PI-RADS Prostate Imaging – Reporting and Data System: 2015, Version 2

The purpose of this article is to review clinical computed tomography (CT) lung screening program elements essential to safely and effectively manage the millions of Americans at high risk for lung cancer expected to enroll in lung cancer screening programs over the next 3 to 5 years. To optimize the potential net benefit of CT lung screening and facilitate medical audits benchmarked to national quality standards, radiologists should interpret these examinations using a validated structured reporting system such as Lung-RADS. Patient and physician educational outreach should be enacted to support an informed and shared decision-making process without creating barriers to screening access. Programs must integrate smoking cessation interventions to maximize the clinical efficacy and cost-effectiveness of screening. At an institutional level, budgets should account for the necessary expense of hiring and/or training qualified support staff and equipping them with information technology resources adequate to enroll and track patients accurately over decades of future screening evaluation. At a national level, planning should begin on ways to accommodate the upcoming increased demand for physician services in fields critical to the success of CT lung screening such as diagnostic radiology and thoracic surgery. Institutions with programs that follow these specifications will be well equipped to meet the significant oncoming demand for CT lung screening services and bestow clinical benefits on their patients equal to or beyond what was observed in the National Lung Screening Trial.

is a multidisciplinary association dedicated to advancing the safe and effective use of ultrasound in medicine through professional and public education, research, development of parameters, and accreditation.

Prostate multiparametric magnetic resonance imaging (mpMRI) may be recommended for patients with a prior negative systematic biopsy (SB). However, a proportion of these patients will continue to have no prostate cancer (PCa) identified on magnetic resonance/ultrasound fusion biopsy (FB) despite abnormal mpMRI findings. In this multi-institutional, retrospective study, clinical and mpMRI parameters were assessed for 285 consecutive patients with at least 1 prior negative biopsy who underwent FB for a Prostate Imaging Reporting and Data System (PI-RADS) score of 3 to 5 at the University of Rochester Medical Center from December 2014 to December 2016, or at the University of Alabama at Birmingham from February 2014 to February 2017. Nomograms were generated for predicting benign prostate pathology on both the targeted biopsy and the concurrent SB. Benign pathology was found in 132 of 285 patients (46.3%). In a multivariate analysis, the predictors of benign prostate pathology on FB were age, prostate-specific antigen, prostate volume, and PI-RADS score. The predicted probabilities were plotted on a receiver operating characteristic curve, and the area under the curve was 0.825. The nomogram demonstrated excellent calibration and a high net benefit in a decision curve analysis. With a theoretical cutoff probability of ≥0.7 used to recommend deferment of FB, 61 of 285 patients (21.4%) would have avoided an unnecessary biopsy, and only 4 of 285 patients (1.4%) with PCa with a Gleason score ≥ 3 + 4 would have been missed. False-positive mpMRI examinations may occur in up to 46.3% of patients with a prior negative biopsy. Thus, a multi-institutional nomogram has been developed and validated for predicting benign pathology after FB in patients with a prior negative biopsy, and this may help to reduce the number of unnecessary biopsies in the setting of abnormal mpMRI findings. Cancer 2018;124:278-85. © 2017 American Cancer Society.

To evaluate the impact of the addition of quantitative apparent diffusion coefficient (ADC) data into the diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system to predict clinically significant prostate cancer (CSPCa). We retrospectively included 91 consecutive patients who underwent prostate multiparametric magnetic resonance imaging (mp-MRI) and histopathological evaluation. Mp-MRI images were reported by the PI-RADSv2 scoring system and patients were divided into groups considering the likelihood of CSPCa. ADC value and ratio were obtained. Findings were correlated with histopathological data. CSPCa was found in 41.8% of cases (n = 38). PI-RADSv2 score 3-5 yielded a sensitivity of 97.4% (95% confidence intervals 86.5-99.5), a specificity of 50.9% (37.9-63.9), and AUC of 0.74 (0.67-0.81) to predict CSPCa. ADC value < 750µm2/s and an ADC ratio < 0.62 were the most accurate thresholds for differentiation of CSPCa, with AUC of 0.81 and 0.76, respectively. Combined PI-RADSv2 score 3-5 and ADC value < 750µm2/s yielded a specificity of 84.9 (72.9-92.2), sensitivity of 70.3 (54.2-82.5), and AUC of 0.77 (0.68-0.86). Combined PI-RADSv2 score 3-5 and ADC ratio < 0.62 yielded a specificity of 86.5 (74.7-93.3), sensitivity of was 64.9 (48.8-78.2), and AUC of 0.75 (0.66-0.84). Quantitative ADC data might not be beneficial to be used routinely in mp-MR imaging as criteria to detect clinically significant lesions due to the reduced sensitivity. Instead, when prostate lesions present a PI-RADSv2 score ≥ 3, additional quantitative ADC criteria can be helpful to increase the PI-RADS score specificity.

