Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness.


Journal

European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774

Informations de publication

Date de publication:
Dec 2021
Historique:
received: 23 01 2021
accepted: 21 05 2021
revised: 09 04 2021
pubmed: 13 6 2021
medline: 17 11 2021
entrez: 12 6 2021
Statut: ppublish

Résumé

We evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer. 210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed. A MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively. The MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer. • Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.

Identifiants

pubmed: 34117556
doi: 10.1007/s00330-021-08089-0
pii: 10.1007/s00330-021-08089-0
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

9556-9566

Informations de copyright

© 2021. European Society of Radiology.

Références

Peters NH, Borel Rinkes IH, Zuithoff NP et al (2008) Meta-analysis of MR imaging in the diagnosis of breast lesions. Radiology 246:116–124
doi: 10.1148/radiol.2461061298
Medeiros LR, Duarte CS, Rosa DD et al (2011) Accuracy of magnetic resonance in suspicious breast lesions: a systematic quantitative review and meta-analysis. Breast Cancer Res Treat 126:273–285
doi: 10.1007/s10549-010-1326-9
Bennani-Baiti B, Baltzer PA (2017) MR imaging for diagnosis of malignancy in mammographic microcalcifications: a systematic review and meta-analysis. Radiology 283:692–701
doi: 10.1148/radiol.2016161106
Morris EA, Comstock CE, Lee CH et al (2013) ACR BI-RADS® magnetic resonance imaging. In: ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. American College of Radiology, Reston
Pinker-Domenig K, Bogner W, Gruber S et al (2012) High resolution MRI of the breast at 3 T: which BI-RADS(R) descriptors are most strongly associated with the diagnosis of breast cancer? Eur Radiol 22:322–330
doi: 10.1007/s00330-011-2256-6
Mann RM, Kuhl CK, Kinkel K, Boetes C (2008) Breast MRI: guidelines from the European Society of Breast Imaging. Eur Radiol 18:1307–1318
Sardanelli F, Boetes C, Borisch B et al (2010) Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. Eur J Cancer 46:1296–1316
doi: 10.1016/j.ejca.2010.02.015
Boetes C, Barentsz JO, Mus RD et al (1994) MR characterization of suspicious breast lesions with a gadolinium-enhanced Turbo-FLASH subtraction technique. Radiology 193:777–781
doi: 10.1148/radiology.193.3.7972823
Heywang SH, Wolf A, Pruss E, Eiermann W, Permanetter W (1989) MR imaging of the breast with Gd-DTPA: use and limitations. Radiology 171:95–103
Kaiser WA, Zeitler E (1989) MR imaging of the breast: fast imaging sequences with and without Gd-DTPA—preliminary observations. Radiology 170:681–686
doi: 10.1148/radiology.170.3.2916021
Fischer U, von Heyden D, Vosshenrich R, Vieweg I, Grabbe E (1993) Signalverhalten maligner und benigner la¨sionen in der dynamischen 2D-MRT der mamma. Rofo 158:287–292
Kuhl CK, Mielcareck P, Klaschik S et al (1999) Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? Radiology 211:101–110
doi: 10.1148/radiology.211.1.r99ap38101
Le Y, Kipfer H, Majidi S et al (2013) Application of time-resolved angiography with stochastic trajectories (TWIST)-Dixon in dynamic contrast-enhanced (DCE) breast MRI. J Magn Reson Imaging 38:1033–1042
doi: 10.1002/jmri.24062
Mann RM, Mus RD, van Zelst J, Karssemeijer N, Platel B (2014) A novel approach to contrast-enhanced breast magnetic resonance imaging for screening: high-resolution ultrafast dynamic imaging. Invest Radiol 49:579–585
Goto M, Sakai K, Yokota H et al (2018) Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions. Eur Radiol 29:1164–1174
doi: 10.1007/s00330-018-5643-4
Herrmann KH, Baltzer PA, Dietzel M et al (2011) Resolving arterial phase and temporal enhancement characteristics in DCE MRM at high spatial resolution with TWIST acquisition. JMRI 34:973–982
doi: 10.1002/jmri.22689
Honda M, Kataoka M, Onishi N et al (2020) New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing. JMRI 51:164–174
doi: 10.1002/jmri.26838
Ohashi A, Kataoka M, Kanao S et al (2019) Diagnostic performance of maximum slope: a kinetic parameter obtained from ultrafast dynamic contrast-enhanced magnetic resonance imaging of the breast using k-space weighted image contrast (KWIC). Eur J Radiol 118:285–292
doi: 10.1016/j.ejrad.2019.06.012
Shin SU, Cho N, Kim SY, Chang JM, Moon WK (2020) Time-to-enhancement at ultrafast breast DCE-MRI: potential imaging biomarker of tumour aggressiveness. Eur Radiol 30:4058–4068
Milon A, Vande Perre S, Poujol J et al (2019) Abbreviated breast MRI combining FAST protocol and high temporal resolution (HTR) dynamic contrast enhanced (DCE) sequence. Eur J Radiol 117:199–208
doi: 10.1016/j.ejrad.2019.06.022
Lee SJ, Ko KH, Jung HK, Koh JE, Park AY (2020) The additional utility of ultrafast MRI on conventional DCE-MRI in evaluating preoperative MRI of breast cancer patients. Eur J Radiol 124:1–9
Lauby-Secretan B, Scoccianti C, Loomis D et al (2016) International Agency for Research on Cancer Handbook Working Group. Body fatness and cancer: viewpoint of the IARC Working Group. N Engl J Med 375:794–798
doi: 10.1056/NEJMsr1606602
Trentham-Dietz A, Newcomb PA, Storer BE et al (1997) Body size and risk of breast cancer. Am J Epidemiol 145:1011–1019
doi: 10.1093/oxfordjournals.aje.a009057
Lyengar NM, Arthur R, Manson JE et al (2019) Association of body fat and risk of breast cancer in postmenopausal women with normal body mass index: a secondary analysis of a randomized clinical trial and observational study. JAMA Oncol 5:155–163
doi: 10.1001/jamaoncol.2018.5327
Platel B, Mus RD, Welte T, Karssemeijer N, Mann R (2014) Automated characterization of breast lesions imaged with an ultrafast DCE-MR protocol. IEEE Trans Med Imaging 33:225–232
Mus RD, Borelli C, Bult P et al (2017) Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions. Eur J Radiol 89:90–96
doi: 10.1016/j.ejrad.2017.01.020

Auteurs

Margaux Pelissier (M)

Department of Radiology, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France.

Khalid Ambarki (K)

Siemens Healthcare GmbH, Siemens Healthcare SAS, Saint Denis, France.

Julia Salleron (J)

Department of Biostatistics, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France.

Philippe Henrot (P)

Department of Radiology, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France. p.henrot@nancy.unicancer.fr.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH