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Iima M, Kataoka M, Honda M, Le Bihan D. Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer. Korean J Radiol 2024; 25:623-633. [PMID: 38942456 PMCID: PMC11214919 DOI: 10.3348/kjr.2023.1188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 02/28/2024] [Accepted: 04/11/2024] [Indexed: 06/30/2024] Open
Abstract
This study systematically reviewed the role of diffusion-weighted imaging (DWI) in the assessment of molecular prognostic biomarkers in breast cancer, focusing on the correlation of apparent diffusion coefficient (ADC) with hormone receptor status and prognostic biomarkers. Our meta-analysis includes data from 52 studies examining ADC values in relation to estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67 status. The results indicated significant differences in ADC values among different receptor statuses, with ER-positive, PgR-positive, HER2-negative, and Ki-67-positive tumors having lower ADC values compared to their negative counterparts. This study also highlights the potential of advanced DWI techniques such as intravoxel incoherent motion and non-Gaussian DWI to provide additional insights beyond ADC. Despite these promising findings, the high heterogeneity among the studies underscores the need for standardized DWI protocols to improve their clinical utility in breast cancer management.
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Affiliation(s)
- Mami Iima
- Department of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, Nagoya, Japan
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat à l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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Hoffmann E, Masthoff M, Kunz WG, Seidensticker M, Bobe S, Gerwing M, Berdel WE, Schliemann C, Faber C, Wildgruber M. Multiparametric MRI for characterization of the tumour microenvironment. Nat Rev Clin Oncol 2024; 21:428-448. [PMID: 38641651 DOI: 10.1038/s41571-024-00891-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 04/21/2024]
Abstract
Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.
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Affiliation(s)
- Emily Hoffmann
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Max Masthoff
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang G Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Max Seidensticker
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Stefanie Bobe
- Gerhard Domagk Institute of Pathology, University Hospital Münster, Münster, Germany
| | - Mirjam Gerwing
- Clinic of Radiology, University of Münster, Münster, Germany
| | | | | | - Cornelius Faber
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Moritz Wildgruber
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
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Kataoka M, Iima M, Miyake KK, Honda M. Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment. Invest Radiol 2024; 59:26-37. [PMID: 37994113 DOI: 10.1097/rli.0000000000001044] [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: 11/24/2023]
Abstract
ABSTRACT A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.
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Affiliation(s)
- Masako Kataoka
- From the Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University, Kyoto, Japan (M.K., M.I., M.H.); Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan (M.I.); Department of Advanced Imaging in Medical Magnetic Resonance, Graduate School of Medicine Kyoto University, Kyoto, Japan (K.K.M); and Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan (M.H.)
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Honda M, Iima M, Kataoka M, Fukushima Y, Ota R, Ohashi A, Toi M, Nakamoto Y. Biomarkers Predictive of Distant Disease-free Survival Derived from Diffusion-weighted Imaging of Breast Cancer. Magn Reson Med Sci 2023; 22:469-476. [PMID: 35922924 PMCID: PMC10552669 DOI: 10.2463/mrms.mp.2022-0060] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 06/12/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To investigate whether intravoxel incoherent motion (IVIM) and/or non-Gaussian diffusion parameters are associated with distant disease-free survival (DDFS) in patients with invasive breast cancer. METHODS From May 2013 to March 2015, 101 patients (mean age 60.0, range 28-88) with invasive breast cancer were evaluated prospectively. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at a b value of 0 s/mm2 [ADC0] and kurtosis [K]) were estimated using a diffusion-weighted imaging series of 16 b values up to 2500 s/mm2. Shifted ADC values (sADC200-1500) and standard ADC values (ADC0-800) were also calculated. The Kaplan-Meier method was used to generate survival analyses for DDFS, which were compared using the log-rank test. Univariable Cox proportional hazards models were used to assess any associations between each parameter and distant metastasis-free survival. RESULTS The median observation period was 80 months (range, 35-92 months). Among the 101 patients, 12 (11.9%) developed distant metastasis, with a median time to metastasis of 79 months (range, 10-92 months). Kaplan-Meier analysis showed that DDFS was significantly shorter in patients with K > 0.98 than in those with K ≤ 0.98 (P = 0.04). Cox regression analysis showed a marginal statistical association between K and distant metastasis-free survival (P = 0.05). CONCLUSION Non-Gaussian diffusion may be associated with prognosis in invasive breast cancer. A higher K may be a marker to help identify patients at an elevated risk of distant metastasis, which could guide subsequent treatment.
