Literature DB >> 26225306

Predicting Consistency of Meningioma by Magnetic Resonance Imaging.

Kyle A Smith1, John D Leever2, Roukoz B Chamoun1.   

Abstract

Objective Meningioma consistency is important because it affects the difficulty of surgery. To predict preoperative consistency, several methods have been proposed; however, they lack objectivity and reproducibility. We propose a new method for prediction based on tumor to cerebellar peduncle T2-weighted imaging intensity (TCTI) ratios. Design The magnetic resonance (MR) images of 20 consecutive patients were evaluated preoperatively. An intraoperative consistency scale was applied to these lesions prospectively by the operating surgeon based on Cavitron Ultrasonic Surgical Aspirator (Valleylab, Boulder, Colorado, United States) intensity. Tumors were classified as A, very soft; B, soft/intermediate; or C, fibrous. Using T2-weighted MR sequence, the TCTI ratio was calculated. Tumor consistency grades and TCTI ratios were then correlated. Results Of the 20 tumors evaluated prospectively, 7 were classified as very soft, 9 as soft/intermediate, and 4 as fibrous. TCTI ratios for fibrous tumors were all ≤ 1; very soft tumors were ≥ 1.8, except for one outlier of 1.66; and soft/intermediate tumors were > 1 to < 1.8. Conclusion We propose a method using quantifiable region-of-interest TCTIs as a uniform and reproducible way to predict tumor consistency. The intraoperative consistency was graded in an objective and clinically significant way and could lead to more efficient tumor resection.

Entities:  

Keywords:  Cavitron Ultrasonic Surgical Aspirator (CUSA); brain tumor; meningioma consistency; meningioma imaging; meningioma surgery

Year:  2015        PMID: 26225306      PMCID: PMC4433385          DOI: 10.1055/s-0034-1543965

Source DB:  PubMed          Journal:  J Neurol Surg B Skull Base        ISSN: 2193-634X


  12 in total

1.  Low-field MR imaging of meningiomas including dynamic contrast enhancement study: evaluation of surgical and histopathologic characteristics.

Authors:  S K Yrjänä; H Tuominen; A Karttunen; N Lähdesluoma; E Heikkinen; J Koivukangas
Journal:  AJNR Am J Neuroradiol       Date:  2006 Nov-Dec       Impact factor: 3.825

2.  Predictors of meningioma consistency: A study in 243 consecutive cases.

Authors:  Bunpot Sitthinamsuwan; Inthira Khampalikit; Sarun Nunta-aree; Prajak Srirabheebhat; Teerapol Witthiwej; Akkapong Nitising
Journal:  Acta Neurochir (Wien)       Date:  2012-06-29       Impact factor: 2.216

3.  Prediction of consistency of meningiomas with preoperative magnetic resonance imaging.

Authors:  N Yamaguchi; T Kawase; M Sagoh; T Ohira; H Shiga; S Toya
Journal:  Surg Neurol       Date:  1997-12

4.  ¹H-MRS of intracranial meningiomas: what it can add to known clinical and MRI predictors of the histopathological and biological characteristics of the tumor?

Authors:  Mikhail F Chernov; Hidetoshi Kasuya; Kotaro Nakaya; Koichi Kato; Yuko Ono; Shigetoshi Yoshida; Yoshihiro Muragaki; Takashi Suzuki; Hiroshi Iseki; Osami Kubo; Tomokatsu Hori; Yoshikazu Okada; Kintomo Takakura
Journal:  Clin Neurol Neurosurg       Date:  2010-12-07       Impact factor: 1.876

Review 5.  Intracranial meningiomas: correlations between MR imaging and histology.

Authors:  F Maiuri; G Iaconetta; O de Divitiis; S Cirillo; F Di Salle; M L De Caro
Journal:  Eur J Radiol       Date:  1999-07       Impact factor: 3.528

6.  Correlation between magnetic resonance images and histology in meningiomas: T2-weighted images indicate collagen contents in tissues.

