalsis (p = 0.027 and 0.009, respectively), but there were no significant differences in motion artifacts on T2-weighted images. Agreement among readers was fair, with kappa values ranging from 0.25 to 0.37.

CONCLUSION

Enema and dietary restriction can improve the quality of prostate MRI by decreasing rectal distension and distortion of diffusion-weighted images and by increasing reader confidence in image assessment. Inter-reader agreement using subjective criteria for analysis of MRI quality is fair.

Multi-practice survey on MR imaging practice patterns in rectal cancer in the United States

PURPOSE

To investigate practice patterns related to MR technique and structured reporting for MRI of rectal cancer at academic centers and private practice groups in the United States.

METHODS AND MATERIALS

A survey developed by active members of the Society of Abdominal Radiology Rectal and Anal Cancer Disease Focus Panel was sent to 100 private practice and 189 academic radiology groups. The survey asked targeted questions about practice demographics and utilization, technical MR parameters and reporting practices related to MRI of rectal cancer. The results were analyzed using software in an online survey program.

RESULTS

The survey received 47 unique responses from academic (37/47, 78.7%) and private practice (10/47, 21.3%) groups. Most practices report using rectal MR for staging newly diagnosed rectal cancer always (29/47, 61.7%), and less than half always do so for re-staging after neoadjuvant chemoradiation (20/47, 42.6%). Most groups perform between 1 to 5 rectal MR studies for baseline staging per week (32/47, 68.1%) and most groups perform 0 to 2 MR studies for re-staging per week (27/47, 57.4%). Regarding patient preparation and MR technical parameters, there is variability, but a few key points include most practices (27/47, 57.4%) acquire axial T2-weighted images at a slice thickness of 3 mm or less, axial T2-weighted images with 2D acquisition (30/47, 63.8%), a T2-weighted axial oblique sequence through the tumor (43/47, 91.5%), and T2-weighted images without fat suppression (37/47, 78.7%). Equal numbers of groups report using a maximal b-value less than 1000 s/mm² (19/43, 44.2%) and 1000 s/mm² or greater (19/43, 44.2%); the rest were unsure. A substantial portion of respondents do not use intravenous contrast (13/47, 27.7%). Most believe that structured report templates contribute to uniformity of reporting practices (39/47, 83.0%), though there is considerable heterogeneity in usage and included elements.

CONCLUSION

There is considerable technical heterogeneity among respondents' answers and reporting practices in MR for rectal cancer, and most of the groups report reading only a modest number of studies per week. Our findings suggest there may be room for improvement in terms of radiologist education for performance and standardization of clinical practice for MR imaging of rectal cancer.

Comparison of 5 Rectal Preparation Strategies for Prostate MRI and Impact on Image Quality

PURPOSE

To compare 5 different rectal preparation strategies for prostate MRI.

METHODS

This 5-arm quality-assurance study evaluated 56 patients per arm (280 patients) including: no preparation, clear-fluids diet (CFD) beginning at 00:00 hours on the day of MRI, Fleet®-enema, enema + CFD, enema + CFD + IV-antispasmodic agent. The study was powered to 0.80 with alpha-error of 0.05. Three blinded radiologists independently evaluated T2-Weighted (T2W) and Diffusion Weighed Imaging (DWI) for: rectal diameter (maximal AP diameter), rectal content (stool, fluid, gas), rectal motion, T2W/DWI image quality, T2W image sharpness and DWI susceptibility artifact using 5-point Likert scales. Overall comparisons were performed using analysis of variance (ANOVA) and Kruskal-Wallis, with pair-wise comparisons using paired t-tests and Wilcoxon sign-rank tests.

RESULTS

Rectal diameter and amount of gas were lower in enema compared to non-enema groups (p < 0.001), with smallest diameter and least gas in the enema + CFD + IV-antispasmodic group (p = 0.022-<0.001). T2W image quality and sharpness were highest in the enema + CFD groups (p < 0.001) with no difference comparing enema + CFD with/without IV-antispasmodic (p = 0.064, 0.084). Motion artifact was least in enema + CFD + IV-antispasmodic group compared to all other groups (p < 0.001), followed by the enema + CFD group (p = 0.008-<0.001). DWI image quality was highest (p < 0.001) and DWI susceptibility artifact lowest (p < 0.001) in the enema + CFD groups (p < 0.001) and did not differ comparing enema + CFD with/without anti-spasmodic (p = 0.058-0.202).

CONCLUSIONS

Use of enema + clear-fluids diet before prostate MRI yields the highest T2W and DWI image quality with the least DWI artifact. IV-antispasmodic use reduces motion on T2W but does not improve image quality on T2W or DWI, or lessen DWI artifact compared to enema + clear-fluids diet.

