Evidence map›Paper›PMID 39071735›Full record

ArticleNeuro-oncology advances

Diffuse low-grade glioma: What is the optimal linear measure to assess tumor growth?

Thomas Dos Santos, Jeremy Deverdun, Thierry Chaptal, Amélie Darlix, Hugues Duffau, Liesjet Elisabeth Henriette Van Dokkum, Arthur Coget, Mathilde Carrière, Eve Denis, Margaux Verdier and 2 more

Abstract read
In one paragraph

Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Review
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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

12 authors.

Thomas Dos SantosDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.ORCID https://orcid.org/0009-0008-9967-9039
Jeremy DeverdunDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Thierry ChaptalDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Amélie DarlixDepartment of Medical Oncology, Institut Régional du Cancer de Montpellier (ICM), University of Montpellier, Montpellier, France.
Hugues DuffauDepartment of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France.ORCID https://orcid.org/0000-0002-6558-2342
Liesjet Elisabeth Henriette Van DokkumDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Arthur CogetDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Mathilde CarrièreDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Eve DenisDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Margaux VerdierInstitute de Recherche en Cancerologie Montpellier, Montpellier University, INSERM, Montpellier, France.
Nicolas Menjot de ChampfleurDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.
Emmanuelle Le BarsDepartment of Neuroradiology, Montpellier University Medical Center, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Radiological follow-up of diffuse low-grade gliomas (LGGs) growth is challenging. Approximative visual assessment still predominates over objective quantification due to the complexity of the pathology. The infiltrating character, diffuse borders and presence of surgical cavities demand LGG-based linear measurement rules to efficiently and precisely assess LGG evolution over time. Methods: We compared optimized 1D, 2D, and 3D linear measurements with manual volume segmentation as a reference to assess LGG tumor growth in 36 patients with LGG (340 magnetic resonance imaging scans), using the clinically important mean tumor diameter (MTD) and the velocity diameter expansion (VDE). LGG-specific progression thresholds were established using the high-grade gliomas-based RECIST, Macdonald, and RANO criteria, comparing the sensitivity to identify progression/non-progression for each linear method compared to the ground truth established by the manual segmentation. Results: 3D linear volume approximation correlated strongly with manually segmented volume. It also showed the highest sensitivity for progression detection. The MTD showed a comparable result, whereas the VDE highlighted that caution is warranted in the case of small tumors with multiple residues. Novel LGG-specific progression thresholds, or the critical change in estimated tumor volume, were increased for the 3D (from 40% to 52%) and 2D methods (from 25% to 33%) and decreased for the 1D method (from 20% to 16%). Using the 3D method allowed a ~5-minute time gain. Conclusions: While manual volumetric assessment remains the gold standard for calculating growth rate, the 3D linear method is the best time-efficient standardized alternative for radiological evaluation of LGGs in routine use.

Indexed as

linear assessmentlongitudinal growth quantificationlow-grade gliomaMRIneuro-oncology

Identifiers

PMID39071735
PMCPMC11274528

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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.