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

Author:

Dos Santos Thomas1ORCID,Deverdun Jeremy12,Chaptal Thierry12,Darlix Amélie34,Duffau Hugues56ORCID,Van Dokkum Liesjet Elisabeth Henriette12,Coget Arthur1,Carrière Mathilde1,Denis Eve1,Verdier Margaux7,Menjot de Champfleur Nicolas128,Le Bars Emmanuelle12

Affiliation:

1. Department of Neuroradiology, Montpellier University Medical Center , Montpellier , France

2. I2FH, Institut d’Imagerie Fonctionnelle Humaine, Department of Neuroradiology, Montpellier University Medical Center , Montpellier , France

3. Department of Medical Oncology, Institut Régional du Cancer de Montpellier (ICM), University of Montpellier , Montpellier,  France

4. Institute of Functional Genomics, University of Montpellier, CNRS, INSERM , Montpellier , France

5. Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center , Montpellier , France

6. Institute of Functional Genomics, INSERM 1191, University of Montpellier , Montpellier , France

7. Institute de Recherche en Cancerologie Montpellier, Montpellier University, INSERM , Montpellier , France

8. Laboratoire Charles Coulomb, University of Montpellier , Montpellier,  France

Abstract

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.

Publisher

Oxford University Press (OUP)

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