Literature DB >> 27734275

Apparent diffusion coefficient and pituitary macroadenomas: pre-operative assessment of tumor atypia.

Benita Tamrazi1,2, Melike Pekmezci3, Mariam Aboian4, Tarik Tihan3, Christine M Glastonbury4.   

Abstract

RATIONALE AND
OBJECTIVES: Pituitary macroadenomas are predominantly benign intracranial neoplasms that can be locally aggressive with invasion of adjacent structures. Biomarkers of aggressive behavior have been identified in the pathology literature, including the proliferative marker MIB-1. In the radiology literature, diffusion weighted imaging and low ADC values provide similar markers of aggressive behavior in brain tumors. The purpose of this study was to determine if there is a correlation between ADC and MIB-1 in pituitary macroadenomas.
MATERIALS AND METHODS: A retrospective review of diffusion imaging and immunohistochemical characteristics of pituitary macroadenomas was performed. The ADC ratio and specimen Ki-67 (MIB-1) indices were measured. Linear regression analysis of normalized ADC values and MIB-1 indices was used to compare these parameters.
RESULTS: There were 17 patients with available ADC maps and MIB-1 indices. Local invasion was confirmed by imaging and intraoperative visualization in 11 patients. The mean ADC ratio for the invasive group was 0.68, with a mean MIB-1 index of 2.21 %. In the noninvasive group, the mean ADC ratio was 1.05, with a mean MIB-1 index of 0.9 %. Linear regression analysis of normalized ADC values versus MIB-1 demonstrates a negative correlation, with a linear slope significantly different from zero (p = 0.003, correlation coefficient of 0.77, and r squared = 0.59).
CONCLUSION: We determine a strong correlation of low ADC values and MIB-1, demonstrating the potential of diffusion imaging as a possible biomarker for atypical, proliferative adenomas, which may ultimately affect the surgical approach and postoperative management.

Entities:  

Keywords:  Diffusion weighted imaging; Magnetic resonance imaging; Pituitary adenoma; Proliferation index (MIB-1)

Mesh:

Substances:

Year:  2017        PMID: 27734275     DOI: 10.1007/s11102-016-0759-5

Source DB:  PubMed          Journal:  Pituitary        ISSN: 1386-341X            Impact factor:   4.107


  18 in total

1.  Preoperative MRI evaluation of pituitary macroadenoma: imaging features predictive of successful transsphenoidal surgery.

Authors:  Jerrold L Boxerman; Jeffrey M Rogg; John E Donahue; Jason T Machan; Marc A Goldman; Curt E Doberstein
Journal:  AJR Am J Roentgenol       Date:  2010-09       Impact factor: 3.959

Review 2.  The cytogenesis and pathogenesis of pituitary adenomas.

Authors:  S L Asa; S Ezzat
Journal:  Endocr Rev       Date:  1998-12       Impact factor: 19.871

3.  Role of PROPELLER diffusion-weighted imaging and apparent diffusion coefficient in the evaluation of pituitary adenomas.

Authors:  Omar M Mahmoud; Atsushi Tominaga; Vishwa Jeet Amatya; Megu Ohtaki; Kazuhiko Sugiyama; Tetsuhiko Sakoguchi; Yasuyuki Kinoshita; Yukio Takeshima; Nobukazu Abe; Yuji Akiyama; Ahmad I El-Ghoriany; Abdel Karim H Abd Alla; Mostafa A M El-Sharkawy; Kazunori Arita; Kaoru Kurisu; Fumiyuki Yamasaki
Journal:  Eur J Radiol       Date:  2010-06-26       Impact factor: 3.528

4.  Pituitary macroadenomas: preoperative evaluation of consistency with diffusion-weighted MR imaging--initial experience.

Authors:  Alberto Pierallini; Francesca Caramia; Carlo Falcone; Emanuele Tinelli; Amalia Paonessa; Alessia Bernardo Ciddio; Marco Fiorelli; Federico Bianco; Stefania Natalizi; Luigi Ferrante; Luigi Bozzao
Journal:  Radiology       Date:  2006-02-01       Impact factor: 11.105

5.  Invasion of the cavernous sinus space in pituitary adenomas: endoscopic verification and its correlation with an MRI-based classification.

