PI-RADS 2.1 – Image Interpretation: The Most Important Updates and Their Clinical Implications

Beyer, Thomas R.; Weber, Marc‐André; Thierfelder, Kolja M.

doi:10.1055/a-1324-4010

Cited by 6 publications

(5 citation statements)

References 48 publications

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“…This last point emphasizes that the current results and conclusions regarding the utility of DCE must be understood within the special context in which all images are of higher diagnostic quality. However, as mentioned previously, in the context of decreased scan quality, DCE has shown evidence of having more robust quality compared to DWI or ADC maps [ 10 , 16 , 17 ].…”

Section: Discussionmentioning

confidence: 97%

“…contrast in prostate imaging is centered on the utility of DCE imaging. The concept of dominant sequences remained unchanged in the latest PI-RADS v2.1 update, with roles for DWI in the peripheral zone and T2WI in the transition zone [ 10 ]. The role of DCE in PI-RADS v2.1 is to serve as a modifier to upgrade peripheral zone lesions from PI-RADS 3 to category 4 in the presence of early focal enhancement [ 6 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…It was also mentioned in PI-RADS v2.1 that when T2WI and DWI are of insufficient diagnostic quality, DCE utilizing I.V. contrast can assist in determining the PI-RADS assessment category [ 10 , 11 ]. In summary, the PI-RADS v2.1 indications for DCE, and thus for I.V.…”

Section: Introductionmentioning

confidence: 99%

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Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

Belue

Yilmaz

Daryanani

et al. 2022

Life

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The role of multiparametric MRI (mpMRI) in the detection of prostate cancer is well-established. Based on the limited role of dynamic contrast enhancement (DCE) in PI-RADS v2.1, the risk of potential side effects, and the increased cost and time, there has been an increase in studies advocating for the omission of DCE from MRI assessments. Per PI-RADS v2.1, DCE is indicated in the assessment of PI-RADS 3 lesions in the peripheral zone, with its most pronounced effect when T2WI and DWI are of insufficient quality. The aim of this study was to evaluate the methodology and reporting in the literature from the past 5 years regarding the use of DCE in prostate MRI, especially with respect to the indications for DCE as stated in PI-RADS v2.1, and to describe the different approaches used across the studies. We searched for studies investigating the use of bpMRI and/or mpMRI in the detection of clinically significant prostate cancer between January 2017 and April 2022 in the PubMed, Web of Science, and Google Scholar databases. Through the search process, a total of 269 studies were gathered and 41 remained after abstract and full-text screening. The following information was extracted from the eligible studies: general clinical and technical characteristics of the studies, the number of PI-RADS 3 lesions, different definitions of clinically significant prostate cancer (csPCa), biopsy thresholds, reference standard methods, and number and experience of readers. Forty-one studies were included in the study. Only 51% (21/41) of studies reported the prevalence of csPCa in their equivocal lesion (PI-RADS category 3 lesions) subgroups. Of the included studies, none (0/41) performed a stratified sub-analysis of the DCE benefit versus MRI quality and 46% (19/41) made explicit statements about removing MRI scans based on a range of factors including motion, noise, and image artifacts. Furthermore, the number of studies investigating the role of DCE using readers with varying experience was relatively low. This review demonstrates that a high proportion of the studies investigating whether bpMRI can replace mpMRI did not transparently report information inherent to their study design concerning the key indications of DCE, such as the number of clinically insignificant/significant PI-RADS 3 lesions, nor did they provide any sub-analyses to test image quality, with some removing bad quality MRI scans altogether, or reader-experience-dependency indications for DCE. For the studies that reported on most of the DCE indications, their conclusions about the utility of DCE were heavily definition-dependent (with varying definitions of csPCa and of the PI-RADS category biopsy significance threshold). Reporting the information inherent to the study design and related to the specific indications for DCE as stated in PI-RADS v2.1 is needed to determine whether DCE is helpful or not. With most of the recent literature being retrospective and not including the data related to DCE indications in particular, the ongoing dispute between bpMRI and mpMRI is likely to linger.

