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Pötsch N, Clauser P, Kapetas P, Baykara Ulusan M, Helbich T, Baltzer P. Enhancing the Kaiser score for lesion characterization in unenhanced breast MRI. Eur J Radiol 2024; 176:111520. [PMID: 38820953 DOI: 10.1016/j.ejrad.2024.111520] [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: 04/04/2024] [Revised: 05/15/2024] [Accepted: 05/19/2024] [Indexed: 06/02/2024]
Abstract
PURPOSE To adapt the methodology of the Kaiser score, a clinical decision rule for lesion characterization in breast MRI, for unenhanced protocols. METHOD In this retrospective IRB-approved cross-sectional study, we included 93 consecutive patients who underwent breast MRI between 2021 and 2023 for further work-up of BI-RADS 0, 3-5 in conventional imaging or for staging purposes (BI-RADS 6). All patients underwent biopsy for histologic verification or were followed for a minimum of 12 months. MRI scans were conducted using 1.5 T or 3 T scanners using dedicated breast coils and a protocol in line with international recommendations including DWI and ADC. Lesion characterization relied solely on T2w and DWI/ADC-derived features (such as lesion type, margins, shape, internal signal, surrounding tissue findings, ADC value). Statistical analysis was done using decision tree analysis aiming to distinguish benign (histology/follow-up) from malignant outcomes. RESULTS We analyzed a total of 161 lesions (81 of them non-mass) with a malignancy rate of 40%. Lesion margins (spiculated, irregular, or circumscribed) were identified as the most important criterion within the decision tree, followed by the ADC value as second most important criterion. The resulting score demonstrated a strong diagnostic performance with an AUC of 0.840, providing both rule-in and rule-out criteria. In an independent test set of 65 lesions the diagnostic performance was verified by two readers (AUC 0.77 and 0.87, kappa: 0.62). CONCLUSIONS We developed a clinical decision rule for unenhanced breast MRI including lesion margins and ADC value as the most important criteria, achieving high diagnostic accuracy.
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Affiliation(s)
- N Pötsch
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Kapetas
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - M Baykara Ulusan
- Department of Radiology, University of Health Sciences Istanbul Training and Research Hospital, Org. Abdurrahman Nafiz Gurman Cad, No:1 Fatih, İstanbul, Turkey
| | - T Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria.
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Pötsch N, Sodano C, Baltzer PAT. Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis. Radiology 2024; 311:e232508. [PMID: 38771179 DOI: 10.1148/radiol.232508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.
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Affiliation(s)
- Nina Pötsch
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Claudia Sodano
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Pascal A T Baltzer
- From the Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
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Urut DU, Karabulut D, Hereklioglu S, Özdemir G, Cicin BA, Hacıoglu B, Süt N, Tunçbilek N. Diffusion tensor imaging: survival analysis prediction in breast cancer patients. RADIOLOGIE (HEIDELBERG, GERMANY) 2024:10.1007/s00117-023-01254-0. [PMID: 38277036 DOI: 10.1007/s00117-023-01254-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/14/2023] [Indexed: 01/27/2024]
Abstract
PURPOSE We aimed to explore the performance of diffusion-tensor imaging (DTI) and apparent diffusion coefficient (ADC) parameters in evaluating disease-free survival (DFS) and overall survival (OS) in patients with invasive breast cancer. MATERIAL AND METHODS A total of 49 women with invasive breast cancer who were diagnosed between 2017 and 2022 were included. All patients underwent breast magnetic resonance imaging (MRI) with DTI and diffusion-weighted imaging (DWI) features, with examiners blinded to the clinical data. Volume anisotropy (VA), fractional anisotropy (FA), and ADC values were measured to assess intratumoral measured heterogeneity. Correlations and differences in diffusion metrics according to OS and DFS status of the cases were analyzed. The discriminative ability of the quantitative findings was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort. RESULTS We evaluated patients with metastases (n = 13, 36.5%) and those without metastases (n = 36, 73.5%). Differences in the ADC, FA, and VA values were observed. The results of Cox regression survival analysis for all the patients included in the survival analysis revealed that DTI metrics contributed to the prediction of overall survival (OS) in the emerging models (p < 0.05). Both FA and VA were associated with OS (p = 0.037 and p = 0.038, respectively). However, ADC was not associated with OS (p = 0.177) or DFS (p = 0.252). CONCLUSION To the best of our knowledge, this is the first study to assess the prognostic value of DTI-MRI in breast cancer with statistical survival analysis techniques. We believe that DTI measurements can be used as a biomarker for OS analysis in breast cancer given the available data.
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Affiliation(s)
- Devrim Ulaş Urut
- BHT Clinic İstanbul Tema Hospital Dep of Radiology, Istanbul Aydin University, Atakent mah. 4.cad. no: 36, 34307, Küçükçekmece/İstanbul, Turkey.
