Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 396

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Relative Cerebral Blood Volume Values to Differentiate High-Grade Glioma Recurrence from Posttreatment Radiation Effect: Direct Correlation between Image-Guided Tissue Histopathology and Localized Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging Measurements

Open access
Hu, L.S., Baxter, L.C., Smith, K.A., Feuerstein, B.G., Karis, J.P., Eschbacher, J.M., Coons, S.W., Nakaji, P., Yeh, R.F., Debbins, J., Heiserman, J.E.·2009·American Journal of Neuroradiology

Abstract

BACKGROUND AND PURPOSE: Differentiating tumor growth from posttreatment radiation effect (PTRE) remains a common problem in neuro-oncology practice. To our knowledge, useful threshold relative cerebral blood volume (rCBV) values that accurately distinguish the 2 entities do not exist. Our prospective study uses image-guided neuronavigation during surgical resection of MR imaging lesions to correlate directly specimen histopathology with localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC) measurements and to establish accurate rCBV threshold values, which differentiate PTRE from tumor recurrence. MATERIALS AND METHODS: Preoperative 3T gradient-echo DSC and contrast-enhanced stereotactic T1-weighted images were obtained in patients with high-grade glioma (HGG) previously treated with multimodality therapy. Intraoperative neuronavigation documented the stereotactic location of multiple tissue specimens taken randomly from the periphery of enhancing MR imaging lesions. Coregistration of DSC and stereotactic images enabled calculation of localized rCBV within the previously recorded specimen locations. All tissue specimens were histopathologically categorized as tumor or PTRE and were correlated with corresponding rCBV values. All rCBV values were T1-weighted leakage-corrected with preload contrast-bolus administration and T2/T2*-weighted leakage-corrected with baseline subtraction integration. RESULTS: Forty tissue specimens were collected from 13 subjects. The PTRE group (n = 16) rCBV values ranged from 0.21 to 0.71, tumor (n = 24) values ranged from 0.55 to 4.64, and 8.3% of tumor rCBV values fell within the PTRE group range. A threshold value of 0.71 optimized differentiation of the histopathologic groups with a sensitivity of 91.7% and a specificity of 100%. CONCLUSIONS: rCBV measurements obtained by using DSC and the protocol we have described can differentiate HGG recurrence from PTRE with a high degree of accuracy.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3174/ajnr.a1377

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 18 references

Cited by

See all 396

Metadata

Authors
Hu, L. S., Baxter, L. C., Smith, K. A., Feuerstein, B. G., Karis, J. P., Eschbacher, J. M., Coons, S. W., Nakaji, P., Yeh, R. F., Debbins, J., & Heiserman, J. E.
Venue
American Journal of Neuroradiology
Published
2008-12-04
Volume
30
Issue
3
Pages
552-558
ISSN
  • 0195-6108 (ISSN-L)
  • 1936-959X
OpenAlex
W2102099315
Cited by
396
References
18
FWCI
7.75
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Relative Cerebral Blood Volume Values to Differentiate High-Grade Glioma Recurrence from Posttreatment Radiation Effect: Direct Correlation between Image-Guided Tissue Histopathology and Localized Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging Measurements. https://app.cochat.ai/papers/10.3174/ajnr.a1377
The paper
Hu, L. S., Baxter, L. C., Smith, K. A., Feuerstein, B. G., Karis, J. P., Eschbacher, J. M., Coons, S. W., Nakaji, P., Yeh, R. F., Debbins, J., & Heiserman, J. E. (2009). Relative Cerebral Blood Volume Values to Differentiate High-Grade Glioma Recurrence from Posttreatment Radiation Effect: Direct Correlation between Image-Guided Tissue Histopathology and Localized Dynamic Susceptibility-Weighted Contrast-Enhanced Perfusion MR Imaging Measurements. American Journal of Neuroradiology. https://doi.org/10.3174/ajnr.a1377

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.