Is Likert better than PI-RADS at predicting prostate cancer on MRI and can a mathematical algorithm achieve similar results?

BACKGROUND: Prostate Imaging Reporting & Data System (PI-RADS) is an internationally recognized system to quantify risk of prostate cancer on magnetic resonance imaging (MRI). However, studies have suggested methods to improve predictive accuracy. PURPOSE: To assess two different methods that aim to improve the accuracy of PI-RADS scores: a subjective Likert score given by experienced reporters, and an objective Calculated Adjustment of PI-RADS Equivocal Score (CAPES). MATERIAL AND METHODS: Five experienced reporters in a quaternary referral unit used a standardized reporting template to prospectively collect PI-RADS and Likert scores for 1467 multiparametric MRI (mpMRI) scans between January 2021 and June 2022. Histology results were recorded for patients who underwent trans-perineal biopsy. The CAPES tool was retrospectively applied to the cases scoring PI-RADS 3. A theoretical standardized biopsy protocol (assuming all patients scoring ≥3 were referred for biopsy) was used to compare the three scoring systems for sensitivity, specificity, and positive predictive value (PPV). RESULTS: Across all reporters, significantly fewer equivocal "3" scores were given using Likert (15.7%) or CAPES (2.2%) compared to PI-RADS (24.1%). Assuming a protocol where all patients scoring ≥3 were biopsied, Likert had a higher specificity (69.0% vs. 54.4%), sensitivity (98.3% vs. 97.7%), and PPV (49.9% vs. 40.3%) than PI-RADS for identifying ISUP ≥2 cancer. The CAPES tool had an even higher specificity (81.4%) and PPV (61.2%) with only a slightly lower sensitivity (93.4%) resulting in 37.1% (n = 316) fewer biopsies than PI-RADS, and 22.4% (n = 155) fewer biopsies than Likert across 1467 patients. CONCLUSIONS: Compared to PI-RADS scoring, Likert scoring or CAPES can result in fewer equivocal scores, greater PPV, and fewer unnecessary biopsies.

Does including histological outcomes in a multiparametric MRI report improve prostate biopsy decision making?

OBJECTIVES: To see if inserting audited histological outcome data for each Likert score into prostate mpMRI reports was helpful for clinicians counselling patients and influenced prostate biopsy uptake. METHODS: A single radiologist reported 791 mpMRI scans for query prostate cancer between 2017 and 2019. A structured template which included histological outcome data from this cohort was devised and included in 207 mpMRI reports between January and June 2021. The outcomes of the new cohort were compared with the historical cohort, and with 160 contemporaneous reports without histological outcome data from the four other radiologists in the department. The opinion of this template was sought from referring clinicians who counselled patients. RESULTS: The proportion of patients biopsied fell from 58.0 to 32.9% overall between the n = 791 cohort and the n = 207 cohort. This was most noticeable in those scoring Likert 3, where the proportion biopsied fell from 78.4 to 42.9%. This reduction was also seen when comparing the biopsy rates of patients scored Likert 3 by other reporters in a contemporaneous n = 160 cohort without the audit information (65.2%) with the n = 207 cohort (42.9%). 100% of counselling clinicians were in favour and 66.7% said it gave them greater confidence to advise the patient when they did not need a biopsy. CONCLUSION: Fewer low-risk patients choose unnecessary biopsies when audited histological outcomes for the radiologist's Likert scores are included in mpMRI reports. ADVANCES IN KNOWLEDGE: Clinicians welcome reporter-specific audit information in mpMRI reports which could result in fewer biopsies.

Predictive radiomics signature for treatment response to nivolumab in patients with advanced renal cell carcinoma.

INTRODUCTION: The anti-programmed cell death protein-1 (PD-1) immune checkpoint inhibitor nivolumab is currently approved for the treatment of patients with metastatic renal cell carcinoma (mRCC); approximately 25% of patients respond. We hypothesized that we could identify a biomarker of response using radiomics to train a machine learning classifier to predict nivolumab response outcomes. METHODS: Patients with mRCC of different histologies treated with nivolumab in a single institution between 2013 and 2017 were retrospectively identified. Patients were labelled as responders (complete response [CR]/partial response [PR]/durable stable disease [SD]) or non-responders based on investigator tumor assessment using RECIST 1.1 criteria. For each patient, lesions were contoured from pre-treatment and first post-treatment computed tomography (CT) scans. This information was used to train a radial basis function support vector machine classifier to learn a prediction rule to distinguish responders from non-responders. The classifier was internally validated by a 10-fold nested cross-validation. RESULTS: Thirty-seven patients were identified; 27 (73%) met the inclusion criteria. One hundred and four lesions were contoured from these 27 patients. The median patient age was 56 years, 78% were male, 89% had clear-cell histology, 89% had prior nephrectomy, and 89% had prior systemic therapy. There were 19 responders vs. eight non-responders. The lesions selected were lymph nodes (60%), lung metastases (23%), and renal/adrenal metastases (17%). For the classifier trained on the baseline CT scans, 69% accuracy was achieved. For the classifier trained on the first post-treatment CT scans, 66% accuracy was achieved. CONCLUSIONS: The set of radiomic signatures was found to have limited ability to discriminate nivolumab responders from non-responders. The use of novel texture features (two-point correlation measure, two-point cluster measure, and minimum spanning tree measure) did not improve performance.

Role of Interventional Procedures in Obstetrics and Gynecology.

Radiological guided intervention techniques are discussed in obstetric and gynecologic patients. Fallopian tube recanalization, postpartum hemorrhage control, techniques of treating uterine leiomyomas, pelvic congestion treatment, and the use of percutaneous and transvaginal ultrasonography-guided aspirations and biopsy are covered. These techniques use basic radiological interventional skills and show how they are adapted for use in the female pelvis.

Calot's triangle.

Calot's triangle is an anatomical landmark of special value in cholecystectomy. First described by Jean-François Calot as an "isosceles" triangle in his doctoral thesis in 1891, this anatomical space requires careful dissection before the ligation and division of the cystic artery and cystic duct during cholecystectomy. The modern definition of the boundaries of Calot's triangle varies from Calot's original description, although the exact timing of this change is not entirely clear. The structures within Calot's triangle and their anatomical relationships can present the surgeon with difficulties, particularly when anatomical variations are encountered. Sound knowledge of the normal anatomy of the extrahepatic biliary tract and vasculature, as well as understanding of congenital variation, is thus essential in the prevention of iatrogenic injury. The authors describe the normal anatomy of Calot's triangle and common anatomical anomalies. The incidence of structural injury is discussed, and new techniques in surgery for enhancing the visualisation of Calot's triangle are reviewed. © .