Evidence map›Paper›PMID 26596767›Full record

ArticleJournal of digital imaging2016

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

Kathleen E Fenerty, Nicholas J Patronas, Christopher R Heery, James L Gulley, Les R Folio

Open access · bronzeAbstract read
In one paragraph

Article in Journal of digital imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Multimedia-enhanced Radiology Reports: Concept, Components, and Challenges.Radiographics : a review publication of the Radiological Society of North America, Inc
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kathleen E FenertyLaboratory of Tumor Immunology and Biology, CCR, NCI, NIH, Bethesda, MD, USA. kfenerty@iupui.edu.
Nicholas J PatronasDepartment of Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA.
Christopher R HeeryLaboratory of Tumor Immunology and Biology, CCR, NCI, NIH, Bethesda, MD, USA.
James L GulleyGenitourinary Malignancies Branch, CCR, NCI, NIH, Bethesda, MD, USA.
Les R FolioDepartment of Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, USA.
Center for Cancer Research · USNational Institutes of Health Clinical Center · US

Funding

Cancer Therapy Clinical Trials Using Novel Recombinant VaccinesZIABC010666 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GULLEY, JAMES L. · 2009 to 2025
$22.4M
Cancer Immunotherapy Clinical TrialsZIABC011547 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI STRAUSS, JULIUS · 2014 to 2023
$8.1M
6 · The paper itself

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.

Indexed as

Tumor BurdenChordomaDiagnostic ImagingHumansRetrospective StudiesTime FactorsClinical oncologyEfficiencyPACSRadiology workflowSegmentation

Identifiers

PMID26596767
PMCPMC4879033
OpenAlexW2187026992

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.