#1320576: Comparison of Radiological Features of American Thyroid Association and American College of Radiology - Thyroid Imaging Reporting and Data System of Evaluating Thyroid Nodules - A Prospective Study in a Tertiary Care Hospital of Pakistan

10 Background: Prostate Imaging Reporting and Data System (PIRADS) Version 2 was recently issued by The American College of Radiology. Each score, from 1 to 5, corresponds to the likelihood of clinically significant cancer. We aim to evaluate the correlation between a higher PIRADS score and the presence of high grade tumor on histopathology. Methods: 300 consecutive 3T Multiparametric Prostate MRI (MP-MRI) were identified from March 26, 2012, to June 29, 2015. We reviewed patient charts and a total of 102 patients underwent either a transrectal ultrasound guided (TRUS) biopsy or a total prostatectomy after the MP-MRI. Thirty-four patients were excluded due to prior radiation or cryoablation to the prostate, leaving 68 treatment-naive patients (44-84 years). MP-MRIs were re-interpreted utilizing the new PIRADS V.2 scoring system and correlated with pathology findings. Statistical comparisons were made using R (v.3.1.2) and Fisher’s exact test. Results: High grade (Gleason 8-10) tumors were found only in MP-MRI with a PIRADS score of 5 and a higher percentage of tumor is found in MP-MRI with PIRADS scores of 4 and 5 (80%) when compared to PIRADS scores of 2 and 3 (32%). Low grade (Gleason 6-7) tumors were also found in both PIRADS 4 and 5 categories. There was a significant relationship between a higher PIRADS score and a finding of cancer on pathology (p = 0.0003, OR=0.118, 95% CI 0.03-0.41). Conclusions: The PIRADS scoring system is a useful tool in suggesting the likelihood of clinically significant cancer, with high grade tumors found only in MP-MRI with a score of PIRADS 5. However, MP-MRI and PIRADS criteria alone are not sufficient for determining clinically significant prostate cancer since both high grade and low grade tumors were found in PIRADS 5 and 4 categories. Correlation with other clinical parameters and biopsy is required for confirmation. A larger scale study would be helpful for further delineation. [Table: see text]

First published in 2019, the Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, enables stratification of these lesions with use of a numeric score based on morphologic features to indicate the risk of malignancy, and offers management guidance. This risk stratification system has subsequently been validated in retrospective studies and has yielded good interreader concordance, even with users of different levels of expertise. As use of the system increased, it was recognized that an update was needed to address certain clinical challenges, clarify recommendations, and incorporate emerging data from validation studies. Additional morphologic features that favor benignity, such as the bilocular feature for cysts without solid components and shadowing for solid lesions with smooth contours, were added to O-RADS US for optimal risk-appropriate scoring. As O-RADS US 4 has been shown to be an appropriate cutoff for malignancy, it is now recommended that lower-risk O-RADS US 3 lesions be followed with US if not excised. For solid lesions and cystic lesions with solid components, further characterization with MRI is now emphasized as a supplemental evaluation method, as MRI may provide higher specificity. This statement summarizes the updates to the governing concepts, lexicon terminology and assessment categories, and management recommendations found in the 2022 version of O-RADS US.