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Affiliation(s)
- Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Osaka, Japan
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
- Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, Kyoto, Kyoto, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Yasuhiro Fukushima
- Department of Applied Medical Imaging, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan
| | - Rie Ota
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Akane Ohashi
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Masakazu Toi
- Department of Breast Surgery, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Kyoto, Japan
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Ji Y, Xu J, Wang Z, Guo X, Kong D, Wang H, Li K. Application of advanced diffusion models from diffusion weighted imaging in a large cohort study of breast lesions. BMC Med Imaging 2023; 23:52. [PMID: 37041466 PMCID: PMC10091641 DOI: 10.1186/s12880-023-01005-6] [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: 09/30/2022] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
BACKGROUND To evaluate multiple parameters in multiple b-value diffusion-weighted imaging (DWI) in characterizing breast lesions and predicting prognostic factors and molecular subtypes. METHODS In total, 504 patients who underwent 3-T magnetic resonance imaging (MRI) with T1-weighted dynamic contrast-enhanced (DCE) sequences, T2-weighted sequences and multiple b-value (7 values, from 0 to 3000 s/mm2) DWI were recruited. The average values of 13 parameters in 6 models were calculated and recorded. The pathological diagnosis of breast lesions was based on the latest World Health Organization (WHO) classification. RESULTS Twelve parameters exhibited statistical significance in differentiating benign and malignant lesions. alpha demonstrated the highest sensitivity (89.5%), while sigma demonstrated the highest specificity (77.7%). The stretched-exponential model (SEM) demonstrated the highest sensitivity (90.8%), while the biexponential model demonstrated the highest specificity (80.8%). The highest AUC (0.882, 95% CI, 0.852-0.912) was achieved when all 13 parameters were combined. Prognostic factors were correlated with different parameters, but the correlation was relatively weak. Among the 6 parameters with significant differences among molecular subtypes of breast cancer, the Luminal A group and Luminal B (HER2 negative) group had relatively low values, and the HER2-enriched group and TNBC group had relatively high values. CONCLUSIONS All 13 parameters, independent or combined, provide valuable information in distinguishing malignant from benign breast lesions. These new parameters have limited meaning for predicting prognostic factors and molecular subtypes of malignant breast tumors.
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Affiliation(s)
- Ying Ji
- Department of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, No. 650, New Songjiang Road, Shanghai, 201620, China
| | - Junqi Xu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220, Handan Road, Shanghai, 200433, China
| | - Zilin Wang
- Department of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, No. 650, New Songjiang Road, Shanghai, 201620, China
| | - Xinyu Guo
- Department of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, No. 650, New Songjiang Road, Shanghai, 201620, China
| | - Dexing Kong
- School of Mathematical Sciences, Zhejiang University, No. 866, Yuhangtang Road, Zhejiang, 310027, China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220, Handan Road, Shanghai, 200433, China
| | - Kangan Li
- Department of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, No. 650, New Songjiang Road, Shanghai, 201620, China.
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Deng X, Duan Z, Fang S, Wang S. Advances in The Application and Research of Magnetic Resonance Diffusion Kurtosis Imaging in The Musculoskeletal System. J Magn Reson Imaging 2023; 57:670-689. [PMID: 36200754 DOI: 10.1002/jmri.28463] [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: 06/22/2022] [Revised: 09/22/2022] [Accepted: 09/22/2022] [Indexed: 11/11/2022] Open
Abstract
Magnetic resonance diffusion kurtosis imaging (DKI) is an emerging magnetic resonance imaging (MRI) technique that can reflect microstructural changes in tissue through non-Gaussian diffusion of water molecules. Compared to traditional diffusion weighted imaging (DWI), the DKI model has shown greater sensitivity for diagnosis of musculoskeletal diseases and can help formulate more reasonable treatment plans. Moreover, DKI is an important auxiliary examination for evaluation of the motor function of the musculoskeletal system. This article briefly introduces the basic principles of DKI and reviews the application and research of DKI in the evaluation of disorders of the musculoskeletal system (including bone tumors, soft tissue tumors, spinal lesions, chronic musculoskeletal diseases, musculoskeletal trauma, and developmental disorders) as well as the normal musculoskeletal tissues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.
