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Zhang B, Guo Z, Lei Z, Liang W, Chen X. Kaiser score diagnosis of breast MRI lesions: Factors associated with false-negative and false-positive results. Eur J Radiol 2024; 178:111641. [PMID: 39053308 DOI: 10.1016/j.ejrad.2024.111641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 07/05/2024] [Accepted: 07/19/2024] [Indexed: 07/27/2024]
Abstract
PURPOSE We sought factors associated with false-negative and false-positive results in the diagnosis of breast lesions using the Kaiser score (KS) on breast magnetic resonance imaging (MRI). METHODS We retrospectively analyzed 1058 patients with 1058 breast lesions who underwent preoperative breast MRI with successful histopathologic results. Two radiologists assessed each lesion according to KS criteria, and clinicopathologic features and MRI findings were analyzed. Multivariate regression analysis was conducted to identify factors associated with false-negative and false-positive KS results. RESULTS Of the 1058 lesions, 859 were malignant and 199 were benign. Particularly high misdiagnosis rates were observed for intraductal papilloma, inflammatory lesion, and mucinous carcinoma. For breast cancer, KS yielded 821 (95.6 %) true-positive and 38 (4.4 %) false-negative results. Multivariate analysis showed that smaller lesion size (≤1 cm) (OR, 3.698; 95 %CI, 1.430-9.567; p = 0.007), absence of ipsilateral breast hypervascularity (OR, 3.029; 95 %CI, 1.370-6.693; p = 0.006), and presence of hyperintensity on T2WI (OR, 2.405; 95 %CI, 1.121-5.162; p = 0.024) were significantly associated with false-negative breast cancer results. For benign lesions, KS yielded 141 (70.9 %) true-negative and 58 (29.1 %) false-positive results. Multivariate regression analysis revealed that non-mass enhancement lesions (OR, 4.660; 95 %CI, 2.018-10.762; p<0.001), moderate/high background parenchymal enhancement (OR, 2.402; 95 %CI, 1.180-4.892; p = 0.016), and the presence of hyperintensity on T2WI (OR, 2.986; 95 %CI, 1.386-6.433; p = 0.005) were significantly associated with false-positive KS results. CONCLUSION Several clinicopathologic and MRI features influence the accuracy of KS diagnosis. Understanding these factors may facilitate appropriate use of KS and guide alternative diagnostic approaches, ultimately improving diagnostic accuracy in the evaluation of breast lesions.
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Affiliation(s)
- Bing Zhang
- Department of Radiology, Second Affiliated Hospital of Xi'an Jiao tong University, Xi'an, Shaanxi, China
| | - Zhuanzhuan Guo
- Department of Radiology, Second Affiliated Hospital of Xi'an Jiao tong University, Xi'an, Shaanxi, China
| | - Zhe Lei
- Department of Radiology, Second Affiliated Hospital of Xi'an Jiao tong University, Xi'an, Shaanxi, China
| | - Wenbin Liang
- Department of Radiology, Second Affiliated Hospital of Xi'an Jiao tong University, Xi'an, Shaanxi, China
| | - Xin Chen
- Department of Radiology, Second Affiliated Hospital of Xi'an Jiao tong University, Xi'an, Shaanxi, China.
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Coskun Bilge A, Aydin H. Assessment of the contribution of the ADC value to the Kaiser score in the differential diagnosis of breast lesions with non-mass enhancement morphology on MRI. Eur J Radiol 2024; 181:111713. [PMID: 39241300 DOI: 10.1016/j.ejrad.2024.111713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 08/28/2024] [Accepted: 08/30/2024] [Indexed: 09/09/2024]
Abstract
PURPOSE To investigate the effectiveness of diffusion-weighted imaging (DWI) as a supplementary tool to the Kaiser score (KS) in diagnosing breast cancer in non-mass enhancement (NME) lesions using breast magnetic resonance imaging (MRI). METHODS This single-center, retrospective study analyzed 360 cases with NME on MRI images. Two breast radiologists independently evaluated each lesion using the Kaiser score (KS) and apparent diffusion coefficient (ADC) values, without knowledge of the pathological outcomes. NME lesions with a KS above 4 and an ADC value below 1.3 × 10-3mm2/s were classified as malignant. Inter-rater reliability was determined using Cohen's Kappa (κ) statistics. The diagnostic performance of KS, DWI, and their combination was assessed by calculating sensitivity, specificity, and the area under the curve (AUC), and the results were compared across the benign and malignant groups. RESULTS The diagnostic performance of KS surpassed that of DWI in predicting the malignancy of NMEs (p = 0.003). The sensitivity of KS alone was 93 %; however, when ADC data was incorporated, the sensitivity decreased to 86 %, with no significant difference observed (p = 0.060). The specificity of the combined KS and ADC (94 %) was significantly higher than that of KS alone (89 %) and DWI alone (73 %) (p < 0.001). CONCLUSION Our findings indicated that although the combination of KS and ADC increased specificity and reduced unnecessary biopsies, the resulting decrease in sensitivity was unacceptable. Therefore, KS alone is superior to the KS-ADC combination in detecting malignancy in NME lesions.
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Affiliation(s)
- Almila Coskun Bilge
- Department of Radiology, Dr Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Turkey.
| | - Hale Aydin
- Department of Radiology, University of Health Sciences, Gulhane Faculty of Medicine, Ankara, Turkey.