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Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

Belue

Yilmaz

Daryanani

et al. 2022

Life

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“…MRI is currently a highly important step in the process of diagnosing suspected prostate cancer [23]. On the basis of over 30 years of experience gained in MR prostate studies, classification systems were created and are constantly updated [82]. However, it is widely acknowledged that a great deal of training is required to determine the image patterns behind prostate cancer, and there are still unclear images where diagnosis is not certain [83].…”

Section: Discussionmentioning

confidence: 99%

Textural Features of MR Images Correlate with an Increased Risk of Clinically Significant Cancer in Patients with High PSA Levels

Gibała¹,

Obuchowicz

Lasek

et al. 2023

JCM

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Background: Prostate cancer, which is associated with gland biology and also with environmental risks, is a serious clinical problem in the male population worldwide. Important progress has been made in the diagnostic and clinical setups designed for the detection of prostate cancer, with a multiparametric magnetic resonance diagnostic process based on the PIRADS protocol playing a key role. This method relies on image evaluation by an imaging specialist. The medical community has expressed its desire for image analysis techniques that can detect important image features that may indicate cancer risk. Methods: Anonymized scans of 41 patients with laboratory diagnosed PSA levels who were routinely scanned for prostate cancer were used. The peripheral and central zones of the prostate were depicted manually with demarcation of suspected tumor foci under medical supervision. More than 7000 textural features in the marked regions were calculated using MaZda software. Then, these 7000 features were used to perform region parameterization. Statistical analyses were performed to find correlations with PSA-level-based diagnosis that might be used to distinguish suspected (different) lesions. Further multiparametrical analysis using MIL-SVM machine learning was used to obtain greater accuracy. Results: Multiparametric classification using MIL-SVM allowed us to reach 92% accuracy. Conclusions: There is an important correlation between the textural parameters of MRI prostate images made using the PIRADS MR protocol with PSA levels > 4 mg/mL. The correlations found express dependence between image features with high cancer markers and hence the cancer risk.

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“…The scale from 1 to 5 is interpreted as follows: 1 and 2-low risk, 3-equivocal risk, 4-high, and 5-very high risk [5]. The PI-RADS system is based on elements identified during the MRI examination on a T2-weighted image (T2WI), apparent diffusion coefficient map (ADC), diffusion-weighted image (DWI), and dynamic contrast-enhanced (DCE) sequences [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Tumor Area Highlighting Using T2WI, ADC Map, and DWI Sequence Fusion on bpMRI Images for Better Prostate Cancer Diagnosis

Teică

Serbănescu

Florescu

et al. 2023

Life

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Prostate cancer is the second most common cancer in men worldwide. The results obtained in magnetic resonance imaging examinations are used to decide the indication, type, and location of a prostate biopsy and contribute information about the characterization or aggressiveness of detected cancers, including tumor progression over time. This study proposes a method to highlight prostate lesions with a high and very high risk of being malignant by overlaying a T2-weighted image, apparent diffusion coefficient map, and diffusion-weighted image sequences using 204 pairs of slices from 80 examined patients. It was reviewed by two radiologists who segmented suspicious lesions and labeled them according to the prostate imaging-reporting and data system (PI-RADS) score. Both radiologists found the algorithm to be useful as a “first opinion”, and they gave an average score on the quality of the highlight of 9.2 and 9.3, with an agreement of 0.96.

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PI-RADS 2.1 – Image Interpretation: The Most Important Updates and Their Clinical Implications

Cited by 6 publications

References 48 publications

Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

Textural Features of MR Images Correlate with an Increased Risk of Clinically Significant Cancer in Patients with High PSA Levels

Tumor Area Highlighting Using T2WI, ADC Map, and DWI Sequence Fusion on bpMRI Images for Better Prostate Cancer Diagnosis

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