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Affiliation(s)
- Xiyang Deng
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Zhiqing Duan
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Shaobo Fang
- Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, Henan, China.,Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, China
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Zhou Z, Chen Y, Zhao F, Sun Z, Zhu L, Yu H, Wang W. Predictive value of intravoxel incoherent motion combined with diffusion kurtosis imaging for breast cancer axillary lymph node metastasis: a retrospective study. Acta Radiol 2023; 64:951-961. [PMID: 35765225 DOI: 10.1177/02841851221107626] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Non-invasive imaging technologies for assessing axillary lymph node (ALN) metastasis of breast cancer are needed in clinical practice. PURPOSE To explore the clinical value of intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) for predicting ALN metastasis of breast cancer. MATERIAL AND METHODS A total of 194 patients with pathologically confirmed breast cancer who underwent IVIM and DKI examination were reviewed retrospectively. The IVIM derived parameters of D, D*, and f and DKI-derived parameters of MD and MK were measured. The independent samples t-test was used to compare the parameters between the ALN metastasis and non-ALN metastasis groups. Receiver operating characteristic (ROC) curve analysis was also performed. RESULTS The D and MD in the ALN metastasis group were significantly lower than those in the non-ALN metastasis group (P < 0.001, P < 0.001). The D*, f, and MK were higher in the ALN metastasis group than in the non-ALN metastasis group (P = 0.015, P = 0.014, and P = 0.001, respectively). The area under the ROC curve (AUC) of D (0.768) was highest. In addition, the diagnostic efficiency of both IVIM and DKI were higher than that of the conventional MRI (P = 0.002, P = 0.048). The diagnostic efficiency of IVIM + DKI were higher than that of the IVIM or DKI alone (P = 0.021, P = 0.004). CONCLUSION IVIM and DKI can be used for predicting breast cancer ALN metastasis with D as the most meaningful parameter.
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Affiliation(s)
- Zhe Zhou
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Yueqin Chen
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Fan Zhao
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Zhanguo Sun
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Laimin Zhu
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Hao Yu
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
| | - Weiwei Wang
- Department of Medical Imaging, 562122The Affiliated Hospital of Jining Medical University, Jining, PR China
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Iima M, Le Bihan D. The road to breast cancer screening with diffusion MRI. Front Oncol 2023; 13:993540. [PMID: 36895474 PMCID: PMC9989267 DOI: 10.3389/fonc.2023.993540] [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: 07/13/2022] [Accepted: 01/10/2023] [Indexed: 02/23/2023] Open
Abstract
Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat á l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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Pistel M, Laun FB, Bickelhaupt S, Dada A, Weiland E, Niederdränk T, Uder M, Janka R, Wenkel E, Ohlmeyer S. Differentiating Benign and Malignant Breast Lesions in Diffusion Kurtosis MRI: Does the Averaging Procedure Matter? J Magn Reson Imaging 2022; 56:1343-1352. [PMID: 35289015 DOI: 10.1002/jmri.28150] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/28/2022] [Accepted: 02/28/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Diffusion kurtosis imaging (DKI) is used to differentiate between benign and malignant breast lesions. DKI fits are performed either on voxel-by-voxel basis or using volume-averaged signal. PURPOSE Investigate and compare DKI parameters' diagnostic performance using voxel-by-voxel and volume-averaged signal fit approach. STUDY TYPE Retrospective. STUDY POPULATION A total of 104 patients, aged 24.1-86.4 years. FIELD STRENGTH/SEQUENCE A 3 T Spin-echo planar diffusion-weighted sequence with b-values: 50 s/mm2 , 750 s/mm2 , and 1500 s/mm2 . Dynamic contrast enhanced (DCE) sequence. ASSESSMENT Lesions were manually segmented by M.P. under supervision of S.O. (2 and 5 years of experience in breast MRI). DKI fits were performed on