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Open Access 19-04-2024 | Pituitary Adenoma | Original Article

Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability

Authors: Mehmet Salih Yildirim, Victor Ulrich Schmidbauer, Alexander Micko, Lisa Lechner, Michael Weber, Julia Furtner, Stefan Wolfsberger, Intesar-Victoria Malla Houech, Anna Cho, Gregor Dovjak, Gregor Kasprian, Daniela Prayer, Wolfgang Marik

Published in: Clinical Neuroradiology

Abstract

Purpose

Pre-surgical information about tumor consistency could facilitate neurosurgical planning. This study used multi-dynamic-multi-echo (MDME)-based relaxometry for the quantitative determination of pituitary tumor consistency, with the aim of predicting lesion resectability.

Methods

Seventy-two patients with suspected pituitary adenomas, who underwent preoperative 3 T MRI between January 2020 and January 2022, were included in this prospective study. Lesion-specific T1-/T2-relaxation times (T1R/T2R) and proton density (PD) metrics were determined. During surgery, data about tumor resectability were collected. A Receiver Operating Characteristic (ROC) curve analysis was performed to investigate the diagnostic performance (sensitivity/specificity) for discriminating between easy- and hard-to-remove by aspiration (eRAsp and hRAsp) lesions. A Mann-Whitney-U-test was done for group comparison.

Results

A total of 65 participants (mean age, 54 years ± 15, 33 women) were enrolled in the quantitative analysis. Twenty-four lesions were classified as hRAsp, while 41 lesions were assessed as eRAsp. There were significant differences in T1R (hRAsp: 1221.0 ms ± 211.9; eRAsp: 1500.2 ms ± 496.4; p = 0.003) and T2R (hRAsp: 88.8 ms ± 14.5; eRAsp: 137.2 ms ± 166.6; p = 0.03) between both groups. The ROC analysis revealed an area under the curve of 0.72 (95% CI: 0.60–0.85) at p = 0.003 for T1R (cutoff value: 1248 ms; sensitivity/specificity: 78%/58%) and 0.66 (95% CI: 0.53–0.79) at p = 0.03 for T2R (cutoff value: 110 ms; sensitivity/specificity: 39%/96%).

Conclusion

MDME-based relaxometry enables a non-invasive, pre-surgical characterization of lesion consistency and, therefore, provides a modality with which to predict tumor resectability.

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Melmed S. Pituitary-Tumor Endocrinopathies. n Engl J Med. 2020;382(10):937–50. https://doi.org/10.1056/NEJMra1810772.CrossRefPubMed

Micko A, Oberndorfer J, Weninger WJ, et al. Challenging Knosp high-grade pituitary adenomas. j Neurosurg. 2019;132(6):1739–46. https://doi.org/10.3171/2019.3.JNS19367.CrossRefPubMed

Villar-Taibo R, Díaz-Ortega C, Sifontes-Dubon M, et al. Pituitary surgery in elderly patients: a safe and effective procedure. Endocrine. 2021;72(3):814–22. https://doi.org/10.1007/s12020-021-02665-6.CrossRefPubMed

Tuleasca C, Ducos Y, Leroy HA, et al. Transsphenoidal resection for pituitary adenoma in elderly versus younger patients: a systematic review and meta-analysis. Acta Neurochir (wien). 2020;162(6):1297–308. https://doi.org/10.1007/s00701-020-04300-1.CrossRefPubMed

Rutkowski MJ, Chang KE, Cardinal T, et al. Development and clinical validation of a grading system for pituitary adenoma consistency. j Neurosurg. 2020;134(6):1800–7. https://doi.org/10.3171/2020.4.JNS193288.CrossRefPubMed

Di Maio S, Cavallo LM, Esposito F, Stagno V, Corriero OV, Cappabianca P. Extended endoscopic endonasal approach for selected pituitary adenomas: early experience. j Neurosurg. 2011;114(2):345–53. https://doi.org/10.3171/2010.9.JNS10262.CrossRefPubMed

Yamada S, Fukuhara N, Horiguchi K, et al. Clinicopathological characteristics and therapeutic outcomes in thyrotropin-secreting pituitary adenomas: a single-center study of 90 cases. j Neurosurg. 2014;121(6):1462–73. https://doi.org/10.3171/2014.7.JNS1471.CrossRefPubMed

Ciric I, Mikhael M, Stafford T, Lawson L, Garces R. Transsphenoidal microsurgery of pituitary macroadenomas with long-term follow-up results. j Neurosurg. 1983;59(3):395–401. https://doi.org/10.3171/jns.1983.59.3.0395.CrossRefPubMed

Zhao B, Wei YK, Li GL, et al. Extended transsphenoidal approach for pituitary adenomas invading the anterior cranial base, cavernous sinus, and clivus: a single-center experience with 126 consecutive cases. j Neurosurg. 2010;112(1):108–17. https://doi.org/10.3171/2009.3.JNS0929.CrossRefPubMed

10.

