Application of the Kaiser score to increase diagnostic accuracy in equivocal lesions on diagnostic mammograms referred for MR mammography

•Kaiser score overcomes potential shortcomings of moderate inter-reader agreement of BIRADS lexicon and provides higher diagnostic accuracy.•Score =8 was highly suggestive of malignancy in 100 % of previously assigned ACR-BIRADS 4 lesions , thus significantly improving certainty.•Unnecessary biopsie...

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Published in:European journal of radiology 2021-01, Vol.134, p.109413, Article 109413
Main Authors: Jajodia, Ankush, Sindhwani, Geetika, Pasricha, Sunil, Prosch, Helmut, Puri, Sunil, Dewan, Ajay, Batra, Ullas, Doval, Dinesh Chandra, Mehta, Anurag, Chaturvedi, Arvind K
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Language:English
Subjects:
Area Under Curve
Breast cancer
Breast Neoplasms - diagnostic imaging
Clinical decision-making
Humans
Image-guided biopsy
Magnetic Resonance Imaging
Mammography
Retrospective Studies
ROC Curve
Scoring system
Sensitivity and Specificity
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container_title European journal of radiology
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creator Jajodia, Ankush
Sindhwani, Geetika
Pasricha, Sunil
Prosch, Helmut
Puri, Sunil
Dewan, Ajay
Batra, Ullas
Doval, Dinesh Chandra
Mehta, Anurag
Chaturvedi, Arvind K
description •Kaiser score overcomes potential shortcomings of moderate inter-reader agreement of BIRADS lexicon and provides higher diagnostic accuracy.•Score =8 was highly suggestive of malignancy in 100 % of previously assigned ACR-BIRADS 4 lesions , thus significantly improving certainty.•Unnecessary biopsies could have been avoided using the Kaiser score clinical decision tool in 60.8 % cases. We aimed to interpret MR mammography (MRM) using the Kaiser scores for equivocal or inconclusive lesions on mammography (MG). Retrospective IRB-approved evaluation of 3623 MG for which MRM was deployed as a problem-solving tool, after inclusion-exclusion criteria were met. Three readers with different levels of experience assigned a final score from 1 to 11 based on the previously established tree classification system. Area under the curve (AUC) derived from receiver operating characteristic (ROC) analysis was used to determine the overall diagnostic performance for all lesions and separately for mass and non-mass enhancement. Sensitivity, specificity, and likelihood ratio values were obtained at different cut-off values of >4, > 5, and > 8 to rule in and rule out malignancy. Histopathology of 183 mass and 133 non-mass enhancement (NME) lesions show benign etiology in 95 and malignant in 221. The AUC was 0.796 [0.851 for mass and 0.715 for NME]. Applying the Kaiser score upgraded 202 lesions with correct prediction in 77 %, and downgraded 28 lesions with correct prediction in 60.8 %. Using a score
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We aimed to interpret MR mammography (MRM) using the Kaiser scores for equivocal or inconclusive lesions on mammography (MG). Retrospective IRB-approved evaluation of 3623 MG for which MRM was deployed as a problem-solving tool, after inclusion-exclusion criteria were met. Three readers with different levels of experience assigned a final score from 1 to 11 based on the previously established tree classification system. Area under the curve (AUC) derived from receiver operating characteristic (ROC) analysis was used to determine the overall diagnostic performance for all lesions and separately for mass and non-mass enhancement. Sensitivity, specificity, and likelihood ratio values were obtained at different cut-off values of &gt;4, &gt; 5, and &gt; 8 to rule in and rule out malignancy. Histopathology of 183 mass and 133 non-mass enhancement (NME) lesions show benign etiology in 95 and malignant in 221. The AUC was 0.796 [0.851 for mass and 0.715 for NME]. 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subjects Area Under Curve
Breast cancer
Breast Neoplasms - diagnostic imaging
Clinical decision-making
Humans
Image-guided biopsy
Magnetic Resonance Imaging
Mammography
Retrospective Studies
ROC Curve
Scoring system
Sensitivity and Specificity
title Application of the Kaiser score to increase diagnostic accuracy in equivocal lesions on diagnostic mammograms referred for MR mammography
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