voxel-by-voxel basis and with volume-averaged signal. Diagnostic performance of DKI parameters D K (kurtosis corrected diffusion coefficient) and kurtosis K was compared between both approaches. STATISTICAL TESTS Receiver operating characteristics analysis and area under the curve (AUC) values were computed. Wilcoxon rank sum and Students t-test tested DKI parameters for significant (P <0.05) difference between benign and malignant lesions. DeLong test was used to test the DKI parameter performance for significant fit approach dependency. Correlation between parameters of the two approaches was determined by Pearson correlation coefficient. RESULTS DKI parameters were significantly different between benign and malignant lesions for both fit approaches. Median benign vs. malignant values for voxel-by-voxel and volume-averaged approach were 2.00 vs. 1.28 ( D K in μm2 /msec), 2.03 vs. 1.26 ( D K in μm2 /msec), 0.54 vs. 0.90 ( K ), 0.55 vs. 0.99 ( K ). AUC for voxel-by-voxel and volume-averaged fit were 0.9494 and 0.9508 ( D K ); 0.9175 and 0.9298 ( K ). For both, AUC did not differ significantly (P = 0.20). Correlation of values between the two approaches was very high (r = 0.99 for D K and r = 0.97 for K ). DATA CONCLUSION Voxel-by-voxel and volume-averaged signal fit approach are equally well suited for differentiating between benign and malignant breast lesions in DKI. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Mona Pistel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.,Siemens Healthineers AG, Erlangen, Germany
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sebastian Bickelhaupt
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Anes Dada
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Elisabeth Weiland
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Rolf Janka
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Evelyn Wenkel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sabine Ohlmeyer
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Karan B. Editorial for "Differentiating benign and malignant breast lesions in diffusion kurtosis MRI: Does the averaging procedure matter?". J Magn Reson Imaging 2022; 56:1353-1354. [PMID: 35561018 DOI: 10.1002/jmri.28229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 04/08/2022] [Indexed: 12/15/2022] Open
Affiliation(s)
- Belgin Karan
- Department of Radiology, Faculty of Medicine, Medipol University, Istanbul, Turkey
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11
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Gu H, Cui W, Luo S, Deng X. Diagnostic Performance of Diffusion Kurtosis Imaging for Benign and Malignant Breast Lesions: A Systematic Review and Meta-Analysis. Appl Bionics Biomech 2022; 2022:2042736. [PMID: 35721236 PMCID: PMC9203235 DOI: 10.1155/2022/2042736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/09/2022] [Accepted: 05/12/2022] [Indexed: 11/21/2022] Open
Abstract
Purpose Magnetic resonance imaging (MRI) has a high sensitivity for differentiating between malignant and non-malignant breast lesions but is sometimes limited due to its low specificity. Here, we performed a meta-analysis to evaluate the diagnostic performance of mean kurtosis (MK) and mean diffusivity (MD) values in magnetic resonance diffusion kurtosis imaging (DKI) for benign and malignant breast lesions. Methods Original articles on relevant topics, published from 2010 to 2019, in PubMed, EMBASE, and WanFang databases were systematically reviewed. According to the purpose of the study and the characteristics of DKI reported, the diagnostic performances of MK and MD were evaluated, and meta-regression was conducted to explore the source of heterogeneity. Results Fourteen studies involving 1,099 (451 benign and 648 malignant) lesions were analyzed. The pooled sensitivity, pooled specificity, positive likelihood ratio, and negative likelihood ratio for MD were 0.84 (95% confidence interval (CI), 0.81-0.87), 0.83 (95% CI, 0.79-0.86), 4.44 (95% CI, 3.54-5.57), and 0.18 (95% CI, 0.13-0.26), while those for MK were 0.89 (95% CI, 0.86-0.91), 0.86 (95% CI, 0.82-0.89), 5.72 (95% CI, 4.26-7.69), and 0.13 (95% CI, 0.09-0.19), respectively. The overall area under the curve (AUC) was 0.91 for MD and 0.95 for MK. Conclusions Analysis of the data from 14 studies showed that MK had a higher pooled sensitivity, pooled specificity, and diagnostic performance for differentiating between breast lesions, compared with MD.