Authors:  Alexander S G Micko; Adelheid Wöhrer; Stefan Wolfsberger; Engelbert Knosp
Journal:  J Neurosurg       Date:  2015-02-06       Impact factor: 5.115

6.  Apparent diffusion coefficient of pituitary macroadenoma evaluated with line-scan diffusion-weighted imaging.

Authors:  C Suzuki; M Maeda; K Hori; Y Kozuka; H Sakuma; W Taki; K Takeda
Journal:  J Neuroradiol       Date:  2007-08-24       Impact factor: 3.447

7.  Clinical significance of Ki-67 labeling index in pituitary macroadenoma.

Authors:  Kyung-Il Paek; Seon-Hwan Kim; Shi-Hun Song; Seung-Won Choi; Hyeon-Song Koh; Jin-Young Youm; Youn Kim
Journal:  J Korean Med Sci       Date:  2005-06       Impact factor: 2.153

Review 8.  Pathohistological classification of pituitary tumors: 10 years of experience with the German Pituitary Tumor Registry.

Authors:  Wolfgang Saeger; Dieter K Lüdecke; Michael Buchfelder; Rudolf Fahlbusch; Hans-Jürgen Quabbe; Stephan Petersenn
Journal:  Eur J Endocrinol       Date:  2007-02       Impact factor: 6.664

Review 9.  Best Practice No 172: pituitary gland pathology.

Authors:  J W Ironside
Journal:  J Clin Pathol       Date:  2003-08       Impact factor: 3.411

Review 10.  Practical pituitary pathology: what does the pathologist need to know?

Authors:  Sylvia L Asa
Journal:  Arch Pathol Lab Med       Date:  2008-08       Impact factor: 5.534

View more
  8 in total

1.  Accuracy of diffusion-weighted imaging-magnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency.

Authors:  Morteza Sanei Taheri; Farnaz Kimia; Mersad Mehrnahad; Hamidreza Saligheh Rad; Hamidreza Haghighatkhah; Afshin Moradi; Anahita Fathi Kazerooni; Mohammadreza Alviri; Abdorrahim Absalan
Journal:  Neuroradiol J       Date:  2018-12-03

2.  Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness.

Authors:  Mariko Doai; Hisao Tonami; Munetaka Matoba; Osamu Tachibana; Hideaki Iizuka; Satoko Nakada; Sohuske Yamada
Journal:  Neuroradiol J       Date:  2019-01-16

3.  Prediction of high proliferative index in pituitary macroadenomas using MRI-based radiomics and machine learning.

Authors:  Lorenzo Ugga; Renato Cuocolo; Domenico Solari; Elia Guadagno; Alessandra D'Amico; Teresa Somma; Paolo Cappabianca; Maria Laura Del Basso de Caro; Luigi Maria Cavallo; Arturo Brunetti
Journal:  Neuroradiology       Date:  2019-08-02       Impact factor: 2.804

4.  Biomarkers of pituitary macroadenomas aggressive behaviour: a conventional MRI and DWI 3T study.

Authors:  Alberto Conficoni; Paola Feraco; Diego Mazzatenta; Matteo Zoli; Sofia Asioli; Corrado Zenesini; Viscardo Paolo Fabbri; Martino Cellerini; Antonella Bacci
Journal:  Br J Radiol       Date:  2020-07-06       Impact factor: 3.039

5.  Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  Oncotarget       Date:  2017-08-24

6.  Radiomics Approach for Prediction of Recurrence in Non-Functioning Pituitary Macroadenomas.

Authors:  Yang Zhang; Ching-Chung Ko; Jeon-Hor Chen; Kai-Ting Chang; Tai-Yuan Chen; Sher-Wei Lim; Yu-Kun Tsui; Min-Ying Su
Journal:  Front Oncol       Date:  2020-12-18       Impact factor: 6.244

7.  Deep Learning for Prediction of Progression and Recurrence in Nonfunctioning Pituitary Macroadenomas: Combination of Clinical and MRI Features.

Authors:  Yan-Jen Chen; Hsun-Ping Hsieh; Kuo-Chuan Hung; Yun-Ju Shih; Sher-Wei Lim; Yu-Ting Kuo; Jeon-Hor Chen; Ching-Chung Ko
Journal:  Front Oncol       Date:  2022-04-20       Impact factor: 5.738

8.  Solid tumor size for prediction of recurrence in large and giant non-functioning pituitary adenomas.

Authors:  Ching-Chung Ko; Chin-Hong Chang; Tai-Yuan Chen; Sher-Wei Lim; Te-Chang Wu; Jeon-Hor Chen; Yu-Ting Kuo
Journal:  Neurosurg Rev       Date:  2021-10-04       Impact factor: 3.042

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.