Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas.
Consistency
Diffusion-weighted imaging
Magnetic resonance imaging
Pituitary adenoma
Journal
Pituitary
ISSN: 1573-7403
Titre abrégé: Pituitary
Pays: United States
ID NLM: 9814578
Informations de publication
Date de publication:
25 Jan 2024
25 Jan 2024
Historique:
accepted:
20
12
2023
medline:
26
1
2024
pubmed:
26
1
2024
entrez:
25
1
2024
Statut:
aheadofprint
Résumé
To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values as prognostic factors of surgical outcomes. Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3 months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values to pons (ADC A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10 Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.
Identifiants
pubmed: 38273189
doi: 10.1007/s11102-023-01377-6
pii: 10.1007/s11102-023-01377-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Theodros D, Patel M, Ruzevick J, Lim M, Bettegowda C (2015) Pituitary adenomas: historical perspective, surgical management and future directions. CNS Oncol 4(6):411–429. https://doi.org/10.2217/cns.15.21 . (in eng)
doi: 10.2217/cns.15.21
pubmed: 26497533
pmcid: 4750488
Rumboldt Z (2005) Pituitary adenomas. Top Magn Reson Imaging 16(4):277–288. https://doi.org/10.1097/01.rmr.0000224684.76006.cf . (in eng)
doi: 10.1097/01.rmr.0000224684.76006.cf
pubmed: 16785843
Vieira L et al (2016) A review on the diagnosis and treatment of patients with clinically nonfunctioning pituitary adenoma by the Neuroendocrinology Department of the Brazilian Society of Endocrinology and Metabolism. Arch Endocrinol Metab 60(4):374–390. https://doi.org/10.1590/2359-3997000000179 . (in eng)
doi: 10.1590/2359-3997000000179
pubmed: 27533614
Lake MG, Krook LS, Cruz SV (2013) Pituitary adenomas: an overview. Am Fam Physician 88(5):319–327 (in eng)
pubmed: 24010395
Bashari WA et al (2019) Modern imaging of pituitary adenomas. Best Pract Res Clin Endocrinol Metab 33(2):101278. https://doi.org/10.1016/j.beem.2019.05.002 . (in eng)
doi: 10.1016/j.beem.2019.05.002
pubmed: 31208872
Buchfelder M, Schlaffer SM, Zhao Y (2019) The optimal surgical techniques for pituitary tumors. Best Pract Res Clin Endocrinol Metab 33(2):101299. https://doi.org/10.1016/j.beem.2019.101299 . (in eng)
doi: 10.1016/j.beem.2019.101299
pubmed: 31431397
Tampourlou M et al (2017) Outcome of nonfunctioning pituitary adenomas that regrow after primary treatment: a study from two large UK Centers. J Clin Endocrinol Metab 102(6):1889–1897. https://doi.org/10.1210/jc.2016-4061 . (in eng)
doi: 10.1210/jc.2016-4061
pubmed: 28323946
Vargas G et al (2015) Clinical characteristics and treatment outcome of 485 patients with nonfunctioning pituitary macroadenomas. Int J Endocrinol 2015:756069. https://doi.org/10.1155/2015/756069 . (in eng)
doi: 10.1155/2015/756069
pubmed: 25737722
pmcid: 4337176
Ramírez C et al (2012) Expression of Ki-67, PTTG1, FGFR4, and SSTR 2, 3, and 5 in nonfunctioning pituitary adenomas: a high throughput TMA, immunohistochemical study. J Clin Endocrinol Metab 97(5):1745–1751. https://doi.org/10.1210/jc.2011-3163 . (in eng)
doi: 10.1210/jc.2011-3163
pubmed: 22419713
Castinetti F et al (2015) Non-functioning pituitary adenoma: when and how to operate? What pathologic criteria for typing? Ann Endocrinol (Paris) 76(3):220–227. https://doi.org/10.1016/j.ando.2015.04.007 . (in eng)
doi: 10.1016/j.ando.2015.04.007
pubmed: 26070464
