Streamlining the Quantitative Metrics Workflow at a Comprehensive Cancer Center

Sujaya H Rao; Mayur Virarkar; Wei Tse Yang; Brett W Carter; T Alex Liu; David Piwnica-Worms; Priya R Bhosale

doi:10.1016/j.acra.2020.06.014

Streamlining the Quantitative Metrics Workflow at a Comprehensive Cancer Center

Acad Radiol. 2021 Oct;28(10):1401-1407. doi: 10.1016/j.acra.2020.06.014. Epub 2020 Jul 21.

Authors

Sujaya H Rao¹, Mayur Virarkar², Wei Tse Yang², Brett W Carter², T Alex Liu³, David Piwnica-Worms⁴, Priya R Bhosale⁵

Affiliations

¹ Office of Translational & Clinical Research, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas.
² Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.
³ Manager, Information Services, Oncology Care and Research Information System, The University of Texas MD Anderson Cancer Center, Houston, Texas.
⁴ Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas.
⁵ Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030. Electronic address: priya.bhosale@mdanderson.org.

PMID: 32709584
DOI: 10.1016/j.acra.2020.06.014

Abstract

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.

Keywords: QIAC; Quantitative imaging; Response assessment; Tumor metrics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Benchmarking*
Humans
Neoplasms* / diagnostic imaging
Prospective Studies
Workflow