Convolutional Neural Networks for Automated Classification of Prostate Multiparametric Magnetic Resonance Imaging Based on Image Quality

Background

Prostate magnetic resonance imaging (MRI) is technically demanding, requiring high image quality to reach its full diagnostic potential. An automated method to identify diagnostically inadequate images could help optimize image quality.

Purpose

To develop a convolutional neural networks (CNNs) based analysis pipeline for the classification of prostate MRI image quality.

Study Type

Retrospective.

Subjects

Three hundred sixteen prostate mpMRI scans and 312 men (median age 67).

Field Strength/Sequence

A 3 T; fast spin echo T2WI, echo planar imaging DWI, ADC, gradient‐echo dynamic contrast enhanced (DCE).

Assessment

MRI scans were reviewed by three genitourinary radiologists (V.P., M.D.M., S.C.) with 21, 12, and 5 years of experience, respectively. Sequences were labeled as high quality (Q1) or low quality (Q0) and used as the reference standard for all analyses.

Statistical Tests

Sequences were split into training, validation, and testing sets (869, 250, and 120 sequences, respectively). Inter‐reader agreement was assessed with the Fleiss kappa. Following preprocessing and data augmentation, 28 CNNs were trained on MRI slices for each sequence. Model performance was assessed on both a per‐slice and a per‐sequence basis. A pairwise t‐test was performed to compare performances of the classifiers.

Results

The number of sequences labeled as Q0 or Q1 was 38 vs. 278 for T2WI, 43 vs. 273 for DWI, 41 vs. 275 for ADC, and 38 vs. 253 for DCE. Inter‐reader agreement was almost perfect for T2WI and DCE and substantial for DWI and ADC. On the per‐slice analysis, accuracy was 89.95% ± 0.02% for T2WI, 79.83% ± 0.04% for DWI, 76.64% ± 0.04% for ADC, 96.62% ± 0.01% for DCE. On the per‐sequence analysis, accuracy was 100% ± 0.00% for T2WI, DWI, and DCE, and 92.31% ± 0.00% for ADC. The three best algorithms performed significantly better than the remaining ones on every sequence (P‐value < 0.05).

Data Conclusion

CNNs achieved high accuracy in classifying prostate MRI image quality on an individual‐slice basis and almost perfect accuracy when classifying the entire sequences.

Evidence Level

4

Technical Efficacy

Stage 1

Value of bowel preparation techniques for prostate MRI: a preliminary study

Background

Bowel preparation before multiparametric MRI (mpMRI) of the prostate is performed widely, despite contradictory or no evidence for efficacy.

Purpose

To investigate the value of hyoscine N-butylbromide (HBB), microenema (ME) and ‘dietary restrictions’ (DR) for artifact reduction and image quality (IQ) in mpMRI of the prostate.

Study type

Retrospective.

Population

Between 10/2018 and 02/2020 treatment-naïve men (median age, 64.9; range 39.8–87.3) who underwent mpMRI of the prostate were included. The total patient sample comprised of n = 180 patients, who received either HBB, ME, were instructed to adhere to DR, or received a combination of those measures prior to the MR scan.

Field strength/sequence

T2-weighted imaging (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI) scanned on two 3T systems.

Assessment

A radiologist specialized in urogenital imaging (R1) and a senior radiology resident (R2) visually assessed IQ parameters on transversal T2w, DWI and ADC maps on a 5-point Likert-like scale.

Statistical tests

Group comparison between IQ parameters was performed on reader level using Kruskal–Wallis and Mann–Whitney U tests. Binary univariate logistic regression analysis was used to assess independent predictors of IQ. Interrater agreement was assessed using Intraclass Correlation Coefficient (ICC).

Results

‘DWI geometric distortion’ was significantly more pronounced in the HBB+/ME−/DR− (R1, 3.6 and R2, 4.0) as compared to the HBB−/ME+/DR− (R1, 4.2 and R2, 4.6) and HBB+/ME+/DR− (R1, 4.3 and R2, 4.7) cohort, respectively. Parameters ‘DWI IQ’ and ‘Whole MRI IQ’ were rated similarly by both readers. ME was a significant independent predictor of ‘good IQ’ for the whole MRI for R1 [b = 1.09, OR 2.98 (95% CI 1.29, 6.87)] and R2 [b = 1.01, OR 2.73 (95% CI 1.24, 6.04)], respectively.

Data conclusion

ME seems to significantly improve image quality of DWI and the whole mpMRI image set of the prostate. HBB and DR did not have any benefit.