Authors:  N Soyama; J Kuratsu; Y Ushio
Journal:  Neurol Med Chir (Tokyo)       Date:  1995-07       Impact factor: 1.742

7.  MRI of intracranial meningiomas: correlations with histology and physical consistency.

Authors:  P Carpeggiani; G Crisi; C Trevisan
Journal:  Neuroradiology       Date:  1993       Impact factor: 2.804

8.  Meningiomas: correlation between MRI characteristics and operative findings including consistency.

Authors:  Y Suzuki; T Sugimoto; M Shibuya; K Sugita; S J Patel
Journal:  Acta Neurochir (Wien)       Date:  1994       Impact factor: 2.216

9.  Using ex vivo proton magnetic resonance spectroscopy to reveal associations between biochemical and biological features of meningiomas.

Authors:  Wolfgang K Pfisterer; Ronald A Nieman; Adrienne C Scheck; Stephen W Coons; Robert F Spetzler; Mark C Preul
Journal:  Neurosurg Focus       Date:  2010-01       Impact factor: 4.047

10.  Use of preoperative magnetic resonance imaging T1 and T2 sequences to determine intraoperative meningioma consistency.

Authors:  Jason M Hoover; Jonathan M Morris; Fredric B Meyer
Journal:  Surg Neurol Int       Date:  2011-10-12
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  9 in total

Review 1.  Predicting Meningioma Consistency on Preoperative Neuroimaging Studies.

Authors:  Mark S Shiroishi; Steven Y Cen; Benita Tamrazi; Francesco D'Amore; Alexander Lerner; Kevin S King; Paul E Kim; Meng Law; Darryl H Hwang; Orest B Boyko; Chia-Shang J Liu
Journal:  Neurosurg Clin N Am       Date:  2016-02-18       Impact factor: 2.509

Review 2.  Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review.

Authors:  Amy Yao; Margaret Pain; Priti Balchandani; Raj K Shrivastava
Journal:  Neurosurg Rev       Date:  2016-11-21       Impact factor: 3.042

3.  Tumor to Cerebellar Peduncle T2-Weighted Imaging Intensity Ratio Fails to Predict Pituitary Adenoma Consistency.

Authors:  Panagiotis Mastorakos; Gautam U Mehta; Ajay Chatrath; Shayan Moosa; Maria-Beatriz Lopes; Spencer C Payne; John A Jane
Journal:  J Neurol Surg B Skull Base       Date:  2018-08-24

4.  The extended, transnasal, transsphenoidal approach for anterior skull base meningioma: considerations in patient selection.

Authors:  Joseph P Castlen; David J Cote; Hasan A Zaidi; Edward R Laws
Journal:  Pituitary       Date:  2017-10       Impact factor: 4.107

5.  Can an Imaging Marker of Consistency Predict Intraoperative Experience and Clinical Outcomes for Vestibular Schwannomas? A Retrospective Review.

Authors:  Robert J Macielak; Michael S Harris; Jameson K Mattingly; Varun S Shah; Luciano M Prevedello; Oliver F Adunka
Journal:  J Neurol Surg B Skull Base       Date:  2019-09-24

6.  Endoscopic Transnasal Resection of Midline Skull Base Meningiomas: Tumor Consistency and Surgical Outcomes.

Authors:  Hissah K Al Abdulsalam; Aljohara K Aldahish; Abdulrahman Albakr; Sajjad Hussain; Ahmad Alroqi; Saud Alromaih; Saad Alsaleh; Abdulrazag M Ajlan
Journal:  J Neurol Surg B Skull Base       Date:  2020-09-10

7.  The endoscope-assisted supraorbital "keyhole" approach for anterior skull base meningiomas: an updated meta-analysis.

Authors:  Danyal Z Khan; Ivo S Muskens; Rania A Mekary; Amir H Zamanipoor Najafabadi; Adel E Helmy; Robert Reisch; Marike L D Broekman; Hani J Marcus
Journal:  Acta Neurochir (Wien)       Date:  2020-09-05       Impact factor: 2.216

8.  Features of tumor texture influence surgery and outcome in intracranial meningioma.

Authors:  Thomas Sauvigny; Franz L Ricklefs; Lena Hoffmann; Raphael Schwarz; Manfred Westphal; Nils Ole Schmidt
Journal:  Neurooncol Adv       Date:  2020-09-10

9.  Pseudoprogression and peritumoral edema due to intratumoral necrosis after Gamma knife radiosurgery for meningioma.

Authors:  In-Ho Jung; Kyung Won Chang; So Hee Park; Hyun Ho Jung; Jong Hee Chang; Jin Woo Chang; Won Seok Chang
Journal:  Sci Rep       Date:  2022-08-11       Impact factor: 4.996

  9 in total

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