Literature DB >> 24289117

A proposed grading system for standardizing tumor consistency of intracranial meningiomas.

Gabriel Zada1, Parham Yashar, Aaron Robison, Jesse Winer, Alexander Khalessi, William J Mack, Steven L Giannotta.   

Abstract

OBJECT: Tumor consistency plays an important and underrecognized role in the surgeon's ability to resect meningiomas, especially with evolving trends toward minimally invasive and keyhole surgical approaches. Aside from descriptors such as "hard" or "soft," no objective criteria exist for grading, studying, and conveying the consistency of meningiomas.
METHODS: The authors designed a practical 5-point scale for intraoperative grading of meningiomas based on the surgeon's ability to internally debulk the tumor and on the subsequent resistance to folding of the tumor capsule. Tumor consistency grades and features are as follows: 1) extremely soft tumor, internal debulking with suction only; 2) soft tumor, internal debulking mostly with suction, and remaining fibrous strands resected with easily folded capsule; 3) average consistency, tumor cannot be freely suctioned and requires mechanical debulking, and the capsule then folds with relative ease; 4) firm tumor, high degree of mechanical debulking required, and capsule remains difficult to fold; and 5) extremely firm, calcified tumor, approaches density of bone, and capsule does not fold. Additional grading categories included tumor heterogeneity (with minimum and maximum consistency scores) and a 3-point vascularity score. This grading system was prospectively assessed in 50 consecutive patients undergoing craniotomy for meningioma resection by 2 surgeons in an independent fashion. Grading scores were subjected to a linear weighted kappa analysis for interuser reliability.
RESULTS: Fifty patients (100 scores) were included in the analysis. The mean maximal tumor diameter was 4.3 cm. The distribution of overall tumor consistency scores was as follows: Grade 1, 4%; Grade 2, 9%; Grade 3, 43%; Grade 4, 44%; and Grade 5, 0%. Regions of Grade 5 consistency were reported only focally in 14% of heterogeneous tumors. Tumors were designated as homogeneous in 68% and heterogeneous in 32% of grades. The kappa analysis score for overall tumor consistency grade was 0.87 (SE 0.06, 95% CI 0.76-0.99), with 90% user agreement. Kappa analysis scores for minimum and maximum grades of tumor regions were 0.69 (agreement 72%) and 0.75 (agreement 78%), respectively. The kappa analysis score for tumor vascularity grading was 0.56 (agreement 76%). Overall consistency did not correlate with patient age, tumor location, or tumor size. A higher tumor vascularity grade was associated with a larger tumor diameter (p = 0.045) and with skull base location (p = 0.02).
CONCLUSIONS: The proposed grading system provides a reliable, practical, and objective assessment of meningioma consistency and facilitates communication among providers. This system also accounts for heterogeneity in tumor consistency. With the proposed scale, meningioma consistency can be standardized as groundwork for future studies relating to surgical outcomes, predictability of consistency and vascularity using neuroimaging techniques, and effectiveness of various surgical instruments.

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Year:  2013        PMID: 24289117     DOI: 10.3171/2013.8.FOCUS13274

Source DB:  PubMed          Journal:  Neurosurg Focus        ISSN: 1092-0684            Impact factor:   4.047


  9 in total

1.  Diffusion-weighted imaging for predicting tumor consistency and extent of resection in patients with pituitary adenoma.

Authors:  Wei Ding; Zheng Huang; Gaofeng Zhou; Lang Li; Mingyu Zhang; Zhenyan Li
Journal:  Neurosurg Rev       Date:  2021-01-28       Impact factor: 3.042

Review 2.  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 3.  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

4.  Higher-Resolution Magnetic Resonance Elastography in Meningiomas to Determine Intratumoral Consistency.

Authors:  Joshua D Hughes; Nikoo Fattahi; J Van Gompel; Arvin Arani; Fredric Meyer; Giuseppe Lanzino; Michael J Link; Richard Ehman; John Huston
Journal:  Neurosurgery       Date:  2015-10       Impact factor: 4.654

Review 5.  Utility of preoperative meningioma consistency measurement with magnetic resonance elastography (MRE): a review.

Authors:  Alexander G Chartrain; Mehmet Kurt; Amy Yao; Rui Feng; Kambiz Nael; J Mocco; Joshua B Bederson; Priti Balchandani; Raj K Shrivastava
Journal:  Neurosurg Rev       Date:  2017-05-31       Impact factor: 3.042

Review 6.  REVIEW: MR elastography of brain tumors.

Authors:  Adomas Bunevicius; Katharina Schregel; Ralph Sinkus; Alexandra Golby; Samuel Patz
Journal:  Neuroimage Clin       Date:  2019-11-23       Impact factor: 4.881

7.  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

8.  Preoperative Prediction of Meningioma Consistency via Machine Learning-Based Radiomics.

Authors:  Yixuan Zhai; Dixiang Song; Fengdong Yang; Yiming Wang; Xin Jia; Shuxin Wei; Wenbin Mao; Yake Xue; Xinting Wei
Journal:  Front Oncol       Date:  2021-05-26       Impact factor: 6.244

9.  Utilization of Discarded Surgical Tissue from Ultrasonic Aspirators to Establish Patient-Derived Metastatic Brain Tumor Cells: A Guide from the Operating Room to the Research Laboratory.

Authors:  Vahan Martirosian; Krutika Deshpande; Michelle Lin; Casey Jarvis; Edith Yuan; Thomas C Chen; Gabriel Zada; Steven L Giannotta; Frank J Attenello; Frances Chow; Josh Neman
Journal:  Curr Protoc       Date:  2021-06
  9 in total

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