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Hijazi M, Chahine R, Berjawi G, Jabbour Y, El Annan T, Ibrahim R, Nassar L. Reliability of Kaiser Score in Assessing Additional Breast Lesions Identified on Staging MRI in Patients with Breast Cancer. Diagnostics (Basel) 2024; 14:1726. [PMID: 39202214 PMCID: PMC11353333 DOI: 10.3390/diagnostics14161726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Revised: 07/28/2024] [Accepted: 08/01/2024] [Indexed: 09/03/2024] Open
Abstract
(1) Background: The Kaiser score is a user-friendly tool that evaluates lesions on breast MRI and has been studied in the general population and a few specific clinical scenarios. We aim to evaluate the performance of the Kaiser score in the characterization of additional lesions identified on staging breast MRI. (2) Methods: The Kaiser score of the biopsied additional lesions identified on staging MRI in recently diagnosed breast cancer patients was retrospectively determined. Statistical analysis was performed to evaluate the diagnostic capability of the Kaiser score and whether it is affected by different imaging and pathological parameters of the additional and the index lesion. (3) Results: Seventy-six patients with ninety-two MRI-detected lesions constitute the studied population. There was a statistically significant difference in the Kaiser score between benign and malignant lesions, irrespective of the pathology of the index cancer (p = 0.221) or the size and the imaging features of the additional lesion. Using a cutoff of 5 and above for suspicious lesions, biopsy could have been avoided in 34/92 lesions. (4) Conclusions: The Kaiser score can assist radiologists in the evaluation of additional MRI lesions identified in recently diagnosed breast cancer patients, thus decreasing the number of unneeded biopsies and delays in definitive surgical management.
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Affiliation(s)
- Madiha Hijazi
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
| | - Reve Chahine
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
| | - Ghina Berjawi
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
| | - Yara Jabbour
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
| | - Tamara El Annan
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
| | - Roy Ibrahim
- Department of Diagnostic Radiology, Lebanese American University Medical Center, Beirut 1100, Lebanon;
| | - Lara Nassar
- Department of Diagnostic Radiology, American University of Beirut Medical Center, Beirut 1107, Lebanon; (M.H.); (R.C.); (G.B.); (Y.J.); (T.E.A.)
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Zhou J, Liu H, Miao H, Ye S, He Y, Zhao Y, Chen Z, Zhang Y, Liu YL, Pan Z, Su MY, Wang M. Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience. Eur Radiol 2024:10.1007/s00330-024-10922-1. [PMID: 38990324 DOI: 10.1007/s00330-024-10922-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 03/23/2024] [Accepted: 05/28/2024] [Indexed: 07/12/2024]
Abstract
OBJECTIVES To compare the diagnostic performance of three readers using BI-RADS and Kaiser score (KS) based on mass and non-mass enhancement (NME) lesions. METHODS A total of 630 lesions, 393 malignant and 237 benign, 458 mass and 172 NME, were analyzed. Three radiologists with 3 years, 6 years, and 13 years of experience made diagnoses. 596 cases had diffusion-weighted imaging, and the apparent diffusion coefficient (ADC) was measured. For lesions with ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 as the modified KS +, and the benefit was assessed. RESULTS When using BI-RADS, AUC was 0.878, 0.915, and 0.941 for mass, and 0.771, 0.838, 0.902 for NME for Reader-1, 2, and 3, respectively, better for mass than for NME. The diagnostic accuracy of KS was improved compared to BI-RADS for less experienced readers. For Reader-1, AUC was increased from 0.878 to 0.916 for mass (p = 0.005) and from 0.771 to 0.822 for NME (p = 0.124). Based on the cut-off value of BI-RADS ≥ 4B and KS ≥ 5 as malignant, the sensitivity of KS by Readers-1 and -2 was significantly higher for both Mass and NME. When ADC was considered to change to modified KS +, the AUC and the accuracy for all three readers were improved, showing higher specificity with slightly degraded sensitivity. CONCLUSION The benefit of KS compared to BI-RADS was most noticeable for the less experienced readers in improving sensitivity. Compared to KS, KS + can improve specificity for all three readers. For NME, the KS and KS + criteria need to be further improved. CLINICAL RELEVANCE STATEMENT KS provides an intuitive method for diagnosing lesions on breast MRI. BI-RADS and KS face greater difficulties in evaluating NME compared to mass lesions. Adding ADC to the KS can improve specificity with slightly degraded sensitivity. KEY POINTS KS provides an intuitive method for interpreting breast lesions on MRI, most helpful for novice readers. KS, compared to BI-RADS, improved sensitivity in both mass and NME groups for less experienced readers. NME lesions were considered during the development of the KS flowchart, but may need to be better defined.
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Affiliation(s)
- Jiejie Zhou
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Department of Radiological Sciences, University of California, Irvine, CA, US
| | - Huiru Liu
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Haiwei Miao
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shuxin Ye
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yun He
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Youfan Zhao
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhongwei Chen
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yang Zhang
- Department of Radiological Sciences, University of California, Irvine, CA, US
| | - Yan-Lin Liu
- Department of Radiological Sciences, University of California, Irvine, CA, US
| | - Zhifang Pan
- First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Min-Ying Su
- Department of Radiological Sciences, University of California, Irvine, CA, US.
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.
| | - Meihao Wang
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
- Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
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Dietzel M, Laun FB, Heiß R, Wenkel E, Bickelhaupt S, Hack C, Uder M, Ohlmeyer S. Initial experience with a next-generation low-field MRI scanner: Potential for breast imaging? Eur J Radiol 2024; 173:111352. [PMID: 38330534 DOI: 10.1016/j.ejrad.2024.111352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 01/24/2024] [Accepted: 01/29/2024] [Indexed: 02/10/2024]
Abstract
PURPOSE Broader clinical adoption of breast magnetic resonance imaging (MRI) faces challenges such as limited availability and high procedural costs. Low-field technology has shown promise in addressing these challenges. We report our initial experience using a next-generation scanner for low-field breast MRI at 0.55T. METHODS This initial cases series was part of an institutional review board-approved prospective study using a 0.55T scanner (MAGNETOM Free.Max, Siemens Healthcare, Erlangen/Germany: height < 2 m, weight < 3.2 tons, no quench pipe) equipped with a seven-channel breast coil (Noras, Höchberg/Germany). A multiparametric breast MRI protocol consisting of dynamic T1-weighted, T2-weighted, and diffusion-weighted sequences was optimized for 0.55T. Two radiologists with 12 and 20 years of experience in breast MRI evaluated the examinations. RESULTS Twelve participants (mean age: 55.3 years, range: 36-78 years) were examined. The image quality was diagnostic in all examinations and not impaired by relevant artifacts. Typical imaging phenotypes were visualized. The scan time for a complete, non-abbreviated breast MRI protocol ranged from 10:30 to 18:40 min. CONCLUSION This initial case series suggests that low-field breast MRI is feasible at diagnostic image quality within an acceptable examination time.
