Resources Required for Semi-Automatic Volumetric Measurements in Metastatic Chordoma: Is Potentially Improved Tumor Burden Assessment Worth the Time Burden?

Abstract

The Response Evaluation Criteria in Solid Tumors (RECIST) is the current standard for assessing therapy response in patients with malignant solid tumors; however, volumetric assessments are thought to be more representative of actual tumor size and hence superior in predicting patient outcomes. We segmented all primary and metastatic lesions in 21 chordoma patients for comparison to RECIST. Primary tumors were segmented on MR and validated by a neuroradiologist. Metastatic lesions were segmented on CT and validated by a general radiologist. We estimated times for a research assistant to segment all primary and metastatic chordoma lesions using semi-automated volumetric segmentation tools available within our PACS (v12.0, Carestream, Rochester, NY), as well as time required for radiologists to validate the segmentations. We also report success rates of semi-automatic segmentation in metastatic lesions on CT and time required to export data. Furthermore, we discuss the feasibility of volumetric segmentation workflow in research and clinical settings. The research assistant spent approximately 65 h segmenting 435 lesions in 21 patients. This resulted in 1349 total segmentations (average 2.89 min per lesion) and over 13,000 data points. Combined time for the neuroradiologist and general radiologist to validate segmentations was 45.7 min per patient. Exportation time for all patients totaled only 6 h, providing time-saving opportunities for data managers and oncologists. Perhaps cost-neutral resource reallocation can help acquire volumes paralleling our example workflow. Our results will provide researchers with benchmark resources required for volumetric assessments within PACS and help prepare institutions for future volumetric assessment criteria.

Trial registration: ClinicalTrials.gov NCT01519817 NCT02179515.

Keywords: Clinical oncology; Efficiency; PACS; Radiology workflow; Segmentation.

Figures

Fig. 1

Process used to segment lesions on MR. a Flowchart of MR segmentation steps. b Axial FLAIR MR showing a partially enhancing clival lesion involving the pons, outlined in red. Normal brain tissue can be seen in the anterior left pons. c Note the short green contour to correct oversampling seen in Fig. 1b. d Corrected and neuroradiologist verified lesion segmentation

Fig. 2

Segmentation steps used on CT. This was followed by verifying segmentation borders in consultation with a general radiologist, with fewer corrections needed since metastases were typically less complex than primary lesions. These were also faster to obtain since semi-automatic segmentation tools were more successful for lung, liver, and other soft tissue lesions

Fig. 3

A schematic comparison of volumetric assessments to traditional tumor assessments that involve one-dimensional measurements, handwriting on paper forms, and typing and retyping data. Although significantly more time is needed to segment lesions, there may be an opportunity for a cost-neutral workflow, where resources saved in data management may be shifted to the time-intensive process of volumetric segmentation

Fig. 4

Example of a 3D volume rendered image illustrating mid-section axial of a large primary chordoma lesion (green) displacing the left kidney anteriorly. Post-processed images such as these can be exported to the radiologist report and linked to the report with hyperlinked text

Fig. 5

An example of an MPVR parasagittal reformat illustrating the distribution of metastases along the mediastinum, heart, and pleural wall