Fiore G et al (2023) Predicting tumor consistency and extent of resection in non-functioning pituitary tumors. Pituitary 26(2):209–220. https://doi.org/10.1007/s11102-023-01302-x . (in eng)
doi: 10.1007/s11102-023-01302-x
pubmed: 36808379
AcitoresCancela A, Rodríguez Berrocal V, Pian H, Martínez San Millán JS, Díez JJ, Iglesias P (2021) Clinical relevance of tumor consistency in pituitary adenoma. Hormones (Athens) 20(3):463–473. https://doi.org/10.1007/s42000-021-00302-5 . (in eng)
doi: 10.1007/s42000-021-00302-5
Alimohamadi M et al (2014) Predictive value of diffusion-weighted MRI for tumor consistency and resection rate of nonfunctional pituitary macroadenomas. Acta Neurochir (Wien) 156(12):2245–2252. https://doi.org/10.1007/s00701-014-2259-6 . (in eng)
doi: 10.1007/s00701-014-2259-6
pubmed: 25338532
AcitoresCancela A, Rodríguez Berrocal V, Pian Arias H, Díez JJ, Iglesias P (2022) Effect of pituitary adenoma consistency on surgical outcomes in patients undergoing endonasal endoscopic transsphenoidal surgery. Endocrine 78(3):559–569. https://doi.org/10.1007/s12020-022-03161-1 . (in eng)
doi: 10.1007/s12020-022-03161-1
Pierallini A et al (2006) Pituitary macroadenomas: preoperative evaluation of consistency with diffusion-weighted MR imaging–initial experience. Radiology 239(1):223–231. https://doi.org/10.1148/radiol.2383042204 . (in eng)
doi: 10.1148/radiol.2383042204
pubmed: 16452397
Mohamed FF, Abouhashem S (2013) Diagnostic value of apparent diffusion coefficient (ADC) in assessment of pituitary macroadenoma consistency. Egypt J Radiol Nucl Med 44(3):617–624
doi: 10.1016/j.ejrnm.2013.05.012
Yiping L, Ji X, Daoying G, Bo Y (2016) Prediction of the consistency of pituitary adenoma: a comparative study on diffusion-weighted imaging and pathological results. J Neuroradiol 43(3):186–194. https://doi.org/10.1016/j.neurad.2015.09.003 . (in eng)
doi: 10.1016/j.neurad.2015.09.003
pubmed: 26585529
Bahuleyan B, Raghuram L, Rajshekhar V, Chacko AG (2006) To assess the ability of MRI to predict consistency of pituitary macroadenomas. Br J Neurosurg 20(5):324–326. https://doi.org/10.1080/02688690601000717 . (in eng)
doi: 10.1080/02688690601000717
pubmed: 17129884
Iuchi T, Saeki N, Tanaka M, Sunami K, Yamaura A (1998) MRI prediction of fibrous pituitary adenomas. Acta Neurochir (Wien) 140(8):779–786. https://doi.org/10.1007/s007010050179 . (in eng)
doi: 10.1007/s007010050179
pubmed: 9810444
Thotakura AK, Patibandla MR, Panigrahi MK, Mahadevan A (2017) Is it really possible to predict the consistency of a pituitary adenoma preoperatively? Neurochirurgie 63(6):453–457. https://doi.org/10.1016/j.neuchi.2017.06.003 . (in eng)
doi: 10.1016/j.neuchi.2017.06.003
pubmed: 29122303
Smith KA, Leever JD, Chamoun RB (2015) Prediction of consistency of pituitary adenomas by magnetic resonance imaging. J Neurol Surg B Skull Base 76(5):340–343. https://doi.org/10.1055/s-0035-1549005 . (in eng)
doi: 10.1055/s-0035-1549005
pubmed: 26401474
pmcid: 4569502
Suzuki C et al (2007) Apparent diffusion coefficient of pituitary macroadenoma evaluated with line-scan diffusion-weighted imaging. J Neuroradiol 34(4):228–235. https://doi.org/10.1016/j.neurad.2007.06.007 . (in eng)
doi: 10.1016/j.neurad.2007.06.007
pubmed: 17719632
Wei L, Lin SA, Fan K, Xiao D, Hong J, Wang S (2015) Relationship between pituitary adenoma texture and collagen content revealed by comparative study of MRI and pathology analysis. Int J Clin Exp Med 8(8):12898–12905 (in eng)
pubmed: 26550206
pmcid: 4612891