Prostate MRI quality: a critical review of the last 5 years and the role of the PI-QUAL score

There is increasing interest in the use of multiparametric magnetic resonance imaging (mpMRI) in the prostate cancer pathway. The European Association of Urology (EAU) and the British Association of Urological Surgeons (BAUS) now advise mpMRI prior to biopsy, and the Prostate Imaging Reporting and Data System (PI-RADS) recommendations set out the minimal technical requirements for the acquisition of mpMRI of the prostate.The widespread and swift adoption of this technique has led to variability in image quality. Suboptimal image acquisition reduces the sensitivity and specificity of mpMRI for the detection and staging of clinically significant prostate cancer.This critical review outlines the studies aimed at improving prostate MR quality that have been published over the last 5 years. These span from the use of specific MR sequences, magnets and coils to patient preparation. The rates of adherence of prostate mpMRI to technical standards in different cohorts across the world are also discussed.Finally, we discuss the first standardised scoring system (i.e., Prostate Imaging Quality, PI-QUAL) that has been created to evaluate image quality, although further iterations of this score are expected in the future.

Do antispasmodics or rectal enemas improve image quality on multiparametric prostate MRI? An 'Evidence-Based Practice' review of the literature

Multiparametric magnetic resonance imaging (mpMRI) of the prostate is increasingly used for the preoperative detection and staging of prostate cancer. Image quality of prostate mpMRI can be significantly degraded by motion related artefact due to bowel peristalsis and susceptibility related artefact, which reduces cancer detection sensitivity. The use of several different methods including anstispasmodic medications and rectal enemas were proposed as potential methods to reduce mpMRI artefacts, but current recommendations in the scientific literature are conflicting and inconsistent. This article seeks to identify the best available evidence to determine which patient preparation method is most effective in improving prostate mpMRI, and provides recommendations for further areas of research. We used the five-step 'Evidence-Based Practice' systematic approach of 'Ask, Search, Appraise, Apply and Evaluate' described by the McMaster University and National Health Service for critical appraisal of topics. We developed a focused clinical question using a PICO format, and performed a primary and secondary literature search through Ovid Medline, Ovid Embase and Cochrane CENTRAL (Wiley). All identified articles were appraised for strength and validity. Seven articles were retrieved which demonstrated conflicting sensitivities and specificities for intravenous hyoscine butylbromide and rectal enema in improving image susceptibility artefact, motion artefact, and anatomic distortion on the T2 or diffusion weighted imaging sequences. Intravenous hysoscine butylbromide is the optimum patient preparation method for improving T2W and DWI image quality in prostate mpMRI. The use of a preparatory rectal enema is not currently recommended, but better quality studies are required.

Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists

Prostate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans.

How to improve image quality of DWI of the prostate-enema or catheter preparation?

OBJECTIVES

To compare the impact of laxative enema preparation versus air/gas suction through a small catheter on image quality of prostate DWI.

METHODS

In this single-center study, 200 consecutive patients (100 in each arm) with either enema or catheter preparation were retrospectively included. Two blinded readers independently assessed aspects of image quality on 5-point Likert scales. Scores were compared between groups and the influence of confounding factors evaluated using multivariable logistic regression. Prostate diameters were compared on DWI and T₂-weighted imaging using intraclass correlation coefficients.

RESULTS

Image quality was significantly higher in the enema group regarding the severity of susceptibility-related artifacts (reader 1: 0.34 ± 0.77 vs. 1.73 ± 1.34, reader 2: 0.38 ± 0.86 vs. 1.76 ± 1.39), the differentiability of the anatomy (reader 1: 3.36 ± 1.05 vs. 2.08 ± 1.31, reader 2: 3.37 ± 1.05 vs. 2.09 ± 1.35), and the overall image quality (reader 1: 3.66 ± 0.77 vs. 2.26 ± 1.33, Reader 2: 3.59 ± 0.87 vs. 2.23 ± 1.38) with almost perfect inter-observer agreement (κ = 0.92-0.95). In the enema group, rectal distention was significantly lower and strongly correlated with the severity of artifacts (reader 1: ρ = 0.79, reader 2: ρ = 0.73). Furthermore, there were significantly fewer substantial image distortions, with odds ratios of 0.051 and 0.084 for the two readers which coincided with a higher agreement of the prostate diameters in the phase-encoding direction (0.96 vs. 0.89).

CONCLUSIONS

Enema preparation is superior to catheter preparation and yields substantial improvements in image quality.

KEY POINTS

• Enema preparation is superior to decompression of the rectum using air/gas suction through a small catheter. • Enema preparation markedly improves the image quality of prostate DWI regarding the severity of susceptibility-related artifacts, the differentiability of the anatomy, and the overall image quality and considerably reduces substantial artifacts that may impair a reliable diagnosis.