Literature DB >> 30717054

Prediction of recurrence in solid nonfunctioning pituitary macroadenomas: additional benefits of diffusion-weighted MR imaging.

Ching-Chung Ko1, Tai-Yuan Chen1,2, Sher-Wei Lim3,4, Yu-Ting Kuo1,5, Te-Chang Wu1,6, Jeon-Hor Chen7,8.   

Abstract

OBJECTIVE: A subset of benign, nonfunctioning pituitary macroadenomas (NFMAs) has been shown to undergo early progression/recurrence (P/R) during the first years after surgical resection. The aim of this study was to determine preoperative MR imaging features for the prediction of P/R in benign solid NFMAs, with emphasis on apparent diffusion coefficient (ADC) values.
METHODS: We retrospectively investigated the preoperative MR imaging features for the prediction of P/R in benign solid NFMAs. Only the patients who had undergone preoperative MRI and postoperative MRI follow-ups for more than 1 year (at least every 6-12 months) were included. From November 2010 to December 2016, a total of 30 patients diagnosed with benign solid NFMAs were included (median follow-up time 45 months), and 19 (63.3%) patients had P/R (median time to P/R 24 months).
RESULTS: Benign solid NFMAs with cavernous sinus invasion, failed chiasmatic decompression, large tumor height and tumor volume, high diffusion-weighted imaging (DWI) signal, and lower ADC values/ratios were significantly associated with P/R (p < 0.05). The cutoff points of ADC value and ADC ratio for prediction of P/R are 0.77 × 10-3 mm2/sec and 1.01, respectively, with area under the curve (AUC) values (0.9 and 0.91) (p < 0.01). In multivariate Cox proportional hazards analysis, low ADC value (< 0.77 × 10-3 mm2/sec) is a high-risk factor of P/R (p < 0.05) with a hazard ratio of 14.07.
CONCLUSIONS: Benign solid NFMAs with low ADC values/ratios are at a significantly increased risk of P/R, and aggressive treatments accompanied by close follow-up with imaging studies should be considered.

Entities:  

Keywords:  ADC; ADC = apparent diffusion coefficient; AUC = area under the curve; CE = contrast enhanced; DWI; DWI = diffusion-weighted imaging; GTR = gross-total resection; MRI; NACP = normal-appearing central pons; NFMA = nonfunctioning pituitary macroadenoma; P/R = progression/recurrence; PFS = progression-free survival; ROC = receiver operating characteristic; ROI = region of interest; RT = radiotherapy; STR = subtotal resection; T1WI = T1-weighted imaging; TSA = transsphenoidal approach; pituitary macroadenoma; pituitary surgery; recurrence

Mesh:

Year:  2019        PMID: 30717054     DOI: 10.3171/2018.10.JNS181783

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  4 in total

1.  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

2.  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

3.  A Preoperative MRI-Based Radiomics-Clinicopathological Classifier to Predict the Recurrence of Pituitary Macroadenoma Within 5 Years.

Authors:  Yu Zhang; Yuqi Luo; Xin Kong; Tao Wan; Yunling Long; Jun Ma
Journal:  Front Neurol       Date:  2022-01-05       Impact factor: 4.003

4.  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

  4 in total

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