Literature DB >> 29098571

Preoperative relative cerebral blood volume analysis in gliomas predicts survival and mitigates risk of biopsy sampling error.

Brendan J McCullough1,2,3,4, Valerie Ader5, Brian Aguedan5, Xu Feng5, Daniel Susanto6,5, Tara L Benkers6, John W Henson7, Marc Mayberg6, Charles S Cobbs6, Ryder P Gwinn6, Stephen J Monteith6, David W Newell6, Johnny Delashaw6, Sarah J Fouke8, Steven Rostad6,9, Bart P Keogh6,5.   

Abstract

Appropriate management of adult gliomas requires an accurate histopathological diagnosis. However, the heterogeneity of gliomas can lead to misdiagnosis and undergrading, especially with biopsy. We evaluated the role of preoperative relative cerebral blood volume (rCBV) analysis in conjunction with histopathological analysis as a predictor of overall survival and risk of undergrading. We retrospectively identified 146 patients with newly diagnosed gliomas (WHO grade II-IV) that had undergone preoperative MRI with rCBV analysis. We compared overall survival by histopathologically determined WHO tumor grade and by rCBV using Kaplan-Meier survival curves and the Cox proportional hazards model. We also compared preoperative imaging findings and initial histopathological diagnosis in 13 patients who underwent biopsy followed by subsequent resection. Survival curves by WHO grade and rCBV tier similarly separated patients into low, intermediate, and high-risk groups with shorter survival corresponding to higher grade or rCBV tier. The hazard ratio for WHO grade III versus II was 3.91 (p = 0.018) and for grade IV versus II was 11.26 (p < 0.0001) and the hazard ratio for each increase in 1.0 rCBV units was 1.12 (p < 0.002). Additionally, 3 of 13 (23%) patients initially diagnosed by biopsy were upgraded on subsequent resection. Preoperative rCBV was elevated at least one standard deviation above the mean in the 3 upgraded patients, suggestive of undergrading, but not in the ten concordant diagnoses. In conclusion, rCBV can predict overall survival similarly to pathologically determined WHO grade in patients with gliomas. Discordant rCBV analysis and histopathology may help identify patients at higher risk for undergrading.

Entities:  

Keywords:  Cerebral blood volume; Glioma; Outcomes; Radiological–pathological correlation; Survival; rCBV

Mesh:

Year:  2017        PMID: 29098571     DOI: 10.1007/s11060-017-2642-2

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  25 in total

1.  Low-grade gliomas: dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging--prediction of patient clinical response.

Authors:  Meng Law; Sarah Oh; James S Babb; Edwin Wang; Matilde Inglese; David Zagzag; Edmond A Knopp; Glyn Johnson
Journal:  Radiology       Date:  2006-01-05       Impact factor: 11.105

2.  Correlation between progression free survival and dynamic susceptibility contrast MRI perfusion in WHO grade III glioma subtypes.

Authors:  Rajiv Mangla; Daniel Thomas Ginat; Shervin Kamalian; Michael T Milano; David N Korones; Kevin A Walter; Sven Ekholm
Journal:  J Neurooncol       Date:  2013-11-01       Impact factor: 4.130

3.  Report of the Jumpstarting Brain Tumor Drug Development Coalition and FDA clinical trials neuroimaging endpoint workshop (January 30, 2014, Bethesda MD).

Authors:  Patrick Y Wen; Timothy F Cloughesy; Benjamin M Ellingson; David A Reardon; Howard A Fine; Lauren Abrey; Karla Ballman; Martin Bendszuz; Jan Buckner; Susan M Chang; Michael D Prados; Whitney B Pope; Alma Gregory Sorensen; Martin van den Bent; Wai-Kwan Alfred Yung
Journal:  Neuro Oncol       Date:  2014-10       Impact factor: 12.300

4.  Observer reliability in histological grading of astrocytoma stereotactic biopsies.

Authors:  M A Mittler; B C Walters; E G Stopa
Journal:  J Neurosurg       Date:  1996-12       Impact factor: 5.115

5.  Correlation between cerebral blood volume measurements by perfusion-weighted magnetic resonance imaging and two-year progression-free survival in gliomas.

Authors:  M V Spampinato; C Schiarelli; A Cianfoni; P Giglio; C T Welsh; S Bisdas; Z Rumboldt
Journal:  Neuroradiol J       Date:  2013-08-27

6.  Interobserver reproducibility among neuropathologists and surgical pathologists in fibrillary astrocytoma grading.

Authors:  R A Prayson; D P Agamanolis; M L Cohen; M L Estes; B K Kleinschmidt-DeMasters; F Abdul-Karim; S P McClure; B A Sebek; R Vinay
Journal:  J Neurol Sci       Date:  2000-04-01       Impact factor: 3.181

7.  Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected].

Authors:  Michael H Lev; Yelda Ozsunar; John W Henson; Amjad A Rasheed; Glenn D Barest; Griffith R Harsh; Markus M Fitzek; E Antonio Chiocca; James D Rabinov; Andrew N Csavoy; Bruce R Rosen; Fred H Hochberg; Pamela W Schaefer; R Gilberto Gonzalez
Journal:  AJNR Am J Neuroradiol       Date:  2004-02       Impact factor: 3.825

8.  Survival analysis in patients with glioblastoma multiforme: predictive value of choline-to-N-acetylaspartate index, apparent diffusion coefficient, and relative cerebral blood volume.

Authors:  Joonmi Oh; Roland G Henry; Andrea Pirzkall; Ying Lu; Xiaojuan Li; Isabelle Catalaa; Susan Chang; William P Dillon; Sarah J Nelson
Journal:  J Magn Reson Imaging       Date:  2004-05       Impact factor: 4.813

9.  Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; T Hirai; T Okuda; Y Shigematsu; L Liang; Y Ge; Y Ushio; M Takahashi
Journal:  AJR Am J Roentgenol       Date:  1998-12       Impact factor: 3.959

10.  Preoperative prognostic value of dynamic contrast-enhanced MRI-derived contrast transfer coefficient and plasma volume in patients with cerebral gliomas.

Authors:  T B Nguyen; G O Cron; J F Mercier; C Foottit; C H Torres; S Chakraborty; J Woulfe; G H Jansen; J M Caudrelier; J Sinclair; M J Hogan; R E Thornhill; I G Cameron
Journal:  AJNR Am J Neuroradiol       Date:  2014-06-19       Impact factor: 3.825

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  3 in total

1.  The histological representativeness of glioblastoma tissue samples.

Authors:  Vilde Elisabeth Mikkelsen; Ole Solheim; Øyvind Salvesen; Sverre Helge Torp
Journal:  Acta Neurochir (Wien)       Date:  2020-10-21       Impact factor: 2.216

Review 2.  Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions.

Authors:  Vittorio Stumpo; Lelio Guida; Jacopo Bellomo; Christiaan Hendrik Bas Van Niftrik; Martina Sebök; Moncef Berhouma; Andrea Bink; Michael Weller; Zsolt Kulcsar; Luca Regli; Jorn Fierstra
Journal:  Cancers (Basel)       Date:  2022-03-05       Impact factor: 6.639

Review 3.  Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading.

Authors:  Lelio Guida; Vittorio Stumpo; Jacopo Bellomo; Christiaan Hendrik Bas van Niftrik; Martina Sebök; Moncef Berhouma; Andrea Bink; Michael Weller; Zsolt Kulcsar; Luca Regli; Jorn Fierstra
Journal:  Cancers (Basel)       Date:  2022-03-10       Impact factor: 6.639

  3 in total

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