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- Bø, Hans Kristian, et al.
(författare)
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Intra-rater variability in low-grade glioma segmentation.
- 2017
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Ingår i: Journal of neuro-oncology. - : Springer Science and Business Media LLC. - 1573-7373 .- 0167-594X. ; 131:2, s. 393-402
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Tidskriftsartikel (refereegranskat)abstract
- Assessment of size and growth are key radiological factors in low-grade gliomas (LGGs), both for prognostication and treatment evaluation, but the reliability of LGG-segmentation is scarcely studied. With a diffuse and invasive growth pattern, usually without contrast enhancement, these tumors can be difficult to delineate. The aim of this study was to investigate the intra-observer variability in LGG-segmentation for a radiologist without prior segmentation experience. Pre-operative 3D FLAIR images of 23 LGGs were segmented three times in the software 3D Slicer. Tumor volumes were calculated, together with the absolute and relative difference between the segmentations. To quantify the intra-rater variability, we used the Jaccard coefficient comparing both two (J2) and three (J3) segmentations as well as the Hausdorff Distance (HD). The variability measured with J2 improved significantly between the two last segmentations compared to the two first, going from 0.87 to 0.90 (p=0.04). Between the last two segmentations, larger tumors showed a tendency towards smaller relative volume difference (p=0.07), while tumors with well-defined borders had significantly less variability measured with both J2 (p=0.04) and HD (p<0.01). We found no significant relationship between variability and histological sub-types or Apparent Diffusion Coefficients (ADC). We found that the intra-rater variability can be considerable in serial LGG-segmentation, but the variability seems to decrease with experience and higher grade of border conspicuity. Our findings highlight that some criteria defining tumor borders and progression in 3D volumetric segmentation is needed, if moving from 2D to 3D assessment of size and growth of LGGs.
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| 2. |
- Stensjøen, Anne Line, et al.
(författare)
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Does Pretreatment Tumor Growth Hold Prognostic Information for Patients with Glioblastoma?
- 2017
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Ingår i: World neurosurgery. - : Elsevier BV. - 1878-8769 .- 1878-8750. ; 101
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Tidskriftsartikel (refereegranskat)abstract
- Glioblastomas are highly aggressive and heterogeneous tumors, both in terms of patient outcome and molecular profile. Magnetic resonance imaging of tumor growth could potentially reveal new insights about tumor biology noninvasively. The aim of this exploratory retrospective study was to investigate the prognostic potential of pretreatment growth rate of glioblastomas, after controlling for known prognostic factors.A growth model derived from clinical pretreatment postcontrast T1-weighted magnetic resonance imaging images was used to divide 106 glioblastoma patients into 2 groups. The "faster growth" group had tumors growing faster than expected based on their volume at diagnosis, whereas the "slower growth" group had tumors growing slower than expected. Associations between tumor growth and survival were examined by the use of multivariable Cox regression and logistic regression.None of the known prognostic factors were significantly associated with tumor growth. An extended multivariable Cox model showed that during the first 12 months of follow-up, there was no significant difference in survival between faster and slower growing tumors. Beyond 12 months' follow-up, however, there was a significant, independent survival benefit in having a tumor with slower pretreatment growth. In a multiple logistic regression model including patients receiving both radiotherapy and chemotherapy (n= 82), slower pre-treatment growth of the tumor was shown to be a significant predictor of 2-year survival (odds ratio 4.4).Pretreatment glioblastoma growth harbors prognostic information. Patients with slower growing tumors have higher odds of survival beyond 2 years, adjusted for other prognostic factors.
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