ObjectiveTo retrospectively determine whether the use of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) helps predict long-term outcomes for prostate cancer (PCa) patients following radical prostatectomy (RP).Materials and MethodsA total of 166 patients with localized PCa evaluated with multiparametric magnetic resonance imaging (mpMRI) at 3T before RP were enrolled. Three groups were created based on PI-RADS v2 score used to predict clinical outcomes: group A, ≥ 3; group B, ≥ 4; group C, 5. We calculated biochemical recurrence-free survival (RFS) and progression-free survival (PFS). Cox proportion hazards models were used to identify variables predictive of biochemical recurrence and disease progression.ResultsDuring a median follow-up of 9.1 years, biochemical recurrence occurred in 67 patients (40.4%) and disease progression occurred in 55 patients (33.1%). In all groups, 10-year RFS and 10-year PFS were significantly lower for PI-RADS scores ≥ 3, ≥ 4 and 5 than for score < 3, < 4 and < 5 (p <0.05), respectively. In multivariate analysis, PI-RADS score ≥ 3 and score 5 were significant independent risk marker for biochemical recurrence (hazard ratio [HR] = 5.58, p = 0.018; HR = 1.75, p = 0.033) and disease progression (HR = 3.99, p = 0.047; HR = 2.31, p = 0.040). Moderate inter-observer agreement was seen for PI-RADS scoring.ConclusionPI-RADS v2 may be used to predict long-term outcomes following RP in PCa.

Assessment of thyroid nodule malignancy risk in medical radiation workers using ACR TI-RADS

IntroductionThyroid nodules are exceedingly common, occurring in up to 76% of adults. Less than 10% are palpable, and the majority are detected incidentally with an estimated prevalence of 68%, 25%, and 18% using ultrasound (US), CT, and MRI, respectively. The rising use of imaging over the last four decades has led to a significant increase in nodule detection or ‘over-identification,’ fine-needle aspiration (FNA), a higher reported incidence of thyroid cancer, and thyroidectomy. The purpose of this study is to provide a descriptive experience with thyroid nodule FNAs one year prior and one year after the implementation of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) at a prototypical community hospital.MethodsA total of 104 patients with 114 thyroid nodules underwent US-guided FNA at Bluewater Health from January 1, 2018, to March 31, 2020, with available cytological results (The Bethesda System). The study population was divided into two cohorts (January 1, 2018, to December 31, 2018 - ‘local best practice cohort’, and March 1, 2019, to March 31, 2020 - ‘ACR TI-RADS cohort’) based on the implementation of the ACR TI-RADS guidelines in March 2019.ResultsThe local best practice cohort (January 1, 2018, to December 31, 2018) comprised 57 thyroid nodules in 52 patients (mean age 66 ± 12; 40 Women). The ACR TI-RADS cohort (March 1, 2019, to March 31, 2020) comprised 57 thyroid nodules in 52 patients (mean age 61 ± 16; 41 Women). There were no statistical differences with respect to age, gender, or thyroid nodule location. Our results show a dramatic decrease in the number of unnecessary FNAs if ACR TI-RADS was implemented from January to December 2018. Thirty (52.6%) of the previously sampled thyroid nodules using the local best practice guidelines would have been followed as per ACR TI-RADS.ConclusionACR TI-RADS is a reliable classification system in routine practice that significantly reduces the number of unnecessary thyroid FNAs with higher specificity compared to local best practice guidelines.

Accuracy and Variability of Prostate Multiparametric Magnetic Resonance Imaging Interpretation Using the Prostate Imaging Reporting and Data System: A Blinded Comparison of Radiologists

Background. Prostate multiparametric magnetic resonance imaging is widely recommended prior to biopsy in clinical practice, with the Prostate Imaging Reporting and Data System (PI-RADS) as the standard tool for guiding diagnosis and treatment decisions. However, analyzing multiparametric magnetic resonance imaging data demands substantial expertise, and the process is often time-intensive and cognitively challenging, leading to variability between and within readers.Aim. To create a deep learning-based computer-aided diagnosis (DL-CAD) system to minimize manual influence on PI-RADS score determination.Materials and methods. Between January 2020 and May 2024, 108 patients with histopathologically confirmed prostate cancer with PI-RADS scores 4–5 were retrospectively selected for model development and training. Additionally, 28 benign cases were included for model validation. Different prostate zones were labeled following PI-RADS v2.1 guidelines to facilitate model selection. Manual segmentation of prostate regions and lesions was performed on T2-weighted (T2W) sequences, and a 3D U-Net architecture was implemented for the DL model using the MONAI framework. Diagnostic performance was assessed using Python-based statistical analysis.Results. The DL-CAD system achieved average accuracy of 78 %, sensitivity of 60 %, and specificity of 84 % for lesion detection. The Dice similarity coefficient for prostate segmentation was 0.71, and the AUROC was 81.16 %.Conclusion. The DL-CAD system demonstrates promise for patients with clinically significant prostate cancer by improving diagnostic accuracy. While it exhibits high specificity, further improvements of sensitivity and segmentation accuracy are necessary. These improvements could be achieved through the use of larger datasets and advanced deep learning techniques, such as transfer learning or ensemble learning, which could enhance sensitivity without compromising specificity. Further multicenter validation is required to accelerate the integration of this system into clinical practice.

