Literature DB >> 35357535

Can DWI provide additional value to Kaiser score in evaluation of breast lesions.

Yongyu An1, Guoqun Mao2, Weiqun Ao1, Fan Mao1, Hongxia Zhang1, Yougen Cheng1, Guangzhao Yang1.   

Abstract

OBJECTIVES: To explore added value of diffusion-weighted imaging (DWI) as an adjunct to Kaiser score (KS) for differentiation of benign from malignant lesions on breast magnetic resonance imaging (MRI).
METHODS: Two hundred forty-six patients with 273 lesions (155 malignancies) were included in this retrospective study from January 2015 to December 2019. All lesions were proved by pathology. Two radiologists blind to pathological results evaluated lesions according to KS. Lesions with score > 4 were considered malignant. Four thresholds of ADC values -1.3 × 10-3mm2/s, 1.4 × 10-3mm2/s, 1.53 × 10-3mm2/s, and 1.6 × 10-3mm2/s were used to distinguish benign from malignant lesions. For combined diagnosis, a lesion with KS > 4 and ADC values below the preset cutoffs was considered as malignant; otherwise, it was benign. Sensitivity, specificity, and area under the curve (AUC) were compared between KS, DWI, and combined diagnosis.
RESULTS: The AUC of KS was significantly higher than that of DWI alone (0.941 vs 0.901, p = 0.04). The sensitivity of KS (96.8%) and DWI (97.4 - 99.4%) was comparable (p > 0.05) while the specificity of KS (83.9%) was significantly higher than that of DWI (19.5-56.8%) (p < 0.05). Adding DWI as an adjunct to KS resulted in a 0-2.5% increase of specificity and a 0.1-1.3% decrease of sensitivity; however, the difference did not reach statistical significance (p > 0.05).
CONCLUSION: KS showed higher diagnostic performance than DWI alone for discrimination of breast benign and malignant lesions. DWI showed no additional value to KS for characterizing breast lesions. KEY POINTS: • KS showed higher diagnostic performance than DWI alone for differentiation of benign from breast malignant lesions. • DWI alone showed a high sensitivity but a low specificity for characterizing breast lesions. • Diagnostic performance did not improve using DWI as an adjunct to KS.
© 2022. The Author(s), under exclusive licence to European Society of Radiology.

Entities:  

Keywords:  Breast tumor; Clinical decision support system; Diffusion magnetic resonance imaging; Magnetic resonance imaging

Mesh:

Substances:

Year:  2022        PMID: 35357535     DOI: 10.1007/s00330-022-08674-x

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   7.034


  41 in total

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Authors:  Maria Adele Marino; Paola Clauser; Ramona Woitek; Georg J Wengert; Panagiotis Kapetas; Maria Bernathova; Katja Pinker-Domenig; Thomas H Helbich; Klaus Preidler; Pascal A T Baltzer
Journal:  Eur Radiol       Date:  2015-10-29       Impact factor: 5.315

2.  Interobserver Variability Between Breast Imagers Using the Fifth Edition of the BI-RADS MRI Lexicon.

Authors:  Lars J Grimm; Andy L Anderson; Jay A Baker; Karen S Johnson; Ruth Walsh; Sora C Yoon; Sujata V Ghate
Journal:  AJR Am J Roentgenol       Date:  2015-05       Impact factor: 3.959

3.  Lesion type and reader experience affect the diagnostic accuracy of breast MRI: a multiple reader ROC study.

Authors:  Pascal A T Baltzer; Werner Alois Kaiser; Matthias Dietzel
Journal:  Eur J Radiol       Date:  2014-11-14       Impact factor: 3.528

4.  A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.

Authors:  Pascal A T Baltzer; Matthias Dietzel; Werner A Kaiser
Journal:  Eur Radiol       Date:  2013-04-12       Impact factor: 5.315

5.  Observer variability and applicability of BI-RADS terminology for breast MR imaging: invasive carcinomas as focal masses.

Authors:  S J Kim; E A Morris; L Liberman; D J Ballon; L R La Trenta; O Hadar; A Abramson; D D Dershaw
Journal:  AJR Am J Roentgenol       Date:  2001-09       Impact factor: 3.959

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Review 7.  Breast MRI: EUSOBI recommendations for women's information.

Authors:  Ritse M Mann; Corinne Balleyguier; Pascal A Baltzer; Ulrich Bick; Catherine Colin; Eleanor Cornford; Andrew Evans; Eva Fallenberg; Gabor Forrai; Michael H Fuchsjäger; Fiona J Gilbert; Thomas H Helbich; Sylvia H Heywang-Köbrunner; Julia Camps-Herrero; Christiane K Kuhl; Laura Martincich; Federica Pediconi; Pietro Panizza; Luis J Pina; Ruud M Pijnappel; Katja Pinker-Domenig; Per Skaane; Francesco Sardanelli
Journal:  Eur Radiol       Date:  2015-05-23       Impact factor: 5.315

8.  A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions.

Authors:  Ramona Woitek; Claudio Spick; Melanie Schernthaner; Margaretha Rudas; Panagiotis Kapetas; Maria Bernathova; Julia Furtner; Katja Pinker; Thomas H Helbich; Pascal A T Baltzer
Journal:  Eur Radiol       Date:  2017-03-08       Impact factor: 5.315

9.  The Kaiser score reliably excludes malignancy in benign contrast-enhancing lesions classified as BI-RADS 4 on breast MRI high-risk screening exams.

Authors:  Ruxandra Iulia Milos; Francesca Pipan; Anastasia Kalovidouri; Paola Clauser; Panagiotis Kapetas; Maria Bernathova; Thomas H Helbich; Pascal A T Baltzer
Journal:  Eur Radiol       Date:  2020-06-06       Impact factor: 5.315

10.  Impact of the Kaiser score on clinical decision-making in BI-RADS 4 mammographic calcifications examined with breast MRI.

Authors:  G J Wengert; F Pipan; J Almohanna; H Bickel; S Polanec; P Kapetas; P Clauser; K Pinker; T H Helbich; P A T Baltzer
Journal:  Eur Radiol       Date:  2019-12-03       Impact factor: 5.315

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  1 in total

1.  Breast MRI: does a clinical decision algorithm outweigh reader experience?

Authors:  Nina Pötsch; Aida Korajac; Philipp Stelzer; Panagiotis Kapetas; Ruxandra-Iulia Milos; Matthias Dietzel; Thomas H Helbich; Paola Clauser; Pascal A T Baltzer
Journal:  Eur Radiol       Date:  2022-07-19       Impact factor: 7.034

  1 in total

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