Acitores Cancela A, Rodríguez Berrocal V, Pian Arias H, Díez JJ, Iglesias P. Effect of pituitary adenoma consistency on surgical outcomes in patients undergoing endonasal endoscopic transsphenoidal surgery. Endocrine. 2022;78(3):559–69. https://doi.org/10.1007/s12020-022-03161-1.CrossRefPubMed

11.

Cappelletti M, Ruggeri AG, Spizzichino L, D’Amico A, D’avella E, Delfini R. Fibrous Pituitary Macroadenomas: Predictive Role of Preoperative Radiologic Investigations for Proper Surgical Planning in a Cohort of 66 Patients. World Neurosurg. 2019;121:e449–e57. https://doi.org/10.1016/j.wneu.2018.09.137.CrossRefPubMed

12.

Tanenbaum LN, Tsiouris AJ, Johnson AN, et al. Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial. AJNR Am J Neuroradiol. 2017;38(6):1103–10. https://doi.org/10.3174/ajnr.A5227.CrossRefPubMedPubMedCentral

13.

Warntjes JB, Leinhard OD, West J, Lundberg P. Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magn Reson Med. 2008;60(2):320–9. https://doi.org/10.1002/mrm.21635.CrossRefPubMed

14.

Hagiwara A, Warntjes M, Hori M et al. (2017) SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement. Invest Radiol. 52(10):647–657. https://doi.org/10.1097/RLI.0000000000000365.

15.

Riederer SJ, Suddarth SA, Bobman SA, Lee JN, Wang HZ, MacFall JR. Automated MR image synthesis: feasibility studies. Radiology. 1984;153(1):203–6. https://doi.org/10.1148/radiology.153.1.6089265.CrossRefPubMed

16.

Krauss W, Gunnarsson M, Andersson T, Thunberg P. Accuracy and reproducibility of a quantitative magnetic resonance imaging method for concurrent measurements of tissue relaxation times and proton density. Magn Reson Imaging. 2015;33(5):584–91. https://doi.org/10.1016/j.mri.2015.02.013.CrossRefPubMed

17.

Bobman SA, Riederer SJ, Lee JN, Suddarth SA, Wang HZ, MacFall JR. Synthesized MR images: comparison with acquired images. Radiology. 1985;155(3):731–8. https://doi.org/10.1148/radiology.155.3.4001377.CrossRefPubMed

18.

Schmidbauer V, Geisl G, Diogo M, et al. SyMRI detects delayed myelination in preterm neonates. Eur Radiol. 2019;29(12):7063–72. https://doi.org/10.1007/s00330-019-06325-2.CrossRefPubMedPubMedCentral

19.

Schmidbauer VU, Dovjak GO, Yildirim MS, et al. Mapping Human Fetal Brain Maturation In Vivo Using Quantitative MRI. Ajnr Am J Neuroradiol. 2021;42(11):2086–93. https://doi.org/10.3174/ajnr.A7286.CrossRefPubMedPubMedCentral

20.

Montejo C, Laredo C, Llull L, et al. Synthetic MRI in subarachnoid haemorrhage. Clin Radiol. 76(10):785.e17–785.e23. 2021. https://doi.org/10.1016/j.crad.2021.05.021..

21.

Kang KM, Choi SH, Kim H, et al. The Effect of Varying Slice Thickness and Interslice Gap on T₁ and T₂ Measured with the Multidynamic Multiecho Sequence. Magn Reson Med Sci. 2019;18(2):126–33. https://doi.org/10.2463/mrms.mp.2018-0010.CrossRefPubMed

22.

Micko ASG, Keritam O, Marik W, et al. Dumbbell-shaped pituitary adenomas: prognostic factors for prediction of tumor nondescent of the supradiaphragmal component from a multicenter series. j Neurosurg. 2021; https://doi.org/10.3171/2021.9.JNS211689.CrossRefPubMed

23.

Micko AS, Wöhrer A, Wolfsberger S, Knosp E. Invasion of the cavernous sinus space in pituitary adenomas: endoscopic verification and its correlation with an MRI-based classification. j Neurosurg. 2015;122(4):803–11. https://doi.org/10.3171/2014.12.JNS141083.CrossRefPubMed

24.

Knosp E, Steiner E, Kitz K, Matula C. (1993) Pituitary adenomas with invasion of the cavernous sinus space: a magnetic resonance imaging classification compared with surgical findings. Neurosurgery. 33(4):610–618. https://doi.org/10.1227/00006123-199310000-00008.

25.

Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess. 1994;6(4):284–90. https://doi.org/10.1037/1040-3590.6.4.284.CrossRef

26.

Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.CrossRefPubMed

27.

Stüber C, Morawski M, Schäfer A et al. (2014) Myelin and iron concentration in the human brain: a quantitative study of MRI contrast. Neuroimage. 93 Pt 1:95–106. https://doi.org/10.1016/j.neuroimage.2014.02.026.

28.

Yamada H, Tanikawa M, Sakata T, Aihara N, Mase M. Usefulness of T2 Relaxation Time for Quantitative Prediction of Meningioma Consistency. World Neurosurg. 2022;157:e484–e91. https://doi.org/10.1016/j.wneu.2021.10.135.CrossRefPubMed

29.

Bai Y, Shen Y, Chen R, et al. Magnetic resonance fingerprinting for preoperative differentiation between gonadotroph and non-gonadotroph pituitary macroadenomas. Eur Radiol. 2021;31(11):8420–8. https://doi.org/10.1007/s00330-021-07950-6.CrossRefPubMed

30.

Stucht D, Danishad KA, Schulze P, Godenschweger F, Zaitsev M, Speck O. Highest Resolution In Vivo Human Brain MRI Using Prospective Motion Correction. plos One. 2015;10(7):e133921. https://doi.org/10.1371/journal.pone.0133921.CrossRefPubMedPubMedCentral

31.

Micko A, Hosmann A, Marik W, et al. Optimizing MR imaging for intraoperative image guidance in sellar pathologies. Pituitary. 2020;23(3):266–72. https://doi.org/10.1007/s11102-020-01035-1.CrossRefPubMedPubMedCentral

32.

Kucharczyk W, Bishop JE, Plewes DB, Keller MA, George S. Detection of pituitary microadenomas: comparison of dynamic keyhole fast spin-echo, unenhanced, and conventional contrast-enhanced MR imaging. ajr Am J Roentgenol. 1994;163(3):671–9. https://doi.org/10.2214/ajr.163.3.8079866.CrossRefPubMed

33.

Mete O, Lopes MB. Overview of the 2017 WHO Classification of Pituitary Tumors. Endocr Pathol. 2017;28(3):228–43. https://doi.org/10.1007/s12022-017-9498-z.CrossRefPubMed

34.

Dutta G, Singh D, Singh H, Srivastava AK, Jagetia A, Sachdeva D. Pituitary fossa chondrosarcoma: An unusual cause of a sellar suprasellar mass masquerading as pituitary adenoma. Surg Neurol Int. 2018;9:76. https://doi.org/10.4103/sni.sni_455_17.CrossRefPubMedPubMedCentral

35.

Orakdöğeny M, Karadereler S, Berkman Z, Erşahin M, Ozdoğan C, Aker F. Intra-suprasellar meningioma mimicking pituitary apoplexy. Acta Neurochir (wien). 2004;146(5):511–5. https://doi.org/10.1007/s00701-004-0239-y.CrossRefPubMed

Title: Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability
Authors: Mehmet Salih Yildirim
Victor Ulrich Schmidbauer
Alexander Micko
Lisa Lechner
Michael Weber
Julia Furtner
Stefan Wolfsberger
Intesar-Victoria Malla Houech
Anna Cho
Gregor Dovjak
Gregor Kasprian
Daniela Prayer
Wolfgang Marik
Publication date: 19-04-2024
Publisher: Springer Berlin Heidelberg
Keywords: Pituitary Adenoma
Aspiration
Magnetic Resonance Imaging
Magnetic Resonance Imaging
Published in: Clinical Neuroradiology
Print ISSN: 1869-1439
Electronic ISSN: 1869-1447
DOI: https://doi.org/10.1007/s00062-024-01407-1

At a glance: The STEP trials

Springer Medicine

Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability

Abstract

Purpose

Methods

Results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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