Exploring the Value of Using Patient-Oriented MRI Reports in Clinical Practice

Purpose Standard radiology reports (SRR) are designed to communicate information between doctors. With many patients having instantaneous access to SRRs on patient portals, interpretation without guidance from doctors can cause anxiety and panic. We designed a patient-centred prostate MRI template report (PACERR) to address some of these challenges and tested whether PACERRs improve patient knowledge and experience. Materials and Methods Patients booked for clinical prostate MRI were randomly assigned to SRR or SRR + PACERR. Questionnaires included multiple-choice that targeted 4 domains (understanding, usefulness, next steps, emotional experience) hypothesized to improve with patient-centred reports and short answer questions, testing knowledge regarding MRI results. Clinical encounters were observed and recorded to explore whether adding PACERR improved communication. Likert scaled-responses and short-answer questions were compared using Mann-Whitney U test and Kruskal-Wallis test. Results Of the 40 participants, the majority were MRI naïve (70%). Patients receiving a PACERR had higher scores in the categories of patient understanding (mean: 4.17 vs. 3.39, p=0.006), usefulness (mean: 4.58 vs. 3.07, p<0.001), and identifying next steps (mean: 1.89 vs. 3.03, p=0.003) but not emotional experience (mean: 4.18 vs. 3.79, p=0.22). PACERR participants found the layout and design more patient friendly (mean: 4.47 vs. 2.61, p<0.001) and easier to understand (mean: 4.37 vs. 2.38, p<0.001). In the knowledge section, overall, the PACERR arm scored better (87% vs. 56%, p=0.004). Conclusion With the addition of Prostate MRI PACERR, participants had better understanding of their results and felt more prepared to involve themselves in discussions with their doctor.

Deep learning-based artificial intelligence applications in prostate MRI: brief summary

Prostate cancer (PCa) is the most common cancer type in males in the Western World. MRI has an established role in diagnosis of PCa through guiding biopsies. Due to multistep complex nature of the MRI-guided PCa diagnosis pathway, diagnostic performance has a big variation. Developing artificial intelligence (AI) models using machine learning, particularly deep learning, has an expanding role in radiology. Specifically, for prostate MRI, several AI approaches have been defined in the literature for prostate segmentation, lesion detection and classification with the aim of improving diagnostic performance and interobserver agreement. In this review article, we summarize the use of radiology applications of AI in prostate MRI.

Multiparametric prostate MRI quality assessment using a semi-automated PI-QUAL software program

The technical requirements for the acquisition of multiparametric magnetic resonance imaging (mpMRI) of the prostate have been clearly outlined in the Prostate Imaging Reporting and Data System (PI-RADS) guidelines, but there is still huge variability in image quality among centres across the world. It has been difficult to quantify what constitutes a good-quality image, and a first attempt to address this matter has been the publication of the Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet. This score includes the assessment of technical parameters that can be obtained from the DICOM files along with a visual evaluation of certain features on prostate MRI (e.g., anatomical structures). We retrospectively analysed the image quality of 10 scans from different vendors and magnets using a semiautomated dedicated PI-QUAL software program and compared the time needed for assessing image quality using two methods (semiautomated assessment versus manual filling of the scoring sheet). This semiautomated software is able to assess the technical parameters automatically, but the visual assessment is still performed by the radiologist. There was a significant reduction in the reporting time of prostate mpMRI quality according to PI-QUAL using the dedicated software program compared to manual filling (5′54″ versus 7′59″; p = 0.005). A semiautomated PI-QUAL software program allows the radiologist to assess the technical details related to the image quality of prostate mpMRI in a quick and reliable manner, allowing clinicians to have more confidence that the quality of mpMRI of the prostate is sufficient to determine patient care.

How to read biparametric MRI in men with a clinical suspicious of prostate cancer: Pictorial review for beginners with public access to imaging, clinical and histopathological database

Prostate Magnetic Resonance Imaging (MRI) is increasingly being used in men with a clinical suspicion of prostate cancer (PCa). Performing prostate MRI without the use of an intravenous contrast (IV) agent in men with a clinical suspicion of PCa can lead to reduced MRI scan time. Enabling a large array of different medical providers (from mid-level to specialized radiologists) to evaluate and potentially report prostate MRI in men with a clinical suspicion of PCa with a high accuracy could be one way to enable wide adoption of prostate MRI in men with a clinical suspicion of PCa. The aim of this pictorial review is to provide an insight into acquisition, quality control and reporting of prostate MRI performed without IV contrast agent in men with a clinical suspicion of PCa, aimed specifically at radiologists starting reporting prostate MRI, urologists, urology/radiology residents and mid-level medical providers without experience in reporting prostate MRI. Free public access ( http://petiv.utu.fi/improd/ and http://petiv.utu.fi/multiimprod/ ) to complete datasets of 161 and 338 men is provided. The imaging datasets are accompanied by clinical, laboratory and histopathological findings. Several topics are simplified in order to provide a solid base for the development of skills needed for an unsupervised review and potential reporting of prostate MRI in men with a clinical suspicion of PCa. The current review represents the first step towards enabling a large array of different medical providers to review and report accurately prostate MRI performed without IV contrast agent in men with a clinical suspicion of PCa.

Multiparametric Prostate MRI in Biopsy-Naïve Men: A Prospective Evaluation of Performance and Biopsy Strategies

ObjectivesThis study aims to prospectively estimate the diagnostic performance of multiparametric prostate MRI (mpMRI) and compare the detection rates of prostate cancer using cognitive targeted transrectal ultrasound (TRUS) guided biopsies, targeted MR-guided in-bore biopsies (MRGB), or both methods combined in biopsy-naïve men.MethodsThe biopsy-naïve men referred for mpMRI (including T2-weighted, diffusion-weighted and dynamic contrast enhanced MRI) due to prostate cancer suspicion (elevated prostate-specific antigen or abnormal digital rectal examination) were eligible for inclusion. The images were scored according to Prostate Imaging Reporting and Data System (PI-RADS) v2, and men with PI-RADS 1–2 lesions were referred for routine systematic TRUS, while those with PI-RADS 3–5 lesions were randomized to MRGB or cognitive targeted TRUS. Men randomized to MRGB were referred to a secondary TRUS 2 weeks after MRGB. Gleason grade group ≥2 was defined as clinically significant prostate cancer. The performance of mpMRI was estimated using prostate cancer detected by any biopsy method as the reference test.ResultsA total of 210 men were included. There was no suspicion of prostate cancer after mpMRI (PI-RADS 1–2) in 48% of the men. Among these, significant and insignificant prostate cancer was diagnosed in five and 11 men, respectively. Thirty-five men who scored as PI-RADS 1–2 did not undergo biopsy and were therefore excluded from the calculation of diagnostic accuracy. The overall sensitivity, specificity, negative predictive value, and positive predictive value of mpMRI for the detection of significant prostate cancer were 0.94, 0.63, 0.92, and 0.67, respectively. In patients with PI-RADS 3–5 lesions, the detection rates for significant prostate cancer were not significantly different between cognitive targeted TRUS (68.4%), MRGB (57.7%), and the combination of the two biopsy methods (64.4%). The median numbers of biopsy cores taken per patient undergoing systematic TRUS, cognitive targeted TRUS, and MRGB were 14 [8-16], 12 [6-17], and 2 [1-4] respectively.ConclusionsmpMRI, in a cohort of biopsy-naïve men, has high negative predictive value, and our results support that it is safe to avoid biopsy after negative mpMRI. Furthermore, MRGB provides a similar diagnosis to the cognitive targeted TRUS but with fewer biopsies.