Literature DB >> 24848829

Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma.

Yi Tang1, Sathish K Dundamadappa, Senthur Thangasamy, Thomas Flood, Richard Moser, Thomas Smith, Keith Cauley, Deepak Takhtani.   

Abstract

OBJECTIVE: A noninvasive method to predict aggressiveness of high-grade meningiomas would be desirable because it would help anticipate tumor recurrence and improve tumor management and the treatment outcomes. The Ki-67 protein is a marker of tumor proliferation, and apparent diffusion coefficient (ADC) is related to tumor cellularity. Therefore, we sought to determine whether there is a statistically significant correlation between ADC and Ki-67 values in meningiomas and whether ADC values can differentiate various meningioma subtypes.
MATERIALS AND METHODS: MRI examinations and histopathology of 68 surgically treated meningiomas were retrospectively reviewed. Mean ADC values were derived from diffusion imaging. Correlation coefficients were calculated for mean ADC and Ki-67 proliferation index values using linear regression. An independent unpaired Student t test was used to compare the ADC and Ki-67 proliferation index values from low-grade and more aggressive meningiomas.
RESULTS: A statistically significant inverse correlation was found between ADC and Ki-67 proliferation index for low-grade and aggressive meningiomas (r(2) = -0.33, p = 0.0039). ADC values (± SD) of low-grade meningiomas (0.84 ± 0.14 × 10(-3) mm(2)/s) and aggressive (atypical or anaplastic) meningiomas (0.75 ± 0.03 × 10(-3) mm(2)/s) were significantly different (p = 0.0495). Using an ADC cutoff value of 0.70 × 10(-3) mm(2)/s, the sensitivity for diagnosing aggressive meningiomas was 29%, specificity was 94%, positive predictive value was 67%, and negative predictive value was 75%.
CONCLUSION: ADC values correlate inversely with Ki-67 proliferation index and help differentiate low-grade from aggressive meningiomas.

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Year:  2014        PMID: 24848829     DOI: 10.2214/AJR.13.11637

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  25 in total

1.  Relation of apparent diffusion coefficient with Ki-67 proliferation index in meningiomas.

Authors:  Ozdil Baskan; Gokalp Silav; Fatih Han Bolukbasi; Ozlem Canoz; Serdar Geyik; Ilhan Elmaci
Journal:  Br J Radiol       Date:  2015-11-05       Impact factor: 3.039

2.  Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping.

Authors:  Shun Zhang; Gloria Chia-Yi Chiang; Jacquelyn Marion Knapp; Christina M Zecca; Diana He; Rohan Ramakrishna; Rajiv S Magge; David J Pisapia; Howard Alan Fine; Apostolos John Tsiouris; Yize Zhao; Linda A Heier; Yi Wang; Ilhami Kovanlikaya
Journal:  J Neuroradiol       Date:  2019-05-25       Impact factor: 3.447

3.  The diagnostic value of using combined MR diffusion tensor imaging parameters to differentiate between low- and high-grade meningioma.

Authors:  Kerim Aslan; Hediye Pinar Gunbey; Leman Tomak; Lutfi Incesu
Journal:  Br J Radiol       Date:  2018-05-31       Impact factor: 3.039

4.  Prediction of progression in skull base meningiomas: additional benefits of apparent diffusion coefficient value.

Authors:  Ching-Chung Ko; Sher-Wei Lim; Tai-Yuan Chen; Jeon-Hor Chen; Chien-Feng Li; Yow-Ling Shiue
Journal:  J Neurooncol       Date:  2018-01-20       Impact factor: 4.130

5.  Imaging and diagnostic advances for intracranial meningiomas.

Authors:  Raymond Y Huang; Wenya Linda Bi; Brent Griffith; Timothy J Kaufmann; Christian la Fougère; Nils Ole Schmidt; Jöerg C Tonn; Michael A Vogelbaum; Patrick Y Wen; Kenneth Aldape; Farshad Nassiri; Gelareh Zadeh; Ian F Dunn
Journal:  Neuro Oncol       Date:  2019-01-14       Impact factor: 12.300

6.  Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes.

Authors:  Yunju Kim; Kyounglan Ko; Daehong Kim; Changki Min; Sungheon G Kim; Jungnam Joo; Boram Park
Journal:  Br J Radiol       Date:  2016-05-20       Impact factor: 3.039

7.  Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade.

Authors:  William L Hwang; Ariel E Marciscano; Andrzej Niemierko; Daniel W Kim; Anat O Stemmer-Rachamimov; William T Curry; Fred G Barker; Robert L Martuza; Jay S Loeffler; Kevin S Oh; Helen A Shih; Mykol Larvie
Journal:  Neuro Oncol       Date:  2015-11-22       Impact factor: 12.300

8.  Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

Authors:  Yae Won Park; Jongmin Oh; Seng Chan You; Kyunghwa Han; Sung Soo Ahn; Yoon Seong Choi; Jong Hee Chang; Se Hoon Kim; Seung-Koo Lee
Journal:  Eur Radiol       Date:  2018-11-15       Impact factor: 5.315

9.  Correlation of diffusion MRI with the Ki-67 index in non-small cell lung cancer.

Authors:  Adem Karaman; Irmak Durur-Subasi; Fatih Alper; Omer Araz; Mahmut Subasi; Elif Demirci; Mevlut Albayrak; Gökhan Polat; Metin Akgun; Nevzat Karabulut
Journal:  Radiol Oncol       Date:  2015-08-21       Impact factor: 2.991

10.  The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.

Authors:  Yiping Lu; Li Liu; Shihai Luan; Ji Xiong; Daoying Geng; Bo Yin
Journal:  Eur Radiol       Date:  2018-08-07       Impact factor: 5.315

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