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Affiliation(s)
- Matthias Dietzel
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Frederik B Laun
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Rafael Heiß
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Evelyn Wenkel
- Radiologie München, Burgstrasse 7, 80331 München, Germany.
| | - Sebastian Bickelhaupt
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Carolin Hack
- Department of Gynecology, Erlangen University Hospital, Friedrich Alexander University of Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Universitätsstraße 21/23, 91054 Erlangen, Germany.
| | - Michael Uder
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Sabine Ohlmeyer
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
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Dietzel M, Bernathova M, Clauser P, Kapetas P, Uder M, Baltzer PAT. Added value of clinical decision rules for the management of enhancing breast MRI lesions: A systematic comparison of the Kaiser score and the Göttingen score. Eur J Radiol 2023; 169:111185. [PMID: 37939606 DOI: 10.1016/j.ejrad.2023.111185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 10/16/2023] [Accepted: 11/02/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE We investigated the added value of two internationally used clinical decision rules in the management of enhancing lesions on breast MRI. METHODS This retrospective, institutional review board approved study included consecutive patients from two different populations. Patients received breast MRI according to the recommendations of the European Society of Breast Imaging (EUSOBI). Initially, all examinations were assessed by expert readers without using clinical decision rules. All lesions rated as category 4 or 5 according to the Breast Imaging Reporting and Data System were histologically confirmed. These lesions were re-evaluated by an expert reader blinded to the histology. He assigned each lesion a Göttingen score (GS) and a Kaiser score (KS) on different occasions. To provide an estimate on inter-reader agreement, a second fellowship-trained reader assessed a subset of these lesions. Subgroup analyses based on lesion type (mass vs. non-mass), size (>1 cm vs. ≤ 1 cm), menopausal status, and significant background parenchymal enhancement were conducted. The areas under the ROC curves (AUCs) for the GS and KS were compared, and the potential to avoid unnecessary biopsies was determined according to previously established cutoffs (KS > 4, GS > 3) RESULTS: 527 lesions in 506 patients were included (mean age: 51.8 years, inter-quartile-range: 43.0-61.0 years). 131/527 lesions were malignant (24.9 %; 95 %-confidence-interval: 21.3-28.8). In all subgroups, the AUCs of the KS (median = 0.91) were higher than those of the GS (median = 0.83). Except for "premenopausal patients" (p = 0.057), these differences were statistically significant (p ≤ 0.01). Kappa agreement was higher for the KS (0.922) than for the GS (0.358). CONCLUSION Both the KS and the GS provided added value for the management of enhancing lesions on breast MRI. The KS was superior to the GS in terms of avoiding unnecessary biopsies and showed superior inter-reader agreement; therefore, it may be regarded as the clinical decision rule of choice.
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Affiliation(s)
- Matthias Dietzel
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Maria Bernathova
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
| | - Michael Uder
- Department of Radiology, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany.
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Waehringer-Guertel 18-20, Vienna, Austria.
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Meng L, Zhao X, Guo J, Lu L, Cheng M, Xing Q, Shang H, Zhang B, Chen Y, Zhang P, Zhang X. Improved Differential Diagnosis Based on BI-RADS Descriptors and Apparent Diffusion Coefficient for Breast Lesions: A Multiparametric MRI Analysis as Compared to Kaiser Score. Acad Radiol 2023; 30 Suppl 2:S93-S103. [PMID: 37236897 DOI: 10.1016/j.acra.2023.03.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 05/28/2023]
Abstract
RATIONALE AND OBJECTIVES To develop the nomogram utilizing the American College of Radiology BI-RADS descriptors, clinical features, and apparent diffusion coefficient (ADC) to differentiate benign from malignant breast lesions. MATERIALS AND METHODS A total of 341 lesions (161 malignant and 180 benign) were included. Clinical data and imaging features were reviewed. Univariable and multivariable logistic regression analyses were performed to determine the independent variables. ADC as a continuous or classified into binary form with a cutoff value of 1.30 × 10-3 mm2/s, incorporated other independent predictors to construct two nomograms, respectively. Receiver operating curve and calibration plot was employed to test the models' discriminative ability. The diagnostic performance between the developed model and the Kaiser score (KS) was also compared. RESULTS In both models, high patient age, the presence of root sign, time-intensity curves (TICs) types (plateau and washout), heterogenous internal enhancement, the presence of peritumoral edema, and ADC were independently associated with malignancy. The AUCs of two multivariable models (AUC, 0.957; 95% CI: 0.929-0.976 and AUC, 0.958; 95% CI: 0.931-0.976) were significantly higher than that of the KS (AUC, 0.919, 95% CI: 0.885-0.946; both P < 0.001). At the same sensitivity of 95.7%, our models showed an increase in specificity by 5.56% (P = 0.076) and 6.11% (P = 0.035), respectively, as compared to the KS. CONCLUSION The models incorporating MRI features (root sign, TIC, margins, internal enhancement, and presence of edema), quantitative ADC value, and patient age showed improved diagnostic performance and might have avoided more unnecessary biopsies in comparison with the KS, although further external validation is required.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.); Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China (L.M., P.Z.).
| | - Xin Zhao
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Jinxia Guo
- General Electric (GE) Healthcare, Beijing, China (J.G.).
| | - Lin Lu
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Meiying Cheng
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Qingna Xing
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Honglei Shang
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Bohao Zhang
- Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (B.Z.).
| | - Yan Chen
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
| | - Penghua Zhang
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.); Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China (L.M., P.Z.).
| | - Xiaoan Zhang
- Department of Radiology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China (L.M., X.Z., L.L., M.C., Q.X., H.S., Y.C., P.Z., X.Z.).