Mahmoud OM et al (2010) Role of PROPELLER diffusion weighted imaging and apparent diffusion coefficient in the diagnosis of sellar and parasellar lesions. Eur J Radiol 74(3):420–427. https://doi.org/10.1016/j.ejrad.2009.03.031 . (in eng)
doi: 10.1016/j.ejrad.2009.03.031
pubmed: 19394778
Su CQ et al (2020) Texture analysis of high b-value diffusion-weighted imaging for evaluating consistency of pituitary macroadenomas. J Magn Reson Imaging 51(5):1507–1513. https://doi.org/10.1002/jmri.26941 . (in eng)
doi: 10.1002/jmri.26941
pubmed: 31769565
Hagmann P, Jonasson L, Maeder P, Thiran JP, Wedeen VJ, Meuli R (2006) Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 26(Suppl 1):S205–S223. https://doi.org/10.1148/rg.26si065510 . (in eng)
doi: 10.1148/rg.26si065510
pubmed: 17050517
Drake-Pérez M, Boto J, Fitsiori A, Lovblad K, Vargas MI (2018) Clinical applications of diffusion weighted imaging in neuroradiology. Insights Imaging 9(4):535–547. https://doi.org/10.1007/s13244-018-0624-3 . (in eng)
doi: 10.1007/s13244-018-0624-3
pubmed: 29846907
pmcid: 6108979
Provenzale JM, Engelter ST, Petrella JR, Smith JS, MacFall JR (1999) Use of MR exponential diffusion-weighted images to eradicate T2 shine-through effect. AJR Am J Roentgenol 172(2):537–539. https://doi.org/10.2214/ajr.172.2.9930819 . (in eng)
doi: 10.2214/ajr.172.2.9930819
pubmed: 9930819
Minosse S, Marzi S, Piludu F, Vidiri A (2017) Correlation study between DKI and conventional DWI in brain and head and neck tumors. Magn Reson Imaging 42:114–122. https://doi.org/10.1016/j.mri.2017.06.006 . (in eng)
doi: 10.1016/j.mri.2017.06.006
pubmed: 28629955
Schaefer PW, Grant PE, Gonzalez RG (2000) Diffusion-weighted MR imaging of the brain. Radiology 217(2):331–345. https://doi.org/10.1148/radiology.217.2.r00nv24331 . (in eng)
doi: 10.1148/radiology.217.2.r00nv24331
pubmed: 11058626
Lu L, Wan X, Xu Y, Chen J, Shu K, Lei T (2022) Prognostic factors for recurrence in pituitary adenomas: recent progress and future directions. Diagnostics (Basel). https://doi.org/10.3390/diagnostics12040977 . (in eng)
doi: 10.3390/diagnostics12040977
pubmed: 36553149
pmcid: 10078567
Fleseriu M et al (2021) Consensus on diagnosis and management of Cushing’s disease: a guideline update. Lancet Diab Endocrinol 9(12):847–875. https://doi.org/10.1016/S2213-8587(21)00235-7 . (in eng)
doi: 10.1016/S2213-8587(21)00235-7
Giustina A et al (2020) Multidisciplinary management of acromegaly: a consensus. Rev Endocr Metab Disord 21(4):667–678. https://doi.org/10.1007/s11154-020-09588-z . (in eng)
doi: 10.1007/s11154-020-09588-z
pubmed: 32914330
pmcid: 7942783
Melmed S et al (2011) Diagnosis and treatment of hyperprolactinemia: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 96(2):273–288. https://doi.org/10.1210/jc.2010-1692 . (in eng)
doi: 10.1210/jc.2010-1692
pubmed: 21296991
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):610–617. https://doi.org/10.1227/00006123-199310000-00008 . (in eng)
doi: 10.1227/00006123-199310000-00008
pubmed: 8232800
Micko AS, Wöhrer A, Wolfsberger S, Knosp E (2015) Invasion of the cavernous sinus space in pituitary adenomas: endoscopic verification and its correlation with an MRI-based classification. J Neurosurg 122(4):803–811. https://doi.org/10.3171/2014.12.JNS141083 . (in eng)
doi: 10.3171/2014.12.JNS141083
pubmed: 25658782
Edal AL, Skjödt K, Nepper-Rasmussen HJ (1997) SIPAP—a new MR classification for pituitary adenomas. Suprasellar, infrasellar, parasellar, anterior and posterior. Acta Radiol 38(1):30–36. https://doi.org/10.1080/02841859709171238 . (in eng)
