LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials

Introduction

Oncology clinical trials are widely conducted in both the academic and private sector and are commonly multicenter due to increased statistical power gained from large patient accrual at more than one site. In the context of both large multicenter trials with blinded central review and early-phase trials at a single site, criteria-specific imaging assessment is required at the site level to determine whether a patient meets enrollment criteria at baseline and continued eligibility at subsequent follow-up assessments. However, local clinical imaging infrastructures face several challenges that are difficult to address to meet these requirements (1). Tumor metrics are often needed at the time of office visit, which can place additional demands on radiologists and clinical workflow when rapid turnaround of complex assessments using varied response criteria is needed. Often times, radiology and cancer center staff struggle to balance clinical trial requirements on top of their daily clinical responsibilities and have few available resources to offset the continuously evolving needs of clinical trials. Many sites still use paper forms or extract measurements from clinical imaging reports, whereas some oncology investigators make their own measurements, raising concerns about objectivity, accuracy, and longitudinal consistency. The imaging metrics obtained in these scenarios are generally not verifiable for audits and do not easily connect back to annotated imaging records.

Moreover, studies have shown that there is significant discordance between oncologist expectations and radiology practice pattern regarding the types of imaging findings that should be included in a radiology report (2–3). For example, one study found that only 26% of radiology reports for follow-up studies in patients with solid tumors included sufficient information to determine response according to RECIST guidelines (4–5). These deficiencies may impact data access, integrity, and validation, consequently altering patient care and trial outcomes. Because of the growing workflow challenges and performance demands of clinical trials, advanced medical imaging informatics are critically needed at cancer centers and other medical centers conducting clinical trials to ensure reliable, reproducible, and protocol-compliant longitudinal imaging assessments (6).

The Tumor Imaging Metrics Core (TIMC; http://www.tumormetrics.org) was established in 2004 as a shared resource to address the needs of the Dana-Farber/Harvard Cancer Center (Boston, MA) by providing centralized imaging review services for oncology clinical trials. To promote communication between oncology and radiology teams, and enhance review and reporting processes, timeliness, and quality, the TIMC developed and implemented an informatics infrastructure, branded Precision Imaging Metrics (PIM; https://www.precisionmetrics.org). PIM provides cancer centers with a clinical trial informatics platform tailored to the specific workflow needs of site reviews and currently has been adopted by seven NCI-designated Cancer Centers around the country, with several other sites considering implementing this system. Architecturally, the PIM solution consists of two interconnected software applications: a web-based workflow informatics management system and an integrated desktop image analysis platform. Although the web-based system is robust and easily accessible, the desktop application must be installed on every computer where image reviews take place and must be part of the hospital network to gain direct access to the hospital's imaging archive, adding IT support requirements at each site performing image assessments. These networking requirements also restrict image reviews to predetermined workstations, reducing the efficiency for radiologists and limiting flexibility with regards to location or working hours.