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Pan J, Huang X, Yang S, Ouyang F, Ouyang L, Wang L, Chen M, Zhou L, Du Y, Chen X, Deng L, Hu Q, Guo B. The added value of apparent diffusion coefficient and microcalcifications to the Kaiser score in the evaluation of BI-RADS 4 lesions. Eur J Radiol 2023; 165:110920. [PMID: 37320881 DOI: 10.1016/j.ejrad.2023.110920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/22/2023] [Accepted: 06/04/2023] [Indexed: 06/17/2023]
Abstract
PURPOSE To explore the added value of combining microcalcifications or apparent diffusion coefficient (ADC) with the Kaiser score (KS) for diagnosing BI-RADS 4 lesions. METHODS This retrospective study included 194 consecutive patients with 201 histologically verified BI-RADS 4 lesions. Two radiologists assigned the KS value to each lesion. Adding microcalcifications, ADC, or both these criteria to the KS yielded KS1, KS2, and KS3, respectively. The potential of all four scores to avoid unnecessary biopsies was assessed using the sensitivity and specificity. Diagnostic performance was evaluated by the area under the curve (AUC) and compared between KS and KS1. RESULTS The sensitivity of KS, KS1, KS2, and KS3 ranged from 77.1% to 100.0%.KS1 yielded significantly higher sensitivity than other methods (P < 0.05), except for KS3 (P > 0.05), most of all, when assessing NME lesions. For mass lesions, the sensitivity of these four scores was comparable (p > 0.05). The specificity of KS, KS1, KS2, and KS3 ranged from 56.0% to 69.4%, with no statistically significant differences(P > 0.05), except between KS1 and KS2 (p < 0.05).The AUC of KS1 (0.877) was significantly higher than that of KS (0.837; P = 0.0005), particularly for assessing NME (0.847 vs 0.713; P < 0.0001). CONCLUSION KS can stratify BI-RADS 4 lesions to avoid unnecessary biopsies. Adding microcalcifications, but not adding ADC, as an adjunct to KS improves diagnostic performance, particularly for NME lesions. ADC provides no additional diagnostic benefit to KS. Thus, only combining microcalcifications with KS is most conducive to clinical practice.
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Affiliation(s)
- Jialing Pan
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Xiyi Huang
- Department of Clinical Laboratory, Lecong Hospital of Shunde, Foshan, Guangdong, China
| | - Shaomin Yang
- Department of Radiology, Lecong Hospital of Shunde, Foshan, Guangdong, China
| | - Fusheng Ouyang
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Lizhu Ouyang
- Department of Ultrasound, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Liwen Wang
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Ming Chen
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Lanni Zhou
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Yongxing Du
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Xinjie Chen
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Lingda Deng
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China
| | - Qiugen Hu
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.
| | - Baoliang Guo
- Department of Radiology, Shunde Hospital, Southern Medical University(The First People's Hospital of Shunde, Foshan), Foshan, Guangdong, China.
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9
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Zhou XZ, Liu LH, He S, Yao HF, Chen LP, Deng C, Li SL, Zhang XY, Lai H. Diagnostic value of Kaiser score combined with breast vascular assessment from breast MRI for the characterization of breast lesions. Front Oncol 2023; 13:1165405. [PMID: 37483510 PMCID: PMC10359820 DOI: 10.3389/fonc.2023.1165405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/06/2023] [Indexed: 07/25/2023] Open
Abstract
Objectives The Kaiser scoring system for breast magnetic resonance imaging is a clinical decision-making tool for diagnosing breast lesions. However, the Kaiser score (KS) did not include the evaluation of breast vascularity. Therefore, this study aimed to use KS combined with breast vascular assessment, defined as KS*, and investigate the effectiveness of KS* in differentiating benign from malignant breast lesions. Methods This retrospective study included 223 patients with suspicious breast lesions and pathologically verified results. The histopathological diagnostic criteria were according to the fifth edition of the WHO classification of breast tumors. The KS* was obtained after a joint evaluation combining the original KS and breast vasculature assessment. The receiver operating characteristic (ROC) curve was used for comparing differences in the diagnostic performance between KS* and KS, and the area under the receiver operating characteristic (AUC) was compared. Results There were 119 (53.4%) benign and 104 (46.6%) malignant lesions in total. The overall sensitivity, specificity, and accuracy of increased ipsilateral breast vascularity were 69.2%, 76.5%, and 73.1%, respectively. The overall sensitivity, specificity, and accuracy of AVS were 82.7%, 76.5%, and 79.4%, respectively. For all lesions included the AUC of KS* was greater than that of KS (0.877 vs. 0.858, P = 0.016). The largest difference in AUC was observed in the non-mass subgroup (0.793 vs. 0.725, P = 0.029). Conclusion Ipsilaterally increased breast vascularity and a positive AVS sign were significantly associated with malignancy. KS combined with breast vascular assessment can effectively improve the diagnostic ability of KS for breast lesions, especially for non-mass lesions.
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Affiliation(s)
- Xin-zhu Zhou
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Lian-hua Liu
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuang He
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui-fang Yao
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Li-ping Chen
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Chen Deng
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuang-Ling Li
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Hua Lai
- Department of Radiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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10
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Avdan Aslan A, Gültekin S. Diagnostic performance of Kaiser score in patients with newly diagnosed breast cancer: Factors associated with false-negative results. Eur J Radiol 2023; 164:110864. [PMID: 37209464 DOI: 10.1016/j.ejrad.2023.110864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/28/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023]
Abstract
PURPOSE To investigate the factors associated with false-negative results in the diagnosis of breast cancer via breast magnetic resonance imaging (MRI) using the Kaiser score (KS). METHODS This institutional review board (IRB)-approved, single-center, retrospective study enrolled 219 consecutive histopathologically proven breast cancer lesions in 205 women who underwent preoperative breast MRI. Two breast radiologists evaluated each lesion according to the KS. The clinicopathological characteristics and imaging findings were also analyzed. Interobserver variability was assessed using the intraclass correlation coefficient (ICC). Multivariate regression analysis was used to investigate factors associated with false-negative KS results for breast cancer diagnosis. RESULTS Of 219 breast cancers, KS yielded 200 (91.3%) true-positive and 19 (8.7%) false-negative results. The interobserver ICC for the KS between the two readers was good, with a value of 0.804 (95% CI 0.751-0.846). Multivariate regression analysis revealed that small lesion size (≤1 cm) (adjusted OR 6.86, 95% CI 2.14-21.94, p = 0.001) and personal breast cancer history (adjusted OR 7.59, 95% CI, 1.55-37.23, p = 0.012) were significantly associated with false-negative KS results. CONCLUSION Small lesion size (≤1 cm) and presence of personal breast cancer history are factors significantly associated with false-negative KS results. Our results suggest that radiologists should consider these factors in clinical practice as potential pitfalls of KS, which may be compensated for by a multimodal approach combined with clinical evaluation.