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care. Keywords: Coronary Artery Disease, Coronary CTA, CAD-RADS, Reporting and Data System, Stenosis Severity, Report Standardization Terminology, Plaque Burden, Ischemia Supplemental material is available for this article. This article is published synchronously in Radiology: Cardiothoracic Imaging, Journal of Cardiovascular Computed Tomography, JACC: Cardiovascular Imaging, Journal of the American College of Radiology, and International Journal for Cardiovascular Imaging. © 2022 Society of Cardiovascular Computed Tomography. Published by RSNA with permission.

Advancements in prostate imaging, particularly multiparametric magnetic resonance imaging (mpMRI), have transformed the diagnosis and monitoring paradigms for prostate cancer (PCa). However, considerable interobserver variability has been reported,emphasizing the importance of standardized scoring and reporting systems. The Prostate Imaging Reporting and Data System (PI-RADS), along with quality assurance protocols such as Prostate Imaging Quality (PI-QUAL), has enhanced the diagnostic accuracy of mpMRI. While mpMRI effectively identifies extraprostatic extension, emerging hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) and radio labeled prostate-specific membrane antigen (PSMA) tracers have improved metastasis detection. In active surveillance settings, the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) recommendations enable the assessment of longitudinal PCa changes. Post-treatment evaluation can also employ dedicated frameworks, such as the Prostate Imaging for Recurrence Reporting (PI-RR) after radical prostatectomy, and either the Prostate Imaging after Focal Ablation (PI-FAB) or the Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET). This article reviews key aspects of mpMRI, including structured interpretation frameworks beyond the widely recognized PI-RADS.

Objective: Objective: To evaluate the accuracy of radiology team recommendations compared with histopathology outcomes using Breast Imaging Reporting and Data System (BI-RADS) categories in breast ultrasound (US). Study Design: Retrospective cross-sectional study. Place and Duration: Radiology Department, Mian Meer Hospital, Lahore, in collaboration with Mayo Hospital, Lahore, Pathology Department, from 02 January 2021 to 03 June 2022. Methodology: Female patients referred from the Well Women Clinic (WWC), which provides breast health services to the local community, and who underwent breast ultrasound performed by consultant radiologists, were included. Patients had USS scans by non-consultants. Male and female patients referred from sources other than the Well Women Clinic were excluded. BI-RADS categories 1–5 were assigned and compared with American College of Radiology (ACR) BI-RADS guidelines and with histopathology reports where available. Category 0 was excluded due to incomplete data. SPSS v29 was used for statistical analysis. Results: Of 48,432 ultrasound referrals, 539 were from WWC; 361 met the inclusion criteria. Mean age was 36.23 ± 13.18 years. BI-RADS distribution: Category 1 = 56.5%, Categories 2–3 = 19.1%, Categories 4–5 = 24.4%. Agreement with ACR BI-RADS guideline recommendations was significant (χ²=475.3, p&lt;0.0001), with accuracies of 100% for discharge, 97% for follow-up, and 97% for referral. Histopathology confirmed malignancy in 41 patients (11.4%). Sensitivity and specificity for malignancy detection were 76% and 95% respectively, with overall diagnostic accuracy of 93%. Conclusion: BI-RADS-based breast ultrasound by consultant radiologists demonstrated high accuracy against histopathology and guideline recommendations and supporting its role as a reliable first-line diagnostic tool. Keywords: Breast Imaging Reporting and Data System, Breast ultrasound, Histopathology correlation, Benign breast disease, Breast cancer diagnosis. How to Cite This: Yousaf A, Zaidi NS, Rauf F, Ahmed R, Malik MR, Abbas S. Accuracy of Recommendations and Histopathology Results with Breast Imaging Reporting and Data System (BI-RADS) – A Retrospective Study. Isra Med J. 2025; 17(1):23-27. DOI: https://doi.org/10.55282/imj.oa1425