Evidence map›Paper›PMID 38871368›Full record

ArticleAJNR. American journal of neuroradiology2024

Distinguishing Pituitary Metastasis and Pituitary Neuroendocrine Tumors through Conventional MR Imaging and Clinical Features.

Sabahattin Yuzkan, Buruc Erkan, Fatih Mert Dogukan, Uluc Ozkiziltan, Serdar Balsak, Fatma Zeynep Arslan, Berk Tutuncuoglu, Ceyda Ceren Arikan, Huseyin Karatay, Ebubekir Akpinar and 6 more

Abstract readMulticenter Study
In one paragraph

Article in AJNR. American journal of neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Sabahattin YuzkanFrom the Department of Radiology (S.Y.), Koc University Hospital, Istanbul, Turkey.ORCID 0000-0002-3066-1737
Buruc ErkanDepartment of Neurosurgery (B.E., E.A.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.ORCID 0000-0001-8586-0613
Fatih Mert DogukanDepartment of Pathology (F.M.D., H.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Uluc OzkiziltanDepartment of Radiology (U.O., C.E., O.K., C.C.), Ege University School of Medicine, Izmir, Turkey.ORCID 0000-0001-9270-976X
Serdar BalsakDepartment of Radiology (S.B.), Bezmialem Vakif University Hospital, Istanbul, Turkey.ORCID 0000-0001-8765-4418
Fatma Zeynep ArslanDepartment of Radiology (F.Z.A., B.T., C.C.A., B.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Berk TutuncuogluDepartment of Radiology (F.Z.A., B.T., C.C.A., B.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Ceyda Ceren ArikanDepartment of Radiology (F.Z.A., B.T., C.C.A., B.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Huseyin KaratayDepartment of Pathology (F.M.D., H.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Ebubekir AkpinarDepartment of Neurosurgery (B.E., E.A.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
Yesim ErtanDepartment of Pathology (Y.E.), Ege University School of Medicine, Izmir, Turkey.
Esra HatipogluDivision of Endocrinology (E.H.), Department of Internal Medicine, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.ORCID 0000-0001-8361-8866
Cenk EraslanDepartment of Radiology (U.O., C.E., O.K., C.C.), Ege University School of Medicine, Izmir, Turkey.
Omer KitisDepartment of Radiology (U.O., C.E., O.K., C.C.), Ege University School of Medicine, Izmir, Turkey.ORCID 0000-0003-4201-5449
Cem CalliDepartment of Radiology (U.O., C.E., O.K., C.C.), Ege University School of Medicine, Izmir, Turkey.
Burak KocakDepartment of Radiology (F.Z.A., B.T., C.C.A., B.K.), Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey drburakkocak@gmail.com.ORCID 0000-0002-7307-396X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeGiven 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

methodsIn 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.

resultsA 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.

conclusionsTwo 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.

Indexed as

Magnetic Resonance ImagingNeuroendocrine TumorsPituitary NeoplasmsAdultAgedDiagnosis, DifferentialFemaleHumansMaleMiddle AgedRetrospective StudiesSensitivity and Specificity

Identifiers

PMID38871368
PMCPMC11383409

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