Literature DB >> 32821962

Validation of combined use of DWI and percentage signal recovery-optimized protocol of DSC-MRI in differentiation of high-grade glioma, metastasis, and lymphoma.

Emetullah Cindil1, Halit Nahit Sendur2, Mahi Nur Cerit2, Nurullah Dag2, Nesrin Erdogan2, Filiz Elbuken Celebi3, Yusuf Oner2, Turgut Tali2.   

Abstract

PURPOSE: With conventional MRI, it is often difficult to effectively differentiate between contrast-enhancing brain tumors, including primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and metastasis. This study aimed to assess the discrimination ability of the parameters obtained from DWI and the percentage signal recovery- (PSR-) optimized protocol of DSC-MRI between these three tumor types at an initial step.
METHODS: DSC-MRI using a PSR-optimized protocol (TR/TE = 1500/30 ms, flip angle = 90°, no preload) and DWI of 99 solitary enhancing tumors (60 HGGs, 24 metastases, 15 PCNSLs) were retrospectively assessed before treatment. rCBV, PSR, ADC in the tumor core and rCBV, and ADC in peritumoral edema were measured. The differences were evaluated using one-way ANOVA, and the diagnostic performance was evaluated using ROC curve analysis.
RESULTS: PSR in the tumor core showed the best discriminating performance in differentiating these three tumor types with AUC values of 0.979 for PCNSL vs. others and 0.947 for HGG vs. metastasis. The ADC was only helpful in the tumor core and distinguishing PCNSLs from others (AUC = 0.897).
CONCLUSION: Different from CBV-optimized protocols (preload, intermediate FA), PSR derived from the PSR-optimized protocol seems to be the most important parameter in the differentiation of HGGs, metastases, and PCNSLs at initial diagnosis. This property makes PSR remarkable and carries the need for comprehensive DSC-MRI protocols, which provides PSR sensitivity and CBV accuracy together, such as the preload use of the PSR-optimized protocol before the CBV-optimized protocol.

Entities:  

Keywords:  DSC-MRI; DWI; Glioblastoma; Metastasis; Primary cranial nervous system lymphoma

Year:  2020        PMID: 32821962     DOI: 10.1007/s00234-020-02522-9

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  5 in total

1.  The role of diffusion-weighted imaging in patients with brain tumors.

Authors:  K Kono; Y Inoue; K Nakayama; M Shakudo; M Morino; K Ohata; K Wakasa; R Yamada
Journal:  AJNR Am J Neuroradiol       Date:  2001 Jun-Jul       Impact factor: 3.825

2.  Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not.

Authors:  J L Boxerman; K M Schmainda; R M Weisskoff
Journal:  AJNR Am J Neuroradiol       Date:  2006-04       Impact factor: 3.825

3.  Added Value of Spectroscopy to Perfusion MRI in the Differential Diagnostic Performance of Common Malignant Brain Tumors.

Authors:  A Vallée; C Guillevin; M Wager; V Delwail; R Guillevin; J-N Vallée
Journal:  AJNR Am J Neuroradiol       Date:  2018-07-26       Impact factor: 3.825

4.  Perfusion-weighted imaging of peritumoral edema can aid in the differential diagnosis of glioblastoma mulltiforme versus brain metastasis.

Authors:  Osnat Halshtok Neiman; Siegal Sadetzki; Angela Chetrit; Stephen Raskin; Gal Yaniv; Chen Hoffmann
Journal:  Isr Med Assoc J       Date:  2013-02       Impact factor: 0.892

5.  Neuropathology of brain metastases.

Authors:  Melike Pekmezci; Arie Perry
Journal:  Surg Neurol Int       Date:  2013-05-02
  5 in total
  4 in total

1.  Assessment of brain tumors by magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging and computed tomography perfusion: a comparison study.

Authors:  Elisa Scola; Ilaria Desideri; Andrea Bianchi; Davide Gadda; Giorgio Busto; Alessandro Fiorenza; Tommaso Amadori; Sara Mancini; Vittorio Miele; Enrico Fainardi
Journal:  Radiol Med       Date:  2022-04-20       Impact factor: 6.313

2.  Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis.

Authors:  Albert Pons-Escoda; Alonso Garcia-Ruiz; Pablo Naval-Baudin; Francesco Grussu; Juan Jose Sanchez Fernandez; Angels Camins Simo; Noemi Vidal Sarro; Alejandro Fernandez-Coello; Jordi Bruna; Monica Cos; Raquel Perez-Lopez; Carles Majos
Journal:  Eur Radiol       Date:  2022-02-01       Impact factor: 5.315

3.  Use of 18F-FDG-PET/CT in differential diagnosis of primary central nervous system lymphoma and high-grade gliomas: A meta-analysis.

Authors:  Guisheng Zhang; Jiuhong Li; Xuhui Hui
Journal:  Front Neurol       Date:  2022-08-17       Impact factor: 4.086

4.  Radiomic Based Machine Learning Performance for a Three Class Problem in Neuro-Oncology: Time to Test the Waters?

Authors:  Sarv Priya; Yanan Liu; Caitlin Ward; Nam H Le; Neetu Soni; Ravishankar Pillenahalli Maheshwarappa; Varun Monga; Honghai Zhang; Milan Sonka; Girish Bathla
Journal:  Cancers (Basel)       Date:  2021-05-24       Impact factor: 6.639

  4 in total

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