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Affiliation(s)
- Aydan Avdan Aslan
- Department of Radiology, Faculty of Medicine, Gazi University, Ankara, Turkey.
| | - Serap Gültekin
- Department of Radiology, Faculty of Medicine, Gazi University, Ankara, Turkey
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11
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Lyu Y, Chen Y, Meng L, Guo J, Zhan X, Chen Z, Yan W, Zhang Y, Zhao X, Zhang Y. Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies. Front Oncol 2023; 13:1074060. [PMID: 36816972 PMCID: PMC9929366 DOI: 10.3389/fonc.2023.1074060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
Objectives To investigate whether combining radiomics extracted from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) with an artificial neural network enables differentiation of MR BI-RADS 4 breast lesions and thereby avoids false-positive biopsies. Methods This retrospective study consecutively included patients with MR BI-RADS 4 lesions. The ultrafast imaging was performed using Differential sub-sampling with cartesian ordering (DISCO) technique and the tenth and fifteenth postcontrast DISCO images (DISCO-10 and DISCO-15) were selected for further analysis. An experienced radiologist used freely available software (FAE) to perform radiomics extraction. After principal component analysis (PCA), a multilayer perceptron artificial neural network (ANN) to distinguish between malignant and benign lesions was developed and tested using a random allocation approach. ROC analysis was performed to evaluate the diagnostic performance. Results 173 patients (mean age 43.1 years, range 18-69 years) with 182 lesions (95 benign, 87 malignant) were included. Three types of independent principal components were obtained from the radiomics based on DISCO-10, DISCO-15, and their combination, respectively. In the testing dataset, ANN models showed excellent diagnostic performance with AUC values of 0.915-0.956. Applying the high-sensitivity cutoffs identified in the training dataset demonstrated the potential to reduce the number of unnecessary biopsies by 63.33%-83.33% at the price of one false-negative diagnosis within the testing dataset. Conclusions The ultrafast DCE-MRI radiomics-based machine learning model could classify MR BI-RADS category 4 lesions into benign or malignant, highlighting its potential for future application as a new tool for clinical diagnosis.
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Affiliation(s)
- Yidong Lyu
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Chen
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Lingsong Meng
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jinxia Guo
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Xiangyu Zhan
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhuo Chen
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenjun Yan
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuyan Zhang
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China,*Correspondence: Xin Zhao, ; Yanwu Zhang,
| | - Yanwu Zhang
- Department I of Breast, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China,*Correspondence: Xin Zhao, ; Yanwu Zhang,
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12
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Kang Y, Li Z, Yang G, Xue J, Zhang L, Rong X. Diagnostic performance of the Kaiser score in the evaluation of breast lesions on contrast-enhanced mammography. Eur J Radiol 2022; 156:110524. [PMID: 36126352 DOI: 10.1016/j.ejrad.2022.110524] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/14/2022] [Accepted: 09/09/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVES We aimed to investigate whether the Kaiser score (KS) could improve the diagnostic performance of breast imaging reporting and data system (BI-RADS) in evaluating breast enhancing lesions on contrast-enhanced mammography (CEM). METHODS Three hundred fifty-nine patients with 375 lesions (231 malignant and 144 benign) were included in this retrospective study from April 2019 to December 2021.Two readers with different levels of experience in breast imaging were asked to give a BI-RADS assessment category according to the CEM BI-RADS and final score based on the KS. The diagnostic performance of all lesions, mass and non-mass enhancement (NME) were assessed by receiver operating characteristic (ROC) analysis, and the areas under the ROC curve (AUCs) were measured. The weighted kappa coefficients were calculated to investigate the interreader agreement. RESULTS The AUCs of the KS for all lesions were 0.915 (95 %CI: 0.884-0.947) and 0.876 (95 %CI: 0.838-0.914) for two readers. When mass and NME were evaluated separately, the AUCs of the KS for mass were higher than those for NME (p < 0.001). The AUCs of BI-RADS for all lesion diagnoses ranged between 0.821 (95 %CI: 0.778-0.864) and 0.842(95 %CI: 0.801-0.883) for two readers. The AUCs of the KS were higher than those of BI-RADS (p < 0.001, p = 0.016). There were no significant differences in the sensitivity between the KS (97.4 %) and BI-RADS (99.6 %) for all lesions (p = 0.130). The specificity of the KS was significantly higher than that of BI-RADS (p < 0.001). Compared with BI-RADS, the application of the KS could have potentially obviated 41.7 % to 47.9 % unnecessary biopsies in 144 benign lesions. Interreader agreement between the two readers of the KS was almost perfect (k = 0.883 [95 % CI: 0.842-0.924]). CONCLUSION The use of the KS provided a high diagnostic performance in distinguishing malignant and benign breast lesions on CEM and outperformed BI-RADS. The application of the KS can downgrade up to 47.9% of unnecessary biopsies of benign breast lesions.
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Affiliation(s)
- Yihe Kang
- Department of Radiology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Zhigang Li
- Department of Radiology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Guang Yang
- Department of Radiology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Jing Xue
- Department of Radiology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Lingling Zhang
- Department of Pathology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China
| | - Xiaocui Rong
- Department of Radiology. The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China.