doi: 10.1080/02841859709171238
pubmed: 9059398
Bonneville JF (2016) Magnetic resonance imaging of pituitary tumors. Front Horm Res 45:97–120. https://doi.org/10.1159/000442327 . (in eng)
doi: 10.1159/000442327
pubmed: 27003878
Romano A et al (2017) Predictive role of dynamic contrast enhanced T1-weighted MR sequences in pre-surgical evaluation of macroadenomas consistency. Pituitary 20(2):201–209. https://doi.org/10.1007/s11102-016-0760-z . (in eng)
doi: 10.1007/s11102-016-0760-z
pubmed: 27730456
Gadelha MR, Barbosa MA, Lamback EB, Wildemberg LE, Kasuki L, Ventura N (2022) Pituitary MRI standard and advanced sequences: role in the diagnosis and characterization of pituitary adenomas. J Clin Endocrinol Metab 107(5):1431–1440. https://doi.org/10.1210/clinem/dgab901 . (in eng)
doi: 10.1210/clinem/dgab901
pubmed: 34908114
Ma Z et al (2016) Predictive value of PWI for blood supply and T1-spin echo MRI for consistency of pituitary adenoma. Neuroradiology 58(1):51–57. https://doi.org/10.1007/s00234-015-1591-8 . (in eng)
doi: 10.1007/s00234-015-1591-8
pubmed: 26376802
Conficoni A et al (2020) Biomarkers of pituitary macroadenomas aggressive behaviour: a conventional MRI and DWI 3T study. Br J Radiol 93(1113):20200321. https://doi.org/10.1259/bjr.20200321 . (in eng)
doi: 10.1259/bjr.20200321
pubmed: 32628097
pmcid: 7465851
Boxerman JL, Rogg JM, Donahue JE, Machan JT, Goldman MA, Doberstein CE (2010) Preoperative MRI evaluation of pituitary macroadenoma: imaging features predictive of successful transsphenoidal surgery. AJR Am J Roentgenol 195(3):720–728. https://doi.org/10.2214/AJR.09.4128
doi: 10.2214/AJR.09.4128
pubmed: 20729452
Sanei Taheri M et al (2019) Accuracy of diffusion-weighted imaging-magnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency. Neuroradiol J 32(2):74–85. https://doi.org/10.1177/1971400918809825
doi: 10.1177/1971400918809825
pubmed: 30501465
Antunes X et al (2018) Predictors of surgical outcome and early criteria of remission in acromegaly. Endocrine 60(3):415–422. https://doi.org/10.1007/s12020-018-1590-8 . (in eng)
doi: 10.1007/s12020-018-1590-8
pubmed: 29626274
Ko CC, Chen TY, Lim SW, Kuo YT, Wu TC, Chen JH (2019) Prediction of recurrence in solid nonfunctioning pituitary macroadenomas: additional benefits of diffusion-weighted MR imaging. J Neurosurg 132(2):351–359. https://doi.org/10.3171/2018.10.JNS181783 . (in eng)
doi: 10.3171/2018.10.JNS181783
pubmed: 30717054
Zeynalova A et al (2019) Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI. Neuroradiology 61(7):767–774. https://doi.org/10.1007/s00234-019-02211-2 . (in eng)
doi: 10.1007/s00234-019-02211-2
pubmed: 31011772
Hughes JD, Fattahi N, Van Gompel J, Arani A, Ehman R, Huston J (2016) Magnetic resonance elastography detects tumoral consistency in pituitary macroadenomas. Pituitary 19(3):286–292. https://doi.org/10.1007/s11102-016-0706-5 . (in eng)
doi: 10.1007/s11102-016-0706-5
pubmed: 26782836
pmcid: 4860122
Hughes JD et al (2016) Adenoid cystic carcinoma metastatic to the pituitary: a case report and discussion of potential diagnostic value of magnetic resonance elastography in pituitary tumors. World Neurosurg 91:669.e11–4. https://doi.org/10.1016/j.wneu.2016.03.044 . (in eng)
doi: 10.1016/j.wneu.2016.03.044
Yao A et al (2020) Pituitary adenoma consistency: direct correlation of ultrahigh field 7T MRI with histopathological analysis. Eur J Radiol 126:108931. https://doi.org/10.1016/j.ejrad.2020.108931 . (in eng)
doi: 10.1016/j.ejrad.2020.108931
pubmed: 32146344