RT Journal Article
SR Electronic
T1 Distinguishing Pituitary Metastasis and Pituitary Neuroendocrine Tumors through Conventional MR Imaging and Clinical Features
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 1063
OP 1069
DO 10.3174/ajnr.A8302
VO 45
IS 8
A1 Yuzkan, Sabahattin
A1 Erkan, Buruc
A1 Dogukan, Fatih Mert
A1 Ozkiziltan, Uluc
A1 Balsak, Serdar
A1 Arslan, Fatma Zeynep
A1 Tutuncuoglu, Berk
A1 Arikan, Ceyda Ceren
A1 Karatay, Huseyin
A1 Akpinar, Ebubekir
A1 Ertan, Yesim
A1 Hatipoglu, Esra
A1 Eraslan, Cenk
A1 Kitis, Omer
A1 Calli, Cem
A1 Kocak, Burak
YR 2024
UL http://www.ajnr.org/content/45/8/1063.abstract
AB BACKGROUND AND PURPOSE: Given their overlapping features, pituitary metastases frequently imitate pituitary neuroendocrine tumors in neuroimaging studies. This study aimed to distinguish pituitary metastases from pituitary neuroendocrine tumors on the basis of conventional MR imaging and clinical features as a practical approach.MATERIALS AND METHODS: In this 2-center retrospective study, backward from January 2024, preoperative pituitary MR imaging examinations of 22 pituitary metastases and 74 pituitary neuroendocrine tumors were analyzed. Exclusion criteria were as follows: absence of a definitive histopathologic diagnosis, history of pituitary surgery or radiation therapy before MR imaging, and pituitary neuroendocrine tumors treated with medical therapy. Two radiologists systematically evaluated 13 conventional MR imaging features that have been reported more commonly as indicative of pituitary metastases and pituitary neuroendocrine tumors in the literature. Age, sex, history of cancer, and maximum tumor size constituted the clinical/epidemiologic features. The primary cancer origin for this study was also noted. Univariable and multivariable logistic regression was used for the selection of variables, determining independent predictors, and modeling. Interobserver agreement was evaluated for all imaging parameters using the Cohen κ statistic or intraclass correlation coefficient.RESULTS: A total of 22 patients with pituitary metastases (8 women; mean age, 49.5 [SD, 13] years) and 74 patients with pituitary neuroendocrine tumors (36 women; mean age, 50.1 [SD, 11] years) were enrolled. There was no statistically significant distributional difference in age, sex, or maximum tumor size between the 2 groups. Lung cancer (9/22; 41%) was the most commonly reported primary tumor, followed by breast (3/22; 13.6%) and unknown cancer (3/22; 13.6%). Logistic regression revealed 3 independent predictors: rapid growth on control MR imaging, masslike or nodular expansion of the pituitary stalk, and a history of cancer. The model based on these 3 features achieved an area under the curve, accuracy, sensitivity, specificity, and Brier score of 0.987 (95% CI, 0.964–1), 97.9% (95% CI, 92.7%–99.8%), 95.5% (95% CI, 77.2%–99.9%), 98.6% (95% CI, 92.7%–100%), and 0.025, respectively.CONCLUSIONS: Two conventional features based on pituitary MR imaging with the clinical variable of history of cancer had satisfying predictive performance, making them potential discriminators between pituitary metastases and pituitary neuroendocrine tumors. In cases in which differentiation between pituitary metastases and pituitary neuroendocrine tumors poses a challenge, the results of this study may help with the diagnosis.AUCarea under the curvePitNETpituitary neuroendocrine tumorPMpituitary metastasisROCreceiver operating characteristic