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13
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Meng L, Zhao X, Guo J, Lu L, Cheng M, Xing Q, Shang H, Wang K, Zhang B, Lei D, Zhang X. Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score. Front Oncol 2022; 12:964078. [PMID: 36303839 PMCID: PMC9595598 DOI: 10.3389/fonc.2022.964078] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/26/2022] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions. Materials and methods In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests. Results There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone. Conclusions Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinxia Guo
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- General Electric (GE) Healthcare, MR Research China, Beijing, China
| | - Bohao Zhang
- Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongmei Lei
- Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Xiaoan Zhang,
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14
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Assessment of breast lesions by the Kaiser score for differential diagnosis on MRI: the added value of ADC and machine learning modeling. Eur Radiol 2022; 32:6608-6618. [PMID: 35726099 PMCID: PMC9815725 DOI: 10.1007/s00330-022-08899-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/10/2022] [Accepted: 05/19/2022] [Indexed: 01/07/2023]
Abstract
OBJECTIVES To evaluate the diagnostic performance of Kaiser score (KS) adjusted with the apparent diffusion coefficient (ADC) (KS+) and machine learning (ML) modeling. METHODS A dataset of 402 malignant and 257 benign lesions was identified. Two radiologists assigned the KS. If a lesion with KS > 4 had ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 to become KS+. In order to consider the full spectrum of ADC as a continuous variable, the KS and ADC values were used to train diagnostic models using 5 ML algorithms. The performance was evaluated using the ROC analysis, compared by the DeLong test. The sensitivity, specificity, and accuracy achieved using the threshold of KS > 4, KS+ > 4, and ADC ≤ 1.4 × 10-3 mm2/s were obtained and compared by the McNemar test. RESULTS The ROC curves of KS, KS+, and all ML models had comparable AUC in the range of 0.883-0.921, significantly higher than that of ADC (0.837, p < 0.0001). The KS had sensitivity = 97.3% and specificity = 59.1%; and the KS+ had sensitivity = 95.5% with significantly improved specificity to 68.5% (p < 0.0001). However, when setting at the same sensitivity of 97.3%, KS+ could not improve specificity. In ML analysis, the logistic regression model had the best performance. At sensitivity = 97.3% and specificity = 65.3%, i.e., compared to KS, 16 false-positives may be avoided without affecting true cancer diagnosis (p = 0.0015). CONCLUSION Using dichotomized ADC to modify KS to KS+ can improve specificity, but at the price of lowered sensitivity. Machine learning algorithms may be applied to consider the ADC as a continuous variable to build more accurate diagnostic models. KEY POINTS • When using ADC to modify the Kaiser score to KS+, the diagnostic specificity according to the results of two independent readers was improved by 9.4-9.7%, at the price of slightly degraded sensitivity by 1.5-1.8%, and overall had improved accuracy by 2.6-2.9%. • When the KS and the continuous ADC values were combined to train models by machine learning algorithms, the diagnostic specificity achieved by the logistic regression model could be significantly improved from 59.1 to 65.3% (p = 0.0015), while maintaining at the high sensitivity of KS = 97.3%, and thus, the results demonstrated the potential of ML modeling to further evaluate the contribution of ADC. • When setting the sensitivity at the same levels, the modified KS+ and the original KS have comparable specificity; therefore, KS+ with consideration of ADC may not offer much practical help, and the original KS without ADC remains as an excellent robust diagnostic method.
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15
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Pötsch N, Korajac A, Stelzer P, Kapetas P, Milos RI, Dietzel M, Helbich TH, Clauser P, Baltzer PAT. Breast MRI: does a clinical decision algorithm outweigh reader experience? Eur Radiol 2022; 32:6557-6564. [PMID: 35852572 PMCID: PMC9474540 DOI: 10.1007/s00330-022-09015-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 05/30/2022] [Accepted: 07/02/2022] [Indexed: 11/28/2022]
Abstract
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. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-022-09015-8.
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Affiliation(s)
- Nina Pötsch
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Aida Korajac
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Philipp Stelzer
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Panagiotis Kapetas
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Matthias Dietzel
- Institute of Radiology, Erlangen University Hospital, Maximiliansplatz 2, 91054, Erlangen, Germany
| | - Thomas H Helbich
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Paola Clauser
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria
| | - Pascal A T Baltzer
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, A-1090, Vienna, Austria.
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16
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Zhong Y, Li M, Zhu J, Zhang B, Liu M, Wang Z, Wang J, Zheng Y, Cheng L, Li X. A simplified scoring protocol to improve diagnostic accuracy with the breast imaging reporting and data system in breast magnetic resonance imaging. Quant Imaging Med Surg 2022; 12:3860-3872. [PMID: 35782247 PMCID: PMC9246725 DOI: 10.21037/qims-21-1036] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 04/19/2022] [Indexed: 12/31/2023]
Abstract
BACKGROUND The breast imaging reporting and data system (BI-RADS) lexicon provides a standardized terminology for describing leision characteristics but does not provide defined rules for converting specific imaging features into diagnostic categories. The inter-reader agreement of the BI-RADS is moderate. In this study, we explored the use of a simplified protocol and scoring system for BI-RADS categorization which integrates the morphologic features (MF), kinetic time-intensity curve (TIC), and apparent diffusion coefficient (ADC) values with equal weights, with a view to providing a convenient and practical method for breast magnetic resonance imaging (MRI) and improving the inter-reader agreement and diagnostic performance of BI-RADS. METHODS This cross-sectional, retrospective, single-center study included 879 patients with 898 histopathologically verified lesions who underwent an MRI scan on a 3.0 Tesla GE Discovery 750 MRI scanner between January 1, 2017, and June 30, 2020. The BI-RADS categorization of the studied lesions was assessed according to the sum of the assigned scores (the presence of malignant MF, lower ADC, and suspicious TIC each warranted a score of +1). Total scores of +2 and +3 were classified as category 5, scores of +1 were classified as category 4, and scores of +0 but with other lesions of interest were classified as category 3. The receiver operating characteristic (ROC) curves were plotted, and the sensitivity, specificity, and accuracy of this categorization were investigated to assess its efficacy and its consistency with pathology. RESULTS There were 472 malignant, 104 risk, and 322 benign lesions. Our simplified scoring protocol had high diagnostic accuracy, with an area under curve (AUC) value of 0.896. In terms of the borderline effect of pathological risk and category 4 lesions, our results showed that when risk lesions were classified together with malignant ones, the AUC value improved (0.876 vs. 0.844 and 0.909 vs. 0.900). When category 4 and 5 lesions were classified as malignant, the specificity, accuracy, and AUC value decreased (82.3% vs. 93.2%, 89.3% vs. 90.2%, and 0.876 vs. 0.909, respectively). Therefore, to improve the diagnostic accuracy of the protocol for BI-RADS categorization, only category 5 lesions should be considered to be malignant. CONCLUSIONS Our simplified scoring protocol that integrates MF, TIC, and ADC values with equal weights for BI-RADS categorization could improve both the diagnostic performance of the protocol for BI-RADS categorization in clinical practice and the understanding of the benign-risk-malignant breast diseases.
