Engaging nurse practitioners and physician assistants to improve patient care and drive productivity in a radiology consult practice at a comprehensive cancer center.

BACKGROUND: The demand for health care in the United States is increasing because of an aging population and an increase in the number of individuals insured. This has led to requests to revamp the primary care infrastructure fundamentally. LOCAL PROBLEM: The optimal use of nurse practitioners (NPs) and physician assistants (PAs) is still a subject of debate, but recently, it was reported that for many medical conditions, NP and PA-managed care outcomes are consistent with physician-managed care outcomes. METHODS: Radiologists' productivity was measured according to relative value units (RVUs)/shift and professional billing changes. Patient care metrics measured were prescribed protocol to patient appointment lead time and number of same-day prescribed imaging protocol changes. INTERVENTIONS: The focus was on radiologists' productivity and patient care for three months before and three months after integrating NP and PA into our abdominal radiology consult service. RESULTS: We observed significant increases in the mean RVUs/shift (15.2 ± 0.9 vs. 6.2 ± 1.8; p = .02), studies read per shift (10.1 ± 0.5 vs. 4.4 ± 1.5; p = .003), revenue per shift hour ($756.20 ± 55.40 vs. $335.40 ± 32.60; p = .007), and protocol prescription to patient appointment lead time (39.3 ± 6.7 days vs. 16.3 ± 2.9 days; p = .005) and saw significant decreases in the mean prescribed CT (19.3 ± 0.6 vs. 3.3 ± 0.6; p = .001) and MRI (11.7 ± 0.6 vs. 8.30 ± 0.12; p = .011) same day protocol changes in NP and PA integrated workflow. CONCLUSIONS: These findings suggest that NP and PA can be effectively integrated into the abdominal radiology consult service, increasing radiologists' productivity and enhancing clinical care.

Baseline CT-based Radiomic Features Aid Prediction of Nodal Positivity after Neoadjuvant Therapy in Pancreatic Cancer.

Purpose To study the association between CT-derived textural features of pancreatic cancer and patient outcome. Materials and Methods This retrospective study evaluated 54 patients (median age, 62 years [range, 40-88 years]; 32 men) with pancreatic cancer who underwent chemoradiation followed by surgical resection and lymph node dissection from May 2012 to June 2016. Three-dimensional segmentation of the pancreatic tumor was performed on baseline dual-energy CT images: 70-keV pancreatic parenchymal phase (PPP) images and iodine material density images. Then, 15 and 19 radiomic features were extracted from each phase, respectively. Logistic regression with elastic net regularization was used to select textural features associated with outcome, and receiver operating characteristic analysis evaluated feature performance. Survival curves were generated using the Kaplan-Meier method. Results The feature of integral total (∫ T), representing the mean intensity in Hounsfield units times the contour volume in milliliters of PPP imaging (hereafter, "∫ T (HU·mL) (PPP)"), is inversely associated with posttherapy pathologic lymph node (ypN) category. A threshold ∫ T (HU·mL) (PPP) less than 507.85 predicted ypN1-2 classification with 96% sensitivity, 34% specificity, and area under the curve of 0.61. Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased overall survival (median, 2.8 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (one event at 3.4 years) (P = .006). Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased progression-free survival (median, 1.5 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (median, 2.7 years) (P = .001). Conclusion A CT-based radiomic signature may help predict ypN category in patients with pancreatic cancer. Keywords: CT-Dual Energy, Abdomen/GI, Pancreas, Tumor Response, Outcomes Analysis © RSNA, 2022 Supplemental material is available for this article.

Streamlining the Quantitative Metrics Workflow at a Comprehensive Cancer Center.

INTRODUCTION: The objective of the project was to describe an efficient workflow for quantifying and disseminating tumor imaging metrics essential for assessing tumor response in clinical therapeutic trials. The clinical research utility of integration of the workflow into the electronic health record for radiology reporting was measured before and after the intervention. MATERIALS AND METHODS: A search of institutional clinical trial databases was performed to identify trials with radiology department collaborators. Investigator initiated trials, or those which lacked a standardized or automated system of collaboration with the research team were selected for the study. A web based application integrated in the electronic health record platform, the Quantitative Imaging Analysis Core (QIAC) initiative was established as a divisional resource with institutional support to provide standardized and reproducible imaging metrics across the institution. The turnaround time for radiology reports before (phase 1) and after web based application workflow (phase 2) was measured. During our test period (November 2014 to June 2015), a total of 68 requests with 37 from phase 1 and 31 from phase 2 were analyzed for patients who were enrolled in prospective clinical therapeutic interventional trials. RESULTS: The mean turnaround time for generation of quantitative tumor metric results after implementation of the web based QIAC workflow (phase 2) was significantly lower than prior (phase 1) (15.9 ± 21.3 vs 31.7 ± 35.4 hours, p= 0.0005). The mean time from the scan to the preliminary assessment was 19.6 ± 25.6 hours before and significantly reduced to 8.0 ± 9.9 hours with implementation of web based QIAC workflow. CONCLUSION: Implementation of a web based QIAC workflow platform enabled significantly improved turnaround time for quantitative tumor metrics reports and enabled faster access to the reports.

White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part I, AJCC staging system, NCCN guidelines, and borderline resectable disease.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Accurate staging of PDAC is an important initial step in the development of a stage-specific treatment plan. Different staging systems/consensus statements convened by different societies and academic practices are currently used. The most recent version of the American Joint Committee on Cancer (AJCC) tumor/node/metastases (TNM) staging system for PDAC has shifted its focus from guiding management to assessing prognosis. In order to preoperatively define the resectability of PDAC and to guide management, additional classification systems have been developed. The National Comprehensive Cancer Network (NCCN) guidelines, one of the most commonly used systems, provide recommendations on the management and the determination of resectability for PDAC. The NCCN divides PDAC into three categories of resectability based on tumor-vessel relationship: 'resectable,' 'borderline resectable,' and 'unresectable'. Among these, the borderline disease category is of special interest given its evolution over time and the resulting variations in the definition and the associated recommendations for management between different societies. It is important to be familiar with the evolving criteria, and treatment and follow-up recommendations for PDAC. In this article, the most current AJCC staging (8th edition), NCCN guidelines (version 2.2019-April 9, 2019), and challenges and controversies in borderline resectable PDAC are reviewed.