Radiology Reports With Hyperlinks Improve Target Lesion Selection and Measurement Concordance in Cancer Trials

Abstract

Objective: Radiology reports often lack the measurements of target lesions that are needed for oncology clinical trials. When available, the measurements in the radiology reports often do not match those in the records used to calculate therapeutic response. This study assessed the clinical value of hyperlinked tumor measurements in multimedia-enhanced radiology reports in the PACS and the inclusion of a radiologist assistant in the process of assessing tumor burden.

Materials and methods: We assessed 489 target lesions in 232 CT examinations of 71 patients with metastatic genitourinary cancer enrolled in two therapeutic trials. We analyzed target lesion selection and measurement concordance between oncology records (used to calculate therapeutic response) and two types of radiology reports in the PACS: multimedia-enhanced radiology reports and text-only reports. For statistical tests, we used the Wilcoxon signed rank, Wilcoxon rank sum test, and Fisher method to combine p values from the paired and unpaired results. The Fisher exact test was used to compare overall measurement concordance.

Results: Concordance on target lesion selection was greater for multimedia-enhanced radiology reports (78%) than the text-only reports (52%) (p = 0.0050). There was also improved overall measurement concordance with the multimedia-enhanced radiology reports (68%) compared with the text-only reports (38%) (p < 0.0001).

Conclusion: Compared with text-only reports, hyperlinked multimedia-enhanced radiology reports improved concordance of target lesion selection and measurement with the measurements used to calculate therapeutic response.

Keywords: Response Evaluation Criteria in Solid Tumors (RECIST) 1.1; hyperlinks; multimedia; radiology reports; tumor assessment.

Fig. 1

Top row shows old workflow, and bottom row shows new workflow. For old workflow, typical tumor assessment started with selection and measurements of index (arbitrary) lesion by radiologist. Lesion selected by radiologist and lesion measurements were often different from information in electronic medical records, which indicated duplicated efforts. Inconsistent text-only radiology reports that compare measurements with measurements from only prior examination (instead of baseline examination) were not adequate for oncologists to assess tumor burden. To record measurement data, oncology registrars (nurse practitioners, physician assistants, oncologists) would handwrite data on Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 worksheets. Later, staff would type data from worksheets into cancer central clinical database. For new workflow design, radiologist assistant helps close communication gaps between radiologists and oncologists by verifying date of baseline examination, selection and measurements of target lesions, and comparisons of lesions over time. Hyperlinked measurements facilitate observation and analysis of target lesions for oncologists, potentially obviating need for handwriting and dual data entry.

Fig. 2

Bar graphs show distributions of target lesions recorded in electronic medical record (EMR) and in radiology reports, regardless of report type, by anatomic location. Other = muscle, kidney, spleen, pancreas, and adrenal glands. A, Target lesions recorded in EMR. Of target lesions recorded in EMRs, 40% were lymph node lesions; 28%, lung lesions; 12%, liver lesions; and 20%, other. B, Of target lesions reported in radiology reports in which measurements were discrepant with EMR, 33% were lymph node lesions; 30%, lung lesions; 10%, liver lesions; and 27%, other.

Fig. 3

Sample multimedia-enhanced radiology report shows data from baseline and four follow-up CT examinations of 59-year-old man with metastatic urothelial carcinoma. A, Sample multimedia-enhanced radiology report in which hyperlinked measurements (arrows) direct oncologists to each measured lesion (3D location, lesion name, series number, and image number). Radiologist dictates “hyperlink” after PACS measurement that automatically imports hyperlink along with series and slice numbers, saving time and reducing errors. Radiologist is also prompted to target lesions that are followed by oncologists. In this case, radiologist identified three target lesions: B01 (F06), B03 (F01), and B24 (F05). Hyperlinks and annotations in coregistered images also direct radiologists to measure same lesions on next follow-up examination for consistency. GU = genitourinary, GI = gastrointestinal. Sample multimedia-enhanced radiology report shows data from baseline and four follow-up CT examinations of 59-year-old man with metastatic urothelial carcinoma. B, Table shows metadata for three target lesions B01 (F06), B03 (F01), and B24 (F05) including measurements, lesion names, series and image numbers, and automated Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 calculations for baseline and four follow-up examinations. Numbers indicating lesion sizes and size changes over time are plotted on graph that radiologist and oncologist can read quickly. Data in parentheses show changes compared with baseline. Dashes (--) indicate not applicable. RT = right, LT = left, DT = doubling time, B23 = finding (lesion measurement) on current follow-up examination.

Fig. 3

Sample multimedia-enhanced radiology report shows data from baseline and four follow-up CT examinations of 59-year-old man with metastatic urothelial carcinoma. A, Sample multimedia-enhanced radiology report in which hyperlinked measurements (arrows) direct oncologists to each measured lesion (3D location, lesion name, series number, and image number). Radiologist dictates “hyperlink” after PACS measurement that automatically imports hyperlink along with series and slice numbers, saving time and reducing errors. Radiologist is also prompted to target lesions that are followed by oncologists. In this case, radiologist identified three target lesions: B01 (F06), B03 (F01), and B24 (F05). Hyperlinks and annotations in coregistered images also direct radiologists to measure same lesions on next follow-up examination for consistency. GU = genitourinary, GI = gastrointestinal. Sample multimedia-enhanced radiology report shows data from baseline and four follow-up CT examinations of 59-year-old man with metastatic urothelial carcinoma. B, Table shows metadata for three target lesions B01 (F06), B03 (F01), and B24 (F05) including measurements, lesion names, series and image numbers, and automated Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 calculations for baseline and four follow-up examinations. Numbers indicating lesion sizes and size changes over time are plotted on graph that radiologist and oncologist can read quickly. Data in parentheses show changes compared with baseline. Dashes (--) indicate not applicable. RT = right, LT = left, DT = doubling time, B23 = finding (lesion measurement) on current follow-up examination.

Fig. 4

Target lesion selection (A), measurement concordance (B), and mean time for tumor measurement extraction from radiology reports (C). A, Multimedia-enhanced radiology reports improved target lesion selection concordance over text-only reports (78% vs 52%, respectively). B, Multimedia-enhanced radiology reports improved target lesion measurement concordance compared with text-only reports (68% vs 38%). C, Mean time to extract individual lesion measurements from multimedia-enhanced radiology reports was almost one third of that required to extract individual lesion measurements from text-only reports for radiologist assistant.