Breast magnetic resonance imaging as a problem solving tool in women recalled at biennial screening mammography: A population-based study in the Netherlands

Gommers, Jessie J. J.; Voogd, Adri C.; Broeders, Mireille J. M.; Smallenburg, Vivian van Breest; Strobbe, Luc J. A.; Rossum, Astrid B. Donkers van; Beek, Hermen C van; Mann, Ritse M.; Duijm, Luciën E. M.

doi:10.1016/j.breast.2021.11.014

Cited by 12 publications

(13 citation statements)

References 23 publications

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“…Thus, lesions with a rating < 3 were considered benign and lesions with a rating ≥ 3 were considered malignant KS as a decision algorithm, seemingly does not require expert training. This is important considering the increasing demand on MRIb examinations because of the medical and economic evidence in favor of extended MRIb indications [3,[31][32][33][34][35][36].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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Objectives Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS. Methods Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves. Results A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723–0.742) as well as the three residents was equal (AUC 0.842–0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts’ ratings using the MR BI-RADS scale (p ≤ 0.05). Conclusion The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical “problem solving MRI” setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience. Key Points • Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical “problem solving MRI” setting. • The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.

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Section: Discussionmentioning

confidence: 99%

“…And, our results show that MRIb interpretation, relying on the KS as a decision algorithm, seemingly does not require expert training. This is important considering the increasing demand on MRIb examinations because of the medical and economic evidence in favor of extended MRIb indications [ 3 , 31 – 36 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…Zu den klassischen Indikationen für die MRT der Mamma gehört das Staging von Brustkrebs, besonders in prämenopausalen Frauen, hoher Brustdichte, invasiv lobulärem Phänotyp und suspizierter Multizentrizität 4 10 . Die vormals etwas globale Indikation der MRT als Problemlöser kann mittlerweile konkretisiert werden: Im Falle positiver Befunde der konventionellen Brustbildgebung kann die Anwendung der MRT dank hohem negativem Vorhersagewert unnötige Kontrollen und Biopsien vermeiden 11 12 13 14 . Sie erhöht somit, im Gegensatz zu früheren Annahmen, Spezifität und positiven Vorhersagewert 11 12 .…”

Section: Introductionunclassified

“…Sie erhöht somit, im Gegensatz zu früheren Annahmen, Spezifität und positiven Vorhersagewert 11 12 . Gerade die Anwendung der MRT als additives Screeningverfahren auch bei Frauen mit intermediärem Risiko sowie die Anwendung zur Vermeidung unnötiger Biopsien ist mittlerweile auf hohem Evidenzniveau belegt 11 12 15 16 . Davon unbenommen sind weitere vorbestehende Indikation wie die Abklärung von Implantaten, klinischen Symptomen wie pathologische Sekretion ohne konventionell bildgebendes Korrelat oder die Verlaufsbeurteilung von neoadjuvanten Therapien, welche deutlich weniger evidenzbasiert sind 3 4 .…”

Section: Introductionunclassified

“…Current evidence demonstrates that in case of positive or unclear findings on conventional breast imaging, performing MRI can avoid unnecessary follow-up and biopsies thanks to its high negative predictive value [11][12][13][14]. The method thus increases the specificity and positive predictive value in contrast to earlier assumptions [11,12]. There is currently a high level of evidence for the use of MRI as an additional screening method in women with an intermediate risk and the use of MRI to prevent unnecessary biopsies [11,12,15,16].…”

Section: Introductionmentioning

confidence: 99%

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Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score

Baltzer

Krug

Dietzel

2022

Rofo

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Background Breast MRI is the most sensitive method for the detection of breast cancer and is an integral part of modern breast imaging. On the other hand, interpretation of breast MRI exams is considered challenging due to the complexity of the available information. Clinical decision rules that combine diagnostic criteria in an algorithm can help the radiologist to read breast MRI by supporting objective and largely experience-independent diagnosis. Method Narrative review. In this article, the Kaiser Score (KS) as a clinical decision rule for breast MRI is introduced, its diagnostic criteria are defined, and strategies for clinical decision making using the KS are explained and discussed. Results The KS is based on machine learning and has been independently validated by international research. It is largely independent of the examination technique that is used. It allows objective differentiation between benign and malignant contrast-enhancing breast MRI findings using diagnostic BI-RADS criteria taken from T2w and dynamic contrast-enhanced T1w images. A flowchart guides the reader in up to three steps to determine a score corresponding to the probability of malignancy that can be used to assign a BI-RADS category. Individual decision making takes the clinical context into account and is illustrated by typical scenarios. Key Points: Citation Format

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Automated analysis of the total choline resonance peak in breast proton magnetic resonance spectroscopy

Javor,

Bennani‐Baiti,

Clauser

et al. 2023

NMR in Biomedicine

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The aim of the current study was to compare the performance of fully automated software with human expert interpretation of single‐voxel proton magnetic resonance spectroscopy (1H‐MRS) spectra in the assessment of breast lesions. Breast magnetic resonance imaging (MRI) (including contrast‐enhanced T1‐weighted, T2‐weighted, and diffusion‐weighted imaging) and 1H‐MRS images of 74 consecutive patients were acquired on a 3‐T positron emission tomography‐MRI scanner then automatically imported into and analyzed by SpecTec‐ULR 1.1 software (LifeTec Solutions GmbH). All ensuing 117 spectra were additionally independently analyzed and interpreted by two blinded radiologists. Histopathology of at least 24 months of imaging follow‐up served as the reference standard. Nonparametric Spearman's correlation coefficients for all measured parameters (signal‐to‐noise ratio [SNR] and integral of total choline [tCho]), Passing and Bablok regression, and receiver operating characteristic analysis, were calculated to assess test diagnostic performance, as well as to compare automated with manual reading. Based on 117 spectra of 74 patients, the area under the curve for tCho SNR and integrals ranged from 0.768 to 0.814 and from 0.721 to 0.784 to distinguish benign from malignant tissue, respectively. Neither method displayed significant differences between measurements (automated vs. human expert readers, p > 0.05), in line with the results from the univariate Spearman's rank correlation coefficients, as well as the Passing and Bablok regression analysis. It was concluded that this pilot study demonstrates that 1H‐MRS data from breast MRI can be automatically exported and interpreted by SpecTec‐ULR 1.1 software. The diagnostic performance of this software was not inferior to human expert readers.

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Breast magnetic resonance imaging as a problem solving tool in women recalled at biennial screening mammography: A population-based study in the Netherlands

Cited by 12 publications

References 23 publications

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

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

Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score

Automated analysis of the total choline resonance peak in breast proton magnetic resonance spectroscopy

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