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Affiliation(s)
- Hongyu Gu
- Department of Radiology, Affiliated Aoyang Hospital of Jiangsu University, Jiangsu 215600, China
| | - Wenjing Cui
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu 210029, China
| | - Song Luo
- Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu 210002, China
| | - Xiaoyi Deng
- Department of Radiology, Affiliated Aoyang Hospital of Jiangsu University, Jiangsu 215600, China
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Meyer HJ, Martin M, Denecke T. DWI of the Breast - Possibilities and Limitations. ROFO-FORTSCHR RONTG 2022; 194:966-974. [PMID: 35439830 DOI: 10.1055/a-1775-8572] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND The MRI of the breast is of great importance in the diagnosis of disorders of the breast. This can be stated for the primary diagnosis as well as the follow up. Of special interest is diffusion weighted imaging (DWI), which has an increasingly important role. The present review provides results regarding the diagnostic and prognostic relevance of DWI for disorders of the breast. METHODS Under consideration of the recently published literature, the clinical value of DWI of the breast is discussed. Several diagnostic applications are shown, especially for the primary diagnosis of unclear tumors of the breast, the prediction of the axillary lymph node status and the possibility of a native screening. Moreover, correlations between DWI and histopathology features and treatment prediction with DWI are provided. RESULTS Many studies have shown the diagnostic value of DWI for the primary diagnosis of intramammary lesions. Benign lesions of the breast have significantly higher apparent diffusion coefficients (ADC values) compared to malignant tumors. This can be clinically used to reduce unnecessary biopsies in clinical routine. However, there are inconclusive results for the prediction of the histological subtype of the breast cancer. DWI can aid in the prediction of treatment to neoadjuvant chemotherapy. CONCLUSION DWI is a very promising imaging modality, which should be included in the standard protocol of the MRI of the breast. DWI can provide clinically value in the diagnosis as well as for prognosis in breast cancer. KEY POINTS · DWI can aid in the discrimination between benign and malignant tumors of the breast and therefore avoiding unnecessary biopsies.. · The ADC value cannot discriminate between immunhistochemical subtypes of the breast cancer. · The ADC value of breast cancer increases under neoadjuvant chemotherapy and can by this aid in treatment prediction.. · There is definite need of standardisation for clinical translation. CITATION FORMAT · Meyer HJ, Martin M, Denecke T. DWI of the Breast - Possibilities and Limitations. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1775-8572.
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Affiliation(s)
- Hans Jonas Meyer
- Diagnostic and Interventional Radiology, University of Leipzig Faculty of Medicine, Leipzig, Germany
| | - Mireille Martin
- Diagnostic and Interventional Radiology, University of Leipzig Faculty of Medicine, Leipzig, Germany
| | - Timm Denecke
- Diagnostic and Interventional Radiology, University of Leipzig Faculty of Medicine, Leipzig, Germany
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He M, Ruan H, Ma M, Zhang Z. Application of Diffusion Weighted Imaging Techniques for Differentiating Benign and Malignant Breast Lesions. Front Oncol 2021; 11:694634. [PMID: 34235084 PMCID: PMC8255916 DOI: 10.3389/fonc.2021.694634] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/07/2021] [Indexed: 12/25/2022] Open
Abstract
To explore the value of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusional kurtosis imaging (DKI) based on diffusion weighted magnetic resonance imaging (DW-MRI) in differentiating benign and malignant breast lesions. A total of 215 patients with breast lesions were prospectively collected for breast MR examination. Single exponential, IVIM, and DKI models were calculated using a series of b values. Parameters including ADC, perfusion fraction (f), tissue diffusion coefficient (D), perfusion-related incoherent microcirculation (D*), average kurtosis (MK), and average diffusivity (MD) were compared between benign and malignant lesions. ROC curves were used to analyze the optimal diagnostic threshold of each parameter, and to evaluate the diagnostic efficacy of single and combined parameters. ADC, D, MK, and MD values were significantly different between benign and malignant breast lesions (P<0.001). Among the single parameters, ADC had the highest diagnostic efficiency (sensitivity 91.45%, specificity 82.54%, accuracy 88.84%, AUC 0.915) and the best diagnostic threshold (0.983 μm2/ms). The combination of ADC and MK offered high diagnostic performance (sensitivity 90.79%, specificity 85.71%, accuracy 89.30%, AUC 0.923), but no statistically significant difference in diagnostic performance as compared with single-parameter ADC (P=0.268). The ADC, D, MK, and MD parameters have high diagnostic value in differentiating benign and malignant breast lesions, and of these individual parameters the ADC has the best diagnostic performance. Therefore, our study revealed that the use of ADC alone should be useful for differentiating between benign and malignant breast lesions, whereas the combination of MK and ADC might improve the diagnostic performance to some extent.
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Affiliation(s)
- Muzhen He
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
| | - Huiping Ruan
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
| | - Mingping Ma
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
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