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Affiliation(s)
- Yuting Zhong
- Medical School of Chinese People’s Liberation Army, Beijing, China
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Menglu Li
- Department of Radiology, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Jingjin Zhu
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
| | - Boya Zhang
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
- School of Medicine, Nankai University, Tianjin, China
| | - Mei Liu
- Department of Pathology, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Zhili Wang
- Department of Ultrasound, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Jiandong Wang
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Yiqiong Zheng
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Liuquan Cheng
- Department of Radiology, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Xiru Li
- Department of General Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
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Stelzer P, Clauser P, Vatteroni G, Kapetas P, Helbich T, Baltzer P. How much can abbreviated protocols for breast MRI increase patient throughput? A multi-centric evaluation. Eur J Radiol 2022; 154:110436. [DOI: 10.1016/j.ejrad.2022.110436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 06/23/2022] [Accepted: 07/04/2022] [Indexed: 11/03/2022]
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Baltzer PAT, Krug KB, Dietzel M. Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score. ROFO-FORTSCHR RONTG 2022; 194:1216-1228. [PMID: 35613905 DOI: 10.1055/a-1829-5985] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
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 · The KS as an evidence-based decision rule to objectively distinguish benign from malignant breast lesions is based on information contained in T2w und dynamic contrast-enhanced T1w sequences and is largely independent of specific examination protocols.. · The KS diagnostic criteria are in line with the MRI BI-RADS lexicon. We focused on defining a default category to be applied in the case of equivocal imaging criteria.. · The KS reflects increasing probabilities of malignancy and, together with the clinical context, assists individual decision making.. CITATION FORMAT · Baltzer PA, Krug KB, Dietzel M. Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1829-5985.
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Affiliation(s)
- Pascal Andreas Thomas Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Medical University of Vienna, Wien, Austria
| | - Kathrin Barbara Krug
- Department of Diagnostic and Interventional Radiology, University Hospital Cologne, Köln, Germany
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Meng L, Zhao X, Lu L, Xing Q, Wang K, Guo Y, Shang H, Chen Y, Huang M, Sun Y, Zhang X. A Comparative Assessment of MR BI-RADS 4 Breast Lesions With Kaiser Score and Apparent Diffusion Coefficient Value. Front Oncol 2021; 11:779642. [PMID: 34926290 PMCID: PMC8675081 DOI: 10.3389/fonc.2021.779642] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 11/10/2021] [Indexed: 12/24/2022] Open
Abstract
Objectives To investigate the diagnostic performance of the Kaiser score and apparent diffusion coefficient (ADC) to differentiate Breast Imaging Reporting and Data System (BI-RADS) Category 4 lesions at dynamic contrast-enhanced (DCE) MRI. Methods This was a single-institution retrospective study of patients who underwent breast MRI from March 2020 to June 2021. All image data were acquired with a 3-T MRI system. Kaiser score of each lesion was assigned by an experienced breast radiologist. Kaiser score+ was determined by combining ADC and Kaiser score. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of Kaiser score+, Kaiser score, and ADC. The area under the curve (AUC) values were calculated and compared by using the Delong test. The differences in sensitivity and specificity between different indicators were determined by the McNemar test. Results The study involved 243 women (mean age, 43.1 years; age range, 18-67 years) with 268 MR BI-RADS 4 lesions. Overall diagnostic performance for Kaiser score (AUC, 0.902) was significantly higher than for ADC (AUC, 0.81; p = 0.004). There were no significant differences in AUCs between Kaiser score and Kaiser score+ (p = 0.134). The Kaiser score was superior to ADC in avoiding unnecessary biopsies (p < 0.001). Compared with the Kaiser score alone, the specificity of Kaiser score+ increased by 7.82%, however, at the price of a lower sensitivity. Conclusion For MR BI-RADS category 4 breast lesions, the Kaiser score was superior to ADC mapping regarding the potential to avoid unnecessary biopsies. However, the combination of both indicators did not significantly contribute to breast cancer diagnosis of this subgroup.
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Affiliation(s)
- Lingsong Meng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- Magnetic Resonance (MR) Research China, General Electric (GE) Healthcare, Beijing, China
| | - Yafei Guo
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Chen
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mengyue Huang
- Department of Magnetic Resonance Imaging (MRI), The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yongbing Sun
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Hernández L, Díaz GM, Posada C, Llano-Sierra A. Magnetic resonance imaging in diagnosis of indeterminate breast (BIRADS 3 & 4A) in a general population. Insights Imaging 2021; 12:149. [PMID: 34674056 PMCID: PMC8531154 DOI: 10.1186/s13244-021-01098-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 09/07/2021] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVE Currently, mammography and ultrasonography are the most used imaging techniques for breast cancer screening. However, these examinations report many indeterminate studies with a low probability of being malignant, i.e., BIRADS 3 and 4A. This prospective study aims to evaluate the value of breast magnetic resonance imaging (MRI) to clarify the BIRADS categorization of indeterminate mammography or ultrasonography studies. METHODS MRI studies acquired prospectively from 105 patients previously classified as BIRADS 3 or 4A were analyzed independently by four radiologists with different experience levels. Interobserver agreement was determined by the first-order agreement coefficient (AC1), and divergent results were re-analyzed for consensus. The possible correlation between the MRI and the mammography/ultrasound findings was evaluated, and each study was independently classified in one of the five BIRADS categories (BIRADS 1 to 5). In lesions categorized as BIRADS 4 or 5 at MRI, histopathological diagnosis was established by image-guided biopsy; while short-term follow-up was performed in lesions rated as BIRADS 3. RESULTS Breast MRI was useful in diagnosing three invasive ductal carcinomas, upgraded from BIRADS 4A to BIRADS 5. It also allowed excluding malignancy in 86 patients (81.9%), avoiding 22 unnecessary biopsies and 64 short-term follow-ups. The MRI showed good diagnostic performance with the area under roc curve, sensitivity, specificity, PPV, and NPV of 0.995, 100%, 83.5%, 10.5%, and 100%, respectively. CONCLUSIONS MRI showed to be useful as a problem-solving tool to clarify indeterminate findings in breast cancer screening and avoiding unnecessary short-follow-ups and percutaneous biopsies.
