Optimizing Radiology Peer Review: A Mathematical Model for Selecting Future Cases Based on Prior Errors

Introduction: Peer review is an essential process for physicians because it facilitates improved quality of patient care and continuing physician learning and improvement. However, peer review often is not well received by radiologists, who note that it is time intensive, subjective, and lacks demonstrable impact on patient care. Current advances in peer review include the RADPEER system with its standardization of discrepancies and incorporation of the peer review process into the PACS itself. Our purpose was to build on RADPEER and similar systems by using a mathematical model to optimally select the types of cases to be reviewed, for each radiologist undergoing review, based on the past frequency of interpretive error, likelihood of morbidity from an error, financial cost of an error, and time required for the reviewing radiologist to interpret the study. Methods: We compiled 612,890 preliminary radiology reports authored by residents and attendings of a large tertiary-care medical center from 1999 to 2004. Discrepancies between preliminary and final interpretations were classified by severity and validated by re-review of major discrepancies. A mathematical model was then used to calculate, for each author of a preliminary report, the combined morbidity and financial costs of expected errors across three modalities (MRI, CT, and CR) and four departmental divisions (Neuroradiology and Abdominal, Musculoskelatal, and Thoracic Imaging). Results: A customized report was generated for each on-call radiologist which determined the category (modality and body part) with the highest total cost function. A universal total cost based on probability data from all radiologists was also compiled. Conclusion: The use of mathematical models to guide case selection could optimize the efficiency and effectiveness of physician time spent on peer review and produce more concrete and meaningful feedback to radiologists undergoing peer review

Interrater Reliability of NI-RADS on Posttreatment PET/Contrast-enhanced CT Scans in Head and Neck Squamous Cell Carcinoma

Purpose: To evaluate the interrater reliability among radiologists examining posttreatment head and neck squamous cell carcinoma (HNSCC) fluorodeoxyglucose PET/contrast-enhanced CT (CECT) scans using Neck Imaging Reporting and Data System (NI-RADS). Materials and Methods: In this retrospective study, images in 80 patients with HNSCC who underwent posttreatment surveillance PET/CECT and immediate prior comparison CECT or PET/CECT (from June 2014 to July 2016) were uploaded to the American College of Radiology's cloud-based website, Cortex. Eight radiologists from seven institutions with variable NI-RADS experience independently evaluated each case and assigned an appropriate prose description and NI-RADS category for the primary site and the neck site. Five of these individuals were experienced readers (> 5 years of experience), and three were novices (< 5 years of experience). In total, 640 lexicon-based and NI-RADS categories were assigned to lesions among the 80 included patients by the eight radiologists. Light generalization of Cohen κ for interrater reliability was performed. Results: Of the 80 included patients (mean age, 63 years ± 10 [standard deviation]), there were 58 men (73%); 60 patients had stage IV HNSCC (75%), and the most common tumor location was oropharynx (n = 32; 40%). Light κ for lexicon was 0.30 (95% CI: 0.23, 0.36) at the primary site and 0.31 (95% CI: 0.24, 0.37) at the neck site. Light κ for NI-RADS category was 0.55 (95% CI: 0.46, 0.63) at the primary site and 0.60 (95% CI: 0.48, 0.69) at the neck site. Percent agreement between lexicon and correlative NI-RADS category was 84.4% (540 of 640) at the primary site and 92.6% (593 of 640) at the neck site. There was no significant difference in interobserver agreement among the experienced versus novice raters. Conclusion: Moderate agreement was achieved among eight radiologists using NI-RADS at posttreatment HNSCC surveillance imaging

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Practical imaging informatics : foundations and applications for medical imaging

This new edition is a comprehensive source of imaging informatics fundamentals and how those fundamentals are applied in everyday practice. Imaging Informatics Professionals (IIPs) play a critical role in healthcare, and the scope of the profession has grown far beyond the boundaries of the PACS. A successful IIP must understand the PACS itself and all the software systems networked together in the medical environment. Additionally, an IIP must know the workflows of all the imaging team members, have a base in several medical specialties and be fully capable in the realm of information technology. Practical Imaging Informatics has been reorganized to follow a logical progression from basic background information on IT and clinical image management, through daily operations and troubleshooting, to long-term planning. The book has been fully updated to include the latest technologies and procedures, including artificial intelligence and machine learning. Written by a team of renowned international authors from the Society for Imaging Informatics in Medicine and the European Society of Medical Imaging Informatics, this book is an indispensable reference for the practicing IIP. In addition, it is an ideal guide for those studying for a certification exam, biomedical informaticians, trainees with an interest in informatics, and any professional who needs quick access to the nuts and bolts of imaging informatics

Evidence for an adverse impact of remote readouts on radiology resident productivity: Implications for training and clinical practice.

After their rapid adoption at the onset of the coronavirus pandemic, remote case reviews (remote readouts) between diagnostic radiology residents and their attendings have persisted in an increasingly remote workforce, despite relaxing social distancing guidelines. Our objective was to evaluate the impact of the transition to remote readouts on resident case volumes after the recovery of institutional volumes. We tabulated radiology reports co-authored by first-to-third-year radiology residents (R1-R3) between July 1 and December 31 of the first pandemic year, 2020, and compared to the prior two pre-pandemic years. Half-years were analyzed because institutional volumes recovered by July 2020. Resident volumes were normalized to rotations, which were in divisions categorized by the location of the supervising faculty during the pandemic period; in 'remote' divisions, all faculty worked off-site, whereas 'hybrid' divisions had a mix of attendings working on-site and remotely. All residents worked on-site. Data analysis was performed with Student's t test and multivariate linear regression. The largest drops in total case volume occurred in the two remote divisions (38% [6,086 to 3,788], and 26% [11,046 to 8,149]). None of the hybrid divisions with both in-person and remote supervision decreased by more than 5%. With multivariate regression, a resident assigned to a standardized remote rotation in 2020 would complete 32% (253 to 172) fewer studies than in identical pre-pandemic rotations (coefficent of -81.6, p = .005) but would be similar for hybrid rotations. R1 residents would be expected to interpret 40% fewer (180 to 108) cases on remote rotations during the pandemic (coefficient of -72.3, p = .007). No significant effect was seen for R2 or R3 residents (p = .099 and p = .29, respectively). Radiology residents interpreted fewer studies during remote rotations than on hybrid rotations that included in-person readouts. As resident case volume is correlated with clinical performance and board pass rate, monitoring the readout model for downstream educational effects is essential. Until evidence shows that educational outcomes remain unchanged, radiology residencies may wish to preserve in-person resident readouts, particularly for junior residents