- Medical School Deparment of Radiology, Trakya University, Edirne, Turkey.
| | - Derya Karabulut
- Medical School Department of Radiology, Trakya University, Edirne, Turkey
| | - Savaş Hereklioglu
- Department of Radiology, Ataturk Training and Research Hospital, Erzurum, Turkey
| | - Gulşah Özdemir
- Medical School Department of Radiology, Trakya University, Edirne, Turkey
| | - Berkin Anıl Cicin
- Medical School Department of Medical Oncology, Trakya University, Edirne, Turkey
| | - Bekir Hacıoglu
- Medical School Department of Medical Oncology, Trakya University, Edirne, Turkey
| | - Necet Süt
- Medical School Dep of Biostatistics and Medical Informatics, Trakya University, Edirne, Turkey
| | - Nermin Tunçbilek
- Medical School Department of Radiology, Trakya University, Edirne, Turkey
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Shahbazi-Gahrouei D, Aminolroayaei F, Nematollahi H, Ghaderian M, Gahrouei SS. Advanced Magnetic Resonance Imaging Modalities for Breast Cancer Diagnosis: An Overview of Recent Findings and Perspectives. Diagnostics (Basel) 2022; 12:2741. [PMID: 36359584 PMCID: PMC9689118 DOI: 10.3390/diagnostics12112741] [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: 10/08/2022] [Revised: 10/26/2022] [Accepted: 11/07/2022] [Indexed: 08/28/2023] Open
Abstract
Breast cancer is the most prevalent cancer among women and the leading cause of death. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced magnetic resonance imaging (MRI) procedures that are widely used in the diagnostic and treatment evaluation of breast cancer. This review article describes the characteristics of new MRI methods and reviews recent findings on breast cancer diagnosis. This review study was performed on the literature sourced from scientific citation websites such as Google Scholar, PubMed, and Web of Science until July 2021. All relevant works published on the mentioned scientific citation websites were investigated. Because of the propensity of malignancies to limit diffusion, DWI can improve MRI diagnostic specificity. Diffusion tensor imaging gives additional information about diffusion directionality and anisotropy over traditional DWI. Recent findings showed that DWI and DTI and their characteristics may facilitate earlier and more accurate diagnosis, followed by better treatment. Overall, with the development of instruments and novel MRI modalities, it may be possible to diagnose breast cancer more effectively in the early stages.
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Affiliation(s)
- Daryoush Shahbazi-Gahrouei
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran
| | - Fahimeh Aminolroayaei
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran
| | - Hamide Nematollahi
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran
| | - Mohammad Ghaderian
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran
| | - Sogand Shahbazi Gahrouei
- Department of Management, School of Humanities, Najafabad Branch, Islamic Azad University, Najafabad 8514143131, Iran
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Qin Y, Tang C, Hu Q, Zhang Y, Yi J, Dai Y, Ai T. Quantitative Assessment of Restriction Spectrum MR Imaging for the Diagnosis of Breast Cancer and Association With Prognostic Factors. J Magn Reson Imaging 2022; 57:1832-1841. [PMID: 36205354 DOI: 10.1002/jmri.28468] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 09/23/2022] [Accepted: 09/23/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Restriction spectrum imaging (RSI) is an advanced quantitative diffusion-weighted magnetic resonance imaging (DWI) technique to assess breast cancer. PURPOSE To investigate the ability of RSI to differentiate the benign and malignant breast lesions and the association with prognostic factors of breast cancer. STUDY TYPE Retrospective. POPULATION Seventy women (mean age, 49.6 ± 12.3 years) with 56 malignant and 19 benign breast lesions. FIELD STRENGTH/SEQUENCE 3-T; RSI-based DWI sequence with echo-planar imaging technique. ASSESSMENT The apparent diffusion coefficient (ADC) and RSI parameters (restricted diffusion f1 , hindered diffusion f2 , free diffusion f3 , and signal fractions f1 f2 ) were calculated by two readers for the whole lesion volume and compared between the benign and malignant groups and the subgroups with different statuses of prognostic factors in breast cancer. STATISTICAL TESTS Mann-Whitney U test or Student's t-test was applied to compare the quantitative parameters between the different groups. Intraclass correlation coefficient (ICC) was used to assess readers' reproducibility. Binary logistic regression was used to combine parameters. Area under the curve (AUC) of receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of parameters to distinguish benign from malignant breast lesions. A P-value <0.05 was considered statistically significant. RESULTS Malignant breast lesions showed significantly lower ADC and f3 values, and significantly higher f1 and f1 f2 values than the benign lesions, with AUC of 0.951, 0.877, 0.868, and 0.860, respectively. When RSI-derived parameters and ADC were combined, the diagnostic performance was superior to either single parameter (AUC = 0.973). The f3 value was significantly differed between estrogen receptor (ER)-positive and ER-negative tumors. The ADC, f1 , f3 , and f1 f2 values were significantly different progesterone receptor (PR)-positive and PR-negative status. DATA CONCLUSION The RSI-derived parameters (f1 , f3 , and f1 f2 ) may facilitate the differential diagnosis between benign and malignant breast lesions. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yanjin Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Caili Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qilan Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yunfei Zhang
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Jingru Yi
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yongming Dai
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Tao Ai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Imaging Features Derived From Dynamic Contrast-Enhanced Magnetic Resonance Imaging to Differentiate Malignant From Benign Breast Lesions: A Systematic Review and Meta-Analysis. J Comput Assist Tomogr 2022; 46:383-391. [DOI: 10.1097/rct.0000000000001289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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