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Affiliation(s)
- Liliana Hernández
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia
| | - Gloria M Díaz
- MIRP Lab-Parque i, Instituto Tecnológico Metropolitano, Medellín, Colombia.
| | - Catalina Posada
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia.,Universidad CES, Medellín, Colombia
| | - Alejandro Llano-Sierra
- Grupo de Investigación del Instituto de Alta Tecnología Médica (IATM), Ayudas Diagnósticas Sura, Medellín, Colombia.,Universidad CES, Medellín, Colombia
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Istomin A, Masarwah A, Vanninen R, Okuma H, Sudah M. Diagnostic performance of the Kaiser score for characterizing lesions on breast MRI with comparison to a multiparametric classification system. Eur J Radiol 2021; 138:109659. [PMID: 33752000 DOI: 10.1016/j.ejrad.2021.109659] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/05/2021] [Accepted: 03/15/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE To determine the diagnostic performance of the Kaiser score and to compare it with the BI-RADS-based multiparametric classification system (MCS). METHOD Two breast radiologists, blinded to the clinical and pathological information, separately evaluated a database of 499 consecutive patients with structural 3.0 T breast MRI and 697 histopathologically verified lesions. The Kaiser scores and corresponding MCS categories were recorded. The sensitivity and specificity of the Kaiser score and the MCS categories to differentiate benign from malignant lesions were calculated. The interobserver reproducibility and receiver operating characteristic (ROC) parameters were analysed. RESULTS The sensitivity and specificity of the MCS were 100 % and 12 %, respectively, and those of the Kaiser score were 98.5 % and 34.8 % for reader 1 and 98.7 % and 47.5 % for reader 2. The area under the ROC-curve was 85.9 and 87.6 for readers 1 and 2. The interobserver intraclass correlation coefficient was excellent at 0.882. Reader 1 upgraded six lesions from BI-RADS 3 to a Kaiser score of >4, and reader 2 upgraded seven lesions. When applying the Kaiser score to 158 benign lesions readers 1 and 2 would have reduced the biopsy rate by 22.8 % and 35.4 %, respectively. CONCLUSIONS The Kaiser score showed high diagnostic accuracy with excellent interobserver reproducibility. The MCS had perfect sensitivity but low specificity. Although the Kaiser score had slightly lower sensitivity, its specificity was 3-4 times greater than that of the MCS. Thus, the Kaiser score has the potential to considerably reduce the biopsy rate for true negative lesions.
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Affiliation(s)
- Aleksandr Istomin
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Amro Masarwah
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Ritva Vanninen
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland; University of Eastern Finland, Cancer Center of Eastern Finland, Kuopio, Finland; University of Eastern Finland, Institute of Clinical Medicine, School of Medicine, Kuopio, Finland
| | - Hidemi Okuma
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland
| | - Mazen Sudah
- Kuopio University Hospital, Diagnostic Imaging Center, Department of Clinical Radiology, Kuopio, Finland; University of Eastern Finland, Cancer Center of Eastern Finland, Kuopio, Finland.
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[Artificial intelligence in breast imaging : Areas of application from a clinical perspective]. Radiologe 2021; 61:192-198. [PMID: 33507318 PMCID: PMC7851036 DOI: 10.1007/s00117-020-00802-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2020] [Indexed: 12/22/2022]
Abstract
Klinisches/methodisches Problem Bei der Mammadiagnostik gilt es, klinische sowie multimodal bildgebende Informationen mit perkutanen und operativen Eingriffen zu koordinieren. Aus dieser Komplexität entsteht eine Reihe von Problemen: übersehene Karzinome, Überdiagnose, falsch-positive Befunde, unnötige weiterführende Bildgebung, Biopsien und Operationen. Radiologische Standardverfahren Folgende Untersuchungsverfahren werden in der Mammadiagnostik eingesetzt: Röntgenmammographie, Tomosynthese, kontrastangehobene Mammographie, (multiparametrischer) Ultraschall, Magnetresonanztomographie, Computertomographie, nuklearmedizinische Verfahren sowie deren Hybridvarianten. Methodische Innovationen Künstliche Intelligenz (KI) verspricht Abhilfe bei praktisch allen Problemen der Mammadiagnostik. Potenziell lassen sich Fehlbefunde vermeiden, bildgebende Verfahren effizienter einsetzen und möglicherweise auch biologische Phänotypen von Mammakarzinomen definieren. Leistungsfähigkeit Auf KI basierende Software wird für zahlreiche Anwendungen entwickelt. Am weitesten fortgeschritten sind Systeme für das Screening mittels Mammographie. Probleme sind monozentrische sowie kurzfristig am finanziellen Erfolg orientierte Ansätze. Bewertung Künstliche Intelligenz (KI) verspricht eine Verbesserung der Mammadiagnostik. Durch die Vereinfachung von Abläufen, die Reduktion monotoner und ergebnisloser Tätigkeiten und den Hinweis auf mögliche Fehler ist eine Beschleunigung von dann weitgehend fehlerfreien Abläufen denkbar. Empfehlung für die Praxis In diesem Beitrag werden die Anforderungen der Mammadiagnostik und mögliche Einsatzgebiete der der KI beleuchtet. Je nach Definition gibt es bereits praktisch anwendbare Softwaretools für die Mammadiagnostik. Globale Lösungen stehen allerdings noch aus.
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Baltzer PAT. Supplemental screening using breast MRI in women with mammographically dense breasts. Eur J Radiol 2020; 136:109513. [PMID: 33422397 DOI: 10.1016/j.ejrad.2020.109513] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 12/28/2020] [Indexed: 01/08/2023]
Affiliation(s)
- Pascal A T Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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